Connecting 2016 to Compete Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators No data 2.35 4.23 LPI score, 2016 (1 is the lowest score; 5 is the highest score) Connecting to Compete 2016 Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators Jean-François Arvis The World Bank Daniel Saslavsky The World Bank Lauri Ojala Turku School of Economics Ben Shepherd Developing Trade Consultants Christina Busch The World Bank Anasuya Raj The World Bank Tapio Naula Turku School of Economics © 2016 The International Bank for Reconstruction and Development/The World Bank 1818 H Street NW Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved The findings, interpretations, and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the Executive Directors of the International Bank for Reconstruc- tion and Development/The World Bank or the governments they represent. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. If you have any questions or comments about this report, please contact: Global Trade Unit The World Bank 1818 H Street NW, Mailstop MC3‑300, Washington, DC 20433 USA Telephone: 202-473-8922 E-mail: LPI@worldbank.org Web site: http://lpi.worldbank.org The report was designed, edited, and typeset by Communications Development Incorporated, Washington, DC. Foreword Anabel González, Senior Director, Trade & Competitiveness Global Practice, The World Bank Group I am pleased to introduce the fifth edition of as a global benchmark. It is not a substitute for Connecting to Compete: Trade Logistics in the in-depth country diagnoses. For this, the World Global Economy. The Connecting to Compete Bank and others have proposed thorough and series features the Logistics Performance Index adequate methodologies such as the Trade and (LPI), a comprehensive measure of the efficiency Transport Facilitation Assessment. The increas- of international supply chains. Its first version ing availability of data, including big data, opens was published in 2007, and it has since been new opportunities to disentangle supply chains updated every two years. in specific country contexts and at detailed in- Logistics organizes the movement of goods dustry or geographical levels. through a network of activities and services op- Building on a rich set of information, the re- erating at global, regional, and local scale. Logis- port shows that improving logistics performance tics encompasses more than freight transporta- is a complex, unfinished, cross-cutting, and tion. Traders delegate increasingly sophisticated evolving agenda. The priorities depend on coun- tasks to networks of specialized service provid- try performance. Countries with the worst per- ers. Efficient logistics connects people and firms formance are dealing with comparatively basic to markets and opportunities and helps achieve trade and transport facilitation reforms, which higher levels of productivity and welfare. the World Bank and partner agencies support in Crucially, logistics is not only a private en- many places. Middle- and high-income econo- deavor, but also a public policy concern. The mies are dealing with new concerns, which the performance and reliability of supply chains de- Connecting to Compete report echoes: sustain- pend on an array of interventions, ranging from able logistics, distribution and urban logistics, trade facilitation at the border to infrastructure skill development and training, and domestic and regulations and to urban planning and and international connectivity bottlenecks. skills. Empirical evidence confirms that logis- Any effective action in logistics policies tics- and connectivity-related interventions have should be the result of coordinated efforts be- the highest potential to reduce the cost of trade tween the private and public sectors. In this re- and to boost integration in global value chains. gard, the support of the International Federation Today, policy makers know that logistics mat- of Freight Forwarders Associations (FIATA) to ters and that they can improve the efficiency of undertake this new edition of the Connecting to the supply chains connecting their countries in- Compete report has been invaluable. ternally and externally. As a former government I sincerely hope the LPI and this biennial re- official, I can confirm that the previous editions port will continue to provide useful knowledge of the LPI, indeed, contributed to this awareness to policy makers, private sector executives, and by proposing a synthetic understanding of the in- others interested in how to make supply chains tricate reality of supply chain networks. work more efficiently for the benefit of all. After almost 10 years, the LPI remains highly relevant. The Connecting to Compete Anabel González report has initiated and facilitated numerous Senior Director policy reforms around the globe. But the LPI Trade & Competitiveness Global Practice should not be overinterpreted beyond its role World Bank Group C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y iii Foreword Huxiang Zhao, President, International Federation of Freight Forwarders Associations (FIATA) I have been asked to make comments on the poor trade. We must remember that moving new publication of the Logistics Performance goods across borders is not the be-all and end- Index in my role as President of FIATA. This all of logistics performance, which requires the is a much needed tool for decision makers to integration of many elements throughout the consider when decisions on logistics capac- entire supply chain. ity and quality need to be made. The LPI is The challenge is to ensure that the LPI and unique as a tool of decision making since it all the insight into markets it contains reaches expresses the perception of operators on the decision makers not only in the public sector ground; this is often as important as hard sta- but also in the private sector to avoid that the tistical data. public sector caters for misconceived private de- FIATA, in representing freight forward- mand; in this regard the role of large and global ers and logistics service providers globally, is organizations such as FIATA is crucial. pleased to have been a part of the development We trust the 2016 Logistics Performance of this 2016 edition, and we are grateful to the Index will be well received by policy makers and LPI team for their continued trust, which is private sector decision makers alike. FIATA is now spanning a number of years. proud to congratulate those members who re- The LPI is instrumental in the policy plied by providing necessary information and is choices of governments, nongovernmental or- grateful to the World Bank for the opportunity ganizations, and private enterprises worldwide, to contribute to this priceless initiative. and the visibility of the freight forwarding and logistics sector as an intrinsic arm of global Huxiang Zhao trade and commerce is crucial. There is no trade President, International Federation of Freight without logistics, and poor logistics often means Forwarders Associations (FIATA) iv C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Acknowledgments This report has been prepared by the World worked with the World Bank since 2000 to de- Bank’s Global Trade Team under the guid- velop the concept. ance of Anabel González (Senior Director) The authors are also grateful to external and José Guilherme Reis (Practice Manager). colleagues for their support and contributions The project leaders were Jean-­ François Arvis in reaching out to forwarding associations and (jarvis1@­ worldbank.org) and ­ Daniel Saslavsky providing inputs for the report, including Ruth (dsaslavsky@worldbank.org). Authors included Banomyong (Thammasat University, Thailand), Professor Lauri Ojala (Turku School of Eco- Nicolette Van der Jagt (CLECAT, European nomics, University of Turku; lauri.ojala@­ utu Association for Forwarding, Transport, Logis- .fi), Ben Shepherd (Principal, Developing Trade tics, and Customs Services), and Cesar Lavalle Consultants; ben@developing‑trade.com), Ana- (ILOS Brazil). Jan Havenga (Department of suya Raj (anasuyaraj.14@gmail.com), Christina Logistics, Stellenbosch University, South Af- Busch (cbusch@­ worldbank.org), and Tapio rica) provided inputs on the Logistics Barom- Naula (tapio.naula@­ tradelogistics.fi). Carolina eter South Africa. Daniel Cramer of BlueTun- Monsalve and Kamal Siblini were peer reviewers dra.com designed, developed, and maintained for this edition’s project concept note. the LPI survey and results websites under the The LPI survey would not have been pos- guidance of the core team. Scott Johnson of sible without the support and participation the World Bank Information Solutions Group of the International Federation of Freight helped the team distribute the survey. The re- Forwarders Associations (http://fiata.com/), port has been edited, designed, and laid out by namely, Marco Sorgetti, FIATA’s Director Communications Development Incorporated. General and CEO. National freight forward- The authors thank the hundreds of employees ing associations and a large group of small, of freight forwarding and express carrier compa- medium, and large logistics companies world- nies around the world who responded to the sur- wide were also instrumental in disseminating vey. Their participation was central to the quality the survey. The survey was designed with Fin- and credibility of the project, and their continu- land’s Turku School of Economics, University ing feedback will be essential as we develop and of Turku (http://www.utu.fi/en/), which has refine the survey and the LPI in years to come. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y v Table of contents Foreword by Anabel González    iii Foreword by Huxiang Zhao    iv Acknowledgments   v LPI ranking and scores, 2016    x Summary and key findings    1 1. The 2016 Logistics Performance Index    5 Introduction   5 Features of the 2016 survey    6 Key findings of the 2016 international LPI    7 Logistics performance is rising, and performance is heterogeneous    9 Trends over the past four LPI editions    13 2. Unbundling logistics performance    17 Infrastructure   17 Services   18 Border procedures and time    18 3. The way forward: New challenges in trade facilitation and logistics    27 Complexity of reforms: Moving away from the border?    27 Trade and transport facilitation remains a priority for poorly performing countries    27 Comprehensive logistics strategies are being developed in middle- and high-income countries 29 A data-driven reform agenda    30 Raising competencies under competitive pressure    30 More networks: The logistics industry response to the decline in impacts on trade growth 31 Logistics skills, competencies, and training    33 Managing the footprint and sustainability of logistics    35 Notes   37 Appendix 1. International LPI results    38 Appendix 2. Domestic LPI results, by region and income group    42 Appendix 3. Domestic LPI results, time and cost data    45 Appendix 4. LPI results across four editions (2010, 2012, 2014, and 2016)    51 Appendix 5. The LPI methodology    55 Appendix 6. Respondent demographics    59 References   61 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y vii Boxes 1.1 Using the LPI   6 1.2 How precise are LPI scores and ranks?    7 1.3 LPI results: Consistent within but not necessarily between regions?    11 1.4 Connectivity, logistics networks, and logistics performance    16 2.1 Timeliness and global value chains    25 3.1 Trade facilitation reforms: East Africa’s Northern Corridor    28 3.2 Major new international initiatives address logistics issues    29 3.3 France Logistique 2025   30 3.4 South Africa: Letting the (large) logistics data speak    31 Figures Figure 1 LPI score as percentage of highest LPI score, by LPI quintile averages, 2007, 2010, 2012, 2014, and 2016    1 1.1 Cumulative distribution of LPI scores    10 1.2 LPI component scores, by LPI quintile    10 1.3 Percentage change in LPI scores, customs, infrastructure, and quality of logistics services, 2014–16    12 1.4 Average LPI scores and minimum-maximum ranges, by income group    13 1.5 LPI overperformers and underperformers    14 1.6 LPI scores as a percentage of the best performer, LPI 2010–16    14 1.7 Weighted aggregate international LPI scores, 2010–16    15 2.1 Respondents rating trade and transport infrastructure quality improved or much improved since 2012, by LPI quintile 18 2.2 Median import lead time and average clearance time, by LPI quintile    19 2.3 Median export lead time, by LPI quintile    20 2.4 Median export lead time, by income group    21 2.5 Red tape affecting import and export transactions, by LPI quintile    22 2.6 Respondents reporting shipments often or nearly always cleared and delivered as scheduled, by LPI quintile    14 2.7 Respondents reporting shipments often or nearly always cleared and delivered as scheduled, by region    25 2.8 Shipments not meeting company quality criteria, by LPI quintile    26 3.1 Respondents reporting low or very low availability of qualified personnel, by employee group and LPI quintile    34 3.2 Respondents reporting low or very low availability of qualified personnel, by employee group and region    34 3.3 The demand for green logistics    35 A6.1 2016 LPI survey respondents, by World Bank income group    59 A6.2 2016 LPI survey respondents, by World Bank region    59 Tables 1 Top 10 average and bottom 10 average LPI scores, 2007–16    2 1.1 Top 10 LPI economies, 2016    8 1.2 Bottom 10 LPI 2016 economies    8 1.3 Top-performing lower-middle-income economies   8 1.4 Top-performing upper-middle-income economies   9 1.5 Top-performing low-income economies   9 1.6 Deviation of each component from the overall LPI score, by quintile    12 1.7 Respondents reporting an improved or much improved logistics environment since 2012, by LPI quintile    13 1.8 Economies with statistically significant changes in LPI scores    15 2.1 Respondents rating infrastructure quality high or very high, by infrastructure type and LPI quintile    17 2.2 Respondents rating infrastructure quality high or very high, by infrastructure type and region    18 2.3 Respondents rating service quality and competence high or very high, by service type and LPI quintile    19 2.4 Respondents rating services high or very high vs respondents rating infrastructure high or very high, by region    19 2.5 Respondents indicating that listed customs procedures are available and being used, by LPI quintile    20 viii C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 2.6 Three border agencies: respondents rating quality and competence high or very high, by LPI quintile    21 2.7 Respondents reporting that shipments are often or nearly always delayed, by delay category and LPI quintile    23 A5.1 Methodology for selecting country groups for survey respondents    56 A5.2 Results of principal component analysis for the international LPI    57 A5.3 Component loadings for the international LPI    57 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y ix LPI ranking and scores, 2016 2016 LPI 2016 LPI 2016 LPI % of % of % of highest highest highest Economy Rank Score performer Economy Rank Score performer Economy Rank Score performer Germany 1 4.23 100.0 Brazil 55 3.09 64.7 Mali 109 2.50 46.6 Luxembourg 2 4.22 99.8 Malta 56 3.07 64.1 Tunisia 110 2.50 46.4 Sweden 3 4.20 99.3 Botswana 57 3.05 63.4 Guatemala 111 2.48 45.8 Netherlands 4 4.19 98.8 Uganda 58 3.04 63.3 Honduras 112 2.46 45.3 Singapore 5 4.14 97.4 Cyprus 59 3.00 62.0 Myanmar 113 2.46 45.2 Belgium 6 4.11 96.4 Romania 60 2.99 61.8 Zambia 114 2.43 44.3 Austria 7 4.10 96.0 Tanzania 61 2.99 61.7 Benin 115 2.43 44.3 United Kingdom 8 4.07 95.2 Rwanda 62 2.99 61.6 Solomon Islands 116 2.42 43.9 Hong Kong SAR, China 9 4.07 95.1 Indonesia 63 2.98 61.5 Albania 117 2.41 43.8 United States 10 3.99 92.8 Vietnam 64 2.98 61.3 Uzbekistan 118 2.40 43.5 Switzerland 11 3.99 92.6 Uruguay 65 2.97 61.2 Jamaica 119 2.40 43.4 Japan 12 3.97 92.1 Argentina 66 2.96 60.8 Belarus 120 2.40 43.4 United Arab Emirates 13 3.94 91.2 Jordan 67 2.96 60.7 Trinidad and Tobago 121 2.40 43.3 Canada 14 3.93 90.8 Pakistan 68 2.92 59.6 Venezuela, RB 122 2.39 43.1 Finland 15 3.92 90.5 Peru 69 2.89 58.7 Montenegro 123 2.38 42.8 France 16 3.90 89.9 Brunei Darussalam 70 2.87 58.0 Nepal 124 2.38 42.7 Denmark 17 3.82 87.3 Philippines 71 2.86 57.5 Congo, Rep. 125 2.38 42.7 Ireland 18 3.79 86.6 Bulgaria 72 2.81 56.0 Ethiopia 126 2.38 42.7 Australia 19 3.79 86.6 Cambodia 73 2.80 55.8 Congo, Dem. Rep. 127 2.38 42.6 South Africa 20 3.78 86.0 Ecuador 74 2.78 55.1 Guinea-Bissau 128 2.37 42.5 Italy 21 3.76 85.4 Algeria 75 2.77 54.9 Guinea 129 2.36 42.1 Norway 22 3.73 84.7 Serbia 76 2.76 54.6 Georgia 130 2.35 41.9 Spain 23 3.73 84.5 Kazakhstan 77 2.75 54.3 Cuba 131 2.35 41.7 Korea, Rep. 24 3.72 84.2 Bahamas, The 78 2.75 54.2 Senegal 132 2.33 41.2 Taiwan, China 25 3.70 83.6 Namibia 79 2.74 54.1 São Tomé and Príncipe 133 2.33 41.1 Czech Republic 26 3.67 82.9 Ukraine 80 2.74 53.8 Djibouti 134 2.32 41.0 China 27 3.66 82.5 Burkina Faso 81 2.73 53.7 Bhutan 135 2.32 41.0 Israel 28 3.66 82.5 Lebanon 82 2.72 53.2 Fiji 136 2.32 40.8 Lithuania 29 3.63 81.6 El Salvador 83 2.71 52.9 Libya 137 2.26 39.2 Qatar 30 3.60 80.6 Mozambique 84 2.68 52.2 Bolivia 138 2.25 38.8 Hungary 31 3.43 75.3 Guyana 85 2.67 51.7 Angola 139 2.24 38.5 Malaysia 32 3.43 75.2 Morocco 86 2.67 51.6 Turkmenistan 140 2.21 37.6 Poland 33 3.43 75.2 Bangladesh 87 2.66 51.6 Armenia 141 2.21 37.4 Turkey 34 3.42 75.1 Ghana 88 2.66 51.5 Liberia 142 2.20 37.3 India 35 3.42 75.0 Costa Rica 89 2.65 51.1 Gabon 143 2.19 36.9 Portugal 36 3.41 74.7 Nigeria 90 2.63 50.5 Eritrea 144 2.17 36.3 New Zealand 37 3.39 74.0 Dominican Republic 91 2.63 50.4 Chad 145 2.16 36.1 Estonia 38 3.36 73.3 Togo 92 2.62 50.1 Kyrgyz Republic 146 2.16 35.8 Iceland 39 3.35 72.7 Moldova 93 2.61 50.0 Madagascar 147 2.15 35.8 Panama 40 3.34 72.5 Colombia 94 2.61 50.0 Cameroon 148 2.15 35.7 Slovak Republic 41 3.34 72.4 Côte d’Ivoire 95 2.60 49.7 Iraq 149 2.15 35.6 Kenya 42 3.33 72.3 Iran, Islamic Rep. 96 2.60 49.6 Afghanistan 150 2.14 35.4 Latvia 43 3.33 72.1 Bosnia and Herzegovina 97 2.60 49.5 Zimbabwe 151 2.08 33.6 Bahrain 44 3.31 71.7 Comoros 98 2.58 49.0 Lao PDR 152 2.07 33.1 Thailand 45 3.26 69.9 Russian Federation 99 2.57 48.7 Tajikistan 153 2.06 32.9 Chile 46 3.25 69.7 Niger 100 2.56 48.4 Lesotho 154 2.03 31.8 Greece 47 3.24 69.4 Paraguay 101 2.56 48.4 Sierra Leone 155 2.03 31.8 Oman 48 3.23 69.3 Nicaragua 102 2.53 47.5 Equatorial Guinea 156 1.88 27.3 Egypt, Arab Rep. 49 3.18 67.7 Sudan 103 2.53 47.4 Mauritania 157 1.87 26.8 Slovenia 50 3.18 67.7 Maldives 104 2.51 46.9 Somalia 158 1.75 23.2 Croatia 51 3.16 67.0 Papua New Guinea 105 2.51 46.8 Haiti 159 1.72 22.2 Saudi Arabia 52 3.16 66.8 Macedonia, FYR 106 2.51 46.8 Syrian Arab Republic 160 1.60 18.5 Kuwait 53 3.15 66.7 Burundi 107 2.51 46.8 Mexico 54 3.11 65.5 Mongolia 108 2.51 46.7 x C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Summary and key findings Logistics performance both in international Logistics performance trade and domestically is central to the eco- converges at the top, but the nomic growth and competitiveness of countries, gap is widening between the and the logistics sector is now recognized as one worst and best performers of the core pillars of economic development. Policy makers not only in the best perform- The results of Connecting to Compete 2016 point ing countries, but also in emerging economies, to Germany as the best performing country, increasingly see the need to implement coher- with an LPI score of 4.23, and Syria as the low- ent and consistent policies to foster seamless est, with a score of 1.60 (equivalent to 19 per- and sustainable supply chain operations as an cent of Germany’s score on a scale from 1 to engine of growth. 5). The converging trend between the top and Efficient logistics connects firms to domes- worst performers that appeared in the previous tic and international markets through reliable LPI surveys (2007, 2010, 2012, and 2014) seems supply chain networks. Conversely, countries to have slightly reversed. The average scores in characterized by low logistics performance each quintile reveal that the gap between the face high costs, not merely because of trans- top 2 quintiles and the countries at the bottom portation costs but also because of unreliable in performance is widening again (figure 1). supply chains, a major handicap in integrating The modest convergence since 2007 was and competing in global value chains. Supply explained in the 2014 report by a perceived chains are complex, but their performance is largely dependent on country characteristics, Figure 1 LPI score as percentage of especially the soft and hard infrastructure and highest LPI score, by LPI quintile institutions that logistics requires to operate averages, 2007, 2010, 2012, 2014, and 2016 well, such as imports, regulations, procedures, and behaviors. Percent 2007 2010 2012 2014 2016 Now in its fifth edition, the Logistics Per- 90 formance Index (LPI) embodies the experience 80 of logistics professionals worldwide and tries to capture the complexity of supply chains in 70 synthetic indicators that are comparable across countries. The LPI has provided valuable infor- 60 mation for policy makers, traders, and other stakeholders, including researchers and aca- 50 demics, on the role of logistics for growth and the policies needed to support logistics in areas 40 such as infrastructure planning, service pro- 30 vision, and crossborder trade and transport Bottom Fourth Third Second Top quintile quintile quintile quintile quintile facilitation. Source: Logistics Performance Index 2007, 2010, 2012, 2014, and 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 1 improvement in trade-supporting infrastruc- that the good logistics performance of India ture in low- and middle-income countries and, does not improve that of its neighbors. Mean- to less extent, in their logistics services and their while, East Asian economies have performed customs and border management. This explana- consistently well across LPI editions. tion may still be largely valid in the majority of ranked countries. In 2016, however, the widen- Supply chain reliability and ing of the gap between the top and the bottom service quality are key objectives was amplified by the highest average scores ever across all performance groups among the top countries (4.13 in 2016) and the lowest average scores among countries at the Logistics firms have a strong incentive to pro- bottom since 2007 (1.84 in 2007; 1.91 in 2016) vide predictable deliveries in both the developed (table 1). and the developing world. Supply chain reli- The differing pace of progress is also seen ability continues to be a major concern among in the ratings on the quality of domestic trade traders and logistics providers. In a global envi- and transport infrastructure. In the domestic ronment, consignees require a high degree of section of the LPI questionnaire, respondents certainty on when and how deliveries will take were asked to assess the extent of improvements place. This is much more important than the in these areas since 2014. While about 60 per- speed of the delivery. Predictability also carries cent of the respondents in the top 2 quintiles a premium, which many shippers are willing to rated the situation in 2016 as improved or much pay. In other words, supply chain predictability improved, only about a third in the bottom is a matter not merely of time and cost, but also quintile and fewer than half in the third and of shipment quality. In the top LPI quintile, fourth quintiles shared this view. only 13 percent of shipments fail to meet com- Logistics performance captures more than pany quality criteria, the same proportion as in income, as observed since the first LPI report 2014. By comparison, nearly three times more in 2007. International supply chains are orga- shipments in the bottom quintile (over 35 per- nized across groups of regional trading coun- cent) fail to meet company quality criteria. This tries. Provisions for services and trade facilita- finding again illustrates that, in supply chain tion initiatives are designed and implemented efficiency and reliability, the logistics gap is real regionally. Reflecting on these mechanisms, and persistent. the LPI data show that performance is quite Infrastructure development continues to consistent within integrated subregions. For accomplish much in assuring basic connectiv- instance, Western and Central Africa shows ity and access to gateways for most develop- lower performance than Southern Africa or ing countries. This has also been consistently than East A ­ frica, which has engaged in signifi- observed in the LPI since 2007. The perceived cant improvement in trade corridor efficiency. quality of certain types of infrastructure also North African and Middle Eastern developing seems to follow a similar pattern across all LPI countries are doing comparatively worse than editions. The quality of information and com- their income level would indicate, due to lack of munications technology (ICT) infrastructure integration, political unrest, and security chal- is again rated highest across all respondents, lenges. In South Asia, lack of integration means and here the gap between lowest and highest Table 1 Top 10 average and bottom 10 average LPI scores, 2007–16 Indicator 2007 2010 2012 2014 2016 Top 10 average 4.06 4.01 4.01 3.99 4.13 Bottom 10 average 1.84 2.06 2.00 2.06 1.91 Source: Logistics Performance Index 2007, 2010, 2012, 2014, and 2016. 2 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y performers is narrowing the most. By contrast, with a low performance record, where delays satisfaction with rail infrastructure remains and unexpected costs are more common. As in low. The widest gap in satisfaction is with ware- previous editions, this edition finds that border housing and transloading infrastructure: while clearance times tend to be longer in countries 65 percent of the respondents in the top LPI with less friendly logistics environments. quintile regarded the quality of these as high The 2016 results (section 2) imply that trade or very high, only 13  percent in the bottom facilitation tools and principles have taken hold quintile had the same view. Ratings on other in many countries thanks to growing awareness types of infrastructure vary by region. and international initiatives to support trade fa- Trade logistics services are provided under cilitation reforms in developing countries. Co- different environments globally. As in 2014, ordination among government control agencies we see that the quality of services provided by continues to require attention, including the logistics firms is often perceived as better than need to introduce best practices in automation the quality of the corresponding infrastructure (for example, single windows) and risk manage- the firms operate. This may partly be explained ment in non–customs control agencies, which by the respondent base, that is, freight forward- have been less open to reform. Accordingly, cus- ers and logistics firms rating their own services. toms agencies have again obtained much higher Nonetheless, the pattern that emerges from re- LPI ratings than the other agencies rated in the sponses across LPI editions is rather uniform: domestic part of the LPI, such as sanitary and the more international operations, such as air phytosanitary control agencies and those en- and maritime transport and services, tend to forcing the quality or technical standards of receive high scores even if infrastructure bottle- goods. necks exist. Railroads, meanwhile, continue to Yet, the implementation of trade and trans- show low ratings almost everywhere. Low-in- port reform is lagging in the logistically con- come countries still score poorly on road freight strained countries that are most in need of at- services. tention from the international community. Service quality differs substantially at Moreover, their neighbors also often face seri- similar levels of perceived infrastructure qual- ous governance challenges (for example, con- ity. This indicates that even high-quality hard flict-ridden or postconflict countries and fragile infrastructure cannot substitute or replace states). Many landlocked developing countries operational excellence, which is based on the and small island states also fall into this cat- professional skills of service providers, well- egory because their connectivity with global functioning soft infrastructure, and smooth markets may be severely challenged by their eco- business and administrative processes. This is nomic size or geography. Long overdue and still explored in section 3. mostly unresolved implementation challenges, such as troubled regional transit regimes, seri- Trade and transport facilitation ously hamper these countries. The realization of is critical for lower performers sensible facilitation policies remain key for fu- ture progress given that many now have a basic Efficient clearance procedures at the border connective infrastructure. are critical to eliminating avoidable delays and Relatively rapid improvements can also be to improving supply chain predictability. To achieved regionally if countries have a strong po- achieve this, governments need to facilitate litical will and align their efforts in implement- trade, while safeguarding the public against ing administrative reform. This is the case, for harmful activities ranging from health hazards example, of the Northern Corridor that links to crime and terrorism. Realizing these two Burundi, Rwanda, and Uganda with the port of objectives­—­ facilitating trade and safeguard- Mombasa in Kenya and also serves eastern parts ing the public interest­—­is a challenge for policy of the Democratic Republic of Congo, South makers and authorities, especially in countries Sudan, and Tanzania (see section 3). Some of C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 3 the soft trade and transport facilitation reforms not so much with border issues, such as in low with a significant impact were implemented performance countries, but with the internal even before hard infrastructure projects were performance of domestic supply chains (a real- completed. The soft reforms provided a greater, ity not well captured in the main LPI index). more rapid return on investment relative to hard Comprehensive strategies increasingly focus not infrastructure. merely on looking at the sources of costs, but on steering a sector with a large footprint in the Logistics friendlier countries face economy and with links to concerns about the complexity, new policy concerns, environment, jobs, land use, urban planning, and competitive pressure and other issues. A growing number of countries follow this The LPI results since 2007 have shown that route, which is rarely easy. The implementation higher service quality is driving logistics per- of reforms involving many stakeholders can formance in emerging and richer economies. be slow. Except in low performing countries, Yet, the development of services, as in third- or short-term, high-impact interventions (the low fourth-party logistics, is a rather complex policy hanging fruits) are likely to have already been agenda not least because the provision of these implemented. Countries successful in introduc- more advanced services cannot be created from ing far-reaching changes have been those com- scratch or developed purely domestically. In bining regulatory reform with investment plan- logistics-friendly countries, manufacturers and ning, interagency coordination, and incentives traders already outsource much of their basic for operators. Detailed, accurate data are needed transport and logistics operations to third-party for policy making and monitoring. The growing providers and focus on their core business, while availability of large datasets or even big data is a managing more complex supply chains. The new opportunity that so far is being seized only more such advanced services are available at a by a few countries, such as Canada and South reasonable price-cost ratio, the more shippers Africa. will outsource their logistics. The current envi- ronment for international trade­ —­structurally *   *   * slower growth patterns relative to before the 2008–09 financial crisis­—­puts a lot of pressure Logistics performance depends on the availabil- on the industry, which is also pushing for qual- ity to traders of reliable supply chains and pre- ity and innovation. dictable service delivery. Global supply chains The 2016 survey confirms that the policy are becoming more complex, and the safety, agenda is becoming more complex. The demand social, environmental, and other regulations for environmentally friendly logistics solutions, affecting traders and operators are becoming or green logistics, is gradually becoming a com- more demanding. Efficient management and mon feature in most advanced logistics environ- information technology (IT) solutions in both ments (section 3). Two-fifths of survey respon- the private and public sectors are vital tools of dents acknowledge this is a major concern in the trade in high-quality logistics. The ability to the top performance quintile. The 2016 survey manage logistics processes in today’s global busi- introduced a new set of questions on skills and ness environment is a crucial factor in national the logistics labor force. The results highlight a competitiveness. shortage of skilled labor, though there are differ- More than ever, comprehensive reform and ences across countries and job profiles. long-term commitments from policy makers There is thus an expanding need for con- and private stakeholders are needed. The cur- sistent strategies that cut across the numerous rent edition of the LPI provides a unique and policy dimensions, especially in high- and mid- updated reference base to understand key logis- dle-income countries. Policy makers in large tics impediments worldwide and to enable well-­ emerging or developed economies have to deal informed policy making and business decisions. 4 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 1 SECTION The 2016 Logistics Performance Index Introduction regulated infrastructure. International trade is processed by border agencies. Services and France is among the highest performing econ- logistics activities are regulated with fiscal, en- omies in terms of logistics. This is a determin- vironmental, safety, land use, and competition ing factor of our competitiveness. It represents objectives. Since the first edition of this report, 10 percent of national GDP, 200 billion euro in 2007, it has become widely recognized that turnover, and 1.8  million jobs. Our coun- these attributes are captured in the concept of try is particularly known for the quality of logistics performance. Logistics performance its workforce, its infrastructure network, its varies across economies and is influenced by equipment, and the availability of land. But policies. this position cannot be taken for granted, and The quote from France also encapsulates the France needs to further progress to become two main objectives of current logistics strate- a world leader. Ranked only 13th in global gies in all types of economies. First, logistics is logistics (LPI World Bank) behind its clos- an input to much of the economy, that is, in- est neighbors, logistics underperformance is dustry, commerce, and so on. The performance costing our economy between 20 billion and of logistics impacts productivity in other sec- 60 billion euro. tors. This is most often presented in negative Communiqué of the French language in terms of average costs of logistics. Government March 20161 Furthermore, logistics can be a sector of devel- opment in and of itself, where countries with This quote is just one recent example of a major high global or regional connectivity expect to economy viewing logistics as a policy concern play the role of a logistics and trade hub, such as and developing a comprehensive approach the Netherlands in Europe and Dubai or Singa- involving public agencies and the private sec- pore in Asia. tor. It follows the experience of many other Benchmarking indicators such as the Logis- advanced economies (for example, Canada, tics Performance Index (LPI) play a role in in- Finland, Germany, and the Netherlands) and forming the trend in logistics-related reforms. emerging and developing economies such as Synthetic indicators may not do justice to the China, Indonesia, Mexico, Morocco, South complexity and variety of operations in supply Africa, Thailand, and Turkey. chains and may emphasize certain activities Logistics refers to a series of services and at the expense of others. The LPI itself for in- activities, such as transportation, warehous- stance was designed to look at the border com- ing, and brokerage, that help to move goods ponent of supply chains, as trade and transport and establish supply chains across and within facilitation was the priority reform area when borders. Although these services and activities the index was created in 2007. Despite some are carried out by private firms for the benefit improvements of the LPI to capture domestic of private firms, service delivery and the effi- concerns such as environmental sustainability ciency of supply chains depend on public sec- or labor and skill shortages, the LPI is less suit- tor provisions and interventions in a number able for gauging the performance of domestic of domains. Logistics uses publicly funded or logistics. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 5 This report is organized in three sections. in up to eight of their main overseas partner The first one introduces the LPI and its main countries (box 1.1). In the domestic question- index and trends across countries. Section 2 un- naire, respondents are asked to provide qualita- bundles the patterns of domestic policies and tive and quantitative data on the logistics envi- endowments and shows how performance var- ronment in the country in which they work. ies across a number of dimensions. The third In 2016, more than 7,000 country assessments and final section looks at implementation and were made by logistics professionals, in line with emerging policy challenges. the past two editions (box 1.2). Moreover, this edition covers 160 countries in the international Features of the 2016 survey LPI, whereas the domestic LPI covers more than 125 countries. This year’s survey attempts to cap- The 2016 LPI survey follows the same method- ture new trends in logistics practices worldwide, ology as the previous four editions of Connect- such as insights into logistics skills and the chal- ing to Compete: a standardized questionnaire lenges in recruiting qualified staff for the indus- with two parts, international and domestic. In try. As in previous versions of the report, this edi- the international questionnaire, respondents tion includes a question on the extent of demand evaluate six core pillars of logistics performance for environmentally friendly logistics solutions. Box 1.1 Using the LPI The World Bank’s LPI analyzes countries in six components: of firms on production location, choice of suppliers, and selection • The efficiency of customs and border management of target markets. Their participation is central to the quality and clearance credibility of the LPI, and their involvement and feedback have been • The quality of trade and transport infrastructure essential in developing and refining the survey in this fifth edition • The ease of arranging competitively priced shipments of the LPI. In 2016, 1,051 logistics professionals participated in the • The competence and quality of logistics services survey for the LPI. • The ability to track and trace consignments • The frequency with which shipments reach consignees Input and outcome LPI indicators within scheduled or expected delivery times The components have been chosen based on theoretical and empirical research and on the practical experience of logistics pro- Customs Timeliness fessionals involved in international freight forwarding. The figure maps the six LPI indicators to two main categories: Supply • Areas for policy regulation, indicating main inputs to the sup- chain Inter- Infra- national ply chain (customs, infrastructure, and services) structure service shipments delivery • Supply chain performance outcomes (corresponding to LPI indicators of time and reliability: timeliness, international Services Tracking shipments, and tracking and tracing) quality and tracing The LPI uses standard statistical techniques to aggregate the data into a single indicator.a (See appendix 5 for a detailed descrip- Service Areas tion of how the LPI is calculated.) This single indicator can be used for delivery policy performance to compare countries, regions, and income groups. It can also be outcomes regulations used for country-level work. (inputs) Time, cost, reliability Because operators on the ground can best assess the vital as- pects of logistics performance, the LPI relies on a structured online survey of logistics professionals from the companies responsible for moving goods around the world: multinational freight forward- See the 2016 LPI questionnaire at http://lpi.worldbank.org/. ers and the main express carriers. Freight forwarders and express carriers are best positioned to assess how countries perform. And a. In all five editions of the LPI (2007, 2010, 2012, 2014, and 2016), statistical their views matter because thes operators directly affect the choice aggregation has produced an overall index that is close to the simple of shipping routes and gateways, thereby influencing the decisions average of country scores across the six LPI components. 6 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 1.2 How precise are LPI scores and ranks? Although the LPI and its components now offer the most compre- lower bound of the 2016 LPI score exceeds the upper bound of hensive and comparable data on country logistics and trade facilita- the 2014 score. tion environments, they have a limited domain of validity. First, the Because of the LPI’s limited domain of validity and the need for experience of international freight forwarders might not represent confidence intervals to account for sampling error, a country’s exact the broader logistics environment in poor countries, which often ranking might be less relevant to policy makers than its proximity rely on traditional operators. International and traditional operators to others in a wider performance group or its statistically signifi- might differ in their interactions with government agencies and in cant improvements. Still, a close examination of the distribution of their service levels. Most agents and affiliates of international net- changes in ranking indicates that these behave similarly across all works in developing countries serve large companies and perform five editions of the index. at different levels, including in time and cost, relative to traditional One should thus interpret especially the ranks and changes in trading networks. ranks from one LPI edition to another with caution. In the aggregate Second, for landlocked countries and small island states, the data in the past four LPI surveys, 46 countries scored 70 percent LPI might reflect access problems outside the country assessed, or more of the top performer. For these countries, the average dif- such as transit difficulties. The rating of a landlocked country, such ference per rank position was 0.021 score points. For the next 53 as Lao PDR, might not adequately reflect local trade facilitation countries scoring 50–69 percent of the top performer, the average reform efforts, as these still depend on international transit routes difference per rank was only 0.011 score points. In the 40–49 per- mainly through Thailand and Vietnam. cent range with 48 countries, the average difference per rank was a To account for the sampling error created by the LPI’s sur- mere 0.006 score points. This means that countries at similar per- vey-based dataset, LPI scores are presented with approximate formance levels may have substantially different ranks, especially 80 percent confidence intervals (see appendix 5). These intervals in the middle and lower range. yield upper and lower bounds for a country’s LPI score and rank.a Confidence intervals must be examined carefully to determine a. Upper bounds for LPI ranks are calculated by increasing a country’s whether a change in score or a difference between two scores LPI score to its upper bound while maintaining all other country scores is statistically significant. An improvement in a country’s perfor- constant and then recalculating LPI ranks. An analogous procedure is mance should be considered statistically significant only if the adopted for lower bounds. Key findings of the 2016 The lower-middle-income group contin- international LPI ues to be led by large economies such as India and Indonesia and emerging economies such as Once more, high-income economies solidify Kenya and Vietnam (table 1.3). their past performance by occupying the top 10 Meanwhile, the top-performing upper- positions of the ranking in 2016 (table 1.1). This middle-income economies show mixed perfor- empirical regularity has been present in all edi- mance, although the overall group composition tions of the LPI. In fact, the composition of the remains similar to previous editions, with South top 15 on the list of best performing countries Africa and China leading the group (table 1.4). has only changed marginally since 2014 and Within the low-income group, East African even 2010. This is not surprising. These coun- countries are leading the performance in this tries have been traditionally recognized as dom- year’s edition (table 1.5). inant players in the supply chain industry, with Figure 1.1 presents the cumulative distribu- a global footprint in transportation and logistics tion of LPI scores. The vertical lines represent services provision. the boundaries of LPI quintiles: five groups con- The bottom 10 countries in the ranking are taining the same number of countries rated in composed of low-income and lower-middle-in- the LPI. The bottom quintile includes countries come countries (table 1.2). Generally speaking, with the lowest LPI scores, and the top quintile, these are either fragile economies affected by those with the highest scores. As in the past, armed conflict, natural disasters, and political in the third and fourth quintiles, the range of unrest, or landlocked countries that are natu- scores is similar. This means that country LPI rally challenged by economies of scale or geogra- scores are closer to each other, and any altera- phy in connecting to global supply chains. tion in the country’s performance (and that of C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 7 Table 1.1 Top 10 LPI economies, 2016 Economy LPI 2016 rank LPI 2016 score LPI 2014 rank LPI 2014 score Germany 1 4.23 1 4.12 Luxembourg 2 4.22 8 3.95 Sweden 3 4.20 6 3.96 Netherlands 4 4.19 2 4.05 Singapore 5 4.14 5 4.00 Belgium 6 4.11 3 4.04 Austria 7 4.10 22 3.65 United Kingdom 8 4.07 4 4.01 Hong Kong SAR, China 9 4.07 15 3.83 United States 10 3.99 9 3.92 Source: Logistics Performance Index 2014 and 2016. Table 1.2 Bottom 10 LPI 2016 economies Economy LPI 2016 rank LPI 2016 score LPI 2014 rank LPI 2014 score Zimbabwe 151 2.08 137 2.34 Lao PDR 152 2.07 131 2.39 Tajikistan 153 2.06 114 2.53 Lesotho 154 2.03 133 2.37 Sierra Leone 155 2.03 na na Equatorial Guinea 156 1.88 136 2.35 Mauritania 157 1.87 148 2.23 Somalia 158 1.75 160 1.77 Haiti 159 1.72 144 2.27 Syrian Arab Republic 160 1.60 155 2.09 na is not applicable. Source: Logistics Performance Index 2014 and 2016. Table 1.3 Top-performing lower-middle-income economies Economy LPI 2016 rank LPI 2016 score LPI 2014 rank LPI 2014 score India 35 3.42 54 3.08 Kenya 42 3.33 74 2.81 Egypt, Arab Rep. 49 3.18 62 2.97 Indonesia 63 2.98 53 3.08 Vietnam 64 2.98 48 3.15 Pakistan 68 2.92 72 2.83 Philippines 71 2.86 57 3.00 Ukraine 80 2.74 61 2.98 El Salvador 83 2.71 64 2.96 Guyana 85 2.67 124 2.46 Source: Logistics Performance Index 2014 and 2016. 8 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 1.4 Top-performing upper-middle-income economies Economy LPI 2016 rank LPI 2016 score LPI 2014 rank LPI 2014 score South Africa 20 3.78 34 3.43 China 27 3.66 28 3.53 Malaysia 32 3.43 25 3.59 Turkey 34 3.42 30 3.50 Panama 40 3.34 45 3.19 Thailand 45 3.26 35 3.43 Mexico 54 3.11 50 3.13 Brazil 55 3.09 65 2.94 Botswana 57 3.05 120 2.49 Romania 60 2.99 40 3.26 Source: Logistics Performance Index 2014 and 2016. Table 1.5 Top-performing low-income economies Economy LPI 2016 rank LPI 2016 score LPI 2014 rank LPI 2014 score Uganda 58 3.04 na na Tanzania 61 2.99 138 2.33 Rwanda 62 2.99 80 2.76 Cambodia 73 2.80 83 2.74 Burkina Faso 81 2.73 98 2.64 Mozambique 84 2.68 147 2.23 Togo 92 2.62 139 2.32 Comoros 98 2.58 128 2.40 Niger 100 2.56 130 2.39 Burundi 107 2.51 107 2.57 na is not applicable. Source: Logistics Performance Index 2014 and 2016. its neighbors) generates larger changes in the most others in their income group (second ranking relative to those countries in other LPI quintile). quintiles (box 1.3). • Logistics-friendly: includes top perform- As in past LPI reports, LPI scores are broken ers, mostly high-income countries (top LPI down into four categories, consistent with the quintile). score quintiles, used in all editions of Connect- ing to Compete, as follows: Logistics performance is rising, and • Logistics-unfriendly: includes countries with performance is heterogeneous severe logistics constraints, such as the least developed countries (bottom LPI quintile). With the fifth edition of the LPI, a number • Partial performers: includes countries with a of trends observed in previous reports repeat level of logistics constraints most often seen themselves. There are still marked differences by in low- and middle-income countries (third component and quintile (figure 1.2). The per- and fourth LPI quintiles). formance of border agencies and infrastructure • Consistent performers: includes countries is the lowest among all quintiles, but especially rated better on logistics performance than so in the worst performing countries. On the C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 9 Figure 1.1 Cumulative distribution of LPI scores Cumulative density 1.0 Bottom quintile Fourth Third Second quintile Top quintile quintile quintile Partial performers 0.8 Logistics unfriendly Logistics friendly 0.6 0.4 Consistent performers 0.2 0.0 1.50 2.00 2.50 3.00 3.50 4.00 4.25 LPI score Source: Logistics Performance Index 2016. other hand, the timeliness component seems pillar. A positive entry indicates that a compo- to outperform the rest and is generally viewed nent score is higher than a group’s overall inter- by logistics professionals as the least problem- national LPI score and vice versa for a negative atic pillar. However, the difference is greatest entry. again among countries that show a dismal over- A number of features stand out. Customs all score. and border agencies continue to underperform We have also examined which of the six systematically in comparison with the other components of the international LPI are above components of the LPI. Infrastructure exhibits the overall index and which are below (table a similar behavior as in previous occasions, with 1.6) as an indication of the performance of each the highest quintile only showing a positive Figure 1.2 LPI component scores, by LPI quintile LPI score Customs Infrastructure Ease of shipping Quality of logistics Tracking and Timeliness arrangements services tracing 4.5 4.0 3.5 3.0 2.5 2.0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile Source: Logistics Performance Index 2016. 10 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 1.3 LPI results: Consistent within but not necessarily between regions? As observed in previous editions of the report, logistics perfor- transport facilitation in particular, much attention has been paid to mance, as captured by the LPI, transcends the overall level of de- the disadvantaged position of low- and middle-income landlocked velopment and income. Geography matters, too. The crossborder countries. Lack of access to the sea poses persistent challenges nature of many logistics activities, such as trucking or freight for- to the growth and development of landlocked developing coun- warding, means that logistics performance is driven in part by tries and has been the main factor hindering their ability to bet- subregional connectivity patterns. The performance of a regional ter integrate with the global trading system. The transit of export gateway may diffuse across regional borders. As the example of and import goods through the territory of at least one neighboring East Africa shows (featured in this report), consistent improvement state and frequent change of transport mode lead to high transac- in integration and corridor performance benefits several countries. tion costs and reduced international competitiveness. The issue of The standard regional groupings (Sub-­ Saharan Africa, Eastern landlocked developing countries has also generated much policy Europe and Central Asia) represent clear hemispheric blocs, yet work such as the 2003 Almaty Program of Action under the United are too large to reveal much about performance convergence or Nations and the Vienna Program of Action 2014–24.a heterogeneity within and between subregions. The trade logistics handicap is illustrated by the average overall In an attempt to reach a finer attribution of performance, re- LPI scores for 2010–16 of landlocked and coastal countries across gions were subdivided as shown in the figure, and LPI score vari- World Bank regions. This comparison shows a rather consistent ance was decomposed in two: on one hand, the variance explained pattern, where coastal countries score better than their landlocked by variations in performance within subgroups and, on the other peers at similar income levels. In the upper-middle-income group, hand, variance explained by variability between subgroups. Overall, this difference in Europe and Central Asia was 0.31 score points. total variance in LPI scores can be explained majorly (64 percent) The difference was even larger among lower-middle-income econo- by variance across subregions. mies in South Asia (0.52 score points). In Sub-­ Saharan Africa, how- While this is an intuitive and expected result, it is also indica- ever, several landlocked countries performed better than coastal tive of the coordinated movement in the rank that regional blocs ones: by 0.20 points in the low-income group and by 0.14 points in can experience relative to neighboring subregions, and it shows the upper-middle-income group. Only Sub-­ Saharan African coun- that subregional convergence in scores merits further analysis. tries in the lower-middle-income group followed the familiar pat- While certain positive regional developments could explain such tern, with a 0.20 point lead by coastal countries over landlocked performance premiums in specific parts of the world (for instance, countries. Among high-income countries of the Organisation for elimination of border formalities within corridors), other, negative Economic Co-operation and Development (OECD), the difference occurrences (such as armed conflict and political unrest) can pres- between landlocked (3.69) and coastal countries (3.71) was almost ent a contagion phenomena not easy to avoid. insignificant (0.02 points) (see figure). Coastal access is another important enabler of logistics per- formance. In development economics generally and in trade and a. World Bank and UN-OHRLLS (2014). LPI score means, by geographical region LPI 2016 mean 4.0 3.5 3.0 2.5 2.0 an ca ca ca es ia c ia uth rica a a ion ca cil pe e cifi ric ric rop As As un tat eri eri eri ri be We Euro Af Af Af Af Pa Eu Co uth st Am Am Am tS rib al ern st rth Ea & Ca en rn rn So ntr Ea al uth rth No ia ste ste nd ntr Ce rat As No So & pe ea So Ce pe & st st de uth ea oo rn Ea In So ste uth lf C le of dd We So Gu h alt Mi we on mm Co Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 11 Table 1.6 Deviation of each component from the overall LPI score, by quintile some factors and groups move faster than oth- ers. In low-income and lower-middle-income Percent countries, average LPI scores have progressed Ease of arranging Quality of the most rapidly in customs, infrastructure, and international logistics Tracking the quality of logistics services (figure 1.3). Quintile Customs Infrastructure shipments services and tracing Timeliness Progress can be also tracked when asking re- Bottom quintile −0.13 −0.14 0.05 −0.05 −0.11 0.35 spondents about the change in the environment Fourth quintile −0.15 −0.19 −0.01 −0.06 −0.06 0.43 Third quintile −0.23 −0.22 0.06 −0.06 −0.01 0.42 for logistics since the last LPI edition. As in the Second quintile −0.19 −0.13 −0.03 −0.12 0.02 0.44 past, survey respondents in better performing Top quintile −0.19 0.04 −0.16 −0.02 0.06 0.28 countries perceive more concrete improvements than in nonperforming economies (table 1.7). Note: All calculations are based on the weighted average score for the LPI and its components over 2007–14. Source: Logistics Performance Index 2016. The contrast is the highest in absolute terms for all services (public and private) and infrastruc- markup compared with the overall score. None- ture variables relative to regulations and gover- theless, this time around, the quality of logistics nance variables. services tends to be lower than the general per- Streamlining border clearance procedures formance across all quintiles. This was not the and ensuring access to physical infrastructure case for the highest performing countries in the will continue to be a priority for low-income past. Moreover, the tracking and tracing com- economies. On the other hand, upper-middle- ponent also is lower than the overall score across income countries have seemingly improved all three lowest quintiles. Although this can be faster in the quality of logistics services, as in explained by a myriad of factors, a possible in- the previous 2014 edition. This continues to terpretation is that, during economic down- support the idea that middle-income countries turns, investments in technology are sometimes have increasingly shifted their focus toward soft postponed. Another interpretation is that the reforms and less so in physical infrastructure. requirements for tracking and tracing are more Still, a notable gap in LPI scores remains challenging than before, and today’s technical between high- and low-income countries (fig- solutions no longer meet the requirements. ure 1.4). High-income countries, on average, As observed from previous editions, average surpass low-income countries by 45  percent country LPI scores generally improve, although in terms of LPI scores. Moreover, among the Figure 1.3 Percentage change in LPI scores, customs, infrastructure, and quality of logistics services, 2014–16 Percentage change Customs Infrastructure Quality of logistics services 15 10 5 0 Low income Lower middle income Upper middle income Source: Logistics Performance Index 2014 and 2016. 12 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y top 30 performing countries, 22 are members Table 1.7 Respondents reporting an improved or much improved of the Organisation for Economic Co-oper- logistics environment since 2012, by LPI quintile ation and Development (OECD), almost un- Percent of respondents changed since the 2014 report. Nonetheless, Component Bottom quintile Fourth quintile Third quintile Second quintile Top quintile countries can still outperform their income Customs 40 53 53 65 65 group peers despite the performance gap. This Other border procedures 31 37 40 54 60 is why income alone cannot explain why per- Trade and transport formance varies widely among countries in cer- infrastructure 34 48 50 60 60 tain income groups. The list of countries over- ICT infrastructure 41 54 67 78 73 performing their income group peers includes Private logistics services 39 63 61 76 65 Logistics regulation 19 35 39 47 35 Kenya, Rwanda, and Uganda, but also China Incidence of corruption 22 36 37 41 40 and India (figure 1.5). Conversely, the list of countries that fare below their potential for a ICT is information and communications technology. Source: Logistics Performance Index 2016. given level of income includes most resource- rich economies such as Equatorial Guinea, Gabon, the Russian Federation, and Trinidad survey-based, sampling errors occur. Statisti- and Tobago. cally significant changes are revealed only if For the first time in the history of the Con- the confidence intervals for the 2016 and 2014 necting to Compete reports, landlocked countries scores do not overlap, which is only the case for are no longer automatically the most unfortu- the economies in table 1.8. nate ones, as evidenced by, for instance, the per- Following up on a feature introduced in the formance of Rwanda and Uganda. Despite the 2014 report, the scores of the six LPI compo- mentioned variations, caution should be exerted nents across the four latest surveys were used when interpreting LPI rankings. to provide a bigger, better balanced picture of country performance. This approach reduces Trends over the past four LPI editions the noise and random variation from one LPI survey to another and enhances the comparison The gap in relative LPI scores­ —­t he scores of the 167 countries in the 2016 edition, one expressed as a percentage of the leading coun- more than in the 2014 aggregation. —­ try’s score­ is quite similar to the gap revealed in past years. Nonetheless, a relatively novel Figure 1.4 Average LPI scores and result is that the average relative score perfor- minimum-maximum ranges, mance in the three lowest quintiles shows a by income group small decrease compared with the last three LPI LPI score editions (figure 1.6). 5 Thus, in the past, the gap between the best and worst performing countries was smaller for countries with lower scores. In the 2016 edition, 4 the relative lowest performer is the Syrian Arab Republic, with a score equal to 19 percent of the 3 score of the highest performer (Germany). In 2014, the relative lowest performer was ­Somalia, with a score equal to 25 percent of the score of 2 the highest performer. The correlation between the 2014 and 2016 LPI scores is stronger than before, with 0.93 in 1 High Upper middle Lower middle Low scores, and 0.90 between ranks (whereas it was income income income income 0.91 and 0.86 between 2014 and 2012). One Note: Vertical rules show minimum-maximum range. Source: Logistics Performance Index 2016. should keep in mind that, because the data are C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 13 Figure 1.5 LPI overperformers and underperformers LPI score 2016 4.5 4.0 South Africa China 3.5 India Kenya Uganda Tanzania 3.0 Rwanda Mozambique Pakistan Brunei Darussalam Burundi Russian Federation 2.5 Belarus Trinidad and Tobago Linear regression Libya Gabon Iraq 2.0 Turkmenistan Montenegro Equatorial Guinea 1.5 5 6 7 8 9 10 11 12 Log of GDP per capita (US$) Note: Fitted values are based on an ordinary least squares regression using data for all countries. Underperformers (black diamonds) are the non–high-income countries with the 10 smallest residuals. Overperformers (black circles) are the non–high-income countries with the 10 largest residuals. Source: Logistics Performance Index 2016. Figure 1.6 LPI scores as a percentage of the can oscillate quite a lot, and the change will not best performer, LPI 2010–16 be statistically significant. This also happened in several countries in 2014–16, especially those Percent 2010 2012 2014 2016 with a wide confidence interval in their scores, 90 indicating more disagreement among the re- 80 spondents. The impact tends to be amplified if the number of observations is low, as is often 70 the case in smaller countries. Large traders, such as China, Germany, the United Kingdom, and 60 the United States, had confidence intervals at 0.05 score points or below in the 2016 LPI, 50 which is about 1 percent or less of their scores. 40 By contrast, the Republic of Congo (confidence interval at 0.48), Morocco, and Lebanon (both 30 at 0.41) had the largest confidence intervals in Bottom Fourth Third Second Top quintile quintile quintile quintile quintile 2016, over 15 percent of their scores. Also in this second aggregated 2010–16 Source: Logistics Performance Index 2010, 2012, 2014, and 2016. LPI, Germany ranked highest at 4.17 (4.10 in the aggregated 2007–14 LPI), followed by the In this 2016 report, the four previous years’ Netherlands 4.12 (4.05) and Singapore 4.10 scores in each component were given weights: (4.06). The top 3 countries are the same, even 6.7  percent for 2010, 13.3  percent for 2012, if the Netherlands and Singapore have traded 26.7 percent for 2014, and 53.3 percent for 2016 places. Of the 28 European Union member (the most recent data carry the most weight; fig- states and the 34 OECD members, 14 and 22, ure 1.7). The method is identical to the one in respectively, were among the top 30 countries. the 2014 report, which used the data for 2007, The non-OECD economies in this group were 2010, 2012, and 2014. Singapore (3rd); Hong Kong SAR, China (8th); The possibility to use such weighted values United Arab Emirates (19th); Taiwan, China is an important feature because an individual (23rd); South Africa (25th); China (26th); country’s score and, consequently, also its rank Qatar (29th; new among the top 30); and 14 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Malaysia (30th). All but two of the top 30 were Table 1.8 Economies with statistically significant changes in LPI scores high-income countries; Malaysia and South Af- rica are upper-middle-income countries. Statistically significant Low Lower middle Upper middle High change in LPI score, 2014–16 income income income income Also this time, all OECD countries were Positive change Tanzania India South Africa Germany in the top third. The top third in the previous Congo, Dem. Rep. Kenya China Israel 2007–14 LPI included all European Union Austria Switzerland member states, but, now, two of them, Roma- Hong Kong SAR, China Singapore nia at 3.05 (ranked 56th) and Bulgaria at 2.96 United Arab Emirates Venezuela, RB (62nd), fall narrowly outside this category. No change 135 countries In the aggregated international LPI, Somalia Negative change Haiti Tajikistan Malaysia again scores lowest at 1.67 (1.63 in the previous Thailand LPI), ranked 167th. Despite some convergence Source: Logistics Performance Index 2014 and 2016. of countries’ logistics performance since the 2007 LPI, the logistics gap between high- and low-income countries remains wide. As in previ- occupies the second-lowest rank, 166th, at 1.94 ous LPI surveys, the countries with the weakest in the aggregated 2010–16 LPI. performance in 2016 were least developed coun- The convergence of performance­ —­ broadly, tries, especially landlocked countries or small the range from rank 40 to 120­ —­ means this island states, some of them also conflict-ridden. space is crowded with countries scores only sep- This is vividly illustrated by the Syrian Arab Re- arated by a few decimals (box 1.4). Thus, some public, which scored 2.31 and was ranked 148th large changes in rank might be witnessed in this of 166 countries in the 2007–14 LPI. Because middle ground, even if the underlying score of its low score and rank in the 2016 LPI, it now changes are only marginal. Figure 1.7 Weighted aggregate international LPI scores, 2010–16 Percent of top performer Weighted average, 2010–16 2012 2014 2016 100 75 50 25 0 165 150 125 100 75 50 25 1 LPI rank Source: Logistics Performance Index 2010, 2012, 2014, and 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 15 Box 1.4 Connectivity, logistics networks, and logistics performance Since the first edition of Connecting to Compete in late 2007, many sector development efforts that may promote connectivity. Larger policy packages promoting gains in logistics, trade facilitation, countries typically have an advantage, and smaller ones have to and transport have been labeled as connectivity. The Asia-Pacific exert more effort to attract international transport at low cost and Economic Cooperation (APEC), for example, has a supply chain sufficient regularity. connectivity initiative, while Indonesia has set up a connectivity As one might expect, the LPI relates to other connectivity in- program, as has a group of countries in Central America and the dicators, such as the Liner Container Shipping Connectivity Index Caribbean. Yet, despite the relevance and coherence of the policies, (LSCI), published by UNCTAD. The figure below illustrates this cor- the concept remains intuitive and often loosely defined, such that relation, but also confirms that the two indicators indeed capture connectivity may become a catchword with too blurry a relation to tied but complementary dimensions in connectivity. such practicalities as trade facilitation and logistics. The point can also be made by taking an inverse approach, focus- Some clarification and formalization of the concept have been ing on trade costs: trade costs are high in poorly connected peripheral proposed.a Trade logistics is supported by companies that operate countries and low in well-connected hubs. Research by the World in networks. International transportation, shipping, or air transport Bank and the United Nations Economic and Social Commission for takes place in complex networks structured in hubs and spokes. The Asia and the Pacific on trade costs has shown that connectivity to connectivity of a country, or perhaps one of its ports or airports, is maritime and air transport networks, along with logistics performance, defined as how central this country is to those networks. Connectiv- are the main determinants of a country’s overall level of trade costs. ity partly reflects geography and the global structure of transporta- An additional challenge that is not addressed by existing data tion and logistics networks. Country-specific trade transaction costs is internal connectivity, particularly in large countries. The LPI mea- coming from supply chain inefficiencies increase economic distance sures performance at key international gateways in countries such and reduce connectivity. Hence, policies that increase logistics per- as India and China, but does not address how easy or difficult it is formance improve connectivity, notwithstanding network geography. to move goods to the hinterland. Yet such movements are important Of course, connectivity is not a purely exogenous concept. from developmental and equity standpoints. Internal trade costs Instead, it is determined by a range of factors. One is market size: likely remain high in many countries, and reducing them could make larger markets create more demand for international shipments; so, a significant difference to the lives of producers and consumers container lines, which operate on a network basis, are more likely outside main cities. for business reasons to make such countries more central in their schedules. It is therefore not only a country’s policies and private a. Arvis and Shepherd (2011); Hoffmann and Ojala (2010). The LPI and the Liner Shipping Connectivity Index Logistics Performance Index 2016 4.5 4.0 3.5 3.0 2.5 2.0 1.5 20 40 60 80 100 120 140 160 180 Liner Shipping Connectivity Index 2015 Source: Logistics Performance Index 2016. 16 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 2 SECTION Unbundling logistics performance The international LPI provides some prelimi- which suggests that developing countries have nary information on the drivers of overall been investing heavily in modern technologies, logistics performance. To unbundle the survey perhaps even leapfrogging intermediate levels results further, however, it is necessary to refer in some cases. Of course, ICTs cannot replace to the domestic LPI. This section is based on the other types of hard infrastructure, so a renewed domestic LPI, where surveyed logistics profes- focus on the other areas is needed. sionals assess the logistics environments in the Infrastructure, though still a constraint in countries where they work. The domestic part developing countries, seems to be improving. thus contains more detailed information on Since the previous LPI survey, there is a general countries’ logistics environments and core logis- perception that infrastructure has improved in tics processes and institutions. This approach all performance quintiles (figure 2.1), but more looks at the logistics constraints within coun- so in the top-performing countries. If this per- tries, not merely at the gateways, such as ports ception reflects a faster rate of infrastructure or borders. It analyzes country performance in improvement from an already strong base in four major determinants of overall logistics per- those countries, it might indicate persistence formance: infrastructure, services, border pro- of the logistics gap identified in previous edi- cedures, and supply chain reliability. tions. Of particular concern is the lower figure recorded in the bottom quintile, which would Infrastructure be consistent with a widening gap. Satisfaction with infrastructure quality Survey respondents in top-quintile countries varies by infrastructure type. As in previous rated their infrastructure far more highly than years, respondents in all LPI quintiles are most others (table 2.1). Differences among the other satisfied with ICT infrastructure. As in 2014, four quintiles are less striking, especially for there is evidence of a narrowing infrastructure roads and rail. It is important to highlight that gap, particularly between the top and bottom the spread of scores is narrowest in informa- quintiles where the rate of improvement seems tion and communications technology (ICT), noticeably more rapid than in the last version of this report; improvement in the middle quintiles is on a par with what has been ob- Table 2.1 Respondents rating infrastructure quality high or very high, by infrastructure type and LPI quintile served previously. By contrast, but in line with previous reports, rail infrastructure inspires Percent of respondents general dissatisfaction. In the bottom quintile, Warehousing and LPI quintile Ports Airports Roads Rail transloading ICT infrastructure generally fails to satisfy, an excep- Bottom quintile 19 21 17 14 13 27 tion to the pattern of variation. Fourth quintile 18 28 13 15 19 33 Similar patterns emerge when the domestic Third quintile 31 35 16 14 27 39 LPI data on infrastructure are disaggregated Second quintile 35 32 24 7 31 60 by World Bank region, excluding high-income Top quintile 63 66 59 36 65 76 countries (table 2.2). The highest ratings in all regions except East Asia and the Pacific are for ICT is information and communications technology. Source: Logistics Performance Index 2016. ICT. Ratings for other types of infrastructure C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 17 Figure 2.1 Respondents rating trade and highly, typically at or close to the strongest transport infrastructure quality scores in this category (table 2.3). 2 Ratings for improved or much improved the other provider types vary more widely across since 2012, by LPI quintile all quintiles, though rail transport service provi- Percent of respondents sion, similar to rail infrastructure, consistently receives low ratings. And, as with infrastruc- 60 ture, countries in the top quintile receive by far 50 the highest ratings for service provider quality and competence. Rail transport aside, service 40 providers in all categories are rated highly in quality and competence in the top-performing 30 countries, although the scores for consignees or shippers are lower than the scores for most other 20 types of service provision. Respondents in all LPI quintiles are nearly 10 always more satisfied with service providers 0 than with infrastructure quality (compare table Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest (low (average (high (highest 2.1 with table 2.3). But the difference is gener- performance) performance) performance) performance) performance) ally smaller in the top-performing countries. Source: Logistics Performance Index 2016. The contrast is particularly strong in the case of maritime transport in the second and third vary more widely by region, but two features quintiles. stand out. First, satisfaction with road and rail The performance gap between services and infrastructure is especially low in Latin America infrastructure appears generally across World and the Caribbean, as in 2014, but also in South Bank regions (table 2.4). It is particularly stark Asia in this edition. Second, satisfaction with for air transport in South Asia and for mari- rail infrastructure is again low in all regions, as time transport in East Asia and the Pacific, Eu- was the case for the analysis by LPI quintile. rope and Central Asia, and South Asia. These data suggest a need to develop transport-related Services infra­structure so that positive reforms to service markets can bring maximum possible benefits The quality and competence of core logistics to end users. service providers is another important part of overall country performance. For countries in Border procedures and time all LPI quintiles, freight forwarders are rated The LPI includes several indicators of border procedures and time. Breakdowns of these Table 2.2 Respondents rating infrastructure quality high or very high, by infrastructure type and region data by region and income group are shown in appendix 2 and by time and cost and by country Percent of respondents in appendix 3. Warehousing and Region Ports Airports Roads Rail transloading ICT East Asia and Pacific 23 37 20 21 8 27 Import and export time Europe and Central Asia 27 48 24 22 30 50 A useful outcome measure of logistics per- Latin America and Caribbean 21 22 12 3 15 34 formance is the time taken to complete trade Middle East and North Africa 33 35 24 20 31 36 transactions. The median import lead time for South Asia 18 25 5 3 18 65 port and airport supply chains, as measured for Sub-Saharan Africa 25 23 18 17 23 32 the LPI, is generally lower in better performing groups (figure 2.2): it takes around three times ICT is information and communications technology. Source: Logistics Performance Index 2016. as long to import in the bottom quintile as in 18 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 2.3 Respondents rating service quality and competence high or very high, by service type and LPI quintile Percent of respondents Maritime Warehousing, Trade and Road Rail Air transport transloading, Freight Customs transport Consignees LPI quintile transport transport transport and ports and distribution forwarders brokers associations or shippers Bottom quintile 17 6 30 36 16 34 17 19 31 Fourth quintile 23 13 36 33 22 41 30 18 29 Third quintile 26 15 50 53 41 54 40 28 33 Second quintile 37 18 48 54 41 56 40 29 28 Top quintile 66 40 75 68 74 80 79 62 49 Source: Logistics Performance Index 2016. the top quintile.3 This substantial gap is larger Table 2.4 Respondents rating services high or very high vs respondents than the one observed in 2014 and closer to the rating infrastructure high or very high, by region 2012 numbers, which may indicate that trade Difference in shares (percentage points) facilitation reforms need to be approached with Maritime Warehousing, renewed vigor. transport Air Road Rail transloading, Region and ports transport transport transport and distribution Importing in all LPI quintiles takes lon- East Asia and Pacific 25 13 7 0 16 ger by land than by air or sea. The correlation Europe and Central Asia 28 5 11 –6 16 between land distance and import lead time Latin America and Caribbean 12 9 5 1 19 suggests that geographic hurdles, in addition Middle East and North Africa 10 0 9 –8 7 to infrastructure, service provision, and other South Asia 33 31 11 1 8 logistics issues, are important in determining a Sub-Saharan Africa 17 17 3 –1 2 country’s ability to connect with world markets. Besides geography and speed en route, an- Source: Logistics Performance Index 2016. other factor in import lead times is the efficiency of border processes. Time can be reduced at all tape, excessive and opaque procedural require- stages of this process, but especially in clearing ments, and physical inspections. Although the goods on arrival (see figure 2.2). Countries with time to clear goods through customs is a fairly low logistics performance need to reform their small fraction of total import time for all LPI border management so that they can cut red quintiles, it rises sharply if goods are physically Figure 2.2 Median import lead time and average clearance time, by LPI quintile Days Import lead time (ports and airports) Import lead time (land) 12 10 Average clearance time without physical inspection 8 Average clearance time with physical inspection 6 4 2 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 19 inspected, even in top-performing countries. high-income countries. Many low-income Core customs procedures are similar across countries have long export lead times, hurt- quintiles. But low performing countries show ing their export competitiveness and ability to a far higher prevalence of physical inspection, trade internationally. even subjecting the same shipment to repeated Unlike lead times, which vary considerably inspections by multiple agencies (table 2.5). worldwide, customs procedures are becoming Export supply chains typically have a much more similar (see table 2.5). Even the bottom- lighter procedural burden than import sup- quintile countries tend to adopt core customs ply chains, so lead times are shorter for ex- best practices. Even as customs procedures be- ports than imports (figure 2.3). But export come gradually more similar, many countries lead times display the familiar logistics gap: still find their supply chain performance con- they are twice as long in low-income countries strained by other border agencies, as customs is relative to high-income countries (figure 2.4). not the only agency in border management. Co- Moreover, export times for land supply chains operation among all such agencies­ —­ standards; differ much more between low-income coun- transport; veterinary; and health, sanitary, tries and the rest than between middle- and and phytosanitary­ —­ is critical to reform. So is Table 2.5 Respondents indicating that listed customs procedures are available and being used, by LPI quintile Percent of respondents, unless otherwise indicated Customs procedure Bottom quintile Fourth quintile Third quintile Second quintile Top quintile Online processing of customs declaration 56 74 87 84 97 Requirement that a licensed customs broker be used for clearance 85 87 86 78 63 Choice of location of final clearance 67 70 65 76 74 Release with guarantee pending final clearance 65 58 55 63 60 Physical inspection of import shipments (percent of shipments) 27 26 21 21 5 Multiple physical inspections of import shipments 13 15 7 5 3 Source: Logistics Performance Index 2016. Figure 2.3 Median export lead time, by LPI quintile Days Port or airport Overland 12 10 8 6 4 2 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2016. 20 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Figure 2.4 Median export lead time, by income group Days Port or airport Overland 14 12 10 8 6 4 2 0 High income Upper middle income Lower middle income Low income Source: Logistics Performance Index 2016. introducing modern approaches to regulatory agencies continue to represent a serious impedi- compliance. ment to overall improvements in border agency Data for the 2016 LPI show that the per- performance. formance gap between customs and other border agencies remains substantial (table Red tape 2.6). For many countries, the key to improv- Indicators for red tape show the same lack of ing border agency performance may in fact lie border coordination, with a resultant burden with reforms to agencies other than customs. on private logistics operators. In countries in the One reason for this difference between agen- bottom quintile, operators typically deal with cies is that fewer inspection procedures are re- around twice as many government agencies and quired for products that are not perishable or documentary requirements as those in countries time sensitive. Another is that health, sanitary, in the top quintile (figure 2.5). Countries in the and phytosanitary agencies have been slow to top quintile typically require two supporting automate. documents for trade transactions; those in the A glance at table 2.6 and its equivalent for bottom, four or five, a persistent logistics gap the 2014 LPI (Connecting to Compete 2014, revealed in the LPI. table 2.6) shows that, whereas customs perfor- Simplifying documentation for imports mance has likely improved in bottom-­ quintile and exports has long been high on the trade countries, quality and standards/­ i nspection facilitation agenda, prompting initiatives to Table 2.6 Three border agencies: respondents rating quality and competence high or very high, by LPI quintile Percent of respondents Customs Quality/standards Health/sanitary and LPI quintile agencies inspection agencies phytosanitary agencies Bottom quintile 26 8 17 Fourth quintile 34 19 21 Third quintile 38 27 19 Second quintile 45 37 25 Top quintile 78 59 53 Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 21 Figure 2.5 Red tape affecting import and export transactions, by LPI quintile Number of supporting documents Import agencies Export agencies Import documents Export documents 5 4 3 2 1 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2016. bring border agencies together and to create Given the difficulties that some countries a single window for trade. The World Bank may face when implementing the new agree- and International Finance Corporation’s ment, there are many caveats for developing and Doing Business indicators place great weight least developed countries, allowing much flex- on such simplification. Still, also needed are ibility in timing and implementation. Initial in- steps in other aspects of border management dications are that some developing countries are and, more generally, soft and hard trade-related being quite ambitious in scheduling obligations infrastructure. to fall into the agreement’s category A, that is, International agreements such as the World applicable after entry into force or after a short Trade Organization (WTO) Agreement on transition period for least developed countries. Trade Facilitation contribute to stimulate re- However, not all countries have submitted noti- forms and improvement. First, they contrib- fications, so the exact extent to which the agree- ute to mutually agreed standards that the low- ment is in fact implemented in the developing est performing countries can target. Further, world is unclear. they are subject to the WTO’s binding trade disciplines, unlike previous conventions. The Delays, reliability, and service delivery agreement also strengthens the delivery of Some causes of underperformance are endog- technical assistance and capacity-building sup- enous to a country’s supply chain: the quality port for developing and least developed coun- of service and the costs and speed of clearance tries. Indeed, global experience suggests that processes are examples. But other causes, such many of the agreement’s measures are relatively as dependence on indirect maritime routes, lie straightforward to implement, while others, outside the domestic supply chain and are not such as introducing national Single Window under a country’s control. systems, can be quite complex and will require The LPI details possible causes of delay that sustained effort from governments. The results are not directly related to how domestic serv- above suggest that the problems in meeting ices and agencies perform (table 2.7). There is, these standards as measured by the adherence again, a striking contrast between the top and to general customs principles (see table 2.5) in bottom LPI quintile countries. This contrast trade facilitation or the amount of red tape (see is especially large in three areas: informal (cor- figure 2.5) are quite concentrated on the lowest rupt) payments, compulsory warehousing, and performers. preshipment inspection. The first two overlap 22 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 2.7 Respondents reporting that shipments are often or nearly always delayed, by delay category and LPI quintile Percent of respondents Compulsory Preshipment Maritime Informal LPI quintile warehousing inspection transshipment Theft payments Bottom quintile 51 32 25 8 24 Fourth quintile 21 22 38 16 21 Third quintile 19 20 15 13 33 Second quintile 15 20 10 12 12 Top quintile 4 6 8 3 4 Source: Logistics Performance Index 2016. with the problems identified in previous edi- Although firms can adopt other strategies, such tions, so it will be important to look closely at as building in redundancies to deal with disrup- the data on delays due to preshipment inspec- tions affecting one supplier, global market forces tion in future years to see whether that factor are such that providing the conditions for pre- continues to stand out as a particular source of dictable, reliable supply chains have become im- difficulties in low performing countries. perative for countries that want their firms to Delays and unexpected costs are common join and move up in global and regional value in bottom-quintile countries, undermining chains. overall supply chain performance. Worse, An additional reason for policy makers the incidence of delays is increasing across to focus greater attention on supply chain re- LPI quintiles, especially in the lower reaches. liability and predictability is the emerging However, bottom-quintile countries report networked structure of global and regional significantly reduced levels of delay from theft trade, which is linked in part to the rise of value and informal payments in this edition of the chains. In a network, small disruptions at one LPI relative to 2014. Sampling error may play point can spread rapidly and sometimes unpre- a role, but this development is potentially dictably to other points. The efficiency gains positive for supply chain reliability in poorly associated with networked production models performing countries. It will be important thus come with increased systemic risk in the to reexamine the data in future years to see sense that the structure itself can be vulnerable if the change is borne out. Nonetheless, the to small shocks affecting crucial links. The up- general pattern suggests that supply chain pre- shot is that countries unable to provide the con- dictability is an acute commercial problem, ditions for developing predictable and reliable particularly in the most poorly performing supply chains will become increasingly discon- countries. The gap between the bottom and nected from world markets where networked fourth quintiles in areas such as compulsory production models are common. Poorly per- warehousing and preshipment inspection is forming countries need greater policy attention notable, suggesting that it may be possible to to improve their connectivity and to stem any improve performance with relatively modest further marginalization from the global trad- policy interventions. ing system. Predictable, reliable supply chains are cen- Supply chain reliability and predictability tral to good logistics performance. Indeed, are further reflected in a key performance met- highly variable lead times can disrupt produc- ric highlighted in the domestic LPI, namely, tion and exporting, forcing firms to adopt costly the timeliness of clearance and delivery (fig- strategies such as express shipments or sharply ure 2.6). Given that the frequency of delays higher inventories, which, because of global and rises sharply with declining logistics perfor- regional value chains that rely on just-in-time mance, it is unsurprising that the timeliness of production, can sharply erode competitiveness. clearance and delivery generally suffers as one C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 23 Figure 2.6 Respondents reporting shipments often or nearly always cleared and delivered as scheduled, by LPI quintile Percent of respondents Imports Exports 100 75 50 25 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2016. moves down the LPI quintiles. Thus, a stark part of logistics reform in poorly performing difference in on schedule arrival rates sepa- countries. rates countries at the bottom and top of the The patterns highlighted above are more LPI ranking. In the top quintile, most respon- striking in some World Bank regions than oth- dents report that import and export shipments ers (figure 2.7). Beyond the export-import per- always or nearly always arrive on schedule; in formance gap, these data show a geographic the bottom quintile, only around half as many predictability gap, with implications for com- do so. Performance in both cases is similar in petitiveness and the spread of regional supply the 2014 LPI, with potentially a slight im- chains and production networks. However, it provement in the case of the top quintile. This is important to approach figure 2.7 with some finding highlights the importance of steps to degree of caution, as data vary considerably from improve the predictability and reliability of one year to another, in part due to differences in supply chains in poorly performing countries response patterns across countries. to avoid widening in this element of the logis- Supply chain predictability is not only a tics gap (box 2.1). matter of time and cost. A further consideration The bottom two LPI quintiles show the for private sector operators and their clients is largest difference between on schedule arrival shipment quality, which varies widely in the rates for exports and those for imports (see fig- 2016 LPI (figure 2.8). In the top LPI quintile, ure 2.6), as in the previous edition. The much only 13 percent of shipments fail to meet com- lower percentage of high ratings for imports pany quality criteria, the same proportion as suggests that supply chain unreliability dis- in 2014. By comparison, nearly three times as criminates in practice (if not in law) against many shipments in the bottom quintile fail foreign goods. As traditional trade barriers to meet company quality criteria. This find- continue to fall around the world, policies con- ing again illustrates that, in supply chain effi- tributing to such de facto discrimination be- ciency and reliability, the logistics gap is real and come ever larger determinants of performance persistent and trade outcomes. Addressing the causes of The most important quality criterion in unexpected delays, including unpredictability freight forwarding is delivery within the prom- in clearance, inland transit delays, and low ised time window. Almost as important is service reliability, should thus be an important the absence of errors in cargo composition or 24 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 2.1 Timeliness and global value chains As indicated in the main text, reliability and timeliness are key con- country-level integration in global value chains. The data source siderations for firms involved in global value chains. Indeed, the abil- is the OECD–WTO Trade in Value Added Database. The upward- ity to ensure on-time delivery and clearance­ —­ as reflected in the data sloping line of best fit clearly indicates there is an association be- summarized in figure 2.6­ —­is an important way in which countries can tween better on-time performance and a higher proportion of im- attract lead firms in global value chains to make investments there. ports accounted for by intermediates, which is representative of an The figure illustrates this relationship. It uses the percent- important function of global value chains. age of intermediate goods imports in total imports as a proxy for Correlation between timely clearance and delivery and share of intermediate imports Intermediate imports (percent of gross imports) 90 80 70 60 Fitted values 50 40 30 0 25 50 75 100 Goods cleared and distributed on time (percent of respondents reporting nearly always or often) Source: Logistics Performance Index 2016. Figure 2.7 Respondents reporting shipments often or nearly always cleared and delivered as scheduled, by region Percent of respondents Imports Exports 100 75 50 25 0 East Asia Europe and Latin America Middle East and South Sub-Saharan and Pacific Central Asia and Caribbean North Africa Asia Africa Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 25 Figure 2.8 Shipments not meeting company quality criteria, by LPI quintile Percent 40 30 20 10 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2016. documentation. The acceptable quality win- in low performing countries. The shipment dow is much narrower (and errors much less quality gap only partly reflects these differing tolerated) in top-performing countries than expectations. 26 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 3 The way forward: New challenges SECTION in trade facilitation and logistics It has been almost 10 years since the first edition of on international trade and transport facilita- Connecting to Compete. The status of logistics as a tion. Two areas have received substantial sup- policy concern is now firmly established. Not only port over the last 15 years: private sector executives, but also policy makers 1. Border management reforms targeting across all types of countries are aware of the con- improvements in customs processing and tribution of efficient supply chains to the national the coordination of controls by other agen- economy. The experience with policy implementa- cies, for instance, risk management, the re- tion and interventions to enable logistics perfor- duction of physical inspection, automation, mance is diverse and increasingly well documented. and the implementation of single windows Yet the logistics agenda saw shifts in priori- to facilitate information sharing, as well as ties over the last 10 years. First, the scope of poli- the transparency of information and trans- cies addressing logistics performance is moving actions for traders. from border issues in trade and transport fa- 2. Trade corridors and transport facilita- cilitation to domestic performance concerns. tion projects are critical to addressing the Moreover, the logistics industry and the public needs of landlocked developing countries sector have to address major challenges such as and targeting improvements such as tran- raising skill and competency levels and adapting sit and border infrastructure (for example, to slower trade growth. Managing the footprint one-stop border facilities; box 3.1), transit and the sustainability of the supply chain is con- procedures, and the reduction of controls firmed as a high priority, thereby reconciling per- in transit. formance with socioenvironmental objectives. Arguably, there is an abundant return on experience in project design and implementa- Complexity of reforms: Moving tion.4 The principles of trade and transport away from the border? facilitation have been formalized and adopted in a number of international agreements under The focus of the LPI and its survey is the perfor- the aegis of United Nations bodies and special- mance of international supply chains. Improve- ized agencies (World Customs Organization, ments in the crossborder movement of goods WTO). Instruments such as the TIR Conven- and logistics services, or trade and transport tion, the Kyoto Convention, and more recently facilitation, has been the first area of attention the WTO Trade Facilitation Agreement have of the LPI. Logistics policies are not limited to been playing an important role in motivating, transportation or trade facilitation. They are guiding, and providing clear technical targets part of a broader agenda that also includes serv- for projects in developing countries. Other ini- ices, the development of facilities, infrastruc- tiatives, not necessarily global, are also energiz- ture, and spatial planning. ing the agenda (box 3.2). Some activities are known to be more dif- Trade and transport facilitation remains a ficult to implement, especially if improvements priority for poorly performing countries involve several countries. Countries with se- So far, in the context of developing countries, vere constraints, such as landlocked countries, international forums and the support provided have special needs. Transit regimes are difficult by international agencies have focused heavily to improve despite the effective benchmarks C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 27 Box 3.1 Trade facilitation reforms: East Africa’s Northern Corridor The Northern Corridor links Burundi, Rwanda, and Uganda with • Introducing digital cargo tracking systems Kenya’s maritime port of Mombasa. It also serves the eastern part • Building one-stop border posts of the Democratic Republic of Congo, South Sudan, and Tanzania, • Reducing weight controls and other controls connecting the five countries of the East African Community and The positive impact of these reforms has been reported along beyond and playing an important role in the movement and trade of the corridor, as follows: goods. The Northern Corridor was once known for multiple barriers • The average dwell time in Mombasa port was reduced from to trade and transport, including lengthy dwell times at Mombasa an average of 13 days in 2006 to 2–3 days in 2016.b port and cumbersome clearance procedures along the corridor. • The Malaba border crossing point between Kenya and In 2012–13, the corridor countries started a series of reforms that Uganda registered a dramatic fall in border clearance times significantly improved the logistics environment and drove down from 24 hours to 6 hours in December 2012 to January 2013.c logistics costs. • Kenyan Customs Services estimate that the time taken to One of the reforms was to introduce Single Customs Territory move cargo from Mombasa to Kampala dropped from 18 clearance procedures within the East African Community, includ- days to 3 days and from Mombasa to Kigali from 21 days ing Burundi and Tanzania. This means final customs clearances for to 6 days. free circulation can be made already at the port of entry in Mom- As result, the cost of doing business has decreased by about basa. Cargo is then released at this port by customs officials of 50 percent.d The case of the Northern Corridor shows that the logis- a respective hinterland country such as Rwanda. Shipments do tics environment can be quickly improved if there is strong political not have to be transported under customs control because official will for administrative reforms. In some cases, the reforms even payments have already been made. The system has significantly preceded the infrastructure development. The example also shows reduced administrative burden and shortened the time required for that, considering the benefits for traders, the returns on investment customs formalities (see figure). Other important trade facilitation in soft reforms can be much higher than any infrastructure project. measures that have had a positive impact on the Northern Corridor include the following: a. “Northern Corridor Performance Dashboard,” Northern Corridor Transit • Introducing a regional customs transit system and Transport Coordination Authority, Mombasa, Kenya, http://kandal- • Interconnecting customs information technology (IT) systems akaskazini.or.ke. • Introducing cargo tracking systems b. World Bank data for 2005; “Northern Corridor Performance Dashboard,” • Improving interagency coordination Northern Corridor Transit and Transport Coordination Authority, Mom- • Starting advance lodgment of declaration basa, Kenya, http://kandalakaskazini.or.ke. • Detailed corridor monitoring on a weekly basisa c. World Bank data. • Introducing networked single windows d. Memo (2014). Clearance times at the Kenya–Uganda border crossing point, Malaba Share of clearance events (percent) Before reform After reform 100 75 50 25 0 3 hours 3–6 6–24 24–48 Over or less hours hours hours 48 hours Clearance time Source: World Bank. 28 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 3.2 Major new international initiatives address logistics issues Since the 2014 edition of the LPI, at least two initiatives of global Trans-Pacific Partnership: The 12-country Trans-Pacific Part- scale have emerged that are likely to have positive impacts on the nership agreement was signed in February 2016, after seven years logistics performance of the participating countries. of negotiations.a Currently, its status is uncertain, as ratification is One Belt, One Road: An initiative that will likely have signifi- pending, including in the United States. It is not clear whether the cant implications for logistics operators is the One Belt, One Road process can be concluded in all countries. Initiative, which is led by China and targets 60+ countries. This From a logistics standpoint, there are a number of relevant as- ambitious program seeks to improve trade connectivity among pects of the agreement. First, logistics is a service, so the agreement Silk Road economies and also countries on the main sea routes provisions on trade in services could facilitate international exchange from China. While in its early stages, the initiative has an ambitious involving logistics providers. The agreement also includes provisions scope. It will target physical infrastructure in a variety of locations, on trade facilitation, in line with existing international agreements. catalyzing finance and investment resources. However, hard infra- One innovative aspect of the agreement that is important to the lo- structure is not enough. There also needs to be a soft component, gistics community is the annex on express delivery services, which involving regulatory reform in service markets such as transport, is designed to level the playing field among private sector delivery logistics, and telecommunications. China’s trade costs with some services and traditional postal operators. If implemented, there is initiative countries are high, particularly with Central Asian coun- potential for these provisions to facilitate the expansion of delivery tries. From this starting point, the initiative can help develop a services in countries where accessibility to such services is low. broad, business-focused program that can work on multiple fronts to bring improvements in trade facilitation and logistics to partici- a. Member countries include Australia, Brunei, Canada, Chile, Japan, Malay- pating countries. sia, Mexico, New Zealand, Peru, Singapore, the United States, and Vietnam. provided by the transit system originating in Comprehensive logistics strategies are Western Europe.5 Service sector performance, being developed in middle- and high- notably of the trucking sector, is critical to the income countries cost and reliability of inland logistics. Enhanc- However, logistics is not limited to transporta- ing these markets is particularly challenging in tion or trade facilitation. It is part of a broader Africa, especially because improvements have to agenda that includes services, the development be implemented in parallel in several countries.6 of facilities, infrastructure, and spatial plan- The World Bank has recently piloted policy ning. Countries are increasingly confronted loans in Burkina Faso and Côte d’Ivoire with with a more complex set of reforms and mea- the objective of modernizing and consolidating sures to be implemented. Design and imple- the trucking sector in both countries. mentation ultimately happen at the country The LPI survey results, especially the de- level or regionally, within consistent country velopments in section 2, confirm the promi- groupings. High- and middle-income countries nence of the trade facilitation agenda. Yet they increasingly look at logistics not only from the also show that, apart from the countries in the perspective of reducing trade costs at the bor- bottom performance quintiles, many devel- der, but of driving a large economic sector with oping countries have converged with the top many externalities because of its links with the performers. Use of information technology rest of the economy and its significant social and (IT) and the number of documents required environment footprint. for clearance, for instance, are not that differ- In physically large countries, internal com- ent across the three top quintiles. Beyond a merce and logistics are an important topic be- certain level, compliance with core guidelines cause internal connectivity is critical to reduc- in trade and transport facilitation may not be ing geographical inequalities. Much of this has the main driver of logistics performance, and to do with logistics, including, in some cases, in- other factors such as behavior and productivity ternal barriers. Given its focus and respondent in logistics services and public agencies may be base, the LPI is not entirely adequate to assess as important. the performance of domestic logistics. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 29 Many countries have engaged in compre- at ports, in terms of cost, time, and reli- hensive strategy exercises, with a strong pub- ability. The automation of the supply chain lic-private dialogue (box 3.3). The outcomes process makes raw data available for these of these exercises vary: blueprints of priori- measurements. There is a now an extensive ties, monitoring and evaluation, or public– body of experience to measure corridor private promotion institutions such as Dina- ­performance.7 log in the Netherlands. Some countries have • The impact of logistics costs and cost reduc- promulgated laws on logistics with the intent tion on productivity and growth. Several of better defining the sector and its operating governments or national logistics associa- environment. The rationale for a law is that lo- tions have monitored this impact through gistics integrates many activities and may not specific firm surveys, for example, Brazil, be properly supported by a regulatory frame- France, Germany, Malaysia, the Nordic work designed for industrial or commercial countries, and Thailand. These surveys try enterprises. There is still limited international to estimate logistics expenditures in manu- experience in this respect. The World Bank has facturing and commerce and to break down so far advised two countries, Greece and Mo- the operating costs of service providers. The rocco, in preparing a regulatory framework for Finnish survey model has been replicated logistics. in several countries, including Greece and ­Kazakhstan.8 A data-driven reform agenda Logistics observatories are being devel- Policy makers are increasingly looking for oped to collect, organize, and interpret these data so they can base decisions on facts. Gen- datasets.9 A few countries, including Canada, eral cross-country benchmarks such as the LPI the Netherlands, and South Africa are devis- are useful and are complemented by connec- ing even more ambitious big data investments tivity indicators for specific modes (shipping, that try to map a country’s entire set of supply air). They provide international comparability chains, from shipper information to tracking but remain coarse-grained benchmarks. More data and beyond (box 3.4). detailed and specific benchmarks are ulti- mately needed to take decisions and assess the Raising competencies under impact of the decisions on ports, corridors, bor- competitive pressure der crossings, trucking reforms, and so on. The needs are in two categories: Most experts agree that the 2008 financial • Measures of performance outcomes of spe- crisis coincided with new trends in global cific chains, for instance, on corridors or trade, ending a phase when trade, and hence logistics, grew faster than production. Accord- ing to the WTO, both trade and production Box 3.3 France Logistique 2025 growth have averaged at 2.5 percent since the “In France, following a Parliament initiative, a national conference on logistics was crisis.10 As a result, many transport and logis- organized in 2015, prepared by a scientific committee establishing a state of the art tics market segments have been struggling and a diagnosis of the current situation. For the first time, the government approved with overcapacity, low freight levels, and poor a strategic plan for logistics (France Logistique 2025), which has now to be imple- profitability. The impact on the main seg- mented. It should be organized around six main topics: manpower, competence, ments and the response from the industry are and education; insertion of logistics in its regional and urban environment; research briefly explained below. This puts pressure on and innovation in logistics technology and management; infrastructure usage opti- the industry to evolve in terms of networks mization; regulation harmonization and simplification; and observation of logistics and products. Proactive policies to enhance (measurement of its social, economic, and environmental performance) under the governance of a steering committee.” the quality and competitiveness of logistics services should also adapt to this new normal Source: Savy 2016. for trade and logistics. 30 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 3.4 South Africa: Letting the (large) logistics data speak South Africa embodies the familiar story of a developing economy was presented annually in the State of Logistics™.a From 2015, with a heavy dependence on bulk industries, a rapidly growing serv- the State of Logistics™ survey was succeeded by Logistics Ba- ice sector, and a struggling manufacturing sector. Although logis- rometer South Africa, published by Stellenbosch University.b The tics costs as a percentage of GDP have decreased 2.4 percentage Logistics Barometer delves deeper into the cost drivers and market points since 2008, they are equivalent to approximately 50 percent dynamics that shape logistics behavior and provides a detailed of GDP in U.S. dollars in the primary and secondary sectors. These picture, geographically and by industry, of how the South African and other provocative statistics have found their way onto the desks economy moves. It is a significant step up in collecting, calibrating, of policy makers and infrastructure planners purely as a result of al- and analyzing large sets of data from many, mostly private sources. most two decades of dedicated datacentric research of freight flows and logistics costs by a consortium of experts involving the private a. State of Logistics™ Surveys (database), Council for Scientific and Indus- sector and the research community, the Council for Scientific and trial Research, Pretoria, South Africa, http://www.csir.co.za/sol/. Industrial Research, and Stellenbosch University. b. Logistics Barometer (database), Stellenbosch University, Stellenbosch, Together with the United States, South Africa is one of the few South Africa, http://www.sun.ac.za/english/faculty/economy/logistics/ countries that have a consistent, statistics-based time series of Pages/logisticsbarometer.aspx. macrologistics costs (see figure). Between 2004 and 2014, this work Source: Jan Havenga, Department of Logistics, Stellenbosch University. Logistics costs, South Africa, 2003–15 Rand (billions) Percent of GDP Percent of transportable GDP 500 60 400 50 300 40 200 30 100 20 0 10 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Source: Logistics Performance Index 2016. More networks: The logistics industry grown since the 2008–09 crisis from around response to the decline in impacts on 7,860 million tons or 40,000 billion ton-miles trade growth in 2009 to over 10,000 million tons and over Starting with maritime transport, the ship- 54,000 billion ton-miles in 2015.12 ping market has seen record low freight levels Despite the high average growth of global since 2008, and the near-term outlook is bleak, container volumes (approximately 5 percent a especially in bulk and tanker shipping. The year since 2010), container freight levels have main freight index for bulk shipping reached remained low, even if some recovery is ex- an all-time low in February 2016, and the cor- pected later in 2016.13 Over 20 ships carrying responding tanker indexes have either been very more than 18,000 twenty-foot equivalent units low or low during most of 2016.11 This develop- (TEU) have entered the main trades since 2013, ment reflects the substantial oversupply in these and over half of all containership orders placed trades even though the world seaborne trade has in 2015 were in the 18,000–22,000 TEU range. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 31 This has had a substantial impact on operational through the top 50 routes compared with ap- patterns and competition in container shipping. proximately one-third by 2010.19 While low maritime freights should be good Many of the big logistics service providers news for shippers, even record low levels do not have struggled with operational issues, includ- necessarily generate more transport volumes.14 ing legacy IT systems, which may be based on an According to Boeing, air cargo currently IT architecture from the 1990s. Switching cor- constitutes only about 1 percent of world trade porate-wide to the latest IT systems in a highly calculated by tonnage, but it represents about competitive market poses significant risks of 35  percent of world trade calculated by the disruption and loss of market share, which has value of goods shipped.15 The importance of air been a major reason to postpone such changes. freight to trade logistics is thus substantial. The A significant feature in recent years, especially global air freight market was severely affected among the large providers, is the growing em- by the economic crisis of 2008 as well: the post- phasis on more sustainable and environmentally crisis peak of 2011 of about 195 billion freight friendly practices. This is largely a customer- ton kilometers was not surpassed until 2015. driven response, and market indications imply Airbus predicts a 4.4 percent annual growth that providers with sustainable operations will from about 200 billion freight ton kilometers in thrive in tomorrow’s marketplace. 2015 to about 480 billion by 2034. This will be Small and medium freight forwarders are largely driven by emerging markets, especially in being forced to evolve to become better and the Asia and Pacific region, where both general more efficient in an environment where manual and express cargoes are expected to continue to data entry is still widespread. They have evolved expand. from pure forwarders to providers of a wider According to the listing of the world’s larg- range of services, such as integrated or third- or est freight forwarders by Armstrong & Asso- fourth-party logistics services. This often in- ciates for 2013 and 2014, the revenues of the volves the creation and maintenance of or al- same top 20 firms were US$185  billion and legiance to wide networks, typically as a non– US$189 billion, respectively.16 The freight for- asset-based operator. This means that freight warding industry, including the largest logis- forwarders, as middlemen among consignors, tics service providers, has witnessed a dilution consignees, and the necessary logistics provid- of yields especially since 2008, and profitability ers, seldom own the facilities or means of trans- has generally been low.17 The global freight for- port themselves. warding market is still fragmented into a mix A notable recent feature in the way small of global providers, hundreds of medium en- and medium freight forwarders develop their terprises, and tens of thousands of small com- business and try to increase their sales is the petitors subjected to disruptive market forces emergence of large and geographically extensive, ranging from shifting demand patterns and in- even worldwide, alliances. Adherence to such creasingly complex global supply chains to an alliances­—­some with several hundred corporate evolving customer base and changing customer members­ —­ does not typically entail large relationships. investments, even if some IT system alignment This means that forwarders have to work may be required, especially in marketing, harder to maintain their revenues and, more im- customer management, and selected operational portantly, their profitability. One of the reasons interfaces. Some of the more established for this is a shift in modes from air to sea.18 A alliances are exclusive so that one cannot key driver behind this trend was the economic have multiple memberships in competing downturn, which prompted traders to find ways networks or alliances. Some have various tiers to cut their supply chain costs while maintain- of membership. There are currently tens if not ing their efficiency. Global flows of goods have hundreds of such freight forwarder networks. also become more disparate: In the early 1990s, The formation of this type of network during two-thirds of global flows of goods moved the past decade or so is not new. Indeed, this has 32 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y been the modus operandi in freight forwarding but particularly in the countries that form for centuries. What is novel is the way these the bottom quintile in the LPI (figure 3.1). In alliances are formed and maintained and how these countries, the shortage of logistics staff their members can provide more versatile in the middle tier, that is, administrative staff services to cater to a broad spectrum of customer and supervisors, is most acute. A similar pic- needs with wide geographical coverage. ture emerges in the second-lowest LPI quintile, The big firms in the business have tried to where the share of low or very low availability reach similar competitive advantage through was rated at around a third for all four occupa- the extensive internalization of such operations, tional levels. The problem of skill shortages is combined with networking in markets, where less acute, but also visible in the third, fourth, independent operations are not feasible. As a and fifth LPI quintile. result, freight forwarding is currently a highly When broken down by geographic region, competitive business in most parts of the world. Latin America and the Caribbean emerges as This also creates a need for operators in the the region with the highest skill gap across all freight forwarding business to develop more employee groups (figure 3.2). A full 43 percent value added services and to provide such services of respondents, for instance, indicated that the to shippers in developing markets, too.20 availability of logistics managers, that is, those with the most sophisticated responsibilities, was Logistics skills, competencies, and either low or very low. Yet, also for each of the training three remaining employee groups (operative, Transporting, storing, and handling goods are administrative, and supervisory), about a third labor-intensive activities. The availability of of respondents indicated low or very low avail- skilled logistics staff is thus an important deter- ability of staff. minant of supply chain performance. A forth- Comparatively high staff shortages of be- coming joint report by the World Bank Global tween 20 percent and 30 percent at all job levels Trade Team and Kühne Logistics University in were reported in South Asia and Sub-­ Saharan Hamburg reviews the availability of qualified Africa. The picture is more nuanced in East Asia staff and the current state of training and educa- and Pacific, were shortages of administrative tion in logistics in 28 developing and developed and managerial staff were more acute than those countries.21 To supplement the report’s analysis, of operative and supervisory staff. In the Mid- the 2016 LPI edition for the first time included dle East and North Africa, the low level of staff a question on logistics skills and competencies. shortage at the managerial level (11 percent) vs. Respondents were asked to indicate the avail- the other levels (around 20 percent each) stands ability (from very high to very low) of qualified out. This could be a favorable outcome of higher personnel in four groups of logistics personnel: education programs (Bachelor of Science and • Operations staff such as truck drivers or Master of Science) in logistics and supply chain warehouse pickers management that were introduced in the region • Administrative staff such as traffic planners, over the past decade. Morocco could serve as an expediters, or warehouse clerks example of a country that, owing to those pro- • Logistics supervisors such as warehouse grams, does not see a severe shortage of manage- shift leaders or traffic controllers rial staff. However, difficulties in finding work- • Logistics managers such as those responsible ers on lower sophistication levels, such as truck for transport, warehousing operations, or drivers and warehouse pickers, are still pertinent supply chain management in the country. The results of the 2016 LPI survey bol- Other findings emerging from the report of ster the report’s findings that logistics faces a the World Bank and Kühne Logistics Univer- global shortage of qualified staff. Qualified sity include the following: staff are scarce at all four occupational levels • Hiring and retaining issues range from dif- in both developed and developing countries, ficulties in finding or retaining truck drivers C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 33 Figure 3.1 Respondents reporting low or very low availability of qualified personnel, by employee group and LPI quintile Percent of respondents Top quintile (highest performance) Fourth quintile Third quintile Second quintile Bottom quintile 60 40 20 0 Operators, blue-collar staff, Administrative logistics staff, Logistics supervisors, Logistics managers, such as truck drivers, such as traffic planners, such as shift leaders, such as those responsible pickers expediters traffic controllers for the supply chain Source: Logistics Performance Index 2016. Figure 3.2 Respondents reporting low or very low availability of qualified personnel, by employee group and region Percent of respondents East Asia & Pacific South Asia Middle East & North Africa Sub-Saharan Africa Europe & Central Asia Latin America & Caribbean North America 60 40 20 0 Operators, blue-collar staff, Administrative logistics staff, Logistics supervisors, Logistics managers, such as truck drivers, such as traffic planners, such as shift leaders, such as those responsible pickers expediters traffic controllers for the supply chain Source: Logistics Performance Index 2016. to problems in filling senior supply chain • With the exception of a few countries, such management positions; the latter is most as Germany or the United Kingdom, logis- acute in emerging markets. This is com- tics training is often limited to short-term, pounded by deficiencies in the skill levels of on-the-job training, characterized by small the staff currently employed in the logistics training budgets, few sources of expertise, sector. Hence, productivity of logistics op- and low quality in the educational experi- erations and the quality of logistics services ence. are suffering. • The reasons for the skill shortage include low salary levels relative to other sectors, the 34 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y low prestige of operational logistics workers, These results are consistent with the grow- lack of vocational school preparation, lim- ing voluntary targets set by a number of large ited labor supply in remote areas where lo- multinational corporations. Many of these have gistics hubs are often located, and new IT publicized ambitious reductions in carbon in- developments in logistics that exceed the tensity relative to outputs, between 20 percent competencies of the existing workforce. and 40 percent in 2010–20. 24 Typically, these To address skill shortages in the logistics objectives are expected to be achieved by shift- sector, training is needed that can be imple- ing to less emission-heavy modes of transporta- mented even on tight budgets and low maturity tion and also by better load factors in freight levels in the educational and logistics sector. transportation. This demand for environmen- Apprenticeships and dual education initiatives tally friendly logistics complements the toolkit such as in Germany could form part of this, as of policy interventions targeting green transpor- could branch campuses of established universi- tation that typically promotes energy efficiency ties or blended learning approaches. Compa- or alters the energy mix through incentives and nies can do their share to retain employees by better standards.25 offering transparent career paths, investment From a policy standpoint, what is less clear in workforce development, appealing work en- today is how to develop policy interventions vironments, and a fair distribution of rewards that not only target the supply side of logistics and responsibilities. Governments can support but also raise the demand for environmentally higher competency levels in the logistics sector friendly logistics, including in developing coun- through several interventions, including regula- tries. Few countries—prominently, the Nether- tory policy, curriculum development, financial lands through the Lean and Green Program— support for training initiatives, harmonization have implemented policies and public–­ private of competence standards, and supplementing dialogue targeting not only the transport sector infrastructure development with human capi- but also the shippers.26 tal investment. Managing the footprint and sustainability of logistics Figure 3.3 The demand for green logistics Green logistics Percent of respondents Sometimes Often or always This edition of the survey, like the two previous 60 editions, included a question on the demand for environmentally friendly international logistics. 50 The results show the same pattern as in the past two editions. Environmentally friendly supply 40 chains are associated with a higher degree of 30 logistics performance (figure 3.3). This trend is good news because logistics has a relatively large 20 footprint not only on the economy but also on the environment. Beyond its freight component, 10 the magnitude of the carbon footprint of logis- tics is not well estimated. The share of freight 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile emissions of greenhouse gases has been esti- (lowest (low (average (high performance) performance) performance) performance) performance) (highest mated at 42 percent of transport emissions and Note: The figure shows the share of the respondents answering often, always, or 7 percent of total emissions.22 In the long term, sometimes to the question “How often do shippers ask for environmentally friendly options (for example, in view of emission levels, choice of routes, vehicles, the share of freight logistics is expected to grow schedules, and so on) in shipping to country x?” The economies are grouped by LPI quintiles. to 60 percent of transport emissions in 2050.23 Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 35 Logistics and spatial planning logistics are crucially important.29 Although not Another major sustainability concern, more covered yet in the LPI survey, logistics in cities local in nature, revolves around the physi- is attracting rapidly growing attention among cal footprint of logistics. Because of growing policy makers who have to reconcile the objec- urbanization in developing countries, rapidly tive of efficient logistics with spatial concerns. increasing urban freight transport has a sig- The World Bank is thus increasingly involved in nificant impact economically (such as through urban logistics projects in Brazil, China, Kenya, inefficiencies and urban competitiveness), Morocco, and other countries. environmentally (air pollution and noise), and socially (quality of life, health, and economic *   *   * possibilities). Most logistics activities require large land Logistics not only connects firms to domestic areas for various types of facilities, such as ware- and international markets, but also links to houses, and good transport infrastructure con- broader policy concerns. Previous LPI reports nections to and from these locations. Yet most emphasized the complexity of the reform of the goods are ultimately distributed and sold agenda and the differentiation in priorities in dense areas. Logistics, including activities depending on the level of logistics performance. such as warehousing, not only compete for space These remain relevant. but also generate traffic in high-­ density areas. In countries with low performance, logistics Several authors have noted the dominance of reforms are still intertwined with the trade and the traditional sector in many developing coun- transport facilitation agenda dealing with bor- tries and the fact that this sector is likely to re- der management improvements, transit facilita- main dominant. 27 Retail stores in developing tion, and enhancements of core infrastructure, countries often operate with small volumes and notably corridors and border facilities. Coun- limited inventory. This implies high densities in tries at intermediate and high levels of perfor- logistics because of the need for many small de- mance deal with broader and more complex liveries with more intermediary steps. issues, which not only target the border compo- In port cities, the development of the busi- nent of supply chains but also the full array of est seaports and airports has often been con- policies addressing the performance and exter- strained by a lack of suitable land for expansion, nalities of domestic supply chains. especially facilities in locations close to or even Therefore, the policy frontiers outlined within urban or suburban areas. In many large above are likely to receive growing attention ports in Europe and Asia, the surge in traffic from policy makers, especially in advanced and to and from China around 2004/05 prompted emerging economies as well as among the orga- ports to develop inland locations­ —­dry ports­ nizations advising them. Areas such as domestic —­ to handle the rapidly growing volumes in a supply chains, sustainability, or labor supply and more efficient and environmentally friendly skills are accompanied by innovative potential manner.28 and require significant investments in the prac- The implementation of relevant city logistics tical knowledge of what does and does not work. measures, policies, planning, and regulations Thus, the World Bank has developed a strong can reduce these effects and contribute to eco- interest in implementing new approaches to im- nomic, environmental, and social sustainability. proving urban and distribution logistics or the Hence, to provide sustainable development, city use of big data to map domestic supply chains. 36 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Notes 1 “La France fait partie des pays du monde les plus 12 UNCTAD (2015). performants pour sa logistique. C’est un facteur 13 UNCTAD (2015). Also see, for example, Lakshmi (2016); déterminant de notre compétitivité, qui représente Hong Liang (2016). 10 % du PIB national, 200 milliards d’euros de chiffres d’affaires, et 1,8 millions d’emplois. Notre pays est 14 UNCTAD (2015). notamment reconnu pour la qualité de sa main d’oeuvre, 15 Boeing (2015). de son maillage d’infrastructures et d’équipements, ou 16 See Logistics Management (2014, 2015). The five encore la disponibilité de ses terrains. Mais cette position largest in 2014 by revenue from logistics operations n’est jamais acquise et la France doit encore progresser according to Armstrong & Associates were: 1. DHL Supply pour devenir un leader mondial. Classée seulement Chain & Global Forwarding (US$32.2 billion); 2. Kühne au 13ème rang mondial de la logistique (indice Banque + Nagel (US$23.3 billion); 3. DB Schenker Logistics mondiale), loin derrière ses voisins les plus proches, la (US$19.9 billion); 4. Nippon Express (US$17.9 billion); and sousperformance logistique de la France coûterait chaque 5. Panalpina (US$7.3 billion). The total revenue of these année entre 20 et 60 milliards d’euros à notre économie” five was US$100.6 billion, or 53.2 percent of the top 20 (Royal, Macron, and Vidalies 2016, 2). firms. Four of the top 5 and 10 of the top 20 firms were 2 Although the respondents in the LPI survey are freight headquartered in Europe. forwarders and express carriers, the quality and 17 See also Stifel Logistics Confidence Index indications in competence of service providers are assessed by their March 2016 at https://www.ajot.com/news/a-return-to peers. -decline-stifel-logistics-confidence-index-falls-month-on 3 Lead time to import is the median time (the value for -month. 50 percent of shipments) from the port of discharge to 18 Manners-Bell and Lyon (2015). arrival at the consignee. 19 http://www.scmr.com/article/freight_forwarding_market_ 4 McLinden et al. (2011). going_through_structural_change. 5 Kunaka and Carruthers (2014). 20 See also Langley and Capgemini Consulting (2014). 6 Raballand and Teravaninthorn (2009). 21 World Bank and KLU, forthcoming. 7 Raballand et al. (2008). 22 ITF (2015). 8 Solakivi et al. (2012). 23 ITF (2015). 9 ITF (2016). 24 Kopp, Block, and Iimi. (2012); McKinnon et al. (2010). 10 WTO (2015). 25 Kopp, Block, and Iimi. (2012); McKinnon et al. (2010). 11 See “Baltic Dry Index,” Lloyd’s List (database), Quandl, 26 www.lean-green.nl. Toronto, https://www.quandl.com/data/LLOYDS/BDI. 27 Blanco (2014). See also “Baltic Tanker Index,” Lloyd’s List Intelligence (database), Maritime Intelligence, Informa UK Limited, 28 Cullinane, Bergqvist, and Wilmsmeier (2012). London, http://www.lloydslistintelligence.com/llint/ 29 Savy (2014). tankers/baltic-index.htm. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 37 APPENDIX 1 International LPI results Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Germany 1 1 4 4.23 4.18 4.27 100.0 2 4.12 1 4.44 8 3.86 1 4.28 3 4.27 2 4.45 Luxembourg 2 1 12 4.22 3.97 4.47 99.8 9 3.90 4 4.24 1 4.24 10 4.01 8 4.12 1 4.80 Sweden 3 1 7 4.20 4.09 4.32 99.3 8 3.92 3 4.27 4 4.00 2 4.25 1 4.38 3 4.45 Netherlands 4 1 6 4.19 4.11 4.27 98.8 3 4.12 2 4.29 6 3.94 3 4.22 6 4.17 5 4.41 Singapore 5 2 9 4.14 4.06 4.22 97.4 1 4.18 6 4.20 5 3.96 5 4.09 10 4.05 6 4.40 Belgium 6 5 9 4.11 4.04 4.18 96.4 13 3.83 14 4.05 3 4.05 6 4.07 4 4.22 4 4.43 Austria 7 3 11 4.10 3.98 4.21 96.0 15 3.79 12 4.08 9 3.85 4 4.18 2 4.36 7 4.37 United Kingdom 8 6 9 4.07 4.03 4.11 95.2 5 3.98 5 4.21 11 3.77 7 4.05 7 4.13 8 4.33 Hong Kong SAR, China 9 6 9 4.07 4.00 4.14 95.1 7 3.94 10 4.10 2 4.05 11 4.00 14 4.03 9 4.29 United States 10 10 12 3.99 3.94 4.04 92.8 16 3.75 8 4.15 19 3.65 8 4.01 5 4.20 11 4.25 Switzerland 11 10 15 3.99 3.92 4.06 92.6 10 3.88 7 4.19 14 3.69 14 3.95 12 4.04 14 4.24 Japan 12 10 15 3.97 3.92 4.02 92.1 11 3.85 11 4.10 13 3.69 12 3.99 13 4.03 15 4.21 United Arab Emirates 13 10 16 3.94 3.88 4.00 91.2 12 3.84 13 4.07 7 3.89 18 3.82 18 3.91 18 4.13 Canada 14 10 16 3.93 3.83 4.03 90.8 6 3.95 9 4.14 29 3.56 15 3.90 9 4.10 25 4.01 Finland 15 9 20 3.92 3.77 4.07 90.5 4 4.01 16 4.01 30 3.51 16 3.88 11 4.04 16 4.14 France 16 13 16 3.90 3.84 3.96 89.9 17 3.71 15 4.01 20 3.64 19 3.82 15 4.02 13 4.25 Denmark 17 6 30 3.82 3.51 4.12 87.3 14 3.82 24 3.75 15 3.66 9 4.01 25 3.74 30 3.92 Ireland 18 11 30 3.79 3.60 3.99 86.6 25 3.47 22 3.77 10 3.83 20 3.79 16 3.98 29 3.94 Australia 19 10 30 3.79 3.58 4.00 86.6 22 3.54 18 3.82 21 3.63 17 3.87 19 3.87 21 4.04 South Africa 20 17 24 3.78 3.70 3.85 86.0 18 3.60 21 3.78 23 3.62 22 3.75 17 3.92 24 4.02 Italy 21 18 24 3.76 3.70 3.81 85.4 27 3.45 19 3.79 17 3.65 21 3.77 20 3.86 22 4.03 Norway 22 15 30 3.73 3.54 3.92 84.7 20 3.57 17 3.95 25 3.62 24 3.70 22 3.82 39 3.77 Spain 23 17 29 3.73 3.62 3.84 84.5 24 3.48 25 3.72 22 3.63 23 3.73 23 3.82 26 4.00 Korea, Rep. 24 20 28 3.72 3.64 3.79 84.2 26 3.45 20 3.79 27 3.58 25 3.69 24 3.78 23 4.03 Taiwan, China 25 15 30 3.70 3.47 3.92 83.6 34 3.23 26 3.57 28 3.57 13 3.95 31 3.59 12 4.25 Czech Republic 26 17 30 3.67 3.52 3.83 82.9 19 3.58 35 3.36 18 3.65 26 3.65 21 3.84 28 3.94 China 27 25 29 3.66 3.61 3.71 82.5 31 3.32 23 3.75 12 3.70 27 3.62 28 3.68 31 3.90 Israel 28 17 30 3.66 3.47 3.85 82.5 23 3.50 30 3.49 37 3.38 28 3.60 26 3.72 10 4.27 Lithuania 29 18 30 3.63 3.45 3.82 81.6 28 3.42 27 3.57 31 3.49 30 3.49 27 3.68 17 4.14 Qatar 30 17 38 3.60 3.36 3.84 80.6 21 3.55 28 3.57 26 3.58 29 3.54 35 3.50 35 3.83 Hungary 31 31 44 3.43 3.30 3.56 75.3 49 3.02 32 3.48 34 3.44 34 3.35 41 3.40 33 3.88 Malaysia 32 31 41 3.43 3.34 3.52 75.2 40 3.17 33 3.45 32 3.48 35 3.34 36 3.46 47 3.65 Poland 33 31 44 3.43 3.30 3.56 75.2 33 3.27 45 3.17 33 3.44 31 3.39 37 3.46 37 3.80 Turkey 34 31 44 3.42 3.28 3.56 75.1 36 3.18 31 3.49 35 3.41 36 3.31 43 3.39 40 3.75 India 35 31 38 3.42 3.36 3.48 75.0 38 3.17 36 3.34 39 3.36 32 3.39 33 3.52 42 3.74 Portugal 36 31 44 3.41 3.27 3.55 74.7 30 3.37 49 3.09 47 3.24 47 3.15 29 3.65 27 3.95 New Zealand 37 25 56 3.39 3.07 3.71 74.0 37 3.18 29 3.55 80 2.77 41 3.22 32 3.58 19 4.12 Estonia 38 31 53 3.36 3.13 3.60 73.3 29 3.41 44 3.18 56 3.07 46 3.18 48 3.25 20 4.08 Iceland 39 30 55 3.35 3.07 3.62 72.7 43 3.13 51 3.02 42 3.32 39 3.26 40 3.42 32 3.88 Panama 40 30 56 3.34 3.07 3.61 72.5 42 3.13 38 3.28 16 3.65 45 3.18 63 2.95 41 3.74 Slovak Republic 41 31 53 3.34 3.12 3.56 72.4 32 3.28 39 3.24 36 3.41 51 3.12 55 3.12 36 3.81 Kenya 42 31 48 3.33 3.21 3.45 72.3 39 3.17 42 3.21 46 3.24 40 3.24 38 3.42 46 3.70 38 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 1  International LPI results Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Latvia 43 31 53 3.33 3.12 3.53 72.1 45 3.11 41 3.24 44 3.28 37 3.29 39 3.42 49 3.62 Bahrain 44 31 53 3.31 3.11 3.51 71.7 41 3.14 48 3.10 41 3.33 33 3.38 44 3.32 51 3.58 Thailand 45 43 50 3.26 3.18 3.33 69.9 46 3.11 46 3.12 38 3.37 49 3.14 50 3.20 52 3.56 Chile 46 31 58 3.25 3.00 3.50 69.7 35 3.19 63 2.77 43 3.30 56 2.97 34 3.50 44 3.71 Greece 47 38 54 3.24 3.10 3.38 69.4 55 2.85 37 3.32 64 2.97 60 2.91 30 3.59 34 3.85 Oman 48 31 58 3.23 3.00 3.47 69.3 61 2.76 34 3.44 40 3.35 38 3.26 57 3.09 57 3.50 Egypt, Arab Rep. 49 44 56 3.18 3.05 3.32 67.7 65 2.75 50 3.07 45 3.27 43 3.20 54 3.15 48 3.63 Slovenia 50 35 67 3.18 2.95 3.42 67.7 53 2.88 43 3.19 53 3.10 44 3.20 46 3.27 60 3.47 Croatia 51 37 67 3.16 2.93 3.39 67.0 47 3.07 53 2.99 51 3.12 42 3.21 52 3.16 67 3.39 Saudi Arabia 52 45 58 3.16 3.03 3.28 66.8 68 2.69 40 3.24 48 3.23 54 3.00 49 3.25 53 3.53 Kuwait 53 40 66 3.15 2.96 3.35 66.7 56 2.83 56 2.92 24 3.62 70 2.79 53 3.16 55 3.51 Mexico 54 45 66 3.11 2.96 3.27 65.5 54 2.88 57 2.89 61 3.00 48 3.14 42 3.40 68 3.38 Brazil 55 49 62 3.09 2.99 3.19 64.7 62 2.76 47 3.11 72 2.90 50 3.12 45 3.28 66 3.39 Malta 56 45 71 3.07 2.84 3.30 64.1 59 2.78 55 2.94 55 3.09 65 2.85 56 3.12 50 3.61 Botswana 57 45 71 3.05 2.82 3.27 63.4 48 3.05 54 2.96 70 2.91 75 2.74 70 2.89 43 3.72 Uganda 58 53 67 3.04 2.93 3.15 63.3 51 2.97 67 2.74 74 2.88 57 2.93 59 3.01 45 3.70 Cyprus 59 49 73 3.00 2.78 3.22 62.0 44 3.11 52 3.00 78 2.80 76 2.72 98 2.54 38 3.79 Romania 60 51 72 2.99 2.81 3.18 61.8 50 3.00 58 2.88 57 3.06 67 2.82 64 2.95 81 3.22 Tanzania 61 56 68 2.99 2.89 3.09 61.7 60 2.78 60 2.81 63 2.98 58 2.92 60 2.98 64 3.44 Rwanda 62 51 72 2.99 2.80 3.17 61.6 52 2.93 76 2.62 59 3.05 63 2.87 58 3.04 69 3.35 Indonesia 63 51 72 2.98 2.80 3.17 61.5 69 2.69 73 2.65 71 2.90 55 3.00 51 3.19 62 3.46 Vietnam 64 49 76 2.98 2.76 3.20 61.3 64 2.75 70 2.70 50 3.12 62 2.88 75 2.84 56 3.50 Uruguay 65 51 73 2.97 2.79 3.16 61.2 58 2.78 61 2.79 69 2.91 53 3.01 74 2.84 59 3.47 Argentina 66 55 71 2.96 2.81 3.11 60.8 76 2.63 59 2.86 81 2.76 66 2.83 47 3.26 61 3.47 Jordan 67 51 79 2.96 2.74 3.17 60.7 83 2.55 62 2.77 49 3.17 61 2.89 62 2.96 71 3.34 Pakistan 68 59 71 2.92 2.81 3.04 59.6 71 2.66 69 2.70 66 2.93 68 2.82 67 2.91 58 3.48 Peru 69 57 81 2.89 2.72 3.06 58.7 63 2.76 75 2.62 68 2.91 64 2.87 65 2.94 80 3.23 Brunei Darussalam 70 51 98 2.87 2.57 3.17 58.0 57 2.78 66 2.75 62 3.00 93 2.57 68 2.91 84 3.19 Philippines 71 60 82 2.86 2.72 3.00 57.5 78 2.61 82 2.55 60 3.01 77 2.70 73 2.86 70 3.35 Bulgaria 72 57 100 2.81 2.56 3.05 56.0 97 2.40 101 2.35 67 2.93 52 3.06 80 2.72 72 3.31 Cambodia 73 59 99 2.80 2.57 3.04 55.8 77 2.62 99 2.36 52 3.11 89 2.60 81 2.70 73 3.30 Ecuador 74 60 99 2.78 2.56 2.99 55.1 74 2.64 88 2.47 65 2.95 84 2.66 86 2.65 77 3.23 Algeria 75 59 107 2.77 2.51 3.03 54.9 108 2.37 80 2.58 77 2.80 59 2.91 72 2.86 91 3.08 Serbia 76 66 101 2.76 2.56 2.97 54.6 87 2.50 85 2.49 90 2.63 69 2.79 66 2.92 79 3.23 Kazakhstan 77 68 101 2.75 2.55 2.95 54.3 86 2.52 65 2.76 82 2.75 92 2.57 71 2.86 92 3.06 Bahamas, The 78 69 98 2.75 2.58 2.92 54.2 72 2.65 68 2.72 79 2.80 73 2.74 87 2.64 105 2.93 Namibia 79 66 103 2.74 2.52 2.97 54.1 73 2.65 64 2.76 86 2.69 86 2.63 100 2.52 85 3.19 Ukraine 80 70 95 2.74 2.60 2.87 53.8 116 2.30 84 2.49 95 2.59 95 2.55 61 2.96 54 3.51 Burkina Faso 81 70 99 2.73 2.57 2.89 53.7 84 2.55 71 2.67 83 2.73 71 2.78 103 2.49 88 3.13 Lebanon 82 54 136 2.72 2.31 3.12 53.2 66 2.73 74 2.64 75 2.84 108 2.45 78 2.75 111 2.86 El Salvador 83 68 110 2.71 2.48 2.93 52.9 107 2.37 114 2.25 76 2.82 83 2.66 76 2.78 74 3.29 Mozambique 84 70 110 2.68 2.48 2.89 52.2 88 2.49 116 2.24 58 3.06 109 2.44 79 2.75 97 3.04 Guyana 85 70 113 2.67 2.44 2.89 51.7 98 2.40 118 2.24 89 2.66 85 2.66 69 2.90 90 3.12 Morocco 86 56 137 2.67 2.25 3.08 51.6 124 2.22 90 2.46 54 3.09 91 2.59 122 2.34 83 3.20 Bangladesh 87 72 110 2.66 2.50 2.83 51.6 82 2.57 87 2.48 84 2.73 80 2.67 92 2.59 109 2.90 Ghana 88 72 110 2.66 2.48 2.84 51.5 93 2.46 86 2.48 85 2.71 98 2.54 101 2.52 82 3.21 Costa Rica 89 72 111 2.65 2.47 2.82 51.1 113 2.33 107 2.32 73 2.89 94 2.55 77 2.77 101 2.98 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 39 Appendix 1  International LPI results Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Nigeria 90 74 112 2.63 2.46 2.80 50.5 92 2.46 96 2.40 118 2.43 74 2.74 82 2.70 95 3.04 Dominican Republic 91 74 111 2.63 2.46 2.79 50.4 101 2.39 111 2.29 87 2.67 79 2.68 88 2.63 93 3.06 Togo 92 70 130 2.62 2.35 2.88 50.1 89 2.49 117 2.24 93 2.62 106 2.46 91 2.60 76 3.24 Moldova 93 74 114 2.61 2.43 2.80 50.0 99 2.39 100 2.35 94 2.60 103 2.48 85 2.67 86 3.16 Colombia 94 74 113 2.61 2.43 2.79 50.0 129 2.21 95 2.43 103 2.55 81 2.67 96 2.55 78 3.23 Côte d’Ivoire 95 68 136 2.60 2.28 2.93 49.7 70 2.67 89 2.46 105 2.54 87 2.62 89 2.62 128 2.71 Iran, Islamic Rep. 96 68 137 2.60 2.26 2.94 49.6 110 2.33 72 2.67 88 2.67 82 2.67 111 2.44 116 2.81 Bosnia and Herzegovina 97 79 113 2.60 2.44 2.75 49.5 67 2.69 77 2.61 140 2.28 99 2.52 95 2.56 103 2.94 Comoros 98 72 136 2.58 2.31 2.85 49.0 75 2.63 98 2.36 98 2.58 88 2.60 113 2.44 115 2.82 Russian Federation 99 85 111 2.57 2.47 2.67 48.7 141 2.01 94 2.43 115 2.45 72 2.76 90 2.62 87 3.15 Niger 100 77 128 2.56 2.37 2.76 48.4 81 2.59 121 2.22 91 2.63 100 2.50 121 2.35 98 3.02 Paraguay 101 72 136 2.56 2.27 2.85 48.4 103 2.38 92 2.45 96 2.58 78 2.69 126 2.30 107 2.93 Nicaragua 102 78 136 2.53 2.31 2.75 47.5 90 2.48 83 2.50 107 2.50 96 2.55 107 2.47 134 2.68 Sudan 103 84 128 2.53 2.36 2.70 47.4 122 2.23 126 2.20 100 2.57 118 2.36 104 2.49 75 3.28 Maldives 104 82 136 2.51 2.30 2.73 46.9 102 2.39 81 2.57 132 2.34 111 2.44 102 2.49 110 2.88 Papua New Guinea 105 73 139 2.51 2.22 2.80 46.8 85 2.55 106 2.32 114 2.46 121 2.35 93 2.58 120 2.78 Macedonia, FYR 106 83 136 2.51 2.31 2.71 46.8 127 2.21 79 2.58 116 2.45 120 2.36 123 2.32 89 3.13 Burundi 107 80 136 2.51 2.28 2.74 46.8 137 2.02 147 1.98 119 2.42 107 2.46 83 2.68 63 3.45 Mongolia 108 84 136 2.51 2.31 2.70 46.7 100 2.39 140 2.05 129 2.37 129 2.31 108 2.47 65 3.40 Mali 109 82 136 2.50 2.28 2.73 46.6 94 2.45 109 2.30 112 2.48 105 2.46 120 2.36 106 2.93 Tunisia 110 74 139 2.50 2.21 2.78 46.4 147 1.96 93 2.44 133 2.33 90 2.59 84 2.67 99 3.00 Guatemala 111 85 136 2.48 2.28 2.67 45.8 91 2.47 127 2.20 120 2.41 130 2.30 110 2.46 100 2.98 Honduras 112 85 137 2.46 2.25 2.67 45.3 126 2.21 143 2.04 97 2.58 110 2.44 99 2.53 108 2.91 Myanmar 113 89 137 2.46 2.26 2.66 45.2 96 2.43 105 2.33 144 2.23 119 2.36 94 2.57 112 2.85 Zambia 114 95 137 2.43 2.26 2.60 44.3 119 2.25 113 2.26 106 2.51 114 2.42 119 2.36 124 2.74 Benin 115 98 136 2.43 2.27 2.59 44.3 130 2.20 97 2.39 104 2.55 104 2.47 129 2.23 130 2.69 Solomon Islands 116 85 144 2.42 2.16 2.67 43.9 79 2.60 124 2.21 139 2.28 112 2.43 132 2.18 121 2.76 Albania 117 95 139 2.41 2.22 2.60 43.8 121 2.23 148 1.98 110 2.48 102 2.48 135 2.15 94 3.05 Uzbekistan 118 89 145 2.40 2.16 2.65 43.5 114 2.32 91 2.45 130 2.36 116 2.39 143 2.05 114 2.83 Jamaica 119 102 136 2.40 2.27 2.53 43.4 109 2.37 120 2.23 117 2.44 126 2.31 116 2.38 136 2.64 Belarus 120 98 139 2.40 2.21 2.58 43.4 136 2.06 135 2.10 92 2.62 125 2.32 134 2.16 96 3.04 Trinidad and Tobago 121 102 137 2.40 2.26 2.53 43.3 104 2.38 104 2.34 137 2.31 132 2.28 127 2.28 119 2.79 Venezuela, RB 122 104 137 2.39 2.25 2.53 43.1 145 1.99 102 2.35 113 2.47 122 2.34 106 2.48 127 2.71 Montenegro 123 95 147 2.38 2.15 2.61 42.8 125 2.22 138 2.07 101 2.56 127 2.31 117 2.37 131 2.69 Nepal 124 87 150 2.38 2.09 2.66 42.7 149 1.93 112 2.27 109 2.50 140 2.13 109 2.47 104 2.93 Congo, Rep. 125 72 155 2.38 1.90 2.86 42.7 142 2.00 78 2.60 126 2.37 133 2.26 105 2.48 143 2.57 Ethiopia 126 98 145 2.38 2.16 2.59 42.7 80 2.60 133 2.12 102 2.56 117 2.37 133 2.18 149 2.37 Congo, Dem. Rep. 127 111 136 2.38 2.27 2.48 42.6 123 2.22 146 2.01 135 2.33 123 2.33 118 2.37 102 2.94 Guinea-Bissau 128 85 151 2.37 2.07 2.67 42.5 95 2.44 152 1.91 99 2.57 148 2.07 114 2.41 123 2.74 Guinea 129 97 150 2.36 2.12 2.60 42.1 117 2.28 145 2.01 124 2.38 97 2.54 97 2.54 148 2.38 Georgia 130 87 153 2.35 2.04 2.66 41.9 118 2.26 128 2.17 131 2.35 146 2.08 112 2.44 117 2.80 Cuba 131 98 150 2.35 2.10 2.59 41.7 105 2.38 108 2.31 136 2.31 135 2.25 124 2.31 145 2.51 Senegal 132 98 153 2.33 2.06 2.60 41.2 115 2.31 119 2.23 143 2.25 115 2.39 136 2.15 138 2.61 São Tomé and Príncipe 133 102 150 2.33 2.11 2.54 41.1 120 2.24 132 2.12 142 2.26 113 2.42 137 2.14 122 2.75 40 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 1  International LPI results Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Djibouti 134 98 153 2.32 2.06 2.58 41.0 106 2.37 110 2.30 111 2.48 152 1.96 139 2.09 132 2.69 Bhutan 135 95 153 2.32 2.04 2.60 41.0 128 2.21 151 1.96 108 2.50 131 2.30 131 2.20 129 2.70 Fiji 136 95 155 2.32 2.02 2.61 40.8 111 2.33 115 2.25 147 2.21 134 2.25 128 2.25 140 2.60 Libya 137 102 155 2.26 1.98 2.55 39.2 153 1.88 142 2.04 123 2.40 101 2.50 153 1.85 113 2.83 Bolivia 138 118 150 2.25 2.10 2.40 38.8 146 1.97 134 2.11 122 2.40 154 1.90 125 2.31 118 2.79 Angola 139 123 150 2.24 2.10 2.38 38.5 157 1.80 129 2.13 128 2.37 128 2.31 130 2.21 141 2.59 Turkmenistan 140 99 157 2.21 1.84 2.58 37.6 143 2.00 103 2.34 127 2.37 145 2.09 154 1.84 142 2.59 Armenia 141 124 153 2.21 2.03 2.38 37.4 148 1.95 122 2.22 146 2.22 137 2.21 147 2.02 139 2.60 Liberia 142 119 155 2.20 2.01 2.40 37.3 135 2.07 144 2.01 145 2.22 147 2.07 140 2.07 125 2.73 Gabon 143 116 155 2.19 1.96 2.43 36.9 134 2.07 141 2.05 141 2.28 142 2.12 142 2.07 144 2.52 Eritrea 144 111 157 2.17 1.86 2.49 36.3 140 2.01 139 2.06 150 2.16 136 2.25 146 2.03 146 2.50 Chad 145 118 155 2.16 1.92 2.41 36.1 133 2.08 136 2.07 121 2.41 149 2.06 141 2.07 155 2.25 Kyrgyz Republic 146 105 157 2.16 1.80 2.51 35.8 156 1.80 150 1.96 152 2.10 151 1.96 115 2.39 126 2.72 Madagascar 147 132 155 2.15 1.97 2.34 35.8 112 2.33 131 2.12 149 2.17 153 1.93 148 2.01 151 2.35 Cameroon 148 131 155 2.15 1.95 2.35 35.7 132 2.09 125 2.21 155 1.98 124 2.32 145 2.04 154 2.29 Iraq 149 137 154 2.15 2.03 2.27 35.6 139 2.01 153 1.87 134 2.33 150 1.97 149 1.98 135 2.66 Afghanistan 150 137 155 2.14 2.02 2.27 35.4 138 2.01 154 1.84 125 2.38 139 2.15 155 1.77 137 2.61 Zimbabwe 151 122 157 2.08 1.77 2.40 33.6 144 2.00 123 2.21 153 2.08 141 2.13 150 1.95 158 2.13 Lao PDR 152 133 157 2.07 1.81 2.33 33.1 155 1.85 155 1.76 148 2.18 144 2.10 156 1.76 133 2.68 Tajikistan 153 138 156 2.06 1.87 2.26 32.9 150 1.93 130 2.13 151 2.12 143 2.12 144 2.04 159 2.04 Lesotho 154 118 159 2.03 1.65 2.41 31.8 151 1.91 149 1.96 158 1.84 138 2.16 151 1.92 150 2.35 Sierra Leone 155 130 159 2.03 1.70 2.36 31.8 152 1.91 137 2.07 138 2.31 155 1.85 157 1.74 156 2.23 Equatorial Guinea 156 140 160 1.88 1.53 2.23 27.3 154 1.88 158 1.50 156 1.89 157 1.75 152 1.89 153 2.32 Mauritania 157 140 160 1.87 1.52 2.21 26.8 131 2.14 157 1.54 154 2.00 158 1.74 159 1.54 157 2.14 Somalia 158 151 160 1.75 1.37 2.13 23.2 159 1.29 156 1.57 157 1.86 156 1.85 160 1.51 152 2.35 Haiti 159 156 160 1.72 1.55 1.88 22.2 158 1.70 159 1.47 159 1.81 159 1.68 158 1.56 160 2.02 Syrian Arab Republic 160 156 160 1.60 1.29 1.91 18.5 160 1.11 160 1.24 160 1.36 160 1.39 138 2.10 147 2.40 Note: The LPI index is a multidimensional assessment of logistics performance, rated on a scale from 1 (worst) to 5 (best). The six core components captured by the LPI survey are rated by respondents on a scale of 1–5, where 1 is very low or very difficult and 5 is very high or very easy, except for question 15, where 1 is hardly ever and 5 is nearly always. The relative LPI score is obtained by normalizing the LPI score: Percentage of highest performer = 100 × [LPI – 1] / [LPI highest – 1]. Thus, the best performer has the maximum relative LPI score of 100 percent. Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 41 APPENDIX 2 Domestic LPI results, by region and income group Percent of respondents Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Question 17: Level of fees and charges High or very high 42 51 52 53 49 70 67 56 54 49 Port charges Low or very low 7 7 15 25 6 8 10 12 11 10 High or very high 50 43 42 45 33 53 44 43 51 43 Airport charges Low or very low 23 8 12 19 8 9 21 12 8 13 High or very high 50 6 59 27 42 59 67 40 36 35 Road transport rates Low or very low 19 50 13 29 12 3 2 17 27 20 High or very high 33 27 28 26 18 39 40 24 34 43 Rail transport rates Low or very low 22 28 43 50 33 18 20 31 33 18 High or very high 22 14 44 32 34 50 41 35 36 40 Warehousing/transloading charges Low or very low 11 36 18 14 19 10 17 17 17 23 High or very high 30 27 16 25 24 24 19 15 33 20 Agent fees Low or very low 22 38 20 27 39 25 35 34 17 26 Question 18: Quality of infrastructure Low or very low 35 29 45 35 25 33 43 26 38 19 Ports High or very high 23 27 21 33 18 25 24 24 27 54 Low or very low 31 10 20 34 36 30 22 30 25 14 Airports High or very high 37 48 22 35 25 23 21 28 36 55 Low or very low 45 36 53 32 53 39 37 44 41 14 Roads High or very high 20 24 12 24 5 18 17 18 19 45 Low or very low 54 49 86 64 63 61 61 53 72 44 Rail High or very high 21 22 3 20 3 17 17 18 12 25 Low or very low 47 16 21 33 48 32 33 30 29 6 Warehousing/transloading facilities High or very high 8 30 15 31 18 23 25 17 25 57 Low or very low 35 7 36 30 11 28 36 21 25 5 Telecommunications and IT High or very high 27 50 34 36 65 32 32 34 43 73 Question 19: Quality and competence of service Low or very low 33 24 49 10 27 30 36 32 24 9 Roads High or very high 27 35 17 34 16 22 14 27 29 58 Low or very low 53 35 74 67 50 59 62 54 58 33 Rail High or very high 21 16 4 11 4 16 15 13 12 33 Low or very low 9 2 10 11 13 22 20 13 10 4 Air transport High or very high 50 54 31 36 56 40 38 42 44 66 Low or very low 21 11 7 1 14 20 16 12 13 6 Maritime transport High or very high 48 55 34 43 51 42 36 46 46 62 Warehousing/transloading Low or very low 25 16 28 20 30 17 23 19 21 4 and distribution High or very high 23 46 34 38 26 25 20 27 41 63 Low or very low 11 10 10 11 13 6 6 6 13 3 Freight forwarders High or very high 37 58 31 49 53 47 48 47 43 75 Low or very low 26 17 43 25 33 20 25 26 26 10 Customs agencies High or very high 33 38 18 29 34 46 46 34 31 69 Quality/standards Low or very low 30 24 45 37 32 27 37 33 28 15 inspection agencies High or very high 25 31 16 25 25 21 16 22 27 53 42 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 2  Domestic LPI results, by region and income group Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Health/sanitary and Low or very low 48 36 53 38 43 31 40 38 40 23 phytosanitary agencies High or very high 23 25 18 25 20 20 21 18 25 43 Low or very low 20 9 18 29 22 12 16 17 17 8 Customs brokers High or very high 34 50 25 29 32 29 26 29 38 68 Low or very low 25 21 34 32 33 25 28 24 29 20 Trade and transport associations High or very high 21 33 32 21 28 23 18 26 31 49 Low or very low 16 9 19 12 5 18 23 14 12 13 Consignees or shippers High or very high 31 35 36 39 41 29 34 28 38 37 Question 20: Efficiency of processes Hardly ever or rarely 23 0 11 20 11 21 19 22 8 7 Clearance and delivery of imports Often or nearly always 56 71 71 53 64 46 48 47 71 85 Hardly ever or rarely 7 2 10 19 3 13 15 10 8 4 Clearance and delivery of exports Often or nearly always 77 86 76 64 85 59 60 67 78 91 Hardly ever or rarely 33 11 19 35 26 20 24 27 17 9 Transparency of customs clearance Often or nearly always 55 48 57 52 35 54 51 43 60 81 Transparency of other Hardly ever or rarely 35 12 20 31 27 22 27 24 20 10 border agencies Often or nearly always 48 49 53 55 35 40 42 44 49 74 Provision of adequate and timely Hardly ever or rarely 25 19 42 33 34 31 36 28 30 15 information on regulatory changes Often or nearly always 49 41 28 42 46 44 39 43 40 66 Expedited customs clearance for Hardly ever or rarely 31 17 18 28 23 32 30 32 19 14 traders with high compliance levels Often or nearly always 50 41 43 50 46 31 28 36 50 65 Question 21: Sources of major delays Compulsory warehousing/ Often or nearly always 10 15 32 35 20 26 23 24 25 7 transloading Hardly ever or rarely 49 54 42 40 33 38 39 41 45 69 Often or nearly always 10 6 34 33 21 23 25 22 21 10 Preshipment inspection Hardly ever or rarely 27 66 32 42 29 41 39 39 45 69 Often or nearly always 13 18 26 22 28 24 32 20 19 8 Maritime transshipment Hardly ever or rarely 27 56 45 28 32 29 25 38 40 55 Criminal activities Often or nearly always 18 8 15 13 22 11 16 13 11 5 (such as stolen cargo) Hardly ever or rarely 64 79 43 64 51 61 62 62 60 83 Often or nearly always 20 9 34 28 40 25 26 28 22 5 Solicitation of informal payments Hardly ever or rarely 47 64 40 44 25 34 26 39 52 78 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 43 Appendix 2  Domestic LPI results, by region and income group Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Question 22: Changes in the logistics environment since 2013 Much worsened or worsened 8 9 29 51 9 7 2 26 18 11 Customs clearance procedures Improved or much improved 78 63 31 28 68 68 76 51 50 59 Much worsened or worsened 7 13 25 60 4 14 11 19 29 11 Other official clearance procedures Improved or much improved 67 53 26 24 45 54 62 41 41 51 Much worsened or worsened 9 4 16 21 13 10 5 16 12 9 Trade and transport infrastructure Improved or much improved 71 56 46 40 54 47 51 51 49 53 Much worsened Telecommunications and or worsened 7 0 3 11 1 9 8 7 5 7 IT infrastructure Improved or much improved 74 73 65 40 82 60 56 57 71 70 Much worsened or worsened 1 0 10 13 11 5 5 6 7 2 Private logistics services Improved or much improved 80 80 50 46 76 61 62 61 65 63 Much worsened or worsened 6 21 31 45 25 13 12 24 26 13 Regulation related to logistics Improved or much improved 63 41 32 22 46 43 44 42 36 31 Much worsened or worsened 5 14 29 37 25 19 18 20 25 6 Solicitation of informal payments Improved or much improved 50 40 28 18 48 43 43 35 36 35 Note: Responses are calculated at the country level and then averaged by region and income group. Source: Logistics Performance Index 2016. 44 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 3 APPENDIX Domestic LPI results, time and cost data Question 24: Export time and cost Question 25: Import time and cost Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Albania 750 3 750 3 Algeria 112 4 474 5 150 1 Angola 25 14 25 14 2,000 10 Argentina 94 2 1,250 7 132 4 1,250 7 Australia 25 1 25 3 25 2 25 3 Austria 207 2 555 3 155 2 527 2 Bangladesh 339 4 304 7 345 5 253 7 Belarus 75 2 1,581 7 750 4 1,710 8 Belgium 83 2 334 4 167 3 276 2 Benin 292 3 909 7 211 2 177 2 Bolivia 1,250 12 1,250 6 612 13 2,000 8 Bosnia and Herzegovina 57 1 256 2 403 3 655 4 Brazil 173 3 415 8 281 4 944 20 Bulgaria 300 1 1,800 4 300 2 880 4 Burkina Faso 474 5 3,500 42 3,500 4 3,500 39 Burundi 230 7 689 12 1,841 15 388 9 Cambodia 87 3 178 5 87 4 407 6 Cameroon 25 8 1,040 11 224 9 339 12 Canada 100 2 401 4 87 2 388 4 Chad 2,092 22 2,092 24 2,092 24 1,250 7 China 130 3 402 6 187 5 649 9 Colombia 109 4 474 3 178 3 300 7 Congo, Dem. Rep. 612 8 300 18 612 7 612 7 Congo, Rep. 296 12 2,000 18 464 12 3,500 14 Costa Rica 150 3 75 3 119 4 Côte d’Ivoire 25 2 25 10 Cuba 75 6 300 10 75 7 Cyprus 43 1 512 5 43 1 296 4 Czech Republic 750 5 2,000 5 750 5 1,250 5 Denmark 25 1 25 1 75 1 75 1 Djibouti 41 2 238 4 117 3 423 6 Dominican Republic 52 4 75 2 36 4 75 4 Ecuador 43 1 25 43 3 Egypt, Arab Rep. 300 2 3,500 1 452 3 2,092 2 Estonia 775 4 2,000 5 Ethiopia 750 6 750 3 Finland 113 2 1,157 5 135 2 1,263 4 France 25 Gambia, The 25 1 25 1 25 1 25 1 Georgia 87 2 87 2 296 2 224 5 Germany 259 3 631 3 285 3 1,043 4 Ghana 260 3 625 4 199 4 276 6 Greece 83 3 1,647 6 83 3 1,647 6 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 45 Appendix 3  Domestic LPI results, time and cost data Question 24: Export time and cost Question 25: Import time and cost Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Guatemala 57 2 612 3 131 3 612 3 Haiti 25 2 25 2 Honduras 149 4 3,500 9 301 7 1,581 8 Hong Kong SAR, China 138 3 446 5 101 3 143 3 Hungary 300 3 300 3 India 231 4 729 6 322 5 473 6 Indonesia 133 3 145 3 126 5 165 5 Iran, Islamic Rep. 108 2 177 2 33 3 156 4 Iraq 300 39 2,000 46 300 7 2,000 14 Ireland 87 2 750 3 43 2 750 4 Israel 300 1 300 2 Italy 279 2 368 4 238 3 302 4 Jamaica 25 3 25 3 25 3 25 3 Japan 43 2 1,250 7 43 3 Jordan 1,250 2 300 7 Kazakhstan 25 3 478 9 25 3 403 8 Kenya 145 3 496 5 262 3 439 6 Korea, Rep. 1,250 2 75 2 2,000 3 75 2 Kuwait 25 2 75 1 75 2 Latvia 25 1 1,800 3 25 1 2,000 3 Lebanon 25 1 25 1 Liberia 300 7 750 10 300 7 750 10 Libya 25 11 25 4 Lithuania 332 2 1,107 4 399 3 1,392 5 Luxembourg 67 2 407 2 130 2 133 2 Macedonia, FYR 105 2 760 2 183 2 633 2 Madagascar 3 Malawi 1,250 1,250 25 Malaysia 75 3 300 7 Maldives 43 6 75 10 83 9 119 10 Malta 25 1 66 3 25 1 25 2 Mauritania 3,500 13 3,500 6 2,000 32 Mauritius 25 2 25 2 25 2 25 2 Mexico 255 2 1,690 5 219 3 1,601 4 Moldova 3,500 25 1,250 3 3,500 32 1,250 3 Mongolia 86 4 1,181 16 75 4 772 12 Morocco 186 4 2,000 6 202 5 1,432 8 Namibia 364 3 1,558 5 613 3 2,092 5 Netherlands 218 3 414 2 184 2 226 2 Niger 25 1 750 12 Nigeria 177 3 447 4 155 3 358 4 Norway 750 2 1,250 4 1,250 3 Oman 300 2 474 3 150 2 474 3 Pakistan 264 4 576 7 391 5 562 6 Panama 75 4 300 10 75 4 300 6 Peru 25 2 25 2 25 1 25 1 Philippines 64 3 241 10 61 7 300 9 46 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 3  Domestic LPI results, time and cost data Question 24: Export time and cost Question 25: Import time and cost Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Poland 300 1 1,054 4 300 1 612 2 Portugal 87 2 1,025 21 296 8 1,620 20 Qatar 48 4 2,094 7 133 3 1,620 5 Romania 377 3 701 3 212 3 1,024 4 Russian Federation 617 5 1,012 5 668 7 2,646 14 Rwanda 440 2 1,006 3 510 3 881 6 Saudi Arabia 47 3 108 2 104 7 595 13 Senegal 1,543 6 1,095 6 297 3 297 4 Serbia 43 1 1,250 4 43 2 750 3 Singapore 31 2 44 2 35 2 107 2 Slovak Republic 1,486 5 889 4 Slovenia 323 2 393 2 325 2 393 2 South Africa 278 3 1,281 6 224 3 730 4 Spain 83 3 750 3 149 4 Sri Lanka 70 1 95 4 43 2 33 2 Sudan 1,233 11 1,872 18 924 12 1,673 16 Sweden 968 3 750 3 Switzerland 75 1 750 5 75 2 750 5 Syrian Arab Republic 300 1 300 1 1,250 5 1,250 5 Taiwan, China 111 1 349 2 166 1 646 2 Tanzania 46 4 234 6 79 4 322 7 Thailand 25 1 25 2 25 1 25 2 Togo 33 2 286 5 25 3 177 6 Trinidad and Tobago 750 7 750 7 Tunisia 113 3 621 5 109 3 1,004 9 Turkey 121 2 1,118 5 119 2 574 4 Uganda 710 5 2,483 8 787 6 1,250 4 Ukraine 923 3 2,904 8 750 2 2,092 5 United Arab Emirates 70 2 307 3 107 2 265 2 United Kingdom 387 2 634 3 357 3 653 4 United States 427 3 1,081 4 237 3 483 4 Uruguay 78 4 512 3 52 3 3,500 2 Uzbekistan 296 18 25 10 512 20 387 12 Vietnam 141 3 249 3 102 3 230 3 Yemen, Rep. 1,250 3 1,250 5 1,250 7 1,250 7 Zambia 445 9 1,432 13 155 6 1,245 12 Zimbabwe 760 5 2,381 9 941 10 2,706 34 a. From the point of origin (the seller’s factory, typically located either in the capital city or in the largest commercial center) to the port of loading or equivalent (port/airport), and excluding international shipping (EXW to FOB). b. From the point of origin (the seller’s factory, typically located either in the capital city or in the largest commercial center) to the buyer’s warehouse (EXW to DDP). c. From the port of discharge or equivalent to the buyer’s warehouse (DAT to DDP). d. Aggregates of the distance indicator for port and airport. Source: Logistics Performance Index 2016. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 47 Appendix 3  Domestic LPI results, time and cost data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Albania 93 1 1 4 4 0 1 6 3 Algeria 53 3 3 3 3 3 6 75 50 Angola 88 5 5 7 7 6 10 35 1 Argentina 84 6 4 6 4 1 4 28 4 Armenia 3 5 6 7 Australia 93 2 1 7 3 2 4 3 1 Austria 96 1 1 2 2 0 1 2 1 Bangladesh 65 4 3 5 4 2 3 30 12 Belarus 92 5 4 4 4 1 2 6 1 Belgium 79 1 1 2 2 1 2 2 1 Benin 59 4 3 2 2 1 1 5 9 Bolivia 40 3 2 9 10 3 35 18 1 Bosnia and Herzegovina 68 2 1 3 3 0 1 11 3 Brazil 90 3 3 3 3 3 4 6 2 Brunei Darussalam Bulgaria 91 2 2 3 3 1 1 16 1 Burkina Faso 90 5 5 6 6 2 4 11 1 Burundi 52 5 4 3 4 3 4 19 10 Cambodia 92 2 2 4 4 2 2 21 10 Cameroon 58 6 7 9 9 3 4 29 21 Canada 89 3 2 2 2 0 3 3 1 Chad 61 4 4 6 4 8 5 11 9 China 72 3 3 5 4 2 3 10 3 Colombia 95 4 4 5 4 3 5 5 6 Congo, Dem. Rep. 40 7 7 6 6 5 6 75 61 Congo, Rep. 59 6 6 2 3 2 3 33 11 Costa Rica 51 2 2 3 2 1 4 9 3 Côte d’Ivoire 2 2 1 2 6 1 Cuba 83 3 3 2 2 5 8 35 6 Cyprus 92 1 1 1 1 1 1 22 9 Czech Republic 40 1 1 2 2 0 1 11 6 Denmark 97 1 1 1 1 0 1 3 3 Djibouti 80 3 3 3 3 1 1 8 5 Dominican Republic 89 3 3 4 4 2 3 20 6 Ecuador 92 4 3 4 3 1 1 2 1 Egypt, Arab Rep. 75 5 3 5 4 2 2 27 4 Estonia 93 1 1 1 1 1 1 1 1 Ethiopia 83 7 4 7 5 2 3 5 8 Finland 93 1 1 1 1 0 1 2 1 France 1 2 3 Gambia, The 88 7 7 1 1 1 Georgia 57 1 1 3 3 0 1 3 1 Germany 94 2 2 2 2 1 2 3 2 Ghana 82 6 6 6 5 2 2 33 6 Greece 92 1 1 2 2 1 1 9 4 48 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 3  Domestic LPI results, time and cost data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Guatemala 57 3 3 4 4 3 4 36 6 Haiti 40 3 3 2 2 7 10 6 1 Honduras 74 3 3 3 3 1 3 21 3 Hong Kong SAR, China 89 3 3 3 4 1 2 3 3 Hungary 97 1 1 1 1 1 1 3 1 India 69 3 4 5 5 2 3 22 4 Indonesia 80 2 2 4 3 2 4 5 2 Iran, Islamic Rep. 65 5 5 6 5 3 4 39 20 Iraq 40 3 5 6 6 3 6 75 75 Ireland 95 1 1 1 1 0 2 1 1 Israel 95 5 3 3 2 0 1 3 1 Italy 91 2 2 3 2 1 2 4 2 Jamaica 93 4 4 4 5 1 4 50 50 Japan 62 3 3 2 1 1 2 1 1 Jordan 83 4 3 4 4 2 3 14 3 Kazakhstan 89 2 2 3 3 1 2 5 2 Kenya 77 5 4 5 4 2 2 40 10 Korea, Rep. 97 2 1 4 2 1 2 18 18 Kuwait 83 3 1 1 1 3 3 75 1 Latvia 93 2 2 2 2 0 2 8 2 Lebanon 96 1 2 2 3 1 2 61 18 Liberia 5 7 4 4 1 2 3 3 Libya 83 4 3 5 4 4 7 35 35 Lithuania 92 2 2 2 2 0 1 3 2 Luxembourg 85 1 1 1 2 0 1 3 2 Macedonia, FYR 79 2 2 3 2 1 1 8 3 Madagascar 83 10 10 5 5 2 7 6 6 Malawi 2 3 7 7 5 6 14 9 Malaysia 83 Maldives 59 3 3 3 3 2 2 13 12 Malta 85 1 1 1 1 1 1 5 2 Mauritania 40 1 2 2 1 0 1 50 18 Mauritius 94 5 4 2 2 1 2 6 1 Mexico 79 3 2 4 3 1 2 9 3 Moldova 88 3 4 3 4 1 2 18 6 Mongolia 88 3 4 3 4 1 1 27 9 Morocco 80 3 2 4 4 2 2 10 3 Namibia 90 2 2 3 3 2 4 7 2 Netherlands 88 1 1 2 1 0 1 2 1 Niger 83 4 4 1 1 1 1 18 6 Nigeria 62 8 7 8 6 3 4 49 13 Norway 93 1 1 1 1 0 1 1 1 Oman 40 4 4 3 3 1 2 11 3 Pakistan 68 4 4 3 3 2 3 22 10 Panama 3 2 2 1 1 3 18 1 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 49 Appendix 3  Domestic LPI results, time and cost data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Peru 83 2 3 1 2 1 1 35 1 Philippines 58 5 5 5 5 3 7 21 3 Poland 95 1 1 1 1 1 1 11 7 Portugal 88 2 1 2 2 1 2 16 4 Qatar 76 5 5 3 3 1 2 32 14 Romania 90 1 1 2 2 1 1 3 1 Russian Federation 55 2 3 4 5 3 5 22 6 Rwanda 79 6 5 6 5 1 1 45 14 Saudi Arabia 65 2 2 3 2 2 4 62 6 Senegal 52 3 3 3 4 1 2 39 7 Serbia 92 1 1 2 2 1 1 3 1 Singapore 87 2 2 1 1 0 1 1 1 Slovak Republic 97 1 1 2 2 0 1 1 1 Slovenia 92 2 2 3 2 0 1 4 1 South Africa 76 2 2 3 2 1 4 4 2 Spain 91 3 2 4 3 1 1 5 3 Sri Lanka 78 3 3 4 3 1 2 37 13 Sudan 68 5 5 5 5 3 5 34 48 Sweden 95 1 1 1 1 0 1 2 2 Switzerland 97 1 1 2 2 0 0 1 1 Syrian Arab Republic 2 2 1 1 1 2 50 18 Taiwan, China 96 3 3 4 4 0 1 3 1 Tanzania 82 6 6 5 5 2 4 61 15 Thailand 93 1 1 2 1 1 2 1 1 Togo 65 3 3 3 3 2 2 19 3 Trinidad and Tobago 40 3 3 6 10 14 50 50 Tunisia 61 4 3 4 3 3 4 66 12 Turkey 68 3 2 3 3 1 2 7 3 Uganda 59 4 5 6 5 2 4 51 10 Ukraine 92 4 4 5 5 1 1 4 3 United Arab Emirates 82 3 3 3 3 1 1 14 4 United Kingdom 88 2 1 2 1 1 1 4 2 United States 96 3 2 3 3 1 2 4 3 Uruguay 91 1 1 1 1 1 2 3 1 Uzbekistan 61 3 3 5 5 4 9 14 9 Vietnam 57 4 3 4 3 1 3 17 9 Yemen, Rep. 93 4 4 3 3 3 Zambia 86 3 3 4 2 3 4 21 2 Zimbabwe 73 5 6 5 5 1 3 35 5 a. Time taken between the submission of an accepted customs declaration and notification of clearance. Source: Logistics Performance Index 2016. 50 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 4 APPENDIX LPI results across four editions (2010, 2012, 2014, and 2016) Scores of the six components across the five LPI surveys were used 167 countries. Each year’s scores in each component were given to generate a big picture to indicate countries’ logistics perfor- weights: 6.7 percent for 2010, 13.3 percent for 2012, 26.7 percent mance more accurately. This approach reduces random variation for 2014, and 53.3 percent for 2016. In this way, the most recent from one LPI survey to another and enables the comparison of data carry the highest weight. International Logistics quality LPI Customs Infrastructure shipments and competence Tracking and tracing Timeliness Mean Mean Mean Mean Mean Mean Mean Economy Rank score Rank score Rank score Rank score Rank score Rank score Rank score Germany 1 4.17 2 4.07 1 4.38 7 3.79 1 4.20 1 4.21 2 4.41 Netherlands 2 4.12 3 4.03 2 4.25 6 3.83 2 4.17 6 4.13 5 4.36 Singapore 3 4.10 1 4.11 3 4.22 4 3.89 5 4.06 9 4.02 6 4.35 Sweden 4 4.08 9 3.84 4 4.19 5 3.84 3 4.13 2 4.19 4 4.37 Luxembourg 5 4.08 8 3.84 10 4.08 1 4.02 13 3.90 14 3.96 1 4.68 Belgium 6 4.06 10 3.82 11 4.07 3 3.89 4 4.07 3 4.17 3 4.38 United Kingdom 7 4.02 5 3.92 6 4.14 8 3.70 6 4.02 7 4.10 7 4.32 Hong Kong SAR, China 8 4.00 7 3.88 12 4.06 2 3.92 10 3.95 11 3.99 9 4.21 United States 9 3.95 15 3.73 5 4.16 21 3.55 7 3.99 4 4.17 10 4.21 Japan 10 3.95 12 3.81 8 4.12 14 3.63 8 3.97 10 4.02 8 4.22 Austria 11 3.93 16 3.70 15 3.93 9 3.67 9 3.97 5 4.16 12 4.19 Switzerland 12 3.92 6 3.88 7 4.12 16 3.60 14 3.89 15 3.96 13 4.16 Canada 13 3.90 13 3.79 9 4.09 28 3.51 12 3.91 8 4.03 16 4.12 France 14 3.88 17 3.68 14 4.00 12 3.64 18 3.80 13 3.98 11 4.21 Finland 15 3.86 4 3.96 17 3.90 22 3.55 15 3.88 16 3.86 21 4.04 Denmark 16 3.84 11 3.81 19 3.82 11 3.65 11 3.94 24 3.70 17 4.12 Norway 17 3.80 14 3.74 13 4.02 26 3.53 16 3.83 22 3.74 24 4.01 Australia 18 3.79 19 3.64 18 3.86 18 3.58 17 3.82 17 3.85 20 4.04 United Arab Emirates 19 3.79 18 3.67 16 3.92 13 3.64 23 3.71 19 3.78 18 4.06 Ireland 20 3.78 20 3.56 22 3.73 10 3.66 20 3.80 12 3.98 25 4.00 Italy 21 3.72 24 3.41 20 3.78 19 3.58 22 3.71 18 3.83 19 4.04 Spain 22 3.71 21 3.51 23 3.73 20 3.57 21 3.74 21 3.74 22 4.03 Taiwan, China 23 3.70 27 3.35 25 3.62 15 3.61 19 3.80 25 3.69 14 4.15 Korea, Rep. 24 3.70 23 3.45 21 3.77 23 3.55 25 3.67 20 3.75 23 4.01 South Africa 25 3.65 25 3.41 26 3.60 24 3.54 24 3.68 23 3.73 27 3.95 China 26 3.60 32 3.27 24 3.70 17 3.59 26 3.55 28 3.60 32 3.88 Czech Republic 27 3.54 26 3.39 34 3.28 25 3.53 27 3.55 26 3.66 34 3.83 Israel 28 3.50 28 3.32 31 3.41 45 3.16 28 3.51 30 3.52 15 4.14 Qatar 29 3.50 30 3.31 30 3.43 29 3.44 29 3.44 34 3.47 31 3.88 Malaysia 30 3.48 35 3.23 29 3.48 27 3.52 31 3.39 31 3.49 37 3.76 New Zealand 31 3.48 22 3.45 27 3.56 51 3.12 34 3.33 29 3.52 28 3.94 Portugal 32 3.46 29 3.32 36 3.21 35 3.30 33 3.36 27 3.64 30 3.91 Poland 33 3.45 34 3.26 44 3.12 30 3.43 32 3.39 35 3.46 26 3.97 Turkey 34 3.44 37 3.17 28 3.49 32 3.33 30 3.42 33 3.49 38 3.76 Lithuania 35 3.39 36 3.18 33 3.28 36 3.30 39 3.24 38 3.39 29 3.92 Hungary 36 3.37 47 2.97 32 3.33 33 3.32 36 3.29 32 3.49 33 3.84 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 51 Appendix 4  LPI results across four editions (2010, 2012, 2014, and 2016) International Logistics quality LPI Customs Infrastructure shipments and competence Tracking and tracing Timeliness Mean Mean Mean Mean Mean Mean Mean Economy Rank score Rank score Rank score Rank score Rank score Rank score Rank score Iceland 37 3.35 31 3.30 42 3.18 41 3.22 35 3.33 39 3.39 39 3.71 Thailand 38 3.29 40 3.11 39 3.20 34 3.32 42 3.16 45 3.28 40 3.69 Estonia 39 3.28 33 3.27 43 3.14 52 3.12 43 3.15 49 3.18 36 3.80 Latvia 40 3.27 42 3.08 48 3.06 39 3.24 41 3.16 37 3.39 42 3.67 Slovak Republic 41 3.27 41 3.09 41 3.19 37 3.28 44 3.13 56 3.08 35 3.82 India 42 3.26 46 2.97 45 3.12 38 3.25 38 3.24 42 3.33 45 3.65 Slovenia 43 3.23 48 2.95 37 3.20 53 3.10 37 3.27 43 3.32 49 3.56 Chile 44 3.23 38 3.16 57 2.94 43 3.18 50 3.03 36 3.40 44 3.65 Panama 45 3.22 43 3.04 46 3.12 31 3.36 52 3.03 55 3.08 41 3.68 Bahrain 46 3.22 39 3.11 47 3.10 44 3.17 40 3.23 40 3.35 65 3.37 Saudi Arabia 47 3.16 58 2.76 35 3.26 54 3.10 49 3.05 48 3.22 48 3.58 Greece 48 3.16 50 2.90 40 3.19 65 2.93 55 2.96 41 3.34 43 3.66 Mexico 49 3.11 57 2.77 56 2.95 59 3.05 46 3.11 44 3.29 58 3.46 Croatia 50 3.11 45 3.01 54 2.98 60 3.05 48 3.07 53 3.13 64 3.39 Oman 51 3.10 53 2.82 38 3.20 42 3.22 53 3.02 65 2.89 61 3.43 Kuwait 52 3.08 54 2.80 50 3.00 40 3.23 64 2.84 50 3.16 60 3.44 Malta 53 3.07 52 2.83 51 3.00 48 3.12 56 2.91 57 3.08 55 3.47 Brazil 54 3.06 70 2.62 49 3.05 68 2.90 45 3.11 46 3.24 57 3.46 Egypt, Arab Rep. 55 3.06 63 2.71 55 2.96 56 3.08 47 3.09 54 3.09 63 3.41 Romania 56 3.05 51 2.87 62 2.76 47 3.13 57 2.91 58 3.08 51 3.53 Cyprus 57 3.04 44 3.02 53 2.98 64 2.93 63 2.84 70 2.84 47 3.61 Vietnam 58 3.03 59 2.75 59 2.80 46 3.15 58 2.91 60 3.00 53 3.51 Kenya 59 3.02 68 2.64 60 2.78 50 3.12 59 2.91 51 3.14 52 3.51 Indonesia 60 2.99 65 2.70 66 2.70 70 2.90 54 3.00 52 3.13 54 3.50 Argentina 61 2.99 72 2.58 58 2.85 66 2.91 60 2.88 47 3.23 56 3.47 Bulgaria 62 2.96 74 2.58 74 2.62 55 3.08 51 3.03 71 2.84 50 3.53 Uganda 63 2.94 49 2.91 82 2.56 63 2.94 72 2.77 78 2.75 46 3.62 Philippines 64 2.94 62 2.72 77 2.60 49 3.12 65 2.84 61 2.98 68 3.30 Uruguay 65 2.88 64 2.70 64 2.71 75 2.83 61 2.86 67 2.87 69 3.29 Peru 66 2.88 67 2.65 69 2.67 69 2.90 68 2.83 63 2.91 70 3.28 Brunei Darussalam 67 2.87 55 2.78 63 2.75 61 3.00 97 2.57 64 2.91 76 3.19 Jordan 68 2.87 82 2.51 68 2.68 57 3.07 70 2.78 75 2.78 67 3.32 Pakistan 69 2.86 66 2.69 70 2.65 62 2.96 73 2.77 74 2.81 75 3.22 Morocco 70 2.84 99 2.42 61 2.78 58 3.05 75 2.73 89 2.65 66 3.34 Botswana 71 2.82 56 2.78 67 2.69 91 2.66 81 2.66 81 2.71 62 3.42 Serbia 72 2.82 96 2.43 81 2.56 74 2.83 66 2.84 62 2.93 71 3.27 Malawi 73 2.81 61 2.73 52 2.99 87 2.70 62 2.86 92 2.62 99 3.01 Ukraine 74 2.81 101 2.40 80 2.56 84 2.72 80 2.67 59 3.02 59 3.45 Bahamas, The 75 2.79 60 2.73 65 2.71 76 2.82 71 2.78 88 2.65 93 3.04 Rwanda 76 2.77 69 2.63 106 2.38 72 2.86 89 2.63 68 2.86 78 3.18 El Salvador 77 2.76 80 2.52 102 2.39 73 2.84 69 2.79 73 2.81 82 3.14 Ecuador 78 2.76 77 2.54 87 2.49 71 2.89 87 2.64 87 2.66 72 3.26 Tanzania 79 2.74 81 2.51 78 2.57 79 2.78 85 2.65 84 2.69 74 3.23 Lebanon 80 2.74 73 2.58 75 2.61 82 2.74 86 2.65 66 2.89 103 2.98 Kazakhstan 81 2.74 91 2.46 73 2.63 80 2.76 88 2.63 69 2.84 89 3.08 Cambodia 82 2.72 75 2.56 104 2.38 67 2.91 96 2.59 76 2.76 88 3.08 52 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 4  LPI results across four editions (2010, 2012, 2014, and 2016) International Logistics quality LPI Customs Infrastructure shipments and competence Tracking and tracing Timeliness Mean Mean Mean Mean Mean Mean Mean Economy Rank score Rank score Rank score Rank score Rank score Rank score Rank score Dominican Republic 83 2.71 89 2.47 96 2.42 81 2.76 74 2.73 80 2.72 84 3.13 Costa Rica 84 2.69 108 2.38 99 2.40 78 2.80 84 2.65 72 2.82 90 3.07 Bosnia and Herzegovina 85 2.69 71 2.59 76 2.60 111 2.57 92 2.62 94 2.60 79 3.18 Sri Lanka 86 2.68 79 2.52 123 2.24 103 2.62 67 2.84 82 2.71 87 3.08 Colombia 87 2.66 106 2.39 88 2.48 102 2.62 77 2.71 97 2.58 77 3.18 Algeria 88 2.66 98 2.42 92 2.46 85 2.71 82 2.66 85 2.68 96 3.02 Namibia 89 2.66 86 2.49 72 2.64 99 2.63 94 2.61 101 2.54 94 3.04 Côte d’Ivoire 90 2.66 85 2.50 95 2.42 90 2.67 90 2.63 79 2.74 107 2.96 Bangladesh 91 2.65 104 2.39 105 2.38 77 2.81 93 2.62 99 2.57 86 3.09 Nigeria 92 2.65 115 2.35 94 2.43 115 2.53 78 2.68 77 2.76 81 3.14 Tunisia 93 2.62 137 2.16 91 2.47 101 2.63 95 2.60 86 2.67 80 3.18 Paraguay 94 2.62 100 2.41 93 2.44 100 2.63 79 2.67 104 2.52 98 3.02 Ghana 95 2.62 112 2.37 89 2.48 86 2.71 103 2.51 95 2.59 97 3.02 Burkina Faso 96 2.62 93 2.46 86 2.50 105 2.59 91 2.62 115 2.46 91 3.07 Guatemala 97 2.62 76 2.56 109 2.35 110 2.57 105 2.49 96 2.58 85 3.12 Russian Federation 98 2.61 152 2.07 90 2.47 114 2.54 76 2.72 83 2.70 83 3.14 Moldova 99 2.58 113 2.36 100 2.40 88 2.69 117 2.40 98 2.57 95 3.03 Maldives 100 2.57 83 2.51 85 2.53 118 2.52 98 2.55 102 2.53 130 2.79 Mauritius 101 2.57 117 2.33 84 2.53 94 2.65 104 2.50 120 2.42 106 2.96 Nicaragua 102 2.56 88 2.48 107 2.37 108 2.58 100 2.51 108 2.51 113 2.91 Albania 103 2.56 123 2.30 137 2.17 97 2.64 99 2.54 127 2.37 73 3.26 Iran, Islamic Rep. 104 2.55 127 2.27 83 2.55 107 2.58 83 2.66 112 2.47 132 2.78 Benin 105 2.54 107 2.38 98 2.41 109 2.58 101 2.51 118 2.43 110 2.93 Guyana 106 2.54 111 2.37 120 2.25 116 2.53 106 2.48 90 2.64 109 2.93 Venezuela, RB 107 2.53 141 2.11 101 2.40 96 2.64 109 2.47 91 2.63 111 2.92 Niger 108 2.53 78 2.54 126 2.22 104 2.60 114 2.43 125 2.38 105 2.97 Macedonia, FYR 109 2.53 126 2.27 79 2.56 121 2.48 108 2.47 122 2.40 101 3.00 Honduras 110 2.53 110 2.38 138 2.15 92 2.66 111 2.46 100 2.55 108 2.94 Togo 111 2.53 114 2.35 131 2.19 98 2.64 126 2.35 93 2.61 102 2.99 Jamaica 112 2.53 92 2.46 103 2.39 112 2.55 116 2.41 105 2.52 125 2.82 Montenegro 113 2.52 105 2.39 111 2.33 89 2.67 125 2.36 107 2.51 120 2.85 Belarus 114 2.51 132 2.21 108 2.36 95 2.65 115 2.42 136 2.34 100 3.01 Mozambique 115 2.48 119 2.32 134 2.18 83 2.74 131 2.30 111 2.48 123 2.83 Georgia 116 2.47 116 2.34 112 2.33 133 2.41 132 2.30 106 2.52 115 2.91 São Tomé and Príncipe 117 2.47 122 2.31 117 2.27 124 2.46 112 2.44 103 2.53 133 2.76 Azerbaijan 118 2.47 94 2.46 71 2.64 106 2.58 155 2.17 145 2.26 142 2.70 Comoros 119 2.46 87 2.49 121 2.25 125 2.46 113 2.44 121 2.41 141 2.71 Papua New Guinea 120 2.46 102 2.40 118 2.25 126 2.45 127 2.35 110 2.48 122 2.83 Senegal 121 2.46 97 2.42 114 2.29 113 2.55 107 2.47 135 2.34 144 2.66 Solomon Islands 122 2.46 84 2.51 119 2.25 150 2.28 110 2.46 133 2.34 118 2.87 Mali 123 2.45 125 2.28 127 2.21 120 2.50 130 2.33 117 2.44 112 2.92 Uzbekistan 124 2.44 138 2.16 113 2.31 141 2.36 122 2.39 123 2.39 104 2.98 Guinea 125 2.42 120 2.32 149 2.08 128 2.44 102 2.51 109 2.50 149 2.63 Ethiopia 126 2.42 95 2.44 144 2.12 117 2.53 121 2.39 132 2.35 151 2.62 Mongolia 127 2.41 129 2.25 143 2.13 134 2.41 140 2.25 131 2.35 92 3.05 C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 53 Appendix 4  LPI results across four editions (2010, 2012, 2014, and 2016) International Logistics quality LPI Customs Infrastructure shipments and competence Tracking and tracing Timeliness Mean Mean Mean Mean Mean Mean Mean Economy Rank score Rank score Rank score Rank score Rank score Rank score Rank score Zambia 128 2.41 121 2.31 132 2.19 137 2.39 128 2.35 124 2.39 126 2.81 Central African Republic 129 2.40 90 2.47 97 2.42 157 2.20 123 2.39 134 2.34 145 2.65 Armenia 130 2.40 135 2.18 115 2.29 130 2.43 118 2.40 146 2.24 124 2.83 Trinidad and Tobago 131 2.40 109 2.38 110 2.34 148 2.31 135 2.28 142 2.28 128 2.79 Guinea-Bissau 132 2.40 103 2.40 148 2.09 119 2.51 142 2.24 130 2.35 134 2.74 Fiji 133 2.39 124 2.29 116 2.28 135 2.39 148 2.22 138 2.32 131 2.78 Myanmar 134 2.38 130 2.25 124 2.22 154 2.25 138 2.27 113 2.47 121 2.84 Bolivia 135 2.38 139 2.16 136 2.17 131 2.42 146 2.23 114 2.47 129 2.79 Nepal 136 2.38 151 2.08 133 2.18 129 2.43 147 2.23 116 2.45 119 2.86 Liberia 137 2.36 133 2.21 128 2.21 139 2.37 129 2.34 143 2.27 138 2.73 Sudan 138 2.35 147 2.11 151 2.07 140 2.36 133 2.29 129 2.36 117 2.88 Burundi 139 2.34 148 2.10 155 2.03 149 2.30 137 2.27 119 2.43 114 2.91 Bhutan 140 2.34 134 2.18 153 2.05 122 2.48 124 2.36 141 2.29 150 2.63 Libya 141 2.33 153 2.07 150 2.08 136 2.39 120 2.40 149 2.20 127 2.81 Angola 142 2.33 157 2.02 140 2.14 123 2.47 141 2.25 139 2.31 136 2.73 Madagascar 143 2.32 118 2.32 130 2.20 147 2.32 153 2.18 147 2.22 143 2.68 Yemen, Rep. 144 2.30 165 1.77 156 2.01 127 2.45 134 2.29 128 2.36 116 2.89 Gambia, The 145 2.29 144 2.11 157 2.00 93 2.65 136 2.28 154 2.12 160 2.52 Turkmenistan 146 2.29 143 2.11 122 2.25 132 2.41 157 2.13 157 2.08 135 2.74 Cameroon 147 2.27 154 2.07 146 2.11 159 2.14 119 2.40 144 2.27 153 2.60 Chad 148 2.27 136 2.16 142 2.13 142 2.36 158 2.12 148 2.21 155 2.58 Congo, Rep. 149 2.26 164 1.84 139 2.15 151 2.26 144 2.23 126 2.37 140 2.72 Cuba 150 2.26 128 2.26 141 2.13 143 2.33 154 2.18 150 2.20 162 2.46 Zimbabwe 151 2.24 156 2.03 125 2.22 155 2.24 139 2.26 153 2.13 156 2.57 Congo, Dem. Rep. 152 2.24 142 2.11 159 1.97 158 2.17 149 2.22 140 2.30 147 2.64 Lao PDR 153 2.24 149 2.10 158 1.98 144 2.33 150 2.21 161 2.02 137 2.73 Tajikistan 154 2.24 145 2.11 135 2.17 145 2.33 143 2.23 152 2.18 164 2.36 Gabon 155 2.23 155 2.05 154 2.05 138 2.38 151 2.21 156 2.09 158 2.55 Kyrgyz Republic 156 2.23 159 1.99 152 2.06 153 2.25 159 2.07 137 2.32 146 2.65 Djibouti 157 2.21 131 2.23 145 2.12 156 2.21 161 2.02 160 2.04 148 2.64 Iraq 158 2.19 160 1.97 160 1.95 146 2.32 160 2.06 158 2.05 139 2.72 Lesotho 159 2.16 158 2.01 147 2.10 163 2.07 145 2.23 159 2.05 161 2.50 Afghanistan 160 2.15 146 2.11 163 1.86 152 2.26 156 2.14 165 1.88 154 2.60 Eritrea 161 2.11 161 1.91 162 1.88 162 2.12 152 2.19 162 1.96 159 2.55 Equatorial Guinea 162 2.10 150 2.10 164 1.79 165 1.99 162 1.96 151 2.19 157 2.57 Mauritania 163 2.07 140 2.12 161 1.93 161 2.12 163 1.93 166 1.87 163 2.40 Sierra Leone 164 2.04 163 1.85 129 2.21 160 2.13 164 1.88 164 1.90 166 2.28 Haiti 165 1.96 162 1.89 166 1.70 164 2.04 165 1.86 163 1.90 165 2.35 Syrian Arab Republic 166 1.94 166 1.61 165 1.72 166 1.84 166 1.73 155 2.12 152 2.62 Somalia 167 1.67 167 1.49 167 1.54 167 1.72 167 1.72 167 1.51 167 2.03 Source: Logistics Performance Index 2010, 2012, 2014, and 2016. 54 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 5 APPENDIX The LPI methodology Because logistics has many dimensions, measur- where limited coverage was observed after the ing and summarizing performance across coun- first phase concluded. tries are challenging. Examining the time and The web engine for 2016 is the same as the costs associated with logistics processes­—­ port new engine put in place in 2012. It follows a processing, customs clearance, transport, and uniform sampling randomized approach to the like­—­is a good start, and, in many cases, gain the most possible responses from under- this information is readily available. But even represented countries. Because the survey en- if complete, this information cannot be eas- gine relies heavily on a specialized country- ily aggregated into a single, consistent, cross-­ selection methodology for survey respondents country dataset because of structural differences based on high trade volume between countries, in country supply chains. Even more important, the randomized approach can help countries many critical elements of good logistics such as with lower trade volumes rise to the top during process transparency and service quality, pre- country selection. dictability, and reliability cannot be assessed The 2015/16 survey engine builds a set of using only time and cost information. countries for the survey respondents that are subject to the rule set (see table A5.1). After 200 Constructing the international LPI surveys, the uniform sampling randomized ap- proach is introduced into the engine’s process The first part of the LPI survey (questions for country selection. For each new survey re- 10–15) provides the raw data for the interna- spondent, the method solicits a response from a tional LPI. Each survey respondent rates eight country chosen at random but with nonuniform overseas markets on six core components of probability, and weights are chosen to evolve logistics performance. The eight markets are the sampling toward uniform probability. Spe- chosen at random based on the most impor- cifically, a country i is chosen with a probabil- tant export and import markets of the coun- ity (N − ni) / 2 N, where ni is the sample size of try where the respondent is located. Among country i so far, and N is the total sample size. respondents in landlocked countries, the selec- The international LPI is a summary indica- tion is based on neighboring transit countries tor of logistics sector performance, combining that form part of the landbridge connecting the data on six core performance components into a landlocked country with international markets. single aggregate measure. Some respondents did The method used to select the group of coun- not provide information for all six components, tries rated by each respondent varies by the char- so interpolation is used to fill in missing values. acteristics of the country where the respondent The missing values are replaced with the coun- is located (table A5.1). try mean response for each question, adjusted Respondents take the survey online. In by the respondent’s average deviation from the the 2016 edition, the survey was open in two country mean in the answered questions. phases, in October–December 2015 and in The six core components are: March–April 2016. The two-phased approach • The efficiency of customs and border manage- helped to build up the respondent base using a ment clearance, rated from very low (1) to more targeted outreach effort in those regions very high (5) in survey question 10. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 55 Table A5.1 Methodology for selecting country groups for survey respondents Respondents from Respondents from Respondents from low‑income countries middle‑income countries high‑income countries Three most important export partner countries + The most important import partner country Five most important export + partner countries Respondents from Four countries randomly, one Two countries randomly from a + coastal countries from each country group: list of five most important export Three most important a. Africa partner countries and five most partner countries b. East, South, and important import partner countries Central Asia + c. Latin America Four countries randomly, one d. Europe less Central from each country group: Asia and OECD a. Africa Three most important b. East, South, and export partner countries Central Asia + c. Latin America The most important import d. Europe less Central Four most important export partner country Asia and OECD partner countries + + + Two land-bridge countries Two countries randomly Respondents from from the combined country Two most important import + landlocked countries groups a, b, c, and d partner countries Two countries randomly, one + from each country group: Two land-bridge countries a. Africa, East, South, and Central Asia, and Latin America b. Europe less Central Asia and OECD Source: Logistics Performance Index 2016. • The quality of trade and transport infrastruc- sample mean and dividing by the standard de- ture, rated from very low (1) to very high (5) viation before conducting the analysis. The out- in survey question 11. put of the analysis is a single indicator, the LPI, • The ease of arranging competitively priced which is a weighted average of the scores. The shipments, rated from very difficult (1) to weights are chosen to maximize the percentage very easy (5) in survey question 12. of variation in the original six LPI indicators • The competence and quality of logistics serv- that is accounted for by the summary indicator. ices, rated from very low (1) to very high (5) Full details on the principal component in survey question 13. analysis procedure are shown in tables A5.2 and • The ability to track and trace consignments, A5.3. The first line of table A5.2 shows that the rated from very low (1) to very high (5) in first (principal) eigenvalue of the correlation survey question 14. matrix of the six core indicators is greater than • The frequency with which shipments reach 1 and much larger than any other eigenvalue. consignees within scheduled or expected deliv- Standard statistical tests, such as the Kaiser ery times, rated from hardly ever (1) to nearly Criterion and the eigenvalue scree plot, suggest always (5) in survey question 15. that a single principal component should be re- The LPI is constructed from these six in- tained to summarize the underlying data. This dicators using principal component analysis, principal component is the international LPI. a standard statistical technique used to reduce Table A5.2 shows that the international LPI ac- the dimensionality of a dataset. In the LPI, the counts for 92 percent of the variation in the six inputs for the analysis are country scores on components. questions 10–15, averaged across all respon- To construct the international LPI, normal- dents providing data on a given overseas mar- ized scores for each of the six original indica- ket. Scores are normalized by subtracting the tors are multiplied by their component loadings 56 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y (table A5.3) and then summed. The component Table A5.2 Results of principal component analysis for the international LPI loadings represent the weight given to each orig- inal indicator in constructing the international Variance proportion LPI. Since the loadings are similar for all six, the Component Eigenvalue Difference Individual Cumulative international LPI is close to a simple average of 1 5.66 5.55 0.94 0.94 the indicators. Although principal component 2 0.11 0.03 0.02 0.96 analysis is rerun for each version of the LPI, the 3 0.08 0.02 0.01 0.98 weights remain steady from year to year. There 4 0.06 0.02 0.01 0.99 is thus a high degree of comparability across the 5 0.05 0.01 0.01 0.99 various LPI editions. 6 0.04 na 0.01 1.00 na is not applicable. Constructing the confidence intervals Table A5.3 Component loadings for the international LPI To account for the sampling error created by the Component Weight LPI’s survey-based methodology, LPI scores are Customs 0.41 presented with approximate 80 percent confi- Infrastructure 0.41 dence intervals. These intervals make it possible International shipments 0.41 to provide upper and lower bounds for a coun- Logistics quality and competence 0.41 try’s LPI score and rank. To determine whether Tracking and tracing 0.41 a change in score or a difference between two Timeliness 0.40 scores is statistically significant, confidence intervals must be examined carefully. For exam- ple, a statistically significant improvement in a the center. The lower bound is the LPI rank a country’s performance should not be inferred country would receive if its LPI score were at the unless the lower bound of the country’s 2016 lower bound of the confidence interval rather LPI score exceeds the upper bound of its 2014 than at the center. In both cases, the scores of score. all other countries are kept constant. To calculate the confidence interval, the The average confidence interval on the 1–5 standard error of LPI scores across all respon- scale is 0.23, or about 8 percent of the average dents is estimated for a country. The upper and country’s LPI score. Because of the bunching of lower bounds of the confidence interval are then LPI scores in the middle of the distribution, the confidence interval translates into an average t(0.1, N–1)S of 20 rank places, using upper and lower rank LPI ± , N bounds as calculated above. Caution is required in interpreting small differences in LPI scores where LPI is a country’s LPI score, N is the and rankings. number of survey respondents for that country, Although it is the most comprehensive data s is the estimated standard error of each coun- source for country logistics and trade facilita- try’s LPI score, and t is Student’s t-distribution. tion, the LPI has two important limitations. As a result of this approach, confidence inter- First, the experience of international freight vals and low-high ranges for scores and ranks are forwarders might not represent the broader lo- larger for small markets with few respondents gistics environment in poor countries, which because these estimates are less certain. often rely on traditional operators. And inter- The high and low scores are used to calcu- national and traditional operators might differ late upper and lower bounds on country ranks. in their interactions with government agencies The upper bound is the LPI rank a country and in their service levels. Second, for land- would receive if its LPI score were at the upper locked countries and small island states, the bound of the confidence interval rather than at LPI might reflect access problems outside the C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 57 country assessed, such as transit difficulties. The 23 refers to the availability of qualified staff for low rating of a landlocked country might not different groups of employees in logistics (opera- adequately reflect the country’s trade facilita- tive, administrative, supervisory and managerial tion efforts, which depend on the workings of staff). complex international transit systems. Land- With a few exceptions, questions 24–35 locked countries cannot eliminate transit inef- ask respondents for quantitative information ficiencies through domestic reforms. on their countries’ international supply chains, offering choices in a dropdown menu. When a Constructing the domestic response indicates a single value, the answer is LPI database coded as the logarithm of that value. When a response indicates a range, the answer is coded The second part of the LPI survey instrument is as the logarithm of the midpoint of that range. the domestic LPI, in which respondents provide For example, export distance can be indicated qualitative and quantitative information on the as less than 50 kilometers, 50–100 kilometers, logistics environment in the country where they 100–500 kilometers, and so forth; so, a response work. of 50–100 kilometers is coded as log(75). Full Questions 17–22 ask respondents to choose details of the coding matrix are available on one of five performance categories. In question request. 17, for example, they can describe port charges Country scores are produced by exponen- in their country as very high, high, average, low, tiating the average of responses in logarithms or very low. As in the international LPI, these across all respondents for a given country. This options are coded from 1 (worst) to 5 (best). Ap- method is equivalent to taking a geometric aver- pendix 2 displays country averages of the per- age in levels. Scores for regions, income groups, centage of respondents rating each aspect of the and LPI quintiles are simple averages of the rel- logistics environment as 1–2 or 4–5. Question evant country scores. 58 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 6 APPENDIX Respondent demographics Operators on the ground are best placed to Figure A6.1 2016 LPI survey respondents, assess the vital aspects of logistics performance. by World Bank income group The LPI thus uses a structured online survey of Number of respondents logistics professionals at multinational freight forwarders and at the main express carriers. The Low income 2016 LPI data are based on a survey conducted 116 High between October and December 2015 and income Lower middle income between March and April 2016 among 1,051 non-OECD 119 322 respondents at international logistics companies in 132 countries. The number of respondents is about the same in the 2016 LPI as in other edi- High income tions of the LPI. OECD 276 Upper middle income 218 Geographic dispersion of respondents Source: Logistics Performance Index 2016. The location of respondents for the 2016 LPI reflects the growing importance of trade facilitation for the developing world. Among the respondents, 62 percent are in either low- Figure A6.2 2016 LPI survey respondents, income countries (11  percent) or middle- by World Bank region income countries (51  percent). The overall Number of respondents number is similar to the 2014 LPI, but, this Latin America & Caribbean year, there are relatively more contributions Middle East & 53 North Africa from low-income countries. Their relative lack 73 of representation, however, is due to their more marginal role in world trade and the difficulty East Asia & Pacific of communicating effectively with operators on 75 High income Europe & 395 the ground (figure A6.1). Central Asia 80 Among developing countries, all regions are well represented (figure A6.2). Compared with South Asia 117 previous surveys, the 2016 edition does a bet- Sub-Saharan ter job of including Sub-­Saharan Africa, thanks Africa 258 in part to the two-stage sampling methodology adopted on this occasion. It remains important to ensure that developing countries from all re- Note: World Bank regions do not include high-income countries, so they are included as a separate category. gions are adequately represented among respon- Source: Logistics Performance Index 2016. dents, although proportions across regions nec- essarily vary from year to year. C O N N E C T I N G T O C O M P E T E 2 0 16  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 59 Respondents’ positions work in Europe (27 percent), Asia (18 percent), in their companies Africa (14 percent), or the Americas (8 percent). The remaining 4 percent are divided between The LPI assesses large companies as well as the Middle East and Australia and the Pacific. small and medium enterprises. Large com- panies (those with 250 employees or more) Bilateral perception issues account for around 24.5 percent of responses, which is slightly higher than in 2014. Most of Bilateral issues might play a role in driving sur- the responses are thus from small and medium vey respondents’ perceptions when rating their enterprises. respective regions. In the last edition of the LPI, Knowledgeable senior company members it was noted that, while idiosyncratic effects can are important to the survey. The 2016 respon- shift the perception of certain regions about the dents include senior executives (53 percent), area logistics performance of more distant trading or country managers (15 percent), and depart- partners and regional neighbors, these effects ment managers (16 percent). These groups of did not represent a significant bias. Using the professionals have oversight responsibilities or case of Latin America, it was found that, while are directly involved in day-to-day operations these effects inevitably exist, despite subjectiv- not only from company headquarters but also ity, the LPI scores were relatively tightly placed from country offices. The relative seniority of around the average, indicating a limited effect of respondents has slightly increased from 2014 to any possible bias. 2016. Two-thirds of respondents are at corpo- In the current edition of the LPI, the two rate or regional headquarters (43 percent) or at data collection phases increased the exposure country branch offices (22 percent). The rest are of the survey to geographies that have been at local branch offices (6 percent) or indepen- traditionally less present among respondents. dent firms (27 percent). In particular, a higher share of respondents The majority of respondents (52 percent) are included logistics operators in Sub-­ Saharan involved in providing a range of logistics serv- Africa. Based on simple comparisons of recip- ices as their main line of work. Such services in- rocal assessments across regions, Sub-­ Saharan clude warehousing and distribution, customer- respondents seemingly tend to be much more tailored logistics solutions, courier services, bulk lenient with other Sub-­ Saharan countries than or break bulk cargo transport, and less than full the rest of the respondents from other geogra- container, full container, or full trailer load phies. While we believe the effect is certainly transport. By contrast, only 33 percent of re- not negligible, controlling for this effect in an spondents are at companies with business mod- ad hoc manner would require a substantial over- els based on full-container or full-trailer load haul of the LPI methodology, possibly creating transport (22 percent) or on customer-tailored a discontinuity in the comparability across edi- logistics solutions (11 percent). tions. In consequence, this possible leniency Among all respondents, 46  percent deal effect should be considered in evaluating the with multimodal transport, 24  percent with results of Sub-­Saharan countries in the overall maritime transport, and 11  percent with air context of the survey. The issue of idiosyncratic transport. Whereas 3 percent only handle do- bias in a perception-­based survey merits further mestic trade, 46 percent deal with exports or im- research to derive additional logistics perfor- ports. 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World Trade Report 2015: ———. 2016. “Logistics as a Political Issue.” Transport Reviews 36 (4): Speeding up Trade; Benefits and Challenges of Implementing the WTO 413–17. Trade Facilitation Agreement. Geneva: WTO. 62 C O N N E C T I N G T O C O M P E T E 2 0 16 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y What is the Logistics Performance Index? Based on a worldwide survey of global freight forwarders and express carriers, the Logistics Performance Index is a benchmarking tool developed by the World Bank that measures performance along the logistics supply chain within a country. Allowing for comparisons across 160 countries, the index can help countries identif y challenges and opportunities and improve their logistics performance. The World Bank conducts the survey every two years. Reliable logistics is indispensable to integrate global value chains—and reap the benefit of trade opportunities for growth and poverty reduction. The ability to connect to the global logistics web depends on a country’s infrastructure, service markets, and trade processes. Government and the private sector in many developing countries should improve these areas—or face the large and growing costs of exclusion. This is the fifth edition of Connecting to Compete, a report summarizing the findings from the new dataset for Logistics Performance Index (LPI) and its component indicators. The 2016 LPI also provides expanded data on supply chains performance and constraints in more than 125 countries, including information on time, cost, and reliability and ratings on domestic infrastructure quality, services, or border agencies. The 2016 LPI encapsulates the firsthand knowledge of movers of international trade. This information is relevant for policymakers and the private sector seeking to identify reform priorities for “soft” and “hard” trade and logistics infrastructure. Findings include: • The “logistics gap” between more and less developed countries persists. The gap between the top ranked countries and those at the bottom of the scale widened in 2016. • Supply chain reliability continues to be a major concern for traders and logistics providers alike. • Infrastructure still plays an important role in assuring basic connectivity and access to gateways for most developing countries. • Improvements in trade facilitation are critical for the countries performing lowest in terms of logistics, including many low- income economies. • The logistics agenda is broadening: the 2016 edition includes findings regarding skills shortages and the growing demand for sustainable logistics solutions.