Publication:
Multidimensional Well-Being Measurement Practices: A Review Focused on Improving Global Multidimensional Poverty Indicators

Loading...
Thumbnail Image
Files in English
English PDF (620.78 KB)
107 downloads
English Text (153.29 KB)
16 downloads
Published
2024-06-12
ISSN
Date
2024-06-13
Editor(s)
Abstract
Multidimensional well-being indicators have the potential to reduce the “bias” associated to monetary indicators. However, they face stringent data constraints. This paper studies the construction of indicators that strike a balance between (i) reliability in approximating conceptually sound well-being comparisons and (ii) simplicity of application and communication. The recommendations focus on global multidimensional poverty measures. The paper identifies three potential sources of improvements: “wasting” less data, better filtering the data, and further developing multidimensional analysis. Less information would be “wasted” by avoiding needlessly dichotomizing all the variables, using the available mortality data, and combining variables from separate surveys. To filter the data better, “equal weights” could be replaced by weights selected from external information on preferences. When the data permit, the unit of analysis should be switched from household level to individual level. Finally, multidimensional indicators should be used to help move beyond a suboptimal “dimension-by-dimension” approach to policy making.
Link to Data Set
Citation
Decerf, Benoit. 2024. Multidimensional Well-Being Measurement Practices: A Review Focused on Improving Global Multidimensional Poverty Indicators. Policy Research Working Paper; 10800. © World Bank. http://hdl.handle.net/10986/41703 License: CC BY 3.0 IGO.
Associated URLs
Associated content
Report Series
Report Series
Other publications in this report series
  • Publication
    The Economic Value of Weather Forecasts: A Quantitative Systematic Literature Review
    (Washington, DC: World Bank, 2025-09-10) Farkas, Hannah; Linsenmeier, Manuel; Talevi, Marta; Avner, Paolo; Jafino, Bramka Arga; Sidibe, Moussa
    This study systematically reviews the literature that quantifies the economic benefits of weather observations and forecasts in four weather-dependent economic sectors: agriculture, energy, transport, and disaster-risk management. The review covers 175 peer-reviewed journal articles and 15 policy reports. Findings show that the literature is concentrated in high-income countries and most studies use theoretical models, followed by observational and then experimental research designs. Forecast horizons studied, meteorological variables and services, and monetization techniques vary markedly by sector. Estimated benefits even within specific subsectors span several orders of magnitude and broad uncertainty ranges. An econometric meta-analysis suggests that theoretical studies and studies in richer countries tend to report significantly larger values. Barriers that hinder value realization are identified on both the provider and user sides, with inadequate relevance, weak dissemination, and limited ability to act recurring across sectors. Policy reports rely heavily on back-of-the-envelope or recursive benefit-transfer estimates, rather than on the methods and results of the peer-reviewed literature, revealing a science-to-policy gap. These findings suggest substantial socioeconomic potential of hydrometeorological services around the world, but also knowledge gaps that require more valuation studies focusing on low- and middle-income countries, addressing provider- and user-side barriers and employing rigorous empirical valuation methods to complement and validate theoretical models.
  • Publication
    The Macroeconomic Implications of Climate Change Impacts and Adaptation Options
    (Washington, DC: World Bank, 2025-05-29) Abalo, Kodzovi; Boehlert, Brent; Bui, Thanh; Burns, Andrew; Castillo, Diego; Chewpreecha, Unnada; Haider, Alexander; Hallegatte, Stephane; Jooste, Charl; McIsaac, Florent; Ruberl, Heather; Smet, Kim; Strzepek, Ken
    Estimating the macroeconomic implications of climate change impacts and adaptation options is a topic of intense research. This paper presents a framework in the World Bank's macrostructural model to assess climate-related damages. This approach has been used in many Country Climate and Development Reports, a World Bank diagnostic that identifies priorities to ensure continued development in spite of climate change and climate policy objectives. The methodology captures a set of impact channels through which climate change affects the economy by (1) connecting a set of biophysical models to the macroeconomic model and (2) exploring a set of development and climate scenarios. The paper summarizes the results for five countries, highlighting the sources and magnitudes of their vulnerability --- with estimated gross domestic product losses in 2050 exceeding 10 percent of gross domestic product in some countries and scenarios, although only a small set of impact channels is included. The paper also presents estimates of the macroeconomic gains from sector-level adaptation interventions, considering their upfront costs and avoided climate impacts and finding significant net gross domestic product gains from adaptation opportunities identified in the Country Climate and Development Reports. Finally, the paper discusses the limits of current modeling approaches, and their complementarity with empirical approaches based on historical data series. The integrated modeling approach proposed in this paper can inform policymakers as they make proactive decisions on climate change adaptation and resilience.
  • Publication
    Rigging the Scores: Corruption through Scoring Rule Manipulation in Public Procurement Auctions
    (Washington, DC: World Bank, 2025-12-02) Chen, Qianmiao
    Public procurement is highly susceptible to corruption, especially in developing countries. Although open auctions are widely adopted to curb it, this paper finds that corruption remains prevalent even within this procurement format. Procurement officers can collaborate with firms to manipulate scoring rules, ensuring predetermined winners, while corrupt firms submit noncompetitive bids to meet minimum bidder requirements. Using extensive data from Chinese public procurement auctions, the paper introduces model-driven statistical tools to detect such corruption, identifying a corruption rate of 65 percent. A procurement expert audit survey confirms the tools’ reliability, with a 91 percent probability that experts recognize suspicious scoring rules when flagged. Firm-level analysis reveals that local, state-owned, and less productive firms are favored in corrupt auctions. Lastly, the paper explores policy implications. Analysis of the national anti-corruption campaign since 2012 suggests that general investigations may be insufficient to address deeply ingrained corrupt practices. Using counterfactuals based on an estimated structural model, the paper shows that implementing anonymous call-for-tender evaluations could improve social welfare by 10 percent by eliminating suspicious rules and encouraging broader participation.
  • Publication
    Labor Demand in the Age of Generative AI: Early Evidence from the U.S. Job Posting Data
    (Washington, DC: World Bank, 2025-11-18) Liu, Yan; Wang, He; Yu, Shu
    This paper examines the causal impact of generative artificial intelligence on U.S. labor demand using online job posting data. Exploiting ChatGPT’s release in November 2022 as an exogenous shock, the paper applies difference-in-differences and event study designs to estimate the job displacement effects of generative artificial intelligence. The identification strategy compares labor demand for occupations with high versus low artificial intelligence substitution vulnerability following ChatGPT’s launch, conditioning on similar generative artificial intelligence exposure levels to isolate substitution effects from complementary uses. The analysis uses 285 million job postings collected by Lightcast from the first quarter of 2018 to the second quarter of 2025Q2. The findings show that the number of postings for occupations with above-median artificial intelligence substitution scores fell by an average of 12 percent relative to those with below-median scores. The effect increased from 6 percent in the first year after the launch to 18 percent by the third year. Losses were particularly acute for entry-level positions that require neither advanced degrees (18 percent) nor extensive experience (20 percent), as well as those in administrative support (40 percent) and professional services (30 percent). Although generative artificial intelligence generates new occupations and enhances productivity, which may increase labor demand, early evidence suggests that some occupations may be less likely to be complemented by generative artificial intelligence than others.
  • Publication
    Investment Policy Reforms and Foreign Direct Investment Inflows
    (Washington, DC: World Bank, 2025-12-01) Fwaga, Sammy; Chakrapani, Deepa; Abebe, Girum
    Foreign direct investment has the potential to introduce much-needed capital and expertise in emerging and developing economies. To attract foreign direct investment, many countries have eased restrictions on foreign ownership in various sectors, reformed their institutions, and set up investment promotion agencies. Until the mid-2010s, Ethiopia remained one of the few countries that resisted this trend, with several stringent restrictions in place on foreign direct investment entry and operations in the country. This study employs a synthetic control method to examine patterns in foreign capital inflows following a series of investment policy reforms that were substantively introduced in the mid-2010s (circa 2015). The study offers evidence that investment policy reforms contributed to a significant foreign direct investment inflow in Ethiopia, compared to what would have occurred in the absence of these policies. An alternative strategy that conservatively specifies the donor country pool using an AI-assisted deep search technique changes the donor pool weighting matrix of the synthetic control method, but the estimated policy effects largely remain robust to this specification. The findings highlight the importance of targeted reforms in promoting foreign direct investment inflow in developing countries.
Journal
Journal Volume
Journal Issue

Related items

Showing items related by metadata.

  • Publication
    A Welfarist Theory Unifying Monetary and Non-Monetary Poverty Measurement
    (World Bank, Washington, DC, 2022-06) Decerf, Benoit
    Multidimensional poverty measures are increasingly used in practice even though they face strong criticism and generate longlasting debates. These contentions primarily find their origin in the divergence between standard poverty identification practices and a welfarist definition of the poor. This paper fills this gap by constructing a poverty measurement theory that (i) adopts a welfarist definition of the poor, (ii) acknowledges that the relevant welfare function is only partially known and (iii) encompasses both market and non-market dimensions of well-being. The theory shows that standard identification practices are not flexible enough in order to properly account for the multidimensional nature of well-being. This nature implies that an individual is poor when she experiences an extremely low outcome in some dimension or/and when she cumulates moderately low outcomes in several dimensions. The paper proposes a simple refinement that better reflects this insight. The paper uses the theory in order to provide answers to several longlasting debates. The theory provides a conceptual foundation from which practitioners may derive guidance for the many choices they face.
  • Publication
    Reconceptualizing Global Multidimensional Poverty Measurement, with Illustration on Nigerian Data
    (Washington, DC: World Bank, 2023-10-03) Decerf, Bonoit; Fonton, Kike
    Multidimensional poverty measures can in theory make well-being comparisons that are less biased than those solely based on monetary poverty. However, global multidimensional poverty measures suffer in practice from limitations that have led to credible criticisms. This paper presents the case for multidimensional poverty measures, two criticisms against their current implementations, as well as recently proposed solutions to improve on these criticisms. The paper develops a method for implementing these solutions in practice. The resulting well-being indicator is used to compare well-being across Nigerian states in 2019. This empirical illustration suggests that these solutions may substantially affect well-being comparisons. The paper also quantifies the potential bias inherent to comparing well-being solely based on monetary poverty. The results find substantially different well-being comparisons between the proposed well-being indicator and monetary poverty even though monetary poverty was (i) high in Nigeria in 2019 and (ii) very heterogeneously distributed across Nigerian states; and (iii) is integrated as one component of the proposed well-being indicator. The paper aims to improve global multidimensional poverty measures by making them more consistent with preference theory and by incorporating the direct impact of mortality, which deprives individuals of the most important functioning.
  • Publication
    A Quick-Fix for Perverse Incentives Inherent in Mainstream Multidimensional Poverty Measures
    (Washington, DC: World Bank, 2025-05-05) Decerf, Benoit
    Most multidimensional poverty measures used in practice, including the global Multidimensional Poverty Index, are based on the adjusted headcount ratio. This paper shows that this poverty index provides perverse incentives. Policies that minimize this index prioritize targeting the least intensely poor individuals, rather than the most intensely poor individuals. This paper proposes a quick-fix solution that tweaks the adjusted headcount ratio without affecting the identification of the poor. The resulting index satisfies the same properties as the adjusted headcount ratio, except for Dimensional Breakdown. The paper argues that this is not a sufficient reason to discard this index, by providing two examples illustrating key limitations of the decomposition across dimensions permitted by Dimensional Breakdown. This decomposition does not provide the necessary information to find optimal policies. More importantly, this decomposition may mislead policy makers on the underlying sources of progress.
  • Publication
    Integrating Mortality into Poverty Measurement through the Poverty Adjusted Life Expectancy Index
    (World Bank, Washington, DC, 2022-07) Baland, Jean-Marie; Cassan, Guilhem; Decerf, Benoit
    Poverty measures typically do not account for mortality, resulting in counter-intuitive evaluations. The reason is that they (i) suffer from a mortality paradox and (ii) do not attribute intrinsic value to the lifespan. The paper proposes the first poverty index that always attributes a positive value to lifespan and does not suffer from the mortality paradox. This index, called the poverty-adjusted life expectancy, follows an expected lifecycle utility approach a la Harsanyi and is based on a single normative parameter that transparently captures the trade-off between poverty and mortality. This indicator can be straightforwardly generalized to account for unequal lifespans. Empirically, we show that accounting for mortality substantially changes cross-country comparisons and trends. The paper also quantifies the fraction of these comparisons that are robust to the choice of the normative parameter.
  • Publication
    Normative Indicators Combining Poverty and Mortality
    (World Bank, Washington, DC, 2022-05) Decerf, Benoit
    This paper surveys the small branch of welfare economics that studies indicators combining poverty and mortality. The paper distinguishes two reasons for constructing such indicators. The first reason is to perform multidimensional well-being comparisons. For this purpose, mortality has (negative) intrinsic value. The key question relates to the trade-off that the indicator makes between poverty and mortality, that is, between the quality and quantity of life. A lifecycle utility approach suggests expressing this trade-off as the number of years spent in poverty that is deemed equivalent to one year lost to mortality. The second reason is to investigate the instrumental role that selective mortality—the fact that the poor tend to die earlier—has on the evolution of poverty measures. Then, the key question is how to define the counterfactual situation against which the instrumental impact of mortality is assessed.

Users also downloaded

Showing related downloaded files

  • Publication
    Digital Progress and Trends Report 2023
    (Washington, DC: World Bank, 2024-03-05) World Bank
    Digitalization is the transformational opportunity of our time. The digital sector has become a powerhouse of innovation, economic growth, and job creation. Value added in the IT services sector grew at 8 percent annually during 2000–22, nearly twice as fast as the global economy. Employment growth in IT services reached 7 percent annually, six times higher than total employment growth. The diffusion and adoption of digital technologies are just as critical as their invention. Digital uptake has accelerated since the COVID-19 pandemic, with 1.5 billion new internet users added from 2018 to 2022. The share of firms investing in digital solutions around the world has more than doubled from 2020 to 2022. Low-income countries, vulnerable populations, and small firms, however, have been falling behind, while transformative digital innovations such as artificial intelligence (AI) have been accelerating in higher-income countries. Although more than 90 percent of the population in high-income countries was online in 2022, only one in four people in low-income countries used the internet, and the speed of their connection was typically only a small fraction of that in wealthier countries. As businesses in technologically advanced countries integrate generative AI into their products and services, less than half of the businesses in many low- and middle-income countries have an internet connection. The growing digital divide is exacerbating the poverty and productivity gaps between richer and poorer economies. The Digital Progress and Trends Report series will track global digitalization progress and highlight policy trends, debates, and implications for low- and middle-income countries. The series adds to the global efforts to study the progress and trends of digitalization in two main ways: · By compiling, curating, and analyzing data from diverse sources to present a comprehensive picture of digitalization in low- and middle-income countries, including in-depth analyses on understudied topics. · By developing insights on policy opportunities, challenges, and debates and reflecting the perspectives of various stakeholders and the World Bank’s operational experiences. This report, the first in the series, aims to inform evidence-based policy making and motivate action among internal and external audiences and stakeholders. The report will bring global attention to high-performing countries that have valuable experience to share as well as to areas where efforts will need to be redoubled.
  • Publication
    Global Economic Prospects, January 2025
    (Washington, DC: World Bank, 2025-01-16) World Bank
    Global growth is expected to hold steady at 2.7 percent in 2025-26. However, the global economy appears to be settling at a low growth rate that will be insufficient to foster sustained economic development—with the possibility of further headwinds from heightened policy uncertainty and adverse trade policy shifts, geopolitical tensions, persistent inflation, and climate-related natural disasters. Against this backdrop, emerging market and developing economies are set to enter the second quarter of the twenty-first century with per capita incomes on a trajectory that implies substantially slower catch-up toward advanced-economy living standards than they previously experienced. Without course corrections, most low-income countries are unlikely to graduate to middle-income status by the middle of the century. Policy action at both global and national levels is needed to foster a more favorable external environment, enhance macroeconomic stability, reduce structural constraints, address the effects of climate change, and thus accelerate long-term growth and development.
  • Publication
    The Container Port Performance Index 2023
    (Washington, DC: World Bank, 2024-07-18) World Bank
    The Container Port Performance Index (CPPI) measures the time container ships spend in port, making it an important point of reference for stakeholders in the global economy. These stakeholders include port authorities and operators, national governments, supranational organizations, development agencies, and other public and private players in trade and logistics. The index highlights where vessel time in container ports could be improved. Streamlining these processes would benefit all parties involved, including shipping lines, national governments, and consumers. This fourth edition of the CPPI relies on data from 405 container ports with at least 24 container ship port calls in the calendar year 2023. As in earlier editions of the CPPI, the ranking employs two different methodological approaches: an administrative (technical) approach and a statistical approach (using matrix factorization). Combining these two approaches ensures that the overall ranking of container ports reflects actual port performance as closely as possible while also being statistically robust. The CPPI methodology assesses the sequential steps of a container ship port call. ‘Total port hours’ refers to the total time elapsed from the moment a ship arrives at the port until the vessel leaves the berth after completing its cargo operations. The CPPI uses time as an indicator because time is very important to shipping lines, ports, and the entire logistics chain. However, time, as captured by the CPPI, is not the only way to measure port efficiency, so it does not tell the entire story of a port’s performance. Factors that can influence the time vessels spend in ports can be location-specific and under the port’s control (endogenous) or external and beyond the control of the port (exogenous). The CPPI measures time spent in container ports, strictly based on quantitative data only, which do not reveal the underlying factors or root causes of extended port times. A detailed port-specific diagnostic would be required to assess the contribution of underlying factors to the time a vessel spends in port. A very low ranking or a significant change in ranking may warrant special attention, for which the World Bank generally recommends a detailed diagnostic.
  • Publication
    The Container Port Performance Index 2020 to 2024: Trends and Lessons Learned
    (Washington, DC: World Bank, 2025-09-22) World Bank
    The Container Port Performance Index (CPPI) provides a global benchmark of how container ports perform in handling vessel calls. Developed jointly by the World Bank and S&P Global Market Intelligence, it measures the time ships spend in port and relates this to the number of containers moved during that time. This approach makes the CPPI a unique diagnostic tool that can highlight patterns in port operations and shed light on global and regional supply chain dynamics. Now in its fifth edition, the CPPI report covers the period from 2020 to 2024. It builds on a well-established methodology to generate scores for more than 400 container ports worldwide. Over time, the CPPI has become a trusted reference point for policymakers, industry stakeholders, and researchers who seek to understand how ports adapt to shocks, recover from disruptions, and identify opportunities for investments, reform and modernization. A major innovation in this edition is the introduction of multi-year trend analysis. Rather than presenting annual snapshots, the report now tracks how CPPI scores have changed across five years. This longitudinal perspective reveals shifts in port performance, showing where scores have risen, fallen, or remained stable. By linking these movements to external factors, the CPPI offers insights into how global and regional supply chains evolve under pressure. The results clearly mirror the crises that have shaken global trade. During the COVID-19 pandemic, CPPI scores in different regions declined sharply as congestion, equipment shortages, and delays overwhelmed many ports. By 2023, global averages rebounded in parallel with easing freight markets and reduced congestion. Yet 2024 brought new challenges: the Red Sea crisis disrupted major trade lanes, while climate-related constraints at the Panama Canal added further stress. These shocks were reflected in lower global and several regional average scores, underscoring the vulnerability of maritime transport to geopolitical and environmental events. The CPPI is not about comparing one port against another, but about understanding changes in performance over time. Ports that improved their scores often did so by reducing time at anchor, optimizing berth operations, investing in digital tools, and strengthening coordination across logistics partners. The evidence confirms that improvements are possible across ports of all sizes, and that rising scores are linked to deliberate actions to minimize time in port relative to containers moved. By consolidating five years of results, this edition transforms the CPPI into a long-term reference point. It shows how global crises have affected shipping, how different regions have adapted, and what lessons can be drawn for future resilience. The World Bank and S&P Global Market Intelligence remain committed to maintaining the CPPI as a global public good, providing transparency, comparability, and practical insights to support more reliable and sustainable maritime supply chains.
  • Publication
    Global Economic Prospects, June 2025
    (Washington, DC: World Bank, 2025-06-10) World Bank
    The global economy is facing another substantial headwind, emanating largely from an increase in trade tensions and heightened global policy uncertainty. For emerging market and developing economies (EMDEs), the ability to boost job creation and reduce extreme poverty has declined. Key downside risks include a further escalation of trade barriers and continued policy uncertainty. These challenges are exacerbated by subdued foreign direct investment into EMDEs. Global cooperation is needed to restore a more stable international trade environment and scale up support for vulnerable countries grappling with conflict, debt burdens, and climate change. Domestic policy action is also critical to contain inflation risks and strengthen fiscal resilience. To accelerate job creation and long-term growth, structural reforms must focus on raising institutional quality, attracting private investment, and strengthening human capital and labor markets. Countries in fragile and conflict situations face daunting development challenges that will require tailored domestic policy reforms and well-coordinated multilateral support.