65644 POVERTY THE WORLD BANK REDUCTION AND ECONOMIC MANAGEMENT NETWORK (PREM) Economic Premise NOVEMBER 2011 • Number 70 JUN 010 • Numbe 18 Who Creates Jobs? Ejaz Ghani, William R. Kerr, and Stephen D. O’Connell There is a consensus that jobs are vital in translating economic growth into lasting poverty reduction and social cohesion. But who creates jobs is an understudied field. This Economic Premise argues that there is a strong link between initial levels of young and small firms and subsequent job growth, as evidenced in India. The economic geography of entrepreneurship in India is still evolving. It is worrying that there are too few entrepreneurs in India for its stage of development. Yet there is no question that entrepreneurship works—cities and states that have embraced entrepreneurship have created more jobs. How- ever, the link between entrepreneurship and job growth is not automatic. Cities that have a higher quality of physical infrastructure and a more educated workforce attract many more entrepreneurs. Supportive incumbent industrial structures for input and output markets are strongly linked to higher entrepreneurship rates. There are many policy levers that can be used by policy makers to promote entrepreneurial growth. Instead of being preoccupied with firm chasing—attracting large mature firms from other locations—policy makers should focus on encouraging entrepreneurship in their communities. The role of entrepreneurs in economic growth and job creation entrepreneurship is still at an early stage (Glaeser, Rosenthal, has a long intellectual tradition. Cantillion (1730) described and Strange 2009; Klapper and Love 2011). How should one entrepreneurship as self-employment, with entrepreneurs buy- define/quantify entrepreneurship? What kind of entrepre- ing at certain prices in the present, and selling at uncertain neurship—mom and pop shops or formal firms—creates more prices in the future. Knight (1921) explained the unique role jobs? Do young and small establishments or large and estab- that entrepreneurs play by emphasizing how entrepreneurs lished firms contribute more to job growth? At what kind of take risk and act upon fundamental market changes—recogniz- geographical scale do entrepreneurial mechanics function? ing opportunity, bearing uncertainty, and directing new ven- Why do some cities attract entrepreneurs while others do not? tures. Schumpeter (1942) linked entrepreneurship to growth Do agglomeration economies differ across industries, cities, by highlighting how they convert new ideas into successful in- and gender? What makes some local governments fiscally more novations, generating “creative destruction� by simultaneously entrepreneurial than others? These questions have started to at- creating new products and eliminating others. More recently, tract attention, but many of them remain unanswered. Glaeser (2007) has identified entrepreneurship with urban success. Quantifying Entrepreneurship While the great giants of economic history recognized the This analysis starts by examining the impact of entrepreneurs link between entrepreneurship, economic growth and job cre- in South Asia (Ghani, Kerr, and O’Connell 2011a). Figure 1 ation, challenges and controversies remain. Understanding of compares the new business registration density of South Asian 1 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise Figure 1. New Business Registration Density and GDP per Capita, even greater for India, given the huge size of the informal sector by Country (2008) (Kanbur 2011) and the urgency to pull millions out of the in- United Kingdom formal and into the formal sector. 9 Following this emerging strand, this note defines entrepre- number of new �rms per 1,000 neurship as the presence of young establishments, less than working-age population 7 three years old, in the formal manufacturing sector. The pri- 5 mary metric of entrepreneurship used here—young establish- Maldives ments per 1,000 workers in the formal sector—shows a slight 3 Malaysia upward trend over time in India; but it also shows significant Brazil Korea, Rep. of heterogeneity across states. 1 Japan Table 1 describes the correlation between the young estab- Thailand India Sri Lanka lishments per worker measure and the other metrics across Pakistan -1 6 7 8 9 10 11 states or industries. There is a modest degree of correlation within the formal group, which is comparable to the 0.4–0.6 log (2000 GDP per capita, in constant PPP $) correlations that Glaeser and Kerr (2009) observed across U.S. Source: World Bank Group Entrepreneurship Snapshots 2010; World Development Indicators 2010. cities for entrepreneurship metrics. The link across metrics is Note: Countries designated as offshore tax shelters excluded. Fitted line depicts regression much weaker in the informal sector, especially in regional varia- of density on 2000 log (GDP/cap) and its square term. Eighty-nine countries with available data shown. tion. The correlation between formal and informal sector mea- sures is much weaker. For example, the correlation between countries with the rest of the world. Contrary to popular belief, young establishments per worker in the formal sector and the it turns out that India, as well as other countries in the region, self-employment rate in the informal sector is about 0.1. There has too few entrepreneurs for its stage of development. is likewise a much weaker correlation between small establish- Demographic trends for India, the second most populous ment metrics and self-employment metrics. This analysis ex- country in the world, suggest that 1 million new workers will cludes self-employment and the informal sector, except as ro- join the labor force every month for the next two decades bustness checks and to contrast results. (Bloom, Canning, and Rosenberg 2011; World Bank 2011a). This is equivalent to the entire popu- lation of Sweden joining the labor force in India Table 1. Correlation between Measures of Entrepreneurship in Indian Manufacturing every year for the next two decades (Kochhar 2011b; Mitra 2011). The pace at which new jobs Correlation to count of young are created will determine whether the demo- establishments per 1,000 workers graphic trends become a dividend or a disaster in Combining India. Formal Informal formal and There are many distinct characteristics of entre- sector only sector only informal preneurship—self-employment, firm size, owner- Correlation across regions ship, entry, and innovation—that have been high- lighted in the literature. Measuring different Count of small establishments per 1,000 workers 0.20 0.10 0.15 aspects of entrepreneurship can be difficult. Re- (< 20 employees), 1989 cent studies note the challenges that come with us- Share of workers in young establishments, 1989 0.64* 0.91* 0.78* ing self-employment metrics to describe the entre- preneurship necessary for economic growth and Share of workers in small establishments, 1989 0.23 -0.04 -0.07 job creation. Due to the much larger raw count of Self-employment share, 1989 0.45 0.34 0.49* self-employed workers, self-employment indices Correlation across industries accord much more weight to hobby entrepreneur- ship than entrepreneurship that can lead to sub- Count of small establishments per 1,000 workers 0.68* 0.39* 0.52* stantial job creation. (< 20 employees), 1989 So the focus has now shifted from self-employ- Share of workers in young establishments, 1989 0.66* 0.77* 0.80* ment to formal establishments that employ paid Share of workers in small establishments, 1989 0.71* 0.04 0.66* workers. These thresholds—being incorporated and paying payroll taxes—are in some sense arbi- Self-employment share, 1989 0.22 0.49* 0.18 trary, but they are natural, given the fundamental Source: Ghani, Kerr, and O’Connell 2011a. interest in describing job creation. Its relevance is Note: * = significant at 10% level. 2 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise Figure 2. Entrepreneurship and Growth in Indian Manufacturing employment growth, 1989–2005 Figure 3. Entrepreneurship and Growth in Indian Manufacturing employment growth, 1989–2005 Goa 1 4 Karnataka Haryana T amil Nadu 2 .5 Kerala Punjab Gujarat 0 Orissa Andhra Pradesh Maharasht ra 0 -2 Utt ar Pradesh W est Bengal Madhya Pradesh -.5 -4 -7.5 -7 -6.5 -6 -5.5 -10 -8 -6 -4 -2 log(new establishments per worker), 1989 log(new establishments per worker), 1989 Source: India Annual Survey of Industries, 1989–2005. Source: India Annual Survey of Industries, 1989-2005. Note: Plotted points represent state-industry clusters. Table 2. Region-Industry Employment Growth in Formal Manufacturing and Various Entrepreneurial Metrics Count of young Count of small Share of workers Share of workers Self-employment Self-employment establishments per establishments per in young in small share in formal share in informal worker worker establishments establishments sector sector (1) (2) (3) (4) (5) (6) A. Dependent variable: region-industry employment growth in formal manufacturing, 1989–2005 Entrepreneurship level 0.334 0.255 0.178 0.269 0.051 0.072 in region-industry in (0.040)*** (0.040)*** (0.046)*** (0.040)*** (0.028)* (0.037)** 1989 Adjusted R-squared 0.108 0.087 0.038 0.090 0.002 0.006 B. Panel A, controlling for initial employment Entrepreneurship level 0.258 0.163 0.101 0.176 0.017 0.040 in region-industry in (0.049)*** (0.040)*** (0.045)** (0.041)*** (0.027) (0.038) 1989 Employment level in -0.097 -0.137 -0.149 -0.135 -0.161 -0.191 region-industry in 1989 (0.030)*** (0.027)*** (0.027)*** (0.027)*** (0.024)*** (0.026)*** Adjusted R-squared 0.125 0.126 0.087 0.129 0.079 0.104 Source: Ghani, Kerr, and O’Connell 2011a. Notes: Estimations quantify the relationship between region-industry employment growth in the formal manufacturing sector over 1989–2005 and initial entrepreneurship conditions in 1989. Column headers indicate entrepreneurship metric employed. All variables are in logs. Estimations report robust standard errors, are unweighted, and have 575 observations. * = significant at 10% level; ** = significant at 5% level; *** = significant at 1% level. Link between New Establishments and Figure 3 provides a comparable picture using region-indus- Job Growth try employment growth and initial entrepreneurship levels. The pattern looks even more powerful and robust at this level Figure 2 provides the simplest representation of the link be- of detail. It is important to note that these correlations are not tween entrepreneurship and job growth. The vertical axis is the between contemporaneous entry rates and employment log employment growth in the region from 1989 to 2005, growth, which can potentially have a mechanical relationship, while the horizontal axis is the log count of new establishments but instead between initial entry rates and subsequent region- per worker in 1989. There is a strong upward slope to the trend industry employment growth. line, similar to that found across cities in the United States Table 2 provides a systematic comparison of the entrepre- (Glaeser and Kerr 2010a), and it is clear that the relationship neurship metrics using the region-industry variation. The sam- does not overly depend upon any one region. ple includes 575 region-industry pairs that have positive employ- 3 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise ment in 1989. Panel A presents an unconditional estimation, region and region-industry levels. This starting point is interest- while panel B conditions on log initial employment (Delgado, ing because it highlights that entrepreneurship at both levels is Porter, and Stern 2010; Glaeser and Kerr 2010a). Column head- important for growth in the local region-industry. Similar pat- ers indicate the entrepreneurship metric employed. terns are evident in the United States. Elasticities, in the first four columns in panel A, range from Column 2 further incorporates a vector of industry fixed ef- 0.18 to 0.33 at the region-industry level: all estimates are statis- fects. These fixed effects capture the general growth of indus- tically significant. In strong contrast, there is a much weaker tries in India between 1989 and 2005 and the levels of entre- link from self-employment metrics, in either the formal or in- preneurship that existed in 1989. Whereas the simplest formal sector, to subsequent job growth. This stresses the im- correlations could have reflected general differences between portance of how entrepreneurship is measured to estimate its textile and chemical industries, for example, these fixed effects link to local job growth. There are similar results in panel B af- require that the estimates only exploit variations across states ter controlling for initial employment levels in region-indus- after controlling for general industry differences. These fixed tries. Coefficients tend to be a quarter to a third smaller, but effects also account for other fixed industry factors like capital they remain economically and statistically significant. High intensity and export behavior. Elasticities are similar in this es- levels of initial employment are correlated with lower job timation, although the region-industry entrepreneurship vari- growth to 2005, indicative of convergence. These estimates able loses about half of its strength. This suggests that general provide simple and transparent evidence. industry differences—some sectors being very entrepreneurial It is natural to worry about omitted factors that could influ- and fast growing across all Indian states—partly explain the ence both employment growth and firm age. Table 3 provides a strong effects in table 2. Nevertheless, region-industry entre- more formal set of growth regressions using young establish- preneurship remains important economically and precisely es- ments in a region-industry context. To address this uncertain- timated in the conditional regression. ty, column 1 begins by simply including the explanatory vari- Column 3 goes a step further and includes a vector of state ables of initial entrepreneurship and employment levels at both fixed effects. Like industry fixed effects, regional fixed effects re- Table 3. Region-Industry Growth Estimations for Formal Manufacturing Employment Base estimation Controlling for age Using only with young Including industry Including industry Weighting by initial structure of standalone establishments fixed effects and region effects region-industry size region-industry establishments (1) (2) (3) (4) (5) (6) A. Dependent variable: region-industry employment growth in formal manufacturing, 1989–2005 Entrepreneurship level 0.215 0.113 0.138 0.164 0.148 0.090 in region-industry in (0.050)*** (0.054)** (0.056)** (0.054)*** (0.060)** (0.044)** 1989 Employment level in -0.124 -0.226 -0.236 -0.228 -0.236 -0.265 region-industry in 1989 (0.034)*** (0.049)*** (0.049)*** (0.047)*** (0.049)*** (0.046)*** Entrepreneurship level 0.244 0.308 in region in 1989 (0.110)** (0.102)*** Employment level in 0.0831 0.196 region in 1989 (0.058) (0.068)*** Average establishment 0.071 age in region-industry (0.146) in 1989 Adjusted R-squared 0.133 0.300 0.328 0.344 0.327 0.325 Industry fixed effects Yes Yes Yes Yes Yes Region fixed effects Yes Yes Yes Yes Source: Ghani, Kerr, and O’Connell 2011a. Notes: Estimations quantify the relationship between region-industry employment growth in the formal manufacturing sector over 1989-2005 and initial entrepreneurship conditions. Entrepreneurship conditions are described through young establishments per worker. Estimations report robust standard errors, are unweighted except for column 4, and there are 575 observations. * = significant at 10% level; ** = significant at 5% level; *** = significant at 1% level. 4 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise move general differences across locations—for example, the low- fluid than in the United States. For the United States, existing er average entry in West Bengal. State fixed effects also remove city population levels, city-industry employment, and industry traits and policies that influence all industries equally: for exam- fixed effects can explain 80 percent of the spatial variation in ple, aggregate regional growth that increases demand for all man- entry rates. The comparable explanatory power for India is 29 ufacturing goods. The estimation now requires that higher em- percent for manufacturing and 33 percent for services. While ployment growth at the region-industry level be linked to higher this lower explanatory power could be due in part to dataset rates of young establishments after removing any systematic in- features and/or subtle, necessary shifts in the empirical estima- dustry and region effects. The importance of region-industry tions, it is clear that a large portion of this gap is due to India entrepreneurship is very robust for this specification choice. being at a much earlier stage of development, both generally This estimate of 0.138 (0.055) is the preferred specification. and for these particular sectors. In other words, estimates suggest that a 10 percent increase in The importance of entrepreneurship to growth and job cre- initial entrepreneurship in a region-industry in 1989 was associ- ation leads to a natural, policy-relevant question: which region- ated with a 1.3 percent higher rate of employment growth to al traits encourage local entrepreneurship? Is it differential re- 2005. This estimate derives from removing effects of initial em- turns to entrepreneurship? Or do entrepreneurs respond to ployment levels and systematic growth effects by regions and differences in the availability of infrastructure and education? industries. While India has historically been weaker in terms of This list is by no means exhaustive, but it parallels the well- growth-oriented entrepreneurship overall, industries and re- known list of explanations for the agglomeration of economic gions that have embraced entrepreneurship have grown faster. activity. Given the potential for the manufacturing sector to expand in Table 4 tests the entrepreneurial returns hypothesis. From India, this is very encouraging for future growth prospects. Indian manufacturing data, the dollar value of shipments per Columns 4–6 provide additional robustness checks on this worker in 2005 in each region-industry is calculated separately conditional specification. First, analysis testing for outliers by for single-unit and multi-unit establishments. This shipment weighting the regression by initial employment in the region- per employee metric is used as a proxy for future profitability industry finds very similar effects. Column 5 further controls and therefore the returns to entrepreneurship. This proxy is for average age of establishments in the region-industry to veri- subject to including industry fixed effects that control for in- fy that the observed young establishment relationship is not dustry-level production techniques. due to broader product cycles and industry evolution (Faber- This analysis did not find a strong relationship between the man 2007; Jovanovic and MacDonald 1994). This broader age heightened presence of young establishments in 1989 and the regressor does little to explain the relationship between job subsequent value per worker in the region-industry. This weak growth and young establishments. explanatory power is for both economic magnitude and statisti- cal significance. These patterns suggest that anticipation of ab- Economic Geography of Entrepreneurship normal returns is not the driving force behind the observed re- There is huge heterogeneity in entrepreneurship across states lationships in India. Demographics, too, have limited in India. The spatial distribution of start-ups in India is more explanatory power. The two most consistent factors that predict overall entre- preneurship are local education levels and the quality of local Table 4. Estimations of Localized Entrepreneurial Returns physical infrastructure (Ghani, Kerr, and O’Connell 2011b). These patterns are true for manufacturing and services. Among Average labor returns Average labor returns for single-units in 2005 for multi-units in 2005 general district traits, quality of physical infrastructure and workforce education are the strongest predictors of entry, with (1) (2) labor laws and household banking quality also playing impor- Entrepreneurship level in 0.024 -0.090 tant roles. There is evidence that strict labor regulations dis- region-industry in 1989 (0.105) (0.225) courage formal sector entry, and better household banking en- Employment level in -0.015 0.033 vironments encourage entry in the unorganized sector. Looking region-industry in 1989 (0.079) (0.039) at the district-industry level, there is extensive evidence of ag- glomeration economies among manufacturing industries. In Adjusted R-squared 0.273 0.145 particular, supportive incumbent industrial structures for in- Observations 607 346 put and output markets are strongly linked to higher establish- Industry fixed effects Yes Yes ment entry rates. Start-ups are more frequent for a city in in- dustries that share common labor needs or have Region fixed effects Yes Yes customer-supplier relationships with the city’s incumbent Source: Ghani, Kerr and O’Connell, 2011a. Note: * significant at 10% level; ** significant at 5% level; *** significant at 1% level. businesses. There is also substantial evidence for the Chinitz 5 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise effect where small local incumbent suppliers encourage entry. lished firms, and not new firms. Cost-benefit analysis is an ex- The importance of agglomeration economies for entry hold cellent tool for evaluating the potential merits of every single when considering changes in India’s incumbent industry struc- targeted intervention. Such analysis forces policy makers to pro- tures from 1989, determined before large-scale deregulation vide quantitative data to back up qualitative arguments and is began, to 2005. therefore an invaluable technique for increasing social welfare (Krueger 2011). Conclusion It is worrying that there are too few entrepreneurs in India Job growth is predicted by higher concentrations of new and and other countries in South Asia for their stage of develop- young establishments in India. The self-employment rate of en- ment. If South Asian countries continue to undertake some trepreneurship does not fully capture the scale of entrepre- basic policy steps to help entrepreneurs—develop infrastruc- neurship or its success. Alternative measures, such as number ture, improve education, lower entry costs, reduce regulatory of formal establishments per worker in an area, are better pre- burdens, further develop financial access—they have the poten- dictors of subsequent job growth. Cities and states that have tial to unleash business creation and job growth. embraced entrepreneurship have created more jobs and experi- It is well known that manufacturing is underdeveloped in enced higher regional growth. Policy message is clear: if job cre- India relative to its economic size, and while India has a dispro- ation is a priority, policy makers should focus on promoting portionately high rate of self-employment and many small entrepreneurship locally. manufacturing establishments, this has not translated as readi- The economic geography of entrepreneurship in India is ly into as many young, entrepreneurial firms as could be expect- still at an early stage. India has much greater variation in spa- ed. Yet there is no question that entrepreneurship works in In- tial outcomes than is present in the United States. The differ- dia! Formal economic job growth—which is what India and ences in the spatial location of entrepreneurship do not seem other countries in the region need to build a robust path to to be a result of differences in entrepreneurial returns. The prosperity—has been strongest in regions and industries that two most consistent factors that attract new entrepreneurs are have exhibited high rates of entrepreneurship and dynamic local education levels and the quality of local physical infra- economies. structure. There are many policy levers that can be used by the The entrepreneurial potential of India is very large (Khanna policy makers to promote entrepreneurial growth (Devan 2008). Most policy steps are not unique to India or South Asia, 2011). but are encouraged worldwide. India has experienced record The empirical link between education and entrepreneurship growth over the past decade. Imagine if India had more entre- has strong roots (Acs et al. 2008). Education improves skill and preneurs: given the link between entry, young establishments spreads ideas faster and wider (Atinc 2010). There are well-un- and job growth, how fast would its growth and job creation derstood limits to the pace with which countries can accumu- then be? late capital, but the limitations on the speed with which the gap Acknowledgments in knowledge can be closed are less clear (Stiglitz 2011). Because of the strong link between education and entrepreneurship, The views expressed here are those of the authors, and not nec- policy makers should remove any constraints that restrict the essarily those of the World Bank or any other institutions they growth of local colleges and educational institutions. Along may be associated with. The authors are grateful to the South with education, physical infrastructure is also essential to sup- Asia Labor Flagship Report Team for providing industry survey porting a modern economy. Goods and services cannot be pro- and census data, and to many colleagues for their comments. duced and delivered without roads, electricity, and telecommu- About the Authors nication. And moving people is as important, if not more important, as moving goods. Ejaz Ghani is an Economic Advisor at the World Bank in South There is no magic formula, or one size fits all, for making cit- Asia PREM, William R. Kerr is an Associate Professor at Harvard ies more enterprising. More competitive cities—that are livable, Business School, and Stephen D. O’Connell is a PhD student in eco- have good infrastructure, invest widely in knowledge generation nomics at CUNY Graduate Center. This note is a summary of and capacity building, are well governed, support sound nation- the chapter “Promoting Entrepreneurship, Growth, and Job al urban policy frameworks, and work through strengthened Creation� by the authors (Ghani, Kerr, and O’Connell 2011a) public and private partnerships at local, national, and interna- in Reshaping Tomorrow: Is South Asia Ready for the Big Leap? tional levels—also attract more entrepreneurs (Pradhan 2011). (Ghani 2011, http://www.oup.com/us/catalog/general/sub- Some targeted interventions work; others fail. Most end up ject/Economics/Developmental/Regional/?view=usa& favoring a few rich and politically well-connected larger, estab- ci=9780198075028). 6 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise References ———. 2010a. “The Secret to Job Growth: Think Small.� Harvard Busi- ness Review 88 (July): 26. 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The Economic Premise note series is intended to summarize good practices and key policy findings on topics related to economic policy. They are produced by the Poverty Reduc- tion and Economic Management (PREM) Network Vice-Presidency of the World Bank. The views expressed here are those of the authors and do not necessarily reflect those of the World Bank. The notes are available at: www.worldbank.org/economicpremise. 7 POVERTY REDUCTION AND ECONOMIC MANAGEMENT (PREM) NETWORK www.worldbank.org/economicpremise