Presentation prepared by Leora Klapper, Senior Economist, World Bank Inessa Love, Senior Economist, World Bank We thank the Ewing Marion Kauffman Foundation, the Development Research Group at the World Bank, and the IFC for financial support. 1
1 Introduction & Methodology 2
1.1 Why a dataset on entrepreneurship? To meet the demand of governments and policymakers for: Diagnosis of private sector development and growth Monitoring and evaluation of policy reforms Data to motivate reforms to increase participation in the formal sector To evaluate the impact of macroeconomic and financial shocks on new firm registration 1. Introduction & Methodology 3
1.2 What is Measured? What is Entrepreneurship? The activities of an individual or a group aimed at carrying out commercial activities in the formal sector under a legal form of business Unit of Measurement Private companies with limited liability. Notably, this is the same definition used by the World Bank s Doing Business report. It is also the most prevalent business form in most economies around the world (Doing Business, 2010). Variable of interest Entry Density, calculated as the number of newly registered limitedliability firms in the corresponding year as a percentage of the country s working age population (ages 15-65), normalized by 1,000. 1. Introduction & Methodology 4
1.2 What is Measured? (cont.) The WBGES focuses on the formal sector and its advantages, such as police and judicial protection (and less vulnerability to corruption and the demand for bribes), access to formal credit institutions, the ability to use formal labor contracts, and greater access to foreign markets. Data on the informal sector has been excluded from this analysis because the only way to enumerate firms in the informal sector is through economic censuses, which due to their high costs are infrequently collected Formal Sector Self Employment Corporations Partnerships Sole Proprietorships Measured Businesses New Economic Units Informal Sector Micro Businesses The WBGES facilitates the analysis of the growth of the formal private sector, relative to the informal sector, and the identification of factors that encourage firms to begin operations in or transition to the formal sector. 1. Introduction & Methodology 5
1.3 Survey & Methodology Survey: Number of newly registered limited liability firms, by year Questions about registration process Translated into four languages (English, Spanish, French, Russian) Methodology & Data: Sent directly to data sources by email and fax Follow-up phone calls Data checking from outside sources, previous versions of WBGES Sent to over 150 countries and received 125 responses Comparable data for 112 countries 1. Introduction & Methodology 6
1.4 Data Sources Business Registries Reasons Documents entry into the formal sector Information source for other government agencies Challenges Different registration and annual filing requirements Available legal forms Identification of exited firms Re-registrations Paper-based registries Decentralized registry systems Data Sources 1.7% 28.7% 69.6% Registry/Ministry Statistical Office Consultants 1. Introduction & Methodology 7
Entry Density Entry Density 1.5 Final Data Final Data Excludes: Informal Sector Data not gathered, despite relevance Sole proprietorships, partnerships Data not gathered, not uniform across countries Measures of active & closed firms Data gathered but excluded because of reliability issues due to different definitions / procedures Countries classified as offshore financial centers by the IMF Data gathered but excluded because some firms not representative of entrepreneurship 12 10 8 6 4 2 0 0 20 40 60 80 Informal Economy (% GDP) 14 12 10 8 6 4 2 0 Non offshore Offshore 1. Introduction & Methodology 8
2 Summary Statistics 9
2.1 Summary Statistics, by country, 2004-2009 averages 2. Summary Statistics 10
2.2 Summary Statistics, by region, 2004-2009 averages 4.5 4.21 4.0 3.5 3.0 2.5 2.26 2.0 1.5 1.31 1.0 0.5 0.77 0.63 0.79 0.58 0.0 High Income East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa WBGES data shows that there is wide variation in new entry across regions and income groups. In other words, there are, on average, about 4 new firms registered every year per 1,000 people in industrialized countries, between 1 and 3 in LAC and ECA, and less than 1 new firm registered in many other regions. 2. Summary Statistics 11
2.3 Summary Statistics, 2004-2009 averages Entry Density, GDP per capita, and Financial Development Entry density 5 Entry density 5 4 4 3 3 2 2 1 1 0 Lowest Highest 0 Lowest Highest Economies ranked by GDP per capita (2000 US$), quintiles Economies ranked by financial development (measured by domestic credit as % of GDP), quintiles These figures show the strong and significant relationship between new business entry density and financial development 2. Summary Statistics 12
3 Registration, Reforms, and the Business Environment 13
3.1: Ease of Doing Business Entry Density 2010 WGBES data shows that various components of a country s business environment are significant indicators of new firm registrations, even after controlling for the overall level of economic development. As a summary measure of the various business environment indicators in a country, Doing Business data contain a country s overall rank. There is a strong positive correlation between a country s overall rank in Doing Business and entry density. 10 9 8 7 6 5 4 3 2 1 0 0 50 100 150 200 Ease of Doing Business Rank 3. Registration, Reforms & the Business Environment 14
Entry Density Entry Density 3.2 Ease of Starting a Business Subindices Entry Density 10 Panel A: Number of Procedures Panel B: Time (in days) 10 8 8 6 4 2 6 4 2 0 0 5 10 15 20 Procedures to start a business 0 0 20 40 60 80 100 Days to start a business Panel C: Cost of starting a business 10 8 6 4 2 0 0 20 40 60 80 100 Cost to start a business (% GNI) Three Doing Business indicators on starting a business show the impact of the business environment and barriers to entry on new firm registration. There is a strong negative correlation between these measures and entry density. A formal econometric analysis extends these simple correlations. The results show that the initial business environment is important for subsequent new business registrations, which suggests a causal relationship. In addition, to ensure that the results are driven by the business environment rather than the overall level of development in a country, the analysis controls for GDP per capita. 3. Registration, Reforms & the Business Environment 15
Entry Density Entry Density 3.3 Corporate Tax Rate & Governance In order to consider the overall economic, political and financial conditions of the surveyed countries over time, entry density is compared to measures of country-level governance. For example, the figure on the right shows the strong and positive correlation between entry density and the governance composite index. The governance composite is on a scale of -2.5 to 2.5, with higher values indicating less risk. Entry density is also compared to the corporate tax rate for 77 countries from KPMG (left), and a strong negative correlation between new firm registration and tax rate can be observed. The strong relationship between entry density and governance and entry density and corporate tax rate are upheld when controlling for the income-level of the country in a multivariate econometric analysis. 10 9 8 7 6 5 4 3 2 10 8 6 4 2 1 0 0 10 20 30 40 50 Corporate Tax Rate 0-2 -1 0 1 2 Kauffman/Kray Governance Index 3. Registration, Reforms & the Business Environment 16
3.4 How do Firms Register? Automating a business registry is a phased process going from a paper-based decentralized registry to an electronic registry, which facilitates remote access and registration. The percentage of countries entering the automation process (electronic data storage) is similar regardless of their stage of economic development. But differences arise as the process advances, resulting in a wide gap between industrialized and developing countries in the latter steps. Very few of the low-income countries surveyed have implemented remote registration and none have implemented internet registration, compared to over 60 percent of high-income countries. High income Upper middle income Lower middle income Low income 100% 80% 60% 40% 20% 0% Electronic data storage Data remote access Registration outside capital city Remote Registration Internet Registration 3. Registration, Reforms & the Business Environment 17
Entry Density, 2009 3.5 Internet Registration 4 40 3 30 2 20 Days to start a business 1 0 No internet registration Incomplete internet registration Complete internet registration 10 0 No internet registration Incomplete internet registration Complete internet registration Cost to start a business It is difficult to isolate the causality between the implementation of electronic registration, improvements in the business environment, and the registration of new businesses. But the data suggest that business registry modernization provides a more favorable business environment for starting a business and facilitates the business registration process. During 2009, average new entry density was highest in countries where the complete business registration process was available online. Countries with remote registration (internet, telephone, one-stop shops, etc) require 30 percent less time to start a business, and costs are reduced by 50 percent (Doing Business Report 2009). 3. Registration, Reforms & the Business Environment 18
3.6 Implementation of One-stop Shop 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 t-3 t-2 t-1 t t+1 t+2 t+3 Implementation of One-Stop Shop Azerbaijan Belarus Burkina Faso Croatia Rwanda Senegal This figure illustrates the evolution of entry density three years before and after implementation of a One-Stop Shop for six developing countries. The data suggest a strong relation between the implementation of electronic registration and the number of new business registered. A necessary caveat is that business registration modernization might be part of a broader package of regulatory reforms, and we do not control for business cycle effects. 3. Registration, Reforms & the Business Environment 19
4 Entrepreneurship and the Financial Crisis 20
Entry Density 4.1 Impact of the Crisis, by income group % Change in New Firms 35% 5 30% 25% 4 20% 3 15% 10% 2 1 5% 0% -5% -10% 2005 2006 2007 2008 2009 0 2004 2005 2006 2007 2008 2009-15% High income Upper middle income Lower middle income Low income Nearly all economies experienced a sharp drop in business entry during the crisis. Only 20 percent of the countries experienced growth in business entry between 2008 and 2009, while 74 percent did between 2006 and 2007. With the onset of the financial crisis, new business registration slowed down, first in advanced economies and then in the rest of the world, paralleling the spread of the crisis. 4. Entrepreneurship and the Financial Crisis 21
New Firms 4.2 Impact of the Crisis, selected countries 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 2005 2006 2007 2008 2009 The figure above displays time series data for 10 selected countries, organized by decreasing GDP per capita. The y-axis displays annual new firm registration in absolute figures to get a better sense of the scale of new firm registration. As evident in the previous figures, the crisis had a significant and negative impact on new firm registration in almost all countries. Richer countries, such as Ireland, Denmark, Latvia and Argentina, felt the crisis beginning in 2008 and experienced two years of large drops in new firm entry. Moving down the income scale, however, it becomes apparent that new firm registration in lower income countries was not impacted until 2009. New firm registration in some countries, such as Jordan and Uganda, was relatively unaffected by the crisis, possibly because of isolation from the global financial system or due to recent private sector reforms that mitigated the impact of the crisis. 4. Entrepreneurship and the Financial Crisis 22
Growth in new firms (%), 2007-09 4.3 Heterogeneous Impact of the Crisis 60 40 20 0-20 -40-60 0 50 100 150 200 Domestic credit (% GDP) Did the crisis affect business entry in some countries more than others? An econometric analysis confirms that countries with higher GDP per capita experienced sharper declines in new registrations during the crisis. Countries in which financial markets play a larger part in the domestic economy also experienced sharper contractions in new firm registration. One plausible channel for this is through firms access to external finance, which is more important in countries with higher levels of financial development. This channel suggests that countries where startups rely more on the banking sector were more likely to experience larger contractions in new firm registration as a result of the credit crunch and withdrawal of finance that characterized the crisis. The analysis also reveals that the ratio of domestic credit to GDP is a more powerful predictor of the impact of the crisis on new firm registration than GDP per capita a notable result, given the high correlation between the two measures of development. 4. Entrepreneurship and the Financial Crisis 23
Avg. Yearly % Change in New Firms 2007-2009 4.4 Firm Entry and Crisis Turbulence 40% 30% 20% Jordan 10% Brazil 0% -1.25-0.75-0.25 0.25 0.75 1.25 Lithuania Morocco -10% -20% Bulgaria -30% The degree to which the crisis affected new firm registration is highly correlated with measures of the severity of the crisis. Using an index from Calderon and Didier (2009) that measures the crisis-related turbulence in 65 countries (with lower numbers indicating greater effects from the crisis), the analysis shows that countries that were hit harder by the crisis also had larger shocks to new firm registration. For example, Brazil and Morocco, which were less affected by the crisis, experienced no decline in new firm registration. But Bulgaria and Lithuania, among those most affected because of the near collapse of their financial markets, saw a drastic drop in new firm registration. -40% Crisis Turbulence Index (Didier, 2009) 4. Entrepreneurship and the Financial Crisis 24
5 Conclusion 25
5.1 Conclusion The 2010 World Bank Group Entrepreneurship Snapshots facilitate a more comprehensive examination of the relationship between business registration, the business environment, and the recent financial crisis. The findings suggest: Dynamic business registration occurs in countries that provide entrepreneurs with reduced red tape and a stable investment climate. Nearly all countries experienced a sharp drop in business entry during the crisis, and that the degree to which the crisis impacted new firm registration is highly correlated with measures of crisis severity. The WBGES database will continue to be updated on a biennial basis for the foreseeable future. Forthcoming editions of the WBGES database will provide insight into how the fiscal and monetary policies implemented by governments in response to the crisis affected the revival of new firm registration. It will also be possible to examine the pre-crisis financial and institutional characteristics that encouraged a rapid and strong recovery in new business registration in the wake of the crisis. 5. Conclusion 26
Annex Regression Results 27
A.1 The impact of the Business Environment on New Firm Registration The dependent variable is the five year average of Entry Density, 2005 to 2009. All explanatory variables are as of 2004. *, **, and *** indicate significance at 10%, 5%, and 1%, respectively. Panel A: Business Environment Indicators Variables 1 2 3 4 5 6 Starting Cost (2004) -0.007** [0.020] Log Starting Days (2004) -0.490* [0.066] Log Starting Procedures (2004) -2.073*** [0.000] Employment Rigidity (2004) -0.006 [0.668] Financial Depth (2004) 0.006 [0.440] Corporate Tax Rate (2004) -0.085** [0.013] Log GDP per capita (2004) 0.713*** 0.767*** 0.558*** 0.854*** 0.729*** 1.002*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Constant -3.194*** -2.188 2.277-4.397*** -3.851*** -3.548* [0.010] [0.123] [0.136] [0.000] [0.000] [0.057] Observations 88 88 88 88 90 58 R-squared 0.379 0.388 0.486 0.364 0.35 0.416 Adjusted R-squared 0.364 0.373 0.474 0.349 0.335 0.395 Annex: Regression Results 28
A.2 The impact of the Business Environment on New Firm Registration The dependent variable is the five year average of Entry Density, 2005 to 2009. All explanatory variables are as of 2004. *, **, and *** indicate significance at 10%, 5%, and 1%, respectively. Panel B: Governance Indicators Variables 1 2 3 4 5 6 7 Governance Composite (2004) 1.038*** [0.007] Voice & Accountability (2004) 0.628** [0.023] Political Stability (2004) 0.429 [0.132] Government Effectiveness (2004) 0.939*** [0.005] Regulatory Quality (2004) 1.235*** [0.001] Rule of Law (2004) 0.633** [0.039] Control of Corruption (2004) 0.624* [0.068] Log GDP per capita (2004) 0.360** 0.558*** 0.698*** 0.356** 0.281* 0.543*** 0.532*** [0.037] [0.000] [0.000] [0.031] [0.078] [0.000] [0.002] Constant -0.789-2.339** -3.308*** -0.847-0.309-2.169** -2.100* [0.549] [0.038] [0.005] [0.486] [0.797] [0.045] [0.096] Observations 91 91 91 91 91 91 91 R-squared 0.409 0.393 0.378 0.408 0.442 0.388 0.389 Adjusted R-squared 0.396 0.379 0.364 0.395 0.429 0.374 0.375 Annex: Regression Results 29
A.3 The Impact of Business Environment Reform on New Firm Registration This table uses an unbalanced six-year panel dataset of 95 countries for 2004 to 2009. The dependent variable is annual entry density. All models include country and year fixed effects, and standard errors clustered at the country-level. *, **, and *** indicate significance at 10%, 5%, and 1%, respectively Variables 1 2 3 4 5 6 Lagged Starting Cost 0 [0.774] Lagged Log Starting Days -0.220* [0.065] Lagged Log Starting Procedures -0.577*** [0.008] Lagged Employment Rigidity -0.012** [0.042] Lagged Governance Composite -0.39 [0.443] Lagged Financial Depth -0.001 [0.842] Lagged Log GDP per capita 0.205 0.122 0.094 0.137 0.287 0.061 [0.751] [0.863] [0.881] [0.824] [0.628] [0.926] Constant 0.212 1.646 2.35 1.093-0.427 1.397 [0.967] [0.771] [0.638] [0.822] [0.927] [0.788] Observations 502 502 502 502 507 490 R-squared 0.956 0.957 0.957 0.956 0.956 0.955 Adjusted R-squared 0.945 0.946 0.946 0.945 0.945 0.944 Annex: Regression Results 30
A.4 The Impact of the Crisis on New Firm Creation This table uses an unbalanced six-year panel dataset of 95 countries for 2004 to 2009. The dependent variable is annual entry density, defined in Table 1. Trend is a linear trend variable equal to 1 in 2004, equal to 2 in 2005, etc., Crisis Dummy, 2009 is equal to 1 in 2009 and 0 otherwise; Crisis Dummy, 2008 is equal to 1 in 2008, and 0 otherwise. All models include country fixed effects and standard errors clustered at the country-level. *, **, and *** indicate significance at 10%, 5%, and 1%, respectively. 1 2 3 4 5 6 Variables Full sample High Income Low/Middle Income Crisis Dummy-2009-0.570*** -0.774*** -0.905*** -1.210*** -0.436*** -0.582*** [0.000] [0.000] [0.002] [0.007] [0.001] [0.004] Crisis Dummy-2008-0.254*** -0.398* -0.178* [0.009] [0.104] [0.069] Trend 0.147*** 0.199*** 0.242*** 0.317*** 0.107*** 0.144*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.001] Constant 1.636*** 1.531*** 3.178*** 3.027*** 1.016*** 0.939*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Observations 516 516 150 150 366 366 R-squared 0.955 0.956 0.935 0.937 0.942 0.943 Adjusted R-squared 0.945 0.946 0.92 0.922 0.929 0.929 Annex: Regression Results 31
A.5 Heterogeneous Response to the Crisis This table uses an unbalanced six-year panel dataset of 95 countries for 2004 to 2009. Variables are defined in Table 1. The dependent variable is annual entry density. Trend is a continuous variable equal to 1 in 2004, equal to 2 in 2005, etc., Crisis Dummy, 2009 is equal to 1 in 2009 and 0 otherwise. Financial Turbulence is an index that measures the degree to which a country has been affected by the crisis; a lower number indicates greater crisis intensity (Calderon and Didier, 2010). All models include country fixed effects and standard errors clustered at the country-level. *, **, and *** indicate significance at 10%, 5%, and 1%, respectively. Variables 1 2 3 4 5 Crisis Dummy, 2009 0.281-0.318** -0.506-0.229-0.816 [0.481] [0.022] [0.198] [0.260] [0.154] Crisis09 *Log GDP per capita (2004-2007) -0.110** 0.027 0.079 [0.048] [0.662] [0.283] Crisis09* PC/GDP per capita (2004-2007) -0.005** -0.006** -0.006** -0.007*** [0.011] [0.039] [0.014] [0.009] Crisis09 *Financial Turbulence (2009) 0.383** 0.375** [0.026] [0.034] Trend 0.150*** 0.150*** 0.151*** 0.176*** 0.176*** [0.000] [0.000] [0.000] [0.000] [0.000] Constant 1.653*** 1.648*** 1.666*** 2.138*** 2.138*** [0.000] [0.000] [0.000] [0.000] [0.000] Observations 510 510 504 332 332 R-squared 0.955 0.956 0.956 0.955 0.955 Adjusted R-squared 0.945 0.946 0.946 0.944 0.944 Annex: Regression Results 32