rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 10233

# **Abstract**

This paper characterizes the firm size distribution by exploiting establishment-level censuses covering both formal and informal firms in Sub-Saharan Africa. The paper finds a “missing middle” in the employment-based size distribution of firms in four Sub-Saharan African countries. This “missing middle” hinges on the inclusion of informal firms, and it is not explained by state- or foreign-owned firms at the top of the size distribution, nor does it emerge from the size distribution of entrants. The paper reconciles these empirical results with a model of firm dynamics with endogenous informality and shows that calibrated values of entry barriers and productivity-dependent idiosyncratic distortions generate a “missing middle” that is consistent with its underlying drivers in the data.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice, the Development Research Group, and the Global Indicators Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at kabreha1@worldbank.org, xcirera@worldbank.org, edavies@worldbank.org, rfattaljaef@worldbank.org, and hmaemir@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
through interbank lending and other risk-sharing arrangements. Fears about the insolvency of one bank can spread into a generalized contagion causing multiple banks to fail.

As banks remain the dominant source of financing for firms and households, a stable, well-functioning banking system is an important determinant of a country’s economic growth and development. A large number of bank failures can cause serious disruptions of a country’s economic activities and result in significant social and fiscal costs (Hoggarth et al. 2002; Smith 2016). Disruption in lending caused by multiple bank failures can result in lost output, lost investments and higher unemployment. In addition, there are long-term societal costs that result from lower economic activity and higher unemployment. More direct fiscal costs of banking crisis include tax-payer funded bailouts, liquidity support to various financial institutions and increased government spending on social safety net programs. More importantly, bank runs and panics can paralyze the payment system by causing failed banks to default on payments in transit. As most of the global economy relies on settlement systems without cash, lack of ability to service and honor demand deposit contracts can have a significant impact on daily commerce. Given the significant costs associated with banking crisis, deposit insurance, to the extent that it prevents contagious runs, can be highly valuable.

A number of papers document the economic benefits of deposit insurance in reducing bank runs. Martin, Puri and Ufier (2017), using account level data, examine the effect that deposit insurance has on inflows and outflows of distressed banks. They find that uninsured depositors flee banks following bad regulatory news and that deposit guarantees reduce the outflow of deposits, providing much needed liquidity. Iyer, Jensen, Johannesen and Sheridan (2017) study a run on uninsured deposits in Danish banks that resulted from a reform that limited insurance coverage. They show that the reform caused a 50% decrease in deposits above the insurance limit. DeLong and Saunders (2011) find that depositors were less prone to withdraw their deposits from weaker banks after the introduction of fixed-rate
who fail to optimally use the resources available in their country. Crucially, the products whose factor intensity puts them at comparative disadvantage exit the US market even faster if the exporting country has a high share of bank credits to the GDP. Our evidence therefore suggests that a strong banking sector can prevent a sub-optimal use of resources by enforcing an e¢ cient export composition before a competitive foreign market does so. A well-developed domestic ...nancial system helps to push the country’s exports towards products congruent with its comparative advantage.

The paper makes three main contributions. First, it introduces a new channel through which ...nance improves resource allocation in the real economy, extending the existing work of developmental and ...nancial scholars. Exports violating the notion of comparative advantage represent an important and rather underresearched facet of resource misallocation. Moreover, the existing work on misallocation su¤ers from the lack of internationally comparable production data at the level of highly disaggregated goods. In contrast, the richness of available trade data permits a detailed and thorough empirical analysis of resource misallocation in a broad sample of countries. As for the ...nance literature, it has traditionally focused on capital misallocation and its consequences for economic growth (Lang et al. 1996, Wurgler 2000). The Heckscher-Ohlin theory compares the overall factor intensity of a product with factor endowment of the exporting country. This framework therefore allows us to examine the role of ...nance in the wider context of resource allocation.<sup>3</sup> Second, the paper contributes to the literature on the e¤ects of ...nancial factors on trade (Beck 2002, 2003; Ju and Wei 2005, Greenaway et al. 2007, Muûls 2008, Manova 2008, Manova et al. 2009). This recently growing line of research shows that ...nancial development improves the export performance of a given country. Finance especially bolsters exports of ...rms that come from ...nancially vulnerable
2005)|
|MYS|Malaysia||AD-MYS-Master ,|||
|NIC|Nicaragua||AD-NIC-Master ,|||
|PAK|Pakistan||AD-PAK-Master ,|||
|PAN|Panama||AD-PAN-Master ,|||
|PRY|Paraguay||AD-PRY-Master ,|||
|PHL|Philippines||AD-PHL-Master ,|||
|POL|Poland||AD-POL-Master ,|||
|SVN|Slovenia||AD-SVN-Master ,|||
|TWN|Taiwan||AD-TWN-Master ,|||
|THA|Thailand||AD-THA-Master ,|||
|TTO|Trinidad and Tobago||AD-TTO-Master ,|||
|URY|Uruguay||AD-URY-Master|||

The WTO data was originally collected and described in Miranda, Torres and Ruiz (1998) and has since been updated as part of the WTO’s Rules Division Antidumping database.<sup>14</sup> We report only the information available in the WTO dataset on investigations for other WTO members, as detailed in the table below, with one “Master” sheet per using country:

> 14 The data for the WTO Rules Division Antidumping database is taken from the Semi-annual reports Members are obliged to submit to the WTO Committee on Anti-Dumping Practices. Thanks to Raul Torres and Johann Human for making this database available.

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Finally, it is interesting to observe the changes of the physical capital coefficients by level of education. In the IV specification for primary and secondary schooling, capital only enters as weakly significant. By contrast, the coefficient for physical capital becomes very significant and alters its long-run elasticity if tertiary education is entered into the estimate.

To the extent that this effect does not merely reflect statistical arbitrariness, a possible interpretation would be that the productivity of physical capital is affected by tertiary schooling. These findings support the conjecture of Romer (1990b) that the level of scientific education should be correlated with the rate of growth and the share of output devoted to investment in physical capital. It should be kept in mind, however, that the reliability of tertiary education data is comparatively poor in Guatemala. Moreover, according to Anderson (2001), low quality and internal inefficiency plague university education. Hence, some care should be taken before drawing too strong conclusions from the observed changes.

# **5.4 Mincerian Human Capital Specification**

An important question is how the effect of schooling at the macro level compares with the microeconomic evidence. The macro returns could be higher because of externalities from education. For example, if post-primary schooling leads to technological progress that is not captured in the private returns to education, or if education produces externalities in the form of the reduction of crime, more informed political decisions, better health and so on. To reconcile the macro effect of schooling with the micro level, Cohen and Soto (2001) estimate the following production function: where _Y_ is output, _A_ total factor productivity, _K_ physical capital, and _HM_ human capital. As first suggested by Bils and Klenow (2000), the micro evidence derived from a log-linear Mincer (1974) formulation can be used to specify the aggregate human capital stock as follows: where _hmt_ is the human capital per worker, _ht_ is average years of schooling and _ψ_ corresponds to the returns to education. This Mincerian approach has become popular in the
The interpretation of responses to managers as to the importance of tax rates for the operation of their business faces similar difficulties as the interpretation of the importance of access to finance, and partly for similar reasons. Just as managers do not take account of the social benefits of a financial system that constrains access to finance by aiming to screen out poor projects, they also do not take account of the social benefits arising from government spending funded by the taxes they pay.

We suggest that the way to interpret the responses of managers on tax rates is that they point to the costs imposed on firms if public inputs are supplied at the cost of higher taxes than necessary. Tax rates are very highly ranked as a constraint by managers in virtually all countries (irrespective of their level of development) but it does not follow that it is a priority everywhere to cut taxation. A high ranking is probably better interpreted as indicating that policies to reduce tax rates while holding other aspects of public infrastructure provision constant (for instance, by improving administrative efficiency) would improve firm performance.

For the public input constraints, we use the survey answers to get at the private cost to the firm of inadequate or unreliable public inputs or burdensome regulation. It is not possible to use micro data of this kind to uncover whether tax rates are a key constraint to firms – firms are unlikely to take into account the public inputs that are paid for by taxation when responding to the question.

# **4.  Are job-creating firms in the South Asia Region also high-performance firms?**

The analysis in this paper relates to formal-sector firms in 8 South Asia Region (SAR) countries: Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan and Sri Lanka. The data were collected in a series of surveys over the 10-year period 2000-2010. Tables 1 and 2 present the number of firms and the median permanent employment by country and year. Firms in the three most-populous countries – India, Bangladesh and Pakistan – account for 80%
4 study for examining these issues because the country produces a large number of international migrants to Malaysia, Saudi Arabia and other countries.<sup>1</sup> Also, the presence of panel household data from Indonesia makes it possible to overcome several of the methodological problems – simultaneity, reverse causality, and omitted variable bias – that bedevil any economic work on international remittances.

At the outset it should be emphasized that even with the presence of panel data this analysis of the impact of remittances on poverty and household expenditures is not without certain methodological problems. One obvious issue is that of selection, that is, households receiving remittances might have unmeasured characteristics (e.g. more skilled, able or motivated members) which are different from households not receiving remittances. If these unmeasured characteristics are constant through time, the use of panel data methodologies can eliminate the bias that they produce in estimating the impact of remittances. But if the unmeasured characteristics change over time, then it is still important to address the problem of selection in unobservable characteristics. We meet this concern by using a three-stage nested logit model to test for selection bias in the household receipt of remittances. The identification of this model is based on the use of instrumental variables. Since past research has found that historical distance to railroad lines and changes in rainfall patterns are important in the receipt of international remittances (e.g. Adams and Cuecuecha, forthcoming; Woodruff and Zenteno, 2007; Munshi, 2003), our identification strategy focuses on these variables.

This instrumental approach enables us to control for selection and to do two things. First, we use the third-stage of the nested logit model to predict two types of income for households receiving remittances: a) the income conditional on their household characteristics and their receipt of remittances (predicted income); and b) the income conditional on their household
firms only contribute to productivity growth if their productivity is higher than survivors when exit occurs (period 1). The fact that the DOPD specification uses different reference periods when estimating the impact of entry and exit is a clear advantage over other decomposition methods that use the same reference period (e.g., Griliches and Regev, 1995; Foster, Haltiwanger, and Krizan, 2001). These alternative methods are likely to result in measurement bias when measuring the contribution of one group or the other.

While the dynamic decomposition has clear advantages over the static decomposition, we use both methods to take advantage of the cross-sectional data that we have for the period since 2016. These data are included in our analysis to highlight current trends as well as the different sources of manufacturing growth over the past decade.

# **IV. Data**

The analysis of business dynamics requires data that both tracks individual establishments over time and is representative of different firm types (e.g., survivors, entrants, and exiting plants). Typically, these criteria are met only by manufacturing censuses and business registers as surveybased data are unlikely to be representative of entrants and exiters as well as firms at different stages of their life-cycle (e.g, young and mature plants). Table 1 lists the data sources that we use to conduct our analysis. In total, we have data on more than 67,000 establishments from 45 country-year samples. Its breakdown is as follows: data covering 21 years for Ethiopia (19962016), 12 years for Côte d’Ivoire (2003-2014), six years for Tanzania (2008-2013), and six years for Bangladesh (1995, 1997, 1999, 2001, 2005, and 2012).

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panel dataset the variable takes a value of 1 if internal armed conflict, zero otherwise. The exception is economies such as Iraq and Afghanistan that were in conflict for all years in the sample and thus attain values of zero. For the cross-section estimations the variable is the number proportion of years that an economy experienced internal conflict between 2005 and 2018.<sup>8</sup> We include data for legal origins that are used as instruments in our Instrumental Variables approach. Data on legal origins capture whether the historical origin of a country’s laws is German, French or from the United Kingdom. These data are obtained from La Porta et al., (2008), who provide an overview of studies using legal origins. In an additional specification, we also use the 1996 to 2003 sample average of the Government Effectiveness measure from the WGI. Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Tables 3 and 4 provide summary statistics for all the variables for the crosssection and panel data sets, respectively. Tables 5 and 6 present the correlation between these variables. Table A1 provides the definitions and sources of all the variables.

# **V. Results**

Table 1 presents the main results. Columns 1, 2 and 3 present the cross-sectional OLS estimation results corresponding to equation (4) with no controls, standard controls, and standard controls plus external debtfinancing shocks, respectively. The specification with the debt shocks is presented separately as it entails a drop in observations. The SCI variable is positive and statistically significant at the 1 percent level for all three specifications presented in the first three columns. Using the specification with the standard set of controls, the magnitude of the SCI coefficient indicates an elasticity of 0.4 percent. However, to be

> 8 All the results presented in this
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[10] exclude also IT. Models [11]-[12] exclude also EE (2004), LT (2009), and BG (2006), but include SK (2004).<sup>a</sup> Lagged 1 year.

_Sources:_ Dependent variables: Calculations with ESS data (see Table 1 for details). Explanatory variables - see Annex 1 (Table A1). Model estimates - own calculations.

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a third district, C, to the union of A and B, if the share of workers that live in C and commute daily to the spatial unit A + B exceeds T<sup>�</sup> , even though it may not have been possible to aggregate C to either A or B directly in round one. The algorithm then continues to run until no districts remain to be aggregated given the commuting flow threshold.<sup>8</sup> Based on his own application of the algorithm to Colombian municipalities, Duranton (2015b) notes that, given the gravitational nature of commuting, the algorithm’s preferred threshold for any application is likely to be decreasing in the sizes of the underlying subnational units being aggregated into metropolitan areas.

# **_Approach #2: The Agglomeration Index (AI)_**

The Agglomeration Index (AI) was originally developed by Uchida and Nelson (2009) for the World Bank’s 2009 World Development Report (WDR) on “Reshaping Economic Geography” and, since then, has been further applied in other World Bank reports, including in World Bank – IMF (2013) and Ellis and Roberts (2016). The AI was designed by Uchida and Nelson for global application. Given the absence of O-D commuting flow data for many countries – especially developing countries – it instead relies on estimated travel times to a set of pre-defined cores to

> 8 Prior to aggregating a given origin district to a given destination district, the algorithm checks that in cases where a district could be aggregated to several destinations, it is, in fact, uniquely added to the one to which it sends the greatest number of workers. When commuting flows between two districts are above the threshold in both directions, the algorithm also ensures that the smaller district is aggregated to the larger (see, Duranton, 2015b, p 184).

4
Policy Research Working Paper 10405

# **Abstract**

Modern inputs and mechanization are promoted across Africa to raise smallholder labor productivity and broker the structural transformation. Yet, adoption has remained low and the implications for returns to labor and labor allocation remain poorly understood. This paper explores the effects of different intensification packages on farm performance, market orientation, and food security using data from lowland rice farmers in Côte d’Ivoire. Employing a multinomial treatment effect model, the findings reveal that intensification increases land and labor productivity, especially when agro-chemicals and mechanized land preparation are combined. Returns to labor double to triple, inducing specialization and greater market orientation as well as greater food security, while productively releasing agricultural labor for other activities. Labor in agriculture becomes more waged. The gender balance remains the same. Child labor input does not decrease. The findings call for greater attention to labor productivity and confirm that agricultural intensification can pay and enhance rural transformation.

This paper is a product of the Social Protection and Jobs Global Practice and the Jobs Global Theme. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at lchristiaensen@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by