rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 9874

# **Abstract**

COVID-19 was a major shock to youth entrepreneurs and their businesses in Kenya. This paper studies the causal impact of grants—worth two months of baseline business revenue—and business development services as potential mitigation measures. Using multiple rounds of phone surveys up to seven months from the start of the pandemic, the analysis finds that youth who are assigned business grants or a combination of grants and business development services are significantly more likely to maintain a business, earn more revenue and profits, retain employees, and report higher confidence and satisfaction with life. There are no corresponding effects of business development services alone, although the follow-up period is extremely short for training effects to materialize. These results suggest that cash infusion for young entrepreneurs in times of an aggregate shock can be instrumental in moderating its immediate harmful impacts.

This paper is a product of the Development Research Group, Development Economics and the Social Protection and Jobs Global Practice. 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 bzia@worldbank.org and asafir@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
London (for example) are generalizable to the country, the province, or even the city, is unknown.

In this paper we review results from lab studies on culture and corruption, attempt to reconcile the findings, and suggest avenues of future research. The rest of this paper proceeds as follows. In the next section we briefly review theory and empirical evidence on corruption. Section III reviews theory and empirical evidence on culture. Section IV focuses on the intersection of corruption and culture, and provides an overview of the non-experimental studies, and an in-depth analysis of lab experiments on corruption and culture. Section V provides some concluding remarks and areas for future research.

# **Corruption: Theory and Empirics**

The general definition of corruption is given as “the use of public office for private gain” (Jain 2001).<sup>5</sup> Under this very general definition, corruption comprises a number of actions,<sup>6</sup> at various levels of government.<sup>7</sup> This naturally leads to measurement difficulties, since, (1) there is little precision in the term, and (2) all actions covered by the definitions are clandestine. The most comprehensive measure for corruption perceptions comes from Transparency International, known as the Corruption Perceptions Index (CPI).<sup>8</sup> The issue with using CPI data is that it is not a perfect instrument for actual levels of corruption, since it assesses perceptions rather than behavior. Since the data is subjective in nature, it is prone to bias, making inference difficult. Olken (2009) demonstrates this by comparing perceptions-based measures of corruption (through villager survey responses on a road-building project) to an objective corruption measure (missing expenditures on the same project). He finds that corruption perceptions and the objective measures are only weakly correlated, with documented biases related to ethnicity and social

> 5 For the interested reader, a richer discussion of definitions of can be
# **Appendix C: Additional Formulas and Proofs**

We briefly review below some relevant technical details and the intuition of our proposed imputation method from Dang _et al._ (2017), Dang _et al._ (2019), and Dang and Lanjouw (2023). Further details and formal proofs are provided in these studies.

Given our consumption model for the base survey (survey 1) and the target survey (survey 2), we can write out Equation (1) in full as follows 1 1 1 1 (C.1) 2 2 2 2 (C.2) cc1 yy = ββ ′xx + υυ + εε cc2 By Assumption 1, since both yy = ββ _x1_ and ′xx + υυ _x2_ are representative of the population at the two survey + εε periods (or at the same time), we can replace _x1_ with _x2_ in Equation (C.1) to obtain the imputed household consumption in survey 2 as 1 2 1 2 1 (C.3) cc1 Further given Assumption 2 that changes in the distributions of the explanatory variables yy = ββ ′xx + υυ + εε between the two periods can capture the change in the poverty rate in the next period, we can jj obtain poverty estimates in the absence of actual consumption data in the target survey xx 1 2 1 2 2) (C.4) where (.) is the given poverty function and is the poverty line in survey _j_ , _j_ = 1 and 2. PP(yy ≤zz ) = PP(yy ≤zz jj Since the poverty function PP (.) is defined as the averaged poverty rate for the population, it is zz an expectation function. Using the iterated expectation rule, combining Equations (C.3) and (C.4) and plugging in the estimated parameters for PP 1 and the estimated distributions of the error terms for and 1, we have 1 2 1 ββ 1 2 2) (C.5)
swedish manufacturing. _The Scandinavian Journal of Economics_ , 91(3): 613–619, September 1989.

- Kenneth J. Arrow. The economic implications of learning by doing. _The Review of Economic Studies_ , 29(3):155–173, June 1962.

- John Baffoe-Bonnie. Interindustry part-time and full-time wage differentials: regional and national analysis. _Applied Economics_ , 36(2):107–118, 2004.

- Susanto Basu. Procyclical productivity: Increasing returns or cyclical utilization? _The Quarterly Journal of Economics_ , 11(3):719–51, August 1996.

- David N. F. Bell and Robert A. Hart. Wages, hours, and overtime premia: Evidence from the british labor market. _Industrial and Labor Relations Review_ , 56(3):470–480, April 2003.

- Renaud Bourles and Gilbert Cette. A comparison of structural productivity levels in the major industrialised countries. _OECD Economic Studies_ , 2005 (2):75–108, 2006.

- Renaud Bourles and Gilbert Cette. Trends in structural productivity levels in the major industrialized countries. _Economics Letters_ , 95(1):151–156, 2007.

- G. E. Brogmus. Day of the week lost time occupational injury trends in the us by gender and industry and their implications for work scheduling. _Ergonomics_ , 50(3):446–474, 2007.

- Gilbert Cette, Samuel Chang, and Maty Konte. The decreasing returns on working time: an empirical analysis on panel country data. _Applied Economics Letters_ , 18(17):1677–1682, 2011.

- Roger Craine. On the service flow from labour. _The Review of Economic Studies_ , 40(1):39–46, 1973.

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sectors, a lot remains to be done especially in terms of funding mobilization. For instance, in 2013, only 0.6% of public expenditures was allocated for preschool education (Minist`eres en charge de l’ ́education et de la Formation, 2017).

# **2.2 Youth Employment Context**

In 2018, an estimated 37% of young women and 22% of young men aged 16 to 35 in Burkina Faso were not in school or employed outside the home (authors’ calculations using the Harmonized Survey on Households Living Standard 2018/19 data). Additionally, 33% of young women and 38% of young men who were working were still living in poverty as defined by earning less than USD 1.90 a day (International Labour Organization, 2020). Against this backdrop, the Government of Burkina Faso through its Youth Employment and Skills Project (PEJDC) recruited 10,255 young women (85%) and men (15%) in 49 communes to implement labor-intensive public works (“PTRHIMO”, in French) in all regions of the country from mid-July 2019. The eligibility conditions were: i) being a Burkina Faso citizen; ii) out of school or never enrolled in school; iii) not a former beneficiary of the project; and iv) aged 16 to 35. PTR-HIMO participants were selected through a call for applications for the public work scheme in each commune by the government. The public work included the construction of bridges and rural roads, the maintenance of urban roads and administrative spaces, and reforestation. The number of desired workers in each site varied depending on the size of the site and the type of work, with a minimum requirement of 30% women at each site. Sites were defined as a _commune_ (municipality) for smaller urban centers or an _arrondissement_ (neighborhood) in the two largest cities, Ouagadougou and Bobo-Dioulasso. Two rounds of selection procedures were followed: i) registration of interested applicants; and ii)
# **VII FIGURES**

## Figure 1. Event Study – Night Light Density

<!-- Start of picture text --> Night Light Density [0 to 63]<br>.1<br>.075<br>.05<br>.025<br> (95% CI)<br>β<br>0<br>-.025<br>-.05<br>1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021<br><!-- End of picture text --> Year _Notes:_ The figure shows the results of an event study estimation for night light density, using data from grids near the refugee camps. The instrument, _SIDCampsij_ , is interacted with years from 1992 to 2021, excluding 2016, the year before the large influx of Rohingya refugees in 2017. The estimates include grid and year fixed effects, with standard errors clustered at the grid level. Bars represent 95% confidence intervals.
aggregate sales in 2019.<sup>78</sup> Appendix Table 29 presents the results of this aggregation. We first consider the set of credit program users (Panel A).<sup>79</sup> The change in indebtedness for these firms takes into account both program and non-program debt.

Consistent with the results in the paper, riskier firms experience larger within-group changes in indebtedness: the leverage of high-risk firms increases by 11.58 percentage points, while the leverage of low-risk firms increases by 8.84 percentage points (Column 1). Nevertheless, riskier firms represent a smaller share of aggregate activity: high-risk firms represent only 6.1% of countrywide sales compared to the low-risk firms that represent 35.6% of aggregate sales (Column 2). As a result, the contribution of high-risk firms as a group to overall indebtedness is smaller (0.71 percentage points) than the contribution of low-risk firms (3.15 percentage points) (Column 3). The small weight of riskier firms in the aggregate, therefore, mitigates the micro selection by riskier firms documented in the paper.

Summing across all risk groups shows that the indebtedness of firms that use the credit program increases by 9.71 percentage points. Those firms experience an increase of 3.6% of GDP in guaranteed credit (Table 7) and a decline in non-guaranteed credit. Extending the analysis to include all active firms (users and non-users) by risk confirms that the higher the risk, the larger the within-change in debt (Appendix Table 29, Panel B). But the higher the risk, the smaller their weight in the economy, attenuating the increase in aggregate risk.<sup>80</sup>

# **Appendix D: Model Details**

This appendix gives further details of the model in Section 7, including equations, calibration, and analysis/intuition. In addition to producing the quantitative results, the model motivates and justifies the empirical predictors of risk in
had larger earlier settlements of migrants also had different prevalent characteristics relative to the other municipalities before the conflict intensified, and these differences may be inducing divergent time patterns which are not explained by IDP inflows. It is possible, for instance, that municipalities with larger pre-

> 14Data on homicide rates come from the Observatory of Human Rights from the Colombian Vice Presidency. Data on the Colombian civil conflict was obtained from the _Centro de Memoria Hist ́orica_ (CMH). As of today, this is the best source of data on civil conflict as it combines information from NGOs and governmental records with testimonies from the victims of the civil conflict. We used data from CMH to construct two measures for the intensity of the Colombian civil conflict: total number of clashes between armed groups and total number of armed actions or attacks which took place between armed groups (i.e., illegal armed groups or the Colombian military).

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4. Measuring divergence and convergence – three confusions in the data While the pattern of divergence among the countries of the bottom billion is source for serious policy concern, the average global picture paints a more sanguine picture, suggesting a degree of convergence overall, and some studies demonstrate _unconditional convergence_ is now present.

The last decade has seen pendulum swing away from the previous consensus around diverging economic destinies (Pritchett 1997), to the more recent findings that global incomes and GDP levels are converging overall (Kremer et al 2021, Lakner and Milanovic, 2015, and Patel et al 2021).<sup>9</sup> Kremer et al (2021) revisit empirical tests of the 1990s that show no evidence of unconditional convergence since the 1960s and extend the analysis for the subsequent 25 years. They find that there is now evidence in support unconditional convergence at the global level since 1990 and convergence since 2000 due to a faster catch-up growth between the poor and higher income countries. Patel et al (2021) also argue in favor of convergence, showing that middleincome countries have experienced accelerated growth rates that have facilitated catching up with richer ones. They call into question the previous claim of unconditional _divergence_ , and the so-called “middle-income trap”. Indeed, rather than being driven by a moderation of growth in richer countries, this is instead supported by accelerating growth in developing countries, especially those found among emerging markets and middle-income countries.

Should we breathe a sigh of relief? Not quite yet. Although each new study typically benefits from additional years of data, consensus is yet to be reached. In a recent survey of crosscountry evidence, Johnson and Papageorgiou (2020) argue that as a group, developing countries have not closed the per capita income gap on the rich world of advanced economies, even in more recent years.

Recent arguments favoring global income convergence tend to emphasize – and their statistical findings are often driven by - the evidence in the years since 2000 that growth has been accelerating among an important subset of
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- R. Summers and A. Heston (1984), "Improved International Comparisons of Real Product and Its Composition, 1950-80", Review of Income and Wealth, June.

- F.W. Taussig (1924), "Labor Costs in the United States Compared with Costs Elsewhere", Quarterly Journal of Economics, November.

- W. Tyler (198C). "Effective Incentives for Domestic Market Sales and Exports", Journal of Development Economics, vol. 18.

-

- W. Tyler, S. Goldberg, and B. Blazic-Metzner (1984), "Brazil On Improving the National Income Accounting Syscem", World Bank, Washington D.C., October, processed.

- United Nations (1981), Recommendations for the 1983 World Programme of Industrial Statistics, Part I, General Statistical Objectives, Statistical Papers, Series M, No. 71 (Part I), New York.

- United Nations (1986/7). Wo. .,omparisons o ' Purchasing Power and Real Product for 1980. Phase I; of the International Comparison Project, Part One, 1986, Part Two, 1987. New York.

- U.S. Bureau of Labor Statistics (1982), Handbook of Methods, Bulletin 21341. washington DC.

- U.S. Dept. of Commerce (1979), Annual Survey of Manufactures 1975-1976, Bureau of the Census, Washington DC, May.

- U.S. Dept. of Commerce (1981a), 1977 Census of Manufactures, General Smmary, Bureau of the Census, Washington DC, April.

- U.S. Dept. of Commerce (1981b), 1977 Census of Manufactures, Final Report Volumes, Volume 2, Industry Statistics, Part I, Major Groups 20-26, Part II, Major Groups 27-34, Part III, Major Groups 35-59, Bureau of the Census, Washington DC, August.

- U.S. Dept. of Commerce (1981c), The NationRl Income and Product
come from UN Comtrade (accessed via WITS), capital stock, total factor productivity and consumption from the Penn World Tables, and arable land from the World Development Indicators (WDI). See the Data Appendix for details.

Table 1 reports the summary statistics for endowments of capital, skilled and unskilled labor, arable land (unadjusted for productivity differences) and total factor productivity in our sample over time (Panel A). Panel B and C report the same statistics for two subgroups: countries with high skilled-unskilled ratio and those with low ratio in 2000. We split the sample into two subgroups by skilled-unskilled labor ratio using the median for this ratio in 2000.<sup>1</sup> The number of countries for which data are available has gradually increased from 45 in 1975 to 107 by 2000, and arguably data for more unskilled labor abundant countries became available in later years. Yet the summary statistics shows that the average number of skilled labor stock exploded over this period. Keeping in mind changing set of countries over the years, the skilled labor endowment for an average country has increased from 7.3 to 25 million, while the unskilled labor endowment of an average country hovered around 30 million. Similar pattern albeit less striking is observed for capital endowment which for an average country stood at 0.9 and 2.2 million US dollars in 1975 and 2010, respectively. Comparing Panel B and C, we see that even through relatively high skilled labor abundant countries tend to have on average larger endowment of skilled labor and smaller endowment of unskilled labor (by construction), much of the changes in skilled labor endowment over time was driven by the group of relatively low skilled labor abundant countries. Skilled labor endowment for an average country in the later group increased from 2.1 million in 1975 to 14 million in 2010, compared to same statistic for the group of relatively high skilled labor abundant countries which only changed from 10 million to 24 million.

Table 2 summarizes sectoral net exports in million US
production activities to changes in factor wages. On the supply side of the labor market, unemployment is endogenous – the model includes a wage curve (a supply curve) that is upward-sloping until full employment is reached, at which point it becomes vertical (see Figure 2.2; its wage curve assumes a minimum unemployment rate of 5%). Unemployment is defined more broadly than in official statistics to include un- and under-employment. In the simulations, a broad definition of unemployment increases the scope for the existing labor force to generate a larger (smaller) amount of effective labor if the incentives to work were to improve (deteriorate) without any change in the labor-force participation rate; in most developing country contexts, this seems realistic. For non-labor factors, the supply curves are typically vertical.

The above discussion did not refer to the evolution of the economy over time. In MAMS, the economy grows over time due to accumulation of capital (determined by investment and depreciation), labor (determined by demography and the educational system), and other factors (following exogenous growth trends), as well as because of improvements in total factor productivity (TFP). Apart from an exogenous component, TFP depends on the levels of government capital stocks.<sup>8</sup> In the context of factor markets, these developments lead to rightward shifts in both demand and supply curves.

# _MDG and education module_

MAMS includes a set of HD (MDG and education) indicators. A built-in poverty module computes the three standard Foster-Green-Thorbecke poverty indicators (headcount poverty, poverty gap, and severity of poverty) on the basis of the assumption that, in both rural and urban areas, per-capita (goods and service) consumption follows a lognormal distribution parameterized on the basis of a Gini coefficient and an initial headcount poverty rate.<sup>9</sup> The prevalence of undernourishment (the share of the population that does not satisfy its dietary energy requirements, i.e. suffer from calorie poverty
real and financial conditions. Specifically, regressions of flows on two global factors – one estimated from 6 non-central advanced countries, and another one estimated from 15 emerging market economies (those with weight in the MSCI index above 1%) – yield an average (across countries and flow types) adjusted _R_<sup>2</sup> of 0.05 (figure A7 of Cerutti et al. (2017c). If the factors are augmented with selected global variables, the adjusted _R_<sup>2</sup> still averages only 0.12.<sup>25</sup> In Appendix C we show that a large part of the discrepancy with our re-

> 25In turn, Cerutti et al. (2017a) likewise find that an emerging-market inflow group factor, specific to the inflow type, accounts on average for just 12 percent of the variance of portfolio equity and bonds as well as bank inflows to 33 emerging markets, using quarterly data over 2001-2015.

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to the Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais (RAIS) data, the Ministry of Economics of Brazil for access to SECEX data, the National Institute of Statistics of Ecuador (INEC) for access to the Ecuadorian social security records (IESS), and Esteban Ferro for access to Ecuador’s business registry data. The authors are particularly grateful to Herlon Brandao, Roberto Castillo, Rosangela Farias,Natalia Garzon, Karla Marra, Jociany Monteiro, Paulo Oliveira, and Diana Zambonino for their warm hospitality and unconditional help with these administrative data. Financial support from the Office of the Chief Economist for Latin American and the Caribbean (LCRCE) at the World Bank is gratefully acknowledged. This paper was also partly supported by the Umbrella Facility for Trade trust fund and the Strategic Research Partnership on Economic Development. 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 of Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the countries they represent. All errors are our responsibility.