rafmacalaba/datause-encoder-data huggingface dataset:
the constraints to firm TFP posed by poor electricity supply in Bangladesh are extremely severe. Our findings parallel those obtained by Dollar et al. (2005) which study the importance of business environment factors for the TFP of ready-made garments firms in Bangladesh, China, India, and Pakistan.<sup>49</sup> The results in Table 4 also show an important negative effect of crime on TFP. Firms making larger protection payments are significantly less productive than other firms. We assume that larger protection payments to be “spared” from organized crime are a proxy for an environment with more potential crime. In unreported regressions, we also find a negative effect of the ratio of security expenses to sales when that variable is the measure for crime.

Heavier bureaucracy and red tape in an industry and location seem to be associated with higher firm TFP, according to the estimates in Table 4. While the effects of the number of days taken to clear customs on TFP are very small and insignificant, the effects of the percentage of time that firm managers must spend dealing with regulations on TFP are actually strong and significant. Also, the results in Table 4 suggest that firm TFP is higher in industries and locations where firms pay a larger percentage of their sales in bribes to get things done. In unreported regressions where we include the percentage of firms in each industry-location cell paying bribes to get things done as the measure of corruption, we also find that firm TFP is higher in industries and locations that have a larger fraction of firms paying bribes.

We interpret the findings on bureaucracy and corruption as reflecting reverse causality. First, better performing firms are likely to be more visible to government officials and thus become more subject to inspections or visits. Moreover, firms with higher productivity are likely to be involved in more activities requiring government permits or meetings with officials such as investments for expansion, exports, etc. Second, as argued by Svensson (2003) and Fisman and Svensson (2005) if government officials have discretion in implementing or enforcing regulations, then they will

> 49 However, our findings differ from those obtained by Hallward-Driemeier, et al. (2003) for Chinese firms in several industries. That study finds no effect of electricity infrastructure on TFP. The difference in results in very likely due to the difference in levels of development of the two countries, and to the fact that physical infrastructure no longer constitutes a bottleneck for growth of Chinese firms, while it is still very relevant for Bangladeshi firms.

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Our main dependent variable of interest at any level of aggregation is the level of industrialization defined as the share of manufacturing in economy wide GDP or in economy wide aggregate employment. To adjust for possible resource boom, we also consider the manufacturing’s percentage contribution to non-oil GDP for the restricted set of oil-exporting countries. Given that these variables are bounded (i.e. these are fractional response variables) we perform our analysis using both the linear fixed-effects panel data model - which is subject to pitfalls similar to linear probability models - as well as the “fixed-effects fractional logit” model recently developed by Hardin, Hardin, Hilbe & Hilbe (2007). Our results overwhelmingly do not support the finding that SSA countries have began to deindustrialize prematurely. Moreover, we document meaningful heterogeneity across SSA subregions. The Southern region is found to be the only subregion to have witnessed deindustrialization. However, we are unable to confirm that this deindustrialization in the Southern region of SSA is premature. The rest of the paper is organized as follows. Section 2 presents the data. Section 3 discusses the relevant methodological issues. Section 4 presents the main results. Section 5 explores geographic heterogeneity. Section 6 considers potential hypotheses and Section 7 concludes.

# **2 Data and Descriptive Analysis**

This section describes the data sources used for the analysis and provides summary statistics as well as trend analysis of our main indicators.

## **2.1 Data Sources and Measurements**

The data for this study come from a variety of sources. The data for manufacturing valued added and manufacturing employment come from the Groningen Growth and Development Center 10-sector Database (Timmer, de Vries & de Vries 2015). The GGDC Database collects time series data on value added and employment for ten broad sectors of the economy for 42 countries (both developed and developing) spanning 1950 through 2012.<sup>2</sup> The advantage of the GGDC is that it provides a long-run series of sectoral productivity that is internationally comparable across a broad range of countries. However, the GGDC’s Africa Sector Database (ASD) only includes eleven sub-Saharan African countries.<sup>3</sup> Thus, for other sub-Saharan African countries, we collect manufacturing value added and GDP time series from

> 2This period of data availability is as of September, 2017.

> 3The Sub-Saharan African countries in the ASD are Botswana, Ethiopia, Ghana, Kenya, Malawi, Mauritius, Nigeria, Senegal, South Africa, Tanzania, and Zambia.

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# **Figure 5**

# **Pension System Equity Holdings as a Share of Domestic Market Capitalization**

This figure shows the size of pension funds' investments in equities across PFAs relative to Chile's domestic equity market capitalization, as a percentage, for the entire sample period (July 1996 to December 2005), as of December of each year.

<!-- Start of picture text --> 12%<br>10.1%<br>10%<br>9.4%<br>8.4%<br>8% 7.6% 7.6%<br>7.3% 7.3%<br>6.9%<br>6.5% 6.6%<br>6%<br>4%<br>2%<br>0%<br>Dec-96 Dec-97 Dec-98 Dec-99 Dec-00 Dec-01 Dec-02 Dec-03 Dec-04 Dec-05<br>Total Pension System Holdings as a Fraction of Domestic Market Capitalization<br><!-- End of picture text --> Source: World Bank Financial Development Indicators for domestic market capitalization.
**Figure 2: Correlation between the relative intensity of communication versus manual tasks and the share of teleworkable jobs in each of ISCO three-digit occupations in 2018**

<!-- Start of picture text --> 531 232413351 14225 2 262 1 234125111411251133235 313441 3 43 2 231121 23324 2 212 243 41 261<br>122<br>216<br>143431 331264<br>213<br>352<br>333<br>214<br>342<br>341<br>211<br>263<br>422<br>311 421265<br>441 132<br>516<br>622831 612<br>961 732 315 343432511 335<br>226<br>92175263633721728128 98111 39486218833962763283427 3871 613 2 525911753257513711611 1 8237481393359418328 1 6512742731754 5 541524121532 3 312432514314 3 5233 2 325 12 1312524141323522222 223 221 952<br>1 1.5 2 2.5 3 3.5<br>Relative intensity of communication / manual tasks<br>1<br>.8<br>.6<br>.4<br>.2<br>Share of telework jobs in occupation group 0<br><!-- End of picture text --> Source: Own elaboration based on EU-LFS data and O*NET surveys. Note: The size of the circles represents the relative size of each ISCO three-digit occupation in employment. The correlation uses the relative size of each occupation as weights.

# 3.3 Migrant-Native Gaps in Income and Health Risk Exposure to COVID-19

Before illustrating the econometric analysis, we present several descriptive statistics of our sample of working age individuals (ages 25-64) from the EU Labour Force Survey. As of 2018, there were 270 million working-age people residing in Western European countries. Almost one out of five (18.7%) of them were foreign-born (Table 1). These immigrants originally come from various high-income Western European countries (3.1%), new EU member states such as Poland and Romania (3.6%), other European countries that are not EU members (3.5%), and other locations outside of Europe (8.1%). Migrant workers are slightly younger than native workers on average (mean age is 43 versus 45.4) and have a slightly lower share of men than the native workforce (48.4% versus 50.2%). Migrants also have slightly lower education levels, with 31.2% having 14
reach the students who are supposed to benefit from the program. However, parents could react by reallocating food in the household away from these children who are already benefiting from the program. Food received by the household under THR is more likely to be shared by other household members, hence reaching children who may be in need of additional food. Because the nutritional benefits would be diluted within the household, the impact on academic performance is likely to be lower for THR than with a school meals program. Which program should be preferred is depends both on the policy objectives as well as on the evidence base. The latter empirical question is addressed by this paper.

The paper uses a randomized experiment to assess the hypothesized relationships between SFPs on the one hand, and enrollment, academic performance, cognitive development and preschool children nutritional status on the other hand. The focus of this study is the Sahel region of northern Burkina Faso in West Africa. Northern Burkina Faso is an appropriate context to evaluate the impact of school feeding program for two main reasons. First, the region has some the world’s lowest primary school participation. On average 20 percent of school age children (6 to 16 years old) attend school, based on recent national surveys (e.g. Institut National de la Statistique et de la Démographie & ORC Macro, 2004). Therefore there exists a large scope for increasing enrollment. Second, income levels are very low and severe food shortages are frequent (Zoungrana et al., 1999). Hence, the value of the food offered should be a sufficient incentive to attract children to school.

Our analysis adds to the literature on education in low-income countries in two ways. First, it rigorously evaluates the impact of two alternative school feeding schemes within the same context. The use of a randomized experiment has the advantage of avoiding the issue of site selection that may have limited the causal interpretation of many previous studies. Hence the paper provides new insights on how a range of educational outcomes including enrollment, absenteeism and academic performances respond to two related types of interventions. Second, in addition to educational outcomes, the paper also explores the impact of SFPs on the nutritional status of school age children as well as of younger children who are not enrolled in school. While previous studies have looked at the nutritional impact of school age children, none has taken into account the potential spillovers effects to younger children. This possibility would imply additional longterm benefit of SFPs which may have been previously under-estimated.

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health-care subsidies in the region (Abuya et al., 2012; B. Bellows, Kyobutungi, Mutua, Warren, & Ezeh, 2013; Obare, Warren, Abuya, Askew, & Bellows, 2014).

Recently growing awareness of health inequalities has sparked increased calls for a progressive, pro-poor expansion of national health systems to move toward UHC (Gwatkin & Ergo, 2011). Although the shape of UHC will vary between countries, the movement is defined by common objectives of incremental improvement in quality, reducing out-of-pocket expenditure at the point of care, and extending access to populations that lack it. Calls for progressive universalism argue that coverage should be extended first to those who are least likely to use services in the absence of the extension. Voucher programs are designed to offer a narrow health care package to a well-defined, disadvantaged population lacking access. In such populations, improved uptake should be observed in the local population within a relatively short time frame, depending on the nature of the service and the degree to which financial barriers constrained earlier access to care.

The goals of voucher programs are to reduce the financial barriers to accessing services for poor and underserved populations, reduce inequality in service use, improve quality of care, achieve cost-effectiveness in service delivery, and improve health outcomes (Bhatia and Gorter 2007; Cave 2001; Gorter et al. 2003). The programs aim to achieve these goals through various mechanisms. The programs, for instance, subsidize services and put in place mechanisms for identifying beneficiaries to ensure that target populations are reached. The programs also employ explicit, performance-based contracting, which, in theory, requires SPs to meet set minimum standards of care before being accredited. It is further expected that accreditation of several SPs should stimulate competition for voucher clients with pressure to improve service quality. The programs also negotiate reimbursements to SPs to maintain costs, which, together with the set minimum standards of care, should ensure cost-effectiveness in service delivery.

This paper presents the results of a quasi-experimental evaluation of the Uganda RHVP and findings from other studies including health worker job satisfaction and trends in out-of-pocket spending on maternal health services. The paper presents outcomes in four broad categories: knowledge, behavior (including utilization and access), quality, and out-of-pocket spending as commonly presented in the literature (Bellows, Bellows, and Warren 2011; Brody, Irige, and Bellows 2015). A fifth category, health status, is not addressed in this study as the sample size required to detect a noticeable difference in mortality or morbidity was beyond the evaluation scope. Future studies could consider undertaking such an endpoint or present results of modeling 6
having a labor contract seem greater for local residents than migrants, even though the increase in contract prevalence was greater for migrants overall.

While formal employment relations, as evidenced by a written labor contract, are more common after the implementation of the Labor Contract Law, the Chinese government and many other observers have noted that labor subcontracting has expanded rapidly as an employment form since the Law’s passage.<sup>8</sup> As a form of employment through a middleman agency, a labor service company, labor subcontracting allows employers to hire employees for shorter terms, with more flexibility, and often at lower wages and with lower social insurance contributions. Overuse or “abuse” of labor subcontracting, such as hiring long-term employees as subcontracted workers, is one of the major reasons that the National People’s Congress revised the Law in 2012.

No official statistics are kept on the extent of labor subcontracting. Based on surveys of 1000 enterprises and 10,000 employees in 25 cities conducted in 2010 and 2011, the AllChina Federation of Trade Unions estimated that 37 million workers (13.1% of all urban workers) are subcontracted labor (All-China Federation of Trade Unions, 2012). This includes 16.2% of workers in state-owned enterprises and 14% of workers in foreign enterprises. The Ministry of Human Resources and Social Security estimates a range between 10 million and 27 million subcontracted workers. Labor subcontracting is in widespread use by state-owned enterprises, government organizations, quasi-government organizations such as hospitals and universities as well as some foreign-invested companies (Wang 2012; Wu and Zhu 2012).

This expansion in labor subcontracting after the Labor Contract Law may indicate that higher levels of formality (more workers have written labor contracts) mask a decline in

> 8 A survey of 133 Chinese enterprises found that 18% of firms experienced a sharp increase in subcontracted labor while another 27% experienced a modest increase following implementation of the new Law (Jiang and Yang, 2011). Another study estimated that in Beijing, the number of subcontracted workers increased by 58% from 2007 to 2008 (Lin and Fan, 2011).

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these measures come from Claessens et al. (2008a). Finally, we also consider the ratio of total foreign claims relative to GDP (Figure 3). Total foreign claims refer to the sum of local plus cross-border claims, where the former are those booked by foreign bank branches or subsidiaries in the host country and the latter are booked outside of the host country.

Foreign bank presence as measured in terms of the number of foreign banks relative to the total number of banks has increased across every region between 1996 and 2005. In particular, Figure 1 shows that in regions like Sub-Saharan Africa and in Eastern Europe more than half of the banks in the system are foreign. Latin America also has a sizeable presence of foreign banks. In this region, the share of foreign banks rose from 27 percent in 1996 to almost 42 percent in 2005. In the Middle East, the share of foreign banks relative to the total number of banks rose from 14 percent to 24 percent between 1996 and 2005. East Asia and South Asia also witnessed an increase in the relative number of foreign banks, but both the change and the level are lower in these regions than in the others. In East Asia, the percentage of foreign banks rose from 12 to 19 percent. In South Asia, this percentage increased only from close to 6 to close to 8 percent.

According to data on the share of assets held by foreign banks, countries in Latin America and, especially, in Eastern Europe and Central Asia witnessed a remarkable transformation in their banking sectors. The share of foreign bank assets rose from an average of 17 percent to 34 percent in the case of the Latin America and 52 percent in the case of the Eastern Europe and Central Asia. Countries in Sub-Saharan Africa also have high levels of foreign bank participation - close to 50 percent of the system is foreign owned. But the increase in foreign bank participation between 1996 and 2005 was smaller than in the other two regions mentioned so far, given that Africa inherited high levels of foreign bank participation due to its colonial past. Relative to the aforementioned regions, the level of foreign bank participation in East Asia and in the Middle East and Northern Africa is much smaller, but in both regions (more so in East Asia) foreign bank presence has increased considerably since the mid-1990s. In East Asia, foreign bank participation increased from 4 to 15 percent. Among countries in the Middle East and Northern Africa, foreign bank presence rose from 7 to 11 percent. On the other hand, in South Asia, the share of assets held by foreign banks has remained fairly constant at 7.5 percent.

4
was necessary to avoid spillovers as the baseline survey was part of a larger field experiment study.

Within each district, the sampling procedure started with our team of enumerators contacting the local authority to request a map of _community-level_ boundaries. Locally known as ‘Rukun Warga’, these are non-official but well-established administrative zones which separate each district into ten community-level zones on average. Conditional on the inclusion criteria, the enumerators then listed the entirety of businesses within each zone until the final count surpassed 2,000 firms.

In January 2016 we listed 2,042 establishments through this protocol. We then randomly selected 1,301 to form our panel of retailers.<sup>3</sup> The study consisted of two waves of data collection, in April 2016 (hereafter the baseline) and then in April 2017 (hereafter the endline). The data were collected as part of a complementary field experiment on business growth of retailers. In between the two waves, a subset of these firms were exposed to experimental interventions, and we control for all treatment indicators throughout the paper in the analysis using endline data.<sup>4</sup>

# **B Data**

## **B.1 Measurement of Variables**

The detailed business survey used in both waves included questions on both entrepreneur and business characteristics. Questions on demographics, cognitive skills, attitudes, and preferences, as well as business assets, management practices, and business performance were asked. Finally, the survey included detailed questions on entrepreneurial aspirations.

## **_Business and Entrepreneurial Measures_**

Regarding business characteristics, we consider the age of the establishment as well as whether the firm is formally registered for taxes. Since formalization levels tend to be low in traditional sectors of emerging economies, we additionally proxy formality by whether the firm address is different from the owner’s home address. We also collect data on the size of the business premises in square meters, the number of full-time employees working in the business, the total number of customers visiting the shop on a typical day, and the firm’s typical daily sales and profits. Relevant to our study, we collect information on entrepreneurs’ future-oriented behaviors leading to firm growth and innovation. For instance, we ask about plans to start or improve book-keeping habits, and any plans

> 3We allocated the remaining 741 businesses to a back-up list. Businesses from this list were used to replace observations lost to refusals or aborted interviews, in random order.

> 4The interested reader is referred to Dalton, Ruschenpohler, Burak, and Zia (2018) for a companion paper on the field experiment. Note that the results in this paper are robust to limiting the sample only to the control group.

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