rafmacalaba/datause-encoder-data huggingface dataset:
of firms. Panel surveys of manufacturing firms in several sub-Saharan African countries were collected as part of the Regional Program on Enterprise Development (RPED) by Oxford University and the World Bank, and have been used in several papers on firm dynamics (Frazer 2005; Söderbom et al, 2006; Sandefur, 2010). These surveys typically include 100-200 manufacturing firms per country, and do not include household enterprises. They report firm death rates of 6.3 percent over two years (Frazer, 2005) and 19 to 44 percent over 5 years (Söderbom et al, 2006), although they do not report attrition rates. Davies and Kerr (2015) conducted a 10-year follow-up survey of a random sample of 1000 firms surveyed in the 2003 Ghanaian manufacturing census. They could not find what had happened to 29 percent of the 386 firms with under 10 workers in their sample, while 25 percent had died.

This review of the existing literature shows that there has been relatively little evidence on the rates of firm death in the most prevalent types of enterprises found in developing countries: micro and small household enterprises that include retail and service firms in addition to manufacturing. Few of these existing studies measure attrition rates, nor do any provide bounds on what the rate of firm death will be when this is taken into account. A number of the studies provide descriptive information on what types of firms are more likely to die, and we will compare our findings on these correlates in Section 5. However, the fact that firm death is only a fraction of the sample, and that single country samples have often been relatively small, has meant that studies typically have relatively few deaths with which to examine the characteristics of who dies. For example, Frazer (2005) pools four rounds of firm surveys from Ghana, and still has only 30 deaths versus 479 survival episodes to compare; while Davies and Kerr (2015) have 95 deaths of firms with 0 to 9 workers.

# **3. Our Approach to Measurement and Our Sample**

Our conceptual unit of analysis is the firm, rather than the entrepreneur, and our focus is on non-farm micro and small enterprises in developing countries. The vast majority of such firms have fewer than ten workers, with the modal firm in many developing countries consisting of just the owner with no paid workers (McKenzie, 2017). We define firm death as having occurred if a firm is open at one point in time, and then is reported as having shut down by the owner in a subsequent survey round. By shut down, we mean that the owner of the firm has decided to stop operating the firm, and no one else is operating it. It is not intended to include temporary closures of a few days or weeks that may occur when the owner is ill or away.

6
# Table 5: Net present value of increased learning

|**Effect size**<br>**percentile**|**Intervention**|**Effect**<br>**size**|**Country**<br>**GNI Per**<br>**Capita,**<br>**2015 PPP**|**Labor Share of**<br>**Income, latest**<br>**available year**|**Average**<br>**income,**<br>**2015 PPP**|**Return**<br>**to**<br>**literacy**|**Percentage**<br>**change in**<br>**earnings**|**NPV$**|
|---|---|---|---|---|---|---|---|---|
|25<sup>th</sup>|India PicTalk|0.06|6,020|0.29|1,769|0.51|0.03|959|
|**Structured**<br>**pedagogy**<br>50<sup>th</sup>|Kenya HALI|0.13|3,060|0.35|1,079|0.59|0.08|1,338|
|75<sup>th</sup>|Brazil new curriculum|0.29|15,020|0.44|6,552|0.72|0.21|24,369|
|**Comuter**<br>25<sup>th</sup>|Peru OLPC|‐0.02|11,960|0.23|2,736|0.72|‐|‐|
|**p**<br>**assisted**<br>**li**<br>50<sup>th</sup>|China remedial class|0.01|14,160|0.49|6,941|0.24|0.002|274|
|**earnng**<br>75<sup>th</sup>|Ecuador learning lab|0.06|11,190|0.37|4,140|0.72|0.04|3,093|
|25<sup>th</sup>|Senegal school grant,<br>grade 5 female|‐0.06|2,390|0.21|497|0.59|‐|‐|
|**School based**<br>**management**<br>50<sup>th</sup>|Gambia school grant|0.01|1,580|0.25|397|0.59|0.01|40|
|75<sup>th</sup>|Senegal school grant,<br>grade 6 male|0.04|2,390|0.21|497|0.59|0.02|213|

Notes: Return to literacy is based on coefficients in Table 6.

References of included interventions: India Pic Talk: He, Linden and Macleod 2009; Kenya HALI: Jukes and Dubeck 2015; Brazil new curriculum: Leme 2010; Peru OLPC: Quispe et al. 2013; China remedial class: Lai et al. 2011b; Ecuador learning lab: Carillo et al. 2010; Senegal school grant, grade 5 female: Carneiro et al. 2015; Gambia school grant: Blimpo et al. 2015; Senegal school grant, grade 6 male: Carneiro et al. 2015. Sources: Authors’ calculations, Snilstveit et al. (2015), World Bank (2016b) and Neiman and Karabarbounis (2013).

25
opportunities with an estimated average sibling correlation of 0.65, and East Asia and Pacic is the second worst (0.64), while Europe and Central Asia had the lowest sibling correlation estimate (0.48). The within region heterogeneity is also substantial; for example, in SubSaharan Africa, the maximum estimate is 0.77 (Madagascar) and the minimum is 0.49 (South Africa).

Third, the evolution of sibling correlation from the 1970s birth cohort to the 1990s birth cohort suggests a rich variety of mobility experiences. At the regional level, some experienced monotonic improvements in intergenerational educational mobility (Latin America and Caribbean, and East Asia and Pacic), while some others faced stagnation (South Asia, and Sub-Saharan Africa). Middle East and North Africa stands out as the only region to have a declining trend in educational opportunities (i.e., monotonically increasing sibling correlation from the 1970s to the 1990s). However, the regional average conceals a lot of country level heterogeneity. For example, notwithstanding a stagnant regional average in South Asia, Bangladesh achieved substantial gains in educational opportunities with sibling correlation declining from 0.67 (1970s) to 0.61 (1990s). In contrast, Pakistan experienced a declining intergenerational educational mobility with sibling correlation increasing from 0.60 (1970s) to 0.68 (1990s).

Fourth, estimates of the role played by intergenerational transmission between father and children vary dramatically depending on the decomposition method used. Consistent with the analysis of Bingley and Cappellari (2019), we nd that the estimated share of intergenerational transmission in sibling correlation is considerably higher when we relax the homogeneity and independence assumptions implicit in the standard methods of decomposition. The estimates from the Bingley and Cappelari (2019) approach suggest an average of 74 percent across 53 countries, and in some countries, the share is higher than 80 percent (many of them in SubSaharan Africa). In contrast, the average share is only 34 percent according to the estimates from Bjorklund et al. (2010) approach.<sup>17</sup> The estimates across birth cohorts show that the share of intergenerational transmission has declined in many countries from the 1970s to the 1990s birth cohort. But there are 13 countries where the share has increased over decades, many of them (11) are located in the Sub-Saharan Africa region.

> 17The average is 30 percent according to the Solon (1999) method, and 18 percent according to the Mazumder (2008) method.

6
Fields (2011) compiles several features that characterize labor markets in most developing economies. The unemployment rate following the formal International Labour Organization definition is typically lower in developing countries than developed countries, illustrating the inadequacy of a general definition to capture the extent of the problem. The unemployment rates for Eastern European countries are on average around 8.4 percent, while those of East Asian and South Asian economies are around 4.4 percent. In most of Asia, Latin America, and Africa, wages are low and working hours are long. The problem of low wages is worsened by uncertain and irregular income flows. Women are disproportionately employed in the informal sector, in casual positions with lower earnings. Overall, the composition of employment in developing countries is different from that in developed countries, with a larger proportion of people engaged in agriculture, self-employment, and own-account work, and a smaller percentage employed in offices and factories. A high proportion of these workers are not covered by government-run job-security programs and therefore do not receive any form of protection from job loss.

Fields also recognizes that wage employment jobs are more coveted than selfemployment jobs. Within wage employment jobs, regular wage jobs are preferred over casual jobs. The high incidence of self-employment is primarily driven by the fact that in most developing countries there are not enough wage employment opportunities available and the cost of waiting for a wage job is too high for most people. Thus, they prefer to set up their own business and create their own employment opportunities, despite the scarcity and high cost of capital. A section of those engaged in self-employment could also be doing so voluntarily, for example, women trying simultaneously to work and fulfill childcare responsibilities. Finally, developing country labor markets are highly segmented (as discussed below). In summary, Fields characterizes developing country labor markets as having “employment problems” rather than “unemployment problems.” As we show in the subsequent sections, these developing country labor market features make households more vulnerable to climate change and reduce the effectiveness of climate mitigation policies.

9
21

**S3 Table. Intervention effects on all secondary outcomes, including index subcomponents**

|||Control<br>Prevalence/|||Intervention<br>Prevalence/|<br>||CI|95%|
|---|---|---|---|---|---|---|---|---|---|
|Outcomes|n|<br>Mean|SD|N|<br>Mean|<br>SD|ITT|Lower|Upper|
|Improved water source|1845|43%||1437|74%||0.24|0.12|0.36|
|Improved sanitation|1843|14%||1437|34%||0.18|0.10|0.25|
|Water governance perception index|1845|0.00|1.00|1438|0.22|0.88|0.19|0.04|0.34|
|Committee selected fairly|600|1.76|0.81|1119|1.82|0.76|0.06|-0.04|0.17|
|Committee treats community fairly|621|4.15|1.31|1158|4.07|1.31|-0.09|-0.27|0.09|
|Committee manages money well|635|3.25|1.12|721|3.31|1.14|0.05|-0.13|0.23|
|Comm responds breakdown well|972|3.69|1.18|1227|3.67|1.23|0.01|-0.13|0.15|
|Confidence committee will solve reported issue|1009|3.10|1.05|1227|3.12|1.03|0.02|-0.13|0.17|
|Satisfaction with water access (1-5)|1845|2.76|1.49|1438|3.38|1.43|0.56|0.27|0.85|
|Time spent collecting water (IHS)|1845|4.17|2.07|1438|4.04|2.05|0.03|-0.20|0.27|
|HHs pay for water (Dummy)|1845|10%||1438|23%||0.09|0.00|0.19|
|Water use expenditure (weekly)|137|153|217|303|254|351|114|-16|243|
|Hygiene and behaviour index|1845|0.00|1.00|1438|0.30|1.07|0.23|0.12|0.34|
|Handwashing score (0-10)|1845|2.79|2.22|1438|3.41|2.16|0.43|0.19|0.67|
|Open defecation (%)|1843|32%||1437|27%||-0.03|-0.08|0.01|
|Self-reported handwashing with soap/ash (%)|1843|67%||1437|82%||0.09|0.06|0.13|
|Frequency of latrine cleaning over past 2 weeks|761|4.89|4.26|648|5.00|4.06|0.25|-0.32|0.82|
|Water in pot is clean and covered (%)|1669|57%||1273|57%||0.02|-0.03|0.07|
|Water treated for consumption, any method (%)|1669|3%||1273|7%||0.03|0.01|0.05|
|Handwashing action|616|15%||489|17%||0.00|-0.04|0.03|
|Handwashing with soap/ash|616|2%||489|4%||0.01|-0.01|0.03|
|Water point has water|380|97%||266|85%||-0.11|-0.18|-0.05|
|WP FIB MPN/100mL|366|79.31|37.92|221|72.41|42.56|-9.46|-18.85|-0.06|
|WP FIB log10 MPN/100mL|366|1.71|0.60|221|1.58|0.70|-0.17|-0.32|-0.02|
|HH FIB MPN/100mL|1098|82.27|35.05|851|79.44|37.71|-3.87|-9.59|1.86|
|HH FIB log10 MPN/100mL|1098|1.76|0.53|851|1.72|0.58|-0.06|-0.15|0.04|
|Weight for age|1223|-1.17|1.16|919|-1.14|1.16|0.06|-0.04|0.15|
|Weight for length|1224|0.14|1.07|918|0.22|1.03|0.10|-0.02|0.22|
|Life satisfaction & self-esteem index|1843|0.00|1.00|1435|0.03|0.98|0.01|-0.12|0.14|
|Life satisfaction (WVS)|1843|4.87|3.20|1435|5.04|2.89|0.20|-0.10|0.49|
|Feel I am person of worth (Rosenberg)|1843|2.25|0.90|1435|2.19|0.90|-0.03|-0.13|0.07|
|Feel that I have good qualities (Rosenberg)|1843|2.42|0.74|1435|2.36|0.75|-0.02|-0.10|0.05|
|Inclined to feel I am a failure (Rosenberg)|1843|1.43|1.11|1435|1.49|1.05|-0.04|-0.16|0.08|
|Able to do things as well as other people (Rosenberg)|1843|2.44|0.75|1435|2.40|0.76|0.01|-0.06|0.08|
|Feel have not much to be proud of (Rosenberg)|1843|0.98|0.98|1435|0.99|0.92|-0.05|-0.14|0.04|
|Take a positive attitude towards self (Rosenberg)|1843|2.35|0.78|1435|2.37|0.74|0.08|-0.01|0.17|
|I am satisfied with myself (Rosenberg)|1843|2.03|1.02|1435|2.12|0.96|0.16|0.07|0.26|
increasing relative scarcity of skilled workers in China and India (as well as most of the developing world) and as a result the skill premium is expected to rise (Figure 7). This widening of wage gaps could lead to increasing inequality within fast-growing economies, although such pressures could be counteracted by a host of effects including falling rural-urban wage differentials, decrease in the gender wage gap, or changing returns to other worker characteristics.

**Figure 7 Skill premiums are likely to rise across the developing world**

<!-- Start of picture text --> Ratio of skilled wages to unskilled wages<br>8<br>7<br>6 2005 2030<br>5<br>4<br>3<br>2<br>1<br>0<br>China IndiaEast Asia Eastern EuropeLatin AmericaMiddle EastSouth AsiaSub-Sah. AfricaDevelopingHigh income<br><!-- End of picture text --> Productivity growth, changing sectoral structure, and widening skill premiums lead to important changes in international competitiveness of developing countries. Low and middle income nations solidify their comparative advantage in exports of manufactured goods, which rise from 79 to 88 percent of total merchandise exports between 2005 and 2030 (Figure 8). The trend is even more pronounced in China and India, which benefit from a TFP growth significantly above the developing country average. In our scenario, 97 percent of Chinese and 98 percent of Indian merchandise exports are likely to originate from manufacturing sectors. As high income countries lose competitiveness in the manufacturing sector due to their lower productivity, the share of manufacturing products in their total exports is likely to decline significantly.

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# **EXvCUrWE** SUMMARY

# **A.** Introduction

i. Since the early 1980s, the Bank has been gradually shifting away from traditional public inves-ment reviews (PIRs), designed to identify sector investment priorities within the macro framework, to comprehensive public expenditure reviews (PERs) that include recurrent expenditures. The Bank's increasing focus on policy-based lending, particularly in low-income countries, has contributed io the growing reliance on comprehensive public expenditure reviews. Since education is largely financed from public sources, and overwhelmingly from the recurrent budget, the shift from PIR to PER naturally has increased attention to education cost and financing issues.

**ii.** Recent reviews have covered PERs in general and the treatment of the main economic sectors. Education issues in PERs, however, have not yet been evaluated. Specifically, this review has the following objectives: a) To assess the extent to which the increased attention to education in PERs contributes to a more integrated treatment of education sector issues within the overall economic environment, particularly in adjusting countries.

b) To compare the government's sector objectives with national expenditure priorities and policy reforms and, where they are inconsistent, to suggest improvements.

c) To review the diversity of methodological approach, data treatment, and sector coverage among education PERs, identifying best practices according to country-specific circumstances.

iii. The analysis relies on a structured review of 36 reports (see annex II) which were selected from a larger sample of PER and PIR reports produced in the 1985-90 period. Countries are classified according to a three-dimensional typology: the ratio of govermnent revenues to GNP, education spending as a share of total government spending, and the primary enrollment rate. This typology, explained in annex III, provides a rough diagnostic framework for comparative analysis of the policy content of education PERs.

# B. The Education Sector in the Macroeconomic Context

iv. PERs are an excellent way of bringing together country economic and sector work (CESW) and linking macro and sector performance issues. But few PERs succeed in convincingly integrating the macro and sector perspectives. Many reports seem to include education in the expenditure analysis as a defensive strategy--to avoid being criticized for the sin of omission. No clear rationale is applied across reports to justify the inclusion of education resources, or human resources in general, in the multisector reviews.

i
data from Mexico and Chile suggest that both the size, of and transitions into the self-employed sector behave procyclically.6 There is increasing evidence both in the sociology and economics literature that suggests a life cycle view of the trajectory between formal and informal selfemployment: in the absence of well-functioning credit markets and effective educational systems, workers may take formal sector jobs to accumulate human and financial capital and then quit to open their own business.<sup>7</sup> In sum, there is ample evidence suggesting that selfemployment is a desirable destination for many workers who voluntarily leave formal employment.

_2. In the absence of government or union induced rigidities, there is still strong evidence of "segmentation. "_ Recent work on Mexico challenges the customary view of the sources of labor market segmentation. Minimum wages are not binding (See Bell 1998) and the evidence suggests that union power is directed largely to the maintenance of employment and find no significant effect on wages.' As Marquez and Ros (1990), noted, and has been confirmed by later studies for Peru (Shaffner,1998)and Guatemala (Funkhauserl998), wages of similar workers rise with firm size, much as they do in industrialized countries. Further, Marquez (1990), and Abuhadba and Romaguera (1993) find evidence consistent with efficiency wage effects in the high correlation of wage differentials among Chile, Venezuela, and Brazil and the

**6** See Maloney (1997b) and Pages(1998). Pais de Barros finds no cyclical movement in Brazil. Saavedra in Peru finds a broadly countercyclical movement but this may be largely driven by secular trends.

7Aroca and Maloney (1998) model the transitions into informality as a destination of entrepreneurs and find evidence using logit techniques adapted to panel logit context.

8 See Maloney and Ribeiro (1998), and Hemandez -Laos (1998). Panagides and Patrinos (1994) find some wage effects, but these are likely to disappear when relevant firm characteristics, such as size, are included.

4
- 17 -

**Figure 17. Model of crop choice**

<!-- Start of picture text --> Total<br>(2,475 plots)<br>Domestic Export<br>(2,320) (155)<br>Maize Rice Groundnuts Cassava Cotton Tobacco Sesame<br>(1,730) (329) (220) (41) (71) (34) (50)<br><!-- End of picture text --> As determinants of crop choice, both alternative- and individual-specific attributes are included in the model. The summary statistics are shown in Table 1. For alternative-specific characteristics _X_ , agro-ecological crop suitability is fundamental, as shown in the literature. For instance, Kurukulasuriya and Mendelsohn (2007) find the particular importance of soil and weather conditions, such as precipitation and temperature, for farmers’ crop choice.

Our crop suitability is measured by potential yield, which represents all these agro-climatic conditions. The data come from the Spatial Production Allocation Model (SPAM) updated by IFPRI. The SPAM basically disaggregates the subnational production data into the 10 × 10 km pixel-scale data using a spatially disaggregated data fusion and optimization approach with various agro-climatic conditions taken into account, such as weather conditions and land use and crop suitability. Given each household’s location in the LSMS data, the crop suitability is defined by the amount of crops that can theoretically be produced under the low-input assumption.

From the economic point of view, crop prices may also be an important factor to incentivize farmers to choose a particular crop. According to the LSMS data, about 40 percent of the households were involved in some market transactions in Tanzania. Using those crop sales data, average local market prices are calculated at each locality (defined by a 50km radius).<sup>11</sup>

> 11 Given the relatively limited geographic coverage of the LSMS, the “locality” must be defined relatively broadly. If there is no observed crop price within a 50km radius, the price available in the closest location is used as a local price.
**17**

**found to be higher (Table** 3). A **rate of distributionally**<sup>**neutral growth**of</sup> **1. 3% per annum would be sufficient to prevent an increase in**<sup>**the number**of</sup> people below three-quarters of the BBS poverty line, at the current popula'Iw growth rate.

Over the last decade or so, Bangladesh has not achieved a rate of gro in real national income or consumptio in excess of twice the rate of population growth. The compound annual growth rate of real GDP was 4.4% o'v.the period 1972 to 1987; the population growth rate over **the** same period was 2.4% (World Bank, 1988). So, extrapolating from recent trends, a corlntirlur increase in the number of people below tlhe BBS poverty line must be ainticipated.

More encouragingly, however, some observers are currently projecting tvrate of growth in real GDP per capita in Bangladesh over the next ten years:. e::ceed that of the 1980s. It maay not be unreasonable to expect a distributionallv neutral growth rate in consumptionI per capita of at leas-;! current rate of population growth, anld, hence, stahl e or slightlv falil g :.u:.i;ers of poor in Bangladesh between now and 2000. A het.teperformance s .;ouid appear to be unlikely under current external and do:nestic CoI:di _:i(ouS_ . If a per capita **annu.al** growth rate of 2.4% can be achiev,kd _wir.ou_ adverse shitf"s in rela:ivineq'alities, or an increacse in tVh ra t population growth, then absolutIe rnurbers of poor in BaIg Iadlsh will s **_:ah_** i i (or fall slightly if one prefers to use a lower poverty line). The hoadcol-. index of poverty will fall at roughly the same rate, while the poverty gap measuie and the distributionally sensitive measure will fall at about 5% and 6% per year respectivelv.