rafmacalaba/data-use-mentions-extended huggingface dataset:
9 A large share of state banks is also attracted to the SME business due to the perceived profitability of the sector (Figure 6b), but the share is somewhat lower than the one for private banks. Interestingly, supply chain links and cross selling do not seem to be important drivers for state banks. These responses could reflect the broad policy mandates imposed on state banks to serve the SME sector, or the lower level of development of SME strategies in these banks, possibly also related to the absence of an SME unit in several of these banks.

Regarding the obstacles to SME lending, the responses in the MENA survey were more clear and consistent than those in the two previous surveys conducted in Latin America and worldwide. As shown in Figures 7a and 7b, MENA banks complain primarily about SME opacity and about the weak financial infrastructure (lack of reliable collateral, weak credit information systems, and weak creditor rights). They complain much less about restrictive regulations (e.g. interest rate controls), excessive competition in the SME segment, or weak demand for loans from SMEs. This pattern is consistently observed in both GCC and non-GCC banks, and also between state and private banks. Interestingly, however, a larger share of state banks indicated that their own internal technical weaknesses constitute an obstacle to SME lending.

The contrast with the two previous surveys is striking. In the Latin American survey (de la Torre, Martinez Peria, and Schmukler (2010)), banks indicated many types of obstacles, including macroeconomic factors, regulations, and excessive competition in the SME business, and the patterns were not consistent across countries. For example, the legal and contractual environment was identified as an important obstacle in only two countries. In the survey conducted by Beck, Demirguc-Kunt and Martinez Peria (2008), macroeconomic factors and competition in the SME segment were also identified as the major obstacles, not the legal and contractual environment. The greater concern expressed by MENA banks about the quality of financial infrastructure is not
4,000 teachers allocated to these districts in response to the results-based financing.

**Results-Based Financing.** The Government fully achieved all three of the staffing-related RBF targets.<sup>20</sup> A Primary Teacher Management Strategy was completed and approved by Government for use to improve teacher distribution as well as more generally supporting improved teacher hiring, promotion, transfer and management. The PqTR in Grades 1-2 in the eight disadvantaged districts was reduced from 166:1 to 107:1, a reduction of 36 percent. The female/male teacher ratio in Grades 5-8 in the eight disadvantaged districts was increased from 0.31 to 0.37, an increase of 19 percent (Ministry of Education, 2021).

# **Di** ff **erence-in-di** ff **erence analysis: Intermediate outcomes**

**Table 4** shows the impact of MESIP on PCR and PTR, drawn from EMIS data. The first row confirms that PCRs and PTRs improved in the comparison group of schools between 2016 and 2020; the second confirms that baseline PCRs and PTRs were higher in the MESIP districts. The third row

> 19 Both 2017 and 2018 deployments also included approximately 1,500 Open Distance Learning (ODL) graduates.

> 20 The Government also fully achieved targets relating to the passage of national strategies and plans to improve female/teacher ratio and reduce repetition rates, but only partially achieved the target relating to repetition (reducing the repetition rate from 23.7 percent to 21.4 percent). In total, the government successfully triggered the release of a total US$12.2 million out of a maximum US$13.5 million in results-based financing.

17
Resource Economists 7_ (6), 1113–50.

- Gibson, J. (2021). Better night lights data, for longer. _Oxford Bulletin of Economics and Statistics 83_ (3), 770–791.

- Gibson, J., S. Olivia, G. Boe-Gibson, and C. Li (2021). Which night lights data should we use in economics, and where? _Journal of Development Economics 149_ , 102602.

- Gollin, D. and C. Udry (2021). Heterogeneity, measurement error, and misallocation: Evidence from African agriculture. _Journal of Political Economy 129_ (1), 1–80.

25
IDA is now much more focused on achieving the desired results in terms of poverty reduction than on inputs (measuring “success” in terms of dollars or bags of wheat given to the government). But the systematic measurement of outcomes raises a number of methodological and practical questions that are still not resolved.

> 63 A problem arises when measuring outcomes that are unobservable, e.g., improvements in governance. Proxies are used in the governance literature, including in the now famous governance index constructed by Kraay and Kaufmann—either quantitative proxies (e.g. the number of changes in government as a gauge of ‘political instability’) or qualitative variables (e.g. the subjective ranking of contract enforcement as a gauge of ‘institutional efficiency’).

51
# **1. Survey of the Literature**

In this section we discuss the main findings of the literature on both advanced economies and developing countries, though the latter is more limited. These studies have focused on the evolution of the gender age gap over the life-cycle, by asking such questions as: When does the gender wage gap emerge? Does one exist at labor market entry or does it emerge over time?

Manning and Swaffield (2008) are among the first to ask such questions using UK data. They find no gender gap at labor market entry but a gap of 25 log points emerges after 10 years. They attribute the gap to a number of factors, such as human capital differences, maternity leave, psychological factors and, to a lesser extent, the lower degree of job mobility, which prevents women from finding higher-paying jobs. Although lower, a gap also emerges ten years from the beginning of the career of women without any children.

Del Bono and Vuri (2011) also find that the gender wage gap appears not immediately but a few years after workers first join the labor market. Compared to Manning and Swaffield (2008), however, they find a greater impact of returns to job mobility on the gender wage gap. They use administrative social security data containing detailed information on job moves of men and women during the first ten years of labor market entry.<sup>1</sup> Bertrand et al. (2010) look at a particular sample, namely a sample of graduates from an MBA of a major American university. As such, the sample presents little heterogeneity and allows the comparison of men and women with very similar skill levels and motivation. The results of the analysis of this sample also suggest that a conditional gender wage gap emerges only after some time, after maternity and the ensuing childcare activities which apparently involve women more than men.

Such findings are echoed in a recent literature on developing countries. Pastore (2010a) finds that the gender wage gap
MALI’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE it via protected wells and boreholes to access water. For sanitation, the statistics close to half of the population relies on improved latrines.

**Figure 9. Half of Mali’s population has access to improved water and sanitation**

<!-- Start of picture text --> a. Water<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1987 1996 2001 2006<br>improved unimproved<br>b. Sanitation<br>100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1987 1986 2001 2006<br>improved unimproved<br>% of population<br>% of population<br><!-- End of picture text --> Source: WHO – Joint Monitoring Program 2010, from Demographic and Health Surveys for 1987,1996, 2001 and 2006 Mali’s achievements in water and sanitation are even more remarkable given the country’s demography and geography. Mali’s population has been growing at an annual rate of 2.5 percent, and people continue to move to the most urbanized areas of the country, creating enormous pressure on existing infrastructure. In the late 1990s, Mali’s expansion strategy focused on water provision through standposts. During the 2000s, however, the emphasis has been on increasing the use of wells, boreholes, and, to some extent, piped water for improved water provision (table 8a). An average of 0.8 percent of the population gained access to piped water annually
*|0.006*|0.018*|
||(0.005)|(0.013)|(0.003)|(0.010)|
|Country FE|Yes|No|Yes|No|
|Year FE|Yes|No|Yes|No|
|Mean dependent var.|38.295|38.295|38.445|38.445|
|Number of countries|128|90|128|90|
|Observations|1,505|90|3,781|90|

_Notes:_ Robust standard errors in parentheses. Standard errors are clustered at the country level. Regressions are weighted by region population. Inequality data in Columns (1)-(2) are taken from the World Development Indicators (WDI). Inequality data in Columns (3)-(4) are taken from the Standardized World Income Inequality Database (SWIID). Inequality and weather variables in the long-differences model are measured by the difference between averages of the earliest 3-year period and averages of the latest 3-year period. The long differences estimation is based on crosssectional data with a smaller sample size compared with panel data. *** p<0.01, ** p<0.05, * p<0.1 56
<!-- Start of picture text --> Figure 4.1. Distributions of estimated welfare gains from Russian WTO accession<br>for the entire sample, the poorest decile, and the richest decile.<br>.25<br>.2<br>.15<br>.1<br>.05<br>0<br>-1 2 5 8 11 14<br>Welfare gains as a percent of consumption from WTO accession<br>all households the poorest decile<br>the richest decile<br><!-- End of picture text --> Of the 55,098 households, there are 59 with gains less than two percent and 7 households with gains above 25 percent. Thus, 99.9 percent of all households have gains that fall in the range of 2 to 25 percent. Fourteen households, or two-hundredths of one percent of the households, are estimated to lose.

Observations in a range 0% to 15% are shown. Deciles are constructed to be representative of ten percent of Russian population based on the weights of the Household Budget Survey 105
4 poverty assessments are based – are seldom representative at the level of any but the largest metropolitan areas in the developing world. They are certainly not representative for smaller towns and cities, and information is not usually disaggregated along these lines.<sup>5</sup> In this paper, we draw upon the considerable additional insights generated by small area poverty estimation (based on the combination of welfare estimates from household surveys with “sample” sizes from National Censuses) to investigate the relationship between poverty and city size in eight developing countries, namely Albania, Brazil, Kazakhstan, Kenya, Mexico, Morocco, Thailand and Sri Lanka. We find substantial variation in the incidence and depth of consumption poverty across city sizes in seven of the eight countries. For all seven countries where the data permits some kind of disaggregation of the incidence of public service access, there is also considerable variation across city sizes. In all cases, poverty is lowest and service availability is greatest in the largest cities – precisely those where governments, the middle-classes, opinion-makers and airports are disproportionately located. This leads us to ask whether, alongside Lipton’s original urban bias, there might also exist a “metropolitan bias” in the allocation of resources (including policy attention) to larger cities, at the expense of smaller towns, where most of the urban poor are located.

There are a number of caveats which require that our results be treated with care. First, although our samples within countries are representative, our _sample of countries_ is not. Although these eight countries are located in all six regions into which the World Bank routinely divides the developing world, they are not random draws.<sup>6</sup> They are countries where there was an early interest in (and the data required for) constructing a poverty map. Second, we use national, rather than international, poverty lines. This has the advantage that poverty is measured in the terms which each particular country’s residents feel is appropriate.
|0.035|70|(13)|-0.446|***|0.038|26|(3)|-0.546|***|0.026|
|North America|81|(2)|-0.511|**|0.034|32|(1)|-0.564||0.000|49|(2)|-0.501|**|0.024|
|South Asia|48|(7)|-0.535|***|0.053|47|(7)|-0.534|***|0.054||||||
|Sub-Saharan Africa|196|(45)|-0.386|***|0.037|193|(45)|-0.385|***|0.037|3|(2)|-0.586|**|0.041|

**Notes:** The gap is estimated as the proportional difference (per cent) of survey means with respect to national accounts means. It is estimated as the ratio of per capita survey mean over the per capita national accounts mean, minus one. A negative (positive) gap estimate indicates that surveys means within the sample are smaller (larger) than national account means. Number of countries in each group given in parenthesis. Robust standard errors clustered at the country level (based on sandwich estimator). Statistical significance from zero, denoted by *p < = .1, **p < = .05, ***p < = .01. Each country is given equal weight within each sub-sample/group estimate, regardless of the number of observations for the country. Additional estimates with alternatives weights are available in Appendix 2. The column labelled “All surveys” pools consumption and income surveys. Due
distributed. Drawing on World Bank data and the 2007 CWIQ Survey, we use a Gini coefficient of 52.6 and an initial headcount poverty rate of 63.8% (World Development Indicators 2010; Backiny-Yetna et al. no date, p. 8). By 2012, the poverty rate is simulated to have declined to 60.2%). We report on the sensitivity of poverty outcomes to a decline in the Gini coefficient to a gradual decline such that, by 2030, it has fallen to the current world-wide average of 40.9.<sup>22</sup>

> 22  It is widely accepted that a log-normal distribution provides a good approximation for within-country income and consumption distributions (Bourguignon 2003; Easterly 2009).  Inter alia, as noted by Easterly (2009, pp. 28-29), (i) empirical cross-country analysis indicates that the higher the initial poverty rate, the lower the poverty elasticity of growth, and (ii) the absolute value of the simulated poverty-elasticity of growth with a log-normal distribution is inversely related to the initial poverty rate and positively related to per-capita income.  The average of the most recent Gini coefficient for all 124 countries with data for the period 2000-2008 was 40.9 (World Development Indicators, December 15, 2010).

39
Carolina, Chapel Hill. The RLMS is a panel survey with annual data available starting in 1994 and is representative at the national level. Data are available through 2016 which maintained a sample size of 7,000 households. The survey includes very detailed information on health status, household expenditure and service utilization, as well as community-level data.<sup>7</sup> The Russian Labor Force Survey (LFS) is a sample survey of the population on the labor market. The survey is conducted by Rosstat on a quarterly frequency and is representative at the regional level. A sample of approximately 65,000 people between the ages of 15 and 72 years is surveyed. Microdata are publicly available for the period covering 2010-2015.

The Life in Transition Survey (LiTS) was originally developed to capture how transition affected the lives of people and how it shapes their views on democracy and the role of the state. It was conducted jointly by the EBRD and the World Bank in 2006, 2010 and 2016. The surveys are

> 6 (Lehmann H. &., 2007) shows for the case of Ukraine that using a productivity-based definition can introduce large measurement errors in transition economies.

> 7 The RLMS survey data and documentation are publicly available at: <u>https://www.hse.ru/en/rlms/downloads</u>

8/67 Informal Employment and Worker’s Wellbeing in Russia
Table S.9: Channels - Proportion of ex-combatant households owning a shop

||_Shop k_|_eepers_||
|---|---|---|---|
||2006|2010|p-value|
|CNDD+|0.558|0.307|0.292|
||(0.287)|||
|FNL|0.12|0.448|0.126|
||(0.126)|||

_Notes:_ Authors’ analysis based on data described in the text. Clustered-robust standard errors are in parentheses. Outliers are excluded (as explained in appendix). Sampling weights are accounted for. For household ex-combatants belonging to each group, the _p_ -value corresponds to a test of equality of means of the share of kiosk owners between both surveys.

# **Appendix B. Online Appendix - The Construction of Variables of Interest**

# _Appendix B.1. The Construction of Consumption Aggregates_

In this appendix, we describe how we cleaned the data and constructed the relevant consumption aggregates for our analysis. First, we introduce the construction of the reference price vector and the local price vectors associated with each household. Second, we explain in detail how we corrected typing mistakes, how we treated missing and vague information, and how we dealt with outliers. Finally, we describe the construction of our main consumption measure which is a consumption aggregate per adult equivalent calculated using constant prices.

_Appendix B.1.1. Prices_ Prices faced by households are crucial in each stage of our analysis. First, in the data cleaning process, prices are an important to fill missing information as well as to detect and correct outliers. Second, in the construction of consumption aggregates, prices are used to make consumption data comparable across space and time. Following Deaton and Zaidi (2002), the harmonization of consumption data is done by scaling consumption values by a Paasche index of prices. Finally, finding a
the region (i.e. Brazil). Hall et al. (2004) for instance document the role of many Asian companies in Asia, alone or in partnerships with OECD companies (Veolia, Ondeo/Suez and Thames). From Hong Kong, Citic Pacific, NWS Holding, China Everbright and China Water are all active in the Chinese market. In Malaysia, Pucak Niaga, Ranhill Utilities and Taliworks Corp are three of the larger water and sanitation companies in the country. Other Malaysian companies such as Pilecon, PPB/Keery Utilities, PBA Holdings Berhad and Salcom are mostly active in China.

> 13 Bechtel is probably the only major actor missing from this list but we did not have enough information to include it.

> 14 Missing from the report are the British Biwater and the Dutch Ne-on who often team up as consortia during the 1990s in particular in East Asia.

> 15 The information available on OPPs includes urban and country population covered by these OPPs in each country together with the number of these firms per country. Therefore, it is not possible to compute the market share of each OPP. However, to compute the CRm, this information is not required since the aggregate market share and the number of the OPPs per country is enough.

16
privatized firms perform better than state firms because they were simply better firms to begin with (and were perhaps privatized for this reason) -- is an important element of our argument that privatization leads in short order to dramatic improvements in performance. To evaluate the presence of selection bias, we test for the equivalence of the pre-privatization performance of sample firms; to verify the subsequent divergence of performance, we apply the same test to the post-privatization data. Both tests involve re-estimation of equation (1) for those firms only for which complete pre- and postprivatization data are available. This allows us to deterrnine whether the _same_ privatized firms that were outperforming state firms after privatization were also outperforming the _same_ state firms prior to privatization.<sup>7 0</sup> To verify that state and privatized firms were in a similar initial "shape," we assessed the excess of revenues over variable costs (labor and materials.) Within the limits of our data, a higher 70 The tests rely on a substantially smaller number of firms: in comparing the pre- and post-privatization performance of the same firms, we can use only finns privatized in 1991 and 1992 (since we had not asked for preprivatization data for firms privatized in 1990) and, among those, only firms that provided data on both pre- and postprivatization performance. The small number of such finns (10 finrs privatized in 1991 and 19 firms privatized in 1992) necessitates grouping of the two "vintages." This, in turn, creates a problem of choosing the demarcation line between the pre- and post-privatization periods for the entire group. In the event, we decided to use 1990-91 as the pre-privatization period and 1992-93 as the post-privatization period, with 1991-92 excluded from the equations. If anytiing, our choice tilts the results in favor of the selection bias hypothesis. Given the already observed quick impact of privatization, one would expect privatized firms to improve their performance somewhat in the year of privatization. Hence, including 1991 in the pre-privatization period for
# **5. Village-level variation in radio access and bed-nets distribution**

The analysis that follows examines two hypotheses. First, if radio access enhances government responsiveness, households with better access to community radio should be able to obtain more bed nets from government distribution programs, particularly free bed nets, than households without. Second, if radio access changes household behavior and increases household demand for and valuation of bed nets, then we should, in principle, see an effect on the prices paid and quantity of bed nets reported by households. However, in the institutional setting in Benin higher-level government officials decide the quantity of bed nets available in a village. We expect local-level media to have little effect on the decisions of these officials, and therefore little effect on the quantity of bed nets supplied locally.

Instead, if radio access increases household demand supply effects should be largely confined to pricing decisions, over which local officials have control. In particular, local officials should sell bed nets that they could otherwise distribute for free in areas with greater radio access. The second hypothesis, then, is that greater radio access will have a positive effect on the number of paid government bed nets that households report and no effect or a negative effect on the number of free government bed nets they report. Because higher level officials responsible for allocations are less responsive to local media, and because the private market in bed nets is small, greater radio access should have no effect on total bed nets in the household.

The Benin data lend themselves especially well to tests of the effects of media access on government accountability, the first hypothesis, since we not only know household access to media, we also know the content of media programming. Prior research has examined the reduced form effects of media access on government transfers, implicitly suggesting that these effects arise because media raises awareness of the transfer program: whether a program exists, eligibility for the program, how one gains access to program benefits, and when those benefits are available. Accountability