rafmacalaba/datause-encoder-data huggingface dataset:
for three arbitrary cut point values (0.3, 0.5 and 0.6), revealing that in correspondence to a low cut point we obtain a very high coverage rate but also a high leakage rate.

In particular, the central panel of Table 2 shows that, using a poverty line of 50 JD and a 50 percent threshold, the model would be able to predict correctly if an individual is poor 90.4 percent of the time, which implies that 9.6 percent of the time the model would predict poor individuals as non-poor (undercoverage rate or exclusion error). The model would also predict correctly if an individual is non-poor 61 percent of the time, which means that 39 percent of the time the model would predict as poor nonpoor individuals (leakage rate or inclusion error). Evidently, the first type of error (under-coverage) is more problematic from a policy and welfare perspective, whereas the second type of error (leakage) is more problematic from a budget perspective.

The first and the last panels repeat the exercise with a probability threshold of 30 percent and 60 percent, respectively. In the former case, the under-coverage rate improves (2.9 percent) while the leakage rate worsens (62.4 percent). In the latter case, the under-coverage rate worsens (15.6 percent) while the leakage rate decreases considerably (28.8 percent). Clearly, changing probability threshold affects targeting results. Hence, it is important to fine tune the parameter related to the probability threshold to obtain results the closest as possible to the error we want to minimize (under-coverage or leakage).

**Table 2 - Coverage and Leakage rates for different choices of cut point**

|||**Ob**|**served poor**||
|---|---|---|---|---|
|||**no**|**yes**|**Total**|
|||_cu_|_t point 30%_||
||**no**|37.64|2.92|13.59|
||**yes**|**62.36**|**97.08**|86.41|
|||_cu_|_t point 50%_||
|**Predicted poor**|**no**|61.01|9.59|25.39|
||**yes**|**38.99**|**90.41**|74.61|
|||_cu_|_t point 60%_||
||**no**|71.20|15.63|32.71|
||**yes**|**28.80**|**84.37**|67.29|

Source: Authors’ estimations based on Jordan UNHCR data.

13
Page 52

# Discrimination and Disadvantage in the Labor Market

117. Discrimination and disadvantages in education and experience impede women's labor force participation, inhibiting overall economic production (Anker and Hein 1986) Discrimination may appear as rationed access to labor markets for particular groups -- including women -- or as lower wages for similar work. Women everywhere tend to be overrepresented in the less skilled, less mechanized, lower paying lines of work (see box from Schumacher 1980) (Anker and Hein 1986). Apparent differences in the patterns of men's and women's formal labor force participation in many countries do not necessarily imply discrimination. Women' s work choices may differ if they (or their families) place greater value on caring for their children themselves and on home-based work (Schultz 1989, Schumacher and others 1980). But considerable evidence from both industrial and developing countries suggests that discrimination and/or disadvantage exist and tend to lock women into fewer, more menial, and less remunerative lines of work (Anker and Hein 1986; Levy 1988). This has obvious implications not only for equity but for economic performance over time.

BOX: 14 Female Participation in the Labor Force in Bogota. Colombia A study of the Bogota labor market in the late 1970s revealed the effects of two decades of sustained economic growth. Unemployment rates had fallen, and female participation in the labor force had risen. In this tight labor market, the labor force component most likely to expand rapidly with rising real wages was that of m&rried women.

For unmarried females, most of the explanatory variables were not significant -- except widowhood and household headship. Clearly, these women had little choice: they had to work to support their families. This finding may be of particular relevance for the 1980s as the economic downturn appears to have been accompanied by a sharp increase in female household leadership.

The study concluded that unmarried women (wieows, divorcees, never married) behave much more like primary workers (somewhat like prime age men), while married women behave more like secondary workers, exhibiting a strong price elasticity of labor supply. This suggests that married women had more choice about whether to work than men or unmarried women.

Overall, the study found that in a tight labor market female labor force participation was determined far more by life cycle and competing home activity considerations than by labor market/career aspirations, despite a strengthening of the education system and almost equal investments in men's and women's education.

Source: Mohan 1985
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-31-

set in an amount both to encourage the widest competition and to discourage less than serious bidse; (ii) the requirement that the CA shall publish in the official govermnent journal or newspaper a brief description of the areas to be subject to the bid tender, the proposed petroleum operations to be conducted (e.g. new exploration; development; enhanced recovery; workover) and instuctions for obtaining bid packages. The CA should also be given discretion both to publish similar such notices in domestic and foreign business and trade publications and to send them directly to bidders whom the CA believes may be intereste&;

- (iii) discretion to the CA to require prospective bidders to purchae geological and geophysical data, well logs or other proprietary information owned by the State concerning the area(s) subject to the bid tender. In such case, the Regs should require that the description and price of such bid package shall be inlduded in the notice to prospective bidders, discussed in (b), above.

Tho eWil to be prevented here Is "proaotion" by an appikcant which doesn't have eithr the fInancial or technical capabilities to fiulil the pioposed MWO. Too often, States new to the setor will award lenes to such companbs, under questionable circumstances, which such campanies will, In turn, seek to sell, assign or'arnn-ou n or most of their rights to an IOC at a signIficant profit, having made no real monetary or work expenditures. Whilb the Bank will not comment directly to a host State on the merits of any such license or PA awarded, t will seek, if requsted, to demonwstrate to the host State best practce in the se-ctor, as a comparison or benchmark.

25 ,Under Bank-financed PEPPs, In addition to broad, International trade publcation of Intended Icensing rounds by host States, such projects include a component for one or several promotion seminars for interesbd Industry companbs in the host State's capital city, as well as In International oil centers such as London, louston, Shngpore, etc.
Policy Research Working Paper 10429

# **Abstract**

Recent years have witnessed considerable methodological advances in poverty mapping, much of which has focused on the application of modern machine-learning approaches to remotely sensed data. Poverty maps produced with these methods generally share a common validation procedure, which assesses model performance by comparing subnational machine-learning-based poverty estimates with survey-based, direct estimates. Although unbiased, survey-based estimates at a granular level can be imprecise measures of true poverty rates, meaning that it is unclear whether the validation procedures used in machine-learning approaches are informative of actual model performance. This paper examines the credibility of existing approaches to model validation by constructing a pseudo-census from the Mexican Intercensal Survey of 2015, which is used to conduct several design-based simulation experiments. The findings show that the validation procedure often used for machine-learning approaches can be misleading in terms of model assessment since it yields incorrect information for choosing what may be the best set of estimates across different methods and scenarios. Using alternative validation methods, the paper shows that machine-learning-based estimates can rival traditional, more data intensive poverty mapping approaches. Further, the closest approximation to existing machine-learning approaches, using publicly available geo-referenced data, performs poorly when evaluated - against “true” poverty rates and fails to outperform tradi tional poverty mapping methods in targeting simulations.

This paper is a product of the Poverty and Equity 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 pcorralrodas@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
meeting startups. As part of Vilcap’s normal training program, trainee investors then continue to evaluate startups three more times, using standardized criteria.

In the second stage, we leveraged the panel dataset of trainee investors’ investment decisions and tested the effect of an additional treatment, added to the first treatment. We prompted treated investors to inquire about startups’ progress during the selection period. Using this panel dataset allowed assessment of whether gender disparities appeared at specific stages of the selection process (e.g., Botelho and Abraham 2017, Bohren et al. 2019).

To conduct the two-stage field experiment, we worked with Vilcap in eight of its investment training programs (two each in four regions – Africa, India, Middle East, and Latin America – allowing for one treatment and one control group in each region). Trainee and professional investors evaluated startups in these eight Vilcap programs. This resulted in a dataset of 31,714 evaluation scores. Our first stage leveraged the cross-section sample of 1,341 dyadic investor-startup decisions by investors made after the investor met a startup founder. This sample included both professional investors as well as trainee investors who were trained by Vilcap to allocate $320,000 to 16 out of 87 startups. The second stage leveraged the panel nature of the trainee investor dataset. We randomized investors into treatment and control groups, with a panel dataset of 1,530 decisions (from 510 investor-startup dyads over three time periods after the initial analysis we observed in the first stage). Both stages of the field experiment were pre-registered.

# **<mark>5. First Stage: S</mark> ystematizing Inquiry about Risk and Reward**

**5.1. Setting and Design.** We systematized how Vilcap prompted investors to inquire about

risk and reward in their evaluation template and assessed the impact on reducing gender disparities in continuing due diligence (H1), and the consistency of investor inquiry across startups (H2). Trainee investors met startups in a 90-minute welcome meeting where each startup founder was encouraged 15
37. For the interwar data available on the weight of foreign bonds in American banks' asset portfolios, see Eichengreen and Portes (1987), pp. 23-24.

38. Details on the Roca-Runciman convention and references to the surrounding literature may be found in Abreu (1984).

39. These plans are described in more detail in Eichengreen (1989).

40. Quotation cited in Eichengreen (1989), pp. 12-13.

41. See in paiticular the critique of Bulow and Rogoff (1988).

42. We imputed the quantity of buybacks from figures provided by the Council of Foreign Bondholders in its Annual Reports on the par value of issues still outstanding.

43. We offer more archival evidence to this effect, drawn from the records of the Council of Foreign Bondholders, in Eichengreen and Portes (1988a).

44. Council of the Corporation of Foreign Bondholders, Minutes, 17 December 1936. Emphasis added.

_45._ Council of the Corporation of Foreign Bondholders, Minutes, 14 March 1940.

46. Emphasis added. Council of the Corporation of Foreign Bondholders, Minutes, 14 December 1941.

47. Council of the. Corporation of Foreign Bondholders, Minutes, 31 May 1944.

48. U.S. Securities and Exchange Commission (1937).

49. Council of the Corporation of Foreign Bondholders, Minutes, 31 May 1937.

53
Penh, exporting firms, and those with poor access to formal finance suffered more losses of sales and falls in profits. The deeper impact on the profits for less productive firms suggests a well-functioning market where more efficient firms weather downturns better than less efficient firms. The mechanism at play is that less efficient firms had to cut output prices to maintain market shares since they could not compete on quality, hence leading to a deeper impact on profits.<sup>5</sup> Based on the CRBS 2009 survey, an estimated 4 percent of formal firms went bankrupt since the previous ICS 2007/2008 survey, with another 5 percent closing for seasonal or other reasons (weighted figures). The large number of bankruptcies is at odds with the lack of formal processes to close a business (in the “Doing Business” publication, Cambodia ranks 149 out 183 of countries in the ‘resolving an insolvency’ indicator, World Bank, 2011)). This suggests that a number of firms closed without due process (and with some overdue wage payments). In the garment sector, the likelihood of bankruptcy was 18.5 percent.<sup>6</sup> In columns (5) and (6) we report the marginal effects from a descriptive Probit regression for the probability that a firm went bankrupt between the 2007/2008 and 2009 surveys. Tourism businesses and more productive firms were less likely to go bankrupt, but larger firms were, surprisingly, more likely to go bankrupt. The higher bankruptcy rate for less efficient firms again suggests a well-functioning market. Firms relying more on informal finance were less likely to go bankrupt than firms relying on, especially, trade credit (which typically would be from suppliers or buyers, and hence disrupted by the crisis).

To put these data in perspective, we compare them to similar data from other countries (Table 3). Correa and Iootty (2010) collected data for 6 countries in Eastern Europe, using a similar survey methodology with a rapid firm survey following a larger survey the year before. The data show that in terms of sales all countries were strongly affected by the global financial crisis. In Cambodia, the percent of firms closed (3.9%) and declines in sales (-30.7%) were relatively high although not the highest. The employment impact in Cambodia has been limited, with relatively few firms (16.6%) reducing their number of permanent workers.<sup>7</sup> However, in terms of total change in employment (-0.8%), employment growth was only lower in Lithuania.

> 5 We have run similar regressions for changes in output prices and find that firms in the bottom tercile of the productivity distribution cut their prices by 4% relative to firms in the top two terciles of the distribution. 6 Weighted figure. This is in line with Ministry of Commerce data, showing that the number of factories declined from 308 in June 2008 to 257 in June 2009 (a fall of 16.3 percent; personal communication to the authors).

> 7 Alternatively, the labor market adjustment could have been made on the wage side in Cambodia. However, survey data do not support that view.

8
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At the country level, financial inclusion can boost efficiency of financial intermediation, through intermediation of greater amounts of domestic savings, and thus improve soundness of investment financing and investment cycles. Provided that quality financial infrastructure and competent supervision are implemented, such improvement will, in turn, produce both greater economic and financial stability (Prasad, 2010; Cull et al., 2012).

The paper proceeds as follows. Section two discusses some stylized facts. Section three explains the employed regression model and estimation approaches. Section four describes the data used for estimation of the regression model. Section five discusses the baseline regression results for the entire sample of 95 countries, along with a robustness analysis using the robust regression approach, and an alternative access to deposit proxy together with a GMM estimator. Section six presents and discusses differences in the model’s estimates across HICs, MICs, and LICs, and reports related robustness tests. Section seven concludes and offers some policy implications.

# **2. Some Stylized Facts**

In this section, we preview some stylized facts about the main variables of interest, i.e. bank deposit growth around the 2008 global financial crisis and access to bank deposits before the crisis. The preview motivates some choices that we make for our regression analysis, and further illustrates the extent of heterogeneity in deposit growth and access to deposits across country income groups.

**Figure 2: Global Growth of Bank Deposits During 2005-2010**

<!-- Start of picture text --> 35<br>1st quartile median 3rd quartile<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>2005 2006 2007 2008 2009 2010<br><!-- End of picture text --> Source: Authors’ calculation based on deposits data from IMF’s FAS database. Note: This figure displays the year on year percentage growth rate of outstanding deposits of commercial banks in national currency calculated for 173 countries.

Consider the global growth in bank deposits first. Figure 2 shows that the median growth in bank deposit across countries dropped significantly from 2007 to 2009 by about 9 percentage 5
ucation with financial investment in the education production function of children. This complementarity may reflect peer and role model effects in addition to more efficient investment by educated parents, and can give rise to a convex CEF. Unlike the standard linear model, relative mobility in our model depends on parent’s schooling level, and the urban and rural relative mobility curves can cross. The approach developed in this paper is of wider interest as it can be applied to household survey data from other developing countries.

For the empirical analysis, we take advantage of the rich household panel data from the Indonesia Family Life Survey (IFLS) to make progress on two major issues highlighted in the literature: (i) truncation bias due to coresident sample, and (ii) omitted variables bias due to ability heterogeneity. An important data constraint on the analysis of intergenerational mobility in developing countries is truncation bias caused by coresidency restrictions in defining household membership in surveys (see Emran et al. (2018)). The IFLS data do not suffer from any significant truncation as the survey collected information on nonresident parents of any household member older than 15.<sup>9</sup> A second important advantage of the IFLS 2014 data used in this paper is that good quality measures of cognitive ability are available which allows us to control for ability heterogeneity across children in the regressions. Our main analysis of intergenerational mobility is based on the 18-40 years old children in the 2014 wave of IFLS who went to school in the 1990s and 2000s. We use the earlier rounds of the panel data (1993, 1997, 2000, 2007) to understand the effects of parent’s education on financial investment in children’s schooling. Another important part of our empirical analysis is the estimates of returns to education at the household level in rural vs. urban areas.<sup>10</sup> The availability of 5 rounds of panel data on household consumption expenditure allows us to provide estimates for both the parental and children’s generations.

The main conclusions from the empirical analysis are as follows. First, the CEF is convex in both rural and urban Indonesia, rejecting the work-horse linear model used in the existing literature. The estimates of relative mobility show contrasting rural-urban pattern:

> 9For a discussion on the advantages of the IFLS data for studying intergenerational mobility in Indonesia, see Mazumder et al. (2019).

> 10The returns to education here relate to a household’s permanent income, not only the labor market returns in a given year as is the case in the Mincerian literature. See below the discussion in section (6.1).

3
colonies in Western Africa which formed the West African Monetary Union in 1962 and immediately established public credit reporting following the French example. Also several Middle Eastern and North African nations adopted PCRs in the 1950s and 1960s - Egypt (1957), Tunisia (1958), Morocco (1966) and Jordan (1966), and Turkey (1951).

In Latin America, Mexico’s PCR is the oldest, established in 1964, with a primary aim related to the policy of directing credit by sector at that time. While a few Latin American countries established PCRs in the 1970s and 1980s, the phenomenon really took off in the 1990s, when ten further PCRs were established in the region. Latin America was not alone, however, in the development of public credit registries in the 1990s – numerous countries in Eastern Europe and Asia developed PCRs over the last ten years. Moreover, many developing countries which do not currently have PCRs are debating their establishment including notably, China and Russia. Table 1 in the Appendix provides basic information on countries with PCRs organized by region.

We now turn to a more detailed analysis of the PCRs that we use for the empirical analysis in the following section. Although Mexico’s PCR was established for other motives, its main objective today is to provide data for banking supervision and economic analysis. Having said that, the registry also distributes information on individual borrowers to banks. In line with these objectives, the Mexican PCR focuses on larger loans that pose a major risk to the financial system; data are only collected on credit exposures of US $20,000 or more and the primary concentration is commercial credit.

The PCRs in Argentina and Brazil were established in the 1990s in response to financial crises also with the primary goal of supporting banking supervision. Over time, though, these registries were transformed to also enhance the information to private financial institutions. The minimum loan size that banks must report was then reduced, increasing the scope of information provided to the financial sector. In Argentina, the PCR first focused on large loans in excess of US $200,000 (i.e.: 200,000 pesos at the 1:1 exchange rate of the early 1990s) but the minimum loan was reduced to only 50 pesos (US$50 before the 2002 devaluation and now about US$17.50). The Central de Risco run by the Brazilian Central Bank began operations in 1998 and has 5