rafmacalaba/datause-encoder-data huggingface dataset:
enhancing the overall impact on poverty, underscoring the need for comprehensive approaches to addressing financial hardship and income disparities.

**Figure 9. Simulated Performance and Poverty and Inequality Impacts of the MSA Scheme under Policy Scenario 1**

- **a. Simulated Coverage (% of decile in each decile)           b. Simulated Benefit incidence (% benefits allocated to each decile)**

<!-- Start of picture text --> 32.3<br>1<br>2<br>3<br>5.6<br>4<br>0.5 0.1<br>5<br>80.9<br> 1 2 3 4 5 6 7 8 9 10<br><!-- End of picture text -->

- **c. Simulated Generosity (benefits as % of MYPP) d.Simulated Inequality, poverty, and poverty gap impact**

<!-- Start of picture text --> 30.1<br>Marginal Contributions to<br>0.00<br>Inequality<br>Change in Poverty Gap 0.84<br>Marginal Contributions to<br>0.28<br>Poverty<br>0.4 0.0 0.0<br>1 2 3 4 5 6 7 8 9 10 Disposable<br><!-- End of picture text --> _Source: Own estimates using CEQ and Bulgaria SILC 2021_ _Note: MYPP refers to Market Income Plus Pensions. Deciles are income deciles. The marginal contribution is calculated by taking the difference between the inequality (or poverty) indicator without the transfer and with it. The marginal contribution is calculated by taking the difference between the inequality (or poverty) indicator without the transfer and with it. Marginal contributions to poverty are measured using at-risk of poverty lines (AROP), fixed at the baseline scenario before the reform was implemented._

**The changes in the heating allowance are particularly noteworthy in this scenario.** This is primarily because the higher threshold for the Monthly Social Allowance (MSA) now extends its coverage, allowing a more substantial number of households to access the benefit. As a result, the heating allowance's benefits become perceptible for households in higher income deciles, reaching up to the fourth decile when considering market income plus pensions (Figure 10, panel a).

**Notably, the distribution of these benefits is relatively equitable for the first three income deciles, ensuring that households across these groups receive similar levels of assistance (Figure 10, panel b).** At the same time, the generosity of the benefits demonstrates an increase, particularly for the first three deciles (figure 10, panel c). In the first decile, this increase exceeds 10% of the household's income, significantly boosting their financial well-being. However, despite the apparent pro-poor concentration of these benefits (as indicated by the negative concentration coefficient), the relatively low incidence or generosity of the heating allowance (equating to 0.26% of market income plus pensions) contributes to the lack of any significant change in income inequality. On the other hand, when considering its impact on poverty, this scenario exhibits a relatively modest marginal effect. Although the marginal contribution

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identified in the Mexican survey. In Chile, about 13% of the sample is considered rural<sup>20</sup> while in Mexico about 24% is rural.

In both countries, a significant percentage of youth in both countries are dropping out of school early and not working after age 18. In the survey, 29.9% of Mexican and 14.2% Chilean youth have dropped out of school prior to completing high school, but 41% of Chileans age 18 to 24 and 27.5% of Mexicans in the same age range are in school.<sup>21</sup> While 20 to 30% of Mexican and Chilean youth are inactive after age 18, 12.8% of Mexican and 6.7% Chilean youth are inactive before age 18.

Chileans have earlier and riskier sex than Mexicans. While only 13% of Mexicans age 15 to 17 report having had their first sexual experience, 27% of Chileans in this age group report the same. Chileans are 10 percentage points less likely to use condoms than are Mexicans, which reflects that 2.5 percent of Mexicans and nearly 4 percent of Chileans age 15-17 have had their first child. Marriage rates in Chile are less than one-third of those in Mexico for each age group.<sup>22</sup> In terms of the risk and protective factors at the micro-level, Mexican and Chilean youth report a high level of personal connections with someone. Mexican youth report a wide range of topics that they communicate with their parents about, from school and work to politics and religion. While Chileans report good relationships with their parents, ten percent of Chileans also note important relationships with other adults. On the negative side, six percent of Chileans have suffered abuse in the home and 8.5 percent report substance abuse in their homes.

Mexican youth tend to trust government institutions less than they trust local institutions. They feel that school quality is good on average, although half say they do not have access to health services. There is a connection to religious institutions as 21 percent of Chilean youth and 9 percent of Mexican youth attend church weekly, with 66 percent of Mexican youth attending church at least once in the past month.

Of the questions on individual risk/protective factors, more than 85 percent of Chilean youth are optimistic about the future, similar to rates in Brazil (Instituto Cidadania

> 20 The sampling was done in communities with at least 2000 inhabitants, so a rural indicator means that the respondent comes from a community with between 2000 and 5000 inhabitants.  An urban respondent lives in a community of at least 5000 people.

> 21 If there is no repetition, youth would finish high school at age 17 or 18 in both countries.

> 22 In Chile and Mexico, the legal age of marriage age is 18, but Mexican youth can marry as early as age 16 with parental consent.

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members on probability of marriage among men (column 3). Both results in Annex 1 and 2 suggest that not controlling for household and individual characteristics prior to the mortality shock may introduce bias in estimating the effect of a mortality shock on probability of earlier marriage.

# **Conclusions**

There are numerous channels through which increased adult mortality due to HIV/AIDS and other diseases could affect demographic behaviors. This paper investigates one such behavior: the probability of earlier marriage among young adults. By extending the existing research beyond schooling and health outcomes for children, this study provides new evidence on the demographic impact of increased adult mortality. Using panel data from Tanzania, the study examines the marriage outcomes of young adults who were followed from childhood for 13 years. The results show a large positive and statistically significant impact of a father’s death on the likelihood of marriage for women. This effect suggests that paternal orphanhood reduces the age of marriage among women between the ages of 17 and 23 years by 32 percent. For instance, while on average 58 percent of women are married by the age of 20, with the orphan effect this proportion increases to 75 percent. However, this impact varies substantially across girls from different backgrounds. Female paternal orphans most affected include girls from poorer households, from households whose primary source of income is farming, and girls who were not in school when orphaned. For young men, on the other hand, neither mother nor fathers’ deaths are associated with differential transition into marriage.

In contrast, while the death of a prime age adult has no impact on transition into marriage among women, the death of a prime-age female household member strikingly reduces the probability of marriage among men. For instance, while on average 54 percent of men are married by the age of 25, the effect of the death of a prime-age female household member reduces this proportion to only 35 percent.

Earlier marriage for young women who are orphaned is a cause for serious concern. Depending on trends in orphanhood rates in HIV/AIDS affected countries, this effect can undermine long-term trends towards delaying marriage observed in many SubSaharan African countries (see Mensch _et al._ , 2005). A shift to early marriage is 11
survey conducted in 2006 in Chengdu, Dalian, Shanghai-Pudong, Shenzhen, and Xi’an allows us to analyze the strengths and weaknesses of public service delivery systems from the citizens’ experience. It is worth noting the differences in the average annual income per capita among the five cities, ranging from RMB11,110 in Xi’an, RMB11,470 in Dalian, RMB12,700 in Chengdu, RMB18,600 in Shanghai-Pudong to RMB31,560 in Shenzen as reported by the survey. The survey suggested that income distribution was most unequal in Shanghai-Pudong (gini coefficient of 0.44), less in Shenzhen and Chengdu (both having gini coefficient of 0.41), and least in Dalian (0.36) and Xi’an (0.34). More detailed analysis follows below.

**Table 1 Five cities – many different outcomes in public service delivery (ranking in 2006)**<sup>**1**</sup>

||Chengdu|Dalian|Shanghai-<br>Pudong|Shenzhen|Xi’an|
|---|---|---|---|---|---|
|Annual income per capita|12,700|11,500|18,600|31,560|11,100|
|Income disparity - Gini coefficient|0.41|0.36|0.44|0.41|0.34|
|**_Health_**||||||
|Seeking care when sick|5|3|1|2|4|
|Overall satisfaction|1|3|4|5|2|
|Affordability of outpatient care for the poor|5|4|1|2|3|
|Affordability of inpatient care for the poor|5|4|2|1|3|
|Seeking care when sick among migrants|5|2|3|1|4|
|**_Education_**||||||
|Overall satisfaction|2|1|3|5|4|
|Affordability of primary education for the poor|4|3|1|5|2|
|Affordability of junior secondary for the poor|4|5|1|3|2|
|Satisfaction among migrants|2|1|4|5|3|
|Transparency and access to information|2|3|1|4|5|
|**_Water_**||||||
|Water taste and purity|3|2|5|4|1|
|Equity by residence status|2|4|1|3|5|
|Transparency and access to information|1|5|2|4|3|

1 Best performers are ranked 1, worst 5.

2 Out-of-pocket payments and fees paid by the poorest quintile relative to their income 14
- 10 -

# <u>Sample and Data Sources</u>

BCP compliance data come from assessments carried out by the IMF and the World Bank beginning in 1999. Some of these assessments are public information and can be found on the institutions’ websites. Others are kept confidential at the request of the country authorities. Moody’s financial strength ratings have been compiled from Bankscope database. Bankscope reports the current rating, the last date in which the rating was revised, and the rating that prevailed before then, but no other historical rating information. Since we need to roughly match the timing of the BCP rating with that of Moody’s ratings, we dropped from the sample banks that had a rating change after more than one year since the BCP compliance evaluation. Only a few banks fall in this category.

Bank-level variables have also been constructed from Bankscope, while macroeconomic variables are mainly from the IMF’s International Financial Statistics. Information about bank ownership is obtained from Bankscope and other miscellaneous sources. Banks are considered state-owned if the government has a controlling share or is the sole owner, and similarly for foreign-owned banks. Detailed variable definitions and sources are reported in Table 1 in the Appendix.

We use BCP assessment data for 39 countries for which we have bank ratings from Moody’s.<sup>9</sup> Not surprisingly, this group includes mostly developed countries and emerging markets, while low-income countries are not represented (Table 2). Some countries have only one or two banks in the sample, but since we are not relying on intra-country variation to

> 9 The BCP assessment data covers 67 countries, but only 39 of these countries have banks large enough to receive a rating from Moody’s.
Planning Institute of Jamaica (PIOJ) and Statistical Institute of Jamaica (STATIN), _Jamaica Survey of Living Conditions_ , various issues Psacharopoulos, George and Harry Patrinos (2004), "Returns to Investment in Education: A further Update," _Education Economics_ Rodriguez, Edgard R. and Erwin R. Tiongson (2001), "Temporary Migration Overseas and Household Labor Supply: Evidence from Urban Philippines," _International Migration Review_ , pp. 708-725 Statistical Institute of Jamaica (STATIN), _The Labor Force_ , various issues World Bank (2002), _Basic Information on Jamaica Survey of Living Conditions_ _________ (2005), _World Development Indicators_ _________ (2006a), _World Development Indicators_

- _________ (2006b), _The Development Impact of Remittances in Latin America_

- _________ (2006c), _Jamaica Poverty Assessment: Breaking the Cycle of Unemployment, Vulnerability and Crime_

Zarate-Hoyos, G. (2004), "Consumption and Remittances in Migrant Households: Toward a Productive Use of Remittances," _Contemporary Economic Policy_ 18
**Gender and Rural Non-farm Entrepreneurship**

Bob Rijkers<sup>1</sup> Rita Costa<sup>2</sup> Key words: gender, entrepreneurship, rural, Indonesia, Bangladesh, Sri Lanka, Ethiopia JEL codes: D13, D22, J21, J24, L25, L26, R30

# **Acknowledgements**

We would like to thank Klaus Deininger, Donald Larson, Josef Loening, Jack Molyneaux, Naotaka Sawada, and Mona Sur for their help in obtaining the data, and seminar participants at the 2011 World Bank Economists’ forum, Reena Badiani, Liang Choon Wang, Mary Hallward-Driemeier, Andrew Mason, Luis Serven, and especially Carolina Sanchez Paramo for helpful discussions and critical feedback. The views expressed here are those of the authors and do not necessarily represent the views of the World Bank, its Executive Board or member countries. All errors are our own.

> 1 MNACE, EPOL

> 2 HDNED, EDU
regression analysis, the dependent variable is defined as the difference between its post-treatment and pre-treatment values to get rid of fixed effects.<sup>8</sup> To obtain a fuller picture of SMEs’ financing options, we also look at several additional aspects of firms’ access to finance. _Line of credit or loan_ is a dummy variable with the value equal to 1 if the firm has some line of credit or loan from a bank, 0 otherwise. _Working capital financed by banks_ captures the proportion of a firm’s working capital financed by banks. _Fixed assets financed by banks_ shows the share of fixed assets funded by banks. _Required collateral_ is the share of loans of all loans for which collateral was required. _The collateral-to-loan ratio_ indicates how much collateral a firm must provide the bank for a loan of a given size.

_Basel Dummy Gest_ is our main explanatory variable of interest—the variable is equal to zero for all firms from (control) countries that did not implement Basel III. For firms from the treated group of countries, this variable takes a value larger than zero, depending on the gestation lag at the time of the first available Enterprise Survey after Basel III implementation—its maximum value is 1. The maximum difference between Basel III implementation and the post-treatment Enterprise Survey is five years, and the value of 1 is assigned in this case. The value of 0.8 is assigned in the case of four years, 0.6 for three years, and so forth. Defining the variable _Basel Dummy Gest_ in this way, we assume that it takes time until financial regulations fully affect SME financing. Alternatively, we employ a dummy variable for Basel III, with the value of 1 in the case of implementation and 0 otherwise. We discuss in the following section the source of our data on Basel III implementation and how we determine whether the country implemented Basel III.

Table 1 presents the summary statistics for firm characteristics, bank system indicators, and country and institutional variables. We observe that more than half of the firms report that they do not have a line of credit and have certain difficulties in accessing finance. The firms typically rely

> 8 Because access to finance is derived from the perceptions regarding financing obstacles, we examine to what extent these perceptions are related to more objective measures of access to finance, such as whether the firm has a line of credit, the proportion of fixed assets financed by banks, or the proportion of working capital financed by banks. We estimate an ordered logit model and find that the perception-based access is statistically significantly related to several (objective but more specific) measures of access to financing. Clearly, this exercise cannot provide a definite test of the accuracy of the commonly used measure of access to finance, but it suggests that the measure has certain links to more specific objective measures of SME financing. The regression results are available in table A.6 in the appendix.

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26

# Education

Govenmment expenditures on education average roughly 11 percent<sup>of total government</sup> spending in low-income and lower-middle-income developing countries.<sup>However, perhaps</sup> because of issucs surrounding equality of opportunity, rigidity in class structure,<sup>the extemal</sup> effects of human capital, and interest in increasing fees to finance secondary<sup>education, education</sup> has played a central role in the benefit incidence literature (for an early discussion<sup>of these</sup> issues, see Psacharopoulos, 1977). In particular, existing benefit<sup>incidence calculations offer</sup> important insights into the likely effects of reallocating governnent<sup>resources from higher</sup> education to primary or secondary education.

Several recent studies done for various developing countries examine<sup>the distribution of</sup> educational benefLts across income classes (see Table 3). Meerman (1979)<sup>for Malaysia and</sup> Selowsky (1979) for Colombia represent the best known studies, but Foxley<sup>et al. (1979) for</sup> Chile, Castenada (1989) for Chile, Riboud (1990) for Costa Rica, and Selden<sup>and Wasylenko</sup> (1992) for Peru also report benefit results for education. Additional benefit incidence<sup>studies for</sup> education include Jallade (1974) for Colombia, Dasgupta and Tilak<sup>(1983) for India, Meesook</sup> (1984) and van de WaUle (1992) for Indonesia, Hammer et al. (1992)<sup>for Malaysia, and Petrei</sup> (1987) for five countries in Central or South America.

All of these studies use household surveys to examine school attendance by household and allocate educational benefits to households based on the number<sup>of children in the household</sup> attending school. Most examine the distribution of benefits separately<sup>for urban and nural</sup> households, and in some cases for households in different size urban areas.<sup>Meerman also</sup> examines the benefits across races within Malaysia.

The studies typically find that benefits are pro-poor as a percentage of household<sup>income</sup> for primary and secondary education and pro-rich for post-secondary education.<sup>Indeed, benefits</sup> from primary and secondary education are often pro-poor when examined<sup>on a dollar basis, as</sup> well. The pro-poor incidence occurs due to the greater number<sup>of children in lower-income</sup> households. Thus, the results of these studies sunmarized in Table<sup>3 generally confirm the</sup> arguments of Psacharopoulos (1977) that expenditure on pnrmary education<sup>is pro-poor, while</sup>
The Effect of Male Migration for Work on Employment Patterns of Females in Nepal Michael Lokshin and Elena Glinskaya<sup>*</sup> _The World Bank_

**Keywords** : migration, remittances, gender, labor force participation, Nepal. **JEL** :  I31, O15, F22

> ***** Michael Lokshin, mlokshin@worldbank.org , Development Research Group; Elena Glinskaya, <u>eglinskaya@worldbank.org</u> , South Asia PREM. Both are at the World Bank, 1818 H Street NW, Washington, D.C., 20433, USA. The findings, interpretations, and conclusions of this paper are those of the authors and should not be attributed to the World Bank, its Executive Directors, or the countries they represent.
previous export spells in the same product category increases the probability that a later flow will survive by more than 50%. Moreover, the results suggest that exporting experience is product rather than market specific. A 100 percent increase in total exports of goods within the same 5 digit product category translates into a reduction of 17 percentage points in the hazard rate. The impact of industry specific and global exporting experience is weaker but not negligible. In addition, the size of the importer’s market for a given product also appears to matter.<sup>10</sup> Finally, we confirm the results of previous studies such as Blyde (2008) and Baldwin and Harrigan (2007) in finding that the economic size of both trading partners contributes to facilitating trade flow survival. A likely reason is that the number of possible matches between firms increases with the size of the two economies.

An interesting measure included in our model is the variable indicating whether the exporter already sells the given product to other countries within the region of the importer. The coefficient of 0.67 suggests that the regional nature of exporting experience should not be neglected. It appears that there are learning effects specific to the product and the importing regions that help exporters sustain their trade relationships. This complements the finding of Roberts and Tybout (1995) who show that experience matters for the initiation of trade flows as well. In conjunction with the general result that the intensive margin is crucially important for export growth, this finding suggests that exporters should not look too far when trying to expand exports of their products to additional markets and that existing exporters can assist new export flows by sharing knowledge and information about existing markets.

We also find evidence that both an initial overvaluation of the exporters’ exchange rate and higher exchange rate volatility during the initiation period of the export flow decrease hazard rates. This is in line with the idea that a trade flow that was initiated despite adverse initial conditions is initiated because the importer regards it as particularly promising. Moreover, a decrease in the exporter’s exchange rate during the lifetime of the trade flow implies that the importer’s purchasing power in the exporter’s

> 10 In the next section, we exclude observations with re-occurring spells from the sample.

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