rafmacalaba/datause-encoder-data huggingface dataset:
Table 1: Raw probability of enrollment in secondary school/madrasa by gender and primary school type

|Primary<br>school<br>attended|Female||Male||Female<br>madras|,<br>a|Female<br>school|,|Male,<br>madrasa|Male,<br>school||
|---|---|---|---|---|---|---|---|---|---|---|---|
||Mean|sd|Mean|sd|Mean|sd|Mean|sd|Mean sd|Mean|sd|
|**Government**|0.65|0.48|0.66|0.47|0.49|0.50|0.68|0.46|0.42 0.49|0.73|0.45|
|**Private/aided**|0.19|0.39|0.19|0.39|0.13|0.33|0.20|0.40|0.12 0.33|0.21|0.41|
|**Madrasa**|0.04|0.19|0.06|0.24|0.17|0.38|0.01|0.07|0.26 0.44|0.01|0.10|
|**NGO**|**0.09**|**0.28**|**0.04**|**0.19**|**0.09**|**0.28**|**0.09**|**0.28**|**0.03 0.18**|**0.04**|**0.19**|
|**Secondary**||||||||||||
|**school**|0.03|0.18|0.04|0.19|0.11|0.32|0.01|0.11|0.14 0.35|0.01|0.08|
|N|5273||3202||1057||4216||696|2506||

Source: Author’s calculation based on sample survey data.

The finding that NGO school graduates make up for a significant fraction of secondary school students today is an important finding: it suggests that a good number of female students who studied in NGO-run primary schools continue into secondary education. But the fact that NGO school graduates today penetrate madrasas and schools pari passu is important considering the fact that madrasa and NGO schools pursue conflicting ideologies and just a decade ago secondary madrasas were seldom open to female students. As a matter of fact, greater NGO school activities could have created pressure on nearby secondary madrasas in the community which have historically catered to boys only to open up and absorb female students. Prospect for such vertical externality is high because NGOs and Islamic faith schools both serve marginalized communities where provision for state aided education is relatively scarce. Despite similar motives, NGOs and Islamic schools in Bangladesh operate in different levels of the education system. NGO schools are exclusively concentrated in the primary sector whereas the registered madrasas operate in both primary and secondary sectors<sup>9</sup> . Therefore, while BRAC run schools compete with primary madrasas for students, their presence in the community can create significant externalities for secondary madrasas. Moreover, given that BRAC schools primarily cater to female students, any potential spillover effects on religious schools will have to operate through enrollment of female students in madrasas. If so, evidence of such externalities has important policy implications as promoting female education and closing gender gap in secondary enrollment is a key MDG target.

To formally, test this proposition, we need data on enrollment in madrasas across villages with and without NGO schools along with information on when the NGO school was set up. In the absence of such data, we test this proposition by looking at female enrollment data (aggregated at school level) and see how this correlates with the presence of BRAC schools in the community. This is discussed in the next section.

> 9 There are about 6000 primary registered madrasas as opposed to 8404 secondary madrasas in Bangladesh.

7
<!-- Start of picture text --> Table A29: Reporters Without Borders Press Freedom Index (RSF)<br>Data Provider Reporters Without Borders<br>Description International nongovernmental organization headquartered in Paris, France, devoted to the<br>protection of reporters and respect of press freedom.<br>Website www.rsf.org<br>Data Source Worldwide Press Freedom Index<br>Type Expert assessment<br>Respondents Reporters, researchers, legal experts and press freedom advocates in assessed countries<br>Frequency Annual since 2002<br>Coverage Global sample of countries<br>Public Access Yes<br>Description The press freedom index is based on a 50-question checklist on the incidence and severity of<br>restrictions on reporters and the media<br>2008 2007 2006 2005 2004 2003 2002 2000 1998 1996<br>Voice and Accountability<br>Press Freedom Index<br>X X X X X X X .. .. ..<br>Political Stability and Absence of Violence<br>NA<br>.. .. .. .. .. .. .. .. .. ..<br>Government Effectiveness<br>NA<br>.. .. .. .. .. .. .. .. .. ..<br>Regulatory Quality<br>NA<br>.. .. .. .. .. .. .. .. .. ..<br>Rule of Law<br>NA .. .. .. .. .. .. .. .. .. ..<br>Control of Corruption<br>NA .. .. .. .. .. .. .. .. .. ..<br>Country Coverage 170 166 166 165 165 164 138 .. .. ..<br>Year of Publication 2008 2007 2006 2005 2004 2003 2002 .. .. ..<br><!-- End of picture text --> 68
# Remittances and Natural Disasters: Ex-post Response and Contribution to Ex-ante Preparedness

## 1. Introduction

The literature suggests that migrant remittance flows increase in the aftermath of natural disasters, macroeconomic or financial crises, and act as a safety net for households that have migrants abroad (World Bank 2006).<sup>1</sup> While there is anecdotal evidence and a number of case studies on this phenomenon, there is little empirical evaluation of the relationship between remittances and natural disasters (see next section for literature survey). In this paper we examine three inter-related questions: (1) How do remittances respond _ex-post_ to natural disasters? (2) Do remittances help recipient households to maintain consumption expenditure in the aftermath of disasters? (3) Are remittancereceiving households _ex-ante_ better prepared for disasters such as earthquakes and floods?

We use cross-country macroeconomic data to examine the ex-post response of migrant remittances to natural disasters for a large sample of developing countries, income groups and geographical regions to examine the hypothesis that remittances respond in a countercyclical (compensatory) manner to natural disasters in the recipient economies.

This paper also relies on micro-level household survey data for several developing countries (Bangladesh, Burkina Faso, Ethiopia and Ghana) to understand how remittances sent by migrants residing in high-income and developing countries contribute to _ex-post_ disaster relief for the affected households, and to _ex-ante_ preparedness against future natural disasters.

To briefly summarize the results based on the different hypotheses tested for the cross-country data and the household surveys from four countries, we find the following. First, remittances increase in response to natural disasters in countries that have a larger emigrant stock as a share of the home country population. Second, in the period after a flood in Bangladesh in 1998, per capita household consumption was higher for households that receive remittances, even after controlling for the possibility that these households may be self-selected. Third, international remittance-receiving households in Burkina Faso and Ghana, especially those that receive remittances from high-income

> 1 There are about 200 million international migrants. A large share of these international migrants or about 156 million people are from developing countries (Ratha and Shaw 2007). Migrants from developing countries sent home an estimated $305 billion in officially recorded remittances in 2008, with these flows larger than official aid and foreign direct investment in many developing countries.

2
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developing countries’ energy projects for private investors.

**Table 16** <u>SYS-GMM parameter estimates</u>

|Variable|Coefficient|Std error|
|---|---|---|
|_lag(privinvt)_|.6671741***|.0380519|
|_growth_|.5274156**|.2763148|
|_bsdev_|.2763148|48.84709|
|_cmdev_|157.4972***|65.3211|
|Obs.|307||
|Fisher test|F(4, 28) = 82.99***||
|Arellano Bond test - Order 1|-2.40***||
|Arellano Bond test - Order 2|0.01||
|Hansen-J|chi2(29) = 21.73||
|Dif-Hansen|chi2(15)= 5.41||

**Table 17** <u>SYS-GMM parameter estimates</u>

|Variable|Coefficient|Std error|
|---|---|---|
|_lag(privinvt)_|.6331002***|.0778513|
|_growth_|.3317886*|.2178169|
|_bsdev_|-32.67342|46.29378|
|_cmdev_|160.1594***|65.28836|
|_indepreg_|306.9391*|182.6289|
|Obs.|307||
|Fisher test|F(5, 28) = 18.41***||
|Arellano Bond test - Order 1|-2.23***||
|Arellano Bond test - Order 2|0.01||
|Hansen-J|chi2(25) = 23.67||
|Dif-Hansen|chi2(13)= 7.97||

# **9. Conclusion**

This paper has set the objective of empirically investigating the determinants of private investment in developing countries’ power projects, seeking to emphasize the importance of economic growth and financial sector development, using dynamic panel model specifications and accounting for some institutional and risk factors that may influence the private sector’s investment decisions.

Our study of a time-series-cross-sectional data set on 37 developing countries from 1990 to 2007 unambiguously demonstrates that economic growth is a key determinant to private investment in 22
**Table 6: Decline in thresholds relative to world GNI per capita (current US$, Atlas method),**

**FY84‒FY16**

|Bank fiscal year|1978|1984|1989|1999|2009|2016|
|---|---|---|---|---|---|---|
|Calendar year of data|1976|1982|1987|1997|2007|2014|
|**Upper bound thresholds for income groupings, GNI per capita**|||||||
|Low|250|410|480|785|935|1,045|
|Lower middle|..|1,670|1,940|3,125|3,705|4,125|
|Upper middle|..|..|6,000|9,655|11,455|12,735|
|World GNI per capita|1,623|2,567|3,290|5,491|8,294|10,779|
|**Ratio of threshold to World GNI per capita**|||||||
|Low|0.15|0.16|0.15|0.14|0.11|0.10|
|Lower middle|..|0.65|0.59|0.57|0.45|0.38|
|Upper middle|..|..|1.82|1.76|1.38|1.18|

_Source_ : http://siteresources.worldbank.org/DATASTATISTICS/Resources/OGHIST.xls, World Bank (1978), and _World Development Indicators_ , accessed November 30, 2015 (series NY.GNP.PCAP.CD) In recent years, inflation rates in many countries have tended to be higher than in those countries included in the SDR. It can perhaps be argued that the inflation adjustment factor (that is, the SDR deflator) does not fully reflect inflation experienced by low and middle income countries, resulting in thresholds that are too low and push countries into higher income groups prematurely. For instance, between 2000 and 2011, the adjustment applied to the thresholds on the basis of the SDR deflator was 36 percent. During the same period the change in the G20 GDP deflator was about 57 percent (in US dollar terms), while the comparable US dollar GDP deflator for the world increased 60 percent.

Furthermore, when the SDR deflator was first used for the operational guidelines in 1983, the economies represented in the SDR made up 56 percent of world GNI (using exchange rates as conversion factors). By 2012 their share had fallen to 51 percent, and the trend has been downward.<sup>15</sup> The decline would likely be sharper if the SDR basket had not been expanded to include the Euro in 1999. In other words, the countries used to calculate the SDR deflator have

> 15 Source: _World Development Indicators_ , accessed May 30, 2014 (series NY.GNP.MKTP.CD).

25
# **II. Deposit Insurance and Financial Depth: Correlations**

At the simplest level, it appears that those countries that adopted explicit deposit insurance from 1980-95 enjoyed slightly higher growth in financial depth than those that did not (Table 1). In the three years after the inception of an explicit program, the average increase in the ratio of M2 to GDP (M2/GDP) was 2.6%. For quasi-money to GDP (QM/GDP), the average increase was 1.9%. The average three-year changes in M2/GDP and QM/GDP for those countries that retained implicit schemes from 1980-95 were both 1.8%. The higher M2/GDP figures for countries with explicit programs do appear to be influenced by a handful of observations. The median three-year increase on that measure for b6th "explicit" and "implicit" countries was 0.8%. However, for QMIGDP, perhaps a purer indicator of financial development because it does not include MI, the median change was 1.8% for explicit countries and 0.9% for implicit ones.

**Table 1: Post-Deposit Insurance Changes in Financial Depth 1980-1995**

|**Statistic**<br>i_________________|**Average Change**<br>**(Three Years After**<br>**Insurance E**<br>Explicit5|**in M2/GDP**<br>**Explicit Deposit**<br>**nacted)**<br>Implicit <sup>6</sup>|**Average Ch**<br>**Quasi-Mone**<br>**(Three Years After E**<br>**Insurance E**<br>Explicit|**ange in**<br>**y/GDP**<br>**xplicit**<br>**nacted)**<br>Impl|**Deposit**<br>icit|
|---|---|---|---|---|---|
|Mean|+2.6%|+1.8%|+1.9%||+1.8%|
|Median|+0.8%|+0.8%|+1.8%||+0.9%|
|Standard Dev.|9.6%|2.6%|4.1%||2.0%|
|Minimum|-8.7%|-2.5%|-7.1%||-0.8%|
|Maximum|+32.1%|+9.4%|+8.7%||+6.4|
|Observations|15|29|1 5||31|

- 5 Includes only those countries that adopted explicit insurance from 1980-95. More pronounced differences between implicit and explicit countries are evident when those countries that adopted explicit insurance prior to 1980 are included in the calculations.

- 6 For those countries that maintained implicit deposit insurance (the control category), changes in financial depth were first calculated over all possible three year periods from 1980-95; those threeyear figures where then averaged.

6
<!-- Start of picture text --> 300 292<br>Small (< 50 people)<br>250 226<br>205 Medium (50-100 people)<br>200 Large (>100 people)<br>150<br>94<br>85<br>100<br>62<br>50<br>2<br>0<br>Number of brick kilns<br><!-- End of picture text -->

**Figure 4. Number of brick kilns by size (people engaged) and province** Source: ILO et al. (2020)

At the province level, the estimated total brick production costs also vary widely, ranging from a high of NRs 46 per brick (TK) in Bagmati province to a low of NRs 15 per brick (VSBK) in Gandaki and Sudurpachim provinces (Table 3). However, the brick production cost ranges from commonly used FC BTK and ZZK across the provinces do not vary much, ranging from high NRs 20 per brick in Bagmati province to a low of NRs 15 per brick in Gandaki and Sudurpachim. Several factors contribute to variations in the cost of brick production across the provinces. For example, in Bagmati province, which includes Kathmandu Valley, coal prices, labor costs, and land rental costs are much higher than in other provinces, even though the average weight of the brick produced in the Bagmati province is relatively lower than in other provinces (Figure 5). Most of the brick kilns in Koshi, Madesh, Lumbini, and Sudurpachim provinces are in the plain terrains and close to the Indian border, and they have easy access to coal (imported from India) and Indian skilled labor ( _Mistri_ ). These factors contribute to a relatively lower cost of brick production compared to brick kilns in Bagmati provinces with the same kiln technology. The average cost of energy (coal) ranges from 38% to 56% of the total costs, with a higher range in the eastern region and a lower range in the western region of the country. In Bagmati province, the average cost of energy is about one-third of the total costs. A similar result, the energy cost of 30% to 40% of total costs, is reported by (Sah et al., 2019) in Kathmandu Valley.

15
LXXX INouclON

# **_Toft_ Al** (continued)

|Country,<br>colnomm, or<br>territory|Total<br>popultion,<br>mid-1985|Total<br>fertility,<br>1985-90|Life<br>expectancy,<br>1985-90|
|---|---|---|---|
|**West.,rlSamoa**<br>|**Bon**projection from prelim.<br>1966 census<br>|Based on prelim. 1986 census<br>|**lased**onCR, ESCWA<br>Stat.<br>Yearbook<br>forAsiaand the Pacific 1988<br>|
|Yemn,Peoples<br>**De.**Rep.<br>of<br>|**Bon***projection bosed on 1988<br>**census**<br> <br> <br>|U.N. 1990 revision<br> <br>|U.N. 1990 revision<br>|
|YemnArabRep.|mani<br>projection<br>fromadjusted<br>1986 census<br> <br>|Based<br>onSank<br>mission report 1989|lased on lank mission report1989|
|Yugoslovia<br>|UNPVSR<br>4/87<br>(official<br>est.)<br> <br>|lased<br>on CBR,<br>UNPVSR<br>10/88<br>(officiatest.)|Based<br>on CDR,<br>UNPVSR<br>10!88<br>(official<br>**est.)**<br>|
|**Zaire**<br>|U.N.<br>1990<br>revision<br> <br> <br> <br>|U.N.<br>1990<br>rovision|U.N.1990<br>revision|
|Zambia<br>|tank<br>projection<br>from<br>1980<br>census<br>**and officiat**1988<br>***St.**|lased<br>on Bank<br>sector<br>report|**Blsed**<br>on Bank<br>sector<br>report|
|Ziabobse|**8ank**<br>projection<br>from<br>1982<br>census|DHS 1988|DNS 1988|

**Notes:** When **a** source for en estimate is directly cited (e.g., UNPVSR 7/86), the estimate is taken as is from that pubtication. An estimate "based on" a source is not reported in that publication but derived from **data** contained in it. When **a** source is given for a fertility or mortality estimate prior to 1985-90, the corresponding 1985-90 estimate is a projection from the earlier estimate. Citations for the main documents referred to here (usually by **abbreviations) are** in the **list** of references.

Not applcable. No estimates were used because no projections were made for these smalL countries.
(panel C of table 5, figure 4). Moreover, we find a five percentage points increase in the share of couples where wives became more progressive while husbands became more conservative between baseline and endline. Spillover women also report a nine percentage points higher desire for more input in household financial decisions (table 4, figure 5), directly conflicting with their husbands’ increased desire for control. These findings align with evidence from India showing that larger differences in couples’ attitudes and men’s social image concerns drive backlash behavior (Cullen et al., 2024). The negative spillover effects we document also accord with those identified by Chatterji et al. (2020), who found increases in IPV among randomly selected community members after a similar program in Rwanda.

If the IPV backlash stemmed from threatened male identity, we would expect the largest effects among couples not already experiencing violence at baseline. Men who were already perpetrating IPV should face little additional motivation to use IPV to assuage threatened identity, while men not perpetrating IPV at baseline may have greater social returns from using IPV to assuage an existing (or acquired) reputation as being more progressive. Indeed, negative treatment effects are greatest for spillover couples where women reported no IPV at baseline (table A9). For women who did report baseline IPV, the intervention also increased the severity of the type of violence they experienced, also consistent with the mechanism of men assuaging threatened identity with worsened IPV.<sup>18</sup> Overall, the evidence strongly supports a backlash mechanism among spillover couples. Quantitative results, corroborated by anecdotal reports, indicate increased friction as women’s and men’s attitudes diverged and aspirations clashed. Moreover, the diffusion of progressive messages by trained couples and through community events threatened spillover men’s identity, leading them to reassert dominance through violence.

# _Evidence on Village-Level Dissemination Effects_

Not all couples belonging to a VSLA live in the same village as their VSLA’s location. This geographic variation enables us to examine the role of the village as a channel for program message dissemination causing spillovers, by studying couples who reside in treated villages but belong to

> 18For example, women experiencing only emotional IPV at baseline escalated to physical and/or sexual IPV at endline. Similarly, women experiencing physical but not sexual IPV at baseline reported increased sexual IPV at endline.

20
we plot the estimated difference-in-differences coefficient for each year, which measures the ii differential change for domestic listed firms relative to foreign listed firms. ββ̂ The regression results confirm that equity issuances only started to diverge across the two groups in the years following the implementation of the Stock Connect program. The difference in equity raised over assets between domestic and foreign listed firms was not statistically significant during the QFII implementation in 2002, the RQFII implementation in 2011, or the QFII/RQFII expansions in 2013. It became statistically significant in 2015, when domestic listed firms increased the equity to assets ratio by 4 percentage points (p.p.) relative to foreign listed firms. This difference increased to more than 10 p.p. in 2016 (Figure 3, Panel A). By 2020, the cumulative amount of equity raised over assets for domestic listed firms reached 50 percent, 21 p.p. higher than that for foreign listed ones (Figure 3, Panel B).<sup>25</sup> Since comparisons between foreign and domestic listed firms may be affected by confounding domestic events unrelated to internationalization, we now focus on the group of domestic listed firms. We estimate difference-in-differences regressions to compare the issuance activity of connected and unconnected domestic listed firms (Table 4 and Figure 4). We present the results from the full sample (left-hand panels) and the PSM sample (right-hand panels). Both groups of firms show similar equity issuance patterns before the Stock Connect program was implemented. Since then, connected firms raised substantially more equity than unconnected firms.

Results with the full sample show that the differences between connected and unconnected firms became significant in 2015. The amount of equity raised over assets was about 4 p.p. higher for connected firms than for unconnected firms in 2015 and 6 p.p. higher in 2016 (Figure 4, Panel A). Differences between connected and unconnected firms were still significant (but smaller) during the MSCI incorporation process (2018-20). By 2020, the cumulative amount of equity raised

> 25 These results are similar when dual listed firms and Hong Kong listed firms are excluded from the foreign listed sample (Table 3).

15