rafmacalaba/datause-encoder-data huggingface dataset:
2002; Demirguc-Kunt and Huizinga, 2004). Further, cross-country comparisons have not confirmed the assertion that deposit insurance is crucial for financial sector development; to the opposite, countries with more generous deposit insurance schemes are found to have lower levels of financial savings and private sector lending (Cull, Senbet and Sorge, 2005).

While strengthening of supervisors’ intervention powers has been at the forefront of efforts improving the supervisory framework, there is little cross-country evidence that empowering supervisors alone will bring stability. There is evidence, however, that powerful bank supervisors might be associated with higher levels of corruption. Beck, Demirguc-Kunt and Levine (2006a) show that firms in countries with more powerful bank supervisors, i.e. supervisors that directly monitor, discipline, and influence banks, are more likely to report major obstacles due to corruption in lending. On the other hand, a supervisory strategy that focuses on empowering private monitoring of banks by forcing banks to disclose accurate information to the private sector tends to lower the degree to which corruption of bank officials is an obstacle to firms raising external finance.

# **3.3. Enabling markets – a new approach**

Rather than replacing market failures with government failures, policies are required that address market failures directly and try to reduce market frictions. This new approach is not a laissez-faire approach as it does not leave the market to itself; rather, it relies on the government to enable and develop markets. It starts from the observation that frictions might prevent markets from functioning well or might even prevent markets from existing in the first place. However, this approach does not seek to replace missing or poorly functioning markets, but rather create the conditions for markets to emerge and function properly. It relies on private institutions to provide financial services efficiently but takes into account their incentive structure. This approach foresees a government that works with the market, but does not leave it to the market.

17
Policy Research Working Paper 6149

# **Abstract**

While there are many positive societal implications of increased female labor force opportunities, some theoretical models and empirical evidence suggest that working can increase a woman’s risk of suffering domestic violence. Using a dataset collected in peri-urban Dhaka, this analysis documents a positive correlation between work and domestic violence. This correlation is only present among women with less education or who were younger at first marriage. These results are consistent with a theoretical model in which a woman with low bargaining power can face increased risk of domestic violence upon entering the labor force as a husband seeks to counteract her increased bargaining power. By contrast, husbands of women who have higher baseline bargaining power cannot resort to domestic violence since their wives have the ability to leave violent marriages. These findings are inconsistent with the models of assortative matching in the marriage market, expressive violence, work in response to economic shocks, or underreporting of domestic violence. The results on age at marriage are also inconsistent with the implications of a reverse causality model in which women enter the labor force to escape violent situations at home, although the results on education are consistent with that story.

This paper is a product of the Human Development and Public Services Team, Development Research Group. 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://econ.worldbank.org. The author may be contacted at rmheath@uw.edu.

_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
# 5. Empirical Results

In this section, we discuss the summary statistics of various indexes of scheme functionality and their constituent indicators for Jalanidhi, KWA-BM, and other community managed schemes. This is followed by a discussion of the results from the PSM exercise.

## 5.1 _Summary Statistics_

Indicators relating to Water Availability and Reliability are based on data from household surveys aggregated at the scheme level. Around 50 percent of Jalandihi schemes and 60 percent of other community managed schemes are supplying water every day of the week. The number is much lower for the KWA schemes where only 27 percent of the schemes were reported supplying water daily. On average, water is available only for 3.7 days for Jalanidhi and other community managed schemes and for 3.2 days for traditional supply driven KWA schemes. Moreover, the supply was considered adequate for 63 percent of Jalanidhi schemes compared to 62 percent for other community managed schemes and 55 percent for KWA schemes. Regarding regularity of water supply, 36 percent of Jalanidhi schemes were reported supplying water irregularly compared to 43 percent of other community managed schemes and 41 percent of KWA schemes. The majority of the respondents from the community schemes found water pressure in the network adequate. Around 33 percent of Jalanidhi schemes and 38 percent of other community managed schemes were reported having low water pressure in the network. In contrast, beneficiaries of around 70 percent of the traditional supply driven schemes complained about low water pressure. Similarly, beneficiaries of around 70 percent of the traditional supply driven schemes reported facing water shortage during summer months compared to only 38 percent for other community managed schemes and 49 percent of Jalanidhi schemes. The community schemes also perform better in terms of quality of water supplied. Beneficiaries of more than 50 percent of the KWA schemes reported getting colored water compared to only 8 percent for Jalanidhi schemes and 13 percent for other community managed schemes.

So Jalanidhi and other community managed schemes perform better compared to traditional supply driven KWA schemes in terms of availability, adequacy and quality of water supply. However, there is no major systemic difference in performance between Jalanidhi and other community managed schemes. Jalanidhi schemes perform marginally better in areas of regularity and adequacy of water supply whereas other community managed schemes perform better in weekly frequency of water supply and lack of seasonal shortage.

12
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Table 7: Association between migration and risk-aversion <u>(Probit)</u>

||(1)|(2)|(3)|
|---|---|---|---|
|VARIABLES|0 = HH migr.<br>1 = HH not migr.|0 = HH migr.<br>1 = HH not migr.<br>and some confict|0 = HH migr.<br>1 =HH not migr.<br>and always confict|
|**Behavioural**||||
|Risk Aversion|-0.179**|-0.363***|-0.400**|
|**Social and Economic Va**|**riables**|||
|Household Size|0.0324**|0.0465**|0.153**|
|Share of Dependent|-0.398***|-0.593***|-0.00753|
|HH Gender = Male|0.104|0.201|0.209|
|HH Age|0.0158***|0.0188***|0.0165***|
|HH Years of Education|-0.0273***|-0.0369***|-0.0426*|
|HH Employed|0.364***|0.503***|0.877***|
|HH Married|0.188|0.0615|1.192***|
|HH Gender * HH Married|-0.21|-0.221|-1.532**|
|**Quality of Dwelling**||||
|Number of Rooms|0.0614*|0.0527|-0.0260|
|Quality of Walls||||
|(baseline=Low)||||
|Medium|-0.175|-0.314|0.509*|
|High|-0.444***|-0.564***|-0.254|
|**Assets**||||
|TV|-0.0738|-0.0483|0.382|
|Fridge|0.078|0.259*|-0.527|
|Stove|-0.273***|-0.372***|-0.939**|
|Bicycle|0.354***|0.408*|0.368|
|Car|-0.280**|-0.486***|-0.319|
|Iron|0.0453|0.113|-0.260|
|Constant|0.819***|0.0513|-2.585***|
|Observations|4,577|1,289|359|
|Pseudo R-squared|0.141|0.19|0.357|

Robust standard errors (not reported) *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 Source: Authors’ estimations based on GHS and ACLED Data 37
strikes increase the user cost of IT related infrastructure because they create voltage surges and dips (Andersen et al., 2011, 2012); accordingly, we expect a negative first-stage coefficient.

Our exclusion restriction, therefore, postulates that lightning strikes affect radicalization only through their impact on internet access. However, as discussed by Manacorda and Tesei (2020), lightning strikes might be correlated with other climatic or topographical characteristics like rainfall, which in turn might affect economic development. Since the instrument varies only at the delegation level, controlling for delegation fixed effects is no longer feasible. We nonetheless include in the vector of control variables _Xdea_ a measure of delegation _d_ ’s income as proxied by (log) nighttime lights, its (log) area, and the (log) average monthly amount of rain that fell there.

**Addressing spatial correlation** The instrumental variable strategy makes salient that deployment of the internet, a network technology, is likely to be spatially correlated. Thus, for both error terms _εdea_ (or _ζdea_ for the fixed-effect estimations) and _νdea_ , we allow for spatial correlation. We first allow _εdea_ and _εde′a′_ to be correlated, by clustering standard errors at the delegation level, but given the potential spatial dependence in internet access and its instrumental variable, our preferred specifications use the procedure from Conley (1999) to accommodate spatial correlation.

# **3 Data**

To estimate equation (1) and its variants, we combine a dataset on Daesh foreign personnel that contains information on Tunisian recruits with socio-economic and other data on the geographic areas those recruits are coming from.

**Daesh foreign recruits** Our main source of data comes from Daesh administrative records on its foreign fighters. The dataset, believed to have been leaked by a defector, covers 3965 male foreign recruits, which constitutes an estimated 30 percent of foreign fighters who joined the organization from early 2013 through late 2014 (Dodwell et al., 2016a).<sup>3</sup>

> 3Dodwell et al. (2016a) checked the information in the database against U.S. Department of Defense intelligence records and found high levels of consistency. The data were used in earlier cross-country studies (Dodwell

5
**40**

Ravallion, Martin, and Monica Huppi (1991) ‘Measuring Changes in Poverty: A Methodological Case Study of Indonesia during an Adjustment Period.’ _World Bank Economic Review_ , Vol. 5 (January) pp. 57-82.

Ravallion, M., and G. Datt (1996): “How important to India’s Poor is the Sectoral Composition of Economic Growth?”; _World Bank Economic Review_ 10(1), pp.1-25.

Ravallion, M., and G. Datt (2002): “Why has Economic Growth been More Pro-Poor in Some States of India than Others?” _Journal of Development Economics_ 65, pp. 381-400.

Ravallion, M., and S. Chen (2004): “China’s (Uneven) Progress Against Poverty” World Bank Policy Research Working Paper No. 3408.

Schultz, Theodore W. (1964): _Transforming Traditional Agriculture_ , New Haven, Conn., Yale University Press.

Thirtle, C., L. Irz, L. Lin, V. McKenzie-Hill and S. Wiggins (2001) “Relationship between Changes in Agricultural Productivity and the incidence of poverty in developing countries” Report commissioned by DFID, London, UK.

Thirtle, Colin, Lin Lin, and Jenifer Piesse (2003): “The Impact of Research-Led Agricultural Productivity Growth on Poverty Reduction in Africa, Asia and Latin America” _World Development_ 31-12, pp.1959-1975 Timmer, Peter (1997): “How Well Do the Poor Connect to the Growth Process?” Harvard Institute for International Development. United States Agency for International Development.

Timmer, Peter (2005): “Agriculture and Pro-Poor Growth: What the Literature Says.” Draft paper, Agricultural and Rural Development Dept., World Bank.

Windmeijer, Frank (2005): “A Finite Sample Correction for the Variance of Linear Efficient TwoStep GMM estimators” _Journal of Econometrics_ 126, pp.25-51.

World Bank (2000): _The Quality of Growth_ , Oxford University Press: Oxford.
**<u>Table A-4 Ranges of VSL estimates by countries, 2006 USD</u>**

||No. of<br>studies|Health|Occupation<br>safety|Transport|Environment|Other|**Total**|**Mean**|**Median**|
|---|---|---|---|---|---|---|---|---|---|
|Australia|17|0.9-2.2|2.2-21.1|1.3-5.4|0.7-5.3|1.1-13.1|**0.7-21.1**|**4.2**|**2.2**|
|Austria|5|---|1.9-9.8|---|---|4.0-9.8|**1.9-9.8**|**6.7**|**6.1**|
|Canada|17|2.0-6.7|0.6-5.8|0.5-30.5|---|2.7-10.8|**0.5-30.5**|**5.4**|**3.7**|
|Demark|2|---|---|1.0-1.4|---|4.9-6.5|**1.0-6.5**|**3.2**|**3.2**|
|Europe|1|---|---|4|---|---|**4**|**4.0**|**4.0**|
|France|2|---|---|1.1-26.6|---|3.8-5.4|**1.1-26.6**|**8.8**|**8.8**|
|Hong Kong|1|---|2|---|---|---|**2**|**2.0**|**2.0**|
|Japan|4|---|11.4-15|---|---|6.1-9.1|**6.1-15.0**|**11.9**|**13.2**|
|New Zealand|10|---|---|0.8-15.9|---|2.1-3.1|**0.8-15.9**|**5.2**|**3.9**|
|South Korea|6|---|1.0-1.9|---|---|0.5-1.0|**0.5-1.9**|**1.2**|**1.1**|
|Sweden|7|---|---|1.6-32.7|---|1.6-5.0|**1.6-32.7**|**5.9**|**4.2**|
|Switzerland|5|---|7.4-10.1|1.0-1.3|---|5.4-9.6|**1.0-10.1**|**5.0**|**5.7**|
|Taiwan|7|---|0.2-2.2|---|---|1.0-1.4|**0.2-2.2**|**1.3**|**1.3**|
|UK|26|---|1.6-8.7|0.7-25.2|23.3|1.0-30.7|**0.8-86.8**|**13.0**|**6.5**|
|US|117|0.2-8.7|0.4-24.4|0.15-37.7|0.8-10.1|0.7-31.4|**0.1-37.7**|**6.7**|**5.3**|
|Multiple|17|---|0.4-22.3|0.15-37.7|0.07-98.7|0.5-62.9|**0.1-98.7**|**9.9**|**5.6**|
|**All**|**244**|**0.2-6.5**|**0.2-86.8**|**0.15-37.7**|**0.07-98.7**|**0.5-62.9**|**0.1-98.7**|**7.0**|**4.9**|
|**Mean**|**---**|**3**|**8.2**|**5.9**|**8.3**|**6.3**|**7**|**---**|**---**|
|**Median**|**---**|**2.7**|**5.5**|**4**|**6**|**4.5**|**4.9**|**---**|**---**|

Source: Australian Safety and Compensation Council (2008). The initial table is in Australian Dollar (2006 price). The authors have converted the VSL value into 2006 US dollar, with the corresponding historical exchange rate 1 Australian dollar=0.742302 US dollar.

35
agricultural and non-agricultural GDP. Agricultural GDP is allocated to subnational levels based on the share of the rural population, whereas nonagricultural GDP is allocated based on the share of nightlight (Ghosh et al. 2010b; Bundervoet et al. 2015). Adding up the estimates for the agricultural and nonagricultural sectors, this approach yields predictions of GDP at the district level: PGDPt is the logarithm of predicted GDP based on nightlight intensity given by where ln(GDPi,t) is the natural logarithm of GDP of district _i_ in month _t_ measured either in constant local currency or constant USD, lighti,t is the sum of nightlight of district _i_ in month _t_ , MANT, SERT, and AGRT is the value-added in manufacturing, services, and agriculture in year T and rpopi,T is the rural population in district _i_ in year T. For annual and quarterly data, and where available, an alternative approach consists in using GDP measured in National Accounts rather than predicted GDP.

The outlined approach has some strong advantages: it is easy to implement, needs very few types of data, and is universally applicable. However, this approach is based on a few assumptions that need to be kept in mind. First, it assumes that in each country the same share of the population in rural areas is employed in agriculture across districts and that all agricultural workers in a country are equally productive. This is of course a simplification and may lead to overestimation of economic activity in districts with relatively low agricultural productivity and underestimation in districts with high agricultural productivity.<sup>3</sup>

> 3 An alternative method to distribute agricultural output is based on land cover data (Souknilanh et al. 2015). But it is not obvious that it will lead to a better approximation and it is certainly much more involved.

8
23 men with a greater proportion residing with a wife. But the estimated elfect is nine times bigger for women than for men at similar levels of nonearned income (Appendix Table A-4): Marriage, it would appear, is not a "normal" good for womn.

Other hypotheses could also account for these patterns of marriage and residence in the Thai data, and the **available** survey data do not distinguish among them. The death of a spouse could **increae** an individua 's wealth through inheritance, and also transfer **the** individual to the *single" category. About half of **the** female headed households in Latin America are widows (e.g. Mohan, 1986; Rosenhouse, 1988). Alternatively, women might be more inclined than men, upon divorce, to move back into the household of their parents, other relatives, or children. Marital and residential histories with the timing of inheritance and transfers are needed to dXscriminate more adequately among these competing explanations for family formation patterns. Undoubtedly they will differ greatly as does the family in different societies.

Households Headed by Vomen: ultiple Causes Comparisons of income and welfare of female and-male headed households are not very informative. Most nale headed households tend to include wives, while customarily few female headed households include husbands 10 In some surveys the husband is treated as the household head even when he is not recently resident in the household. Which women find themselves in families that are called *male headed' or in female headed households will be influenced by their resources and other opportunities, as in Thailand. Several studies have found an associatiqn between wealth of individuals and decreased frequency of divorce, separation, and death of spouse (Becker et &I., 1977;
difference in educational persistence becomes negligible for the most educated parents.

# **Sources of Gender in Urban China**

To understand the role played by parental financial investment in children’s education, we utilize the data from the first round of the CFPS survey (2010) to estimate the parameters of the investment equation (i.e., equation (10) above) in Table T3.CU and test the equality of the coefficients across gender. The evidence in Table T3.CU is clear that parental financial investment in schooling does not depend on the gender of a child; we cannot reject the null hypothesis that _θ_ 0<sup>_d_=</sup><sup>_θ_</sup> 0<sup>_s_and</sup><sup>_θ_</sup> 1<sup>_d_=</sup><sup>_θ_</sup> 1<sup>_s._Theseconclusionsareconsistent</sup> with the other existing evidence (see, for example, Tsui and Rich (2002)).

The estimates of the parameters of the investment function and the estimates of the mobility equation discussed above can be summarized in the following binary relations for sons vs. daughters: We first look at the implications of the evidence on the functional form of the intergenerational schooling persistence regressions. The evidence of convexity in the case of sons (i.e., _ψ_<sup>ˆ</sup> 2<sup>_s>_0) implies that we can reject the null hypothesis of</sup><sup>_δ_</sup> 5<sup>_s_= 0 in favor of</sup><sup>_δ_</sup> 5<sup>_s>_0</sup><sup>_._This</sup> is interesting evidence for the Becker et al. (2015, 2018) hypothesis that higher educated fathers are more efficient in financial investment in education.<sup>32</sup> The linearity of the CEF for the daughters, however, cannot be interpreted as evidence in favor of the linear model. With _δ_ 5<sup>_s>_0,itisdifficulttosatisfy</sup><sup>_θ_ˆ</sup> 1<sup>_d_=</sup><sup>_θ_ˆ</sup> 1<sup>_s_if</sup><sup>_δ_</sup> 5<sup>_d_= 0.</sup>

# **Learning from the Investment Equation**

Two pieces of evidence in urban China are similar to that in urban India: (i) the returns to education are higher for girls (see Table T4.C), and (ii) _θ_<sup>ˆ</sup> 0<sup>_d_=</sup><sup>_θ_ˆ</sup> 0<sup>_s_.Asdiscussedinsection</sup>

> 32 We are not aware of any other analysis of intergenerational educational persistence that provides such evidence in favor of the Becker et al. (2015, 2018) convexity hypothesis in a developing country.

28
The key reason that WTO is important is the political economy dimension. Given the concentrated benefits to industries that achieve protection, industry groups will typically lobby for protection. On the other hand, since the benefits to consumers are diverse and less concentrated, they typically do not lobby against protection, but hope others with similar interests will lobby on their behalf. This so called “free rider problem” in political decision-making results in an absence of representation of the views of the consumer and broader economic interests in political discussions of tariffs. Lobbying and political economy considerations often allow special interests to strongly influence policy so that reforms are slow. WTO accession, however, requires across the board reform in many sectors, and the pressure of a WTO negotiation engages policy makers at the highest levels of government. Experience has shown that high- level policy-makers, who have the economy-wide interest in mind, will often intervene to impose reform on slow moving Ministries. In the case of Russia, the process began to move when Putin made WTO accession a priority in his first term.

In section III, I summarize many of the key reforms that Russia has made. It is difficult to argue that Russia would have made reforms as widespread and as deep as it has without the external pressure of WTO accession. Reforms are accomplished in the context of WTO accession that would not normally be achieved so quickly. That is, WTO bindings and external pressure make it easier for a government to adopt a trade policy designed to promote growth and poverty reduction. Moreover, unlike unilateral reforms, once a country commits to a reform at the WTO, it is bound by an international commitment that is difficult to reverse in the future by a less reform mined government. I conclude that the process of negotiating bilateral market access with the countries on its WTO Working Party on Accession, has led to a dramatic increase in reforms regarding the Russian trade and foreign investment regimes, and thereby has helped Russia move toward an open economy model of economic development.

# **III. Russian Commitments to Foreign Exporters and Investors**<sup>**5**</sup>

# **Non-Agricultural Market Access (NAMA)**

**Overall Tariffs.** Russia agreed to reduce its bound MFN tariffs to about 8 percent on average. How does this compare to recent levels of tariffs in Russia? Russia’s tariff schedule contains over 11,000 tariff lines. On about 1,700 of these, the tariff is written as: “x percent, but not less than y euros.” That is, a specific tariff of y euros per unit applies if the specific tariff exceeds the ad valorem tariff.  This amounts to applying the maximum of either the specific or ad valorem tariff. Previous calculations of Russia’s tariffs have either inappropriately ignored the specific tariffs that often apply or have

> 5 The United States Trade Representative (2006) has released five “Fact Sheets” with details of Russian commitments as part the US-Russia bilateral protocol. See this source for further details.

4