rafmacalaba/datause-encoder-data huggingface dataset:
intervention districts are pooled (Table 3, first column), the association is clearly strongest in Phongsaly district compared to Khua or Nhot districts.<sup>1</sup> Given these challenges, and the availability of pre- and post-intervention data, we used two distinct difference-in-difference (DiD) estimators to construct two plausible counterfactuals. First, the within-district DiD compares the changes in outcomes from baseline to follow-up in takeup villages vs. non-takeup villages in the same district: where Y0 and Y1 denote outcomes at baseline and follow-up respectively, and T and C denote within-district treatment (takeup) and control (non-takeup). At the child level, this is an intent-totreat analysis (ITT), as we do not account for whether individual children received transfers of food at school or via rations, but only whether they lived in a take-up village or not. Formally, our DiD specification is where Y _ivt_ is the outcome for child _i_ in village _v_ at time _t_ , Takeup is the treatment indicator, and Round2 is the follow-up survey, X represents household characteristics and V stands for the set of dummy variables for each village. εit is the error term which is composed of individual and family unobserved fixed characteristics as well as a stochastic disturbance term,  it:

> 1 These multivariate results are consistent with the bivariate associations shown in Figure 1. Odds ratios for takeup regressed on current enrollment in 2006 are 4.32 for Phongsaly (p <.001); 1.29 for Khua (p = 0.456); and 2.22 for Nhot Ou (p = .001).

9
2_. The Developmn ogf Pxices and Incomes aftgr EC-92 There is broad agreement among analysts that EC-92 will bring tenefits to EC countries when all the directives ar. implemented. There is very much less agreement on how large those benefits are likely to be and how they will be distributed over member countries or regions. And there even less agreement - largely because there has been so little analysis of this question - on how strong the effects on other economies (North American, East Asian, developing countries and East European) would be. In fact there is little agreement on whether the net impacts on the outside economies will be positive or negative, let alone what the distribution of the changes will be across the OECD, NICs, developing countries, or East Europe.

In general terms, the EC countries can expect higher income levels and lower prices as internal barriers to trade come down under the EC-92 program. Increased competition, greater efficiency through exploiting economies of scale and the wider scope for investing according to comparative advantage, removal of internal customs duties and ocher transactions costs,2 the removal of price discrimination, competitive tendering for government contracts, free circulation of goods from the cheapest supplier, a lower cost of capital through more efficient (for which read integrated) financial markets; these are all things which will reduce prices within the EC. Falling prices will of course expand the EC markets and therefore lead to expanding income levels (as well as incomes higher in real terms because prices are lower than otherwise). One can expect this to have a continuing effect through increased investment, both in response to rising incom3s and the lower costs of capital (an accelerator argument, in the absence of risk premia) and in order to exploit greater efficiency through economies of sale and comparative advantage (again without risk premia). Foreign producers may also be tempted to invest in the EC to establish a base within the union.
Results show that over the two decades output-efficiency growth was faster in the most inefficient countries, showing that there is a “catching-up” phenomenon. However, when measuring input-efficiency, the previous results do not hold: most regions increased expenditure levels without increasing output. Appendix D summarizes, on a regional basis, the change in productivity of public spending decomposed into efficiency change and technological change.<sup>15</sup>

# **IV. Explaining Inefficiency Variation Across Countries**

This chapter seeks to identify factors correlated with inefficiency scores variation across countries. This two-stage approach attempts to identify statistically significant regularities common to efficient or inefficient countries using the more basic statistical techniques. This exercise does not try to identify supply or demand factors that affect health and education outcomes, such as those described by Filmer (2003). The scope is limited to verifying statistical association between the efficiency scores and environmental variables.

# **IV.1. Method, Variables and Data Description**

Given that the dependent variable, the efficiency scores, is continuous and distributed over a limited interval (between zero and one), it is appropriate to use a censored (Tobit) regression model to analyze the relationships with other variables. The panel consist of a large numebr of countries (varying from 70 to 140 depending on the output indicator) and only two time periods. The literature on panel estimation has shown that in panels with this configuration, that is, a large number of cross-section units (countries) and a relatively short time dimension (2 periods), the fixed-effects estimators of the coefficients will be inconsistent (Maddala, 1987) and their variance will be biased downward (Greene, 2003b). Hence the random effects panel estimation method was preferred.

The dependent variable in the Tobit panel is the input efficiency score calculated by DEA method in the first stage. The input-oriented estimator reflects the consideration that input choices are more under the policymaker’s control. The independent variables reflect environmental effects included in precursor papers, as well as suggested by others recently. We included the following independent variables<sup>16</sup> .

**a. The size of government expenditure** . Most of the papers surveyed in the previous section explore the relationship between the size of the government (or expenditure as a percentage of GDP) and efficiency levels.  The objective is to verify if additional pubic spending is associated with better education and health outcomes.  While some papers have found a negative association between efficiency and expenditure levels (GuptaVerhoeven 2001, Jarasuriya-Woodon 2003, and Afonso et.al. 2003), others have found a positive association (Evans et.al. 2003) and others have found no significant impact (Filmer and Pritchett, 1999)

> 15 The results on country-by-country basis can be found at the PRMED website indicated in footnote 1. 16 The precise definition and sources is can be found in Appendix B, Table B.6.

25
Policy Research Working Paper 9959

# **Abstract**

Understanding how different households cope with COVID-19 among a vulnerable population is important for the policy design aiming at relieving hunger and poverty in a low income setting. This paper uses original household data from five waves of a phone survey conducted between May 2020 and June 2021 in Kenya (sample size 31,715) and investigates the gender differences in household coping strategies during the COVID-19 shock. It finds that femaleheaded households are less likely to cope by selling assets or taking loans, compared with male-headed households. Instead, femaleheaded households rely more on social networks to cope. No difference in coping by reducing meals is observed across these two types of households. This paper documents that the reasons behind the gender difference include that female-headed households are poorer, and they are more likely to rely on friends and family to cope with shocks even prior to the COVID-19 shock. The findings suggest that widowed and divorced women are in high need of relief programs, and governments should provide easily accessible loans to avoid negative impacts in the long term from households selling assets.

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 yuanweii.xu@gmail.com, adelius@worldbank.org, and upape@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
realistically for the case of developing countries, forcing banks to share some of the information may reduce the rents from private information and push the sector towards larger, less fragmented and more efficient institutions. In short, there is then a subtle relationship between information availability and credit market competition and this remains an area where further research on the implications of sharing credit information would be helpful.

The competitiveness of the credit market is also related to the competitiveness of the market in information itself and as we have argued above a PCR will normally, and should normally, coexist with private credit bureaus. This is most definitely **not** an issue of either/or. However, the private credit bureau market, in general, will have sharply increasing returns to scale, and is often dominated by a few large players - especially in smaller countries where there is a very real danger of only one significant private company that will then have severely diminished incentives for responsiveness to client demands and innovation and may charge high prices. The existence of a PCR can assist entry into the private credit bureau market by lowering entry costs in making a set of basic credit information available at low cost. A healthy, competitive private credit bureau industry should then be free to compete on adding additional information and developing other value-added services such as credit scoring products rather than surviving on information-rents alone.

The design features of public credit registries can also impact upon the role they will have in promoting competition in both financial and non-financial markets. For example, it is important to attempt to widen the access to PCR data beyond common rules regarding reciprocity for access to the data. This may impact considerably on competition in other sectors including insurance and even trade where trade credit is important.

The policy with respect to the assignment and distribution of borrower ratings by a PCR also may potentially impact competition in a financial market. For example, if ratings are tied in a one-to-one fashion to provisioning requirements, this could discourage lenders from undertaking more detailed analysis of marginal borrowers and unduly restrict credit to this market segment. Distributing the borrower ratings back to the financial system as part of the PCR credit report may also create incentives problems. For example, if banks know that when they lower a 21
**The Domestic Segment of Global Supply Chains in China under State Capitalism**

Heiwai Tang<sup>1</sup> , Fei Wang<sup>2</sup> , and Zhi Wang<sup>3</sup>

**Key words:** value-added trade; global supply chain; intra-national trade; state capitalism

**JEL Classification Numbers:** F1, C67, C82

> 1 School of Advanced International Studies, Johns Hopkins University, 1717 Massachusetts Ave NW, Suite 709, Washington, DC 20036, U.S.A. 2 School of International Trade and Economics, University of International Business and Economics, P.O. Box 119, No. 10 Huixin Dongjie, Beijing 100029, China.

> 3 United States International Trade Commission, 500 E Street SW, Washington, DC 20436, U.S.A.
16 offers made to individuals in the country of Paraguay, they find that political agents target vote buying to individuals with greater feelings of reciprocity. A large literature on get-out-the-vote campaigns in the US finds that personal or direct contact with households are the most persuasive in getting them to vote on election day, compared to other strategies that are more broadly targeted, such as distributing pamphlets (DellaVigna and Gentzkow, 2009).

This argument might logically extend to comparing the marginal vote-returns from spending on broad public goods versus privately targeted transfers—broadly provided public goods might not generate the same strength of reciprocal feelings in individual voters as do private, one-to-one transfers. Even when an incumbent government provides broad public goods, voters that are targeted with private benefits from a rival party might still vote against the incumbent. Political studies of vote-buying, largely concentrated in Latin America and in poorer constituencies in the US, have provided theoretical arguments as well as empirical evidence that low-income or poor voters are more likely to be targeted with vote-buying offers, and more likely to comply (Harding, 2008; Stokes, 2005; Brusco et al, 2004).

Others have argued for India that since the poor live at or near subsistence levels they are more likely to reward with a vote even a small welfare transfer made directly to their household rather than broad performance in the delivery of public goods (Varshney, 2000). Their private voting action may therefore be at odds with their publicly declared preferences for public goods, such as when they answer questions about priority problems for the village. The nature of voting behavior, especially among the poor, alluded to in this literature implies that jobs and welfare transfers may be a lower risk electoral strategy in terms of the expected vote returns compared to a strategy that invests in broad public goods.
country. The data on school enrollment and literacy rates are from the World Bank’s World Development Indicators database. For each country, we use the schooling and literacy rates for the year 2000.

Fourth, we control for the overall level of economic development. The research summarized in Demirgüç-Kunt and Kane (2002) suggests that high deposit insurance limits are more feasible in countries with better institutional environments because good institutions serve to mitigate the moral hazard effects of explicit deposit insurance. The public interest view would thus suggest that the level of deposit insurance coverage is likely to be higher in countries with better institutional environments. To the extent that such systems also bring about safer banks, the private demand for deposit insurance would be lower in these countries. Private interest theory thus predicts that coverage levels of deposit insurance are likely to be lower in countries with a high level of economic development. As measure of the overall level of economic development, we include per capita GDP in 1995 expressed in 1995 U.S. dollars. We refer to this variable as GDPCAP. In the regressions, we use the logarithm of this variable. The data on per capita income are from the World Bank’s World Development Indicators database.

Fifth, we control for the effect of differences in demographics of the population. Since elderly people typically have more liquid assets than younger people and tend to mainly use bank deposits as a savings vehicle, private interest theory predicts that legislators from countries with a larger share of elderly people are more likely to vote in favor of high coverage limits of deposit insurance. As proxy for the importance of elderly constituents we use the variable POP65, which is the share of the total population in the country with age 65 and above at year-end 2000. The data on the share of the population 13
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28
fractionalization ( _Ethfrac (Montalvo & R.Q.)_ and _Relfrac (Montalvo & R.Q.)_ ). In addition to these three sources, Roeder (2001) has developed an ethno linguistic fractionalization index ( _Ethfrac (Roeder)_ ), which is mainly on the original Soviet sources from the 1960s together with other Soviet ethnographic studies from the 1980s.

We primarily rely on Fearon’s (2003) and Fearon and Laitin’s (2003) widely used measures of ethnic and religious fractionalization. We also use the alternative measures to test the robustness of our results, a strategy advocated by both Fearon (2003) and Alesina et al. (2003). Additionally, Montalvo and Reynal-Querol (2005) argue that it is polarization rather than fractionalization that matters. It measures “the normalized distance of a particular distribution of ethnic and religious groups from a bimodal distribution” (see Montalvo and Reynal-Querol 2005: of group _i_ and _n_ is the number of existing groups. Polarization approaches unity when the population is made up of two equally sized groups and then declines as the number of groups increases further, whereas fractionalization increases monotonically with the number of groups. Empirically, across countries ethnic polarization ( _Ethpol (Montalvo-R.Q.)_ ) is related to ethnic fractionalization in a non-linear way: Ethnic polarization first rises with increasing fractionalization, but then falls at an intermediate level of fractionalization. Religious polarization ( _Relpol (Montalvo-R.Q.)_ ) is somewhat different; it first increases as fractionalization increases and then at higher levels of fractionalization there is no relationship to polarization. See Montalvo and Reynal-Querol (2005) for a detailed discussion. Thus, we also test ethnic and religious polarization in our models of militarization.

Recently, Cederman and Girardin (2005) have criticized conflict scholars for using measures of ethnic fractionalization and polarization, arguing that these measures fail to capture the essence of ethnic conflict. In their view, what matters are not relative group sizes, but which group of which size holds state power and which demographically significant ethnic groups are excluded from state power. From this premise, they develop an index of ethno-nationalist exclusion ( _Ethexclusion_ ) with an ethnic group in power in the center, interacting in a star-like fashion with each non-governmental ethnic group, but without interaction of the nongovernmental groups with each other. Whereas the fractionalization and polarization indices take on the same value whether or not an ethnic majority or minority holds state power, Cederman 7
# **3. The extent of EAP’s financial integration**

In this section, we examine the degree to which EAP economies have integrated financially with economies in the North and the South (inter-regional integration) and with other EAP economies (intra-regional integration). Exploiting the bilateral nature of our dataset, we study the patterns of EAP’s financial integration along the intensive margin (value of investments) and the extensive margin (number of partners/connections) for portfolio investments, syndicated loans, M&As, and greenfield investments. We also explore whether EAP has been a net exporter or a net importer of the different types of cross-border investments.

# _3.1. Inter-regional investments_

EAP economies have become increasingly more financially connected with the rest of the world (economies outside the EAP region) in terms of portfolio investments, syndicated loans, and M&As, but not in greenfield investments. For example, the value of syndicated loans and M&As more than doubled between 2003 and 2014 (Figure 1). In contrast, greenfield investments decreased by about 24 percent during the same period. This expansion in EAP’s financial integration has not been a monotonic process. As illustrated in Figure 1, investments to and from EAP have been characterized by boom and bust patterns.

The expansion of EAP’s inter-regional investments is not attributable just to the fast growth in real economic activity observed across the region. EAP’s GDP increased to about 28 percent of world GDP by 2014, up from about 20 percent in 1990. As is well known, China’s growth has been particularly high: its GDP grew from around 2 percent of world GDP in 1990 to about 13 percent in 2014. Nonetheless, when financial investments are scaled by GDP, the documented patterns still hold. That is, we still observe expansions in inter-regional portfolio investments, syndicated loans, and M&A flows to and from EAP. Naturally, greenfield investments still follow a downward-sloping trend. For 8