rafmacalaba/data-use-mentions-extended huggingface dataset:
health services outside of clientelist practices. This argument was made in the previous section, on the basis of the institutional setting in the Philippines, which allows for exploiting microlevel, idiosyncratic variation in vote buying across municipalities within the same province, keeping big, macro-level political, socio-economic, and institutional factors fixed.

Second, the analysis at the village level has the degrees of freedom and rich survey data to explore a large number of specifications, with different combinations of variables in the Wijk and Zjkvectors, to test that the correlation between health services and vote buying is not driven by other, observable, factors. This includes, of course, the variables found to be systematically correlated with vote buying in this sample (in the previous section): the congressional district fixed effects, dominance of political clans, and the indicator variables for the economic power of the mayor’s family. The analysis also tests for robustness to measuring vote buying using two different survey questions, as presented in the previous section.

Third, concern that unobserved factors might mechanistically drive the correlation, independent of clientelism, is allayed by differentiating the sources for measuring vote buying versus health service delivery. The measures of municipal service delivery are gathered from official government records, and from government respondents, while vote buying is measured through household surveys. This makes it unlikely that unobserved factors that drive household responses to potentially sensitive questions on vote buying are accounting for the correlation with service delivery, since the primary source for measuring service delivery is external to the household.

Fourth, the correlation of vote buying with other services is explored, where higher tier politicians can play an important and perhaps even larger role, and which might be relatively more “targetable”. These services serve as “placebo” tests because municipal vote buying should not be as robustly or significantly correlated with those services where outcomes depend upon the actions of multiple agents, or that are more compatible with or complementary to clientelist political practices. Political conditions at the municipal-level may not matter in the same way
, namely the share of manufacturing valued added in GDP at constant prices and the share of manufacturing employment in economywide employment. Our data come from a variety of sources and comprises of an unbalanced panel of 41 African countries. We also explore potential explanations or correlates of deindustrialization such as natural resource endowment. Our key finding is that deindustrialization does not appear to be the common experience of the majority of Sub-Saharan African countries. Only the Southern SSA subregion appears to have deindustrialized over the period under study. We do not, however, find evidence that this deindustrialization of the southern subregion has occured 24
that dictatorial leaders are less constrained in setting policies and that government responses to pressure from interest groups are stronger in democracies.

8 Of the 42 democratic transitions (see table S.1 and the discussion below) included in the data set, only five occurred in countries that are currently members of the OECD (Spain, Portugal, Mexico, South Korea, and Turkey), and these transitions occurred at times when they had considerably lower incomes than at present.

9 For a discussion of the relationships among various estimators in the context of panel data, see Mundlak (1978) and Mundlak and Larson (1992).

10 This restriction is partially addressed by adding several covariates in the vector _Xi,t_ , to increase the similarity between treated and control countries.

11 See Ashenfelter (1978) and Ashenfelter and Card (1985) for a general discussion of this subject.

12 Polity IV has a longer time series and therefore includes more usable political reforms than other existing democracy indices. For example, in addition to its shortcomings due to classification bias (see Papaioannou and Siourounis 2008), the use of the Freedom House data strongly limits the number of usable transitions because the information only begins in 1972. For a critical discussion of democracy indices, see Munck and Verkuilen (2002).

13 We thank an anonymous referee for focusing our attention on this issue.

> 14 It is important to note that the use of the “continuous” Polity2 index, instead of a

discrete index, does not affect our qualitative conclusions; a higher Polity2 score increases the level of agricultural protection. These additional results are not reported to conserve space, but they may be obtained from the authors upon request.

32
is<br>assumed for all countries.|
|Aggregate depreciation rateδ|Std LTGM|Latest value from PWT 8.1.|
|Public capital and private capital<br>depreciation ratesδ<sup>�</sup>, δ<sup>�</sup>|LTGM‐PC|δ<sup>�</sup>= 2% for all countries, which is the average depreciation rate for<br>structures in the PWT 8.1.δ<sup>�</sup>, individual country‐specific, is the residual<br>from the weighted average calculation.|
|**Initial Conditions**|||
|Initial capital‐to‐output ratio<br>��<br>��|Std LTGM|Individual country values are based on the most recent data in PWT 8.1.<br>(Capital stock at constant 2005 national prices (2005 US$ mil.)/Real GDP at<br>constant 2005 national prices (2005 US$ mil.)). K/Y below 1.5 or above 3.5<br>were trimmed to those values to remove outliers.|
|Initial measured public capital‐<br>to‐output and private capital‐to‐<br>output ratios<br>��<br>��<br>��<br>~~,~~<br>��<sup>�</sup><br>��|LTGM‐PC|Individual country values are derived by applying 2015 shares of public and<br>private capital calculated by the IMF Fiscal Affairs Dept. to PWT data on<br>��<br>��<br>~~.~~<br>IMF data:http://www.imf.org/external/np/fad/publicinvestment/.|
|**Projected Paths**|
,591.784|<br>1.981.267|1.680.147|<br>12.502|

Sources: United States (1977) and (1975) from US Census of Manufactures. Industry Series, table la. United States (1975) originally from 1975 Annual Survey of Manufactures.

Brazil (gross value of output, value added US census concept and employment) from 1975 Censo Industrial Brasil, tables 3 and 26: additional information for calculation of value added at present and former national accounts concept derived from tables 15 and 35 (see also chapter II). Mexico **(gross** value of output and amploy-meat, f. Re-;aen General, table 5: additional information for calculation of value added derived from tables 19 and 20 (see also chapter II).
Let us however, not confuse perception of harmony with lack of conflict, or conflict with violence. Here the WBGNS 2006 has limitations. It focuses on _knowledge of incidents of conflict_ . It does not capture civil disputes such as those regarding property, about which complainants may seek mediation or other recourse. The disputes that come to the Madaripur Legal Aid Association (MLAA), discussed later, are primarily family related but property related matters and enforcement of contracts also form a large part of the case-load. Our content analysis of shalish ―stories‖ also shows that minor property disputes are common sources of tension between households. Other property related disputes stem from petty thefts. In addition, shalish of all types and our own data from village courts indicate that there are large number of cases of theft, street fights and property disputes.

<!-- Start of picture text --> Figure 3: Perception of occurrence of spousal violence in the<br>community safety of women<br>Perception of occurence of spousal violence in the community<br>Based on the question “Is it usual in your community for xx to happen”<br>Based on the question "Is it usual in your community for xx to happen"<br>100 Source: World Bank Gender Norms Survey 2006<br>90<br>80 Older Women (45-60)<br>70 Younger Women (15-25)<br>Men (25-50)<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>%<br>Wife beaten for going out without telling husband Wife beaten for not getting money from natal home Wife beaten for neglecting house/children Wife beaten for not cooking properly Wife beaten on suspicion of being in realtionship with another<br><!-- End of picture text --> There could be several reasons why the reported perception of harmony is so high. First, pride
# **1.  Introduction**

Approximately 84% of Bangladesh’s people are directly or indirectly dependent on agriculture for their livelihood, and agriculture contributes about 24% of gross domestic product (Bangladesh Bureau of Statistics, 2001). Rice is the major staple crop, accounting for 76% of the cultivated area, 78% of the irrigated area, 52% of agricultural GDP, and 71% of caloric intake (Bangladesh Bureau of Statistics, 2001). Plant, animal and insect pests pose a constant threat to rice production, inflicting losses conservatively estimated at 10-15% annually (FAO, 2001). Farmers have used toxic chemicals extensively for pest control, because of their reputation for speed and effectiveness. However, rising use of chemical pesticides has also posed serious health risks, as well as threatening widespread ecological damage. These problems will undoubtedly increase if Bangladeshi farmers respond to rapidly-rising food demand by intensifying their use of chemicals for pest control.

In response to rising concern about the sustainability of conventional agriculture, the government has collaborated with international assistance agencies to promote Integrated Pest Management (IPM). IPM has no standard definition, but comprises approaches that range from carefully-targeted used of chemical pesticides to biological techniques that use natural parasites and predators to control pests (Sorby et al., 2003). Since chemical pesticides are expensive for poor farmers, IPM also offers the prospect of lower production costs and higher profitability. Of course, adoption of IPM may reduce overall profitability if it also lowers productivity, or induces more intensive use of other production factors. However, application of IPM techniques may also raise overall productivity, by encouraging more effective use of other inputs. Data scarcity has hindered a full accounting of IPM’s impact on profitability, health and local ecosystems.

Using new survey data, this paper attempts such an accounting for farmers in Bangladesh. We compare outcomes for farming with IPM and conventional techniques, using simple input-use accounting and estimation of conventional and frontier production functions, along with farmers’ assessments of
1997). Ethnic fractionalization has been suggested as an important explanation for poor African performance (see Collier and Gunning (1999) and Easterly and Levine (1997)).

The second component is basic property rights protection. Cross-country evidence suggests that countries with worse property rights have lower aggregate investments, worse access to finance, and slower economic growth (North 1990; Knack and Keefer 1995; Acemoglu, Johnson and Robinson 2001). Acemoglu and Johnson (2005) find evidence that property rights institutions (i.e., those related to government expropriation) tend to be more important than contracting institutions (e.g., those safeguarding private transactions). Some new firm-level evidence also points to the importance of property rights (Johnson, McMillan and Woodruff 2002; Cull and Xu 2005) and the adverse effects of corruption. Potential mechanisms for the property rights effects include better external finance (Demirguc-Kunt and Maksimovic 1998), better asset allocation (Claessens and Laeven 2003), and a higher share of large formal firms (Demirguc-Kunt et al. 2006). To capture the protection of property rights, we rely on political competition, in particular, the number of years that the ruling party has been in power from the Data of Political Institutions (DPI, based on Beck et al. 2001 and Keefer 2007). Our reasoning is that the longer a ruling party has been in power, the more absolute power the ruling party has, and the higher the risk of unconstrained government expropriation.<sup>11</sup> There are clearly alternative explanation for this party monopoly variable. For instance, a ruling party with

> 11 This intuition seems to capture the reality of most developing countries well.   However, some argue that several East-Asian countries also have low political competition as measured by this variable but seem to have performed well in the past several decades.  Gehlbach and Keefer (2010a, 2010b) suggests that this may be due to much better ruling party institutionalization in East Asian countries relative to other countries
# **2.2. Formulas for the optimal sample size and the optimal allocation of samples across areas**

In his influential book on survey sampling, Cochran (1977) presents two key formulas for designing any stratified simple random sampling. The first formula determines the minimum sample size required to achieve a certain level of statistical reliability regarding the relationship between one statistic and another targeted variable. The second formula, based on Neyman’s (1934) original allocation rule, determines the optimal allocation of the sample across strata.<sup>3</sup> These two key formulas, presented in Cochran’s (1977) book, assume that the sample follows a simple stratified random sampling design.<sup>4</sup> However, most surveys that we are interested in—that is, household income and expenditure surveys and integrated household surveys designed to measure living standards and monitor poverty and welfare patterns—are not a simple stratified random sample, but rather use multi-stage stratified clustered sampling designs.<sup>5</sup> Therefore, the original Cochran (1977) formulas for designing a sample for a living standards household survey is generally not appropriate and would result in an inadequate determination of the sample size and a sub-optimal allocation of the sample across strata. Nevertheless, the formulas are widely used for the selection of the sample size and allocations across strata.

In this paper, we propose a modification to Cochran’s sample size formula to estimate adequate sample sizes for multi-stage stratified clustered surveys. Cochran’s (1977) original formula, building on work by C <mark>ornfield (1951) and Kish (1965), estimates sample size by</mark> calculating the minimum sample size required to achieve a certain level of precision (plus or minus x

> 3 The Neyman’s (1934) original allocation rule minimizes the variance of the sample mean of a targeted variable given a fixed pre-established sample size assuming that the cost of sampling in each stratum is
11

**Table 5:** _Values of governance index, EBRD-based structural reform index and FDI cumulative inflows per capita in 1990-2003_

||Albania|BiH|Bulgaria|Croatia|Czech R.|Estonia|Macedonia|Hungary|
|---|---|---|---|---|---|---|---|---|
|Governance|-0.38|-0.75|0.10|0.25|0.78|0.88|-0.30|0.85|
|FDI cumulative per capita|343|280|835|2,147|3,771|3,013|476|3,697|
|EBRD-based Index|26|13|43|48|65|62|33|72|
||Latvia|Lithuania|Moldova|Poland|Romania|S&M|Slovak R.|Slovenia|
|Governance|0.44|0.50|-0.35|0.62|-0.12|-0.91|0.45|0.75|
|FDI cumulative per capita|1,461|1,091|156|1,431|482|260|1,647|2,028|
|EBRD-based Index|49|52|36|63|38|3|51|57|

Notes: EBRD-based index ranges between 0 and 100 (fully operational market structures; Governance ranges between minimum of – 2.5 (dysfunctional) and +2.5 (perfect quality). Source: EBRD transition reports various issues, IMF balance of payments statistics and derived from data available at <u>www.worldbank.org/wbi/governance/gov_data.htm</u>

**Figure 3:** _FDI cumulative inflows over 1990-2003 per capita (in US dollars) and EBRD-based index of progress in second-generation
(WTO) and the Paris-based Centre d’Etudes Prospectives et d’Informations Internationales (CEPII). An important contribution of this project has been an exhaustive coverage of preferential trade arrangements (PTAs) across the world, combined with calculation of the AVE of specific duties. Combined with differences in the bilateral composition of trade, the result is that protection varies by sector and partner for each importer. These data have in turn been integrated with the GTAP database for 2001. We have modified these data further to assume full utilization of the 2001 EU Everything but Arms (EBA) initiative as well as AGOA for those African countries benefiting from more liberal rules of origin, as this has been implemented over a period extending beyond the benchmark year of the original protection data. We have also imposed the elimination of ATC quotas on textiles and clothing on the benchmark, an event which occurred on January 1, 2005. This is of course an important dimension of preference erosion in its own right, insofar as the constraint on the most efficient producers under the ATC implied there was an “implicit” preference for the non- or less-constrained developing country exporters. The impacts of the ATC are assessed in greater detail in Francois, Spinanger, and Woertz (2005)—we return to the magnitude of the associated erosion in the concluding section.

The model itself is a relatively standard general equilibrium model, with CobbDouglas consumer demand over broad categories, and CES-based demand within product categories. For primary sectors, this is Armington-based trade (see the discussion in Francois and Reinert 1997), while other sectors are modeled as being monopolistically competitive. Scale elasticity estimates are based on Antweiler and Trefler (2002) and Francois (2001).<sup>23</sup> Factor supplies are fixed nationally, and are allocated between sectors through factor markets.

The experiment itself is relatively straightforward. We eliminate, on a multilateral basis, all OECD import tariffs on all goods. This includes the ad-valorem equivalents (AVEs) of specific tariffs and
**Table A9** Secular Trends in IPV in ELA Only Communities

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||**IPV often **<br>**Non-Goal**|**index**<br>**Goal**|**IPV in last **<br>**Non-Goal**|**year index**<br>**Goal**|
|Post|-0.033<br>|-0.350***|-0.071|-0.296***|
||(0.059)|(0.107)|(0.060)|(0.102)|
|Observations|1,285|458|1,285|458|

_Notes._ Each column in this table presents coefficient estimates of _θ_ 1 from a separate estimation of the following specification: _Yic_ = _α_ + _θ_ 1 _Postt_ + _ψagei_ + _εic_ . In columns 1 and 3, the sample is restricted to non-goal setting participants in ELA only communities. In columns 2 and 4, the sample is restricted to goal setting participants in ELA only communities. The outcome in columns 1 and 2 is the IPV often index and the outcome in Columns 3 and 4 is the IPV in last year index. Standard errors, clustered at the club level, are presented in parentheses below coefficient estimates. .01 ***, .05 **, .10 *. _Source._ Female baseline and endline data, balanced panel, restricted to females in ELA only communities.

**Table A10** Impact of Treatments on Intimate Partner Violence (Restricted to those who report sometimes or never condom use at baseline)

||(1)|(2)|(3)|(4
8% of respondents) and agriculture (22.9%), followed by small business activities (11.9%). Over forty percent of the household heads are illiterate or can only sign their name.

Almost half of the households are members of a microcredit organization which is consistent with other data on micro-finance membership (e.g. World Bank 2008). Consistent with this high level of micro-credit borrowing, access to credit is not perceived by households to be an important constraint: 72.4% of households had a loan at the time of the interview and 86.4% report that they could get a loan if needed during an emergency. A significantly lower 4
methods on survey responses and measurement of land rights. At a descriptive level, the standard practice of obtaining data on individuals’ land rights from proxy respondents -even if they profess to be knowledgeable- rather than directly from (co-)owners may under- (over)estimate the extent to which women (men) have (co-)ownership rights while exhibiting the opposite bias in terms of the type of rights female or male (co-)owners can exercise.

Regression analysis using the IHPS data as -reported by all individual parcel owners suggests that genderspecific (long-term) rights to transfer land via bequest or sale (but not (short-term) rights to make decisions on investment or production) affect investment and diversification into cash crops. Right holders’ gender matters on its own and in interaction with local norms: Female bequest and, in non-matrilineal inheritance regimes, sale rights affect investment in soil fertility (proxied by the use of organic manure) whereas male bequest rights increase the level of cash crop adoption.

These results cannot be replicated using the data from the IHS4 which allowed for proxy reporting on parcel ownership and rights. This finding materializes despite the IHS4 sample being significantly larger and 3
them to cut back on essential expenditures such as food, education or health, with potential long-term implications for human capital and the perpetuation of poverty.

Countries heavily dependent on remittances such as Guatemala and its Central American neighbors must be prepared for such negative shocks. One possible policy approach comprises strengthening social assistance mechanisms to protect vulnerable households. This could include expanding the coverage of existing programs to households with migrants, even if these households are not necessarily among the poorest. Of course, wider safety nets have substantial fiscal implications. Emerging evidence from the COVID-19 pandemic, however, suggests that countries with stronger social assistance platforms in place were better positioned to quickly provide necessary relief (World Bank 2020b).<sup>xxvi</sup> In doing so, they likely more effectively mitigated the transmission of negative effects and limited longer-term consequences, including those on the human capital of the next generation that we found to have been significant after the 2008 Great Recession.

# **5. Conclusions**

Research demonstrates that migration is closely linked to improvements in individual- and household-level well-being and children living in migrant households often have better human capital outcomes. In this paper, we examined whether an economic crisis emanating from the United States affected children in migrant households in a predominantly indigenous, rural region of Guatemala characterized by high outmigration, poverty and child undernutrition. The 2008 Great Recession had substantial negative effects on migrants living in the United States, but full assessment of the crisis must incorporate effects transmitted elsewhere.

Using difference-in-difference strategies with panel data and baseline measurement prior to the economic shock, we find that young Guatemalan children were negatively affected by the