rafmacalaba/data-use-mentions-extended huggingface dataset:
week-of-sample by two-degree grid cell level; when I instead impute length distributions at the one-week-of-sample by one-degree grid cell level, I find that the closures policy increases juvenile catch by 49% (delta method standard error is 5.7%).<sup>45</sup> Figure C1a displays the resulting length distribution data for all sets. I calculate the number of individuals caught by non-SNP sets with each set’s length distribution and tons caught.

For example, suppose the reported percentage juvenile for a non-SNP set is 20%, the individuals-weighted average percentage juvenile among SNP sets in the two-week-of-sample by two-degree grid cell is 10%, and the average length distribution for the two-week-of-sample by two-degree grid cell is as follows: 2% of individuals are between 11 and 11.5 cm, 8% of individuals are between 11.5 and 12 cm, 60% of individuals are between 12 and 12.5 cm, and 30% of individuals are between 12.5 and 13 cm. Then the imputed length distribution for the set is: 4% of individuals are between 11 and 11.5 cm, 16% of individuals are between 11.5 and 12 cm, 53.33% of individuals are between 12 and 12.5 cm, and 26.67% of individuals are between 12.5 and 13 cm. This length distribution implies that the average weight of individuals caught by this set is 12.1 grams. If the set caught 50 tons of anchoveta, then it caught 4,132,685 individual anchoveta, of which 826,537 are juvenile.<sup>46</sup> Next, I match all sets to landing events in order to correct the length distribution, percentage juvenile, and number of individuals caught by all sets. Unlike vessels in the electronic logbook data, the closures policy does not give third-party inspectors an incentive to misreport percentage juvenile because the regulator does not use landings data to determine closures during my study period.

Vessels report when
As a result, they tend to save more in good times, increasing their consumption by less than the increase in income. Specifically, we follow the specification of this type of preferences explored by Aizenman (1998). In this setting, loss-averse agents tend to treat the future asymmetrically, assigning a greater probability weight to bad states of nature (compared to the probability weights that they would assign in the conventional case) in measuring expected utility. As a result, saving responds asymmetrically under loss aversion, in contrast to the conventional expected utility framework.

# **3 Econometric Methodology**

The econometric approach used in this paper to assess the extent to which terms-of-trade shocks affect asymmetrically private savings dwells on timeseries, cross-country regression techniques. A key step in the estimation is to distinguish between the transitory and permanent components of the terms of trade. The permanent component of the terms of trade is measured by the trend series obtained with three different filters: the standard Hodrick-Prescott (HP) filter, an "optimal" version of the HP filter, and a nonparametric method. In each case, the filtered series is used to capture the transitory component of terms-of-trade shocks.

The filtering techniques used here can be briefly presented as follows. Consider a seasonally-adjusted variable _Xt_ that can be written as the sum of an unobserved trend component, x*, and a residual cyclical component, **x4:** The standard HP filter (see Hodrick and Prescott (1997)) employs an adjustment rule whereby the trend component moves continuously and adjusts gradually. Formally, the unobserved trend component x* is extracted by solving the following minimization problem: Thus, the objective is to select the trend component that minimizes the sum of the squared deviations from the observed series, subject to the constraint that changes in _x*_ vary gradually over time. The Lagrange multiplier (or smoothing parameter) A is a positive number that penalizes changes in 9
12 _uncompetitive prices_ , and _unreliable delivery_ constitute important reasons to import inputs instead of using local suppliers.

Most evidence as to how characteristics of local suppliers restrict the level of local sourcing is based on the perception of foreign firms. An exception is a study (Jordaan 2011b) that utilizes survey information obtained from a random sample of local suppliers of two types of firms: MNC affiliates and large domestic producer firms in northeastern Mexico. For 10 of 11 different problems that local suppliers experience with their client firms, suppliers of MNC affiliates indicate that they experience these problems more frequently. Most suppliers of MNC affiliates indicate that their client firms have very strict price demands. Other problems that these suppliers often encounter include an inflexibility to change product specifications, the need for client-specific investments, and rigid demands regarding product quality.

_Improvements in performance triggered by problems with inputs (pecuniary externalities)_ . Although these problems may limit the use of local suppliers, they may also _trigger changes in conduct and foster technology dissemination_ , culminating in productivity spillovers. Positive pecuniary externalities occur when domestic firms respond to stringent input demand conditions by improving their performance. Good examples of this effect are provided by Atkin, Khandelwal, and Osman (2017) and Godart and Görg (2013). The latter use WBES data for more than 1,000 domestic firms in a number of emerging economies to estimate drivers of productivity, including variables that capture whether domestic firms supply to MNC affiliates, whether their client firms have put pressure on them to lower production costs and/or supply better products, and an interaction term between having foreignowned client firms and experiencing pressure to improve. Their findings show that of these three control variables, only the interaction term carries a significant and positive coefficient, suggesting that the strict requirements that foreign firms apply to their demand for inputs result in positive productivity effects among domestic suppliers.

_Support to local suppliers from MNC affiliates_ . As for technology dissemination, MNC affiliates often provide support to (potential) local suppliers when they perceive that doing so
_We underscore the critical importance of rejecting protectionism and not turning inward in times of financial uncertainty. In this regard, within the next 12 months, we will refrain from raising new barriers to investment or to trade in goods and services, imposing new export restrictions, or implementing World Trade Organization (WTO) inconsistent measures to stimulate exports._

- G20 Declaration, November 15, 2008

# **1. Introduction**

The imposition of the Smoot-Hawley tariffs during the early days of the Great Depression has since established a widespread presumption that import tariffs and other forms of trade protection rise during periods of macroeconomic weakness. During the Great Recession, the fear of new import restrictions led to pre-emptive statements like the G20 Declaration of November 2008.

This paper uses quarterly data for the United States, European Union, Australia, Canada, and South Korea to estimate the impact of macroeconomic shocks on import protection policies over 1988-2010. We find evidence of a robust countercyclical trade policy response in the pre-Great Recession period of 1988:Q1-2008:Q3. For example, a one standard deviation increase in the change in the domestic unemployment rate is associated with a 52 percent increase in the number of imported products over which an economy initiates new temporary trade barrier investigations in the following quarter. Other macroeconomic factors also have important effects on trade policy; a one standard deviation appreciation in the bilateral real exchange rate leads to a 33 percent increase in import protection while a one standard deviation _decrease_ in the growth rate of real GDP in a foreign trading partner results in a 60 percent increase. Finally, when we extend our analysis through 2010:Q4 so as to analyze the Great Recession, one noteworthy change is to the relationship between import protection and a _trading partner’s_ economic growth. During the Great Recession, governments refrained from imposing new temporary trade barriers against trading partners experiencing their own weak or negative economic growth.

Our evidence paints a complex picture of the role that macroeconomic shocks play in determining trade policy for countries bound by the WTO. In
munities, the government proved unable to reduce the power of village heads (Alexander, 1996, p.187). The Report of Land Tenure Commission, published in 1994, concluded that village heads remained much more powerful than VIDCOs and continued to perform wide-ranging functions (Ncube, 2011, p.94). Another study noted that where VIDCOs were successful, it was because they served as advisers to rather than rivals to the village head (Munro, 1998, p.270).

Since the mid-1990s, the government has focused on trying to regulate village heads, rather than creating parallel institutional structures. Village heads now have official recognition and receive small salaries of $25 per month from the state. They have official duties per Zimbabwean law, including collecting levies and taxes, maintaining an up-to-date population register, and allocating land. There are regulations regarding the procedures through which they are supposed to make decisions and how to treat villagers. However, village heads continue to have much more de facto power than they do under the law, and they frequently do not follow regulated procedures. Indeed, many village heads have retained a measure of independence from both formal legal regulations and informal partisan pressures to support Zimbabwe’s ruling party. Village heads are much more divided in their political loyalties than higher-level traditional leaders, who have been more thoroughly co-opted by state patronage.<sup>7</sup> The main complaints against village heads are that they abuse their power by allowing their personal interests and biases to enter into their decision-making. In particular, they do not follow regulations requiring broader consultation before making decisions and they are frequently accused of self-interested behavior and favoritism, especially, in Zimbabwe’s polarized political system, along partisan lines.<sup>8</sup> Village heads are often accused of favoring their co-partisans in food distribution and court cases. Importantly, many but not all of these complaints are against village heads affiliated with the ruling party; village heads affiliated

> 7An underground pro-democracy organization in
, while represents communes; and every household h is nested h= 1, . . . ; II withing a community . Equation 1 summarizes the model for the log of household per capita expenditure cc= 1, . . . ; CC l ) as a function of covariates , which vary by household h in community .<sup>8</sup> cc cch cch (yy xx cc

> 6 EHCVM (Enquête Harmonisée sur le Conditions de Vie des Ménages 2018–2019, Harmonized Survey on Household Living Standards 2018–2019), Living Standards Measurement Study, World Bank, Washington, DC, https://microdata.worldbank.org/index.php/catalog/4292.

> 7 RGPHAE 2013 (2013 Recensement Général de la Population et de l'Habitat, de l'Agriculture et de l'Elevage; Population and Housing Census, 2013) (dashboard), National Agency of Statistics and Demography, Dakar, Senegal, https://www.ansd.sn/enquete-et-etude/recensement-general-de-la-population-et-de-lhabitat-de-lagriculture-etde-lelevage.

> 8 Even though it is popular, the logarithmic transformation is not always ideal, especially for small values of welfare where it can produce left skewed distributions. The analysis implemented a data-driven approach to transformations by Box-Cox tests and a log-shift transformation, with the objective of selecting one that reduces departures from normality (see Corral Rodas et al. 2022). Simulation studies show that data-driven transformations may reduce bias and noise caused by departures from normality (see Corral Rodas et al. 2022; Tzavidis et al. 2018).

7
- 7-

# Sector of Employment

The second dimension of the matrix is the sector in which graduates of the different modes are expected to work. These include agriculture, industry and commerce/services. The skills to be taught -- and thus curricula, institutional design, and costs-- very considerably across these sectors.

# Country Income Level

A third dimension has also been important in these analyses. This is the per capita income level of the country in which investments are made. The analysis uses the national per capita income categories as reported by the World Bank in the World Development Report. Income serves as a rough indicator of the nature of the economy that is to be served by training, an extremely important dimension given the crucial place that employment oppottunities hold in establishing the external efficiency of training institutions.

Our general review of the pattern of Bank investments in the education sector covers each of these modes and employment sectors, as well as investments in all forms of general education. The review of project experience does not deal with university-level VET, general teacher training or diversified secondary schools, focusing instead on secondary, post-secondary, non-formal and teacher training investments and institutions.
formal savings account; (iii) household members can access formal credit if needed; (iv) household has saved in last 4 weeks; (v) household savings in last 4 weeks; (vi) household total savings.

4. **Psychological well-being index** : A psychological well-being index is computed separately for women and men as the standardized weighted average of scores on the Center for Epidemiologic Studies Depression (CES-D) 7-point scale (Radloff 1977), the World Values Survey (WVS) questions on happiness and life satisfaction, Cohen’s 4- item stress scale (Cohen, Kamarck, and Mermelstein 1983), and the log of cortisol levels obtained through saliva samples adjusted for confounders.<sup>14</sup> We adapted some questions in these indicators to the social, cultural and religious norms in the country. For this we used a combination of extensive piloting, and topic and local expertise from research members with expertise in the area and in Afghanistan.

5. **Women’s empowerment index** : We consider two indices. The first is a standardized index combining indicator variables for whether the women’s decision was taken into consideration and/or followed on household finances (credit and savings) and expenditure decisions (food, household repairs, clothing, land, property and other high-value expenditures). This set is consistent with other studies and was prespecified in our pre-analysis plan (PAP). The second is a standardized index with additional indicators on voice and agency. This broader index was not pre-specified, but was constructed to follow internationally agreed standards from the United Nations and Klugman et al (2014). This second set includes the original indicator plus five other dimensions: (i) women’s participation in decisions on children’s investments; (ii) women’s participation in decisions related to their own fertility, time use, and mobility to work outside home and open a business, as well as effective access to inputs and resources including ownership
# **1. Introduction**

Financial inclusion, typically defined as the use of formal financial services, has become a subject of growing interest for researchers, policy makers, and other financial sector stakeholders.<sup>1</sup> Financial exclusion is problematic when it is involuntary. In other words, exclusion deserves policy action when there are individuals whose marginal benefit from using financial services exceeds the marginal costs, but who are excluded by barriers—such as high account fees, large distances, and lack of suitable products—that result from market failures. The market failures could be due to a host of factors, such as imperfect information, noncompetitive markets, shortcomings in the contractual environment, and lack of physical infrastructure.

A growing body of research using field experiments shows that financial inclusion can have significant beneficial effects for individuals, providing both an economic and a political rationale for policies that promote financial inclusion.<sup>2</sup> In particular, the evidence is most compelling when it comes to the use of bank accounts. Having a bank account increases savings (Aportela, 1999), female empowerment (Ashraf et al., 2010), and consumption and productive investment of entrepreneurs (Dupas and Robinson, 2009).

In addition, previous studies focusing on the unbanked in the US have argued that not having a bank account can have a wide range of harmful effects. For instance, the lack of a bank account can make liquidity management and payments difficult, which could result in high fees associated with the use of money orders or check-cashing services (Lusardi, 2010). Also, cash transactions present financial and personal risks for those unbanked, since individuals have no

> 1 In its most recent communiqué, the G20 agreed to “take the financial inclusion agenda forward” and “to assist countries, policymakers and stakeholders in focusing global efforts on measuring and sustainably tracking progress on access to financial services globally.” Furthermore, according to a recent survey of bank regulators across 143
average dry air mixing ratio of methane<sup>4</sup> ), corrected for bias associated with XCH4 dependence on surface albedo.<sup>5</sup> Recent global research by Sha et al. (2021) has shown that S5P CH4 measures correspond very closely to independent measures taken at ground stations maintained by TCCON (Total Carbon Column Observing Network).<sup>6</sup> Sentinel-5P’s bias-corrected XCH4 data exhibit a difference of −0.26±0.56 % when compared with the corresponding TCCON data. Per the ESA’s recommendation, we use only pixels with quality values greater than 0.5. The data have been

> 4 the total atmospheric column between the surface and the top of the atmosphere normalized to the corresponding dry air column.

> 5 For more technical details, see the documentation at https://sentinel.esa.int/documents/247904/3541451/Sentinel5P-Methane-Product-Readme-File

> 6 Current TCCON sites are located in the United States, China, Canada, Germany, Poland, France, Japan, Australia, New Zealand, the Republic of Korea, Réunion, and Ascension Island.

3
Given this result, we next check whether treatment decreases the male head‘s knowledge of the candidate choice of women in his household. Using follow-up survey data which asked the male head and each woman in the household about whether other women in the household had cast a vote and for whom they had voted, we construct cross-reports regarding candidate choice. Using these cross-reports, we find that male heads in treated households are indeed significantly less informed about the candidate choice of women in their households.

Interestingly, we also find evidence of cognitive dissonance (e.g., Mullainathan and Washington, 2009). Women in control clusters, among whom turnout was lower, were less likely to believe that the election was free and fair and more likely to report witnessing or hearing instances of violence in the village, compared to reports by women in treated clusters.

While there is an extensive literature on the impact of Get-out the Vote or GOTV campaigns in developed countries, and in the US in particular (see Gerber and Green, 2000a and 2000b), much less is known about the impact of such campaigns in developing countries where voters tend to have poorer access to information and institutionalized party structures are also much less developed (Aker et al. 2010, Banerjee et al. 2010 and Pande 2011 for a review).<sup>7,8</sup> This paper contributes, therefore to two literatures. First, it adds to this nascent literature on preelection voter information campaigns in developing countries. Second, it is the only paper which, to our knowledge, assesses the impact of information externalities on voter turnout and candidate choice. This is critical for correctly measuring the cost-effectiveness of an information campaign, but it is also important for assessing the types of information that can be successfully transmitted through social networks.<sup>,</sup> In this regard, our paper is closest to Duflo and Saez (2003) and contributes also to the burgeoning literature on social networks and peer effects (e.
Suharto era Post Suharto era Suharto era Post Suharto era<br>.4 .2<br>.2 .1<br>0<br>0<br>PC family PC family<br>β β -.1<br>-.2 -.2<br>-.4 -.3<br>.2 4<br>0 2<br>PC family-.2 PC family0<br>β β -2<br>-.4<br>-4<br>-.6<br>.4 .4<br>.2<br>.2<br>0<br>PC family PC family<br>β 0 β -.2<br>-.2 -.4<br>.5 .5<br>PC family0 PC family0<br>β -.5 β -.5<br>-1 -1<br><!-- End of picture text --> _Note:_ The figure depicts annual variation in the estimated impact of the market share of Suharto family firms on the outcome of interest. The dots depict the coefficient estimates ′93 ′94 ′09, estimated using the regression: = ∑ Y Y which are presented in Table jjii αα , αα , ... ... . αα YY C5.1, with 1996 as the omitted year. ii=1993,..,2009 ii jj ii=1993,..,2009 measures the aggregate market share of Suharto family firms (the average of ii jjii jj ii jjii αα PC (MMSS) ∗DD(Y = tt) + ∑ γγ SS ∗DD(Y = tt) + ππ + ττ + εε their aggregate market share in 1996 and 1997), jj measures Suharto-era (time-invariant) industry characteristics, is a PC (MMSS) vector of industry fixed effects, and is a vector of year fixed effects
<!-- Start of picture text --> Age-groups: 45-54 years, 55-65, 65-74, 75-84, 95»<br>All-cause deaths (expected): 2020 Excess deaths: 2020 Excess deaths: 2021<br>N countries = 66 N countries = 54 N countries = 57<br>10<br>a °<br>8 o (|? — °<br>° i re} y, |\ O °<br>° mAOTO ° 5<br>omy } ' aE v I °<br>° : 0 e<br>ane J 4 5 5° i<br>4 +c i Oo incO y=lo £9 \ 2)52 eee = 0 0 D o: = — om<br>° & OoOo eawehishiy/ Bam D> <1 RAY Ao£25 5S° Ooooer °o. o 0 peicra2 ‘:<br>° LEE eve: = O 30s Meee ae 0 ? 0 ° elle l= ° 05 e<br>° ° 8 ) i?) role} ° 6) ° ° 8<br>foo<br>0 ° 8<br>$20,000 $40,000 $60,000 $20,000 $40,000 $60,000 $20,000 $40,000 $60,000<br>GNI per capita (PPP)<br>Note: Results are based on the country-specific Poisson model described in the text applied to the WHO Global<br>Excess Deaths dataset. Each point represents the median predicted relative risk of mortality between men and women<br>for a single country from a simulation of 1,000 parameter draws of the Poisson model. The lines for each group are<br>loess fits of this median ratio of predicted mortality, using 85% of the points in the neighborhood at each point<br>along the x-axis. The shaded areas show the
or close contacts on whether the individual in our sample was currently operating a business. This enables us to have data on survival status for 99.3 percent of the sample at one year, and 97.2 percent at three years. There is no significant difference in data availability with treatment status at the three-year horizon, although those assigned to treatment are 1 to 2 percentage points more likely to have data available at the one year horizon.

In addition to the survey data, we have two other sources of information that aid in assessing impact. The first are photos of the inventories of the businesses, which were taken at the time of the baseline survey and in rounds 2 and 4. We had two independent field staff value these inventories based on the market prices of the different items, and average these values to get a 10