rafmacalaba/datause-encoder-data huggingface dataset:
the asset; who can decide who inherits the asset; and who can decide what type of crops to cultivate.

Based on the findings from the first phase, the project produced a Gender and Assets Toolkit<sup>11</sup> , which includes a list of best practices for collecting gender and assets data at the project level. The best practices highlight (1) the importance of using both quantitative and qualitative research methods for understanding complex gender and assets dynamics, and (2) the need for analyzing gender asset gaps over time rather than simply capturing snapshots of men’s and women’s control over assets. In addition, this list focuses on the importance of tailoring data collection methods to specific contexts and measuring ownership, use, and control rights rather than simply focusing on asset ownership.

# **3.4 Women’s Empowerment in Agriculture Index**

The Women’s Empowerment in Agriculture Index (WEAI) survey instrument, developed by the IFPRI, Oxford Poverty and Human Development Initiative, and the United States Agency for International Development (USAID), captures data on five domains of empowerment in agriculture, one of which is the access to and control of productive capital.<sup>12</sup> The purpose of the survey instrument is not to identify individual asset ownership, but to collect data to use in an indicator of women’s empowerment in agriculture.

The WEAI was piloted in Bangladesh, Guatemala, and Uganda in 2011-12 and has since been collected in baseline surveys for Feed the Future’s 19 focus countries across Asia, Latin America, and Africa south of the Sahara. In general, these surveys are representative of Feed the Future’s zones of influence. In some cases, the WEAI modules are integrated in larger surveys, but in all cases, the WEAI is administered with a Household Questionnaire, which includes a household roster. Within each household, the individual survey instrument is administered to both a primary and a secondary respondent—one man and one woman aged 18 and over—who are self-identified as the primary members responsible for social and economic decision making within the household. They are usually, but not necessarily, husband and wife. The interview may also be conducted solely with a woman primary respondent if there is no adult man in the household.

Questions on productive assets are included in the section for the domain on control of productive capital. Each respondent is asked a series of questions about agricultural resources and assets, including agricultural land, large livestock, small livestock, poultry, fish pond/fishing equipment, mechanized and non-mechanized farm equipment, nonfarm

> 11 The toolkit can be accessed at <u>https://tinyurl.com/gaaptoolkit.</u>

> 12 For more information on the WEAI, please visit <u>https://www.ifpri.org/topic/weai-resource-center.</u>

12
|TBT|Technical Barriers to Trade|
|---|---|
|TEU|Twenty Feet Equivalent Unit<br>|
|TF|Trade Facilitation|
|TTF|Transport and Trade Facilitation|
|TTFSE|Trade and Transport Facilitation in Southeast Europe|
|UNCTAD|United Nations Conference for Trade and Development|
|UNECE|United Nations Economic Commission for Europe|
|UneDocs|United Nations electronic Trade Documents|
|UNESCAP|United Nations Economic and Social Commission for Asia and the Pacific|
|UNIDO|United Nations Industrial Development Organization|
|US|United States|
|VAT|Value Added Tax|
|WB|World Bank|
|WCO|World Customs Organization|
|WTO|World Trade Organization|

3
<!-- Start of picture text --> Nepal<br>India<br>;<br>ae:<br>« “nr ] \<br>; Bay of Bengal<br>Bangladeshi0.287 - 0.750 Population (% Total Pop.) Myanmar<br>10.751 - 1.000<br>MM 1.001 - 1.400<br>Ml 1.401 - 1.900<br>MMM 1.901 - 8.805<br>EE<br><!-- End of picture text --> <!-- Start of picture text --> ge.<br>8,459 - 18,000<br>| 18,001 - 26,000<br>Ml 26,001 - 31,000<br>aoa MMHM 31,00136,001 -- 36,00057,147<br>4<br>Myanmar<br>.<br>4<br><!-- End of picture text -->
It is essential for the mechanism of the model to assume that when a government defaults, international lenders cannot seize the international reserves held by the central bank. Otherwise, the relevant statistic would be the foreign net position, as in Arellano (2008). To illustrate this point, suppose that after a default, a central bank cannot maintain control of its reserves. Therefore, accumulating reserves would increase the repayment value but not the default value. Thus, buying one reserve asset would decrease the probability of default to the same magnitude as increasing debt by one bond, but in the opposite direction. Subsection 2.3 describes the case of Argentina in 2015, which is consistent with this assumption and guarantees that vulture funds will not be allowed to seize the reserves held by an independent central bank.<sup>7</sup> The model is solved numerically to evaluate its quantitative predictions regarding the levels of international reserves, public debt, and sovereign spreads. I calibrate the model using data for Mexico, a typical emerging economy with an independent central bank, which is a common reference for studies on reserve accumulation. The central bank’s discount factor is disciplined by matching the money market interest rate, and the government’s discount factor is calibrated internally by targeting public debt.<sup>8</sup> I find that, under the benchmark calibration, model simulations account for 75% of the average level of reserves observed in Mexico from 1994 to 2017. Moreover, I also find that in periods of high income and low spreads, the government increases borrowing and the central bank accumulates more reserves, which accounts for a high and positive correlation between reserves and debt that is consistent with the pattern observed in the data.

Finally, I contrast the baseline model with an economy in which the central bank is as impatient as the government is (i.e. consolidated government). I show that, in accordance with Alfaro and Kanczuk (2009), a sovereign default model with a consolidated government cannot rationalize simultaneously positive levels of debt and reserves. By comparing these two economies, I quantify the welfare gains of having an independent central bank that can accumulate reserves. I find that accumulating reserves by 6 _._ 5% of GDP reduces the net debt position by 3 _._ 0% of GDP and increases social welfare by 0 _._ 1%. Welfare gains come from reducing the costs of front-loading public spending and mitigating the distortion in households’ intertemporal consumption.

> 7Any other government agency that is granted independence, such as a sovereign wealth fund, does not have access to the special status that central bank reserves receive in international law.

> 8By following this calibration strategy, the model can match high levels of debt without implying an outrageous domestic interest rate as standard default models do when assuming a low discount factor.

3
middle were mainly due to the size effect, i.e. the greater number of poor people that exited poverty by connecting with growth in the middle (through non-farm activities in rural areas and secondary towns - which may entail physical migration, but could also happen for example through commuting or simply switching occupations locally).

Together these case study and cross-country results call attention to the spatial allocation and orientation of infrastructure and policies in steering the world’s ongoing urbanization and development. As most recently documented by Ferré, Ferreira and Lanjouw (2012) in 8 countries across the world and Coulombe and Lanjouw (2013) in 12 Sub-Saharan African countries, secondary towns continue to enjoy much lower access to basic infrastructure services than the metropoles, prompting them to voice the possible existence of a “metropolitan bias”, not unlike Behrens and Bala (2013). While the results presented here do not purport to establish causality as such, the findings are consistent with the call for spatially blind provision of social services and infrastructure advocated by the World Bank’s 2009 World Development Report “Reshaping Economic Geography” (World Bank, 2009), so that migration is only motivated by economic opportunities and not by the search for better amenities.

They further suggest that growth promoting interventions that enable poor people to access growth and basic infrastructure services more directly (as through rural diversification and secondary town development) are also more likely to lift more of them out of poverty, than when the benefits of growth have to spatially trickle down from the metropoles. But most importantly, the empirical regularity with which these relations have been observed, and their robustness against a series of alternative hypotheses, underscore the pertinence of the question and call for much deeper reflection about the optimality of the ongoing urbanization processes, not least in areas where urban concentration is already high (as in Sub-Saharan Africa).

24
in each industry and year.<sup>39</sup> As in the tariff data, we begin with TTB data at the product-level, aggregate to the HS 6-digit level, extract HS 6-digit categories that correspond to final goods using the BEC classification, and then aggregate to WIOD industries. The TTB coverage ratio is the (unweighted) share of HS 6-digit final goods products within a WIOD sector for which a given importing country has a TTB in effect against a particular trading partner. We construct TTB coverage ratios for each year separately (1995, 2000, 2005, and 2009), which allows for both the imposition of new TTBs and removal of existing TTBs over time.

# **3.4 First Peek at the Data**

Before moving to formal analysis, we pause to introduce the bilateral tariff data, since their use is relatively new to the literature. We first review a few salient facts about bilateral tariff preferences, and then relate observed tariff variation to value-added content in an illustrative case to ideas.

**Tariff Preferences** Our identification strategy exploits differences between bilateral applied tariffs and applied MFN rates. Bilateral applied tariffs differ from MFN tariffs because countries offer preferential (lower-than-applied MFN) tariffs to selected partners under various preference schemes. We provide a summary description of these schemes and their relative importance here, with details provided in Appendix B.

There are four main sources of tariff preferences in our data. The first is the Generalized System of Preferences (GSP), which accounts for the majority of preferences. It is an explicitly unilateral (non-reciprocal) preference scheme, in which developing countries receive preferential treatment from high-income importers.<sup>40</sup> An important feature of the GSP program is that each GSP-granting country unilaterally chooses the set of GSP-receiving countries to which and sectors in which it extends preferences, and these choices differ across GSP-granting countries and time.

Free trade agreements and customs unions, authorized under WTO Article XXIV, are a second source of preferences. These agreements embody a high degree of reciprocity, in that

> 39In constructing these coverage ratios, we follow the approach described in Bown (2011). Coverage ratios are a convenient tool for aggregating TTBs across products and measuring their overall intensity, which avoids needing to convert heterogeneous TTB measures (e.g., ad valorem duties, specific duties, price undertakings, or quantitative restrictions) into ad valorem equivalents. For emphasis, the coverage ratio measures the stock of TTBs in force, not the flow of newly imposed TTBs. Further, the stock measure accounts for removal of TTBs as they expire.

> 40In our data, GSP-granting countries include Australia, Canada, the EU, Japan, Russia, Turkey, and the United States; recipients include Brazil, China, India, Indonesia, South Korea, Mexico, Russia, Turkey, and Taiwan.

23
and _T_ periods, the relationship between the prices of goods in different regions and periods is assumed to follow: where  _j_ , _t_ is the price level in region _j_ and period _t_ relative to the base region/period,  _k_ is the price level of good _k_ relative to the base good, and<sup>_u_</sup> _k_ , _j_ , _t_ is a random disturbance term. The price parameters (  _j_ , _t_ and  _k_ ) in equation (1) can be directly estimated in a log-linear regression model, using the _K_  _J_  _T_ prices from a spatially disaggregated price survey: where the weight _wk,j,t_ for good _k_ in region _j_ and period _t_ is described below, _Dj,t_ is a dummy variable for region _j_ and period _t_ , _Dk_ is a dummy for good _k_ , and <sup>ˆ</sup> is the intercept plus the coefficient of the omitted base category dummies.

We use two types of weights so as to generate two price indexes for evaluating deflators from the food Engel curve. These represent two of the three broad approaches to approximating a cost-of-living index, with the demand systems approach not used. First, we use a variable-weight price index, by using as weights: ( _skj_ , _t_<sup></sup> _sk_ 01,/) 2 where _skj,t_ is the average budget share of item _k_ , in region _j,_ and time _t_ , and _sk0,_ 1 is the average budget share for item _k_ in the base period in region 0 (which we set to be the urban sector of the Red River region, where Hanoi is). We refer to this price index as WCPD_vw (for variable-weight), which gives estimated time-space deflators: 16
shifts that are robust to the endemic non-normality.

We begin by documenting the heterogeneity in the ways in which country distributions differ from the frontier benchmark, the US, and highlight some important regularities characterizing the convergence process. While relatively longer left tails do characterize underdevelopment, this is not true among more advanced countries for which it is the best firms that lag the frontier. Further, across the development process, the median score moves up broadly proportionately with the mean, implying that movement in the overall mass of the distribution is a critical part of the process.

We then revisit the issue of which factors appear to drive these difference in managerial quality across the whole distribution, employing recent advances by Machado and Mata (2005) and Firpo et al. (2009) to decompose the contributions of covariates and coefficient differences. In particular, we confirm Bloom and Van Reenen (2007)’s findings, and recently those of Bandiera et al. (2013) about the importance of ownership and in fact find the effect emerges much more strongly across the global sample than in their four advanced country sample and is especially important for the poorest countries. Likewise, the human capital of the managers appears central, particularly among more advanced countries. This suggests that the mechanics of convergence change across the process. However, the competitiveness of the firm environment does not seem to be driving the distributions for most countries and this is especially the case, surprisingly, in the lower tails where we might expect competition to be most biting.<sup>6</sup> Finally, the explanatory power of the covariates appears to decrease with the quality of management. That is, we can explain less in the rich countries than in the poor at every quantile, and less among the best firms than among the worst in a given country.

> 6As they note, competition could work either through the more rapid exit of badly managed firms and/or the inducement of greater managerial effort. They cite Syverson (2004a, 2004b) who focuses on productivity and offers supportive evidence for these predictions in his analysis of the U.S. cement industry, finding that tougher competition is associated with both a higher average level of productivity and a lower dispersion of productivity, as the less efficient tail of firms have been selected out. On the other hand, they also note that the sign is not a priori obvious. Profit margins will be lower when competition is more intense, so the rewards of the profit related component of pay will also be lower, and this could tend to depress managerial

2
the proportion of persons stating that tax evasion is never justified by 1.5 percentage points. These findings demonstrate the relevance of institutions that enhance political participation and trust in the parliament and the justice system. Such institutions have beneficial effects on social capital and the political outcome not only in Western Europe but also in Eastern Europe as Frey (2003a) shows.

Torgler and Schneider (2007a, 2009) show that that improving governance and institutional quality and tax morale helps lessen a possible incentive to go underground. The results are quite robust using more than 25 proxies of governance and institutional quality, testing for endogeneity and running a broad variety of specifications. _Table 1_ provides an overview of the results. Working with a survey done in the Czech and Slovak Republics, Hungary, and Poland, Hanousek and Palda (2004) find strong support that there is a positive correlation between tax evasion and the perceived government services based on the taxes paid.

If institutions affect tax morale and the shadow economy, it may be worthwhile to explore also its impact on tax performance. The level of tax performance is related to the availability of what may be called the ―exit option‖ of the so-called shadow economy. In general, the larger the shadow economy, the lower we would expect tax effort to be. Hence, one can measure the extent of tax effort to discover whether institutional quality (measured by corruption and voice and accountability) affects that behavior. In other words, it may be important to explore not only traditional variables such as tax burden, the sectoral composition, the richness of a country or the labor market conditions - but also institutional and governance quality. The more taxpayers believe that others work in the shadow economy, the lower the moral costs of behaving dishonestly and evading taxes by moving their own activities to the shadow economy. In this way the potential intrinsic motivation to comply and contribute to public sector activities gets crowded out. This relationship has been shown empirically by Bird et al. (2006). Public finance matters are usually resolved through political channels, hence, as mentioned previously, history suggests that the need to secure an adequate degree of consensus from the taxed is one of the principal ways in which democratic institutions have spread. A better political system is more interested in providing citizens what they want, and it transmutes individuals‘ and firms‘ preferences into policy decisions in a more efficient manner (Bird et al., 2008).

16
# Housing Subsidies for Refugees: Experimental Evidence on Life Outcomes and Social Integration in Jordan<sup>*</sup>

_⃝_ r Abdulrazzak Tamim<sup>2</sup> Emma Smith<sup>3</sup> I. Bailey Palmer<sup>4</sup> Edward Miguel<sup>5</sup> Samuel Leone<sup>6</sup> Sandra V. Rozo<sup>7</sup> Sarah Stillman<sup>8</sup>

## **JEL Classification:** D22, J61, O17

**Keywords:** Refugees, Housing, Forced Migration, Social Integration

1 Author order is Certified Random _⃝_ r (AEA Confirmation Code gEv7QgDTbi7f). We are grateful to Hasan Ebussuutoglu, Joaquin Fuenzalida, Jonathan Gorham, Peter Grinde-Hollevik, Mansi Kalra, Meghana Kumar, Charlotte McClelland, Ei Thandar Myint, Jonathan Old, Gufran Pathan, Benjamin Shenouda, and Andy Theocharous for their outstanding support as research assistants. We are also grateful for comments received from seminar participants at University of California Davis, ESOC, World Bank, George Mason University, Georgetown University, American University, and the BITSS Forecasting in the Social Sciences Workshop. University of California Berkeley IRB approval #2019-01-11713. This study is registered in the AEA RCT Registry (AEARCTR-0006141). We gratefully acknowledge financial support from Innovation for Poverty Action’s Peace and Recovery Fund and the World Bank Development Research Group. We thank our Jordan-based implementing partner, and survey firm, Mindset Social & Marketing Research, and in particular, Mohammad Qardan, Rana Samara, and Mohammad Nababteh.

> 2University of California Berkeley, atamim@berkeley.edu

> 3Georgetown University, emma.smith@georgetown.edu

> 4University of California Berkeley, bailey.palmer@berkeley.edu

> 5University of California Berkeley and NBER, emiguel@berkeley.edu

62University of California Berkeley.

> 7World Bank, Development Research Group, sandrarozo@worldbank.org

> 8London School of Economics, s.v.stillman@lse.ac.uk
_Panel B: Inequality_

|Dependent variable: Gini<br>index|Adding<br>country-<br>specific<br>linear time<br>trend|Adding<br>region-<br>specific<br>linear time<br>trend|Adding<br>temperature<br>change|Adding<br>temperature<br>squared<br>term|Adding<br>temperature cubic<br>term|Adding<br>temperature<br>squared term<br>and temperature<br>change|Adding<br>temperature<br>interaction<br>term|
|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|Temperature|0.290***|0.175***|0.537***|0.283***|0.282***|0.533***|0.512***|
||(0.103)|(0.040)|(0.099)|(0.087)|(0.086)|(0.101)|(0.104)|
|∆Temperature|||0.209**|||0.249*|0.099|
||||(0.092)|||(0.135)|(0.164)|
|Temperature squared||||-0.001|-0.003|-0.003|-0.005|
|||||(0.004)|(0.013)|(0.007)|(0.007)|
|Temperature cubic|||||0.000<br>(0.000)|||
|Temperature*∆Tempearture|||||||0.012<br>(0.013)|
|Controlling for rainfall|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Subnational FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Number of countries|128|128|128|128|128|128|128|
|Number of regions|1,484|1,484|1,484|1,484|1,484|1,484|1,484|
|Observations|4,129|4,129|4,129|4,129|4,129|4,129|4,129|

_Notes:_ Robust standard errors in parentheses. Standard errors are clustered at the subnational level. Regressions are weighted by region population. Inequality is measured by Gini index. *** p<0.01, ** p<0.05, * p<0.1 47
22 government **is** far **more severe** in poor areas, and this poses the issuie of how rapidly the benefits of rural industrial development can be expected to diffuse under a policy of local self-reliance.

The independence of the banking system from local pressures in China and clear property rights (including accountability for losses) will be important in maintaining a tight budget constraint for local communities and holding the TVP sector to market-based behavior.<sup>20</sup> Although the problem of predation is most severe for poor areas that seek to use their enterprises to borrow from the banking system to fund current expenses, it could spread to more prosperous areas should China experience a major economic downturn.

# V. Labor Markets and Incentives.

# A. Labor Markets for Rural Industrv

Labor markets are still fragmented in China, with significant obstacles to both rural-urban and rural-rural migration. The extent to which development of the TVP sector is contributing to a loosening of the labor market and the extent to which rural firms face a reasonably competitive labor market are important issues in assessing the incentives for participants in ,he sector and the sector's place in economic reform.

Some indication of the mobility of labor in the four sample counties is provided by data on the original homes of employees in sampled enterprises (table 8). The most striking contrast is between the two advanced areas, Wuxi and Nanhai. In Wuxi, very few employees come from outside the towns or villages of their current employment; in Nanhai, almost half came from outside the community and 15 percent came from other counties or provinces. This is especially striking since Wuxi County is considered to have a scarcity of labor,