rafmacalaba/datause-encoder-data huggingface dataset:
- Gallego, F.A., E. Näslund-Hadley, and M. Alfonso. 2021. "Changing Pedagogy to Improve Skills in Preschools: Experimental Evidence from Peru." _The World Bank Economic Review_ 35 (1): 261-286.

- Ganimian, A.J., K. Muralidharan, and C.R. Walters. 2021. _Augmenting State Capacity for Child Development: Experimental Evidence from India._ (No. w28780): National Bureau of Economic Research.

- Gormley, W.T., D.A. Phillips, K. Newmark, K. Welti, and S. Adelstein. 2011. "Social‐emotional effects of early childhood education programs in Tulsa." _Child Development_ 82 (6): 20952109.

- Gray-Lobe, G., P.A. Pathak, and C.R. Walters. 2021. _The Long-Term Effects of Universal Preschool in Boston._ (No. w28756): National Bureau of Economic Research.

Hamre, B. K., R. C. Pianta, A. J. Mashburn, and J. T. Downer. 2012. "Promoting young children's social competence through the preschool PATHS curriculum and MyTeachingPartner professional development resources." _Early Education & Development_ 23 (6): 809-832.

- Havnes, T., and M. Mogstad. 2015. "Is universal child care leveling the playing field?" _Journal of Public Economics_ 127: 100-114.

- Havnes, T., and M. Mogstad. 2011. "No child left behind: Subsidized child care and children's long-run outcomes." _American Economic Journal: Economic Policy_ 3 (2): 97-129.

Heckman, J.J., S.H. Moon, R. Pinto, P.A. Savelyev, and A. and Yavitz. 2010. "The rate of return to the HighScope Perry Preschool Program." _Journal of Public Economics_ 94 (1-2): 114-128.

- Johnson, R.C., and C.K. Jackson. 2019. "Reducing inequality through dynamic complementarity: Evidence from Head Start and public school spending." _American Economic Journal: Economic Policy_ 11 (4): 310-49.

- Kline, P., and C.R. Walters. 2016. "Evaluating public programs with close substitutes: The case of Head Start." _The Quarterly Journal of Economics,_ 131 (4): 1795-1848.

- Lipsey, M.W., D.C. Farran, and K. Durkin. 2018. "Effects of the Tennessee Prekindergarten Program on children’s achievement and behavior through third grade." _Early Childhood Research Quarterly_ 45: 155-176.

- Martinez, S., S. Naudeau, and V. Pereira. 2017. _Preschool and child development under extreme poverty: evidence from a randomized experiment in rural Mozambique._ Washington D.C.: The World Bank.

Neuman, S.B., and L. Cunningham. 2009. "The impact of professional development and coaching on early language and literacy instructional practices." _American Educational Research Journal_ 46 (2): 532-566.
Policy Research Working Paper 8478

# **Abstract**

The costs of financial intermediation have important consequences for financial development. Using banklevel data for 160 countries during 2005–14, this paper analyzes the composition and sources of bank net interest margins. First, it uses an accounting decomposition framework to provide summary statistics on the size of net interest margins and highlight the cost and profit components in countries, regions, and income groups. Second, it uses regression analysis to examine the underlying bank-level, structural, macroeconomic, and institutional determinants of net interest margins. Finally, the paper uses the results of the econometric analysis to construct country-level bar charts of relative contributing factors to financial intermediation costs. The results provide evidence-based guidance on key areas of structural reforms to reduce the costs of financial intermediation.

This paper is a product of the Finance, Competitiveness and Innovation 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/research. The authors may be contacted at pcalice@worldbank.org and nzhou@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
# **Figure B13: Phosphate**

<!-- Start of picture text --> Log scale<br>6.5<br>Log price Permanent component<br>5.5<br>4.5<br>3.5<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> <!-- Start of picture text --> Log scale<br>2.0<br>Medium-term cycle Transitory component<br>1.0<br>0.0<br>-1.0<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> _— 54 —_
100) of the _Impact Vulnerability_ ( _IVUL_ ) for the host and investor countries of the CDM projects are obtained from Buys et al (2007) and used in our empirical analysis.

Estimates of six dimensions of governance of the host and investor countries are obtained from Kaufmann et al (2007). The six dimensions of governance are: Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption. Kaufmann et al estimate these dimensions of governance of 212 countries during the period of 1996-2006 based on several hundred individual variables measuring the perceptions of governance reflecting the views of public sector, private sector and NGO experts, as well as thousands of citizen and firm survey respondents worldwide. Kaufmann et al (2007) aggregate these individual measures into the above six categories, using a statistical methodology known as unobserved components model. In particular, they first rescale the individual indicators from each underlying source in order to make them comparable across data sources. Then they construct a weighted average of each of these rescaled data sources to construct the aggregate indicators of governance. The weights they assign to each data sources are based on the estimates of the precision of each source that are produced by the unobserved components model. Combining the six governance measures of Kaufmann et al. (2007), a _Governance_ variable ( _GOVR_ ) is constructed, using a Principal Component Analysis (PCA) that reflects overall governance level of the host and investor countries of each of the CDM projects.

We used the ease of doing business (EDB) indicators as a proxy for the transaction costs associated with the CDM projects implementation. EDB indicators, comparing business regulations and protection of property rights across 178 countries and over time are obtained from World Bank (2008). The EDB index ranks economies from 1 to 178 by measuring regulations affecting 10 stages of a business’s life: starting a business, dealing with licenses, employing workers, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts, and closing a business. The index reflects the ranking of simple average of country percentile rankings on each of the 10 topics, with a higher rank indicating less favorable business atmosphere. The ranking on each of the 10 topics is the simple average of the percentile ranking on its component indicators.<sup>7</sup> The rankings remain almost the

> 7 The choice of aggregation method has little influence on the ranking. More complex aggregation methods such as principal components and unobserved components yield nearly identical rankings (Djankov and others, 2005).

11
international trade literature, however, that absent monopoly power on exports, the expansion of value-added through export taxes is socially undesirable. i.e., it will typically reduce economic welfare.<sup>19</sup> It is likely; however, that Russia possesses some monopoly power on the exports of timber. Russia possesses the largest share of world forest reserves (22%),20 and Russian timber plays a significant role on world markets for some products. For example, about 40% of world conifer is produced in Russia.<sup>21</sup> For markets geographically close to Russia, such as Finland and Sweden, Russia’s role is even more important. Finland imports about 25 percent of its timber and about 80 percent of its imports are of Russsian of Russian origin. Russia’s share of the combined Finnish-Swedish timber market is about 11.4 percent.<sup>22</sup> Given some monopoly power on world export markets for Russia, there is a positive export tax that would increase Russian economic welfare. But the planned Russian government’s export tax of 80 percent may considerably exceed the optimal export tax, so it is necessary to analyze the problem more carefully to estimate the optimal export tax.

The analysis of optimal export pricing for Russia on timber exports differs in a crucial way from the gas pricing problem discussed above. In the case of gas pricing, Gazprom has a monopoly on export sales of Russian gas. In the case of timber, there is competition among timber exporters from Russia. If Russia as a whole possesses monopoly power on its timber exports, competition among timber exporters will prevent the firms from exploiting that monopoly power. An export tax by the Russian government could be used to extract the monopoly rents for Russia as a whole.

In general, the Russian government would want the export price to be at a level where the marginal revenue from additional timber sales to the country equals marginal costs. We can use the mathematics of the gas pricing analysis, where the Russian government is playing the role of Gazprom on exports. Abstracting from transportation costs, it is optimal for the Russian government to have its firms charge a price where

> 19 See Takacs (2008) for an excellent elaboration of how export taxes reduce economics welfare.

> 20 See  www.forest.ru.

> 21 “Russian Newspaper (Rossiiskaya Gazeta)”,#4317, 03.16.2007. Internet page: "Российская <u>газета"</u> - <u>Федеральный выпуск No4317 от 16 марта 2007 г.</u>

> 22 Khramov et al.(2008, p4).

15
The second potential threat to validity depends on the existence of general equilibrium effects on local labor markets.<sup>9</sup> Our data suggest that these effects are not likely at play. We do not observe any trend in the control group’s search for employment or employment activity across the different survey waves. The control group’s median income from selfemployment is similar at midline and endline, thereby suggesting that no shifts occurred in economic behavior due to anticipation of the program. In addition, given that the casual labor markets in Djibouti are segmented by gender and virtually absent for women, general equilibrium effects on the local labor market are unlikely.

# **4. Empirical Approach**

## **4.1. Data sources**

A baseline household survey was administered to eligible households in the first quarter of 2014, immediately before the public works program rolled out for group A. Two more rounds of surveys were conducted at staggered times based on timing of the rollout of the public works (Figure A1). Midline surveys were administered over the course of three weeks while the public works were taking place. This survey included a weekly questionnaire on employment and intra-household transfers with a rotating set of modules on time use (week 1 and 3), expenditures (week 2), and food security (week 3). The endline surveys were conducted over three consecutive weeks nine months after the households completed the public works program. In terms of specific calendar dates, the timing of the midline and endline surveys varied by group. In addition, administrative data, including program data on payments and transactions obtained from the financial institution responsible for paying the program beneficiaries, was used to complement the survey data.

Each treatment group was interviewed with its corresponding randomized control group both at midline and at endline—that is, group A was interviewed with group C, and group B was interviewed with group D. The endline survey for a treatment group and its corresponding control group took place before the latter was offered the public works opportunity.

## _Household Survey_

Extensive baseline and endline questionnaires were administered separately to current and prospective beneficiary women and their husbands. The survey for woman covered household socioeconomic characteristics, non-labor income, transfers, time use, durable assets, housing characteristics, household expenses, health and nutrition practices, food security, intra-household decision making, personality traits, and mental health and well-

> 9 For example, Imbert and Papp (2015) show that the rollout of NREGA in India results in increases in private sector wages. Franklin et al. (2023) find spatial spillover effects on private wages in urban areas in Ethiopia due to changes in the labor supply from commuters who live in the treated neighborhoods.

11
# **The Global Resort to Antidumping, Safeguards, and other Trade Remedies Amidst the Economic Crisis**

Chad P. Bown<sup>1</sup> World Bank, Brandeis University & The Brookings Institution JEL classification: F13 Keywords: trade policy, WTO, antidumping, safeguards, countervailing measures 1 Chad P. Bown manages the World Bank’s trade policy transparency initiative to update data made freely and publicly available via the _<u>Global Antidumping Database</u>_ website which has tracked and published earlier monitoring updates for 2008, including Bown (2009a). The data collection efforts for this project were financially supported by the Development Economics Research Group at the World Bank and DFID’s GTFA initiative. Aksel Erbahar, Laura Gutowski, Ludmila Cieszkowsky Elias, and Paul Deng provided outstanding research assistance. Thanks to Bernard Hoekman, Simon Evenett, Gaspar Frontini, Richard Newfarmer, Tom Prusa, Mike Moore, Maurizio Zanardi, Hylke Vandenbussche, Robert Feinberg, Kara Reynolds and seminar participants at the Zurich airport lounge, the George Washington University “Antidumping Use Across the World Conference,” and the World Bank/CEPR “Trade Implications of Policy Responses to the Crisis Conference” for useful comments on an earlier draft. All remaining errors are my own Correspondence: Chad P. Bown, Department of Economics and International Business School, Brandeis University, Mailstop 021, 415 South Street, Waltham, MA 02454-9110 USA, tel: +1.781.736.4823, fax: +1.781.736.2269, email: <u>cbown@brandeis.edu, web: http://www.brandeis.edu/~cbown/</u> .

.
Figure 9. Contribution to the decline in National Moderate Poverty Headcount <u>(share of total decline in poverty)</u> <!-- Start of picture text --> 34<br>17<br>74 74<br>18 21<br>-15 -24<br>-10<br>Thailand, 2000 to 2009<br>Occupation share<br>Transfers<br><!-- End of picture text --> <!-- Start of picture text --> 7<br>7<br>97<br>9<br>38<br>- 6<br>-7<br><!-- End of picture text --> <!-- Start of picture text --> 17<br>74<br>18<br>-15<br>Peru, 2004 to 2010<br>Occupation share<br>Transfers<br><!-- End of picture text --> <!-- Start of picture text -->
-44<br>Bangladesh, 2000 to 2010<br>Consumption-income ratio<br>Labor Income<br><!-- End of picture text -->

<!-- Start of picture text --> Labor Income Capital Transfers<br>Other Non-labor Unexplained<br>Source: Shapely value estimates based on Peru's ENAHO 2004 -2010, Thailand's SES 2000 -2009, and Bangladesh's HIES<br>2000 -2010.<br>Figure 10. Changes in the Structure of Employed Population gure 10. Changes in the Structure of Employed Population ure 10. Changes in the Structure of Employed Population ges in the Structure of Employed Population es in the Structure of Employed Population ployed Population loyed Population yed Population ed Population pulation ulation<br>A. Occupational Structure B. Economic Sector<br>(percent change in employed population) (percent change in employed population)<br>0.3 30%<br><!-- End of picture text --> <!-- Start of picture text --> Figure 10. Changes in the Structure of Employed Population gure 10. Changes in the Structure of Employed Population ure 10. Changes in the Structure of Employed Population ges in the Structure of Employed Population es in the Structure of Employed Population ployed Population loyed Population yed Population ed Population pulation ulation<br>A. Occupational Structure B. Economic Sector<br>(percent change in employed population) (percent change in employed population)<br>0.3 30%<br>25%<br>0.2 20%<br>15%<br>0.1<br>10%<br>5%<br>0<br>0%<br>-0.1 -5%<br>-10%<br>-0.2 -15%<br>-20%<br>-0.3<br>Bangladesh, Peru, Thailand,<br>Bangladesh, Peru, 2004- Thailand, 2000- 2000-2010 2004-2010 2000-2009<br>2000-2010 2010 2009<br>Agriculture Industry<br>Farmer Daily workers Self-employed<br>Private Services Public Sector<br>Salaried Family worker<br><!-- End of picture text --> 26
**Table S2.E: Results for the baseline specification with interaction terms (same sector x network variables) added**

|VARIABLES|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
||newprod|invdum|anyrd|it|pcf_tech|suprat|htrain|ftrain|
|supbuy|0.0249|-0.0687|0.0572|-0.0735|0.0295|-0.0283|0.0631|-0.100|
||(0.136)|(0.129)|(0.114)|(0.199)|(0.252)|(0.0368)|(0.117)|(0.138)|
|samesup|-0.0493|-0.0307|-0.00481|-0.0674|-0.0857|0.00506|0.0207|-0.0602|
||(0.0666)|(0.0773)|(0.0563)|(0.0957)|(0.115)|(0.0201)|(0.0654)|(0.0671)|
|samecus|<br>0.0460|<br>-0.0417|<br>-0.0198|<br>0.0581|<br>-0.105|<br>0.0109|<br>0.0253|<br>0.0795|
||(0.0666)|(0.0769)|(0.0739)|(0.106)|(0.108)|(0.0233)|(0.0807)|(0.0725)|
|same_sec|-0.0452*|-0.0402|-0.0229|-0.0522|-0.109**|-0.00294|-0.0198|-0.0690**|
||(0.0273)|(0.0297)|(0.0212)|(0.0340)|(0.0490)|(0.00822)|(0.0154)|(0.0291)|
|ldist|<br>-0.00553*|<br>-0.000262|<br>-0.0104*|<br>-0.0170**|<br>-0.0158*|<br>-0.00195|<br>-0.0169***|<br>-0.0176***|
||(0.00288)|(0.00201)|(0.00563)|(0.00698)|(0.00926)|(0.00157)|(0.00309)|(0.00274)|
|ad_fmage|-0.000611|-0.000780***|-0.001000|-0.00187|-0.00322*|-0.000149|-0.000206|0.00180|
||(0.000574)|(0.000272)|(0.00105)|(0.00131)|(0.00173)|(0.000335)|(0.000720)|(0.00114)|
|ad_meduc|0.00864<br>(0.00906)|0.0141<br>(0.00955)|-0.00997<br>(0.00833)|0.0644**<br>(0.0286)|0.0475**<br>(0.0226)|-0.00392*<br>(0.00237)|0.0112<br>(0.0184)|0.00648<br>(0.0160)|
|ad_mexper|-0.000761|0.000113|-0.000573|-0.000880|-0.00312*|0.000214|-0.00167**|-0.000962|
||(0.000896)|(0.000386)|(0.00132)|(0.00151)|(0.00169)|(0.000478)|(0.000802)|(0.000839)|
|ad_mfemale|-0.00138|0.000628|-0.00547|0.0904**|0.00925|0.00769|0.0182|-0.0118|
||(0.0185)|(0.00597)|(0.0285)|(0.0455)|(0.0482)|(0.0111)|(0.0258)|(0.0178)|
|ad_lemp|0.00630|0.0218**|0.0304**|0.189***|0.121***|0.0110**|0.0876***|0.0989***|
||(0.00943)|(0.00903)|(0.0137)|(0.0264)|(0.0298)|(0.00490)|(0.0155)|(0.0143)|
|secdist|0.00270|-0.00365|1.18e-05|-0.00101|0.00150|6.95e-05|0.000434|0.00819**|
||(0.00473)|(0.00472)|(0.00335)|(0.00484)|(0.00723)|(0.00140)|(0.00291)|(0.00403)|
|seclink|0.0459|0.0349|0.0684|0.00469|0.0899|0.0116|0.0317|0.106|
||(0.0721)|(0.0839)|(0.0560)|(0.116)|(0.128)|(0.0185)|(0.0767)|(0.0700)|
|Constant|<br>0.486***|<br>0.471***|<br>0.264***|<br>0.430***|<br>1.007***|<br>0.172***|<br>0.323***|<br>0.285***|
||(0.0190)|(0.0220)|(0.0424)|(0.0594)|(0.0721)|(0.0135)|(0.0362)|(0.0363)|
||||Standard e<br>*** p<0.01|rrors in parent<br>, ** p<0.05, *|heses<br>p<0.1||||

5
standards on maternal dietary diversity, the WHO (2013) recommendations on child immunizations schedules, the WHO and UNICEF (2006) guidelines on drinking water and sanitation, as well as the 1990 UNICEF strategy on improved nutrition of children and women. In Bolivia and Peru country specific immunization practices are used. These immunization schedules follow closely the WHO guidelines.

The prevalence of adequacies varies across countries and resource access, but in most contexts children were most likely to be adequate in care and least likely to be adequate in environment and health. Adequate care was the facet which was most likely to be met in all countries with the exception of Indonesia, where the prevalence of adequate food was greater than the prevalence of adequate care (Figure 5a, 6a and 7a). In all countries it is adequate environment and health that is most lacking. With the exception of Bolivia, in the most recent survey for each country only 10 % or less of the children lived in a household where the housing infrastructure and health opportunities were adequate (Figure 7a). However, for Bolivia no information on sanitation was collected and thus the measure is not comparable to the other countries where sanitation measures were included.

# **3.2.1 Adequate food security**

In most countries either adequate dietary diversity or adequate meal frequency is the component of food security which is least prevalent among children. In four of the seven data set with comparable information we find meal frequency to be the least prevalent component and in three it is dietary diversity (Figure 5a). The two South American countries have above 80% of the children consuming foods from at least four of the seven groups. Indonesia also has more than 80% of children with diverse diets, however, the measure is not comparable to the others since it is based on household food consumption and not child‐specific food consumption. Except for Ethiopia and Zimbabwe, more than half of the children under 6 months are exclusively breastfed. The highest prevalence of exclusively breastfed children are in Cambodia (78%) and Peru (81%).

22
sures of well-being. First, we develop a simple conceptual framework of whether an individual is satisfied with their consumption where we incorporate the salience of nonconsumption factors. The framework incorporates the well-known issues affecting subjective indicators of well-being- the possibility that scales used to answer such questions are individual-specific and can be impacted by frame-of-reference effects. However, this framework adds a new way in which subjective welfare metrics might be difficult to interpret- the possibility that the respondent-specific scales on which subjective welfare questions depend might not be stable over time. Specifically, we demonstrate how crises might cause the scales used by individuals to determine satisfaction to change at the same time that consumption might be changing, and it becomes an empirical issue as to whether subjective welfare metrics move in the same direction as consumption.

Second, we empirically investigate the ability of subjective measures of welfare to capture changes in traditional measures of deprivation in a crisis using the mostly non-violent capture of the Republic of Yemen’s capital. The capital was captured by Houthi forces in September 2014 while a nationally representative household survey was being conducted. The survey included both traditional consumption modules and a full subjective welfare module. Importantly, previous research has demonstrated that the capture led to immediate and large increases in consumption-based and employment-based measures of deprivations, and there is little evidence that the sampling of the survey was affected by the capture (e.g., Tandon 2019).

However, the change in subjective welfare metrics did not match the increase in deprivations captured by more traditional welfare metrics. The survey asked the household head to rate their satisfaction with a number of welfare dimensions individually (e.g., satisfaction with food consumption, income, etc.). Despite the large and immediate increase in traditional measures of deprivation following the capture, the subjective metrics of welfare moved in the _opposite_ direction. There was an increase of between 11 and 15 percentage points of household heads that reported to be satisfied with food consumption, income, and work, all of which were dimensions in which traditional metrics significantly worsened.

3