rafmacalaba/datause-encoder-data huggingface dataset:
involved in off-farm self-employment and wage work. In Morocco, Uganda, Rwanda, India and Nepal, wage work dominates; the surveys reveal that most of this work is agricultural, including work on other households' farms.<sup>11</sup> _Child schooling and health outcomes_ : Defining our child outcome variables is more straightforward. Schooling is measured as a dummy variable for whether boys and girls aged 5-19 attended school during the last year. For health outcomes, we use anthropometric indices of growth status (weight-for-height, a measure of wasting, and height-for-age, a longer-term measure of stunted growth). These are presented in terms of z-scores, or standard deviations from the WHO reference population. Ideally, we would like to measure women’s time devoted to household nutrition and child rearing. Most surveys do not allow direct measures of such effects, but they do elicit the weight and height of young children.<sup>12,13</sup> Anthropometric outcomes are also a function of nutritional investments and other longer-term factors related to child care, and unlike other health indicators do not suffer from measurement error correlated with socioeconomic household characteristics (Alderman and Garcia, 1994; Strauss and Thomas, 1998). Table 4 presents summary statistics for the child schooling and health outcome variables by gender.

_Explanatory variables_ : Table 5 provides the exact definitions of the dependent variables and summary lists of all explanatory variables by regression.<sup>14</sup> The aim in all regressions is to control for identical factors across countries but specific variable configurations may vary according to the data and peculiarities of each country. The outcome regressions (equation (6)) control for a large set of household and individual characteristics. The household variables are essentially the same across regressions while individual level variables differ according to whether the specific outcome refers to women or children. Individual-level variables include factors that may affect women's decisions to engage in off-farm work, such as age and age squared, years of schooling and years

> 11 Exceptions include Uganda, where 60% of wage-earning women did non-agricultural work, including teaching, retail (shops/trade), handicrafts, and manufacturing/construction.  In Morocco, about 45% of women in wage work were primarily in industrial occupations.

> 12 Direct time use data on women's time spent with children was either not available or very limited across the surveys, and is in any case difficult to isolate in the context of household activities.

> 13 The lower age cutoff for the anthropometric data is 6 months, while the upper age cutoff varies across the surveys (3, 4 or 5 years of age).

> 14 A statistical addendum containing summary statistics for all variables and the regressions across the different surveys is available from the authors.

18
# **Remote-learning, Time-Use, and Mental Health of Ecuadorian High-School Students during the COVID-19 Quarantine**<sup>**#**</sup>

Igor Asanov<sup>a</sup> , Francisco Flores<sup>a</sup> , David McKenzie<sup>b</sup> , Mona Mensmann<sup>c</sup> , Mathis Schulte<sup>d</sup> _JEL Classification Codes:_ O12, O15, I25 _Keywords:_ Remote-learning; Time-use; COVID-19

# We thank the World Bank’s ComPEL and SIEF programs for the funding used for this rapid response survey. It builds on a larger ongoing project funded by SIEF, IPA and the IGL, in collaboration with Thomas Åstebro, Guido Buenstorf, and Bruno Crépon. We thank the technical team of the Ministry of Education of Ecuador, Zone 2 for their collaboration on this work. Anastasiya-Mariya Noha, Sara Elizabeth Manayay for excellent research assistance, and Claudio Gallardo Leon for his work leading the survey efforts. Human Subjects approval for this project was approved by the Universidad San Francisco de Quito (USFQ), IRB approval number 2018-208E.

a University of Kassel b World Bank c Warwick Business School d HEC Paris
12 long-term **Y** effect as well as a short-term a effect on the money supply25. This is a standard error-correction framework which allows the expansion in domestic credit to have an effect which is spread out over time. If a equals unity, then the short run effect of credit expansion on money is one-for-one. Otherwise, domestic credit expansion partly leaks out into the balance of payments even in the first quarter. The coefficient t measures the speed of convergence to the steady state value of money. If the coefficient **Y** is not 23 Note that this equation does not report any interest sensitivity in the demand for money. Most commentators have supposed that the openness of the capital market might mean that such interest differentials as emerge between the CFA countries and France - and they have approached two percentage points at times even since 1981 - would be enough to induce important capital flows. This should show up as a degree of interest sensitivity in the demand for money. An earlier analysis of the demand for money in Cote d'Ivoire did identify an interest rate effect in the Ivorian demand for money, but the coefficient was barely significant and not robust to changes in equation specificatica.

That study (Honohan 1988) reported the following equation for monthly data (seasonally adjusted) in M2, 1979.01 to 1987.06: DeLM - 0.0401 - 0.103 DelNL, + 0.567 Rdiff - 1.954 Time + Dummies (3.16) (3.92) (1.93) (1.67) RSQ - 0.941 SEE - 0.0262 DW - 1.81 Where DelM is the logarithmic monthly change in M2; and RdLff is the differential between money market rates in Cote d'Ivoire and France. The dummies intercept shifts to cope with shifting seasonality at the beginning and end of the harvest season: they exclude all outliers beyond four standard deviations.

The interesting feature of this equation is the possible sensitivity of the money stock to the international interest rate differential. However the effect is very impreeisely measured and is not quite significant at the five per cent level. One could not assert with confidenee that the effect was not a statistical artifact.

Furthermore it is not robust to fairly small changei in the specification or in the sample period. By extending the sample it be omes evident that in the mid 1970s there was a positive association between tei interest differential in favour of Abidjan and the quantity of money. While this can be blamed on simultaneity, and interpreted as a policy response and thus a supply effect. Leite and Makonnen (1986) were equally unable to find a robust impact of interest on saving in the BCEAO countries.

One plausible hypothesis explaining the difficulty in identifying a strong effect is that mobile liquid assets of Ivorians are already held outside of Africa. On this interpretation, applicable possibly also to the other CFA countries, the money supply in the CFA zone is held primarily for transactions purposes; the role of interest rate policy in this low-inflation environment may then be more to allow for rational allocation of credit than to ensure that mobile funds remain in Africa.
# **Figure 7-1.  Infrastructure Investment across Countries (percentage of GDP)**

<!-- Start of picture text --> ( a) Total Investment<br>8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>1981 1984 1987 1990 1993 1996 1999 2002 2005<br><!-- End of picture text --> <!-- Start of picture text --> (b) Public Investment<br>5.0<br>4.5<br>4.0<br>3.5<br>3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>1981 1984 1987 1990 1993 1996 1999 2002 2005<br><!-- End of picture text --> <!-- Start of picture text --> (c) Private Investment<br>3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>1981 1984 1987 1990 1993 1996 1999 2002 2005<br>IND PAK IDN<br><!-- End of picture text --> Data source: Calderón, Odawara, and Servén (2008).

38
quarters of the sample derive from women who had been SHG members while the remaining quarter were from women who were not program members but had similar profiles in terms of wealth, caste and location.<sup>15</sup> SHG members were selected at random and, where a woman could not be not be reached, the next woman on the SHG member list was contacted. Non-SHG members were selected to be close matches for those already interviewed from the same or adjacent villages to minimize bias related to regional variations across the state. Surveyors were trained to interview participants in settings when they were alone and to assure interviewees of anonymity. In addition, respondents were told in the consent protocol that interviews would take approximately one hour and that it was acceptable to decline to answer at any point. The data used in this paper were collected and recorded by trained surveyors, working from script in interviews carried out between March and August of 2017. Summary descriptive statistics for variables used in this study can be found in Table 1.<sup>16</sup> In addition, and by way of context, we also present data on the average family size of SHG members, as well as house construction type and income compared with controls (see Table 2a, 2b, 2c). By caste, ages are broadly similar though there is some evidence that family sizes and material living standards (as indicated by income and house type) are slightly lower for SHG members. If the controls were materially better off, our analysis might be regarded as somewhat conservative.<sup>17</sup>

> 15 To obtain a balance of experience across SHG members, the sample was further divided in equal proportions into those who had been members for less than three years, three to five years and more than five years (i.e. 1,500 observations in each category). Because the program targets the poorest women, non-members tended, on average, to have slightly higher incomes than SHG members.

16 The consent protocol and written summary of instructions to the surveyors are available from the authors on request. PSM analysis uses dichotomized indicators.

> 17 The difference might not be entirely surprising, as the program seeks to target for participation those who are worst off. Income data are often missing, not surprisingly, so the household type is perhaps a better indicator of household asset values. The propensity score

15
experimental evidence and results on the influence of transparency in benefit delivery on the overall support for targeted social assistance and on program design preferences.

The paper shows that support for redistributive programs is sensitive to the level of trust in the system’s ability to deliver benefits to intended beneficiaries. In fact, although transparency does not appear to significantly affect the overall rates of giving (controlling for program design), it does have a significant positive effect on the giving by youth and by those people who exhibit low trust in the existing delivery of safety nets, especially in the case of unconditional cash transfers. Moreover, among those low-trust individuals, enhanced transparency makes cash-based transfers more attractive than in-kind transfers. Because the latter are generally less effi cient but may be perceived as less prone to elite capture, transparency could thus also enhance program effi ciency by allowing policy makers to switch from in-kind to cash transfers without losing the support of their middle-class citizens.

# Annex 1: Sample design and selection protocols

The experiment’s sampling strategy adopted the definition developed by the Government of Jordan’s study of the middle class (ESC 2008), which defined the middle class as those households that have per capita incomes between twice and four times the Jordan’s national poverty line. This definition corresponded to the population between the 4th and the 8th income decile according to the 2004 Jordanian census, the latest available at the time. For this study, middle-class primary sampling units (PSUs) in the census were selected by a three-step process: 1) constructing a proxy means test regression using Jordan’s 2010 Household Expenditure and Income Survey;<sup>30</sup> 2) applying coeffi cients from that regression to the 2004 census data; and 3) choosing PSUs with resulting average scores between 4th and 8th income deciles. Within the population of middle-class PSUs, 21 sampling units were selected for the experiment via random selection with probability proportionate to size.

Within each sampling unit, the following protocol was used to recruit the needed 20 individuals (10 for treatment, 10 for control) at the same time and place. The day before the experiment in a PSU, a team of enumerators would visit the selected PSU, and the team leader would use a random walk method to select households for recruitment. Enumerators then visited this sample of households, introducing themselves with an invitation letter from the Center for Strategic Studies in Jordan (CSS), and used a Kish (1949) table to identify one eligible person who was at least 18 years old to be invited to a meeting the next day at a the reserved location (usually a nearby public school). The purpose of

> 30 The regression included the following variables, which appear in both the Household Expenditure and Income Survey and the census: average household size, owning a fixed phone, a computer, internet connection, central heating, microwave, home ownership, and having at least one family member with university education

17
WPS3634

# **QUANTIFYING THE RURAL-URBAN GRADIENT IN LATIN AMERICA AND THE CARIBBEAN**

Kenneth M. Chomitz, Piet Buys, and Timothy S. Thomas

## **Abstract**

This paper addresses the deceptively simple question: what is the rural population of Latin America and the Caribbean? It argues that rurality is a gradient, not a dichotomy, and nominates two dimensions to that gradient: population density, and remoteness from large metropolitan areas. It uses geographically referenced population data (from the Gridded Population of the World, version 3) to tabulate the distribution of populations in Latin America, and in individual countries, by population density and by remoteness. It finds that the popular perception of Latin America as a 75% urban continent is misleading. Official census criteria, though inconsistent between countries, tend to classify as ‘urban’ small settlements of less than 2000 people. Many of these settlements are however embedded in an agriculturally based countryside. The paper finds that about 13% of LAC populations live at ultra-low densities, of less than 20 per square kilometer. Essentially all these people are more than an hour distant from a large city, and more than half live more than four hours distant. A quarter of LAC population is estimated to live at densities below 50, again essentially all of them more than an hour distant from a large city. Almost half (46%) of LAC lives at population densities below 150 (a conventional threshold for urban areas), and more than 90% of this group is at least an hour distant from a city; about a third of them (18% of LAC total) are more than four hours’ distant from a large city.

World Bank Policy Research Working Paper 3634, June 2005 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ Acknowledgments: This paper was prepared as a background paper to _Beyond the City: The rural contribution to development_ . We are grateful to Andrew Nelson and Juan Robalino (who contributed to a precursor versions of this work), and thank Uwe Deichmann and Deborah Balk for helpful comments. We are very grateful to CIESIN for sharing the GPW3 data. The denominations used and the boundaries shown on maps herein do not imply, on the part of the World Bank, any judgment on the legal basis of any territory or any endorsement or acceptance of such boundaries.
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32
# _INTRODUCTION_

Unilateral trade liberalization is at the core of economic reform packages implemented in several emerging economies in the last decades.<sup>1</sup> Microeconomic effects of trade reform episodes have received a lot of attention recently. Empirical works have concentrated on how trade openness shapes firms’ productivity (Pavcnik (2002), Trefler (2004), Amiti and Konings(2007), Lileeva and Trefler (2010) and Bas and Ledezma (2010) among others). Bernard et al.(2010), using firm-product level data, also show that trade liberalization affects multi-product firms’ export patterns.<sup>2</sup> However, there is scarce evidence on the different mechanisms through which unilateral trade liberalization in a country affects the export performance of firms located in other countries.

This paper sheds new light on intra-firm adjustments due to trade integration combining the unilateral trade liberalization process experienced by China at the end of the 90s with firm-product-destination data for French firms (1999-2005). After a unilateral trade reform involving asymmetric countries, two opposite forces are at stake: market access expansion and strengthening of competitive pressures in the liberalized market. The main contribution of this paper to the literature is to investigate this trade-off. On the one hand, tariff reductions increase foreign demand and induce firms to export more products to the liberalized markets. On the other hand, we also expect an intensification of foreign competition in each market. This channel is related to the tougher competition of third countries in the liberalized market that might affect negatively the expansion of French exports to that destination.

Addressing the trade-off between market access expansion and tougher competition, we can evaluate French firms’ export strategies in the event of a unilateral trade liberalization.<sup>3</sup> We give specific attention to the France-China trade relationship so to account for the role of China in the global trading system and its trade policy commitment. Using French micro-level data, our empirical strategy consists in investigating how French firms’ product scope and export sales changed as a consequence of China’s largest unilateral tariff liberalization vis-`a-vis Asian trade liberalization. We focus on a sample of Asian 2
**Figure 22: Bottom 20 six‐digit products with lowest HHI (least concentrated) of overall GVC Exports, 2014**

<!-- Start of picture text --> 0.08 0.7<br>0.07 0.6<br>0.06<br>0.5<br>0.05<br>0.4<br>0.04<br>0.3<br>0.03<br>0.2<br>0.02<br>0.01 0.1<br>0 0<br>620341 870322 850730 851230 902820 570231 851240 870899 870829 850710 841990 842890 852490 843139 870321 540720 560129 870891 851220 560122<br>Six‐digit products, H0 Nomenclature<br>HHI of GVC Exports EXPRELY of GVC Exports<br>Notes: Values expressed in ratios computed from original variables expressed in thousand current USD, and calculated on the total number of 254 countries/geographies left<br>after excluding two small countries (Bermuda and Luxembourg) with normalized 2001 GDP >1 from the original dataset with 256 countries/geographies with available data on<br>at least some years along the 27‐year period spanning 1988‐2014, even though some may have missing data in some years (HS 1988/92 nomenclature, mirror data, six‐digit<br>products). All trade data is drawn from Comtrade on WITS, and countries' GDP data comes from WB WDI.<br>Sources: Trade: World Bank MC‐GVC database (http://wits.worldbank.org/WITS/WITS/AdvanceQuery/GVC/GVCQueryDefination.aspx?Page=GVCIndicator).<br>World GDP: World Bank WDI (http://databank.worldbank.org/data/reports.aspx?source=world‐development‐indicators).<br>HHI of GVC Exports<br>EXPRELY of GVC Exports<br>breeches, reciprocating pist electric accumulator signalling equipment and calib wo vehicle parts nes accessories of bodies nes electric accumulators of and equip or unloa for sound or other s loading pist synthet wadding, ne for motor vehicles visual signalling equip and arti<br>wipes, defrosters and de<br>APPAREL FINAL: Men's or boys' trousers, MOTOR VEHICLES FINAL: Automobiles with ELECTRONICS INTERMEDIATE: Nickel‐cadmium MOTOR VEHICLES INTERMEDIATE: Sound ELECTRONICS FINAL: Liquid supply, production TEXTILES FINAL: Pile floor coverings of wool..., MOTOR VEHICLES INTERMEDIATE: Windscreen MOTOR VEHICLES INTERMEDIATE: Motor MOTOR VEHICLES INTERMEDIATE: Parts and MOTOR VEHICLES INTERMEDIATE: Lead‐acid ELECTRONICS FINAL: Parts of machinery, plant ELECTRONICS FINAL: Lifting, handling, loading ELECTRONICS INTERMEDIATE: Recorded media ELECTRONICS FINAL: Parts of lifting, handling, AUTOS FINAL: Automobiles with reciprocating TEXTILES FINAL: Woven fabrics obtained from TEXTILES FINAL: Wadding and articles of MOTOR VEHICLES INTERMEDIATE: Radiators MOTOR VEHICLES INTERMEDIATE: Lighting or TEXTILES FINAL: Wadding of man‐made fibres<br><!-- End of picture text --> 36
<!-- Start of picture text --> Change in Poverty Headcount - 2007:2011<br>4<br>a 4 C<br>i ee oa4%<br>a ae<br>ha cease et ee<br>; F a<br>\ae 7 a.<br>a Ly<br>;fo a m (9,38)<br>m (-2,9]<br>m (-13,-2]<br>(-40,-13]<br>ONo data<br>——<br><!-- End of picture text --> <!-- Start of picture text --> Low conflict intensity<br>Central<br>0.4<br>Southwest<br>/ 1.6 Poverty HCR (%) Casualties. per<br>L High conflict intensity Bis | 4900 inhabitant<br>(40,80) in 2012<br>Source: NRVA 2011-12<br><!-- End of picture text -->