rafmacalaba/datause-encoder-data huggingface dataset:
**H4 (social contact).** Respondents who report having higher levels of contact with Venezuelans will prefer less restrictive policies across all dimensions.

# **3. Venezuelan Migration to Colombia and Institutional Context**

The Venezuelan humanitarian, economic and social crisis over the last decade, has resulted in resulted in the outflow of over 5.91 million Venezuelan citizens (around 16% of the country’s population) from the country. Over 4.5 million have stayed in the Latin American region, with Colombian being the main host.

Colombia shares a large border with Venezuela spanning 1,378 miles (see Figure A1). In addition, Venezuela and Colombia were part of the same country in the early 19<sup>th</sup> century ( _Gran Colombia_ ). As a result, both countries have a shared history and share important cultural similarities. It is therefore not surprising that Colombia has been a major recipient of Venezuelans with an estimated 1.75 million now living in the country.<sup>3</sup> The official crossing points at the Colombia-Venezuela border have remained open for much of the Venezuelan crisis. The border crossing points were temporarily closed in 2015 but re-opened in 2016, after which a large number of migrants crossed (see Figure 1). It has always been relatively easy for Venezuelans to cross the border at unofficial border-crossing points.

<!-- Start of picture text --> Figure 1 - Number of Venezuelan migrants in Colombia<br>2000000<br>1500000<br>1000000<br>500000<br>0<br>2014 2016 2018 2020<br>Year<br>Number of Venezuelan migrants<br><!-- End of picture text --> _Source_ : Authors' calculations using data published by the Ministry of External Relations 2020. The vertical solid line indicates the border closure in 2015 and the dashed line the re-opening of the border in 2016.

> 3 This represents about 3.6% of Colombia’s population and 7.2% of the labour force (Santamaria 2020).

10
1,000 employees by country and shows that robot intensity in the manufacturing sector in 2015 was most advanced in the Republic of Korea, Germany, Sweden, the United States, Denmark and Belgium. Among these, the intensity of robot use increased discernibly between 2003 and 2015 in Korea, the United States, and Belgium, but remained largely unchanged in Germany and Sweden. Robotization remains more limited in Australia, Canada, and Portugal, though these countries are also increasing progressively the intensity of robot use in the manufacturing sector. Figure 4 plots the evolution of robots per 1,000 employees by sector. Electronics, automotive products, rubber and plastics, and metal products are the manufacturing industries in which robotization is most pronounced and has advanced most rapidly between 2003 and 2015. In contrast, the intensity of robot use in textiles, apparel, and leather products remains the most limited. These differences in the extent of robotization across industries reflect both the technological feasibility and commercial viability of adoption.

In sum, robot adoption has increased significantly over time, although at different speeds in different countries and sectors, which is convenient for identification. Appendix figures 3 and 4 display clearly the extent of variation in robot adoption across sectors, countries and time. It is particularly useful to compare electronics and textiles, apparel, and footwear – both GVC-intensive – which stand out as manufacturing industries where robotization in high-income countries advanced the most and least between 2003 and 2015. Figure 5 shows that robots per 1,000 employees in the electronics sector relative to apparel among HICs is negatively correlated with the flow of FDI from HICs to LMICs in the electronics sector relative to apparel between 2003 and 2015. This correlation naturally does not amount to causality but is indicative of a possible negative association between robotization in HICs and less offshoring to LMICs.

**Figure 3: Operational Stock of Robots per 1000 Employees in HICs, by country, 2004-2015**

<!-- Start of picture text --> 4.50<br>South Korea<br>4.00 Germany<br>Sweden<br>3.50 United States<br>Denmark<br>3.00 Belgium<br>Spain<br>2.50 Italy<br>Finland<br>2.00 France<br>Austria<br>1.50 UK<br>Switzerland<br>1.00 Portugal<br>Norway<br>Australia<br>0.50<br>0.00<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br>‐0.50<br><!-- End of picture text --> Note: Calculations based on International Federation of Robotics Database 8
||(0.005)|(0.005)|
|---|---|---|
|No of electrical outages per day in a typical month|-0.031|0.021|
||(0.024)|(0.026)|
|Average duration of electrical outages (hours)|0.001**|-0.000|
||(0.000)|(0.002)|
|lnLxlnK|-0.012**|-0.008***|
||(0.006)|(0.001)|
|lnLxlnM|-0.040***|-0.035***|
||(0.007)|(0.002)|
|lnKxlnM|0.007|0.002**|
||(0.007)|(0.001)|
|lnL<sup>2</sup>|0.052***|0.044***|
||(0.013)|(0.002)|
|lnM<sup>2</sup>|0.034***|0.033***|
||(0.002)|(0.001)|
|lnK<sup>2</sup>|0.005***|0.006***|
||(0.002)|(0.001)|
|Firm owns or shares a generator Y/N|0.014|0.158***|
||(0.049)|(0.047)|
|Losses due to breakage/spoilage shipped domestically (% of value of<br>the products|-0.003|0.002|
||(0.007)|(0.004)|
|Log of age of firm|0.009|0.032|
||(0.020)|(0.029)|
|Foreign ownership Y/N|0.087|0.124|
||(0.069)|(0.076)|
|Exports 10% or more of sales Y/N|0.089*|0.141**|
||(0.049)|(0.063)|
|Security costs (% of sales)|-0.013*|-0.010*|
||(0.007)|(0.005)|
|Establishment competes against unregistered or informal firms Y/N|-0.106***|-0.011|
||(0.039)|(0.049)|
|Number of years firm was unregistered at start|-0.005|-0.010**|
||(0.004)|(0.004)|
|Formal training Y/N|0.016|0.088*|
||(0.039)|(0.049)|
|Constant|7.086***|7.251***|
||(0.639)|(0.461)|
|Region (within country) Fixed Effects|Yes|Yes|
|Sector (2 digit) Fixed Effects|Yes|Yes|
|Number of observations|7,909|8,548|

Note: Survey weights have been applied to all regressions, using Stata’s svy prefix. Linearized Taylor standard errors that account for survey stratification are indicated in parentheses. *** p<0.01, ** p<0.05, * p<0.1 26
illiquid forms of wealth such as building quality. Following Filmer and Pritchett (2001) we proxy household wealth with the first principal component of a set of indicators of ownership of durable assets (such as fans, radios, cameras, televisions, bicycles, refrigerators and motorcycles). We again take this from the baseline survey, so that it is predetermined at the time of treatment.

- _iii) Entrepreneurial ability_ is a more nebulous concept, and so we explore several proxy measures. The first, and most standard in the literature (e.g. Paulson and Townsend 2004), is to use the number of years of education of the enterprise owner. Secondly, we follow Djankov et al. (2005) and use the score of the entrepreneur on a digit span recall test. Thirdly, we use the first principal component of years of education, digit span recall, time taken to solve a maze, and self-assessed efficacy in ability to carry out business tasks such as keeping accounts, making a sale to a new customer, and identifying market opportunities. This latter measure is a broad measure of entrepreneurial ability, and has a correlation of 0.64 with digit span and 0.79 with education.

- _iv) Risk aversion_ is measured from lottery experiments played with real money with each firm owner. Firm owners were given the choice between 40 rupees for certain, or a gamble with X percent chance of 10 rupees and 100-X percent chance of 100 rupees. A 10-sided dice was used to vary the odds of the higher payment from 10 percent up to 90 percent. The probability threshold at which an individual switches from the safe payment to the risky gamble then provides a measure of risk aversion, and can be used to derive the coefficient of relative risk aversion for a CRRA money utility function, which we take as our measure of risk aversion.

- _v) Uncertainty_ is measured by eliciting from firm owners their subjective distribution of firm profits (Manski, 2004; Lybbert et al, 2005). In the October 2005 survey, firm owners were given a sheet with different ranges of profits, such as <500 rupees, 500-1000 rupees, 1000-1500 rupees, etc. They were then asked to place 20 marks in cells, representing how many firms just like theirs they think would have profits in each range in December 2005. We use these subjective distributions to estimate the coefficient of variation of expected profits, which we take as our measure of the riskiness of firm profits as perceived by the firm owner.

# **8.3. Results on Treatment Effect Heterogeneity**

Table 7 presents the results from estimating equation (11) allowing for different forms of heterogeneity in the treatment effects. We estimate the return from the treatment, because risk and credit constraints could affect the proportion of cash treatments which were invested in the enterprise. Column 1 presents the overall treatment 26
WPS4164

# **An Analysis of Livestock Choice:**

# **Adapting to Climate Change in Latin American Farms**<sup>**1**</sup>

S. Niggol Seo University of Aberdeen Business School, UK and Robert Mendelsohn School of Forestry and Environmental Studies, Yale University, USA

## **Abstract**

This paper explores how Latin American livestock farmers adapt to climate by switching species. We develop a multinomial choice model of farmer’s choice of livestock species. Estimating the models across over 1200 livestock farmers in seven countries, we find that both temperature and precipitation affects the species Latin American farmers choose. We then use this model to predict how future climate scenarios would affect species choice. Global warming will cause farmers to switch to beef cattle at the expense of dairy cattle.

World Bank Policy Research Working Paper 4164, March 2007 _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._

> 1 This project was funded by the World Bank.  We thank Emilio Ruz, Flavio Avila, Jorge Lozanoff, Luis José María Irias, Magda Aparecida de Lima, César Teherán, Jorge González, Flavio Játiva, Alfredo Albin, Liubka Valentina Trujillo, Luisa Caraballo Silva, and Ariel Dinar for their contributions to this effort.  This project was funded by the Research Committee of the World Bank under the study 'Climate Change and Rural Development' that was tasked managed by Ariel Dinar.

1
**Figure 1  Sri Lanka: Formal Remittances Surpass FDI Inflows**

<!-- Start of picture text --> U $ billion<br>1.4 0.5<br>0.45<br>1.2<br>0.4<br>1 0.35<br>Remittances<br>0.3<br>0.8<br>0.25<br>0.6 FDI<br>0.2<br>0.4 0.15<br>0.1<br>0.2<br>0.05<br>0 0<br>1988 1991 1994 1997 2000 2003<br>Source: World Bank (2005)<br><!-- End of picture text --> _Remittance flows are set to continue increasing as unskilled workers continue to migrate to the Middle East (Annex 1)._ For the unskilled worker, temporary migration to the Middle East<sup>4</sup> brings in earnings that are 8 times greater than what could be expected at home.<sup>5</sup> The Sri Lanka Bureau of Foreign Employment (SLBFE) estimates that 49 percent and 21 percent of Sri Lankans departing to work overseas in 2003 were housemaids or unskilled, respectively (Figure 2). Notably, nearly 70 percent of Sri Lankan temporary migrants are female (Annex 1); most of them working as housemaids. Just over one percent of all migrant workers are classified as skilled.

**Figure 2  Sri Lanka.  Skill Level of Departing Migrant Workers (2003)**

<!-- Start of picture text --> 30%<br>49%<br>21%<br>Housemaids<br>Unskilled<br><!-- End of picture text --> <!-- Start of picture text --> Others (Professional, Skilled and Clerical)<br><!-- End of picture text --> _Source: SLBFE_ 2
Policy Research Working Paper 7752

# **Abstract**

This papers investigates to what extent internal migration contributes to improving households’ welfare in Ghana. Using the most recent and nationally representative household survey (Ghana Living Standards Survey 2012/13), the estimates indicate that on average migration increases consumption significantly, and the effect is driven by households migrating from inland regions to the coastal areas of the country. The analysis also finds heterogeneous effects by gender and educational attainment, with migrant households headed by males and highly educated individuals faring significantly better than migrant households headed by females and low-educated individuals. The paper shows convincing evidence that the positive impact of migration on consumption is attributable to a physical mobility effect rather than changes in labor force status or sector of economic activity. However, the migration process in Ghana has important downsides, such as the brain drain and disruption of the social fabric in the communities originating migration. Future research in this area is warranted to have a more comprehensive picture of the social impact of migration in Ghana.

This paper is a product of the Poverty and Equity Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at vmolini@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
WPS4219

# **Government Expenditures on Education, Health, and Infrastructure: A Naive Look at Levels, Outcomes, and Efficiency**

## **Antonio Estache Marianela Gonzalez Lourdes Trujillo ***

## **Abstract**

All interested parties seem to agree that it is important to be able to monitor public-sector performance at the sectoral level, but most current work based on multicountry databases does not lend itself to country-specific conclusions. This is due to a large extent to major data limitations both on sectoral expenditures and on sectoral outcomes. This paper discusses the related issues and shows what we can do with the current data in spite of the drastic limitations. The main conclusions of the paper are that any efforts to assess country-specific performances in relative terms are likely to be difficult in view of the data problems. A rough sense of performance across sectors can be estimated for groups of countries, allowing some modest benchmarking exercises. These estimates show that low-income countries generally lag significantly behind higher-income countries although not equally so in all sectors. They also show that efficiency has improved during the 1990s in energy and education but has not improved significantly in transport.

### World Bank Policy Research Working Paper 4219, May 2007

_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._

> * Estache works for the World Bank in Washington, DC.  Gonzalez is with the Universidad Las Palmas de Gran Canaria (ULPGC), Spain. Trujillo is affiliated with ULPGC and with the Center for Regulation and Competition Policy (CRCP), City University, London. We are grateful to Tim Coelli, Ariel Fiszbein, Ana Goicoechea, Pablo Gottfret, Santiago Herrera, Kai Kayzer, Eduardo Ley, Harry Patrinos, Sergio Perelman, Pierre Pestiau, Anand Rajaram, David Saal, Philippe Vanden Eeckaut, and participants at a seminar sponsored by the U.K. Department for International Development for useful discussions and reactions at various stages of the preparation of this paper.
- Skoufias, E. and S. Parker (2001) “Conditional Cash Transfers and Their Impact on Child Work and Schooling: Evidence from the PROGRESA Program in Mexico” _Economia,_ 2(1):45-86.

- Snilstveit, B., Stevenson, J., Menon, R., Phillips, D., Gallagher, E., Geleen, M., Jobse, H., Schmidt, T. and E. Jimenez (2016). “The impact of education programmes on learning and school participation in low- and middle-income countries: a systematic review summary report”, 3ie Systematic Review Summary 7. London: International Initiative for Impact Evaluation (3ie)

- Subbarao, K., C. del Ninno, C. Andrews, and C. Rodríguez-Alas (2013). “Public Works as a Safety Net Design, Evidence, and Implementation” Washington, DC: World Bank.

- Tarozzi, A., J. Desai, and K. Johnson (2015): “The Impacts of Microcredit: Evidence from Ethiopia,” _American Economic Journal: Applied Economics_ , 7: 54–89.

29
We calculate connection costs within settlements by applying unit costs from KMOE (2008) to the estimates of lengths for low-voltage distribution lines and the number of required MV-LV transformers. We develop these estimates for each settlement using an optimal grid configuration for the settlement’s area. We estimate the latter from the settlement’s population, using a constant-elasticity model of the areapopulation relationship that we have fitted to a sample of African towns and cities whose areas and populations are known.<sup>13</sup> Once we have accounted for all transmission and distribution investments, we convert them to levelized costs and add the relevant levelized power generation cost to obtain total levelized supply cost per kWh.

# **_Illustration of the expansion algorithm_**

Figure 7 illustrates the application of our methodology to sequential construction of a centralized grid for Ethiopia. Figure 7a depicts the distribution of almost 1,000 settlements (dots) of known population size along with the locations of large power sources (blue rectangles). Figure 7b illustrates the operation of the algorithm. Under our assumption of a fixed demand per household, the algorithm creates the first bulk supply point (BSP) in the town with the largest total demand within the reach of a MV distribution system (120 km). It connects the BSP to the nearest generator with a HV line. Then it creates the second BSP in the town with the largest total demand in the remaining area. It connects the second BSP to the first BSP or a proximate power generator, whichever is closer. The process continues until all towns in Ethiopia are within BSP coverage zones. Then the algorithm extends medium-voltage (MV) lines along least-cost paths to connect each BSP to all the settlements within its coverage area (Figure 7c). The settlements connected to a given BSP form a supply area (Figure 7d).

> 13 Using a cross-country dataset for population ( _P_ ) and area ( _A_ ), we estimate the relationship _A=aPb_ . We then use the estimated parameters to project areas from known populations for settlements (demand points) in the case study countries.  We assume that towns are square, so that settlement width ( _W_ ) is equal to the square root of estimated area.  Low-voltage lines must be configured so that each household is no more than 48 meters from a line (KMOE 2008).  So the required number of lines ( _N_ ) is _W_ /(48 * 2), plus two additional lines for closing and cross-connection.  Total transmission line length for a settlement is _N_ * _W_ .

12
The paper contributes to the literature on the economic analysis of conflict. Most of this literature focuses on the causes of conflicts or analyzes their economic consequences in a macro or cross-country framework (Collier and others 2003, Collier and Hoeffler 2001, Collier 1998, 1999). With the notable exception of the work by Verwimp on the Genocide in Rwanda (Verwimp, 2004a, 2004b, 2003a, 2003b), few studies have used micro-level household data to look at the causes or consequences of conflict.<sup>1</sup> At the same time, by looking at the long-run consequences of mortality, morbidity and negative educational shocks, this study can contribute to a better understanding of the fertility decisions, the marriage market and the long-term benefits associated with education and good health.

This paper is structured as follows: Section II documents the excess mortality that took place during the period and decomposes it by birth cohort, gender, and family background. Section III analyzes fertility behaviors and the marriage market. Section IV investigates the long-term impact of the period on health, while section V describes the consequences on the educational attainment of the population. Section VI concludes.

# **II.  Mortality**

Estimates of mortality under the Khmer Rouge regime vary widely and are the subject of an intense debate. Sometimes this debate is more ideological than scholarly. This is not surprising, given that the government overthrown by the Khmer Rouge, led by Lon Nol from 1970 until 1975, was pro-American, that the Khmer Rouge under Pol Pot advocated a radical form of Marxism and that the regime that took control of the country in 1979 was backed by the Vietnamese. According to former Khmer Rouge, the death toll did not exceed 20,000, while according to the Vietnamese government, there were over three million victims (Heuveline 1998).

An independent Finnish Inquiry Commission estimated the death toll at one million using demographic accounting (Kiljunen 1984). Probably the most careful exercise of demographic reconstruction, comparing the population structure before and after the mortality crisis, has been accomplished by Heuveline (1998 (a)) using 1993 electoral lists.<sup>2</sup> He proposes, for the entire 1970-80 period, a central estimate between 2.2 million and 2.8 million, although he is not excluding values as low as 1.2 million or as high as 3.4 million.

> 1 See also on Mozambique, Brück (2000 and 2001) and on India, Justino (2001).

> 2 Earlier estimates based on the reconstruction approach include Ea (1981), Banister and Paige Johnston (1993) and Vickery (1984).

2
Behaviour of Firms

- 43 -

# BibUography

Commander, Simon, Leonid Liberman and Ruslan Yemtsov. 1993a. "Wage and Employment Decisions in the Russian Economy: An Analysis of Developments in 1992". World Bank, mimeo Pinto, Brian, Marek Belka and Stefan Krajewski. 1992. "Transforming State Enterprises in Poland: Microeconomic Evidence on Adjustment". World Bank, mimeo Standing, Guy. 1992. "Industrial Wages, Payments Systems and Benefits". Paper presented to ILO Conference on Employment Restructuring in Russian Industry. ILO, mimeo