rafmacalaba/datause-encoder-data huggingface dataset:
- 2 -

# **I. INTRODUCTION**

1. In recent years, there has been renewed interest in access to jobs in relation to transport connectivity. In the developing world, about 13 percent of youth (ages 15 to 24) are unemployed. In particular in Sub-Saharan Africa, about 14 million working age people are added to the labor market every year (McArthur, 2014). Ensuring sustained access to jobs seems to be a prerequisite for inclusive and robust economic growth. In Africa, urban unemployment is often much higher than the national unemployment rates ( **Table 1** ) (Girsberger and Meango, 2017). In addition, vulnerable employment, such as informal jobs and family workers, is especially high at nearly 70 percent in Sub-Saharan Africa (ILO, 2016).

2. Access to jobs is not a new topic in the literature but has long been discussed in different but relevant contexts, such as urban growth and mobility, traffic congestion, car ownership, modal choice, residential locational choice, environmental sustainability and gender inequality in the labor market. For example, Hymel (2009), using a historic highway development plan as an instrument, shows that traffic congestion weakened subsequent employment growth in U.S. metropolitan areas. Jin and Rafferty (2017) also find a similar result particularly during the 2000s.

**<u>Table 1. Unemployment rates in West Africa</u>**

|<br>|<br>|<br>Unemployment (% of<br>labor force)<br> <br>|
|---|---|---|
|Country|Capital|Capital<br>National|
|Benin|Lome|6.0<br>0.7|
|Burkina Faso|Ouagadougou|<br>20.1<br>2.7|
|Côte d'Ivoire|Abidjan|15.5<br>3.8|
|Mali|Bamako|10.7<br>6.3|
|Niger|Niamey|22.1<br>1.5|
|Senegal|Dakar|20.0<br>5.7|
|Togo|Cotonou|9.4<br>1.9|

Sources: Girsberger and Meango (2017); WDI.

3. In a basic monocentric urban model, all employment is assumed to be in the center of a city, called the central business district (CBD). The people’s demand for travel to work,
# **The Role of Information and Cash Transfers on Early Childhood Development: Evidence from Nepal**

Michael Levere Mathematica Policy Research P.O. Box 2393 Princeton, NJ 08543 <u>mlevere@mathematicampr.com</u> Gayatri Acharya Prashant Bharadwaj World Bank Group Department of Economics 1818 H St. NW UC San Diego Washington, DC 20433 9500 Gilman Dr. #0508 <u>gacharya@worldbank.org</u> La Jolla, CA 92093 <u>prbharadwaj@ucsd.edu</u> JEL Code: I15 Keywords: Cash transfer; information; early childhood development; Nepal; nutrition; maternal health; randomized controlled trial Thanks to Karthik Muralidharan, Jasmine Rajbhandary, Tara Shrestha, Venkatesh Sundararaman, Kanchan Tamang, Bishnu Thapa, and Karishma Wasti. This project would not have been possible without support from the Government of Nepal's Poverty Alleviation Fund and the Ministry of Local Development and Federal Affairs. We are grateful for funding from the Strategic Impact Evaluation Fund (SIEF).
reduction scenario, we execute three additional scenarios where each of the three components is liberalized separately, and where we simulate preferential tariff reduction.

The results are presented in table 11. For all four EACU countries, the aggregate welfare gains exceed deep integration within the EACU alone, but are considerably less than multilateral liberalization by the EACU. In the cases of Tanzania and Rwanda, the gains are very significantly smaller than with multilateral liberalization. In the case of preferential liberalization of services alone, the gains are very significantly reduced compared with the multilateral liberalization scenarios due to the relatively low market shares of partner countries in the services sectors of the Tripartite countries. The exception to this pattern is Kenya, which has a significant share of the insurance market in COMESA, where we estimate a very high ad valorem equivalent of the barriers to services providers. The improved market access for Kenyan insurance suppliers under the protected umbrella of very high barriers creates substantial gains for insurance services suppliers from Kenya in COMESA markets. We verified this this explanation by executing a scenario in which we preferentially liberalize services barriers within the Tripartite area, but exclude preferential reduction in insurance services barriers. In this scenario, the estimated gains to Kenya fall dramatically to 0.2 percent of consumption, significantly less than multilateral liberalization of services. The trade facilitation gains are larger than in the EACU Central or EACU Liberal scenarios, since the reductions in the AVE of time costs of trade extend to two additional regions of the model. In the case of Kenya, trade diversion dominates the tariff reduction scenario and there is a slight loss from tariff liberalization, despite the improved market access.

# **5.5 Sector Impacts: Diverse Trade Facilitation Impacts and the Political Economy of Regionalism**

In tables 12a-12e, we present the results at the sector level for output in the six African regions of our model. These results are presented for all the scenarios discussed above. Given that we assume that total employment and the capital stock are fixed in the medium term, if labor expands in some sectors, it must contract in other sectors. There are two key insights from the results on the changes in sector output.

**5.5.1 Trade Facilitation Impacts on Sector Output vary with the Ad Valorem Equivalents at the Sector Level.** First, our more accurate database on the time costs of trade

26
# _The Standard Approach to Benefits Transfer_

Due to the limited number of empirical estimates of the VSL in developing countries, economists have frequently used benefits transfer to estimate developing country VSLs. Most transfers are based on income differences between countries: As the lifecycle model suggests, the VSL should depend on consumption and, hence, on income. If risk preferences, discount rates and survival probabilities were the same in all countries, equation (7) would imply that the VSL should be proportional to consumption/income. The standard approach to benefits transfer treats the ratio of the VSL to per capita income as constant across countries, and uses estimates of the VSL from high income countries to estimate the VSL in middle and low income countries. We discuss the implications of this approach and then ask whether the empirical evidence from mortality risk studies in middle income countries supports it.

The simplest approach to benefits transfer is illustrated by equation (9), which says that the VSL in India—measured in US dollars—equals the VSL in the US, multiplied by the ratio of per capita income in India ( _YIndia_ ) to per capita income in the US ( _YUSA_ ). _ε_ is the income elasticity of the VSL. The equation assumes that preferences, e.g., attitudes towards risk, are the same in both countries. When ε = 1, the equation implies that the ratio of the VSL to per capita income is the same in both countries.

Equation (10) is consistent with the simplified version of the life cycle model (equation (7) above) if consumption is proportional to per capita income. The life cycle model implies that the VSL is proportional to current consumption _if people have the same discount rates, survival probabilities and the same risk preferences in both countries._ One approach to benefits transfer would be use equation (10) with _VSLUSA_ based on Kochi et al. (2006). Transferring a VSL of $5.4 million (2000 USD) to Turkey would imply a VSL in Turkey of $960,000. The corresponding figure for Colombia would be $640,000. Both figures are consistent with the VSLs used by Smyth et al. (2004a) and Ghesquiere et al. (2006). It should be noted that the VSL/Y ratio implied by the use of Kochi et al. is approximately 140:1, a figure that coincides with Miller’s (2000) recommended approach to benefits transfer.

Equation (10), however, assumes that risk preferences, discount rates and survival probabilities are constant across countries, which may, however, be unjustified. One way of testing this assumption is to examine the ratio of the VSL to per capita income based on available studies. Is it approximately constant? Miller’s (2000) ratio of 140:1 is based on studies from 13 high income countries. Averaging the VSL/Y ratios reported by Robinson (2008) from 11 studies in middle income countries, however, implies a VSL/Y ratio closer to 80:1. For example, Liu, Hammitt and Liu (1997) find a ratio of 77:1 in 19
|Forest Sector Development Project - Supplemental Credit|Lan Thi Thu Nguyen|
|---|---|
|Forest Sector Development Project - Supplemental Credit|Lan Thi Thu Nguyen|
|Forest Sector Development Project - Supplemental Credit|Lan Thi Thu Nguyen|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Jepirachi Carbon Off Set Project|Claudia Croce|
|Second Economic Management and Growth|Susan Ngoza Mpande|
|Second Economic Management and Growth|Susan Ngoza Mpande|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|State Governance and CapacityBuildingProject|Ikechukwu John Azubike Nweje|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|Governance and Institutional Development Project|Anne-Lucie Lefebvre|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|WWB Facilityfor Affiliate Capitalization|Ousa Sananikone|
|Pilot Water Supply& Sanitation Project|Maria Angelica Sotomayor Araujo|
|Pilot Water Supply& Sanitation Project|Maria Angelica Sotomayor Araujo|
|Pilot Water Supply& Sanitation Project|Maria Angelica Sotomayor Araujo|
|Pilot Water Supply& Sanitation Project|Maria Angelica Sotomayor Araujo|
|Pilot Water Supply& Sanitation Project|Maria Angelica Sotomayor Araujo|
<!-- Start of picture text --> 2 2.<br>72 e ‘=<br>s ) 5 (Co)<br>a e ae<br>2e<br>2 e ott<br>= £<br>oO ee e } Tet A<br>2 e. 3%<br>agi’ e . 2 Ps<br>oO<br>30 80 130 180 230<br>Distance to Electric Grid (Km) 0 50 100 150 200<br>Distance to Nearest Main Road (Km)<br>2 pw<br>s $0<br>me} uo]<br>ore Lo<br>5 e an<br>6 ° 6.<br>ou ° kd )<br>fe) Pate)<br>5 3°<br>8 ° 8g<br>es a ©<br>0 50 100 150 200 0 50 100 150 200<br>Distance to Electric Grid (Km) Distance to Nearest Main Road (Km)<br>Source: DHS<br><!-- End of picture text -->
Figure 11. Percentage of Population (15+) that has Saved Money in a Financial Institution <!-- Start of picture text --> 2011 2014<br>70% 70%<br>60% 60%<br>50% 50%<br>40% 40%<br>30% 30%<br>20% 20%<br>10% 10%<br>0% 0%<br>Turkey BRIC Rest of High Rest of Turkey BRIC Rest of High Rest of<br>Developing Income ECA Developing Income ECA<br>World World<br>Lowest quintile q2 q3 q4 top quintile<br><!-- End of picture text --> _Source_ : FINDEX 2011, 2014 Between 2011 and 2014, Turkey succeeded in increasing its savings rate at financial institutions at a faster rate than comparator country groups. However, bank use for savings in Turkey, at 9.1 percent, is still lower than the developing world average of 10.3 percent in 2014. Moreover, decomposing the growth of formal savings in Turkey points to specific cohorts that drive the heterogeneous increase. The increase in the top quintile of income earners was higher in comparison to the lower quintiles. Figure 11 displays the increasing disparity among the income quintiles in Turkey between 2011 and 2014. In addition to the heterogeneity in terms of earnings, individuals older than 65, and the ones who have higher education were able to expand their formal savings rates at a higher pace. Therefore, it will be important for Turkey to build on its success of increasing formal savings by ensuring that this growth is evenly spread across different age, income and level of education cohorts.

There is high dissimilarity in savings using financial institutions, but not compared to countries with similar coverage. Compared to all 145 countries in the FINDEX database, the dissimilarity index is high at 33.7 (Figure 30). However, countries with similar coverage also have very high inequity in formal savings, and many at rates higher than in Turkey. The decomposition of the dissimilarity in 2011 shows that level of income and gender are the two main reasons of not being able to save at financial institutions in Turkey. Age stands out as a larger source of dissimilarity among the benchmark countries.

Between 2011 and 2014, Turkey’s coverage rate in formal savings increased from 4.2 percent to 9.2 percent. However, this increase is not coupled with an improvement in the d-index as Turkey’s dissimilarity rises slightly during the same period. The Shapley decomposition of the d-index shows that the impact of gender decreased while the contribution of education increased. However Turkey’s gender portion of dissimilarity in 2014 was still higher than the benchmark countries with the exception of Algeria. Going forward, making formal savings more abundant amongst individuals with a lower level of income and education could help Turkey in lowering the d-index and boost equitable financial inclusion.

13
Policy Research Working Paper 6739

# **Abstract**

This paper aims at assessing the impact of migration on export performance and more particularly the effect of African migrants on African trade. Relying on a new data set on international bilateral migration recently released by the World Bank spanning from 1980 to 2010, the authors estimate a gravity model that deals satisfactorily with endogeneity. The results first indicate that the protrade effect of migration is higher for African countries, a finding that can be partly explained by the substitution between migrants and institutions (the existence of migrant networks compensating for weak contract enforcement, for instance). This positive association is particularly important for the exports of differentiated products, suggesting that migrants also play an important role in reducing information costs. Moreover, focusing on intra-African trade, the pro-trade effect of African migrants is larger when migrants are established in a more geographically and ethnically distant country. All these findings highlight the ability of African migrants to help overcome some of the main barriers to African trade: the weakness of institutions, information costs, cultural differences, and lack of trust.

This paper is a product of the Poverty Reduction and Economic Management Unit, Africa Region 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 rsingh9@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
from conflict have strong negative effects on GDP growth (Ra and Singh 2005). In particular, for a 4.2% decline in development expenditures, Nepal is forecast to have lost about 1.7% of annual growth in GDP between the 2005-2009 fiscal years. That said, the decline in GDP growth is likely to be an underestimate as other factors such as destruction of infrastructure, disruption of activities, lower private investment, and displacement of people are not taken into account in the specifications. Such effects are incorporated in our estimations through the inclusion of controls for region and year.

Nepal‟s civil war also resulted in a disproportional increase in consumption by households with relatively more land, with the landless or those with extremely small amount of land suffering from relative deprivation. Such increases in inequality help to explain the rise in Maoist recruitment activities, since such activities were relatively more pronounced in districts where inequality had increased significantly (Macours, 2010). We control for the effects of poverty and inequality in our models.

Existing literature is not conclusive that a greater proportion of Nepalese women did in fact enter the labor force as a result of the conflict-induced changes in household composition and income. Assessment results reported in the World Bank (2004) indicate that the absence of husbands and their income led to a dramatic increase in women‟s household and farm work burdens, but the findings do not specify whether this increased work burden coincided with higher rates of employment. The income effect from remittances sent home by migrant husbands could have acted as a disincentive for women to become employed. Also, the departure of a spouse who contributed to household farm production may have put more pressure on women to increase their hours of work in subsistence farming. Both of these arguments help to explain Lokshin and Glinskaya‟s (2009) finding of an inverse relationship between men‟s migration and 7
|**Table 3: Short-term Effec**|**ts of Systematic**<br>**Parcels reg**|**Registration,**<br>**. first-time**|**Basic Regres**<br>**Reg.**|**sion and Placeb**<br>**sales**|**o Test**<br>**Reg. m**|**ortgages**|**Built area**|
|---|---|---|---|---|---|---|---|
||**Total**|♀ C**o-own**|**Total**|♀ C**o-own**|**Total**|♀ C**o-own**|**Registered**|
|**Panel A: Regression**||||||||
|Syst. dummy (SyD)|9.191***|8.006***|0.083***|0.090***|0.021|0.022*|0.142***|
||(0.340)|(0.310)|(0.028)|(0.019)|(0.018)|(0.013)|(0.008)|
|R-squared|0.472|0.477|0.054|0.058|0.031|0.027|0.639|
|Mean dep. var.|0.163|0.052|0.038|0.012|0.030|0.007|0.067|
|SD dep. var.|0.600|0.293|0.221|0.117|0.183|0.084|0.092|
|**Panel B: Placebo**||||||||
|Pseudo syst. dummy|0.015|0.046***|-0.007|-0.009|-0.003|0.005|0.000|
||(0.027)|(0.013)|(0.014)|(0.008)|(0.010)|(0.003)|(0.001)|
|R-squared|0.014|0.011|0.013|0.011|0.006|0.001|0.288|
|Mean dep. var.|0.157|0.049|0.036|0.011|0.028|0.007|0.065|
|SD dep. var.|0.593|0.282|0.214|0.113|0.176|0.081|0.091|

_Note:_ Regressions in panel A are for 2000–14 with systematic first-time registrations in 2011–13; placebo tests in panel B are for 2000–08 with a pseud-systematic registration six years earlier; dependent variables are as indicated in the table title. Population density, share of built-up area of the block, block and year fixed effects, and a constant are included throughout; the coefficients are not reported. The number of observations (i.e., 250m x 250m blocks) is 22,710 (1,514 for 15 years) in panel A and 13,626 (1,514 for 9 years) in panel B. Mean and standard deviation for the dependent variable are for the pre-program period. Standard errors are in parentheses. * p<0.10, ** p<0.05, *** p<0.010.

22
_The Global Information and Communications Technology Industry: Where Vietnam Fits in GVCs_

- Phan, Chau. 2008. “Vietnam as an IT Outsourcing Destination.” Capstone Project for Business, Policy and Strategy Course. Available from Washington Research Library Consortium: http://aladinrc.wrlc.org/handle/1961/4778

- Sturgeon, Timothy. 2002. “Modular Production Networks: A New American Model of Industrial Organization.” _Industrial and Corporate Change_ 11 (3): 451–96.

- Sturgeon, Timothy, and Momoko Kawakami. 2011. “Global Value Chains in the Electronics Industry: Characteristics, Crisis, and Upgrading Opportunities for Firms from Developing Countries.” International Journal of Technological Learning, Innovation and Development 4 (1): 120–147.

- Sturgeon, Timothy, and JiRen Lee. 2005. “Industry Co-evolution: A Comparison of Chinese Taipei and North American Electronics Contract Manufacturers.” In _Global Chinese Taipei: Building Competitive Strengths in a New International Economy_ , ed. Suzanne Berger and Richard K. Lester. Armonk, NY: M.E. Sharpe.

- Sturgeon, Timothy, and Richard Lester. 2004. “The New Global Supply-base: New Challenges for Local Suppliers in East Asia.” In _Global Production Networking and Technological Change in East Asia,_ ed. Yusuf Shahid, M. Anjum Altaf, and Kaoru Nabeshima, paper 2. Oxford UK: Oxford University Press.

- Sturgeon, Timothy, and Olga Memedovic. 2010. “Measuring Global Value Chains: Intermediate Goods Trade, Structural Change and Compressed Development.” UNIDO Working Paper. United National Industrial Development Organization,Vienna.

37
27 Table 10: Foreign Population of Australia by Sex and Number of Years since Immigrating <!-- Start of picture text --> 0-4 YEARS TEARI Aw* OVCR TO IfieL v STAT901<br>"USTRIA ANAO& MAL PEKALI PlesStil s ^AL II I I? f n P112*10" MA I 10 FEMALE PE; O"<br>C"ILE I 16 I 4 A 144 $262<br>CHINA 13 I(A 6 58 447 ?*<br>TPRUS 14? 1.99 lit? I? 6 121 1 194 IP,<br>89C"OSLOVAICIA 716 '143 III I 156 64 1 ?468<br>MOT I 91 63 III 13643<br>INGLAND(INCL FRANCE UK Ukagirltdo .416 IC 34? i Is 190 V 4 A 31 1 4 ? 0 14 5 I 144 14 I?&?4386ii<br>G ONART if IIF I 4 43<br>GaElca 0<br>HONG Kom 16 5 4 s ?6 1<br>NUWaAAl 59 A Ms 5')67 p I I 1 S? 14 4 "94? 1 4 1 ?13a 9<br>inciA 4AA4 i464 I I 9; r 04<br>IMOWSIA a &all I I19 I<br>I vALT RILAND(atpulLIC) ?e , 64 Is 54 5 I I ? 14 ?<br>LArVIA 4 42 134 1<br>LCIAnDa 444<br>RALA 7S<br>TVIIA &A<br>OUL A 1866i 212 1<br>A# 6<br>i"(W CALA 3 44i 41 16 44<br>WAYNINIO IRELAND 1 H 31" 6 of a?4<br>PAPIJA WE GUINCA 1491 a I II I9<br>PwILIPPiNwas 140<br>POLANO 464 11916 1 4<br>PORTUGAL S93? 6 4 1 4 2 2s<br>SCOTLAme 1 04 R<br>SINGA P" 4 4 4944 66 4?3 7441<br>SOUTH AllICA SPAIN (*EPUILIC) I I I ? I I R i64?061<br>1:11CLANKA<br>of<br>A<br>igicTiW&LINAM VI 15 ?<br>TYNGIILAVIA io<br>0 16 It 79 1 41<br>TOTAL OWt1SJAS go*" 2 164 2 1 4 4 4 ? 13 4251 41 Is, is 3603<br><!-- End of picture text --> Source: Australian Bureau of Statistics, unpublished data.