rafmacalaba/datause-encoder-data huggingface dataset:
considerable heterogeneity within the informality and self-employment sectors. The Latin American literature is reviewed more fully in Fields et al. (forthcoming).

In addition to the work done on earnings mobility, there also is a literature on income mobility in developing countries. For a sampling of this literature, the interested reader may consult the studies on South Africa, Indonesia, Venezuela, and Spain by Fields and associates (2003) and on China by Jalan and Ravallion (2000) as well as the work by the Chronic Poverty Research Centre (www.chronicpoverty.org) on countries around the world, especially their flagship publication (Chronic Poverty Research Centre, 2004).

4. Cross country time series data. The simplest kind of time series data is that which follows given variables within a country over time. Time series data allow for the determinants of changes over time to be modeled explicitly. For example, the wage elasticity of formal sector labor demand in South Africa was estimated using such data; Fields, Leibbrandt, and Wakeford (2000) present their own and earlier estimates. Despite differences in time periods and estimation methods, these studies concurred that the range of estimates was on the order of -0.4 to -0.6 – certainly not zero. This finding led policymakers in that country to recognize that the push by the Congress of South African Trade Unions for higher wages would likely result in reduced formal sector employment.

Another useful kind of time series data is collected for a number of countries for a number of years, producing what is called cross country time series data. An insightful use of such data has been made by Rama (2003a) to address the question of whether greater integration with world markets is a source of prosperity for developing and transition economies or a source of increased hardship. Since both views are plausible theoretically and rigorous models have been devised to support them, it becomes an empirical question as to what matters in what direction. The data set used by Rama was information on the wage in a particular occupation in a particular year for each of a large number of countries, from which wage levels and wage inequality were constructed as dependent variables. Explanatory variables included measures of economic openness, labor market policies, and social protection policies. The research produced three broad conclusions. First, the effects of globalization on labor market outcomes are neither always positive nor always negative. Second, social protection programs are effective in 38
and presents descriptive statistics. Section 4 discusses the empirical strategy and section 5 presents the empirical results. The final section concludes.

# 2 Country Context

Ethiopia is one of the largest countries in Africa, characterized by low levels of urbanization, high rates of poverty (23.5% of the population lived below the national poverty line in 2016) and low levels of human development, with only about half the adults being literate and only one-third of youth (aged 15 -24) having completed primary school (World Bank, 2020).

There are also major gender gaps. Women are less likely to own land alone or jointly (40% compared to 48% of men, with men owning a larger proportion of land than women) and to use a bank account (15% compared to 25% of men), and almost one in four women have experienced physical violence since the age of 15 (23%) and sexual violence (10%) (CSA & ICF, 2017). Access to health care service is also a problem for women due to poverty and distance to the health facility. Female rates of agricultural labor participation are 55%, compared to 83% for men (Hasanbasri et al., 2021). As elsewhere in the world, women and girls do most of the unpaid household and care work (Admasu, Crivello, & Porter, 2021; Pankhurst, Crivello, & Tiumelissan, 2016), which reduces their time available to engage in education and/or paid employment.

Ethiopia traditionally had an open-door policy towards refugees and is among the largest hosts of refugees in Africa.<sup>3</sup> In the Horn of Africa, refugee movements have been driven by the conflict in South Sudan, the prevailing political environment in Eritrea, and the conflict and drought in Somalia (World Bank Group & UNHCR, 2015). The number of refugees in Ethiopia has increased over the last decade, exceeding 735,000 in 2020 (UNHCR, 2020a). The majority of refugees live in the 24 government managed camps, near the borders of their respective country of origin (Figure A2), located in Tigray region and the four emerging regions: Afar, Benishangul-Gumuz, Gambella, and Somali (UNHCR, 2020a). The four regions that host refugees are also the least developed regions in the country, characterized by poor infrastructure, high poverty rate, low administrative capacity and poor development indicators (Pape et al., 2018; UNHCR, 2020a).

While Ethiopia has long history of hosting refugees, their prospects for durable solution has been hindered by the traditional encampment policy (Zetter & Ruaudel, 2016). Refugees were disadvantaged because of legal restrictions on their right to work, restriction on movement and residence, and inability to obtain business licenses, which prohibits them from taking up most forms of formal employment or establish their own enterprise. These legal restrictions together with the isolation of refugees living in camps limited their livelihood opportunities (Samuel,

> 3 In addition to refugees, Ethiopia has a large number of internally displaced persons (IDPs) with more than 1.8 million IDPs in 2020 (IDMC, 2020; IMO, 2020). The main causes of displacement are conflict, drought and floods (IDMC, 2020).

3
of our results to differential attrition in the firm survey sample in Section 6.3. By order of preference we interviewed the CEO, legal counsel, or another suitable respondent. We surveyed a range of perceptions of the justice system, asked them to report the economic costs associated with having an ongoing case, and elicited their willingness to pay for judicial services associated with faster pre-trial proceedings.

# **4 The 2013 pre-trial reform**

The legal reform we study aimed to increase judicial efficiency of the pre-trial trial procedure and, in doing so, improve the business and investment climate (Minist`ere de la Justice, 2013).<sup>9</sup> The decree application was staggered across the six civil and commercial chambers of the Regional First Instance Court of Dakar between October 2013 and March 2014 (Figure 2). It modifies the civil and commercial procedure in two main ways: first, it sets a fourmonth limit on the pre-trial procedure; and second, it gives pre-trial judges the ability to “desk reject” a case based on poor evidence ( _“irrecevabilit ́e en l_<sup>_′_</sup> _ ́etat”_ ).<sup>10</sup> Before the application of the decree, only half of all civil and commercial cases completed pre-trial in four months or less, and the average case underwent 8.3 pre-trial hearings over a 157-day period (Table 2).

This new instrument of “desk-rejection” can only be exercised in the first pre-trial hearing, which precludes its use for ongoing cases. Similarly, judges were not obligated to apply the new deadline to ongoing cases. We use these features for our identification (together with the fact that judges belong to only one chamber), as we define cases that enter after decree application as treated, while those that entered before decree application serve as our comparison group in our event study. However, judges may also try to meet the new four-

> 9 _◦_ Decree n 2013-1071 was ratified by the ministerial council on July 18, 2013 and published on August 6, 2013.

> 10Before the reform, such cases would undergo the pre-trial procedure to be then judged on the limited evidence.

9
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26 M. FAY, D. MARTIMORT, S. STRAUB with Public Debt = Multilateral Debt + Bilateral Debt + Institutional Debt + Public National Debt, and (4.2) _PrivateFinancing_ = _CommercialDebt_ + _PrivateEquity._ Based on this, the financing indicators used in the paper are computed as follows: = (4.3) _ShareofPrivateFinancing PrivateFinancing/TotalFinancing,_ where Total Financing = Public Financing + Private Financing, and (4.4) _ShareofPrivateDebt_ = _PrivateDebt/TotalDebt,_ where Total Debt = Public Debt + Commercial Debt.

Following the model, the institutional and financial market characteristics that are relevant to the financial structure of projects fall in several categories.<sup>26</sup> First, the availability of private project financing is likely to be dependent on features of the financial sector, including the perceived cost of bankruptcy and the level of competitiveness. We consider the following proxies:

- The Doing Business Resolving Insolvency indicator, as a measure of the cost of audit facing financial institutions that lend to the projects.

- The ratio of the assets of the five largest banks to total commercial banking assets, as a measure of the competitiveness of local financial markets, from the World Bank Global Financial Development Database.

Second, we consider the cost of public funds, due to distortionary taxation:

- The marginal cost of public funds (MCF) estimates computed by Ensor (2016) for 106 countries, following Auriol and Warlters’ (2012) model.

Third, we consider two measures of institutional quality from the World Bank Worldwide Governance Indicators (WGI): Regulatory Quality, and Control of Corruption.

Figure 1 illustrates the correlations between the project-level ratio of private to total debt, as defined in (4.4), and the level of development, measured with per capita GDP.<sup>27</sup> The non-linear fit reveals an inverse U-shaped relationship, with the share of private finance being maximized at an intermediate level of pcGDP. The left panel uses the whole set of projects with financial information. To adjust for the fact that countries with a lot of projects such as Brazil, India, or Mexico, are potentially biasing the pattern, the right panel shows country averages pooled over the three years.

In the Appendix, Figure A1 provides equivalent correlations using instead the ratio of private to total financing defined in (4.3). The conclusions are unchanged.

As argued above, the concave pattern linking private finance use and pcGDP is likely to be the result of complex relationships between different features of the institutional

> 26See the Appendix for a detailed description of all the variables and their sources.

> 27The sample covers 327 projects, excluding 34 projects for which there is no debt financing.
RURAL-URBAN GROWTH LINKAGES IN INDIA

# Table of Contents

||||Page|
|---|---|---|---|
||EXE|CUTNE SIRY<br>..............................|I|
|L|INTR|ODUCTION ................................|1|
|IL|DES|CRIPTIVE<br>PROFILE OF NONFAM ACTIVITY .......<br>.....|2|
||A.|hIportance<br>....|2..........<br>2|
||B.|Location .6||
||C.|Compositon .8||
||D.|Fe-male Participaton .10||
||E.|Trends .12||
|IIL|AGR|ICULTUE AND GROWTH<br>OF THE_NONFAR_ECONOY ..|.....<br>15|
||A.|Key Linkages ...........................|15|
||B.|, ior Evidence ..........................|16|
||C.|Comparisons Across States ..................|18|
|IV.|ESTI|MATING RURAL A(;RICULTURAL<br>GROWTH<br>MULTPLIERS..<br>|.....<br>26|
||A.|Econometric Model ........................|26|
||B.|Income Multipliers<br>........................|29|
||C.|Employment Multipliers<br>.....................|31|
||D.|Projections<br>............................|31|
|V.|PRO<br>DEM|JECTIONS<br>OF NATIONAL MANUFACTURING<br>AND TERTIARY<br>AND RESULTING<br>FROM AGRKILTURAL GROWTH .....<br>. . . .|.<br>40|
||A.|Semi-Input-OutputModelingof GrowthMultipliers.|..<br>. 40|
||B.|<br>Results<br>.........<br>. .. . .. . . .. . .. . .. . . ..|.<br>43|
|Vl|CON|CLUSIONS<br>..........<br>..<br>............<br>.. .. .. .|.<br>47|
||REFE|RENCES<br>...........<br>.. .. .. .. .. .. .. .. .. .. .|.<br>49|

## APPENDIX A. SUPLEMNTARY TABLES

## APPENDIX B: A FIVE-SECTOR SEMI-INPUT-OUTPUT W)OEL

Background paper prepared for the 1991 Country Economic Memorandum for India
Policy Research Working Paper 10565

# **Abstract**

This paper describes a new survey designed to collect comprehensive and granular information about required skills and tasks for detailed occupations in Vietnam. The Survey of Detailed Skills asks workers in Vietnam about their skills and tasks for a set of 30 occupations that are in demand or of strategic importance for economic growth. In doing so, the survey generates practical, detailed information at the occupation level that policy makers and practitioners can use to inform their efforts to build skills in Vietnam. The Survey of Detailed Skills makes several contributions. Most existing efforts to profile occupational skills and tasks in developing countries draw on data from other countries, most frequently the Occupational Information Network (O*NET) in the United States. However, recent research has shown that translating these data across countries via occupational crosswalks yields inaccurate results. The Survey of Detailed Skills is among the first surveys to collect detailed O*NET-type information at the detailed occupational level in a developing country setting. The collection of information about detailed skills means that these skills can be flexibly grouped into different categories (for example, socioemotional skills, digital skills, routine skills, and interpersonal skills) as needed. The use of a consistent scale anchored to the time spent using or performing a skill or task creates clarity for respondents while also yielding a measure of skill and task importance that is easily interpreted. The Survey of Detailed Skills requires outlays on administering the survey, and inclusion of all occupations in Vietnam with regular updating would require ongoing investment.

This paper is a product of the Social Protection and Jobs 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/prwp. The authors may be contacted at hmoroz@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
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assuming that in LAC countries a deeper level of accountability to the Executive might affect the autonomy of the agency.

# **A. Formal vs. informal:**

The formal aspects of agencies’ accountability reflect the existence of agencies’ internal and external (Executive, Legislative and Judicial branches) structures for accountability, while informal aspects are related to the implementation of provisions in their statutes or laws. For instance, while question 51 of the ERGI asks the agency whether it is accountable to the Executive or the Legislative branch, question 52 of the ERGI explores the actual reporting obligations of the agencies before one or the other branches of government.

Disparities between the formal and informal aspects of accountability are the largest among all variables. As mentioned previously, the driving factors of those disparities are the types of reporting instruments the agency must use and the types of obligations of the regulator before the Executive and the Legislative. It is important to highlight that the ERGI is oriented towards an accountability mechanism based on legislative control over the agency, with only informational reporting obligations to the Executive. Hence, an agency will achieve a higher score in the informal accountability index if it is fully accountable to the Legislative and only subject to informative reporting obligations to the Executive. Also, and in connection with the agencies’ reporting instruments, the ERGI gives higher scores to an accountability scheme that combines hearing obligations before the Parliament with an annual report of its performance.

**Figure 19: Formal Accountability Index**

**Figure 20: Informal Accountability Index**

<!-- Start of picture text --> Formal Accountability Index Informal Accountability Index<br>Source: LAC Electricity Regulatory Governance Database, The World Bank, 2007. Source: LAC Electricity Regulatory Governance Database, The World Bank, 2007.<br>1 1<br>.8 .8<br>Index (0-1) .6.4 Index (0-1) .6.4<br>.2 .2<br>0 0<br>T&T PER MEX ESV COL BRA BOL BAR T1 NIC C R PAN GUA ECU ARG T2 R D JAM HON CHI URU T&T GUA T1 BRA R D BOL URU BAR ESV COL ARG T2 NIC PER MEX JAM C R ECU HON CHI PAN<br><!-- End of picture text --> Countries at the top of the Formal Accountability Index have only informational reporting obligations to the Executive and, particularly in the case of Trinidad and Tobago, the obligation to submit a report that must be approved by the Parliament. Their agencies are also required to submit an annual report and their directors are subject to public hearings before the Congress. Countries that do not meet the minimum requirements to implement this accountability scheme are the Dominican Republic, Jamaica, Honduras, Chile, and Uruguay.

When it comes to the practices that characterize agencies’ accountability, only two countries, Trinidad and Tobago and Guatemala, are among agencies with desirable levels of informal

- 31 -
suggest that cross-national variation in annual instructional time is quite marked. Thus, for example, while the relative emphasis on mathematicc or science in the official primary curriculum may change slowly over time or vary quite modestly over national space, measures of the number of hours mathematics and science subjects are taught each year are thought to vary more markedly. Also, many scholars .naintain that students learn more when they are exposed to more instruction in a particular subject area or when they spend more time "on task" (Fisher and Berliner, 1985;<sup>Karweit,</sup> 1985; Murphy and Hallinger, 1989). One might then draw the following two inferences: 1) nations gain more, in economic or political terms, when their mass school systems require more<sup>overall</sup> time of fornal instrucdion; and 2) nations gain more when they expose greater numbers of<sup>students</sup> to greater amounts of formnal instruction. The first inference assumes an additive effect of instructional time whereas the second one assumes a multiplicativ **e** ffect. Both ideas wilU be tested in this study.

To develop estimates of annual instrucdonal time, published sources and official correspondence were examined so as to retrieve informaadon on the length of the school year (in weeks or days), the length of the school week (in weekly school periods or actual hours<sup>of</sup> instruction), and the length of a school period (in fractions of hours). Combining<sup>previously coded</sup> curricular information with this new information, estimates of average annual<sup>hours of instruction</sup> fo: each subject area were constructed for about 80 nations in the 1945-69 period<sup>and some 100</sup> nations in the 1970-86 period. These figures refer to the number of forrnal instructional<sup>hours that a</sup> typical pfimary school student is supposed to receive each year in a given<sup>subject area. Whenever</sup> possible, school time set aside for recesses, breaks, assemblies and the like was excluded. Although some error is inherent in this sort of data, there is good reason to believe<sup>that they permit</sup> reasonably valid and reliable comparisons across national space (for further discussion of how<sup>these</sup> figures were estimated, see Kamens and Benavot, forthcoming).

# Th Meaning of Official Curicular Data

The curricular data employed in this study are official policy declarations<sup>of subjects to be</sup> taught in primary schools, generally produced by government education officials in the form of q