rafmacalaba/datause-encoder-data huggingface dataset:
Taking Stock of Wholesale Power Markets in Developing Countries: A Literature Review _Energy Integration: An Outstanding Dilemma_ . _Evolution of Global Electricity Markets_ . Elsevier. https://doi.org/10.1016/B978‐0‐12‐397891‐2.00014‐6

- Roques, F. A. (2008). Market design for generation adequacy: Healing causes rather than symptoms. _Utilities Policy_ , _16_ (3), 171–183. https://doi.org/10.1016/j.jup.2008.01.008

- Rudnick, H., Araneda, J. C., & Mocarquer, S. (2009). Transmission planning‐from a market approach to a centralized one‐the Chilean experience. In _2009 IEEE Power & Energy Society General Meeting_ (pp. 1–7). IEEE. https://doi.org/10.1109/PES.2009.5275552

- Rudnick, H., Barroso, L. A., Skerk, C., & Blanco, A. (2005). South American reform lessons ‐ twenty years of restructuring and reform in Argentina, Brazil, and Chile. _IEEE Power and Energy Magazine_ , _3_ (4), 49–59. https://doi.org/10.1109/MPAE.2005.1458230

- Rudnick, H., & Montero, J.‐P. (2002). Second Generation Electricity Reforms in Latin America and the California Paradigm. _Journal of Industry, Competition and Trade_ , _2_ (1–2), 159–172. https://doi.org/10.1023/A:1020887106859

- Ryan, N. (2014). _The Competitive Effects of Transmission Infrastructure in the Indian Electricity Market_ . Retrieved from

- http://campuspress.yale.edu/nicholasryan/files/2014/10/ryan_competition_india_electricity _2014oct23‐1gdti64.pdf

- Sen, A. (2014). _Divergent Paths to a Common Goal? An Overview of Challenges to Electricity Sector Reform in Developing versus Developed Countries_ (No. EL10).

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http://www.nera.com/content/dam/nera/publications/archive1/5566.pdf

- Sidak, J. G., & Baumol, W. J. (2001). Stranded Costs. _SSRN Electronic Journal_ . https://doi.org/10.2139/ssrn.283232

- Singh, A., Jamasb, T., Nepal, R., & Toman, M. (2015). _Cross‐Border Electricity Cooperation in South Asia_ (Policy Research Working Paper No. 7328). Washington, DC.

- Sioshansi, F. P. (2008). _Competitive Electricity Markets: Design, Implementation, Performance_ . Oxford, UK: Elsevier Ltd.

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2011, 2012): License, Localization, Herfindahl, Education and Vocational Training.

- 2) Data for the following variables is taken from the Welfare and Monitoring Survey (2011): Electricity, Transport and Water.

|Variable Name|Variable Description|
|---|---|
|Dependent variable|Growth of employment|
|License|Share of employment in licensed enterprises|
|Localization|Log of Localization|
|Herfindahl|Log of Hirschmann Herfindahl index)|
|Education|Average years of school education|
|Vocational Training|% of labor force with TVET training|
|Electricity|% of households using electricity for lighting|
|Transport|Log of households’ average distance to access public transport|
|Water|Log of households’ average distance to access drinking water|
|Year|Year fixed effects|
|City|Cityfixed effects|

# **5 Policy and Conclusions**

The distribution of economic activity and employment over physical space (i.e. economic geography) is central to economic development. Geographical variations in industrialization are an important factor affecting geographical variations in jobs. And so the question of which kinds of industries and cities are creating employment and why is vital to an understanding of economic growth and development. City leaders care increasingly about creating and maintaining employment within particular locations by encouraging industries and firms. They are interested in understanding what sorts of policy levers affect economic outcomes – is it a set of infrastructures? Fiscal incentives? Good business environment? Or could it be agglomeration – the compounding effect of existing industries and firms? The primary objective of this study is to investigate what drives employment and economic growth in Ethiopian cites so as to inform leaders how best to prioritize policy decisions.

Ethiopia has a small, yet significant, window of opportunity to exploit its demographic dividend. Its labor force doubled over the last two decades, and it continues to have a very large youth bulge entering the labor market in the next 20 years. Many of these young people will be moving to cities in search of employment. Urbanization could become one of the most important catalysts to tackle economic growth and job creation in the next few years, even decades. Cities should aim to create the conditions for entrepreneurs, firms, and industries to become competitive.

An analysis of industrial development and employment outcomes reveals that:

- On average, formal manufacturing employment is concentrated in Addis. However, **much of new job creation is coming from emerging cities** (such as Adwa, Sebeta and Debrezeit). Other fast-growing cities, like Mekele, Nazareth and Awassa, attract new firms, but without commensurate increases in employment. **Capital intensity in many cities is growing** – which might be worrying if policy makers would like to focus on encouraging labor-intensive production.

- **97 per cent of new job creation comes from large firms** . Most firms are small

30
17 550 vehicles per kilometer of road. The maximum value in the sample, 425, is found in Paris. It is interesting to note that Paris is often considered to be one of the more successful world cities in effectively controlling the use of motor vehicles. In contrast, no saturation level is found from the national level data for both total road and paved road networks. The result is not surprising as the national road networks are rarely congested.

# **4. Concluding Remarks**

This paper explores alternative specifications for the relations of vehicle ownership, road length, and the vehicle-road ratio with various independent variables at the national and urban level. It examines three issues: dependent variable definition, equation specification, and urban historical spatial endowments. We first summarize the results of these efforts and then comment on the overall implications of the findings.

**Dependent variable definition.** The analysis here compared the results of normalized (e.g., vehicles per thousand persons) and non-normalized (e.g., vehicles) dependent variables in regression equations to explain vehicle ownership and road length. For vehicle equations at the national and urban level, the normalized and non-normalized results were very similar because the elasticity of population with vehicle ownership is approximately 1, and population has a constant scale effect on vehicle ownership. The road length regressions at the national level produced similar results with normalized (road length per square kilometer) and non-nornalized (road length) dependent variables. This was not true at the urban level where the nornalized dependent variable had been road length per capita. In the urban road length equation, population had an elasticity of around 0.8, and because it differed from 1, the non-normalized equation elasticities differed from the normalized equation elasticities. The general lesson from this exercise is that normalized dependent variables should not be used without testing for their validity. Nonnormalized variables are generally preferable.

**Equation specifications.** The first question addressed was whether the elasticities of the various dependent variables were constant or varying with respect to the main independent variables--income, population, and population density. The results of this exercise are summarized in Table 5. The results of main interest pertain to the income elasticities, where the most notable feature is the contrast between the national level and urban level results. The income elasticity of vehicle ownership is weakly variable at the

**Table 5. Summary of Elasticity Results--Constant versus Variable**

|Dependent||National||Urban|
|---|---|---|---|---|
|variable|Income|Population|Pop. density|Income|
|Vehicles|variable?|constant|constant|constant|
|Road length|constant|constant|constant|variable|
|Vehicle-road ratio|variable|variable|constant|variable|
(column 3). In column 4, we add the industry fixed effects. We do not control for the level of Herfindahl index here separately as it is absorbed by the industry fixed effects. Results in column 4 show that controlling for industry fixed effects causes the interaction term between _Nondiscrimination_ and the Herfindahl index to become smaller in magnitude but it is still positive, economically large and significant at close to the 10 percent level (p-value of .105). To get a sense of the magnitude involved, consider the specification in column 4 where the interaction term is smallest in magnitude. Estimates in the column imply that mandating of the nondiscrimination clause is associated with an increase in female (to total) employment by 3.93 percentage points (p-value of .103) in the most competitive industry (Leather). The corresponding change for the two least competitive industries is much larger equaling 10.1 percentage points (significant at less than the 1 percent level) in Electronics and 11.6 percentage points (significant at less than the 1 percent level) in the Textiles sector. We believe that these results are consistent with the hypothesis stated above.

# 5.7 _Other robustness checks_

The following additional robustness checks were performed (i) The _WBL_ variable was replaced with all its sub-components (41 dummy variables); (ii) share in employment and in sales (from ES data) of the various sectors was controlled for (listed in Table 1) in a given country under the assumption that there may be spurious correlation when a development strategy provides a big push to sectors that utilize women labor more intensively; (iii) cultural differences across countries was accounted for using the percentage of population that is Catholic, Muslim, Protestant and the rest; (iv) legal origin of countries (English, French and Socialist legal origin) was controlled for; (v) net official development assistance and official aid received as a percentage of GDP (average values over 2005-2006, World Bank) was controlled for; (vi) a 23
2000 (and 88.8% of the stock in 1990). For the remaining 7.3 percent (11.2 percent in 1990), we usually have information on the country of origin but have to extrapolate the skill structure on the basis of available information. In the spirit of the Carrington and Detragiache or Adams studies, a method based on the US census requires extrapolating the skill structure on the basis of 42 percent of the total OECD stock (36 percent in 1990). Our paper is a strong improvement on earlier e¤orts.

Our method allows to distinguish about 190 sending countries in 2000 and 170 countries in 1990 (before the secession of the Soviet block, ex-Yugoslavia and exCzechoslovakia). Our measures can be used to examine the changes in the international distribution of migration rates, to test for the (push and pull) determinants per skill group, or to evaluate the macroeconomic consequences of migration on source and destination countries.

The remainder of this paper is organized as follows. Section 2 describes the methodology. Emigration rates for 1990 and 2000 are presented in Section 3. Section 4 presents the key indicators of skilled migration. Finally, Section 6 concludes.

# 2 Methodology

This section describes the methodology and the data sources used to compute emigration rates of skilled workers for a large set of sending countries. Building on Carrington and Detragiache, we de...ne the brain drain as the proportion of working age individuals (aged 25 and over) with at least tertiary educational attainment, born in a given country but living in another country, taking into account neither their occupation, nor where education took place, nor when they arrived. To build such indicators, we proceed in two steps. We ...rst compute emigration stocks by educational attainment from all countries of the world. Then, we evaluate these numbers as a proportion of the labor force born in the sending country. This gives emigration rates per educational attainment.

These two steps rely on various assumptions. We distinguish the general assumptions required when all existing data are collected and the speci...c assumptions inherent to this particular release of the database (some information is estimated on the basis of survey data). These speci...c assumptions will be progressively relaxed as new o¢cial statistics become available.

## 2.1 Step 1 - Emigration stocks

International emigration data are usually not available or of bad quality. Hence, brain drain can only be captured by aggregating consistent immigration data collected in receiving countries. Information about the origin and skill of natives and immigrants is available from national population Censuses. More speci...cally, country i’s Census usually identi...es individuals on the basis of age, country of birth j, and skill level s.

6
Quad (Canada, EU, Japan and US) countries which account for the bulk of developing country exports to developed country markets. These analyses were supplemented by informnation gathered from TPRs of major developed countries as they relate to market access conditions for developing countries.

# A. Tariffs

# 1. Overall Averages

The results of the 'URA on the MFN tariffs of the developed countries have been studied extensively in previous studies whose main findings will be summarized here (Martin &Winters, 1996; UNCTAD/WTO, 1997;OECD, 1997). Broadly speaking, tariffs on imports of manufactures into the major industrial countries markets were reduced by an average of 40 per cent from a trade weighed average of 6.3 per cent to 3.8 per cent with the reductions to be phased in over five years and the first instalnent to be put in place on January 1, 1995.19 Countries have reduced their tariff rates accordingly since then. Moreover, in 1997, following the Information Technology agreement, duties on a number of products in this sector were reduced to zero on an MFN basis (See Finger and Schuknecht, 1999).

The tariffication of various measures of support and protection in the agricultural sector has resulted in substantial increases in the initial tariff levels applicable to a wide range of agricultural products in some major markets. Thus, the average applied MFN rate for agricultural commodities (production weighted) in 1996 ranged from 7.9 per cent in the U.S, and 10.7 per cent in the EU, to 0.5 per cent in Australia (OECD, 1997, Table 3.1). Subsequently, developed countries are to reduce agricultural tariffs by 36 per cent across the board, at the same time as access for agricultural products is being enhanced through reductions in domestic support measures.

> 'sSee Article 15 of the.UR Agreement on the Procedures for Implementation of GATT Article VI.

> '<sup>9</sup> The EU advanced from January 1, 1997 to January 1, 1996 its schedule of implementation of the third stage of tariff reductions for most non-agricultural products as part of its compensation for the EU enlargement through the accession of Austria, Finland and Sweden (WTO,TPR. European Union, 1997, p.<sup>1</sup> 5).

45
and the within-family individual-level variation in factors that produce better outcomes both in Grade 6 and later grades (e.g. intelligence, motivation, and health).

Furthermore, we find evidence that strongly supports the case that ENLACE captures the subject-specific skills that the test is designed to measure. To do so, we adapt our main specification and run a regression of ENLACE test scores in a particular subject area at Grades 9 and 12 on the score for the same subject area in Grade 6 controlling for the individual’s Grade 6 score in the other subject area, plus a vector of twin fixed effects. The intuition behind this econometric model is that we can control for factors that have a common effect on math and language test scores by including in the equation scores on the other subject area. We find that Grade 6 test scores in mathematics (or Spanish) have a strong relationship to test scores in the same subject in Grades 9 and 12, conditional on grade 6 test scores in the other subject. An increase of 1 SD in math (or Spanish) test scores in Grade 6 is associated with increases of 0.26 (0.31) and 0.33 (0.32) SD in test scores in Grades 9 and 12. All results are statistically significant at the one percent level.

In addition, our results show that Grade 12 test scores are a good predictor of college enrollment and, conditional on being employed, hourly wages. A 1 SD increase in grade 12 test scores is correlated with a 10 percentage points increase in the likelihood of being enrolled in university. Conditional on being employed, individuals with 1 SD higher test scores in Grade 12 enjoy wages that are 6 percent higher one or two years after graduating, even after controlling for upper secondary school GPA and other socio-economic variables. Also, we observe that students enrolled in majors that require higher math (Spanish) skills, e.g. engineering (Social Sciences), have higher test scores in this subject.

Evidence from high-income countries shows that achievement levels in test scores are good predictors of future education and labor market trajectories. For instance, using longitudinal data from the United States, Rose (2006) and Jencks and Phillips (2011) show that high school test scores are positively correlated with earnings both for seven and 10 years in the future. Rivera-Batiz (1992) finds a correlation between math test scores and the likelihood of securing a full-time job. A positive correlation between test 4
**Table 7. Robustness test: Trade openness**

|[1]<br>High|[2]<br>trade open|[3]<br>ness|[4]<br>Lo|[5]<br>w trade ope|[6]<br>nness|
|---|---|---|---|---|---|
|2nd stage: Output i<br>|nformality<br>|||||
|Real GDP per capita (in logs)<br>-0.70<br>|-0.58<br>|-0.17<br>|-8.86***<br>|-8.83***<br>|-9.16***<br>|
|(1.51)<br>|(1.51)|(1.85)|(2.91)|(2.89)<br>|(3.43)<br>|
|Control of Corruption<br>0.34<br>|0.34<br>|0.34<br>|-0.77<br>|-0.76<br>|-0.83<br>|
|(0.49)|(0.50)|(0.55)|(0.86)|(0.85)|(0.92)|
|Regulatory Quality<br>0.86*<br>|0.87*<br>|0.88*<br>|-1.12<br>|-1.12<br>|-1.14<br>|
|(0.49)<br> <br>|(0.50)<br>|(0.53)<br>|(0.96)<br>|(0.96)<br>|(0.94)<br>|
|Rule of Law<br>-0.68<br>(0.65)<br>|-0.67<br>(0.66)|-0.65<br>(0.69)|1.55*<br>(0.84)|1.55*<br>(0.84)|1.61*<br>(0.89)|
|Commercial bank branches<br>-0.18***<br>(0.06)|-0.19***<br>(0.05)|-0.23***<br>(0.08)|-0.04<br>(0.10)|-0.04<br>(0.09)|-0.02<br>(0.15)|
|1st stage: Bankingsecto<br> <br>|r developm|ent||||
|Commercial bank branches in the region<br>0.93***<br>(0.21)|||0.64**<br>(0.29)|||
|Distance-discounted commercial bank branches (regional)|0.54**<br>(0.22)|||0.51***<br>(0.18)||
|Distance-discounted commercial bank branches (global)||3.21***<br>(0.86)|||1.76<br>(1.11)|
|Observations<br>1,122|1,122|1,122|1,033|1,033|1,035|
|R-squared<br>0.99|0.99|0.99|0.99|0.99|0.99|
|Kleibergen-Paap rk LM statistic<br>16.63***<br> <br>|18.66***<br>|13.86***<br>|4.61**|4.47***|2.78*|
|Cragg-Donald Wald F statistic<br>18.83|23.62|13.78|4.7|5.11|2.52|

Notes: Standard errors clustered at the country level in parentheses, *** p<0.01, ** p<0.05, * p<0.1. Here common controls and constant terms are omitted for brevity. All regressions include both country fixed effects and year fixed effects. The dependent variable at the second stage is DGE-based output informality (in percent of GDP). “High (low) trade openness” are countries where trade flow (i.e., imports plus exports) as a share of GDP is above (below) median. Commercial bank branches are per 100,000 adults. GDP per capita is in constant 2010 U.S. dollars. See sections 2 and 3 for detailed data descriptions and empirical methods. Data are between 2004 and 2018.

24
**Figure 2** . **Microfinance Products offered in MENA**

<!-- Start of picture text --> Region Total<br>Egypt<br>Morocco<br>Lebanon Microenterprise<br>Jordan Islamic finance<br>Iraq Consumer<br>Palestine Housing<br>Mortgage<br>Syria<br>Tunisia<br>Yemen<br>0% 20% 40% 60% 80% 100%<br><!-- End of picture text --> Source: (Sanabel 2010) However, there are some signs that this limited selection may increase: in Egypt, Bank Misr plans to introduce Islamic microfinance activities to its 33 Islamic branches, and also develop a _mudaraba_ (profit sharing agreement) product in addition to the _murabaha_ product; in Yemen, Tadhamon Islamic Bank opened an MSE division in late 2006; and in the UAE, Noor Islamic Bank and Emirates Post Holding Group announced plans to establish a company to offer Shariah-compliant financial services to low-income clients.<sup>13</sup> Table 1 provides a survey of different implementations of _Shariah_ -compliant microfinance institutions in Syria, Bangladesh, Iran, and Indonesia. Although the Islamic microfinance projects follow similar concepts of conventional microfinance, including group saving and monitoring, targeting female borrowers, etc., two characteristics distinguished them from conventional ones. First, _Shariah_ compliant microfinance institutions actively adopted various Islamic financial tools, such as trade and project finance, _Murabahah,_ as well as non-financing instruments such as _Waqf and Qard al-Hassan_ , in the process of absorbing savings and making loans. Some of these institutions also gained funding support from _Zakah_ collection. Second, since interest income is prohibited, most institutions charged administrative/service fees plus a portion of the profit from the business venture. Looking back, the innovative combination of traditional and Islamic finance has been successful in most cases under study, as suggested by the relatively high recovery rate and fast expansion of their scale in recent years. Despite success in implementing _Shariah_ -compliant micro-finance, the practice has not spread as widely as one would have hoped. We discuss some of the challenges in the next sections of the paper.

> 13 (Pearce 2010)

13