rafmacalaba/datause-encoder-data huggingface dataset:
The first part of this paper re-examines CONALEP's performance compared to a welldesigned control group. Contrary to previous evaluations, this paper shows that CONALEP graduates search longer for a job but that job congruency is higher compared to the control group. In agreement with previous evaluations, this paper shows that CONALEP increases graduates' earnings. However, the order of magnitude of earnings increase differs greatly from previous studies. This paper finds that on average, CONALEP increases graduates earnings by 22 percent -not the 30 or 40 percent found in other studies- compared to a control group.

The second part of this paper evaluates the benefits of the 1991-1992 CONALEP reforms. Results indicate that graduates from the pre-reformed program (94 Survey) search longer for a job compared to those of the post-reformed program (98 Survey). Moreover, graduates from the post-reformed program have 45 percent more probability of finding a job than those from the pre-reformed program. Furthermore, the 94 Survey cohorts earned higher hourly earnings than the 98 Survey cohorts. A plausible explanation is that since 1994, real wages have decreased in Mexico by almost 40 percent.

The third part of this paper examines CONALEP's cost-effectiveness. The results indicate that CONALEP is a highly cost-effective program. In addition, as mentioned by other authors, CONALEP has had spillover effects on the rest of the technical education system by stimulating other educational institutions to be more efficient and to adapt to a changing economic and social situation (Carnoy and others 2000).

It is difficult to discern the relative contribution of the different factors responsible for the good overall performance of CONALEP, but it is safe to conclude that the special features of CONALEP as a whole have made it possible. These are as follows: autonomous national 46
FIGURE 3

# KENYA: FINANCIAL TAXES

<!-- Start of picture text --> Meicur, I<br>a2<br>3<br>26<br>24<br>2.2<br>cL 2<br>1.8<br>1.6<br>1.4<br>1.2<br>I<br>Q4-<br>Q2-<br>0-<br>111 Ga 1G98 1984 1GMS 1986 Gr IG<br>CLrr CE9RRAco E NOB3<br><!-- End of picture text --> 43
most influential in weakening economists’ attachment to unitary models.

Like other household allocation outcomes (Thomas 1990, 1994), intergenerational transfers may reflect individualistic preferences of husband and wife in decision-making, and thus the differential bargaining power of parents may influence the allocation of land and education to children. Stronger inheritance rights to women, after the reform, are likely to improve her outside options thereby generating greater bargaining power within marriage that increases her influence over intrahousehold allocation of resources. If husband and wife have different preferences ( _δ_ ) over daughters (and sons), and if mothers’ value daughters education more than the father, then after the reform, one might observe a relative increase in the educational attainment of the daughters.

# **4 Data and Estimation Strategy**

## **4.1 Data and Hypotheses**

We use data from the 2006 round of the nationally representative Rural Economic and Demographic Survey (REDS) conducted by the Indian National Council for Applied Economic Research. In addition to information included in standard multi-purpose household surveys, the REDS contains data on the household head’s parents (generation I), heads siblings (generation II), as well as head’s children (generation III), providing us with a quantitative measure for inter-generational transfers of key assets. We focus on Maharashtra and Karnataka and, as our strategy relies on within household variation, drop the few non-Hindus (3 percent of the sample) in these two states to obtain a sample of 1,371 households with 10,565 individuals in three generations for the analysis. While our main results use data from these two states, we present additional robustness checks using data from five north Indian states that did not amend the Act in 1994.<sup>21</sup> For all males and females in generation II we observe information on basic individual attributes (e.g., age, education, number of children, year of marriage), spousal characterclothing in households with children.

> 21 We use a sample of 2810 rural Hindu households from Uttar Pradesh, Rajasthan, Bihar, Madhya Pradesh, Orissa, primarily to perform additional specification checks. The North Indian states did not amend the Hindu Succession Act until the national amendment in 2005.

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relatively high for its per capita income levels; both had approximated<sup>20 percent of</sup> GDP during the 1970s. The incremental capital output ratio, while having risen<sup>from</sup> 3 in the 1960s to 4 between 1972 and 1977, was not unreasonable,<sup>particularly given</sup> the oil price shcwk in the early 1970s. The tax revenue ratio<sup>had increased from about</sup> 12 percent in 1966-67 to 21 percent in 1979-80, and the current<sup>fiscal account had</sup> produced a surplus of 2.5 to 4 percent of GDP annually for the investment<sup>program.</sup> Public and private investment in human capital formation yielded<sup>educational and</sup> health indicators well above the X crage for Sub-Saharan Africa.<sup>Pnmary school</sup> enrollment was not far from being universal. A life expectancy of 55 years and<sup>an</sup> infant mortalUty rate of 83 per 1,000 live births were in 1980 significantly<sup>more</sup> favorable than the average for Sub-Saharan Africa.

The structure of production also changed significantly after<sup>Independence. The</sup> government had distributed to smaller farmers' a considerable amount<sup>of</sup> high-potential and medium-potentia **l** and that had belonged<sup>to large farmers, and had</sup> encouraged smail farmers to cultivate tea, coffee, and hybrid<sup>maize, and to take up</sup> dairy farming. The smallholders' share of coffee and tea production<sup>had increased</sup> from practically nothing in 1955 to 40 and 70 percent respectively<sup>in the early 1980s.</sup> Between 1965 and 1979, the small-scale farm area under<sup>improved varieties of maize</sup> increased about forty fold. The impetus for smallholder activities<sup>helped rural income</sup> grow by 5.2 percent annually from 1974 to 1982, much of it<sup>in nonfarm activities.</sup> Growth of income was probably just as strong in the earlier years.<sup>Collier and Lall</sup> (1984) estimated that, in the Central Province, rural income per<sup>adult equivalent</sup> increased at 3.8% p.a. during 1963-74 and Crawford and Thorbeck<sup>(1984) estimated</sup> 7
Table 1: Descriptive relationship between self-employment and migration, all survey waves

||**Any**<br>**migration**|**Internal**<br>**migration**|**International**<br>**migration**|**Any**<br>**migration**|**Internal**<br>**migration**|**International**<br>**migration**|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Self-employed|-0.025***|-0.023***|-0.002*|-0.026***|-0.024***|-0.001*|
||(0.003)|(0.003)|(0.001)|(0.003)|(0.003)|(0.001)|
|Aged 25 to 34|-0.071***|-0.068***|-0.004***|-0.071***|-0.068***|-0.004***|
||(0.005)|(0.005)|(0.001)|(0.005)|(0.005)|(0.001)|
|Aged 35 to 44|-0.114***|-0.105***|-0.007***|-0.113***|-0.106***|-0.007***|
||(0.005)|(0.004)|(0.001)|(0.005)|(0.004)|(0.001)|
|Aged 45 to 54|-0.119***|-0.111***|-0.008***|-0.119***|-0.111***|-0.007***|
||(0.005)|(0.005)|(0.001)|(0.005)|(0.005)|(0.001)|
|Aged 55 to 65|-0.125***|-0.118***|-0.007***|-0.124***|-0.118***|-0.006***|
||(0.005)|(0.005)|(0.002)|(0.005)|(0.005)|(0.002)|
|Years of education|0.004***|0.004***|0.000|0.004***|0.004***|0.000|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Female|0.003|0.005**|-0.002***|0.003|0.005**|-0.002***|
||(0.003)|(0.002)|(0.001)|(0.003)|(0.002)|(0.001)|
|arcsinh(income)||||-0.001**|-0.001|-0.000***|
|||||(0.000)|(0.000)|(0.000)|
|Wage worker mean|0.119|0.109|0.010|0.119|0.109|0.010|
|Sample size|87,741|87,713|75,601|87,493|87,465|75,353|

_Notes:_ The sample is the set of individuals aged 18-65 surveyed in the CFPS 2010 and 2016, ELMPS 1998, 2006 and 2012, IHDS 2005 and 2011/12, IFLS 2000, 2007/08 and 2014/15, MxFLS 2002, 2005/06 and 2009/12, LSMS-ISA 2010/11, 2012/13 and 2015/16, KHDS 1991/94, 2004 and 2010, and PSID 2001, 2007 and 2017. We drop respondents who are not self-employed or paid workers in the baseline wave of each survey. Refer to online appendix section B for more details on variable construction in the different surveys. Each column reports marginal effects from a probit regression of an indicator for migration on an indicator for self-employment at baseline. Each regression controls for country-wave fixed effects. Columns (4)-(6) additionally control for the inverse hyperbolic sine (arcsinh) of the respondent’s income in the baseline wave. Standard errors in parenthesis are clustered at the respondent level.

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economic growth of the economy. Since appreciation of the real exchange rate will hurt the international competitiveness of an economy, inequality has negative implications for sound macroeconomic management. However, the robustly negative relationship between real exchange rates and inequality does not imply that huge redistributive policies will automatically bring real depreciation of domestic currency, improve the external balance, and accelerate economic growth. Among other damaging effects, excessively expansionary redistributive policies motivated by inequality may cause domestic inflation and can distort incentives and hurt productivity which slow down long-term economic growth (Al-Marhubi, 2000).

Log of terms of trade, liquidity, real per capita GDP, and trade openness all have the expected signs and are significant in different specifications. Terms of trade improvement leads to an appreciation as is consistent with theory and other empirical studies [ Edwards and van Wijnbergen, 1987: Neary, 1988: Kahn and Ostry, 1991: Tokarick, 1995]. However, regional dummy variables for east Asia and Latin America are insignificant in most cases, and thus we could not find any regional impact on the cross-country behavior of inequality and real exchange rates. Also, the log of net foreign assets (CCA) measured as a cumulative current account with the bench mark figure of 1978 is insignificant throughout the different specification of the model.

Another question is whether different income level have different transmission mechanism from inequality to the real exchange rate. Since we do not have sufficient number of observations for two different categories, OECD dummy variable is included in the estimation to capture the possible role of income level to the transmission mechanism. Estimation results are reported in Table 7.

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In developing economies in Europe and Central Asia (ECA), the share of adults with an account at a financial institution increased from 45 percent in 2011 to 65 percent in 2017. Compared with the rest of the world, developing economies in ECA had relatively high levels of account ownership as of 2011 and experienced moderate growth over time.

Within ECA there is considerable variation across countries in the growth of account ownership (figure 1). In the euro area, 90 percent of adults already owned an account by 2011. The share increased marginally to 95 percent in 2017.

**Figure 1. Account ownership in Europe and Central Asia varies widely by subregion**

<!-- Start of picture text --> 2011 2014 2017<br>100%<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Central Central Eastern Northern Russian South Southern Turkey Western Western<br>Asia Europe & Europe Europe Federation Caucasus Europe Balkans Europe<br>the Baltics<br>share of adults with an account<br><!-- End of picture text --> _Source_ : Global Findex database. The bars represent the share of adults aged 15 and above who have an account at a financial institution or with a mobile money provider.

The pattern differs in the rest of the region. All three developing economies in Eastern Europe—Belarus, Moldova, and Ukraine—witnessed an increase in account ownership of more than 20 percentage points between 2011 and 2017 (table 1). The Baltic economies experienced an increase in account ownership from a high base level. In 2017 almost all adults in Estonia and Latvia had an account.

Financial inclusion levels are lower in Central Europe. A few Central European economies, such as Croatia and Czech Republic, had stagnant levels of account ownership in the past decade. In Romania, account ownership grew from 45 percent in 2011 but remained at around 60 percent since 2014. Countries in the Western Balkans experienced moderate growth in account ownership, from 55 percent in 2011 to 63 percent in 2017. In Central Asia and the South Caucasus, account ownership doubled from about 20 percent in 2011 to roughly 40 percent in 2017. Armenia, Georgia, the Kyrgyz Republic, and Tajikistan saw significant increases in account ownership of 15 to more than 20 percentage points between 2014 and 2017.

4
10 Apperaix Table A4 shows houiehold consumption and the share of goods and various services consumed by households as a percent of GNP; data sourceo are similar to thtose for Table Al.

# C. **Internacional** _Comparisons_ of Service Activity

How low were services in the Soviet Union? In this section, we present some estimates of how far Russia and other former Soviit states are below international activity norms for different services. Activity levels are measured by shares in value added, employment, and end use.

For value added and employment, the approach is to use regression analysis to comp~are the sectoral structure of Russia and other former Soviet states with countries at similar leve'.s of PPP-based per capita income. For countries other than the USSR, PPP-based per capita incomes are taken from the Summers and Heston data set (see Summers and Heston 1988). For Russia and the other Soviet republics, we use World Bank estimates of PPC-based per capita GDP for 1987.12 Yearly estimates are extrapolated on the basis of real growth rates for the USSR and periodic information on ratios of per capita income in each of the republics as compared to the lJnion. 13 Regression analysis is undertaken for total services and for service subsectors coinciding or falling within the conceptual categories distinguished above -- namely, infrastructure, business and nonsumer services, and public sezvices. Emphasis is given to the business and consumer services category, by investigating i.ts omajor components -- t.rade, financial services, and consumer services. Serviceo in this category are normally provided by the private sector 12 See the World Bank's World Development ReDort 1993, Table 30.

13 USSR real GDP growth rates are taken from Easterly and Fisher 1992, and republic/USSR ratios are obtained from IMF/IBRD/OECD/EBRD 1991.
A shift in favor of _boro_ cultivation has led to a significant increase in rice production due to the much higher yields of the _boro_ variety. As Table 1 clearly shows, _boro_ rice has nearly three times higher yields than _aus_ , and two times higher than _aman_ . Due to differences in environmental conditions, these yield differentials exhibit strong regional variation. Summary statistics from _thana_ -level panel indicate a significant increase in rice productivity between 1995-96 and 2000, with total annual production per acre rising by an average of 42 percent at the median (Appendix Table A1).<sup>3</sup> According to the Bangladesh Bureau of Statistics (BBS), total aggregate production of rice rose by 30 percent in the period from 1995-96 to 1999-2000 and by 42 percent between 1995-96 and 2000-2001, validating the observed increase from survey data (Dorosh 2004).

**<u>Table 1. Yields of</u>** **_<u>aus</u>_** **<u>,</u>** **_<u>aman</u>_** **<u>and</u>** **_<u>boro</u>_** **<u>rice in Bangladesh.</u>**

||Yie<br>_Aus_|lds (kg/ac<br>_Aman_|re)<br>_Boro_|Yield<br>_Boro_/_Aus_|ratios<br>_Boro_/_Aman_|
|---|---|---|---|---|---|
|Northwest|0.47|0.73|1.37|2.91|1.88|
|South Ganges Flood Plain|0.45|0.53|1.51|3.36|2.85|
|Coastal|0.43|0.50|1.29|3.00|2.58|
|North Central|0.40|0.63|1.24|3.10|1.97|
|Meghna Flood Plain|0.52|0.73|1.09|2.10|1.49|
|Eastern Hills|0.55|0.71|0.84|1.53|1.18|
|All Bangladesh|0.46|0.64|1.25|2.72|1.95|

Source: Calculated from Bangladesh Bureau of Statistics annual data, which are reported in World Bank (2002b).

Productivity improvement has had dramatic consequences for rice harvests. While average production volume was approximately 15 million tons during 1980-90 and 18.8 million tons during 1990-2000, it exceeded an average of 24.9 million tons during 20002003. The significantly higher level of rice production in the 2000 HIES than in the 199596 HIES is largely a result of policies that allowed a shift to high-yielding rice varieties and to irrigated _boro_ rice rather than solely being a consequence of weather differences between these two survey years (Dorosh 2004, Del Ninno and Dorosh 2003, World Bank 2002b).

> 3 While this increase seems realistic given the changes in crop intensity of _boro_ production and the yield differential between _boro_ and the other rice varieties, the mean increase of nearly 80 percent (not shown) is much less realistic. The mean is heavily influenced by the outliers in a community-level panel, and they have far greater weight in the panel data set with slightly over 200 communities than in a household panel of over 5,000 observations in each year.

11
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# **Table  13a:       Piecemeal Sensitivity Analysis: Impact on Kenya of EACU Deep Integration and  Multilateral Liberalization**

||**P**|**arameter Valu**|**e**|**Equiv**<br>**EACU D**|**alent Va**<br>**eep Inte**|**riation**<br>**gration**|**as a %**<br>**EACU**|**of Consu**<br>**Liberal**|**mption**<br>**ization**|
|---|---|---|---|---|---|---|---|---|---|
|Parameter|Lower|Central|Upper|Lower|Central|Upper|Lower|Central|Upper|
|σ(qi, qj) – services sectors|2|3|4|0.96|0.96|0.96|1.81|1.81|1.83|
|σ(qi, qj) – goods sectors||see below||0.78|0.96|1.16|1.90|1.81|1.87|
|σ(va, bs)|0.625|1.25|1.875|0.96|0.96|0.96|1.79|1.81|1.83|
|σ(D, M)||see below||0.95|0.96|0.97|1.80|1.81|1.83|
|σ(M, M)|GTAP values|30||1.06|0.96|NA|1.86|1.81|NA|
|σ(L, K)|0.5|1|1.5|0.96|0.96|0.96|1.82|1.81|1.81|
|σ(A1,...An)|0|0|0.25|NA|0.96|0.96|NA|1.81|1.81|
|εEACU,εCOMESA,εSADC|Lower (upper) v|alues are 0.5 (1.|5) central|0.94|0.96|0.99|1.67|1.81|1.90|
|εEU ,εROW,εUSA,εCHINA|values. See tabl|e 7 for central val|ues.|||||||
|θr|0|0|1|NA|0.96|0.91|NA|1.81|0.77|
|θm|0.025|0.05|0.075|0.96|0.96|0.96|1.81|1.81|1.81|
|**σ(qi, qj) – IRTS goods**|**P**|**arameter Valu**|**e**|**σ(D, M)-**|**-CRTS s**<br>|**ectors**<br>|**Par**|**ameter V**|**alue**|
|chemicals and metals|3.4|6.8|10.2||||Lower|Central|Upper|
|energy and minerals|5.8|11.6|17.4|agricultur|e and for|estry|1.3|2.5|3.8|
|food products|2.6|5.1|7.7|other serv|ices||0.8|1.5|2.3|
|petroleum and coal prod.|2.1|4.2|6.3|trade|||0.8|1.5|2.3|
|other manufacturing|3.9|7.7|11.6|utilities|||1.4|2.8|4.2|
|textiles, apparel and leather|3.8|7.6|11.4|||||||
|wood andpaperproducts|3.2|6.3|9.5|||||||

## **Key:**

σ(qi, qj): Elasticity of substitution between firm varieties in imperfectly competitive sectors σ(va, bs): Elasticity of substitution between value-added and business services σ(D, M): Elasticity of substitution between domestic goods and imports in CRTS sectors σ(M, M): Elasticity of substitution between imports from different regions in CRTS sectors σ(L, K): Elasticity of substitution between primary factors of production in value added σ(A1,...An): Elasticity of substitution in intermediate production between composite Armington aggregate goods εROW, εEU, εCHINA, εUSA εEACU, εCOMESA, εSADC: Vectors of elasticities of imperfectly competitive firms' supply in the Rest World, EU, China. USA, EACU, COMESA and SADC with respect to the price of their outputs.

θr: Share of rents in services sectors captured by domestic agents θm: Shares of value added in multinational firms due to specialized primary factor imports Source: Authors’ estimates.

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