rafmacalaba/datause-encoder-data huggingface dataset:
# **1. INTRODUCTION**

1. One of the earliest studies to systematically document changes in distributional outcomes in countries of Eastern Europe and Central Asia during their transition from planned to market economies was carried out by the World Bank in 2000.<sup>1</sup> This study found that although income disparities between the rich and the poor increased in virtually all transition economies during the 1990s, the extent of increase varied considerably across countries: for example, among Central European transition countries, the increase in inequality was considerably lower than that observed in the Commonwealth of Independent States (CIS). In explaining the main causes for the observed increase in income inequality, the study highlighted the role of increased inequality of labor earnings, which in turn could be traced to a rapid rise in returns to education. Government tax and transfer policies were found to have a powerful impact on the distribution of disposable incomes: for example taxes and transfers dampened the rises in income inequality due to increased dispersion of earnings in Central European countries to a considerably greater extent than in the CIS.

2. This paper focuses on selected Central European and Baltic countries—in particular, Poland, Hungary, Slovenia, Slovakia, the Czech Republic, Latvia, Lithuania, and Estonia (henceforth referred to as the EU8). Citizens of EU8 countries, it appears, have a high aversion to income inequality. Most respondents interviewed in these countries in the EBRD-World Bank Life in Transition Survey either “strongly agreed” (36 percent) or “agreed” (38 percent) with the statement “the gap between the rich and the poor in this country should be reduced”.<sup>2</sup> Likewise, there seems to be very strong public support for direct state involvement in tackling inequality: an overwhelming majority of respondents thought the government should either be “strongly involved” (51 percent) or “moderately involved” (40 percent) in reducing the gap between the rich and the poor (Chart 1).

**Chart 1. Strong Public Support for Reduced Income Inequality**

<!-- Start of picture text --> Strongly<br>Disagree<br>Not<br>Disagree<br>involved<br>Strongly<br>Agree Neither<br>Strongly<br>Moderately involved<br>involved<br>Agree<br>Responses to the statement “The gap between the rich Desired extent of state involvement in reducing<br>and the poor in this country should be reduced” income gap between rich and poor<br>Source: 2006 EBRD-World Bank Life in Transition Survey data for EU EU8 countries.<br><!-- End of picture text --> 3. Given these strong political preferences, one would expect public policy in these countries to play an important role in reducing income inequalities, both through the national taxation as well as

> 1 _Making Transition Work for Everyone: Poverty and Inequality in Europe and Central Asia_ , World Bank, Washington DC (2000). 2 For more details about this survey, see Annex 1.
confounds the interpretation of the estimate. This requires data that matches speci fi c students and teachers, a requirement that is hard to ful fi ll in most countries; Ehrenberg and others (1991) for instance use district level data, which could partially explain the lack of a relationship between teacher absence and student learning in their study.

# 3 Theory

The model is based on Das and others (2004a). It is extended here to explicitly focus on the implications of uncertainty in teacher inputs on household decisions about educational inputs and cognitive achievement, as measured by test scores. The model assumes a household (with a single child attending school) that derives (instantaneous) utility from the cognitive achievement of the child TS and the consumption of other goods X. The household maximizes an intertemporal utility function U(.), additive over time and states of the world with discount rate β(< 1) subject to an intertemporal budget constraint (IBC) relating assets in the current period to assets in the previous period, current expenditure and current income. Finally, cognitive achievement is determined by a production function relating current achievement (TSt) to past achievement (TSt−1), household educational inputs (zt), teacher inputs (mt), non-time varying child characteristics (μ) and non time-varying teacher and school characteristics (η). We impose the following structure on preferences and the production function for cognitive achievement:

[A1] Household utility is additively separable, increasing, and concave in cognitive achievement and other goods.

[A2] The production function for cognitive achievement is given by TSt = F (TSt−1, mt, zt, μ, η) where F (.) is concave in its arguments.

Under [A1] and [A2] the household problem is Here u and v are concave in each of its arguments. The intertemporal budget constraint (2) links asset levels At+1 at t +1 with initial assets At, private spending on educational inputs zt, income yt and the consumption of other goods Xt. The price of educational inputs is the numeraire, the price 6
ii

# 111) The main conclusions of the paper are as follows:

- a. World cocoa prices have been falling; and given the large stocks of cocoa In the world and the expected Increase In world output, the price will continue to fall Into 1990, declIning 25 percent below the 1987 levol. rollowing the 25-year cocoa cycle, the price will recover to the 1987 level by 1995 and reach a cyclical high somewhat after the year 2000 expected to be two to three times the 1987 level.

- _b._ There Is evidence from the Agricultural Economics Survey for Cocoa Producer Pricing that Improved Incentives have Induced new plantings of cocoa. Thirty-three percent of the land under cocoa by farmers interviewed was planted In the past four years.

C. It Is recommended that the government sustain a policy of providing adeq4uate price Incentives to cocoa producers. To be realistic and because of fluctuations In the world price, cocoa buying prices should be based on real costs and not Just on an artificially-set proportion of the f.o.b. price. In the context of growing population and Income, a price of 120 cedis (in 1987 prices) Is not adequate to sustain cocoa production over the long term; If a food grain selfsufficiency policy Is adopted, neither Is a price of 140 cedis. Except for this case, a price of 140 cedis will sustain but not Increase cocoa production over the longer term. Over the medium term (say ten years), somewhat larger volumes of cocoa production can be produced at these prices. Note that a price of 120 (1987) cedis Is equivalent to a price of 165 cedis In 1988 prices. d. In order that the government can continue to provide the required price Incentives In the cocoa subsector, the exchange rate regime should be liberalized so that at any polnt In time the prevailing rate Is approximately equal to Its equilibrium level. This Is only one of the ma,iy benefits from a llberalized exchange rate regime.

e. In addition to foreign exchange earnings, a low cocoa tax, high cocoa production policy impacts very positively on the Incomes of the rural poor, and this policy Is preferred on Income distributional grounds. In contrast, taxing cocoa farmers directly lowers the Income of cocoa farmers, Indirectly lowers the Income of food producers and transfers Incomes from these farmers to food consumers. Since cocoa farmers are poorer than consumers of taxed goods, and nontraded foods producers are much poorer than food consumers In jeneral, such taxation worsens the Income distributlon.
Finally, we offer new light on two puzzles arising from experiments evaluating the effect of education subsidies in developing countries. The first of these puzzles is that most studies evaluating the effect of CCTs (to parents) on test scores estimate positive effects on enrollment and/or attendance but find no evidence of gains in test scores (with the notable exceptions of Barham, Macours and Maluccio, 2016 and Baird et al., 2011). While this lack of evidence of cognitive skills gains can be rationalized in part by sample selection issues – in studies using school-based tests, children induced to attend by the CCT may have lower skill levels– and/or school quality being negatively affected by increased school participation, we replicate this finding using data from a sample of eligible children who are not selected based on school attendance and largely ruling out the worsening school quality mechanism. Indeed, we find that our other two interventions have effects on attendance of the same order of magnitude as the CCT, but have positive effects on test scores an order of magnitude larger than the CCT. This finding points to the conclusion that introducing parental incentives on attendance produces specific negative spillovers on learning. The second well-known puzzle arising from previous research on which we shed new light is that simply distributing free school uniforms has had large effects on attendance, enrollment, and pregnancy outcomes in Kenya (Duflo et al., 2015 and Evans and Ngatia, 2017), which, as noted by Kremer and Holla (2009), is difficult to reconcile with simple models of human capital investment where decisions are solely made by parents.<sup>6,7</sup> 6 In urban Ecuador, Hidalgo et al. (2013) find that a program of free school uniforms _decreases_ attendance, which they argue may be due to a combination of factors including the fact that only 63% of schools where children were told that they would receive free uniforms actually did.

7 Examples of ITT (LATE) effects reported in these studies are: 3.8 (7.0) %- points or 20 (37)% decrease in absenteeism in Evans and Ngatia (2017), and 8
# **Introduction**

Many policy makers want to encourage entrepreneurship in their local economies given its central role in economic growth and development. Entrepreneurship helps allocate resources efficiently, strengthens competition among firms, supports innovation and new product designs, and promotes trade growth through product variety. Perhaps most important for policy makers, high rates of local entrepreneurship are linked to stronger subsequent job growth for regions. Ghani et al. (2011) show this pattern for the manufacturing sector in India since 1990: Even after controlling for overall state and industry dynamics, places in India that had higher rates of entry at the start of the 1990s experienced stronger local job growth in the formal sector over the next two decades. Similar results are evident in the United States (e.g., Glaeser and Kerr 2011), and Fritsch (2008) reviews localized growth impacts across several countries and time periods.

This importance of entrepreneurship leads to a natural, policy-relevant question: Which regional traits encourage local entrepreneurship in South Asia? Multiple studies have considered this question in advanced economies, especially for the manufacturing sector, but there is very little empirical evidence for developing countries like India. This lack of research hampers the effectiveness of policy efforts to promote job growth through entrepreneurship. The roles that education or infrastructure, for example, have for entry in an advanced economy like the United States may be quite different from a setting like India where illiteracy and lack of roads and sanitation continue to hamper development. Likewise, we have extensive evidence on the importance of agglomeration economies in advanced countries, but the relevance of these patterns in developing economies has not been consistently established. Audretsch et al. (2012) emphasize the very localized nature of entrepreneurship determinants.

We investigate these questions for manufacturing and services in India at the district level. Within these two industry groups, we also compare the formal and informal sectors. We quantify the factors and traits of districts and industries that systematically predict stronger entry levels in recent years. Much of the work on spatial determinants of entrepreneurship for advanced economies focuses on manufacturing, and so it is natural to begin there and compare the patterns for India with those in the United States. Our goal is to determine the general degree to which the economic geography of India can be explained with a parsimonious set of specifications, and to compare the specific factors identified to be important in the two contexts. This work most closely relates to Glaeser and Kerr (2009), Mukim (2011), and Jofre-Monseny et al. (2011).<sup>1</sup>

> 1 Other closely related studies include Chinitz (1961), Acs and Armington (2006), Drucker and Feser (2007), Rosenthal and Strange (2010), and Delgado et al. (2010a,b). Mukim and Nunnenkamp (2011) consider location decisions of foreign firms in India.

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# **Impact of Property Rights Reform to Support China’s Rural-Urban Integration: Village-Level Evidence from the Chengdu National Experiment**

# **1. Introduction**

While the rapid economic growth observed in China over the last decade is the result of many factors, a land tenure system that strictly separates rural from urban land and that allows expropriation of rural land and its conversion to urban land in a way that provides large margins to local governments has significantly contributed to the associated expansion of industrial activity. At the same time, this dualism between rural and urban land and the ability of local governments to generate enormous amounts of revenue by expropriating land cheaply and selling it to developers at prices that are orders of magnitude higher than what is being paid in compensation has also contributed to income inequality. Moreover, it led to inefficient land use, large ‘land banks’ by local governments, rural unrest, and -given China’s limited agricultural land endowment- concerns about negative impacts on food security. The latter may arise either directly -by irreversibly converting land from agricultural to non-agricultural uses- or indirectly by reducing investment and efficiency-enhancing land transfers by farmers who fear expropriation with limited compensation. Most experts agree that this situation is not sustainable and that, to change it, simultaneous action in a number of areas is needed (World Bank and DRC, 2014).

Cognizant of this challenge, a number of national experiments were conducted to explore the scope for alternative and potentially more sustainable arrangements. In this context, the city of Chengdu in Sichuan Province was selected by the central government as a “rural-urban integration reform experiment zone” in 2008. Efforts undertaken in the context of the experiment are of interest as they involved systematic verification of all types of land assets, relaxation of the restrictions imposed by the _hukou_ system of urban residency permits, and measures to improve land market functioning. They were expected to enhance tenure security and reduce transaction costs in land and labor markets so as to encourage land-related investment, enhance allocative efficiency, create jobs, and improve overall economic performance. But there was also concern that far-reaching reforms in this area would be costly to implement and give rise to disputes or socially undesirable land transfers and migration.

As property rights and their links to rural-urban integration have recently been identified as key reform areas by China’s leadership, drawing the lessons from past reform experiments is important. Yet, beyond anecdotal accounts, few studies aim to assess either the magnitude of associated impacts or their incidence among different types of households. We use a survey of 529 neighboring villages that are separated from each other by the prefecture boundary to analyze reform effects on tenure security, land use, and land as 2
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The difference between World Bank and other statistics seems to result chiefly from the fact that adjustments are effected at the World Bank. Some of these adjustments are intended to correct for the fact that the method of preparing the accounts does not always conform to the United Nations standard system or for inconsistencies in the accounts. Other, more delicate, adjustments take account of country economists' opinions concerning the reliability of the official data. Subject to the quality of these adjustments and uniformity of the principles underlying them, it seems preferable to work with the World Bank statistics. The advantage of the other series is that they are available more rapidly and more regularly.

As the illustrative model shows (cf. table 3, equations 3 and 4), the coefficient of determination is in fact a little better using the World Bank data.

The use, still rare, of the statistics of the international comparison project, perfectly justified for comparing standard of living leveis and trends, is much less justified for measuring economic efficiency through growth of product. This efficiency cannot be judged in each country without taking into account the structure of costs and scarcities, which is reflected in the country's price system.

# 1.1.3 The choice of the base year

The growth rates are calculated on CDP series measured at constant prices. The base year in which these series were originally established naturally varies from country te country. The series of aggregates published by the international agencies, including the World Bank, have used a base year varying with the country, which nevertheless, as we have seen, ensured a certain harmonization of the statistics. The next edition of the World Tables will present aggregates on a uniform base year for all countries, the year 1980. These data could not be used up till now and all the cross-sectional analyses of growth studied here use series established on base years varying from country to country. This practice raises a problem that has been ignored by all of the studies examined.

For example, ths price system that can be used to aggregate the various branches of activity differs greatly, depending on whether we are dealing with the pre- or post-oil shock period. In an oil-producing country, the weight given to growth of the mining sector differs widely according to whether the base is prior to or subsequent to the oil shock. If the growth of the mining sector differs from that of the rest of the economy, this results in a difference of evaluation of overall growth, depending on the base adopted. 1/ The problem arises when a country's growth is relatively highly conce-trated in a sector whose production is subject to wide variations in relative prices and grows at a different rate from the rest of the economy. This was true of the mineral producing countries, particularly those that were new producers or, on the contrary, declining producers during the period.
Table 3 Monte Carlo Simulation: N=1000, Varying coefficient structure

||||Typ|e1|||Typ|e2||
|---|---|---|---|---|---|---|---|---|---|
|||||MAE|StErr|||MAE|StErr|
|y=xβ(|t)|TRUE|Bias|Ratio|Ratio|TRUE|Bias|Ratio|Ratio|
||x1|-1.140|0.000|-0.030|0.103|-0.092|0.011|0.033|0.154|
|<br>CQR-Q10|x2|-0.035|0.010|-0.038|0.120|-0.086|0.010|0.016|0.156|
||cons|0.356|-0.010|-0.046|0.182|-0.086|-0.043|0.178|0.170|
||x1|0.404|-0.002|-0.052|0.067|0.845|-0.009|-0.021|0.056|
|CQR-Q50|x2|0.601|-0.001|-0.050|0.065|0.841|-0.004|-0.016|0.045|
||cons|0.998|0.003|-0.031|0.085|0.853|0.029|0.011|0.059|
||x1|1.938|0.001|-0.048|0.098|2.282|-0.001|-0.045|0.045|
|CQR-Q90|x2|1.236|-0.005|-0.038|0.098|2.280|-0.010|-0.067|0.054|
||cons|1.644|0.004|-0.046|0.139|2.309|-0.002|-0.066|0.073|
||x1|-1.211|0.002|-0.046|0.170|-0.097|0.018|-0.027|0.174|
|UQR-Q10|x2|-0.044|0.002|-0.023|0.072|-0.078|0.012|-0.031|0.157|
||cons|0.482|-0.004|-0.025|0.066|-0.074|-0.056|0.078|0.162|
||x1|0.418|-0.003|-0.059|0.119|0.900|-0.008|-0.023|0.031|
|UQR-Q50|x2|0.535|-0.003|-0.071|0.112|0.737|-0.005|-0.015|0.026|
||cons|0.899|0.007|-0.061|0.124|0.757|0.017|-0.031|0.028|
||x1|1.982|0.001|-0.079|0.150|2.214|-0.002|-0.039|0.051|
|UQR-Q90|x2|1.296|0.002|-0.060|0.136|2.321|0.001|-0.022|0.077|
||cons|1.778|-0.003|-0.093|0.141|2.499|-0.006|-0.031|0.057|

# **4. Wage inequality in Grenada**

This illustration focuses on an empirical application of our proposed method for the case of Grenada, focusing on the description of wage inequality trends in the country between 2013 and 2020 using the annual Labor Force Survey (LFS). This survey provides the only source of information that can be used to describe the status of the labor market and the distribution of labor income in the country.

One major limitation of this survey, however, is the collection of labor income data. Compared to standard household surveys or labor force surveys in most developed countries, labor income recorded in the LFS in Grenada is only available in brackets. Furthermore, there is a large proportion of the employed population who do not declare their labor income. Table 4 provides an overview of the labor income distribution across time.
Table A7: IV estimates

|Dependent variable:|Loan availability<br>(1)|Loan application<br>(2)|
|---|---|---|
|Constrained by informal|-0.590**<br>[0.273]|-0.614**<br>[0.307]|
|Account|0.0431<br>[0.0281]|0.0390<br>[0.0308]|
|No need|-0.108***<br>[0.0392]|-0.109**<br>[0.0440]|
|Age|0.0244|0.0282|
||[0.0181]|[0.0203]|
|Size|0.0174|0.0153|
||[0.0119]|[0.0133]|
|Export|0.00551|0.00503|
||[0.0274]|[0.0302]|
|Model|2SLS|2SLS|
|Time FE|yes|yes|
|Geographic area FE|yes|yes|
|Additional controls|yes|yes|
|Observations|1951|2011|
|Underidentifcation (p-value)|0.000|0.000|

_Notes:_ 2SLS estimates. In this table, we instrument _Constrained by informal_ with the average of firms’ belonging stratum defined at the intersection of macro-sector (manufacturing vs services), geographical area, in the previous wave of the firm. All regressors are timed consistently with previous analyses. Unreported controls follow the specification in Table 4. Measures are defined in Table B4. Robust standard errors in brackets. *, **, *** indicate statistical significance at the 10%, 5%, and 1%, respectively.

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