rafmacalaba/datause-encoder-data huggingface dataset:
# **<u>Physical environment</u>**

Agricultural production depends on the physical environment or natural conditions. We represent the environment by using two variables: potential dry matter (PDM) and a factor of water availability (FWA).<sup>20</sup> The first variable is intended to measure the theoretical potential production of dry matter. The production of dry matter requires moisture. Arid areas may have a large value for PDM, but actual production is small due to water deficit. The relative water availability is measured by the ratio of actual transpiration to potential transpiration. These two variables are country specific and do not vary with time.

# **IV. Sample Description**

The sample was determined by the data availability and the preference for a balanced data panel in order to simplify the analysis. It consists of annual data from 30 countries<sup>21</sup> for a 29-year period (1972-2000). The information conveyed by the sample is summarized in Table 1. The first column presents the average annual growth rate of the variables over the sample period. Agricultural output grew at a rate of 5.43 percent, whereas agricultural capital grew at a higher rate of 5.77 percent. Agricultural labor declined at the average rate of 0.6 percent. Thus, the average labor productivity increased at the average rate of 6.03 percent, and the ratio of capital to labor increased at the average rate of 6.37 percent. The growth rate of capital of agricultural origin (4.94 percent) is lower than that of fixed capital (5.80 percent). Fertilizer grew on average at the rate of 1.87 percent, whereas the agricultural area grew at the rate of 0.01 percent, implying a growth in the fertilizer-land ratio. The growth of agricultural output took place in spite of unfavorable prices as indicated by the decline in the terms of trade of agriculture at the average rate of 1.26 percent. These results signal an increase in productivity. The technology measures show a growth rate of schooling of 1.67 percent and 1.41 percent for peak yield.

> 20 The measures are based on Buringh, van Heemst, and Staring (1979) and were used in Mundlak and Hellinghausen (1982) and Binswanger et al. (1987).

> 21 Countries included in the study are: Australia, Austria, Canada, Cyprus, Denmark, Egypt, Finland, France, Greece, India, Indonesia, Italy, Kenya, Republic of Korea, Malawi, Mauritius, Morocco, Netherlands, Norway, Pakistan, Peru, Philippines, Sri Lanka, Sweden, Republic of Tanzania, Tunisia, Turkey, United Kingdom, United States, and Uruguay.

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households about their use of financial services hold the most promise for measuring outreach well, but their cost and the other logistical hurdles have made it difficult to develop a standard method of questioning that would generate comparable financial usage data across countries and within countries over time. Our experimental analysis was designed to contribute to our understanding about the comparability of financial usage data generated under different question formats.

Our main findings are straightforward, intuitive, and, we hope, useful for future data gathering efforts. We find that rates of household usage are similar when the head reports on behalf of the household or when the rate is tabulated from a full enumeration of individual use. By contrast, randomly selected informants provide a less complete picture of household use of financial services than the other two methods. The comparability of data across the head of household and the full enumeration is potentially important because interviewing only the head is much less costly than interviewing all household members. At the same time, some surveys, for example those measuring labor force participation, are designed to be full enumerations. By using the head of household when possible and a full enumeration when it is dictated for other reasons, there is potential to increase the number of countries for which comparable data can be generated. For formal credit, informal savings, and insurance we find higher reported usage when questions are asked about specific financial products rather than about the respondents’ dealings with types of financial institutions. Product-related cues appear to be important for respondents regarding these services, and not just those who we would expect to be less financially knowledgeable. Although we only tested product-based and institution-based usage in the context of personal use of financial services, it would seem 35
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especially those with multinational parents, and much improvement will be needed in the commercial environment before a dynamic and competitive seed industry emerges in these countries.

3.34 National and international agricultural research stations have a positive role to play in seed developmetht for non-rice crops. Highyielding wheat and corn varieties developed at CIMMYT parallel the success of rice varieties developed at IRRI. Sorghum, millets, cassava, and some legumes are under development in CGIAR centers, although results are still mixed. Even when major improvements are made in basic genetic material, however, successful adaptation to the myriad local environments likely to be encountered at the margins of rice production, where diversification will first take place, still means a complex breeding, reproduction, and distribution effort will remain for each country. There is little evidence that public research programs and distribution mechanisms will be aggressive and efficient in these tasks.

# Agricultural Chemicals

3.35 Increased fertilizer use, especially of nitrogen fertilizers such as urea, has provided much of the "fuel" for higher rice yields in Asia. High-yielding rice varieties and the irrigation facilities essential for their high productivity are sometimes described as the "motor" and "body' of an integrated system designed to transport passengers. Without additional nutrients supplied by fertilizer, modern varieties 'rnder - irrigated conditions do not achieve their maximum potential yieles just as an automobile is limited by fuel availability in its distance traveled. Although farmers have sometimes been slow to learn this or to apply optimal quantities of fertilizer, there are now few Asian farmers growing irrigated paddy who do not purchase at least small quantities of fertilizer. Knowledge, risk, and constraints in obtaining credit may still limit these purchases to socially suboptimal levels, but the initial step of adoption has been taken by most rice farmers. In addition, much research has been carried out showing optimal levels of fertilizer use in varying circumstances, and the researchers' recommendations for applying a balanced set of nutrients to rice crops--the combination of nitrogen, phosphorus,
where _Yit_ is an indicator for having ever been married or pregnant for individual _i_ in Round _t_ , _αi_ and _δ_ t are individual and time fixed effects, and _TitC_ and _TitU_ are dummies that switch on for CCTs and UCTs during the two-year program.

# **3.3. Results**

# **3.3.1. Schooling**

# _Enrollment_

Table III describes enrollment rates by term, including a cumulative variable for the number of terms the girl was enrolled in school during the two-year intervention that takes on a value between 0 and 6. When we examine self-reported enrollment rates in Panel A, we see that enrollment rates in the control group steadily decline over time with the sharpest declines occurring between school years. Impact estimates suggest that these rates were significantly higher in both treatment arms, and that the UCT arm outperformed the CCT arm: the program impact on the number of terms the girls were enrolled in school during the two-year intervention is 0.41 terms in the UCT arm, compared to 0.23 terms in the CCT arm – a difference that is significant at the 95% confidence level.

Self-reported enrollment data can be subject to reporting bias. For example, comparing program impacts using self-reports to monitored data, Barrera-Osorio et al. (forthcoming) report that significant positive bias in self-reported school enrollment compresses the difference between treatment and control groups causing a downward bias in observed program impact. Baird and Özler (2010) confirm this finding for Malawi and show that differential misreporting can further bias program impacts. As described in Section 2.4, we tried to confirm the self-reported enrollment by visiting the schools the girls reported to be enrolled in and asking their teachers about their 19
# **7. REFERENCES**

Ackermann T., Andersson G., Söder L., 2001. “Overview of government and market driven programs for the promotion of renewable power generation”, Renewable Energy, Volume 22, Issues 1–3, January– March 2001, Pages 197-204.

Barradale, M. J. (2010). "Impact of public policy uncertainty on renewable energy investment: Wind power and the production tax credit." Energy Policy **38** (12): 7698-7709.

Batlle, C., Pérez-Arriaga, I.J.; Zambrano-Barragán, P. “Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing”, Energy Policy, Volume 41, February 2012, Pages 212-220 Batlle, C., Barroso, L., 2011. “Support schemes for renewable energy sources in South America”. MITCEEPR Working Paper 11-001.

Bridge to India, 2011-2014. “India Solar Compass”. Quarterly reports, October 2012 to April 2014.

Buckman, G., J. Sibley, et al. (2014). "The large-scale solar feed-in tariff reverse auction in the Australian Capital Territory, Australia." Energy Policy **72** (0): 14-22.

Butler, L. and K. Neuhoff (2008). "Comparison of feed-in tariff, quota and auction mechanisms to support wind power development." Renewable Energy **33** (8): 1854-1867.

Couture T., Gagnon Y., 2010. “An analysis of feed-in tariff remuneration models: Implications for renewable energy investment”, Energy Policy, Volume 38, Issue 2, Pages 955-965.

Cunha G., Barroso L., Bezerra B., 2014. “Lessons Learned from the Auction-Based Approach to Integrate Wind Generation in the Brazilian Electricity Market”, 2014 Cigre Session.

Cunha G., Barroso L., Porrua F., Bezerra B., 2012. “Fostering wind power through auctions: the Brazilian experience”, IAEE Energy Forum, Spring, Second Quarter 2012.

Del Río P., Linares P., 2012. “Back to the future? Rethinking auctions for renewable electricity support”, IIT Working Paper -12-038.

del Río, P. and E. Cerdá (2014). "The policy implications of the different interpretations of the costeffectiveness of renewable electricity support." Energy Policy **64** (0): 364-372.

del Río, P. and P. Linares (2014). "Back to the future? Rethinking auctions for renewable electricity support." Renewable and Sustainable Energy Reviews **35** (0): 42-56.

Eberhard, A., 2013. “Feed-in Tariffs or Auctions? Viewpoint: Public Policy for the Private Sector”, Note 338, Word Bank, International Finance Corporation.

EC (European Commission), 2013. “Communication from the Commission: Delivering the Internal Electricity Market and Making the Most of Public Intervention”. Accessed at http://ec.europa.eu/energy/gas_electricity/doc/com_2013_public_intervention_en.pdf EIA (Energy Information Administration), Department of Energy, 2013. “China: Analysis Brief”. Accessed at http://www.eia.gov/countries/analysisbriefs/China/china.pdf 34
opinion, that the realized losses are due to privatization. In all observed cases, the purchaser of the privatized entity did not assume ownership of all pre-privatization assets and liabilities. While this might seem strange from an economic perspective -- buyers could have simply paid negative prices (i.e. been paid by the province) -- political reality and the buyer's desire to "start afresh" dictated that a residual entity be created to ensure a positive price.

Although the individual cases varied, the basic strategy was to shift attractive assets to the privatized entity and then match those assets with liabilities, while leaving the privatized entity with sufficient net worth. The key determinant of the size of the residual entity was, therefore, the quality of the public provincial bank's assets (See Table 4).

**Table 4: Size of Residual Entities**

|Bank|% of Pre-Priv.<br>Assets|% of Pre-Priv.<br>Liabil.|% non-<br>performing<br>Pre-Priv.<br>(1994)|% Normal<br>Pre-Priv.<br>(1994)|Physical Assets<br>as % of Pre-<br>Priv. Assets|
|---|---|---|---|---|---|
|Chaco|54.0|51.3|**32.6|**52.6|8.9|
|Formosa|36.7|66.2|4.0|79.4|2.5|
|Mendoza|61.2|61.2|20.2|49.5|0.3|
|Misiones|28.6|65.8|12.5|71.6|5.3|
|Prv Soc Men|49.7|49.7|34.2|43.4|1.0|
|Rio Negro|24.6|23.7|47.3|28.4|1.2|
|Salta|73.3|58.7|75.9|7.5|4.5|
|San Juan|34.2|76.4|23.1|68.8|1.5|
|San Luis|31.6|87.1|12.9|80.9|35.5|
|Sant del Est|*81.1|*84.4|***71.8|***13.8|3.7|
|Tucuman|66.7|67.0|53.4|43.8|4.6|

Sources: See Table 2 with regard to % of pre-privatization assets and liabilities in the residual entity. The % nonperforming and the % normal loans data comes from B.C.R.A. balance sheets. Data on physical assets comes from Fondo Fiduciario balance sheets for residual entities at the time of privatization. * Calculations described in Table 2.

** 1993 data were used. By 1994, the effects of privatization were evident in Chaco's portfolio quality data. *** 1993 data were used. No data were available for 1994.

A simple regression shows that the worse the public provincial bank's portfolio, the larger the residual entity.<sup>23</sup>

- 23 The observation for San Luis was dropped from the estimation because the physical assets reported in its residual entity balance sheet implied an implausibly high percentage of those assets in its portfolio (Table 4). Although not reported here, the qualitative result is similar when % normal loans replaces % non-performing in the regression -- a high percentage of normal loans implies a smaller residual entity. These results are for portfolio quality measured _prior_ to privatization -- before the pre-privatization audit. Similar qualitative results obtain, however, when post-audit portfolio quality replaces the pre-audit measures in the regression. The only

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21 a little cash in hand can pose a real obstacle to purchasing contraceptives for impoverished villagers. The most affordable item is the free one; if affordability is a high priority, contraceptives should be provided free and exceptions should be made only for reasons that clearly outweigh the presumption of no charges.

Eqjity. The poor should have as ready access to vital services as those who are not poor. Free or subsidized services, as in social marketing programs, help achieve this. Some countries have in effect a dual system, providing contraceptives at a somewhat higher cost through the social security network or commercial outlets, but at lower cost through the Ministry of Health. Variations in dual systems deserve further thought; they may aid cost recovery and help cross- subsidization while still retaining equity and affordability.

Reimbursement justifications. In some circumstances, as where dire poverty exists, clients who accept sterilization and the IUD may be reimbursed for travel costs to a medical facility, time lost from work, extra foods, and so on. If the service is provided free, reimbursement removes a true cost obstacle. It requires greater public expense, but it increases both equity and affordability. Economic analyses over the years have shown a large net gain, even in the short run, from the investment of public funds in contraceptive services, an argument favoring cost reimbursements to clients in cases where out-of-pocket costs constitute a significant barrier to contraceptive use.

Incentive effects. In countries with anti-natalist policies, where incentives of one type or another are acceptable and feasible, the question arises as to their net cost to the government. Some incentive
in the educational composition of the workforce in acquired domestic fi rms<sup>29</sup> . The only signi fi cant change is for the group of low educated workers in manufacturing, whose share falls by 1 percentage point following the acquisition. Table A5 in the Appendix shows that there is no evidence of signi fi cant changes following the acquisition in the size of the fi rms in manufacturing. Therefore, this decrease in the share of low educated workers is re fl ecting a decrease in the number of low educated workers. In non-manufacturing the number of employees increases by 25 percent and 27 percent, by the second and third year following the acquisition and, therefore, the number of low educated workers must increase accordingly<sup>30</sup> . To check the robustness of the results relative to the fi rms included in the control group, I estimate the same model including all the domestic and foreign fi rms in the sample. The results are presented in column (4) of table 2<sup>31</sup> . In sum, if foreigners choose to enter a market by acquiring an existent domestic fi rm, they may look for a fi rm where they need to make adjustments in the workforce composition or they may target a fi rm whose workforce composition is close to the desired level. My fi ndings show that foreigners choose this second option since there is no signi fi cant adjustment in workforce composition following the acquisition. This seems a reasonable strategy in the presence of important employment protection in the Portuguese labor market (see Blanchard and Portugal, 2001).

# 4. Wages in Foreign Firms

To analyze the differences in the wage structure for the three education groups, I estimate hourly wages per employee as a function of several fi rm and worker characteristics, including

> 29Although not reported, these results are robust to the inclusion of the domestic acquisitions of foreign fi rms in the sample.

> 30Speci fi cation (3.2) is restrictive as it estimates an average effect following the acquisition, and restricts the impact to be zero in the years before the acquisition. I allowed for a more fl exible speci fi cation where the acquisition can affect the workforce composition up to four years before and after the acquisition year (see Jacobson et al., 1993, for a similar methodology). For manufacturing I fi nd that, 3 years before the acquisition the proportion of low educated workers starts decresing and the proportions of medium and high increasing. Specially in the third year following the acquisition there is evidence of quantitatively important changes. In non-manufacturing, the share of low educated workers also has a negative trend that is accompanied by an increase in the share of the medium educated. These changes start three years before the acquisition and, again, are not statistically different from zero.

> 31For computational reasons the coefficients in this model were not restricted.

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**Table 7. Educational Achievement at Age 17**

|||Urban|||Rural|||AR||
|---|---|---|---|---|---|---|---|---|---|
||Male|Female|AR|Male|Female|AU|Male|Female|All|
|Level of education completed||||||||||
|None|23.9|47.5|35.5|61.8|65.0|63.0|42.9|54.2|47.8|
|Primary|64.6|45.2|55.0|38.2|35.0|37.0|51.3|41.3|46.9|
|Lower secondary|11.6|7.3|9.5|-|-|-|5.8|4.5|5.2|
|All|100.0|100.0|100.0|100.0|100.0|100.0|100.0|100.0|100.0|
|Average years of education|7.2|4.7|6.0|3.6|2.3|3.1|5.4|3.8|4.7|

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where ���� ��������� is the variable of interest, namely, whether individual � of country � during year � believes income distribution is very unfair or not; � is a vector of individual characteristics that includes the age, sex, civil status, education, and type of job; ��� is the country’s Gini coefficient; � is a vector of country and subnational fixed effects<sup>19</sup> ; � is a vector of year fixed effects and ���� is the error term.

We are interested in the sign and magnitude of �� and ��. The first of these coefficients captures the relationship between the individual’s characteristics and unfairness perceptions. If unfairness is uncorrelated with observable characteristics, then this coefficient should not be statistically different from zero. On the other hand, �� captures the relationship between the Gini coefficient and the perceived fairness after controlling for an individual’s covariables. If subjective measures of income inequality are significantly correlated with their objective counterparts, we would expect this coefficient to be positive and statistically different from zero.

# **4.3 RESULTS**

Table 2 summarizes the main results of the Logit regressions under different specifications. Column (1) presents the results controlling only for the Gini coefficient. Column (2) includes basic demographic indicators: age, age squared and gender. Column (3) incorporates dummies for civil status and educational variables, namely, literacy and maximum educational attainment. Column (4) includes dummies for labor market variables: labor force participation and unemployment. Column (5) incorporates access to basic services—running water and sewerage—and asset ownership, namely ownership of a computer, washing machine, telephone and car. Column (6) replicates the same specification as column (5), but with Ordinary Least Squares (OLS). All specifications include country, subnational and year fixed effects.

Our first result is that the Gini coefficient has a positive and statistically significant relationship with unfairness perceptions, consistent with the evidence shown in the previous section. For example, in a country with average characteristics, a decrease of one point of the Gini coefficient (from 0.496 to 0.486) decreases by about half a percentage point the share of the population that believes income distribution is very unfair. Such magnitude is quite similar with the Logit (column 5) and OLS (column 6) estimates, and does not vary much across different specifications (columns 1-5). It is important to stress that the interpretation is not causal. The relationship between income inequality and unfairness perceptions can go both ways. On one hand, higher inequality can increase the share of the population that believes distribution is unfair. But as more people perceive income

> 19 Latinobarómetro’s survey is representative in each country at the subnational level, so we include 380 subnational fixed effects to capture unobservable heterogeneities at this level.

17