rafmacalaba/datause-encoder-data huggingface dataset:
3 separability between input decisions and sales decisions that it implies is not necessary for the results that are established here.

The assumption that there are increasing marginal costs to diverting sales from the restricted towards the unrestricted market may be interpreted as indicating the short-run effects of a VER. In the shortrun, with the quantities of factors employed in the industry being fixed, different factor intensities will result in increasing marginal costs to altering the product mix. Alternatively one can view the two products as differentiated. 1/ The above assumptions allow us to represent our model diagramatically. In figure 1, foreign export demands in the restricted (A) and unrestricted (B) markets are represented in quadrants I and II, respectively, while quadrant III depicts the substitution possibilities facing the Industry as it reallocates production between sales foru-rket A and those for market B. It is obtained by the aggregationz **ot** the substitution possibilities facing each representative exporter. The bowed-out shape of the *export transformation" curve, G(XA, XB) = X, reflects the assamption of increasing costs to product mix shifts. Assuming that one can write an aggregate footwear production, X, successive increments in sales to market B impose increasing resource costs in terms of larger and larger decreases in export sales to market A. Quadrant IV is the 45° line which translates export sales to A from quadrant III to quadrant I.

The unrestricted allocation, A*, is represented by the pricequantity pairs (P*A, X*A) and (P*B, X*B), where superscript asterisks are used to denote the unrestricted equilibrium. 2/ The slope of the export transformation curve is given by
# **1.  Introduction**

The decision to invest abroad is typically a two-step process for investors. First, they decide in which country to invest. Second, they decide in which companies to invest. Studies such as Aggarwal, Klapper, and Wysocki (2005) find that disclosure at the firm level is an important determinant of firm choice for institutional investors. Since information asymmetry appears to be worst for smaller firms, foreign investors often steer clear of these firms, even if they are listed. This implies that investors that are looking for international diversification choose to invest in only the largest listed firms. Indeed, Dahlquist and Robertsson (2001), Kang and Stulz (1997), Edison and Warnock (2004), and Cai and Warnock (2004) all find that foreign owners prefer large firms. Leuz, Lins, and Warnock (2007) find that information asymmetry and monitoring costs lead investors to choose firms with the least opaque earnings, also implying that foreign investment would go directly to large firms. As such, it isn’t immediately obvious whether small listed firms would benefit from foreign portfolio investment, defined by the International Monetary Fund as equity and debt issuances including country funds, depository receipts, and direct purchases by foreign investors of less than 10% control (Balance of Payments Manual, 1993). This is especially the case in countries where property rights are less strictly enforced.

Although the likelihood of small firms accessing foreign capital directly is very small, foreign portfolio investment (FPI) could have implications on capital allocation in the domestic market. Wurgler (2000) finds that financial markets facilitate capital allocation. Since capital market liberalization allows for foreign investment and deepens financial markets (Henry, 2000),<sup>1</sup> one could argue that FPI could improve capital allocation. Thus, small public firms could see an improvement in their access to capital with an increase in the level of FPI.<sup>2</sup> This suggests that FPI could actually improve access to finance for small listed firms. If FPI is beneficial to the access to financing of small listed firms, by what mechanism does it help? Does the impact of FPI on the access to financing of small listed firms change depending on the level of property rights protection? To answer these questions, this paper examines the impact of FPI on the access to 1
**Table 8: Comparison of Means of Unweighted and Weighted Intercept Samples**

||Sao|Paulo|Curi|tiba|
|---|---|---|---|---|
||**Unweighted **<br>**Intercept**|**Weighted**<br>**Intercept**|**Unweighted **<br>**Intercept**|**Weighted**<br>**Intercept**|
|Proportion Male|0.50|0.58|0.60|0.60|
|Age|46.6|51.6|48.0|48.4|
|Proportion Married|0.48|0.43|0.60|0.62|
|Proportion with Nikkei Spouse if Married|0.82|0.78|0.77|0.73|
|Proportion with some University education|0.58|0.59|0.65|0.62|
|Proportion working for pay|0.67|0.69|0.59|0.61|
|Household Size|3.29|3.46|3.42|3.43|
|Proportion Issei|0.15|0.12|0.11|0.10|
|Proportion Nissei|0.47|0.45|0.53|0.56|
|Proportion Sansei|0.36|0.42|0.35|0.32|
|Proportion Yonsei|0.02|0.02|0.01|0.01|
|Proportion who ever studied/worked in Japan|0.45|0.35|0.34|0.34|
|Proportion of households with member ever in Japan|0.65|0.59|0.51|0.49|
|Proportion with household member currently in Japan|0.35|0.33|0.18|0.16|
|Proportion with household member who..|||||
|Reads Japanese/Nikkei newspapers|0.39|0.28|0.21|0.18|
|Listens to Japanese/Nikkei radio programs|0.25|0.21|0.17|0.15|
|Watches Japanese/Nikkei TV programs|0.43|0.36|0.47|0.45|
|Reads Japanese/Nikkei books/magazines|0.42|0.31|0.37|0.32|
|Reads newspapers from Nikkei associations|0.39|0.28|0.46|0.37|
|Checks Japanese/Nikkei websites on the internet|0.24|0.17|0.29|0.24|

# **4.3 The Snowball Survey in São Paulo State**

The final type of survey method trialed was that of a snowball survey. The questionnaire used was the same as used for the stratified random sample. Our plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (i) a Nikkei household with a member currently in Japan; (ii) a Nikkei household with a member who has returned from Japan; and (iii) a Nikkei household without members in Japan and where individuals had not returned from Japan. They were also asked to say the number of households they knew in each category, which could then be used to weight the sample.

The first step was therefore to select the seed households. One approach likely to be followed by researchers attempting a snowball survey is to use ethnic organizations as the source of the seed households. To replicate what a reasonable researcher might do, we therefore decided to use Nikkei associations to obtain the seed households. In collaboration with Sudameris, we therefore contacted 25 associations throughout the state of São Paulo, who had prior associations with Sudameris. The purpose of the survey was 27

-  -
of defaults. Additionally, the pilot project included a Risk Sharing Guarantee Facility financed by the Inter-American Development Bank (IDB). This Risk Sharing Facility covered up to a maximum fraction of the credit exposure (principal and interest) for guaranteed loans after exhausting the first loss amount to be assumed by our partner bank. This guarantee may also have influenced the effort exerted by our partner bank when monitoring loans and collecting payment.

We study the effectiveness of the EFL tool in increasing access to credit for loan applicants and we also ask whether this increased access results in worse repayment behavior. That is, we first investigate whether being offered a loan by our partner bank based on their EFL score increased the overall use of SME credit in our sample. Clearly, SMEs with an EFL score above the threshold were more likely to obtain a loan from our partner bank than those with an EFL score below this threshold. However, SMEs with an EFL score below the threshold could potentially have gotten a loan from other financial institutions different from our partner bank, in which case loan use may not increase. Second, we ask whether SMEs that were offered a loan based on the EFL tool exhibit repayment behavior different from SMEs that were not offered a loan based on the EFL tool.

We estimate the causal impact of the EFL tool on SME loan use and repayment behavior using several regression discontinuity (RD) methods around the EFL score threshold. For this analysis, we obtained detailed data on formal credit usage and credit scores from Equifax Peru. We use the Equifax credit score four years after the loan application as a measure of repayment behavior. Since the EFL tool may be particularly relevant for loan applicants who do not have a credit history, we conduct our analysis in the full sample of applicants, as well as in two subsamples: (i) applicants with thin credit bureau files and (ii) applicants with thick credit bureau files. We define applicants with a “thick credit bureau file” as those applicants whose Equifax score was based on their credit history and applicants with a “thin credit bureau file” as those whose Equifax score was based on demographics and other sources, such as the tax authority.

Our results show that in the full sample of applicants, the EFL tool increased the probability of taking out a new SME loan from any financial institution during the six months following the pilot loan application by up to 19 percentage points (compared to about 59 percent just below the EFL score threshold). When analyzing the subsamples, we see that the effect of the EFL tool on taking out a new SME loan during the six months following the application is much larger for applicants with thin credit bureau files, with an increase of up to 59 percentage points (compared 4
Since low-carbon technologies are generally more capital intensive than high-carbon technologies, we have the following result.

Result #7. If the low-CO2 project is more capital intensive than the high-CO2 project (i.e. ), then the switching price will increase as the discount rate increases.

# **6. Empirical estimates of hurdle and switching prices for electric power generation**

To further assess our results derived in sections 2-5, we present selected estimates of hurdle and switching prices for electric power generation. The analysis is necessarily „stylized,‟ abstracting from important questions of base versus peak load dispatch and other critical aspects of „real world‟ energy systems. Similarly, we use levelized costs to normalize different project lifetimes as well as to provide the numeraire for comparison – prices, costs and emissions are all expressed per kilowatt-hour (or multiples thereof).

Following expression (3), hurdle prices are calculated as where is the electricity price, _lcoe_ is the levelized cost of electricity generation and _e_ is CO2 emissions.

Figure 2 depicts the ranges for hurdle prices derived from recent studies. While emission factors for each technology were taken from ESMAP (2007) and the Royal Academy of Engineering (2004), electricity prices were derived from IEA (2012). The levelized cost estimates are based on an overview of a large number of recent studies presented in IEA (2010).<sup>10</sup> Obviously, using

> 10 For clarity, the assumptions are also shown in table 6. Prices in IEA (2010) are post-tax.

19
Policy Research Working Paper 5332

# **Abstract**

Access to energy, especially modern sources, is a key to any development initiative. Based on cross-section data from a 2004 survey of some 2,300 households in rural Bangladesh, this paper studies the welfare impacts of household energy use, including that of modern energy, and estimates the household minimum energy requirement that could be used as a basis for an energy poverty line. The paper finds that although the use of both traditional (biomass energy burned in conventional stoves) and modern (electricity and kerosene) sources improves household consumption and income, the return on modern sources is 20 to 25 times higher than that on traditional sources. In addition, after comparing alternate measures of the energy poverty line, the paper finds that some 58 percent of rural households in Bangladesh are energy poor, compared with 45 percent that are income poor. The findings suggest that growth in electrification and adoption of efficient cooking stoves for biomass use can lower energy poverty in a climate-friendly way by reducing carbon dioxide emissions. Reducing energy poverty helps reduce income poverty as well.

This paper—a product of the Agriculture and Rural Development Team, Development Research Group—is part of a larger effort in the department to understand the role of energy in growth and poverty reduction. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at skhandker@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
selected from the Albanian and Serbian population of Kosovo, respectively. It comprises a community questionnaire as well as a household questionnaire designed to provide the necessary empirical base line for the future economic development of Kosovo and designing its poverty reduction strategy. As such, it includes detailed information on individual, household and community characteristics collected over a period of three months-between September and December 2000. This analysis focuses on the education module of the household questionnaire. We use two dependent variables to measure education. The first dependent variable of interest is enrollment in secondary education, a variable that takes the value of one if the individual has ever been enrolled in secondary education and zero otherwise. The sample is restricted to individuals who finished primary education (completed grade 8). The second dependent variable in the next part of the analysis is the highest grade achieved by those that have enrolled in secondary education. Our sample includes Kosovar Albanians and Serbs aged 16-35 years. We perform the analysis separately on the two cohorts of Albanians as we expect the political and economic changes to have a significant impact on their education patterns. The entire Serb sample is analyzed using a dummy variable to identify the two cohorts. We do this for two reasons. First, given the size of the Serb sample, it is not practical to analyze the two cohorts separately. Second, we don't expect the change in the education system to have affected the Serbs much, so we treat them only as a comparison group.

Other literature emphasizes the importance of household wealth in determining education outcomes (Deolalikar, 1997). Given the lack of a retrospective history of incomes, and the substantial changes observed in the last years, we use an asset-based measure to identify potential income effects. If durable goods reflect previous incomes, the value of durables in a 11
# Table of Contents

|||PAGE|
|---|---|---|
|I.|Introduction|1|
|II.|Investment Trends|5|
|III.|Determinants of Private Fixed Investment:<br>Model Specification|8|
|IV.|Effective Cost of Borrowing|13|
|V.|Estimation Results|15|
|VI.|The Model Applied: An Empirical Analysis<sup>of</sup><br>Private Investment in Turkey 1980-86|19|
|vII.|Conclusions|24|
||References|26|

This paper is part of a larger study on Turkey's<sup>recovery from the</sup> debt crisis, undertaken joincly with Ritu<sup>Anand and Roberto Rocha, both from</sup> the World Bank. We are indebted to them<sup>for many helpful discussions, and to</sup> John Brondolo and Reza Firuzabadi for competent<sup>research assistance. In Turkey</sup> the assistance provided by Hasan Ersel,<sup>Yavuz Ege, Given Sak and Gazi Ercel is</sup> gratefully acknowledged. The authors also thank<sup>B. Balassa and J. Khalilzadeh-</sup> Shirazi for very useful comments. The views<sup>expressed in this paper are our</sup> own and do not necessarily reflect those of<sup>the institutions we are affiliated</sup> with.
Given the interpretation of the li, i = 1 to n, as pure leisure demands, it is then claimed that the model has at least two strong, testable restrictions on comparative statics effects:

- since the Slutsky matrix is symmetric, the compensated derivatives of each member's pure leisure demand/labor supply with respect to the other's wage are equal, so that the uncompensated derivatives differ only in respect of income effects;

- the effect of a change in total household income on consumption or leisure demand/labor supply is independent of the source of the change in this income, and, in particular, of whose wage rate or non-labor income change causes the income change. This is often called, misleadingly, the “income pooling hypothesis”, and there is a growing literature concerned with showing that this hypothesis is rejected by the data.

The relevance of the first restriction depends not only on the assumption that non-market time is pure leisure, but also on its corollary, that there is no household production. Thus, it is important to keep in mind that the first restriction is relevant only if we view, for example, the time mothers spend on home child care as pure leisure, providing no private benefits for other family members, including the children who must, presumably, be looking after themselves. If we do not hold this view, then the leisure demand/labor supply functions appropriately take the form in (5b) and the model imposes the Slutsky symmetry restrictions only on _individual_ compensated cross price effects. If the model is estimated on time use data that allow domestic production to be separated from pure leisure, the wage rates of other family members can, in general, also enter indirectly through the prices of domestic goods, as shown in Apps and Rees (1996).

These issues are not new. That the empirical specification of the standard household model, in which all demands are aggregated across family members, is inappropriate for a system estimated on data for assigned goods has long been recognized in the development literature on health and human capital outcomes. For example, Pitt and Rosenzweig (1986) in their analysis of health outcomes and food consumption discuss at length the limitations of the standard household model in the context of these assigned goods.

14
57 The ratio of retail kerosene to diesel prices in each country in January 2012 is shown in figure A2.1. The fuel pricing policy in each country is described briefly in table A2.2.

Figure A2.1: Ratio of kerosene prices to diesel prices in January 2012

|0.49<br>0.36<br>0.31<br>Malawi<br>India<br>Nigeria|
|---|
|0.56<br>0.51<br> <br><br>Indonesia<br>Ghana<br>|
|0.59<br><br>Gabon|
|0.65<br>Angola|
|0.67<br>Sri Lanka|
|0.67<br>Cameroon|
|0.68<br>Zambia|
|0.72<br>Madagascar|
|0.72<br>Japan|
|0.73<br>Bolivia|
|0.75<br>Uruguay|
|0.76<br>Mozambique|
|0.77<br>South Africa<br>|
|0.78<br>Togo|
|0.78<br>Ethiopia<br>|
|0.79<br>Senegal<br>|
|0.80<br>Tunisia<br>|
|0.81<br>Argentina|
|0.81<br>Kenya<br>|
|0.84<br>Uganda<br>|
|0.84<br>Honduras<br>|
|0.86<br>Turkey|
|0.86<br>Niger<br>|
|0.86<br>Costa Rica<br>|
|0.90<br> <br>Pakistan<br>|
|091<br> <br>Dominican Republic<br>|
|0.97<br>.<br><br>Iraq<br>|
|0.99<br>Nicaragua|
|0.99<br> <br>Vietnam<br>|
|0.99<br> <br>Tanzania<br>|
|100<br>Egypt Arab Rep|
|100<br>.<br>Yemen Rep<br>, .|
|1.00<br>.<br>Jordan<br>, .|
|100<br>Banladesh|
|100<br>.<br>Neal<br>g|
|1.00<br>.<br>Liberia<br>p|
|1.00<br>Côte d'Ivoire|
|2<br>Chil|
|1.0<br>e|
|<br>Cbdi|
|<br>1.02<br>Ji<br>amoa|
|1.03<br>amaca|
|1.09<br>Guatemala|
|1.16<br>Philippines|
|1.19<br>Thailand<br>|
|0.00<br>0.20<br>0.40<br>0.60<br>0.80<br>1.00<br>1.20<br>1.40|

_Sources:_ Table A2.1 and author’s calculations.
18 then detect if private and cooperative firms present a different behavioral pattern with respect to public ones.16

|**Table 6. Tests of o**<br>**homogeneity betw**<br>**enterprises**|**verall model and spe**<br>**een public and priva**|**cific variables**<br>**te/cooperative**|
|---|---|---|
|345 observations<br>R =.21|||
|MSE =.311|||
|Variable|Test statistic (1)|p-value|
|z(o)|32(1)1.23|.90|
|z(o)*n(k)|8 <sup>2 </sup>(4) 13.84|.01|
|z(o)*s(i,t)|2(16) = 25.76|.07|
|z(o)*m(t)|82(2)= 7.34|.05|
|All the above|2(23) = 77.05|.01|

(1) The estimation procedure is heteroschedasticity consistent. Thus, T<sup>2</sup> statistics are used (see Huber, 1967, and White, 1980). Yearly data Results are reported in Table 6. They show that, with respect to public firms, private and cooperative enterprises belong to a different population, thus confirming the robustness of the results reported in the previous section. The overall significance of the variables including z(o) is in fact quite high, i.e. I per cent. Furthermore, the tests relative to the specific variables show a significantly different response with respect to each one of them -- particularly size -- the only exception being the variable z(o) alone, which is not significantly different from zero.

By using the same methodology we have also investigated the possibility that cooperative and private firms did not conform to the same model; the results obtained have led us to reject such hypothesis.'<sup>7</sup> 16 Given the structure of the data set, we first attempted to develop a panel data random effects model. The results of the Breush Pagan Lagrangian multiplier test for random effects over the presence of a statistically significant variance in the unit specific random variable have rejected such assumption; thus showing the reliability of standard OLS techniques, which we applied in the regression of (4). 17 The test was performed in accordance with the same methodology discussed above. The related F statistic was F(21, 174)=1.05. Model heterogeneity was then significant only at the 40 percent level of confidence. We have also performed the following diagnostic tests: (1) Ramsey RESET test for omitted