rafmacalaba/datause-encoder-data huggingface dataset:
**Table 4: Attrition**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|4P Assignment|-0.07124|-0.17888|-0.09383|-0.22338|
||(0.683)|(0.317)|(0.587)|(0.206)|
|4P Propensity Score|0.07897|-0.12860|0.06994|-0.16800|
||(0.719)|(0.575)|-0.75|(0.451)|
|4P Propensity Score X 4P Assignment|0.16151|0.38872|0.20688|0.47874|
||(0.615)|(0.246)|(0.516)|(0.149)|
|Observations|886|886|886|886|
|Characteristics of spouse of HH head (values for missing spouses<br>coded as zero)|Yes|Yes|No|No|
|Dummyforpresence of spouse of HH head|Yes|No|Yes|No|
|F-test of all vars(p-val)|0.677|0.609|0.590|0.455|
|P-values inparentheses: *p<0.1 **p<0.05 ***p<0.01|||||

27
# **Stability and Evolution of Preferences for Improved Cookstoves - A Differencein-Difference Analysis of a Choice Experiment from Ethiopia**

# **1. Introduction**

Non-market valuation methods are used to determine the value, preferences and potential consumer demand for non-market environmental goods and policies. Valuation studies, in particular statedpreference methods that involve surveys, are often costly, and therefore conducted infrequently (Bliem et al. 2012, Brouwer and Bateman 2005, Mørkbak and Olsen 2014, Price et al. 2016). If the values obtained from these studies are stable over time, meaning there is no significant change in preferences among the given survey sample over time, they can be used in future analysis (Bliem et al. 2012, Brouwer and Bateman 2005, Morten and Olsen 2014, Price et al. 2016). Therefore, rather than acquiring funding for data collection, historical data that exhibit stability can be used for benefit transfer and cost-benefit analysis in the future.

However, due to the hypothetical nature of these valuation techniques, it is often difficult to determine the credibility or validity of the results as time progresses. Credibility is a measure of temporal validity, or as Mørkbak and Olsen (2014) state, “Does an individual respondent provide identical answers to identical questions over time, assuming that preferences are stable?” If preferences are not found to be stable, the use of results from stated preference studies conducted in the past for benefit transfer, cost-benefit analysis and calculation of welfare over time becomes problematic.

Further, the few studies on measuring stability of preferences elicited from choice experiment surveys have been conducted in developed country settings. At the same time there is a growing use of non-market valuation surveys, especially choice experiments, in developing country contexts to guide environmental policy and regulations. Understanding if preferences elicited in developing country settings, especially in rural communities, are stable is important with regard to using results from non-market valuation studies over time.

Therefore, the first focus of this work is to determine if preferences elicited using choice experiment surveys in developing country settings are stable over time. We test the temporal stability of preferences for identical respondent groups over a three-year period, using identical choice experiment surveys, in a test-retest experimental setting.

The background of the study is a valuation study on preferences for clean cookstoves and a randomized controlled trial (RCT) of improved cookstoves conducted in Ethiopia. The main objective of the valuation study was to use a choice experiment survey to examine Ethiopian households’ 2
Policy Research Working Paper 6362

# **Abstract**

Mass media play a crucial role in information distribution and in the political market and public policy making. Theory predicts that information provided by the mass media reflects the media’s incentives to provide news to different groups in society and affects these groups’ influence in policy making. The paper use data on agricultural policy from 69 countries spanning a wide range of development stages and media markets to test these predictions. The empirical results are consistent with theoretical hypotheses that public support for agriculture is affected by the mass media. In particular, an increase in media (television) diffusion is associated with policies that benefit the majority to a greater extent and is correlated with a reduction in agriculture taxation in poor countries and a reduction in the subsidization of agriculture in rich countries, ceteris paribus. The empirical results are consistent with the hypothesis that increased competition in commercial media reduces transfers to special interest groups and contributes to more efficient public policies.

This paper is a product of the Partnerships, Capacity Building Unit, Development Economics Vice Presidency. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at alessandro.olper@unimi.it and Jo.Swinnen@econ.kuleuven.be.

_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
require registration as unemployed.

Conclusions: While the official unemployment estimates of the SPO undoubtedly are correct in claiming a strong increase in unemployment rates from the 1960s to the mid-1980s, it is not possible to substantiate the estimates in all detail. That LFSs have always been conducted at an agricultural slack season indicates that the level of unemployment as measured by the LFSs is exaggerated even assuming that the agricultural labor market always clear. We cannot know the degree of exaggeration but with agricultural markets clearing it may be a secondary matter.LFSs suggest that the national unemploymient rate may have increased from some 3-4 percent at the end of the 1960s to 12.7 percent in 1985 as compared with the smaller increase from 5 to 12.7 percent estimated by the SPO. In agreement with the SPO estimates, placement office statistics suggest that most, if not all this increase took place from the mid-1970s to the early 1980s. Beyond that indicators are conflicting. Auxiliary placement indicators agree with the population censuses that unemployment rates may have increased slightly from 1965 to 1975 but suggest no increase during the second half of the 1960s and show a certain decline 1970-73 followed by considerable increase 1973-76. This is in disagreement with the SPO estimates which indicate steady increase from 1962 to 1985 apart from a slight drop in 1974 and 1977, yet appear plausible considering emigration. As for the development during the 1980s indicators are conflicting. Urban

- 19 -
and source country, which allows us to test for heterogeneity in the relationship between political instability and FDI flows.

Overall, the fDi Markets database contains 7,427 investments made in the region by well over 4,500 multinational corporations (MNCs), which we aggregate to the sector-country level shown in Table 1. The table shows the distribution of these investments across MENA countries and broad economic sectors: resources and energy, tradable non-resource manufacturing, tradable services, and non-tradable manufacturing and services based on the classification of Jensen and Kletzer (2005), which is described in Appendix A2. The nontradables category is a residual group covering inter alia mostly investments in non-tradable services such as utilities, real estate, construction, and the financial services sector. Overall, most capital was invested in resources and energy (30%), followed by non-tradables<sup>9</sup> (28%), and tradable services (26%), with non-resource manufacturing (16%) ranking at the bottom. These broad aggregates, however, mask considerable differences in the sectoral distribution of greenfield FDI across destination countries. In terms of the amount of capital invested, the most investments originated from the Middle East and North Africa (34%), followed by Europe and Central Asia (29%), South and East Asia (19%), and North America (16%).

Greenfield FDI flows also vary over time, as illustrated in the right panels of Figure 1. For visual ease of interpretation, we use annual moving averages, which smooth out volatility in greenfield FDI inflows. Despite the averaging, the FDI inflows depicted in the plots exhibit substantial volatility. Countries in Northern Africa all experienced a surge in greenfield FDI until 2008-2009 when trade and capital flows collapsed in the aftermath of the global economic and financial crisis. Mild recovery of FDI inflows in 2010 appears to have been interrupted by the Arab Spring, which led to further reductions in FDI inflows. Greenfield FDI inflows into GCC countries remained relatively stable over the period, although it is notable that to varying degrees

> 9 Non-tradables mainly include investments in the construction, real estate, and financial services.

12
# IV. TIETP Performance Evaluation

This chapter analyzes the effects of TIETP to substantiate whether such incentive measures to encourage end‐consumers to use electronically traceable payments help reduce underreporting in cash‐intensive retail sectors, the motivation for this policy as described in the previous chapter. First, as a descriptive analysis, we will examine the volume of electronically traceable payments, the taxpayer ratio as a percentage of business income earners, and effective PIT rates in Korea, which will provide broad evidence for reductions in underreporting. We then estimate TIETP’s quantitative tax revenue effects using counterfactual analysis.

## 1. Descriptive Analysis for TIETP

### Increase in Electronically Traceable Payments

TIETP allowed wage and salary income earners to claim tax deductions for their credit card, debit/check card, and bearer‐identifiable prepaid card spending, which is believed to have had a substantial impact on cashless payments since its introduction in 1999. Figure 4 shows the volume of electronically traceable payment (ETP) as a percentage of GDP from 1991 to 2014. Credit card transactions increased very sharply immediately after TIETP’s introduction in 1999. They had been merely 4.9 percent in 1999, but they had skyrocketed to 34.3 percent by 2002. In absolute terms, ETP soared from W 28.5 trillion (approximately US$26 billion) to W 261.7 trillion (approximately US$238 billion) during the same period.

Since 2003, when the TIETP deduction rate for debit cards increased from 20 percent to 30 percent to favor them over credit cards, debit card payments started to rise sharply. In 2005, the electronically traceable cash receipt (ETCR) was included as eligible for TIETP. With these two changes, a considerable amount of credit card payments seems to have shifted to these two alternatives, moderating the increase of credit card transactions since 2003, as shown in Figure 4.

In 2014, the total value of credit, debit, check, and prepaid cards, not including ETCR, reached W 631.6 trillion (approximately US$574 billion), 42.5 percent of GDP. Since 2005, card payments as a ratio to GDP in Korea ranks highest among the 23 member countries of the Committee of Payments and Market Infrastructures, Bank for International Settlements.<sup>50</sup>

> 50. Card payments (not including e‐money) as a ratio to GDP was 30.5 percent in 2005, 36.7 percent in 2010, and 42.5 percent in 2014. Data retrieved from statistics on payment, clearing, and settlement systems in the CPMI countries (each year; see table 9e for comparative tables).

30
Policy ReseaRch WoRking PaPeR 4571

# **Abstract**

This paper analyzes poverty in Haiti based on the first Living Conditions Survey of 7,186 households covering the whole country and representative at the regional level. Using a US$1 a day extreme poverty line, the analysis reveals that 49 percent of Haitian households live in absolute poverty. Twenty, 56, and 58 percent of households in metropolitan, urban, and rural areas, respectively, are poor. At the regional level, poverty is especially extensive in the northeastern and northwestern regions. Access to assets such as education and infrastructure services is highly unequal and strongly correlated with poverty. Moreover, children in indigent households attain less education than children in nonpoor households. Controlling for individual and household characteristics, location, and region, living in a rural area does not by itself affect the probability of being poor. But in rural areas female headed households are more likely to experience poverty than male headed households. Domestic migration and education are both key factors that reduce the likelihood of falling into poverty. Employment is essential to improve livelihoods and both the farm and nonfarm sector play a key role.

This paper—a product of the Sustainable Development Division, Social Development—is part of a larger effort in the department to reduce poverty and increase social inclusion. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at dverner@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
# Table 7: Fiscal Deficit and Private Sector Credit

|Dependent Variable|Real Private<br>Share|Sector Credit as<br>of GDP|Real Credit<br>to Private<br>Sector|
|---|---|---|---|
||1968-88<br>(1)|1974-88<br>(2)|1968-88<br>(3)|
|1. Constant|-0.69|-1.42|-1831.5|
|2. Fiscal Deficit/GDP|-0.39<br>(2.26)|--|--|
|3. Growth of GDP|25.7*<br>(1.92)|--|--|
|4. Real Credit to Public<br>Sector/GDP||-0.52<br>(2.11)||
|5. Real Lending Rate|||-644.4"<br>(-1.95)|
|6. Real Credit to Public<br>Sector||--|-0.41"<br>(-2.03)|
|7.Real GDP|||0.07**<br>(2.91)|
|Adjusted R<sup>2</sup>|0.39|0.45|0.68|

All coefficients related to the financing of fiscal deficit confirm the "crowding out" effect of increased fiscal deficit. Thus if fiscal adjustment is successful in reduci.ng deficits, the availability of credit to private sector will improve and private investment will rise. However, if reduction in deficit is undertaken through reduction in expenditure and this is disproportionately borne by government's investment expenditure especially on infrastructure, as has happened in Kenya private investment will fall.

25
- [67] Munshi, K. and M. Rosenzweig (2016), “Networks and Misallocation: Insurance, Migration, and the Rural-Urban Wage Gap", _American Economic Review,_ 106(1): 46-98.

- [68] Platteau, J.P. (1995a), “A Framework for the Analysis of Evolving Patron-Client Ties in Agrarian Economies,” _World Development_ , 23(5): 767-786.

- [69] Platteau, J.P. (1995b), “An Indian Model of Aristocratic Patronage,” _Oxford Economic Papers_ , 47(4): 636-662.

- [70] Platteau, J.P. and Abraham, A. (1987), “An inquiry into quasi-credit contracts: The role of Reciprocal Credit and Interlinked Deals in Small-scale fishing communities”, _Journal of Development Studies_ , 23: 461?90.

- [71] Rosenzweig, M. (1988), “Risk, Implicit Contracts and the Family in Rural Areas of Low-income Countries", _Economic Journal,_ 98: 1148-1170.

- [72] Schechter, L. and A. Yuskavage (2011a), “Inequality, Reciprocity, and Credit in Social Networks,” _American Journal of Agricultural Economics_ , 94(2): 402-410.

- [73] Schechter, L. and A. Yuskavage (2011b), “Reciprocated Versus Unreciprocated Sharing in Social Networks,” working paper.

- [74] Schoeni, R. F. (1996), “Does Aid to Families with Dependent Children Displace Familial Assistance?”, Rand Working Paper, DRU-1453-RC.

- [75] Townsend, R. (1994), “Risk and Insurance in Village India,” _Econometrica_ , 62(3): 539-91.

- [76] Udry, C. (1994), “Risk and Insurance in a Rural Credit Market: An Empirical Investigation in Northern Nigeria,” _Review of Economic Studies_ , 61(3): 495-526.

- [77] Walker, M. (2017), “Informal Taxation and Cash Transfers: Experimental Evidence from Kenya", Working Paper.

32
- Table S.27: Estimating non-attrition probability.

- Table S.28: Lee (2009)’s 95% confidence intervals of the treatment effects.

- Table S.29 to Table S.33: Checking on spillover effects on children’s educational achievement.

- Table S.34: Impacts on children’s mid-term examination results.

- Table S.35: Checking on multiple-hypothesis testing.

# **References**

- Anderson, M. L., December 2008. Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry preschool, and early training projects. Journal of the American Statistical Association 103 (484), 1481–1495.

- Baird, S., Bohren, A., McIntosh, C., Ozler,<sup> ̈</sup> B., March 2014. Designing experiments to measure spillover effects. Policy Research Working Paper 6824, World Bank, Development Research Group, Poverty Inequality Team.

- Benjamini, Y., Krieger, A. M., Yekutieli, D., September 2006. Adaptive linear step-up procedures that control the false discovery rate. Biometrika 93 (3), 491–507.

- Blakesley, R. E., Mazumdar, S., Dew, M. A., Houck, P. R., Tang, G., III, C. F. R., Butters, M. A., March 2009. Comparisons of methods for multiple hypothesis testing in neuropsychological research. Neuropsychology 23 (2), 255–264.

- Dhaliwal, I., Duflo, E., Glennerster, R., Tulloch, C., 2013. Comparative Cost-Effectiveness Analysis to Inform Policy in Developing Countries: A General Framework with Applications for Education. University Of Chicago Press., Chapter 8 in Education Policy in Developing Countries, edited by Paul Glewwe.

- Evans, D., Kremer, M., Ngatia, M., 2008. The impact of distributing school uniforms on children’s education in Kenya.Washington, DC: Mimeo, World Bank.

- Evans, D. K., Popova, A., January 2016. Cost-effectiveness analysis in development: Accounting for local costs and noisy impacts. World Development 77, 262–276.

- Furukawa, C., 2014. Do solar lamps help children study? contrary evidence from a pilot study in Uganda. Journal of Development Studies 50 (2), 319–341.

41
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- 35 -

enables us to assess the contribution to Korean growth of policies pursued in the base year. The contribution to growth of policies pursued in other years is evaluated by introducing the policies of the alternative year into the model in place of the base year policies and computing a new equilibrium in the presence of each. Comparison between each of the equilibria and the policy neutral equilibrium then provides the model estimates of the year's policy contributiorn to growth in the year. The effects of policies over a number of years are evaluated as the sum of the individual year's effects.

We have performed these calculations using both the 1962 and 1982 base year models; different results are obtained in each case, depending upon the choice of base year model. We also perform calculations for different types of policy evaluation, for a removal of all export subsidies, for the tax component alone and for the direct (or indirect) tax component.

# Calibration

Parameter values for the production and demand functions in the model are determined by using calibration techniques. Calibration procedures that are widely used in other applied general equilibrium models are followed (see Mansur and Whalley (1984)). The requirement for parameter values chosen in this way is that they should be capable of replicating the base year microconsistent data set as an equilibrium solution to the model, given extraneous estimates of elasticities of substitution, policy parameters, endowments and other data.
would reduce their emission intensities by 8%, 24% and 33%, respectively from the BAU case. If the carbon tax is raised to a very high rate of US$ 250/tCO2, the average emission intensity of Annex I country would drop by 46%. On the other hand, the 250/tCO2 carbon tax in Annex I countries would cause emission intensity of Non-Annex countries to increase slightly, by 2.8%. Although Annex I countries’ emission intensity would still be 1.9 times as high as that of NonAnnex I countries at 250/tCO2 carbon tax case, the gap in emission intensity between Annex I and Non-Annex I countries would drop by almost 65%.

One interesting observation is that at carbon tax rate greater than 50/tCO2, not only Annex I countries would suffer with economic losses but also non-Annex country starts exhibiting economic losses despite the fact these countries are exempted from any carbon tax. This is due to international trade effect. Although a carbon tax in Annex I countries might cause moving some emission intensive industrial production to Non-Annex countries, this substitution effect would not be able to cause a complete offset of losses in economic outputs that occurred in Annex I countries.

Table 1 presents percentage change in emission intensities in various countries and region. Countries such as Russia, Australia, United Kingdom and United States would exhibit relatively higher drop of their emission intensities, whereas France will see the lowest drop. This is because the energy system, particularly electricity generation is based on fossil fuels, such as coal in the former countries, whereas more than 80 percent of electricity is generated from nuclear power plants in France. All developing countries would experience increase in emission intensity as these countries are exempted from carbon tax. This clearly indicates the leakage in emission reduction as the carbon tax in Annex I countries would cause migration of carbon intensive industrial production to Non-Annex I countries.

An important issue is that the emission intensities of developed and developing countries move towards convergence only when the former undertake a large cut in their emissions, whereas the latter are allowed to increase their emissions. In other words, the movement towards the convergence occurs if a high carbon tax is imposed to developed countries, and developing countries are exempted from any carbon tax. However, meeting the ultimate objective of the UNFCCC - stabilizing atmospheric concentration of GHG emissions at the level that avoids climate change - would not be possible through reductions of GHG emissions from developed 9