rafmacalaba/datause-encoder-data huggingface dataset:
cyclical commodity price cycles. Furthermore, as Jensen et al (2013) found using OPIC data, the positive sign of GDP growth represents governments’ less incentive to breach contracts during economic crisis as they are concerned about the loss of reputation by breaching contracts, which creates the short-term financing difficulty during the economic crisis. This cross-country result deals with incentive effects of short-term economic cycles on governments’ action to breach contracts (which tests Hypothesis 3), and therefore, it differs from my contract-level finding (in Table 3) in which higher growth during contractual period (the median contract age is 9 years that is relatively long-term; see Table 1) appears to improve the survival rate of contracts.

Second, in column (3), the marginal effect of democracy is small and does not significantly reduce BOC risk, which is contrary to my finding in the contract-level analysis. In column (3), instead of a static measure of democracy, I include dummies of democratization (with to 1-2 year lags). It shows that BOC is likely to be triggered 1-2 years after political transition took place which is consistent with Hypothesis 4 and confirms that an adverse political transition is likely to trigger BOC events. In column (4), a dummy of fragile states appear to be insignificant.

Third, resource dependency (in aid and primary commodities) appears to be a major determinant of BOC events. If a country is largely donor dependent (i.e., aid revenue is major non-tax revenue), the government would lose an incentive to invest in building fiscal capacity (Besley and Persson, 2013). The square term of Aid/GNI is positively signed, but the linear term is negatively signed. This indicates that aid could create fiscal buffers up to a certain level, but it destroys the fiscal capacity when the country becomes a _donordarling_ (i.e., Aid/GNI ratio is above a certain threshold dependency level), leading to higher BOC risk above the threshold. In addition, the log of resource rents is also positively signed and suggests that larger natural resource dependency increases the BOC risk, which supports the resource curse story.

Finally, the average propensity of BOC events (in the past five years) is included in column (1)-(4) that is consistently positive in all specifications, which suggests a significant evidence of state dependency of BOC risk. As in the case of expropriation, BOC events tend to repeat in the same set of countries.<sup>17</sup> Columns (5)-(7) control for country and year fixed effects to check the robustness of my findings after removing unobserved heterogeneity.<sup>18</sup> As expected, the level of state dependency gets weaker (i.e., the magnitude of the average of BOC in the past 5 years gets smaller) in this specification. It also confirms my

> 17 See Eden, Kraay, and Quan (2012) for the analysis on expropriations.

> 18 Using the fixed effect model in column (6), Hausman specification test rejects the hypothesis that country-level 2 effects are adequately modeled by a random-effect model (χ7 =115.12; p-value=0.000).

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functions is not well-established in the literature, particularly at the observed, high levels of PM2.5, this should be interpreted as only suggestive evidence of a link rather than the exact magnitude of the health-pollution slope.

# **6.1 Indoor air pollution and child growth**

Panel A of Table 4 reports results with a child’s height-for-age z-score as the dependent variable and the log of the maximum particulate matter concentrations as the key variable on the right-hand side. Following the known sensitive period of growth, in columns 1 through 3 we focus on children currently under 36 months of age who would be contemporaneously impacted by the measured pollution level.<sup>9</sup> There is a clear, statistically significant link between reductions in log maximum PM2.5 and improvements in child height-for-age. Column 3, which includes individual and household level controls, suggests that a 24 percent decrease in maximum PM2.5, the observed decrease across treatment and control households with young children, relates to a 0.1 standard deviation increase in height for age (0.24*(e<sup>-0.569</sup> -1)). This effect is sizable yet smaller than the 0.3 standard deviation estimate in Table 2.

Columns 4 through 6 of Panel A repeat the analysis including all children under 76 months old who had the potential to benefit from the intervention during their sensitive period of growth. This approach requires that pollution readings captured at the follow-up wave reflect exposure across the 40-month period. The negative and statistically significant relationship between maximum PM2.5 and height-for-age persists, although the magnitude falls by approximately 40 percent. The 37 to 76month group independently has an estimate of -0.201 (p-value = 0.11), suggesting that the link between measured pollution and height-for-age is strongest for children in the sensitive growth period.

> 9 Appendix Table A6 repeats the analysis in Table 4 using the mean PM2.5 concentration rather than the maximum.

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- 36 -

The joint hypotheses "market powez, partial or no tax shifting" could not be rejected by the competing pair of joint hypotheses for either specification of the model. On the other hand, "perfect competition, no tax shifting" was rejected quite decisively by the alternative pair of joint hypotheses for the specification with materials as the num6raire input.

Since our non-nested hypothesis tests show that full short-run forward shifting of the CIT has to be rejected for the industries we examined, we know that the CIT influenced the rental prices of capital services during the sample period. It is therefore useful to determine what effect tax incentives had on the decisions of the industries we studied. But first we report in table (6) below the elasticities of the demand for labour and for materials with respect to small changes in the wage rate, the price of materials, and the rental prices of investment in physical and knowledge capital. Then, in table (7), we show the effect of the investment tax credit for physical investment on the endogenous variables of the model. Finally, in table (8), we report the effect of a small reduction in the fraction of R&D which the firms are allowed to expense.

The formulae from which all these elasticities were computed can be found in appendix (5).

|able<br>**(6)**<br>Pakistani chemical and 2harxace<br>Elasticitios of the demand for labo<br>with respoet tnQ hanges in the inout pric<br>(approximate<br>standard errors|utical<br>industries<br>ur and**for**materials<br>es. midpoint of the sample<br>in brackets)|
|---|---|
|eLV&a<br>0.761<br>eMWL<br>(0.310)|<br>0.174<br>(0.190)|
|eLW4=<br>0.781<br>eMM<br>(0.315)|=<br>-<br>0.188<br>(0.194)|
|eLRpK<br>0.00092<br>MaPK<br>(0.00551)|-<br>0.0135<br>(0.0093)|
|eLRpp<br>N-<br>0.0202<br>**Suup**<br>(0.0140)|0.00008<br>(0.00016)|

The results of table (6) show that the own-price elasticities bth have the correct negative sign. Furthermore, the elasticities of the demand for labour
Ugainda: Buy-Back of Commercial Debt 6 Table 1 Upnda: External Debt Proflile (Millions of US Dollars; As of June 30, 1992)

||DOD|o/w<br>Arrears|Debt Se<br>1991/92|rvice Due<br>1992t93|
|---|---|---|---|---|
|Multilateral|1756.8|86.3|86.9|79.6|
|World Bank<br>IMF|1067.2<br>271.1|0.0<br>0.0|18.2<br>41.7|19.3<br>22.6|
|OECD Bilaterals|278.8|80.8|45.7|25.9|
|Non-OECD Bilateral|376.9|193.2|_81.5_|35.1|
|Commercial Banks|15.5|15.1|6.2|0.3|
|Commercial Non-Bank|226.1|207.8|9.0|4.7|
|PenaltyInterest|-|-|20.0|30.0|
|Total|2654.0|53.2|249.3|175.7|

_Source: External Debt Management Office, Rank of Uganda_ creditors. Commercial creditors accounted lbr the largest proportion of arrears, about 38 percent of the total; followed by non-OECD bilaterals, 33 percent; multilateral creditors, 15 percent; and OECD bilaterals, 14 percent. Total DOD was over 122 percent of gross domestic product and the principal and interest payments necessary to service this debt, estimated at US$176 million in 1992193, implied a debt-service ratio of about 80 percent, on a commitment basis, excluding any servicing of the outstanding arrears which represented an additional 265 percent of the export of goods and non-fdctor services in 1992/93. The debt-service ratio for 1991/92 was 128 percent, largely reflecting the higher payments due to the IMF in that year.

Given the magnitude of the problem, and the gravity of the external debt situation, the Government, using resources from an ongoing World Bank technical assistance project, recruited a team of international financial advisors (S.G. Warburg & Co.) in 1990 to (i)
Policy Research Working Paper 5118

# **Abstract**

The literature shows that divorced, separated, and widowed individuals in Africa are at significantly increased risk for HIV. Using nationally representative data from 13 countries in Sub-Saharan Africa, this paper confirms that formerly married individuals are at significantly higher risk for HIV. The study goes further by examining individuals who have remarried. The results show that remarried individuals form a large portion of the population—usually larger than the divorced, separated, or widowed—and that they also have higher than average HIV prevalence. This large number of high-risk remarried individuals is an important source of vulnerability and further infection that needs to be acknowledged and taken into account in prevention strategies.

This paper—a product of the Human Development and Public Services Team, Development Research Group—is part of a larger effort in the department to understand the determinants of the HIV/AIDS epidemic. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at ddewalque@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
represented four distinct quarterly surveys that we merged together. Thus, any seasonality in wages (bonuses or raises) should be averaged out over the course of each survey.

In each survey round, workers were asked the number of hours they had worked over the past seven days. By contrast, the measures of earnings varied from year to year,<sup>4</sup> so to construct our measure of hourly wages:

- In 2003, workers were asked monthly earnings from their main activity in the past year. We calculate each worker’s average hourly earnings by dividing this amount by the hours worked in the past week multiplied by 4.33 (the average number of weeks in a month, across the year).

- In 2005, 2010 and 2013, workers were asked about earnings from the previous week in their primary job, so we divide this by the hours worked in the past week.

- In 2015 and 2016, workers were asked take home earnings for the past one month. We calculate average hourly earnings by dividing this amount by the hours worked in the past week multiplied by 4.33.

In each round, earnings were asked to paid employees: both regular wage workers and well as casual/piece rate workers. While, prior to 2013, self-employed workers were asked about their earnings, for consistency over our period of study, we restrict our sample to paid employees. We deflate all wages to 2010 taka using the consumer price index.<sup>5</sup> There may be differences in the wages calculated across the different survey rounds. The fact that the 2003 survey asked about monthly earnings over the past year presumably means that respondents reported their average monthly income over the year, which reduces variance between workers. Similarly, the average weekly pay over the past month in 2015 and 2016 could display lower variance than in rounds 2005-2013, when workers reported weekly pay directly. However, any level differences between years would be absorbed in the year fixed effects in the regression

> 4Because these different measurements may have different amounts of noise, it is possible that estimation results are affected by heteroskedasticity. Following the recommendation of Ferman and Pinto (2019) on differences-indifferences settings with few treated and many control groups in the presence of heteroskedasticity, we reestimate treatment effects using FGLS in Table A2. Results are very similar to our main estimates, providing reassurance that those main estimates are not significantly affected by heteroskedasticity.

> 5 `https://ycharts.com/indicators/bangladesh_consumer_price_index_wdi`

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# **Community Managed Forest Groups and Preferences for REDD+ Contract Attributes: A Choice Experiment Survey of Communities in Nepal**

Sahan T. M. Dissanayake*, Prakash Jha, Bhim Adhikari, Rajesh Bista, Randall Bluffstone, Harisharan Luintel, Peter Martinsson, Naya Sharma Paudel, E. Somanathan, Michael Toman

**Keywords:** REDD+, Community Forestry, Nepal, Choice Experiment, Interaction Terms

**JEL Codes:** Q23, Q51, 013

*Corresponding author: Sahan T. M. Dissanayake, Department of Economics, Colby College, Diamond, 3rd floor 5230 Mayflower Hill Waterville, ME 04901-8852. <u>sdissan2@gmail.com</u>
ephemeral river lengths, river basin area, river basin elevation, river gradients, and river gradient-year interaction terms.

# _IV. COST-BENEFIT ANALYSIS_

We now use our estimated coefficients to provide a cost-benefit analysis of large and small dams. Unfortunately, we do not have explicit information on the costs of construction of the dams in our database. However, Alexander and van Wyk (2005) provide estimates of costs for nine dams in South Africa according to their height and capacity, and we use these data to infer the costs of dams in our sample. More specifically, we regress their unit costs in terms of dollar per cubic meter of capacity on dam height and find the following relationship: where both coefficients are significant at the 1 percent level. Using the mean values of the capacity and height of small and large dams from our sample as given in table 1, these estimated coefficients suggest that large and small dams have average unit costs of $0.12/m<sup>3</sup> and $0.35/m<sup>3</sup> and average total costs of $15,123,640 and $124,531, respectively.

To determine the average total benefits of our large and small irrigation dams, we need both an indicator of their average annual benefit to agricultural production and their average life span. The annual benefits can be derived from our estimated coefficients and the fact that one unit of NPP roughly translates into 1 kilocalorie of food. Conveniently, the units of the annual NPP measure (gC/m<sup>2</sup> /year) can be roughly converted into kilocalories and, hence, to their nutritional value if the crop involves food products. That 40
understated. However, one measure suggests that the data are not far from reality. The program to replace or repair housing made payments totaling $2,500 per household, almost exactly the same average amount as the grants reported by wage workers. SME owners reported grants averaging around $1,600.

Perhaps the most interesting aspect of the reported aid is the lack of correlation between reported losses and reported grants and loans. For SME owners, where we are able to separate business from household aid, the correlation between the reported loss of household assets and the grants (loans) received is 0.70 (0.27). For business assets, on the other hand, there is essentially no correlation between the reported losses and the (very small level of) grants received; the correlation between losses of business assets and loans to replace those assets is 0.16. For wage workers, the correlation between grants and household losses is 0.31. Finally, for microenterprise owners, there is no correlation between the level of losses on the one hand and grants or loans on the other. So while overall aid flows into Sri Lanka following the tsunami were large, and while at least some aid there flowed directly to households suffering losses, the data suggest that targeting is particularly poor with regard to damage suffered by business owners.

# _Enterprise recovery_

Given the lack of insurance and low aid flows, we find it surprising that owners report the majority of damaged assets had been replaced or repaired by the summer of 2007. Households report having replaced 60% of lost assets, while SME and microenterprise owners report having replaced more than two-thirds of their assets. By April 2008, 75 percent of microenterprise owners reported having replaced all of the housing assets damaged by the tsunami. Where did they obtain funds to repair or replace damaged assets? The survey data allow us to provide some insight on this question, and to say something about the speed of recovery, with regard to the microenterprises.

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Timber certification is expected to have most of its impact at the retail trade level, where the final consumer can directly exert their influence. So far, several retailers in Europe and the US have shown interest in timber certification. The tropical timber that goes to final consumption and it is "visible" by the consumer is estimated to be around 50-60% for Europe." While there are no firm estimates available, the authors' discussions with NGOs, wholesalers, retailers and market exporters involved in the certification effort indicated that between 10-20% of the timber in the European tropical timber market will potentially be affected by certification, while certification is likely to affect between 5-10% of the US tropical timber market. In short, the "niche" market for which TC may become a major factor in influencing consumer decisions is only a small part of the total market for tropical wood in developed economies.

# **b) The size and the distribution of the "green premium"**

Price increases either due to excess demand or due to certification cost recovery will be limited by the possibilities of substitution between tropical and other timbers or materials. However, price increases due to certification will be more prevalent in the "niche" market segments described earlier. The final impact on producer revenue will depend on relevant priceelasticities for these products and on the shift in demand for certified wood. For our calculations we consider the case of "green premium" as described in Annex 1. More specifically the "green premium" is assumed to be the difference between the price of the certified good and the price of the same good prior to the adoption of certification.

Some advocates of certification, however, claim that the main impact of certification will not be brought about through increased prices paid by the consumer. Rather, they argue that the consumer will pay the same price for certified timber; this will come about due to the introduction of improved inventory tracking systems under certification, enabling retailers to bypass a number of intermediaries in the trade, and buy more directly from the producer"<sup>6</sup> . A larger share of the incremental revenue available would therefore be captured by the producer, as a result of reduced trade intermediation.'<sup>7</sup> This could provide a greater incentive than a price increase on the final product (which would have been captured by wholesalers and/or retailers). However, further analysis is needed for a proper evaluation of these claims.

> **1**<sup>**5**</sup> **See** FAO (1991) study on high-value markets for tropical sawnwood, plywood and **veneer** in the European Community. **1'This** has **already happened** in one **retail storm** in the US which has actually cut the price of timber products made from certified **timber because** it is **buying direct from the producer.**

> **'**<sup>**7**</sup> **The** reduced **trade** intermediation **will** result in lower **production cost that** will shift the supply curve for certified timber to the right.

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investments, and employment compensation and retraining for those most affected, such as workers in a coal-mining community.<sup>45</sup> The distributional analysis in Section 4.4 above considered the case of cash transfers benefitting a wide segment of the population (70 percent), not just the poor. The reason is that it may be counterproductive to shift all revenues to the poorest quintile, as the support of the middle class could be critical. Broad-based and adequate compensation methods are necessary: if benefits are diffuse, it can be much harder to identify and manage the political coalition needed for reforms (Clements et al. 2013; Inchauste and Victor, 2017). Moreover, it can minimize the public discontent of a few which could very well lead to the reversal of reforms (Moerenhout, 2017). Specifically, under revenue recycling ‘mode’ (a) in Figures 8 and 9, proportional redistribution of climate mitigation policy revenues to the poorest 70 percent of households may help increase reform acceptability. Of course, the broader coverage should be re-assessed over the years, given the limited fiscal resources and the 50-50 share between cash transfers and infrastructure investment (‘mode’ (c)) is context-specific: other economies with a more urgent need for basic infrastructure, including for adaptation, may prefer to shift more into public investment.<sup>46</sup> Most economies in the region have some form of fossil fuel subsidy, though they have been slowly moving away from such subsidies towards better-targeted cash transfers out of necessity, given tight post-pandemic fiscal space (see World Bank, 2022a, Table 1.1). Still, explicit fossil fuel subsidies in 2021 averaged 0.8 percent of GDP in South Asia, varying widely (from insignificant amounts in Nepal, to 2.5 percent of GDP in Pakistan - see Figure 14). What is more, universal price subsidies for fossil fuels are typically untargeted and benefit wealthy households in absolute terms, which is associated with weak redistributive outcomes (see Clements et al., 2013; Abdallah et al., 2015; Coady et al., 2015).

> 45 Recent empirical work by Hille et al. (forthcoming) explores the employment effects of various policies such as a fossil fuel subsidy phaseout. They find that the net employment effects are small but positive. However, having the ex-ante knowledge of these quantitative effects can facilitate compensatory actions for workers. Vagliasindi (2013) also discusses in-depth experiences in various countries, including India, in eliminating fossil fuel subsidies.

> 46 South Asia is highly exposed to climate-related extreme events. According to the Global Climate Risk Index and the IMF Climate Change Dashboard, most economies in the region are ranked as the most climate-vulnerable globally (Germanwatch, 2021). The frequency and severity of climate impacts have intensified and are projected to worsen, due to gradual global warming - South Asia will see hotter weather, longer monsoon seasons, and increased droughts in upcoming decades (IPCC, 2018).

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