rafmacalaba/datause-encoder-data huggingface dataset:
averages of water and sanitation with a dummy variable for households with both types of infrastructure (column three). As indicated, for those who have both a secure water supply and good sanitation, the nutrition of children improves with the average level of infrastructure access within the neighborhood. As we also include the average consumption of the neighborhood, this impact of infrastructure is distinct from the overall effect (not significant) of being in a well off neighborhood.7 Similarly, the rural regression in column four of table 4 interacts the neighborhood infrastructure with a dummy variable for those who do _not_ have access to either type of infrastructure within their own home. As with column two, this specification confirms that the infrastructure of neighbors affects those rural households who have neither assured water or sanitation in their homes.

Nhile we are able to distinguish the impact of neighborhood infrastructure according to the level of the most common household infrastructure provision, we cannot repeat this for all possible combinations. The share of the urban population with neither sanitation nor good water is too small to run a regression with that sub-sample. Similarly, too few rural residents have both types of infrastructure to run a rural regression analogous to the urban regression in column three.' We explore one further variation of the initial specification. Columns 5 and 6 of table 4 indicate the results of explicitly distinguishing the role of sanitation and of water supply. As mentioned, this differs a bit from the question of whether the impact of 6. We also explored whether the impact of the education of other women in the conmunity differs according to the level of the education of women in the household. The coefficient for the interaction (not illustrated here) was not significant.

7. This specification includes the fMll urban sample. Since the other coefficients in common with the restricted sample regression (colurn one in table 4) differ little in magnitude from the results in columnn one this provides some assurance that selectivity does not affect the results.

8. However, we are able to explore the sensitivity of the results in table 4 by seeing if the results change is we reclassify the infrastructure variables. For example, if we redefine the categories of rural infrastructure into having i) either no infrastructure in the household or only sanitation water, ii) having only water or iii) having both water and sanitation. As indicated in table 2, this involves shifting 41 households. Estimating this model (not reported in table 4) has the effect of reducing the coefficient of having one type of infrastructure [that is, water] by 10% in a regression analogous to that in column 2. As the standard error increases by 4%, the coefficient becomes statistically significant at only the 10% level. However, the impact of the percentage of the commnunity members with both types remains unaffected.

_15_
continued to be based on crude aggregates of around 25 products chosen for tractability and consistency with production and consumption data that are generally available only at much higher degrees of aggregation. In this study, we use the broad approach to aggregation developed by Bach and Martin (2001) to deal with the problem of aggregation when protection rates vary substantially within the groups used in the analysis. Under this approach, we form distinct aggregates for both expenditure on goods, and for tariff revenues, distinguishing, following Anderson (2009), between quantity aggregates at domestic and international prices.

Before applying the approach, we first consider its implications using a simple, graphical approach. We show that the use of optimal aggregators has two important implications. Within each aggregate group used, the marginal impact of a tariff reduction on expenditures will be greater than its marginal impact on tariff revenues, since each reduction in tariffs increases the volume of imports on which tariffs are collected. This difference allows us to capture true welfare gains that are omitted when using traditional trade-weighted averages, and which decline as liberalization proceeds. However, as tariffs decline, rising weights on tariffs that have experienced large tariff reductions increase the weights on reductions in these tariffs. This qualitative analysis raises a question that we address in the analysis—of whether optimal aggregators have a larger impact when considering complete tariff liberalization, or in the initial stages of liberalization.

To provide an answer to the questions posed, we apply the technique, using detailed tariff information provided by the MAcMapHS6v2.1 database, in a modified version of the LINKAGE global general equilibrium model, taking into account the nested structure of import demand in that model. Using this aggregation procedure with a conservative estimate of the elasticity of substitution between six-digit tariff lines results in a substantial increase— close to a doubling—in the estimated welfare gains from complete liberalization of global trade barriers both for aggregate country groups and for most individual countries. The impact is not the same across countries, with some of the exceptions providing very important insights. Perhaps the most interesting exception is Chile, where the low variability of tariffs means conventional aggregation causes little understatement of the welfare gains from own-liberalization, while picking up stronger adverse impacts from tariff preference erosion in markets subject to free trade agreements. Comparison of our results with the latest available estimates of the implications of allowing for extensive-margin growth suggests that using optimal aggregators is likely to be in the same order of magnitude of importance as accounting for the effects of extensive-margin growth in the range of varieties 26
**Table 3.  Intermediate Indicators of Empowerment: Market Domain**

||**Sub-domain: Credit**||
|---|---|---|
|**Presence of rules (institutions)**|**Enactment of rules (institutions)**|**Existing data**<br>**sources/indices**|
|_Formal_<br>•Number of laws/acts supporting pro-<br>poor credit rules<br>•Existence of regulatory framework<br>for credit and savings provision|_Formal_<br>•Number of formal transparency and accountability<br>mechanisms and procedures for credit provision<br>agencies<br>•Number of reported cases of corrupt practices within<br>credit provision agencies per year as percentage of<br>total transactions<br>Informal (cultural)<br>•Percentage of informal credit sources providing<br>credit with exploitative terms and conditions<br>•Percentage of women accessing formal credit<br>sources per year<br>•Percentage of women accessing informal credit<br>sources per year<br>•Percentage of ethnic/religious minorities accessing<br>informal credit sources per year<br>•Percentage of ethnic/religious minorities accessing<br>formal credit sources per year<br>•Percentage of women controlling use of credit within<br>household<br>**Sub-domain: Labor**|There are no pre-existing data<br>sources for data in the credit<br>sub-domain. Data must be<br>collected using the national<br>survey or in-depth research<br>techniques.|
|**Presence of rules (institutions)**|**Enactment of rules (institutions)**|**Existing data**<br>**sources/indices**|
|_Formal_<br>•Number of international instruments<br>and conventions on Core Labor<br>Standards, the rights of the child, and<br>the right to work (full employment,<br>choice and conditions of work)<br>ratified (1, 2, 3)<br>•Number of laws/acts supporting pro-<br>poor labor shifts in labor market<br>segmentation<br>•Number of regulatory reforms for<br>economic participation over<br>preceding two years<br>•Legislation exists to ensure equal|_Formal_<br>•Total number of cases filed against employers for<br>non-compliance with core labor standards per year<br>•Number of cases filed by the state against employers<br>for non-compliance with core labor standards per<br>year<br>•Percentage of employers complying fully with state<br>regulations as percentage of total number of<br>employers<br>_Informal (cultural)_<br>•Percentage of women able to choose their<br>employment options<br>•Percentage of ethnic/religious minorities able to|(1) International Labour<br>Organisation<br>(2) Office of the UN High<br>Commissioner for Human<br>Rights<br>(3) World Bank Country Policy<br>and Institutional<br>Assessment<br>(4) US State Department –<br>Country Reports on Human<br>Rights Practices<br>Where no data source is<br>identified, data must be<br>ll<br>d<br>i<br>h<br>i<br>l|

69
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- 18 -

Table 4: Analysis of Revised Willingness-to-pay<sup>Bids</sup>

|Village|Public Tap|IPrivate Connection|
|---|---|---|
|EDEM<br> <br>|||
|PERCENTAGE<br>OF BIDS REVISED<br>PERCENT<br>REVISE**D**OWN<br>PERCENT<br>REVISED<br>UP<br> <br> <br>|23<br>79<br>29<br>|33<br>65<br>35<br>|
|MEAN PERCENTAGE<br>REDUCTION<br>OF<br>DOWNWARD<br>REVISED<br>BIDS|68|63|
|EKWEGBE<br> <br>|||
|PERCENTAGE<br>OFBIDS REVISED<br>PERCENT<br>REVISE**D**OWN<br>PERCENT<br>REVISED<br>UP<br>MEAN PERCENTAGE<br>REDUCTION<br>OF<br>DOWNWARD<br>REVISED<br>BIDS|7<br>50<br>50<br>80|9<br>0<br>100<br>n/a|
|UMUNKO<br> <br>|||
|PERCENTAGE<br>OFBIDS REVISED<br>PERCENT<br>REVISE**D**OWN<br>PERCENT<br>REVISED<br>UP<br>MEAN PERCENTAG**E**<br>R DUCTION<br>OF<br>DOWNWARD<br>REVISED<br>BIDS|16<br>73<br>27<br>53|1i<br>82<br>18<br>57|

Figure 11 <!-- Start of picture text --> REASONS RESPONDENTS PAY ifERSUS<br>WTP BIDS GIVEN FOR IMPROVED SYSTEM<br>60-<br>P 0-<br>C 30 1A<br>sDES EKWUSUZ UNUNKD<br>_ NAOWAL n oUon AmoUWri?E Iovnnsnr<br>0131 PLO OY o<br><!-- End of picture text -->
the minimum wage (11.99 percent), and forcefully suggests that the price index used to index wage contracts this year is the change in the minimum wage. Note also that there are no distortions associated with the rate of inflation. Quite surprisingly, we find very little zero wage changes, but the -1 bin shows a small spike. This concentration of tiny wage cuts is suggestive of measurement error.

We move next to the low-inflation years. Panel A of figure 3 shows the wage change distribution in Uruguay in 2000-2001, when inflation is at its low for the period (4.35 percent). The most striking feature with respect to the high-inflation year is the growth in the spike at zero, which now accounts for almost 25 percent of the wage change observations. As before, there is some concentration of observations around the rate of inflation, but to a much lesser extent than in 1997-1998. Panel B of figure 3 shows the 1999-2000 histogram in Brazil. As before, the change in the minimum wage is associated with a large spike, amounting to 14 percent of the wage changes. The novelty is that there appears to be a second distortion in the positive wage change range, this time associated with the rate of inflation. This could indicate that as inflation comes down, some agents start indexing their wages to expected inflation.

In sum, visual inspection of the wage change histograms suggests an important presence of downward rigidities and indexation in both countries in all years. However, obtaining precise measures of downward wage rigidities is complicated because of the presence of measurement error in the data and the existence of different focal points for wage indexation. The next section presents a model that deals with these two features and provides us with clean measures of DNWR and the extent of wage indexation.

# 3 Methodology

There are different approaches in the literature to estimating rigidities from individual worker data.<sup>4</sup> Focusing on job stayers between two consecutive years, a number of studies draw inferences about rigidities based on asymmetries in the wage change distribution (see, e.g., Card and Hyslop (1997) and Dickens et al. (2007)). A second group of estimates

> 4 Using industry data, Holden and Wulfsberg (2009) and Holden and Wulfsberg (2008) study the incidence of DRWR and DNWR, respectively, in developed countries.

10
- Jeuland, M. A. and S. Pattanayak. 2012. “Benefits and Costs of Improved Cookstoves: Assessing the Implications of Variability in Health, Forest and Climate Impacts.” _PloS one,_ 7 **,** e30338.

- Johnson, M, R. Edwards, A. Ghilardi, V. Berrueta, D. Gillen, C.S. Frenk, O Masera. 2009. “Quantification of Carbon Savings from Improved Biomass Cookstove Projects.” _Environmental Science & Technology,_ 43: 2456-2462.

- Jones, D. 1988. “Some Simple Economics of Improved Cookstove Programs in Developing Countries.” _Resources and Energy_ , 10: 247-264.

- Kaimowitz, D., Angelsen, A. (1998). _Economic models of tropical deforestation: A review_ . Center for International Forestry Research (CIFOR), Bogor, Indonesia.

- Lewis, J. and S. Pattanayak. 2012. “Who Adopts Improved Fuels and Cookstoves? A Systematic Review. _Environmental Health Perspectives_ , Vol. 120: 637-644.

- MacDicken, KG, 1997. _A Guide to Monitoring Carbon Storage in Forestry and AgroForestry Projects._ Arlington, USA: Winrock International

- Manibog, F. 1984. “Improved Cooking Stoves in Developing Countries: Problems and Opportunities.” _Annual Review of Energy_ , Vol. 9: 199-227.

- Marcott, S, J. Shakun, P. Clark and A. Mix. 2013. “A Reconstruction of Regional and Global Temperature for the Past 11,300 Years,” _Science_ . Vol. 339: 1198-1201.

- Martin II, W. J., R. I. Glass, J. M. Balbus, F. S. Collins, 2011. ‘A Major Environmental Cause of Death’ _Science_ 334(6053): 180-181.

- Masera, O., Edwards, R., Arnez, C.A., Berrueta, V., Johnson, M., Bracho, L.R., RiojasRodriguez, H., Smith, K.R. 2007. Impact of Patsari improved cookstoves on indoor air quality in Michoac·n, Mexico. _Energy for Sustainable Development_ , Vol. 11:45 - 56.

- Megen Power Ltd. 2008. _Final Report: Impact Assessment of Mirt Improved Biomass Injera Stoves [sic] Commercialization in Tigray, Amhara and Oromiya National Regional States_ , Submitted to the MoARD/GTZ SUN Energy Programme, Addis Ababa.

- Mobarak, A. M., P. Dwivedi, R. Bailis, L. Hildemann and G. Miller. 2012. “Low Demand for Nontraditional Cookstove Technologies.” _PNAS_ 109: 10815-10820.

- Nepal, M, A. Nepal and K. Grimsrud, 2010. “Unbelievable but improved cookstoves are not helpful in reducing firewood demand in Nepal, _Environment and Development Economics_ , Vol. 16: 1-23.

- Pearson, TR, Brown, SL, Birdsey, RA. 2007. _Measurement guidelines for the sequestration of forest carbon._ U.S.: Northern research Station, Department of Agriculture

- Practical Action Ethiopia. _Healthy Hoods Ethiopia Fact Sheet_ , https://practicalaction.org/healthy-smoke-hoods-tool/country_data/ethiopia.pdf Accessed May 12, 2015.

- Rehfuess, E., Mehta, S., Prüss-Üstün, A. 2006.“Assessing Household Solid Fuel Use: Multiple Implications for the Millennium Development Goals, _“Environmental Health Perspectives._ Vol. 114.

24 | P a g e
|**Table A6: Impact on Other Measures o**|**f Profits and Sale**<br>Log<br>Total|**s**<br>Best<br>Month|Worst<br>Month|Recall of<br>best 2019|Recall of<br> worst 2019|Alternate<br>Index|
|---|---|---|---|---|---|---|
|**Panel A: Profits**|||||||
|Assigned to Personal Initiative|0.36***|190.7***|13.9|157.3|-2.87|0.13*|
||(0.13)|(61.3)|(10.5)|(127.0)|(36.2)|(0.070)|
|Assigned to Traditional training|0.13|38.6|6.78|2.74|-6.21|0.029|
||(0.13)|(55.9)|(9.86)|(136.4)|(35.9)|(0.066)|
|Sample Size|976|1337|1337|852|818|1337|
|Control Mean|4.5|299.0|52.0|338.7|100.5|-0.0|
|Control SD|1.4|665.9|133.4|996.4|241.6|0.9|
|p-value: PI = Trad|0.057|0.010|0.478|0.247|0.923|0.143|
|**Panel B: Sales**|||||||
|Assigned to Personal Initiative|0.40***|627.9*|134.3|1757.0*|619.0|0.20*|
||(0.12)|(352.1)|(100.6)|(1020.1)|(542.7)|(0.11)|
|Assigned to Traditional training|0.16|31.3|104.5|-896.9|-308.8|0.041|
||(0.13)|(333.2)|(96.1)|(841.4)|(470.1)|(0.089)|
|Sample Size|1043|1337|1337|852|842|1337|
|Control Mean|6.1|1956.9|505.7|1993.2|724.4|-0.0|
|Control SD|1.6|4805.3|1313.6|4797.1|1854.5|0.9|
|p-value: PI = Trad<br>Notes:<br>Regressions include randomization stra<br>parentheses. *, **, *** denote significa<br>**Log**denotes log of total profits or sales<br>**Best Month**and**Worst Month**are for<br>**Recall of best 2019**and**Recall of worst**<br>best and worst months of 2019.<br>**Alternate index**is an index of standard|0.035<br>ta fixed effects a<br>nce at the 10, 5,<br>in all businesses<br>profits or sales in<br>**2019**are the rec<br>ized z-scores of t|0.083<br>nd baseline<br>and 1 perce<br>in the past<br>the best an<br>all in 2021 o<br>he best and|0.765<br>of outco<br>nt levels r<br>month, co<br>d worst m<br>f their pro<br>worst m|0.056<br>me. Robust<br>espectively<br>nditional o<br>onths of 2<br>fits and sal<br>onths in bot|0.320<br>standard err<br>.<br>n operating.<br>021.<br>es in the<br>h 2021 and|0.160<br>ors in<br>2019.|

34
By contrast to China, many countries in Sub-Saharan Africa have had significant periods of exchange rate overvaluation that have hindered their export sectors and overall competitiveness. A cursory analysis of the data shows that countries with the most overvalued exchange rate have had some of the lowest growth prospects. The most well-known episode of pronounced overvaluation was in the 1987-1994 period when the CFA franc became significantly overvalued and required a strong devaluation of 50 percent in 1994 to restore equilibrium and spur exports. (Devarajan, 1997) The improved performance of the CFA franc zone during the 1997-2002 period with respect to TFP reflects the effect of devaluation on tradables as well as other structural reforms (Tahari et al, 2004). The devaluation of the franc provided a strong stimulus to investment and to exports in the region. In recent years, there has been an appreciation in the REER in the presence of a strong euro and an adverse impact on cotton producers, such as Burkina and others (Zafar, 2005, 2009).<sup>14</sup> Many countries such as Uganda, Mozambique, and Cameroon have only attained export surges due to a depreciating currency. The empirical evidence from SSA experience shows that it is rare to find a growth surge in the presence of a seriously overvalued exchange rate, with the exception of oil producing economies. In sum, is fair to say that an overvalued exchange rate in Africa have contributed to a macroeconomic environment to low returns on capital and labor.

In parallel, a related lesson from China in relation to macroeconomic and monetary management is the prevention of higher rates of inflation and exchange rate appreciation due to the large inflows of foreign exchange. How did China do this and how can Africa learn from this?

significant amount of flows are of a speculative nature as has been the case in China. Even the more rigorous use of the macroeconomic balance approach argued by Williamson and Cline relies on subjective measures and judgments on current account surpluses. Secondly, the welfare impacts of a large revaluation have not been taken into account. Thirdly, it is not mentioned that China runs trade deficits with many other Asian countries from whom it imports capital equipment and there is the widely circulated, but erroneous view, that the cause of the US current account deficit is China’s undervalued exchange rate, rather than the consumption glut in the US. If China reduces exports to US, that slack will simply be taken up by another low-cost Asian economy. Thus, for these reasons, estimates of a large undervaluation of the Chinese renmimbi need to be taken with a degree of caution.

14 In trade-weighted terms, the REER has appreciated 15 percent since the euro introduction in 1999 and is very sensitive to bilateral swings in the dollar-euro rate. Prudent monetary and fiscal policy by the regional central banks in the franc zones has acted to mitigate the extent of appreciation.

26
investigations.<sup>16</sup> The failure to find evidence of our political economic determinants affecting the WTO-challenge decision would be consistent with the theory that the WTO membership is acting rationally and not challenging cases that would either have high market access gains and/or which would could be litigated at relatively low cost, because they anticipate that dispute settlement panels would indeed show “deference” and follow Article 17.6, thus placing an extraordinarily low probability on the expectation of a successful legal outcome to the case.

We classify a U.S.-imposed trade remedy as being challenged if we can find evidence of a formal dispute being initiated under the GATT or WTO. We consider all challenges to U.S.-imposed remedies, whether the challenge concerns the investigation of dumping, subsidies, or injury, or whether it is an investigation during an administrative or sunset review. Most of the data on _which_ trade remedies were formally challenged by foreign countries through GATT/WTO dispute settlement proceedings are also available in publicly available data bases. For example, the WTO’s website has all of the data on formal disputes covering the period since 1995, as well as some antidumping and countervailing disputes that resulted in formal panel reports under the GATT period. A handful of antidumping and countervailing duty disputes that took place under the dispute settlement provisions of the Tokyo Round Codes were pieced together by examining unpublished GATT documents. The summary of these GATT/WTO challenges to U.S. trade remedies imposed over the 1992-2003 period is listed in table 2.

In the next two sections we detail the variables and data we use to represent the expected benefits and costs of our empirical investigation.

# **3.2 Expected Benefits to Initiating a Dispute**

# **3.2.1 Exporter market access benefits from a successful dispute**

What are the expected benefits to initiating a dispute against a U.S.-imposed trade remedy, and when would they be large? For the purpose of this investigation, we focus on the direct, short-term economic benefits to participating in the dispute, i.e. the improved terms of market access that would result if the U.S. removed the trade remedy in question. Thus, we expect a foreign country is more likely to initiate proceedings when it has lost a substantial amount of trade due to the U.S. remedy. Given that the imposition of many U.S. remedies has a

> 16 Formally, Article 17.6(i) states that when a WTO panel reviews the national authority’s antidumping investigation and decisions, “[i]f the establishment of the facts was proper and the evaluation was unbiased and objective, even though the panel might have reached a different conclusion, the evaluation shall not be overturned...”

10
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