rafmacalaba/datause-encoder-data huggingface dataset:
_18_

## Table I

# Welfare Coet et Ase _VEt_ _wdr CM ( 1964 billies)

|ColIumn|Total<br> <br>Costs<br>C<br>18(2+B)|Rent<br>ots<br>2|1ie'1ortio<br>!ts<br>t<br>_/_<br>a|EnployF<br>nt<br>n Chont n<br>Autos $ 4|
|---|---|---|---|---|
|1 Low Elasticity<br>_3/_|6.92<br>7.71|(88.9)|<br>1.21|-22.6|
|2. Central<br>Elasticity|9.92<br>7.80|(82.5)|<br>2.02|-U6.2|
|3. High Elasticity<br>_S/_|10.84<br>7.88|(82.2)|<br>8.01|-84.1|
|4. Central<br>Elasticity<br>with US capturing<br>come rents|10.26<br>7.77|(87.1)|2.51|-40.9|
|5. Central<br>Elasticity<br>with<br>US capturing<br>some rents<br>and xog<br>onous wage<br>distortions|10.01<br>7.77|(87.1)|<br>2.31|-40.9|
|6. Central<br>Elasticity<br>with<br>US capturing<br>some rents,<br>-xogenous<br>wage distortions<br>and *ndogonous<br>terms of<br>trade|7.27<br>7.77|(87.1)|<br>-0.60|-80.7|

Distortion costs are calculated as the dilfference betwen totel costs and rent costs.

/ Thousand san _years._ _2/_ Low (high) elasticity estimated are obtained by lowertng (increasing) central elasticity values by one standard deviation.
Table A11: Effect size balance of observations included in the tax record and firm survey samples

||Panel A: Tax|record samp|le (party level)|Panel B: Fir|m survey sam|ple (frm level)|
|---|---|---|---|---|---|---|
||(1)<br>Likelihood<br>of pre-trial<br>completion|(2)<br>Duration of<br>pre-trial<br>hearings (in|<br>(3)<br>Intention to<br>appeal|<br>(4)<br>Share of<br>frm’s cases<br>done in 4|(5)<br>Average<br>duration of<br>frm’s cases|(6)<br>Share of<br>frm’s cases<br>with|
||in 4 months|days)||months||intention to<br>appeal|
|In tax record sample|-0.024|15.324|0.023||||
||(0.019)|(5.533)|(0.021)||||
|Entered after decree|0.139|-74.014|0.037||||
|application|(0.025)|(6.730)|(0.027)||||
|In tax record sample|-0.028|-2.840|-0.031||||
|X Entered after|(0.026)|(7.877)|(0.040)||||
|In survey sample||||-0.021|-0.840|0.012|
|||||(0.045)|(13.310)|(0.052)|
|Case(s) after decree||||0.121|-63.338|-0.012|
|application||||(0.021)|(6.007)|(0.027)|
|In survey sample X||||0.007|9.572|0.009|
|Case(s) after||||(0.056)|(16.067)|(0.067)|
|Efect if in sample|0.112|-76.854|0.005|0.128|-53.766|-0.002|
|P-value: efect if in sample|0.001|0.000|0.886|0.015|0.000|0.969|
|Chamber FEs|Yes|Yes|Yes|Yes|Yes|Yes|
|Calendar month FEs|Yes|Yes|Yes|Yes|Yes|Yes|
|R-Squared|0.122|0.191|0.042|0.020|0.062|0.003|
|Observations|5401|5112|3093|2154|2081|1480|

<u>Notes:</u> Balance on decree effect size. Panel A: Comparing decree effect size for case parties across court-only and tax record sample; as in the tax record analysis using ANCOVA, controls include chamber fixed effects and calendar month fixed effects, and standard errors (in parentheses) are clustered at the (chamber x hearing of entry) level. Panel B: Comparing decree effect size for firms across court-only and firm survey sample; as in the firm survey analysis, we control for the number of cases the firm had; as the baseline number of employees (also controlled for in that analysis) stems from the firm survey, here we use baseline (2012) revenues (inverse hyperbolic sine transformation) to control for firm size instead; robust standard errors in parentheses. All models estimated by OLS. Significance levels are denoted as follows: * p _<_ 0.10, ** p _<_ 0.05, *** p _<_ 0.01.

65
Policy Research Working Paper 7949

# **Abstract**

This paper uses comprehensive and comparable firm-level manufacturing census data from four Sub-Saharan African countries to examine the extent, costs, and nature of within-industry resource misallocation across heterogeneous firms. The paper finds evidence of severe misallocation in which resources are diverted away from high-productivity firms toward low-productivity ones in all four countries, although the magnitude differs across countries. The paper shows that a hypothetical reallocation of resources that equalizes marginal returns across firms would increase manufacturing productivity by 31.4 percent in Côte d’Ivoire and as much as 162.7 percent in Kenya. The paper emphasizes the importance of the quality of the underlying data, by comparing the results against those from the World Bank Enterprise Surveys. The comparison finds that the survey-based results underestimate the extent of misallocation vis-a-vis the census. Finally, the paper finds that the size of existing distortions is correlated with various measures of business environment, such as lack of access to finance, corruption, and regulations.

This paper is a product of the Trade and Competitiveness Global Practice Group and the Development Research Group. 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 xcirera@worldbank.org and rfattaljaef@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 3: Details of datasets used in the current study**

|MDG|Indicator|No. countries|No. surveys|Surve<br>Average|ys per country<br>Minimum|Maximum|
|---|---|---|---|---|---|---|
|1|Stunting|53|156|2.9|2|5|
|1|Underweight|54|158|2.9|2|5|
|4|IMR|41|126|3.1|2|5|
|4|U5MR|41|125|3.0|2|5|
|4|Full immunization|60|178|3.0|2|6|
|4|Measles immunization|63|188|3.0|2|6|
|5|ANC4+|41|127|3.1|2|5|
|5|SBA|41|127|3.1|2|5|
|5|Contraceptive prevalence|38|87|2.3|2|4|
|6|Condom use in risky intercourse|15|32|2.1|2|3|
|6|HIV prevalence|9|18|2.0|2|2|
|6|Malaria nets (children)|23|54|2.3|2|3|
||Average|40|115|2.7|2|4.5|

Source: Authors’ calculations from original DHS and MICS datasets.

22
# **Table 6: Union & Nonunion Hourly Wages** _(1989 pesos)_ **by Region**

||North|Region<br>Other|Total|
|---|---|---|---|
|Union|4,352|3,996_*_|4,065_*_|
|Nonunion|4,068 t|3,036|3,283|
|Total|4,137t|3,321|3,506|

Source: INEGI (1989) Notes: t indicates statistical different at the 99% level from 'other' region. * indicates statistical different at the 99% level from nonunion sector.

Hourly wages examined only by region show a considerable hourly wage advantage in the northern states, as previously noted (Table 3). Hourly wages examined only by union status, when not accouting for differences in worker quality, reveal a considerable wage advantage for union members. However, when hourly wages are examined by both union status and region, there is a revealing disparity. The mean hourly wage level in the northern region between the union and nonunion sector is only 6.98 percent, which, when controlled for endowment differences between the two sectors, amounts to the aforementioned -2.1 percent union wage gap. In the rest of the country, the mean wage rate difference between the two sectors is 31.6 percent or a much greater wage gap of 14.1 percent, when accounting for worker differences. This evidence seems to further substantiate the weaker position of unions in the northern region vis-i-vis the rest of the country. This assertion is further supported by the ob. erved -2.3 percent probability of union membership in northern states found in the above union status logit analysis. This evidence suggests that Mexican labor in the northern states is less likely to organize and when organized is weaker in comparison to organized labor in the rest of the country.

26
grosser measures such as growth of exports relative to firms outside of the cluster but in the same sector.<sup>17</sup> However, some insights can be obtained about whether some recent success stories in Asia conform to the contours of the new industrial policy. We consider in detail the evolution of the Indian software sector centered in Bangalore. The development of the software sector was attributable primarily to activities of private actors. Its success reflected a complex set of interactions between domestic and foreign responses to perceived opportunities. Many of the same patterns, with different details, can be documented for other success stories such as the Hsinchu Science Park in Taiwan (Saxenian 1999, 2001), the Special Economic Zones in China (Rosen, 1999, Huang, 2002), and Bangladesh’s rise as a clothing exporter (Rhee, 2000). In the Indian software sector and the Bangladeshi garment sector, the initiating force was private, the government playing almost no role except for the fundamental one in India of providing good education, a policy that does not fall into the domain of selective industrial policy.

In Taiwan (China) the establishment of a science park and legislation in China to allow special economic zones to attract FDI were due to an initial government stimulus. A critical input for the success was foreign participation that dealt with some of the roles cited above as requisites of industrial policy (source of new technology, facilitation of learning, source of new product ideas, centralized marketing allowing economies of scope, and coordination of entry of complementary firms). In China, the SEZs mimicked the effect that would have arisen from a free trade policy, i.e., it negated previous adverse public policies. It did not discriminate among sectors. The decision to foster a science park by Taiwan (China) comes closer to a proactive industrial policy. Unfortunately, the experience at Hsinchu has not been systematically evaluated.

Many nations have attempted to use export-processing zones of one form or another to catalyze foreign direct investment and perhaps generate agglomeration economies. Evaluation of these suggests that while potentially a useful instrument, they have had indifferent results.<sup>18</sup> Success stories can be pointed to in Korea and Taiwan (China) in the 1950s and early 1960s, and of course in the special economic zones of China. But there have been more than a thousand such efforts. There are few clues in the

> 17 Humphrey and Schmitz 2002 provides an extensive survey of the empirical literature on clusters as well as a useful discussion of whether they offer a locally controlled  alternative to participation in networks.

34
by about 0.3 standard deviations. In contrast, the crime and violence index loses its significance when assuming that attritors reached higher values of the outcome distribution. Nevertheless, the effect size does not change much which makes us confident that estimated reduction is not an artifact of the data selection.

In addition, we address potential attrition bias by re‐weighting observations based on their likelihood to be included in the final sample. Control group participants that were reached during the phone survey had an 82 percent likelihood to be reached for the final survey, while control group participants that were not reached during the phone survey had only a 46 percent likelihood to be reached for the final survey. Likelihoods to be reached in the final survey differ similarly for the treatment group. We thus attach sampling weights to all observations based on the inverse likelihood to be successfully interviewed for the final survey. Results are reported in Tables A2.3 to A2.6.

All intention‐to‐treat estimates proof robust to our re‐weighing exercise. The weighted regressions confirm a positive average effect on the savings, investment and debt index, a negative effect on the likelihood to be vulnerable to crime and violence, and a positive effect on the list experiment on cattle raiding.

Turning to results that distinguish between “training and grant” and “training, but no grant” largely confirm our main results. Our main results show positive effects on consumption and savings for participants that received training and grant, and this finding is confirmed in the weighted regressions. What is more, the weighted regressions confirm our positive finding on the effect of grant and training on psychological well‐being. For participants that only received the training, but not the grant, we can also confirm that estimates on trust, on crime and violence and on the list experiment regarding aggressive arguments show a weakly significant negative effect.

# 6. Conclusion

Our study used the example of the unplanned cancellation of the South Sudan Youth Business Start‐ Up Grant Program to evaluate the impacts of interventions that fail to be implemented as planned. Overall, our results suggest that the impact of failed interventions is mixed and depends on the gender of participants and their ex post treatment status. In this instance, on average across all participants, the intervention was largely ineffective. Most socio‐economic or psychological and behavioral indicators neither worsened nor improved.

However, when considering ex post treatment groups and gender, some groups were detrimentally affected by the intervention. In particular, female participants that had expected to receive the cash grant but did not due to the cancellation of the program showed a strong reduction in their trust level. We also found some evidence that these women were less likely to migrate. Given that large shares of 18
participation, the data on WTO disputes over the 1995-2008 period reveal three interesting patterns. First, the data show a steady trend of WTO self-enforcement actions undertaken by developing countries throughout the WTO era, in strong contrast to the declining trend of self-enforcement actions undertaken by the developed countries over the same period. Second, while we show developing countries to be interested in enforcing the WTO commitments of their rich (especially U.S. and EC) trading partners, they are also increasingly interested in enforcing the WTO commitments of other developing countries. Finally, the data show that developing countries focus their self-enforcement actions on types of WTO violations that are more directly observable to exporting firms and their government policymaker representatives, especially antidumping. While some of this can be attributed to the global proliferation in this particular form of import protection, the pattern may also reflect the higher cost of identifying other types of violations that may also result in loss of market access, such as illegal subsidies to competing products and domestic regulatory barriers.

Many developing countries point to the high cost of self-enforcement, and several have proposed that the WTO should bear all costs associated with the efforts of developing countries to enforce their market access rights. In recognition of the need for this type of assistance, a group of nations established the Advisory Centre on WTO Law (ACWL) in 2001 to help overcome one particular obstacle to developing country use of WTO dispute settlement – the high cost of litigation. The second half of the paper analyzes how the availability of ACWL assistance has affected the WTO enforcement efforts of developing countries. The paper thus contributes to a growing literature that examines the obstacles confronting developing countries as they use WTO dispute settlement to self-enforce the market-access commitments of their trading partners.<sup>1</sup>

> 1  Scholars who have studied WTO enforcement efforts of developing countries include economists, political scientists, and legal scholars, e.g., Bown (2005), Bown and Hoekman (2005, 2008), Horn, Mavroidis and Nordström (2005), Shaffer (2003, 2006), Nordström and Shaffer (2008), Busch and Reinhardt (2003), Busch, Reinhardt and Shaffer (2008), and Davis and Bermeo (forthcoming). See Bown (forthcoming) for a synthesis of the literature from an economic perspective.

3
16 <!-- Start of picture text --> DISPOSABLE INCOME COPONENTS.<br>(in 1980 pesos as % of GDP)<br>0-<br>-0.02<br>-0.04<br>~-0.06<br>X-00<br>-0.14<br>1980 19Bt 1982 1983191841915 1986 1987 19188 1989 1990<br>y~.<br>r-T- - i- -NFS<br><!-- End of picture text --> <!-- Start of picture text --> Figure 4 b)<br><!-- End of picture text --> <!-- Start of picture text --> INFLATION-ORIVEN DOMESTIC TRANSFERS<br>(in 1980 pesos as % of GDP)<br>0.Z5.<br>0.15<br>0.05<br>0<br>198019811982 198319841985 9881987198819891990<br>Do_s_k ODbi -Cl hkln Tax<br><!-- End of picture text --> Figure 5
Historians have almost always used statistics to assess and explain government policy toward the poor; i.e. the supply of relief. Higher pauper rates and expenditures on relief have, therefore, been taken to indicate less restricted relief practice and hence a better safety net for the poor. However, recent innovative work by Joan Hannon (1984b, 1986) on New York State and by Mary Mackinnon (1984, 1986) on England suggests that pauper rates can be used to get a measure of poverty provided we control for differences in policy.

In both Britain and America, local autborities were legally obliged to provide some form of relief to applicants. This relief was not always generous. Indeed, and as we shall see below, it was a satter of central government concern then and now that "over generous" assistance should not encourage the poor to become a tax burden on the state or reduce individual incentives to work and save. In both countries, the workhouse or poorhouse test was used to diminish this risk. Certain classes of paupers were often only offered relief inside the workhouse. It was hoped that the unpleasant conditions of the workhouse would discourage application by all but the most needy. Hannon and MacKinnon suggest that the proportion of paupers relieved inside the workhouse or poorhouse is a good proxy for the harshness of this aspect of government policy.

Figure 5 (taken from PP, 1900, X, Appendix II, pp.10-11 and 22-23, and PP, 1904, VXXXII) tests the claim that pauper statistics can be used to proxy poverty. It uses a survey made at 28 places in England in 1899 of incomes of people over age 65. The horizontal axis shows the proportion of old people who had incomes under lOs a week among those who's incomes are known. The vertical axis shows the proportion of old people surveyed who were or had been on 39
Thus far the paper has used waves 1 and 6 of the survey. This section will exploit the four waves that lie in between. In what follows it is useful to bear in mind that consumption was measured comparably within waves 1, 5 and 6 and within waves 2, 3 and 4 – but not between these two groups of waves.<sup>26</sup> As our left hand side variable is consumption growth, a first set of concerns relate to whether migrants start out from similar consumption positions at baseline (compared to non-migrants) and whether, prior to migration, they are following a similar growth path. We can test this by regressing baseline consumption on future migration status (Mi,2010) and use baseline village fixed effects (θv) and control for the initial household characteristics (wj) used in Equation 6 (and listed in Table 5): In the first column of Table 11, Yi is the natural logarithm of the consumption level at baseline. The insignificance of the future migration coefficient shows that our extensive controls manage to capture all heterogeneity with respect to baseline startoff levels: migrants started off at the same position as non-migrants, _ceteris paribus_ .

We then append the right-hand side of Equation (7) with (logged) consumption at the baseline. The second column of Table 11 exploits information on consumption growth between rounds 2, 3 and 4 (1992-1994) to ask whether growth across those three rounds can be explained by future migration status. We find that it cannot: migrants and non-migrants were on the same growth curve prior to migration, given our controls.

# _[Table 11 here]_

Finally, we exclude that there are any time invariant traits of migrants and nonmigrants, such as risk preferences, that are jointly determining their migration decision and the respective roles they take on in the insurance arrangement. This test exploits the fact that some migrants migrated after we observe them in 2004. We

> 26 The primary concern is the difference in recall period. Beegle et al. (2012) look at how differential recall periods affect consumption aggregates, using data from a survey experiment conducted in Tanzania.

23
shocks. Plugging into (6) yields

**Exclusion restriction and threats to identification** Our exclusion restriction therefore postulates that gold prices affect poaching through ivory prices only, i.e. not through the unobserved ivory supply shocks _εsct_ . We next discuss the plausibility of such assumption.

First, the economic rationale for the instrument – the Hotelling condition – holds only when storage levels are almost always positive. This condition is sufficient, but not necessary for the instrument to be relevant. We nonetheless find evidence of ivory prices being a unit root process (see below), which is consistent with prices being governed by the Hotelling condition. However, we also do not require the Hotelling condition to hold in the entire sample. If storage levels are positive in only a subset of the sample, the instrument would be relevant in that subsample. Ultimately, the strength of the first stage provides an assessment of the instrument’s relevance.

Next, we need to address the possibility that shocks to gold markets _zt_ affect poachers’ incentives through channels other than ivory prices. Interest rates and global demand can indeed be correlated with the world economic conditions in general and local economic growth and social stability in particular, thereby affecting agents’ opportunity cost of poaching. We address this issue by controlling for GDP growth and a measure of conflicts in our regressions. More specifically, if a surge in the price of gold and other minerals increases labor demand in mining, that would create a shortage of would-be poachers. To look into this possibility, we use data on the locations of mining extraction from Berman et al. (2017) and find that the geographical overlap between the elephant range and mines is negligible. There is only one poaching site in our data with active mining, located in South Africa (see Figure A1 in the online Appendix). Our estimates are robust to dropping that single site; results and additional details available upon request. Finally, while world interest rates could also affect ivory markets through other factors such as shipping costs or the demand for ivory, the transmission mechanism to poachers would still be through ivory prices they receive.

Finally, a prediction of the storage model is that prices are not stationary. However, nonstationarity of the instrument and the variables being instrumented is not a challenge to the estimation strategy as discussed in Phillips and Hansen (1990). We test for the stationarity of the price data using the Dickey-Fuller test with time trends. The null hypothesis of a random walk cannot be rejected. Robustness checks using Phillips-Perron tests yield similar 9