rafmacalaba/datause-encoder-data huggingface dataset:
In an attempt to form an econometric foundation for our claim regarding instrumental validity, we rely first on the over-identification test results provided by the ivreg2 procedure in Stata. For instrumental validity, and thereby the inability to reject the null hypothesis of the over-identification test, the test statistic should be statistically insignificant. For our case, instrumental validity is proven (at least technically) by insignificant Hansen’s J Statistics, which are reported for all models and calculated under the assumption of heteroskedastic error terms, as shown in Table 6.. We also provide the results of relevant tests regarding the strength of our instruments. At the outset, the p-values for the Anderson Identification/IV Relevance Tests from the ivreg2 procedure in Stata support our claim regarding the adequate explanatory power of our instruments. Complementing these findings, we present the first stage regression results for the first model as an example in Table 4 in order to substantiate our assertion regarding instrumental relevance. Moreover, referring to a common threshold employed in the literature (Staiger and Stock, 1997), we consider a value of the F-statistic above 10 from the test of joint significance of the instruments in the first stage regression as necessary to conclude that our group of instruments is sufficiently strong. As indicated in Table 3, the Cragg-Donald F-statistic estimated as part of the ivreg2 procedure in Stata for the first model is 12.56 and passes our “rule-ofthumb” test. Although the F-statistics for the second and the third model are lower than 10, in the case of multiple endogenous regressors, the use of the F-statistics may not be adequate, and it is unclear whether the same threshold rule would apply (Baum et al, 2003). In this respect, the use of the Shea Partial R<sup>2</sup> , which account for the inter-correlations among the instruments, is instead recommended (Baum et al, 2003). The estimated Shea statistics for the models with multiple endogenous regressors are also reported at the bottom of columns (2) and (3) in Table 3.

# **_5.2 Regression Results_**

In Table 5, we report the IV Probit estimates. In column (1), we estimate the model with the total number of months of past migration experience. In column (2), we disaggregate this variable based on the country of the migrant’s destination. Finally, in column (3), we explore the differential impact of past migration experience before and after the year 2000. The reported coefficients are marginal effects calculated at the sample mean of all other variables. Starting in column (1), as per initial hypothesis, the impact of past migration on business ownership is positive and significant. One year increase in household past migration experience raises the

- 20 -
The Venezuelan data typically reports duties in CIF (cost, insurance, freight) terms, though on some occasions they are reported as FOB (free on board). Furthermore, the data in P_AD_DATE and F_AD_DATE is missing. Resolutions would come into effect on the date of publication, but that date was not usually listed in the files. Some notes on publication may be available on the CASS website. Also, the “DUMP” and “INJ” series are largely identical, because CASS makes both decisions simultaneously.

# **3.15 South Africa (ZAF)**

South African antidumping investigations are administered by the Trade Remedies Directorates in the Department of Trade and Industry (DTI). The outcomes of investigations are published in the International Trade Administration Commission’s reports. Data for South Africa was kindly provided by Gustav Brink and is based on Brink (2005). Holden (2002) provides an earlier analysis of South African antidumping as a reaction to trade liberalization or an anti-competitive instrument. The two articles contain descriptions of the antidumping process in South Africa, but a current summary of antidumping procedures can be found on the Department of Industry and Trade’s website.

The South African workbook contains the standard data items, as in Section 2, as well as a few additional data items described below.

**Table 3.15.1 : Additional South African Data Included in AD-ZAF-v1.0.xls**

|**Column**|**Variable Name**|**Description**|
|---|---|---|
|**In AD-Z**|**AF-Master :**||
|**U.**|**P_AD_DUTY**|The maximum (or range of) preliminary antidumping duty (duties) imposed|
|**V.**|**F_AD_DUTY**|The maximum (or range of ) final antidumping duty (duties) imposed|
|**W.**|**GP_P_Report**|The government publication reporting the outcomes of the preliminary stage|
|**X.**|**GP_F_Report**|Thegovernmentpublication reportingthe outcomes of the final stage|
|**In AD-ZA**|**F-Foreign-Firms:**||
|**D.**|**AD_MARGIN_FIRM**|The final firm-specific dumping margin(s) found|
|**E.**|**P_AD_DUTY**|The preliminary firm-specific antidumping duty imposed|
|**F.**|**F_AD_DUTY**|The final firm-specific antidumpingdutyimposed|

35
the most water scarce countries in the world with only about 120 cubic meters of renewable internal freshwater resources available per capita. Food imports now account for around 80% of cereal consumption. In 2000, the Republic of Yemen used 10% of its export earnings to import food; by 2012 this had risen to 35%.

Agriculture remains a key sector in the Yemeni economy and the main source of income – direct and indirect - for nearly three-quarters of the population while employing more than half of the labor force. Yet agricultural productivity is very low and faces severe resource constraints that limit the potential for productivity growth. The ground waters on which more than half of agricultural output now depends are almost fully exploited and reserves are being rapidly depleted.

Behind this depletion, lies specific crop selection. In particular, _qat_ - a stimulant widely chewed by Yemenis – accounts for around 40% of total water resource use. While profitable at current relative prices, _qat_ crowds out production of food crops or export crops, and its consumption creates both social and health problems. However, a recent World Bank study (2010) concluded that reducing the subsidy to diesel fuel was unlikely to reduce water extraction or extend the life of the aquifers significantly. It is possible that technological changes combined with changes in institutional arrangements and energy prices may be able to achieve more efficient and sustainable resource use.

# **6. Simulating the impact of fuel price changes on congestion in Cairo**

Preliminary to a more in-depth exploration of the external costs of fuel subsidies and as a simplified benchmark for quantifying the impact, we now apply a simple simulation exercise to look at the impact of a fuel price increase (i.e., a fall in subsidy) on the social cost of congestion in Cairo. The data for the baseline case are taken from the World Bank Congestion Study (2010) that estimated the social cost of congestion in 11 major corridors in Cairo.<sup>5</sup> The social costs of congestion in the study were divided into four major categories. These were; (i) the cost of travel time delay imposed on users; (ii) the cost of travel time unreliability (both for passenger and freight transport); (iii) the cost of excess fuel consumption and, (iv) CO2 emissions. The estimation of costs was done using two approaches – speed plots and volume-to-capacity. They yielded the following magnitudes;

- Speed plots approach: (a) cost of travel time delay– 2.6 billion Egyptian pounds (LE); (b) cost of travel time unreliability – 1.71 billion LE; (c) cost of excess fuel consumption – 2.85 billion LE; and (d) cost of CO2 emissions – 0.097 billion LE;

- Volume-to-capacity ratio approach:  (a) cost of travel time delay– 2.4 billion LE; (b) cost of travel time unreliability – 1.71 billion LE; (c) cost of excess fuel consumption – 2.38 billion LE; and (d) cost of CO2 emissions – 0.086 billion LE;

The total social cost of congestion was estimated at roughly 7 billion LE, amounting to 0.6% of 2010 GDP.

> 5 Note that the magnitudes for the Greater Cairo region are roughly twice as large.

23
Peru. In Colombia, instructional time was positively related to science achievement, while in Peru, teacher time spent explaining and the number of class hours per week on science were negatively related to student achievement.

Textbooks and instructiongl materials. For the past decade, researchers have documented the affect of textbooks on student achievement in developing countries. A review of this research notes that of 18 correlational studies of textbook effects on student learning, 15 (83%) report statistically significant positive results (Heyneman, Farrell, & Sepulveda-Stuardo, 1981). Two studies with experimental assignment of students to textbook conditions also report significant effects of textbooks on achievement (Heyneman, Jamison & Montenegro, 1984; Jamison, Searle, Galda & Heyneman, 1981). A recent study of textbook effects on mathematics achievement in Thailand indicates that textbooks affect achievement by substituting for higher levels of teacher education and by delivering a more coherently organized curriculum (Lockheed, Vail & Fuller, 1986). The effects of instructional materials on science achievement have been studied extensively. Teacher and student use of textbooks were positively related to science achievement in India and Paraguay; use of individual reading materials by teacher affected student achievement in India, and frequent use of audio visual materials affected science achievement in Iran and Chile (Heyneman and Loxley, 1983). In two related studies, Arriagada (1981, 1983) found positive effects for teachers use of instructional materials (audio-visual aids in Colombia and "individual aids" in Peru).

6
- E. Bosio, S. Djankov, F. Jolevski, and R. Ramalho. Survival of Firms during Economic Crisis. Policy Research Working Paper Series 9239, The World Bank, May 2020. URL https://ideas.repec.org/p/ wbk/wbrwps/9239.html.

- M. Bruhn. Can wage subsidies boost employment in the wake of an economic crisis? evidence from mexico. _The Journal of Development Studies_ , pages 1–20, 2020.

- J. Chen, Z. Cheng, K. Gong, and J. Li. Riding out the covid-19 storm: How government policies affect smes in china. _Available at SSRN 3660232_ , 2020.

- R. Chetty, J. N. Friedman, N. Hendren, M. Stepner, and T. O. I. Team. How did covid-19 and stabilization policies affect spending and employment? a new real-time economic tracker based on private sector data. Working Paper 27431, National Bureau of Economic Research, June 2020.

- X. Cirera, M. Cruz, E. Davies, A. Grover, L. Iacovone, J. E. L. Cordova, D. Medvedev, F. O. Maduko, G. Nayyar, S. Reyes, and J. Torres. Policies to Support Busineses through the Covid-19 Shock: a Firm-Level Perspective. Technical report, World Bank, Mimeo 2020.

- R. Dai, H. Feng, J. Hu, Q. Jin, H. Li, W. Ranran, R. Wang, L. Xu, and X. Z. Zhang. The impact of covid-19 on small and medium-sized enterprises:evidence from two-wave phone surveys in china. Working paper, Center for Global Development, Spetember 2020a.

- R. Dai, J. Hu, and X. Z. Zhang. The impact of coronavirus on china’s smes: Findings from the enterprise survey for innovation and entrepreneurship in china. Working paper, Center for Global Development, Febuary 2020b.

- S. De Mel, D. McKenzie, and C. Woodruff. Enterprise recovery following natural disasters. _The Economic Journal_ , 122(559):64–91, 2012.

- F. Di Mauro and C. Syverson. The covid crisis and productivity growth. Technical report, VOXEU, April 2020.

- R. Duval, G. H. Hong, and Y. Timmer. Financial frictions and the great productivity slowdown. _The Review of Financial Studies_ , 33(2):475–503, 2020.

- Facebook, OECD, and W. Bank. The Future of Business Survey. Technical report, 2020. URL https://dataforgood.fb.com/global-state-of-smb/.

- R. W. Fairlie. The impact of covid-19 on small business owners: Evidence of early-stage losses from the april 2020 current population survey. Working Paper 27309, National Bureau of Economic Research, 2020a.

- R. W. Fairlie. The impact of covid-19 on small business owners: The first three months after socialdistancing restrictions. Working Paper 27462, National Bureau of Economic Research, 2020b.

- L. Foster, C. Grim, and J. Haltiwanger. Reallocation in the great recession: cleansing or not? _Journal of Labor Economics_ , 34(S1):S293–S331, 2016.

15
24 attenuate over time as new cohorts accumulate post-transition experience.

Column (6) shows that the returns to experience are correlated with the number of years since the transition out of communism began. Ten years after the transition is initiated, returns are 10 * 0.08 = 0.8 percentage points higher, a large effect given the mean of 3.2%. This correlation holds if one controls for whether the country has achieved high-income status by year _t_ (Panel B), suggesting the effect of transitioning out of communism is not purely due to economic development.

Figure 3(a) shows the effects of transitioning out of communism in a more flexible manner. To obtain these effects, we run panel regressions for all 951 country-years available in 1990-2016 (country fixed effects and year fixed effects included) and include dummies corresponding to different groupings of years since a transition. “3” includes 1-3 years, “6” includes 4-6 years, ..., and “27” includes 25-27 years. “30” (28-+) is the omitted category (standard errors clustered at the country level). The effects are generated for the returns based on the 0-15 bins but also for the returns based on the 0-25 bins and the 0-5 bin. As seen, countries that just began their transition start with much lower returns. Fast convergence is observed for groupings 6 to 12 (hence between 4 and 12 years after a transition). Returns continue converging after that but at a slower pace. Returns are still 1 percentage point lower after more than 25 years. As expected, returns adjust much faster when considering less experienced bins, showing how the patterns are driven by new cohorts accumulating post-communist experience. The results on fast convergence echo the results of Dauth et al. (2019) who study the determinants of wage convergence between East and West German workers.<sup>43</sup> Alternatively, we can study whether communist experience has lower returns than post-communist experience. For each respondent in the 40 ex-communist countries, we separate their potential work experience into experience before the transition (incl.) and experience strictly after the transition. We re-run the main regression (eq. (1)) using 5-year bins for each type of experience. We plot the estimated coefficients in Figure 3(b). The results show that an individual with 20 years of post-communist experience earns about 50% more than an individual with no experience. For communist experience, the differential is at least -25%, implying that post-communist experience has negative

> 43We also find significant negative effects of transitioning out of communism on the returns to education (Appx. Table A.19). Again, once we account for the relatively higher returns to education, the effects of transitioning out of communism on experience and education are similar.
Bank, 1993; Angrist et al., 2006).<sup>18</sup> The test is also a strong determinant of college entrance as it fulfills the qualifying requirements in several subjects. The second outcome of interest measures academic achievement. Conditional on _Icfes_ registration, we measured academic learning by the actual performance of the students on the test. The exam is a standardized test that assesses the academic achievement of students in various subjects such as Mathematics, Language, Biology, Chemistry, Physics, History, Geography, and a foreign language chosen by the student. We focus on the impacts of the program on the standardized scores in the Mathematics and Language modules (35 questions each) and the overall score in the test excluding foreign language.

# **4. Empirical Analysis**

## **4.1 Research Design**

The FA program was not randomly assigned as eligibility requirements were based on geographic and welfare targeting. Only extremely poor households with at least one child between 7 and 18 years old and a score in the proxy-means test that falls _Sisben_ 1 level are deemed eligible for the education transfer of FA. Additionally, the program was initially implemented only in certain qualified municipalities based on their supply of health, education and financial services. These eligibility criteria may be problematic for evaluation as they may induce different sources of selection bias including observable and unobservable factors that could be correlated with program eligibility and educational outcomes. For instance, small towns like those initially targeted by the program may have poorer public infrastructure, less dynamic economies, and therefore lower returns to schooling. Parents living in these places may be less willing to send their children to school. In this case, lower improvements in school attainment over time among participant children relative to nonparticipant children in other towns could be mistakenly attributed to the program as negative effects. Moreover, given that participation in the program is voluntary, those families who sign up for the program in treatment areas may be different in many aspects from those who decide not to

> 18 A small fraction of individuals also take the ICFES test after they have finished high school. Also, since the test can be taken many times, only the first registration date and score is kept for the small number of students who took it more than once.

14
cooperative model of bargaining and signaling. Predictions from the model are then econometrically tested with survey data collected from the same population that is the focus of the ethnographic interviews. Thus, our paper is unusual in two respects. Firstly, it introduces asymmetric information into a model of household bargaining where domestic violence is used as a signal of the husband's satisfaction with the marriage. Secondly, it combines economic and anthropological methods to rigorously examine violence within the context of Indian marriage markets employing data collected by the authors. We find that marital violence is not only closely linked to low dowry payments, but that a woman who comes from a wealthy family is more likely to be beaten by her husband in an effort to extract higher transfers from her parents.

The paper is structured as follows: Following this introduction Section 2 summarizes the cultural context and the ethnographic information, Section 3 outlines the theoretical model, Section 4 describes the data and lays out the econometric methodology, and Section 5 analyzes the empirical results, provides policy implications and concludes the paper.

# **2. Cultural Context**

To understand why the phenomenon of dowry violence is so widespread, it might help to outline the basic nature of Indian marriage markets4: Marriage is restricted to endogamous groups, i.e.: people are only permitted to marry within a well-defined set of families who make up their sub-caste. Sub-castes usually share a common characteristic that distinguishes them from other groups; for instance, they may all traditionally practice one occupation, or they may follow unique religious practices. The sub-caste we study in this paper is a potter community in the South Indian State of Karnataka. The craft of pottery was their primary source of employment for many generations, but today the majority are casual laborers. Yet, any individual from the community would face large social sanctions if s/he married someone who belonged to a nonpotter caste. Thus, while their caste affiliation may no longer reflect their current occupation, it continues to define them as a social group.

A second feature of the marriage market is that it is patrilocal - brides leave their parents' home to live with their husbands. A third is that marriages are arranged for both grooms and brides by their parents. Finally it is important to note that marriage is considered final and, while

> _4_ While there other important factors that affect domestic violence (Karlekar 1998, Rao 1998), this paper focuses on its connection with the marriage market.

4
Table 2. Country Fixed Effects Estimation

|Dependentvariable:|Logof<sup>realpri</sup><br>|<sup>vateinvestm</sup><br>|<sup>ent</sup><br>||
|---|---|---|---|---|
||**Model **<br> <br>|<br>|Model**II**<br>||
||Coef.<br>**t**<br>|<br>|Coef.<br>|t<br>|
|**Log**ofrealpublicinvestment<br>|-.1201513<br>|-2.033**<br>|-.3324242<br>|-3.109**|
|LogoflaggedrealGDP|4.607274<br>|6.695**<br>|6.830853<br>|2.893**<br>**|
|**Trend**<br>_|.2715046|5.483**<br>|.3513241<br>|2.157<br>|
|**Laggedcapitalstock**|2.94e-07|2.488**<br>|-1.80e-07|-0.482|
|Regulatorybodyinplace<br>|.2573572<br>|0.497<br>|||
|Realrateofinterest|-.0118967<br>|-3.775**<br>|-.0131696<br>|-0.420<br>|
|**Investmentrice**<br>|-.131716<br>|-0.112<br>|.7038148<br>|0.145<br>**|
|Dummy:Passageoflegislation<sup>opening</sup><br>**thesector_**|3.640372<br>|7.026**<br>|6.087679<br>|5.717<br>**|
|Dummy:Telecommunications|.5296759<br>|0.819<br>|6.806443<br>|3.200<br>|
|Dummy:Roads<br>|.6889568<br>|1.258<br>|1.643749<br>|1.179<br>|
|Dummy:Water<br>'|-2.344596<br>|-4.135**<br>|1.604541<br>|0.982<br>|
|Dummy:**Electricity**<br>|.9701421|1.789*|1.725853<br>|1.181<br>**|
|Regulatorybodyinsidetheministry<br>|||4.018742<br>|2.858<br>**|
|Dummy:Appointmentofregulator<br>approvedbylegislature<br>|||-5.512656<br>|-2.370<br>|
|Number of membersofregulatory<br>commission<br>|||.2788061<br>|1.556<br>**|
|Dummy:Regulator'sbudget<sup>solely</sup><br>fromgovernment|||-5.512654<br>|-3.489<br>|
|Dummy:Rateofreturnlegislation|||-.9717241<br>|-0.472<br>|
|Constant|-55.26021|-6.700**|-86.95147<br>|-3.107**|
|NumberofObs.|693||183<br>||
|R-sqwithin<br>|0.5122||0.6469J||
|*Significantat10%level<br>**Significantat5%level|||||

Investment volume is negatively<sup>related to the realrateof interest and to thepriceof investment</sup> goods but significantly positively<sup>related to whetheror not legislationenablingprivate entryhas</sup> been passed - the mere act of<sup>liberalizingprivateentry into a sector increasesprivateinvestment</sup> by 3.6%. Interestingly, the<sup>dummy for passageof suchlegislationabsorbsa fair amount of the</sup> effect of having a regulatory<sup>body in placeand indicatesthat in manycasesthe legal basis for</sup> private entry is probably more<sup>importantthanthe actualinstitutional frameworkgoverning</sup> private sector participation.<sup>7Usinga dummy to capturetheopening of the sector is limitingin</sup> that it does not capture critical<sup>elementsof the competitiveenvironmentpost-</sup>

> 7 When we ran the regressions<sup>without includingthe dummyfor legislationliberalizingprivate entry we obtained</sup> higher significance on the existence<sup>of a regulatorybody.</sup>

17