rafmacalaba/datause-encoder-data huggingface dataset:
Card, David and Jesse Rothstein. 2007. “Racial Segregation and the Black-White Test Score Gap.”, _Journal of Public Economics_ , 91(11-12): 2158-84.

Chandra, Amitabh. 2000. “Labor Market Dropouts and the Racial Wage Gap: 1940-2000. _American Economic Review_ , 90(2): 333-338.

Cutler, David M. and Edward L. Glaeser. 1997. “Are Ghettos Good or Bad?”. _Quarterly Journal of Economics_ , 112(3): 827-872.

Fryer, Roland G. and Steven D. Levitt. 2004a. “Understanding the Black-White Test Score Gap in the First Two Years of School”, _Review of Economic and Statistics_ , 86(2): 448-464.

Fryer, Roland G. and Steven D. Levitt. 2004b. “The Causes and Consequences of Distinctively Black Names”, _Quarterly Journal of Economics_ , 119(3): 767-805.

Fryer, Roland G. and Paul Torelli. 2005. “An Empirical Analysis of ‘Acting White’ ”. NBER Working paper 11334.

Heckman, James J., Thomas M. Lyons and Petra E. Todd. 2000. “Understanding BlackWhite Wage Differentials: 1960-1990.”, _American Economic Review_ , 90(2): 344-349.

Hu, Wei-Yin. 2000. “Immigrant Earnings Assimilation: Estimates from Longitudinal Data.” _American Economic Review_ , 90(2): 368-372.

Hum, Derek and Wayne Simpson. 2004. “Reinterpreting the Performance of Immigrant Wages from Panel Data”, _Empirical Economics_ , 29(1): 129-47.

Jaynes, Gerald D. “The Labor Market Status of Black Americans: 1939-1985.”, _Journal of Economic Perspectives_ , 4(4): 9-24.

Johnson, William, Yuichi Kitamura and Derek Neal. 2000. “Evaluating a Simple Method for Estimating Black-White Gaps in Median Wages.”, _American Economic Review_ , 90(2): 339-343.

Juhn, Chinhui, Kevin M. Murphy and Brooks Pierce. 1991. “Accounting for the Slowdown in Black-White Wage Convergence”, in M. Kosters, ed., _Workers and their wages: Changing patterns in the United States._ Washington, DC. American Enterprise Press, 107-43.

Kim, Seik. 2008. “Economic Assimilation of Foreign-Born Workers in the United States: An Overlapping Rotating Panel Analysis”. Working Paper, University of Washington.

Neal, Derek. 2004. “The Measured Black-White Wage Gap among Women Is Too Small” _Journal of Political Economy,_ 112: S1-S28.

19
regional demand for food sectors more than that for other industries, and that higher demand encouraged food production and attracted global supermarket entering the region at the same time.

To examine our results against this alternative explanation, we compute the average real wage in the region as a measure of the regional income level. We add the interactive term between _FOOD_ and logarithm of the average wage to our model and conduct our analysis with firm fixed effects, first differences and long differences. The results are reported in Table 18, Table 19 and Table 20<sup>13</sup> , respectively. The interactive term between _FOOD_ and wage rate is positively correlated with productivity in fixed-effect models but not in the first differenced model. This implies that the regional income level does affect firm productivity in food supplying sectors differently from non-food sectors. However, in terms of growth in firm productivity, the relationship between regional income level and productivity does not exhibit systematic differences across food and non-food sectors. Our variable of interest, the interactive term between _FOOD_ and global chain presence, remains positive and statistically significant in all of the specifications. It implies that despite the impact of regional income changes, our main results still hold and suggest that the regional expansion of global retail chains facilitates productivity growth of food supplying sectors located in the same region.

We also repeat our instrumental variable estimates after including the control for the regional income level. We report the estimation results in Table 21. The F-tests and Shea’s partial R2 show that the instruments are correlated with the potentially endogenous variable. However, the augmented models pass the Sargan test only in two of six specifications. In terms of estimates, the interactive term between FOOD and the measures of global chains’ presence remains positive and significant at conventional levels. The coefficients on the interactive term between FOOD and regional average wage rate are similar to those produced by the fixed-effect estimation.

# **6.8 Extensions**

As an extension we conduct the baseline analysis separately for manufacturing firms of different sizes. The results are reported in Table 22. We find that the positive correlation between

> 13 As the wage data are only available only since 1997 and the explanatory variables are lagged by one period, these regressions are based on the period 1998 to 2005, which explains a smaller number of observations.

21
both the domestic and export markets. In addition, it is considerably less restrictive than the industry-level proportionality assumption commonly made by existing studies, as we still allow ...rms to be heterogeneous in terms of their shares of exports in total sales.

Thus, the DVA and DVAR of a non-processing exporter are: where the superscript ‘O’stands for ordinary exports. Similar to processing exports, there are transactions between non-processing exporters and the rest of the economy. After the adjustment based on the proportionality assumption, we follow the same procedures as outlined in Table 1 to adjust the estimates of the DVAR, similar to what we did for processing exporters. We ...rst obtain imputed �<sup>F</sup> based on the estimates from KWW12. Then we identify imported capital based on the United Nations Broad Economic Categories (BEC) list of capital goods, and adjust for �<sup>K</sup> i<sup>.Finally, we drop excessive importers.However, unlike</sup> what we can do for processing exporters that export excessively, there is no corresponding ...lter we can use to drop the excessive ordinary exporters. Including them in the sample will result in an overestimation of the DVAR of ordinary exports. With this caveat in mind, our approach is transparent and general enough to be applied to estimate the DVAR of di¤erent types of exporting ...rms and thus countries with varying prevalence of processing trade.

We use the ground-up approach to measure the DVAR of Chinese aggregate exports, by taking the weighted average over the DVARs of processing and ordinary exports, with weights equal to the corresponding export shares.<sup>32</sup> As shown in Table 2, the average DVAR

> 32Here we measure the DVAR for single-industry exporters only. As we have done for processing exports, we can also do it for multiple-industry ...rms as well. The drawback is that excessive processing importers are identi...ed as those that have import-export less the 25th percentile of the DVAR of ordinary exporters in the same year, but not the same sector-year. These numbers are available upon request.

18
Both depositors and stockholders were sources of management discipline. An asymmetric information problem could arise between these groups. Typically, most bank depositors were thought to be uninformed about the true solvency of the bank. These uninformed depositors based withdrawal decisions on imperfect signals of bank solvency, such as long withdrawal lines. In contrast, informed depositors, such as large corporate depositors, could quickly withdraw funds if bank solvency was threatened. Because of this information asymmetry, double liability imposed the greatest threat of loss on those stakeholders most informed about the bank's condition-the stockholders.

One goal of federal deposit insurance in 1933 was to protect and stand in for uninformed depositors by limiting initial deposit insurance coverage to $5,000. But because the rate charged to banks for deposit insurance coverage was fixed (non-risk based), it introduced the well-known moral hazard problem of deposit insurance. Arguably, if double liability had been retained as a complement to federal deposit insurance, the regulatory discipline of double liability would have offset the moral hazard incentives introduced with deposit insurance. Indeed, double liability had coexisted with the blanket federal guarantee of national bank notes without the moral hazard problems that arose in the 1980s with deposit insurance.

# _Capital Formation Advantages_

Contingent liability may allow more efficient capital formulation in developing countries if capital is mostly fixed wealth. In this case contingent liability can be viewed as a form of off-balance sheet capital (for example, land and other fixed assets), available to creditors if the bank closes. Arguably, offbalance sheet capital may be of equal or greater value to liability holders compared with on-balance sheet capital for several reasons. First, book asset values may not accurately reflect market asset values, while off-balance sheet capital may be easier to value. In addition, off-balance sheet capital may be of 9
former which is defined as firms between 50 and 150 employees.<sup>5</sup> Moreover, I find evidence of a positive, although small effect of the program on untreated firms that belong to the same sector and region of Apex’s treated exporting firms.

The remainder of this paper is organized as follows: Section 2 provides a literature review on the impact of EPAs on exports. Section 3 describes the data and the program and provides some descriptive statistics. Section 4 discusses the identification strategy. Section 5 shows the empirical results followed by robustness checks and section 6 concludes the paper.

# **2 Related Literature and Motivation**

The discussions in trade literature about the effectiveness of export promotion policies in the 1980s were marked by criticism of their distance from the private sector.<sup>6</sup> This topic has gained attention again, particularly in the context of developing and emerging economies facing a more open-to-trade environment. As highlighted by Lederman et al. (2010), the number of EPAs has tripled over the past two decades and most of them have focused on assisting exporters in understanding and finding markets for their products.

There are two main approaches that have been used to analyze EPAs’ effectiveness. The first one is based on a more aggregated and bilateral trade flow.<sup>7</sup> Overall, these studies find positive impacts of export promotion efforts in different regions. Rose (2007) finds a positive effect of opening a country’s embassy on export performance. Ferguson and Forslid (2014) also find a positive effect of opening Swedish embassies abroad on boosting the number of Swedish exporting firms, particularly for medium-sized firms.<sup>8</sup> Gil-Pareja et al. (2014) also provide evidence of a positive impact of regional export promotion offices for Spain. These offices seem to be more effective on promoting export, the more distant they are from their country.<sup>9</sup> Hayakawa et al. (2011) also find a positive effect of promotion agencies on the export increases in Japan and Korea. Their results suggest that establishing an EPA office abroad is equivalent to signing a free trade agreement (FTA) with the same country. Lederman et al. (2010) show the results of an international survey of 88 EPAs and find positive impact of EPA budgets on export, particularly in Eastern Europe, Asia, Latin America and Sub-Saharan Africa.

Yet, the previous approach does not identify the impact at the level of benefited firms.

> 5Firms’ sizes are defined according to the number of employees. See section 5.2 for further details.

> 6See Krueger (1980), Hogan et al. (1991) and Lederman et al. (2010)

> 7Hogan et al. (1991) is also an example of this approach.

> 8Those firms may be more sensitive to fixed entry cost related to informational barriers.

> 9They attribute this effect to the incomplete information barriers’ problem.

3
**Table 4. Impacts on CO2 emissions and economic outputs at the sectoral level in 2030 (% change from the baseline)**

|**Sector**|**CO2 emis**|**sions**|**Sectoral o**|**utput**|
|---|---|---|---|---|
||Not-Linked<br>Case|Linked<br>Case|Not-Linked<br>Case|Linked<br>Case|
|Agriculture, Forestry, Animal Husbandry and Fishery|-11.4|-4.1|-0.6|-0.1|
|Mining and washing of coal|-53.7|-26.0|-34.5|-15.0|
|Extraction of petroleum and natural gas|-27.8|-10.9|-12.7|-4.4|
|Mining and processing of metal and nonmetal|-22.2|-8.6|-5.3|-1.6|
|Food, tobacco, textile, leather, fur, feather, timber, furniture, paper, printing|-28.5|-11.9|-1.2|-0.2|
|Processing of petroleum, coking, processing of nuclear fuel|-32.9|-13.8|-13.7|-5.0|
|Manufacture of chemical products|-25.4|-10.2|-5.7|-1.8|
|Manufacture of non-metallic mineral products|-27.6|-11.9|-3.4|-1.0|
|Smelting and processing of metals|-26.8|-11.2|-4.8|-1.4|
|Other manufacture|-25.7|-10.2|-2.4|-0.7|
|Production and distribution of electric power and heat power|-34.2|-14.8|-18.9|-7.0|
|Production and distribution of gas|-39.9|-15.9|-19.2|-5.2|
|Production and distribution of tap water|-23.6|-9.4|-2.9|-0.9|
|Construction|-12.2|-4.6|0.7|0.1|
|Transport, storage and postal services|-18.5|-5.6|-2.3|-0.6|
|Other services|-19.3|-6.4|0.7|0.2|

19
-32 -

# Biblography

Braverman, A., and J.L. Guasch. 1990. 'Agricultural Reform in Developing Countries: Reflections for astemn Europe.' _Amercan Jounal of Agrcultural Economics_ (December) 72(5): 1743-51.

- Brooks, K. 1991. "Decollectivizationin East/Central Europe.' Draft. Washington, D.C.: World Bank.

- Brooks, K., J.L.. Guasch, A. Braverman, and C. Csi. 1991. vAgriculture and the Transition to the Market." _Joumnal of Economic Perspectives_ (Fall) 5(4): 149-61.

- Cskid, Csaba. 1983. 'Economic Management and Organization of Hungarian Agriculture." _Journal of Comparaive Economics 7:_ 317-28.

- **1** 985. 'An Outlook of Food Supply and Demand in CMEA Countries.' _Acta Oeconomica_

- 35(1-2): 145-64.

- _. 1989. 'The CMEA Countries and World Trade in Food and Agricultural Products." in _Agicuure and Goverments in an Interdependent World._ Oxford: InternatonalAssociation of Agricultral Economists/Dartnouth.

- _, 1990. 'Agriculural Changes in Eastern Europe at the Beginning of the 1990's. _"American Journal of Agricultural Economics_ (December) 72(5): 1733-42.

- -. 1991. 'Agricure and Agricultral Policy in Eastern Europe.' In _Agriculural Economics_

- _and Policy: International Challenges for the Mneties._ Amsterdam: Elsevier.

- CsAki, Csaba, and G. Varga. 1990. 'Agricultural Reform in Easte Europe in the 90's." Paper prepared for the World Bank Conference on Agricultural Transition in Eastern Europe, August 29-September 1, Budapest.

- Nello, S. Senior. 1990. 'Agricultural Trade Between the European Economic Community and Cental East Europe." Paper prpared for Instituto Nazionale Economica Agara Seminar, April 19, Rome.

- Polish-European Community-World Bank Task Force. 1990. _An Agricuural Strategy for Poland._ Washington, D.C.: World Bank.

- Wadelin, K.E., ed. 1990. _Communist Agriculture: Fanning in the Soviet Union and Eastern Europe._ London, New York: Routledge.

- Wadekin, K.E., and J.L. Brada, eds. 1988. _SociaUstAgricultum in 7ansidon._ Boulder, Colo.: Westview Press.
# **5.2 Ambient Quality and Health Damage**

Estimating the impact of total emissions on human health (represented here by expected mortality) requires four additional steps.

First, the World Bank's dispersion model (mentioned in Section 4.1) is used to estimate the impact of industrial emissions on air quality in each municipio. The model incorporates the effects of total emissions, the relative impact of plant size, and the size of the area over which the emissions are dispersed.

The second step is conversion of the concentration increments (by plant size) into changes in the probability of mortality for municipio populations. For this, the particulate 'doseresponse function, developed by Ostro (1994) from a number of prior studies, is deployed. In particular, a 0.1 Ig/rm<sup>3</sup> reduction in concentration induces a fall of .067 per 100,000 in the mortality rate.

These estimated concentration increases are then multiplied by municipio population to obtain expected mortality from the emissions of small, medium and large plants.

Finally, the expected numbers of deaths are aggregated across municipios to obtain expected mortality increments by income decile.

The results are portrayed in Table 4.

Do the poor sufler from more pollution in Brazil? In fact, the results strongly suggest the converse. Table 4 shows that 95% of annual expected mortality from industrial air pollution is in the highest two income deciles. Furthermore, the great majority of these deaths (97% in decile 9 and 76% in decile 10) are attributable to emissions from large plants.

15
variables. However, it seems reasonable to think that they at least in part reflect an effect running from the specific institutions and regulations measured by these two datasets to the relevant outcomes. To the extent that this is the case, our goal in this paper is to document the extent to which these correlations between the aggregate GII and DB measures and outcomes of interest can be unbundled into differential impacts of the many highly‐detailed subcomponents of these broader measures.

This raises the question of a second feature of the data that we want to document before moving on: the many disaggregated variables underlying these two broad variables have surprisingly (at least to us) low intercorrelations among themselves. We summarize these in Table 3. The rows of Table 3 correspond to the GII and DB datasets at varying levels of disaggregation. For each level of disaggregation, we compute all of the pairwise correlations between the variables at that level of disaggregation. Then we summarize the distribution of these (many!) estimated correlations by reporting the 10<sup>th</sup> , 25<sup>th</sup> , 50<sup>th</sup> , 75<sup>th</sup> and 90<sup>th</sup> percentiles for each combination of indicators and levels of disaggregation. For example, the median pairwise correlation among all combinations of GII variables is 0.4 at the GII‐12 level of disaggregation, 0.25 at the GII‐45 level of disaggregation, and just 0.09 at the GII‐303 level of disaggregation. At this highest level of disaggregation, fully 90 percent of all pairwise correlations are less than 0.35. In the case of Doing Business, the median pairwise correlations are just 0.32 and 0.18 at the DB‐10 and DB‐41 levels of disaggregation. These quite moderate pairwise correlations between the disaggregated indicators are a key feature of the data because they highlight their potential to be informative about their corresponding outcomes. Had these individual disaggregated indicators been very highly correlated with each other, it would have been obvious a priori that it would be very difficult to identify the partial effects of any one of them due to problems of strong collinearity. However, this does not appear to be a major problem in the GII and DB data.<sup>12</sup> For comparison purposes, we also document the distribution of the pairwise correlations between the outcome variables of interest. There is a striking contrast here with the individual indicators. The outcome variables are quite strongly correlated with each other,with a median pairwise correlation of 0.61 for the GII outcomes measuring corruption, and 0.68 for the DB outcomes measuring the regulatory environment. We interpret these high correlations as suggesting that these different candidate dependent variables are measuring broadly similar outcomes.

> 12 Of course, these pairwise correlations are not sufficient to indicate or rule out problems of collinearity in models with more than two explanatory variables.  We discuss below in Section 5 why our main instability results are likely not due to problems of collinearity among regressors.

12
Our conclusion is that labor market policies in Mexico are still limited and underfunded. Even though the country has implemented a variety of active labor market programs, the funding and coverage of these programs are insufficient for dealing with either the current crisis or future ones. Total unemployment withdrawals from pension funds represented 0.14 percent of nominal GDP in 2009. This contrasts with allocations of 0.5 to 2 percent of GDP in European Union (EU) and other Organisation for Economic Co-operation and Development (OECD) countries for passive labor market policies (see figure 4.1). The budgets of temporary employment programs, training, and intermediation services represent less than 0.3 percent of the Mexican GDP whereas these active labor market policies account for between 0.5 to 1 percentage point of the GDP in EU and OECD countries. In order to have better mechanisms for dealing with the aftermath of the current crisis and, more important, with future crisis, Mexico needs to enhance its labor market policies both in terms of funding and design. As mentioned before regarding the expansion of PET, Mexico seems ready to consider a technical analysis for an enhanced unemployment protection mechanism, as well as further expansions of its labor policies.

**Figure 4.1: Unemployment Withdrawals from Pension Accounts and Unemployment Rate**

<!-- Start of picture text --> Unemployment withdrawals from pension accounts<br>and unemployment rate<br>180,000 7<br>160,000<br>6<br>140,000<br>5<br>120,000<br>4<br>100,000<br>80,000 3<br>60,000<br>2<br>40,000<br>1<br>20,000<br>0 0<br>number of withdrawals<br>unemployment rate (in percentage)<br>Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11<br><!-- End of picture text --> _Source:_ INEGI, BIE, SEDESOL, and data provided by the National Commission for the Pension System ( _Comisión Nacional del Sistema de Ahorro para el Retiro_ —CONSAR).

39