rafmacalaba/datause-encoder-data huggingface dataset:
observations for Romania, just 11, is the likely cause of the lack of significant results for the pairwise means tests for any country.

To sum up, Romania’s discrepancies are large by European standards in the cases of exports of C sawnwood (a negative discrepancy: imports reported by trading partners are less than exports reported by Romania) and imports of NC sawnwood (a positive discrepancy: imports reported by Romania are greater than exports reported by trading partners). We turn now to a consideration of factors that might explain these mean tendencies. We take a quick look at some basic theory before delving into detail on the econometric analysis.

**Table 6. Relative discrepancies (** ∆ **_ij_ ) for sawnwood imported by European countries during 1982-97, aggregated across all exporting countries.** Positive discrepancies indicate that reported imports were greater than reported exports; negative discrepancies indicate the reverse.

|_Ct_|_NC sa_<br>_Nb_|_wnwood_|_C sa_<br>_Nb_|_wnwood_|
|---|---|---|---|---|
|_ounry_|_umer of_<br>_observations_|_Mean discrepancy_<br>|_umer of_<br>_observations_|_Mean discrepancy_<br>|
|Austria|268|0.171<sup>***</sup><br>|229|0.054<sup>**</sup>|
|Belgium-Lux.|404|0.008<sup>††</sup><br>|297|0.006|
|Croatia|44|0.029<sup>†</sup><br>|51|−0.036<br>|
|Cyprus|150|0.193<sup>***</sup><br><sup>***</sup>|110|0.132<sup>***</sup>|
|Czech Republic|46|0.179 <br>|46|0.014|
|Denmark|311|−0.009<sup>††</sup>|204|0.028|
|Faeroe Islands|-|-<br>|45|−0.124<sup>**</sup>|
|Finland|255|0.021<sup>††</sup><br>|72|−0.026|
|France|439|0.082<sup>***</sup>|315|−0.022|
|Germany|486|0.005<sup>††</sup>|334|0.075<sup>***</sup>|
|Greece|216|−0.019<sup>†</sup>|164|0.061|
|Hungary|39|0.113<sup>*</sup><br>|59|0.209<sup>***</sup>|
|Iceland|89|−0.019<sup>††</sup>|141|0.017|
|Ireland|216|0.017<sup>††</sup>|190|−0.009|
|Italy|547|0.168<sup>***</sup>|356|0.117<sup>***</sup><br>|
|Malta|63|0.097<br>|64|0.359<sup>***</sup>|
|Netherlands|456|0.023<sup>††</sup><br>|310|0.025<br>|
|Norway|286|0.184<sup>***</sup><br>|160|0.084<sup>***</sup>|
|Poland|71|0.154<sup>**</sup><br><sup>***</sup>|64|0.047|
|Portugal|193|0.113|117|0.032|
|**_Romania_**|**_32_**|**_0.199_**<sup>**_**_**</sup><br>|**_11_**|−**_0.090_**|
|Russia|48|0.201<sup>***</sup>|32|0.090|
|Slovenia|64|0.059|50|−0.172<sup>**</sup>|
|Spain|436|0.107<sup>***</sup>|268|0.084<sup>***</sup>|
|Sweden|338|0.039<sup>*,††</sup><br>|152|−0.066<sup>*</sup>|
|Switzerland|239|0.101<sup>***</sup>|236|0.000|
|UnitedKingdom|510|0.070<sup>***</sup>|384|0.089<sup>***</sup>|
|Yugoslavia|31|0.071|29|−0.118|

Notes: a. Table includes only countries with at least 25 observations in the EFI Database (except for Romania). b. Trade flows for Central and Eastern European countries in the EFI Database are mainly for the 1990s. c. Sample includes only trade flows with reported imports and exports both ≥ 100 m<sup>3</sup> . d.<sup>***</sup> ,<sup>**</sup> ,<sup>*</sup> : mean is significantly different from zero at 1%, 5%, 10% level. e.<sup>†††</sup> ,<sup>††</sup> ,<sup>†</sup> : mean is significantly different from Romanian mean at 1%, 5%, 10% level.

9
areas once under guerrilla control are less likely to be victims of violent crime or extortion related to gang activity. This aligns with enduring norms of cooperation and higher levels of social capital as well as with qualitative evidence gathered from interviews with locals and former guerrilla commanders, who repeatedly expressed thoughts such as: _“The fact that the maras (gangs) are barely present in these areas reflects that the self-organization of the people worked.”_ (Joaqu ́ın Villalobos, FMLN Military Commander, interview conducted on March 23, 2022).

# **VI.E Other mechanisms**

Other potential mechanisms such as child recruitment, disproportionate improvements in control areas, or changes in the supply and quality of education could underlie our results.

_Peace agreement and post-conflict policies—_ As we noted in the background section, all reforms of the peace agreement (e.g., the reform of the Judicial System) were implemented at the national level and may not prompt our effects. For example, although the agreement created a national police force, we find no differences in enforcement or number of state institutions across areas. As we have shown, the results do not arise from differences in post-land redistribution that was also part of the agreement. Finally, the post-conflict political environment does not seem to explain the results. For example, the ARENA government elected right after the agreement did not lower public investment to punish guerrilla areas. Although we cannot assess the voting patterns of these areas immediately after the war, evidence from the 2014 and 2015 elections do not show that these areas favored a specific party. If anything, there was a small and negative effect on the vote share for the leftist party, as shown in Table D.12. We find that effects on development were still negative when the FMLN won elections, and when former guerrilla areas received more investment (not less) related to infrastructure reconstruction efforts such as roads and schools.

41
# **Table 1: Estimated change in area (km**<sup>**2**</sup> **) for various mangrove species and assemblages, 2015–2050**

|**M**|||_Ei‐_|**Ma**|**ngrove Assem**|**blage, 2050**|<br>_Aii‐_||_Phi‐_|_Ci‐_|
|---|---|---|---|---|---|---|---|---|---|---|
|**angrove**<br>|||_xcoecara_<br>||||_vcenna_||_oenx_<br>|_erops_|
|**Assemblage,**<br>**2015**|_Ceriops‐_<br>_Excoecaria_|_Excoecaria‐_<br>_Heritiera_|_Rhizophora‐_<br>_Ceriops_|_Excoecaria_|_Sonneratia_|_Avicennia_|_Bruguiera‐_<br>_Cereops_|_Ceriops_|_Xylocarpus‐_<br>_Aegiceras_|_Excoecaria‐_<br>_Heritiera_|
|_Ceriops‐_<br>_Excoecaria_|65.967|0.727|0.819|16.842|0.212|1.130|4.211|0.0054|0.005|0|
|_Excoecaria‐_<br>_Heritiera_|0.624|32.206|2.133|4.685|0.252|12.408|14.955|0.514|0.418|0|
|_Excoecaria‐_<br>_Rhizophora‐_<br>_Ceriops_|0.092|0.063|299.115|2.525|0.121|11.126|4.910|0.358|2.291|0|
|_Excoecaria_|16.262|4.046|25.29|353.500|0.061|6.203|8.616|0.018|0.934|0|
|_Sonneratia_|0.243|0.684|4.5|0|35.007|2.885|1.356|0|0.671|0|
|_Avicennia_|4.095|0.838|12.978|14.871|0|718.681|0.005|4.986|0.049|0.084|
|_Avicennia‐_<br>_Bruguiera‐_<br>_Cereops_|8.619|7.026|29.907|0|0|23.820|338.535|5.543|2.638|0|
|_Ceriops_|1.715|0.939|5.814|4.23|0.027|4.478|12.323|148.762|1.871|0|
|_Phoenix‐_<br>_Xylocarpus‐_<br>_Aegiceras_|0.017|0.023|1.8|0.579|0.123|6.485|1.256|2.828|47.110|0|
|_Ceriops‐_<br>_Excoecaria‐_<br>_Heritiera_|0|0|0.198|0.003|0|0.824|0|0.001|0.379|0.001|

12
# **Table 3. Descriptive Statistics**

||||Full sample||||Below 5|0% external deb|t as % of GNI|||Above 5|0% external deb|t as % of GNI||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Mean|Median|Maximum|Minimum|Std. Dev.|Mean|Median|Maximum|Minimum|Std. Dev.|Mean|Median|Maximum|Minimum|Std. Dev.|
|Sovereign default|0.48|0.00|1.00|0.00|0.50|0.36|0.00|1.00|0.00|0.48|0.58|1.00|1.00|0.00|0.49|
|CPIA|3.80|3.78|6.00|2.05|0.72|3.87|3.80|6.00|2.11|0.71|3.73|3.75|6.00|2.05|0.72|
|Current account as % of FDI|‐366.14|‐117.80|31614.29|‐34771.29|3299.79|‐373.74|‐115.40|31614.29|‐34588.25|3275.93|‐359.04|‐119.88|21485.71|‐34771.29|3328.24|
|Current account as % of GNI|‐2.19|‐2.38|18.52|‐17.49|4.71|‐1.86|‐2.04|9.87|‐10.21|3.24|‐2.49|‐3.18|18.52|‐17.49|5.74|
|Current account as % of reserves|‐34.67|‐26.47|998.98|‐530.20|94.45|‐32.37|‐24.41|151.62|‐460.49|60.75|‐36.82|‐29.93|998.98|‐530.20|117.61|
|Effective interest rate|5.43|5.04|21.19|0.09|2.34|5.64|5.33|13.44|2.11|1.95|5.24|4.84|21.19|0.09|2.64|
|Average maturity|16.66|15.50|385.40|0.00|17.73|16.37|13.50|385.40|0.00|25.07|16.93|16.80|34.70|0.00|5.34|
|External debt as % of GNI|58.44|51.32|253.21|4.13|36.25|31.29|31.86|49.82|4.13|10.97|83.82|71.73|253.21|50.05|33.11|
|External debt as % of reserves|799.56|513.22|8399.82|44.79|962.08|450.09|322.83|2281.43|44.79|370.25|1126.17|737.59|8399.82|135.48|1201.78|
|GDP growth|3.48|4.00|16.10|‐13.40|4.47|4.06|4.30|15.20|‐12.90|4.26|2.95|3.60|16.10|‐13.40|4.61|
|Inflation rate|51.93|9.30|11749.60|‐30.30|538.70|39.31|10.90|2075.80|‐1.40|183.58|63.72|7.95|11749.60|‐30.30|728.48|
|Openness|77.94|64.38|436.51|15.47|50.70|58.90|52.86|212.08|15.47|31.53|95.73|75.74|436.51|29.16|58.28|
|Overvaluation|41.21|40.35|95.00|0.00|17.28|41.80|39.68|95.00|15.18|16.49|40.67|40.94|78.45|0.00|18.00|
|Primary deficit as % of GNI|0.54|0.23|21.70|‐20.02|4.46|‐0.05|‐0.08|7.71|‐10.54|2.89|1.10|0.70|21.70|‐20.02|5.49|
|Short term debt as % of reserves|114.40|64.88|2399.83|0.94|199.08|70.47|46.68|610.47|0.94|74.30|155.46|81.25|2399.83|4.81|261.06|
|Short term debt as % of total external debt|15.02|12.95|65.06|0.83|10.13|16.78|15.40|65.06|1.61|10.63|13.38|10.96|61.14|0.83|9.36|
|US T‐Bill rate|5.37|5.07|14.08|1.61|2.19|5.21|5.02|14.08|1.61|2.16|5.53|5.41|14.08|1.61|2.22|
|Observations/countries|||503/46|||||261/39|||||242/35|||

13
**Figure 1: The Demand for Formality in Sri Lankan Firms as a Function of the Net Cost of Formalizing**

<!-- Start of picture text --> 0 100000 200000 300000 400000 500000<br>Net cost of being formal (Sri Lankan Rupees)<br>.3<br>.25<br>.2<br>.15<br>Proportion who become Formal .1<br>.05<br><!-- End of picture text -->

**Source:** based on de Mel et al. (2013) Figure 3.

# **_BEING FORMAL_**

Informal firms are often referred to as “operating in the shadows”, afraid to market themselves widely or locate in very visible locations for fear of attracting the attention of the law. In addition, firms which do not issue tax receipts may not be able to sell to certain customers, such as the government or larger firms. As a result, one of the channels through which formalizing may help firms is through expanding their customer base.

This is the channel which has most support from different studies in the literature. In Bolivia, McKenzie and Sakho (2010) find that firms that become formal as a result of being located slightly closer to the tax office issue more tax receipts and have greater sales. In Brazil, Fajnzylber et al. (2011) find that firms that open up just after introduction of the SIMPLES program, which simplified regulation by combining different types of tax registrations and payments, are more likely to operate in a permanent location, although this could reflect a change in the types of individuals which decide to open firms after the reform, instead of a causal impact of formalizing. In Sri Lanka, firms which formalized as a result of experimental inducement are 26 percentage points more likely to advertise (de Mel et al, 2013).

11
Montreal Protocol (CFCs and halons—so-called “Annex A” substances) at the time the treaty entered into force in 1989; countries with consumption of less than 0.3 kg per capita were given Article 5 status.

For example, the methyl bromide phaseout schedule for non-Article 5 countries establishes a baseline at a country’s total consumption in the year 1991. Annual consumption cannot exceed this baseline by 1995. Annual consumption cannot exceed 75% of its baseline by 1999, 50% of baseline by 2001, 30% of baseline by 2003 and must be completely phased out to 0% of baseline in 2005. For Article 5 countries, the baseline level is set to average yearly consumption over the period 1995–1998. Annual consumption is required to be at or below baseline in 2002, at most 20% of baseline in 2005, and 0% in 2015.

Table 1 displays the ozone depleting substances regulated under the Montreal Protocol, along with the amendment that introduced their phaseout, specified dates for 0% consumption and production for Article 5 and non-Article 5 countries, and common uses of the substance. The Montreal Protocol groups ODS types into “Annexes” based on introduction date and phaseout schedule.

CFCs, HCFCs and HFCs all have common applications as refrigerants in both commercial and residential systems. They also can be used as aerosol propellants, solvents, and cleaners (Brack, 2017). HCFCs were developed as an alternative to CFCs with lower ozone depleting potential, but were quickly subject to control measures themselves with the Copenhagen Amendment in 1992. HFCs were developed as alternatives to HCFCs and have zero ozone depleting potential. They, however, are very potent greenhouse gases—the most common HFC emitted, HFC-134a, has a 100year global warming potential 1,300 times higher than CO2. Currently, alternatives to commonly used HFCs include the creation of HFCs with lower global warming potential, natural refrigerants, and hydrofluoroolefins (HFOs).<sup>6</sup> Figure A.1 in the Appendix displays the total emissions of the aggregated HFC measure for Article 5 countries and non-Article 5 countries. Displayed with the emission paths are the CFC and HCFC phaseout schedules for Article 5 and non-Article 5 countries. From 1990–2018 HFC emissions increased dramatically for both country groups. All Annex A and B gases (CFCs, halons, other CFCs, CTCs, and TCA) were phased out for developed countries by

> `6` https://ec.europa.eu/clima/eu-action/fluorinated-greenhouse-gases/climate-friendly-alternatives-hfcs ~~en~~ .

8
# **Racial Peer Effects at Work:**

# **Evidence from Worker Deaths in Brazil**<sup>∗</sup>

**Katharina Fietz**<sup>†</sup> **Aiko Schmeißer**<sup>‡</sup>

## **JEL Classification:** J15, J21, J63

> ∗We thank Marco Caliendo, Javier Feinmann, Katrin Huber, Simon J ̈ager, Jann Lay, Elizabeth Linos, Shushanik Margaryan, Suanna Oh, Amanda Pallais, Josefina Posadas, Nina Roussille, Pedro C. Sant’Anna, Sulin Sardoschau, Liam Wren-Lewis, and participants of the Development Economics Network Berlin (DENeB) Workshop, Ruhr Graduate School in Economics (RGS) Doctoral Conference, Berlin Network of Labor Market Research (BeNA) 20 Year Jubilee Conference, Doctorissimes PhD Conference, European Development Research Network (EUDN) PhD Workshop, Research Institute for Development, Growth and Economics (RIDGE) Workshop on Public Economics, German Development Economics (GDE) Conference, Warwick Economics PhD Conference, European Society for Population Economics (ESPE) Annual Conference, International Conference on Development Economics (ICDE), and the 39th meeting of the European Economic Association for valuable comments. In addition, we are grateful to the Brazilian Ministry of Labor for granting data access to the _Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais_ (RAIS).

- †University of G ̈ottingen, GIGA; `katharina.fietz@giga-hamburg.de`

- ‡University of Potsdam, BSoE; `schmeisser@uni-potsdam.de`
6

## **Table 2**

|**M**|**acroecono**|**mic**<br>**Ind**|**icators**|||||
|---|---|---|---|---|---|---|---|
||1990|1991|1992|1993|1994|1995|1996<br>(est.)|
|Real GDP growth rate|-3.896|<br>-8.4%|-9.7%|-14.2%|-23.5*|-11.8%|-7.9%|
|GNP per capita (US$)(Atlas)|..|2636|2753|2439|1913|1650|1514|
|Aseof GDP||||||||
|Current account deficit|||||-6.1|-4.2|-2.2|
|Fiscal Deficit||-14|-29|-12|-8.2|-4.7|-2.8|
|External Debt|..|..|..|..|23.8|23.0|21.4|
|Real exchange rate index<br>(1/1993=100)|..|..|125|108|54|47|39|
|Nominal exchange rate (1000 LC/$)|0.0006|0.0022|0.0336|1.288|49.86|147.0|200.0|
|Inflation<br>rate (year average)|..|..|1210|4735|891|376|75|

Data Source: World Bank Second, while total **employment** only fell by 10 percent between 1992 and 1995 and open unemployment remains low (2.4 percent in 1995) , significant changes have occurred in terms of labor force participation, occupational choice and allocation of time between various occupations. As explained below, these changes have induced a decline in the number of contributors to the social security system.

# 3.2. Changes in Labor Force Participation and Occupational Choice

Labor force participation rates observed in the FSU were high, mostly due to the fact that women had reached in the early 80s the highest labor force participation rates in the world<sup>3</sup> (see Mincer, 1985). As in other industrialized countries, women had been drawn into the labor force through the migrations from rural toward urban areas, substituting work outside the household for family agricultural work. The process had been accompanied by a marked rise in the level of women's education and a similarly sharp decline in fertility. The soviet socialist economic system, ideology and growth strategy had played an additional key role in hastening the incorporation of women in the labor force (see Ofer & Vinokur 1985).

Although labor force participation rates were high over most of the life-cycle, rates were extremely low before the age of 20 and were falling sharply after the age of 55 for women and 2Estimate based on World Bank Household Survey (1995) - other estimates (See Rapawy 1996, WB Poverty Assessment 1996) are of the same order of magnitude. Inspite of low open unemployment, there is evidence of hidden unemployment. It is estimated that in 1995, approximately 2 million employees of state-owned enterprises stay on the payroll although working for shorter hours or on leave without pay.

**3** except among the Moslem population who had quite different demographic and labor force behavior (higher fertility and lower labor force participation) than the rest of the population.
- Tilly, C. 1975. The formation of national states in Western Europe. Princeton, N.J.: Princeton University Press.

- Tilly, C. 1985. War making and state making as organized crime. Cambridge: Cambridge University Press.

- Tilly, C. 1992. Coercion, capital, and European states, AD 990-1990. Cambridge, Mass.: B. Blackwell.

- Ullman, M. 1961. Cities of mainland China: 1953 and 1958. [Washington]: Foreign Manpower Research Office.

- Voigtländer, N., Voth, H.-J. 2009. “Malthusian Dynamism and the Rise of Europe: Make War, Not Love.” _American Economic Review: Papers & Proceedings_ 99(2), 248–254.

- Voigtländer, N., Voth, H.-J. 2013a. "Gifts of wars: warfare and Europe’s early rise to riches." _Journal of Economic Perspectives_ 27(4), 165–186.

- Voigtländer, N., Voth, H. J. 2013b. "The three horsemen of riches: plague, war, and urbanization in early modern Europe." _Review of Economic Studies_ 80(2), 774-811.

- Wade, R. 1990. Governing the market: economic theory and the role of government in East Asian industrialization. Princeton: Princeton University Press.

- Wang, T. 1957. Zhong wai jiu yue zhang hui bian (Compilation of Old Treaties Between China and Foreign States) (Di 1 ban.). Beijing: Sheng huo du shu xin zhi san lian shu dian ;Xin hua shu dian fa xing.

- Wang, Y., Wang, S. (Eds.). 1902. Huangchao Dao Xian Tong Guang zouyi:(Memorials to the Emperor Daoguang, Xianfeng, and Tongzhi). Shanghai: Jiu jing zhai.

- Wang, Z., Wang, H., Tian, Y., Xiang, D., Zhu, Q., Hu, X., ... Guan (Eds.). 1952. Taiping tianguo: (Taiping Heavenly Kingdom). Shanghai: Shenzhou guoguang she.

- World Bank. 2011. conflict, security, and development. Washington, DC: World Bank.

- Wu, J. 1950. The Impact of the Taiping Rebellion upon the Manchu Fiscal System. _The Pacific Historical Review_ 19(3), 265–275.

- Wu, J. (Ed.). 1990. Zhongguo difangzhi chaye lishi ziliao xuanji (Collections of Historical Records of Tea in Chinese Gazetteers). Beijing Shi: Nongye chubanshe; Xinhua shudian Beijing faxingsuo faxing.

- Yan, Z., Xu, Yi., Yao, X., Sun, Y., Wang, J., Li, Y., ... Luo, E. 1955. Zhongguo jindai jingjishi tongji ziliao xuanji (Collections of Statistics of Modern China Economic History). Beijing: Kexue chubanshe.

- Young, A. 2017. "Consistency without Inference: Instrumental Variables in Practical Application." Mimeo, LSE.

- Zhang, A. 1996. The Changes in Land Relationship after the Taiping Rebellion. _Shanghai Normal University Academic Journal_ 1996(1), 123–128.

- Zhang, T., Zou, H.-F. 1998. “Fiscal Decentralization, Public Spending, and Economic Growth in China,” _Journal of Public Economics_ 67(2), 221-240.

- Zhao, G. 1986. Man and land in Chinese history: An economic analysis. Stanford, Calif.: Stanford University Press.

- Zheng, Q. 2008. Concessionary Policy of Qing Government after the Suppression of the Taiping RebellionTitle. _The Qing History Journal_ 3, 59–69.

- Zhu, X. 1992. Zhongguo sichou shi (History of Silk in China). Beijing: Fangzhi gongye chubanshe; Xinhua shudian jingxiao.

43
which is shaped by trade policy. In other words, an important insight from the model is that the impact of infrastructure on a given country will depend on its level of trade openness, which in turn is affected by trade policy.

# **3. Quantifying the effects of the Belt and Road Initiative**

In this section, we calibrate our model to assess the impact of the transport infrastructure related to the Belt and Road Initiative. While the scope of the initiative is still taking shape, the BRI is structured around two main components, underpinned by significant infrastructure investments:<sup>11</sup> the Silk Road Economic Belt -the “Belt”- and the New Maritime Silk Road -the “Road” (Figure 1). The “Belt” links China to Central and South Asia and onward to Europe, while the “Road” links China to the nations of Southeast Asia, the Gulf countries, East and North Africa, and on to Europe. Six economic corridors have been identified: (1) the China-Mongolia-Russia Economic Corridor; (2) the New Eurasian Land Bridge; (3) the China–Central Asia–West Asia Economic Corridor; (4) the China–Indochina Peninsula Economic Corridor; (5) the ChinaPakistan Economic Corridor; and (6) the Bangladesh-China-India-Myanmar Economic Corridor. The 71 economies highlighted in Figure 1 are those that are geographically located along the Belt and the Road and are considered as “BRI economies” in this paper.

# **a. Taking the model to the data**

The simple equilibrium structure of the model presented in the previous section allows to simulate counterfactuals with a large number of countries and sectors without any computational issue. This is important given the global nature of the shock we are studying: due to network effects, BRI transport infrastructure investments are expected to change bilateral trade costs among many country pairs in the world and not only for countries that will participate to the initiative. A key advantage from solving the model in relative changes is that it minimizes the data requirements to calibrate the model.

We use the newly available database in GTAP 10 to calibrate our model and consider a total of 107 countries and “regions” and 31 sectors.<sup>12</sup> To compute the model and perform counterfactual analysis, the following aggregates are used for all the countries considered in the analysis and for a constructed rest of the world, based on GTAP 10 data.

- j

- • γn : share of value added in gross output by country and sector.

> 11 Transport projects are estimated to cover about one-quarter of total BRI investment (Bandiera and Tsiropoulos, 2019).

> 12 See Annex A for the full list of countries and regions used in this paper.

13