rafmacalaba/datause-encoder-data huggingface dataset:
nearly identical, and so we are confident that our instability finding is not driven by the particular choice of the prior parameter g.

Another possible objection to the instability finding is that it reflects multicollinearity problems in the individual models considered by BMA. As is well‐known, one consequence of having nearly collinear regressors in finite samples is that parameter estimates are highly‐sensitive to small changes in model specification. Moreover, individual slope coefficients would themselves be very imprecisely estimated. Together this would potentially be reflected in large posterior variances of the slope parameters of interest. However it is less clear that this will matter for posterior model probabilities and the derived posterior inclusion probabilities, since these reflect only differences across models in model size and goodness‐of‐fit. Indeed, the strong tradeoff between model size and R‐squared due to our choice of a small value for the prior parameter g helps to ensure that models with near‐collinear regressors are assigned low posterior probabilities (since adding a near‐collinear regressor to a model will result in only a very small improvement in R‐squared). In addition, we have also computed (but not reported) posterior standard deviations conditional upon inclusion for the GII‐12 and GII‐45 levels of disaggregation. If collinearity were important we would expect to find large conditional standard deviations for the slope coefficients reflecting the low information content of collinear regressors. Yet we find that these posterior standard deviations are not especially large. At the GII‐45 level of disaggregation, we find that roughly the top half of all variables as ranked by their PIPs have ratios of the posterior mean to the posterior standard deviation in excess of two, suggesting that conventional levels of statistical significance are attained by these variables.

A final very pedestrian potential explanation for our instability result across outcomes is that it might simply reflect differences across outcomes in the set of countries included in the analysis. Not all of the outcome variables are available for all countries, and in order to use as much information as possible we have performed our analysis using the largest available set of countries for each choice of y variable. However, if the set of included countries changes systematically from one outcome to the next in terms of the relevant determinants of outcomes, then this would contribute to our instability finding (as noted by Feldkircher and Zeugner (2010) in their comment on Ciccone and Jarocinski (forthcoming)). To investigate this possibility we repeated the analysis of the DB‐41 dataset, but restricting attention to 26
# **Table 1: Classification of the Financial Sector Policy Response to COVID-19**

# _Panel A. Cumulative number of measures taken (up to September 1_<sup>_st_</sup> _, 2020)_

|**Category**<br>**Focus**|All<br>countries|High<br>Inc.|EAP|ECA|LAC|MENA|SAR|SSA|
|---|---|---|---|---|---|---|---|---|
|**Banking Sector**|**_1694_**|**_811_**|**_116_**|**_228_**|**_187_**|**_53_**|**_157_**|**_142_**|
|Prudential|861|486|42|121|70|17|59|66|
|Support borrowers|703|270|60|91|97|35|83|67|
|Integrity|63|28|5|7|12|0|7|4|
|Operational continuity|53|23|6|4|7|1|8|4|
|Crisis management|14|4|3|5|1|0|0|1|
|**Financial Markets and NBFIs**|**_399_**|**_177_**|**_38_**|**_43_**|**_57_**|**_2_**|**_45_**|**_37_**|
|Market functioning|215|93|17|24|33|2|32|14|
|Non-bank financial institutions|134|75|8|15|13|0|9|14|
|Public debt management|50|9|13|4|11|0|4|9|
|**Liquidity and funding**|**_788_**|**_281_**|**_71_**|**_88_**|**_138_**|**_17_**|**_66_**|**_127_**|
|Liquidity support|483|173|37|52|92|8|46|75|
|Easing of policy rates|232|49|33|35|42|9|17|47|
|Assetpurchases|73|59|1|1|4|0|3|5|
|**Payments Systems**|**_248_**|**_36_**|**_17_**|**_24_**|**_25_**|**_22_**|**_29_**|**_95_**|
|Digital payments|194|26|15|16|20|16|21|80|
|Relaxation of compliance requirements|19|3|0|3|2|0|2|9|
|Cash / Cheque usage restrictions|18|2|0|2|1|4|4|5|
|Cash acceptance|17|5|2|3|2|2|2|1|
|**TOTAL**|**_3129_**|**_1305_**|**_242_**|**_383_**|**_407_**|**_94_**|**_297_**|**_401_**|

12
54

# REFERENCES

Atkinson, Tony, L. Rainwater and Tim Smeeding (1994), “Income Distribution in OECD countries: The Evidence from the Luxembourg Income Study (LIS)", mimeo, May 18.

Bruno, Michael (1993), “Stabilization and Reform in Eastern Europe: Preliminary Evaluation" in Blejer, Mario et. al, Eastern Europe in Transition: From Recession to Growth, World Bank Discussion Paper No. 196, World Bank: Washington, D.C, pp. 12-37.

Bird, Edward J., Johannes Schwarze and Gert G. Wagner (1992), "The Changing Value of Human Capital in Eastern Europe: Lessons from the GDR", DIW Discussion paper No.55, Berlin.

Blanchard, Olivier, Simon Commander and Fabrizio Corricelli (1993), "Unemployment and Restructuring in Eastern Europe and Russia”, in Unemployment, Restructuring and the Labor Market in Eastern Europe and Russia, Economic Development Institute of the World Bank, Washington: World Bank, Carr, E.H., (1966), The Bolshevik Revolution, 1917-1923, volume 2, London: Pinguins.

Chase, Robert (1995), "Returns to Education and Experience in Transition Czech Republic and Slovakia", Yale University, mimeo, January.

Commander, Simon and Fabrizio Corricelli (1993), "Output Decline in Hungary and Poland in 1990/1991: Structural Change and Aggregate Shocks", in Blejer, Mario et. al, Eastern Europe in Transition: From Recession to Growth, World Bank Discussion Paper No. 196, World Bank: Washington, D.C, pp. 168-198.

Fijalkowski, Tadeusz (1192), O Zatrudnieniu i Bezrabociu oraz Pomocy Spolecznej: Ustawi, Akty Wykonawcze, Objasnienia, Warsaw 1992.

Flanagan, Robert J. (1993), "Were Communists Good Human Capitalists? The Case of the Czech Republic", Stanford University, mimeo.

Golinowska, Stanislawa (1994), "Public Social Expenditures" in Social Policy and Social Conditions in Poland, Occasional Papers, Institute of Labor and Social Studies: Warsaw, pp. 29-69.

Gomulka, Stanislaw (1995), "The IMF-Supported Programs of Poland and Russia, 1990-1004: Principles, Errors, and Results", Journal of Comparative Economics, 20:3, pp. 316-345, Hollander, Paul (1991), “Politics and Social Problems” in Jones, Anthony, Walter D. Connor and David E. Powell, Soviet Social Problems, The John M. Olin Critical Issues Series, Harvard University Russian Research Center, Cambridge: Harvard University Press.

Johnson, Paul and Steven Webb (1993), "Explaining the Growth in UK Income Inequality", The Economic Journal, 103:March, pp. 429-435.

Johnson, David, Stephanie Shipp and Eva Jacobs (1994), “Expenditure Trends and Measures of Inequality: 1960-92", paper presented at the 23rd conference of the Association for Reasearch in Income
<!-- Start of picture text --> Figure 2: Changes Over Time in Governance Indicators 1998-2007<br>Voice and Accountability<br><!-- End of picture text --> <!-- Start of picture text --> 3<br>2<br>1<br>G HAHR V<br>Y U G L SO<br>KEN PER<br>N ER S LE LBR ID N 0 S GP<br>-3 -2 N GA -1 V EN 0 THA 1 2 3<br>1998<br>A FG<br>I RQ C IV -1<br>IZRN W E<br>B LR<br>ER I<br>-2<br>-3<br>Rule of Law<br>3<br>2<br>EST<br>KIR 1<br>0 T TO<br>G EO<br>-3 -2 R W AY U G -1 A 0 R G 1 2 1998 3<br>B OL<br>LB R T JK ER I<br>-1<br>C IV V EN<br>Z W E<br>-2<br>-3<br>2007<br>2007<br><!-- End of picture text --> 28
This does not necessarily represent a problem; it could simply make it more difficult to estimate a significant impact of detailed comments on inspector actions and customs outcomes in Section 5.4.

The estimates presented in panel A of Table 5 confirm that declarations that were selected for detailed comments received on average comments that were 213 characters longer than those in the control group, for which the average length of comments is 169 characters. The treated declarations were, _ceteris paribus_ , 44.3 percentage points more likely to include price information, which is a sizeable increase given that only 24.8 percent of comments on declarations in the control group mention a price of any kind. In addition, detailed comments are 10.8 percentage points more likely to refer to a prior transaction, and 6.3 percentage points more likely to refer to a weight measure. Moreover, the improvement in the quality of the comments was especially pronounced for declarations subject to higher taxes – as is shown in panel B of Table 5. This suggests that the comments became more relevant, as the RMU did a good job in providing them for the riskier declarations.

Discussions with staff from both customs and GasyNet indicated that the improvement in the RMU’s performance was the most dramatic institutional change they had witnessed. Recall that, prior to the start of the experiment, the RMU was considered to be dysfunctional. At the launch of the experiment, the head of the RMU decided to divide the unit’s work into three teams: one inspector and three analysts per team to increase internal accountability and optimize workflow. A standardized reporting framework was adopted for all teams. In less than two weeks, the RMU’s work dramatically changed. The new organizational structure incentivized the inspectors who were appointed head of their respective teams to share their knowledge with newly recruited analysts on potential fraud cases and give them advice on what to look for, e.g., historical cases of fraud for some economic operators, abnormal price valuation for some imports. Moreover, they created a database of historical fraud cases and improved documentation of their risk analysis to facilitate internal knowledge transfer. Weekly meetings were organized with all senior managers in customs and head of unit/inspectors from the RMU to discuss contentious cases in terms of goods valuation and decisions were collectively taken on how to handle such cases in order to reduce discrepancies in customs procedures across ports and inspectors. At the end of the RCT, the work organization of the RMU instituted at the start of the RCT was maintained. The transformation of the RMU 28
48

## **<u>WEB APPENDIX NOT FOR PUBLICATION</u>**

# **A Regional Patterns of Production & Consumption Cities**

**Asia.** Web Appx. Fig. D.1 shows the location of production cities and consumption cities in Asia. Unlike China, India has a mix of specialized production cities (e.g., Bangalore and Kanpur) and consumption cities (e.g., Kolkata). Apart from some large production cities in Malaysia and Vietnam, other cities in Asia (e.g, in Indonesia, the Islamic Republic of Iran, Iraq, and the Philippines) are either consumption or neutral cities.

**Africa.** Data are sparser in Africa (Web Appx. Fig. D.2). Nevertheless, one can see the dearth of production cities. With the exception of South Africa, most African cities are consumption cities, with more extreme consumption cities (in red) in Nigeria, Sierra Leone, Sudan or Mozambique. This is expected given the reliance of many African countries on resource exports, which fuels consumption in urban areas.

**Europe.** In Europe (Web Appx. Fig. D.3), countries have production and neutral cities. Productive urbanization increases as one moves away from the “edge” of Europe, i.e. Southern Spain or Eastern Turkey, in line with the division of labor and production sharing within the EU bloc and the importance of intra- and inter-regional trade.

**North America.** North America (Web Appx. Fig. D.4) has many production and neutral cities located in the Northeast or the East Coast of the United States and the North and Center of Mexico (so either where there are maquiladoras or close to Mexico City). Production cities can be seen in Central America, where production sharing brought in manufacturing activities from the United States (or Mexico) following reforms in the 1990s. Californian cities are neither consumption nor production centers, while Southern U.S. cities (e.g., Miami and Houston), coastal cities in Mexico (e.g., Acapulco and Cancun), and cities in the Dominican Republic or Haiti are (non-extreme) consumption cities (in yellow or orange).

**South America.** In South America (Web Appx. Fig. D.5), only the Southeastern areas of Brazil have production cities (S _a_  ̃o Paulo is, however, a neutral city). The rest of Brazil has consumption cities (Rio is a clear consumption city). In Argentina, Bolivia, Chile and Paraguay, cities are either neutral (e.g., Buenos Aires and Santiago de Chile) or consumption cities. Ecuador and Peru have slightly more consumption cities and Colombia and the Rep ́ublica Bolivariana de Venezuela have many large and small
1 should be at least as strong as that for good 2: accordingly, let _a_ = 0 _._ 5. Without loss of generality, set the prices of both goods in the town at unity in all periods. A survey of 30 villages in upland Orissa for the year 2009-10 (Bell and van Dillen, 2012) yields the finding that in the absence of an all-weather road, the unit transport costs for paddy, the main crop, were a bit less than 0.1, but those for other commercial crops somewhat higher. Applying the same to fertilizers, seeds and other goods bought in, households in such villages then face the price vector **p** _t_ = (0 _._ 9 _,_ 1 _._ 1) _∀ t_ . As for the trip to school, the great majority of India’s villages have a primary one of their own; but only a small minority have a secondary or high school, and in the absence of an allweather road, the daily round-trip time can be rather long. The averages for primary and secondary school pupils in the Orissa villages lacking such a road were 23 and 76 minutes, respectively. Allowing, say, twelve hours for sleeping, eating and bathing at home, and taking into account the higher opportunity costs of older children’s time, let _τ_ = 0 _._ 08. The direct costs of state schooling are surely modest: recalling (8), let _σt_ be 0.15 times the opportunity cost factor _p_ 1 _tαt_ (1 + _τ_ ) _γ_ , whereby _αt_ has yet to be determined. For the moment, we also defer discussion of the inter-temporal taste parameters _b_ 1 and _b_ 2.

Coming by estimates of premature adult mortality is a far easier task than that of morbidity. In a setting of three overlapping generations, each generation corresponds to about 20 years, the age at which full adulthood is attained. The rate _qt_ therefore corresponds to 20 _q_ 20, the probability that an individual will die before reaching 40, conditional on reaching 20. For India in 2005, WHO (2007) gives 20 _q_ 20 = 0 _._ 065 and 30<sup>_q_</sup> 20<sup>= 0</sup><sup>_._123.Somethingclosertothelatterissuitedtoourpresentpurposes,first,to</sup> allow for some mortality in the first part of old age, which the rigid time structure of the model rules out, and secondly, to reflect higher mortality among rural middle-aged adults than the all-India average. Hence, let _q_ 1 = 0 _._ 125. If history and international experience are any guides, this is sure to fall over the coming generation, PMGSY or no. It does not seem too much to hope that India will do as well then as China does now, so let _q_ 2 = 0 _._ 053. Where morbidity and disability are concerned, school-age children typically suffer less sickness than their parents, who, in turn, are in better health than their aged parents. The findings from the Orissa survey confirm as much, the average number of days of reported sickness being 5.6 a year, though the contribution of chronic ailments may not have been properly covered. It is also possible that sickness was interpreted as being too unwell to go about the usual daily business at all, as opposed to being in a state of diminished capacity to do so. Thus, the vector **d** 1 = (0 _._ 02 _,_ 0 _._ 04 _,_ 0 _._ 08) represents a rather speculative stab at an estimate for period 1. Since 14
<!-- Start of picture text --> Latin America & Carib. 2080 Mid. East & North Afr. 2080 East Asia & Pac. 2080<br>30 '' 30 ': 30 ''<br>20 20 i 20<br><!-- End of picture text --> <!-- Start of picture text --> Zz 10 z 10 : Zz 10 '<br>>g=5-10°'' g=>5 -10°'''' =>5 -10 ''<br><!-- End of picture text --> <!-- Start of picture text --> 30 H 30 t co] '<br>' g : g '<br>RCP 26 RCPB5 2 RCP 26 RCP85S 2 RCP 26 RCPBS 2 Climate models<br>= HadGEM2-ES<br><!-- End of picture text --> <!-- Start of picture text --> Sub-Saharan Africa, 2080 South Asia‘ 2080 Europe & Cent. Asia; 2080 IPSL-CM5A-LR<br>30 :' 0 : 20 :' = GFDL-ESM2MMIROC-ESM-CHEM<br>1 H ' lm NorESM1-M<br>20 \ 20 :H 20 '<br><!-- End of picture text --> <!-- Start of picture text --> = 10 z 10 : z 10<br>=&‘2<br>g° g ° : a °<br>2 -10 3 -10 i 3 0<br>ca - 1 a '<br><!-- End of picture text --> <!-- Start of picture text --> 2 2 20<br>20 20 20<br>' g H H g<br>RCP 26 RCP8S 9 RCP 26 RCP8S 2 RCP 26 RCP8S 9<br><!-- End of picture text -->
Policy Research Working Paper 7004

# **Abstract**

Do export promotion agencies impact the probability of non-exporting firms to export? In the last decade many countries have introduced export promotion agencies to support their firms to deal with asymmetric information problems and make feasible additional gains from trade. Some recent studies have found that the support of these agencies has been effective with respect to the intensive and extensive margins of trade. Nevertheless, because of the lack of information on non-exporting firms, few of them analyze their impact on the probability of promoting new exporters. This paper evaluates the impact of the Brazilian Trade and Investment Promotion Agency (ApexBrasil) on firms’ export status using a unique firm-level dataset that covers the full manufacturing sector in Brazil. To identify the impact of Apex’s assistance on firms’ export propensity, the paper relies on a procedure of matching difference-in-difference estimators. The empirical results show evidence of the program’s positive impact on the probability of promoting new exporters. The effect is heterogeneous according to firms’ size categories and sectors. Furthermore, the findings suggest that the program has spillover effects. Although the evidence of positive effect is robust, the low propensity to export for both the treated and the control groups reinforces the importance of other firms’ determinants (for example, productivity), which is widely emphasized by the trade literature.

This paper is a product of the Global Modeling and Analytics Team, Development Prospects 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 author may be contacted at mvargasdacruz@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
Figure 3

# Effect of one Additional Year of Total Education per Person on Real GDP (%)

## Percentage change in real GDP

<!-- Start of picture text --> East Asia<br>3% 1<br>Lat/n America<br>2%-<br>Mene<br>1% t<br>South Asia<br>0%<br>Afr/ca<br>3 4 5 6<br>Average years of total education<br><!-- End of picture text --> 24
Sergio Firpo and Alysson Portella. Decline in Wage Inequality in Brazil: A Survey

|**1**|**Intr**|**oduction**<br>**2**|
|---|---|---|
|**2**|**Ret**|**urns to Schooling and Experience and the Role of Relative Supply**|
||**in I**|**nequality Reduction**<br>**6**|
||2.1|Education and experience: Composition vs. price efects<br>. . . . . . . . .<br>7|
||2.2|Relative supply, quality of education, skill obsolescence and the reduction|
|||in skill and experience premia . . . . . . . . . . . . . . . . . . . . . . . .<br>8|
||2.3|Changes in occupational structure and the supply of skills<br>. . . . . . . .<br>11|
|**3**|**Cha**|**nges in Demand:**<br>**Trade Liberalization, Commodity Shocks, and**|
||**Tec**|**hnological Change**<br>**13**|
||3.1|Trade liberalization and its impact on inequality . . . . . . . . . . . . . .<br>13|
||3.2|Commodity boom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .<br>16|
||3.3|Efects of trade liberalization on regional, racial, and gender wage gaps<br>.<br>18|
||3.4|Skill- and age-biased technical change . . . . . . . . . . . . . . . . . . . .<br>21|
|**4**|**Cha**|**nges in Institutions: Minimum Wages and Formality**<br>**23**|
||4.1|Minimum wage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .<br>23|
||4.2|Role of formalization and unions. . . . . . . . . . . . . . . . . . . . . . .<br>25|
|**5**|**Con**|**clusion and a Guide for the Future**<br>**27**|
||5.1|General conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .<br>27|
||5.2|What to expect in the coming years . . . . . . . . . . . . . . . . . . . . .<br>29|

# **1 Introduction**

The rising inequality in high-income countries has received attention from the public recently, although academic circles have discussed this subject for many decades. Among the explanations for this trend, the most prominent one is perhaps the deceleration in the growth of the supply of college-educated workers coupled with an increase in demand for skilled labor due to skill-biased technological changes (Autor, 2014; Van Reenen, 2011). Advances in technology, especially computers and automation, also contributed to the polarization in employment and wages across occupations in most developed countries after the 1980s, by displacing workers in routine, codifiable jobs to service occupations at the same time that these advances complemented non-routine, cognitive-intensive jobs (Autor and Dorn, 2013). Offshoring of some jobs may also have played a role in increasing polarization (Firpo et al., 2011). Studies have also looked at the contribution of the workplace-specific wage premium and noticed that an important share of the increasing inequality was due to its increasing dispersion together with assortativeness of high-paying firms and high-productivity workers (Card et al., 2013). Finally, institutional factors 2