rafmacalaba/datause-encoder-data huggingface dataset:
services to formal firms is low, and the state’s monitoring and enforcement power is weak.

These cost and benefit considerations are affected by the structural characteristics of underdevelopment, dealing in particular with educational achievement, production structure, and demographic trends. Other things equal, a higher level of education reduces informality by increasing labor productivity and, therefore, making labor regulations less onerous and formal returns potentially larger. Likewise, a production structure tilted towards primary sectors like agriculture, rather than to the more complex processes of industry, favors informality by making legal protection and contract enforcement less relevant and valuable. Finally, a demographic composition with larger shares of youth or rural populations is likely to increase informality by making monitoring more difficult and expensive, by placing bigger demands on resources for training and acquisition of abilities, by creating bottlenecks in the initial school-to-work transition, and by making more problematic the expansion of formal public services (see Fields, 1990; Schneider and Enste, 2000; ILO, 2004).

Popular and even academic discussions often focus on particular sources of informality, rather than taking this comprehensive approach. Thus, some observers stress insufficient enforcement and related government weaknesses such as corruption; others prefer to emphasize the burden of taxes and regulations; yet others concentrate on explanations dealing with social and demographic characteristics.

As suggested above, all these possibilities make sense, and there is some evidence to support each of them. To illustrate this, Figure 2 presents cross-country scatter plots of each of the four measures of informality versus proxies for the major proposed determinants of informality. The sample observations include all countries with available data, and, for illustration purposes, countries in Latin America and the Caribbean are highlighted in the figures. The proxies for the determinants of informality are as follows.<sup>9</sup> An index on the prevalence of law and order --obtained from _The International Country Risk Guide_ -- to proxy for both the quality of formal public services and government’s enforcement strength. An index of business regulatory freedom --taken from Fraser Foundation’s _Economic Freedom of the World Report_ -- to represent the ease

> 9 Again, details on definitions and sources of all variables are presented in Appendix 2.

9
# **5.2.2 Aggregate model with GDP**

In this subsection we introduce GDP as the main pressure-of-demand variable, while in the former sub-section we used the unemployment rate. We present our findings in Table 4. Again, nominal wages are explained by prices, a deterministic time trend, policy dummy variables, and our pressure of demand variable, GDP. As above, the pattern of wages in the beginning of the 1980s is out of line with the developments of the economy. That is, wages are too high and to capture this, we include dummy variables (D1984 and D80-84). On the basis of the diagnostic test statistics presented in the bottom of Table 4 and charts presented in Figures 9 and 10, we observe no evidence of model misspecification.

The findings reveal that the pressure-of-demand variable affects wages positively both in the short and long term, revealed by the statistically significant impact on wages from both GDP growth and GDP in levels. This indicates that the strength of demand in the labor market is important for Zimbabwean wages.

**Figure 9 Residual plots, ECM for total wages (including GDP)**

<!-- Start of picture text --> DLT t_w<br>25~~~~~~~~~.<br>.2~~~~~~~~~.<br>.8e<br>lS75 1985 1995 1975 1985 1995<br>Corr." loUr; c"*leiw D ... i ts<br>DLTot_* DSo= Sol<br>-. 6 .2 /<br>2 3 4 5 -4 -3 -2 -1 0 X 2 3 4 5<br><!-- End of picture text --> 23
The community social capital index is constructed as an average of binary variables pertaining to the presence of a town hall, a community hall, a church, or a park in the barangay. The commercial capital index is constructed by adding barangay-level variables on the number of financial institutions, industrial establishments and stores and dividing by 30 (the highest number attained'<sup>4</sup> ).

Summary statistics on the model variables can be found in Annex Table 1.

In order to capture any omitted (observable as well as unobservable) provincial/sectoral level determinants of consumption, we also allow for strata fixed effects where 168 strata are identified by the rural and urban sectors of individual provinces.

In the simple construct of model (1), the y-parameters yield measures of the impact of the crisis on household living standards. For instance, an estimated value of -0.05 for J implies that the exposure to labor market shock alone reduces per capita consumption by _5%._ However, model (1) also carries the implication that a given shock has the same proportional impact on consumption for all households affected by that shock. This seems an overly strong assumption. Presumably, a shock may hit some households more severely than others, and similarly, some households may be better able to protect their living standards than others when hit by a particular shock. For instance, the impact of a wage shock may depend on the education level of the workers and the effect of drought may depend on the ownership of land. In general, the impact of the shock would be expected to be a function of the characteristics and circumstances faced by the household. This consideration leads us to an augmented version of model (1) where we interact shock variables with a set of household and community characteristics (Zj):

> 14 For each of these three indicators, the APIS questionnaire records the actual number if less than 10, and records 10 if there are 10 or more of them in the _barangay._

12
<!-- Start of picture text --> 1980s m@ 7990-1994 O74 995-99 Oo 2000H4 @ 2005-06 me2o00F<br>60)<br>50)<br>od<br>=<br>we «40<br>&<br>[=]<br>=<br>= 30<br>i=]<br>o<br>S<br>rs 20)<br>=w<br>10<br>if<br>Trade and Economic Social sectors Public Sector Financial and Private<br>Management Govemance Sector Development<br>B<br>3<br>3<br>Bo<br>34<br>S<br>Ka}<br>g<br>E &<br>2<br>Oo<br>0 50 100 150 200<br>total number of PSG conditions<br><!-- End of picture text -->
and the Society of Government Economists, at the meetings of the American Economic Association, New Orleans, January 6, 2001.

Frankel, Jeffrey A. Regional Tradinig Blocs: In the World Economic System. Washington DC: Institute for International Economics, 1997.

Frankel, Jeffrey A. (1999a) "No Single Currency Regime Is Right for all Countries or at All Times." Essays in International Finance, No. 215. New Jersey: International Finance Section, Department of Economics, Princeton University, 1999.

Frankel, Jeffrey A. (1 999b) "The International Financial Architecture." Policy Brief _#51._ Washington, DC: The Brookings Institution, June 1999. <http://www.brook.edu/comm/PolicyBriefs/pbO51/pb51 .htm>.

Frankel, Jeffrey A. "The Asian Financial Crisis in Perspective." Regional Co-operation & Asian Recovery. Ed. Peter Petri. Singapore: Institute of Southeast Asian Studies, 2000. 20-35.

Frankel, Jeffrey, Eduardo Fajnzylber, Sergio Schmukler, and Luis Serven. "Verifying Exchange Rate Regimes." Draft of paper prepared as part of the Regional Studies Program of the Latin American and Caribbean Region of the World Bank. 17 May 2000.

Frankel, Jeffrey, Sergio Schmukler and Luis Serven. "Global Transmission of Interest Rates: Monetary Independence and the Exchange Rate Regime." Washington, DC: World Bank, 2000.

Freeman, Nick J. "A Regional Platform for Trading Southeast Asian Equities: Viable Option or Lofty 'Red Herring'?" Singapore: Institute of Southeast Asian Studies, 2000.

Freeman, Nick J. and Frank L. Bartels. "Portfolio Investment in Southeast Asia's Stock Markets: A Survey of Institutional Investors' Current Perceptions and Practices." Singapore: Institute of Southeast Asian Studies, April 2000.

Fukasaku, Kiichiro and Fukunari Kimura. "Globalization and Intra-Firm Trade: Further Evidence." Frontiers of Research in Intra-industry Trade. Eds. P.J. Lloyd and Hyun-Hoon Lee. Basingstoke: Palgrave, 2002.

Glick, Reuven. "Fixed or floating: is it still possible to manage in the middle? Financial Markets and Policies in East Asia. Ed. G. de Brouwer. London: Routledge, 2002. 200234.

Goldberg, Linda S. and Michael W. Klein. "Foreign Direct Investment, Trade and Real Exchange Rate Linkages in Southeast Asia and Latin America." NBER Working Paper 6344. Cambridge, MA: NBER, 1997.

136
# **Distributional Effects of Competition: A Simulation Approach**<sup>**1**</sup>

Carlos Rodríguez-Castelán<sup>2</sup> Abdelkrim Araar<sup>3</sup> Eduardo A. Malásquez<sup>4</sup> Sergio Olivieri<sup>5</sup> Tara Vishwanath<sup>6</sup>

**Keywords:** Poverty, Inequality, Market concentration, Distributional Effects, Simulation, Mexico **JEL codes:** C15, D31, D42, D43, E37

> 1 The authors would like to thank Rogelio Granguillhome for his outstanding research assistance. The authors would also like to thank two peer reviewers of a World Bank Quality Enhancement Review (QER) meeting: Samuel Freije-Rodriguez and Jasmin Chakeri. The paper and the simulation method have also benefited from comments by Paloma Anos-Casero, Najy Benhassine, Carolina SanchezParamo, Ambar Narayan, Oscar Calvo-Gonzalez, Mark Dutz, Mariana Vijil, Carlos Urzúa, Siddharth Sharma, Francesca de Nicola, Carlos Silva-Jauregui, Luis Felipe Lopez-Calva, Lourdes Rodriguez-Chamussy, Dennis Medvedev, Alan Fuchs, Moritz Muller, Martha Martinez Licetti, Tanja Goodwin, Mariana Iootty, Christine Qiang, Peter Kusek, Bob Rijkers, Leonardo Iacovone, Camilo Mondragon, Jan Imhof, Gabriel Lara, Rose Mungai, Arden Finn, and participants at the World Bank Poverty and Equity Global Practice (GP) BBL series (launch event of WELCOM), the World Bank Macroeconomics, Trade and Investment GP Week, the Poverty and Equity GP Management Team meetings, the Poverty and Equity GP 2018 Learning Week, and staff meetings of regional teams of the Poverty and Equity GP for South Asia and the Middle East and North Africa, as well as the Investment and Competition team of the Finance, Competitiveness, and Innovation GP and IFC. This paper was partially funded by the U.K. Prosperity Fund “Improving Business Environment for Prosperity” (IBEP) TF. The findings, interpretations, and conclusions in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank Group, its Executive Directors, or the countries they represent.

> 2 Lead Economist, Poverty and Equity GP, World Bank (crodriguezc@worldbank.org) (corresponding author)

> 3 Research Fellow, University of Laval, World Bank and PEP (aabd@ecn.ulaval.ca)

> 4 Economist, Poverty and Equity GP, World Bank (emalasquez@worldbank.org)

> 5 Senior Economist, Poverty and Equity GP, World Bank (solivieri@worldbank.org)

> 6 Lead Economist, Poverty and Equity GP, World Bank (tvishwanath@worldbank.org)
**Bolivia:** The total payroll tax for pensions is actually about 15 percent when the mandatory "Fondos Complementarios" are included.

In addition, the payroll tax rates found in Appendix Table A.7 of the book include several errors which are described in Section II of this annex. In addition, footnote (a) on page 368, should read "Total labor cost is defined here as taxable wages plus employer share of payroll tax for pensions" and on the same page, footnote d should read, "The pension payroll tax for France and Switzerland includes mandatory occupational schemes." Since publication of the study, the USSSA has published data for 1993 which are not included in the STARS data diskette. Preliminary analysis suggest that payroll tax rates rose in at least 28 countries between 1991 and 1993, continuing the trend over the last several decades. Data for the payroll tax for pensions for 1961 and 1981 also appear in STARS for many countries.

# **Section III Privately-Managed Pension Schemes**

This section reviews data related to privately-managed pension coverage which appear in various parts of the report but are concentrated in Chapters 5 and 6. For much of the data used in these chapters, the reader should refer to the cited sources for more information. For example, the methodology and sources for the investment portfolios and simulated rates of return to occupational pension schemes in the OECD which appear in Chapter 5 are explained in Davis (1993).

# A. **Coverage in Privately-Managed Occupational Pension Schemes**

Table 5.1 presents occupational pension coverage data from a variety of sources. For the most part, occupational pensions for state or state enterprise employees which are operated as supplementary pension schemes over and above the main national scheme are included in these statistics. For example, about half of workers covered by occupational schemes in Brazil work for state enterprises. Another example is found in the second column where the Luxembourg Income Study data on the percentage of persons over 65 receiving occupational pensions includes supplementary pensions of public employees. In other words, some occupational pension schemes are publicly-managed.

44
Table 5: Correlation of district traits and 1-person establishment development

||Overall<br>growth<br>1989→2010<br>|Overall<br>growth<br>2000→2010<br>|1-Person<br>firm growth<br>1989→2010<br>|1-Person<br>firm growth<br>2000→2010<br>|Average 1-person<br>firm employment<br>share 1989-2010<br>|Tradables 1-<br>person firm<br>growth<br>1989→2010<br>|Tradables 1-<br>person firm<br>growth<br>2000→2010<br>|Tradables 1-person<br>firm employment<br>share 1989-2010<br>|
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Log population|-0.24*|-0.19*|-0.07|-0.09|-0.38*|-0.02|-0.10*|-0.16*|
|Log population density|0.07|-0.06|0.02|-0.11*|-0.10*|-0.02|-0.12*|-0.02|
|Share of population that is urban|0.01|-0.05|0.00|-0.02|-0.32*|0.10*|0.08|-0.06|
|Share of population that is middle aged (15-49)|0.04|0.08|0.00|0.08|-0.16*|0.06|0.08|-0.07|
|Share of population in scheduled caste/tribe|-0.08|-0.08|-0.05|-0.13*|-0.15*|-0.09|-0.07|0.01|
|Female labor force participation rate|0.04|0.04|0.01|0.02|0.35*|-0.03|-0.06|0.19*|
|Educated worker share (middle and up)|0.08|0.03|0.07|0.11*|0.05|0.14*|0.06|0.07|
|Literacy rate|-0.02|-0.03|0.00|0.02|-0.10*|0.10*|0.01|0.06|
|Infrastructure: share of villages with electricity|-0.08|-0.09|0.01|-0.10*|-0.04|0.05|0.04|0.19*|
|Infrastructure: share of villages with paved roads|-0.04|-0.06|0.01|-0.06|-0.28*|0.09|-0.05|0.04|
|Labor laws strength|-0.06|0.01|-0.03|0.00|-0.05|0.00|0.02|-0.06|
|Travel time to nearest of India's ten largest cities|0.02|0.05|-0.03|0.02|0.30*|-0.05|0.01|0.29*|
|Share of households with a bank account|0.01|-0.08|-0.01|-0.09|-0.17*|-0.01|-0.08|0.09*|

Notes: Table documents correlations between district traits and the development of 1-person establishments. District traits are from the 2001 Population Census. District traits are expressed in log values or percentage point values as indicated. We winsorize variables at their 1%/99% values. An asterisk denotes a correlation is statistically significant at the 10% level.
- [18] Harding, D. and A. R. Pagan (2002). “Dissecting the Cycle: A Methodological Investigation,” Journal of Monetary Economics, 49, 365-381.

- [19] Huidrom, R., A. Kose, and F. Ohnsorge (2016). “Having Space and Using It: Fiscal Policy Challenges in Developing Economies,”CEPR Working Paper forthcoming.

- [20] Ilzetzki, E. O., E. G. Mendoza, and C. A. Vegh (2013). “How Big (Small?) Are Fiscal Multipliers?”Journal of Monetary Economics, 60, 239-254.

- [21] Kraay, A. C. (2012). “How Large Is the Government Spending Multiplier? Evidence from World Bank Lending,”Quarterly Journal of Economics, 127, 829-887.

- [22] Mineshima, A., M. Poplawski-Ribeiro, and A. Weber (2014). “Size of Fiscal Multipliers,” in Post-Crisis Fiscal Policy, ed. by C. Cottarelli, P. Gerson, and A. Senjadji, Cambridge, MA: MIT Press, 315-372.

- [23] Nickel, C. and A. Tudyka (2014). “Fiscal Stimulus in Times of High Debt: Reconsidering Multipliers and Twin Deficits,”Journal of Money, Credit, and Banking, 46(7), 1313-1344.

- [24] Owyang, M. T., V. A. Ramey, and S. Zubairy (2013). “Are Government Spending Multipliers Greater during Periods of Slack? Evidence from Twentieth-Century Historical Data,” American Economic Review, 103, 129-134.

- [25] Perotti, R. (1999). “Fiscal Policy in Good Times and Bad,”Quarterly Journal of Economics, 114, 1399-1436.

- [26] – – —(2005). “Estimating the Effects of Fiscal Policy in OECD Countries,”CEPR Discussion Paper 4842.

- [27] Ramey, V.A. (2011). “Identifying Government Spending Shocks: It’s all in the Timing,”Quarterly Journal of Economics 126, 1-50.

- [28] Ramey, V.A. and S. Zubairy (2014). “Government Spending Multipliers in Good Times and in Bad: Evidence from U.S. Historical Data,”NBER Working Paper No. 20719

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15
Policy Research Working Paper 9985

# **Abstract**

Exclusionary policies, such as limits on refugees’ movement and the right to work, are often justified as reasons to minimize economic and social tensions with host communities. While these policies have a negative effect on refugees’ economic outcomes, their ability to mitigate frictions with host communities is unknown. Inclusionary policies, on the other hand, could foster mutual gains and positive relations. This paper builds an extensive dataset of attitudes and economic outcomes, refugee populations, and policies at the sub-national level covering 14 years (2005-2018) and most low- and middle-income countries. Using event study and difference-in-differences methodologies, it assesses the effects of the arrival of large waves of refugees and finds little evidence that large refugee arrivals have a negative effect on average attitudes or economic outcomes in the short-term. There are also no significant differences between places with restrictive and inclusive policies, including de jure access to the labor market and opening camps.

This paper is a product of the Social Sustainability and Inclusion Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at aksoyc@ebrd.com.

_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
||**(1)**|**(2)**<br>**Table A.1.**|**(3)**<br>**Determinan**|**(4)**<br>**ts of the Bil**|**(5)**<br>**ateral Curr**|**(6)**<br>**ent Account**|**(7)**<br>|**(8)**|**(9)**|
|---|---|---|---|---|---|---|---|---|---|
|Constant|-0.006<br>[11.119]|-0.003<br>[1.912]|-0.006<br>[3.805]|-0.007<br>[4.904]|-0.004<br>[2.649]|-0.011<br>[4.631]|-0.015<br>[6.959]|-0.014<br>[6.256]|-0.009<br>[3.727]|
|Dom. Savings*(NFA/W)|0.265<br>[3.192]|||||||||
|Dom. Savings||0.241|0.297|0.302|0.152|0.058|0.078|0.075|0.043|
|||[2.905]|[3.625]|[3.280]|[2.065]|[4.346]|[7.764]|[6.686]|[3.423]|
|For. Savings||0.025|0.021|0.017|0.019|-0.014|-0.023|-0.028|-0.023|
|||[1.563]|[1.073]|[0.810]|[1.055]|[2.615]|[4.146]|[5.159]|[4.476]|
|US Long-term Bond||-0.234|-0.017||-0.272|-0.126|-0.033||-0.131|
|||[2.960]|[0.826]||[3.966]|[5.551]|[3.920]||[6.068]|
|US Short-term Bond||0.153||-0.004|0.179|0.08||-0.016|0.094|
|||[2.411]||[0.209]|[3.176]|[4.011]||[2.194]|[4.915]|
|US Stocks|||0.003|0.002|0||0.002|0.002|0.004|
||||[0.542]|[0.439]|[0.065]||[1.355]|[1.164]|[2.690]|
|JP Long-term Bond||0.244|0.013||0.377|0.038|0.007||0.058|
|||[2.411]|[1.369]||[3.369]|[1.538]|[2.763]||[2.526]|
|JP Short-term Bond||-0.233||0.011|-0.349|-0.029||0.005|-0.042|
|||[2.241]||[1.004]|[3.065]|[1.201]||[1.761]|[1.850]|
|JP Stocks|||-0.006|-0.006|-0.01||-0.006|-0.006|-0.007|
||||[1.296]|[1.230]|[2.415]||[4.762<br>]|[<br>4.901]|455<br>[5.<br>]|
|D.US Long-term Bond||-0.047|0.057||-0.092|-0.049|-0.006||-0.041|
|||[0.528]|[1.003]||[1.103]|[3.167]|[0.477]||[2.793]|
|D.US Short-term Bond||-0.024||0.027|0.077|0.057||-0.019|0.093|
|||[0.338]||[0.542]|[1.166]|[1.910]||[0.753]|[3.171]|
|D.US Stock|||0.006|0.006|0.002||0.000|-0.001|0.002|
||||[1.136]|[1.076]|[0.616]||[0.139]|[0.290]|[1.105]|
|D.JP Long-term Bond||0.048|0.014||0.146|0.056|0.004||0.101|
|||[0.566]|[1.899]||[1.297]|[1.331]|[1.250]||[2.478]|
|D.JP Short-term Bond||-0.044||0.018|-0.13|-0.053||0.002|-0.094|
|||[0.522]||[1.537]|[1.181]|[1.244]||[0.570]|[2.279]|
|D.JP Stock|||-0.001|-0.002|0.000||-0.003|-0.003|-0.004|
||||[0.180]|[0.418]|[0.109]||[2.350]|[2.340]|[3.055]|
|Observations|35|34|34|34|34|180|180|180|180|
|R-squared<br>This table reports the regre<br>changes in expected asset r<br>domestic and foreign saving<br>percentage of U.S. total we<br>of observations._t-statistics_|0.24<br>ssions of the <br>eturns. Expec<br>s are expresse<br>alth. Expected<br>are shown in|0.68<br>bilateral curren<br>ted asset return<br>d as a percenta<br>asset returns a<br>brackets.|0.57<br>t account betw<br>s are obtained <br>ge of GNP. Net<br>re denominated|0.54<br>een Japan and <br> from the VAR<br>foreign asset<br>in U.S. dollar|0.82<br> the U.S. on: <br> estimation pr<br>positions, take<br>s. The table al|0.60<br>domestic and f<br>esented in Tab<br>n from Lane an<br>so shows the R|0.62<br>oreign savings<br>le 2. The bilat<br>d Milesi-Ferre<br>-squared for e|0.59<br>, expected ass<br>eral current ac<br>tti (2005), are<br>ach equation a|0.67<br>et returns, and<br>count and the<br>expressed as a<br>nd the number|
# Month of Birth and Children’s Health in India

_Michael Lokshin and Sergiy Radyakin_<sup>_*_</sup> The World Bank

**Keywords** : Nutrition, anthropometry, child health, seasonality, poverty, India

**JEL:** J12, I32, O12

> *Michael Lokshin <u>mlokshin@worldbank.org</u> and Sergiy Radyakin <u>sradyaking@worldbank.org</u> are both at the Development Research Group, World Bank, 1818 H Street NW, Washington D.C., 20433, USA. We thank Harold Alderman, Jishnu Das, Monica Das Gupta, and Toan Q. Do for their constructive comments. The findings, interpretations and conclusions of this paper are those of the authors and should not be attributed to the World Bank, its Executive Directors or the countries they represent.