Skip to main content

Advertisement

SpringerLink
Log in

Contagious corruption, informal employment, and income: evidence from Brazilian municipalities

  • Original Paper
  • Published:
The Annals of Regional Science Aims and scope Submit manuscript

Abstract

Using data on 434 Brazilian municipalities, this paper explores the influence both corruption and the size of the informal sector have on economic outcomes, while allowing for the possibility of spatial dependence. Overall, this paper finds that the size of the informal sector has a statistically significant and negative association with economic outcomes that is much larger in magnitude than what is predicted by least squares estimates due to its exclusion of spillover effects, while corruption has no significant relationship. Specifically, a one standard deviation increase in the size of the informal sector is associated with a 26 % cumulative decrease in GDP per capita, compared to the maximum of a 17 % decline predicted by least squares.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. The focus on this paper is exclusively on the effect of corruption and the size of the informal sector on income levels, though the direction of the effect likely goes both ways (see, e.g., Ihrig and Moe 2004; Gundlach and Paldam 2009). However, both of these reverse effects are slow to take effect (La Porta and Shleifer 2014; Gundlach and Paldam 2009) and are likely more important in longer run analyses. This paper considers relatively shorter-term effects (a maximum of ten years). However, these reverse causality concerns will be discussed and addressed in the results section of this paper.

  2. As an example of how ignoring spatial dependence can cause OLS to either underestimate or overestimate effects of institutions on income levels, Bologna et al. (2016) find that once spatial dependence is taken into account, the positive impact of economic freedom on per capita income levels becomes larger in magnitude using US metropolitan areas as the unit of analysis.

  3. La Porta and Shleifer (2008) estimate that a country starting with 50 % of employment associated with the informal sector, and subsequently experiences a growth in per capita income of 7 % per year such that it doubles in 10 years, would only see their informal employment drop to 20 % after 50 years.

  4. However, this size has been decreasing slightly in more recent years due to an economic expansion (Corseuil and Foguel 2012). For example, informal employees accounted for 63 % of total employees in 2000, while informal employees accounted for only 56 % of total employees in 2010.

  5. See Ferraz and Finan (2011) for details on the political processes in Brazilian municipalities and for examples of corruption occurring in these municipalities.

  6. This definition of the informal sector includes military and public service employees, accounting for only about 17 % of informal employment as defined in this paper (IBGE). Results do not change when excluding military and public service employees from the definition. For brevity, these results are not presented in this paper, but are available upon request.

  7. All main results are replicated in Appendix 2 “Full tables with corruption and size informal included separately ” where I do include corruption and informal sector size separately in each regression.

  8. I additionally estimate results with \(k = 5\) and \(k = 7\) with no change in the results. Results available upon request.

  9. GeoDa software is made freely available by the GeoDa Center for Analysis and Computation within the School of Geographical Sciences and Urban Planning at Arizona State University.

  10. GeoDa output includes the Anselin–Kelejian (1997) (A–K) test statistic. The null hypothesis associated with this test is no remaining spatial autocorrelation in the error term. As reported below, the tests suggest that not all of the spatial dependence is captured by this technique. This fits with the specification testing results above; the WALD test indicates that the spatially lagged explanatory variables are especially important to include in specifications with income per worker as the dependent variable. Though the SAR results are reported as robustness checks, I consider the SDM to be the preferred specification.

  11. The correlation coefficient between these two variables is 0.285.

  12. The results in differ slightly from Bologna (2016) only because I include the additional institutional control variable.

References

  • Aidt T (2009) Corruption, institutions, and economic development. Oxf Rev Econ Policy 25:271–291

    Article  Google Scholar 

  • Anselin L (2002) Under the hood: issues in specification and interpretation of spatial regression models. Agric Econ 27:247–267

    Article  Google Scholar 

  • Anselin L, Kelejian HH (1997) Testing for spatial error autocorrelation in the presence of endogenous regressors. Int Reg Sci Rev 20(1–2):153–182

    Article  Google Scholar 

  • Attila G (2008) Is corruption contagious? An econometric analysis. NUPI Working Paper No. 742. Norwegian Institute of International Affairs (NUPI), Oslo

  • Becker SO, Egger PH, Seidel T (2009) Common political culture: evidence on regional corruption contagion. Eur J Political Econ 25(3):300–310

    Article  Google Scholar 

  • Bologna J (2015a) Corruption: the good, the bad, and the uncertain. SSRN Working Paper (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2379061)

  • Bologna J (2016) The effect of informal employment and corruption on income levels in Brazil. J Com Econ 44(3):657–695

    Article  Google Scholar 

  • Bologna J, Lacombe DJ, Young AT (2016) A spatial analysis of incomes and institutional quality: evidence from US metropolitan areas. J Inst Econ 12(1):191–216

    Google Scholar 

  • Braga B, Guillén D, Thompson B (2015) Local government spending and employment in Brazil: evidence from a natural regression discontinuity. Mimeo

  • Campos J, Lien D, Pradhan S (1999) The impact of corruption on investment: predictability matters. World Dev 27(6):1059–1067

    Article  Google Scholar 

  • Choi JP, Thum M (2005) Corruption and the shadow economy. Int Econ Rev 46(3):817–836

    Article  Google Scholar 

  • Corseuil CH, Foguel MN (2012) Economic expansion and increase in labour market formality: a poaching approach. Rev Bras Econ 66(2):207–224

    Article  Google Scholar 

  • Cravo TA, Resende GM (2014) Economic growth in Brazil: a spatial filtering approach. Ann Reg Sci 50(2):555–575

    Article  Google Scholar 

  • Cukier J, Wall G (1994) Informal tourism employment: vendors in Bali, Indonesia. Tour Manag 15(6):464–467

    Article  Google Scholar 

  • Das J, DiRienzo C (2012) Spatial decay of corruption in Africa and The Middle East. Econ Pap 31(4):508–514

    Article  Google Scholar 

  • Donchev D, Ujhelyi G (2014) What do corruption indices measure? Econ Politics 26(2):309–331

    Article  Google Scholar 

  • Dreher A, Schneider F (2010) Corruption and the shadow economy: an empirical analysis. Public Choice 144(1):215–238

    Article  Google Scholar 

  • Drukker DM, Egger P, Prucha IR (2013) On two-step estimation of a spatial autoregressive model with autoregressive disturbances and endogenous regressors. Econ Rev 32(5–6):686–733

    Article  Google Scholar 

  • Elhorst JP (2010) Applied spatial econometrics: raising the bar. Spat Econ Anal 5:9–28

    Article  Google Scholar 

  • Farrell D (2004) The hidden dangers of the informal economy. McKinsey Q 2004:26–37

    Google Scholar 

  • Ferraz C, Finan F (2008) Exposing corrupt politicians: the effects of Brazil’s publicly released audits on electoral outcomes. Q J Econ 123(2):703–745

    Article  Google Scholar 

  • Ferraz C, Finan F (2011) Electoral accountability and corruption: evidence from the audits of local governments. Am Econ Rev 101(4):1274–1311

    Article  Google Scholar 

  • Goel RK, Nelson MA (2007) Are corrupt acts contagious? Evidence from the United States. J Policy Model 29(6):839–850

    Article  Google Scholar 

  • Goel RK, Saunoris JW (2014) Global corruption and the shadow economy: spatial aspect. Public Choice 161(1–2):119–139

    Article  Google Scholar 

  • Gundlach E, Paldam M (2009) The transition of corruption: from poverty to honesty. Econ Lett 103(3):146–148

    Article  Google Scholar 

  • Hall RE, Jones CI (1999) Why do some countries produce so much more output per worker than others? Q J Econ 114(1):83–116

    Article  Google Scholar 

  • Higgins MJ, Levy D, Young AT (2006) Growth and convergence across the US: evidence from county-level data. Rev Econ Stat 88(4):671–681

    Article  Google Scholar 

  • Hussmanns R (2005) Measuring the informal economy: from employment in the informal sector to informal employment. Policy Integration Department Working Paper No. 53, Bureau of Statistics International Labour Office, Geneva

  • Ihrig J, Moe KS (2004) Lurking in the shadows: the informal sector and government policy. J Dev Econ 73(2):541–557

    Article  Google Scholar 

  • Kelejian HH, Murrell P, Shepotylo O (2013) Spatial spillovers in the development of institutions. J Dev Econ 101:297–315

    Article  Google Scholar 

  • La Porta R, Shleifer A (2008). The unofficial economy and economic development. NBER Working Paper Series No. 14520

  • La Porta R, Shleifer A (2014) Informality and development. J Econ Perspect 28(3):109–126

    Article  Google Scholar 

  • LeSage JP, Pace RK (2010) The biggest myth in spatial econometrics. SSRN Working Paper (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1725503)

  • LeSage J, Fischer M (2008) Spatial growth regressions: model specification, estimation and interpretation. Spat Econ Anal 3(3):275–304

    Article  Google Scholar 

  • LeSage J, Pace RK (2009) Introduction to spatial econometrics. Taylor and Francis CRC Press, Boca Routon

    Book  Google Scholar 

  • Loayza NA (1996) The economics of the informal sector: a simple model and some empirical evidence from Latin America. Carnegie Rochester Conf Ser Public Policy 45:129–162

    Article  Google Scholar 

  • Magalhães A, Hewings G, Azzoni C (2005) Spatial dependence and regional convergence in Brazil. Investig Reg 6:5–20

    Google Scholar 

  • Mauro P (1995) Corruption and growth. Q J Econ 110(3):681–712

    Article  Google Scholar 

  • McMillan J, Zoido P (2004) How to subvert democracy: Montesinos in Peru. J Econ Perspect 18(4):69–92

    Article  Google Scholar 

  • Meghir C, Narita R, Robin J (2015) Wages and informality in developing countries. Am Econ Rev 105(4):1509–1546

    Article  Google Scholar 

  • Olken BA (2007) Monitoring corruption: evidence from a field experiment in Indonesia. J Political Econ 115(2):200–249

    Article  Google Scholar 

  • Olken BA (2009) Corruption perceptions vs. corruption reality. J Public Econ 93(7–8):950–964

    Article  Google Scholar 

  • Olken BA, Barron P (2009) The simple economics of extortion: evidence from trucking in Aceh. J Political Econ 117(3):417–452

    Article  Google Scholar 

  • Olken BA, Pande R (2012) Corruption in developing countries. Ann Rev Econ 4:479–509

    Article  Google Scholar 

  • Pederson S (2003) The shadow economy in Germany, Great Britain, and Scandinavia: A measurement based on questionnaire surveys. Research Unit Study No. 5, The Rockwool Foundation Research Unit, Copenhagen

  • Reinikka R, Svensson J (2005) Fighting corruption to improve schooling: evidence from a newspaper campaign in Uganda. J Eur Econ Assoc 3(2–3):259–267

    Article  Google Scholar 

  • Resende GM (2013) Spatial dimensions of economic growth in Brazil. ISRN Economics 2013: doi:10.1155/2013/398021

  • Rey SJ, Montouri BD (1999) U.S. regional income convergence: a spatial econometric perspective. Reg Stud 32(2):143–156

    Article  Google Scholar 

  • Schneider F (2005) Shadow economies around the world: what do we really know? Eur J Political Econ 21(3):598–642

    Article  Google Scholar 

  • Schneider F (2007) Shadow economies and corruption all over the world: new estimates for 145 countries. Econ Open Access Open Assess E-J 9(2):1–53. doi:10.5018/economics-ejournal.ja.2007-9

    Google Scholar 

  • Schneider F, Enste DH (2000) Shadow economies: size, causes, and consequences. J Econ Lit 38(1):77–114

    Article  Google Scholar 

  • Schneider F, Williams CC (2013) The shadow economy. The Institute of Economic Affairs, London

    Book  Google Scholar 

  • Seldadyo H, Elhorst JP, De Haan J (2010) Geography and governances: Does space matter? Pap Reg Sci 89(3):625–640

    Article  Google Scholar 

  • Sequeira S, Djankov S (2010) An empirical study of corruption in ports. MPRA Paper 21791, University Library of Munich, Germany

  • Shleifer A, Vishny RW (1993) Corruption. Q J Econ 108(3):599–617

    Article  Google Scholar 

  • Treisman D (2007) What have we learned about the causes of corruption from ten years of cross-national empirical research? Ann Rev Political Sci 10:211–244

    Article  Google Scholar 

  • Ulyssea G (2006) Informality in the Brazilian labor market: a literature review. Rev Econ Política 26(4):596–618

  • Wei S (1997) Why is corruption so much more taxing than tax? Arbitrariness kills. NBER Working Paper No. 6255

Download references

Acknowledgments

I would like to thank Claudio Ferraz and Frederico Finan for kindly sharing their data.

Author information

Authors and Affiliations

  1. College of Business and Economics, West Virginia University, Morgantown, WV, 26506-6025, USA

    Jamie Bologna

Authors
  1. Jamie Bologna
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jamie Bologna.

Appendices

Appendix 1: full tables

See Tables 9, 10, 11, 12, 13, 14, 15, 16, and 17.

Table 9 Benchmark OLS estimates of the impact corruption and the size of the informal economy have on GDP per capita and total income per worker from Bologna (2016)
Full size table
Table 10 Direct, indirect, and total effects of corruption and the size of the informal economy on GDP per capita in 2004
Full size table
Table 11 Direct, indirect, and total effects of corruption and the size of the informal economy on total income per worker in 2000
Full size table
Table 12 Direct, indirect, and total effects of corruption and the size of the informal economy on GDP per capita in 2010
Full size table
Table 13 Direct, indirect, and total effects of corruption and the size of the informal economy on total income per worker
Full size table
Table 14 SAR Model raw coefficient estimates of the effect of corruption and the size of the informal economy on GDP per capita in 2004 and total income per worker in 2000
Full size table
Table 15 SAR Model raw coefficient estimates of the effect of corruption and the size of the informal economy on GDP per capita in 2010 and total income per worker in 2010
Full size table
Table 16 SAR Model marginal effects estimates of the direct, indirect, and total effects of corruption and the size of the informal economy on GDP per capita and income per worker in the first period of interest
Full size table
Table 17 SAR Model marginal effects estimates of the direct, indirect, and total effects of corruption and the size of the informal economy on GDP per capita and income per worker in the second period of interest
Full size table

Appendix 2: full tables with corruption and Size Informal Included Separately

See Tables 18, 19, 20, 21, 22, 23, 24, and 25.

Table 18 Direct, indirect, and total effects of corruption on GDP per capita in 2004
Full size table
Table 19 Direct, indirect, and total effects of corruption on total income per worker in 2000
Full size table
Table 20 Direct, indirect, and total effects of corruption on GDP per capita in 2010
Full size table
Table 21 Direct, indirect, and total effects of corruption on total income per worker in 2010
Full size table
Table 22 Direct, indirect, and total effects of the size of the informal economy on GDP per capita in 2004
Full size table
Table 23 Direct, indirect, and total effects of the size of the informal economy on total income per worker in 2000
Full size table
Table 24 Direct, indirect, and total effects of the size of the informal economy on GDP per capita in 2010
Full size table
Table 25 Direct, indirect, and total effects of the size of the informal economy on total income per worker in 2010
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bologna, J. Contagious corruption, informal employment, and income: evidence from Brazilian municipalities. Ann Reg Sci 58, 67–118 (2017). https://doi.org/10.1007/s00168-016-0786-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00168-016-0786-1

JEL Classification

Search

Navigation