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Financial development and inequality: Brazil 1985–1994

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Abstract

We examine the impact of financial development on earnings inequality in Brazil in the 1980s and first half of the 1990s. The evidence—based initially on time-series, and then on the relatively novel panel time-series data and analysis—shows that financial development had a significant and robust effect in reducing inequality during the period. We suggest that this is not only because the poorer can invest the acquired credit in either short or long-term productive activities, but also because those with access to financial markets can insulate themselves, via a process of financial adaptation, against recurrent poor macroeconomic performance, which is exemplified in Brazil by high rates of inflation. The main implication of the results is that a deeper and more active financial sector alleviates the high inequality seen in Brazil without the need for distortionary taxation.

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Notes

  1. Moreover, panel time-series does not suffer from the usual criticism applied to cross-sectional analysis, (i.e. that periods of high inflation are usually followed by short periods of low inflation, which would cancel each other out and therefore bias the estimates). See Bruno and Easterly (1998).

  2. In addition, Aghion and Bolton (1997) argue that more access to credit is not a sufficient condition to reduce inequality because the trickle-down mechanism occurs only at very high rates of capital accumulation. Because of that they advocate some redistribution, which would improve economic efficiency and welfare in the early stages of development.

  3. In addition, dollarisation was widely used in some Latin American countries, (e.g. Argentina, Uruguay and Peru), as an instrument of protection against high inflation. However, in Brazil dollarisation was never fully implemented, and therefore it did not play such a role against high inflation, see Singh (2006). Furthermore, an IDB (2005) report argues that private credit in Latin America is at 28% of the GDP, and in developed countries the same measure is at 84% of the GDP, which illustrates how restrictive the financial sector is in Latin America in general, and how limited the protection offered by financial institutions against high inflation tends to be.

  4. For more about the the Real Plan, see Agénor and Montiel (2008).

  5. See Corseuil and Foguel (2002) for more details on how to best deflate earnings and income data from Brazil.

  6. For more on inequality measures and their properties, see Sen and Foster (1997).

  7. See Beck et al. (2001) for more on measures of financial development.

  8. For more on the problem of financial repression in developing countries, see Agénor and Montiel (2008) or Easterly (2002).

  9. In addition, we also check for unit roots using the test provided by Ng and Perron (2001), which takes into account the structural breaks taking place during the hyperinflationary bursts, and the results confirm the ones above.

  10. Additionally, we run a regression with PERSONAL in levels, since the Ng-Perron test suggests stationarity in this case. The estimate is not statistically significant, though.

  11. An alternative is the test by Levin et al. (2002), however this test ignores the possibility of heterogeneity in panels, and is therefore restrictive.

  12. Moreover, the reason for not using a GMM-type estimator is because under T > N we would incur overfitting. Also important to mention is that GMM estimators break down when the variables are believed to be I(1). See Smith and Fuertes (2008) or Bond (2002).

  13. See Chamberlain (1992), or Anderson and Hsiao (1981, 1982).

  14. For example, Boyd et al. (2001) argue that inflation presented detrimental effects to financial development in a panel of countries between 1960 and 1995, and Bittencourt (2008) confirms these detrimental effects using Brazilian data.

  15. Alternatively, some would argue that the high inflation rates might have a direct impact on inequality. See, for instance, Cardoso et al. (1995), de Barros et al. (2000), Ferreira and Litchfield (2001), and Bittencourt (2009) for the direct regressive effect of high rates of inflation on inequality in Brazil.

  16. Additionally, Phillips and Moon (1999) argue that a spurious regression under T > N is less of a problem. This is because the pooled estimators are averaging over the regions, and therefore the noise is attenuated and the estimates consistent.

  17. In addition, the imperfect wage indexation due to the lower bargaining power by the poor is believed to have played a role in compressing lower wages at the time. See Dornbusch and Simonsen (1983).

  18. Fiess et al. (2007) report evidence using Brazilian data covering the period of 1983–1989, which suggests that the underground economy played an important role in absorbing displaced workers from the formal sector at the time.

  19. Singh (2006), Singh and Cerisola (2006), and Santiso (2006) highlight the importance of the much improved macroeconomic performance in Latin America recently to produce better economic outcomes. Furthermore, Carvalho and Chamon (2008) argue that after the reforms of the 1990s the Brazilian income has grown by much more than the official figures suggest, which reinforces the importance of macroeconomic stability on welfare in general.

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Acknowledgments

I thank Paul Gregg, Ron Smith, Frank Windmeijer, Melanie Khamis, Yuji Tamura, Fabien Postel-Vinay, Jonathan Temple, Nauro Campos and seminar participants at Bristol, RES in Nottingham, Verein für Socialpolitik in Berlin, DEGIT XI in Jerusalem, EEA in Vienna, SAE in Oviedo, RES in London, ECINEQ in Berlin, ERSA Institutions and Growth Workshop in Cape Town and three referees for comments. Financial support from the Economics Department at Bristol and Economic Research Southern Africa is acknowledged.

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  1. Department of Economics, University of Pretoria, Lynnwood Road, Pretoria, 0002, South Africa

    Manoel Bittencourt

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Correspondence to Manoel Bittencourt.

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Bittencourt, M. Financial development and inequality: Brazil 1985–1994. Econ Change Restruct 43, 113–130 (2010). https://doi.org/10.1007/s10644-009-9080-x

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