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The end of Brazilian big inflation: lessons to monetary policy from a standard New Keynesian model

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Abstract

The paper analyzes economic stabilization in Brazil in the context of a New Keynesian model estimated with Bayesian techniques. Dataset covers the period 1975–2012. Our methodology is based on tests for multiple structural breaks at unknown dates and counterfactual exercises. The results show that inflation and output volatility present an inverted U-shape pattern, peaking at the 1985–1994 sample. Changes in the monetary policy stance and milder shocks accounted for the reduced inflationary volatility (about 50% each, in some specifications). However, some assumptions indicated that a sharp decline in the Phillips curve slope was also important for controlling inflation. Concerning to output, the sole explanation for its volatility fall seemed to be smaller shocks. Therefore, we conclude that a mix of the “good luck” and “good policy” hypotheses mainly originated the current period of increased stability in the country.

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Notes

  1. In July 1994, Brazilian government launched a monetary plan in order to fight soaring inflation rates, the so-called Real Plan.

  2. Measured by the cyclical component of HP-filter decomposition (\(\lambda =1600\); Hodrick and Prescott 1997). GDP data are provided by Bonelli and Rodrigues (2012).

  3. General Price Index—Internal Availability (IGP–DI), published by Getúlio Vargas Foundation.

  4. From 1988 to 1993, annual inflation reached triple-digit figures in every year, except in 1991.

  5. BCB started to operate in 1965.

  6. As measured by the general prices index.

  7. The so-called Bresser, Summer, Collor I, and Collor II plans.

  8. In addition, real GDP growth was around 3.8% p.a. on average between 1994 and 1997.

  9. CMN is somehow related to the Federal Reserve Board of Governors, while the BCB is its executive branch. Nowadays, three members, the Minister of Finance (chair), the Minister of Planning and Budget, and the President of the Central Bank constitute CMN.

  10. In addition, our model does not explicitly consider fiscal variables. While exchange rate changes and fiscal policy are relevant for inflation determination, we would rather keep our model parsimonious, leaving changes in these as exogenous disturbances that affect BCB behavior. By doing this, we are also able to focus on the possible effects of monetary policies on the Brazilian stabilization.

  11. Dynare 4.3.3 is the utilized software.

  12. This proxy allows for a better fit in the Bayesian estimation. Besides, as long as target inflation goes to the intercept term in Eq. (5), we do not necessarily need to use annualized quarterly inflation rates in our estimations.

  13. Inflation and Selic data are available at https://www.ipeadata.gov.br.

  14. Nevertheless, it is noteworthy that the posterior standard deviations implied by the model tended to overestimate the volatility of inflation and interest rate. Interestingly, Canova (2009) obtained a similar result. We guess that it could be due to a characteristic of the theoretical model, which is relatively simple, or even to difficulties found in DSGE models when matching some moments of aggregate prices, as Caballero (2010) pointed it.

  15. A complete list of the results is available in “Appendix,” Tables 9, 10 and 11.

  16. Specifically, in model b, samples 1975–84 and 1985–94.

  17. Indexation has regularly attracted a great deal of attention in Brazilian policy-making.

  18. The fact that a Taylor Principle is satisfied for the 1985–1994 period, when inflation was very high (see Table 10), could also suggest that BCB had targets for the inflation tax (as a share of GDP). With prices growing quickly and eroding the real stock of money, financing public deficits with seigniorage required increasing monetary expansions and, therefore, higher inflation rates.

  19. We discard the year of 1994, because it can be seen as a transition period.

  20. Consumption elasticity and output persistence are quite stable along the estimation samples and are disregarded at this point of our analysis.

  21. A higher value for \(\kappa \) denotes prices that are more flexible.

  22. Not coincidentally, we titled our paper honoring Sargent (1982) work.

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Acknowledgements

We would like to thank two anonymous referees for many helpful comments and suggestions. The first author gratefully acknowledges the Brazilian National Council for the Improvement of Higher Education (CAPES) for the scholarship received, process number BEX 9649/12-3.

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Authors and Affiliations

  1. Department of Economics, Federal University of Juiz de Fora, Av. Dr. Raimundo Rezende, 330, Centro, Governador Valadares, MG, 35012-140, Brazil

    Luckas Sabioni Lopes

  2. Department of Economics, University of California, Riverside, CA, 92521, USA

    Marcelle Chauvet

  3. Department of Rural Economy, Federal University of Viçosa, Av. Purdue, s/no Campus Universitário, Viçosa, MG, 36570-900, Brazil

    João Eustáquio de Lima

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  1. Luckas Sabioni Lopes
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  2. Marcelle Chauvet
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Correspondence to Luckas Sabioni Lopes.

Appendix

Appendix

See Tables 9, 10, and 11.

Table 9 Private and inertia parameters estimates in each subsample
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Table 10 Policy parameters estimates in each subsample
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Table 11 Exogenous shocks estimates in each subsample
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Lopes, L.S., Chauvet, M. & de Lima, J.E. The end of Brazilian big inflation: lessons to monetary policy from a standard New Keynesian model. Empir Econ 55, 1475–1505 (2018). https://doi.org/10.1007/s00181-017-1324-4

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