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Eficácia das intervenções do Banco Central do Brasil sobre a volatilidade da taxa de câmbio nominal

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  • Oliveira, Fernando Nascimento
  • Plaga, Alessandra Ribeiro

Abstract

This paper analyzes the effectiveness of instruments of intervention used by the Central Bank of Brazil over the conditional volatility of the nominal exchange rate. Central Bank of Brazil used as intervention instruments, standard instruments of the literature – such as interest rate and interventions in the spot market, and unusual instruments – such as public bonds indexed to the dollar and foreign exchange rates swaps. The conditional volatility of the exchange rate was modeled using an E-GARCH model, Nelson e CAo (1992). We used daily data of nominal exchange rate and the interventions for the period from January of 1999 to September of 2006. Our results showed that in all sample periods we study, including the ones with currency crisis, some instrument of intervention affected the conditional volatility of the nominal exchange rate.

Suggested Citation

  • Oliveira, Fernando Nascimento & Plaga, Alessandra Ribeiro, 2011. "Eficácia das intervenções do Banco Central do Brasil sobre a volatilidade da taxa de câmbio nominal," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 65(1), March.
  • Handle: RePEc:fgv:epgrbe:v:65:y:2011:i:1:a:1469
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    1. Vella, Francis, 1993. "A Simple Estimator for Simultaneous Models with Censored Endogenous Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(2), pages 441-457, May.
    2. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-235, April.
    5. Maurice Obstfeld, 1988. "The Effectiveness of Foreign-Exchange Intervention: Recent Experience," NBER Working Papers 2796, National Bureau of Economic Research, Inc.
    6. Kathryn M. Dominguez, 1993. "Does Central Bank Intervention Increase the Volatility of Foreign Exchange Rates?," NBER Working Papers 4532, National Bureau of Economic Research, Inc.
    7. Rogoff, Kenneth, 1984. "On the effects of sterilized intervention : An analysis of weekly data," Journal of Monetary Economics, Elsevier, vol. 14(2), pages 133-150, September.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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