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Modelos Lineares e Não Lineares da Curva de Phillips para Previsão da Taxa de Inflação no Brasil

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  • Arruda, Elano Ferreira
  • Ferreira, Roberto Tatiwa
  • Castelar, Ivan
Abstract
This paper compares forecasts of Brazilian monthly inflation rate generated from different linear and nonlinear time series and Phillips’ curve models. In general, the nonlinear models had a better performance. The VAR model produced the smallest mean square forecast error (MSE) among linear models, while overall best forecasts were generated by the extended Phillips curve with a threshold effect, which presented a 20% smaller MSE than the VAR model. The Diebold e Mariano (1995) test indicated a significant difference between forecasts generated from the VAR and the expanded Phillips curve with a threshold.

Suggested Citation

  • Arruda, Elano Ferreira & Ferreira, Roberto Tatiwa & Castelar, Ivan, 2011. "Modelos Lineares e Não Lineares da Curva de Phillips para Previsão da Taxa de Inflação no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 65(3), September.
    • Handle: RePEc:fgv:epgrbe:v:65:y:2011:i:3:a:1523
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    1. Joel Bogdanski & Alexandre Antonio Tombini & Sergio R. Da C. Werlang, 2001. "Implementing Inflation Targeting in Brazil," Money Affairs, CEMLA, vol. 0(1), pages 1-23, January-J.
    2. Sergio Afonso Lago Alves, 2001. "Avaliação das Projeções do Modelo Estrutural do Banco Central do Brasil para a Taxa de Variação do IPCA," Working Papers Series 16, Central Bank of Brazil, Research Department.
    3. Correa, Arnildo da Silva & Minella, André, 2010. "Nonlinear mechanisms of the exchange rate pass-through: A Phillips curve model with threshold for Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(3), September.
    4. Galí, Jordi & Gertler, Mark, 1999. "Inflation Dynamics: A Structural Economic Analysis," CEPR Discussion Papers 2246, C.E.P.R. Discussion Papers.
    5. G. Ascari & E. Marrocu, 2003. "Forecasting inflation: a comparison of linear Phillips curve models and nonlinear time serie models," Working Paper CRENoS 200307, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Rumler, Fabio & Valderrama, Maria Teresa, 2010. "Comparing the New Keynesian Phillips Curve with time series models to forecast inflation," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 126-144, August.
    7. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    8. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    9. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    10. repec:onb:oenbwp:y::i:148:b:1 is not listed on IDEAS
    11. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    12. Boero, Gianna & Marrocu, Emanuela, 2004. "The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts," International Journal of Forecasting, Elsevier, vol. 20(2), pages 305-320.
    13. Frederic S. Mishkin, 2007. "Inflation Dynamics," International Finance, Wiley Blackwell, vol. 10(3), pages 317-334, December.
    14. Phelps, Edmund S, 1969. "The New Microeconomics in Inflation and Employment Theory," American Economic Review, American Economic Association, vol. 59(2), pages 147-160, May.
    15. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    16. Demosthenes N. Tambakis, 1998. "Monetary Policy with a Convex Phillips Curve and Asymmetric Loss," IMF Working Papers 1998/021, International Monetary Fund.
    17. Joseph Stiglitz, 1997. "Reflections on the Natural Rate Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 3-10, Winter.
    18. Marcelo Kfoury Muinhos & Sergio Afonso Lago Alves, 2003. "Medium-Size Macroeconomic Model for the Brazilian Economy," Working Papers Series 64, Central Bank of Brazil, Research Department.
    19. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    20. Areosa, Waldyr Dutra & Medeiros, Marcelo, 2007. "Inflation Dynamics in Brazil: The Case of a Small Open Economy," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    21. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    22. Dionísio Dias Carneiro & André Monteiro D´Almeida Monteiro & Thomas Wu, 2002. "Mecanismos não-lineares de repasse cambial para o IPCA," Textos para discussão 462, Department of Economics PUC-Rio (Brazil).
    23. Greg Tkacz & Carolyn Wilkins, 2008. "Linear and threshold forecasts of output and inflation using stock and housing prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 131-151.
    24. Sargent, Thomas J, 1971. "A Note on the 'Accelerationist' Controversy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 3(3), pages 721-725, August.
    25. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    26. Roberto Tatiwa Ferreira & Herman Bierens & Ivan Castelar, 2005. "Forecasting Quarterly Brazilian GDP Growth Rate With Linear and NonLinear Diffusion Index Models," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 6(3), pages 261-292.
    27. Laxton, Douglas & Rose, David & Tambakis, Demosthenes, 1999. "The U.S. Phillips curve: The case for asymmetry," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1459-1485, September.
    28. Douglas Staiger & James H. Stock & Mark W. Watson, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter.
    29. Paul Davidson & Jan A. Kregel (ed.), 1997. "Improving the Global Economy," Books, Edward Elgar Publishing, number 1203.
    30. Caesar Lack, 2006. "Forecasting Swiss inflation using VAR models," Economic Studies 2006-02, Swiss National Bank.
    31. Clements, M.P. & Krolzig, H.-M., 1997. "A Comparison of the Forecasting Performance of Markov-Switching and Threshold Autoregressive Models of US GNP," The Warwick Economics Research Paper Series (TWERPS) 489, University of Warwick, Department of Economics.
    32. Andrew J. Filardo, 1998. "New evidence on the output cost of fighting inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 83(Q III).
    33. Friedman, Milton, 1977. "Nobel Lecture: Inflation and Unemployment," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 451-472, June.
    34. Sarantis, Nicholas, 1999. "Modeling non-linearities in real effective exchange rates," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 27-45, January.
    35. Carlos Hamilton Vasconcelos Araujo & Marta Baltar Moreira Areosa & Osmani Teixera de Carvalho Guillén, 2004. "Estimating Potential Output And The Output Gap For Brazil," Anais do XXXII Encontro Nacional de Economia [Proceedings of the 32nd Brazilian Economics Meeting] 041, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    36. Marcelle Chauvet, 2000. "Leading Indicators of Inflation for Brazil," Working Papers Series 7, Central Bank of Brazil, Research Department.
    37. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    38. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
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    Cited by:

    1. Thiago Carlomagno Carlo & Emerson Fernandes Marçal, 2016. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4846-4860, October.
    2. Barros, Geraldo Sant’Ana de Camargo & Carrara, Aniela Fagundes & Castro, Nicole Rennó & Silva, Adriana Ferreira, 2022. "Agriculture and inflation: Expected and unexpected shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 178-188.
    3. Weider Loureto Alves & Roberto Tatiwa Ferreira, 2023. "Phillips curve and the exchange rate pass-through: a time–frequency approach," Empirical Economics, Springer, vol. 64(5), pages 2165-2181, May.
    4. Sachsida, Adolfo, 2013. "Inflação, Desemprego e Choques Cambiais: Uma Revisão da Literatura sobre a Curva de Phillips no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(4), November.
    5. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    6. Ant?nio Cl¨¦cio de Brito & Elano Ferreira Arruda & Ivan Castelar & Nicolino Trompieri Neto & Cristiano Santos, 2019. "Core Inflation, Expectations and Inflation Dynamics in Brazil," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(6), pages 1-1, June.
    7. Vicente da Gama Machado & Marcelo Savino Portugal, 2014. "Phillips curve in Brazil: an unobserved components approach," Working Papers Series 354, Central Bank of Brazil, Research Department.
    8. Garcia, Márcio G.P. & Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2017. "Real-time inflation forecasting with high-dimensional models: The case of Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 679-693.
    9. Fabrizio Almeida Marodin & Marcelo Savino Portugal, 2019. "Exchange Rate Pass-Through in Brazil: À Markov Switching DSGE Estimation for the Inflation Targeting Period," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 36-66, March.
    10. Carlos Medel, 2021. "Forecasting Brazilian Inflation with the Hybrid New Keynesian Phillips Curve: Assessing the Predictive Role of Trading Partners," Working Papers Central Bank of Chile 900, Central Bank of Chile.
    11. Medeiros, Marcelo C & Vasconcelos, Gabriel & Freitas, Eduardo, 2016. "Forecasting Brazilian Inflation with High-Dimensional Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(2), November.
    12. Ferreira, Diego & Palma, Andreza Aparecida, 2015. "Forecasting Inflation with the Phillips Curve: A Dynamic Model Averaging Approach for Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 69(4), December.
    13. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    14. Castelar, Ivan & Arruda, Elano Ferreira & Oliveira de Olivindo, Maria Thalita Arruda, 2018. "Business cycles, expectations and inflation in Brazil: a New-Keynesian Phillips curve analysis," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    15. Mário Jorge Mendonça & Adolfo Sachsida, 2012. "Inflação Versus Desemprego: Novas Evidências Para o Brasil," Discussion Papers 1763, Instituto de Pesquisa Econômica Aplicada - IPEA.

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