(This abstract was borrowed from another version of this item.)"> (This abstract was borrowed from another version of this item.)">
[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/anp/en2008/200807211607140.html
   My bibliography  Save this paper

Modelos lineares e não lineares da curva de Phillips para previsão da taxa de Inflação no Brasil

Author

Listed:
  • Elano Ferreira Arruda

    (CAEN/UFC)

  • Roberto Tatiwa Ferreira

    (CAEN/UFC)

  • Ivan Castelar

    (CAEN/UFC)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Elano Ferreira Arruda & Roberto Tatiwa Ferreira & Ivan Castelar, 2008. "Modelos lineares e não lineares da curva de Phillips para previsão da taxa de Inflação no Brasil," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211607140, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    • Handle: RePEc:anp:en2008:200807211607140
    as

    Download full text from publisher

    File URL: http://www.anpec.org.br/encontro2008/artigos/200807211607140-.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    10. 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.
    11. Galí, Jordi & Gertler, Mark, 1999. "Inflation Dynamics: A Structural Economic Analysis," CEPR Discussion Papers 2246, C.E.P.R. Discussion Papers.
    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. 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).
    14. 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.
    15. 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.
    16. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    17. 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.
    18. 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.
    19. 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.
    20. Demosthenes N. Tambakis, 1998. "Monetary Policy with a Convex Phillips Curve and Asymmetric Loss," IMF Working Papers 1998/021, International Monetary Fund.
    21. Joseph Stiglitz, 1997. "Reflections on the Natural Rate Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 3-10, Winter.
    22. Friedman, Milton, 1977. "Nobel Lecture: Inflation and Unemployment," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 451-472, June.
    23. 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.
    24. repec:onb:oenbwp:y::i:148:b:1 is not listed on IDEAS
    25. 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.
    26. 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.
    27. 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].
    28. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    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. 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.
    32. 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.
    33. Frederic S. Mishkin, 2007. "Inflation Dynamics," International Finance, Wiley Blackwell, vol. 10(3), pages 317-334, December.
    34. 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.
    35. Marcelle Chauvet, 2000. "Leading Indicators of Inflation for Brazil," Working Papers Series 7, Central Bank of Brazil, Research Department.
    36. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    37. 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.
    38. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Mário Jorge Mendonça & Adolfo Sachsida, 2012. "Inflação Versus Desemprego: Novas Evidências Para o Brasil," Discussion Papers 1763, Instituto de Pesquisa Econômica Aplicada - IPEA.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    3. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    4. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    5. Phiri, Andrew, 2015. "Examining asymmetric effects in the South African Philips curve: Evidence from logistic smooth transition regression (LSTR) models," MPRA Paper 64487, University Library of Munich, Germany.
    6. Sznajderska, Anna, 2014. "Asymmetric effects in the Polish monetary policy rule," Economic Modelling, Elsevier, vol. 36(C), pages 547-556.
    7. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    8. Kevin Lansing, 2009. "Time Varying U.S. Inflation Dynamics and the New Keynesian Phillips Curve," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(2), pages 304-326, April.
    9. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    10. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    11. Szafranek, Karol, 2017. "Flattening of the New Keynesian Phillips curve: Evidence for an emerging, small open economy," Economic Modelling, Elsevier, vol. 63(C), pages 334-348.
    12. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    13. 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.
    14. Bozani, Vasiliki & Drydakis, Nick, 2011. "Studying the NAIRU and its Implications," IZA Discussion Papers 6079, Institute of Labor Economics (IZA).
    15. Baffigi, Alberto & Bontempi, Maria Elena & Felice, Emanuele & Golinelli, Roberto, 2015. "The changing relationship between inflation and the economic cycle in Italy: 1861–2012," Explorations in Economic History, Elsevier, vol. 56(C), pages 53-70.
    16. Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
    17. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    18. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
    19. Christopher J. Neely & David E. Rapach, 2008. "Real interest rate persistence: evidence and implications," Review, Federal Reserve Bank of St. Louis, vol. 90(Nov), pages 609-642.
    20. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, vol. 32(1), pages 138-153.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:anp:en2008:200807211607140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Rodrigo Zadra Armond (email available below). General contact details of provider: https://edirc.repec.org/data/anpecea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.