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Modelos Para La Inflación Básica de Bienes Transables y No Transables en Colombia

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  • José Luis Torres

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Abstract

En este trabajo se estiman modelos de corto plazo para pronosticar la inflación de bienes transables y no transables en Colombia. Estos modelos no existían en el Banco Central antes de 2004 y son de gran utilidad para la toma de decisiones de política monetaria. También se evalúan los beneficios, en términos de análisis y de capacidad pronóstico, de utilizar métodos que capturen la posible no linealidad de la curva de Phillips en los datos colombianos. Aunque existen diferentes razones que justifican una relación no lineal de corto plazo entre producto e inflación, cada una de ellas sugiere una forma diferente para la curva. Por esta razón, se utilizan redes neuronales artificiales (ANN) y los mínimos cuadrados flexibles (FLS), procedimientos que tienen la gran ventaja de que no imponen de antemano ninguna forma funcional que pueda sesgar los resultados. Una vez se hace la estimación de los modelos de inflación de transables y de no transables, se comparan los pronósticos de estos dos modelos no lineales con los de dos estimaciones lineales, se analizan las funciones de impulso respuesta de cada uno de los modelos y además se realiza una prueba de no linealidad. Se encuentra que la curva de Phillips en Colombia podría ser no lineal y por tanto resulta pertinente considerar modelos no lineales para su estimación. Finalmente, con estos modelos se intenta explicar el proceso de desinflación que ha vivido la economía colombiana en los últimos años tanto en la inflación de transables, como en la de no transables.

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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 365.

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Handle: RePEc:bdr:borrec:365

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Keywords: Inflación; Curva de Phillips no Lineal; Redes Neuronales Artificiales; Mínimos Cuadrados Flexibles.;

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References

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  1. Luis Fernando Melo Velandia & Martha Alicia Misas Arango, 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a través de Mínimos Cuadrados Flexibles," BORRADORES DE ECONOMIA 003244, BANCO DE LA REPÚBLICA.
  2. Taylor, John B, 1980. "Aggregate Dynamics and Staggered Contracts," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 1-23, February.
  3. Andrew J. Filardo, 1998. "New evidence on the output cost of fighting inflation," Economic Review, Federal Reserve Bank of Kansas City, issue Q III.
  4. Laurence Ball & N. Gregory Mankiw & David Romer, 1988. "The New Keynsesian Economics and the Output-Inflation Trade-off," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 1-82.
  5. Jordi Galí & Mark Gertler, 1998. "Inflation dynamics: A structural econometric analysis," Economics Working Papers 341, Department of Economics and Business, Universitat Pompeu Fabra.
  6. Javier Gómez & Juan Manuel Julio, 2000. "An Estimation of the Nonlinear Philips Curve in Colombia," BORRADORES DE ECONOMIA 001975, BANCO DE LA REPÚBLICA.
  7. Robert J. Gordon, 1997. "The Time-Varying NAIRU and its Implications for Economic Policy," NBER Working Papers 5735, National Bureau of Economic Research, Inc.
  8. Enrique López E. & Martha Misas A., 1999. "Un Examen Empirico De La Curva De Phillips En Colombia," BORRADORES DE ECONOMIA 003676, BANCO DE LA REPÚBLICA.
  9. Tkacz, Greg & Hu, Sarah, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Working Papers 99-3, Bank of Canada.
  10. Shapiro, Carl & Stiglitz, Joseph E, 1984. "Equilibrium Unemployment as a Worker Discipline Device," American Economic Review, American Economic Association, vol. 74(3), pages 433-44, June.
  11. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
  12. Martha Misas A. & Enrique López E. & Carlos A. Arango A. & Juan Nicolás Hernández A., 2003. "La Demanda de Efectivo en Colombia: Una Caja Nagra a la Luz de las Redes Neuronales," BORRADORES DE ECONOMIA 002963, BANCO DE LA REPÚBLICA.
  13. Eliasson, Ann-Charlotte, 2001. "Is the Short-run Phillips Curve Nonlinear? Empirical Evidence for Australia, Sweden and the United States," Working Paper Series 124, Sveriges Riksbank (Central Bank of Sweden).
  14. Kalaba, Robert E. & Tesfatsion, Leigh S., 1989. "Time-Varying Linear Regression Via Flexible Least Squares," Staff General Research Papers 11196, Iowa State University, Department of Economics.
  15. Douglas Laxton & Peter B. Clark & David Rose, 1995. "Asymmetry in the U.S. Output-Inflation Nexus - Issues and Evidence," IMF Working Papers 95/76, International Monetary Fund.
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Cited by:
  1. Eliana Gómez & Miguel I. Gómez & Luis F.Melo & José Luis Torres, . "Forecasting Food Price Inflation in Developing Countries with Inflation Targeting Regimes: the Colombian Case," Borradores de Economia 409, Banco de la Republica de Colombia.
  2. Gomez, Miguel I. & Gonzalez, Eliana & Melo, Luis F. & Torres, Jose L., 2006. "Forecasting Food Price Inflation, Challenges for Central Banks in Developing Countries using an Inflation Targeting Framework: the Case of Colombia," 2006 Annual meeting, July 23-26, Long Beach, CA 21181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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