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Some evidence of smooth transition nonlinearity in Colombian inflation

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  • Luis Arango
  • Andres Gonzalez

Abstract

Evidence of smooth transition autoregressive (STAR) representations is found in two, out of three, time series of different measures of annual inflation in Colombia during this decade for monthly data. The STAR-type nonlinearities are asymmetric for inflation computed as the variation of CPI while for (a measure of) core inflation are symmetric. Thus, LSTAR and ESTAR models were, respectively, estimated. No evidence of nonlinearity is found for traded goods inflation. Given the local dynamic properties of the estimated LSTAR model, only positive shocks to prices could shift negative accelerating inflation rate from the upper to the lower regime. By the same token, only stochastic shocks can move the core accelerating inflation rate from the outer regime to the middle one but the explosive nature of this regime will impulse the accelerating inflation rate to the outer one.

Suggested Citation

  • Luis Arango & Andres Gonzalez, 2001. "Some evidence of smooth transition nonlinearity in Colombian inflation," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 155-162.
  • Handle: RePEc:taf:applec:v:33:y:2001:i:2:p:155-162
    DOI: 10.1080/00036840122443
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    Cited by:

    1. Juan Carlos Cuestas & Estefanía Mourelle, 2009. "Inflation persistence and asymmetries: evidence for African countries," NBS Discussion Papers in Economics 2009/2, Economics, Nottingham Business School, Nottingham Trent University.
    2. Pillai N., Vijayamohanan, 2008. "In Quest of Truth: The War of Methods in Economics," MPRA Paper 8866, University Library of Munich, Germany.
    3. Luis Fernando Melo & Martha Misas A., 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a Través de Mínimos Cuadrados Flexibles," Borradores de Economia 283, Banco de la Republica de Colombia.
    4. Andrew Phiri, 2012. "Threshold effects and inflation persistence in South Africa," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 4(3), pages 247-269, July.
    5. Faria, João Ricardo & Cuestas, Juan Carlos & Mourelle, Estefanía, 2010. "Entrepreneurship and unemployment: A nonlinear bidirectional causality?," Economic Modelling, Elsevier, vol. 27(5), pages 1282-1291, September.
    6. 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 3244, Banco de la Republica.
    7. Kulaksizoglu, Tamer & Kulaksizoglu, Sebnem, 2009. "The U.S. Excess Money Growth and Inflation Relation in the Long-Run: A Nonlinear Analysis," MPRA Paper 23780, University Library of Munich, Germany.
    8. Georgios P. Kouretas & Mark E. Wohar, 2012. "The dynamics of inflation: a study of a large number of countries," Applied Economics, Taylor & Francis Journals, vol. 44(16), pages 2001-2026, June.
    9. Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La inflación en Colombia: una aproximación desde las redes neuronales," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 20(41-42), pages 143-214, June.
    10. Sehati , Elham & Mousavi Jahromi , Yeganeh & Mehrara , Mohsen & Najafizadeh , Abbas, 2018. "Non-Linear Inflationary Dynamics based on the Concept of Missing Money in Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(2), pages 221-243, April.
    11. Estefania Mourelle & Juan Carlos Cuestas & Luis Alberiko Gil‐alana, 2011. "Is There An Asymmetric Behaviour In African Inflation? A Non‐Linear Approach," South African Journal of Economics, Economic Society of South Africa, vol. 79(1), pages 68-90, March.
    12. Arize, Augustine C. & Malindretos, John, 2012. "Nonstationarity and nonlinearity in inflation rate: Some further evidence," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 224-234.
    13. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 3029, Banco de la Republica.
    15. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR model – wavelet improvements under GARCH distortion," Working Paper Series in Economics and Institutions of Innovation 184, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    16. Munir A. Jalil & Luis Fernando Melo, 2000. "Una Relación no Líneal entre Inflación y los Medios de Pago," Borradores de Economia 145, Banco de la Republica de Colombia.
    17. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    18. Anoop Chaturvedi & Shivam Jaiswal, 2020. "Bayesian Estimation and Unit Root Test for Logistic Smooth Transition Autoregressive Process," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 733-745, December.

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    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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