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The Net Barter Terms Of Trade : A Smooth Transition Approach

Author

Listed:
  • Persson, Anna

    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Teräsvirta, Timo

    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

This paper analyzes the net barter terms of trade measured by the primary commodity price index relative to the index of unit values of export of manufactures from industrial countries. The starting-point is that the series is stationary but possibly nonlinear. Statistical tests indicate that the logarithmed series is nonlinear, and we estimate a Smooth Transition Autoregressive model to describe the process. The dynamics of the model are illustrated by use of parametrically estimated local spectra and generalized impulse response functions. Our model encompasses models from several previous studies, and our conclusion is that the starting-point of the empirical analysis very much determines the outcome.

Suggested Citation

  • Persson, Anna & Teräsvirta, Timo, 1999. "The Net Barter Terms Of Trade : A Smooth Transition Approach," SSE/EFI Working Paper Series in Economics and Finance 335, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0335
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    References listed on IDEAS

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    1. Sapsford, D, 1985. "The Statistical Debate on the Net Barter Terms of Trade between Primary Commodities and Manufactures: A Comment and Some Additional Evidence," Economic Journal, Royal Economic Society, vol. 95(379), pages 781-788, September.
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    4. Spraos, John, 1980. "The Statistical Debate on the Net Barter Terms of Trade between Primary Commodities and Manufactures," Economic Journal, Royal Economic Society, vol. 90(357), pages 107-128, March.
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    7. Matthias G. Lutz, 1999. "A General Test of the Prebisch–Singer Hypothesis," Review of Development Economics, Wiley Blackwell, vol. 3(1), pages 44-57, February.
    8. Powell, Andrew, 1991. "Commodity and Developing Country Terms of Trade: What Does the Long Run Show?," Economic Journal, Royal Economic Society, vol. 101(409), pages 1485-1496, November.
    9. Jansen, Eilev S & Terasvirta, Timo, 1996. "Testing Parameter Constancy and Super Exogeneity in Econometric Equations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 735-763, November.
    10. Perron, Pierre & Vogelsang, Timothy J, 1992. "Testing for a Unit Root in a Time Series with a Changing Mean: Corrections and Extensions," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 467-470, October.
    11. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.
    12. Cuddington, John T & Urzua, Carlos M, 1989. "Trends and Cycles in the Net Barter Terms of Trade: A New Approach," Economic Journal, Royal Economic Society, vol. 99(396), pages 426-442, June.
    13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    14. Prebisch, Raúl, 1950. "The economic development of Latin America and its principal problems," Sede de la CEPAL en Santiago (Estudios e Investigaciones) 29973, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    15. Helg, Rodolfo, 1991. "A note on the stationarity of the primary commodities relative price index," Economics Letters, Elsevier, vol. 36(1), pages 55-60, May.
    16. Ardeni, Pier Giorgio & Wright, Brian, 1992. "The Prebisch-Singer Hypothesis: A Reappraisal Independent of Stationarity Hypotheses," Economic Journal, Royal Economic Society, vol. 102(413), pages 803-812, July.
    17. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
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    Citations

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    Cited by:

    1. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    2. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
    3. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
    4. Boris Petkov, 2018. "Natural Resource Abundance: Is it a Blessing or is it a Curse," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(3), pages 25-56, September.
    5. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. 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.
    7. Hany Fahmy, 2014. "Modelling nonlinearities in commodity prices using smooth transition regression models with exogenous transition variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(4), pages 577-600, November.
    8. G. K. Randolph TAN, 2004. "Long Memory in Import and Export Price Inflation and Persistence of Shocks to the Terms of Trade," Econometric Society 2004 Far Eastern Meetings 732, Econometric Society.

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    More about this item

    Keywords

    Development economics; encompassing; generalized impulse response function; local spectrum; nonlinearity; raw material prices; smooth transition autoregression.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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