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Improved Testing And Specification Of Smooth Transition Regression Models

  • Alvaro Escribano
  • Oscar Jorda

This paper extends previous work in Escribano and Jorda (1997) and introduces new LM specification procedures to choose between Logistic and Exponential Smooth Transition Regression (STR) Models. These procedures are simpler, consistent and more powerful than those previously available in the literature. An analysis of the properties of Taylor approximations around the transition function of STR models permits one to understand why these procedures work better and it suggests ways to improve tests of the null hypothesis of linearity versus the alternative of STR-type nonlinearity. Monte-Carlo experiments illustrate the performance of the different tests introduced. The new procedures are then implemented on a study of the dynamics of the U.S. unemployment rate.

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File URL: http://www.econ.ucdavis.edu/working_papers/97-26.pdf
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Paper provided by California Davis - Department of Economics in its series Department of Economics with number 97-26.

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Handle: RePEc:fth:caldec:97-26
Contact details of provider: Postal: University of California Davis - Department of Economics. One Shields Ave., California 95616-8578
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Web page: http://www.econ.ucdavis.edu/
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  1. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
  2. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March.
  3. Pesaran, H.M. & Potter, S.M., 1995. "A Floor and Ceiling Model of U.S. Output," Cambridge Working Papers in Economics 9407, Faculty of Economics, University of Cambridge.
  4. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
  5. PFANN, Gerard A. & PALM, Franz C., . "Asymmetric adjustment costs in non-linear labour demand models for the Netherlands and U.K. manufacturing sectors," CORE Discussion Papers RP -1044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
  7. Burgess, Simon M & Dolado, Juan J, 1989. "Intertemporal Rules with Variable Speed of Adjustment: An Application to U.K. Manufacturing Employment," Economic Journal, Royal Economic Society, vol. 99(396), pages 347-65, June.
  8. Álvaro Escribano & Oscar Jordá, 2001. "Testing nonlinearity: Decision rules for selecting between logistic and exponential STAR models," Spanish Economic Review, Springer, vol. 3(3), pages 193-209.
  9. Burgess, Simon M, 1988. "Employment Adjustment in UK Manufacturing," Economic Journal, Royal Economic Society, vol. 98(389), pages 81-103, March.
  10. Pissarides, Christopher A, 1992. "Loss of Skill during Unemployment and the Persistence of Employment Shocks," The Quarterly Journal of Economics, MIT Press, vol. 107(4), pages 1371-91, November.
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