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A multi-level panel STAR model for US manufacturing sectors

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Author Info

  • Dick van Dijk

    (Econometric Institute, Erasmus University Rotterdam, The Netherlands)

  • Dennis Fok

    (Econometric Institute, Erasmus University Rotterdam, The Netherlands)

  • Philip Hans Franses

    (Econometric Institute, Erasmus University Rotterdam, The Netherlands)

Abstract

We introduce a multi-level smooth transition model for a panel of time series, which can be used to examine the presence of common nonlinear business cycle features across many variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which allows for unrestricted nonlinearity. We introduce a second-stage model linking the parameters that determine the timing of the switches between business cycle regimes to observable explanatory variables, thereby allowing for lead-lag relationships across panel members. We discuss representation, estimation by concentrated simulated maximum likelihood and inference. We illustrate our model using quarterly industrial production in 19 US manufacturing sectors, and document that there are subtle differences across sectors in leads and lags for switches between business cycle recessions and expansions. Copyright © 2005 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.822
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 20 (2005)
Issue (Month): 6 ()
Pages: 811-827

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Handle: RePEc:jae:japmet:v:20:y:2005:i:6:p:811-827

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References

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  1. Wolak, Frank A., 1989. "Local and Global Testing of Linear and Nonlinear Inequality Constraints in Nonlinear Econometric Models," Econometric Theory, Cambridge University Press, vol. 5(01), pages 1-35, April.
  2. Forni, Mario & Reichlin, Lucrezia, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 453-73, July.
  3. repec:cup:etheor:v:11:y:1995:i:3:p:437-83 is not listed on IDEAS
  4. Michael T. Owyang & Jeremy M. Piger & Howard J. Wall, 2004. "Business cycle phases in U.S. states," Working Papers 2003-011, Federal Reserve Bank of St. Louis.
  5. Arturo Estrella & Frederic S. Mishkin, 1999. "Predicting U.S. Recessions: Financial Variables as Leading Indicators," NBER Working Papers 5379, National Bureau of Economic Research, Inc.
  6. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
  7. Paap, Richard & Franses, Philip Hans & van Dijk, Dick, 2005. "Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method," Journal of Development Economics, Elsevier, vol. 77(2), pages 553-570, August.
  8. Marco Del Negro, 1999. "Asymmetric shocks among U.S. states," Working Papers 9903, Centro de Investigacion Economica, ITAM.
  9. 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.
  10. Engle, Robert F. & Issler, Joao Victor, 1995. "Estimating common sectoral cycles," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 83-113, February.
  11. Bidarkota Prasad V., 1999. "Sectoral Investigation of Asymmetries in the Conditional Mean Dynamics of the Real U.S. GDP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(4), pages 1-12, January.
  12. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
  13. Lee, Kevin, 1997. "Modelling economic growth in the UK: An econometric case for disaggregated sectoral analysis," Economic Modelling, Elsevier, vol. 14(3), pages 369-394, July.
  14. Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
  15. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 437-483, June.
  16. Cooper, Suzanne J, 1998. "Multiple Regimes in U.S. Output Fluctuations," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 92-100, January.
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Citations

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Cited by:
  1. Fok, D. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2004. "Forecasting aggregates using panels of nonlinear time series," Econometric Institute Research Papers EI 2004-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Ketenci, Natalya, 2010. "The Feldstein –Horioka Puzzle and structural breaks: evidence from EU members," MPRA Paper 26010, University Library of Munich, Germany.
  3. Ralf Becker & Denise Osborn, 2007. "Weighted smooth transition regressions," The School of Economics Discussion Paper Series 0724, Economics, The University of Manchester.
  4. Peltonen, Tuomas A. & Popescu, Adina & Sager, Michael, 2009. "Can non-linear real shocks explain the persistence of PPP exchange rate disequilibria?," Working Paper Series 1073, European Central Bank.
  5. Béreau, Sophie & Villavicencio, Antonia López & Mignon, Valérie, 2010. "Nonlinear adjustment of the real exchange rate towards its equilibrium value: A panel smooth transition error correction modelling," Economic Modelling, Elsevier, vol. 27(1), pages 404-416, January.
  6. Derek Stimel, 2010. "Choice of Aggregate Demand Proxy and its Affect on Phillips Curve Nonlinearity: U.S. Evidence," Economics Bulletin, AccessEcon, vol. 30(1), pages 543-557.
  7. Chakroun, Mohamed, 2009. "Health care expenditure and GDP: An international panel smooth transition approach," MPRA Paper 14322, University Library of Munich, Germany.
  8. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "Spatial agglomeration and productivity in Italy: a panel smooth transition regression approach," Openloc Working Papers 1204, Public policies and local development.
  9. JUDE, Cristina & LEVIEUGE, Gregory, 2013. "Growth effect of FDI in developing economies: The role of institutional quality," MPRA Paper 49321, University Library of Munich, Germany.
  10. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.

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