A Multi-Level Panel Smooth Transition Autoregression for US Sectoral Production
Macroeconomic time series are often obtained as an aggregate across regions or economic sectors. Even when the ultimate goal is to forecast the aggregate series it may be beneficial to consider the underlying disaggregate series. This especially holds when the disaggregate series are generated by a non-linear process. The aggregate of such series follows a very complicated process. Aggregating a number of relatively simple models for individual regions or sectors to a model of the macro series may lead to a more accurate description than when a model for the aggregate is considered. We introduce a multi-level smooth transition model for a panel of time series variables, which can be used to examine the presence of common non-linear features across many such variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which might render estimation problems for some of the panel members. To keep the model tractable, we introduce a second-stage model, which links the parameters in the transition functions with observable explanatory variables. We discuss representation, estimation by concentrated simulated maximum likelihood and inference. We illustrate our model for data on industrial production of 18 US manufacturing sectors, and document that there are subtle differences across sectors in leads and lags for business cycle recessions and expansions.
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|Date of creation:||11 Aug 2004|
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- Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, December.
- van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000.
"Smooth Transition Autoregressive Models - A Survey of Recent Developments,"
SSE/EFI Working Paper Series in Economics and Finance
380, Stockholm School of Economics, revised 17 Jan 2001.
- Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
- van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Marco Del Negro, 1999.
"Asymmetric shocks among U.S. states,"
9903, Centro de Investigacion Economica, ITAM.
- 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.
- Vahid, Farshid & Engle, Robert F., 1997. "Codependent cycles," Journal of Econometrics, Elsevier, vol. 80(2), pages 199-221, October.
- 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.
- Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-60, Oct.-Dec..
- 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.
- 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.
- 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.
- Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
- Engle, Robert F. & Issler, Joao Victor, 1995. "Estimating common sectoral cycles," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 83-113, February.
- repec:fgv:epgrbe:v:47:n:2:a:1 is not listed on IDEAS
- 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.
- Mario Forni & Lucrezia Reichlin, 1998.
"Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics,"
Review of Economic Studies,
Oxford University Press, vol. 65(3), pages 453-473.
- Mario Forni & Lucrezia Reichlin, 1998. "Let's get real: a factor analytical approach to disaggregated business cycle dynamics," ULB Institutional Repository 2013/10147, ULB -- Universite Libre de Bruxelles.
- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, December.
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