《A multi-level panel STAR model for US manufacturing sectors (p 811-827)》.pdf

JOURNAL OF APPLIED ECONOMETRICS J. Appl. Econ. 20: 811–827 (2005) Published online in Wiley InterScience (). DOI: 10.1002/jae.822 A MULTI-LEVEL PANEL STAR MODEL FOR US MANUFACTURING SECTORS DENNIS FOK, DICK VAN DIJK* AND PHILIP HANS FRANSES Econometric Institute, Erasmus University Rotterdam, The Netherlands SUMMARY 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. 1. INTRODUCTION Characterizing business cycle dynamics has long been a topic of intense research. The stylized empirical fact that recessions are much shorter but more severe than expansions has led recently to the application of a wide range of nonlinear time series (regression) models to macroeconomic variables such as industrial output and (un)employment. Most studies in this area make use of aggregate, often nat