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A multi‐level panel STAR model for US manufacturing sectors
Author(s) -
Fok Dennis,
van Dijk Dick,
Franses Philip Hans
Publication year - 2005
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.822
Subject(s) - business cycle , econometrics , inference , panel data , recession , lag , representation (politics) , observable , computer science , nonlinear system , economics , macroeconomics , law , computer network , physics , quantum mechanics , artificial intelligence , politics , political science
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.