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Censored latent effects autoregression, with an application to US unemployment
Author(s) -
Franses Philip Hans,
Paap Richard
Publication year - 2002
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.627
Subject(s) - unemployment , economics , econometrics , autoregressive model , vector autoregression , great recession , sample (material) , recession , regression , keynesian economics , statistics , macroeconomics , mathematics , chemistry , chromatography
A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond with unobserved positive shocks. The generating mechanism of these latent shocks is a censored regression model, where linear combinations of lagged explanatory variables lead to positive shocks, while otherwise shocks are equal to zero. We apply this censored latent effects autoregression to monthly US unemployment, where the positive shocks are found to be predictable using various leading indicators. The model fits the data well and its out‐of‐sample forecasts appear to improve on those from alternative models. Copyright © 2002 John Wiley & Sons, Ltd.