Testing Stationarity for Unobserved Components Models
AbstractUnobserved components (UC) models are widely used to estimate stochastic trends in macroeconomic time series, with the existence of a stochastic trend typically motivated by a stationarity test. However, given the small sample sizes available for most macroeconomic variables, standard Lagrange multiplier tests of stationarity will perform poorly when the data are highly persistent. To address this problem, we propose the alternative use of a likelihood ratio test of stationarity based on a UC model and demonstrate that a bootstrap version of this test has far better small-sample properties for empirically-relevant data generating processes than bootstrap versions of the standard tests. An application to U.S. real GDP produces stronger support for the presence of large permanent shocks when using the likelihood ratio test as compared to standard tests.
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Bibliographic InfoPaper provided by School of Economics, The University of New South Wales in its series Discussion Papers with number 2012-41A.
Length: 30 pages
Date of creation: May 2013
Date of revision:
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Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-24 (All new papers)
- NEP-ECM-2013-06-24 (Econometrics)
- NEP-ETS-2013-06-24 (Econometric Time Series)
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