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Unit Root Quantile Autoregression Inference

Roger KoenkerRoger Koenker is Professor of Economics and Statistics and Zhijie Xiao is Associate Professor of Economics , University of Illinois, Urbana-Champaign, IL 61820. This research was supported in part by National Science Foundation grant SES-02-40781. The authors thank the editor, an associate editor, and three referees for their detailed and constructive commentsZhijie XiaoRoger Koenker is Professor of Economics and Statistics and Zhijie Xiao is Associate Professor of Economics , University of Illinois, Urbana-Champaign, IL 61820. This research was supported in part by National Science Foundation grant SES-02-40781. The authors thank the editor, an associate editor, and three referees for their detailed and constructive comments

2004en

ABI

Annotatsiya

We study statistical inference in quantile autoregression models when the largest autoregressive coefficient may be unity. The limiting distribution of a quantile autoregression estimator and its t-statistic is derived. The asymptotic distribution is not the conventional Dickey–Fuller distribution, but rather a linear combination of the Dickey–Fuller distribution and the standard normal, with the weight determined by the correlation coefficient of related time series. Inference methods based on the estimator are investigated asymptotically. Monte Carlo results indicate that the new inference procedures have power gains over the conventional least squares-based unit root tests in the presence of non-Gaussian disturbances. An empirical application of the model to U. S. macroeconomic time series data further illustrates the potential of the new approach.

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DOI: 10.1198/016214504000001114

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