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Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns

Antonio Galvao (), Montes-Rojas, Gabriel () and Sung Park ()
Additional contact information
Antonio Galvao: galvao@illinois.edu
Montes-Rojas, Gabriel: Department of Economics, City University, London, http://www.city.ac.uk/economics/staff/montes-rojas/index.html
Sung Park: Wang Yanan Institute for Studies in Economics (WISE), Xiamen University

No 09/04, City University Economics Discussion Papers from Department of Economics, City University, London

Abstract: This paper studies quantile regression in an autoregressive dynamic framework with exogenous stationary covariates. Hence, we develop a quantile autoregressive distributed lag model (QADL). We show that these estimators are consistent and asymptotically normal. Inference based on Wald and Kolmogorov-Smirnov tests for general linear restrictions is proposed. An extensive Monte Carlo simulation is conducted to evaluate the properties of the estimators. We demonstrate the potential of the QADL model with an application to house price returns in the United Kingdom. The results show that house price returns present a heterogeneous autoregressive behavior across the quantiles. The real GDP growth and interest rates also have an asymmetric impact on house prices variations.

Keywords: quantile autoregression; distributed lag model; autoregressive model (search for similar items in EconPapers)
JEL-codes: C14 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ure
Date: 2009-03
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