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

Author

Listed:
  • Antonio F. Galvao JR.
  • Gabriel Montes-Rojas
  • Sung Y. Park

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.
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Suggested Citation

  • Antonio F. Galvao JR. & Gabriel Montes-Rojas & Sung Y. Park, 2013. "Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 307-321, April.
  • Handle: RePEc:bla:obuest:v:75:y:2013:i:2:p:307-321
    DOI: 10.1111/obes.2013.75.issue-2
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    File URL: http://hdl.handle.net/10.1111/10.1111/obes.2013.75.issue-2
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    References listed on IDEAS

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    1. James M. Poterba, 1991. "House Price Dynamics: The Role of Tax Policy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(2), pages 143-204.
    2. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    3. Leslie Rosenthal, 2006. "Efficiency and Seasonality in the UK Housing Market, 1991-2001," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 289-317, June.
    4. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    5. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(02), pages 186-199, June.
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    Cited by:

    1. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    2. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    3. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.
    4. Haroon Mumtaz & Paolo Surico, 2015. "The Transmission Mechanism In Good And Bad Times," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1237-1260, November.
    5. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
    6. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    7. repec:bpj:sndecm:v:22:y:2018:i:2:p:0:n:4 is not listed on IDEAS
    8. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(4), pages 693-724.
    9. repec:eee:jmvana:v:158:y:2017:i:c:p:20-30 is not listed on IDEAS
    10. repec:vul:omefvu:v:8:y:2017:i:1:id:217 is not listed on IDEAS
    11. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(4), pages 693-724.
    12. repec:spr:empeco:v:52:y:2017:i:4:d:10.1007_s00181-016-1114-4 is not listed on IDEAS
    13. Xu, Qifa & Niu, Xufeng & Jiang, Cuixia & Huang, Xue, 2015. "The Phillips curve in the US: A nonlinear quantile regression approach," Economic Modelling, Elsevier, vol. 49(C), pages 186-197.

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