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Dynamic Censored Regression and the Open Market Desk Reaction Function

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  • Robert Jong
  • Ana María Herrera

Abstract

The censored regression model and the Tobit model are standard tools in econometrics. This paper provides a formal asymptotic theory for dynamic time series censored regression when lags of the dependent variable have been included among the regressors. The central analytical challenge is to prove that the dynamic censored regression model satisfies stationarity and weak dependence properties if a condition on the lag polynomial holds. We show the formal asymptotic correctness of conditional maximum likelihood estimation of the dynamic Tobit model, and the correctness of Powell's least absolute deviations procedure for the estimation of the dynamic censored regression model. The paper is concluded with an application of the dynamic censored regression methodology to temporary purchases of the Open Market Desk. This article has supplementary material online.

Suggested Citation

  • Robert Jong & Ana María Herrera, 2011. "Dynamic Censored Regression and the Open Market Desk Reaction Function," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 228-237, April.
  • Handle: RePEc:taf:jnlbes:v:29:y:2011:i:2:p:228-237
    DOI: 10.1198/jbes.2010.07181
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    File URL: http://hdl.handle.net/10.1198/jbes.2010.07181
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    Cited by:

    1. Ordoñez-Callamand, Daniel & Hernandez-Leal, Juan D. & Villamizar-Villegas, Mauricio, 2018. "When multiple objectives meet multiple instruments: Identifying simultaneous monetary shocks," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 78-101.
    2. Qu, Xi & Lee, Lung-fei, 2013. "Locally most powerful tests for spatial interactions in the simultaneous SAR Tobit model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 307-321.
    3. Qu, Xi & Lee, Lung-fei, 2012. "LM tests for spatial correlation in spatial models with limited dependent variables," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 430-445.
    4. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    5. Jean-Yves Gnabo & Luiz de Mello & Diego Moccero, 2010. "Interdependencies between Monetary Policy and Foreign Exchange Interventions under Inflation Targeting: The Case of Brazil and the Czech Republic," International Finance, Wiley Blackwell, vol. 13(2), pages 195-221, August.
    6. repec:eee:ecolet:v:162:y:2018:i:c:p:112-115 is not listed on IDEAS
    7. repec:eee:eejocm:v:28:y:2018:i:c:p:108-123 is not listed on IDEAS
    8. Chen, Ho-Chyuan & Chang, Kuang-Liang & Yu, Shih-Ti, 2012. "Application of the Tobit model with autoregressive conditional heteroscedasticity for foreign exchange market interventions," Japan and the World Economy, Elsevier, vol. 24(4), pages 274-282.
    9. Ana Maria Herrera & Pinar Ozbay, 2005. "A Dynamic Model of Central Bank Intervention," Working Papers 0501, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

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