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Some Results on Cointegration with Random Coefficients in the Error Correction Form: Estimation and Testing

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  • P. W. Fong
  • W. K. Li

Abstract

. This study considers a time‐series model with random coefficients in cointegration. The estimation problem can be solved by maximizing the log‐likelihood. Asymptotic distributions of the least squares and maximum likelihood estimates are considered. The randomness of the cointegration vector is checked by a score‐based test approach. The test statistic converges asymptotically to a functional of Brownian processes. An empirical application to two cointegrated series, federal fund rate and 90‐day treasury bill rate is considered.

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  • P. W. Fong & W. K. Li, 2004. "Some Results on Cointegration with Random Coefficients in the Error Correction Form: Estimation and Testing," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 419-441, May.
    • Handle: RePEc:bla:jtsera:v:25:y:2004:i:3:p:419-441
    DOI: 10.1111/j.1467-9892.2004.01913.x
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    Cited by:

    1. Fong, P.W. & Li, W.K. & An, Hong-Zhi, 2006. "A simple multivariate ARCH model specified by random coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1779-1802, December.
    2. Hui, Cho-Hoi & Fong, Tom Pak-Wing, 2015. "Price cointegration between sovereign CDS and currency option markets in the financial crises of 2007–2013," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 174-190.
    3. Nielsen, Heino Bohn & Rahbek, Anders, 2014. "Unit root vector autoregression with volatility induced stationarity," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 144-167.

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