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An approximate likelihood function for panel data with a mixed ARMA(p, q) remainder disturbance model

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  • Wen‐Den Chen

Abstract

. An approximate likelihood function for panel data with an autoregressive moving‐average (ARMA)(p, q) model remainder disturbance is presented and Whittle's approximate maximum likelihood estimator (MLE) is used to yield an asymptotic estimator. Although an asymptotic approach, the power test is quite successful for estimating and testing. In this approach, we do not need to calculate the transformation matrix in exact form. Through the Riemann sum approach, we can construct a simple approximate concentrated likelihood function. In addition, the model is also extended to the restricted maximum likelihood (REML) function, in which the package of Gilmour, Thompson and Cullis [Biometrics (1995) Vol. 51, pp. 1440–1450] is applied without difficulty. In the case study, we implement the model on the characteristic line for the investment analysis of Taiwanese computer motherboard makers.

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  • Wen‐Den Chen, 2006. "An approximate likelihood function for panel data with a mixed ARMA(p, q) remainder disturbance model," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(6), pages 911-921, November.
    • Handle: RePEc:bla:jtsera:v:27:y:2006:i:6:p:911-921
    DOI: 10.1111/j.1467-9892.2006.00495.x
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    2. Chen, W.D., 2016. "Policy failure or success? Detecting market failure in China's housing market," Economic Modelling, Elsevier, vol. 56(C), pages 109-121.

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