A note on Phillips (1991): "A constrained maximum likelihood approach to estimating switching regressions"
Phillips [Phillips R.F., 1991. A constrained maximum likelihood approach to estimating switching regressions.Â Journal of Econometrics 48, 241-262] proposed a constrained maximum-likelihood approach to estimating the parameters in a switching regression model. In this note, we propose a new approach which leads to a proof of a more general result than Phillips's. Specifically, we prove that the Constrained MLE (CMLE) is still strongly consistent when the constant c decreases to 0 at the rate of as n increases to [infinity], with [alpha]>1. We also suggest a suitable [alpha], hence cn, for practice based on simulation results.
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- Smith, Aaron & Naik, Prasad A. & Tsai, Chih-Ling, 2006.
"Markov-switching model selection using Kullback-Leibler divergence,"
Journal of Econometrics,
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- Smith, Aaron D. & Naik, Prasad A. & Tsai, Chih-Ling, 2005. "Markov-Switching Model Selection Using Kullback-Leibler Divergence," Working Papers 11976, University of California, Davis, Department of Agricultural and Resource Economics.
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- Phillips, Robert F., 1991. "A constrained maximum-likelihood approach to estimating switching regressions," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 241-262.
- Kiefer, Nicholas M, 1978. "Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model," Econometrica, Econometric Society, vol. 46(2), pages 427-34, March.
- Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
- Devroye, Luc, 1982. "Bounds for the uniform deviation of empirical measures," Journal of Multivariate Analysis, Elsevier, vol. 12(1), pages 72-79, March.
- Naik, Prasad A. & Shi, Peide & Tsai, Chih-Ling, 2007. "Extending the Akaike Information Criterion to Mixture Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 244-254, March.
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