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http://dx.doi.org/10.5351/CKSS.2008.15.2.161

Further Applications of Johnson's SU-normal Distribution to Various Regression Models  

Choi, Pilsun (Department of International Trade, Konkuk University)
Min, In-Sik (Department of Economics, Kyung Hee University)
Publication Information
Communications for Statistical Applications and Methods / v.15, no.2, 2008 , pp. 161-171 More about this Journal
Abstract
This study discusses Johnson's $S_U$-normal distribution capturing a wide range of non-normality in various regression models. We provide the likelihood inference using Johnson's $S_U$-normal distribution, and propose a likelihood ratio (LR) test for normality. We also apply the $S_U$-normal distribution to the binary and censored regression models. Monte Carlo simulations are used to show that the LR test using the $S_U$-normal distribution can be served as a model specification test for normal error distribution, and that the $S_U$-normal maximum likelihood (ML) estimators tend to yield more reliable marginal effect estimates in the binary and censored model when the error distributions are non-normal.
Keywords
$S_U$-normal distribution; skewness and kurtosis; normality test;
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  • Reference
1 Choi, P. and Nam, K. (2007). Asymmetric and leptokurtic distribution for heteroscedas- tic asset returns: the $S_U-normal$ distribution. Forthcoming in Journal of Empirical Finance
2 Choi, P. and Min, I. (2007). Estimating endogenous switching regression model with a °exible parametric distribution function: application to Korean housing demand. Forthcoming in Applied Economics
3 Rockinger, M. and Jondeau, E. (2001). Entropy Densities with an application to autore- gressive conditional skewness and kurtosis. Journal of Econometrics, 106, 119-142
4 Johnson, N. L. (1949). Systems of frequency curves generated by methods of translation. Biometrika, 36, 149-176   DOI
5 Theodossiou, P. (1998). Financial data and the skewed generalized T distribution. Management Science, 44, 1650-1661   DOI   ScienceOn
6 Theodossiou, P. (2000). Distribution of financial asset prices, the skewed generalized error distribution, and the pricing of options. Working Paper, Rutgers University
7 McDonald, J. B. and Yexiao, J. X. (1996). A comparison of semi-parametric and partially adaptive estimators of the censored regression model with possibly skewed and leptokurtic error distributions. Economics Letters, 53, 153-159   DOI   ScienceOn
8 Klaauw, B. and Konig, R. H. (2003). Testing the normality assumption in the sample selection model with an application to travel demand. Journal of Business and Economic Statistics, 21, 31-42   DOI   ScienceOn
9 van der Klaauw, B. and Konig, R. H. (2003). Testing the normality assumption in the sample selection model with an application to travel demand. Journal of Business and Economic Statistics, 21, 31-42   DOI   ScienceOn
10 Andrews, D. W. K. (1997). A conditional Kolmogorov test. Econometrica, 65, 1097-1128   DOI   ScienceOn
11 Zheng, J. X. (2000). A consistent test of conditional parametric distributions. Econometric Theory, 16, 667-691   DOI   ScienceOn
12 Bollerslev, T. (1987). A conditionally heteroskedastic time series model for speculative prices and rates of return. The Review of Economics and Statistics, 69, 542-547   DOI   ScienceOn
13 Choi, P. (2002). Essays on modeling asymmetric and leptokurtic distributions of asset returns, Ph.D. Thesis, Texas A&M University
14 Fan, Y., Li, Q. and Min, I. (2006). A nonparametric bootstrap test of conditional distributions. Econometric Theory, 22, 587-613
15 Hansen, B. E. (1994). Autoregressive conditional density estimation. International Economic Review, 35, 705-730   DOI   ScienceOn
16 McDonald, J. B. (1996). An application and comparison of some flexible parametric and semi-parametric qualitative response models. Economics Letters, 53, 145-152   DOI   ScienceOn