Biørn, Erik and Wangen, Knut R. (2012): New Taxonomies for Limited Dependent Variables Models.
Download (97Kb) | Preview
We establish a `map' for describing a wide class of Limited Dependent Variables models much used in the econometric literature. The classification system, or language, is an extension of Amemiya's typology for tobit models and is intended to facilitate communication among researchers. The class is defined in relation to distributions of latent variables of an arbitrarily high dimension; the region of support can be divided into an arbitrary number of subsets, and the observation rules in each subset can be any combination of the observed, censored, and missing status. Consistent labeling is suggested at different levels of detail.
|Item Type:||MPRA Paper|
|Original Title:||New Taxonomies for Limited Dependent Variables Models|
|Keywords:||Limited dependent variables, Latent variables, Censoring, Truncation, Missing observations|
|Subjects:||C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C24 - Truncated and Censored Models; Switching Regression Models
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
|Depositing User:||Erik Biorn|
|Date Deposited:||24. Sep 2012 02:33|
|Last Modified:||11. Feb 2013 21:43|
Amemiya, T. (1984): Tobit models: A survey. Journal of Econometrics, 24, 3-61.
Dagenais, M.G. (1975): Application of a threshold regression model to household purchases of automobiles. Review of Economics and Statistics, 57, 275-285.
Hein, J.L. (2002): Discrete Structures, Logic, and Computability, Second Edition. Sudbury, MA: Jones and Bartlett Publishers.
Li, P. (2011): Estimation of sample selection models with two selection mechanisms. Computational Statistics and Data Analysis, 55, 1099-1108.
Maddala, G.S. (1983): Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.
Nelson, F.D. (1977): Censored regression models with unobserved, stochastic censoring thresholds. Journal of Econometrics, 6, 309-327.
Schnedler, W. (2005): Likelihood estimation for censored random vectors. Econometric Reviews, 24, 195-217.
Toomet, O. and Henningsen, A. (2008): Sample selection models in R: Package sampleSelection. Journal of Statistical Software, 27, 1-23.