HASAN, HAMID and Rehman, Attiqur (2013): A potential solution to problems in ordered choice models involving endogenous ordinal variables for self-reported questions.
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Abstract
Most of the surveys in social sciences generally consist of ordinal variables. Sometimes researchers need to model behaviour of ordinal variables in simultaneous equation system involving many endogenous ordinal variables. This situation leads to a very complex likelihood function which is extremely hard to solve. The solutions suggested in the literature are even harder to understand by applied researchers. The present study suggests a simulation method to avoid this problem altogether by converting ordinal variables into continuous variables and use standard simultaneous regression models. The proposed method involves generating random numbers from continuous probability distributions (uniform and truncated normal distributions) within a discrete probability distribution. This method can be fruitfully be used in ordered logit and probit models. The limitations of this method are also discussed.
Item Type: | MPRA Paper |
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Original Title: | A potential solution to problems in ordered choice models involving endogenous ordinal variables for self-reported questions |
Language: | English |
Keywords: | Endogenous Ordinal variables, Simultaneous Equation System, Ordered Logit, Ordered Probit. |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics |
Item ID: | 44908 |
Depositing User: | HAMID HASAN |
Date Deposited: | 09 Mar 2013 19:48 |
Last Modified: | 01 Oct 2019 13:38 |
References: | Baltaqi, B. H. (2010). Econometrics. Springer. Heckman, James. J. (1977). Dummy Endogenous Variables in a Simultaneous Equation System, Econometrica, Vol. 46, No. 4, pp. 931-959. Kuklys, W., 2005. Amartya Sen’s Capability Approach – Theoretical Insights and Empirical Applications. Springer, Berlin et al. Long, J. Scott and Jeremy Freese. (2006). Regression Models for Categorical Dependent Variables Using Stata, Second Edition. College Station, Texas: Stata Press. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/44908 |