ALTERNATIVE SEMIPARAMETRIC ESTIMATION FOR NON-NORMALITY IN CENSORED REGRESSION MODEL WITH LARGE NUMBER OF ZERO OBSERVATION

Andres Purmalino, Asep Saefuddin, Hari Wijayanto

Abstract


A large number of zero observation on the response variable in the socio-economic field are often found in household demand models. This will imply on the method to estimate parameters in the model used. Ordinary least square estimators of linear models to be biased and inconsistent. One model to overcome is using censored regression model is also know as tobit model. However, non-normality in the Tobit Estimators being inconsistent. Another alternative estimators is censor least absolute deviations (CLAD). CLAD estimator is consistent and asymptotically normal for a wide class of distribution. This study was to focus on the application of Tobit and Censored Least Absolute Deviations (CLAD) estimators for LPG demand. The data used is the LPG expenditure in rural areas in the provinces of West Java that the number zero observations is 39 percent of the sample. The result shows that CLAD and Tobit estimators are consistent estimators. But along with increasing the number of samples, the CLAD estimators performance is getting better than Tobit estimators.
Keywords : Zero observation, CLAD, Tobit, Consistent estimator, LPG demand


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Indonesian Journal of Statistics and Its Applications pages