• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1077-1085
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• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.733-749
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• 2018

Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.57-65
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• 2019

If aging apartments are left unimproved through remodeling, the city will be eventually slum. As the government recognizes remodeling as an alternative to reconstruction, the law has been revised mainly to increase the housing area, increase the number of house and allow the vertical extension for making remodeling costs. However, the remodeling is still not activated yet in the market. Therefore, this study analyzes the decision factors of apartment remodeling in Seoul metropolitan area based on Heckman two-stage analysis considering sampling error. Research findings indicate that the decision for remodeling is determined by the characteristics of the household, housing, and time-lapse variables. And also the number of household members, net assets, housing satisfaction, the 11-20, 21-30, and more than 30 years of building are identified as the significant variables as a result of remodeling choice probability analysis. It is noteworthy that the significant variables from then remodeling cost analysis are net assets, area, more than 30 years of building, and unit housing price. It is also notable that the policy, which extend the housing area to cover remodeling cost, are not actually effective to activate the remodeling, and the age in the case of elderly people in Seoul and Gyeonggi-do who are expected to have high net assets and income is not significant variables. This study is expected to provide more objective and reliable implication to the policy makers, the home owner and the investors on the decision making process related to the remodeling project.