• Environmental and Resource Economics Review
• /
• v.14 no.2
• /
• pp.447-474
• /
• 2005

Respondents, in the willingness to pay (WTP) survey, may have preference intensity about their stated WTP values. This study elicited a post-decisional intensity measure for each observed WTP answer for gathering information on the degree of preference intensity. In order to deal with the WTP data with preference intensity, this paper considers using the Type 3 Tobit model. This is usually estimated by the parametric two-stage estimation method assuming homoskedastic and bivariate normal error structure. However, if the assumptions are not satisfied, the estimates are inconsistent. The author has tested the hypotheses of homoskedasticity and normality, and could not accept them at the 1% level. The assumptions required to estimate the parametric Type 3 model are, therefore, too strong to be satisfied. As an alternative the parametric model, this study applies a semiparametric Type 3 Tobit model. The results show that the semiparametric model significantly outperforms the parametric model, and that more importantly, the mean WTP from the parametric model is significantly different from that from the semiparametric model.

• Environmental and Resource Economics Review
• /
• v.6 no.2
• /
• pp.233-258
• /
• 1997

본 논문은 가상가치기법(CVM)을 이용하여 대구시 수도물 수질개선의 경제적 편익에 대한 결정요인을 분석하고자 한다. 자료는 양분선택형 설문조사자료이며, 추정기법으로서 단일지수모형구조(single-index model)를 가정하는 두개의 준모수 추정법이 원용되었다. 비교목적으로 양분선택형 가상가치기법 문헌에서 전통적으로 사용되어 온 probit모형에 의한 추정결과도 아울러 제시된다.

• The Korean Journal of Applied Statistics
• /
• v.14 no.1
• /
• pp.161-175
• /
• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• The Korean Journal of Applied Statistics
• /
• v.28 no.6
• /
• pp.1121-1131
• /
• 2015

Logistic models with a random intercept are useful to analyze longitudinal binary data. Traditionally, the random intercept of the logistic model is assumed to be parametric (such as normal distribution) and is also assumed to be independent to variables. Such assumptions are very strong and restricted for application to real data. Recently, Garcia and Ma (2015) derived semiparametric efficient estimators for logistic model with a random intercept without these assumptions. Their estimator shows the consistency where we do not assume any parametric form for the random intercept. In addition, the method is computationally simple. In this paper, we apply this method to analyze toenail infection data. We compare the semiparametric estimator with maximum likelihood estimator, penalized quasi-likelihood estimator and hierarchical generalized linear estimator.

• Environmental and Resource Economics Review
• /
• v.21 no.4
• /
• pp.947-980
• /
• 2012

This study analyzes the long-run impacts of climate change on Korean agriculture and economy. We estimate the impacts of climate change on the productivities of major agricultural products including rice, dairy and livestock using both a simulation approach and a semiparametric econometric model. The former predicts a decline in productivity while the latter predicts an increase in productivity due to climate change, especially for rice. A recursive dynamic CGE model is used to analyze the general equilibrium impacts of productivity change under the two different scenarios, derived from the two productivity analysis approaches. The loss of GDP in 2050 is 0.2% or 0.02% of total GDP depending on the scenario. It is shown that the losses in dairy and livestock sectors are larger than that in rice sector, although the losses in those two non-rice sectors have been ignored by most existing works.

• The Korean Journal of Applied Statistics
• /
• v.33 no.1
• /
• pp.25-46
• /
• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Communications for Statistical Applications and Methods
• /
• v.5 no.3
• /
• pp.777-792
• /
• 1998

병원의 임상연구실험에서 종종 환자들의 치료에 따른 병세의 호전상태를 여러단계로 분류하여 상이한 치료방법에 대한 치료효과간의 차이론 알고자 하는 경우가 있다. 이와 같이 다중상태의 생존자료를 분석하기 위해서 본 논문에서는 semi-Markov 모형에 Cox 회귀모형을 적용하여 회귀계수와 기저생존함수를 추정하고 이를 바탕으로 반응확률함수를 추정하였다. 그리고 본 논문의 결과를 실제 임상실험에서 얻어진 자료에 적용하여 분석하였다.

• 한국노년학
• /
• v.32 no.4
• /
• pp.1063-1086
• /
• 2012

The purpose of this study is to understand the current state of the older people's social exclusion by identifying patterns of the change in social exclusion level through a longitudinal analysis with an aim of exploring the predictors of changes. To this end, this study has adopted the panel data, the English longitudinal Study of Ageing(ELSA). The data of 7631 respondents who aged over 50 were used for the final analysis. The social exclusion of the older people was analyzed into five different sub-dimensions: social relationship; cultural activities; access to health services; financial security; and sense of loneliness. The person-centered approach that focuses on the various patterns of the trajectories of change has used semi-parametric group based model in order to estimate different trajectories among individuals. The data was analyzed using Spss 18.0 and SAS 9.2 proc traj. In results, First, semi-parametric group-based model analysis has shown that the older people are not 'homogeneous' group with similar exclusion level in every individual with same trajectories of change, but can be divided into various categories with diverse intercept and slope. Second, different trajectories in change of exclusion level help to confirm that the older people's social exclusion level increases gradually over time or remains unchanged. Third, this analysis has provided the useful guidelines to identify the high-risk groups of social exclusion. Forth, the variables that make difference in more than three dimensions include gender, age, self-perceived health, physical activity, weekly income, marital status, family relation, and beneficiary status. Implications and further suggestion were discussed.

• 한국노년학
• /
• v.37 no.3
• /
• pp.617-635
• /
• 2017

The aim of this study was to investigate both poverty and depression among older adults, focusing on the relationship of these two trajectories. For expanding the understanding about elderly poverty and depression, the study measured the longitudinal patterns of various transition in these two variables. The data for the study is 1st to 9th waves (2006-2014) of Korea Welfare Panel Study (KoWePS), and 4,431 older adults were used for the final analysis. For data analysis, Semi-parametric group-based modeling and Dual trajectory model were selected. The main results of this study were followings; First, The trajectory groups were identified: non-poverty, decrease poverty, increase poverty, remain high-poverty, chronic poverty groups and 4 trajectories of depression: stable, remain low-depression, risk of depression, chronic depression groups. Second, the study was tried to anticipate the longitudinal transition of poverty and depression status, and investigate the concurrent relationship in these two variables. It turned out that the stable poverty status led the stable depression, and vice versa. Based on these result, this study for elderly welfare were discussed to reduce risk for poverty and depression.

• The Korean Journal of Applied Statistics
• /
• v.29 no.1
• /
• pp.171-180
• /
• 2016

Basel committee suggests using Value-at-Risk (VaR) and expected shortfall (ES) as a measurement for market risk. Various estimation methods of VaR and ES have been studied in the literature. This paper compares semi-parametric methods, such as conditional autoregressive value at risk (CAViaR) and conditional autoregressive expectile (CARE) methods, and a Gaussian quasi-maximum likelihood estimator (QMLE)-based method through back-testing methods. We use unconditional coverage (UC) and conditional coverage (CC) tests for VaR, and a bootstrap test for ES to check the adequacy. A real data analysis is conducted for S&P 500 index and Hyundai Motor Co. stock price index data sets.