• Title/Summary/Keyword: Multinomial Probit

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Development of a Recursive Multinomial Probit Model and its Possible Application for Innovation Studies

  • Jeong, Gicheol
    • STI Policy Review
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    • v.2 no.2
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    • pp.45-54
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    • 2011
  • This paper develops a recursive multinomial probit model and describes its estimation method. The recursive multinomial probit model is an extension of a recursive bivariate probit model. The main difference between the two models is that a single decision among two or more alternatives can be considered in each choice equation in the proposed model. The recursive multinomial probit model is developed based on a standard framework of the multinomial probit model and a Bayesian approach with a Gibbs sampling is adopted for the estimation. The simulation exercise with artificial data sets is showed that the model performed well. Since the recursive multinomial probit model can be applied to analyze the causal relationship between discrete dependent variables with more than two outcomes, the model can play an important role in extending the methodology of the causal relationship analysis in innovation research.

Residential Heating Fuel Choice in Korea - A Multinomial Probit Analysis - (Multinomial Probit 모형을 이용한 가정용 난방연료 선택에 관한 연구)

  • Kim, Yeonbae;Shin, Seong-Yun
    • Environmental and Resource Economics Review
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    • v.11 no.4
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    • pp.609-632
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    • 2002
  • 국민소득이 빠르게 증가함에 따라 1990년대 이후 가정용 난방연료의 소비구조 역시 크게 변화하고 있다. 본 연구는 에너지 및 교통수요분석에 많이 사용되는 Multinomial Probit 모형을 이용하여 가정용 난방연료의 선택 행태를 분석하였다. 모형의 추정방법으로는 베이지안(Baysian) 방법론에 의한 Gibbs Sampling기법 (McColluch et al., 2000)을 이용하여 Multinomial probit 모형에서 선택대안이 3개 이상일 경우 발생할 수 있는 추정상의 어려움을 극복하였다. 한국가구패널조사(KHPS) 자료를 이용하여 서울과 경기도 대도시 지역을 대상으로 분석한 결과, 석유와 천연가스가 연탄에 비해 더 밀접한 상호 대체관계를 가지고 있는 것으로 나타났다. 또한 소득이 높은 가구일수록 천연가스에 대한 선호도가 더 높은 것으로 나타나서 향후 공급망 확대에 따라 난방연료용 가스 소비가 더욱 늘어날 것으로 예상된다.

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Variational Bayesian multinomial probit model with Gaussian process classification on mice protein expression level data (가우시안 과정 분류에 대한 변분 베이지안 다항 프로빗 모형: 쥐 단백질 발현 데이터에의 적용)

  • Donghyun Son;Beom Seuk Hwang
    • The Korean Journal of Applied Statistics
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    • v.36 no.2
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    • pp.115-127
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    • 2023
  • Multinomial probit model is a popular model for multiclass classification and choice model. Markov chain Monte Carlo (MCMC) method is widely used for estimating multinomial probit model, but its computational cost is high. However, it is well known that variational Bayesian approximation is more computationally efficient than MCMC, because it uses subsets of samples. In this study, we describe multinomial probit model with Gaussian process classification and how to employ variational Bayesian approximation on the model. This study also compares the results of variational Bayesian multinomial probit model to the results of naive Bayes, K-nearest neighbors and support vector machine for the UCI mice protein expression level data.

Economic Values of Recreational Water: Rafting on the Hantan River (수자원의 휴양가치분석 : 한탄강 래프팅을 사례로)

  • Kwon, Oh Sang;Lim, YoungAh;Kim, Won Hee
    • Environmental and Resource Economics Review
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    • v.16 no.3
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    • pp.427-449
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    • 2007
  • This study estimates the recreation benefits of rafting on the Hantan River. A choice experiment is conducted and the economic values of controlling water stream and water quality are estimated. Both the conditional logit and the multinomial pro bit models are estimated. This study rejects the IIA assumption of the conditional log it model and supports using a more flexible model such as the multinomial probit model.

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An Analysis of Factors Influencing the Choice of New Farming Type (취농 유형 선택에 영향을 미치는 요인분석)

  • Kim, Seongsup;Lee, In Kyu;Jeong, Jae Won
    • Journal of Korean Society of Rural Planning
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    • v.24 no.4
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    • pp.27-35
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    • 2018
  • This study analyzed the factors influencing the choice of new farming type in order to prepare the countermeasures against structural changes of farm labor force. The analytical model was the multinomial logit model(MNL). The test for Independence and Irrelevance Alternatives(IIA) assumption in MNL shows that the IIA assumption in our data is rejected. Alternatively, we chose the multinomial probit model(MNP) that does not assume IIA. Data were obtained from 2010 census of Agriculture, Forestry and Fisheries of Statistics Korea. New farming types are succession(13.9%), return-to-farming(45.0%), part-time-farming(32.5%) and etc(8.6%). Analysis results showed that the characteristics of farms, commodity, management, and region influenced the choice of new farming type. This study is expected to help policy makers to produce support policies by new farming types in order to increase the number of new farmers and to make them easier to settle down in agriculture.

Consumer Preferences for Digital Cable Broadcasting Service in Korea: A Choice Experiment Study

  • Ku, Se-Ju;Yoo, Seung-Hoon;Kwak, Seung-Jun
    • Asian Journal of Innovation and Policy
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    • v.5 no.2
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    • pp.185-196
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    • 2016
  • A digital cable broadcasting service is a multimedia broadcasting service that provides high definition and various supplementary services by using digital transmission. Korea implemented a complete digital broadcasting service by 2012. This study applied a choice experiment to investigate consumer preferences, and it calculated the marginal willingness to pay for this service. Moreover, we employed a multinomial probit model to relax the assumption that all respondents have the same preference for attributes being valued. The results suggest that respondents value channels, definition, video-on-demand (VOD) service, pay-per-view (PPV) service, and commerce based on TV (T-commerce). On the other hand, online gaming may be less important as an attribute for digital cable broadcasting service in Korea.

A Bayesian Variable Selection Method for Binary Response Probit Regression

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.167-182
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    • 1999
  • This article is concerned with the selection of subsets of predictor variables to be included in building the binary response probit regression model. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the probit regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. The appropriate posterior probability of each subset of predictor variables is obtained through the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as the one with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

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An Exploratory Study on User Characteristics of Social Media: From the Perspective of Consumer Innovativeness (소셜미디어 이용자 특성에 대한 탐색적 연구: 소비자혁신성을 중심으로)

  • Shin, Hyunchul;Kim, Yongwon;Kim, Yongkyu
    • Journal of Digital Convergence
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    • v.18 no.10
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    • pp.195-206
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    • 2020
  • This study aims to analyze the effect of consumer characteristics such as consumer innovativeness on using popular social media in Korea. Social media usage is estimated by probit and multinomial probit model with user characteristics using Korea media panel data of 2019. According to the analysis, users with hedonoc innovativeness are likely to use social media, while users with cognitive innovativeness are not likely to use it. Regarding individual social media usage, functional innovativeness increases the probability of using Kakaostory, and hedonic innovativeness increases the likelihood of using Instagram. However, cognitive innovativeness decreases the probability of using Kakaosotry and Naver Band. This study gives insights into finding out specific social media for marketing certain products with innovativeness. In future research, it may be worthwhile to analyze under the assumption that a social media user is using several social media simultaneously.

A Review on Dynamic Changes of Consumer's Attributes and Marketing Mix Strategies of Cut Roses in Korea (장미에 대한 선호속성의 동태적 변화와 마케팅 믹스전략 탐색)

  • Kim, Bae-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.10
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    • pp.4328-4336
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    • 2011
  • The aim of this study is to find changes of the attributes that influence the purchase of cut roses during recent five years(2007~2011) and suggest some implications on ways to promote cut roses marketing. For this purpose, a survey was conducted through the Internet among 1,100 randomly chosen people living in Seoul, Inchon and Gyeonggi Province in 2011. A total of 1,023 valid replies were received for the analysis of the survey which was carried out by the subsidiary consulting firm. The survey panels and estimation models to analyze changes of consumers' preference attributes during recent five years are same to them of Kim, et al.(2007). That is, empirical analysis tools such as ordered probit model, multinomial logit model, and conjoint analysis were used according to Kim, et al.(2007). This paper suggests several policy implications to set up the target market of cut roses and marketing mix strategy to specify the best 4P(product, price, place and promotion).

Estimating the Attribute Values of 4 Major River Estuaries in Korea -Focusing on Testing for the IIA Assumption in MNL Model and the Alternative Models- (4대강 하구의 속성 가치 추정 -다항로짓모형에서 IIA가정의 검토와 대안 모형을 중심으로-)

  • Shin, Youngchul
    • Environmental and Resource Economics Review
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    • v.22 no.3
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    • pp.521-545
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    • 2013
  • This study applied choice experiment(CE) method(which is included in the stated preference method) to estimate values of some important attributes(i.e. type of estuary, water quality of river in estuary, water quality of sea in estuary, biodiversity level of estuary) of 4 major river(Hangang, Guemgang, Yeongsangang, Nakdonggang) estuaries in Korea. Although the multinomial logit model(MNL) is generally applied to analyse the CE data, testing for IIA assumption with the Hausman and McFadden test in MNL model shows that the IIA assumption in our data is rejected. Therefore, the heteroscedastic extreme value model(HEV) and the multinomial probit model(MNP) which are not based on the IIA assumption are used to analyse our CE data. As results, the coefficients and the elicited economic values of MNL model are seriously distorted if the IIA assumption is not satisfied in MNL model. The estimation results of MNP model show that the economic values are elicited as 352.3 billion won(95% C.I. 261.1 - 477.8 billion won) for natural estuary, 411.5 billion won(95% C.I. 338.5 - 525.5 billion won) for one grade improvement of river water quality in estuary, 358.9 billion won(95% C.I. 292.5 - 457.0 billion won) for one grade improvement of sea water quality in estuary, and 151.9 billion won(95% C.I. 99.0 - 218.6 billion won) for one grade improvement of biodiversity level of estuary. Therefore, the value of estuary is reached to 2,197.0 billion won(95% C.I. 1,721.0 - 2,879.9 billion won) if any natural estuary in 4 major rivers has good water quality of river in estuary(i.e. 2nd grade), good water quality of sea in estuary(i.e. 1st grade), and good biodiversity level of estuary.