• Journal of Labour Economics
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• v.25 no.1
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• pp.75-95
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• 2002

Using 3 years of panel data on nearly 3,507 households, the Korea Labor Income Panel Survey(KLIPS) data, the authors measure the determinants of poverty and unemployment, and the extents to which poverty influenced unemployment. The probit analysis of unemployment shows that unemployment probability is lower, when male, lower age and is higher, high-school and over junior college, work duration is over 3 years. The probit analysis of poverty shows that poverty probability is lower, when male, higher education level, longer career. specially unemployment and social insurance is determinants of increasing poverty. Bivariate probit model of unemployment and poverty also provides similar findings to those probit analysis and shows an evidence of the influence of unemployment on poverty along with the positive role of social welfare policy such that social welfare receipt reduces the impact of unemployment on poverty.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.45-60
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• 2014

We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

• Journal of Environmental Impact Assessment
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• v.25 no.2
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• pp.124-140
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• 2016

Using the Korea Labor Institute Panel Study(KLIPS), this study investigates the impacts of water pollution on life satisfaction in Korea. Panel random-effects ordered probit model is used to consider the ordered property of life satisfaction data and heterogeneity of panel data. The proxy variables to reflect the degree of water pollution are biochemical oxygen demand(BOD) and total phosphorus(TP). In addition to the environmental variables above, other determinants used in various studies on life satisfaction such as economic, social, and demographic characteristics are included. Estimation results show that water pollution is negative and significant for life satisfaction. Other indicators such as income, age, house ownership, gender, education are positively related while urban residence and own business are shown to be negatively related.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.513-537
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• 2010

According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.210-219
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• 2010

Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

• Asian Journal of Business Environment
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• v.14 no.2
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• pp.11-18
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• 2024

Purpose: The purpose of this study is to empirically evaluate the unintended welfare losses induced by paid sick leave, examine the severity of the unintended moral hazard loss caused by paid sick leave, and evaluate how much moral hazard cost society can accept to obtain paid sick leave benefits. Research Design, Data and Methodology: We examine the Medical Expenditure Panel Survey data collected in 2013 and 2014 by employing a panel probit analysis to control for individual heterogeneity. Results: The estimation result shows that the probability of absence due to paid sick leave increases from 4.91% to 7.84%. Among them, excluding the probability of increasing absence from 1.29% to 2.69% due to the actual disease, the probability of absence due to the moral hazard was estimated to be 2.41% to 6.49% in the proposed models. Based on the result, if we evaluate the increase in absence caused by moral hazard as a social cost, the estimated cost is approximately $174 to $297 per worker per year. Conclusion: Considering these expected costs, our society can obtain the access benefit from paid sick leave if we are willing to accept the moral hazard cost.

• Korean Journal of Organic Agriculture
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• v.17 no.4
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• pp.413-439
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• 2009

This study conducts a survey and test to understand U.S. public's perception about multifunctionality. The questionnaire suggests seven alternative way of providing questions about intangible benefits provided by agriculture in the U.S. The final questionnaire was administered as an e-mail survey in June 2008 to a nationally representative household panel maintained in the U.S. by the Ipsos Observer. Data analysis shows that 64 percent of respondents considered the multifunctionality of agriculiture as an important issue and 45 percent of respondents were in favor of increasing government expenditure to support farmland preservation. Using Fishbein's multi-attribute model as a theoretical background, this paper develops an empirical model to assess and attributes of multifunctionality. For the analysis, bivariate orderd probit model was set up to reflect respondent's attitude. Regression analyses show that two questions (how much you agree with agriculture's intangible benefit and increasing government expenditure to support agriculture) are shaped by different sets of facts.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.315-323
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• 2019

Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

• 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.