• Title/Summary/Keyword: Probit model

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Empirical Analysis of 3 Statistical Models of Hospital Bankruptcy in Korea (병원도산 예측모형의 실증적 비교연구)

  • 이무식;서영준;양동현
    • Health Policy and Management
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    • v.9 no.2
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    • pp.1-20
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    • 1999
  • This study was conducted to investigate the predictors of hospital bankruptcy in Korea and to examine the predictive power for 3 types of statistical models of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 30 bankrupt and 30 profitable hospitals in 1. 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the predictive power of statistical models of hospital bankruptcy were compared. The major findings are as follows. 1. Nine out of 21 indicators - fixed ratio, quick ratio, operating profit to total assets, operating profit to gross revenue, normal profit to total assets,normal profit to gross revenue, net profit to gross revenue, inventories turnrounds, and added value per adjusted patient - were found to be significantly predictitive variables in Logit and Probit models. 2. The predicdtive power of discriminant model of hospital bankruptcy in 1. 2, and 3 years before bankruptcy were 85.4, 79.0, and 83.8% respectively. With regard to the predictive power of the Logit model of hospital bankruptcy, they were 82.3, 75.8, and 80.6% respectively, and of the Probit model. 87.1. 80.6, and 88.7% respectively. 3. The predictive power of the Probit model of hospital bankruptcy is better than the other two predictive models.

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Development of Bicycle Level of Service Model from the User's Perspective Using Ordered Probit Model (순서형 프로빗 모형을 이용한 이용자 중심의 자전거 서비스 수준 모형 개발)

  • Lee, Gyeo-Ra;Rho, Jong-Ki;Kang, Kyung-Woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.2
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    • pp.108-117
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    • 2009
  • The South Korean government is looking for a solution to the ever-growing problems of traffic congestion, and surging international oil prices: the use of the humble bicycle to get to places. However, Many people feel inconvenient using bicycle because of the insufficient bicycle infrastructure and lack of the safety and connectivity between existing pathways. In this study, bicycle level of service model using ordered probit model is developed considering safety, convenience, connectivity, and factors that affect bicycle LOS. The ordered probit model would be recommended for the research which relates in choice, preference and strength etc. Bicycle level of service criteria is calculated by applying this model reflecting bicyclist's point of view. The model which develops from this research which accomplishes a bicycle level of service evaluation and represent alternative solution to encourage bicyclist. It is believed that the proposed model would be greatly utilized in bicycle network planning, bicycle road and facility alternatives testing, projects funding priority.

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A Bayesian inference for fixed effect panel probit model

  • Lee, Seung-Chun
    • 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.

Assessing Public Attitude for Multifunctional Roles of the U.S. Agriculture Using a Bivariate Ordered Probit Model (Bivariate Ordered Probit 모형을 이용한 미국 농업의 다원적 기능에 대한 소비자 인식분석)

  • Han, Jung-Hee;Moon, Wan-Ki;Cho, Yong-Sung
    • 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.

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Interdependence of Poverty and Unemployment and the Welfare Policy Effectiveness (빈곤과 실업의 원인과 복지정책의 효과)

  • An, Chong-Bum;Kim, Cheol-Hee;Jeon, Seung-Hoon
    • 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.

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A Study on the Estimation of Human Damage Caused by the LP Gas Flame in Enclosure using Probit Model

  • Leem, Sa-Hwan;Huh, Yong-Jeong
    • Journal of the Korean Institute of Gas
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    • v.13 no.3
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    • pp.43-48
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    • 2009
  • The energetic and environmental problems have been getting serious after the revolution of modern industry. Therefore, demand of gas as an eco-friendly energy source is increasing. With the demand of gas, the use of gas is also increased, so injury and loss of life by the fire have been increasing every year. Hence the influence on flame caused by Vapor Cloud Explosion in enclosure of experimental booth was calculated by using the API regulations. And the accident damage was estimated by applying the influence on the adjacent structures and people into the PROBIT model. According to the probit analysis, the spot which is 5meter away from the flame has nearly 100% of the damage probability by the first-degree burn, 27.8% of the damage probability by the second-degree burn and 14.5% of the death probability by the fire.

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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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A Study on the Satisfaction of School meals about Elementary, Middle and High School's Students in Jeonbuk Area : An Ordered Probit Analysis (순위프로빗모형을 이용한 전북지역 초.중.고교 학생들의 학교급식에 대한 만족도 분석)

  • Lim, Sung-Soo;Yang, Jae-Seong
    • Korean Journal of Organic Agriculture
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    • v.21 no.4
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    • pp.539-554
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    • 2013
  • This study analyses the factors that affect the satisfaction of school meals program. To obtain the data, 54 elementary, middle and high schools in Jeonbuk area were chosen for survey. A ordered probit model analysis is conducted to identify the key explanatory variables that affect the satisfaction of school meals about elementary, middle and high school's students. Also, a ordered probit model is used to calculate marginal effects of several key variables. The study finds that key factors that affect to increase the satisfaction of school meals are rural area schools, elementary school's students, and education for school meals or food nutrition. The satisfaction of school meals in urban and rural school's students are significantly different. Also, the satisfaction of school meals about elementary, middle and high school's students are significantly different. To do this, importance of school meals is to build up the safe agricultural supply system. For safe agricultural supply system, local agricultural products provided in school meals should be supplied based on GAP, HACCP certificated companies such as US FTS(Farm to School) program.

Bayesian Analysis of Korean Alcohol Consumption Data Using a Zero-Inflated Ordered Probit Model (영 과잉 순서적 프로빗 모형을 이용한 한국인의 음주자료에 대한 베이지안 분석)

  • Oh, Man-Suk;Oh, Hyun-Tak;Park, Se-Mi
    • The Korean Journal of Applied Statistics
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    • v.25 no.2
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    • pp.363-376
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    • 2012
  • Excessive zeroes are often observed in ordinal categorical response variables. An ordinary ordered Probit model is not appropriate for zero-inflated data especially when there are many different sources of generating 0 observations. In this paper, we apply a two-stage zero-inflated ordered Probit (ZIOP) model which incorporate the zero-flated nature of data, propose a Bayesian analysis of a ZIOP model, and apply the method to alcohol consumption data collected by the National Bureau of Statistics, Korea. In the first stage of a ZIOP model, a Probit model is introduced to divide the non-drinkers into genuine non-drinkers who do not participate in drinking due to personal beliefs or permanent health problems and potential drinkers who did not drink at the time of the survey but have the potential to become drinkers. In the second stage, an ordered probit model is applied to drinkers that consists of zero-consumption potential drinkers and positive consumption drinkers. The analysis results show that about 30% of non-drinkers are genuine non-drinkers and hence the Korean alcohol consumption data has the feature of zero-inflated data. A study on the marginal effect of each explanatory variable shows that certain explanatory variables have effects on the genuine non-drinkers and potential drinkers in opposite directions, which may not be detected by an ordered Probit model.