• Title/Summary/Keyword: tobit regression

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Analysis of Bank Efficiency Between Conventional Banks and Regional Development Banks in Indonesia

  • ABIDIN, Zaenal;PRABANTARIKSO, R.Mahelan;WARDHANI, Rhisya Ayu;ENDRI, Endri
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.1
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    • pp.741-750
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    • 2021
  • The research aims to analyze the level of efficiency by grouping banks during the period 2017 - 2018 into category 1 and category 2 banks and then dividing them as Regional Development Banks (BPD) and Non-BPD Conventional Commercial Banks (BUK) within each category. The research objects are banks within the categories BPD and BUK comprised 18 BPDs and 35 BUKs. The research methodology uses 3 stages, first, using Data Envelopment Analysis (DEA) we measure the level of bank efficiency; second, using the Tobit regression model we evaluate the effect of financial performance on DEA efficiency, and third, using the Mann-Whitney test we determine whether there is a difference in the efficiency of category 1 and 2 banks. The results showed that there was a decrease in the efficiency of category 1 and 2 banks but on average, the efficiency of category 1 banks is higher than category 2 banks. The estimation results of the Tobit regression model show that only the ROA variable affects the efficiency level of category 1 banks, while category 2 banks are influenced by NPL and ROA variables. In the Mann-Whitney test, it was proven that there were differences in efficiency between BUK and BPD in category 1 and 2 banks.

Analyzing the Influence Factors on Efficiency of Railway Transport using DEA and Tobit Model (DEA와 Tobit 모형을 이용한 철도산업 효율성 결정요인 분석)

  • Lee, Yoon-Mi;Yoo, Jae-Kyun
    • Journal of the Korean Society for Railway
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    • v.12 no.6
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    • pp.1030-1036
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    • 2009
  • In 1990's, in Europe and some advanced nations, the structural reform of the railroad industry for improving the productive efficiency of the railroad industry and competitive power had been progressed. This paper empirically explores the relationship between railway restructuring and productive efficiency in the railway industry. We use Data Envelopment Analysis (DEA) to construct efficiency scores, and explain these scores, using Tobit regression analysis by using variables reflecting institutional factors and organizational type. Our results suggest that vertical separation, infrastructure and services are separated, and horizontal separation, passenger service and freight service are separated, improve productive efficiency. We also find that market competition has positive effect on the efficiency, but independent management from the government has negative effect, which is in line with economic intuition as well as with expectations on the railway restructuring. As a consequence, increased independence without sufficient competition and adequate regulation may deteriorate incentives for productive efficiency.

Analysis of Accident Factors at Arterial Roads Using Tobit Model (Tobit 모형을 이용한 간선도로 사고 요인 분석)

  • Kim, Kyung Hwan;Park, Byung Ho
    • International Journal of Highway Engineering
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    • v.15 no.2
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    • pp.131-138
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    • 2013
  • PURPOSES : The intents of the study are to identify the accident factors and to demonstrate the potentials of tobit model as a tool to study the number of accidents on arterial roads segments. METHODS : This paper uses a tobit regression as a methodology to analyze the factors affecting the number of accidents. In pursuing the above goal, this study gives particular attentions to analyzing the data of 2,446 accidents (1,610 in major arterial roads and 836 in minor arterial roads) occurred on arterial roads in 2007 to 2010. RESULTS : First, 3 accident models which were classified by total arterial roads, major arterial roads and minor arterial roads, and were all statistically significant were developed. Second, the exclusive right-turn lane as common variable, and the number of accident, traffic volume, number of lanes, link length, rate of median, number of entrances, number of pedestrian crossings, number of curves, number of bus stops and exclusive left-turn as specific variables of the models were selected. Finally, the paired sample t-test could not be rejected the null hypotheses of three types of models. CONCLUSIONS : Using data from vehicle accidents on arterial roads, the estimation results show that many factors related to roadway geometrics and traffic characteristics significantly affect to the number of accidents.

The Estimation of Domestic Construction Technology Full-Text Services using Tobit Model (Tobit 모형을 이용한 국내 건설기술 원문서비스 가치 추정)

  • Jeong, Seong-Yun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.6
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    • pp.656-662
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    • 2016
  • We have provided a variety of domestic construction technology related full-text services through the Construction Technology Digital Library system since 2001. CODIL is a system that services the database related to construction technology data. On the other hand, there is growing demand for DB every year, but the required budget is shrinking. Therefore, this study investigated the satisfaction to effectively service the construction technique-related full-text with a limited budget. The monetary value of full-text to express satisfaction with the quantified value was estimated using the Tobit model. The Tobit model is used as a contingent valuation method to estimate the value of non-market goods. This model is the limited dependent variable regression model to observations by censoring the limit of the left side or right side so that a biased outlier is not reflected in the willingness to pay. A survey was conducted by sampling 312 respondents. The mean, median, truncating the willingness of payment were calculated for the six types of the full-text services using the Tobit model. The statistically significant variables affecting the willingness to pay for the full-text services were identified. The mean value of per the full-text service was estimated to be 46,530 won. The significance of this study was to use the Tobit model to estimate the value of the construction technology-related full-text services for the first time in Korea.

Assessment of Interruption Costs on the Industry Load through Using the Microscopic Method (미시적 방법을 이용한 산업체 수용가의 공급지장비용 함수(SCDF) 산정)

  • Kim, Yong-Ha;Lee, Pyong-Ho;Kim, Young-Gil;Sin, Hyung-Chul;Oh, Seok-Hyun;Woo, Sung-Min
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.25 no.4
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    • pp.88-96
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    • 2011
  • This paper assesses interruption costs on the industry load through using the microscopic method. For assessment, the questionnaire was made on Korea Standard Industry Categorization which is composed of 28 type of industry Then, the survey was distributed to 1889 business in 12 area by staffs of KEPCO. The collected data is changed to the trustworthy data by using Bad Data Selection method and then the interruption costs of industry load was calculated by Tobit Regression which is tool analysing both collected data and the others.

Bayesian Interval Estimation of Tobit Regression Model (토빗회귀모형에서 베이지안 구간추정)

  • Lee, Seung-Chun;Choi, Byung Su
    • The Korean Journal of Applied Statistics
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    • v.26 no.5
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    • pp.737-746
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    • 2013
  • The Bayesian method can be applied successfully to the estimation of the censored regression model introduced by Tobin (1958). The Bayes estimates show improvements over the maximum likelihood estimate; however, the performance of the Bayesian interval estimation is questionable. In Bayesian paradigm, the prior distribution usually reflects personal beliefs about the parameters. Such subjective priors will typically yield interval estimators with poor frequentist properties; however, an objective noninformative often yields a Bayesian procedure with good frequentist properties. We examine the performance of frequentist properties of noninformative priors for the Tobit regression model.

An Investigation of Factors Affecting Management Efficiency in Korean General Hospitals Using DEA Model (DEA모형을 이용한 종합병원의 효율성 측정과 영향요인)

  • Ahn, In-Whan;Yang, Dong-Hyun
    • Korea Journal of Hospital Management
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    • v.10 no.1
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    • pp.71-92
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    • 2005
  • The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.

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Analysis on Awareness and Characteristics of Consumers Purchasing Punica Granatum (석류 소비자 구매의식과 구매특성 분석)

  • Kim, Mi-Ok;Cho, Yong-Been
    • Journal of Agricultural Extension & Community Development
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    • v.23 no.1
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    • pp.15-25
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    • 2016
  • In this study, we examined the awareness of consumers purchasing Punica granatum by conducting a survey on consumption of Punica granatum for the consumer panel of the Rural Development Administration (RDA) and derived the purchasing characteristics from the actual purchase date analyzed in a Linear regression model and Tobit model. Most consumers had been purchasing Punica granatum for health and beauty, and the proportion of that consumers were willing to repurchase Punica granatum was 93.1%. The result of examining the biggest considerations in 5 point scale when choosing a Punica granatum was in the order of freshness (4.37)> price (4.15)> safety (4.13)> size(3.86)> brand (3.27)> discount event (2.76). When we compared the results between a linear regression model and tobit model, the signs of all variables are consistent with each other. However, it was estimated that all absolute values of the coefficient values in the results of the tobit model analysis were larger than the values in the linear regression model, except for the "favorite purchasing place" of a weekday traditional markets. Punica granatum is known as a good fruit for postmenopausal women and it seems that the higher age is, the more purchase there will be. The more income a housewife had, the greater purchase there was. In the case of the purchase amount, a selecting for a eating pleasure was bigger than a selecting for a need of health. Therefore, it is necessary to develop Punica granatum with a taste in consumer preferences.

A Study on the Dissemination Structure of Unfilled Positions in Universities Across the Country using Big Data: Using Panel and Tobit Regression Model (빅 데이터를 활용한 대학의 지역·권역별 학과의 미충원 파급구조 연구: 패널회귀모형과 토빗회귀모형의 응용을 중심으로)

  • Dong Woo Chae;Kun Oh Jung
    • Journal of Information Technology Applications and Management
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    • v.30 no.1
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    • pp.33-52
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    • 2023
  • This study observes the difference in the actual regional ripple effect of the decrease in admission resources due to the decrease in school age population, which has been weak in empirical studies, and how much the decrease in competition rate by department nationwide provides a significant shock to the decrease in enrollment rate in the population unit. An empirical quantitative analysis was attempted. As a result of applying the panel-tobit regression model, a clear gap was confirmed in the decrease in the registration rate due to the decrease in the competition rate both nationally and in the provinces, and in particular, a highly significant relationship was derived with the decrease in the recruitment rate. In particular, the sensitivity of the risk of unrecruitment due to a decrease in competition rate was the highest in the Jeolla region (0.499), followed by the Gangwon region (0.475) and the Gyeongsang region (0.471), and the metropolitan region (0.158) was confirmed to be the most stable. This suggests that the gap in insufficient funding has gradually widened by region over the past 10 years, and that the shock wave becomes more pronounced in the provinces farther away from the metropolitan area. Based on this study, if we deviate from the standardized application of university development policies for the metropolitan area and regional universities, and present a customized higher education strategy for each region, it will be an opportunity to prevent local extinction due to a decrease in the school-age population and achieve coexistence with higher education institutions and regions at the same time.

Bayesian analysis of Korean income data using zero-inflated Tobit model (영과잉 토빗모형을 이용한 한국 소득분포 자료의 베이지안 분석)

  • Hwang, Jisu;Kim, Sei-Wan;Oh, Man-Suk
    • The Korean Journal of Applied Statistics
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    • v.30 no.6
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    • pp.917-929
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    • 2017
  • Korean income data obtained from Korea Labor Panel Survey shows excessive zeros, which may not be properly explained by the Tobit model. In this paper, we analyze the data using a zero-inflated Tobit model to incorporate excessive zeros. A zero-inflated Tobit model consists of two stages. In the first stage, individuals with 0 income are divided into two groups: genuine zero group and random zero group. Individuals in the genuine zero group did not participate labor market since they have no intention to do so. Individuals in the random zero group participated labor market but their incomes are very low and truncated at 0. In the second stage, the Tobit model is assumed to a subset of data combining random zeros and positive observations. Regression models are employed in both stages to obtain the effect of explanatory variables on the participation of labor market and the income amount. Markov chain Monte Carlo methods are applied for the Bayesian analysis of the data. The proposed zero-inflated Tobit model outperforms the Tobit model in model fit and prediction of zero frequency. The analysis results show strong evidence that the probability of participating in the labor market increases with age, decreases with education, and women tend to have stronger intentions on participating in the labor market than men. There also exists moderate evidence that the probability of participating in the labor market decreases with socio-economic status and reserved wage. However, the amount of monthly wage increases with age and education, and it is larger for married than unmarried and for men than women.