• Journal of Families and Better Life
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• v.19 no.6
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• pp.145-155
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• 2001

The purposes of this study were first to construct statistical and econometric models based on Amemiya\`s Type I Tobit mainly addressing the issue of statistical efficiency; second to explore income, price, and curvilinear age effects on the explained variable in order to illustrates its statistical marginal effects related to econometric issues; finally to provide invaluable insight for graphical simulations as a new interpretation approach using Tobit analysis. Results indicated that interpretation for the mean marginal effects of three possible cases of dependent variable was more likely to be evident to understand Tobit results compared to conventional analysis only using latent variable, beta. Results also revealed that prediction value of dependent variable can be possibly and easily projected by the independent variable changed whereas only beta value can not illustrate its projection as independent variables'changes.

• International Journal of Human Ecology
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• v.4 no.2
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.1-17
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• 2010

This paper focuses on measuring the efficiency of container yards in container terminals in Busan and Gwangyang using Data Envelopment Analysis (DEA) approach. It analyses the relative efficiency of 11 container terminals based on the data for the period between 2006 and 2009 to offer a fresh perspective. The applied framework assumes inputs to be container cranes, transtainer cranes and yard tractors and output as container transshipment volume. Through the analysis, the differences between the impact of using of container cranes, transtainer cranes and yard tractors, top handler & reach stacker on container yard efficiency are measured. Moreover, the associations between the three input factors are analyzed as well. This paper also employs heteroscedastic Tobit model to show the impact of explanatory variables on container yard efficiencies. I took into consideration the strategies for operation of container cranes, transtainer cranes and yard tractors in container yard.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.87-94
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• 2020

In this study, the factors affecting the efficiency of 48 projects of private R&D institutes were analyzed using the Tobit model. Influencing factors were selected as open R&D network size, IT industry, interaction between R&D network size and IT industry, and type of R&D network cooperation. As a result of Tobit analysis, the R&D network size, the IT industry, and the type of R&D network cooperation were found to be significant. The larger the open R&D network size, the lower the efficiency, and the IT industry showed lower R&D efficiency than other industries. In addition, cooperation with universities and research institutes showed lower R&D efficiency than cooperation with companies. As a result of these studies, companies will be able to select and focus on cooperation with the outside in relations and investment allocation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.26-37
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• 2017

The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8719-8727
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• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Korean Management Science Review
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• v.34 no.2
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• pp.57-66
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• 2017

The purpose of this study is to analyze the multidimensional productivity of the shipbuilding performance and to explain the role of different factors, such as man-hour, dock period, number of building block, launching process rate, automatic welding percent, and drawing fault rate which are important production-related variables in most shipbuilding companies. The shipbuilding productivity is obtained using Data Envelopment Analysis (DEA) approach. Then, a Tobit model is considered to measure the influence of different factors on the measured productivity. The results reveal that this productivity measure can substitute a representative shipbuilding productivity index (CGT/man-hour) in shipbuilding industries. Also, this multidimensional productivity analysis using DEA and Tobit reveals complex relationships between production-related variables and CGT and sale.

• 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.

• 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.

• 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.