Household Automobile and Motorcycle Ownership Analyzed with Random Parameters Bivariate Ordered Probit Model

2012 ◽  
Vol 2279 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Panagiotis C. Anastasopoulos ◽  
Matthew G. Karlaftis ◽  
John E. Haddock ◽  
Fred L. Mannering
Keyword(s):  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Random Parameters ◽  
Bivariate Ordered Probit ◽  
Bivariate Ordered Probit Model

scholarly journals Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

2019 ◽  
Vol 16 (14) ◽  
pp. 2632 ◽  
Author(s):  
Chen ◽  
Song ◽  
Ma
Keyword(s):  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Seat Belt ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Random Parameters ◽  
Factors Affecting ◽  
Bivariate Ordered Probit ◽  
Bivariate Ordered Probit Model

The existing studies on drivers’ injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers’ injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

scholarly journals Estimation urban railway demand in Yogyakarta using Bivariate Ordered Probit Model

2018 ◽  
Vol 181 ◽  
pp. 02009 ◽  
Author(s):  
Wida Yuliar Rezika ◽  
Sapto Priyanto ◽  
Muhammad Zudhy Irawan
Keyword(s):  
Travel Time ◽  
High Growth ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Demand Model ◽  
Private Vehicle ◽  
Railway System ◽  
Bivariate Ordered Probit ◽  
Bivariate Ordered Probit Model

The urban railway system is believed to solve transportation problems caused by the high growth of private vehicles and urbanization. This study is going to analyze the potential demand for the urban railway in Yogyakarta, Indonesia based on bivariate ordered probit model. The survey of preference stated with 120 samples conducted in Yogyakarta. The model of train demand is distinguished between public transport users and private vehicle users using seven scenarios. In-train travel time, waiting time, tariff, and ticketing discount for students are four factors considered in the model. The demand model shows that in-train travel time is the most important factor influence for train demand. Meanwhile, the scenario result reveals that respondents except student are willing to pay more to obtain shorter travel time, students who use private vehicle are reluctant to shift into the train, and ticketing discount brings no effect to stimulate them to use the train.

Migration and Subjective Poverty in sending countries: An analysis of the Egyptian case

2014 ◽  
Vol 11 (3) ◽  
pp. 353-367 ◽  
Author(s):  
Yehudith Kahn ◽  
Audrey Dumas ◽  
Yovav Eshet ◽  
Nir Billfeld
Keyword(s):  
Probit Model ◽  
Ordered Probit ◽  
Survival Strategy ◽  
Significant Determinant ◽  
Individual Level ◽  
Subjective Poverty ◽  
Bivariate Ordered Probit ◽  
The Individual ◽  
The Impact ◽  
Bivariate Ordered Probit Model

Migration has traditionally been used as a survival strategy in times of financial crisis; however, a debate exists as to whether migration influences poverty on the individual level. The current study analyses the influence of past subjective poverty on migration choice and to determine the impact of migration on current subjective poverty perception. Using a simultaneous bivariate ordered probit model, we found that poorer individuals in Egypt tend to migrate more than others. Migration was found to be a significant determinant of current poverty in Egypt. Finally, migration improved migrant’s financial situation. 

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