scholarly journals A Zero-Inflated Ordered Probit Model to Analyze Hazmat Truck Drivers’ Violation Behavior and Associated Risk Factors

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 110974-110985
Author(s):  
Jinzhong Wu ◽  
Wenji Fan ◽  
Wencheng Wang
Keyword(s):  
Risk Factors ◽  
Probit Model ◽  
Truck Drivers ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Associated Risk Factors

scholarly journals Exploring Risk Factors with Crash Severity on China Two-Lane Rural Roads Using a Random-Parameter Ordered Probit Model

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Shikun Xie ◽  
Xiaofeng Ji ◽  
Wenchen Yang ◽  
Rui Fang ◽  
Jingjing Hao
Keyword(s):  
Risk Factors ◽  
Injury Severity ◽  
Random Parameter ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Crash Severity ◽  
Critical Factors ◽  
Traffic Crashes ◽  
Rural Roads

Understanding the factors that contribute to traffic crashes can help provide a fundamental basis to plan and develop appropriate countermeasures for road safety issues emerging in particular on two-lane rural roads. However, most of the studies have focused on urban roadways and freeway systems, and few studies have investigated the issue of heterogeneity on two-lane rural roads. The purpose of this study is to uncover the risk factors influencing crash severity on two-lane rural roads in China. A sample of 1490 traffic crashes occurring on two-lane rural roads between 2012 and 2017 was collected from the Mouding County Highway Bureau in Yunnan, China. A random-parameter ordered probit model was estimated using these data to capture underlying unobserved characteristics in personal traits, vehicle attributes, roadway conditions, environmental factors, and crash attribute. To better understand the effect of critical factors on crash severity outcome probability, an elasticity analysis was then introduced. The results show that six factors such as driver’s attribution, illegal driving behaviour, access segment, day of week, vehicle type, and crash form have a significant impact on the injury severity, and the impacts of driving behaviours, access segment, and vehicle-fixed object crashes had significant variation across observations. Besides, the correlations between critical factors and the probability of serious injury sustained in traffic crashes are identified and discussed. The local driver indicator has more positive impact on the crash severity than nonlocal driver, and nonaccess segment appears a higher probability of serious or vicious collisions. It is worth mentioning that motorcycle-involved crashes do show an obvious correlation with crash injury severity. As for crash forms, vehicle-vehicle crashes are more likely to lead to severe crash injury. Besides, high-risk driving behaviour (e.g., fatigue driving, speeding, and converse driving), weekends, and holidays are found to have significant contribution to increasing the probability of traffic crash injuries and fatalities on two-lane rural roads.

Do the heterogeneous determinants of life satisfaction affect differently across borrowers of diverse credit sources? A propensity score approach

2018 ◽  
Vol 45 (8) ◽  
pp. 1142-1158 ◽  
Author(s):  
Tiken Das ◽  
Manesh Choubey
Keyword(s):  
Life Satisfaction ◽  
Propensity Score ◽  
Probit Model ◽  
Ordered Probit ◽  
Primary Data ◽  
Ordered Probit Model ◽  
Future Research ◽  
Content Type ◽  
Credit Access ◽  
Physical Assets

Purpose The purpose of this paper is to evaluate the non-monetary effect of credit access by providing an econometric framework which controls the problem of selection bias. Design/methodology/approach The study is conducted in Assam, India and uses a quasi-experiment design to gather primary data. The ordered probit model is used to evaluate the non-monetary impact of credit access. The paper uses a propensity score approach to check the robustness of the ordered probit model. Findings The study confirms the positive association of credit access to life satisfaction of borrowers. It is found that, in general, rural borrower’s life satisfaction is influenced by the ability and capacity to work, the value of physical assets of the borrowers as well as some other lenders’ and borrowers’ specific factors. But, the direction of causality of the factors influencing borrowers’ life satisfaction is remarkably different across credit sources. Research limitations/implications The study argues to provide productive investment opportunities to semiformal and informal borrowers while improving their life satisfaction score. Although the results are adjusted for selection and survivorship biases, it is impossible with the available data to assess which non-income factors explain the findings, and therefore this limitation is left to future research. Originality/value The study contributes to the literature of rural credit by assessing the probable differences among formal, semiformal and informal credit sources with respect to non-monetary impacts.

scholarly journals The Organization of Political Violence by Insurgencies

2012 ◽  
Vol 18 (3) ◽  
Author(s):  
Roos Haer
Keyword(s):  
Political Violence ◽  
Probit Model ◽  
Ordered Probit ◽  
Process Theory ◽  
Ordered Probit Model ◽  
Armed Groups ◽  
Human Right ◽  
Armed Group ◽  
The World ◽  
The Relationship

AbstractA range of theories have attempted to explain the variation in civilian abuse of warring parties. Most of these theories have been focused on the strategic environment in which these acts take place. Less attention is devoted to the perpetrators of these human right abuses themselves: the armed groups. This study tries to fill this niche by using the organizational process theory in which it is assumed that armed groups, like every organization, struggles for survival. The leader tries to ensure the maintenance of her armed group by increasing her control over her troops. The relationship between the level of control and the perpetrated civilian abuse is examined with a new dataset on the internal structure of more than 70 different armed groups around the world. With the help of a Bayesian Ordered Probit model, this new dataset on civilian abuse is analyzed. The results show that especially particular incentives play an important role.

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