Effect of driver,roadway, collision,and vehicle characteristics on crash severity: a conditional logistic regression approach

The aim of the study is to examine the factors that appear to have a higher potential for serious injury or death of drivers in traffic accidents in Turkey, such as collision type, roadway surface, vehicle speed, alcohol/drug use, and restraint use. Driver crash severity is the dependent variable of this study with two categories, fatal and non-fatal. Due to the binary nature of the dependent variable, a conditional logistic regression analysis was found suitable. Of the 16 independent variables obtained from Turkish police accident reports, 11 variables were found most significantly associated with driver crash severity. They are age, education level, restraint use, roadway condition, roadway type, time of day, collision location, collision type, number and direction of vehicles, vehicle speed, and alcohol/drug use. This study found that belted drivers aged 18–25 years involving two vehicles travelling in the same direction, in an urban area, during the daytime, and on an avenue or a street have better chances of survival in traffic accidents.     

Inter-industry network structure and the cross-predictability of earnings and stock returns

We examine how the patterns of inter-industry trade flows impact the transfer of information and economic shocks. We provide evidence that the intensity of transfers depends on industries’ positions within the economy. In particular, some industries occupy central positions in the flow of trade, serving as hubs. Consistent with a diversification effect, we find that these industries’ returns depend relatively more on aggregate risks than do returns of noncentral industries. Analogously, we find that the accounting performance of central industries associates more strongly with macroeconomic measures than does the accounting performance of noncentral industries. Comparing central industries to noncentral ones, we find that the stock returns and accounting performance of central industries better predict the performance of industries linked to them. This suggests that shocks to central industries propagate more strongly than shocks to other industries. Our results highlight how industries’ positions within the economy affect the transfer of information and economic shocks.     

Macroeconomic implications of mortgage loan requirements: an agent-based approach

It is a well-known fact that the housing market, with its associated mortgage securities, plays a crucial role in modern economies. The recent crisis of 2007, triggered by the U.S. real estate bubble, confirms this key role and suggests the importance of regulating mortgage lending. This paper investigates these issues by designing a housing market with a linked mortgage lending instrument in the Eurace agent-based model. Our results show that the presence of a housing market in the model has relevant macroeconomic implications, driven mainly by the additional amount of endogenous money injected into the economy by new mortgages. This additional money generally helps to support and stabilize aggregated demand, thus improving the main economic indicators. However, if the regulation of mortgage lending is too lax, involving an increase in the debt-service-to-income ratio (DSTI), then the additional supply of mortgages no longer enhances macroeconomic performance, and the stability of the economic system is undermined. Based on a number of recent discussions, a regulation of stock control that targets households’ net wealth (a stock), rather than income (a flow) is designed and analyzed. The results show that regulation of stock control can be combined effectively with DSTI to increase the stability of the housing market and the economy as a whole. Interestingly, the regulation based on stock control also directly affects mortgage distribution among households, avoiding excessive concentration. From a policy perspective, our results suggest that the use of a mild flow control regulation, coupled with a stricter stock control measure, fosters sustainable growth and eases first-time buyers access to the housing market, encouraging homeownership.

     

Online image content analysis of political figures: an exploratory study

This study investigates the emotional content of facial images of South Korean politicians. The data were drawn from official websites of 18th National Assembly members. We categorized facial expressions (smiling, frowning, and no expression) by using photos on the websites. The smiling image was the most prevalent facial expression regardless of the socio-political-demographic attributes of the politicians. The existence and strength of the smiling image had significant positive correlations with the politicians’ web visibility. Opposition parties were significantly more likely to show frowning or expressionless images than the ruling party. The more experienced politicians were more likely to continue their use smiling images than similarly aged politicians with less experience.