Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach

Abstract

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver’s psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver’s propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.     

The Responsiveness of Corporate Investments to Changes in Corporate Income Taxation During the Financial Crisis: Empirical Evidence from Slovenian Firms

I examine the responsiveness of corporate investments to changes in corporate income taxation during the financial crisis. When investigating tax effects in financially constrained firms, the model of investment demand needs to be extended to include an additional channel through which taxes could affect investments. I model the tax effects via two transmission channels, the traditional user cost of capital channel and the cash flow channel, which is crucial for financially constrained firms. The empirical results show that corporate investments in financially constrained firms do not respond to changes in corporate income taxation through the user cost of capital channel, but there is strong evidence of the effect that materializes through the cash flow channel.     

Language and ideology: quantitative thematic analysis of New Year speeches given by Czechoslovak and Czech presidents (1949–2011)

The relationship between ideology and language is analyzed by using quantitative linguistic methods to measure the thematic concentration of texts. The assumption is that totalitarianism and democracy represent radically different types of ideology and that this difference will be reflected in different levels of thematic concentration in texts of the same genre. The analysis focuses on the New Year speeches given by Czechoslovak and Czech presidents; these texts were chosen because they represent a relatively clearly delineated genre with a long tradition and because they are one of the most important outlets for the public expression of political opinions by the head of state. The results of statistical tests show that there exist significant differences between the thematic concentrations in the speeches of presidents from the totalitarian period and the period of democracy. The analysis also revealed that the largest differences in thematic concentrations were between the speeches made by the presidents representing the most ideologically polarized positions: the leader of the 1948 communist coup Klement Gottwald and the public face of the 1989 democratic Velvet Revolution Václav Havel.     

Misspecified Recovery

Asset prices contain information about the probability distribution of future states and the stochastic discounting of those states as used by investors. To better understand the challenge in distinguishing investors' beliefs from risk‐adjusted discounting, we use Perron–Frobenius Theory to isolate a positive martingale component of the stochastic discount factor process. This component recovers a probability measure that absorbs long‐term risk adjustments. When the martingale is not degenerate, surmising that this recovered probability captures investors' beliefs distorts inference about risk‐return tradeoffs. Stochastic discount factors in many structural models of asset prices have empirically relevant martingale components.     

The impact of China's imports on European Union industrial employment

As the EU's biggest supplier of imported goods and a second trading partner, China has become an increasingly important actor on the global economic scene. This paper reports new evidence through analyzing whether the EU labour market is affected by exposure to imports from China. Drawing on a panel dataset of 27 EU countries, over the 2003–2013 period, and using the pooled mean group estimator, the results show that imports from China have a negative effect on industrial employment. This result holds separately for the all analyzed categories: all products, manufactured products as well as for the sub‐groups.     

Short-term forecasting of GDP with a DSGE model augmented by monthly indicators

DSGE models are useful tools for evaluating the impact of policy changes, but their use for (short-term) forecasting is still in its infancy. Besides theory-based restrictions, the timeliness of data is an important issue. Since DSGE models are based on quarterly data, they suffer from the publication lag of quarterly national accounts. In this paper we present a framework for the short-term forecasting of GDP based on a medium-scale DSGE model for a small open economy within a currency area. We utilize the information available in monthly indicators based on the approach proposed by Giannone et al. (2009). Using Austrian data, we find that the forecasting performance of the DSGE model can be improved considerably by incorporating monthly indicators, while still maintaining the story-telling capability of the model.     

Working in the digitized economy: HRM theory & practice

In our introduction to this special issue on the gig economy, we provide some context to how and why this phenomenon should be studied, with a particular emphasis on Human Resource Management. We then describe the four articles that comprise the special issue, and we note some common themes. Our introduction concludes with some suggestions for future research on the gig economy.     

Optimal hedging with higher moments

This study proposes a utility‐based framework for the determination of optimal hedge ratios (OHRs) that can allow for the impact of higher moments on hedging decisions. We examine the entire hyperbolic absolute risk aversion family of utilities which include quadratic, logarithmic, power, and exponential utility functions. We find that for both moderate and large spot (commodity) exposures, the performance of out‐of‐sample hedges constructed allowing for nonzero higher moments is better than the performance of the simpler OLS hedge ratio. The picture is, however, not uniform throughout our seven spot commodities as there is one instance (cotton) for which the modeling of higher moments decreases welfare out‐of‐sample relative to the simpler OLS. We support our empirical findings by a theoretical analysis of optimal hedging decisions and we uncover a novel link between OHRs and the minimax hedge ratio, that is the ratio which minimizes the largest loss of the hedged position. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark 32:909–944, 2012     

Panel quantile regressions for estimating and predicting the value-at-risk of commodities

Using a flexible panel quantile regression framework, we show how the future conditional quantiles of commodities returns depend on both ex post and ex ante uncertainty. Empirical analysis of the most liquid commodities covering main sectors, including energy, food, agriculture, and precious and industrial metals, reveal several important stylized facts. We document common patterns of the dependence between future quantile returns and ex post as well as ex ante volatilities. We further show that the conditional returns distribution is platykurtic. The approach can serve as a useful risk management tool for investors interested in commodity futures contracts.