An Economic Analysis of Auto Compensation Systems: Choice Experiences From New Jersey and Pennsylvania

Nearly since the first automobile traveled on U.S. soil, questions about how best to compensate people injured by their use have been raised. As early as in 1932, in fact, the tort system of imposing costs on negligent drivers was strongly criticized, and a system of compensation without regard to negligence recommended. Yet despite various efforts to identify and implement improved systems during the past more than 70 years, no clear best compensation mechanism has been found. Current discussions have focused on the “choice” system, under which insureds are allowed to select either a tort system or a no‐fault system of compensation at the time of insurance purchase. New Jersey and Pennsylvania, which implemented very similar choice programs in 1989 and 1990, respectively, offer an opportunity to observe the effects of choice on outcomes such as: use of attorneys, speed of payment, and consistency (equity) of payment. Our results indicate outcomes consistent with expectations in New Jersey (NJ), which switched from no‐fault to choice, but inconsistent with expectations in Pennsylvania (PA), which switched from tort to choice. Furthermore, analysis of tort versus no‐fault selectors postchoice in New Jersey and Pennsylvania does not offer clear evidence of no‐fault's lower administrative costs and speedier, more equitable payment in these jurisdictions.     

On exact D-optimal designs with 2 two-level factors and n autocorrelated observations

In this paper we consider the exact D-optimal designs for estimation of the unknown parameters in the two factors, each at only two-level, main effects model with autocorrelated errors. The vector of the n random errors in the observed responses is assumed to follow a first-order autoregressive model (AR(1)). The exact D-optimal designs seek the optimal combinations of the design levels as well as the optimal run orders, so that the determinant of the information matrix of BLUEs for the unknown parameters is maximized. Bora-Senta and Moyssiadis (1999) gave some conjectures about the exact D-optimal designs based on their experience of several exhaustive searches. In this paper their conjectures are partially proved to be true.Received: January 2003 / Accepted: October 2003Partially supported by the National Science Council of Taiwan, R.O.C. under grant NSC 91-2115-M-008-013.Supported in part by the National Science Council of Taiwan, R.O.C. under grant NSC 89-2118-M-110-003.     

Analysis and Forecast of the State of Environmental Protection in Russia

The main purpose of the present study is to analyse the emission dynamics of atmospheric and water pollutants in Russia and cost of their removal in the 1980s and early 1990s, and to forecast them by means of a Dynamic Input–Output Model according to different scenarios of future economic development till 1998. Main results of the work are:– methodological principles have been elaborated for singling out the environmental protection sector within the national economy;– a method has been offered for including the ecological block into a Dynamic Input–Output Model of the Russian economy;– a method of data preparation has been elaborated for the ecological block of the above-named model, the data base which characterizes the ecological situation in Russia has been formed and analysed;– calculations for 1994–1998 have been executed for forecasting the economic and ecological development of Russia using the above-mentioned model and the results obtained have been analysed. The results showed that if the existing tendencies towards low environmental protection capital costs remain the same, then the negative environmental impact will increase. In order to implement ecological programs and international agreements, to increase the proportion of removed pollutants, it is necessary to increase substantially expenditures on purifying water and air resources. The proportion of environmental protection investments in the total amount of the national economy capital costs should increase by up to 12–40% according to different scenarios of the economic development and different purposes of the environmental protection policy.     

Ownership concentration and bank risk: international study on acquisitions

This paper explores the effects of different types of bank ownership concentration on changes in bank risk during acquisition years. Using multi-country data from 2000 to 2006, during which market failures caused by various crises and government interventions are less influential to acquisition decisions, we collect 505 banking acquisition deals from 23 countries to examine which type of ownership concentration (such as financial intermediary, capital investor, non-financial, and state ownership) brings larger changes to an acquirer’s risk from pre-acquisition year to post-acquisition year (including non-performing loans, capital adequacy ratio, loan loss reserve, and credit rating). The empirical analyses show that acquirer banks with a concentration of shares owned by financial intermediaries and non-financial firms experience larger risk changes during acquisition years. In contrast, the risk changes of acquirer banks with a concentration of capital investors and state ownership are lower. Robustness checks from the random effect estimation, instrumental variables model, reverse causality, and different subsamples of (non-)U.S. or different levels of regulation enforcement confirm these results.     

Performance of Moving Average Trading Rules in a Volatile Stock Market: The Russian Evidence

This article examines the profitability of dual moving average crossover (DMAC) trading strategies in the Russian stock market over the 2003–12 period. It contributes to the existing technical analysis (TA) literature by testing, for the first time, the applicability of ordered weighted moving averages (OWMA) as an alternative calculation basis for determining DMACs. In addition, this article provides the first comprehensive performance comparison of DMAC trading rules in the stock market that is known as one of the most volatile markets in the world. The results show that the best trading strategies of the in-sample period can also outperform their benchmark portfolio during the subsequent out-of-sample period. Moreover, the outperformance of the best DMAC strategies is mostly attributable to their superior performance during bearish periods and, particularly, during stock market crashes.     

Optimal constrained investment in the Cramer-Lundberg model

We consider an insurance company whose surplus is represented by the classical Cramer-Lundberg process. The company can invest its surplus in a risk-free asset and in a risky asset, governed by the Black-Scholes equation. There is a constraint that the insurance company can only invest in the risky asset at a limited leveraging level; more precisely, when purchasing, the ratio of the investment amount in the risky asset to the surplus level is no more than a; and when short-selling, the proportion of the proceeds from the short-selling to the surplus level is no more than b. The objective is to find an optimal investment policy that minimizes the probability of ruin. The minimal ruin probability as a function of the initial surplus is characterized by a classical solution to the corresponding Hamilton-Jacobi-Bellman (HJB) equation. We study the optimal control policy and its properties. The interrelation between the parameters of the model plays a crucial role in the qualitative behavior of the optimal policy. For example, for some ratios between a and b, quite unusual and at first ostensibly counterintuitive policies may appear, like short-selling a stock with a higher rate of return to earn lower interest, or borrowing at a higher rate to invest in a stock with lower rate of return. This is in sharp contrast with the unrestricted case, first studied in Hipp and Plum, or with the case of no short-selling and no borrowing studied in Azcue and Muler.     

Process innovation capability and subsequent collaborative team performance in travel planning: a knowledge exchange platform perspective

Purpose: Backpacker tourism is flourishing in this century as the high development of Internet technology which enables travellers to search for resources they need easier. The research goal of this study was to exam how virtual skill and collective efficacy affect process innovation capability and subsequent team performance of collaborative design team in a virtual community. Design/methodology/approach: In this study, we formulated the virtual team model from the perspectives of open innovation paradigm and virtual competence, and we collected virtual community participation samples from the online communities. Invitation emails were delivered to numerous trip plan initiators in two well-known online travel communities for filling survey questionnaires for this study. In total, 3000 invitation messages were mailed, of which 373 were returned completed. The model and hypotheses were tested by structural equation modelling. Findings: Virtual competence, including collective efficacy and virtual media skill, is the essential key to facilitate process innovation capability and subsequent team performance success. Besides, knowledge sharing significantly moderates the relationship between process innovation capability and the team performance. Originality/value: Backpackers in the online travel communities have to have not only the willingness to collaborate, but also the abilities of using the correct tool to help with their tasks. When a self-efficacy gets into collective efficacy, it enables the collaborative team to develop with good virtual competencies. Accordingly, trip plan initiator and participants of a virtual team are as expertise contributors between conformity in online communities and online compulsive control tendencies.     

Electronic and in-person service quality of hybrid services

The service industries have experienced dramatic changes in service delivery format because of fast-paced innovation in information technology. Hybrid services involve service deliveries through conventional and technology-enabled environments, each of which is complementary and non-interchangeable. However, limited research has examined consumer behavior in response to a series of relevant service episodes in different channels at different points in time. In other words, how customers perceive service quality at each service encounter and how the cumulative effect of these perceptions influences customers’ overall service value assessment and satisfaction remain unclear. This study addresses this research gap by investigating the sequential influence of e-service quality on in-person service quality in a hybrid service format in which interpersonal and computer-mediated services coexist but at different points in time. Empirical analysis shows that e-service quality directly and positively affects in-person service quality, which fully mediates the effects of e-service quality on perceived value and customer satisfaction. The sequence of service encounters matters because in-person service quality perception has a stronger effect than e-service quality on customer metrics. Cumulative quality perceptions significantly influence perceived value and overall customer satisfaction. Theoretical and managerial implications are presented in the discussion.