The Effect of Educational Background On Performance and Organisational Commitment

In this research note Gedaliahu Harel, Senior Lecturer in Human Resource Management at the Israel Institute of Technology, and Yehuda Baruch, Visiting Fellow at the City University Business School, explore the effects of a special educational and training programme that affects the backgrounds of employees in technical jobs measured by variables such as level of performance, professionalism, and organisational commitment. the results are considered in terms of the particular population examined and the implications discussed for the use of special vocational education and training.     

Teamwork in Modern Organizations: Implications for Technology Education

Characteristics of teamwork in modern organizations and workplaces are examined, in order to extrapolate the means for imparting teamwork skills within technology education. Goals and tasks for the team, team composition, team-player styles, phases of team development, communication and interpersonal skills, decision making, leadership, and evaluation of team performance are discussed. Teamwork skills are acquired gradually as a result of experience. Mere provision of a joint task to a group of people does not produce teamwork spontaneously. In order to promote teamwork, technological tasks at school need to include considerable degrees of freedom and decision-making by pupils. When the teacher becomes a facilitator of the process, instead of being primarily a source of knowledge and a decision-maker, team members can determine the assignment of roles in the group by themselves. Evaluation of teamwork in technology education is an integral part of alternative assessment.     

Adolescent injuries in relation to economic status: An international perspective

The primary objective of the study was to examine the relationship between patterns in car-to-car crashes involving young drivers and car and driver characteristics and the research design was a national register-based prospective cohort study. Individual records in a cohort born 1970 – 1972 are linked to road-traffic-crash data (1988 – 2000). Subjects' first police-registered two-car crash leading to severe or fatal injury (n = 4875) are identified. Typical crash patterns are highlighted and associations between pattern and both car and individual socio-demographic characteristics are tested. Four crash patterns are highlighted. Male drivers and those with lower educational attainment are over-represented in all patterns. Pattern-based risk levels vary considerably according to car safety level and driver's age at time of injury and socio-economic status. Crash patterns might be considered in young adult driver education systems, bearing in mind the consistent higher risks of male drivers and of drivers with lower educational attainment.     

Analysis of efficient markets

A simple trading model is presented in which Bayes’ rule is used to aggregate traders’ forecasts about risky assets’ future returns. In this financial market, Bayes’ rule operates like an omnipotent market-maker performing functions that in 1776 Adam Smith attributed to an “invisible hand.” We have analyzed two distinct cases: in the first scenario, the traders’ forecast errors are uncorrelated, and in the second scenario, the traders’ forecast errors are correlated. The contribution of our paper is fourfold: first, we prove that the “efficient market” mean-return can be expressed as a complex linear combination of the traders’ forecasts. The weights depend on the forecast variances, as well as on the correlations among the traders’ forecasts. Second we show that the “efficient” variance is equal to the inverse of the sum of the traders’ precision errors, and is also related to the correlations among the traders’ forecast errors. Third, we prove that the efficient market return is the best linear minimum variance estimator (BLMVE) of the security’s mean return (in the sense that it minimizes the sum of the traders’ mean squared forecast errors). Thus, an efficient market aggregates traders’ heterogeneous information in an optimal way. Fourth, we prove that an efficient market produces a mean return (price) as a Blackwell sufficient (most informative) experiment among all possible aggregated expected return (price) forecasts.     

A new paradigm for forecasting security returns in a market regulated by price limits

Numerous futures markets in the US and many stock markets around the world set a “limit” price before each trading session, based on the settlement price at the end of the previous trading day. Price limits are boundaries set by market regulators to restrict large daily fluctuations in the price of securities. Once the return limit is triggered, traders cannot observe the equilibrium return that would have prevailed in the absence of such regulation. We develop an innovative approach for forecasting security returns (and prices) in a market regulated by price limits. Our forecasting model allows for multiple limit-hits. The model is robust, straightforward and easy for practitioners to use. A few numerical predictions are provided for hypothetical securities, and for seven traded futures contracts.     

Institutional Change and Union Membership: A Longitudinal Analysis of Union Membership Determinants in Israel

We examine the degree to which factors associated with workers' union membership decisions are sensitive to shifts in the institutional environment of unions. Comparative logit analyses of the relationship between potential determinants of membership and actual union membership over time suggestthat the factors associated with membership are elastic and may reflect shifts in the institutional context of unions.     

Forecasting futures returns in the presence of price limits

In a futures market with a daily price‐limit rule, trading occurs only at prices within limits determined by the previous day's settlement price. Price limits are set in dollars but can be expressed as return limits. When the daily return limit is triggered, the true equilibrium futures return (and price) is unobservable. In such a market, investors may suffer from information loss if the return “moves the limit.” Assuming normally distributed futures returns with unknown means but known volatilities, we develop a Bayesian forecasting model in the presence of return limits and provide some numerical predictions. Our innovation is the derivation of the predictive density for futures returns in the presence of return limits. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:199–210, 2005     

Experimental study of repeated team-games

We report an experiment in which the Intergroup Prisoner's Dilemma (IPD) game was contrasted with a structurally identical (single-group) Prisoner's Dilemma (PD). The games were played repeatedly for 40 rounds. We found that subjects were initially more likely to cooperate in the IPD game than in the PD game. However, cooperation rates decreased as the game progressed and, as a result, the differences between the two games disappeared. This pattern is consistent with the hypothesis that subjects learn the structure of the game and adapt their behavior accordingly. Computer simulations based on a simple learning model by Roth and Erev (Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term, Games and Economic Behavior 8, 164–212, 1995) support this interpretation.     

Project Valuation With Time-Varying Cash Flows: A Bayesian Approach

This article investigates the valuation of a project when the distributions of cash flows vary over time. The decision maker is assumed to be a Bayesian decision maker under uncertainty. Using the dynamic programming principle of backward induction and assuming that the capital asset pricing model is valid in each time period, we derive the project's valuation formulas and systematic risks, and investigate their characteristics. Our valuation formulas embed a Bayesian learning effect and differ from the traditional textbook capital budgeting formulas.