Quantitative Methods for Environmental Justice Assessment of Transportation

Application of Executive Order 12898 to risk assessment of highway or rail transport of hazardous materials has proven difficult; in general, the location and conditions affecting the propagation of a plume of hazardous material released in a potential accident are unknown. Therefore, analyses have only been possible in a geographically broad or approximate manner. The advent of geographic information systems and development of software enhancements at Sandia National Laboratories have made kilometer-by-kilometer analysis of populations tallied by U.S. Census blocks along entire routes practicable. Tabulations of total or racially/ethnically distinct populations close to a route, its alternatives, or the broader surrounding area, can then be compared and differences evaluated statistically. This article presents methods of comparing populations and their racial/ethnic compositions using simple tabulations, histograms, and chi-square tests for statistical significance of differences found. Two examples of these methods are presented: comparison of two routes and comparison of a route with its surroundings.     

Evaluating the Simplified Conjoint Expected Risk Model: Comparing the Use of Objective and Subjective Information

The simplified Conjoint Expected Risk (CER) model by Holtgrave and Weber posits that perceived risk is a linear combination of the subjective judgments of the probabilities of harm, benefit, and status quo, and the expected harm and benefit of an activity. It modifies Luce and Weber's original CER model—that uses objective information to evaluate financial gambles—to accommodate activities such as health/technology activities where values of the model variables are subjective. If the simplified model is a valid modification of the original model, its performance should not be sensitive to the use of subjective information. However, because people may evaluate information differently when objective information is provided to them than when they generate information on their own, the performance of the simplified CER model may not be robust to the source of model-variable information. We compared the use of objective and subjective information, and results indicate that the estimates of the simplified CER model parameters and the proportion of variance in risk judgments accounted for by the model are similar under these two conditions. Thus, the simplified CER model is viable with activities for which harm and benefit information is subjective.     

Long-term Success of Adaptation Strategies: Evidence from Finnish Companies

This study analyses the success of adaptation strategies applied by Finnish companies during the recession in 1989–93. Five different strategies emerged from data gleaned from a questionnaire answered by 750 companies. In the medium term, investment in new product development and marketing and in the acquisition of new customers was the most successful strategy while a strategy heavily based on negotiating finance contracts and restructuring was the most unsuccessful. To evaluate the long-term effects of adopted strategies, financial statements from 644 companies in 1994 and 1997 were analysed. The results supported the medium-term conclusions. In general, they suggested that in the long-term, active adaptation strategies are most likely to lead to sustained success whereas passive (financial) strategies are associated with a high risk of failure.     

Testing Fair Wage Theory

Fairness considerations often are invoked to explain wage differences that appear unrelated to worker characteristics or job conditions, but non-experimental tests of fair wage models are rare because market data rarely permit researchers to measure individual workers’ productivity and its value. We use data from the baseball labor market to address this problem, and find no support for fair wage theory. We do find, however, that fairness premia can be illusory: Wages appear to incorporate fairness premia in regressions that control for variation in individuals’ physical output, but such premia evaporate when the value of that output is held constant.

Team‐Level Antecedents of Individuals' Knowledge Networks*

Individuals' knowledge networks are widely considered to contribute substantially to the effectiveness and efficiency of organizations. While the positive effects of knowledge networks as a primary driver of social capital have recently received considerable research attention, potential determinants of individuals' network building have not yet been adequately addressed. In this study, we investigate how certain team‐level properties affect team members' development of knowledge networks through the course of a team project. Using data from 430 team leaders and team members pertaining to 145 software development projects, we test cross‐level hypotheses using hierarchical linear modeling (HLM). The results indicate that the team's perception of the organizational knowledge‐sharing climate, the team's networking preference, and the team's perceived importance of networking for project success positively affect individuals' network building. Furthermore, a team's perception of the adequacy of its technical competency and a team's perception of the adequacy of its material resources inhibit team members' individual network development. Theoretical and managerial implications are discussed.     

Distribution of the cross-correlations of squared residuals in ARIMA models

ABSTRACT The distribution of the cross-correlations of squared residuals from Box-Jenkins models is considered in very general conditions, and the asymptotic distribution is derived. A test for a lagged relationship in volatility for economic time series under instantaneous causality is proposed, and its empirical behaviour is studied. An example involving the international stock market's volatility is studied, and an interesting result is observed.     

NEIGHBOUR ANALYSIS WITH ADJUSTMENT FOR INTERPLOT COMPETITION

In field experiments involving a large number of experimental plots, a neighbour analysis can be used to control environmental variation by estimating the trend within blocks. The effect of interplot competition is another important source of variation which has an influence on the estimation of treatment contrasts. To reduce the effect of the variation from these sources and to improve the precision of comparison between treatments, a spatial model is proposed for incorporating both trend effect and interplot competition. It is a modification to the residual maximum likelihood neighbour analysis of Gleeson & Cullis (1987) using the two neighbouring treatment effects to estimate interplot competition. A real example is used to illustrate this methodology. The results indicate that the extended model gives no appreciable difference in standard error of mean differences compared with the model taking into account the trend effect only. However, the rankings of estimated treatment means do differ. More research using both real and simulated data is required before such models that incorporate trend and competition effects can be confidently recommended.