TAXES, TORTS, AND THE TOXICS RELEASE INVENTORY: CONGRESSIONAL VOTING ON INSTRUMENTS TO CONTROL POLLUTION

Theories of rational political ignorance and congressional voting imply that Congress members may take different interests into account when they vote on technical amendments than when they vote on a bill's final passage. This article uses votes on Superfund reauthorization to examine what factors influence politicians' support for different instruments to control pollution and how the interests Congress members take into account vary with the anticipated degree of electoral scrutiny. Controlling for a legislator's general support for environmental programs, a representative's votes on specific policy instruments in Superfund legislation depended on the district-level costs and benefits of the instruments.     

DO MORAL COMMUNITIES PLAY A ROLE IN CRIMINAL SENTENCING? Evidence from Pennsylvania

Religion and social control have been a sociological concern since Durkheim and Weber, and the relationship between religion and punishment has long been the subject of speculation. However, surprisingly little empirical research exists on the role of religion or religious context in criminal justice, and almost no research on the role of religious context on actual sentencing practices. We conceptualize the potential relationships between religious context and sentencing severity by drawing from the focal concerns and court community perspectives in the sentencing literature and from the moral communities theory developed by Rodney Stark. We suspect that Christian moral communities might shape notions of perceived blameworthiness for court community actors. Such moral communities might also affect notions of community protection—affecting perceptions of dangerousness, or perhaps rehabilitation, and might influence practical constraints/consequences (e.g., local political ramifications of harsh or lenient sentences). We examine these questions with a set of hierarchical models using sentencing data from Pennsylvania county courts and data on the religious composition of Pennsylvania counties from the Associated Religion Data Archives. We find that county Christian religious homogeneity increases the likelihood of incarceration. In addition, Christian homogeneity, as well as the prevalence of civically engaged denominations in a county condition the effects of important legally relevant determinants of incarceration. Furthermore, we find evidence that Christian homogeneity activates the effect of local Republican electoral dominance on incarceration. We argue that Christian homogeneity affects sentencing practices primarily through local political processes that shape the election of judges and prosecutors.     

WORK‐RELATED ACCIDENTS AND THE LEVEL OF MARKET COMPETITION: AN ANALYSIS OF WORKER INJURY RATES AT U.S. STEEL CORPORATION, 1907–1939

We investigate the relationship between accident rates and industry structure for the United States’ steel industry during the first four decades of the 20th century. We develop a dominant firm theoretical model linking accident rates to number of competitors, showing a positive correlation between accident avoidance and the number of fringe competitors. We then test this theory empirically and, when controlling for other influences, find that reductions in the dominant firm’s market share reduce worker injury rates substantially. (JEL L13, L61, N62, N82)     

Cyclic tournaments and cooperative majority voting: A solution

A new solution concept is axiomatically characterized for tournaments that represent cooperative majority voting. The predicted set of outcomes lies inside the top-cycle set, the uncovered set, and the Banks set.This research was supported by NSF grants SES 8612120 and SES 8896228. I thank Georges Bordes, Gary Cox, Bhaskar Dutta, Richard McKelvey, Nicholas Miller, Emerson Niou, Peter Ordeshook, and Peyton Young for helpful comments. Niou is responsible for the example in Sect. 4. Presented at the Public Choice Society Meetings, Tucson, March 1987, and at the Jacob Marschak Interdisciplinary Colloquium on Mathematics in the Behaviorial Sciences, UCLA, October 1988.     

A concept of an integrated transport model

This paper is one of a series being produced on the application of Operational Research techniques in the integrated planning of public service resource provision and consumption. It describes a conceptual basis for planning transportation services within the context of a public service, the others are related to Health Services, Educational Services and community development services.Two sub-models, a linear sub-model and a dynamic sub-model are linked to form the integrated approach to the planning problem. The overall concept is to evaluate in terms of penalties and benefits the alternative plans of resource provisions.It is of interest to know that the principles of the Linear model described here has been applied to long range planning in the Health Service in the U.S.A. and U.K., and has been reported at the NATO conference, Portugal (1974). The Dynamic model has been used, in a more unstructured fashion than described here, by the Greater London Councils. The model in this paper is to form the basis of a more detailed evaluation of alternative transportation plans.     

Testing parameter of the power series distribution of a zero inflated power series model

The Zero Inflated Power Series Distribution (ZIPSD) contains two parameters. The first parameter indicates inflation of zero and the other parameter is that of the Power Series distribution. We provide three asymptotic tests for testing the parameter of Power Series distribution, using an unconditional (standard) likelihood approach, a conditional likelihood approach and a test based on sample mean, respectively. The performance of these three tests has been studied for Zero Inflated Poisson Distribution (ZIPD). Asymptotic Confidence Intervals for the parameter are also provided.     

COVARIANCE MODELS FOR LATTICE DATA

Given observations on an m × n lattice, approximate maximum likelihood estimates are derived for a family of models including direct covariance, spatial moving average, conditional autoregressive and simultaneous autoregressive models. The approach involves expressing the (approximate) covariance matrix of the observed variables in terms of a linear combination of neighbour relationship matrices, raised to a power. The structure is such that the eigenvectors of the covariance matrix are independent of the parameters of interest. This result leads to a simple Fisher scoring type algorithm for estimating the parameters. The ideas are illustrated by fitting models to some remotely sensed data.     

PERMUTATION MODELS FOR RELATIONAL DATA

A common problem in sociology, psychology, biology, geography, and management science is the comparison of dyadic relational structures (i.e., graphs). Where these structures are formed on a common set of elements, a natural question that arises is whether there is a tendency for elements that are strongly connected in one set of structures to be more—or less—strongly connected within another set. We may ask, for instance, whether there is a correspondence between golf games and business deals, trade and warfare, or spatial proximity and genetic similarity. In each case, the data for such comparisons may be continuous or discrete, and multiple relations may be involved simultaneously (e.g., when comparing multiple measures of international trade volume with multiple types of political interactions). We propose here an exponential family of permutation models that is suitable for inferring the direction and strength of association among dyadic relational structures. A linear-time algorithm is shown for MCMC simulation of model draws, as is the use of simulated draws for maximum likelihood estimation (MCMC-MLE) and/or estimation of Monte Carlo standard errors. We also provide an easily performed maximum pseudo-likelihood estimation procedure for the permutation model family, which provides a reasonable means of generating seed models for the MCMC-MLE procedure. Use of the modeling framework is demonstrated via an application involving relationships among managers in a high-tech firm.