Policy Coalitions in the U.S. Congress: A Spatial Duration Modeling Approach

This paper applies spatial duration models to the analysis of cosponsorship coalitions in the U.S. House of Representatives. This approach provides a unique and simultaneous statistical analysis of ideological space (specifically, coalition formation) and geographical space. Typically, duration models are associated with temporal longitudinal data, but recently have been adapted to the spatial domain (Pellegrini and Reader 1996). In this paper, spatial duration models are further adapted to examine ideological space including a consideration of unobserved sources of spatial variation (or omitted variable bias). We examine two features of cosponsorship coalitions, breadth and clustering. Breadth is defined as the ideological distance between the two most extreme members of the coalition which is an important “signal” to the rest of Congress regarding the scope and broad appeal of the proposed legislation. In contrast, clustering refers to the distance between individual members of a coalition and reveals the tendency, or not, of ideologically similar members of Congress to support various bills. To examine breadth and clustering, we employ spatial duration models of cosponsorship that permit a multivariate analysis incorporating both the characteristics of members of Congress and the geographical regions they represent. Results indicate that cosponsorship coalition patterns are primarily determined by the content of the legislation, not the actions of the coalition leadership. While the leadership characteristics of sponsors have a limited effect on cosponsorship breadth, the size of the coalition is the primary determinent. Leadership characteristics also have little effect on cosponsorship clustering. Rather, clustering is due to members' policy preferences, as measured by distance to the coalition leader. In addition, the duration analysis results suggest that geographical proximity between members of Congress “overcomes” ideological distance. Finally, the spatial duration approach is noted as a fruitful methodology for examining explicitly spatial patterns in both ideological or geographical space.     

A Note on the Spatial Correlation Structure of County-Level Growth in the U.S.

This paper examines the spatial correlation structure of county-level growth across the contiguous United States. Estimated spatial correlograms using data on four different measures of aggregate economic activity—population, employment, income, and earnings—over the period 1984–1994 indicate that cross-county interdependence is limited to relatively short ranges of distance. For each of the measures, the average correlation between the growth rates of two counties approaches zero within a range of approximately 200 miles. Moreover, the rate at which correlations decline with distance is not uniform. Inside of roughly 40 miles correlations show only a very slow rate of decline whereas beyond this range they drop off at a substantially higher rate.     

Market Rules and Spatial Outcomes: Insights from the Corporate Restructuring of U.S. Food Retailing

In this paper a study of the corporate restructuring of the U.S. food retail industry, during and following the period of regulatory relaxation and high-leverage capital transformations of the 1980s, is used to interrogate the complex relationships between market regulation, investment regimes, corporate strategies, and spatial outcomes. It is shown that changes in the “rules” governing investment and competition in the United States in the 1980s triggered countervailing spatial processes in the food retail industry. Those processes took more than a decade to work themselves through, but by the late 1990s a radically altered corporate landscape was beginning to emerge. In particular, consolidation of the industry had finally gained momentum–creating an industry whose leading firms are likely by 2002 to have a market share double the level of the early 1990s. The paper concludes by considering the insights which a consideration of corporate restructuring and regulation in this U.S. industry offers for some important areas of conceptual debate in economic geography. In particular, it is argued that industries in which capital structure transformations of the firm must be confronted and treated as a central issue have an intrinsic, but until recently neglected, importance in theoretical debate in the discipline.     

A Half Century of Health Data for the U.S. Population: The Integrated Health Interview Series

The U.S. National Health Interview Survey (NHIS) is the world's longest survey time series of health data and a rich source of information on health conditions, behaviors, and care from the 1960s to the present. NHIS public-use files are difficult to use for long-term analysis, due to complex file structure, changes in questionnaire content, and evolving variable names and coding schemes. Researchers at the Minnesota Population Center have created the Integrated Health Interview Series (IHIS) to overcome these problems. IHIS provides access to thousands of consistently coded and well-documented NHIS variables on the Internet and makes it easy to analyze health trends and differentials. IHIS multiplies the value of NHIS data by allowing researchers to make consistent comparisons over half a century and thus to study U.S. health status as a dynamic process. This article describes the main features of IHIS and suggests fruitful avenues for historical research using these invaluable health data.     

PLANNING: LESSONS FROM THE U.S.S.R.

Evaluation of the success of a plan requires the collection of statistics and indicators for monitoring purposes. In the health care field, outcomes are notoriously difficult to measure. To the extent that a successful program of prevention should result in providing less of a service, a conflict exists between planning and prevention: in the absence of outcome measures, success will be indistinguishable from failure, as in both cases, planned targets would not be met. To avoid this dilemma, an indicator-oriented planning system would be predicted to operationalize prevention in countable terms requiring increased inputs, or increased numbers of processes, regardless of the payoffs in health benefits. Screening, check-ups, and one-on-one contacts with health professionals would be emphasized at the expense of group-oriented activities or societal changes. Planning can thus have counter-productive policy implications. This theory is illustrated by reference to the current health care system in the U.S.S.R., including their anti-smoking and anti-alcoholism programmes.     

COINTEGRATION BETWEEN U.S. WHEAT MARKETS

ABSTRACT. Average monthly price data from twelve hinterland markets and the Houston port price for wheat are studied in a cointegration framework using the Engle-Granger "two-step" procedure and Johansen's maximum likelihood procedure. Out-of-sample forecasts from an error correction model are compared to those from a vector autoregression fit to levels and a univariate autoregression fit to first differences. This comparison suggests that modeling these (cointegrated) data as a levels vector autoregression, rather than as an error-correction process, results in significantly higher error bias, but lower error variance, at long horizons.     

The Relational Sources of Advocacy Strategies: Comparative Evidence from the European and U.S. Climate Change Sectors

How do advocacy organizations make tactical choices? This paper contributes to theory building in advocacy studies by examining how the decision‐making processes of advocacy organizations are affected by the choices of their peers. Drawing on qualitative interviews with practitioners in two contexts—the European Union and the United States—I document that organizations face pressures toward cohesion and differentiation with the tactical choices of other organizations. Other important processes—such as rational evaluation of political opportunities, resource dependence, and ideological constraint—are also reported to be influential, although these processes are sometimes influenced by relational dynamics. These findings suggest new variables and relationships of interest for future quantitative research and provide insight into the growing complexity of climate politics.