Social problems clusters as contexts for claimsmaking: implications for the study of off-campus housing

ABSTRACT

Many social problems claims occur in a context that involves (1) actors’ recognition of other stakeholders, (2) relationships among those actors, and (3) varying temporal frameworks that influence how each claimsmaker views the current collection of issues. We call actors’ involvement in overlapping issues a social problems cluster, a set of claimsmaking efforts that involve many of the same people and groups as advocates, or opponents. Using a case study of local student housing issues as an example, we suggest the following regarding the social problems cluster. First, we consider how the interactions among social problems cluster members shape what happens with a particular issue. Second, we consider the way participants within one social problems cluster recognize links may reflect participants’ biographies, interests, ideologies, and so forth. Attending to how the social problems cluster’s members interact and link issues helps to locate a particular claim within its broader context.     

A note on the analysis of parity progression ratios

Contingency table modeling procedures are proposed to examine the effects of independent variables on parity progression ratios. The methodology is outlined and an incremental-factorial linear model is developed.     

Population forecasts and confidence intervals for sweden: a comparison of model-based and empirical approaches

This paper compares several methods of generating confidence intervals for forecasts of population size. Two rest on a demographic model for age-structured populations with stochastic fluctuations in vital rates. Two rest on empirical analyses of past forecasts of population sizes of Sweden at five-year intervals from 1780 to 1980 inclusive. Confidence intervals produced by the different methods vary substantially. The relative sizes differ in the various historical periods. The narrowest intervals offer a lower bound on uncertainty about the future. Procedures for estimating a range of confidence intervals are tentatively recommended. A major lesson is that finitely many observations of the past and incomplete theoretical understanding of the present and future can justify at best a range of confidence intervals for population projections. Uncertainty attaches not only to the point forecasts of future population, but also to the estimates of those forecasts' uncertainty.     

A Theory of Disagreement in Repeated Games With Bargaining

This paper proposes a new approach to equilibrium selection in repeated games with transfers, supposing that in each period the players bargain over how to play. Although the bargaining phase is cheap talk (following a generalized alternating‐offer protocol), sharp predictions arise from three axioms. Two axioms allow the players to meaningfully discuss whether to deviate from their plan; the third embodies a “theory of disagreement”—that play under disagreement should not vary with the manner in which bargaining broke down. Equilibria that satisfy these axioms exist for all discount factors and are simple to construct; all equilibria generate the same welfare. Optimal play under agreement generally requires suboptimal play under disagreement. Whether patient players attain efficiency depends on both the stage game and the bargaining protocol. The theory extends naturally to games with imperfect public monitoring and heterogeneous discount factors, and yields new insights into classic relational contracting questions.     

NEW DOMAINS FOR STRUCTURAL ANALYSIS

Can network thinking be extended to the broad range of social organization conventionally studies by sociologists? Applying structural thinking to American election data, it is possible to detect a social-economic hierarchy solely from the links among categories, without reference to external numerical indicators of rank. It is possible to detect and verify sensible and suggestive relative social positions for categories of income, education, gender, age, religion, race, party identification, and region – forming correlated hierarchies. The special contribution of the structural analysis is its simultaneous attention to detail and the overview of links, coupled with less dependence on a priori assumptions.     

Book reviews

Clinical Social Work. Helen Northen. (New York: Columbia University Press, 1982.)

The Fifty‐Minute Hour: A Collection of True Psychoanalytic Tales. Robert Lindner. (New York and London: Jason Aronson, 1982.)

Clinical Work With Children. Judith M. Mishne. (New York: The Free Press, 1983.)

The Father Figure. Lorna McKee and Margaret O'Brien, Editors. (London: Tavistock Publications, 1982.)     

Applied Nonparametric Instrumental Variables Estimation

Instrumental variables are widely used in applied econometrics to achieve identification and carry out estimation and inference in models that contain endogenous explanatory variables. In most applications, the function of interest (e.g., an Engel curve or demand function) is assumed to be known up to finitely many parameters (e.g., a linear model), and instrumental variables are used to identify and estimate these parameters. However, linear and other finite‐dimensional parametric models make strong assumptions about the population being modeled that are rarely if ever justified by economic theory or other a priori reasoning and can lead to seriously erroneous conclusions if they are incorrect. This paper explores what can be learned when the function of interest is identified through an instrumental variable but is not assumed to be known up to finitely many parameters. The paper explains the differences between parametric and nonparametric estimators that are important for applied research, describes an easily implemented nonparametric instrumental variables estimator, and presents empirical examples in which nonparametric methods lead to substantive conclusions that are quite different from those obtained using standard, parametric estimators.