The Study of Political Feedback Using Nonrecursive Causal Models: The Case of State Divorce Policies

Abstract

Researchers interested in policy feedback effects can use the nonrecursive modeling strategies proposed here when time series data are not available for assessing feedback dynamics. This strategy is illustrated in a study of the impacts of American state divorce policies on divorce behavior and the responsiveness of policies to divorce rates. The findings show appreciable impact and feedback effects. In states where divorces are easier to obtain, the incidence of divorce is higher; and where divorce is more widespread, states are likely to implement more permissive divorce policies.

Previewing Policy Sciences: Multiple Lenses and Segmented Visions

“…Regression models, such as Schneider and Jacoby’s (1996) study of state Medicaid adoptions include variables for environmental factors, political factors, and organizational factors and isolating the effects of individual variables while holding other variables constant. Ordinary least squares models have been supplemented by non recursive causal models (Dean 1980), time series models (Newcomer and Hardy 1980), and substantively weighted least squares (Meier, Gill, and Waller 2000). While regression methods estimate the overall effects of multiple variables, the methodology does little to estimate whether the configuration of variables produces particular outcomes.…”

Public Opinion and Policy Change in the American States

“…Despite the failure to uncover sharp attitudinal differences across the regions, research has continued to discover policy differences among the cultural regions (Sharkansky, 1969;Johnson, 1976;Sigelman, 1976;Dean, 1980). These findings have left us with an interesting puzzle: How can similar opinions and differences in policy exist simultaneously?…”