WIRTH, G.; J. SEDRANSK; and P. REITAN (1977) "Strategies forSelection of a Leadership Sample in Applied Survey Research:A Case Study in Erie and Niagara Counties, New York, 1976,"Environmental Studies Center, SUNY/Buffalo. Occasional PaperNo. 5.

THE STUDY OF POLITICAL FEEDBACK USING NONRECURSIVECAUSAL MODELS: THE CASE OF STATE DIVORCE POLICIESGillian Dean, Brookings Institution

ABSTRACT

Researchers interested in policy feedback effects can use thenonrecursive modeling strategies proposed here when time seriesdata are not available for assessing feedback dynamics. Thisstrategy is illustrated in a study of the impacts of Americanstate divorce policies on divorce behavior and the responsivenessof policies to divorce rates. The findings show appreciable impactand feedback effects. In states where divorces are easier to ob-tain, the incidence of divorce is higher; and where divorce is morewidespread, states are likely to implement more permissive divorcepolicies.

Scholars concerned with political accountability and govern-mental responsiveness need a better empirical understanding ofpolitical feedback, or the extent to which policies reflect and respondto the people they are intended to affect. Political scientists, policyanalysts, and others have long acknowledged the need for researchin the area of political feedback, but little has been done to satisfythis need (Easton, 1965; Deutsch, 1966; Fowler and Lineberry, 1972).Like many provocative questions in the political world, feedbackdoes not easily lend itself to rigorous analysis. An interest in politi-cal feedback prompts a careful look at those aspects of the policyprocess that happen after governmental policies are formulated andbefore they are modified. But these aspects of the process are dif-ficult to conceptualize, measure, and assess empirically (Dean, 1975).

Ideally, quantitative research on policy feedback would rely ontime series data and models that reflect temporal lags between policyimpacts and subsequent policy decisions. When time series data arenot available, nonrecursive causal models can be used to elaboratecorrelation relations between policies and their consequences. Non-recursive models allow researchers to inquire about policy impactsand political feedback at the same time. One question is how arepeople really affected by the policies aimed at them? Another questionis how do people's responses influence changes in these policies, or,how responsive are policies to the impacts they engender? Thesegeneral research concerns can be diagrammed:

Impact effectPOLICY OUTPUT

Feedback effect

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POLICY CONSEQUENCES

The research reported here employs a nonrecursive approachto feedback and impact in a study of state government divorce poli-cies. States enjoy broad powers to regulate many areas of publicmorality and the family, and the past fifteen years have seen drama-tic changes in state divorce policies. In most states, divorces areeasier to obtain. In the same period, there have been marked up-ward changes in state divorce rates. The study focuses upon theinterrelations between divorce policies and divorce behavior orrates. The major questions concern

Impact: Do more permissive divorce policies lead to higherdivorce rates? and

Feedback: Do differences in divorce rates affect differences indivorce policies?

THE MODEL AND ITS CONTROL VARIABLES. Impact and feedbackare assessed in the context of other influences on state divorcerates and policies. Earlier studies of divorce behavior stressedthree contextual factors other than laws that influence divorcerates. In areas where education, income and social stability arehigher, divorce rates are lower (see Udry, 1966; Cutright, 1971;Fenelon, 1971). These variables are included in the causal modelas exogenous variables influencing divorce rates.

There has been virtually no research on the feedback effectsof divorce, but general discussions of feedback processes sug-gest six variables in addition to divorce rates that may influence theresponsiveness of divorce policies to divorce behavior in a state:

1) Public opinion that favors permissive divorce policies willencourage permissive policies.

2) State political culture—the particular area pattern of orienta-tion to political and policy action. Using this concept devel-oped by Elazar (1966), states with more traditional valuesare expected to have less permissive divorce policies (seealso Patterson, 1968).

3) Church interest groups and area religious culture maysignificantly influence policies. The model posits that stateswith large Catholic populations will have more restrictivedivorce policies (see Fairbanks, 1979; Elliott, 1950).

4) Legislative professionalism may also influence divorce policies(Grumm, 1971). The more professional the state legisla-ture, the more likely it is to keep up with citizen demands,and the more permissive its divorce policies will be.

5) Legislative apportionment may also influence divorce policies.Well-apportioned legislatures, in which urban and othergroups are more equitably represented, are more likely tocreate permissive laws (see Grumm, 1968; Pulsipher andWeatherby, 1969).

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6) Innovative states are expected to be more responsive todivorce rates and hence more likely to adopt and implementpermissive divorce policies than are states which are notinnovative in their policies (Walker, 1969).

MEASURING THE VARIABLES. The permissiveness of state divorcepolicies is measured as the policies are implemented in the judicialsystem rather than as they are enunciated in legal statutes. Thisavoids the ambigioity of statutes, which have different meanings indifferent states, and simplifies the model by eliminating additionalfactors that can intervene in the translation of laws into practicedpolicies (see Rheinstein, 1972).

Four aspects of divorce policy are used to measure permissive-ness: 1) cost of divorce, 2) amount of time it takes to get a di-vorce, 3) how carefully jurists hear divorce cases, and 4) ease ofobtaining a divorce in a state compared with other states. Datafor these measures were obtained from a questionnaire mailed na-tionwide to 519 professors and lawyers concerned with family law(Dean, 1975). These data were combined in an additive,standardized index.

Divorce rates are measured by the numbers of final decreesgranted in 1970 per 1000 married women between the ages of 14 and50. This measures the rate of divorce in relation to the popula-tion most likely to divorce; older married women, less exposed tothe risk of divorce are excluded. What about migratory divorces,those obtained in a state where neither party is a bona fide resident?Data are not readily available, but estimates suggest that migratorydivorce constitutes only about three or four percent of the divorcesin the United States (Cahan, 1932; Jacobsen, 1959; Plateris, 1971),and in this study's questionnaire, experts on divorce estimatedmigratory divorce at 2.9 percent of the national total. However,such divorces make up 25 to 30 percent of the total divorces inNevada, and Nevada is therefore excluded from the analysis.

Data for divorce rate are from 1970, but data for some of theother variables are not available for this time period. For example,the policy questionnaire records information for 1973, and some ofthe measures for the second set of control variables were takenbefore 1970. However, in most instances it would have been inap-propriate to measiwe these variables at the 1970 time point becausetheir effects on divorce policy and divorce rates work over alonger period.

The three variables that affect the impact of divorce policieson divorce rates are measured using U.S. Census data (Dean, 1975).

1) Income: per capita personal income for 1970.

2) Education: 1970 median education level of women in thestate. (Women are considered because the base for thedivorce rate is derived from the number of women in thestate).

3) Social stability: intercounty migration rates for 1970.

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Intercorrelations among these three control variables are weak,except in the case of income and education, where the correlationis reasonably high (r = .57). This suggests that we must inter-pret the regression results with care, to avoid problems withcollinearity.

The variables affecting the linkage between divorce rates andpolicies are measured as follows (Dean, 1975):

1) Mass public opinion: a 1959 Gallup survey, modified byWeber (1971) to indicate state level public preferences on divorcepohcies.

2) Political culture: Sharkansky's (1969) translation ofElazar's observations of state cultures. The index increases invalue as states are more traditionalistic.

3) The percent of the state's population that is Catholicused because there are no data directly reflecting the strength ofrehgious culture or Catholic interest groups in the states.

4) Legislative professionalism: the Grumm index, which tapslegislative pay, session length, staffing and other services.

5) Apportionment: the David-Eisenberg index of urbanunderrepresentation.

6) Innovativeness: Walker's (1969) index of state policyadoption. '^ '

Several of these control variables are highly intercorrelated:

Table 1. Correlations among Variables Affecting the FeedbackLinkage of Divorce Rates and Policies.

Opin. Cult. Cath. Prof. Innv. Malp.

Public opinionPolitical culturePercent CatholicProfessionalismInnovationMalapportionment .j^o -.4U3 .502 300 ,602

Because this collinearity would make it difficult to interpret

-.501.441.192.518.325

-.403.005

-.459-.403

.260

.502

.502.652.300

fooHK^^i,^"'^'^""'^"* Factor, reflects the social environment of thefeedback process. PoUtical culture, public opinion, and percent

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Table 2. Factor Analyses of Variables Affecting the Feedback Link-age of Divorce Rates and Policies (Orthogonal Rotation).

Environment Factor Institutions Factor

Political CulturePublic OpinionPercent Catholic

ProfessionalismInnovativenessMalapportionment

-.865.749.662

-.034.540.580

.166

.071

.342

.946

.749

.471

Catholic weigh heaviest on this factor. Public opinion has a nega-tive loading on the factor; the other two major variables havepositive loadings. These signs show that states with proportion-ally higher populations of Catholics are in fact states with morepermissive divorce policies, supported by public opinion andpolitical culture.

2) Institutions Factor, reflects the way political institutionsdetermine divorce policies. On this factor, the high loading vari-ables are innovativeness, professionalism, and apportionment.States with high scores on either the environment or the institu-tions factors are expected to have more permissive divorce policies.

ANALYSIS OF THE MODEL. The first hypothesized linkage is thatwhere divorce policies are more restrictive divorce rates are lower.Education, income and social stability are also expected to affectdivorce rates. The second major hypothesis is that divorce rateswill have a feedback effect on divorce policies. The Institutionsand Environment factors are also expected to influence policies.U-sing the following notation:

DIV = divorce ratePOL = divorce policyEDUC = education levelINC = income level

MIG = migration rates (socialstability)

ENV = environment factorINST = institutions factor

these two sets of linkages can be combined and their reciprocalrelationships expressed as a set of interdependent simultaneousequations:

(1) POL = a + biiDIV + bi2EDUC +

(2) DIV = a + b2lP0L + b22lNST +

Ordinary least squares is an inappropriate estimation procedurein this situation, so a simple and applicable alternative procedure,two stage least squares, is used to evaluate the model (Theil, 1971:chs. 9-10). The structural form of the model is shown in equations(3) and (4) with the estimated coefficients as given by the two

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stage procedure. The numbers under the coefficients are Stu-dent's t values. These values are significant at the .05 level whent - 2.01; they are significant at the .01 level when t * 2.68.

(3) DIV = 9.88 + 6.181 POL - .744 EDUC + .022 INC + .350 MIG

(.728) (2.059) (.508) (.797) (1.391)

(4) POL = -.992 + .072 DIV - .190 INST - .144 ENV

(2.254) (2.579) (2.026) (1.810)

Estimated results show divorce policy strongly affects divorce behav-ior, and that divorce behavior has an important effect on policy.

In equation (3), which predicts divorce rates, divorce policyIS positavely related to rates. The estimated coefficient for policyIS substantively large and statistically significant, suggesting thatmore permissive policies lead to higher divorce rates. ^Policy^is theonly statistically significant determinant of divorce rates. Migrations statistically almost significant, but neither education or incLe

i r , ^ ' ^ t " ^^® previously noted colUnearity between incomeand education may be distorting the significance tests for the esti-Gfl̂ iJon f. >f ^^? variables. However, when either income or edu-cation is omitted from the basic model, the remaining of the two vari-ables IS still an insignificant determinant of divorce. The basicconclusion is that divorce appears to be more responsive to poUcythan to the other, less manipulable, factors.

"^*/°"-^^^' which predicts divorce policies, indicates that as^ rates increase, divorce policies become increasingly permis-s ve. The environment factor's negative relation to divorce poKcysuggests the policy strength of Catholic groups. Even in stateswhose political culture and public opinion support permissive divorcepohcies, larger proportions of Catholics result in more restructivepolicies Divorce policies appear to be more responsive to religiousinterests than to public opinion or area culture.

institutions factor, we notice a surprisinginnovative, better-apportioned and morere more likely to have restrictive policies

'^^'^ '" ^ tl explained by themfn Sf

mmBMA925

is the dependent variable. This suggests that the scaling differ-ences mask the fact that the impact link from policy to divorce isabout as strong as the feedback link from divorce to policy.

The coefficients of determination for the structural equations,while not small, suggest that a sizeable proportion of the varianceremains unexplained by the model. Analysis of the residuals, how-ever, showed no far outliers and no clearly discernible patterns.

SUMMARY AND IMPLICATIONS. This analysis indicates that restric-tive divorce policies tend to decrease the incidence of divorce, whilehigher divorce rates lead to more permissive divorce policies, atleast as these are practiced in the courts. One may infer from thesefindings that the no-fatilt and other more permissive divorce laws towhich almost all states are turning will in fact facilitate divorce.The findings also suggest that states will tend to respond to demandsfor divorce by liberalizing their divorce policies.

The study relies on cross sectional rather than time series data,and its reciprocal modeling does not precisely and comprehensivelyreflect dynamic impact and feedback processes. Evidence aboutcross sectional differences can be suggestive of the form and natureof change over time, however it cannot let us say whether the de-mand for divorce will create a spiral of more liberal policies, followedby increased demands, followed by more liberal policies. If we viewincreases in divorce as a siphoning off of "pent up" demand for di-vorce, which could not be satisfied under more onerous legal proce-dures, a divorce threshold is plausible. This would mean that nomatter how easy obtaining a divorce became, the demand for it wouldnot exceed this threshold level.

On a more general level, this research illustrates the utility ofnonrecursive causal models for the analysis of political feedback andpolicy impacts. As policy research becomes increasingly orientedto theoretical development, it will need more sophisticated analyticapproaches. The model suggested here has wide ranging applica-bility for analysis because it makes possible the study of large num-bers of reciprocal relations that political research has not yetwidely explored.

REFERENCES

CAHAN, A.(1932) Statistical Analysis of American Divorce. NewYork: Columbia University Press.

CUTRIGHT, P. (1971) "Income and family events: Marital instability,"Journal of Marriage and the Family 33: 291-306.

DEAN, G. (1975) "Impact and feedback effects: Divorce policies anddivorce in the American states." Unpublished Ph.D. dissertation.University of Wisconsin.

DEUTSCH, K. (1966) The Nerves of Govemment: Models of PoliticalCommunication and Control. New York: Free Press.

EASTON, D. (1965) A Systems Analysis of Political Life. New York:John Wiley.

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ELAZAR, D. J. (1966) American Federalism: A View from the States.New York: Thomas Y. Crowell.

ELLIOTT, M. A. (1950) "Divorce legislation and family stability,"Annals of the American Academy of Political and Social Sci-ences 252: 134-147.

FAIRBANKS, D. (1979) "Politics, economics and the public morality "Policy Studies Journal, 714-721.

FOWLER, E. P. and R. L. LINEBERHY (1972) "Patterns of feedback incity politics," in D. R. Morgan and S. A. Kirkpatrick (eds.)Urban Political Analysis: A Systems Approach. New York: FreePress, 361-367.

GRUMM, J. (1968) "Structural determinants of legislative output "Presented at the Conference on the Measurement of Politics inthe American States, Inter-University Consortium for PoliticalResearch, Ann Arbor, Michigan.

(1971) "The effects of legislative structure on leqisla-tive performance" in R. Hofferbert and I. sharkansky (eds )State and Urban Politics. Boston: Little, Brown.

JACOBSEN, P. (1959) American Marriage and Divorce. New York-Rinehart.

PATTERSON, S. C. (1968) "The political culture of the Americanstates,' Journal of Politics 30: 187-209.

PLATERIS, A. (1971) "The Statistics of divorce" in B. N. Adams andT. Weirath (eds.) Readings on the Sociology of the FamilyChicago: Markham.

PULSIPHER, A. G. and J. L. WEATHERBY, JR. (1969) "Malapportion-ment, party competition and the functional distribution ofgovernmental expenditures," American Political Science Review62: 1207-1219.

RHEINSTEIN, M. (1972) Marriage Stability, Divorce and the LawChicago: University of Chicago.

SHARKANSKY, I. (1969) "The utility of Elazar's political culture "Polity 2: 66-83.

THEIL, H. (1971) Principles of Econometrics. New York: John

UDRY, J. R. (1966) "Marital instability by race, sex, educationand occupation, using 1960 data," American Journal of Sociol-ogy 72: 203-209.

WALKER, J. L. (1969) "The diffusion of innovation among the Ameri-can states," American Political Science Review 63: 880-899.

WEBER, R. E. (1971) Public Policy Preferences in the StatesBloomington, Indiana: University of Indiana Institute ofPublic Administration.

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RESEARCH METHODS

Focusing explicitly on methodological questions, the two arti-cles in this section, despite disparate foci, illustrate complementaryneeds in the analysis of policy impact: the need for specific meth-odological techniques and the need for a substantive focus aroundwhich analytical methodology can be developed. In an example ofthe former, Kathryn Newcomer and Richard Hardy, using as theirsubject matter the effect of reapportionment on state expendituresfor large cities, test different linear trend models. In a contributionto the literature on time-series analysis, they examine, and identifythe relative advantages and disadvantages of, three models. Anexample of the second need is presented in Marcia Ory's discussionof concepts and methodologies to be used in Family Impact Analysis.This type of analysis is important because it makes the analyst shiftattention from a specific policy to an institution on which one ormore policies have an impact. Ory carefully takes the readerthrough the steps necessary to perform Family Impact Analysis.

ANALYZING POLICY IMPACT: SELECTION OF A LINEARTREND MODELKathryn E. Newcomer, University of Nebraska-LincolnRichard J. Hardy, University of Missouri-Columbia

ABSTRACT

Policy analysts, as well as politicians, have shovm greatinterest in assessing both short-term and long-term consequencesof public policies in recent years. Recent time-trend studieshave attempted to depict the time dimension of policy consequencesthrough extensions of regression techniques. This study examinesthree linear trend models which have been used to depict policyimpact through time-series analyses, and identifies the relativeadvantages and disadvantages associated with the use of each model.The three models are applied in a quasi-experimental time-seriesdesign to time-series of per capita state expenditures for largecities, in eight states, over a twenty-year period. Differencesin degrees of multicollinearity and autocorrelation inherent inthe three models are discussed, and the model providing the mostconservative coefficient estimates is identified.

Policy analysts, as well as politicians, have shown great inter-est in assessing both short-term and long-term consequences ofpublic poUcies in recent years. It is well-recognized that knowledgeof the time dimension underlying policy results constitutes a criticalconstraint on analyses of policy impact.

With this understanding, recent time-trend studies have at-tempted to depict the time dimension of policy consequences throughextensions of regression techniques (McCrone and Hardy, 1978;

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