Dissolving the relationship between divorce laws and divorce rates

Dissolving the Relationship Between DivorceLaws and Divorce Rates

IRA MARK ELLMAN

and

SHARON L. LOHR

Arizona State University, Tempe, Arizona, USAE-mail: ira.ellman@asu.eduE-mail: sharon.lohr@asu.edu

I. Introduction

Law and other causes influence the divorce rate. Thus much is axiomatic. But when an attemptis made to go further and determine the relative influence and effect of law and the sum ofother causes, then the controversy opens.1

Some questions never seem to go away. Walter Willcox made the preceding observationin 1891. Labor Commissioner Carroll Wright had just released the first comprehensivedata on marriage and divorce in the United States,2 from which he observed that it is“quite apparent that the lines of statistics are curved in accordance with laws enactedjust prior to the curves,”3 and he concluded that changes in law “may account” for thechanges in divorce statistics. But when Willcox examined the legal changes in detail, heconcluded that “the influence of law, if not nil, is at least much less than commonlysupposed.”4

In 1891, almost all divorces were granted on grounds of desertion, adultery, cruelty,drunkenness, failure to provide, or imprisonment. These restrictive grounds were partlythe result of efforts by mid-19th century crusaders who believed that their enactmentwould reduce the divorce rate.5 Despite the crusaders’ efforts, however, the nationaldivorce rate increased steadily from 1867 to 1930. The divorce rate was 0.3 per 1,000

1Willcox, Walter F. (1891). The Divorce Problem: A Study in Statistics, New York: AMS Press.2Wright, Carroll D. (1889). A Report on Marriage and Divorce in the United States, 1867 to 1886. Washington, D.C.: U.S.

Government Printing Office (1889).3Wright, p. 150.4Willcox, p. 55.5Friedman, L.M. (1985). A History of American Law (2nd ed.). 204–207, 498–504, New York: Touchstone Books.

International Review of Law and Economics 18:341–359, 1998© 1998 by Elsevier Science Inc. 0144-8188/98/$19.00655 Avenue of the Americas, New York, NY 10010 PII S0144-8188(98)00014-3

population in 1867, 0.7 per 1,000 population in 1900, and 1.6 per 1,000 population in1930.6

In the 1990s every state has some form of no-fault divorce law, and the divorce rateper 1,000 population seems to be declining. Nevertheless, the controversy about theeffect of divorce laws on divorce rates remains. Some persons propose reintroducingconsiderations of fault into divorce proceedings, claiming that the perceived economicand social penalties would reduce the divorce rate. Extreme divorce laws certainly seemlikely to influence divorce rates. When South Carolina repealed its ban on divorce in1878, the state experienced an immediate change in the divorce rate. But, of course, noone suggests reinstituting a ban on divorce. Instead, modern fault proponents urgeeither or both of two less draconian legal rules, which we describe below. But we noteat the outset that we find no evidence that either measure would reduce the incidenceof divorce. Because we also believe that they are both likely to distort the bargainingprocess between spouses in a way that produces unjust results, we believe that theirenactment would be poor public policy.

The rule that fault proponents usually urge would require a showing of spousal faultas a ground for divorce, either absolutely, or—and this is the more common propos-al—as the only basis upon which one may petition for a divorce other than living apartfor several years. Such “fault-or-long-wait” laws would work a significant change from thedominant form of no-fault divorce now available in most states, in which either spousemay obtain a divorce unilaterally without proving fault and without waiting more than6 months, or at most a year, from the parties’ separation. Our earlier papers haveexplored why “fault-or-long-wait” reforms would, if enacted, be nearly certain to causeserious unintended difficulties for innocent parties,7 and we do not revisit those issueshere. Those earlier papers also summarized some of the empirical literature concernedwith whether the widespread adoption of no-fault divorce between 1968 and 1985contributed to the increase in divorce rates, and we concluded that the literaturepresents no persuasive evidence of any such effect.

The second rule that some proponents are urging would permit divorce courts toconsider marital misconduct—adultery, personal nastiness, and the like—in their ad-judication of alimony claims and their allocation of marital property. At least one recentpaper argues that such a rule, as distinct from a fault rule on the grounds for thedivorce, contributes to a reduction in the divorce rate. The argument may be of specialinterest because it does not seem as great a departure from existing law. About half thestates already allow some consideration of marital misconduct in fashioning thesefinancial elements of the divorce decree, a fact that the authors rely upon for theirempirical showing.8

Section II of this paper considers some theoretical difficulties with the argument thatfault-regarding rules on the financial components of divorce would reduce divorcerates. Sections III and IV then return to the empirical evidence bearing on the impact

6Plateris, Alexander A. (1973). 100 Years of Marriage and Divorce Statistics, United States, 1867–1967, at 22, Departmentof HEW Publication number (HRA) 74-1902. Washington, D.C.: U.S. Government Printing Office.

7See Ellman, Ira Mark, and Sharon Lohr. (1997). “Marriage as Contract, Opportunistic Violence, and Other BadArguments for Fault Divorce.” University of Illinois Law Review 3:719; and Ellman, Ira Mark. (1997). “The MisguidedMovement to Revive Fault Divorce, And Why Reformers Should Look Instead to The American Law Institute.”International Journal of Law, Policy and Family 11:216.

8The authorities are systematically described in Ellman, Ira Mark. (1996). “The Place of Fault in a Modern DivorceLaw.” Arizona State Law Journal 28:773.

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of either kind of fault rule—divorce grounds and divorce financials—on divorce rates.Section III examines the data analyses of two papers that have asserted that no-faultregimes cause divorce, and Section IV presents our own analysis of the availableevidence. This detailed examination reaffirms our conclusion that there is no evidencethat divorce laws affect trends in divorce rates.

II. Theoretical Considerations

In No-Fault Divorce and At-Fault People,9 Brinig and Buckley argue that existing divorcelaws in about half the states that make marital misconduct relevant in alimony awardsor property allocations should result in reduced divorce rates because they impose a“sanction” on marital misconduct.10 They set out to demonstrate this hypothesis in theempirical part of their article, which attempts to compare the experience in states withsuch rules with that in states that allocate property and adjudicate alimony claims on ano-fault basis. Why should such a sanction affect the divorce rate? Here Brinig andBuckley are not clear. One can read them as making either or both of the followingarguments: (1) Badly behaved spouses will be less likely to seek divorce under a faultdivorce law because that law would leave them worse off than would a no-fault law; or(2) fault divorce laws will discourage marital misconduct, and a lower rate of miscon-duct will lead to fewer divorces. We explain here why we believe it unlikely that onewould find empirical support for either argument.

Consider the first argument. The problem is that any fault-based financial penaltyimposed on the guilty spouse is a payment to the innocent one. So, if a fault-basedfinancial penalty creates a disincentive for the guilty spouse to seek divorce, then it alsocreates an incentive for the innocent one to seek it. (Either spouse can obtain a divorceunder modern no-fault rules.) The incentive structure would discourage divorce only ifthere is a systematic imbalance in the impact of the same dollar incentives on guilty andinnocent spouses, such that the guilty spouses are deterred more than the innocentspouses are encouraged. That particular imbalance is not impossible, but neither is itinevitable. Indeed, the opposite imbalance is arguably more likely, in which caseincreased filings by the innocent spouses would exceed the reduction in filings by theguilty spouses, leading to an overall increase in divorce rates.11

As for the second argument, we note that in an earlier paper with a different

9This issue, pages 325–340.10Actually, Brinig and Buckley’s thesis is not entirely clear. Although they say that “one would expect less fault and

fewer divorces when fault bears a financial penalty,” they are not clear as to why one would have that expectation. Theydo suggest at one point that fault rules impose a financial penalty that will deter marital misbehavior, and one mightsurmise that they also believe that the spouses are therefore less likely to seek divorce. If that surmise is correct, it wouldseem that their thesis is multistep: (1) fault rules contain financial penalties for fault, (2) which deter maritalmisconduct, (3) which in turn reduces the incidence of divorce. Although this seems to be the most plausible readingof their thesis (we cannot discern any other reading that makes any sense at all), it is also a reading that is inconsistentwith their classification of states as “fault” and “no-fault.” Their statistical analysis, if it is to support their thesis, mustclassify as a “fault” state only those states having divorce laws that impose a financial penalty on marital misconduct. Yettheir analysis treats five states—Arkansas, Utah, Maine, Alaska and New Mexico—as fault states even though their lawsbar the consideration of marital misconduct in alimony and property allocation. Their explanation is that becausethese states permit a spouse to seek divorce on fault as well as no-fault grounds, they “permit the innocent party tointroduce fault into the settlement negotiations.” But anyone can always introduce anything into the settlementnegotiations: the question is whether the availability of fault divorce grounds gives the introduced issue some bite thatit would not otherwise have. It is unclear how claims of misconduct could have any bite in these five states.

11In considering the power of the incentives, one might believe that income effects are likely. That is, one mightassume that the same dollar change in alimony would affect the motivations of a poorer spouse more than a richer one.

343I.M. ELLMAN AND S.L. LOHR

coauthor,12 Brinig offered a more specific version of it: She argued that fault rules deterspousal violence. We have elsewhere exposed theoretical and empirical flaws in thatmore specific claim,13 some of which also apply here, and we do not repeat them. Ourmost general concern arises from our doubt that a court’s possible consideration offault, in a divorce action not yet filed, would have much impact on the personalbehavior of spouses toward one another, or with third persons in a romantic triangle.There are immediate and powerful forces at work in such intimate conduct that seemlikely to swamp the far more remote and contingent consequences that the divorce lawmay impose.

Beyond that general concern, there is a serious discontinuity between the secondargument and the empirical inquiry in this paper. Brinig and Buckley wish to test theirargument by comparing the experience in no-fault states with the experience in statesthat already allow courts to consider fault in fixing a divorce’s financial elements. Butthe incentive structure in existing fault laws—the necessary subject of their empiricaltest—does not conform to the theoretical model of the fault laws whose impact theywish to examine. There are two important departures. First, fault is relevant in far fewerdivorces under existing fault laws than it would be in the system they prefer. Only 15states permit the consideration of fault in the allocation of marital property, and manyof these states restrict its role significantly.14 For most of the “fault” states that theyexamine, therefore, misconduct can play a role only through the alimony rules. Yet nostate makes alimony available in every divorce, and most studies find that it is awardedin only about 20% of all divorce decrees.15 In the remainder no award is made, perhapsbecause the duration of the marriage was too short, or the spouses’ economic circum-stances are not sufficiently disparate to require an award under the governing law. Butwhatever the reason for the failure of an alimony award, one can see that any fault rulethat adjusts the amount of an award, when made, would be relevant in only a minorityof all divorces. Therefore, it seems unlikely that alimony is an important factor influ-encing marital behavior generally, much less a major cause in the overall divorce rate.

Second, even if one focuses on the 20% of divorces that include alimony awards, theactual law departs from Brinig’s model, because the actual law, as contrasted with themodel, does not make simple adjustments in alimony awards, up or down, according tothe marital behavior of the spouses.16 In some fault states, for example, a spouse whocommits adultery is barred from receiving any alimony at all, or is barred unless shemakes a special showing of severe economic privation, whereas adultery by the alimonyobligor is irrelevant. Other states, either by case law or custom (these matters being leftlargely to the discretion of the trial court judge) apply the same approach generally:The obligee’s misconduct may reduce an award, but the obligor’s misconduct will notenlarge it. So even if one assumes that the spouses’ marital conduct is affected greatlyby the fault provisions of their state’s alimony law, it turns out that as the actual lawoperates, such deterrence value is one-sided, the conduct applies only to the potential

Men are usually better off than their wives. If one also believed that they are more often guilty of legally recognized faultthan are their wives, then the resulting imbalance in the incentives would yield more, not fewer, divorces.

12See Brinig, Margaret F., and Steven M. Crafton. (1994). “Marriage and Opportunism.” Journal of Legal Studies23:869.

13See Ellman and Lohr, supra note 7.14See Ellman, supra note 8.15See the studies cited in American Law Institute, Principles of the Law of Family Dissolution (proposed final draft, part

I, 1997) at 302.16We rely, in the following description of existing fault law, on Ellman, supra note 8.

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obligee. Might such a regime encourage exploitation by the potential obligor, which, inturn, leads to more divorce? Might such a regime encourage the potential obligee whois disenchanted with her marriage to file for divorce earlier, and not to wait longer tosee if things improve, for fear that during such a wait she might take some action thatwill reduce her alimony claim? We do not try to answer such speculations. We merelyobserve that there are good reasons to doubt that existing fault rules deter misconductand, for that reason, deter divorce—the proposition that Brinig and Buckley test in theempirical portion of their article.

III. No-Fault Divorce and Full-Fault Statistics

Although the theoretical arguments for fault divorce do not hold up on examination,it might still be possible that, for some unarticulated reason, existing no-fault regimesin fact result in higher divorce rates than existing fault regimes. Therefore, we turn nowto empirical evidence. A number of studies have examined changes in divorce rates thatmight be associated with a change in law for divorce grounds.17 Wright and Stetson, forexample, concluded that divorce law changes had little effect on the incidence ofdivorce in most states.18 As these papers basically agree with our conclusions, we shallnot discuss them further. We focus instead on two papers that conclude, from theiranalysis of the same data set we use in Section IV, that no-fault laws cause increases indivorce rates. We examine the premises and conclusions of these papers, and we showthat the conclusions of both papers rely on flawed statistical analyses. Their empiricalresults should, therefore, be disregarded in public policy debates.

Nakonezny, Shull, and Rodgers

Nakonezny et al.19 concluded that “the switch from fault divorce law to no-fault divorcelaw led to a measurable increase in the divorce rate.”20 One analysis they offered for thisconclusion was a paired t-test that examined the difference, in each state, between thedivorce rate before and after that state’s adoption of no-fault divorce. The post-no-faultdivorce rate was defined as the average divorce rate for 3 consecutive years after theeffective date of the no-fault divorce law. The pre-no-fault divorce rate was defined asthe average divorce rate for 3 consecutive years preceding the effective date of theno-fault divorce law.

The analysis of Nakonezny et al. is flawed21 because they ignored the fact that over

17Many of these are cited in Peters, H. Elizabeth (1986). “Marriage and Divorce: Informational Constraints andPrivate Contracting.” American Economic Review 76:437, 448. For a more recent compilation and summary, seeEllman, supra note 7, at 216, 220, 238, note 23.

18Wright, Gerald C., and Dorothy M. Stetson. (1978). “The Impact of No-Fault Divorce Law Reform on Divorce inAmerican States.” Journal of Marriage and Family 40:575, at 580. The exceptions that they found to this rule wereCalifornia and Florida.

19Nakonezny, Paul A., Robert D. Shull, and Joseph Lee Rodgers. (1995). “The Effect of No-Fault Divorce Law onthe Divorce Rate Across the 50 States and Its Relation to Income, Education, and Religiosity.” Journal of Marriage andthe Family 57:477.

20Nakonezny et al., supra note 19 at 485.21There are also has a number of other errors; for example, the dates of changes in the law are incorrect for a

number of states. We discuss another shortcoming of their analysis in Section IV. Another criticism of the causalargument of Nakonezny et al. is given in Glenn, Norval D. A Reconsideration of the Effect of No-Fault Divorce onDivorce Rates.” Journal of Marriage and the Family 59:1023. Glenn shows that for states adopting no-fault divorce outsideof the “divorce boom” period of the 1970s, “the mean divorce rate was no higher in the 3 years after adoption than inthe 3 years before adoption” (p. 1023).

345I.M. ELLMAN AND S.L. LOHR

60% of the states adopted no-fault divorce grounds between 1970 and 1973—years ofincreasing divorce rates nationwide, both in states that changed their law during thisperiod and in states that did not. Thus, a simple before and after comparison does notwork. If it did, one could show, by looking at states that did not change their lawsbetween 1969 and 1974, that legal stability caused an increase in divorce rates (becausethe average divorce rates in those states are significantly higher for the period 1972–1974 than for the period 1969–1971).22

Nakonezny et al. claim to deal with this difficulty by comparing the change in divorcerate over the period surrounding the change in divorce law with a “comparison group”that consisted, for each state, of a randomly selected 6-year period that did not overlapwith the 6 years surrounding the no-fault enactment date. Finding that the change inaverage divorce rates over the randomly selected period was less than the change overthe period surrounding the adoption of no-fault divorce, the authors concluded therewas “no period effect interpretation.” This claim makes no sense. The same logic wouldlead to the conclusion that attending high school causes a rise in male testosteronelevels, based on evidence that the increase during that 4-year period is much steeperthan during any randomly chosen 4-year period on either side of the high schoolyears.23 The statistical significance found by Nakonezny et al. is merely an artifact of thenational increase in divorce rates in the early 1970s.

Brinig and Buckley

Brinig and Buckley performed multivariate analyses on data from the National Centerfor Health Statistics. They fit two types of models: pooling of cross-sectional and timeseries method, and two-stage least squares. With both models, they incorporate anumber of explanatory variables, including an indicator variable for the no-fault statusof state i in year t.

We shall not discuss whether these models are appropriate for the data; rather, wefocus on a particular aspect of their application in Brinig and Buckley. In the Kmenta24

model, the explanatory and response variables are transformed using estimated autore-gressive parameters for each state. After this transformation, and possibly after anadditional transformation intended to remedy heteroscedasticity, the model may beexpressed as

Y*it 5 ai 1 Xitb 1 Zitg 1 eit,

where Y*it is the transformed response at time t in state i, ai is a fixed-state effect for statei, Zit is the transformed indicator variable for whether state i is no-fault at time t, and Xit

is the transformed matrix of other explanatory variables. The eit are presumed inde-

22p-Value , 0.0001 for paired t-test. The same holds true for comparing states that did not change their divorce lawsin any successive 3-year periods that include 1971. Thus, the average divorce rate is higher for 1970 to 1972 than for1967 to 1969, and is higher for 1974 to 1976 than for 1971 to 1973.

23Nakonezny et al. do not identify the particular 6-year period chosen for the comparison done for each state. Wesurmise that any period between 1950 and 1990 (the years for which they analyze the data) might have been chosen,so long as it did not overlap that particular state’s change in divorce law. Arizona changed its divorce law in 1973,during the societal changes of the early 1970s. So, their analysis might have relied upon a 6-year period surrounding1954, or 1963, or 1985. Yet these as well as many other possible 6-year periods cannot serve as a control for estimatingthe effect of Arizona’s divorce law, because other factors that might have influenced the divorce rate and that mighthave prompted the change in law were not present during those periods.

24Kmenta, Jan. (1986). Elements of Econometrics (2nd ed.). New York: Macmillan, p. 616.

346 Divorce laws and divorce rates

pendent and identically distributed normal random variates, and the model parametersare estimated using least squares.

Brinig and Buckley studied the period 1980 to 1991. During that period, accord-ing to their Table 1, only two states changed from the “fault” category to the“no-fault” category: Illinois in 1984 and Kentucky in 1987. States such as California,which enacted no-fault in 1969, have a value of 1 for the NO-FAULT variablethroughout the time period. States such as Alaska (which Brinig and Buckleyerroneously categorize as a fault state) have a value of 0 for the NO-FAULT variablefor every year considered. The multiple regression coefficients, however, estimatethe changes in response associated with each explanatory variable after all otherexplanatory variables have been adjusted for in the model. Consequently, thecoefficient for the no-fault indicator variable Zit in Brinig and Buckley’s model isestimating the contribution of Zit to the model after accounting for the fixed-stateeffects and for all other covariates. For all states except Illinois and Kentucky,however, the untransformed indicator variable is either identically 0 or identically 1between 1980 and 1991. For 47 of the states, then, any potential contribution of theno-fault status toward explaining variability in the data is incorporated in thefixed-state effect ai. The NO-FAULT terms in Brinig and Buckley’s models thus donot estimate the effect of no-fault generally, but only estimate the change inKentucky and Illinois, after adjusting for the other variables in the regression. Itseems likely to us, then, that the statistical significance of their terms is due merelyto the particular choice of additional explanatory variables.25

The fact that their NO-FAULT variable cannot estimate the effect of no-fault lawsor practice is, we believe, more than sufficient to discredit their data analysis. Thereare additional problems, however. As we note in Table 1, Brinig and Buckleymisclassify divorce laws in eight states, or mistake the date of change in the law. Inaddition, the analysis ignores several prominent features of the data, which we notein Section IV.

Even if their analysis was flawless, however, and if the statistical significance fortheir NO-FAULT term meant that divorce rates were higher in states and years withno-fault divorce, there is no basis for their conclusion that the no-fault divorce lawshave caused the divorce rate to increase. A surfer and wave arrive at the beach aboutthe same time; this does not mean that the surfer created the wave. And certainlythere is no evidence that going back to fault for property awards would have anyeffect on divorce rates.

25Some of these variables are unusual. It is well known that the divorce rate varies in different regions of the UnitedStates. Rather than including a regional variable, however, Brinig and Buckley use ENTRY 5 (Year of admittance intothe Union—1788), treating the original states as having been admitted in 1789. Thus Delaware has ENTRY 5 1;California has ENTRY 5 62; Arizona has ENTRY 5 124; Alaska has ENTRY 5 171. By including ENTRY as a continuousvariable, Brinig and Buckley claim that the “frontier effect” is three times as high in Alaska as in California, and 171times as high in Alaska as in Delaware. The ENTRY variable is not even needed, because including the fixed-state effectsai in the model would adjust for the mean divorce rate of each state, and hence also adjust for regional effects. If onewanted to account for population mobility, we believe that a much better variable to examine would be immigrationto the state. The Spearman correlation coefficient between ENTRY and the average divorce rate from 1980 to 1985 is0.48; the correlation between (number of immigrants to state between 1970 and 1980)/(1970 population of state) andthe average divorce rate from 1980 to 1985 is 0.76 (omitting Louisiana and Nevada). The latter correlation isremarkably high for a social science statistic. We plan to consider its importance further in a forthcoming article.

347I.M. ELLMAN AND S.L. LOHR

TABLE 1. Dates of change in divorce law for the 50 states*

Name Incompatibility or separation Irretrievable breakdown Property division and alimony

Alabama 1971 FaultAlaska 1935 1974 1974Arizona 1973 1973Arkansas 1937 1979 1979California 1969 1969Colorado 1971 1971Connecticut 1973 FaultDelaware 1970 1974 1974Florida 1971 1986Georgia 1973 FaultHawaii 1972 1960Idaho 1971 1990Illinois 1983 1977Indiana 1973 1973Iowa 1970 1972Kansas 1969 1990Kentucky 1972 FaultLouisiana 1965 FaultMaine 1973 1985Maryland 1937 FaultMassachusetts 1975 FaultMichigan 1971 FaultMinnesota 1974 1974Mississippi 1976 FaultMissouri 1973 FaultMontana 1975 1975Nebraska 1972 1972Nevada 1931 ?New Hampshire 1971 FaultNew Jersey 1971 1980New Mexico 1973 1976New York 1966 FaultNorth Carolina 1931 FaultNorth Dakota 1971 FaultOhio 1974 FaultOklahoma 1953 1975Oregon 1971 1971Pennsylvania 1980 FaultRhode Island 1975 FaultSouth Carolina 1969 FaultSouth Dakota 1985 FaultTennessee 1977 FaultTexas 1925 1969 FaultUtah 1953 1987 1987Vermont 1941 FaultVirginia 1960 FaultWashington 1973 1973West Virginia 1977 FaultWisconsin 1969 1977 1977Wyoming 1977 Fault

*For most of the dates for change in the law for divorce grounds, we are indebted to the thorough scholarship ofKay, Herma Hill. (1987). “Equality and Difference: A Perspective on No-Fault Divorce and its Aftermath,” University ofCincinnati Law Review 56:1. We also relied on The Council of State Governments, The Book of the States, VolumesXVIII–XXIII, 1970–1981; Jacob, Herbert. (1981). Silent Revolution: The Transformation of Divorce Law in the United States,Chicago: University of Chicago Press; Ellman, supra note 8; and Sepler, supra note 28. The dates for change in the lawfor property division and alimony are generally those in Brinig and Buckley. Eight exceptions, for which we establishedthat their dates are incorrect, are: Alaska, Arkansas, Delaware, Florida, Kentucky, Maine, New Mexico, and Utah. Anannotated version of Table 1, documenting the basis for the dates that we used, is available from the authors.

348 Divorce laws and divorce rates

IV. Analysis of Divorce Rate Data

Data Sources

In analyzing the data, our goal was to see whether there were any changes in divorcerates after the enactment of a no-fault divorce law for grounds, property, or alimony, or,whether there were divorce rate changes after a change in case law that made a stateeffectively no-fault for property and alimony. A change in the divorce rate after a changein the law would not necessarily imply that the law caused the divorce rate change, butit would be consistent with a causal hypothesis. If, on the other hand, a change in lawhas no detectable effect on the divorce rate, perhaps efforts to reduce the divorce ratemight be better spent in other arenas.

We used the number of divorces per 1000 population to measure the divorce rate ineach state.26 These statistics are used for international comparisons of divorce rates andare easily obtained. It is possible that an alternative measure, the number of divorces per1000 married couples, might show slightly different long-term trends. Perhaps thedivorce rate per 1000 population is declining in the 1990s because the number ofmarried couples is also declining. But in any event, the number of divorces per 1000married couples would likely show similar short-term effects associated with changes inlaw.

In our analyses, we omitted Louisiana and Nevada. Before the widespread adoptionof no-fault grounds for divorce, Nevada provided divorces to nonresidents from faultstates through a combination of relaxed divorce grounds and short residency require-ments. It has an unusually high divorce rate for every year because its small populationmakes its divorce rate particularly sensitive to the large number of decrees granted tononresidents. It is also the only state to show a decreasing rather than increasing divorcerate between 1960 and 1980, the period during which nationwide no-fault reformsreduced advantages that a Nevada divorce offered to residents of other states. Weomitted Louisiana because of the high amount of missing data—in many years, data ondivorces in half of the state’s 64 parishes were not reported to the National Center forHealth Statistics. We included New Mexico in the graphical analyses, but note that it toohas a large amount of missing data—in 1987, for example, divorces and annulmentswere not reported for 10 of the 33 counties in New Mexico.27

The other information that we needed to examine possible changes associated withdivorce law was the dates of the changes in law for each state. State-by-state historicaldata of this kind is difficult to obtain. Changes may result from judicial decisions orstatutory amendments, and the dates of changes in state statutes are not always easilyavailable. Thus, care must be taken when classifying states by their divorce law and whenassigning a date to a change from fault to no-fault. Table 1 gives the dates that we used.As a rule, states that adopted a pure no-fault system of divorce removed fault fromconsideration in property division at the same time. States that merely added no-fault

26The sources of all data were Vital Statistics of the United States (various years), published by the National Center forHealth Statistics, and volumes of Statistical Abstract of the United States, Washington, D.C.: U.S. Government PrintingOffice.

27If the population of nonreporting areas is 10% or more of the state population in a given year, as occurred in NewMexico in 1987, Vital Statistics in the United States does not publish the divorce rate. Thus, New Mexico and Indiana bothlack data for several years. There is a question of whether the statistical analyses should include divorce rate data fromNew Mexico and Indiana, because their data are fragmentary. We included data from these states in all analysesreported in Section IV. However, we also analyzed the data without using New Mexico and Indiana, and we found thatthe omission had no important effect.

349I.M. ELLMAN AND S.L. LOHR

FIG. 1. Divorce rates per 1000 population for all states except Nevada and Louisiana, 1960 to 1992. A circlemarks the date of enactment of a law adding irremediable breakdown as grounds for divorce; a trianglemarks the data of addition of separation as grounds for divorce; and a cross (1) marks the date of changeto no-fault for property division and alimony awards. The sources for these dates are given in Table 1.

350 Divorce laws and divorce rates

FIG. 1. Continued.

351I.M. ELLMAN AND S.L. LOHR

grounds to existing fault grounds for divorce often retained fault for dividing property.When state statutes were silent on whether fault may be considered in property divisionand alimony, we relied on case law.

Looking at the Data

Much can be learned by simply plotting the divorce rates for different states over time,a technique that has been ignored in most previous work attempting to assess therelationship between divorce law and divorce rates.28 The data are plotted in Figure 1,for the period 1960 to 1992. A number of features are apparent from the plots:

1. There are large variations in the divorce rate corresponding to regions of theUnited States; consequently, any analysis of the data should incorporate the regionaldifferences in some way. Except for Florida, the states with the highest divorce rates arelocated in the western United States. These are also the states that tend to be no-faultfor property and alimony, and the states that changed to no-fault relatively early. Butthis regional disparity in divorce rates long predates modern no-fault laws. Divorce rateshave always been highest in the western states.29

2. In every state except California and New York, the divorce rate began its increasebefore the changes in the law. In California, the divorce rate rose from 4.2 per 1000population in 1969 to 5.7 per 1000 in 1970, then declined to 5.4 per 1000 in 1971.California’s divorce rate has stayed between 4.5 and 6.2 since then. Before 1966, theonly ground for divorce in New York was adultery; in 1966, the law was changed to allowdivorce after a 2-year separation (amended to a 1-year separation in 1970). The divorcerate in New York climbed steadily between 1967 and 1975, then leveled off.

In most other states, the date of change to no-fault for either grounds or for propertyand alimony seems to fall on a roughly straight line of increasing slope. The exceptionto this is in Arkansas, where divorce rates declined dramatically after the introductionof no-fault property allocation in 1979.

It is clear from the plots that changes in the divorce laws in individual states could nothave precipitated the general increase in divorce rates in the early 1970s; the divorcerates increased in all states during that time period, whether no-fault divorce wasimplemented or not. For example, one certainly cannot blame Arizona’s increase indivorce rates between 1966 and 1972 on divorce law changes, as Arizona did notbecome no-fault until 1973. It seems more plausible to think that societal forcescontributed to both the increase in divorce rates and changes in the law.

3. In several states, the year of enactment of the no-fault law exhibited a slightdepression in the divorce rate, followed by a surge the next year. We noted this patternfor California, above; it can also be seen in Arizona, Utah (with a year lag), Montana(peak followed by decrease), Wyoming, Kansas, Texas, Pennsylvania, Maine, and Con-

28We note two exceptions: Sepler, Harvey J. (1981). “Measuring the Effects of No-Fault Divorce Laws Across FiftyStates: Quantifying a Zeitgeist.” Family Law Quarterly 15:65; and Wright, Gerald C., Dorothy M. Stetson. (1978). “TheImpact of No-Fault Divorce Law Reform on Divorce in American States.” Journal of Marriage and the Family 40:575–580.Sepler plotted divorce rates through 1979 for states using a logarithmic scale. Wright and Stetson plotted adjusteddivorce rates for the states that changed their divorce law in 1971, and for California and Florida separately.

29In “Statistics of Divorce.” (1909). Journal of the American Statistical Association 11:486, 491, Joseph A. Hill noted: “Thedivorce rate is increasing in all parts of the United States; but in the East the increase is comparatively slow, while inthe West it is much more rapid, so that the two sections appear to be drawing farther apart in this respect instead ofnearer together.”

352 Divorce laws and divorce rates

necticut. A similar effect was noted in 1889 by Keller30 for divorces in France. The same“dip-followed-by-peak” pattern is seen in divorce statistics of Canada. Overall, thedivorce rate in Canada increased between 1971 and 1983. In 1984 and 1985, however,the divorce rate declined; after the Divorce Act of 1985, which made marriage break-down the only grounds for divorce in Canada, the divorce rate peaked in 1987 and thenleveled off again at 1982 levels.31 We see two possible causes for this transitory shift inthe divorce rates. First, some couples, anticipating the change in the law, may delayfiling for divorce in the last year before the legal change becomes effective. Second, ifno-fault divorces are processed more rapidly than divorces obtained under traditionalfault regimes, then the number of divorces in the years immediately after the legalchange may be swelled with several years’ worth of cases that have been in the pipeline.

This pattern has implications for statistical analyses: If it is ignored, a statisticallysignificant difference in the divorce rate may be due to this dip-followed-by-peak patternrather than to any lasting effect of the divorce law. The papers by Nakonezny et al. andBrinig and Buckley discussed in Section III ignore this pattern in their analyses; bothpapers thereby artificially inflate the contrast and the statistical significance betweenno-fault years and fault years.

An Intervention Analysis of the Data

In the plots, we identified three factors that need to be considered in a statisticalanalysis: (1) the general trend in divorce rates for all states; (2) the large regionaleffects; and (3) the “dip-followed-by-peak” pattern. A number of approaches could betaken for these data; we used an intervention analysis.32 In an intervention analysis, anARIMA model is fit to a time series (the divorce rate for a state from 1960–1992), withadditional terms included to measure the possible effect(s) of an intervention (changesin divorce law).

Because a number of states were missing data in the time series, and because thereexists dependence among states, we analyzed each state separately. This allowed us toestimate and to remove the general trend in divorce rates for a region from each timeseries, with only a small loss in efficiency. We treated each region (west, north central,south, and northeast)33 of the country separately. To look at California, then, weconsidered all states in the west except for California (and, of course, Nevada). We thenweighted the data points for the other states so that neighboring states that changedtheir divorce laws would not exert undue influence on the analysis.34 Using the

30Keller, Benjamin. (1889). “Divorces in France.” Journal of the American Statistical Association 1:469: “As a naturalresult of these laws one would expect to find an abnormal number of absolute divorces granted in the first years of theirexistence, for the statistics for those years would naturally include not only “divorces directs,” as the French call thosewhich have not been preceded by a limited divorce or separation de corps, but also a large proportion of decrees grantedto persons who had previously obtained limited divorces, and who, unless reconciled, would obviously desire to havesuch separations converted into absolute divorces,” (p. 469).

31Jane Gentleman and Evelyn Park. (1996). “Patterns of Divorce in Canada: 1970–1993.” Proceedings of the SurveyMethods Section of the Statistical Society of Canada, Ottawa, Canada, at p. 197–202. The statistics quoted here are on p. 199.

32Box, George E.P., and George, Tiao. (1975). “Intervention Analysis with Applications to Economic and Environ-mental Problems.” Journal of the American Statistical Association 70:70–79.

33The west includes states in the Pacific and Mountain regions in Figure 1; north central includes west north centraland east north central; south includes west south central, east south central, and south atlantic; northeast includes NewEngland and Middle Atlantic.

34We started with a default weight of 1. For the analysis of California, for example, we started by giving all years forArizona weight 1. But Arizona changed its law in 1973: We did not want to have the short-term impact of Arizona’s law,

353I.M. ELLMAN AND S.L. LOHR

weighted data, we employed the Super Smoother35 to estimate the regional trend indivorce rates. The smoothed trend line nonparametrically accounts for other factorssuch as unemployment, religious affiliations, or female participation in the work force,that might be thought to influence divorce rates.36 Because our interest is in possibleeffects of law, rather than in other possible determinants of divorce, this nonparametricapproach allowed us to account for other factors without explicitly identifying them. Wethen subtracted the overall trend line from the other states from the time series forCalifornia. The resulting residual series was used with the intervention analysis. Theresidual series for California is displayed in Figure 2.

Let yt represent the residual in year t. Following Box and Tiao, let P t(T) be an indicator

variable representing a pulse at time T: P t(T) 5 1 if t 5 T, and P t

(T) 5 0 if t Þ T. Similarly,let S t

(T) be an indicator variable representing a step at time T: S t(T) 5 1 if t Ä T, and S t

(T)

5 0 if t , T. We considered only intervention models with step and pulse terms for thedates of change in law, and for the year after the date of change. An ARIMA(0,1,1)

if such existed, dominating the overall trend line; we also did not want to exclude Arizona entirely from the trendestimation. As a compromise, we assigned the divorce rate in Arizona weight 0 for 1973; weight 0.2 for 1972 and 1974;weight 0.4 for 1971 and 1975; weight 0.6 for 1970 and 1976; and weight 0.8 for 1969 and 1977. By having a graduallyincreasing weight function, we avoid jumps in the smoothed trend that would result from suddenly reintroducing astate with a high average divorce rate into the data. Weights were assigned to the data from the other states in the westin a similar fashion to Arizona. In this way, we were able to estimate the trend in the overall divorce rates in the west,without depending on data from California and without relying heavily on data in years surrounding a change in thedivorce laws.

This was just one possible weighting that could be used; results of the intervention analyses were almost identicalwith different weighting schemes. In the northeast, for example, it was possible to estimate the trend line with just statesthat did not change their laws at all during the time period. In the west, however, every state changed its divorce lawbetween 1969 and 1990; if we completely excluded states that changed their laws from the trend line, we would not beable to do an analysis.

35Friedman, Jerome H. (1984). “A Variable Span Smoother.” Technical Report No. 5, Laboratory for ComputationalStatistics, Dept. of Statistics, Stanford University, California. The Super Smoother uses local cross-validation to choosethe bandwidth of the nonparametric smoother, and it is implemented in S-PLUS. See S-PLUS 4 Guide to Statistics, DataAnalysis Products Division, MathSoft, Seattle, 1997, p. 160.

36A discussion of possible factors and a literature review is given in Cameron, Sam. (1995). “A Review of EconomicResearch into Determinants of Divorce.” British Review of Economic Issues 17:1–22.

FIG. 2. Residual series for California, after removing the trend line for the western states. The peak in1970, immediately after enactment of the 1969 California Family Law Act, is apparent. Afterward,however, the divorce rate in California declined relative to the other states in the west. As in Figure 1,a circle marks the date of enactment of a law adding irremediable breakdown as grounds for divorce;a triangle marks the data of addition of separation as grounds for divorce; and a cross (1) marks thedate of change to no-fault for property division and alimony awards.

354 Divorce laws and divorce rates

model with lagged intervention term P t(1969) fit the data for California well. Letting B be

the backshift operator, i.e., Byt 5 yt21, the model we adopted for California is yt 5uBP t

(1969) 1 Nt, with an ARIMA(0,1,1) model for Nt. The maximum likelihood estimateof u was u 5 0.90, with approximate standard error 0.19 and a corresponding t-statisticof 4.72.

The model indicates a statistically significant increase in the California divorce rate in1970; other than that, there is no statistically significant change in level in the differ-enced series. The effect of no-fault divorce reform in California seems to have been apulse at 1970, with no lasting carryover. The steady decline in divorce rates in Californiarelative to the remainder of the West appears in the differencing of the series. Themodel fits well overall, but it has moderately large positive residuals in 1965 and 1984.

Space does not permit us to present models for all states in detail. Instead, we focushere on states that changed their divorce law after 1975 and on those states thatchanged to no-fault for property and spousal maintenance at a different date than theychanged to no-fault for grounds. By focusing on these states, we can examine possiblesequelae to law change by comparison with the trend in the other states in the region,which for the most part did not undergo any changes in divorce law during this period.

West. Idaho changed to no-fault for property in 1990, too recently to be able to detecta possible long-term effect of the change. In the residual series (Figure 3a), however,the relative peak in 1990 is apparent.37 The notable feature in the Utah residual series(Figure 3b) is the peak in 1989, which may or may not be related to the change in lawin 1987. The Wyoming residual series (Figure 3c) exhibits a short period of increasestarting in 1980, and then levels off. One cannot be confident that an increase in thedivorce rate is reasonably attributed to a change in the law 3 years earlier, rather thanto other confounding variables. But even if the divorce law was an important contrib-uting cause, the resulting increase was a transitory phenomenon lasting 2 years. Thepeak in 1980 also follows a period of widespread immigration into Wyoming. Wyomingexperienced a net in-migration of 85,000 people between 1970 and 1980, a numberequal to 25% of Wyoming’s 1970 population of 332,000.

South. As noted above, the Arkansas divorce rate rose precipitously in 1971, anddropped just as precipitously after 1979. As this pattern is evident from Figure 1, we donot include the plot of the residual series. A differenced time series model with anindicator variable for the years between 1971 and 1979 fits the data well. The otherstates with separate changes in law for property and grounds in the south, like Arkansas,provide no support for a hypothesis that the change to no-fault for property division andspousal maintenance increased divorce rates. Florida (Figure 3d) only shows a declinerelative to other states in the South after 1986. The residual series for Oklahoma (Figure3e) peaked in 1974, the year preceding the change to no-fault for property division.Mississippi (Figure 3f), which changed to no-fault for grounds in 1976 but retained faultfor property division and alimony, also peaked before the change in law.

37This is a difficult series to fit because it is short and has a number of prominent features; one possible model isyt 5 u1P Pt

(1971)/(1 2 dB) 1 u2P t(1990) 1 Nt, with Nt an AR(1) process. The parameter estimate (6 approximate

standard error) for u1 is 20.49 6 0.19; for d, 0.89 6 0.12; and for u2 0.41 6 0.16.

355I.M. ELLMAN AND S.L. LOHR

FIG. 3. Residual series for the states Idaho, Utah, Wyoming, Florida, Oklahoma, Mississippi, Illinois, Kansas,Maine, and New Jersey. As in Figure 1, a circle marks the date of enactment of a law adding irremediablebreakdown as grounds for divorce; a triangle marks the data of addition of separation as grounds fordivorce; and a cross (1) marks the date of change to no-fault for property division and alimony awards.Note that the vertical axes for the various states do not employ the same scale as one another.

356 Divorce laws and divorce rates

FIG. 3. Continued.

357I.M. ELLMAN AND S.L. LOHR

North Central. Figure 3g shows no reason to believe that divorce law changes in Illinois(1977 and 1983) had any affect on divorce rates. Not surprisingly, pulse or step termsin intervention models fit for Illinois are not statistically significant. Kansas (Figure 3h)shows a small (and statistically significant, regardless of other terms included in themodel) peak after the property change in 1990. However, we cannot yet tell whetherdivorce rates will restabilize at late-1980s rates. An examination of South Dakota’sdivorce rates in Figure 1 reveals little change after the adoption of no-fault divorce in1985, a trend roughly similar to that of other states in the region. Wisconsin shows nochange in the divorce rate slope after adoption of no-fault divorce in 1977, also seen inFigure 1.

Northeast. Two states in the northeast changed the law or practice for property at adifferent time than no-fault enactment. Maine (Figure 3i) exhibits no detectable effectof the 1985 change. New Jersey (Figure 3j) could be fit by a number of different timeseries models: In none of them were pulse or step terms for 1971 or 1980 statisticallysignificant.

Our analyses indicate that (1) for states changing their divorce laws in the early 1970s,the divorce rates began rising before changes in law, and (2) for states changing their lawsafter 1975, there is no evidence that the effect of the divorce law change was anythingother than transitory.

V. Conclusion

It is well known that associations can be shown between many things that have no causallink. The inclination to attribute causal connections is nonetheless often strong, par-ticularly in areas of social concern. Surely, most people believe it would be a good thingif marriages were, on average, more durable. The hope that a relatively simple changein the law could bring about such a worthwhile result tempts judgment.

But the hope does not survive a careful examination of the data. As we havedemonstrated, in almost all states divorce rates began increasing before legal changesto no-fault divorce. Those changes sometimes yielded a short-term increase in thedivorce rate of a year or two, but there is no evidence of any long-term effect. We findit far more plausible to conclude that divorce rates and divorce laws share causalinfluences. In the 1960s and 1970s, when changing cultural factors yielded more maritalinstability, pressures also rose to amend divorce laws to make divorce more accessible.In the 1980s and 1990s, the social pendulum began its return arc. Divorce rates leveledoff, then fell, and those who make and comment upon social policy now find restrictivedivorce laws more appealing than did their older brothers and sisters. Although theproponents of more restrictive laws hope to bring about societal change, the truth isthat, like their predecessors, the change they seek has already begun, and their policypreference may well be its consequence rather than its cause.

Although we believe our views on this matter are correct, we do not claim that theyare original. But it seems that as the pendulum swings they bear repeating. We beganthis paper with 100-year-old words of wisdom from Walter Willcox. We close it withcomments from a contemporary researcher:

It is unlikely that we can “explain” differences in divorce rates by the laws.Sociologists and demographers have asserted or demonstrated for some decadesthat easier divorce laws have only a small effect on the divorce rates. When such lawsare new, there is a spurt in the rates, which quickly subsides. But the secular curve,

358 Divorce laws and divorce rates

or the long-term trend, which smooths out any temporary pips or declines (as in awar or depression), will show a steady rise.

I believe, nevertheless, that we can perceive the effects of legal changes evenwhen they are not major. The key relationship is this. Both the rise in divorce ratesand the laws come from the same source, changing values and norms in the largersociety, alterations in economic opportunities, political ideologies, even the modelspresented by the mass media. Under any legal system, some people try to leave theirmarriages under the existing laws, but many will also press toward new laws withfewer restrictions. If some barriers are removed, some people get divorced whowould not have done so before. But if the deeper social forces that drive bothactions become stronger, then still other people will try to dissolve their unionsunder restrictions they now consider hard, and some will work toward even fewerbarriers. At times, the legal barriers hold for rather long periods against muchpolitical pressure, but then people become more ingenious in working out ways ofbreaking out of their unions.38

38Goode, William J. (1993). World Changes in Divorce Patterns, New Haven: Yale University Press, p. 322.

359I.M. ELLMAN AND S.L. LOHR