measuring fertility demand

Demography, Vol. 32, No. I, February 1995

Measuring Fertility Demand*

Elizabeth ThomsonYvonne Brandreth

Department of Sociology andCenter for Demography and Ecology1180 Observatory DriveUniversity of Wisconsin-MadisonMadison, WI 53706

We propose a multidimensional conceptualization of fertility demand and evaluatepotential measures of each dimension, using data from a telephone survey ofWisconsin residents age 18-34. Most of the measures met tests for interval-levelmeasurement; all produced high estimates of test-retest reliability. We found supportfor only two dimensions of demand, intensity and certainty; potential measures ofcentrality had relatively low associations with any of the latent dimensions. Demandcertainty improved prediction of fertility expectations beyond a trichotomous (yes,no, don't know) measure, but demand intensity did not. We found mixed evidence forthe conceptualization of fertility demand as a single continuum on which desire toavoid pregnancy is the opposite of desire to have a child.

The demand for children is central to all theories and predictive models of fertilitybehavior or outcomes. As contraceptive failure declined, sterilization increased, and newtreatments for infertility emerged, it appeared that the gap between fertility demand andactual births would shrink. Instead we find recent increases in unplanned births (Williams1991), and little improvement in the predictive power of fertility desires or fertilityintentions. We believe that gaps between fertility demand and actual births reflect limitedconceptualization and measurement of demand. With better measures, we can obtain muchmore accurate predictions-as 'well as clearer understandings-of future fertility.

In this paper we propose and test a multidimensional model of fertility demand, usingmeasures developed for telephone interviews. Data from a random sample of persons age18-34 are used to evaluate fundamental properties of measurement (equal intervals,test-retest reliability), to test the multidimensional model, and to examine the assumptionthat the desire to have a child and the desire to avoid pregnancy form two ends of a singlecontinuum.

* This research was supported by Grant HD23898 and Center Grant HD05876 from the Center for PopulationResearch, National Institute for Child Health and Human Development. We thank Nora Cate Schaeffer. whocodirected the Wisconsin Fertility Motivation Survey, for suggestions and comments, and Mary Lou Brady. theWFMS survey coordinator, for data quality.

Copyright © 1995 Population Association of America

81

82 Demography, Vol. 32, No.1, February 1995

AVAILABLE MEASURES OF FERTILITY DEMAND

Fertility demand traditionally has been measured with questions about ideal, desired,intended, or expected births. McClelland's (1983) review concluded that prospectivefamily-size desires are the most appropriate measures of fertility demand. Ideal family sizeis linked more closely to fertility norms than to personal preferences (Clay and Zuiches1980); intended or expected births reflect the combined effect of fertility demand andsituational constraints on achieving desired fertility.

Prospective family size desires provide some information about demand forparity-specific births. Women who want three children, for example, may have strongerdesires for the second birth than women who want only two children. Such information,however, does not tell us about variations in strength of desires among those who want thesame number of children.

Two types of scales, the IN-Scale and various forms of expectancy-value scales, havebeen developed to measure fertility demand more precisely. The IN-Scale (Coombs,Coombs, and McClelland 1975) is constructed from choices between pairs of family sizes orbetween combinations of family size and sex composition. This scale explains additionalvariance in fertility behaviors beyond that explained by desired family size or by social,economic, and demographic characteristics (Coombs 1974), but is not parity-specific.

Expectancy-value scales are based on the benefits and costs of having or not havingchildren (Fawcett 1983). Scales are constructed by summing the products of evaluations andsubjective probabilities for relatively long lists of possible child-related outcomes (e.g.,marital quality, economic well-being), and usually are focused on the next birth.Expectancy-value scales are associated strongly with single-item measures of fertilitydesires, intentions, and behaviors (e.g., Davidson and Jaccard 1975), but they requirerelatively long segments of interview time. In addition, they may tap only conscious fertilitymotives or socially acceptable reasons for having or not having children, and may misselements of desire based on unconscious motives or emotions.

Both the IN-scale and the expectancy-value scales assume that the strength of desire fora child falls along a single continuum. Although our ultimate goal is to simplify measures offertility demand, we propose a more complex conceptualization of the latent construct.Fertility desires can be viewed as a type of attitude; Raden (1985) argues for amultidimensional conceptualization of attitude strength. His theoretical discussion and ourearlier empirical work (Schaeffer and Thomson 1992) suggest three dimensions of fertilitydemand: intensity, centrality, and certainty.

Intensity may be closest to 'the concept of attitude strength. Schuman and Presser(1981), however, suggest that respondents find it easier to claim intense feelings thanfeelings with other properties resembling strength, so intensity may not be the most accuratepredictor of long-range behavior or outcomes. Intensity also may reflect individual variationin emotionality rather than strength of demand; some people may feel more intensely thanothers about everything they want to do, but still will be constrained by choices amongalternatives and therefore will be no more likely to translate intense feelings into behaviorsthan people whose feelings are less intense.

Centrality denotes strength of fertility desires in comparison with other life goals. Themeasurement problem is to determine the appropriate universe of goals within which someare more central than others. Theoretical discussions (e.g., Converse 1970) suggest thatcentrality should be assessed in relation to a relatively stable standard, the self. That is,centrality is the importance of a goal for achieving or avoiding "possible selves" (Cantor etaI. 1986).

Certainty reflects the extent to which a person knows how she feels or what she wants.Desires held with certainty should be relatively stable, not subject to much change by

Measuring Fertility Demand 83

ordinary variations in daily experience. Respondents should find it easy to report suchdesires during an interview; uncertainty about desires may cause random measurement erroror nonresponse. We emphasize that certainty about desires is not the same thing as certaintyabout plans or about the likelihood of achieving desires. The two types of certainty may belinked, however; those who are less certain about what they want may also be less certainabout what they will do, or what will happen to them.

Another issue of dimensionality is raised by Miller's (1986) concept of proception,which he argues is more than the absence of contraception. Most measures of fertilitydemand assume a continuum, with those who do not want a child at one end and those whodo so at the other (e.g., Beach et al. 1982). Other measures simply ignore possible variationin desire not to have a child, assigning to all who do not want a child the same (lowest)score on a continuum of desire for a child. We consider the possibility that proceptivedesires are not simply the opposite of contraceptive desires.

However simple or complex, measures of fertility demand generally are not evaluatedrigorously. Almost all analyses of fertility-demand measures assume but do not testinterval-level measurement. (For an exception, see Morgan 1985.) Most studies reportinteritem reliability for multiple-indicator scales; a few provide information on test-retestreliability. No studies have considered the multidimensional or dual-continuum hypothesesdiscussed above.

THE WISCONSIN FERTILITY MOTIVATION SURVEY

The structured survey questions we examined were developed through a series ofunstructured and semistructured interviews with small samples of adults age 18-34,stratified on marital and parental status (Schaeffer and Thomson 1992). Respondents wereselected through random-digit dialing of Madison and Milwaukee (Wisconsin) telephoneexchanges. These interviews provided words and phrases from everyday language todescribe the desire to have children or the desire to avoid pregnancy.

We conducted structured telephone interviews in 1989-1990 with a random sample of543 Wisconsin residents age 18-34, also stratified by marital and parental status andidentified through random-digit dialing. The sampling method produced an estimatedresponse rate of 55 %. We also estimated response rates for separate "batches" used tostratify the sample; these rates varied within five percentage points. Therefore nonresponsedid not appear to be associated strongly with the stratifying criteria, namely marital andparental status. Spouses of'.married respondents were asked to participate in a parallelinterview, conducted in most cases immediately after the interview with the primaryrespondent. The response rate for spouses was 86 % and produced 250 spouse interviews.Individuals or couples reporting pregnancy or sterilization were excluded from the analysesreported below. The maximum analytic sample size is 412 primary respondents; for theinterval-measurement tests, we added responses from 128 spouses.

We conducted a one-month follow-up survey with a randomly selected subset ofprimary respondents, in which measures of fertility demand were repeated. The responserate for this survey was 88 percent of the random sample, resulting in 212 follow-upinterviews. We included 163 of those respondents in the analytic sample; persons reportingpregnancies or sterilizations were excluded.

We constructed measures of fertility demand from the three sets of questions shown inthe appendix. (The question about birth expectation at the end of the appendix is ourpredictive validity criterion.) Each measure varies from the most extreme response in thedirection of not wanting a child to the most extreme response in the direction of wanting achild. Our analyses explicitly test this single-continuum specification of demand. For some


analyses we divide each measure into two, one representing the desire to have a child, andthe other the desire to avoid a birth.

We constructed two intensity measures from responses to the first set of questions inthe appendix. Before asking whether they wanted a child, we asked all respondents to ratehaving a child and not having a child by feelings of happiness and satisfaction, ranging from-3 (very unhappy, dissatisfied) to +3 (very happy, satisfied). We subtracted each response(happy, satisfied) about not having a child from the parallel response about having a child.The resulting scales theoretically range from -6 to + 6; higher scores represent more intensedesires for a child.

Our key measure of centrality was derived from the next set of questions. After askingwhether the respondent wanted a child, we asked about changes in self-concept that mightbe associated with having or not having a child. The questions are listed in the appendix,along with the five words used to describe self changes. Responses scored + 1 were "morefulfilled," "less selfish," "more responsible," "more masculine" and "less feminine" (formales), and "less masculine" and "more feminine" (for females). The opposite changesreceived scores of -1; "no difference" was scored o. Distributions of responses for thesequestions were consistent with the value we assigned to each quality. For example, only ahandful of respondents said that having a child would make them feel less fulfilled, moreselfish, or less responsible, or that not having a child would make them feel more fulfilledor less selfish. Most respondents said that both outcomes would result in no change in theirmasculine or feminine qualities; the most frequent report of expected change was amongwomen (about one-third) who believed they would be more feminine if they had a child. Wesummed scores for having a child and subtracted scores for not having a child. The resultingscales theoretically range from -10 to + 10; higher scores represent positive perceptions ofself-concept associated with having a child.

The third set of questions ("feeling modifiers" in the appendix) produced potentialmeasures of intensity ("strong" feelings), centrality ("important" feelings), and certainty("sure," "mixed," and "changing" feelings). These responses differ from those describedabove in that they were provided only in one direction: those who wanted a child (or werenot sure) rated their desire for a child; those who did not want a child rated their desire notto have a child. We scored ratings for not having a child in negative numbers, placing themon the opposite side of the scale from ratings by those who wanted a child. For example, themeasure for "strong" feelings is scored from very strong feelings about not wanting a child(-4) to very strong feelings about wanting a child (+4). The middle positions are "not atall" strong feelings in each direction (-1 for not having a child, + 1 for having a child).

ANALYSIS AND RESULTS

Table 1 presents descriptive statistics for the happiness, satisfaction, and self-changemeasures. Most respondents had positive scores because about three-quarters wanted tohave a child. We found slightly larger proportions of respondents than expected at multiplesof 3 or -3 on happiness and satisfaction, reflecting preferences for extreme (-3, +3) ormiddle (0) positions on the original ratings. Likewise, the large proportion at 0 on theself-change measure reflects high proportions of "no difference" responses to the originalquestions, especially for changes associated with not having a child. These distributionscould reflect respondent bias, but also may reflect the nature of fertility demand. Becausethe birth of a child is a major life event, people may express only moderate feelings untilthey decide whether or not to have a child. At that point, when anticipating the outcome(birth or no birth), their feelings may become stronger in the direction of their decision.

Table 2 presents distributions of responses to feeling modifiers, from the most extreme

Measuring Fertility Demand

Table 1. Fertility Demand Measures, Have versus Not Have a Child

Response: Have a Child-Not Have a Child

85

Score Happiness Satisfaction Self-Change"

-6 3.5% 3.2% 0.0%-5 0.5 1.5 0.0-4 1.2 0.2 0.2-3 5.2 5.0 0.5-2 2.5 2.2 0.2-I 2.5 3.7 4.9

0 12.3 13.4 21.4I 6.2 4.7 15.52 9.1 10.2 15.23 17.8 18.4 16.74 10.4 11.9 13.35 9.6 6.0 7.46 19.3 19.4 4.7

Valid Cases 405 402 407Source: Wisconsin Fertility Motivation Survey, 1989-1990. Respondents able to have children.

(wife) not pregnant.a Theoretical range -10 to + 10; observed range -4 to +8; values 6-8 combined for this table.

responses for not wanting a child (top) to the most extreme responses for wanting a child(bottom). Extreme responses to these questions were not uniformly more popular than otherresponses; nor were the weakest responses, closest to a true midpoint, chosen frequently.The difference between these distributions and those for the happiness, satisfaction, andself-change measures suggests that bias toward extreme responses may contribute to thedistributions we see in Table 1. Yet the proportion of respondents at the midpoint on feelingmodifiers could be low because we did not ask respondents how strong, important, sure,mixed, and changing were their feelings about both alternatives (having and not having achild). Had we done so, respondents who did not want a child (for example) probably wouldhave chosen the weakest response for feelings in the opposite direction (e.g., "not at allstrong" feelings about having a child), and we would have seen considerable lumping at the"neutral" or near-neutral points of these measures.

Interval Measurement

The first question we asked is whether the constructed measures can be assumed to beinterval. Interval-level measures offer considerable flexibility in choice of analytic methods.Tests of interval measurement also provide a strong test of the hypothesis that demand for achild is the opposite of demand not to have a child. Interval measurement implies, forexample, that the conceptual distance between moderately sure and very sure desires to haveno (more) children is the same as the distance between moderately sure and very sure desiresto have a(nother) child. This test is strong because it also forces the distance betweenslightly sure and moderately sure desires in either direction to be the same as that betweenmoderately sure and very sure desires. If we reject interval measurement for the full scale,our rejection could be due to unequal distances between pairs of responses on each side of

Tab

le2.

Fert

ility

Dem

and

Mea

sure

s,R

espo

nses

Con

tinge

nton

Dir

ectio

n

Feel

ing

Mod

ifie

rs

Str

ong,

Impo

rtan

tSu

reM

ixed

Des

ire

Not

toH

ave

aC

hild

Ver

y9.

8%6.

1%13

.7%

Mod

erat

ely

9.3

8.5

7.3

Onl

ypo

sitiv

e5.

1%Sl

ight

ly/A

little

a2.

75.

11.

2M

ostly

posi

tive

12.2

Not

atal

l1.

02.

90.

7Po

sitiv

e,ne

gativ

e5.

4D

esir

eto

Hav

ea

Chi

ldN

otat

all

3.4

3.6

5.4

Posi

tive,

nega

tive

16.1

Slig

htly

/Alit

tle"

10.5

11.9

7.8

Mos

tlypo

sitiv

e40

.6M

oder

atel

y33

.337

.521

.7O

nly

posi

tive

20.7

Ver

y29

.924

.342

.2V

alid

Cas

es40

841

141

041

1So

urce

:W

isco

nsin

Fert

ility

Mot

ivat

ion

Surv

ey,

1989

-199

0.R

espo

nden

tsab

leto

have

child

ren,

(wif

e)no

tpr

egna

nt.

aM

odif

ier

for

"str

ong"

feel

ings

.

~

Cha

ngin

g

Not

atal

l19

.1%

Mon

thly

2.2

Wee

kly

1.2

Dai

ly0.

50 ~

Dai

ly4.

73 Q

Wee

kly

7.8

IICI

"'l

Mon

thly

13.2

= "C:lN

otat

all

51.2

=- ~40

8-< ~ ~ r- Z ? :- ~ ~ 0

-"'l = ="'l ~ ... ~ ~


the scale (e.g., the distance from slightly to moderately is not the same as from moderatelyto very) rather than to misspecification of demand along a single continuum.

To check the latter possibility, we also attempted to test interval measurement for eachside of our constructed measures. Suppose responses on the side of wanting a child wereinterval, and those on the side of not wanting a child were interval, but the combinedresponses were not. Consequently the distance between corresponding points on oppositesides of the scale would not be twice the distance from each point to the middle. Such aresult could occur if we distorted the meaning of responses about having children and nothaving children by forcing them to take opposite values.

We examined the interval properties of fertility demand measures using log-linearmodels presented by Goodman (1979) and Clogg (1984). Briefly, these models are based oncross-classifications of each measure with an instrumental variable known to be associatedwith the latent construct, fertility demand. The saturated model includes a differentassociation parameter for each cell of the table. By placing equality constraints onassociation parameters for different response categories (e.g., very, moderately, slightly, notat all sure), we can test the assumption of equal distances between categories-that is,interval-level measurement.

We specified tests of interval-level measurement under various conditions. Becausethese tests depend on the strength of instrumental variable effects, we used two differentinstrumental variables, age (l8~23, 24-29, 30-34) and parity (no children, one child, twoor more children), in parallel tests. We considered the possibility that underlying effects ofage or parity, or the measurement parameters themselves, differed by respondent's sex. Wealso varied the assumptions about the nature of age and parity effects on fertility demand.(These analyses excluded single parents because single parenthood might interact with ageor parity effects on fertility demand.) To provide sufficient cases in each cell of the tables,we included spouse respondents. Interval measurement tests were based on a maximumsample of 453 respondents, of whom 128 were spouses.

The augmented sample produced essentially the same distributions for demandmeasures as those shown in Tables 1 and 2. Even with spouse responses, however, it wasnecessary to combine responses at the tail ends of the distributions to obtain convergence forsome models. Thus tests for equal intervals are less exact than if we had enough cases tocross-classify each possible score by respondent's age or parity. (Cross-classifications andgoodness-of-fit statistics for all models are available on request.)

Results of these tests were remarkably consistent across variations in the instrumentalvariable (age or parity), respondent's sex, and assumptions about other aspects of themodel. The first column of Table 3 provides a summary of test results. Happiness,satisfaction, and self-change scores all passed the interval-measure test. As a result, theyalso passed the stronger test of a single continuum running from the most extreme feelingsabout not having a child to the most extreme feelings about having a child. Among thefeeling modifiers, however, only the sure and the mixed measures passed the test; modelsspecifying unequal intervals for strong, important, and changing feelings fit significantlybetter than the equal-interval models.

As noted above, rejection of equal intervals could arise from forcing feelings abouthaving a child to be opposite to feelings about not having a child, rather than from unequaldistances on each side of the measure. Therefore we tested for interval measurement ofstrong, important, and changing feelings about having a child. Strong and importantfeelings about having a child passed the test. We could not test interval measurement forchanging feelings; within the restricted range of wanting a child, the measure was notassociated significantly with age or parity. (Recall that tests of interval measurement dependon the strength of instrumental variable effects.) We also could not test for interval


Table 3. Interval Measurement and Test-Retest Reliability

. MeasureIntervalLevel"

Cronbach'sAlpha"

.85

.80

.78

YesYesYes

Happiness ScaleSatisfaction ScaleSelf-Change ScaleFeeling Modifiers

Strong No" .94Important Noc .90Sure Yes .95Mixed Yes .92Changing No .91

Birth Expectation No .73

Source: Wisconsin Fertility Motivation Survey, 1989-1990; respondents able to have children,(wife) not pregnant.

a Single parents excluded; spouse respondents included; valid responses vary from 442 to 454.b Primary respondents selected randomly for one-month follow-up; valid responses vary from

157 to 159.C Responses on the "want child" side of the scale passed the interval-measurement test.

measurement on the "no child" side of each measure because the number of cases wasinsufficient for full cross-classification.

Taken together, these tests provide moderate support for interval-level measurement.They also provide moderate support for the single-continuum hypothesis because severalsingle-continuum measures passed the interval test. Yet because some measures did not passthe interval measurement test, we conducted our subsequent analyses under assumptions ofordinal as well as interval measurement, and under assumptions of two continua as well asone continuum of fertility demand.

Reliability

Among primary respondents who completed the one-month follow-up interview, 27 %reported different desired family- sizes across interviews; only 7 % (n = 11) changed fromwanting a child to not wanting a child, or vice versa. The Pearson product-momentcorrelation between the two responses was .90.

We compared the product-moment correlation, which assumes interval measurementand linear association, with the polychoric correlation between each measure at the originaland the one-month follow-up survey. The polychoric correlations were slightly larger thanthe product-moment correlations, but were consistent with them. The second column inTable 3 therefore reports Cronbach's alpha as the estimate of test-retest reliability for eachmeasure.

Reliability estimates were reasonable for subjective phenomena that may have changedover a month's time. Happiness and satisfaction measures produced estimates above .8;self-change, just below that level. All of the feeling modifiers had reliability estimatesabove .9. The lowest reliability was estimated for the birth expectation measure (likelihoodof having a child), at .73. Birth expectations may be subject to more real change over aone-month period, in view of changing life circumstances, than are fertility desires; thus thereliability estimate for the likelihood rating is biased downward.


Dimensionality

89

To test our three-dimensional conceptualization of fertility demand (intensity, certainty,centrality), we estimated confirmatory factor models with data from primary respondents atthe initial interview. We tested models under assumptions of ordinal measurement, wherepossible. The asymptotic covariance matrix was generated with PRELIS (Joreskog andSorbom 1988), and we used LISREL 7 (Joreskog and Sorbom 1989) to produce weightedleast squares parameter estimates and goodness-of-fit statistics for each model.

We estimated separate models for "want child" measures and for "not want child"measures, as well as for the combined measures that specify a single continuum of fertilitydemand. Because the feeling modifiers were measured only in the direction of therespondent's goal, analyses of "want child" measures were limited to those who wanted achild, and analyses of "not want child" measures to those who did not. The latter set ofanalyses was based on fewer than 100 cases, and models using weighted least squares didnot converge. Thus we also estimated each set of models under the interval-measurementassumption, using maximum likelihood. All tests produced essentially the same results. Weview this finding as indirect support for the single-continuum hypothesis. The patterns ofassociations among measures were very similar in each direction of fertility demand; thecombined measure (want versus not want a child) produced the same pattern with strongerassociations than each subset. This is what ought to happen if each side of a particularmeasure represents a truncated section of a single underlying continuum.

In preliminary analyses, we found that "strong" feelings did not load on an intensityfactor with happiness and satisfaction, but on the same factor as measures of demandcertainty. Therefore we were left with only two intensity measures, as well as two centralitymeasures.

We tested four models of fertility" demand for each set of measures: want a child, notwant a child, want versus not want a child. (Goodness-of-fit statistics and parameterestimates are available on request.) Model I specified one factor with eight measures.ModellA also specified a single factor, but included correlations between disturbance termsfor measures with similar response formats (happiness and satisfaction; strong, sure, andimportant feelings). Although Model IA fit significantly better than Model I, thedisturbance correlations were much larger than expected: almost half of the total associationbetween happiness and satisfaction scores was attributed to the disturbance correlation ratherthan to the underlying latent factor.

Model 2 specified two factors: the happiness and satisfaction measures constituteintensity, and the remaining-measures reflect a combined centrality/certainty factor. Thetwo-factor model fit significantly better than Model I, and the latent factors explained moreof the observed variance in happiness and satisfaction than did Model IA. The last model(Model 3) represented our three-factor specification of fertility demand: intensity(happiness, satisfaction), centrality (self-change, important feelings), and certainty (strong,sure, mixed, and changing feelings). This model did not fit significantly better than Model2. Two measures had much lower factor loadings than others representing the same factor:self-change representing centrality, and changing feelings representing certainty. Weexcluded these measures from the covariance matrix and retested each model, with virtuallyidentical results.

On the basis of these analyses, we constructed scales for only two dimensions offertility demand, intensity and certainty. Each scale is scored so that the most intense ormost certain desires not to have a child have negative values, with parallel positive valuesfor the most intense or most certain desires to have a child. We also separated the two endsof each scale for further tests of the single-continuum hypothesis. The intensity scale is theaverage of the happiness and satisfaction measures (alpha = .94). We constructed a


certainty scale from the average of mixed, strong, and sure feelings; this gives a slightlylower weight to "only positive" feelings than to "very" strong or sure feelings (alpha =.96). (We obtained virtually identical results when we included importance ratings in thecertainty measure.)

Construct and Predictive Validity

Table 4 presents mean scale scores for each dimension of fertility demand in relation tothe respondent's first response to the question about wanting a child (no, maybe or don'tknow, yes). For the intensity scores, which were not contingent on those responses, personswho did not want a child had negative scores on average, those who wanted a child or werenot sure had positive scores. Those who did not want a child appear to feel less intenselythan those who did because the absolute value of their mean score is smaller. Uncertainrespondents have intensity scores between the "no" and the "yes" respondents, but arecloser to the latter group.

We constructed the certainty scale to be positive for the "maybe, don't know" and the"yes" groups, and negative for those who did not want a child. We found that the meanscores were approximately equal and opposite for those who said "yes" and those who said"no" about wanting a child. As expected, those who gave an uncertain response abouthaving a child had lower scores on the certainty scale than those who said "yes." Even so,their scores were well above the minimum (1.0) on the "want child" side of the scale.

To further test construct and predictive validity, we estimated structural models offertility expectations (likelihood rating) using ordinary least squares regression. Thesemodels were estimated with and without exogenous characteristics such as age, parity,marital status, education, and Catholic religion, with virtually identical results. Althoughexogenous variables explained statistically significant variation in fertility demand andexpectations, they explained no unique variation in expectations, net of demand. This resultsupports the validity of the scales because demand should be associated strongly with suchcharacteristics and should mediate most of their effects on fertility expectations in a contextof relatively high fertility control.

As shown in Table 5, we first estimated a model using only the initial responses about

Table 4. Demand Strength by Direction (WantINot Want a Child)

Initial Response

Strength Measure

IntensityMeanSDValid cases

CertaintyMeanSDValid cases

No Child

-1.422.84

86

-2.900.60

92

Maybe

1.671.489

2.190.679

Child

3.382.16

304

2.870.65

304

Note: Intensity responses scored -6 to +6 for all respondents; certainty scores constructed to benegative for respondents who do not want a child (-3.67 to -1), positive for those who "maybe" or dowant a child (l to 3.67).

Source: Wisconsin Fertility Motivation Survey, 1989-1990; respondents able to have children,(wife) not pregnant.


Table 5. Fertility Demand and Fertility Expectations

DirectionModel

91

StrengthModel

Demand DirectionNo childMaybe

Child

Demand Strength(child vs. no child)Intensity

Certainty

Constant

Adjusted R2

1.50**(.42)

2.18**(.15)

1.61**(.13).36**

-2.13**(.63)

-1.97**(.56)

.02(.03).70**(.11)

3.68**(.31).46**

Note: Listwise present N = 394.Source: Wisconsin Fertility Motivation Survey, 1989-1990; respondents able to have children,

(wife) not pregnant.** p < .01.

having another child: dummy variables for wanting a child and for those who said "maybe"or "don't know" versus the omitted category of not wanting a child. Distinguishinguncertain from "yes" responses significantly increased the explained variance in fertilityexpectations. The coefficients translate into a predicted likelihood score between 1 and 2 forthose who did not want a child; those who wanted a child were predicted to have a score of3.9, well below the maximum possible score of 5. The coefficient for the small number ofrespondents who were uncertain about wanting future births put them closer to those whowanted a child than to those who did not, with a predicted score of 3.1; this is remarkablyclose to the value labeled "50-50 chance."

As shown in the second column of Table 5, intensity and certainty measuressignificantly increased the explained variance in fertility expectations, beyond thatexplained by initial responses about having a child. Only certainty, however, had astatistically significant coefficient. The dummy variables representing initial responsescontinued to have statistically significant effects, and together added significant incrementalexplained variance to that explained by intensity and certainty. The coefficients for thedummy variables became negative because of the scoring of intensity and certainty. Forexample, those who wanted or "maybe" wanted a child were assigned positive scores oncertainty indicators, those who did not want a child were assigned negative scores, and theminimum difference between the two groups was 2 (+ 1 for uncertain desires to have achild, -1 for uncertainty about not having a child). Multiplying this minimum difference bythe regression coefficient (.70) produces a minimum predicted difference in birth likelihoodof 1.40 between those who want (or maybe want) a child and those who do not. Thisdifference almost counterbalances the negative coefficients for the dummy variables (-2.13,-1.97). The small difference between the coefficients for the two dummy variables in thestrength model shows that differences in demand intensity and certainty capture all of the


difference in expectations between those who initially said "yes" and those who said"maybe" or did not know whether they wanted a child.

The implications of these coefficients are shown more clearly in Figure I, where wepresent predicted fertility expectation scores by direction and level of intensity and certainty.The horizontal axis ranges from the most intense and most certain desires not to have achild, at the left, to the most intense and most certain desires for a child, at the right. Thediscontinuity between the lines is produced by the net negative coefficients for the dummyvariables in the strength model. Respondents with the most intense and most certain feelingsabout not wanting a child were predicted to have the lowest possible likelihood score (1 ="very unlikely" have a child); low intensity and uncertainty about not having a childincreased the likelihood to almost 3, "50-50 chance." Among those who wanted a child,low-intensity or uncertain feelings predicted expectations below the 50-50 chance of havinga child; those with the most intense and most certain feelings were predicted to haveexpectations close, but not quite equal, to the maximum likelihood for having a child.Predictions for those who first said they were uncertain about wanting a child were veryclose to those for respondents who said "yes," given the same level of intensity andcertainty. We did not predict birth expectations for high intensity or certainty scores amongthose who were uncertain whether they wanted a child; such respondents are unlikely toexpress the most extreme feelings about having a child, and in this sample, they did not.

Although predicted values for low-strength desires to avoid a birth are greater thanthose for low-strength desires to have a child, the differences are not great. The underlyingrelationship between strength of desire and likelihood of birth may be relatively flat at lowlevels of strength, with accelerating gaps in likelihood as demand strength increases (seeBeach et al. 1982). On the other hand, the predicted discontinuity rests almost entirely onthe the assumption that our certainty measure is interval, and that we have scoredappropriately the distance between weak desires for a child and weak desires not to have achild.

The regression estimates in Table 5 constrain the effect of intensity and certainty to bethe same for wanting and not wanting a child, specify fertility demand as a single

Very Likely 5 ,...-------------------------,

.......................................................................................................................; ..: .

....:> ....................................................................................., , .

:';';';'~'~'-;-;~'.

2

4

Very Unlikely 1

50/50 Chance 3

Not Want Child Want ChildStrength of Desire to Have/Avoid Birth

Source: Wisconsin Fertility Motivation Survey. Respondents able to have children; (wife) not pregnant: listwiseN=394.

Figure I. Predicted Likelihood, Having A(nother) Child


continuum, and result in the parallel slopes in Figure 1. To test this assumption once more,we specified interactions between the direction of demand (child, no child) and the intensityand certainty scales. If effects of demand for a child are not equal and opposite to effects ofdemand for not having a child, the two sides of the scale may have meanings that are notequal and opposite. We did not find statistically significant interactions. A single coefficientfor each dimension, consistent with the conceptualization of demand as a single continuum,represents effects of demand on fertility expectations.

DISCUSSION AND CONCLUSIONS

Our analyses demonstrate that small improvements in the measurement of fertilitydemand can substantially improve prediction of expected fertility. (Predictions ofsubsequent births depend, of course, on the link between expected and achieved fertility.)Several of the measures we analyzed passed tests of interval measurement and producedreasonable test-retest reliability estimates; thus they are strong candidates for future use intelephone or mail surveys.

We hypothesized that fertility demand might have more than one dimension. We foundthe greatest support-and the greatest predictive validity-for the dimension we labeled"certainty." We emphasize that demand certainty is not the same concept as certainty aboutfertility outcomes. The unstructured interviews revealed a clear difference between thesetwo forms of certainty (Schaeffer and Thomson 1992), and our structured questions refermostly to feelings or preferences, not to expected or intended births. Although we wouldalso recommend that fertility expectations or intentions be measured with a certainty scale(as in our analysis), it is an empirical question whether such measures would accountcompletely for effects of demand certainty on births.

At this point, the questions about strong and sure feelings seem to be better measuresof demand certainty than those on mixed or changing feelings. The former questions havebeen used more commonly in surveys of subjective phenomena, and the adverb modifiers(e.g., very, moderately) were selected from words that have been shown to representapproximately equal distances (Bass, Cascio, and O'Connor 1974). Questions about mixedand changing feelings, on the other hand, were developed from the unstructured andsemistructured interviews preceding the telephone survey; they require modification andfurther testing before we can recommend their use. We do not think that strong or surefeelings can substitute for the type of uncertainty-ambivalence-captured by thesedescriptors (Schaeffer and Thomson 1992). Perhaps adding a fourth response category to thethree degrees of mixed feelings would increase associations between this measure and othermeasures of demand certainty. The indicator of changing feelings might be improved byusing relative rather than absolute quantifiers (e.g., all the time, most of the time, about halfthe time) or different absolute timing references.

The hypothetical dimension of demand intensity was represented only by the happinessand satisfaction measures. Tests of confirmatory factor models discounted the hypothesisthat common response scales rather than a single latent variable accounted for theassociation between the two measures, but we would be more confident about finding anintensity dimension if we had found measures with different response scales loading on theintensity factor. The fact that intensity was not associated significantly with fertilityexpectations is consistent with Schuman's and Presser's (1981) assertion that intensefeelings are easy to claim and therefore are less likely to be translated into expectations oraction than are other types of attitude strength.

We are not sure, however, that "happy" and "satisfied" are the best measures ofintensity. The original ratings seemed to pose problems for some respondents, particularly


in reference to not having a child. Substantial proportions of respondents had scores on thepositive side of happiness or satisfaction with having a child, even though they reportedsubsequently that they did not want a child. Such inconsistencies were much less commonfor those who wanted a child; almost all had given negative responses to the possibility ofnot having a child. Perhaps a hypothetical birth is viewed in the same way as an actual birththat was not wanted or intended; respondents may be as unwilling to express unhappiness ordissatisfaction with a hypothetical child as with a child already born.

We were unable to demonstrate the existence of demand centrality. We continue tobelieve, however, that fertility demand is linked to self-concepts, and that further effortsshould be made to develop centrality measures and to determine whether this dimension canbe distinguished from intensity and certainty. In retrospect, the questions on self-change didnot allow for sufficient variation in the degree of change associated with having or nothaving a child. We should also consider alternative self-descriptors. Even though the termswe used were derived from unstructured interviews with similar respondents, surveys on thevalue of children may suggest additional or alternative terms. Finally, it may not make senseto ask respondents about self-changes associated with not having a child; we found thatrespondents had more difficulty answering these questions and were much more likely toreport no change than when they considered self-descriptors associated with having a child.Because not having a child is maintaining the status quo, we may need some other way ofspecifying possible selves associated with having no (more) children.

A central question that we attempted to answer is whether any dimension of fertilitydemand can be specified as a continuum with desire to avoid pregnancy at one end anddesire to have a child at the other. Our findings on this point are mixed. Two constructedmeasures forcing these desires to be at opposite ends (strong feelings and important feelings)did not pass tests for interval measurement. This evidence would be more compelling if wehad found that intervals on each side of these measures were equal. Although the "wantchild" side of each measure passed interval measurement tests, we had too few cases on the"not want child" side to conduct parallel tests.

The confirmatory factor and predictive validity analyses, on the other hand, supportedthe conceptualization of a continuum with desire to avoid births at one end and desire tohave a child at the other. Measures constructed along a single continuum produced the samefactor structure as measures limited to either side of the continuum. Also, intensity andcertainty of demand had effects of the same size on fertility expectations among respondentswho wanted and among respondents who did not want a child. We advise including parallelquestions with each goal (child, no child) as the stimulus in fertility surveys. Such responsescan be reverse scored (as in-our analysis) and used to make fertility demand measures morereliable, and they may provide further evidence for distinguishing two continua of fertilitydemand.

Several of the measures in this analysis are used commonly in large-scale surveys, andsome are relatively new. Most offer much more precision in measuring fertility demand thandoes desired number of additional births. Several appear to be interval, and thus appropriatefor linear models estimated with ordinary least squares methods. Because they come fromrespondents' own words describing feelings about having and not having children, they areeasy to understand and therefore strong candidates for telephone interviews. Thus they canbe used to inexpensively monitor changes in fertility demand and to predict changes infertility more accurately.


Appendix. Questions, Wisconsin Fertility Motivation Survey

Happiness, Satisfaction

95

We would like to know your feelings about having a(nother) child, whether or not you are ableto, or plan to have one. On a scale that goes from -3 for very unhappy to +3 for very happy, andwhere 0 stands for in-between, what number stands for how unhappy or happy you would feel if youhad a(nother) child? ... what number stands for how dissatisfied or satisfied you would feel if youhad a(nother) child?

Now I'm going to tum the question around. Think about NOT having a(nother) child, ever. Whatnumber ... stands for how unhappy or happy you would feel if you did NOT have a(nother) child?And what number . . . stands for how dissatisfied or satisfied you would feel if you did NOT havea(nother) child?

Self-Change

Compared to the way you are now, would having a child make you less (WORD), more(WORD), or wouldn't it make a difference to how (WORD) you would be? WORD = fulfilled,selfish, responsible, masculine, feminine.

What about NOT having a child? Would that make you less (WORD), more (WORD), orwouldn't it make a difference to how (WORD) you would be? (Same WORD list as for having achild)

Feeling Modifiers

Strong. Overall, are your feelings of wanting (to have, not to have) another child very strong,moderately strong, a little strong, or not at all strong? (not at all = I ... very = 4)

Important. Is having (no more, more) children something that is very important, moderatelyimportant, slightly important, or not at all important to you? (not at all = 1 ... very = 4)

Sure. How sure are you that you (want, do not want) to have another child? Are you very sure,moderately sure, slightly sure, or not at all sure? (not at all = 1 ... very = 4)

Mixed. Would you say your feelings about having (more, no more) children are only positive,mostly positive, or equally mixed with negative feelings? (equally mixed = I ... only positive =3)

Changing. In the last six months, would you say that your feelings about having (a, another)child have gone back and forth from day to day, week to week, month to month, or haven't they goneback and forth at all? (l = day to day.... 4 = not at all).

Birth Expectation

How likely is it that you will have a(nother) child, sometime in the future? Would you say it isvery unlikely, somewhat unlikely, about a 50/50 chance, somewhat likely, or very likely? (veryunlikely = 1 ... very likely = 5).

REFERENCESBass, B. M., W. F. Cascio, and E. J. O'Connor. 1974. "Magnitude Estimations of Expressions of

Frequency and Amount." Journal of Applied Psychology 59:313-20.Beach, L. R., A. Hope, B. D. Townes, and F. L. Campbell. 1982. "The Expectation-Threshold

Model of Reproductive Decision Making." Population and Environment 5:95-108.


Cantor, N., H. Markus, P. Niedenthal, and P. Nurius. 1986. "On Motivation and the Self-concept."pp. 96---121 in Handbook of Motivation and Cognition: Foundations of Social Behavior, editedby R. M. Sorrentino and E. T. Higgins. New York: Wiley.

Clay, D. C. and J. 1. Zuiches. 1980. "Reference Groups and Family Size Norms." Population andEnvironment 3:262-79.

Clogg, C. C. 1984. "Some Models for the Analysis of Association in Multiway Cross-ClassificationsHaving Ordered Categories." pp. 224-60 in The Analysis of Cross-Classified Data HavingOrdered Categories, by L. Goodman. Cambridge, MA: Harvard University Press.

Converse, P. E. 1970. "Attitudes and Non-attitudes: Continuation of a Dialogue." Pp. 163-89 in TheQuantitative Analysis ofSocial Problems, edited by E. R. Tufte. Reading, MA: Addison-Wesley.

Coombs, C. H., L. C. Coombs, and G. H. McClelland. 1975. "Preference Scales for Number andSex of Children." Population Studies 29:273-98.

Coombs, L. C. 1974. "The Measurement of Family Size Preferences and Subsequent Fertility."Demography 11:587--611

Davidson, A. R. and J. 1. Jaccard. 1975. "Population Psychology: A New Look at an Old Problem."Journal of Personality and Social Psychology 31:1073-82

Fawcett, J. T. 1983. "Perceptions of the Value of Children: Satisfactions and Costs." Pp. 429-57 inDeterminants of Fertility in Developing Countries, Vol. I: Supply and Demand for Children,edited by R. A. Bulatao and R. D. Lee. New York: Academic Press.

Goodman, L. A. 1979. "Simple Models for the Analysis of Association in Cross-ClassificationsHaving Ordered Categories." Journal of the American Statistical Association 74:537-32.

Joreskog, K. G. and D. Sorbom. [988. PRELIS. Mooresville, IN: Scientific Software.___. 1989. LISREL 7 User's Reference Guide. Mooresville, IN: Scientific Software.McClelland, G. H. 1983. "Family-Size Desires as Measures of Demand." Pp. 288-343 in

Determinants of Fertility in Developing Countries, Vol I: Supply and Demand for Children.edited by R. A. Bulatao and R. D. Lee. New York: Academic Press.

Miller, W. B. 1986. "Proception: An Important Fertility Behavior." Demography 23:579-94.Morgan, S. P. 1985. "Individual and Couple Intentions for More Children: A Research Note."

Demography 22:125-32.Raden, D. 1985. "Strength-Related Attitude Dimensions." Social Psychology Quarterly 48:312-30.Schaeffer, N. C., and E. Thomson. 1992. "The Discovery of Grounded Uncertainty: Developing

Standardized Questions about Strength of Fertility Motivation." Pp. 37-81 in SociologicalMethodology 1992, edited by P. Marsden. Washington, DC: American Sociological Association.

Schuman, H. and S. Presser. 1981. Questions and Answers in Attitude Surveys. Orlando: AcademicPress.

Williams, L. B. 1991. "Determinants of Unintended Childbearing among Ever-Married Women in theUnited States: 1973-1988." Family Planning Perspectives 23:212-14.

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