Household Demand for Health Insurance: 

Price and Spouse’s Coverage

Marjorie Honig 

Department of Economics 

Hunter College, and the 

Graduate School of CUNY 

and 

International Longevity Center 

60 E. 86th Street 

New York, NY 10028 

and 

Irena Dushi 

International Longevity Center 

60 E. 86th Street 

New York, NY 10028 

Revised December 2004 

Report submitted to U. S. Department of Labor, Employee Benefits Security Administration, in 

fulfillment of obligations pursuant to funding under SP-02-001. The authors would like to thank 

Partha Deb, Marjorie Flavin, Donna Gilleskie, Kathleen McGarry, Sara Rix, and Patricia Willis 

for helpful comments. 
Abstract

 Demand for employment-based health insurance has traditionally been treated as an 

individual rather than a household decision. Dual-earner households are now the typical U.S. 

married household, however, and most firms offer family coverage as one of the options 

available to employees. Findings from a model that jointly estimates married workers’ take-up 

of their own employer-based insurance with both their own and their spouses’ insurance offers 

indicate that both own insurance price and opportunities for coverage under spouses’ employerbased plans are statistically important determinants of insurance take-up in dual-earner 

households. 

 Relative take-up elasticities with respect to own price and spouse’s offer indicate that 

potential coverage by spouses plays the larger role for both husbands and wives in the decision 

of whether to take their own coverage. We find evidence of selection into jobs offering health 

insurance among wives in dual-earner households, but not among husbands. Our findings also 

suggest that dual-earners may not be aware of the potential trade-off between wages and health 

benefits. Data are taken from the 1996 panel of the Survey of Income and Program Participation 

(SIPP). 
3 

Household Demand for Health Insurance: 

Price and Spouse’s Coverage 

 Demand for employment-based health insurance has traditionally been treated as an 

individual rather than a household decision. Dual-earner households are now the typical U.S. 

married household, however, and most firms offer family coverage as one of the options available 

to employees. Thus casual observation and economic theory suggest that the insurance coverage 

decision commonly takes place in a household joint optimization framework. 

Previous research has focused on the employee rather than the household decision in large 

part because of the unavailability of data providing a key element in the take-up decisions of all 

working households -- the price of insurance -- together with information critical to the decisions 

of dual-earner households -- whether spouses are offered their own health insurance. In this study, 

we estimate household offer and take-up functions using the 1996 panel of the Survey of Income 

and Program Participation (SIPP) which provides information on the out-of-pocket premium for 

each worker in the household offered insurance. The data also provide additional features of 

insurance offers and detailed demographic and employment information on spouses as well as 

respondents. 

Our findings from a selection model that estimates married workers’ take-up of their own 

employer-based insurance with both their own and their spouses’ insurance offers indicate that 

both own insurance cost and opportunities for coverage under spouses’ employer-based plans are 

statistically important determinants of insurance take-up in dual-earner households. Relative 

elasticities of price and spouse’s offer suggest that potential coverage by spouses plays a larger 
4 

role in the decision whether to elect own coverage. We also find evidence of worker sorting into 

jobs offering health insurance among wives in dual-earner households, but not among husbands. 

Finally, our findings suggest that dual-earners may be unaware of the potential trade-off between 

wages and health benefits. 

The next section reviews the evidence to date on the influence of price and spouse’s 

coverage on insurance take-up. We then develop a selection model of household offers and takeup and provide a number of alternative scenarios of joint optimization in dual-earner households. 

The next section describes our estimation strategy and the SIPP data. The last section presents our 

findings and discusses their implications for the alternative models of household decision-making 

that we have posed, followed by a brief summary. 

 

I. Measuring Price and Spousal Options 

Determining the relative roles of price and alternative coverage options in explaining takeup has been complicated by the absence of information on both factors in a single data source. 

Studies estimating the effect of price on insurance demand using employer surveys have lacked the 

necessary information on spouse’s offers. Chernew, Frick, and McLaughlin (1997), for example, 

limit their analysis to single workers. Cooper and Vistnes (2001) find a strong negative impact of 

premiums on single and married worker take-up, but are unable to evaluate the role of spousal 

offers. Analyses using household surveys, lacking data on prices facing workers and eligible 

spouses, have used proxies such as firm size (reflecting loading fee charges), household marginal 

tax rates, or geographical identifiers, and have focused on the less complex issue of worker rather 
5 

than household demand [Early studies are surveyed in Marquis and Long (1995); see also Gruber 

(2001), Bernard and Selden (2003), and Gruber and Washington (2003)]. 

Monheit, Schone, and Taylor (1999), examining the probability of double coverage among 

dual-offer households, avoided the limitations of these data sources by merging the 1987 Medical 

Expenditure Panel Survey household component with the survey’s insurance component to link 

demographic information with employer-provided information on premiums. Information on 

insurance price was available for only a small fraction of the sample, however, either because 

workers refused to identify employers or employers failed to respond. Findings on a sample of 

656 dual-offer households with reported premium values indicate that double coverage was elected 

only when both spouses were offered no-cost coverage; in cases in which only one spouse was 

offered no-cost coverage, the no-cost option was elected. 

Marquis and Kapur (2004) also examine the role of price on the choices of households 

offered dual coverage using data from the March CPS, 1997-2001, and the 1997 Robert Wood 

Johnson Foundation Employer Health Insurance Survey. Consistent with the findings of Monheit 

et al, families with children were more likely to purchase two family policies when both employers 

paid the full premium cost. If both employers paid the full premium for single coverage, families 

were more likely to purchase some type of plan from both employers. 

Blumberg, Nichols, and Banthin (2001) merge the 1996 versions of the Medical 

Expenditure Panel Survey household and insurance components to examine take-up for single and 

family workers. Take-up functions are estimated separately for single workers and for workers in 

family units (married or with children). Workers in families, but not single workers, were found to 

respond to out-of-pocket premiums. As in the earlier versions of these surveys, information on 
6 

 

insurance price was available for only a small proportion (15 percent) of the sample. Price 

elasticities differed depending on whether they were estimated on a sample limited to reported 

premium values (.04) or on the full sample using imputed values (.14).1

 Workers who had spouses 

with insurance offers were found to have lower take-up rates. Spousal offers in this analysis are 

treated as exogenous and the issue of joint decision-making is not addressed. 

Dushi and Honig (2003) use data from several supplements to the Current Population 

Survey (CPS) covering the period 1988-2001 to examine the relative roles of insurance cost and 

spousal coverage in decisions to elect employer-based coverage. Employee take-up is estimated 

on a pooled cross-section sample of 47,737 married wage and salaried workers as a function of 

price (measured by the employee’s share of total premium costs, the only available price measure 

in the CPS), firm size, employee characteristics, and whether the spouse is covered under his or 

her own employer plan (conditional on having a working spouse), which is treated as endogenous 

to the employee’s take-up decision. 

Findings indicate that the decisions of workers to elect coverage are significantly 

influenced both by their share of plan costs and by whether their spouses are covered under their 

own plans. While highly significant, magnitudes of cost-sharing effects are not large. Paying part 

or all of the total premium results in a two percentage point decline in take-up among married men 

and a five percentage point decline among married women. The effect of having spouses with 

their own insurance is considerably larger. Spouses’ coverage lowers the likelihood of husbands’ 

1

 The authors correct for potential selectivity in the sample of non-respondents when imputing price values for the full 

sample of workers offered coverage. 
7 

 

take-up of own insurance by nearly one-quarter and the likelihood of wives’ take-up of own 

insurance by 50 percent. 

In this analysis, we make use of the more complete information on prices that employees 

face, and on the demographic and employment characteristics of both respondents and spouses, in 

the 1996 panel of the SIPP. Only recently available, these data provide two measures of insurance 

price, the out-of-pocket premium and the worker’s share of total premium cost, for which survey 

response rates are high. 

Information in the SIPP on spouses’ offers comparable to that provided for respondents 

allows us to consider take-up in dual-earner households as a joint decision. This information also 

permits us to treat the receipt of insurance offers in a joint decision-making framework. The 

possibility that workers may sort into jobs offering different wage/benefit packages was first raised 

in the context of health insurance take-up by Goldstein and Pauly (1976). Profit maximization 

among firms in competitive markets requires that firms offering benefits such as health insurance 

pass the costs to workers in the form of lower wages. Because workers are likely to differ in their 

demand for insurance, those with strong tastes for insurance will be willing to accept the wage 

offset and will, accordingly, select into firms offering insurance. 

Empirical confirmation of worker sorting has been limited, however. Monheit and Vistnes 

(1999) find lower offer rates among single workers who report weak preferences for health 

insurance coverage in the 1987 National Medical Expenditure Survey.2 Blumberg et al (2001) 

find evidence of sorting in a pooled sample of male and female workers who are married or have 

2

 See their discussion of studies providing some empirical evidence consistent with sorting behavior. See also the 

review of the early literature in Currie and Madrian (1999). 
8 

children. Evidence on whether dual-earner households engage in joint job sorting is mixed. 

Buchmueller (1996/97) finds no evidence that full-time working wives sort into jobs that do not 

offer insurance if their husbands are offered coverage. Abraham and Royalty (2004), in contrast, 

find that husband’s/wife’s coverage has statistically significant negative effects on spouse’s labor 

force participation, full-time work status, and offer of insurance coverage. 

Evidence of a wage/insurance tradeoff is equally limited. Findings by Gruber (1994) and 

more recently Olson (2002), support the prediction of a negative relationship between wages and 

insurance offers. The latter, for example, finds that wages are lower among full-time working 

wives with insurance coverage. 

II. Estimating Household Demand for Health Insurance

 We first consider the demand for insurance by an individual worker. Let TU be the 

probability that an employee elects offered insurance coverage, which is a function of employee 

characteristics X, price P, and unobservables, including tastes for insurance, ε1: 

 TUi = α0 + Xiα1 + α2Pi + ε1i (1) 

 The parameters of this demand equation estimated on workers offered health insurance will 

be biased if workers select into jobs that offer health insurance based on their preferences for 

insurance, which are unobserved. We thus estimate insurance take-up in a sample-selection 

framework: 

 TUi = α0 + Xiα1 + α2Pi + ε1i 

 (2) 

 Offi = β0 + Xiβ1 + Ziβ2 + ε2i 
9 

 

 where Off is the probability of receiving an offer, X is a vector of individual characteristics, Z is a 

vector of job characteristics, and the ε’s are the error terms. If job sorting is an important aspect of 

worker behavior, Cov(ε1,ε2)>0. If, in addition, workers sort on price, P is endogenous to take-up. 

 Estimation of insurance demand in the case of a married worker in a dual-earner household 

is more complex because of the option of coverage under a spouse’s employment-based plan. 

Assuming that dual-earner households maximize household rather than individual utility, the couple 

may decide whether to select into jobs with offers of insurance coverage, which member should do 

so if not both and, based on offer outcomes, who should elect coverage if there is more than one 

offer.3

 The wife’s take-up, shown below, may thus be jointly determined with both her own and 

her husband’s offer: 

 TUwi = α0 + Xwiα1 + α2Pwi + α3Offhi + ε1i 

 

 Offwi = β0 + Xwiβ1 + Zwiβ2 + β3Offhi + ε2i (3) 

 

 Offhi = γ0 + Xhiγ1 + Zhiγ2 + γ3Offwi + ε3i

The husband’s take-up is determined similarly: 

 TUhi = α0 + Xhiα1 + α2Phi + α3Offwi + ε1i 

 

 Offhi = β0 + Xhiβ1 + Zhiβ2 + β3Offwi + ε2i (3’) 

 

 Offwi = γ0 + Xwiγ1 + Zwiγ2 + γ3Offhi + ε3i

3

 We do not specify here the process by which dual-earner households arrive at a single objective function regarding 

insurance coverage. There is an extensive literature on household decision-making, including models in which 

spouses’ preferences are heterogeneous and decisions are a function of the bargaining power of each partner, and, more 

recently, models of preference-based assortative matching. See Becker (1973, 1974), McElroy and Horney (1980), 

Manser and Brown (1980), Lundberg and Pollak (1993, 1996), Browning and Chiappori (1998), and Lich-Tyler 

(2003). 
10 

 

 The model above generates a number of alternative scenarios of household decisionmaking regarding health insurance coverage, depending on whether the couple is aware that 

insurance offers may be offset by lower offered wages and whether they engage in job selection on 

the basis of insurance offers. 

 In Scenario 1, couples are aware of a potential wage/benefit offset and select into jobs that 

provide them with the best combination of wage income and insurance coverage. The household 

decides which partner will sort into a job with an offer of family health insurance and which one 

into a job with a good wage offer, and the household will receive a single insurance offer. Offer 

decisions are thus jointly determined. Error terms of the two offer equations, ε2ε3, will be 

negatively correlated due to joint optimization of the wage/offer package. Coefficients of spouses’ 

offers in the wife’s and husband’s offer equations, β3 and γ3, will also be negative.4

 In addition, error terms ε1ε2 will be positively correlated for the partner sorting into a job 

with an offer because the couple’s taste for insurance, expressed in this offer, will be reflected in a 

higher probability that he/she elects coverage for the family. Finally, α3, the coefficient of 

spouse’s offer in the husband’s and wife’s take-up equations, will be negative because the 

household elicits only one offer. 

 Scenario 2, a less restrictive model, does not assume household awareness of a 

wage/benefit offset. The trade-off between wages and insurance may not, in fact, be transparent to 

workers because firms paying high wages (due to other, not easily observed, factors related to 

4

 We present models for both the wife (3) and husband (3') for clarity of exposition throughout our discussion. Offer 

equations in (3) and (3') are identical but in reverse order for wives and husbands. In Table 1, which reports our 

estimation results, coefficients of spouse’s offer are the β3's in (3) and (3').
11 

 

demands of jobs) may also offer better benefits. It may thus appear to the typical worker that the 

relationship is, on the contrary, positive.5 

 Scenario 2 does, however, maintain the assumption of Scenario 1 that one partner sorts 

into a job on the basis of an insurance offer to guarantee that the household receives an offer (thus 

Cov (ε1,ε2)>0 for this partner), and that the other partner sorts on a wage offer. Because the 

household is not aware of the possibility of a wage/insurance trade-off, however, the wage-sorting 

spouse does not sort against an insurance offer. Thus his/her best wage offer may be randomly 

associated with an insurance offer. Errors ε1ε2 in this partner’s offer and take-up equations will 

not be correlated, however, because he/she has not selected into this job on the basis of the offer. 

 The couple may decide to conduct their searches either simultaneously or sequentially. If 

job search is simultaneous, coefficients of spouses’ offers in the wife’s and husband’s offer 

equations, β3 and γ3, will be zero. The partner sorting on a wage offer may receive an insurance 

offer, but this offer is not a function of his/her spouse’s offer outcome; the other partner sorts on an 

insurance offer, regardless of the offer outcome of his/her partner. Correlation of the error terms 

of the two offer equations, ε2ε3, will also be zero due to the randomness of the offer outcome of the 

wage-sorting spouse. 

 If job searches are sequential, the partner designated to search for an insurance offer waits 

for the outcome of his/her partner’s search because it may yield an insurance offer. The 

coefficient of spouse’s offer, β3, in this partner’s offer equation, will thus be negative because 

5

 In addition, firms with worker heterogeneity may recover insurance costs through higher out-of-pocket premiums 

rather than reduced wages. In the presence of imperfect worker sorting, firms may use high premiums to select 

workers with strong tastes for insurance, allowing minimal wage reductions for remaining employees (Levy 1998). As 

Cooper and Vistnes (2001) observe, their own finding, and that of other researchers, that take-up rates are more 

sensitive to changes in employee contributions than total premiums implies that employees view the out-of-pocket 

premium as the relevant price of insurance and may not recognize that higher employer contributions reduce wages. 
12 

 

he/she responds to the offer outcome of the partner. The coefficient of spouse’s offer, γ3, in the 

offer equation of the wage-sorting partner will be zero, as in the case of simultaneous search. 

Correlation of the error terms of the two offer equations, ε2 ε3, is indeterminate, however. If the 

wage-sorting partner does not receive an offer, his/her partner will sort into a job with an offer to 

assure that the household has access to health insurance; thus Cov(ε2,ε3)<0. If the wage-sorting 

partner does receive an offer, then there is no need for the other partner to sort on insurance; 

Cov(ε2,ε3)=0 if an offer is received randomly. 

 Whether there is simultaneous or sequential job search, the coefficient of spouse’s offer, α3, 

in each partner’s take-up equation is likely on average to be negative. In households with just one 

offer, the partner with the offer takes it and α3<0. If, instead, this partner is in a household with 

two offers, and the household maximizes on take-up, only one offer is taken. Thus, α3<0 if this 

partner’s offer is not taken, but α3>0 if it is taken. 

 Thus far, we have assumed that joint utility maximization takes place at both the offer and 

take-up stages. It is possible, of course, that the issue of insurance coverage does not enter into 

household job search and thus Cov (ε1,ε2)=0 for both partners (Scenario 3). Nonetheless, offers 

may be received randomly. In this case, β3, γ3, and Cov (ε2,ε3) are indeterminate. However, if 

households optimize with respect to take-up, α3<0, as in Scenario 2 above. 

III. Data and Estimation 

 The SIPP is conducted by the Bureau of the Census on a nationally representative sample of 

the civilian non-institutionalized population.6 All household members are interviewed at four6

 The 1996 Panel contains 40,188 households and 95,402 individuals. 
13 

 

month intervals over a four-year period and asked a series of core demographic and economic 

questions. In addition, topical modules (waves) focus on specific areas of interest. We use the 

Wave 5 module in which all workers in the household were asked about employer offers of 

insurance, eligibility, participation, out-of-pocket premiums, and cost-sharing arrangements.7

 They 

were also asked whether alternative benefits were offered such as employer contributions to a 401(k) 

plan, medical savings accounts, tax-free employee contributions to a flexible spending account, or 

cash or salary bonuses. Demographic information on respondents and spouses includes race and 

ethnicity, education, age, health status, and family characteristics include income, home ownership, 

and presence of children. Our sample consists of 1,268 matched households in which both spouses 

are working either full- or part-time. 

7 Survey response rates for out-of-pocket premium and cost-sharing are 81 and 95 percent of takers, respectively; 

imputed values are provided for non-reporting takers. There were inconsistencies in responses with respect to cost 

sharing and out-of-pocket premiums. Some respondents reported that the employer paid the full cost but gave a 

positive amount for the out-of-pocket premium; others reported that they paid some of the cost but reported a zero 

amount for the out-of-pocket premium. We excluded such cases. Similar to other surveys on health insurance 

coverage, SIPP collects information on plan features, including price, only for workers electing coverage. We impute 

values for non-takers using selection-correction imputation. 

 Estimating demand for health insurance by dual-earner households is complicated because 

the offer decisions of the two partners are jointly determined. Estimating model (3) for the wife, 

for example, contains elements of both a structural model of household offers, Offw and Offh (each 

partner’s offer is endogenous to the other’s offer) and a sample selection model (wife’s offer, Offw, 

and her take-up, TUw). 
14 

 

 We thus estimate Offh separately and include its predicted value in both equations, Offw 

and TUw, of the wife’s selection model. Specifically, we estimate a reduced form probit equation 

of the probability that her spouse has an offer as a function of his individual and job 

characteristics, as well as those of his wife (instead of including his wife’s offer, Offw, as in 

simultaneous estimation). We then include the fitted value of her husband’s offer as a regressor in 

both the wife’s offer and take-up equations.8

 Since Offh is treated as endogenous to Offw and TUw, 

we require at least one instrument in Offh that does not appear in Offw and TUw, but is correlated 

with Offh and uncorrelated with ε1 and ε2. Previous researchers have used spouse’s individual 

and/or job characteristics as instruments.9 The estimated parameter of the predicted husband’s 

offer will be biased, however, if either his job attributes are correlated with ε2 (because he changed 

jobs in response to his wife’s insurance offer) or his individual characteristics are correlated with 

ε2 (due to assortative mating).10 We tested for this potential bias in the linear structural model 

referred to in footnote 8 and were unable to reject the null hypothesis that our instruments for Offh

are not correlated with ε2.

11 We then estimate Offw and TUw jointly using a standard Heckman 

selection procedure for probit models.12 

 In addition to the spouse’s offer, we also treat the out-of-pocket premium as endogenous in 

8

 To assess the robustness of our results using this reduced form approach, we also estimated a structural model of the 

two offers by 2SLS and 3SLS. The signs and significance levels of the coefficients of spouse’s offer in the offer 

equations were consistent in the three approaches. 

9

 Buchmueller (1996/1997), for example, uses both spouses’ individual and job characteristics; Olson (2002) uses firm 

size and union status. 

10 See the discussion of these possibilities in Royalty and Abraham (2004). 

11 We use an overidentification test because we have more instruments than necessary to identify spouse offer equations. 

The test (Sargan) statistic is 19.17 (p-value = 0.260); the comparable statistics for Offw in the husbands’ model is 11.4 

(p-value = 0.781). 

12 The husband’s offer and take-up equations, Offh and TUh, are estimated similarly. We also estimated the take-up 

equation, including a sample selection correction derived from the estimation of the offer equation, by OLS and 
15 

 

the take-up equation of each partner. Price may be endogenous for two reasons. If workers select 

into jobs because of strong preferences for health insurance, their response to the price of 

insurance will not reflect that of the typical employee.13 In addition, price may be set by 

employers according to the preferences of their employees, as discussed above. 

Because price is available only for employees who elect coverage, we use a regression-based 

method to impute the out-of-pocket premium for non-takers.14 We first estimate a reduced form 

take-up equation, excluding the premium, among employees who are offered health insurance and 

generate the inverse Mills ratio (λ).15 We then estimate among takers the out-of-pocket premium 

and cost sharing equations, including λ to control for differences between takers and non-takers.16 

Using estimated parameters from this second step, we impute the premium for both takers and nontakers excluding λ from the imputation.17 We exclude λ because we expect price to be related to the 

take-up decision and λ is used as a regressor to estimate price.18 Because we focus on married 

probit. Signs and significance levels of the estimated parameters were comparable to our maximum-likelihood 

estimates. 

13 For the same reason, wage may also be endogenous to the take-up decision. We refrain from treating it as such 

because of the number of other endogenous variables in our estimation and because it is not the major focus of our 

investigation. 

14 Hot deck imputation does not take into account differences in the unobservables that may determine election of 

coverage. See Blumberg et al (2002); also see Marquis and Louis (2002) for imputation of premiums for employers not 

offering insurance. 

15 We include individual characteristics such as gender, race, ethnicity, age groups, presence of children, log wage, 

homeownership, as well as job characteristics such as firm size, occupation, and industry. 

16 The premium and cost-sharing equations are estimated using a standard Heckman procedure. In the first step, the 

cost sharing (whether employee pays none [=0] or a positive amount [=1] ) equation is estimated; in the second step, 

we estimate the dollar amount of the out-of-pocket premium conditional on a positive amount. Log wage, firm size, 

industry, occupation, region, MSA, health insurance alternatives, and λ are the regressors which are common to both 

stages. We use education as an exclusion restriction in the cost sharing equation to identify the premium. While firm 

size, occupation, and industry are included in λ and in the estimated premium equation, the structural take-up equation 

is identified by excluding them. 

17 We use these imputed values for both takers and non-takers because we treat price as endogenous in the take-up 

equation. 

18 Inclusion of λ may otherwise result in a negative bias in the coefficient of price in the take-up equation. 
16 

 

households, we use the family rather than the single premium.19 

Identification of the take-up equation requires that the offer equation include at least one 

variable that does not appear in the take-up equation. We use as exclusion restrictions firm size, 

occupation and industry.20 Finally, all exogenous variables that appear in the offer equations are 

also included in the take-up equations. 

IV. Estimation Results

 Table 1 reports estimates of the probabilities of receiving a health insurance offer and of 

electing coverage in dual-earner households. Columns 1 and 2 present estimates of insurance takeup and offers of wives, and columns 3 and 4 present estimates for husbands. 

 Estimates in columns 1 and 3 confirm the intuition that dual-earner households jointly 

maximize with respect to the take-up of insurance. Coefficients of spouses’ offers (α3 in 3 and 3') 

are negative and significant in the take-up equations of both wives and husbands (p-values <.01), 

indicating that partners are less likely to elect their own offered coverage if spouses also have 

insurance options. 

 Values of ρ, indicating the correlation of residuals ε1ε2 in offer and take-up equations, are 

reported at the bottom of columns 1 and 3. The significant positive correlation for wives (0.82; pvalue=.07) indicates that job sorting is an important aspect of household behavior. This finding 

19 The out-of-pocket premium may be measured with error either because of reporting errors or because the amount of 

the out-of-pocket premium depends on the number of family members covered. To account for the latter, we control 

for the presence of children in the household in our premium imputation. 

20 If these firm characteristics affect offer and, through offer, the premium, the estimated effect of the premium on takeup may be biased. We therefore estimated the take-up equation conditional on the offer to test for this possibility and 

found the premium estimate to be robust. 
17 

allows us to eliminate Scenario 3 which, alone among the three alternative models of household 

behavior formulated above, does not provide for job search on health insurance coverage. 

 The insignificant value of ρ for husbands, however, suggests that job sorting on health 

insurance is an activity in dual-earner households that is engaged in primarily by wives. Job 

selection on health insurance by one spouse exclusively is consistent with both Scenarios 1 and 2. 

Also consistent with both scenarios is our finding, discussed above, that the coefficients of 

spouses’ offers, α3, are negative and significant in the take-up equations of both husbands and 

wives. 

 Scenarios 1 and 2 differ depending on whether the household is aware of the possibility of a 

wage/benefit offset. If this were the case (Scenario 1), the coefficients of the spouse’s offer (β3 in 3 

and 3'), would be negative and significant in the offer equations of both wife and husband. The 

coefficient of the wife’s offer in the husband’s offer equation, however, is not different from zero, 

indicating that the partners do not jointly optimize the receipt of insurance offers. This behavior is 

not consistent with recognition of the likelihood that jobs offering health benefits pay lower wages, 

all else equal. 

 We thus turn to Scenario 2, in which one partner sorts on an insurance offer to provide 

coverage for the household and the other partner sorts on wages (but does not sort against an 

insurance offer). This behavior is consistent with two alternative modes of job search, 

simultaneous or sequential, by the couple. If search is simultaneous, coefficients of spouses’ 

offers in both partners’ offer equations are expected to be zero (because offers are drawn 

randomly). We find, however, that in the wife’s offer equation, the coefficient of husband’s offer 

is negative and significantly different from zero (p-value<.01). 
18 

 

 If job search is sequential, the coefficient of spouse’s offer in the offer equation of the 

insurance-sorting partner will be negative and significant because he/she responds to the offer 

outcome of the wage-sorting partner, which may involve an insurance offer or not. Our finding 

that, in the wives’ offer equation, the coefficient of spouse’s offer is negative and significant 

suggests that, on average, it is the wife who is designated to sort on insurance, and she does so in 

response to the insurance offer outcome of her husband. If he happens to receive an offer, she 

does not sort on insurance (although she may receive an offer randomly); if he does not receive an 

offer, she sorts into a job with an insurance offer. 

 In sequential search, correlation of the error terms ε2ε3 of the two offer equations is 

indeterminate. If the wage-sorting partner does not receive an offer, his/her partner sorts into a job 

with an offer to assure that the household has access to health insurance; thus Cov(ε2,ε3)<0. If the 

wage-sorting partner receives an offer, there is no need for the other partner to sort on insurance, 

but he/she may receive an offer randomly. In this case, Cov(ε2,ε3) is predicted to be zero, in 

contrast to alternative scenarios discussed above, which require Cov(e2,e3)<0. We find, however, 

that offer equation residuals ε2 ε3 are positively correlated.21 This result is anomalous, given that all 

other estimated parameters are consistent with a model of sequential job search. We attribute this 

positive correlation to remaining unobserved aspects of positive assortative mating that we have 

been unable to control for in our estimation.22 

21 Correlation from a bivariate probit estimation of the two offer equations is .14 (p-value=.02). 

22 We remove potential effects of assortative mating by instrumenting spouse’s offer using spouse’s personal and job 

characteristics. These instruments easily pass the over-identification test, as discussed above. Other unobservable 

characteristics, as well as unobserved tastes, may remain to introduce a positive correlation into the residuals of the 

two offer equations.
19 

 

 We now turn to discussion of the question raised at the beginning of this paper: Does 

either the price of a dual-earner’s own health benefits or the option of coverage under a spouse’s 

insurance play a role in the decision to elect one’s own employer-provided coverage? If both, 

which factor is more important? 

 Estimates of the take-up decision of wives and husbands offered coverage (columns 1 and 3 

in Table 1) indicate that the out-of-pocket premium is an important determinant of take-up for both 

wife and husband (p-values<.01). Price elasticities are .19 for wives and .08 for husbands.23 The 

opportunity for coverage under spouses’ employer plans also has a significant negative impact on 

whether they elect their own coverage (p-values<.01), as discussed above. The elasticity of wives’ 

take-up of their own offers with respect to their husbands’ offers is .45; husbands’ elasticities with 

respect to their wives’ offers is .19. Two patterns emerge from these results. Husbands’ take-up of 

their own employment-based benefits is less responsive to the price of their own insurance and to 

opportunities for coverage afforded by their wives’ employment than is their wives’ take-up. 

Secondly, for both wives and husbands, an increase in the probability that their spouses have health 

insurance options results in a larger decline in the likelihood that they take their own offered 

coverage than an increase in their out-of-pocket premiums. 

 Columns 1 and 3 also indicate that the take-up of offered insurance of both wives and 

husbands is less likely if their employers offer alternatives to health benefits such as contributions 

to 401(k) plans, medical savings accounts, tax-free employee contributions to flexible spending 

accounts, or cash or salary bonuses. The wage is also a significant determinant of whether wives 

and husbands elect their own coverage. Among demographic factors, neither health status nor age 

23 These values are in the range found in other studies. See, for example, Short and Taylor (1989), Gruber and Poterba 
20 

 

affects the take-up of offered coverage; however, the presence of children in the household 

substantially reduces wives’ take-up of their own offers. Because we examine dual-earner 

households, the availability of alternative insurance coverage for children from public sources is 

unlikely to explain this result.24 A more plausible explanation is that in households with dual 

offers, the presence of children increases the probability that not only children but also wives will 

be covered under husbands’ plans. This is particularly likely if husbands’ higher wages are 

associated with more generous insurance coverage. 25

 Columns 2 and 4 report estimates of the offer equations of wives and husbands. As 

discussed above, wives are less likely to be in jobs offering health benefits if their husbands have 

employment-based offers, whereas husbands’ offers are unrelated to their wives’ offers. Firm and 

worker characteristics are strongly linked to the probability that members of the household are 

offered coverage. Larger firms and higher wages are positively associated with the probability of 

receiving an offer among both wives and husbands.26 Employment in service-oriented occupations 

(laborers are the omitted category) is associated with a lower likelihood of being offered coverage 

for both spouses, as is employment in technical occupations and goods-producing industries for 

husbands. Interestingly, being in a union does not have an additional effect for husbands, but it 

reduces substantially the probability that wives are offered coverage. Wives are more likely to be 

(1994), Marquis and Long (1995), Chernew et al (1997), and Blumberg et al (2001). 

24 The proportion of families receiving public insurance coverage for children in our sample is very small. SCHIP, the 

insurance program at the state level for children in low-income families, was not introduced until 1997 and thus is not 

included in our data. 

25 The mean weekly wage among husbands in our sample is $735; among wives, the mean is $494. 

26 The coefficient of the wage in both offer and take-up equations may be biased but the direction of the bias is 

indeterminate. Workers with stronger tastes for insurance are more likely to sort into jobs offering insurance and to 

take it up, but are likely to be paid lower wages if there is a wage/benefit tradeoff; the bias in the wage coefficient in 

this case will be negative. If, however, workers with strong tastes for insurance have unobserved characteristics that 

are associated with higher wages, the bias will be positive. Because of the complexity of our model and because the 
21 

 

offered coverage in the south, and husbands less likely in the midwest, compared to the northeast. 

Wives are less likely to receive offers in urban areas. Wives with children and husbands in poor 

health are less likely to work in jobs offering coverage. 

 While there are no observed racial or ethnic differences in the take-up of insurance, nonHispanic black and Hispanic husbands are considerably less likely to be in jobs offering insurance 

than non-Hispanic white husbands, and Hispanic wives are less likely to be offered insurance than 

non-Hispanic wives. 

V. Conclusion

 Findings from a selection model that jointly estimates married workers’ take-up of their own 

employer-based insurance with both their own and their spouses’ insurance offers indicate that both 

own insurance price and opportunities for coverage under spouses’ employer-based plans are 

important determinants of insurance take-up in dual-earner households. Relative elasticities with 

respect to price and spouse’s offer indicate that potential coverage by spouses plays the larger role 

in the decisions of both husbands and wives regarding take-up of their own coverage. Husbands’ 

elasticity of take-up with respect to his wife’s offer is .19 and wife’s elasticity with respect to her 

husband’s offer is .45 Price elasticities are .08 for husbands and .19 for wives. 

existence of a wage/insurance tradeoff is not the major focus of our analysis, we do not instrument for wages. 

 We also find evidence that wives, but not husbands, in dual-earner households sort into 

jobs offering health insurance. Finally, our findings suggest that dual-earners may be unaware of 

the potential trade-off between wages and health benefits. 
22 

References 

Becker, Gary S. 1973. “A Theory of Marriage: Part I.” Journal of Political Economy 81(4): 

813-846. 

Becker, Gary S. 1974. “A Theory of Marriage: Part II.” Journal of Political Economy 82(2): 

S11-S26 

Bernard, Didem, and Thomas M. Selden. 2003. “Employer Offers, Private Coverage, and the 

Tax Subsidy for Health Insurance: 1987 and 1996.” International Journal of Health 

Care Finance and Economics 2:297-318. 

Browning, Martin, and Pierre-Andre Chiappori. 1998. “Efficient Intra-Household Allocations: 

A General Characterization and Empirical Tests.” Econometrica 66(6):1241-1278.

Blumberg, Linda J., Len M.Nichols, and Jessica S. Banthin. 2001. “Worker Decisions to 

Purchase Health Insurance.” International Journal of Health Care Finance and 

Economics 1(3/4):305-25. 

Buchmueller, Thomas C. 1996/97. “Marital Status, Spousal Coverage, and the Gender Gap in 

 Employer-Sponsored Health Insurance.” Inquiry 33:308-316. 

Chernew, Michael, Kevin Frick, and Catherine G. McLaughlin. 1997. “The Demand for 

Health Insurance Coverage by Low-Income Workers: Can Reduced Premiums Achieve 

Full Coverage?” Health Service Research 32(4):453-470. 

Cooper, Philip F., and Jessica Vistnes. 2001. “The Effect of Out-of-Pocket Premium Costs and 

 Workforce Characteristics on the Decision to Take Up Offers of Health Insurance.” 

Mimeo, Agency for Healthcare Research and Quality. 

Currie, Janet, and Brigette C. Madrian. 1999. “Health, Health Insurance and the Labor Market.” 

Handbook of Labor Economics, Vol. 3C, edited by Orley Ashenfelter and David Card. 

 Amsterdam:Elsevier:3309-3406. 

Dushi, Irena, and Marjorie Honig. 2003. “Price and Spouse’s Coverage in Employee Demand 

 For Health Insurance.” AEA Papers and Proceedings 93(1):252-256. 

Goldstein, Gerald, and Mark Pauly. 1976. “Group Health Insurance as a Local Public Good.” 

 In The Role of Health Insurance in the Health Services Sector, ed. Richard Rosen. 

73-110. New York: Neale Watson Academic Publications for the National Bureau of 

Economic Research. 

Gruber, Jonathan, and James Poterba. 1994. “Tax Incentives and the Decision to Purchase 

 Health Insurance: Evidence from the Self-Employed.” Quarterly Journal of Economics 

 (August):701-733. 

Gruber, Jonathan. 2001. “The Impact of the Tax System on Health Insurance Coverage.” 

International Journal of Health Care Finance and Economics 1(3/4):293-304. 

Gruber, Jonathan, and Ebonya Washington. 2003. “Subsidies to Employee Health Insurance 

 Premiums and the Health Insurance Market.” Mimeo, MIT and NBER. 
23 

Levy, Helen. 1998. “Who Pays for Health Insurance: Employee Contributions to Health 

 Insurance Premiums.” Mimeo, U.C. Berkeley. 

Lich-Tyler, Stephen. 2003. “Preference-based Assortative Matching in Marriage Markets.” 

 Mimeo. University of Michigan at Ann Arbor. 

Lundberg, Shelly, and Robert Pollak. 1993. “Separate Spheres Bargaining and the Marriage 

 Market.” Journal of Political Economy 101(6):988-1010. 

Manser, Marilyn, and Murray Brown. 1980. “Marriage and Household Decision Making: A 

 Bargaining Analysis.” International Economic Review 21(1):31-44. 

Marquis, M. Susan, and Stephen H. Long. 2001. “Employer Health Insurance and Local Labor 

Market Conditions.” International Journal of Health Care Finance and Economics

1(3/4):273-292. 

Marquis, M. Susan, and T. A. Louis. 2002. “On Using Sample Selection Methods in Estimating 

 The Price Elasticity of Firms’ Demand for Insurance.” Journal of Health Economics 

 21:137-145. 

Marquis, M. Susan and Kanika Kapur. 2004. “Family Decision Making When Two Workers are 

Offered Group Coverage.” Working Paper. U.S. Department of Labor. Employee 

Benefits Security Administration. http://www.dol.gov/ebsa/publications. 

Monheit, Alan C., Barbara S. Schone, and Amy K. Taylor. 1999. “Health Insurance Choices in 

 Two-Worker Households: Determinants of Double Coverage” Inquiry 36:12-29. 

Monheit, Alan C., and J. Primoff Vistnes. 1999. “Health Insurance Availability at the 

 Workplace: How Important are Worker Preferences?” Journal of Human Resources 

 34(4):770-785. 

Olson, Craig A. 2002. “Do Workers Accept Lower Wages in Exchange for Health Benefits?” 

Journal of Labor Economics 20 (2): S91-S114. 

Royalty, Anne Beeson, and Jean M. Abraham. 2004. “Health Insurance and Labor Market 

 Outcomes: Joint Decision-Making Within Households.” Mimeo. Indiana University 

 Purdue University Indianapolis and University of Minnesota. 

Short, Pamela F., and Amy K. Taylor. 1989. “Premiums, Benefits, and Employee Choice of 

 Health Insurance Options.” Journal of Health Economics 8:293-311. 
Independent variable Take-up Offer Take-up Offer

Constant 1.665 -3.128*** 3.222*** -1.102***

(1.151) (0.449) (1.030) (0.406)

Out-of-pocket premiuma -0.012*** -0.013***

(0.002) (0.003)

HI alternatives -0.313*** -0.250*

(0.114) (0.138)

Spouse has offera -0.537*** -0.222*** -0.485*** 0.0006

(0.127) (0.072) (0.139) (0.052)

Log weekly wage 0.489*** 0.579*** 0.191* 0.294***

(0.090) (0.051) (0.109) (0.038)

Home ownership 0.103 0.008 0.186 0.217***

(0.115) (0.074) (0.136) (0.063)

Childrenb -0.378*** -0.376*** -0.090 0.019

(0.090) (0.054) (0.105) (0.051)

Poor/fair health 0.131 -0.033 -0.264 -0.291***

(0.188) (0.119) (0.233) (0.109)

Age -0.050 0.011 -0.007 -0.022

(0.038) (0.022) (0.040) (0.019)

Age2 0.0004 -0.0003 -0.0001 0.0002

(0.001) (0.000) (0.001) (0.000)

Non-Hispanic black -0.199 -0.131 0.012 -0.218**

(0.168) (0.103) (0.206) (0.098)

Non-Hispanic other 0.146 0.183 -0.196 -0.101

(0.208) (0.126) (0.254) (0.114)

Hispanic -0.191 -0.258** -0.195 -0.256***

(0.165) (0.102) (0.206) (0.094)

Midwest 9071 0.110 -0.135 -0.115*

(0.135) (0.080) (0.156) (0.068)

South -0.072 0.367** -0.095 0.051

(0.143) (0.079) (0.161) (0.067)

West -0.027 0.122 0.038 -0.067

(0.147) (0.092) (0.165) (0.077)

Table 1. Heckman selection estimates of the probabilities of receiving a health insurance offer and of 

electing coverage, dual-earner households 

Wives Husbands

24 
Table 1 (cont.)

MSA -0.128 -0.228*** -0.164* -0.039

(0.094) (0.051) (0.097) (0.046)

Firm size 25-99 0.724*** 0.508***

(0.097) (0.083)

Firm size 100+ 0.785*** 0.857***

(0.073) (0.065)

Union member -0.359*** -0.066

(0.107) (0.114)

Professional occupation -0.035 -0.070

(0.141) (0.077)

Technical occupation 0.022 -0.202***

(0.106) (0.072)

Service occupation -0.315** -0.339**

(0.145) (0.137)

Producation/craft/repair occupation 0.059 0.027

(0.162) (0.095)

Goods-producing industry c -0.112 -0.161***

(0.089) (0.056)

High school graduate 0.067 -0.046

(0.114) (0.092)

Some college 0.055 -0.016

(0.129) (0.115)

College graduate 0.003 -0.114

(0.140) (0.111)

ρ (rho)

p -value

N 836 1268 940 1268

a

 Treated as endogenous.

b

 Children = 1 if children present in household. 

 * p < .1, ** p < .05, and *** p < .01

(0.429)

c

 Industry = 1 if agriculture, mining, construction or manufacturing; and 0 if transportation, utilities, trade or 

services.

Notes: Dependent variables: Take-up = 1 if individual elects own coverage; Offer = 1 if individual is offered 

health insurance by employer. Robust standard errors in parentheses. Omitted racial, education, region, firm 

size and occupational categories are Non-Hispanic white, high school drop out, east, firm size <=24, and 

laborers, respectively.

0.820

(0.073)

0.510

25