Matching or Bargaining

Table 3.4 reports results from two different specifications. The table has four

columns. Columns 1 and 2 report benchmark estimates from a specification using seemingly unrelated regressions without fixed effects. The seemingly unrelated regressions (SUR) in columns 3 and 4 add individual fixed effect for both partners as well as an individual fixed effect. The results show that physical activity behaves very different to the rest of the preventive behaviors.

The results for the effect of physical activity are striking. First, in the specification with individual fixed effects (columns 3 and 4) the coefficient on own lagged participation in physical activity drops as compared with the specification without fixed effects although it remains significant. Second, individual physical activity participation is statistically

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independent of partner‘s physical activity participation in the specification with fixed effects at the individual level. The statistically significant effect of partner‘s in the specification without the fixed effects entirely disappear in specification with fixed effects.

In all other cases, the effect of spouses past behavior is relevant in determining each the respondent‘s behavior regardless of the presence of the individual fixed effects. Given the modeling presented above, these results suggest that while the correlation between spouses in smoking behavior, normal weight maintenance, flu shot, cholesterol screening, and cancer related screening (prostate, mammogram and pap smear) may arise as a consequence of a decision-making model, the correlation in physical activity is likely to be due to positive assortative matching.

Table 3.4. Matching vs. bargaining.

Dependent variable= Corresponding preventive

activity at t

(1) (2) (3) (4)

SUR with no fixed effects SUR with fixed effects Male Female Male Female

(1)

Respondent's Physical Activity at t-1

0.325*** 0.333*** 0.263*** 0.281*** (0.009) (0.009) (0.006) (0.006) Spouse's Physical Activity at

t-1 0.041*** 0.034*** 0.004 -0.006 (0.009) (0.008) (0.006) (0.006) (2) Respondent's Non-smoker status at t-1 0.799*** 0.813*** 0.799*** 0.822*** (0.006) (0.006) (0.006) (0.005) Spouse's Non-smoker status

at t-1

0.020*** 0.031*** 0.021*** 0.026*** (0.006) (0.006) (0.006) (0.005)

(3)

Respondent's normal weight at t-1

0.753*** 0.737*** 0.753*** 0.748*** (0.006) (0.006) (0.006) (0.006) Spouse's normal weight at t-1

0.010* 0.020*** 0.01 0.015**

(0.005) (0.007) (0.006) (0.006)

(3) Respondent's flu shot at t-1

0.440*** 0.465*** 0.438*** 0.472*** (0.013) (0.013) (0.013) (0.013) Spouse's flu shot at t-1

0.098*** 0.101*** 0.094*** 0.092*** (0.013) (0.013) (0.013) (0.013)

103 (4) Respondent's cholesterol screening at t-1 0.265*** 0.239*** 0.266*** 0.248*** (0.013) (0.013) (0.013) (0.012) Spouse's cholesterol screening at t-1 0.042*** 0.074*** 0.042*** 0.072*** (0.012) (0.013) (0.012) (0.012) (5) Respondent's prostate screening (male)/Pap smear test (female) at t-1

0.295*** 0.043*** 0.293*** 0.041*** (0.014) (0.015) (0.014) (0.015) Spouse's prostate screening

(female)/Pap smear test (male) at t-1 0.072*** 0.400*** 0.072*** 0.406*** (0.013) (0.014) (0.013) (0.014) (6) Respondent's prostate screening (male)/mammography (female) at t-1 0.294*** 0.424*** 0.292*** 0.426*** (0.014) (0.013) (0.014) (0.013) Spouse's prostate screening

(female)/mammography (male) at t-1

0.077*** 0.053*** 0.075*** 0.049*** (0.014) (0.013) (0.014) (0.013) Number of coupled observations

15,750

Number of couples

3,150

All columns show the marginal effect of the variable in question in separate models predicting the preventive activity at t. All regressions were controlled by controlled for the inverse mills ratio, age, age

squared, race, veteran status, working status (full time, part time, unemployed, partly retired, retired, disabled, other), number of household residents, self-reported health status, insurance status, life insurance status, long term care insurance, education years, mental health (CESD score), residence in one of 10 census

divisions and wave. Standard errors are in parentheses. ***, **, * denote statistical significance at the 1-percent, 5- percent, and 10-percent level, respectively.

In appendix table A.3.2, I repeat the analysis differentiating matching vs. bargaining but instead of pairing both members of household in the seemingly unrelated regressions for each preventive activity, I include all the preventive activities at once for each household member. In this manner, efficiency in the estimates is gained by the fact that the error terms are assumed to be correlated across the equations. The results are very similar to those in table 3.4.

In addition, I repeat table 3.4 but this time including the spouses‘ covariates

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little variation with respect to table 3.4. However, this specification proves to be highly collinear and thus is avoided.

Some more evidence regarding the effect of bargaining within the household comes from examining the couple‘s decision to start or stop one of the preventive behaviors in the survey. I look into whether the respondent‘s decision to start or stop one of these behaviors at t is affected not only by past respondent‘s and spouse‘s behavior, but also by concurrent spouse‘s decision. Initiation of preventive behavior takes place strictly when the person had not engaged in such behavior at the previous wave. Similarly, termination is indicated when such activity was present at t-1 (t-2 for clinical activities) but no longer observed at t. Table 3.5 presents summary statistics of preventive activity initiation and termination.

Table 3.5. Summary statistics for initiation and termination of preventive activity.

Preventive Activity Initiation of preventive activity Termination of preventive activity

Male Female Male Female

Physical activity 13.85% 12.98% 16.49% 16.47% (34.54%) (33.61%) (37.11%) (37.09%) Nonsmoker status 2.60% 2.32% 1.36% 1.23% (15.93%) (15.06%) (11.57%) (11.03%) Normal weight status 4.22% 4.47% 4.43% 5.81% (20.12%) (20.66%) (20.58%) (23.39%) Flu shot 17.91% 17.49% 4.41% 4.27% (38.35%) (37.99%) (20.53%) (20.23%) Cholesterol screening 13.04% 14.21% 7.07% 7.95% (33.68%) (34.92%) (25.63%) (27.05%)

105 Prostate screening

12.55% 9.90%

(33.14%) (29.87%)

Pap smear test 9.87% 14.14%

(29.83%) (34.85%)

Mammography 9.12% 17.02%

(28.80%) (37.58%)

Standard errors in parenthesis

Table 3.6 shows that for all behaviors except for physical activity, there is a strong and significant relationship between the household members‘ decision to initiate a

preventive activity regardless of the presence of individual level fixed effects (table A.3.4 in appendix shows similar results for termination). This lends credibility to the household bargaining process in which spouses are constantly negotiating their participation and termination of preventive behavior jointly. Notably, the magnitude of the effects decreases considerably once the fixed effects are added. This might indicate that the omitted

household effects in columns 1 and 2 biases upwards the coefficient on spouse activity initiation.

Table 3.6. Effect of spouse decision to initiate a given preventive behavior on respondent’s decision to start such behavior, full sample.

Dependent variables= Initiation of corresponding

preventive activity at t

(1) (2) (3) (4) SUR with no fixed

effects SUR with fixed effects Male Female Male Female

Spouse initiation of physical activity at t

0.128 0.128 0.066 0.065

(0.090) (0.090) (0.089) (0.070) Spouse initiation of non-smoker

status (i.e. quitting) at t

0.267*** 0.261*** # #

106 Spouse initiation of normal weight

status at t

0.024*** 0.025*** 0.013 0.019** (0.009) (0.010) (0.009) (0.009) Spouse initiation of flu shot at t

0.538*** 0.552*** 0.296*** 0.299*** (0.013) (0.014) (0.014) (0.014) Spouse initiation of cholesterol

screening at t

0.105*** 0.115*** 0.052*** 0.063*** (0.014) (0.015) (0.014) (0.015) Spouse initiation of Pap smear

screening (male respondents) prostate screening (female screening) at t

0.111*** 0.119*** 0.060*** 0.059*** (0.014) (0.015) (0.014) (0.015) Spouse initiation of

mammography (male

respondents) prostate screening (female respondent) at t

0.094*** 0.085*** 0.059*** 0.059*** (0.016) (0.014) (0.016) (0.013)

Number of coupled observations 15,750 Number of couples 3,150

All columns show the marginal effect of the variable in question in separate models predicting the initiation of each preventive activity at t. All regressions were controlled for respondent‘s and spouse's past participation in the relevant preventive activity at t-1, the inverse mills ratio, age, age squared, race, veteran status, working status (full time, part time, unemployed, partly

retired, retired, disabled, other), number of household residents, self-reported health status, insurance status, life insurance status, long term care insurance, education years, mental health

(CESD score), residence in one of 10 census divisions and wave. Standard errors are in parentheses.

***, **, * denote statistical significance at the 1-percent, 5-percent, and 10-percent level, respectively. # _{The models regarding smoking quitting did not converge when fixed}

effects at the individual level were included.

In 3.7, I repeat the analysis of the joint initiation of preventive activities with a reduced sample. Of the 15,750 observations of table 3.6, I dropped those observations that are not eligible to initiate a given preventive activity because they already engage in such. In appendix A.3.5, I do the proper for termination dropping those observations in which the dependent variable is not eligible to terminate a preventive activity because he or she is not undertaking it. The samples in both cases, initiation and termination, were reduced and is reported in both table 3.7 and table A.3.4, respectively. The results not only corroborate what was found in tables 3.6 and A.3.3, in fact, the magnitudes of the association between spouses are even stronger when only people that are eligible are studied.

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Table 3.7. Effect of spouse decision to initiate a given preventive behavior on respondent’s decision to start such behavior among those eligible to initiate.

Dependent variables= Initiation of corresponding preventive activity at t among people

eligible to initiate

SUR with no fixed effects

SUR with fixed effects

Number of observations (Number

of individuals) Male Female Male Female Male Female

Spouse initiation of physical

activity at t 0.02 0.012 0.011 0.008

7,187 9,025 (0.014) (0.009) (0.015) (0.012) (2,335) (2,915) Spouse initiation of non-

smoker status (i.e. quitting) at t

0.609*** 0.226*** 0.327*** 0.259*** 2,183 2,890 (0.034) (0.012) (0.035) (0.024) (1,174) (1,815) Spouse initiation of normal

weight status at t 0.027** 0.022** 0.014 0.027**

9,202 8,652 (0.011) (0.010) (0.011) (0.013) (2,420) (2,531) Spouse initiation of flu shot

at t 0.691*** 0.519*** 0.389*** 0.372*** 2,362 2,653 (0.021) (0.016) (0.022) (0.021) (1,537) (1,748) Spouse initiation of cholesterol screening at t 0.184*** 0.094*** 0.090** 0.103*** 1,332 1,584 (0.039) (0.019) (0.039) (0.036) (927) (1,095) Spouse initiation of Pap

smear screening (male respondents) prostate screening (female screening) at t 0.204*** 0.193*** 0.111*** 0.095*** 783 2,074 (0.037) (0.033) (0.038) (0.031) (586) (1,425) Spouse initiation of mammography (male respondents) prostate screening (female respondent) at t 0.137*** 0.147*** 0.085** 0.116*** 619 1,441 (0.040) (0.039) (0.042) (0.037) (466) (1,015) All columns show the marginal effect of the variable in question in separate models predicting the initiation of each preventive activity at t. All regressions were controlled for respondent‘s and spouse's past participation in the relevant preventive activity at t-1, the inverse mills ratio, age, age squared, race, veteran status, working status (full time, part time, unemployed, partly retired, retired, disabled, other), number of

household residents, self-reported health status, insurance status, life insurance status, long term care insurance, education years, mental health (CESD score), residence in one of 10 census divisions and wave. Standard errors are in parentheses. ***, **, * denote statistical significance at the 1-percent, 5-percent, and

10-percent level, respectively. .

In addition, I look at a variation on the specification for changes in weight. Instead of examining the effect of spouse‘s initiation or termination of a normal weight status, I look at the association between spouses‘ changes in BMI. Table 3.8 presents the results of seemingly

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unrelated regressions between spouses with and without fix effect. The correlations are positive and significant even when fixed effects are included.

Table 3.8. Effect of spouse’s BMI change on respondent’s BMI change.

Dependent variable=Respondent's

change in BMI

(1) (2) (3) (4) SUR with no fixed

effects SUR with fixed effects Male Female Male Female

Spouse BMI change 0.133*** 0.208*** 0.069*** 0.102*** (0.007) (0.012) (0.008) (0.011) Seemingly unrelated regression of both household members' BMI at t. All regressions were controlled with the inverse mills ratio, age, age squared, race, veteran status, working status (full time, part time, unemployed, partly retired, retired, disabled, other), number of household residents, self-reported health

status, insurance status, life insurance status, long term care insurance, education years, mental health (CESD score), residence in one of 10 census

divisions and wave. Standard errors are in parentheses. ***, **, * denote statistical significance at the 1-percent, 5-percent, and 10-percent level,

respectively.