Fatter attraction: anthropometric and socioeconomic matching ... - Ivie

Table 13: SUR Regressions of Wife’s Characteristics on Husband’s Characteristics.
Full sample broken down by Family Income (below and above the median).
I. Low Family Income Wife’s BMI Wife’s Education
A. Index’s coefficients on
Husband’s Log Wage
−0.480***
(0.159)
0.405***
(0.120)
Husband’s BMI 0.065*
(0.035)
Wife’s Age 0.032***
(0.010)
−0.070***
(0.025)
−0.021***
(0.008)
R 2 0.07 0.10
Sample size 2,126
B. MRS = ratio of coefficients
Husband’s Log Wage
Husband’s BMI
−7.36
(4.61)
Equality of ratios test Chi 2 (1) = 0.09
(p-value = 0.7639)
−5.79**
(2.64)
II. High Family Income Wife’s BMI Wife’s Education
A. Index’s coefficients on
Husband’s Log Wage
−0.361***
(0.140)
0.456***
(0.101)
Husband’s BMI 0.110***
(0.037)
Wife’s Age 0.038***
(0.010)
−0.077***
(0.025)
−0.028***
(0.008)
R 2 0.08 0.11
Sample size 2,125
B. MRS = ratio of coefficients
Husband’s Log Wage
Husband’s BMI
−3.28**
−5.94***
(1.65)
(2.33)
Equality of ratios test Chi 2 (1) = 0.95
(p-value = 0.3298)
Note: We consider individuals who are in the normal-overweight range, BMI [18.5, 30).
Wife’s age is in the range [20, 50]. Bootstrapped standard errors (1,000 replications based on
1,099 (low income) and 1,030 (high income) clusters in household head id) are reported in
parentheses. All regressions include state and year fixed effects.
*** p-value < 0.01, ** p-value < 0.05, * p-value < 0.1
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