bargaining power that may be correlated with the education and assets measures. While spouses’ education are included as a potential bargaining source, its caveats are already discussed (see section 2). My focus, however, is not to evaluate intrahousehold bargaining based on education, but to control for any potential correlation between education and asset measures of bargaining.

**Individual health and occupation** : There is limited variation across rounds even in the short-term health outcome measure, an individual’s weight (in kilograms) for height (in centimeters). Boys tend to do better than girls and adult males better than adult females, while this gender difference reverses for the adolescent group. This might be indicative of some transitory catch-up for females as they past childhood, which later disappears as they progress toward adulthood.

As mentioned before, occupation data were collected once in the survey. These were coded into 47 different occupations. Based on the metabolic constant (mc) provided for a detailed list of activities for male and female in World Health Organization (1985), I classify the energy intensity of occupations into high ( _mc >_ 4), medium (2 _._ 5 _< mc ≤_ 4), and low ( _mc ≤_ 2 _._ 5) category<sup>16</sup> . Energy intensity of occupation of different age-sex group vis-a-vis their energy intake are further discussed below. As described in Section 4, both the energy intensity of occupation and health outcome are utilized to construct the health endowment measure.

**Calorie intake and energy-intensity of occupation** : A useful feature of IFPRI survey is that it provides individual food intake data for each round using a 24-hour recall methodology asking the person with primary responsibility for preparing meals, about recipes prepared, ingredients for those recipes and amounts eaten by various family members and guests. The survey has information of quantity of individual intakes of about 200 food items (categorised into 17 food groups), which are converted into calories, protein, and micronutrients (vitamin A, vitamin C, vitamin D, niacin, riboflavin, thiamine, folate, iron, and calcium).

Calorie intake data broadly resembles to PRH claim that gender difference in calorie allocation is age-dependent and so is the gender difference in energy-intensity of occupations. To replicate PRH finding in IFPRI sample, I first use PRH’s age-group classification ((age _<_ 6, 6 _≤_ age _<_ 12, and age _≥_ 12). The mean calorie consumption (averaged over four rounds) across age-groups are higher in IFPRI than in PRH sample (see Table 2). However, there is no significant gender difference for the group less than _<_ 6 years. Conversely, consistent with PRH, I find significant gender difference for the age-group _≥_ 12 years. While PRH does not find any significant gender

> 16PRH cited the same source for classification of energy intensity of occupations but did not describe different cut-off points of mc they used for their classification. Basal metabolic rate (BMR) for an individual is the amount of energy spent when the person is in sleep. Energy requirement for different activities per minute is BMR times the mc of that activity. For instance, mc for cleaning house for a female is 3, while that for digging earth for male is 5.7.

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