Identifying Non-Cooperative Behavior Among Spouses:

Child Outcomes in Migrant-Sending Households

Session 4E: Growth, Jobs and EarningsMay 15, 2008

Joyce ChenOhio State University

• When monitoring is imperfect, allocations can only be coordinated to the extent that they can be verified

• Household decision-making may not be fully cooperative – individuals may attempt to conceal allocations from each other

• Migration increases the scope for such behavior in so far as it induces household members to maintain separate residences

Motivation

• Determine how transparency of income affects intra-household allocation– Improve targeting of development programs – Better understand the consequences of migration on

sending households

• Examine another, less commonly studied dimension of migration – migration with the intent to rejoin the sending household

Non-Cooperative Decision-Making

• When transaction costs of cooperation are high, households revert to non-cooperation (Lundberg and Pollak, 1993)

• This will not affect provision of household public goods unless production is organized along “separate spheres”

• Migration increases cost of monitoring allocations and forces household production into a separate sphere

A Simple Example

• A household consists of two decision-makers, a husband and a wife

• Individuals consume two public goods, x and y

• When the husband migrates, he must rely on his wife for the provision of public goods

• x is easily observable, but y is difficult to monitor

A Simple Example

• When migration occurs, the husband and wife can still reach a cooperative agreement on x

• But determination of y is more likely to default to a non-cooperative process

• Non-cooperative behavior implies – Shift in consumption towards goods preferred by the

wife, but only if those goods are difficult to monitor– Magnitude of these changes will be responsive to the

efficacy/intensity of monitoring

Data and Specification

• China Health and Nutrition Survey– 5 rounds (1989, 1991, 1993, 1997, 2000)– approx. 4000 households and 15,000 individuals– Observable outcomes – height, weight, schooling– Less observable inputs – individual time allocation,

nutritional intake

• 1990s were a period of rapid growth in intra-national migration in China, fueled by relaxation of migration restrictions and increased openness and marketization

Data and Specification

• Migration defined as living away from home for at least one month in the last year

• Most outcomes defined over the previous one week – restrict sample to dads away during the entire week preceding the survey

• To distinguish non-cooperative behavior from income effects, control for full income with wages and productive assets

Data and Specification

• Migration is endogenous - individual fixed effects included to control for unobserved characteristics correlated with migration

• Community-year fixed effects included to control for time-varying factors correlated with migration

• Estimate reduced-form demand equations for schooling, health and household labor

Data and Specification

• Include number of months away– Proxy for intensity of monitoring– Outcomes may require time to adjust

• Allow child’s age and number of sibling, by gender, to vary with father’s migration status

• Additional controls for parents’ ages, household size and month and year of survey

Identifying the Counterfactual

• Direct effects of migration– Reduction in father’s household labor– Increase in household income– Possible change in bargaining power

• Appropriate counterfactual is the set of allocations that would have been chosen, conditional on these changes, if spouses could costlessly commit to cooperation

Identifying the Counterfactual

• Reduction in father’s household labor: increases mother’s household labor, ambiguous effect on child household labor

• Increase in household income: increases mother’s household labor and decreases child household labor

• Increase in father’s bargaining power: also increases mother’s household labor and decreases child household labor

Distinguishing Non-Cooperation

• Migration in a cooperative model should increase mother’s household labor, unless migration increases mother’s bargaining power

• Non-cooperative model suggests that the mother will decrease own household labor when the father migrates because time allocation is difficult to monitor

• Mothers’ labor, both in the household and in income-generating activities, is decreasing in months the father is away

• Decrease in mother’s household labor is not consistent with a model in which decision-making is cooperative and time allocation adjusts to compensate for the father’s absence

Table 2. Mothers' Time Allocation,Mother Fixed Effects Estimates

Do Any Work HoursChores (ex. chores)

Father Away 0.077 * 12.19(1.66) (1.52)

Months Father Away -0.031 -5.581 *(1.63) (1.81)

Months Away Squared 0.002 0.459 *(1.48) (1.90)

Marginal Effect of Away -0.041 -4.397(1.36) (1.03)

Sample Mean 0.974 43.50Observations 6450 5996

• Probability that girls do either chore is increasing in months away, and the opposite for boys

• Statistically significant only for laundry, but average marginal effects are quite large

Table 3. Children's Time Allocation, Child Fixed Effects Estimates

Prepare DoFood Laundry

Boys Girls Boys GirlsDad Away 0.253 -0.116 0.228 -0.365

(1.51) (0.56) (1.17) (1.27)Months Away -0.047 0.065 -0.084 * 0.164 **

(0.97) (1.01) (1.65) (2.11)(Months Away)^2 0.003 -0.003 0.007 * -0.013 **

(0.82) (0.63) (1.79) (2.19)(Age-6)*Away -0.044 0.006 0.013 -0.015

(1.15) (0.11) (0.31) (0.21)(Age-6)^2*Away 0.004 0.000 -0.001 0.002

(0.95) (0.07) (0.35) (0.25)Marginal Effect of Away -0.064 0.120 -0.061 0.191

(0.74) (1.07) (0.07) (1.56)

Sample Mean 0.057 0.117 0.073 0.187Observations 8476 8329

• The level of household production is observable, but the inputs to production are not – substitute children’s time for mom’s

• Results may be consistent with a cooperative model of the household if migration increases mothers’ bargaining power

• Should lead to changes in other goods favored by mothers, e.g. child health (Duflo, 2003; Thomas 1990)

• No significant effects on child health - not consistent with an increase in mother’s bargaining power

• But large changes in calorie intake - changes in time allocation must be balanced with changes in nutrition in order to maintain health

Table 4. Children's Health and Nutrition, Child Fixed Effects Estimates

Body Mass Daily CalorieIndex Intake

Boys Girls Boys GirlsDad Away -0.671 0.657 288.0 -409.8

(0.80) (0.38) (1.04) (0.92)Months Away 0.203 -0.18 10.96 53.31

(0.80) (0.40) (0.12) (0.38)(Months Away)^2 -0.025 0.02 -3.574 -2.433

(1.13) (0.52) (0.43) (0.22)(Age-6)*Away 0.155 -0.539 -181.0 ** 211.4 *

(0.60) (1.03) (2.05) (1.76)(Age-6)^2*Away -0.015 0.063 18.11 ** -24.68 **

(0.61) (1.21) (1.98) (1.99)Marginal Effect of Away 0.351 -0.898 -139.7 160.5

(0.96) (1.05) (0.98) (0.70)

Sample Mean 17.14 17.11 1851 1711Observations 6121 7303

• Changes in time allocation are larger for – Children who are more productive– Activities that provide higher disutility to mothers

• Siblings have a reinforcing effect on the extensive margin and an offsetting effect on the intensive margin

• Mothers’ BMI appears stable – In fact, mothers consume less calories and protein to

conceal the reduction in their household labor– Suggests that non-cooperative behavior occurs in

equilibrium because an incentive-compatible contract must give moms higher consumption of private goods

Conclusion

• Mothers do engage in non-cooperative behavior, in a surprising way

– Not consistent with change in bargaining power– Not consistent with reallocation of time to compensate

for father’s absence

• But, in this case, it is largely innocuous - does not appear to affect children’s human capital accumulation

Further Research

• Need data on both migrants and sending households to provide a complete picture of migration and its economic impact– Importance of transparency, monitoring and

enforcement… for both parties– Policies that affect migration decisions and

circumstances

• Improve data collection for temporary migrants, e.g. income vs. remittances, travel and visitation patterns, individual expenditures