In this paper, a formal test of intra-household commitment is derived and performed. To that end, two models of household intertemporal behaviour are developed. In both models, household members are characterized by individual preferences. In the first formulation, household decisions are always on the ex ante Pareto frontier. In the second model, the assumption of intra-household commitment required by ex ante efficiency is relaxed. It is shown that the full-efficiency household Euler equations are nested in the no-commitment Euler equations. Using this result, the hypothesis that household members can commit to future allocations of resources is tested using the Consumer Expenditure Survey. I strongly reject this hypothesis. It is also shown that the standard unitary framework is a special case of the full-efficiency model. However, if household members are not able to commit, household intertemporal behaviour cannot be characterized using the standard life-cycle model. These findings have two main implications. First, policy makers can change household behaviour by modifying the decision power of individual household members. Second, to evaluate programmes designed to improve the welfare of household members, it would be beneficial to replace the standard unitary model with a characterization of household behaviour that allows for lack of commitment.

Saving decisions are made jointly by household members who generally earn risky incomes. Consequently, to interpret saving patterns it is crucial to analyze the relationship between intra-household risk sharing and intertemporal choices. To that end in this paper the household is characterized as a group of agents with possibly heterogeneous preferences making efficient decisions. Two results are obtained. First, it is shown that risk sharing can increase the amount saved by the household. Second, I find that an increase in risk aversion and prudence of an individual member can reduce household risk aversion and prudence. These results are consistent with the empirical evidence collected using the HRS. 1

We document that the US marriage market is characterized by two systematic empirical patterns. First, there is a quantitatively large, strong, and persistent negative relationship between changes in cohort size and marriage rates of women. Second, the same negative correlation holds for men. We then establish the features a model should possess to generate these patterns. A standard matching model with search frictions is rejected by the data because it produces a negative relationship for women but a positive relationship for men. We generalize the standard model to show under what conditions it rationalizes both patterns.

We discuss the most popular static and dynamic models of household behavior. Our main objective is to explain which aspects of household decisions different models can account for. Using this insight, we describe testable implications, identification results, and estimation findings obtained in the literature. Particular attention is given to the ability of different models to answer various types of policy questions.

In this paper, we develop a dynamic model of politicians who can engage in corruption. The model provides important insights into the determinants of corruption and how to design policies to combat it. We estimate the model using data from Brazil to measure voters’ willingness to pay for various commonly proposed anticorruption policies, such as increasing audit probabilities, raising politicians’ wages, and extending term limits. We document that while audit policies effectively reduce corruption, a multipronged approach that bundles an audit policy with other policies can achieve much higher welfare gains.

Testing Efficient Risk Sharing with Heterogeneous Risk Preferences: Reply by Maurizio Mazzocco and Shiv Saini. Published in volume 108, issue 10, pages 3114-15 of American Economic Review, October 2018

We propose a method that enables one to test efficient risk sharing even when households have different risk preferences. The method is composed of three tests. The first one determines whether in the data households have homogeneous risk preferences. The second and third tests evaluate efficient risk sharing when the hypothesis of homogeneous risk preferences is rejected. We use this method to test efficient risk sharing in rural India. Using the first test, we strongly reject the hypothesis of identical risk preferences. Using the second and third tests, we reject efficiency at the village but not at the caste level.

Aggregate shocks affect most households’ and firms’ decisions. Using three stylized models, we show that inference based on cross-sectional data alone generally fails to correctly account for decision making of rational agents facing aggregate uncertainty. We propose an econometric framework that overcomes these problems by explicitly parameterizing the agents’ decision problem relative to aggregate shocks. Our framework and examples illustrate that the cross-sectional and time-series aspects of the model are often interdependent. Therefore, estimation of model parameters in the presence of aggregate shocks requires the combined use of cross-sectional and time-series data. We provide easy-to-use formulas for test statistics and confidence intervals that account for the interaction between the cross-sectional and time-series variation. Lastly, we perform Monte Carlo simulations that highlight the properties of the proposed method and the risks of not properly accounting for the presence of aggregate shocks.

Using the Panel Study of Income Dynamics, we provide evidence that to understand household decisions and evaluate policies designed to affect individual welfare, it is important to add an intertemporal dimension to the by-now standard static collective models of the household. Specifically, we document that the observed differences in labor supply by gender and marital status do not arise suddenly at the time of marriage, but rather emerge gradually over time. We then propose an intertemporal collective model that has the potential of explaining the observed patterns.