Research Database

We show how to use panel data on household consumption to directly estimate households’ risk preferences. Specifically, we measure heterogeneity in risk aversion among households in Thai villages using a full risk-sharing model, which we then test allowing for this heterogeneity. There is substantial, statistically significant heterogeneity in estimated risk preferences. Full insurance cannot be rejected. As the risk sharing, as-if-complete-markets theory might predict, estimated risk preferences are unrelated to wealth or other characteristics. The heterogeneity matters for policy: Although the average household would benefit from eliminating village-level risk, less-risk-averse households who are paid to absorb that risk would be worse off by several percent of household consumption.

We develop a new methodology to compute differences in the expected longevity of individuals who are in different socioeconomic groups at age 50. We deal with two main problems associated with the standard use of life expectancy: that people’s socioeconomic characteristics evolve over time and that there is a time trend that reduces mortality over time. Using HRS data for individuals from different cohorts, we estimate a hazard model for survival with time-varying stochastic endogenous covariates that yields the desired expected durations. We uncover an enormous amount of heterogeneity in expected longevities between individuals in different socioeconomic groups, albeit less than implied by a naive (static) use of socioeconomic characteristics. Our analysis allows us to decompose the longevity differentials into differences in health at age 50, differences in mortality conditional on health, and differences in the evolution of health with age. Remarkably, it is the latter that is the most important for most socioeconomic characteristics. For instance, education and wealth are health protecting but have little impact on two-year mortality rates conditional on health. Finally, we document an increasing time trend of all these differentials in the period 1992–2008, and a likely increase in the socioeconomic gradient in mortality rates in the near future. The mortality differences that we find have huge welfare implications that dwarf the differences in consumption accruing to people in different socioeconomic groups.

This paper develops a model with partial insurance against idiosyncratic wage shocks to quantify risk sharing, and to decompose inequality into life-cycle shocks versus initial heterogeneity in preferences and productivity. Closed-form solutions are obtained for equilibrium allocations and for moments of the joint distribution of consumption, hours, and wages. We prove identification and estimate the model with data from the CEX and the PSID over the period 1967–2006. We find that (i) 40% of permanent wage shocks pass through to consumption; (ii) the share of wage risk insured privately increased until the early 1980s and remained stable thereafter; (iii) life-cycle productivity shocks account for half of the cross-sectional variance of wages and earnings, but for much less of dispersion in consumption or hours worked.

Fifty-eight years ago, Harberger (1954) estimated that the costs of monopoly, which resulted from misallocation of resources across industries, were trivial. Others showed the same was true for tariffs. This research soon led to the consensus that monopoly costs are of little significance—a consensus that persists to this day.

This paper reports on a new literature that takes a different approach to the costs of monopoly. It examines the costs of monopoly and tariffs within industries. In particular, it examines the histories of industries in which a monopoly is destroyed (or tariffs greatly reduced) and the industry transitions quickly from monopoly to competition. If there are costs to monopoly and high tariffs within industries, we should be able to see these costs whittled away as the monopoly is destroyed.

In contrast to the prevailing consensus, this new research has identified significant costs of monopoly. Monopoly (and high tariffs) is shown to significantly lower productivity within establishments. It also leads to misallocation within industry: resources are transferred from high to low productivity establishments.

From these histories a common theme (or theory) emerges as to why monopoly is costly. When a monopoly is created, “rents” are created. Conflict emerges among shareholders, managers, and employees of the monopoly as they negotiate how to divide these rents. Mechanisms are set up to split the rents. These mechanisms are often means to reduce competition among members of the monopoly. Although the mechanisms divide rents, they also destroy them (by leading to low productivity and misallocation).