Research Database

This study argues that strong evidence contradicting the traditional assumption of time-consistent preferences is not available. The study builds and analyzes the implications of a deterministic general equilibrium model and compares them to data from the U.S. asset market. The model implies that (1) because of dynamic arbitrage, the prices of retradable assets cannot reveal whether preferences are time-inconsistent; but (2) the prices of commitment assets, investments which must be held for their lifetime, can. These prices will be higher than the present values of their future payoffs only when preferences are time-inconsistent. And (3) when preferences are time-inconsistent, people will not hold both retradable and commitment assets. Empirical observations on two examples of commitment assets—education and individual retirement accounts—are not consistent with these model implications.

This article describes a newly constructed data set of all U.S. state banks from 1782 to 1861. It contains the names and locations of all banks and branches that went into business and an estimate of when each operated. The compilation is based on reported balance sheets, listings in banknote reporters, and secondary sources. Based on these data, the article presents a count of the number of banks and branches in business by state. I argue that my series are superior to previously existing ones for reasons of consistency, accuracy, and timing. The article contains examples to support this argument.

The welfare effects of alternative monetary arrangements are computed for an economy calibrated to U.S. data. In the model world, people vary their holdings of liquid assets in order to smooth their consumption. In such worlds, we find that the feature of an arrangement that matters is the equilibrium after-tax real return on savings. We also find that relative to a tax on labor income, seigniorage is a poor source of revenue.

We study transition in a model in which the process of moving workers from matches in the state sector to new matches in the private sector takes time and involves uncertainty. When there are incentive problems in this rematching process, the optimal scheme may involve forced layoffs, involuntary unemployment, and a recession.

This paper surveys recently developed methods for Bayesian inference and their use in economic time series models. It begins by reviewing aspects of Bayesian inference essential to understanding the implications of the Bayesian paradigm for time series analysis. It next describes the use of posterior simulators to solve otherwise intractable analytical problems. The theory and the computational advances are brought together in setting forth a practical framework for decision-making and forecasting. These developments are illustrated in the context of the vector autoregressions, stochastic volatility models, and models of changing regimes.

Social learning plays an important role in models of productivity dispersion and long-run growth. In economies with a continuum of producers and unbounded productivity distributions, social learning can sometimes leave long-run growth rates completely indeterminate. This paper modifies a model in which potential entrants attempt to imitate randomly selected incumbent firms by introducing an upper bound on how much entrants can learn from incumbents. When this upper bound is taken to infinity, a unique long-run growth rate emerges, even though the economy without upper bound has an unbounded continuum of balanced growth rates.