Research Database

The current literature offers two views on the nature of the labor income process. According to the first view, which we call the “restricted income profiles” (RIP) model, individuals are subject to large and very persistent shocks while facing similar life-cycle income profiles (MaCurdy, 1982). According to the alternative view, which we call the “heterogeneous income profiles” (HIP) model, individuals are subject to income shocks with modest persistence while facing individual-specific income profiles (Lillard and Weiss, 1979). In this paper we study the restrictions imposed by the RIP and HIP models on consumption data—in the context of a life-cycle model—to distinguish between these two hypotheses. In the life-cycle model with a HIP process, which has not been studied in the previous literature, we assume that individuals enter the labor market with a prior belief about their individual-specific profile and learn over time in a Bayesian fashion. We find that learning is slow, and thus initial uncertainty affects decisions throughout the life cycle. The resulting HIP model is consistent with several features of consumption data including (i) the substantial rise in within-cohort consumption inequality, (ii) the non-concave shape of the age-inequality profile, and (iii) the fact that consumption profiles are steeper for higher educated individuals. The RIP model we consider is also consistent with (i), but not with (ii) and (iii). These results bring new evidence from consumption data on the nature of labor income risk.

The article shows that in a finite-trader version of the Diamond and Dybvig model (1983), the ex ante efficient allocation can be implemented as a unique equilibrium. This is so even in the presence of the sequential service constraint, as emphasized by Wallace (1988), whereby the bank must solve a sequence of maximization problems as depositors contact it at different times. A three-trader example with constant relative risk-aversion utility is used in order to illustrate clearly the requirements that the sequential service constraint imposes on implementation.

This study assesses five common explanations for the large decline in U.S. total factor productivity (TFP) during the Great Depression: changes in capacity utilization, factor input quality, and production composition; labor hoarding; and increasing returns to scale. The study finds that these factors explain less than one-third of the 18 percent TFP decline between 1929 and 1933. The rest of the decline remains unexplained. The study offers a potential explanation: declines in organization capital, the knowledge firms use to organize production, caused by breakdowns in relationships between firms and their suppliers, for example. As some firms failed during the Depression, efficiency in surviving firms decreased; managers had to shift time away from production in order to establish new relationships, and firms had to shift to unfamiliar technologies that initially were operated inefficiently.

This study describes how the U.S. government measures real consumption growth and how it tries to take account of a complicating factor: that the goods and services offered to consumers change over time; new products are introduced and old products are improved. The 1996 Boskin Commission critique of this government methodology is described, along with the changes made in response to that critique. Also described is recent research related to how real consumption growth should be measured in the presence of new and better products.

The Suffolk Bank in Boston is well known as having been the clearinghouse for virtually all the banknotes that circulated in New England between 1836 and 1858. An examination of 19th century bank balance sheets shows that during and after the U.S. banking Panic of 1837, this private commercial bank also provided some services that today are provided by central banks. These include lending reserves to other banks (providing a discount window) and keeping the payments system operating. Because of Suffolk’s activities, banks in New England fared better than banks elsewhere during the Panic of 1837. And after the panic, when much of the United States suffered a prolonged economic slowdown, New England fared better than the rest of the country, at least partly because of Suffolk’s central bank-like activities.

This study evaluates the conventional wisdom that modern Phillips curve-based models are useful tools for forecasting inflation. These models are based on the non-accelerating inflation rate of unemployment (the NAIRU). The study compares the accuracy, over the last 15 years, of three sets of inflation forecasts from NAIRU models to the naive forecast that at any date inflation will be the same over the next year as it has been over the last year. The conventional wisdom is wrong; none of the NAIRU forecasts is more accurate than the naive forecast. The likelihood of accurately predicting a change in the inflation rate from these three forecasts is no better than the likelihood of accurately predicting a change based on a coin flip. The forecasts include those from a textbook NAIRU model, those from two models similar to Stock and Watson’s, and those produced by the Federal Reserve Board.

This article reviews recent work that generalizes a random matching model of money to permit there to be a mix of transactions: some accomplished through the use of tangible media of exchange and the rest through some form of credit. The generalizations are accomplished by specifying assumptions about common knowledge of individual histories that are intermediate between no common knowledge and complete common knowledge. One of the specifications permits a simple representation of the sense in which more common knowledge is beneficial. The other permits a comparison between using outside money and using inside money as a medium of exchange.