Knowledge that Transforms

General equilibrium models that predict a reduction in asset prices when baby boomers retire typically assume that people consume all of their wealth before they die. However, many people hold substantial wealth when they die. I develop a rational expectations, general equilibrium model with a bequest motive. In this model, a baby boom increases stock prices, and stock prices are rationally anticipated to fall when the baby boomers retire, even though consumers continue to hold assets throughout retirement. The continued high demand for assets by retired baby boomers does not attenuate the fall in the price of capital.

Although it is clear that the volatility of asset returns is serially correlated, there is no general agreement as to the most appropriate parametric model for characterizing this temporal dependence. In this paper, we propose a simple way of modeling financial market volatility using high-frequency data. The method avoids using a tight parametric model by instead simply fitting a long autoregression to log-squared, squared, or absolute high-frequency returns. This can either be estimated by the usual time domain method, or alternatively the autoregressive coefficients can be backed out from the smoothed periodogram estimate of the spectrum of log-squared, squared, or absolute returns. We show how this approach can be used to construct volatility forecasts, which compare favorably with some leading alternatives in an out-of-sample forecasting exercise.

Enterprise restructuring is expected to improve efficiency in transition economies. With data from former East Germany, we compare the efficiency of family farms and partnerships with large-scale successor organizations of the collective and state farms (LSOs). Using parametric and nonparametric techniques, we show that LSOs display lower technical efficiency than do family farms and partnerships but that this difference is small and declining during transition, mainly as a result of structural changes in agriculture. Family farms are not as scale efficient as partnerships and LSOs, and partnerships are superior to all other organizational forms.

A longstanding issue in empirical economics is the behavior of average labor productivity over the business cycle. This paper provides new insights into the cyclicality of aggregate labor productivity by examining the cyclical behavior of productivity at the plant level as well as the role of reallocation across plants over the cycle. We find that plant-level productivity is even more procyclical than aggregate productivity, because short-run reallocation yields a countercyclical contribution to labor productivity. At the plant level, we find that cyclicality of productivity varies systematically with long-run employment growth. Over the course of the cycle, plants that are long-run downsizers exhibit significantly greater procyclicality of productivity than do long-run upsizers. When we control for the direction of a cyclical shock, we find that the fall in productivity from an adverse cyclical shock for long-run downsizers is significantly larger in magnitude than is the fall in productivity from an equivalent adverse cyclical shock for long-run upsizers. We argue that these findings raise questions about one of the most popular explanations of procyclical productivity: changing factor utilization over the cycle.

Using a large data set, the authors find that smokers select riskier jobs, but receive lower total wage compensation for risk than do nonsmokers. This finding is inconsistent with conventional models of compensating differentials. The authors develop a model in which worker risk preferences and job safety performance lead to smokers facing a flatter market offer curve than nonsmokers. The empirical results support the theoretical model. Smokers are injured more often controlling for their job's objective risk and are paid less for these risks of injury. Smokers and nonsmokers, in effect, are segmented labor market groups with different preferences and different market offer curves.

Using two decades of annual data, we explore the links between real exchange rates and employment, wages, and overtime activity in U.S. manufacturing industries. Especially in industries with lower price-over-cost markups, exchange rates have statistically significant effects on industry wages, with the magnitude of these effects rising as industries increase their export orientation and declining as imported input use becomes more important. Exchange rate implications for jobs and hours worked are smaller and less precisely measured. We find a much higher response of overtime wages and overtime hours to transitory exchange rates movements.

Several specifications of state-space models are used to obtain estimates of the NAIRU for the G7 except Japan, plus Australia, over the past 28 years. A Phillips curve-type regression is shown to deliver estimates that do not mimic low-frequency movements in unemployment rates, even when a drift is included in the specification of the NAIRU. Standard errors around the estimates are extremely large. Using information about the behavior of unemployment, in addition to inflation, alleviates both these shortcomings.

Estimates of the Taylor rule using historical data from the past decade or two suggest that monetary policy in the U.S. can be characterized as having reacted in a moderate fashion to output and inflation gaps. In contrast, the parameters of optimal Taylor rules derived using empirical models of the economy often recommend much more vigorous policy responses. This paper attempts to match the historical policy rule with an optimal policy rule by incorporating uncertainty into the derivation of the optimal rule and by examining plausible variations in the policymaker's model and preferences.

We measure income uncertainty at the level of U.S. states, and the extent to which it has been reduced through risksharing, using a method recently developed by Athanasoulis and van Wincoop (2000). Risk is measured as the standard deviation of state-specific income growth uncertainty, measured by using the error term of a regression of income growth on variables in the information set. Risk sharing is measured by the extent to which this standard deviation has been reduced through financial markets and federal fiscal policy. The advantage of this measure over the existing risk sharing literature is that the interpretation does not depend on many auxiliary assumptions. Our findings on the extent of risk sharing are insensitive to the only assumption we need to make, the variables that are in the information set. We find that the standard deviation of state-specific income growth uncertainty is reduced by less than half through financial markets and federal fiscal policy. We show that the extent of risk sharing would be much higher if agents held better diversified portfolios across the states.

This paper examines the evolution of productivity in U.S. manufacturing plants from 1963 to 1992. We define a vintage effect as the change in productivity of recent cohorts of new plants relative to earlier cohorts of new plants, and a survival effect as the change in productivity of a particular cohort of surviving plants as it ages. Both factors contribute to industry productivity growth, but play offsetting roles in determining a cohort's relative position in the productivity distribution. Recent cohorts enter with higher productivity than earlier entrants did, whereas surviving cohorts show productivity increases as they age. These two effects roughly offset each other, however, so there is a rough convergence in productivity across cohorts in 1992 and 1987.