Research Database

We present a simple theory of the quality of elected officials. Quality has (at least) two dimensions: competence and honesty. Voters prefer competent and honest policymakers, so high-quality citizens have a greater chance of being elected to office. But low-quality citizens have a “comparative advantage” in pursuing elective office, because their market wages are lower than the market wages of high-quality citizens (competence), and/or because they reap higher returns from holding office (honesty). In the political equilibrium, the average quality of the elected body depends on the structure of rewards from holding public office. Under the assumption that the rewards from office are increasing in the average quality of office holders there can be multiple equilibria in quality. Under the assumption that incumbent policymakers set the rewards for future policymakers there can be path dependence in quality.

This paper begins with the observation that the volatility of factor input growth is insufficient to explain the volatility in the growth rate of output, and explores the empirical plausibility of the hypothesis that this fact is due to the presence of productive externalities and increasing returns to scale. We construct a quantitative equilibrium macroeconomic model which incorporates these features, and allows for demand shocks operating at the level of the consumer. We employ the method of Hall (1986) and Parkin (1988) to measure these demand shocks, and use these measured disturbances to conduct stochastic simulations of the model. We find that the model with increasing returns, when driven by measured demand shocks, generates time series which replicate the basic stylized facts of U.S. business cycles, although with lower amplitude. However, in the absence of increasing returns the measured demand shocks do not produce a characteristic business cycle response. When preference shocks are combined with productivity shocks, we find that both the increasing returns and the constant returns models correctly predict a weak correlation between hours and wages, while the predictions of the increasing returns model provide the better overall match with the data.

This paper studies the empirical performance of stochastic volatility models for twenty years of weekly exchange rate data. We concentrate on the effects of the distribution of the exchange rate innovations for parameter estimates and for estimates of the latent volatility series. We approximate the density of the log of exchange rate innovations by a mixture of normals. The major findings of the paper are that: (1) explicitly incorporating fat-tailed innovations increases the estimates of the persistence of volatility dynamics; (ii) estimates of the latent volatility series depend strongly on the estimation technique; (iii) the estimation error of the volatility time series is so large that finance applications to option pricing should be interpreted with care. We reach these conclusions using three different estimation techniques: quasi maximum likelihood, simulated EM, and a Bayesian procedure based on the Gibbs sampler.

This paper examines the response of sectoral real wages and location probabilities to oil price shocks using U.S. micro-panel data (the National Longitudinal Survey of Young Men). The goal is to determine whether the observed response patterns are consistent with so-called “sectoral shift” theories of unemployment. These theories predict that shocks that change sectoral relative wages should increase unemployment in the short run and lead to labor reallocation in the long run. Consistent with these predictions, the oil price changes of the 1970s resulted in substantial movements in industry relative wages and significant reallocation of labor across industries, while both oil price increases and decreases resulted in short run increases in unemployment. However, equilibrium sectoral models imply that real shocks that change relative wages across sectors should induce flows of labor into those sectors where relative wages rise. In fact, real oil price shocks are found to have substantially reduced respondents’ location probability in the construction industry, which had a wage increase relative to all large industries. The industry with the greatest increase in employment share was services, which had among the greatest wage declines. These are clear contradictions of the predictions of equilibrium sectoral models. Nevertheless, a more general class of models where both relative wage movements and quantity constraints generate labor flows appears to be quite consistent with the data.

In a stochastic equilibrium model some stochastic processes are usually exogenously given, while others are either chosen optimally by agents or emerge from market equilibrium conditions. When we simulate such a model, often we aim at studying the relations among variables in the model as we vary parameters of policy and of behavior of economic agents. We are no more certain (indeed often less certain) of what is reasonable or interesting behavior for the exogenous variables (some of which may be unobservable) than of the variables chosen by agents or fixed in markets. It turns out that if we are flexible about which variables’ behavior we take as given in the model solution computation, freeing ourselves from the convention that the variables exogenous to the model economy must be taken as given in the simulation computations, great computational savings may result.

This study uses John Rawls’ behind-the-veil of ignorance device as a fairness criterion to evaluate social policies and applies it to a contracting model in which the terms equality of opportunity and equality of result are well defined. The results suggest that fairness and inequality—even extreme inequality—are compatible. In a static world, when incentives must be provided, fairness implies equality of opportunity, but inequality of result. In a dynamic world of long-lived individuals, fairness implies not only inequality of result, but also, eventually, infinite inequality of result. If each period of the dynamic model is interpreted as a generation, then eventual infinite inequality holds for opportunity as well, as long as fairness is from the perspective of the first generation. If preferences of later generations are taken into account, then inequality of opportunity still occurs, although not at extreme levels.

This study focuses on the analysis of energy price shocks in the generation of business cycle phenomena. These shocks are transmitted through endogenous fluctuations in capital utilization. The production structure of the model gives rise to an empirical measure of ‘true’ technology growth that is exempt from recent criticisms levelled at the standard measure, i.e., Solow residual growth. The model is calibrated and evaluated for the U.S. economy using annual data over the 1960–1988 period. At business cycle frequencies, the model accounts for 74–91 percent of the volatility of U.S. output; closely matches the strong negative correlation between output and energy prices manifested in the U.S. data; and is generally consistent with other facts characterizing U.S. business cycles. Energy price shocks make a significant quantitative contribution to the model’s ability to explain the data.