Much management accounting research focuses on design of incentive compensation contracts. A basic assumption in these contracts is that performance-based incentives improve employee performance. This paper reports on a field test of the multi-period incentive effects of a performance-based compensation plan on the sales of a retail establishment. Analysis of panel data for 15 retail outlets over 66 months indicates a sales increase when the plan is implemented, an effect that persists and increases over time. Sales gains are significantly lower in the peak selling season when more temporary workers are employed.

Using a panel of 51 prices from 48 cities in the United States, we provide an upper bound estimate of the rate of convergence to purchasing power parity. We find convergence rates substantially higher than typically found in cross-country data. We investigate some potentially serious biases induced by i.i.d. measurement errors in the data, and find our estimates to be robust to these potential biases. We also present evidence that convergence occurs faster for larger price differences. Finally, we find that rates of convergence are slower for cities farther apart. However, our estimates suggest that distance alone can only account for a small portion of the much slower convergence rates across national borders.

This paper reports overwhelming evidence against the hypothesis that the federal funds rate follows a martingale over the two-week reserve maintenance period, establishing that banks do not regard reserves held on different days of the week to be perfect substitutes. A theoretical model of the federal funds market is proposed that could account for these empirical regularities as the result of line limits, transaction costs, and weekend accounting conventions. The paper concludes that such transaction costs lie at the heart of the liquidity effect that enables the Federal Reserve to change the interest rate on a daily basis.

This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context of our model, that persistent volatility is caused by traders experimenting with different beliefs based upon past profit experience and their estimates of future profit experience. A major theme of our paper is to introduce adaptive agents in the spirit of Sargent (1993) but have them adapt their strategies on a time scale that is slower than the time scale on which the trading process takes place. This will lead to positive autocorrelation in volatility and volume on the time scale of the trading process which generates returns and volume data. Positive autocorrelation of volatility and volume is caused by persistence of strategy patterns that are associated with high volatility and high volume. Thee following features seen in the data: (i) The autocorrelation function of a measure of volatility such as squared returns or absolute value of returns is positive with a slowly decaying tail. (ii) The autocorrelation function of a measure of trading activity such as volume or turnover is positive with a slowly decaying tail. (iii) The cross correlation function of a measure of volatility such as squared returns is about zero for squared returns with past and future volumes and is positive for squared returns with current volumes. (iv) Abrupt changes in prices and returns occur which are hard to attach to 'news.' The last feature is obtained by a version of the model where the Law of Large Numbers fails in the large economy limit.

In the first half of this century, special attention was given to two features of the business cycle: the comovement of many individual economic series and the different behavior of the economy during expansions and contractions. Recent theoretical and empirical research has revived interest in each attribute separately, and we survey this work. Notable empirical contributions are dynamic factor models that have a single common macroeconomic factor and nonlinear regime-switching models of a macroeconomic aggregate. We conduct an empirical synthesis that incorporates both of these features. It is desirable to know the facts before attempting to explain them; hence, the attractiveness of organizing business-cycle regularities within a model-free framework. During the first half of this century, much research was devoted to obtaining just such an empirical characterization of the business cycle. The most prominent example of this work

When the underlying price process is a one-dimensional diffusion, as well as in certain restricted stochastic volatility settings, a contingent claim's delta is bounded by the infimum and supremum of its delta at maturity. Further, if the claim's payoff is convex (concave), the claim's price is a convex (concave) function of the underlying asset's value. However, when volatility is less specialized, or when the underlying process is discontinuous or non-Markovian, a call's price can be a decreasing, concave function of the underlying price over some range, increasing with the passage of time, and decreasing in the level of interest rates.

We use data from an agricultural labour market in which workers receive both time- and piece-rate wages and shift frequently among employers and tasks, to assess the roles of comparative advantage, information problems and preferences in determining the allocation of workers. The estimates which impose minimal structure not implied by economic theory are consistent with a one-factor productivity model, and indicate that information asymmetries are present but workers are sorted according to comparative advantage. In particular, the disproportionate presence of female workers in weeding activities is due not to worker or employer preferences but to comparative advantage and statistical discrimination.