We develop a maximum relative entropy formalism to generate optimal approximations to probability distributions. The central results consist of (a) justifying the use of relative entropy as the uniquely natural criterion to select a preferred approximation from within a family of trial...

Given the objective of estimating the unknown parameters of a possibly nonlinear dynamic model using a finite (and relatively small) data set, it is common to use a Kalman filter Maximum Likelihood (ML) approach, ML-type estimators or more recently a GMM (Imbens, Spady and Johnson, 1998), BMOM...

Using a maximum entropy technique, the authors estimate the market shares of each firm in an industry using the available government summary statistics such as the four-firm concentration ratio and the Herfindahl-Hirschmann Index. They show that their technique is very effective in estimating...

We use three conventional inequality indices-the Gini, the coefficient of variation of income, and the relative mean deviation of income-and the Atkinson index to examine the effect of income tax rates, the minimum wage, and all the major government welfare and transfer programs on the evolution...

We use a nonlinear, nonparametric method to forecast the unemployment rates. We compare these forecasts to several linear and nonlinear parametric methods based on the work of Montgomery et al. (1998) and Carruth et al. (1998). Our main result is that, due to the nonlin-earity in the data...