This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G7 countries. The models use the spread between short-term and long-term interest rates as leading indicators for GDP, and their success in capturing business cycles is gauged by non-parametric...

We use US regional and state data to determine which regions have contributed most to the apparent decline in income growth volatility in the United States. We study changes in the variance of income growth in each region, changes in the covariance of growth between regions and changes in...

This paper proposes neural network based measures of predictability in conditional mean, and then uses them to construct nonlinear analogues to autocorrelograms and partial autocorrelograms. In contrast to other measures of nonlinear dependence that rely on nonparametric estimation of densities...