While differencing transformations can eliminate nonstationarity, they typically reduce signal strength and correspondingly reduce rates of convergence in unit root autoregressions. The present paper shows that aggregating moment conditions that are formulated in differences provides an orderly...

This paper introduces a new estimation method for dynamic panel models with fixed effects and AR(p) idiosyncratic errors. The proposed estimator uses a novel form of systematic differencing, called X-differencing, that eliminates fixed effects and retains information and signal strength in cases...

Using recently developed model selection procedures, we determine that exchange rate returns are driven by a two-factor model. We identify them as a dollar factor and a euro factor. Exchange rates are thus driven by global, US, and Euro-zone stochastic discount factors. The identified factors...