In a recent article, Nowak-Lehmann, Dreher, Herzer, Klasen, and Martínez-Zarzoso (2012) (henceforth NDHKM) conclude that foreign aid has not had a significant effect on income, based on evidence from panel data potentially covering 131 countries over the period 1960-2006. The present study...

There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is inconsistent, when the instruments are lags of noncausal variables. This paper argues that this inconsistency depends on distributional assumptions, that do not always hold. In...

Misspecification of agents' information sets or expectation formation mechanisms may lead to noncausal autoregressive representations of asset prices. Annual US stock prices are found to be noncausal, implying that agents' expectations are not revealed to an outside observer such as an...

We propose the Volume Coefficient of Variation (VCV), the ratio of the standard deviation to the mean of trading volume, as a new and easily computable measure of information asymmetry in security markets. We use a microstructure model to demonstrate that VCV is strictly increasing in the...

The VAR approach for testing present value models is applied to a nonlinear asset pricing model with three types of agents, using historical US stock prices and dividends. Besides rational long-term investors, that value assets according to expected dividends, the model includes rational and...

We propose the Volume Coefficient of Variation (VCV), the ratio of the standard deviation to the mean of trading volume, as a new and easily computable measure of information asymmetry in security markets. We use a simple microstructure model to demonstrate that VCV is strictly increasing in the...

We develop a volatility decomposition derived from flexible local projections to quantify the relative contributions of expected discount rates and cash flows to the variation of dividend yields. Local projections enable the incorporation of large information sets, the use of monthly data along...