A recent literature has developed that combines two prominent empirical approaches to ex ante policy evaluation: randomized controlled trials (RCT) and structural estimation. The RCT provides a "gold-standard'' estimate of a particular treatment, but only of that treatment. Structural estimation...

Although independent unobserved heterogeneity--variables that affect the dependent variable but are independent from the other explanatory variables of interest--do not affect the point estimates or marginal effects in least squares regression, they do affect point estimates in nonlinear models...

It is standard practice in empirical work to allow for clustering in the error covariance matrix if the explanatory variables of interest vary at a more aggregate level than the units of observation. Often, however, the structure of the error covariance matrix is more complex, with correlations...

We use administrative data on a sample of births between 1978 and 1985 to investigate the short, medium and long-term consequences of poor infant health. Our findings offer several advances to the existing literature on the effects of early infant health on subsequent health, education, and...

American politics have been characterized by a high degree of partisan conflict in recent years. Combined with a divided government, this has led not only to significant Congressional gridlock, but also to spells of high fiscal policy uncertainty. The unusually slow recovery from the Great...

Using a unique panel dataset and a new model, this article investigates the dynamic effects of counterfeit sales on authentic-product price dynamics. We propose a Bayesian random-changepoint simultaneous equation model that simultaneously takes into account three important features in empirical...

Although ARCH-related models have proven quite popular in finance, they are less frequently used in macroeconomic applications. In part this may be because macroeconomists are usually more concerned about characterizing the conditional mean rather than the conditional variance of a time series....

When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's finite-sample properties, derived here, can depart substantially from the standard regression setting....

Despite the availability of more sophisticated methods, a popular way to estimate a Pareto exponent is still to run an OLS regression: log(Rank)=a-b log(Size), and take b as an estimate of the Pareto exponent. The reason for this popularity is arguably the simplicity and robustness of this...