The interest rate is generally considered as an important driver of macroeconomic investment. As an innovation, this paper derives the exact shape of the "hysteretic" impact of changes in the interest rate on macroeconomic investment under the scenarios of both certainty and uncertainty. We...

This paper questions unconventional fiscal policy effects when the monetary policy rate is at the zero lower bound. We provide evidence for the US that the spread between the policy rate and the US-LIBOR, which is more relevant for private sector transactions, increases with government...

We develop a two-sector, heterogeneous-agent model with incomplete financial markets to study the distributional effects and aggregate welfare implications of alternative monetary policy rules in emerging market economies. Relative to inflation targeting, exchange rate management benefits...

In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the...

Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting...

This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can easily deal with the commonly encountered and widely discussed "initial conditions problem," as well as the...

Researchers are often interested in estimating the causal effect of some treatment on individual criminality. For example, two recent relatively prominent papers have attempted to estimate the respective direct effects of marriage and gang participation on individual criminal activity. One...

This paper assesses the effectiveness of unconfoundedness-based estimators of mean effects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among...

Estimation of average treatment effects under unconfoundedness or exogenous treatment assignment is often hampered by lack of overlap in the covariate distributions. This lack of overlap can lead to imprecise estimates and can make commonly used estimators sensitive to the choice of...