In the causal inference literature a class of semi-parametric estimators is called robust if the estimator has desirable properties under the assumption that at least one of the working models is correctly specified. A standard example is a doubly robust estimator that specifies parametric...

This document summarizes the thrust of my monograph book Disasters and the Networked Economy (2003, NY: Routledge. 228 pp. ISBN: 978-0-415-66629-9). It is no substitution for the book, but it attempts to make salient the main concepts, explanations and conclusions of it. It does so by first...

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a "Poor (Wo)man's Bootstrap" based on one-dimensional...

This paper proposes a measure of the intensity of competition in labor markets on the basis of limited data. Large-scale socioeconomic surveys often lack detailed information on competitive behavior. It is particularly difficult to determine whether a worker moves between the different segments...

This paper uses the Italian income tax treatment of 2006/7 as a quasi-natural tax experiment to offer some fresh empirical evidence on how labour supply responds to exogenous income tax hikes. We adopt the identification strategy based on TWFE panel data Difference-in-Differences (DID) model to...

Economic analysis has approached the problem of the neutrality of money through methods of supply-demand equilibrium in which changes in aggregate demand due to monetary or fiscal policy are equivalent to changes in the denomination of the monetary standard. We re-examine this question using...

The bootstrap is a convenient tool for calculating standard errors of the parameters of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the...

The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...

Heterogeneity in patient populations is an important issue in health economic evaluations, as the cost-effectiveness of an intervention can vary between patient subgroups, and an intervention which is not cost-effective in the overall population may be cost-effective in particular subgroups....