This paper considers the problem of identification, estimation and inference in the case of spatial panel data models with heterogeneous spatial lag coefficients, with and without (weakly) exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation...

A broad empirical literature uses “event study” research designs for treatment effect estimation, a setting in which all units in the panel receive treatment but at random times. We make four novel points about identification and estimation of causal effects in this setting and show their...

A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies...

This paper describes a non-parametric, unconditional, hyperbolic quantile estimator that unlike traditional non-parametric frontier estimators is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S....

The majority of work in mortality modeling involves factor-based approaches, with little use of information on the determinants and interpretable risk factors of mortality. At the same time, in the demographic community, there has been a lack of research attention towards the study of mortality...