This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC...

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...

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...

"I perform the joint estimation of a reduced-form dynamic model of the transition from one grade level to the next, and a Mincer wage equation, using panel data taken from the NLSY. A very high degree of flexibility is achieved by approximating the distributions of idiosyncractic grade...

This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists. QTE are an...

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time varying heterogeneity. These include limited dependent variable models with both unobserved individual effects and endogenous explanatory variables, and sample selection models with...

This paper addresses the selection of smoothing parameters for estimating the average treatment effect on the treated using matching methods. Because precise estimation of the expected counterfactual is particularly important in regions containing the mass of the treated units, we define and...

We show why considering a number of education-dependent covariates in the wage equation decreases coefficient of education in the wage equation. We use a meta-analysis of results for Portugal to show, empirically, that this is the case. The coefficient decreases when we use covariates that can...

A key assumption in regression discontinuity analysis is that units cannot manipulate the value of their running variable in a way that guarantees or avoids assignment to the treatment. Standard identification arguments break down if this condition is violated. This paper shows that treatment...

In this paper the extensive empirical literature on the gender wage gap is reviewed with particular attention given to the identification of the key parameters in the specified human capital wage regression models. This aspect has been of great importance in the literature chiefly for two...