Based on the Canadian National Population Health Survey we estimate the effects of individual sports and exercise on individual labor market outcomes. The data covers the period from 1994 to 2008. It is longitudinal and rich in life-style, health, and physical activity information. Exploiting...

One important goal of this study is to develop a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first...

Nationwide health interventions are difficult to evaluate as contemporaneous control groups do not exist and before-after approaches are usually infeasible. We propose an alternative semi-parametric estimator that is based on the assumption that the intervention has no direct effect on the...

In this paper we use a transparent statistical methodology – synthetic control methods – to implement data-driven comparative studies about the impact of autocratic transition on real per capita GDP. The applied methodology compares the growth of countries that experienced a transition to...

In this paper we specify a linear Cliff and Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate a multi-step...

Pension benefit guarantee policies have been introduced in several countries to protect private pension plan members from the loss of income that would occur if a plan was underfunded when the sponsoring firm terminates a plan. Most of these public insurance schemes face financial difficulty and...

We argue that in modelling cross-country growth models one should first identify so-called outlying observations. For the data set of Sala-i-Martin, we use the least median of squares (LMS) estimator to identify outliers. As LMS is not suited for inference, we then use reweighted least squares...