Currently there is little practical advice on which treatment effect estimator to use when trying to adjust for observable differences. A recent suggestion is to compare the performance of estimators in simulations that somehow mimic the empirical context. Two ways to run such 'empirical Monte...

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 that household heads with a strong internal economic locus of control are more likely to hold equity and hold a larger share of equity in their investment portfolio. This relation holds when we control for economic preferences and possible confounders such as financial literacy,...

In this paper we develop a job portfolio model of dual job holding based on a Stone-Geary utility function. We derive the associated Slutsky equation components. Because the job portfolio model applies only to unconstrained dual jobholders, we separate individuals who moonlight because of an...

Many models of investor behavior predict that investors prefer assets that they believe to have positively skewed return distributions. We provide a direct test of this prediction in a representative sample of the Dutch population. Using individual-level data on return expectations for a broad...

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the...

We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data generation processes (DGPs) based on actual data. We consider 24...

Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups – such as segregation, isolation or concentration indexes – are often only capable of identifying just one aspect of this distribution. The...

This paper investigates the finite sample properties of a range of inference methods for propensity score-based matching and weighting estimators frequently applied to evaluate the average treatment effect on the treated. We analyse both asymptotic approximations and bootstrap methods for...

Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we...