This paper aims to estimate the price and income elasticities of the demand for essential commodities in Cote d'Ivoire. Using data from the 2002 Cote d'Ivoire Living Standard Survey and a theoretical framework developed by Crawford et al. (2003), we analyse price effects on the demand for groups...

We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators. Very informative administrative Swiss data with detailed regional information are combined with exogenous regional variation in programme...

This paper evaluates the effect of a voucher award system for assignment into vocational training on the employment outcomes of unemployed voucher recipients in Germany, along with the causal mechanisms through which it operates. It assesses the direct effect of voucher assignment net of actual...

This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

We show that the OLS and fixed‐effects (FE) estimators of the popular difference-in-differences model may deviate when there is time varying panel non-response. If such non-response does not affect the common-trend assumption, then OLS and FE are consistent, but OLS is more precise. However,...

Based on a unique composite dataset measuring heterogeneous sports participation, labour market outcomes and local facilities provision, this paper examines for the first time the association between different types of sports participation on employment and earnings in England. Clear...

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...

This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based...

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...

Uncovering the heterogeneity of causal effects of policies and business decisions at various levels of granularity provides substantial value to decision makers. This paper develops new estimation and inference procedures for multiple treatment models in a selection-on-observables frame-work by...