This paper analyzes conditions under which various single-equation estimators are asymptotically normal in a simultaneous equations framework with many weak instruments. In particular, our paper adds to the many instruments asymptotic normality literature, including papers by Morimune (1983),...

We provide analytical formulae for the asymptotic bias (ABIAS) and mean squared error (AMSE) of the IV estimator, and obtain approximations thereof based on an asymptotic scheme which essentially requires the expectation of the first stage F-statistic to converge to a finite (possibly small)...

A regression model is considered where earnings are explained by schooling and ability. It is assumed that schooling is measured with error and that there are no data on ability. Regressing earnings on observed schooling then yields an estimate of the return to schooling that is subject to...

We extend the standard evaluation framework to allow for interactions between individuals within segmented markets. An individual's outcome depends not only on the assigned treatment status but also on (features of) the distribution of treatments in his market. To evaluate how the distribution...

Propensity score based-estimators are commonly used to estimate causal effects in evaluation research. To reduce bias in observational studies researchers might be tempted to include many, perhaps correlated, covariates when estimating the propensity score model. Taking into account that the...

This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...

This paper derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously updated GMM estimators under potentially misspecified models. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model...

In this paper, we propose a model based on multivariate decomposition of multiplicative - absolute values and signs - components of several returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

We use a simple New Keynesian model, with firm specific capital, non-zero steady-state inflation, long-run risks and Epstein-Zin preferences to study the volatility implications of a monetary policy shock. An unexpected increases in the policy rate by 150 basis points causes output and inflation...