In this paper we explore the application of structured additive distributional regression for the analysis of conditional income distributions in Germany following the reunification. Using a bootstrapped Kolmogorov-Smirnov test we find that conditional personal income distributions can generally...

In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting;...

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...

The Economic Research Forum (ERF) produced a one-off survey of micro & small private enterprises (MSE) in a number of Middle East and North African countries (MENA). It contains sufficient information to fit a production function and additional information about the owner’s education type; the...

In addition to the wide believed positive effects on growth, employment and wages, FDIs are often perceived as sources of funds for development. Developing countries, especially low income and emerging economies, welcome FDIs because of their favorable budgetary implications. All that resulted...

This paper shows how asymptotically valid inference in regression models based on the weighted least squares (WLS) estimator can be obtained even when the model for reweighting the data is misspecified. Like the ordinary least squares estimator, the WLS estimator can be accompanied by...

In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...

This paper shows how asymptotically valid inference in regression models based on the weighted least squares (WLS) estimator can be obtained even when the model for reweighting the data is misspecified. Like the ordinary least squares estimator, the WLS estimator can be accompanied by...

This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions have zero derivative with respect to the first step and the first step does not affect the asymptotic variance. They are constructed by adding to the moment functions the...