After more than 20 years of European Monetary Union (EMU), surprisingly few scientific studies exist which study the growth effects of introducing a common currency in large parts of the European Union. I do so using a large panel (NUTS3 data) of regional data for the EU-15. Some 800 (treated)...

This paper was presented in June 1974 at the Symposium ―On the Measurement of Factor Productivities‖ at the castle Reisensburg in Bavaria, and was published in the book of proceedings from this Symposium. It contains results of several years of research about the economies of six East...

The paper introduces for the most frequently used three-dimensional panel data sets several random effects model specifications. It derives appropriate estimation methods for the balanced and unbalanced cases. An application is also presented where the bilateral trade of 20 EU countries is...

We present a unifying identification strategy of dynamic average treatment effect parameters for staggered interventions when parallel trends are valid only after controlling for interactive fixed effects. This setting nests the usual parallel trends assumption, but allows treated units to have...

When there are multiple outcome series of interest, Synthetic Control analyses typically proceed by estimating separate weights for each outcome. In this paper, we instead propose estimating a common set of weights across outcomes, by balancing either a vector of all outcomes or an index or...

I study inverse probability weighted M-estimation under a general missing data scheme. The cases covered that do not previously appear in the literature include M-estimation with missing data due to a censored survival time, propensity score estimation of the average treatment effect for linear...

ExpEnd is a Gauss programme for non-linear generalised method of moments (GMM) estimation of exponential models with endogenous regressors for cross section and panel data. The estimators included in this package are simple Poisson pseudo ML; GMM for cross section data using moment conditions...

This paper presents a generalized moments (GM) approach to estimating an R-th order spatial regressive process in a panel data error component model. We derive moment conditions to estimate the parameters of the higher order spatial regressive process and the optimal weighting matrix required to...

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...

We analyze the conditions under which the Synthetic Control (SC) estimator is asymptotically unbiased when the number of pre-treatment periods goes to infinity. We show that the SC estimator is generally asymptotically biased if treatment assignment is correlated with time-varying unobserved...