In non-experimental sciences the errors associated with model misspecifications in primarystudies carry over to meta-analysis. We use Monte Carlo simulations to analyse the effects ofthese misspecifications on results of a meta-analysis using a meta-estimator that calculates asimple average...

The evaluation of interventions such as active labor market policies or medical programs by means of a randomized controlled trial is often considered the gold standard. However, randomized experiments might face severe shortcomings especially if performed at the group level. One such problem is...

The traditional approach to estimate spatial models bases on a preconceived spatial weights matrix to measure spatial interaction among locations. The a priori assumptions used to define this matrix are supposed to be in line with the "true" spatial relationships among the locations of the...

We investigate into the simulated (Monte Carlo) performance of some LAD-based estimators vis-a-vis that of the LS-based estimators for multi-equation linear econometric models of various error specifications - such as Normal, Cauchy, Gamma, Beta1 and Beta2 - in presence of outliers different in...

Researchers in empirical corporate finance often use bounded ratios (e.g. debt ratios) as dependent variables in their regressions. Using the example of estimating the speed of adjustment toward target leverage, we show by Monte Carlo and resampling experiments that commonly applied estimators...

Foreign currency debt has led to many crises in emerging markets. However, in the past decade, firms in emerging economies have drastically increased their foreign currency borrowing, making them significantly exposed to depreciation shocks. To reduce their exposure to external shocks, central...