The Covid-19 pandemic caused a global economic crisis, leading governments to provide substantial State Aid to support firms. This paper examines the effectiveness of Covid-related financial support in Spain and Italy, focusing on its impact on firm recovery. Using a difference-in-differences...

We study the impact of broadband availability on firms' total factor productivity (TFP) using German firm-level data between 2010 and 2015. We adopt a control function approach to causally identify and separately estimate productivity for 46 two-digit manufacturing and service sectors. Over the...

After 20 years of transition from an economy integrated in an exchange scheme of planned economies towards an open market economy based on the ideas of competition, we ask whether East German firms succeeded in finding their place in the international division of labour. We concentrate on the...

Understanding the causes of the slowdown in aggregate productivity growth is key to maintaining the competitiveness of advanced economies and ensuring long-term economic prosperity. This paper is the first to provide evidence that investment in Knowledge-Based Capital (KBC), despite having a...

This paper investigates the factors that explain the level and dynamics of manufacturing firm productive efficiency. In our empirical analysis, we use a unique sample of about 39,000 firms in 256 industries from the German Cost Structure Census over the years 1992-2005. We estimate the...

This paper provides the first comprehensive review of the empirical and theoretical literature on the determinants of the elasticity of substitution between capital and labor. Our focus is on the two-input constant elasticity of substitution (CES) production function. By example of the U.S., we...

This paper deals with the data generation process implemented for an analysis of the impact of the 9-Euro ticket on mode choice. We discuss the assumptions made and procedures used to process a raw dataset that is based on GPS traces of individuals' movements and on survey data into the...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

We study repayment and delinquency in an innovative loan contract that offers borrowers a wide range of flexibility. Using a large administrative dataset, we perform unsupervised pattern analysis to study how borrowers repay within the framework of this loan. We identify eight clusters that can...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...