In accordance with its statutes, the Halle Institute for Economic Research (IWH) pursues an intensive bilateral knowledge transfer on the basis of excellent scientific research with its partners in the non-academic community. In so doing, the IWH contributes to better informed decision making on a societal level. The overarching goal is to foster mutually beneficial exchanges that involve the provision of evidence-based knowledge to society (transfer from the academic to the non-academic community) and the integration of questions of public interest into its research agenda (transfer from the non-academic to the academic community).

Based on the Competing Values Framework (CVF), we score 10-K text to measure company culture in four types (collaborative, controlling, competitive, and creative) and examine its role in firm stability. We find that firms with higher controlling culture fared significantly better during the 2008–09 crisis. Firms with stronger controlling culture experienced fewer layoffs, less negative asset growth, greater debt issuance, and increased access to credit-line facilities during the crisis. The positive effect of the controlling culture is stronger among the financially-constrained firms. Overall, the controlling culture improves firm stability through greater support from capital providers.

We explore the impact of financial frictions on the employment effect of labour market reforms. Our study combines a new cross-country reform database on labour market reforms with matched firm-bank data for nine euro area countries over the period 1999 to 2013. While we find that labour market reforms are overall effective in increasing employment, restricted access to bank credit can undo up to half of medium to long-term employment gains at the firm-level. Entrepreneurs without sufficient access to credit cannot reap the full benefits of more flexible employment regulation.

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

We explore the interaction between labour market reforms and financial frictions. Our study combines a new cross-country reform database on labour market reforms with matched firm-bank data for nine euro area countries over the period 1999 to 2013. While we find that labour market reforms are overall effective in increasing employment, restricted access to bank credit can undo up to half of long-term employment gains at the firm-level. Entrepreneurs without sufficient access to credit cannot reap the full benefits of more flexible employment regulation.