This study examines the impact of environmental, social and governance (ESG) disclosure on firms’ labour investment efficiency. Our results indicate that such impact is positive. ESG disclosure is more effective in curtailing over-hiring and when over-investment in physical capital is high. The uncovered positive association is mainly fuelled by the volume of social and governance disclosure (environmental disclosure barely affects labour investment efficiency), and is more pronounced for firms with a weaker corporate social responsibility performance. The results from the empirical analysis survive a battery of robustness tests, including the use of alternative measures to capture labour investment efficiency, different control variables in regression models, and controlling for endogeneity in ESG disclosure. Our analysis and findings are novel to the literature and contribute to ongoing debates about the impact of ESG disclosure on firms’ performance and about potential benefits and costs of mandatory disclosure.

This study evaluates the risk associated with capital allocation in cryptocurrencies (CCs) using a basket of 27 CCs and the CC index EWCI-. We apply basic statistical tests to model the body distribution of CC returns. Consistent with prior research, the stable distribution (SDI) is the most suitable model for the body distribution. However, due to less favorable properties in the tail area for high quantiles, the generalized Pareto distribution is employed. A combination of both distributions is utilized to calculate Value at Risk and Conditional Value at Risk, revealing distinct risk characteristics in two subgroups of CCs.