Dissertation, Otto-Friedrich-Universität Bamberg, 2024

Three research projects are at the core of this thesis. Their common point of departure is the seminal paper by Alfarano et al. (2012), in which the authors analyze the statistical and distributional patterns that characterize profitability of corporations in the U.S. during the years 1980 to 2011. They find the profitability of competitive corporations, measured by their return on assets (ROA), to be best described by a stationary diffusion process comprising a deterministic mean-reverting tendency and stochastic noise. The parameters of the process then are the median (location) and mean deviation from the median (dispersion) of the profit rates of the overall population of competitive firms and a firm-specific diffusion constant.

In this thesis, we find this process to describe the statistical behavior of profit rates in very different countries and very different time periods. Time-series and cross-sections of profit rates fall onto Laplace distributions for the U.S. between 1863 and 2013 (chapter 3), for Germany between 1919 and 1944 (chapter 4) as well as 45 countries around the world between 1983 and 2013 (chapter 5). So profit rates display qualitatively the same statistical behavior, culminating in the Laplace distribution of profit rates, across time and space. Significant departures from the distribution are transitory and only occur under exceptional circumstances, such as severe economic depressions or wartime. Quantitative differences in the parameter values, however, appear persistently across countries, potentially being the result of country-specific characteristics like the legal system. Thus, departures from the distribution mark exceptional economic conditions and severe distress while different parameter values seem to be the result of country-specificities. Overall, profitability qualifies as reliable vital signs of the economy with robust statistical patterns across space and time. Departures from these statistical patterns then carry substantial information about the potential length and severity of crises.