Zusammenfassung Die Autoren erklären den bisherigen Verlauf von Covid-19 in Deutschland durch Regressionsanalysen und epidemiologische Modelle. Sie beschreiben und quantifizieren den Effekt der gesundheitspolitischen Maßnahmen (GPM), die bis zum 19. April in Kraft waren. Sie berechnen den erwarteten Verlauf der Covid-19-Epidemie in Deutschland, wenn es diese Maßnahmen nicht gegeben hätte, und zeigen, dass die GPM einen erheblichen Beitrag zur Reduktion der Infektionszahlen geleistet haben. Die seit 20. April gelockerten GPM sind zwischen den Bundesländern relativ heterogen, was ein Glücksfall für die Wissenschaft ist. Mittels einer Analyse dieser Heterogenität kann aufgedeckt werden, welche Maßnahmen für eine Bekämpfung einer eventuellen zweiten Infektionswelle besonders hilfreich und besonders schädlich sind.

We model the evolution of the number of individuals that are reported to be sick with COVID-19 in Germany. Our theoretical framework builds on a continuous time Markov chain with four states: healthy without infection, sick, healthy after recovery or after infection but without symptoms and dead. Our quantitative solution matches the number of sick individuals up to the most recent observation and ends with a share of sick individuals following from infection rates and sickness probabilities. We employ this framework to study inter alia the expected peak of the number of sick individuals in a scenario without public regulation of social contacts. We also study the effects of public regulations. For all scenarios we report the expected end of the CoV-2 epidemic.

AbstractWe develop a model where individuals accumulate fatigue from work intensity when choosing hours worked. Fatigue captures intertemporal costs of labour supply and leads to a utility loss. As fatigue increases, individuals optimally choose to work fewer hours. The model also predicts that if individuals cannot easily shift consumption over time, they will work fewer hours but accumulate more fatigue when work intensity increases. Calibration to 19 European countries provides evidence for the claim that a higher share of the service sector is linked to increasing work fatigue and that public provisions of healthcare improves recovery and mental health.JEL codesE71, I12, J22

We model the evolution of the number of individuals that are reported to be sick with COVID-19 in Germany. Our theoretical framework builds on a continuous time Markov chain with four states: healthy without infection, sick, healthy after recovery or after infection but without symptoms and dead. Our quantitative solution matches the number of sick individuals up to the most recent observation and ends with a share of sick individuals following from infection rates and sickness probabilities. We employ this framework to study inter alia the expected peak of the number of sick individuals in a scenario without public regulation of social contacts. We also study the effects of public regulations. For all scenarios we report the expected end of the CoV-2 epidemic.

Many countries consider the lifting of restrictions of social contacts (RSC). We quantify the effects of RSC for Germany. We initially employ a purely statistical approach to predicting prevalence of COVID19 if RSC were upheld after April 20. We employ these findings and feed them into our theoretical model. We find that the peak of the number of sick individuals would be reached already mid April. The number of sick individuals would fall below 1,000 at the beginning of July. When restrictions are lifted completely on April 20, the number of sick should rise quickly again from around April 27. A balance between economic and individual costs of RSC and public health objectives consists in lifting RSC for activities that have high economic benefits but low health costs. In the absence of large-scale representative testing of CoV-2 infections, these activities can most easily be identified if federal states of Germany adopted exit strategies that differ across states.

This paper analyzes data on female and male entrepreneurship that were collected by the World Bank Group's Entrepreneurship Database. Recognizing the importance of a differentiated approach to entrepreneurship in terms of legal entities, the data on female and male business owners are collected at the level of limited liability companies and sole proprietorships. Forty-four of the 143 economies that participated in the Entrepreneurship project provided some sex-disaggregated data for 2016. The paper finds that the gender gap in business ownership remains high in many economies around the world. In the majority of the analyzed economies, less than one-third of new limited liability company owners are women. Although sole proprietorships are more frequently used by female entrepreneurs, only three economies have similar or equal number of women business owners relative to men. The gap in female entrepreneurship is especially apparent in low-income economies, where women are much less likely than men to start a new business. The paper also provides new insights into the relationship between female entrepreneurship and various institutional factors, including women's financial inclusion, the gender gap in education, and legal rights disparities. The analysis suggests a need to expand the collection of sex-disaggregated data, to trace the economies' progress in narrowing the existing gender gap in entrepreneurship.