ABSTRACT
Among the models applied to analyze survival data, a standout is the inverse Gaussian distribution, which belongs to the class of models to analyze positive asymmetric data. However, the variance of this distribution depends on two parameters, which prevents establishing a functional relation with a linear predictor when the assumption of constant variance does not hold. In this context, the aim of this paper is to re-parameterize the inverse Gaussian distribution to enable establishing an association between a linear predictor and the variance. We propose deviance residuals to verify the model assumptions. Some simulations indicate that the distribution of these residuals approaches the standard normal distribution and the mean squared errors of the estimators are small for large samples. Further, we fit the new model to hospitalization times of COVID-19 patients in Piracicaba (Brazil) which indicates that men spend more time hospitalized than women, and this pattern is more pronounced for individuals older than 60 years. The re-parameterized inverse Gaussian model proved to be a good alternative to analyze censored data with non-constant variance.
ABSTRACT
Short-time work (STW) policies provide subsidies for hour reductions to workers in firms experiencing temporary shocks. They are the main policy tool used to support labour hoarding during downturns and were aggressively used during the coronavirus disease 2019 (COVID-19) pandemic. Yet, very little is known about their employment and welfare consequences. This article leverages unique administrative social security data from Italy and quasi-experimental variation in STW policy rules to offer evidence on the effects of STW on firms' and workers' outcomes during the Great Recession. Our results show large and significant negative effects of STW treatment on hours, but large and positive effects on headcount employment. We then analyse whether these positive employment effects are welfare enhancing, distinguishing between temporary and more persistent shocks. We first provide evidence that liquidity constraints and rigidities in wages and hours may make labour hoarding inefficiently low without STW. Then, we show that adverse selection of low productivity firms into STW reduces the long-run insurance value of the program and creates significant negative reallocation effects when the shock is persistent.
ABSTRACT
We examine whether the COVID-19 crisis affects women and men differently in terms of employment, working hours, and hourly wages, and whether the effects are demand or supply driven. COVID-19 impacts are studied using administrative data on all Dutch employees up to December 2020, focussing on the national lockdowns and emergency childcare for essential workers in the Netherlands. First, the impact of COVID-19 is much larger for non-essential workers than for essential workers. Although female non-essential workers are more affected than male non-essential workers, on average, women and men are equally affected, because more women than men are essential workers. Second, the impact for partnered essential workers with young children, both men and women, is not larger than for others. Third, single-parent essential workers respond with relatively large reductions in labour supply, suggesting emergency childcare was insufficient for them. Overall, labour demand effects appear larger than labour supply effects.