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We examine the effects of the COVID-19 pandemic on the economic decline expected in Germany in 2020. The magnitude of the economic slump that will occur in 2020 depends on the extent of the slump during the shutdown, on the point in time, at which a significant easing of shutdown occurs, and on the length of adjustment process towards the structures that prevailed before the pandemic. We derive several scenarios and find that the shutdown will only remain in the single-digit percentage range if we apply very optimistic assumptions about the extent of the initial decline in GDP during the shutdown and the speed of adjustment after opening up of the economy. However, assuming that the economic crisis cannot end before the medical crisis ends, which medical experts project not to happen before the end of 2020, such optimistic assumptions do not appear realistic. Hence, we find it more likely that the percentage decline of GDP in Germany will be two-digit in 2020. Our findings are in contrast to the growth projections recently issued by the German Council of Economic Experts or by the Federal Ministry of Economic Affairs and Energy of Germany.
This paper proposes a method for deriving the joint asymptotic distribution of sample proportions when the population and sample size increase jointly to infinity. The joint distribution of the sample proportions is derived by reducing the multi- variate to a univariate problem and applying the Cramer-Wold device. Knowing the asymptotic distribution we are in a position to conduct inference on linear or non-linear functions of the population proportions such as a ratio or the log-odds. We motivate and develop our method by means of a topical epidemiological application, namely the infection fatality rate of a virus such as SARS-CoV-2. We demonstrate that our method can be extended to more general settings of interest.
Background: In view of steadily rising healthcare expenditures (HCE), studies on spending distributions can provide important guidance for policy decisions. Since the majority of HCE is concentrated in a few high-cost cases, this study focusses on the spending distribution between different cost-risk groups. We show detailed allocation structures, distinguishing several categories of HCE and the survival status of insureds to gain insights regarding the share of mortality costs.
Methods: Our analyses rely on data from a large sickness fund that covers around four million insureds. We classify the population into ten equal risk groups by costs and then determine expenditure shares of total HCE and daily per-capita expenditures depending on survival status and risk group affiliation.
Results: Our results offer that the often stated dominating effect of mortality costs of HCE is only evident in lower cost-risk groups and almost exclusively attributable to inpatient care. Furthermore, HCE in the calendar year of death is the same for most cost-risk groups, with the exception of risk groups at both ends of the distribution. However, in the case of the highest cost-risk group, the difference between survivors and decedents is proportionally small. The differences in cost structure between decedents in high-risk and other risk groups are primarily attributable to pharmaceutical spending.
Conclusion: Short-term high HCE in the year of death occur equally in all cost-risk groups and are hardly avoidable. By contrast, in the extremely high cost-risk groups, the cost difference between the year before death and the year of death is much smaller. Overall, this group remains the main target to influence the rise in HCE and its characteristics should be considered with respect to future HCE projections.
We examine the role of tax incentives, tax awareness, and complexity in tax evasion. We observe a specific type of tax evasion among business owners in Swedish administrative panel data, after the tax authority has approved all tax returns. For the period 2006–2009, approximately 5% of tax returns overstate a claimed dividend allowance. Tax awareness decreases and complexity increases the likelihood of misreporting. Our results indicate that some observed misreporting could be accidental, while some misreporting is deliberate tax evasion. We identify a positive and significant effect of tax rates on tax evasion, by exploiting a large kink in the tax schedule. The majority of misreporting cases remains undetected by the tax authority. Self-correction of tax evasion by taxpayers is the dominant type of detection.