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Wissenschaftsmanagement
(2017)
Winning Frankfurt
(2017)
Our paper estimates the impact of immigration on the sustainability of the Italian public finances using the methodology of Generational Accounting. We take into account socio-economic differences between the main migrants’ communities resident in Italy and we present three possible scenarios to reflect the potential economic degree of integration of foreigners in the Italian territory. Moreover, for each scenario we propose several options for migrants concerning both the length of permanence in Italy and the possible collection of retirement benefits. Our results show that the burden of current fiscal policy reduces as integration of the foreign-born increases. If migrants’ children are economically perfectly integrated, the fiscal gap is reduced from 71.9 to -15.3 percent of GDP.
In this thesis, we(1) use operations research methods to provide insights into three areas associated with health care operations management. In Chapter 2, we use a discreteevent supply chain simulation to asses if coordination among partners is beneficial in a supply chain with the characteristics of the German pharmaceutical market. We find that the greatest cost savings and service levels could be achieved through a highly integrated collaboration although most of its impact could already be achieved through sharing point-of-sales demand information. Results suggest that coordination is most beneficial in situations where product shelf life is short and demand variation is high.
In Chapter 3 we consider quality-of-life maximizing sequences of prophylactic surgeries for female carriers of a BRCA1/2 genetic mutation, who face a significantly elevated breast and ovarian cancer risk. Using a Markov Decision Process model, we determine the optimal surgery sequence that maximizes the carrier’s expected lifetime qualityadjusted life years (QALYs). Baseline results demonstrate that a QALY-maximizing sequence recommends a bilateral mastectomy between ages 30 and 60 and bilateral salpingo-oophorectomy after age 40 for BRCA1 carriers. Surgeries are recommended later for BRCA2 carriers, as their cancer risk is lower. The model’s structural properties show that when one surgery has already been completed, there exists an optimal control limit after which performing the other surgery is always QALY-maximizing.
In Chapter 4, we develop a two-stage model for optimizing when and where to assign Ebola treatment unit (ETU) beds—across geographic regions—during an infectious disease outbreak’s early phase. The first stage includes a dynamic transmission model that forecasts occurrence of new cases at the regional level, thus capturing connectivity among regions; in this stage we introduce a coefficient for behavioral adaptation to changing epidemic conditions. The second stage includes two approaches to efficiently allocate intervention resources across affected regions. Such an allocation could have prevented up to 3,434 infections over an 18-week period during the 2014 Ebola outbreak in West Africa, a 58% improvement compared with the actual allocation.
(1) In Chapter 2, 3, and 4, the term ’we’ refers to the authors of Nohdurft & Spinler (2016), Nohdurft et al. (2016a), and Nohdurft et al. (2016b), respectively.
In this article we examine the influence of two goal compensation schemes on lying behavior. Based on the die rolling task of Fischbacher/Föllmi-Heusi (2013), we apply an individual goal incentive scheme and a team goal incentive scheme. In both settings individuals receive a fixed bonus when attaining the goal. We find that under team goal incentives subjects are less inclined to over-report production outputs beyond the amount which is on average necessary for goal attainment. Investigating subjects’ beliefs on their team mates’ behavior under team goal incentives reveals that subjects who either believe that lying is not profitable (i.e., the team goal cannot be reached with a lie) or not absolutely necessary (i.e., there is a good chance that the team goal can also be reached without lying) tend to be honest. We also find that subjects who believe that the team goal has already been reached by their team mates tend to over-report production outputs. Across treatments, women are found to be more honest than men. Subjects’ ersonality is not associated with reported production outputs. Our work contributes to previous research on how different compensation schemes affect unethical behavior in organizational settings.
Strong consistency of the least squares estimator in regression models with adaptive learning
(2017)
This paper looks at the strong consistency of the ordinary least squares (OLS) estimator in a stereotypical macroeconomic model with adaptive learning. It is a companion to Christopeit & Massmann (2017, Econometric Theory) which considers the estimator’s convergence in distribution and its weak consistency in the same setting. Under constant gain learning, the model is closely related to stationary, (alternating) unit root or explosive autoregressive processes. Under decreasing gain learning, the regressors in the model are asymptotically collinear. The paper examines, first, the issue of strong convergence of the learning recursion: It is argued that, under constant gain learning, the recursion does not converge in any probabilistic sense, while for decreasing gain learning rates are derived at which the recursion converges almost surely to the rational expectations equilibrium. Secondly, the paper establishes the strong consistency of the OLS estimators, under both constant and decreasing gain learning, as well as rates at which the estimators converge almost surely. In the constant gain model, separate estimators for the intercept and slope parameters are juxtaposed to the joint estimator, drawing on the recent literature on explosive autoregressive models. Thirdly, it is emphasised that strong consistency is obtained in all models although the near-optimal condition for the strong consistency of OLS in linear regression models with stochastic regressors, established by Lai & Wei (1982), is not always met.