Kosten der Maßnahmen aus dem Rentenpaket II vom März 2024 und Finanzierungsoptionen
Oliver Holtemöller, Christoph Schult, Götz Zeddies
IWH Studies,
No. 2,
2024
Abstract
Im Zuge des demografischen Wandels nehmen die Ausgaben der gesetzlichen Rentenversicherung in Deutschland in Zukunft deutlich zu, während die Lohnsumme, aus der die Beiträge zu finanzieren sind, gedämpft wird. Immer weniger Beitragszahler stehen in dem umlagefinanzierten System immer mehr Rentnern gegenüber. Bisher hat der Nachhaltigkeitsfaktor in der Rentenformel dafür gesorgt, dass sowohl Beitragszahler als auch Rentenempfänger durch den demografischen Wandel belastet werden. Das von der Bundesregierung vorgeschlagene Rentenpaket II hebt die Wirkung des Nachhaltigkeitsfaktors durch eine Haltelinie für das Rentenniveau faktisch auf. Dies führt zu erheblichen Mehrausgaben der gesetzlichen Rentenversicherung gegenüber dem bisherigen Rechtsrahmen. Dadurch wird der ohnehin auf deutlich über 20% steigende Beitragssatz nochmal um etwa einen Prozentpunkt stärker zunehmen. Das mit den Rentenpaket II geplante Generationenkapital kann aufgrund seines geringen Volumens den Anstieg des Beitragssatzes nur um etwa 0,2 Prozentpunkte abfedern, und das auch nur, wenn sich die Erwartungen an die Rendite nach Kosten erfüllen. Eine Beibehaltung des Nachhaltigkeitsfaktors und eine Stärkung individueller Vorsorge inklusive individueller Kapitalansprüche wäre eine gute Alternative zum Rentenpaket II.
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Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
No. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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ENTRANCES
ENTRANCES aims at examining the effects of the coal phase-out in Europe. How does the phase-out transform society – and what can politics do about it? The EU-funded,…
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Evaluation of the InvKG and the federal STARK programme
Evaluation of the InvKG and the federal STARK programme InvKG = Coal Regions Investment Act STARK = Strengthening the Transformation Dynamics and Awakening in the Coalfields and…
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Loose (Interview)
When there were almost no flats in Halle yet ... Brigitte Loose about IWH's foundation and development Ms Loose, how did you experience the early days of IWH? Looking back, it was…
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Research Clusters
Three Research Clusters Research Cluster "Economic Dynamics and Stability" Research Questions This cluster focuses on empirical analyses of macroeconomic dynamics and stability.…
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Research Groups
Our Research Groups Banking, Regulation, and Incentive Structures Data Science in Financial Economics Econometric Tools for Macroeconomic Forecasting and Simulation Education,…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Evidence-based Support for Adaptation Policies in Emerging Economies
Maximilian Banning, Anett Großmann, Katja Heinisch, Frank Hohmann, Christian Lutz, Christoph Schult
Low Carbon Economy,
No. 1,
2023
Abstract
Climate change is increasingly evident, and the design of effective climate adaptation policies is important for regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change on three vulnerable countries (Kazakhstan, Georgia, and Vietnam) and design specific adaptations. We use a Dynamic General Equilibrium (DGE) model for Vietnam and an economy-energy-emission (E3) model for the other two countries. Our simulations until 2050 show that selected adaptation measures, in particular in the agricultural sector, have positive implications for GDP. However, some adaptation measures can even increase greenhouse gas emissions. Focusing on GDP alone can lead to welfare-reducing policy decisions.
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