This paper documents a link between bank concentration and markups in nonfinancial sectors. We exploit concentration-increasing bank mergers and variation in banks’ market shares across industries and show that higher credit concentration is associated with higher markups and that high-market-share lenders charge lower loan rates. We argue that this is due to the greater incidence of competing firms sharing common lenders that induce less aggressive product market behavior among their borrowers, thereby internalizing potential adverse effects of higher rates. Consistent with our conjecture, the effect is stronger in industries with competition in strategic substitutes where negative product market externalities are greatest.

Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies.
This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution.
The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.

Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies. This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution. The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.

Climate change projections show that the average global temperature will very likely increase further. Policymakers need to implement suitable mitigation policy measures. This thesis uses dynamic general equilibrium models (DGEs) to analyse the potential economic effects of mitigation policy. Chapter 2 documents the forecasting performance of standardly estimated macroeconomic models and compare them to extended versions. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of macroeconomic models. Chapter 3 studies potential economic consequences of a coal phase-out in Germany, using a spatial dynamic general equilibrium model. A phase-out until 2035 is not worse in terms of welfare compared to a coal exit until 2040. Chapter 4 develops a dynamic stochastic general equilibrium (DSGE) model with risky capital and oil as production factors. The contribution of financial market frictions and oil market disturbances to the US business cycle are low. An oil tax increase, to reduce crude oil consumption by 10% can cause a contraction of GDP by 1 to 2%.

Nach der Mittelfristprojektion des IWH wird das Bruttoinlandsprodukt in Deutschland in den Jahren bis 2025 preisbereinigt um durchschnittlich ½% wachsen, und damit einen Prozentpunkt langsamer als im Zeitraum von 2013 bis 2019. Dies ist nicht nur auf den starken Einbruch im Jahr 2020 zurückzuführen, sondern auch darauf, dass die Erwerbsbevölkerung spürbar zurückgehen wird. Die Staatseinnahmen expandieren deutlich langsamer als in den vergangenen Jahren. Auch nach Überwindung der Pandemiekrise dürfte der Staatshaushalt im Fall unveränderter gesetzlicher Rahmenbedingungen ein strukturelles Defizit von etwa 2% relativ zum Bruttoinlandsprodukt aufweisen, und die Schuldenbremse würde weiter verletzt. Konsolidierungsmaßnahmen zur Rückführung dieser Defizitquote auf ½% würden die Produktion in Deutschland unter die Normalauslastung drücken. Mit Hilfe des finanzpolitischen Simulationsmodells des IWH kann gezeigt werden, dass dabei eine ausgabenseitige Konsolidierung die Produktion weniger belastet als eine einnahmenseitige. Es spricht, auch aus theoretischer Sicht, viel dafür, die Schuldenbremse zwar nicht abzuschaffen, aber ein Stück weit zu lockern.