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Professor Dr. Oliver Holtemöller

Professor Dr. Oliver Holtemöller
Aktuelle Position

seit 3/14

Stellvertretender Präsident

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 8/09

Leiter der Abteilung Makroökonomik

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 8/09

Professor für Volkswirtschaftslehre


Martin-Luther-Universität Halle-Wittenberg

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Forschungsschwerpunkte
  • quantitative Makroökonomik, Konjunkturzyklen und Prognose
  • angewandte Ökonometrie und Zeitreihenanalyse
  • monetäre Ökonomik
  • makroökonomische Politik
  • ökologische Makroökonomie

Oliver Holtemöller ist stellvertretender Präsident des Instituts. Er ist Professor für Volkswirtschaftslehre, insbesondere Makroökonomik an der Martin-Luther-Universität Halle-Wittenberg und Leiter der Abteilung Makroökonomik am IWH.

Von 2001 bis 2003 war er wissenschaftlicher Mitarbeiter im Sonderforschungsbereich 373: Quantifizierung und Simulation Ökonomischer Prozesse an der Humboldt-Universität zu Berlin. Von 2003 bis 2009 war er Juniorprofessor für Allgemeine Volkswirtschaftslehre an der RWTH Aachen.

Er hat Volkswirtschaftslehre, Angewandte Mathematik und Praktische Informatik an der Justus-Liebig-Universität Gießen studiert. Anschließend war er von 1998 bis 2001 Stipendiat der Deutschen Forschungsgemeinschaft (DFG) und absolvierte das gemeinsame Graduiertenkolleg Angewandte Mikroökonomik der Freien Universität Berlin und der Humboldt-Universität zu Berlin. Die Promotion erfolgte 2001 an der Freien Universität zu Berlin (Dissertation: Vector Autoregressive Models and Monetary Policy Analysis).

 

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Ihr Kontakt

Professor Dr. Oliver Holtemöller
Professor Dr. Oliver Holtemöller
- Abteilung Makroökonomik
Nachricht senden +49 345 7753-800 Persönliche Seite LinkedIn Profil

Publikationen

Zitationen
1326

Neueste Publikationen

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Is There an Information Channel of Monetary Policy?

Oliver Holtemöller Alexander Kriwoluzky Boreum Kwak

in: Oxford Bulletin of Economics and Statistics, im Erscheinen

Abstract

Exploiting the heteroskedasticity of the changes in short-term and long-term interest rates and exchange rates around the FOMC announcement, we identify three structural monetary policy shocks. We eliminate the predictable part of the shocks and study their effects on financial variables and macro variables. The first shock resembles a conventional monetary policy shock, and the second resembles an unconventional monetary shock. The third shock leads to an increase in interest rates, stock prices, industrial production, consumer prices, and commodity prices. At the same time, the excess bond premium and uncertainty decrease, and the U.S. dollar depreciates. Therefore, this third shock combines all the characteristics of a central bank information shock.

Publikation lesen
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Zwölf-Punkte-Kompass zur Überwindung der deutschen Wachstumsschwäche

Geraldine Dany-Knedlik Oliver Holtemöller Stefan Kooths Torsten Schmidt Timo Wollmershäuser

in: Wirtschaftsdienst, im Erscheinen

Abstract

Die Projektgruppe Gemeinschaftsdiagnose prognostiziert für das Jahr 2025 einen leichten Zuwachs des Bruttoinlandsprodukts in Deutschland um 0,2 %. Im weiteren Prognosezeitraum stimuliert die expansive Finanzpolitik die Konjunktur. Die Institute prognostizieren für die kommenden beiden Jahre Expansionsraten von 1,3 % und 1,4 %. Strukturelle Probleme wie abnehmende Wettbewerbsfähigkeit und der demografische Wandel bleiben bestehen. Um Wachstumsperspektiven für die deutsche Wirtschaft zu schaffen, bedarf es einer umfangreichen Reformpolitik. Zur Orientierung präsentieren die Institute einen Zwölf-Punkte-Kompass für den Herbst der Reformen.

Publikation lesen
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Growth Clubs and Regional Economic Convergence in Germany

Oliver Holtemöller Christoph Schult Anna Solms

in: IWH Discussion Papers, Nr. 4, 2026

Abstract

Many countries and regions remain below the level of economic activity of the world’s most advanced economies. Some countries form growth clubs, some are stuck in the middle-income trap, and some stay on a very low level of economic activity. Although this situation is well documented on the country level, there is less evidence at the sub-national level within countries. We estimate county-level capital stocks and price indices and provide a comprehensive county-level data set for Germany. We find no evidence of convergence across all counties even if we condition on important drivers of long-term growth such as physical and human capital accumulation. Instead, we identify five convergence clubs, using endogenous clustering. We analyze differences in growth paths and describe the identified clusters based on variations in contributions of capital, labor, and total factor productivity to economic growth. Additionally, we examine the role of migration for regional development and find that net migration has in particular contributed to growth in richer regions.

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Referierte Publikationen

cover_Oxford-Bulletin-of-Economics-and-Statistics.png

Is There an Information Channel of Monetary Policy?

Oliver Holtemöller Alexander Kriwoluzky Boreum Kwak

in: Oxford Bulletin of Economics and Statistics, im Erscheinen

Abstract

Exploiting the heteroskedasticity of the changes in short-term and long-term interest rates and exchange rates around the FOMC announcement, we identify three structural monetary policy shocks. We eliminate the predictable part of the shocks and study their effects on financial variables and macro variables. The first shock resembles a conventional monetary policy shock, and the second resembles an unconventional monetary shock. The third shock leads to an increase in interest rates, stock prices, industrial production, consumer prices, and commodity prices. At the same time, the excess bond premium and uncertainty decrease, and the U.S. dollar depreciates. Therefore, this third shock combines all the characteristics of a central bank information shock.

Publikation lesen
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International Trade Barriers and Regional Employment: The Case of a No-Deal Brexit

Hans-Ulrich Brautzsch Oliver Holtemöller

in: Journal of Economic Structures, Vol. 10 (11), 2021

Abstract

We use the World Input–Output Database (WIOD) combined with regional sectoral employment data to estimate the potential regional employment effects of international trade barriers. We study the case of a no-deal Brexit in which imports to the United Kingdom (UK) from the European Union (EU) would be subject to tariffs and non-tariff trade costs. First, we derive the decline in UK final goods imports from the EU from industry-specific international trade elasticities, tariffs and non-tariff trade costs. Using input–output analysis, we estimate the potential output and employment effects for 56 industries and 43 countries on the national level. The absolute effects would be largest in big EU countries which have close trade relationships with the UK, such as Germany and France. However, there would also be large countries outside the EU which would be heavily affected via global value chains, such as China, for example. The relative effects (in percent of total employment) would be largest in Ireland followed by Belgium. In a second step, we split up the national effects on the NUTS-2 level for EU member states and additionally on the county (NUTS-3) level for Germany. The share of affected workers varies between 0.03% and 3.4% among European NUTS-2 regions and between 0.15% and 0.4% among German counties. A general result is that indirect effects via global value chains, i.e., trade in intermediate inputs, are more important than direct effects via final demand.

Publikation lesen
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Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany

Katja Heinisch Oliver Holtemöller Christoph Schult

in: Energy Economics, Vol. 95, 2021

Abstract

In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. We study potential economic consequences of a coal phase-out in Germany, using a multi-region dynamic general equilibrium model. Four regional phase-out scenarios before the end of 2040 are simulated. We find that the worst case phase-out scenario would lead to an increase in the aggregate unemployment rate by about 0.13 [0.09 minimum; 0.18 maximum] percentage points from 2020 to 2040. The effect on regional unemployment rates varies between 0.18 [0.13; 0.22] and 1.07 [1.00; 1.13] percentage points in the lignite regions. A faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,100 [6300; 12,300] people by 2040. A coal phase-out until 2035 is not worse in terms of welfare, consumption and employment compared to a coal-exit until 2040.

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Arbeitspapiere

cover_DP_2026-04.jpg

Growth Clubs and Regional Economic Convergence in Germany

Oliver Holtemöller Christoph Schult Anna Solms

in: IWH Discussion Papers, Nr. 4, 2026

Abstract

Many countries and regions remain below the level of economic activity of the world’s most advanced economies. Some countries form growth clubs, some are stuck in the middle-income trap, and some stay on a very low level of economic activity. Although this situation is well documented on the country level, there is less evidence at the sub-national level within countries. We estimate county-level capital stocks and price indices and provide a comprehensive county-level data set for Germany. We find no evidence of convergence across all counties even if we condition on important drivers of long-term growth such as physical and human capital accumulation. Instead, we identify five convergence clubs, using endogenous clustering. We analyze differences in growth paths and describe the identified clusters based on variations in contributions of capital, labor, and total factor productivity to economic growth. Additionally, we examine the role of migration for regional development and find that net migration has in particular contributed to growth in richer regions.

Publikation lesen
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Optimal Monetary Policy in a Two-sector Environmental DSGE Model

Oliver Holtemöller Alessandro Sardone

in: IWH Discussion Papers, Nr. 18, 2024

Abstract

In this paper, we discuss how environmental damage and emission reduction policies affect the conduct of monetary policy in a two-sector (clean and dirty) dynamic stochastic general equilibrium model. In particular, we examine the optimal response of the interest rate to changes in sectoral inflation due to standard supply shocks, conditional on a given environmental policy. We then compare the performance of a nonstandard monetary rule with sectoral inflation targets to that of a standard Taylor rule. Our main results are as follows: first, the optimal monetary policy is affected by the existence of environmental policy (carbon taxation), as this introduces a distortion in the relative price level between the clean and dirty sectors. Second, compared with a standard Taylor rule targeting aggregate inflation, a monetary policy rule with asymmetric responses to sector-specific inflation allows for reduced volatility in the inflation gap, output gap, and emissions. Third, a nonstandard monetary policy rule allows for a higher level of welfare, so the two goals of welfare maximization and emission minimization can be aligned.

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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

in: IWH Discussion Papers, Nr. 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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