Professorin Christiane Baumeister, Ph.D.

Professorin Christiane Baumeister, Ph.D.
Aktuelle Position

seit 6/19

Research Fellow der Abteilung Makroökonomik

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 7/20


University of Notre Dame


  • empirische Makroökonomik
  • Prognosen
  • angewandte Ökonometrie
  • Energiemärkte

Christiane Baumeister ist seit Juni 2019 Research Fellow am IWH. Ihre Forschungsinteressen umfassen empirische Makroökonomik, Energiemärkte, angewandte Zeitreihenökonometrie, Geldpolitik und Prognosen.

Christiane Baumeister ist Professorin an der wirtschaftswissenschaftlichen Fakultät der University of Notre Dame. Sie ist auch ein Faculty Research Fellow des NBER und ein Research Affiliate des CEPR. Zuvor war sie als Principal Researcher in der internationalen Wirtschaftsabteilung der Bank of Canada beschäftigt. Sie war als Gastforscherin am IWF und verschiedenen Zentralbanken wie den Federal Reserve Banks von St. Louis, Dallas, Cleveland und Kansas City, der Reserve Bank of New Zealand, der Banque de France und der Bank of Finland.

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Professorin Christiane Baumeister, Ph.D.
Professorin Christiane Baumeister, Ph.D.
Mitglied - Abteilung Makroökonomik
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Energy Markets and Global Economic Conditions

Christiane Baumeister Dimitris Korobilis Thomas K. Lee

in: Review of Economics and Statistics, im Erscheinen


We evaluate alternative indicators of global economic activity and other market funda-mentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. World industrial production is one of the most useful indicators. However, by combining measures from several different sources we can do even better. Our analysis results in a new index of global economic conditions and measures for assessing future energy demand and oil price pressures. We illustrate their usefulness for quantifying the main factors behind the severe contraction of the global economy and the price risks faced by shale oil producers in early 2020.

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A Comparison of Monthly Global Indicators for Forecasting Growth

Christiane Baumeister Pierre Guérin

in: International Journal of Forecasting, Nr. 3, 2021


This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world real GDP growth using mixed-frequency models. It shows that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecasting accuracy, while other monthly measures have more mixed success. Specifically, the best-performing model yields impressive gains with MSPE reductions of up to 34% at short horizons and up to 13% at long horizons relative to an autoregressive benchmark. The global economic conditions indicator also contains valuable information for assessing the current and future state of the economy for a set of individual countries and groups of countries. This indicator is used to track the evolution of the nowcasts for the U.S., the OECD area, and the world economy during the COVID-19 pandemic and the main factors that drive the nowcasts are quantified.

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Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions

Christiane Baumeister James D. Hamilton

in: Journal of International Money and Finance, December 2020


This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha’s (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.

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