Professor Christiane Baumeister, PhD

Professor Christiane Baumeister, PhD
Current Position

since 6/19

Research Fellow Department of Macroeconomics

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

since 7/17

Associate Professor of Economics

University of Notre Dame

Research Interests

  • empirical macroeconomics
  • forecasting
  • applied econometrics
  • energy economics

Christiane Baumeister joined the Department of Macroeconomics as a Research Fellow in June 2019. Her research focuses on empirical macroeconomics, applied time series econometrics, energy markets, monetary economics, and forecasting.

Christiane Baumeister is the Robert and Irene Bozzone Associate Professor of Economics at the University of Notre Dame. She is also a Faculty Research Fellow of the NBER and a Research Affiliate of the CEPR. Prior to joining Notre Dame in July 2015, she was a Principal Researcher in the International Economic Analysis Department at the Bank of Canada. She has been a visiting scholar at the IMF and various central banks, including the Federal Reserve Banks of St. Louis, Dallas, Cleveland, and Kansas City, the Reserve Bank of New Zealand, the Bank of France, and the Bank of Finland.

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Professor Christiane Baumeister, PhD
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Publications

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Energy Markets and Global Economic Conditions

Christiane Baumeister Dimitris Korobilis Thomas K. Lee

in: Review of Economics and Statistics, forthcoming

Abstract

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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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

Abstract

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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Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks

Christiane Baumeister James D. Hamilton

in: American Economic Review, No. 5, 2019

Abstract

Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not.

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