Target audience and registration

The course is only available for five students each semester of the Masters program in Economics. 6 Credits (PO 2012 and PO 2015) can be obtained. Assignments are based on the "first-come, first-serve" principle. The registration at the examination office has to be done before the early-exams-deadline.

Course

Each student has to conduct an empirical study and write a paper of appr. 20 pages.

Topic

The chair  focuses on topics concerning financial markets, commodities and monetary economics. The chosen topic should cover one of these areas. Personal preferences and ideas are always welcomed and considered. Basic knowledge in econometrics and empirical research is mandatory. Knowledge in Excel and econometric software is beneficial.

Master-thesis

Once the project course is successfully completed, the empirical results can serve as the basis for the Master-thesis.

Contact person

Please contact directly the tutor which offers topics concerning your interest.
 

Topic-suggestions
 

Tutor: Prof. Dr. Martin T. Bohl

1. Monetary Policy: Quantifying Monetary Shocks

• Ramey, V.A. (2016), „Macroeconomic Shocks and Their Propagation”, in: Handbook of  Macroeconomics, Vol. 2A, pp. 71-162.
• Nakamura, E. & Steinsson, J. (2018), “High-Frequency Identification of Monetary Non-Neutrality: The Information Effect”, in: Quarterly Journal of Economics, Vol. 133 (3), pp. 1283-1330.
• Altavilla, C., Brugnolini, L. ,Gürkaynak, R.S. , Matto, R. & Ragusa, G. (2019), “Measuring euro area monetary policy”, in: Journal of Monetary Economics, Vol. 108, pp. 162-179.

2. Unstructured Data in Monetary Policy and Financial Analysis

• Loughran, T. & McDonald, B. (2011), “When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks”, in: The Journal of Finance, Vol. 66 (1), pp. 35-65.
• Shapiro, A.H. & Wilson, D.J. (2022), “Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives using Text Analysis”, in: Review of Economic Studies, Vol. 89 (5), pp. 1-38.
• Apel, M., Blix Grimaldi, M., & Hull, I. (2022): “How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC’s Minutes and Transcripts” in: Journal of Money, Credit, and Banking, Vol. 54 (5), pp. 1460-1490.

3. Economics of Financial Crises and Credit Cycles

• Schularick, M. & Taylor, A.M. (2012), “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008”, in: American Economic Review, Vol. 102 (2), pp. 1029-1061.
• Baron, M., E. Verner & Xiong, W. (2021), “Banking Crises Without Panics", in: Quarterly Journal of Economics, Vol. 136 (1), pp. 51-113.
• Sufi, A. & Taylor, A.M. (2022), “Financial Crises: A Survey”, in: Handbook of International Economics: International Macroeconomics, Vol. 6, pp. 291-340.

Tutor: Lars Kranzmann

4.  Understanding Central Banks through Text Analysis

• Gentzkow, M., Kelly, B. & Taddy, M. (2019), “Text as Data.”, in: Journal of Economic Literature, Vol. 66 (3), pp. 535-574.
• Ferrara, F.M. & Angino, S. (2022), “Does clarity make central banks more engaging? Lessons from ECB communications”, in: European journal of Political Economy, Vol. 74, Article 102146.
• Apel, M., Blix Grimaldi, M. & Hull, I. (2022), “How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC’s Minutes and Transcripts” in: Journal of Money, Credit, and Banking, Vol. 54 (5), pp. 1460-1490.

5. Construction of a Financial Stress Index

• Cardarelli, R., Elekdag, S. & Lall, S. (2011), “Financial stress and economic contractions”, in: Journal of Financial Stability, Vol. 7, pp. 78-97.
• Hakkio, C.S. & Keeton, W.R. (2009), “Financial Stress: What Is It, How Can It Be Measured, and Why Does It Matter?” in: Economic Review, Federal Reserve Bank of Kansas City (Second Quarter), pp. 5-50.
• Vermeulen, R., Hoeberichts, M., Vašíček, B., Zigraiova, D, Smidkova, K. & de Haan, J. (2015), “Financial Stress Indices and Financial Crises”, in: Open Economic Review, Vol. 26, pp. 383-406.

Tutor: Niklas Humann

6. Evaluating and Refining Forecasts: A Comparative Analysis of (Machine Learning) Models in Forecasting (Macro-)Economic Variables

• Petropoulos, F. et al. (2022), „Forecasting: Theory and Practice”, in: International Journal of Forecasting, Vol. 38, pp. 705-871.
• Bok, B., Caratelli, D., Giannone, D., Sbordone, A.M. & Tambalotti, A. (2018), „Macroeconomic Nowcasting and Forecasting with Big Data”, in: Annual Review of Economics, Vol. 10, pp. 615-643.
• McCracken, M. & Ng, S. (2016), „FRED-MD: A Monthly Database for Macroeconomic Research”, in: Journal of Business & Economic Statistics, Vol. 34 (4), pp. 574-589.
• Elliott, G. & Timmermann, A. (2016), „Economic Forecasting”, Princeton University Press.

7. Commodities as an Investment? Financialization and the Rising Connectedness in International Financial Markets

• Zhang, D. & Broadstock, D.C. (2020), „Global Financial Crisis and Rising Connectedness in the International Commodity Markets”, in: International Review of Financial Analysis, Vol. 68, Article 101239.
• Diebold, F.X., Liu, L., & Yilmaz, K (2017), „Commodity Connectedness”, NBER Working Paper No. 23685.
• Cheng, I.-H. & Xiong, W. (2014), „Financialization of Commodity Markets”, in: Annual Review of Financial Economics, Vol. 6, pp. 419-441.