Working papers

Multi-dimensional monetary policy shocks based on heteroscedasticity

IRENE Working Papers 24-03, IRENE Institute of Economic Research., 2024 Joint with Daniel Kaufmann [ Working Paper ] Abstract: We propose a two-step approach to estimate multi-dimensional monetary policy shocks and their causal effects requiring only daily financial market data and policy events. First, we combine a heteroscedasticity-based identification scheme with recursive zero restrictions along the term structure of interest rates to disentangle multi-dimensional monetary policy shocks and derive an instrumental variables estimator to estimate dynamic causal effects. Second, we propose to use the Kalman filter to compute the linear minimum mean-square-error prediction of the unobserved monetary policy shocks. We apply the approach to examine the causal effects of US monetary policy on the exchange rate. The heteroscedasticity-based monetary policy shocks display a relevant correlation with existing high-frequency surprises. In addition, their dynamic causal effects on the exchange rate are similar. This suggests the approach is a valid alternative if high-frequency identification schemes are not applicable.

Three Centuries of Swiss Economic Sentiment

[ Mimeo ] Abstract: There is a lack of consistent and well-measured Swiss business cycle indicators over long historical episodes. This paper fills this gap by constructing a business cycle indicator on quarterly frequency spanning from 1820 to 2021. Using textual data such as historical company records, newspapers, and business association reports, I develop a business cycle indicator, drawing on sentiment and count-based measures related to key economic concepts. This approach involves extensive data collection, surpassing existing datasets in scope and historical coverage. The composite indicator demonstrates strong correlations with real economic activity, effectively capturing historical downturns and expansions. I also employ it to estimate recession probabilities, shedding light on Switzerland’s economic history. This paper contributes by introducing a comprehensive business cycle indicator, assembling a rich textual dataset, presenting innovative text mining methods, and establishing the first business cycle dating for Switzerland in the 19th and early 20th centuries.

Do daily lead texts help nowcasting GDP growth?

IRENE Working Papers 23-02, IRENE Institute of Economic Research, 2023 [ Working Paper ] [ Presentation ] Abstract: This paper evaluates whether publicly available daily news lead texts help nowcasting Swiss GDP growth. I collect titles and lead texts from three Swiss newspapers and calculate text-based indicators for various economic concepts. A composite indicator calculated from these indicators is highly correlated with low-frequency macroeconomic data and survey-based indicators. In a pseudo out-of-sample nowcasting exercise for Swiss GDP growth, the indicator outperforms a monthly Swiss business cycle indicator if one month of information is available. Improvements in nowcasting accuracy mainly occur in times of economic distress.

Publications

A daily fever curve for the swiss economy

Swiss Journal of Economics and Statistics, 156(6), doi:10.1186/s41937-020-00051-z, 2020 Joint with Daniel Kaufmann [ Dashboard ][ Publication ][ Online Appendix ][ Codes & Data ] [ Presentation ] News coverage: [ Finanz und Wirtschaft 1 ][ Finanz und Wirtschaft 2 ][ Solothurner Zeitung ][ Republik 1 ][ Republik 2 ][ Economics Observatory ][ Neuchâtel Économie ] Other releases: [ Ökonomenstimme ][ LexTech Institute ] Abstract: We develop a fever curve for the Swiss economy using publicly available daily financial market and news data. The indicator can be computed with a delay of one day. Moreover, it is highly correlated with macroeconomic data and survey indicators of Swiss economic activity. Therefore, it provides timely and reliable warning signals if the health of the economy takes a turn for the worse.

Ph.D. Thesis

Three Essays in Macroeconomics with Applications in Textual Analysis

[ Full thesis | Chapter 1 Chapter 2 Chapter 3] My dissertation contributes three essays to the growing literature in economics that utilizes textual analysis to address questions in macroeconomics. The first chapter develops a daily business cycle indicator for Switzerland. Using financial market and news data, a timely “fever curve” is created, offering more accurate nowcasts of economic activity than existing indicators. The second chapter focuses on disentangling the effects of different U.S. monetary policy shocks on the exchange rate based on a new methodology that identifies shocks based on changes in the variance-covariance matrix of financial variables. The third chapter constructs a historical business cycle indicator for Switzerland from 1821 to the present. Using textual data from company records and newspapers, a chronology of Swiss economic fluctuations is provided, aligning with well-known events and offering new insights into historical business cycles.

Other projects

AI in economic resarch: A guide for students and instructors

IRENE Policy Reports 24-03, IRENE Institute of Economic Research, 2024 Joint with N. Ostovan and D. Kaufmann [ Policy report ]

Study to evaluate the future data compilation for the Swiss Consumer Sentiment Index

Staatssekretariat für Wirtschaft SECO, Bern, Schweiz. Grundlagen für die Wirtschaftspolitik 43, 2024 Joint with G. Lutz, B. Wernli, E. Antal, O. Lipps, V. Legler, D. Kaufmann [ Policy report ]