Richard Schnorrenberger
Moin!
I am a postdoctoral research associate and teaching assistant at the Institute for Statistics and Econometrics of Kiel University.
My research interests are mostly linked to time series analysis and macro-finance forecasting in a data-rich environment. Throughout the initial years of my Ph.D., my research agenda has been focused on yield curve modeling in times of financial distress. However, with the return of inflationary waves in global markets after the pandemic, I concentrated my research endeavors on improving cutting-edge models for inflation forecasting using novel machine learning methods and non-traditional datasets.
You can find more about my work in the Research section and my background in the CV section.
News
(June, 2024) 🎓 Excited to share a personal milestone: I have successfully defended my PhD thesis! This journey has been both challenging and rewarding. I am deeply grateful to everyone who supported me along the way, especially my wife, my PhD supervisor, colleagues, and co-authors.
(March, 2024) New De Nederlandsche Bank working paper alert: "Harnessing Machine Learning for Real-Time Inflation Nowcasting", available here. Joint work with Aishameriane Schmidt (Erasmus Universiteit Rotterdam & Tinbergen Institute) and Guilherme Valle Moura (UFSC). This paper has also been accepted for presentation at outstanding conferences in 2024, including the 2nd Annual Conference of the Brazilian Central Bank and the International Association for Applied Econometrics Annual Conference.
(December, 2023) New Deutsche Bundesbank working paper alert: "Nowcasting Consumer Price Inflation Using High-frequency Scanner Data: Evidence from Germany", available here. Joint work with Günter W. Beck (University of Siegen), Kai Carstensen (Kiel University), Jan-Oliver Menz (Deutsche Bundesbank), and Elisabeth Wieland (Deutsche Bundesbank). A research letter has also been recently published here on the Deutsche Bundesbank website.
(June, 2023) The working paper version of our work "Nowcasting Consumer Price Inflation Using High-frequency Scanner Data: Evidence from Germany" (see Research section) has been accepted for presentation at many outstanding conferences this summer term, including the 9th Annual Conference of the International Association for Applied Econometrics, Inflation: Drivers and Dynamics 2023 Conference (Fed of Cleveland and the ECB), ECONDAT 2023 Spring Meeting (Bank of England), and 43rd International Symposium on Forecasting.
(May, 2023) The joint work on "Inflation nowcasting in persistently high inflation environments" with my Brazilian fellows Aishameriane Schmidt and Guilherme Valle Moura has been accepted for presentation at the following conferences: 43rd International Symposium on Forecasting, 29th International Conference on Computing in Economics, BSE Summer Forum on Macroeconometrics and Policy Evaluation, European Meeting of the Econometric Society and Financial Econometrics meets Machine Learning.
(January, 2023) It is with great joy that I would like to share the following news. I will be an intern at the Deutsche Bundesbank during the summer term of 2023. I will be joining the Prices team at the Division of Business Cycle Analysis and Projections.
(November, 2022) The collaborative work on "Nowcasting Consumer Price Inflation Using High-frequency Scanner Data: Evidence from Germany" (see Research section) has been presented at the 23rd IWH-CIREQ-GW Macroeconometric Workshop on Inflation: Modelling, Forecasting and Monetary Policy Reactions in Halle, Germany. I would like to express my gratitude for the excellent discussion and the great feedback received from the attendees. The suggestions have already been included in our research agenda!
(September, 2022) On July 13th, I presented my single-authored Ph.D. paper at the 42nd International Symposium on Forecasting (ISF 2022) in Oxford, England. I also presented this work in a poster format at the 12th European Seminar on Bayesian Econometrics (ESOBE 2022) held in Salzburg, Austria on September 8. The paper is entitled "Bond portfolio optimization in turbulent times: a dynamic Nelson-Siegel approach with Wishart stochastic volatility" (see Research section). On both occasions, I had the chance to discuss my work with leading experts and enthusiasts in the field, hence making these academic experiences part of the greatest achievements in my career thus far!
(June, 2022) A VoxEU article based on the ongoing project "Nowcasting German inflation using scanner price data" has been available here. It provides a small taste of the usefulness of high-frequency scanner data to monitor real-time food price inflation in the aftermath of the Russian invasion of Ukraine.