Graduate School of North American Studies
John F Kennedy-Institut für Nordamerikastudien
Daniel Dieckelmann is a PhD candidate of Economics at the John F. Kennedy Institute of Freie Universität Berlin.
His research fields are Macro-Finance, Economic History, Financial Stability, and Systemic Risk.
With a double background in Information Systems and Economics, Daniel is further interested in machine learning and the history of economic thought. His current research explores the quantitative history of banking crises and the possibility of their prediction.
Daniel has worked for the European Central Bank, in the financial sector, and for tech start-ups.
During his PhD studies, Daniel has been hosted by Cornell University, the Bank of Israel, and the Institute of New Economic Thinking for research stays.
Download Daniel’s CV here.
2018-2019 / 2020:
Money, Banking, and Financial Crises: A historical North American perspective.
Intermediate undergraduate economics, Freie Universität Berlin
Undergraduate economics, Heidelberg University
Prof. Dr. Max Steinhardt, Freie Universität Berlin (First advisor)
Prof. Matthew Baron, PhD, Cornell University (Second advisor)
Prof. Dr. Moritz Schularick, Unibersity of Bonn
Priv.-Doz. Dr. Till Strohsal, Freie Universität Berlin
Cross-Border Lending and the International Transmission of Banking Crises
Collaboration with the Bank of Israel
Abstract: This paper introduces a new transmission channel of banking crises where sizable cross-border bank claims on foreign countries with high domestic crisis risk enable contagion to the home economy. This asset-side channel opposes traditional views that see banking crises originating from either domestic credit booms or from cross-border borrowing. I propose a combined model that predicts banking crises using both domestic and foreign factors. For developed economies, the channel is predictive of crises irrespective of other types of capital flows, while it is entirely inactive for emerging economies. I show that policy makers can significantly enhance current early warning models by incorporating exposure-based risk from cross-border lending.
The Historical Banking Crisis Database, 1870-2016
with Matthew Baron, Cornell University
Abstract: We construct a new quantitative and narrative database of banking crises, covering 46 countries since 1870, and show two ways in which modern banking crises are different from past crises. First, although unlevered bank equity losses are lower for post-1945 crises (relative to pre-1914 crises), bank equity losses are considerably greater, due to higher bank leverage. Second, in the pre-1914 period, bank equity returns are sensitive to trade, commodity, and monetary gold shocks, but less so to real estate returns and past credit booms---whereas the reverse is true in the post-1945 period. In particular, few pre-1914 banking crises are credit booms gone bust.
Laissez Faire or Laissez Faire Faillite? 150 Years of Bank Bailouts
Work in progress.
Boom Bust Whom? Disaggregated private credit in the United States, 1896-2017.
Abstract: This paper examines whether the functional differentiation of private credit matters with respect to financial stability and economic growth. I present new historical data on total private credit to the non-financial sector in the United States for the past 120 years. The new series is disaggregated by type of borrower (household, businesses) and by type of loan (mortgage, non-mortgage). I find that no single credit components outperforms the others in predicting financial crises. However, total private credit levels above 80% rapidly increase their probability. Household non-mortgage credit has a positive short-term effect on income growth that is offset by a subsequent negative effect over the medium run. Business non-mortgage credit depresses income growth and puts the economy on a lower output level. Reversely, income growth induces growth in business debt, especially after the Second World War. The effects of mortgage credit remain ambiguous both in terms of financial stability and economic growth.