Climate Stress Tests, Bank Lending, and the Transition to the Carbon-neutral Economy
Larissa Fuchs, Huyen Nguyen, Trang Nguyen, Klaus Schaeck
IWH Discussion Papers,
Nr. 9,
2024
Abstract
We ask if bank supervisors’ efforts to combat climate change affect banks’ lending and their borrowers’ transition to the carbon-neutral economy. Combining information from the French supervisory agency’s climate pilot exercise with borrowers’ emission data, we first show that banks that participate in the exercise increase lending to high-carbon emitters but simultaneously charge higher interest rates. Second, participating banks collect new information about climate risks, and boost lending for green purposes. Third, receiving credit from a participating bank facilitates borrowers’ efforts to improve environmental performance. Our findings establish a hitherto undocumented link between banking supervision and the transition to net-zero.
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Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
Nr. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
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CompNet Database
The CompNet Competitiveness Database The Competitiveness Research Network (CompNet) is a forum for high level research and policy analysis in the areas of competitiveness and…
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Does IFRS Information on Tax Loss Carryforwards and Negative Performance Improve Predictions of Earnings and Cash Flows?
Sandra Dreher, Sebastian Eichfelder, Felix Noth
Journal of Business Economics,
January
2024
Abstract
We analyze the usefulness of accounting information on tax loss carryforwards and negative performance to predict earnings and cash flows. We use hand-collected information on tax loss carryforwards and corresponding deferred taxes from the International Financial Reporting Standards tax footnotes for listed firms from Germany. Our out-of-sample tests show that considering accounting information on tax loss carryforwards does not enhance performance forecasts and typically even worsens predictions. The most likely explanation is model overfitting. Besides, common forecasting approaches that deal with negative performance are prone to prediction errors. We provide a simple empirical specification to account for that problem.
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Conditional Macroeconomic Survey Forecasts: Revisions and Errors
Alexander Glas, Katja Heinisch
Journal of International Money and Finance,
November
2023
Abstract
Using data from the European Central Bank's Survey of Professional Forecasters and ECB/Eurosystem staff projections, we analyze the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the updating and ex-post performance of predictions for inflation, real GDP growth and unemployment are related to beliefs about future oil prices, exchange rates, interest rates and wage growth. While oil price and exchange rate predictions are updated more frequently than macroeconomic forecasts, the opposite is true for interest rate and wage growth expectations. Beliefs about future inflation are closely associated with oil price expectations, whereas expected interest rates are related to predictions of output growth and unemployment. Exchange rate predictions also matter for macroeconomic forecasts, albeit less so than the other variables. With regard to forecast errors, wage growth and GDP growth closely comove, but only during the period when interest rates are at the effective zero lower bound.
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Climate Stress Tests, Bank Lending, and the Transition to the Carbon-Neutral Economy
Larissa Fuchs, Huyen Nguyen, Trang Nguyen, Klaus Schaeck
SSRN Working Papers,
Nr. 4427729,
2023
Abstract
Does banking supervision affect borrowers’ transition to the carbon-neutral economy? We use a unique identification strategy that combines the French bank climate pilot exercise with borrowers’ carbon emissions to present two novel findings. First, climate stress tests actively facilitate borrowers’ transition to a low-carbon economy through a lending channel. Stress-tested banks increase loan volumes but simultaneously charge higher interest rates for brown borrowers. Second, additional lending is associated with some improvements in environmental performance. While borrowers commit more to reduce carbon emissions and are more likely to evaluate environmental effects of their projects, they neither reduce direct carbon emissions, nor terminate relationships with environmentally unfriendly suppliers. Our findings establish a causal link between bank climate stress tests and borrowers’ reductions in transition risk.
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Datenschutz
Datenschutzerklärung Wir nehmen den Schutz Ihrer persönlichen Daten sehr ernst und behandeln Ihre personenbezogenen Daten vertraulich und entsprechend der gesetzlichen…
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Brown Bag Seminar
Brown Bag Seminar Financial Markets Department In der Seminarreihe "Brown Bag Seminar" stellten Mitarbeiterinnen und Mitarbeiter der Abteilung Finanzmärkte und deren…
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Seed Fund
Seed Fund Projects SEED 2022/01 Environmental Macroeconomics: Modelling Regional and Sectoral Heterogeneity IWH-Projektleiter: Gregor von Schweinitz Projektpartner: Martin Quaas…
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