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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The Importance of Credit Demand for Business Cycle Dynamics
Gregor von Schweinitz
IWH Discussion Papers,
Nr. 21,
2023
Abstract
This paper contributes to a better understanding of the important role that credit demand plays for credit markets and aggregate macroeconomic developments as both a source and transmitter of economic shocks. I am the first to identify a structural credit demand equation together with credit supply, aggregate supply, demand and monetary policy in a Bayesian structural VAR. The model combines informative priors on structural coefficients and multiple external instruments to achieve identification. In order to improve identification of the credit demand shocks, I construct a new granular instrument from regional mortgage origination.
I find that credit demand is quite elastic with respect to contemporaneous macroeconomic conditions, while credit supply is relatively inelastic. I show that credit supply and demand shocks matter for aggregate fluctuations, albeit at different times: credit demand shocks mostly drove the boom prior to the financial crisis, while credit supply shocks were responsible during and after the crisis itself. In an out-of-sample exercise, I find that the Covid pandemic induced a large expansion of credit demand in 2020Q2, which pushed the US economy towards a sustained recovery and helped to avoid a stagflationary scenario in 2022.
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Market-implied Ratings and Their Divergence from Credit Ratings
Iftekhar Hasan, Winnie P. H. Poon, Jianfu Shen, Gaiyan Zhang
Journal of Financial Research,
Nr. 2,
2023
Abstract
In this article, we investigate the divergence between credit ratings (CRs) and Moody's market-implied ratings (MIRs). Our evidence shows that rating gaps provide incremental information to the market regarding issuers' default risk over CRs alone in the short horizon and outperform CRs over extended horizons. The predictive ability of rating gaps is greater for more opaque and volatile issuers. Such predictability was more pronounced during the 2008 financial crisis but weakened in the post-Dodd-Frank Act period. This finding is consistent with credit rating agencies' efforts to improve their performance when facing regulatory pressure. Moreover, our analysis identifies rating-gap signals that do (do not) lead to subsequent Moody's actions to place issuers on negative outlook and watchlists. We find that negative signals from MIR gaps have a real economic impact on issuers' fundamentals such as profitability, leverage, investment, and default risk, thus supporting the recovery-efforts hypothesis.
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Reports des European Forecasting Network (EFN)
Reports des European Forecasting Network (EFN) Das European Forecasting Network...
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CompNet Database
The CompNet Competitiveness Database The Competitiveness Research Network (CompNet)...
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IWH-CompNet Discussion Papers
IWH-CompNet Discussion Papers Die IWH-CompNet Discussion Papers beinhalten...
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Evidenzbasierte Politikberatung (IWH-CEP)
Zentrum für evidenzbasierte Politikberatung (IWH-CEP) ...
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Arbeitspapiere
Macroeconomic Effects from Sovereign Risk vs. Knightian Uncertainty ...
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Elderly Left Behind? How Older Workers Can Participate in the Modern Labor Market
Oliver Falck, Valentin Lindlacher, Simon Wiederhold
EconPol Forum,
Nr. 5,
2022
Abstract
In her 2021 State of the Union address, European Commission’s President Ursula von der Leyen announced that “[the EU] will invest in 5G and fiber. But equally important is the investment in digital skills.” Indeed, the EU Recovery and Resilience Facility, which runs until 2026, has earmarked substantial funds to tackle the digital divide, in acknowledgment of the fact that the EU is not only missing ICT specialists but also that many Europeans do not have sufficient digital skills to thrive in today’s society and labor market. Many observers argue that older workers in particular lack digital skills, suffering more often from computer anxiety and showing lower computer self-efficacy (Czaja et al. 2006). This lack of skills hampers their employability and productivity in a technologically fast-changing world.
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