Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Historical Social Research,
Special Issue: Governing by Numbers
2019
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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Badly Hurt? Natural Disasters and Direct Firm Effects
Felix Noth, Oliver Rehbein
Finance Research Letters,
2019
Abstract
We investigate firm outcomes after a major flood in Germany in 2013. We robustly find that firms located in the disaster regions have significantly higher turnover, lower leverage, and higher cash in the period after 2013. We provide evidence that the effects stem from firms that already experienced a similar major disaster in 2002. Overall, our results document a positive net effect on firm performance in the direct aftermath of a natural disaster.
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Benign Neglect of Covenant Violations: Blissful Banking or Ignorant Monitoring?
Stefano Colonnello, Michael Koetter, Moritz Stieglitz
Abstract
Theoretically, bank‘s loan monitoring activity hinges critically on its capitalisation. To proxy for monitoring intensity, we use changes in borrowers‘ investment following loan covenant violations, when creditors can intervene in the governance of the firm. Exploiting granular bank-firm relationships observed in the syndicated loan market, we document substantial heterogeneity in monitoring across banks and through time. Better capitalised banks are more lenient monitors that intervene less with covenant violators. Importantly, this hands-off approach is associated with improved borrowers‘ performance. Beyond enhancing financial resilience, regulation that requires banks to hold more capital may thus also mitigate the tightening of credit terms when firms experience shocks.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?
Katja Heinisch, Axel Lindner
Applied Economics Letters,
Nr. 3,
2019
Abstract
This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.
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Avoiding the Fall into the Loop: Isolating the Transmission of Bank-to-Sovereign Distress in the Euro Area and its Drivers
Hannes Böhm, Stefan Eichler
Abstract
We isolate the direct bank-to-sovereign distress channel within the eurozone’s sovereign-bank-loop by exploiting the global, non-eurozone related variation in stock prices. We instrument banking sector stock returns in the eurozone with exposure-weighted stock market returns from non-eurozone countries and take further precautions to remove any eurozone crisis-related variation. We find that the transmission of instrumented bank distress, while economically relevant, is significantly smaller than the corresponding coefficient in the unadjusted OLS framework, confirming concerns on reverse causality and omitted variables in previous studies. Furthermore, we show that the spillover of bank distress is significantly stronger for countries with poorer macroeconomic performances, weaker financial sectors and financial regulation and during times of elevated political uncertainty.
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Living with Lower Productivity Growth: Impact on Exports
Filippo di Mauro, Bernardo Mottironi, Gianmarco Ottaviano, Alessandro Zona-Mattioli
IWH-CompNet Discussion Papers,
Nr. 1,
2018
Abstract
This paper investigates the impact of sustained lower productivity growth on exports, by looking at the role of the productivity distribution and allocative efficiency as drivers of export performance. It follows and goes beyond the work of Barba Navaretti et al. (2017), analysing the effects of productivity on exports depending on the dynamics of allocative efficiency. Low productivity growth is a well-documented stylised fact in Western countries – and possibly a reality likely to persist for some time. What could be the impact of persistent sluggish growth of productivity on exports? To shed light on this question, this paper examines the relationship between the productivity distribution of firms and sectoral export performance. The structure of firms within countries or even sectors matters tremendously for the nexus between productivity and exports at the macroeconomic level, as the theoretical and empirical literature documents. For instance, whether too few firms at the top (lack of innovation) or too many firms at the bottom (weak market selection) drives slow average productivity at the macro level has very different implications and therefore demands different policy responses.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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Africa’s Skill Tragedy
Jan Bietenbeck, Marc Piopiunik, Simon Wiederhold
Journal of Human Resources,
Nr. 3,
2018
Abstract
We study the importance of teacher subject knowledge for student performance in Sub-Saharan Africa using unique international assessment data for sixth-grade students and their teachers. To circumvent bias due to unobserved student heterogeneity, we exploit variation within students across math and reading. Teacher subject knowledge has a modest impact on student performance. Exploiting vast cross-country differences in economic development, we find that teacher knowledge is effective only in more developed African countries. Results are robust to adding teacher fixed effects and accounting for potential sorting based on subject-specific factors.
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