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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
IWH Discussion Papers,
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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Inference in Structural Vector Autoregressions when the Identifying Assumptions are not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations
Journal of Monetary Economics,
Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.
Zu den rentenpolitischen Plänen im Koalitionsvertrag 2018 von CDU, CSU und SPD: Konsequenzen, Finanzierungsoptionen und Reformbedarf
Zeitschrift für Wirtschaftspolitik,
In the coalition agreement from February 7, 2018, the new German federal government drafts its public pension policy, which has to be evaluated against the background of demographic dynamics in Germany. In this paper, the consequences of public pensions related policy measures for the German public pension insurance are illustrated using a simulation model. In the long run, the intended extensions of benefits would lead to an increase in the contribution rate to the German public pension insurance of about two and a half percentage points. Referring to pension systems of other countries, we discuss measures in order to limit this increase in the contribution rate.