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Elias Bengtsson

25 August 2017
This paper proposes a framework for monitoring vulnerabilities related to the residential real estate sector in a cross-country context. The framework might be useful for complementing or cross-checking signals available from existing approaches. It takes into account three dimensions of real estate sector vulnerabilities (i.e. valuation, household indebtedness and the bank credit cycle) and enables monitoring across countries in a simple and informative way. Indicators are derived from the early warning literature and policy publications. They are aggregated in a modelfree way to a vulnerability measure, explicitly capturing the level and the dynamics of vulnerabilities. The measure proves to be a significant predictor of historical real estate crises, with a better forecasting performance than the majority of advantageously in-sample calibrated model-based estimates. The monitoring framework allows for a simple and transparent analysis across different dimensions, provides a cross-check of consistency of signals from several indicators, and accounts for the developments in terms of the levels and dynamics. In view of its good forecasting performance, it is a useful complement of model-based toolkits for analysing vulnerabilities in the residential real estate sector.
31 July 2017
This paper presents a new database for financial crises in European countries, which serves as an important step towards establishing a common ground for macroprudential oversight and policymaking in the EU. The database focuses on providing precise chronological definitions of crisis periods to support the calibration of models in macroprudential analysis. An important contribution of this work is the identification of financial crises by combining a quantitative approach based on a financial stress index with expert judgement from national and European authorities. Key innovations of this database are (i) the inclusion of qualitative information about events and policy responses, (ii) the introduction of a broad set of non-exclusive categories to classify events, and (iii) a distinction between event and post-event adjustment periods. The paper explains the two-step approach for identifying crises and other key choices in the construction of the dataset. Moreover, stylised facts about the systemic crises in the dataset are presented together with estimations of output losses and fiscal costs associated with these crises. A preliminary assessment of the performance of standard early warning indicators based on the new crises dataset confirms findings in the literature that multivariate models can improve compared to univariate signalling models.
JEL Code
G01 : Financial Economics→General→Financial Crises
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E60 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General
H12 : Public Economics→Structure and Scope of Government→Crisis Management