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Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The ex-post threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-ofsample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.

This book approaches macroprudential oversight from the viewpoint of three tasks. The focus concerns a tight integration of means for risk communication into analytical tools for risk identification and risk assessment. Generally, this book explores approaches for representing complex data concerning financial entities on low-dimensional displays. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats. Accordingly, this book creates a Self-Organizing Financial Stability Map (SOFSM), and lays out a general framework for mapping the state of financial stability. Beyond external risk communication, the aim of the visual means is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence.

AbstractThe 2007–2008 financial crisis has paved the way for the use of macroprudential policies in supervising the financial system as a whole. This article views macroprudential oversight in Europe as a process, a sequence of activities with the ultimate aim of safeguarding financial stability. To conceptualize a process in this context, we introduce the notion of a public collaborative process (PCP). PCPs involve multiple organizations with a common objective, where a number of dispersed organizations cooperate under various unstructured forms and take a collaborative approach to reaching the final goal. We argue that PCPs can and should essentially be managed using the tools and practices common for business processes. To this end, we conduct an assessment of process readiness for macroprudential oversight in Europe. Based upon interviews with key European policy makers and supervisors, we provide an analysis model to assess the maturity of five process enablers for macroprudential oversight. With the results of our analysis, we give clear recommendations on the areas that need further attention when macroprudential oversight is being developed, in addition to providing a general purpose framework for monitoring the impact of improvement efforts.

AbstractThis paper focuses on multi‐attribute design problems in which several quantitative and/or qualitative attributes are simultaneously involved. Preference elicitation methods dealing with decision‐makers' preferences are often employed to solve such problems. The present paper proposes a conceptual framework that considers preference elicitation as a process shaped by the interaction of different factors including the researcher, methodology, questionnaire and respondent in a given context, at the same time. The aim of the framework is to assist in choosing a decision support tool among various multi‐attribute decision‐making methods, as well as in evaluating and understanding preference elicitation results. To illustrate and exemplify the use of the framework, it is applied to a real‐world case of end user preferences of mobile service platforms. We make use of two methods that are suitable for such a setting: analytic hierarchy process and conjoint analysis. Albeit with considerable discrepancies, the results show that both methods provide insightful information on the principle. Nonetheless, to a large degree, these methods perform differently in the case of non‐complex tasks and unknowledgeable respondents, which the process view aids in evaluating and understanding. Copyright © 2015 John Wiley & Sons, Ltd.

AbstractThis paper investigates leading indicators of systemic banking crises in a panel of 11 EU countries, with a particular focus on Finland. We use quarterly data from 1980Q1 to 2013Q2, in order to create a large number of macro‐financial indicators, as well as their various transformations. We make use of univariate signal extraction and multivariate logit analysis to assess what factors lead the occurrence of a crisis and with what horizon the indicators lead a crisis. We find that loans‐to‐deposits and house price growth are the best leading indicators. Growth rates and trend deviations of loan stock variables also yield useful signals of impending crises. While the optimal lead horizon is three years, indicators generally perform well with lead times ranging from one to four years. We also tap into unique long time‐series of the Finnish economy to perform historical explorations into macro‐financial vulnerabilities.