Topic: Contributed on Early warning system and systemic risk indicators I Title: Assessing capital-based macroprudential policy using an integrated early warning GVAR model Authors:  Markus Behn - European Central Bank (Germany) [presenting]
Marco Gross - European Central Bank (Germany)
Tuomas Peltonen - European Systemic Risk Board (Germany)
Abstract: We develop an integrated early warning global vector autoregressive (EW-GVAR) model to quantify the cost and benefits of capital-based macroprudential policy measures in a forward-looking manner. The model contains a logistic component to predict the probability of banking sector crises and a GVAR component to capture the dynamics of credit and other macro-financial variables in response to capital ratio shocks, thus endogenising the predictor variables used in the logistic early warning model. Our setup helps uncovering the transmission channels of capital-based measures and also allows considering cross-country spillover effects when assessing the net benefits of macroprudential measures. Our model may be used to achieve a more precise calibration of capital-based measures, thus helping to contain systemic risk while at the same time accounting for potential costs of macroprudential policy.