Monetary and macroprudential policies in an estimated model with financial intermediation

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractWe estimate the Smets and Wouters (2007) model augmented with the Gertler and Karadi (2011) financial intermediation sector on US data by using real and financial observables. Given the framework of the estimated model, we address the question whether and how standard monetary policy should interact with macroprudential policy in order to safeguard real and financial stability. For this purpose, monetary policy is described by a flexible inflation targeting regime using the interest rate as instrument, while the macroprudential regulator adopts a tax/subsidy on bank capital in a countercyclical manner in order to stabilize nominal credit growth and the output gap. We look at the gains from coordination between the central bank and the macroprudential regulator under alternative assumptions regarding the degree of importance assigned to output gap fluctuations in the macroprudential mandate. The results suggest that there can be considerable gains from coordination if the macroprudential regulator has been assigned a sufficiently high weight on output gap stabilization, i.e. the common objective with monetary policy. If, on the other hand, the main focus of the macroprudential mandate is on credit growth, the macroprudential policy maker can reach better outcomes, while the central bank does worse, in the absence of coordination. Therefore, whether and to which extent monetary policy gains from coordination with the macroprudential regulator depends on the relative weight assigned to output fluctuations in the macroprudential mandate. Our counterfactual analysis further confirms the effectiveness of the countercyclical macroprudential tax/subsidy in containing the amplification effects triggered by a financial shock, and suggests that having a macroprudential regulatory tool at work could have successfully avoided the massive drop in credit such as the one observed at the onset of the Great Recession.JEL classification: E42, E44, E52, E58, E61

Leaning Against Windy Bank Lending

“…Based on Compustat data, Gilchrist and Zakrajšek (2012) use prices of individual corporate bonds traded in the secondary market. As noted by Gelain and Ilbas (2017), this series of spread is closely related to measures of financial intermediary health, which makes it a highly informative financial indicator. magnitude and behavior closest to the BP-FFR, given that both rates are used as observables in the estimation, and it represents the closest data counterpart of the theoretical definition of the spread in the model.…”

Imperfect information about financial frictions and consequences for the business cycle

“…Since for a simulation of the model variable outcomes become important, we need to calibrate the shock processes such that we are able to match the moments of real data. For this reason, we base our calibration for the four shocks monetary policy shock, total factor productivity, capital quality shock, and incentive shock on estimates from Gelain and Ilbas (2014), who estimate a model with a financial sector identical to Gertler and Karadi (2011) with US data. Based upon these values, we adjust the autoregressive parameters and the standard deviation of the shocks (Table 1) to match the volatility of output growth during the period 1984-2014.…”

Dealing with financial instability under a DSGE modeling approach with banking intermediation: A predictability analysis versus TVP-VARs

“…where = 100( 1) is the common quarterly trend growth rate of GDP, consumption, investment and wages; N = 100( N 1) is the quarterly trend growth rate of net worth of …nancial intermediaries, as in Gelain and Ilbas (2014); h is the steady-state hours of work; is the steady-state quarterly in ‡ation rate; and r n is the steady-state quarterly nominal interest rate. A hat over a variable represents log-deviation from steady state.…”