In the previous sections, we simulated the dynamics of the model under a productivity and a monetary policy shocks, assuming a constant loan-to-value ratio (i.e. in our model
m represents the loan-to-value ratio and is a parameter equal to 0.35). Since we are
ultimately interested in understanding the eectiveness of time-varying LTV ratios as a macroprudential tool (which are still to be introduced in the model), in this section we seek to get some insights regarding the monetary transmission mechanism in the case of a less stringent regulatory requirement for this ratio.
As aforementioned, we introduce a collateral constraint, in which the parameter m rep-
resents a loan-to-value ratio. This ratio can be thought of as a legal or regulatory constraint on banks. Since we will introduce time-varying LTV ratios in a later stage of this project, this exercise gives us a avour of how it can impact on the monetary shock propagation. With this purpose, we depart from our baseline calibration and we re-run the simulation procedure assuming the same parameters' values, except for m, which is
Recall that the collateral constraint is given by
Rl,tLt≤mEt[Πt+1Qt+1(1−δ)Kt] (5.77)
Therefore, the LTV orm is then determined by the total amount of lending divided by
the expected value of the collateral at time t:
m= Rl,tLt
Et[Πt+1Qt+1(1−δ)Kt]
(5.78) By assuming a low LTV ratio we thereby impose a tighter collateral constraint on the entrepreneurs' side of the model. It means that entrepreneurs can borrow less given a xed expected amount of physical capital. We consider two regimes for the LTV ratio: a stricter regime (Regime 1), in which we assume a low value of 0.35 (our baseline scenario) and an alternative and more exible regime (Regime 2), in which we assume a high value of 0.89, as in Iacoviello (2005). The comparison of the dynamics of the model after a monetary policy tightening under very distinct LTV ratios is presented in Figure 5.8:
Figure 5.8: Monetary Policy Shock under a low and a high LTV ratio.
A positive monetary policy shock in the context of a tighter (low) LTV ratio (Regime 1) causes a smaller fall in output, driven by a less drastic fall in entrepreneurs' consump- tion. In Regime 2, in turn, the transmission mechanism of a monetary policy shock is
considerably amplied when a less strict loan-to-value ratio is required. Results suggest that, ceteris paribus, the sensitivity of borrowing to changes in the value of the collat- eral increases when the collateral constraint is relaxed. Calza et al. (2013) have similar ndings.
Therefore, the propagation dynamics of monetary policy under dierent LTV ratios suggest that a tighter LTV ratio dampens the credit cycle and decreases volatility in the economy, outcomes that are in line with the macroprudential policy ultimate goals of nancial and macroeconomic stability. In terms of monetary policy implications, the amplication eects associated to less stringent regulatory requirements must be taken into account by monetary policymakers when assessing the implications of monetary policy changes.
In the context of a monetary union such as the euro area, this result is even more important. While the monetary policy is common to all the Member States that belong to the euro area, some macroprudential instruments are of the exclusive responsibility of the national macroprudential authorities. This is precisely the case of the loan-to- value ratios and other instruments that aim at mitigating the systemic risk that may arise from asset price bubbles (such as loan-to-income and debt-service-to-income ratios). Under this peculiar institutional and regulatory set-up, it is possible to observe divergent national macroprudential policies targeting the real estate sector (more or less strict LTV ratios), which may hamper the eectiveness of monetary policymaker eorts to stabilize prices within the euro area.
5.5 Conclusions
The introduction of a macroprudential oversight of the nancial system raises very in- teresting questions to researchers and economic policy makers. The institutional and regulatory setup in the euro area are particularly challenging, since it combines central- ized monetary and macroprudential policy powers at the ECB, but, at the same time, discretion is allowed to national supervisory authorities in certain domains of macropru- dential policy, such as in counterveiling real estate bubbles. Given that macroprudential tools available to the ECB and those available to national authorities are imperfect substitutes, how should the ECB as a monetary authority respond in the case national authorities refrain from leaning against the bubble, e.g. because they do not fully in- ternalize the associated nancial stability risks, which may partly spill over to other
countries? And how should the ECB as a macroprudential authority react, acknowledg- ing that its incomplete macroprudential policy toolkit may be not as eective as the one under the national authorities guard?
To the extent such risks complicate the ECB's task to maintain price stability, there may be monetary policy rationale to respond to them. But, in this simplied example, it would have to choose between policy-controlled interest rates or counter-cyclical cap- ital buers, both of which could only partly mitigate the risks. The question is which tool would be best suited, in this second-best scenario, to counteract the price stability implications of the bubble.
The DSGE framework with a banking sector constrained by two sources of nancial fric- tions was developed in this chapter as a rst step to answer some of the current concerns of euro area policy makers. Three main conclusions stand out from our simulations. First, when merging two sources of credit frictions in an otherwise standard New Key- nesian framework, the collateral constraint type of credit friction is dominant over the incentive constraint proposed by Gertler and Karadi (2011). Against this background, the net worth channel of the banking sector from the Gertler and Karadi (2011) model is not so relevant and, as a consequence, the model's large eect on the economy also vanishes under a technology and monetary type of shocks. This is a robust property of our framework, since it holds for dierent calibration scenarios and alternative monetary policy rules.
Second, the inclusion of a collateral constraint, that can be seen as a prudent bank behaviour, enhances banks' resilience to shocks. This ability is improved when a more stringent LTV ratio is considered. These outcomes oer some insight in terms of the ben- ets of introducing time-varying loan-to-value ratios as a macroprudential tool. Finally, less stricter regulatory requirements for the loan-to-value ratio amplify the propagation mechanism of monetary policy shocks.
As previously stated, the embeddedness in this two nancial frictions model of macropru- dential tools, such as countercyclical capital requirements and time-varying loan-to-value ratios, will be work for future research. Once this task is completed, we will be focusing our analysis on the assessment of how eective macroprudential policy is in counteracting the eects of shocks in the business cycle, assuming a perfect control of both instruments and considering two scenarios: one including a monetary policy response and the other abstracting from monetary policy.