Matriz FODA

The central bank sets the interest rate according to the Taylor rule that reacts gradually to output and inflation deviations from the steady state. Steady state inflation is zero,π = 1. ωπ and

ωy measure the interest rate response to inflation and output, respectively.ρris the degree of interest rate smoothing and the

monetary policy shockεv,tis i.i.d.N(0, σ2εv,t). Rt =R1−ρrR ρr t−1 πt π ωπ _yt y !ωy!1−ρr εv,t (3.21)

In line with the recommendations of the Basel Committee on Banking Supervision for the countercyclical risk-based BC ra- tio, the rule on the BC ratio (3.22) reacts to changes in the credit-to-output ratio, et =

Bt Pt

yt , from its steady state, e = B y.

The indicator captures the interaction of loan supply and loan demand as the factor is influenced by the co-movement of credit and output. Since positive deviations represent a boom phase and negative deviation a bust phase, the reaction parameterχυ

is positive for the countercyclical adjustment of the BC ratio,

χυ > 0. The Basel Committee on Banking Supervision (2010)

proposes a prompt release of changes in response to financial stress in the economy, which is why I assume no rigid adjust- ment of the rule.

υt =υ

_et e

χυ

(3.22) The countercyclical leverage ratio (3.23) changes the credit limit of borrowers in response to deviations of the real credit aggre- gate, bt = Bt_Pt, from its steady state, b = B_P. Several studies

identify the credit aggregate as an efficient indicator of credit market imbalance, e.g., Lambertini et al. (2013).21 Thus, the

21_{Several studies recommend a prompt adjustment of the ratio to the eco-}

countercyclical rule withχl < 0 implies a tight credit limit in

times of credit growth and relaxed credit conditions with de- clining lending. lt =l bt b !χl (3.23)

3.3.5 Model closing equations

In a symmetric equilibrium, the goods market is cleared ac- cording to: yt =cb,t+cs,t− φP 2 _πt π −1 2 yt− φWS 2 K_tb Bt −υ !2 K_tb −φs 2 R_ts R_ts₋₁ −1 !2 R_tsD_ts− φb 2        Rb t Rb_t−1 −1        2 Rb_tBb_t +δbK B t−1 Pt . (3.24) The housing market (3.25) clears when housing demand is equal to the fixed supply of one.

1=hb,t+hs,t (3.25)

Moreover, labor markets clear. The following analysis of the non-linear system is conducted using real variables denoted by small letters.22

22_{All first order conditions, model closing equations and laws of motion are}

3.4 Calibration

The calibrated model primarily matches Eurozone data. Cali- bration values are summarized in table 3.1. Where it applies, parameters are presented as quarterly numbers. The borrow- ers’ discount factor of 0.975 assures loan demand and a binding borrowing constraint for small deviations from the steady state. The savers’ discount factor withβs = 0.996 implies a saving rate Rs_t of 1.2 percent per annum (p.a.), while with a steady state interest rate elasticity for deposits ofǫs = −150, the pol- icy rate is four percent p.a.. To realize a loan rate of around six percent p.a., the steady state interest rate elasticity of loan demandǫb must be 200. The steady state bank leverage ratio is four percent, which is a little higher than the Basel III reg- ulation for banks’ leverage ratio. By assuming a buffer on the regulatory ratio, the approach follows Gerali et al. (2010).23 To model an imperfect pass-through to loan interest rates, the loan rate adjustment cost parameterφbis set to 100. I pick a deposit

rate adjustment cost parameterφsof 35 in line with Gerali et al.

(2010).24 Given the retail interest rates, the calibration of the steady state leverage ratio implies a BC depreciation rateδBof

one. Full depreciation of BC from one period to the next allows

23_{When examining the risk-weights BC ratio, Gerali et al. (2010) assume a}

ratio of nine percent instead of the regulatory eight percent risk-weighted BC.

24_{Gerali et al. (2010) base their adjustment costs on net rates, which explains}

to capture the extreme BC erosion during the last financial cri- sis in the model.25 Based on Gerali et al. (2010), the banks’ leverage deviation costs are adjusted for gross rates and is set to 100. The fractionτof total bank profits constructs the bank’s capital position, which I set to 77 percent as in Roger and Vlˇcek (2011). Vice versa the fraction (1−τ), so 23 percent of profits are disbursed as dividends to savers. As the ECB reports an average housing wealth to gross domestic product ratio of 313 percent (ECB, 2009b, p.20) and Musso et al. (2011) records a ratio of 240 percent for around the same time period from 2000 to 2006, I target a implied steady state housing wealth to annual gross domestic product ratio of 290 percent by set- ting the weight of housing in the households’ utility function to

jh=0.06. Similar to Rubio and Carrasco-Gallego (2015a), the parameter associated with the Frisch elasticity of labor is set to 2. The national average LTV ratios of borrowers within the EU vary from above 100 to 60 percent (Banca D’Italia, 2013). By setting the LTV ratio to 90 percent, the mortgage debt to annual gross domestic product ratio in steady state is 23 per- cent consistent with the estimate of 22.6 percent for outstand- ing housing loans to GDP in 2007 (ECB, 2009b, p.21). The price elasticity of demandǫPof six affects a 20 percent markup on prices in steady state. The price adjustment cost parame- terφPis calibrated to 25 which implies that firms change their

25_{This assumption regarding BC depreciation reinforces the financial multi-}

prices every 8 months in line with empirical studies. Following the estimate of Rubio and Carrasco-Gallego (2015a) forα, the parameter governing the labor income share for savers is set to 0.64.

The Taylor rule responds to inflation deviation with an intensity ofωπ =2 and to output deviations withωy =0.01 (Gerali et al.,

2010). The interest rate smoothing parameter is 0.8 as in Rubio and Carrasco-Gallego (2015a).

The standard deviation of the technology shock is set to 0.02 in order to affect a 1.5 percent change of output. The persis- tence of the technology shock is 0.9 in line with the estimate of Gerali et al. (2010). The financial shock is a multi-shock that pushes up the costs of loans or, to put it differently, reduces the credit availability to the real sector, as applied in Angelini et al. (2012). Through the implied correlation of 0.7, the BC depreciation shock entails a shock on the markup and mark- down of the retail rates. I justify this approach by the fact that the macroprudential authority is confronted with a set of shocks that are hard to disentangle. The BC depreciation shock with a standard deviation of 0.01 is more pronounced than the shock to the bank interest rates with a standard deviation of 0.006. In line with the estimates of Gerali et al. (2010), the persistence is

ρskb = 0.81 for the BC depreciation shock,ρmks = 0.86 for the

markdown, andρmkb =0.78 for the markup shock, respectively. The shock on BC produces an eight percent reduction of BC,

followed by a 12 percent decline in borrowing. The shock pro- vokes a drop in output of two percent.26 The financial shock mimics quite well the severe developments after the outbreak of the crisis in 2008/09.

3.5 The implications of countercyclical