Impact of the Credit Crunch on the Polish Economy · Credit crunch increase in lending restrictions increase in spreads between the intebank rates and the credit rates. decline in

Motivation Model Calibration Preliminary Results Summary

Impact of the Credit Crunch on the PolishEconomy

(preliminary and incomplete)

Micha l Brzoza-Brzezina and Krzysztof Makarski

Economic Institute NBP and Warsaw School of Economics

June 2009

M. Brzoza-Brzezina and K. Makarski Credit Crunch


Plan of the Presentation

1 Motivation

2 Model

3 Calibration

4 Preliminary Results

5 Summary




1 Motivation

2 Model

3 Calibration


5 Summary



Main recent shocks in Poland

Credit crunch

increase in lending restrictionsincrease in spreads between the intebank rates and the creditrates.decline in loans to households and firms

Decline in external demand for Polish goods and services (anddecline in export)

Depreciation of the Polish zloty.

Capital outflow?



Main recent shocks in PolandLending restrictions in Poland. (Source: NBP)

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

2004 2005 2006 2007 2008 2009

LTV_MORTGAGE LTV_ENTERPRISE




Credit crunch




Capital outflow?



Main recent shocks in PolandSpreads on loans to households in Poland. (Source: NBP)

-.05

-.04

-.03

-.02

-.01

.00

.01

.02

.03

.04

1998 2000 2002 2004 2006 2008

SPREAD_F SPREAD_H




Credit crunch




Capital outflow?



Main recent shocks in PolandLoans to households in Poland. (Source: NBP)

-.4

-.3

-.2

-.1

.0

.1

.2

.3

.4

1998 2000 2002 2004 2006 2008

LOAN_H_HP LOAN_F_HP




Credit crunch




Capital outflow?



Main recent shocks in PolandExport in Poland. (Source: Central Statistical Office)




Credit crunch




Capital outflow?



Main recent shocks in PolandReal exchange rate in Poland. (Source: NBP)




Credit crunch




Capital outflow?



Main recent shocks in PolandCapital inflow. (Source: NBP)



Response of GDP (Source: Central Statistical Office)



Question

What is the role of financial frictions in this process?

How much of GDP decline is generated by financial frictions?



Methodology

Dynamic Stochastic General Equilibrium (DSGE) of Polisheconomy.

The advantages of DSGE models

They take into account the influence of future on today’sdecisions in a coherent way (rational expectations)MicrofoundationsCalibration/Estimation of the so called deep parameters(describing e.g. preferences, technologies) - gives rise to thepossibility of studies on changes in policies (this approach isimmune to the Lucas critique)




1 Motivation

2 Model

3 Calibration


5 Summary



Key Features

New Keynesian model of business cycle

Non-neutrality of monetary policy due to:

Nominal rigidities - prices and wages are set according to aCalvo scheme (Calvo, 1983)

Monetary Policy

Taylor rule (Taylor, 1993)

Financial frictions - we extend Iacoviello (2005):

stochastic shocks to credit constraints and spreads,small open economy.



Basic structure

Standard new Keynesian model of business cycle fluctuations.

Households

Monetary and fiscal authorities

Three stages of production: final good producers,intermediate good producers, and wholesale good producers(entrepreneurs)

Housing and capital producers.

Prices of intermediate goods and wages are sticky.

Banking sector, nominal rigidities, spreads plus creditconstraints.

Perfect competition in the other markets



Households

There are two types of households: patient, P, and impatient,I . The type i ∈ {P, I} maximizes utility

E0 ∑t(βi )tu(ct , χt , nt , εt), subject to

the budget constraint and the borrowing constraint

RHL,tL

it ≤ mH

t Et

[Pχ,t+1 (1− δχ) χi

t

]where mF

t ∼ AR(1). Thus consumers need housing ascollateral to get a loan.

In equilibrium patient HHs save and impatient HHs borrow.



Wholesale good producers (entrepreneurs)

Do not work, run firms. Sell their product in a competitivemarket.

Are impatient (βE = βI ).

Own capital use it as collateral for loans.

Maximize utility

E0 ∑t(βE )tu(ct , εt), subject to

the flow of funds, the production function and the borrowingconstraint

RFL,tL

Ft ≤ mF

t Et [Pk,t+1 (1− δk) kt ]

where mFt ∼ AR(1). Thus producers need capital as collateral

to get a loan.



Other producers

Other producers are standard.

Intermediate good producers operate in monopolisticenvironment. Have sticky prices - Calvo pricing. Do not owncapital.

Final good producers put together domestic and foreignintermediate goods (imperfect substitutability) and sell finalgoods in a competitive market. Do not own capital.

Housing and capital good producers are standard (cost ofinstallation).



BankingDeposits

Policy rate - the interbank rate Rt .

Banks collect deposits from patient households and depositthem in the interbank market. zD,t ∼ AR(1) affects thespread between the interbank rate Rt and the HHs depositrate RH

D,t (follows from DIB,t = zD,tDt).

There are nominal rigidities (Calvo) that slow down theadjustment of the interest rates. The flexible deposit rate is(in log deviations from the steady state) RH

D,t = zD,t + Rt .With nominal rigidities this relationship becomes morecomplex.



BankingLoans

Furthermore, banks take loans in the interbank market andgrant loans to impatient HHs and firms. zL,t ∼ AR(1) affectsthe spread between the interbank rate Rt and the lending rateRL,t (follows from Lt = zL,tLIB,t).

There are nominal rigidities (Calvo) that slow down theadjustment of the interest rates. The flexible HHs loan rate is(in log deviations from the steady state) RH

L,t = Rt − zHL,t and

for firms RFL,t = Rt − zF

L,t . With nominal rigidities thisrelationship becomes more complex.

Borrowing constraints tied to housing (HHs) and capital(firms).

Banks have also access to the international nominal interestrate adjusted for risk premium.



Monetary and fiscal authority

Central bank - the Taylor rule; log-linear version of the form:

Rt = γR Rt−1 + (1− γR)[γππt + γGDPˆGDPt ] + ϕt

The government budget, very simplified (to keep Ricardianequivalence only patient HHs are taxed)

Gt = TPt

where

Gt+1 =(

1− ρg

)µg + ρgGt + εg ,t+1, εg ,t ∼ N [0, σg ]



Definition of Decentralized Equilibrium

Definition

An equilibrium is a set of allocations and prices, that:

solves the decision problems of all agents populating theeconomy

satisfies the government budget constraints

satisfies the Taylor rule

clears all markets




1 Motivation

2 Model

3 Calibration


5 Summary



Solution

The model was solved with 1-st order perturbation(linearization)

The model parameters were crudely calibrated.

In future we plan Bayesian estimation and/or propercalibration.



Calibrated model parameters

A group of parameters are taken from the literature(parameters that affect business cycle behavior).

A group of parameters is obtained from the data (parametersthat affect the steady state).

Crude calibration of the shocks affecting financial markets

the initial shocks to spreads were calibrated to match theobserved change to spreads.the initial shocks to LTVs were calibrated to match (givenprevious calibration of the shocks to spreads) the observeddecline in loans.persistence was not calibrated, it was set at reasonable values.



IRF to a monetary policy shock

10 20 30 40−3

−2

−1

0

1x 10

−3 gdp

10 20 30 40−4

−2

0

2x 10

−3 c

10 20 30 40−0.01

−0.005

0i

10 20 30 40−10

−5

0

5x 10

−4 pi

10 20 30 40−8

−6

−4

−2

0x 10

−3 l_f

10 20 30 40−0.03

−0.02

−0.01

0

0.01l_h

10 20 30 40−10

−5

0

5x 10

−3 spread_f_l

10 20 30 40−10

−5

0

5x 10

−3 spread_h_l

10 20 30 40−5

0

5

10x 10

−3 R



IRF to a 10% households LTV shock

10 20 30 40−5

0

5

10x 10

−3 gdp

10 20 30 40−0.01

0

0.01

0.02c

10 20 30 40−5

0

5

10

15x 10

−3 i

10 20 30 40−1

0

1

2

3x 10

−3 pi

10 20 30 40−4

−2

0

2

4x 10

−3 l_f

10 20 30 40−0.05

0

0.05

0.1

0.15l_h

10 20 30 40−6

−4

−2

0

2x 10

−4 spread_f_l

10 20 30 40−6

−4

−2

0

2x 10

−4 spread_h_l

10 20 30 40−5

0

5

10x 10

−3 R



IRF to a 10% firms LTV shock

10 20 30 40−1

0

1

2

3x 10

−3 gdp

10 20 30 40−1

0

1

2

3x 10

−3 c

10 20 30 40−5

0

5

10

15x 10

−3 i

10 20 30 40−2

0

2

4x 10

−4 pi

10 20 30 40−0.05

0

0.05

0.1l_f

10 20 30 40−2

0

2

4

6x 10

−3 l_h

10 20 30 40−4

−2

0

2x 10

−4 spread_f_l

10 20 30 40−4

−2

0

2x 10

−4 spread_h_l

10 20 30 400

1

2

3

4x 10

−4 R



IRF to a spread on loans to HHs shock

10 20 30 40−5

0

5

10x 10

−4 gdp

10 20 30 40−1

0

1

2x 10

−3 c

10 20 30 40−1

0

1

2x 10

−3 i

10 20 30 40−2

0

2

4x 10

−4 pi

10 20 30 40−4

−2

0

2x 10

−4 l_f

10 20 30 40−5

0

5

10

15x 10

−3 l_h

10 20 30 40−1

−0.5

0

0.5

1x 10

−4 spread_f_l

10 20 30 40−3

−2

−1

0

1x 10

−3 spread_h_l

10 20 30 40−5

0

5

10x 10

−4 R



IRF to a spread on loans to firms shock

10 20 30 40−5

0

5

10

15x 10

−5 gdp

10 20 30 40−6

−4

−2

0

2x 10

−4 c

10 20 30 400

1

2

3x 10

−3 i

10 20 30 40−2

−1

0

1x 10

−5 pi

10 20 30 400

1

2

3

4x 10

−3 l_f

10 20 30 40−2

−1

0

1

2x 10

−4 l_h

10 20 30 40−4

−3

−2

−1

0x 10

−3 spread_f_l

10 20 30 40−10

−5

0

5x 10

−6 spread_h_l

10 20 30 40−2

0

2

4x 10

−5 R




1 Motivation

2 Model

3 Calibration


5 Summary



Simulation description

The goal of the simulation is to find the impact of the creditcrunch alone.

Shocks to spreads set to match values to match observedchange in spreads.

Shocks to LTVs set to match (given the previously calibratedinitial shocks to spreads) observed decline in loans.

Persistence set at reasonable values.

Two questions:

do we need shocks to LTVs?does the credit crunch alone have an important effect?

Given that the crudeness of the calibration results should beonly treated as a documentation of the model’s possibilities.



Spreads in the model

0 5 10 15 20 25 30 35 40-5

0

5

10

15

20x 10

-3

spread_h_lspread_f_l



Spreads as a source of the credit crunch in the model

0 5 10 15 20 25 30 35 40-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

l_hl_f



Spreads and LTVs as a source of the credit crunch in themodel

0 5 10 15 20 25 30 35 40-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

l_hl_f



Credit crunch and GDP in the model

0 5 10 15 20 25 30 35 40-20

-15

-10

-5

0

5x 10

-3

gdp




1 Motivation

2 Model

3 Calibration


5 Summary



Summary and work for the nearest future

Model seems to be very promising in terms of its ability toreplicate the credit crunch impact.

A proper calibration or Bayesian estimation needs to be done

It should result in a proper decomposition of shocks.

Financial frictions seem to have an important effect on theeconomy.

Spreads alone may not be enough to quantitatively replicatethe observed behavior of financial variables thus also shocks toLTVs are needed.

Possibly policy analysis.


Documents

Impact of the Credit Crunch on the Polish Economy · Credit crunch increase in lending restrictions increase in spreads between the intebank rates and the credit rates. decline in