Monetary Transmission Mechanism in Central and Eastern Europe: Gliding on a Wind of Change

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www.oenb.at [email protected]

Monetary Transmission Mechanism in Central and Eastern Europe

Balázs Égert

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Oest er r eichische Nat ional bank

Introduction• The presentation is based on the paper: Coricelli, F., B. Égert and R. MacDonald, 2006, Monetary

transmission in Central and Eastern Europe: Gliding on a Wind of Change, BOFIT DiscussionPaper No. 8.

• Objectives– Description of the individual MTM channels

– Establishing the connection between the separate channels

– Providing a systematic and critical survey of the empirical literature for the CEECs

– Trying to disentangle the relative importance of the different channels

– Speculate on future developments

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Channels• Interest rate channel

– first stage: interest rate pass-through– second stage: impact of changes on the real economy

• Exchange rate channel– MP and the exchange rate (UIP, VAR, FX interventions)– FX pass-through to prices– FX and the real economy; trade and investment

• Asset price channel• Credit channel

– bank lending channel– broad lending channel– bank capital$ channel

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LTmarket&banking(depositandloan)nominalinterestrate

INTEREST CHANNEL

GLOBAL

DEMAND

OUTPUT

INFLATIONASSET PRICE CHANNEL

Portfolio adjustment: desired liquiditylevel => bonds <-> equity

Equity andproperty prices

Wealth effectTobin qLiquidity effect

CREDIT CHANNELBalancesheetchannel

Bank lendingchannel

Capacitytoborrow

FX pass-through; Cost channel: imported intermediate and final goodsExpectation channel

EXPECTATIONS CHANNEL

Real exchange rate

Balance sheet (foreign currency denominated)

NetExports

I PN RV IE VS AT TM EEN CT O N S.

Competitiveness

Marshall Lerner condition

Long-term realinterest rate

MONETARY POLICY RULE

Trade balance

UIP

Bank capitalchannel

Income effect

Substitution effect

Cost of capital

Interestratepass-through

Structure ofbanking sector

Nominalexchange

rate

FX

Interventions

Short-termnominalinterestrate

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Interest Rate Pass-Through• Factors leading to incomplete pass-through

• Interest elasticity of demand for deposits and loans is less than 1.– Imperfect substitution between d/l and financial assets of the same maturity (money market, T-

bills)– Imperfect substituton between d/l and other external financing (equity, bond)– Low competition betweeen banks and between banks and other fi. Intermediaries– Switching costs

• Interest rate cycles: increase (decrease) in ir => loan (deposit) rates adjust faster• Adjustment/menu costs (when changing interest rates)• Maturity mismatch: the higher the share of long-term non-market priced deposit =>

lower PT• Small, less liquid and less capitalised banks react faster• Relationship banking => interest rate smoothing• Macroeconomic conditions

– GDP growth– Inflation, level and variability

• Factors leading to overshooting: PT>1– Loan rates: higher rates to counteract higher risk stemming from asymmetric

information rather than a reduction of the supply of loans.

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IRPT

• Problems (term structure)

Figure 1. The transmission between interest rates

first stage

second stagemonetary policy approach cost of funds approach

Monetary policy rate ( MPi ) Longer-term market rates ( Mi )

Retail rates ( Bi )

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Interest rate pass-through• key findings for the euro area

• Bank retail interest rates adjust sluggishly in the short run, especially overnight and short-term deposit rates and rates on consumer loans. At the same time, there is some evidence regarding a possible complete pass-through in the long-run, in particular for short-term corporate loan rates and perhaps also for housing/mortgage rates. It seems that long-run pass-through is incomplete for (short-term) deposit rates and consumer loans.

• However, large amount of heterogeneity exists both for short-term adjustments and for long-run pass-through across the retail interest rate landscape.

• Ample evidence is found in favour of asymmetric adjustment in the pass-through process. Nevertheless, no systematic pattern emerges.

• Although economies of the euro exhibit substantial heterogeneity with regard to the interest rate pass-through, it appears that it became faster and more homogeneous after the introduction of the euro. DeBondt (2002) suggests thisto be due to increased competition, lower switching costs and costs associatedwith asymmetric information and a rise in the interest rate elasticity of demandfor banking products.

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Oest er r eichische Nat ional bankInterest rate pass-through - CEECTable 1. Long-Run Interest Rate Pass-Through Estimates for the CEECs

Author Time LR PT Author Time LR PTLoans LT

BR => MMR CZ ALL, 4Y CER 1997:2- 0.64CZ CER (2004) 1997:2-2002:12 0.89 c CZ ALL T (2004) 1995:1-2004:2 0.65HU CER (2004) 1994/1997- 1.02 CZ ALL, NEW T (2004) 1995:1-2004:2 0.83PL CER (2004) 1994:1-2002:12 1.00 c HU ALL Árvai 1995:12- 1.04LT N (2005) 1999:1-2004:11 1.03 c HU ALL T (2004) 1995:1-2004:2 0.67

1.01 HU COR, >1Y CER 1994/1997- 1.02 cDeposits ST HU COR SK (2004) 1995:1 - 1.11

CZ ALL CER (2004) 1997:2-2002:12 0.75-0.84 HU COR HKN. 2001:1-2004:1 0.98 cCZ ALL T (2004) 1995:1-2004:2 0.79 HU COR, panel HKN. 2001:1-2004:1 0.95CZ HH SK (2004) 1993:1-2003:12 0.07 PL COR, 1Y CER 1994:1- 1.02 cHU ALL T (2004) 1995:1-2004:2 0.82 PL COR, 1Y WP (2002) 1995-2002 1.03 cHU HH CER (2004) 1994/1997- 0.49-0.89 PL ALL T (2004) 1995:1-2004:2 0.85HU HH, 1Y CER (2004) 1994/1997- 0.92 PL COR SK (2004) 1996:12- 0.99HU HH, 1Y SK (2004) 1995:1 - 2003:12 0.36-0.82 EE COR SK (2004) 1997:4- 0.58PL HH CER (2004) 1994:1-2002:12 0.94 c LV COR SK (2004) 1999:1- 1PL HH, 1M WP (2002) 1995-2002 0.8 LT COR N (2005) 1999:1- 0.88 cPL HH, 3M,6M,12M WP (2002) 1995-2002 0.91 c LT ALL, AV N (2005) 1999:1- 0.87PL ALL T (2004) 1995:1-2004:2 0.98 LT COR SK (2004) 1999:1- 1PL HH, 1M-12M SK (2004) 1996:12-2003:12 0.82-0.91 ROM ALL T (2004) 1995:1-2004:2 0.73PL COR, 1M-12M SK (2004) 1996:12-2003:12 0.82-0.93 ROM ALL, NEW T (2004) 1995:1-2004:2 0.62EE ALL, 3M,6M,12M SK (2004) 1994:1-2003:12 0.57-0.72 SK ALL T (2004) 1995:1-2004:2 0.79LV HH, 1M-12M SK (2004) 1999:1-2003:12 0.32-0.47 SK ALL, NEW T (2004) 1995:1-2004:2 0.93LV COR, 1M-12M SK (2004) 1999:1-2003:12 0.34-0.78 SI ALL T (2004) 1995:1-2004:2 1.85LT HH N (2005) 1999:1-2004:11 0.61 0.92LT HH, 1M-12M SK (2004) 1999:1-2003:12 0.70-0.75 Loans ConsumerLT ALL, 1M-12M SK (2004) 1992:1-2003:12 0.70-0.81 CZ Kot (2004) 1996:1-2004:1 0.42SK ALL T (2004) 1995:1-2004:2 1.26 CZ SK (2004) 1993:1- 0.26SK ALL, 1M-12M SK (2004) 1995:1-2003:12 0.28-0.71 HU Kot (2004) 1998:1-2004:4 0.36SI ALL T (2004) 1995:1-2004:2 1.41 HU SK (2004) 1995:1 - 0.51

0.78 HU HKN. 2001:1-2004:1 0.81Deposits LT PL Kot (2004) 1997:1-2004:4 0.59

CZ ALL, 4Y CER (2004) 1997:2-2002:12 0.85 PL WP (2002) 1997-2002 0.85CZ ALL T (2004) 1995:1-2004:2 0.49 PL SK (2004) 1996:12- 0.6CZ HH SK (2004) 1993:1-2003:12 0.28-0.62 EE SK (2004) 1997:4- 0.21HU ALL T (2004) 1995:1-2004:2 0.90 LV 6-12M SK (2004) 1999:1- 0.82HU HH, >1Y CER (2004) 1994/1997- 0.91 LV NEW SK (2004) 1999:1- 2.76HU HH, >1Y SK (2004) 1995:1 - 2003:12 0.90 LT 6M SK (2004) 1999:1- 0.82HU HH HKN. (2004) 2001:1-2004:1 0.86 LT 12M SK (2004) 1999:1- 0.77HU COR HKN. (2004) 2001:1-2004:1 0.87 SK SK (2004) 1995:1- 0.02HU COR, panel HKN. (2004) 2001:1-2004:1 0.87 0.54PL HH, >1Y CER (2004) 1994:1-2002:12 0.96 c Mortgage LoansPL ALL T (2004) 1995:1-2004:2 0.91 HU SK (2004) 1995:1 - 0.98PL HH, 2Y SK (2004) 1996:12-2003:12 0.91 EE SK (2004) 1997:4- 0.40PL COR, 2Y SK (2004) 1996:12-2003:12 0.88 LV SK (2004) 1999:1- 1.01PL COR, 3Y SK (2004) 1996:12-2003:12 0.83 LT N (2005) 1999:1- 1.12 cEE HH SK (2004) 1994:1-2003:12 0.6 LT 5Y SK (2004) 1999:1- 1.24EE COR SK (2004) 1994:1-2003:12 0.48 LT >5Y SK (2004) 1999:1- 0.06EE ALL SK (2004) 1994:1-2003:12 0.5 0.78LV HH SK (2004) 1999:1-2003:12 0.48 Goverment securityLV COR SK (2004) 1999:1-2003:13 0.07 CZ 5Y CER 1997:2- 0.77LT HH, 2Y SK (2004) 1999:1-2003:12 0.69 HU 1Y CER 1994/1997- 0.98 cLT HH, >2Y SK (2004) 1999:1-2003:12 0.69 HU 5Y CER 1994/1997- 0.84LT ALL, 2Y SK (2004) 1992:1-2003:12 0.52 PL 1Y CER 1994:1- 0.96 cLT ALL, >2Y SK (2004) 1997:1-2003:12 0.47 PL 5Y CER 1994:1- 0.80 cROM ALL T (2004) 1995:1-2004:2 0.78 0.92SK ALL T (2004) 1995:1-2004:2 1.01SK ALL, 2Y SK (2004) 1995:1-2003:12 0.24SK ALL, 5Y SK (2004) 1995:1-2003:12 0.2SK ALL, >5Y SK (2004) 1995:1-2003:12 0.06SI ALL T (2004) 1995:1-2004:2 1.57

0.69Loans ST

CZ ALL, 1Y CER (2004) 1997:2-2002:12 0.76CZ ALL T (2004) 1995:1-2004:2 0.76CZ ALL, NEW T (2004) 1995:1-2004:2 1.04CZ COR SK (2004) 2001:1-2003:12 0.95HU ALL Árvai (1998) 1995:12-1998:06 0.95HU ALL T (2004) 1995:1-2004:2 1.09HU COR, 1Y CER (2004) 1994/1997- 1.01 cHU COR SK (2004) 1995:1 - 2003:12 1.01EE COR SK (2004) 1997:4-2003:12 0.77LV COR SK (2004) 1999:1-2003:12 1.13LT COR N (2005) 1999:1-2004:11 1.02 cLT COR SK (2004) 1999:1-2003:12 1.13ROM ALL T (2004) 1995:1-2004:2 0.79ROM ALL, NEW T (2004) 1995:1-2004:2 0.25SK ALL T (2004) 1995:1-2004:2 1.62SK ALL, NEW T (2004) 1995:1-2004:2 1.21SK COR SK (2004) 1995:1-2003:12 0.65SI ALL T (2004) 1995:1-2004:2 2.07

1.01Notes:

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Oest er r eichische Nat ional bankInterest rate pass-through - CEEC

RateAverage long-run pass-

throughBase rate => money market rate

1.01

Short-term deposit rate 0.72Long-term deposit ate

0.69

Short-term lending rate

1.01

Long-term lending rate 0.91Consumer lending rate

0.51

Housing / mortgage lending rate

0.73

Goverment security yields

0.92

Long-Run Interest Rate Pass-Through Estimates for CEE

Source: Authors' calculations.

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Oest er r eichische Nat ional bankInterest rate pass-through - CEEC

• 1 same as for the euro area• 2 same as for the euro area

• 3 less evidence in favour of asymmetric adjustmet• 4 increase in the pass-through over time

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Oest er r eichische Nat ional bankDeterminants of IRPT

• Time series: introducing Herfindahl- Hirschman index (HHI)– Poland: higher HHI increases (decreases) PT for deposits (loans)

• Cross-section in two stages– Sandner and Kleimeier (2004);

• CEE8, real GDP and financial depth do not matter• Inflation and its variability matters

+less concentrationless bad loans

more foreign participation increases IRPT– Opiela (1999)

• The same for bank-level pass-through coeffs (state ownership and cap matter)

• Panel setting for bank level data– Chmielewski: bad loans, capital adequacy ratio and profitability matter

Conflicting results:- concentration (decreases PT) foreign ownership (increases PT)- profitability (decreases PT) foreign ownership (increases PT)- capitalisation (decreases PT) foreign ownership (increases PT)

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Second Stage: The Money Channel

• Price stickiness: changes in nominal interest rate => changes inshort-term and long-term real interest rates

– cost of capital => investment

– spending on housing and durable goods: also interest sensitive

• two conflicting effects

– income effect: A rise in the income of holders of interest bearing assets

– substitution effect, i.e. higher interest rates favour savings to consumption

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Credit Channel

– Bank lending channel

• 1. MP <-> banks => decrease in credit supply

• 2. Banks and firms => firms cannot substitute credit with otherexternal financing

• assumptions: • a.) the income elasticities of credit demand and money demand are the

same, and

• b.) the interest elasticity of credit demand equals that of credit supply

• relaxing b) leads to either amplification or attenuation (Kierzenkowski, 2005)

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Credit Channel

– Broad Lending Channel• The imperfect substitution between external and internal financing• the cost of external financing is higher with the external financing

premium => depends on net wealth, serving as collateral for loans and credits. The higher the net wealth of the borrower is, the lower the external risk premium

• MP can influence net wealth, – via the interest rate,– asset price and– exchange rate channels

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Credit channel– Income effect (or cash-flow channel): an increase (decrease) in short term

interest rates increases (decreases) the cost of servicing short-term and floating-rate debt, which reduces (raises) cash-flow and thus net wealth

– Debt channel: an unexpected rise in inflation makes the real costs of servicing the debt lower, the terms of which are determined in nominal terms.

– Asset price channel 1: an increase (decrease) in short term interest rates lowers (increases) the price of equity, bonds and housing, which thus directly influences net wealth.

– Asset price channel 2: Wealth and liquidity effect of households: monetary policy can impact on household’ borrowing capacity as described in the asset price channel

– Exchange rate channel: if asses or credits/loans are denominated in foreign currency, nominal exchange rate developments can increase (decrease) their value in domestic currency, which also exerts an influence on borrowing capacity.

– Second-round effects: If spending of households or firms falls as a consequence of monetary policy action, other firms revenue also falls, leading to a decrease in net wealth as a function of rigidities on the cost side.

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Credit channel– The Bank Capital Channel– The standard credit channel literature is criticised to assume that the

central bank affects loan supply by altering the required reserves => inflation targeting framework (interest rate setting). => inflation targeting central banks may not be able to control required reserves

– loan supply can be strongly affected via changes in bank capitalrequirements if it is costly for banks to raise equity

– But is it really an operational channel for MP???

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Credit channel- Trojan horses– First stage

• Multi-bank holding networks, escape for small banks• An overall well-capitalised banking system may be less conducive for

the bank capital channel.• A high degree of concentration of the banking sector implies the

absence of small banks (this also weakens the interest pass-through!)

• The maturity structure of loans and the trade-off between fixed or variable interest rates

• Relationship lending, loan commitments• The government’s involvement in the banking sector

– Second stage• trade credits• altering capacity utilisation if financial constraints are anticipated in

advance (Wang, 2001)• soft budget constraint

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Credit channel - empirical evidence• Major problem: credit market in equilibrium

– But: credit demand and credit supply regimes

– Hurlin and Kierzenkowski (2004): till 1999 excess credit supply, after 1999, excess credit demand in Poland.

• Implications for monetary policy =>

– Excess credit supply: overliquidity, banks will not change retail interest rates to diminish demand (already unsatisfactory to clear the market) => Attenuation of MP actions

– Excess credit demand: credit rationing, => Amplification of MP actions

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Credit channel - OECDTable 3. Summary of the Empirical Literature on the Credit Channel in Developed Countries

Country Bank Lending Channel (LC)

Broad LC Trade credit

Overall 1st stage 2nd stage Bernanke-Gertler(1995) US, spread data YES ?? Kashyap et al. (1994) US, spread data YES ?? Miron et al (1994) US, spread data NO NO Bernanke-Blinder (1992) US, VAR, loans YES Morgan (1998) US, VAR,

committed loans NO

Gertler-Bernanke (1993) US, VAR NO/YES King (1986) US NO Romer-Romer (1990) US NO Ramey (1993) US NO Escriva-Haldale (1994) Spain HH Dale-Haldale (1995) UK HH Kakes (1998) Netherlands HH?? Kashyap et al. (1993, 1996) US YES Oline-Rudebusch (1996) US NO YES Ludvigson (1998) US, automobile Negligible Kashyap-Stein (1995,2000) US YES Baum et al. (2004) US YES Favero et al. (1999) Europe NO Ehrmann et al. (2001) Europe YES Altunbas et al (2002) Europe BK Pizarro-Barceló (2004 ) Spain YES, BK Gambacrota-Mistrulli (2003)

Italy BK

Yalcin et al. (2004) UK YES YES Chatelain et al. (2001) Europe YES YES Kohler et al (2000) UK YES Nilsen (2002) US YES Mateut et al (2002) UK YES Mateut (20054) US, UK, DE, AT YES Notes: BK denotes the existence of the bank capital channel. HH=loans to households, ? = questionable or weak evidence

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Credit channel - CEECs

Author Country Type of assets Size Liq Cap BadL OwnSchmitz (2003) CEEC5+B3 Total loans X X -- XPruteanu (2004) Czech

RepublicTotal loans – bad

loansX X X X X

Juks(2004) Estonia Bank deposits X -- --H loans X -- --C loans ? ? -- --

Havrylchyk and Jurzyk(2005)

Poland Total loans X --

Wróbel and Pawloska(2002)

Poland Total loans X X -- --

Chmielewski (2005) Poland Total loans XH loansC loans

FX loansPLN loans

Golodniuk (2005) Ukraine Total loans X -- --Consumer loan X -- --

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Exchange rate channel• Monetary Policy Actions and the Exchange Rate

– Interest rate moves, FX interventions, VAR• Exchange Rate and Prices

– FX => import prices => consumer prices and– FX => import prices =>producer prices => consumer prices

– pricing behaviour of firms:• producer currency pricing; PCP: full pass-through, LOOP holds; (adjustment

in output and employment)• local or consumer currency pricing, LCP: zero pass-through; deviation from

LOOP (adjustment in mark-ups)

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Oest er r eichische Nat ional bankDiffering Pass-Through for Imported, Producer and Consumer Prices

• Pass-through for import prices is between 0 and 1• third degree price discrimination eventually preventing a complete pass-

through even for homogenous imported goods.• For price discrimination to apply, it is necessary that

– i.) firms are able to separate different markets from each other,– ii.) firms are capable of preventing the resale of the products and – iii.) they have market power (Goldberg and Knetter, 1997). – Recent example: boat trip Vienna-Bratislava-Vienna

• Additional factors explaining market segmentation are:– (a) transportation costs, – (b) custom duties, – (c) non-tariff barriers,– (d) differences in characteristics of even relatively homogenous products, – (e) home or brand loyalty– (f) presence of multinationals, and – (g) intra-firm trade (Darvas, 2001).

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Oest er r eichische Nat ional bankDiffering Pass-Through for Imported, Producer and Consumer Prices

• Even if pass-through for import prices is complete, the following structure applies

• PT(imports) >PT(producer prices) > PT(consumer prices)

• explanations:– imported final goods: distribution costs

» wholesaling» retailing» (including transportation, marketing and advertisement)» LARGE DEVALUATION (Burnstein et al. 2002,2004) => flight from quality

– imported intermediate goods» final products: combination of imported and domestic goods» PCP for imported goods but LCP for the final product» sticky prices in local currency

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A Slow-Down of the Pass-Through to Prices Over Time?• The Role of the Macroeconomic Environment

• difference between developed and developing countries• decline of pass-through for both groups of countries

• two-stage approach• level of inflation• variability of inflation• FX volatility• openness and country size

• The Composition of Trade and Imports• shift in the composition of imports from raw materials (high pass-through)

towards manufactured goods (low pass-through) => decline in the exchange rate pass-through for imported goods.

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Oest er r eichische Nat ional bankA Slow-Down of the Pass-Through to Prices Over Time?• Evidence Based on Individual Imported Goods

• Frankel et al. (2005)(Marlboro cigarettes, Coca-cola, Cognac, Gilbey’s gin, Time magazine, Kodak colour film, Cointreau liqueur and

Martini&Rossi Vermouth )

– pass-through is incomplete even at the docks

– pass-through is lower for the US than elsewhere => no composition effect

– pass-through to import prices increased over time, while it decreased for retail and the CPI level for developing countries (but not for developed countries)

– important factors influencing the size of the pass-through are • a.) distance (transport costs),

• b.) GDP per capita,

• c.) the level of inflation, and to a lesser extent

• d.) the size of the economy.

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Differing Pass-Through for Imported, Producer and Consumer Prices

• The Role of Expectations• permanent or temporary change

• exchange rate as an anchor for expectations– any change in the exchange rate will be fast incorporated into expectations and

thus into prices (both tradable and non-tradable). In contrast, if the exchange rate is not used as an intermediary target, expectations are not that strongly associated with the exchange rate resulting in a lower pass-through. A floating exchange rate regime will have little influence on non-tradable prices.

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Trade and investment• Marshall-Lerner condition: sum of the price elasticities of export and

import demand is higher than unity• BUT: full pass-through to import prices (in local currency) and zero to export

prices (in foreign currency) => incomplete pass-through => can cause the failure of the ML condition

• Valuation effect: mismatch between the asset and liability side of foreign assets

• Burstein et al. (2004): import content of investment is significantly higher than the import content of consumption. Pass-through to investment prices is potentially higher than that to the price of consumer goods.

• However, pass-through is also incomplete because of the non-tradable component of investment. Contrary to consumer goods, the bulk of the non-tradable component is due to construction services while the share of distribution services is negligible.

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Trade and investment• Campa-Goldberg (1995):

• sectoral investment depends on– the export share and

– the import content of production of the sector.• More specifically, exchange rate depreciation (appreciation) expands

(decreases) investment if the export share is high. A high import content of sectoral production works in the opposite direction.

• High mark-up sectors do not tend to respond to exchange rate movements in investment demand, whereas low mark-up sectors respond stronger to changes in the exchange rate.

• CREDIT CHANNEL: small firms in low-mark-up sectors very vulnerable• NET WEALTH: balance sheet effect could counterbalance competitive

effects

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FX PT– Recursive VAR (based on the distibution chain

• Oil/commodity prices => output gap => FX => IMP => PPI=>CPI

– single equation in first differences

• Short-term pass-through:• Long-run pass-through:

– Relationship to EqRER– Darvas(2001):

ttminad

tEQtt

*ttt )pq()qq(pep εφδχβα +−+−+Δ+Δ+=Δ −− 11 (9)

tEQttt )qq(e εηγ +−+=Δ −− 11 (10)

st

oiltt

oilt pp ε+ΔΕ=Δ − )(1 (1)

dt

stttt yy εεβ ++Ε= − 111 )~(~ (2)

et

dt

stttt ee εεβεβ +++ΔΕ=Δ − 22211 )( (3)

importt

et

dt

st

importtt

importt pp εεβεβεβ ++++ΔΕ=Δ − 3332311 )( (4)

PPIt

importt

et

dt

st

PPItt

PPIt pp εεβεβεβεβ +++++ΔΕ=Δ − 444342411 )( (5)

CPIt

PPIt

importt

et

dt

st

CPItt

CPIt pp εεβεβεβεβεβ ++++++ΔΕ=Δ − 55545352511 )( (6)

0ϕ )1/(

10∑∑==

−k

jj

l

jj βϕ

t

n

i

m

jjtiijjt

l

jj

k

jjtjt zepp εδϕβα ++Δ+Δ+=Δ ∑∑∑∑

= =−−

==−

1 0,

01

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FX PT - CEECs• Short-Term Interest Rates and The Exchange Rate

– VAR– Rezessy (2004)

• Official Foreign Exchange Interventions

• exchange interventions may be more effective in emerging market economies (Canales-Kirjenko, 2003):

( central bank interventions are not always fully sterilized;

( the size of interventions is large relative to market turnover in narrow forex markets;

( the market organization and the regulatory framework may be more conducive to interventions;

( moral suasion may play a bigger role, and

( because of the larger informational advantage of the central banks vis-à-vis market participants.

( BIS (2005)

( CZ: Disyatat and Galati (2005) and Égert and Komarek (2005)

( HR: Égert and Lang (2005)

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FX PT - CEECsTable 3. Summary of the Exchange Rate Pass-Through in Transition Economies

IMPORT PRICES PPI CPIshort-run long-run short-run long-run short-run long-run

Average of the sampleAVERAGE 0.44 0.62 0.16 0.52 0.31 0.33

Country-specific averagesCEEC5

Czech Rep 0.34 0.58 -- 0.41 0.10 0.11Hungary 0.58 0.74 -- 0.57 0.38 0.35Poland 0.57 0.80 -- 0.60 -- 0.29Slovakia 0.41 1.01 -- 0.73 -- 0.35Slovenia 0.26 0.40 -- 0.78 0.20 0.53

Baltic 3Estonia 0.59 0.83 -- 0.47 0.00 0.35Latvia 0.43 0.45 -- 0.66 -- 0.39Lithuania 0.22 0.32 -- 0.55 0.07 0.32

SEEBulgaria -- -- 0.94 -- 0.68Croatia -- -- 0.17 -- 0.22Romania (EFF/EUR) -- -- 0.22 0.48 0.06 0.21Romania (USD) -- -- 0.23 0.53 0.28 0.42

CISRussia -- -- 0.11 0.23 0.42 0.40Ukraine -- -- -- -- -- 0.44

Notes: The averages are based on non-negative pass-through estimates. Negative pass-through estimateswere set to zero. The average of country specific averages does not equal to the figure given in the raw“AVERAGE” as the sample specific average is obtained as the average of all available pass-throughestimates.

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Oest er r eichische Nat ional bankFX PT - CEECs

– cross-country heterogeneity of the pass-through especially for the CPI• Czech Republic vs. Slovenia (53%) and Bulgaria (68%)• Pass-through to the CPI tends to be higher for countries at a lower stage of

development (Korhonen and Wachtel, 2005)• accommodative monetary policy at some stage (Slovenia and Romania) -

> implicite indexation on the rate of crawl and changes in the exchange rate (both tradable and non-tradable goods)

• Estonia: between 0% and 50%– the pass-through is different for different sub-groups of the CPI, PPI

and import prices• Russia: foods, goods, services• CPI cleaned from non-market prices (Mihaljek and Klau (2001)) => pass-

through higher• biased downwards by roughly 10% for Latvia when the price measure

includes non-market prices (Bitans, 2004).• Pass-through is higher for manufactured goods than for raw materials

» => Composition effect in doubt?

– Decline of the pass-through over time– Importance of reference currency (USD vs. euro) Romania, CZ, HU

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Oest er r eichische Nat ional bankAsset prices– Equity, bonds, housing– desired level of liquidity => monetary easing => excess liquidity => buying

assets => increase in prices => decrease in the interest rate (bond) => furtherpressure for prices

• The Non-Financial Corporate Sector

– Tobin’s q : the market value of firms over the replacement cost of capital• if q>1 then market value is higher compared with the replacement cost of capital

and thereby new investments are cheaper relative to the market value of firms.• if q<1 firms would not seek to buy new equipment because it is more

advantageous to acquire other firms with market value less than their replacement cost of capital.

• Also applies to housing if q>1, new construction, if q<1, buy old housing

– asset price booms and busts : market valuation plays a role in investment decisions => should MP react to large swings in asset prices? (asset price booms and busts are observed to occur on a regular basis)

• Conservative view: MP should react only if they imply higher future inflation• “macroeconomic” asset price bubble => with macro effect (distorsion of

investment decisions)

– Bubbles in different asset markets may be related one to another• first stock market bubble, then burst, MP relax, interes rates drop => housing

market boom triggered

34


Asset prices• Households

– wealth effect channel of equity and property prices => Modigliani’s lifecycle theory

• Households’ consumption spending is believed to be driven by disposable lifetime wealth. Because equity and property is part of this wealth, a rise (fall) in equity and housing prices triggered by monetary policy action results in increasing (diminishing) lifetime wealth and thus leads to an increase (decrease) in consumption spending.

– liquidity effect.• Mishkin (2001), spending on durable goods and housing is by a large extent

influenced by consumers’ perception regarding the likelihood of running into financial difficulties. The higher the ratio of liquid financial assets to debt, the lower the probability of financial distress will be. Thus, an increase in equity prices decreases the danger of future problems related to debt and therefore encourages households to consume more goods and housing.

35


Asset prices• Spillovers

– broad lending channel: changes in asset prices => net wealth

– credit channel operational: • Interest rate increase => stock price decreases because of financial constraints

(lower supply and profit) =>– feedback: higher external financing premium for the firms

– lower net wealth (of other firms and household holding the firms shares)

– wealth effect (households) => credit channel

– heterogeneous development of firms’ share prices. • More change when producing more interest-sensitive goods or services as a change

in interest rates modifies the demand for their goods and services (interest rate channel, Ehrmann and Fratzscher, 2005, JMBC).

• In a second stage, such firms are more exposed to the credit channel.

36


Asset prices

Table B3. Factors influencing the asset price channel CEE5 B3 SEE EURO AREA

CZ HU PL SK SI EE LV LT BG CR RO EUR MAX MIN Stock markets - 2003

Capitalisation (% of GDP3) 18.3 17.4 15.3 7.1 20.7 2.1 8.1 12.9 6.3 16.7 8.8 54.4 96.3 17.2 Total value traded to GDP 9.6 10.0 4.1 2.0 2.6 0.4 1.3 1.1 1.0 0.8 0.8 48.8 111.8 4.3

Bond markets – 2003 Private bond market capitalization 7.2 3.4 NA NA NA NA NA NA NA NA 32.0 56.6 0.4 Public bond market capitalization 51.5 40.9 29.1 NA NA NA NA NA NA NA NA 53.2 97.1 20.1 total debt issuance by non-fin corp 0.3 0.0 6.0 NA 0.9 0.6 NA NA NA NA NA 12.9 50.4 0.6

Domestic investment funds Investment funds 4.3 5.4 4.7 5.0 8.1 3.5 0.5 NA NA NA NA 51.3 292.5 9.5 Pension funds 3.7 6.5 7.9 NA 2.0 1.9 0.4 0.1 NA NA NA 12.4 106.9 0.0

Source: WDI (2004), ECB (2005)

37


VAR Studies• Price puzzle 1: a monetary policy contraction causes a rise in the inflation rate rather than a drop

• propositions:– the forward looking component of the monetary policy shock might have

been misidentified (Sims, 1992) => look for variables which help to forecast inflation => commodity prices

– conventional VAR: only up to 8 or 10 variables => combine factoranalysis with VAR (factor augmented VAR, FAVAR), (Bernanke, Boivinand Eliasz, 2004)

– variables good at predicting inflation (such as accurate inflation forecasts) are not much help in solving the price puzzle (Giordani (2004) and Hanson (2004))

• Giordani(2004): include output gap (commodity prices are just correlatedwith economic cycles)

• Hanson (2004): Once the period is carefully hand-picked to remove overlaps between different monetary policy rules, the price puzzle disappears.

38


VAR Studies• Price puzzle 1: a monetary policy contraction causes a rise in the inflation rate rather than a drop

• propositions:– Barth and Ramey (2000): cost channel: prices tend to rise in the wake

of a monetary policy tightening because an increase in interest rates gives rise to higher production costs reflected in higher inflation rate.

• Exchange rate puzzle 2: a monetary policy contraction causes a depreciation of the exchange rate => unsuccessful defence of pegged exchange rate regimes

• => depreciation causes inflation => price puzzle!!!

• Price puzzle 2: emerging markets. • a monetary policy tightening reflected in higher real interest rates increases the

probability that the government will default as a consequence of higher interest payments. Hence, the risk premium rises, and this pushes foreign capital to leave the country, which in turn causes the exchange rate to depreciate. If exchange rate pass-through to domestic prices is high enough, such a depreciation leads to rising inflation (Blanchard, 2004 and Favero and Giavazzi, 2004)

39


VAR Studies• US vs. euro area

• small price puzzle in the US, no price puzzles in the euro area => cost channel; the cost channel tends to be small in the US during the 1990s but is even less important for the euro area (Rabanal, 2003).

• prices tend to fall, gradually but permanently, in the euro area as well as in the US.

• output reacts in a similar way in both economies entities. It first drops but then recovers gradually (humped shaped reaction)

• BUT: output responses are determined more by household consumption rather than by investment in the US, while the opposite appears to be the case in the euro area. => households behave differently, while firms behave similarly in the US and in the euro area

– >Output composition puzzle

40

Oest er r eichische Nat ional bankVAR Studies - CEECsTable 1. Summary of VAR Results

Author ResultsArnostova - Hurník (2004) CZ; full period: FX and price puzzle, output: U-shaped

1998-: price and output:: U-shaped, no FX puzzleBitans et al (2003) LV: Prices: slow decrease and then slow recovery

Creel - Levasseur (2005) Inflation: Price puzzle for allOutput increases, for 1999-2004, no reaction for HU

Darvas (2005) Price puzzle CZ(1998,2004), HU(1994,1998), drop in PLOutput:: drops most PL, least in HU, but recovers quicker in PL than in HU

Response profiles change over timeEFN (2004) Mostly not significant (EE, SI, LT)

Inflation: CZ: price puzzle; HU, LV: U-shaped; SK: permanent decrease (Q); U-shaped (M); PL: nothing (Q, M),

Output: CZ, HU: U-shape; PL: Strong drop then recovery (M); SK: permanentincrease

Elbourne -deHaan (2005) CEEC10; Inflation: largest and quickest drop: SK and ROM,; PL CZ protracted,others small, HU: price puzzle

Output: large quick :CZ; mostly quick,; slow SK EEGanev et al (2002) Inflation: SI, CZ permanent rise, LV, SK: temporary fall, HU permanent fall

Output:: decrease fastest in HU, more permanently in CZ, decreases and adjust in SKand SI, increases in the rest, BG, ROM large fluctuations

Héricourt (2005) Inflation; CZ: price and FX puzzle; HU, SI: Price puzzle,Output: CZ: GDP and IIP different

EE, PL,SK: nothingJarocinski (2004) CEEC5+ROM; Price puzzle,

Kuijs (2001 M2 shock: SK: increase in inflation (ULC incr.), little impact on output.Maliszewski (1999) Inflation: PL: declines and recovers partially

Output:: PL: declines and recovers partially (stronger than inflation)Maliszewski (2002) Inflation: CZ,PL: slow decline and stabilisation at lower level

Output:: CZ,PL humped shaped, but not full recoveryMaliszewski (2002) Inflation: CZ,PL slow decline and stabilisation at lower level

Output, humped shaped, but not full recovery (PL) and stab at lower level (CZ)Vonnák (2005) HU, 1992-2003: price puzzle

HU, 1995-203: quick decline in output, slow decline in prices, FX appreciationWróbel (2001) Prices: PL first increase, then decrease and slight recovery, but still negative

Output: PL first increases, then decreases full recoveryCredit: PL large decrease then slow recovery

41

Oest er r eichische Nat ional bankVAR Studies - CEECsTable 2. Summary of VAR Studies

Author Country/Period VAR VariablesArnostova - Hurník

(2004)CZ, 1993:Q1-2003:Q4;

1998:Q1-2003:Q4;VAR I, E,Y, P(core), I*

Bitans et al (2003) LV, 1995:1-2002:3 VAR, E, Y(IP), P(PPI),Exog:: I*,Y(IP)*

Creel - Levasseur (2005) CZ, HU, PL199:1-2004:4

VAR in level, recursive I,E(NEEF),Y(IP),P,Credit,M2

Exog: I*, Y(IP),P (euro area)Darvas (2005) CZ, HU, PL

1994:Q4-2004:Q3VAR, k=1, contemporaneous

restrictions., TVC VARI,Q,Y,P

EFN (2004) CEEC5, B31993/1995:Q1- 2002:Q2

VAR in level, recursive CEEC5: I,Y,Q,P,M2Exog: I*,Y*,P* (euro area)

B3: I*, Y, P, M2Exog:: Q, Y*,P*

Elbourne - deHaan(2005)

CEEC10 VAR, level

Ganev et al (2002) CEEC8, BG.ROM VAR, generalised IR I,E,Y(IP),P(core)Ex:og:Y(IP)*,P(PPI)*,I*(euro

area)Héricourt (2005) CEEC5, EE,

1995:1-2004:9VAR, level, recursive, K=3 I,E,Y(IP), Y(GDP), P, Credit

Jarocinski (2004) CEEC5+Rom VAR, level, Bayesian I,E,Y(IP),PKuijs (2001 SK, 1993:3-2000:12 VECM, I(r),E(DEM),Y,P(core),ULC,

M2,YExog: P*,oil,regprice, fisc

Maliszewski (1999) PL1993:01–1999:04

VAR in level, k=6, zerorestriction

I, E, Y(IP), P

Maliszewski (2002) CZ, PL1993:1-2002:4

VAR in level, k=6, Bayesian,period split in two samples

I, E,Y(IP);P

Maliszewski (2002) CZ, PL1993:1-2002:4

VAR in level, k=6, Bayesian,period split in two samples

I, E, Y(IP);P,EMBI

Vonnák (2005) HU, 1992:Q2-2003:Q4 VAR in level, alternative ident I,E,Y,PWróbel (2001) PL, 1995:1-200:12 VAR, CEE I, Y(IP), credit-to-GDP, retail

sales, real wages, M2Notes: I= interest rate; E=exchange rate, Y(IP)=output(industrial production), P=inflation.

42


VAR Studies• For the same country:

– price puzzle– a permanent decline– or a temporary fall in the inflation rate after a monetary policy

contraction– the same for output

– sources of heterogeneity• sample period (sub-samples and TVC)• identification scheme (recursive vs. others)• set of variables included• GDP vs. IIP

43


Future outlooks• IRPT:

– Macro side• Increase:

– Money market volatility is likely to fall when adopting the euro– Financial depth is likely to rise

• Decrease:– Inflation rates are falling– GDP growth may slow down in the longer run

– Banking sector• Slow pass-through

– Less foreign penetration in Poland, Slovenia and Latvia– High share of non-performing loans in Poland and Slovenia– Low capital adequacy ratios in Slovenia– Very high concentration rates in Estonia and Lithuania

• Faster pass-through– Low concentration in Hungary and Poland

– Generally, market concentration is higher than in the euro area => IRPT is likely to slow down

44


Macro Side & Banking sectorTable B1. Factors amplifying or attenuating the interest rate pass-through, 2004

CEE5 B3 SEE EURO AREA CZ HU PL SK SI EE LV LT BG HR RO EUR MAX MIN MACROECONOMY Inflation (%) 2.6 6.8 3.6 7.5 3.7 3.0 6.2 1.1 6.1 2.1 11.9 2.2 3.1 0.2 MM volatility 0.75 1.92 1.88 1.37 1.23 0.54 0.41 0.60 0.95 5.10 0.46 GDP growth (%) 4.4 4.6 5.3 5.5 4.2 7.8 8.3 7.0 5.6 3.8 8.3 2.1 4.7 1.2 Financial depth Private credit to GDPa 0.30 0.38 0.28 0.35 0.39 0.29 0.29 0.17 0.22 0.50 0.08 1.02 1.52 0.61 BANKING SECTOR Concentration -Herfindahl index 1103 795 692 1154 1425 3887 1021 1854 NA NA NA 966 2680 178 -5 largest banks (in total assets%) 64.0 52.7 50.2 66.5 64.1 98.6 62.4 78.9 47.0a 58.0a 66.0a 52.9 84.3 22.1 Foreign banks Change in number 1995-2003 3 8 28 -2 0 -1 -1 7 22 18 13 % in total assets in 2003 96.0 83.3 67.8 96.3 36.0 97.3 95.6 47.2 86.0 91.0 State ownership (% in total) 1995 17.6 49 71.7 61.2 41.7 9.7 9.9 61.8 NA 51.9 84.3 2003 3.0 7.4 25.7 1.5 12.8 0.0 4.1 0.0 0.4 3.4 40.6 Bad loans (% in total) 1995 26.6 na 23.9 41.3 9.3 2.4 19 17.3 12.5 12.9 37.9 2003 5.0 3.8 25.1 9.1 9.4 0.5 1.5 2.6 4.4 9.4 1.6 Bank liquidity Bank capitalisation Source: Inflation and GDP growth: Eurostat/NewCronos, MM volatility is money market volatility based on the relative standard deviation of monthly observations for 1-month money market interest rates from 2002 to 2004. Private credit to GDP: World Bank Development Indocators (WDI) 2005, banking sector concentration: ECB (2005): EU Banking Structures, October, except for Bulgaria, Croatia and Romania: WDI 2005. Data on foreign banks, state ownership and bad loans are obtained from the EBRD Transition Report (2004) a 2003

45

Oest er r eichische Nat ional bank• ERPT:

– Decrease in ERPT• Fall of inflation to very low levels• Abandonment of accomodative monetary policies (Slovenia, Hungary,

Romania)– Composition effect

• Fairly substantial everywhere except Slovenia• Euro adoption => via the impact of EUR/USD on DE, FR, IT & rest of the

effective basketTable 8. Long-Run Exchange Rate Pass-Through in Transition Economies

CPI ΔCPI COMPOSITIONEFFECT

EXCHANGE RATE PASS-THROUGH

% % LEVEL CHANGE To IMPORT To PPI To CPICzech Rep 1.6 -6.4 73.8 +20.1 0.65 0.41 0.23 Hungary 3.5 -15.0 77.3 +19.4 0.87 0.57 0.30 Poland 2.1 -12.8 67.7 +12.4 0.84 0.60 0.31 Slovakia 2.8 -3.2 69.1 +30.9 1.01 0.73 0.35 Slovenia 2. -5.9 67.5 +5.5 0.40 0.78 0.53 Estonia 4.2 -5.1 0.83 0.47 0.35 Latvia 7.0 -1.1 0.45 0.66 0.39 Lithuania 2.7 -7.6 0.32 0.55 0.32 Bulgaria 5.0 -13.8 60.2 +20.3 -- 0.94 0.68 Croatia 3.3 -2.4 66.5 +22.2 -- 0.17 0.22 Romania (EFF/EUR) 9.1 -146.9 68.6 +24.0 -- 0.48 0.21 Romania (USD) -- 0.53 0.42

46


Future outlooks• Asset price channel

– Limited importance, probably also in the future– Stock and bond markets

• No fund raising on the stock market (very few listed companies and new introductions)

• No fund raising in the bond markets => financing public debt– Property market

• May grow more important with the development of housing-related borrowing Table 11. Factors influencing the asset price channel

CEEC5 B3 SEE CIS CZ HU PL SK SI EE LV LT BG CR RO RU UA Stock market capitalisation (% of GDP, 2003) 22.8 14.5 25.8 New capital raised (% of GDP, 2003) 0.6 0.3 0.6 Listed companies (2003) 49 203 134 Bond market capitalisation Number of private bond issuers (2003) 12 3 22 Market capitalisation of bonds (% of GDP) Private sector 3.0 0.0 2.8 Public sector 28.9 23.3 14 Number of bonds listed 41 8 53 Market capitalisation of bonds (% of GDP) Private sector 2.1 0.0 1.1 Public sector 10.8 8.1 1.4 Foreign vs. domestic investors (wealth effect) Property prices / loans Residential Commercial Ownership rate Level of household indebtedness

47

Oest er r eichische Nat ional bankSome Facts: Bank Credit to the Private Sector (%GDP)

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Bulgaria

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Czechrep.

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Croatia

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Estonia

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Hungary

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Latvia

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Lithuania

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Lithuania

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Poland

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Romania

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Slovakia

0%10%20%30%40%50%60%70%80%90%

1990

Q1

1991

Q4

1993

Q3

1995

Q2

1997

Q1

1998

Q4

2000

Q3

2002

Q2

2004

Q1

Slovenia

Source: authors’ calculations based on IFS/IMF (lines 22b,d and 99b)

48


Future Outlook• Credit channel

• Second stage– firms may escape domestic monetary policy

» Trade credit and other inter-firm loans» Foreign currency borrowing

• Good news: firms and banks escaping from domestic monetary policy are strongly influenced by euro area monetary conditions (through parent institutions, themselves subject to the credit channel in the euro area)

• Asymmetric effect across sectors and countries

• The service sector is more vulnerable to the credit channel– Small firms are mainly concentrated in services– Manufacturing (received most FDI) : interest rate channel

Huge heterogeneities across countries (low and high mark-up sectors)» Food production: Poland, Bulgaria, Croatia, Romania» Electrical, optical and transport equipments: Czech Rep., Hungary, Slovakia

49


SMEs

20

30

40

50

60

70

80

90

Cze

ch R

Hun

gary

Pola

nd

Slov

ak ia

Slov

enia

Esto

nia

Latv

ia

Lith

uani

a

Bulg

aria

Cro

atia

Rom

ania

private sector (%GDP)

SMEs (%GDP)

20

30

40

50

60

70

80

90

100

Cze

ch R

Hun

gary

Pola

nd

Slov

ak ia

Slov

enia

Esto

nia

Latv

ia

Lith

uani

a

Bulg

aria

Cro

atia

Rom

ania

SMEs in services (% of total)

Source: World Bank

50


Network effects in Manufacturing

Czech Rep.

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Hungary

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Poland

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Slovakia

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

lSlovenia

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Estonia

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Latvia

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

s

Tran

s& Fin.

Rea

l

Lithuania

.0

10.0

20.0

30.0

40.0

50.0

Agri

Min

ing

Man

ufEl

ectr.

Con

str

Trad

eH

otel

sTr

ans& Fin.

Rea

l

Source: WIIW

51

Oest er r eichische Nat ional bankManufacturing

0

5

10

15

20

25

30

35

Bulg

aria

Cro

atia

Cze

ch R

epub

lic

Esto

nia

Hun

gary

Latv

ia

Lith

uani

a

Pola

nd

Rom

ania

Slov

ak R

epub

lic

Slov

enia

Fran

ce

Ger

man

y

Uni

ted

Stat

es

High-technology exports (% of manufacturedexports), 2003

% of total FDI in manufacturing

0

10

20

30

40

50

60

70

80

Cze

ch R

ep.

Hun

gary

Pol

and

Slo

vaki

a

Slo

veni

a

Est

onia

Latv

ia

Lith

uani

a

Cro

atia

Machinery,electrical and transport eq.Food, textile, leather, wood, paper

Source: WIIW and World Bank

52


• Credit channel - Households

• Sources: Backé and Zumer (2005); European Commission (2005)

0

10

20

30

40

50

60

Esto

nia

Latv

ia

Lith

uani

a

Pola

nd

Cze

ch R

.

Hun

gary

euro

area

Household debt (%GDP)

0

10

20

30

40

50

60

70

80

Cze

ch R

.

Hun

gary

Pola

nd

Slov

akia

Slov

enia

Esto

nia

Latv

ia

Lith

uani

a

Household lending in total domestic lendingchange (199- 20049

Table B4-A. Credit channel – Credit to the economy (% of GDP) CEE5 B3 EURO AREA CZ HU PL SK SI EE LV LT EUR MAX MIN

Credit to the corporate sector 17.5 24.3 14.7 17.0 31.2 23.1 32.2 20.1 41.0 59.6 25.2 Credit to the households 12.0 15.4 14.9 7.6 12.6 20.7 16.9 8.1 49.5 77.3 26.0 For housing purchases 8.0 10.2 5.5 6.1 2.8 16.6 11.9 5.6 33.7 67.9 13.7 For consumer credit 2.6 3.2 6.1 1.5 6.9 1.9 2.7 1.2 6.7 10.4 2.8 For other household lending 1.4 2.0 3.3 NA 2.8 2.2 2.3 1.3 9.1 14.1 0.9

Source: ECB (2005)

Monetary Transmission Mechanism in Central and Eastern Europe: Gliding on a Wind of Change

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