THE INTEREST RATE PASS-THROUGH IN POLAND

Grzegorz Szafrański1

T

-

P

1997-2005

Abstract

We analyze the interest rate pass-through on aggregated data for Poland 1997-2005 by ARDL models with ECM. We present a few theoretical arguments for imperfect (i.e. incomplete and sluggish) monetary transmission on emerging financial markets. With TAR class of models we check for the asymmetries in the mechanism of price adjustment to the long-term equilibrium and for the structural breaks. We find that the short-term multiplier for deposits is a subject to structural break in 2001 and that the speed of adjustment to equilibrium depends on the sign (and not on the size) of those changes. Like in other up-to-date studies for post-accession countries including Poland, and the Eurozone there is a strong heterogeneity in interest pass-through between products and group of clients.

Keywords: interest rate pass-through, monetary transmission, emerging financial market. JEL Classifications: E43, E52, G21.

1. Interest rate pass-through in emerging market economies

The questions about monetary transmission are important for performing disinflationary policy in emerging market economies. Under popular direct inflation targeting the interest rate pass-through is a very important impact channel, while such instruments of monetary policy as the exchange rate interventions or legal reserve requirements become of a limited use. The developing money market in emerging economies, supplied by permanent budget deficits with risk-free securities, should support monetary policy effectiveness. Although the short-term money market interest rates tend to follow main monetary policy

rates quickly,2 the central bankers do not expect any longer that the money market rates are passed through to the banking sector completely and immediately. The monetary impulses may still be seriously modified by banks’ responses. Potentially imperfect mechanism of retail interest rate adjustment to the changing market conditions calls for its precise quantification. The structural breaks in the data, and rapid changes in the money market conditions introduce serious measurement problems.

There is a vast theoretical literature on incomplete interest rate pass-through in the context of imperfect internal (inside the banking industry) and external (within the whole financial market) market competition (see the review in Chmielewski 2004). The authors agree that under perfect competition and complete information the banks set their retail interest rates i for deposits according to the opportunity cost and for loans according to the marginal cost of funds faced on the money market and represented by market rate r (see de Bondt 2002):

r

i=δ₀ +δ₁ , (1)

where δ₀ is a constant mark-up for a banking product (deposit or loan) with a given maturity,

1

δ is a derivative of retail price with respect to marginal cost of funds.

Parameter δ₁ depends on the demand elasticity of deposits and loans. If banks are price-takers, then the demand is fully elastic, and δ₁ is supposed to be equal to one. Because of the oligopolistic structure, entry barriers, and product differentiation price elasticities of demand at the bank level and at the industry level can draw together. This leads to symmetrical though not perfect reactions of retail bank interest rates to changes in money market rates δ₁<1 (see Kot 2004).

2 _{Estimations for the over-liquid Polish market suggest equivalent (i.e. one to one) and rapid changes. Possible}

time leads and lags in money market reactions depend on the fact whether the monetary policy changes are expected or unexpected (see the event methodology applied in Serwa 2006 for Poland).

The circumstances, when banks overreact, and increase their retail rates more than the increase in marginal cost of funds (δ₁>1), are not relevant for loans in the long run, as the relatively high interest rates would encourage the borrowers with higher default risk (adverse selection problem) and attract more risky projects (moral hazard problem). Of this reasons banks may prefer setting loan rates below the market clearing levels and allocate credits only to their long-term customers. In consequence it could rather lead to upward stickiness of interest rates than to the overshooting effect. This kind of asymmetry stems directly from incomplete information on borrowers available to lenders. In the booming credit market under oligopoly there are other sources of asymmetry in interest rate pass-through. While the downward price tendency (due to convergence to the European Union levels) was ruling on the Polish money market, it was leading to less than equivalent cuts in loan interest rates. As the loans become relatively more expensive, one could expect the possible reductions in amounts of credits granted. They were however compensated by the inflow of demand from new credit customers.

Furthermore, when the financial market is under-developed (i.e. the banking sector is the main external source of financing the economic activity and there are only imperfect substitutes for bank products), the banks may possess significant market power over their customers, and are not willing to change their prices in a less profitable direction. The lower is the amount of external refinancing the higher is the incentive for banks to postpone the reductions in credit rates (when money market prices decrease) and to delay the increases in deposit rates (when money market rates grow). The product heterogeneity in interest rate pass-through is observed in Polish sector not only with respect to loans and deposits, but for different group of customers as well. The bank interest rate policies for corporate and private customers differ because there are more opportunities for enterprises to invest or to finance their activity.

This sticky interest rate behaviour is linked to menu costs (while changing price lists), contract customer-bank relations (while switching between bank products), and switching costs (while shifting accounts between banks). Because of menu costs interest rate adjustments may be less frequent but more substantial. The retail rates move significantly only if money market rate changes are big enough (e.g. more than 50 basis points). The last motive – switching costs – can become more and more important in emerging markets, where the long-term bank-customer relations are only just establishing.3 The monopolised market for banking services with strong product segmentation is also a good explanation for sluggish interest rate adjustment. The banks do not react immediately to the changes in market conditions. Setting new price levels for loans and deposits in such bureaucratic institutions as banks could last on average about two weeks. In reality we observe only partial adjustment in this period. The complete adjustment usually takes place (if it does) in several months after the money market movements. Nevertheless, the adjustment lags do not lead to the losses in the market share of a particular bank in a long run, as the price elasticity for banking products is lower in a short run.

2. Testing interest rate pass-through in error correction framework

To devise an aggregated interest rate pass-through mechanism we start with a long-term relation between retail banking rates and money market rate like (1). If the hypothesis about unit root in both interest rate series cannot be rejected at usual significance level and residuals from (1) are found to be weakly stationary,4 we assume that (1) is a cointegrating relation between it and rt. Then to estimate the imperfect pass-through mechanism we use

the error-correction model (ECM) representation: t t t t t r i r i =κ +λ ∆ +γ − δ +δ +ε ∆ _{0 0} ( ₋₁ ( _{0 1 −1})) , with εt ~NID(0,σ) (2)

3 _{However, under growing banking competition for new clients the fast adjustments can become serious}

marketing advantage.

where NID(0,σ) is a normally identical distributed process with zero mean and finite variance. Parameter λ₀ denotes a short-term multiplier, δ₀ +δ₁r_t represents a long run equilibrium

(attractor) of the dynamic process with a long-term multiplier δ₁. The adjustment to the long-run equilibrium is proportional to the last-period error correction term (ECT) which measures the distance from the long-run equilibrium ECTt =it₋₁−(δ₀+δ₁rt₋₁). Parameter γ is the speed of adjustment – constant over the sample.

As the adjustment process may be more complex than (2), we let for the additional dynamics including AR- (∆it−i) and DL-terms (∆rt−j) if necessary:

5 t t q j j t j p i i t i t i r ECT i =κ + κ ∆ + λ ∆ +γ +ε ∆

∑

∑

The Engle-Granger two-step procedure rests on the OLS estimation of the long-term multiplier δ₁ in a static representation. After that we estimate the dynamic ECM. Instead of checking for the complete pass-through (δ₁ =1) in a static model (1), we test it in Bewley regression framework that directly provides the estimator of the standard error of δ₁ in a dynamic framework (see Hendry 1995):

t q j j t j p i i t i t r i r i =δ +δ +

∑

∑

Both, ECM and Bewley regression are the representations of an autoregressive distributed lag model, henceforth ARDL:

t q j j t j p i i t i t i r i =α +

∑

∑

Using a lag operator L: Li_t =i_t−1 and lag polynomials: ( )=1− ₁ − ₂ 2 +...− ₊₁ p+1 p L L L L A α α α , 1 1 2 2 1 0 ... ) ( + + + + + + = q q L L L L

B β β β β we write ARDL model as:

t t t B L r i L A( ) =α₀ + ( ) +ε . (6)

The general ARDL representation is convenient for calculating a mean adjustment lag MAL i.e. an average time needed to adjust after a shock to the long-run equilibrium (see Hendry 1995, p. 215): ) 1 ( ) 1 ( ' ) 1 ( ) 1 ( ' A A B B MAL= − , (7)

where A' L( ) and B' L( ) denote derivatives of polynomials A(L) and B(L). For example in ARDL model (3) with p=1 and q=1:

2 1 2 1 2 1 0 2 1 1 2 2 α α α α β β β β β − − + + + + + = MAL (8)

Recently, there is a renewed interest in quantification of short- and long-run effects of interest rate pass-through within ECM framework. Some studies for emerging markets: Wróbel, Pawłowska (2002) and Chmielewski (2003) for Poland, Horvath, Kreko, Naszodi (2004) for Hungary, Crespo-Cuaresma et al (2004) and Kot (2004) for Poland, Czech and Hungary, and Kleimeier and Sander (2005) for new EU members show heterogonous responses of banking sector for different banking products in different countries. The most up-to-date studies for the euro area (De Bondt et al 2005, and Sorensen and Werner 2006) report also some methodological improvements and theoretical explanations of heterogeneity between Member States. Wróbel and Pawłowska (2002) on aggregated data have discovered equivalent (one-to-one) long-term pass-through for all deposits (except for 1-month), and corporate loans of maturity lower than 5 years (except for consumer credits). The study stresses an insignificant increase in the long-run estimates after expanding the sample period 1995-2000 for another 14 months. They argue that this feature could “reflect asymmetry in banks’ reactions – i.e. a bigger response of deposit rates when money market rates fall than when they go up”, but it was not formally tested.6 The pass-through was found to be sluggish. The average time for adjustment to the equilibrium tends to go up with the maturity of

6 _{Crespo-Cuaresma (2004) in his study has not found a significant asymmetry in the adjustment process for}

deposits (from 2.5 months for one-month deposits to 4 months for 12-months). Contrary, the complete or almost complete pass-through takes more time for credits of shorter maturity (up to 3.8 months for consumer credit). The reported ECM specifications do not include AR- and DL-terms. They are also poorly fitted and potentially miss-specified. Horvath et al (2004) for Hungary obtain more precise results using more general specifications. This study confirms the significant difference in the short-term multiplier between aggregated household and corporate sector. Chmielewski (2004), and Horvath et al (2004) estimate also panel regression for individual bank data. Chmielewski (2004) looking for bank-specific disturbances in long-run pass-through connects them with cyclical financial standing of banks. Horvath et al (2004) test for asymmetries and structural breaks in short-term multiplier and in equilibrium adjustment dynamics. It is done with TAR model using interaction dummies; It for short-term multiplier, Jt for equilibrium adjustment, and indicator variables xt, yt with respective thresholds tx, ty. Here we present this concept for simplicity in ARDL(2,2) representation:

t t t t t AD t t t UP t t r I r ECT J ECT i r i =κ +λ ∆ +λ ∆ +γ +γ +κ ∆ +λ∆ +ε ∆ _{0 0 0 1 −1 1 −1} , (9) where    > = otherwise 0 x if 1 _{t x} t t I ,    > = otherwise 0 y if 1 _{t y} t t J .

With different indicators and thresholds we can check non-linear ECM specifications: • for sign asymmetries; xt =∆rt with tx=0, and yt =ECTt with ty =0,

• for size asymmetries; xt = ∆rt with tx =0.5, and yt = ECTt with ty =0.5, • for structural breaks; x_t =t with a given t_x, and y_t =t with a given t_y.

We can freely combine thresholds and indicators from different non-linear specifications (e.g. structural break in short-term multiplier with asymmetrical adjustment to equilibrium).

3. Polish banking industry: aggregated data and structural changes

We analyze the interest rate pass-through in the Polish banking industry for retail banking products of different maturity. The monthly (end-of-month) data reported by National Bank of Poland (NBP) are based on the averages of nominal interest rates offered by the major Polish banks.7 For the deposits flexible interest rates (if available) were favoured at the bank level over fixed rates, and for loans – the interest rates offered to the customers with the best financial standing. Individual banking interest rates were aggregated to the sector averages by the weights connected with the contribution of the bank portfolio to the overall balance sheet position for each type of product. We deal with the following types of banking products; private deposit of maturity from 1 to 24 months (notation in tables; d1 for one month, d3 for 3 months, and d6, d12, d24 analogically), short-term (below 1 year) consumer credits (cred), and corporate credits from 1 to 5 years (c1, c3, c5), all in local currency. Figure 1 presents the predominant downward tendency in the retail interest rates for the sample period 1997-2005.

The data on retail interest rates are subject to the methodological changes in the definition of economic agents after March 2002.8 Because of that we resigned of examining data on household mortgage credit, and long-term consumer credits. Corporate deposits were also out of the interest due to their lower relevance in a balance sheet in relation to household deposits. Short-term consumer credits (cash credits before March 2002) were the subject of the most severe structural changes, because of the introduction of the consumer credit act.

7 _{The number of the reporting banks was changing during the period (from 15 in 1999 to 11 in 2006). Their}

contribution in the deposit and credit portfolio of the sector usually exceeded 70%.

8 _{The changes in banking statistics were implied by new classification of economic agents according to ESA’95}

standards. They affected both monetary aggregates and information on average bank interest rate. Private deposits before the methodological change stand for the products offered to private individuals only, and after that change – to households (including small entrepreneurs and individual farmers). Respectively, small entrepreneurs and individual farmers were excluded from the corporate sector after March 2002.

Figure 1. Banking deposit rates for households 0 4 8 12 16 20 97 98 99 00 01 02 03 04 05 d1 0 4 8 12 16 20 97 98 99 00 01 02 03 04 05 d3 0 4 8 12 16 20 97 98 99 00 01 02 03 04 05 d6 0 4 8 12 16 20 97 98 99 00 01 02 03 04 05 d12 0 4 8 12 16 20 24 97 98 99 00 01 02 03 04 05 d24 4 8 12 16 20 24 28 97 98 99 00 01 02 03 04 05 K1R 4 8 12 16 20 24 28 97 98 99 00 01 02 03 04 05 K3R 4 8 12 16 20 24 28 97 98 99 00 01 02 03 04 05 K5R 0 4 8 12 16 20 24 28 97 98 99 00 01 02 03 04 05 WIBOR1M

Source: GUS data.

Following other studies for Poland (see Wróbel, Pawłowska 2002, Kot 2004, and Chmielewski 2004) we apply Warsaw Interbank Offered Rate for one-month deposits (WIBOR1M) as the benchmark for money market interest rate because its maturity is close to the monetary policy intervention rate (open market instrument). Although some authors recommend it (see Sorensen and Werner 2006), we do not use interest rate of the maturity equivalent to the banking product under investigation. Firstly, the market for interbank deposits of longer than 3-months maturity do not provide reliable information on the cost of funds, because of its low liquidity. Secondly, long-term treasury bills or bonds depend more on government deficits than on monetary policy instruments. Thirdly, popular overnight interbank deposits are exposed to the end-of-month price effects because of legal reserve requirements and there are not many retail products of very short maturity offered by Polish

banks.9 Finally, the correlations of WIBOR1M with the policy instruments are the highest in the group of potential money market interest rates. The money market monthly averages are calculated on the basis of the working-days quotations (so called fixings at the interbank market). Thus retail rates (end-of-month data) follow WIBOR1M changes with two-weeks lag needed to make a price decision in the banking institutions.

Except for the above mentioned change in the standards of banking system statistics in March 2002, there were institutional changes that made the pricing of the bank products more competitive and transparent. Many of them were connected with the incorporation of the European banking standards. The first one was the introduction of new banking law that strengthened the autonomy of supervision institution and created the Monetary Policy Council (MPC). Soon in March 1998 MPC has implemented a direct inflation targeting policy that could potentially affect the monetary transmission mechanism. The other changes that could play a role were new recommendations for managing bank risks (including interest rate risk), substantial changes in the legal reserve requirements,10 and the introduction of free-floating exchange rate regime11. Some important changes commenced in 2001. The decision of abandoning the restrictive stance in monetary policy by MPC was followed by the longest series of interest rate cuts and strong market expectations for further reductions. The prevailing speculation on fixed interest rate treasury securities could also affect the interbank pass-through. In 2001 WIBOR started to be quoted according to the new interbank agreement (more rates of different maturity with stronger contract-setting warranties). Next two years saw the implementation of New Capital Accord of Basel Committee regulations with transparent interest rate regulations and more effective policy instruments (end-of-day deposit, intra-day credit).

9 _{We have excluded current and personal accounts from the analysis as other services provided with those}

accounts and the fees are more important than interest income.

10 _{The legal reserve to local currency time deposits ratio in September 1999 fell down from 11% to 5%.}

11 _{In April 2000 after many years of crawling peg (from Oct.1991) and crawling band (from May 1995)}

4. Results of linear ECM and non-linear ECM-TAR

From 1998 nominal interest rates in Poland follow downward disinflationary trend with few periods of reversals connected with fighting the inflation pressures by MPC actions. All retail interest rates and interbank rate under consideration are found to be non-stationary. For most of them deterministic detrending methods are not sufficient to obtain stationarity and taking first difference is necessary to avoid spurious regression problems.

To find long-term relations between interbank rate and retail interest rates we use both, static (1) and Bewley (4) equations. The results for long-term pass-through are almost invariant to the method used (see Table 1 and Table 2).12 We have not rejected the complete pass-through hypothesis for corporate credits only. From 80% to 85% of initial change in interbank rate was transmitted to the deposit rates. The similar estimates were reported by Horvath et al (2004) on Hungarian aggregated data. The long-term multipliers tend to increase with the maturity of deposits, but not as much as it was found in some previous studies for Poland (see Wróbel, Pawłowska 2002, Crespo-Cuaresma et al 2004).

Low p-values in unit root test (ADF) for residuals from (1) and negative estimates of γ (all statistically significant) confirm the appropriateness of ECM approach. The optimal lag structure was derived by minimizing Schwarz Bayesian Criterion (BIC) and eliminating the insignificant AR-terms (∆it−i+₁) and DL-terms (∆rt−j). Maximal selected lags p and q in equation (3) were zero or one. The ECM specifications (with one or two dummies for outliers) are relatively well-fitted (R-squared more than 60%) except for consumer credits.13 The explained part of the variance for changes in deposit rates is decreasing with their maturity from 70% to 60% (see Table 1 and Table 2).

12 _{The long-term multipliers are increasing while expanding the sample. To improve the reliability of relations}

we attempted to incorporate the ratio of legal reserve for deposits as the factor explaining the modified cost of funds. We also estimated some switching regressions to let for major regime shifts in long-run relations. The ECMs formulated for the modified residuals did not perform better in diagnostic and out-of-sample tests.

13 _{The ECM for consumer credits is possibly miss-specified due to the structural break in the data (March 2002)}

and legal regulations concerning the effective interest rate not visible in nominal data presented by NBP. We do not comment more results for this group of credits.

Table 1 Symmetrical error-correction mechanism for household deposits d1 d3 d6 d12 d24 constant δ₀ -1.496 -1.670 -1.643 -1.200 -0.863 LT relation δ1 0.795 0.811 0.834 0.849 0.860 LT Bewley δ '₁ 0.800 0.812 0.828 0.836 0.850 LT standard deviation 0.021 0.025 0.027 0.033 0.033 complete pass-through δ1=1 No No No No No adjusted R2 RSQ 0.9864 0.9844 0.9832 0.9792 0.9797 p-value of (ADF) 0.0058 0.0007 0.0007 0.0015 0.0012 error correction γ -0.13 -0.12 -0.12 -0.12 -0.11 ST adjustment λ₀ 0.36 0.38 0.38 0.37 0.37 ar term κ₁ 0.27 0.25 0.23 0.25 0.00 dl term λ1 0.00 0.00 0.00 0.00 0.15

mean average lag MAL 2.1 2.3 2.6 2.5 3.7

adjusted R2 RSQ 0.7201 0.7067 0.6657 0.5696 0.5992

Akaike Criterion AIC -0.0730 0.2151 0.3785 0.6640 0.5742

Schwarz Criterion SIC 0.0504 0.3386 0.5019 0.7875 0.6977

Durbin-Watson DW 2.34 2.13 2.23 2.29 2.17

No. of observations 109 109 109 109 109

No. of dummies 1 1 1 1 1

statistics and estimates of

Long-term relation

Short-term dynamics

Source: Own calculations, results for long-term equations (1), and (4), and for short-term dynamics according to the equation (3). All dummies for December 1998.

Table 2 Symmetrical error-correction mechanism for credits

cred c1 c3 c5

constant δ₀ 12.27 1.87 2.61 2.83

LT relation δ1 0.594 1.003 0.979 0.960

LT Bewley δ '1 0.595 1.025 1.006 0.984

LT standard deviation 0.014 0.018 0.024 0.032

complete pass-through δ1=1 No Yes Yes Yes

adjusted R2 RSQ 0.9238 0.9853 0.9814 0.9782 p-value of (ADF) 0.0090 0.0094 0.0032 0.0131 error correction γ -0.12 -0.20 -0.13 -0.13 ST adjustment λ0 0.26 0.49 0.43 0.47 ar term κ₁ 0.00 0.00 0.00 0.00 dl term λ₁ 0.09 0.00 0.13 0.12

mean average lag MAL 3.4 2.6 3.3 3.0

adjusted R2 RSQ 0.3674 0.7378 0.7293 0.7473

Akaike Criterion AIC 1.0825 0.3833 0.3259 0.4916

Schwarz Criterion SIC 1.1813 0.5061 0.4740 0.6398

Durbin-Watson DW 1.92 2.13 2.05 2.55

No. of observations 109 110 109 109

No. of dummies 0 2 2 2

statistics and estimates of

Long-term relation

Short-term dynamics

Source: Own calculations, results for long-term equations (1), and (4), and for short-term dynamics according to the equation (3). Dummies for December 1998 and 2002.

Almost a half of the initial change is transmitted to the banking sector in the same month. The short-term multiplier is comparable with other studies (about 0.37 for deposits,

and 0.45 for corporate loans), but the strength of error correction mechanism (12%-13%) is at the low end of those estimates. More general specification of ECM (with AR- and DL-terms) than in other Polish studies possibly reduced the reported MAL measured according to formula (7). The average time needed to adjust to the equilibrium is increasing with the maturity of deposits and loans from two months for short-term deposits (see Table 1) to three months for 5-years credits (see Table 2).

To improve the results we check for asymmetries and structural breaks according to nonlinear TAR-ECM specifications mixing indicators and thresholds from equation (9). In Table 3 we present only the best fitted models for time deposits with significant AR-terms. We do not report results for loans as the evidence of asymmetries and structural breaks in their dynamics is rather poor and ambiguous. Similarly size asymmetries performed worse in all cases for deposits and loans. In result of the selection procedure we found the strongest evidence of sign asymmetries for speed of adjustment coefficient γ for short-term deposits only, and structural breaks in short-term adjustment parameter λ₀. The period of structural break with maximal Chow test statistics was recorded in the first quarter of 2001 (February-March). At this time the MPC changed its stance in monetary policy from restrictive to neutral which was accompanied with some institutional changes on the financial market.

Table 3 Non-linear ECM for household deposits

d1 d3 d6 d12 d24

error correction term γ -0.37 -0.31 -0.19 -0.22 -0.25

sign asymmetry γAD 0.30 0.20 0.00 0.00 0.00 ST adjustment λ₀ 0.33 0.33 0.30 0.29 0.30 structural break λ₀UP 0.34 0.46 0.49 0.66 0.54 ar term κ₁ 0.17 0.15 0.15 0.00 0.00 dl term λ1 0.00 0.00 0.00 0.00 0.00 adjusted R2 RSQ 0.7931 0.7785 0.7388 0.6657 0.6436

Akaike Criterion AIC -0.3579 -0.0484 0.1401 0.4655 0.4512

Schwarz Criterion SIC -0.1851 0.1244 0.2883 0.5883 0.5739

Durbin-Watson DW 2.13 2.15 2.26 2.00 2.13

No. of observations 109 109 109 110 110

No. of dummies 1 1 1 1 1

Short term dynamics statistics and estimates of

Source: Own calculations, results for equation (9). All dummies for December 1998. All estimates are significant at 1%, except for one estimate in italics – significant at 5%.

The best non-linear ECMs for deposits performed better in terms of their fitting (see Table 3) and predictive power. The main result of non-linear analysis for deposits is the more than two-fold increase in the short-term multiplier after 2001. This structural change shortens the period of average return to equilibrium twice, which is very fast as for European banking standards. With ECM-TAR methodology we observe also the significant strengthening of the error correction mechanism. For long-term deposits about 20% of the distance to the equilibrium is corrected in the next month. For short-term deposits it is even more than 30%, but it acts efficiently only in the periods of negative long-run equilibrium errors. When the errors are positive (i.e. at the periods of falls in money market interest rates), the error correction mechanism is substantially weakened. The adjustment takes then the form of short-term multiplier with autoregressive corrections due to significant AR-short-terms.

4. Conclusions

We confirmed that the error-correction framework is a useful tool in analysing the interest rate pass-through on the Polish market. It can explain from 60% to 70% of the monthly variance in retail interest rate changes depending on the type of the bank product and the method used. There is a strong evidence of complete pass-through for corporate credits. With linear ECM we have found that mean adjustment lag for those loans is about three months. The results for consumer credits are unconvincing probably due to the breaks in the time series. The money market rates were transmitted to household deposit rates only in about 80% in the period 1997-2005. The most suitable method for their analysis is non-linear ECM-TAR. The more than two-fold increase in short-term multiplier for deposits after 2001 should be a matter of further research. We relate it theoretically to institutional changes and strong expectations for interest rate falls.

References:

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interest rates in euro area countries, Working Paper Series 518, European Central Bank.

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Bank-Specific Financial Disturbances, paper presented at the ECB Workshop Asset Prices and Monetary Policy held on December 11-12, 2003 in Frankfurt.

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Grzegorz Szafrański

K

W POLSKIM SYSTEMIE BANKOWYM W LATACH

1997-2005

Za pomocą modelu ARDL z mechanizmem korekty błędem (ECM) analizujemy kanał (transmisji) stóp procentowych na zagregowanych danych polskiego sektora bankowego. Przedstawiamy teoretyczne podstawy potencjalnie niedoskonałej (niepełnej i opóźnionej) transmisji stóp procentowych na wschodzących rynkach finansowych. Stosując nieliniowe modele typu ECM-TAR sprawdzamy możliwe asymetrie w mechanizmie dostosowań stóp do poziomu długookresowej równowagi i możliwość wystąpienia w nich strukturalnych załamań. Dla depozytów terminowych ustalono, że krótkookresowy mnożnik kanału stóp procentowych był przedmiotem strukturalnej zmiany po 2001 roku, a szybkość dostosowań do równowagi zależy raczej od kierunku zmian stóp procentowych niż od rozmiaru nierównowagi. Podobnie jak dla krajów post-akcesyjnych i strefy euro znaleziono znaczące różnice w kanale stóp procentowych dla depozytów i kredytów, oraz dla różnych grup klientów.

Słowa kluczowe: kanał (transmisji) stóp procentowych, mechanizm transmisji pieniężnej, wschodzące rynki.