A C T A U N I V E R S I T A T I S L O D Z I E N S I S FOLIA OECONOMICA 192, 2005
P io tr W d o w iń sk i*
FINAN CIAL M ARKETS A N D ECO NO M IC G RO W TH IN PO LAND: SIM U L A T IO N S W ITH AN ECO NO M ETRIC M O DEL**
Abstract. In this paper we present simulations o f economic performance o f the Polish economy based on a quarterly econometric model. The model consists o f 22 stochastic equations which link the financial market with the real economy. The purpose o f the research is to present effects o f changes to domestic and foreign interest rates and the E U R /U SD exchange rate on economic growth in Poland over the period Q2, 1993 - Q2, 2003.
Keywords: financial market, economic growth, econometric model, simulation, Poland. JEL Classification: C3, C5, E6, FI, G l.
1. INTRODUCTION
T h e accession o f P oland and o th er countries o f C en tral and E astern E u ro p e (C E E ) in to the E u ro p e an U nion on M ay 1, 2004 is a social and econom ic challenge and a m ilestone in the history. T h e m em bersh ip in the E U is expected to im prove the social and econom ic p o ten tial o f new m em ber states. T h e econom ic effects will be particularly im p ortan t. In case o f P oland, in p artic u la r, we can expect th a t the ties in foreign tra d e w ith the E U and financial linkages will be fu rth er strengthened. Finally, th e integration o f the P olish financial m ark e t with the E u ro p ean and w orld m ark e ts will cu lm inate w ith the expected ad o p tio n o f the euro.
In this p ap e r we present sim ulations o f the sh o rt-term econom ic grow th in P o la n d based o n a q u arte rly econom etric m odel. T h e m odel has a b ac k g round in theories o f in tern atio n al econom ics. It co n tain s th e blocks which * Dr (Ph.D., Assistant Professor), Department of Econometrics, University o f Łódź. ** I would like to thank my colleagues from the Department o f Econometrics and participants o f FindEcon 2004 conference at Department of Econometrics (University o f Łódź) for helpful comments and suggestions. Financial support from the Polish Committee for Scientific Research within the grant N o. 2H02B01624 is gratefully acknowledged. The usual disclaimer applies.
link the financial m ark e t with the real econom y. W e search fo r effects o f changes to dom estic and foreign interest rates and the exchange rate E U R /U S D on the m ain m acroeconom ic indicators o f the Polish econom y.
T here is a com prehensive literature on m acroeconom etric m ultiple-equation m odeling o f the Polish econom y, b o th in the sh o rt and long term . T he m odels focus on the whole econom y (e.g. C h arem za 1994, W elfe W. (ed.) 1996 and 1997, B artcczko and Bocian 1996, Welfe W. et al. 2000, C harem za and S trzała 2000, Welfe A. et al. 2002, Bradley and Zaleski 2003) o r they are d e v o te d to p a rtic u la r secto rs o r m a rk e ts (e.g. M aciejew ski 1981, Ł apińska-S obczak 1997, M ilo et al. 1999, K arad elo g lo u et al. 2001, M ilo and Ł apińsk a-S obczak 2002, Brzeszczyński and Kelm 2002, Plich 2002, W dow iński and M ilo 2002, W dow iński 2002). T here also exists an extensive and grow ing literatu re on m acroeconom ic and financial m a rk e t m odeling either w ith low o r high frequency d a ta in case o f Poland (e.g. Sztaudynger 1997, M ilo (ed.) 2000, Osiewalski and Pipień 2000, K eim 2001, Sokalska 2002, O sińsk a 2002, C harem za and Strzała (cds.) 2002, D o m a n M . and D o m an R. 2003, W dow iński 2004, to m ention ju st a few).
T h e p a p e r is structured as follows. In Section 2 we present the m odel and estim ation results. S im ulation scenarios are given in Section 3. Finally, we present concluding rem arks and policy im plications.
2. THE QUARTERLY ECONOMETRIC MODEL
In this section we describe the quarterly m odel o f the Polish econom y. T he m odel consists o f 22 stochastic eq u atio n s and an identity for gross dom estic p ro d u c t (G D P ). We have introduced the follow ing building blocks into the m odel:
• prices - consum er price index, p ro du cer price index, im po rt and ex p o rt prices fro m /to the E U 15, C E E countries (C E E C s), and th e rest of the w orld (R W );
• m oney m a rk e t - m oney supply M l and М 2, interest rates (m oney m a rk e t ra te and lending rate);
• exchange rates - P L N /U S D , P L N /E U R and the nom inal effective exchange ra te o f the zloty (N E E R );
• im ports and exports fro m /to the EU 15, C E E C s, and R W co un try regions.
W e have also estim ated eq uations fo r the capital m a rk e t risk, private co n su m p tio n , average wages, and unem ploym ent rate.
T his m odel can be used in sim ulation analyzes o f alternative m onetary, fiscal and trad e policies as well as ex-ante forecasts o f m ain econom ic ind icators in P oland. We stressed an im pact o f the real exchange ra te and
d em and for im ports and exports as well as effects o f the price fo rm ation system. T h e tra d e balance is derived as a difference o f ex po rts and im ports. The m odel is closed w ith a G D P identity. In the sim ulation m odel we have introduced recursive tran sfo rm atio n s by which we generate a num b er o f variables: real wages, tra d e balance in US dollars, shares o f im p o rts/exp orts fro m /to specified co u n try regions in to tal im p o rts/ex p o rts, shares o f im ports/exports in G D P , terms o f trade, trade balance in total and in breakdow n by co u n try groups.
In F ig u re 1 we present a flow -chart o f the m odel.
Fig. 1. Flow-chart o f the model (symbols in bold indicate endogenous variables; dotted line indicates lagged dependence)
In the price setting m echanism , producer prices (P P I) are affected through im p o rt prices, nom inal average wages, exchange rates and a real interest rate. T his represents a cost side o f p roducer price fo rm a tio n . C onsum er prices (C P I) are determ ined by cost, incom e, and m oney factors. E x po rt prices are influenced either by p roducer prices o r G D P prices. N om inal average w ages are determ ined by co n su m er prices (wage ind exation ),
productivity, M d labour m arket imbalance (unem ploym ent rate). These factors are essential in the price-w age inflationary feedback.
T h e im p o rt and exp o rt eq u atio n s are given in a K eynesian trad itio n as function s o f incom e and relative prices. W e have in tro d u ced foreign trade break dow n by co u n try regions: E U 15, C E E C and RW . H ence, all respective variables - incom e and prices - are country-specific. In th e sim ulation m odel net ex ports is given by an identity.
T h e m oney m a rk e t is represented by m oney supply M 1 and М 2, interest rates (m oney m a rk e t ra te and lending rate), and exchange rates P L N /U S D , P L N /E U R and N E E R . T h e equ ations for exchange rates P L N /U S D and P L N /E U R are given in a m o netary fram ew ork.
W e have introduced the capital m ark e t in P oland in to the m odel by explaining the co u n try beta risk proposed in W dow iński an d W rzesiński (2004) and fu rth e r elaborated in W dow iński (2004).
T h e m odel has been estim ated w ithin the sam ple th a t ranged between 22 and 46 observations over the period o f Q2, 1993 - Q2, 2003. Below we give estim atio n results o f selected equ atio n s th a t belong to the capital m a rk e t, the m oney m ark e t, and the price setting m echanism to p rep are a focus to financial sim ulations w ith th e m odel. We also com m en t on foreign tra d e block.
W e have applied selected tests to determ ine statistical p ro perties o f estim ated equ ations. T herefore, we have: R 2 - adjusted coefficient of determ ination, SE E - standard equation error, D - W - D urbin-W atson statistic, B-G - B reusch-G odfrey statistic to test for serial co rrelatio n in residuals, J -B - Ja rq u e -B e ra statistic to test fo r n o rm ality o f resid u als, A R C H - autoregressive conditional heteroscedasticity in residuals test statistic, W H ITE - heteroscedasticity in residuals test statistic, A D F - (augm ented) Dickey-Fuller test statistic, C H O W - C how ’s stability o f estim ates test statistic, T P - turning p oints test statistic o f forecasting accuracy. Respective test probabilities and i-S tu d en t statistics are given in brackets. T h e dum m y variables and A R term s announced in estim ation results were introduced into selected equations to ac co u n t for outliers and to elim inate serial co rrelatio n in residuals if o th er p rocedures failed. A lthough n o t rep orted , those effects in dum m ies and A R term s were highly significant which gives m ore insight into structural changes to endogenous variables.
Below we present an outline o f estim ation results.
The capital market risk
(1) fiwiG.t — 0-03 + 0.02(iMAf — i'mm), — 1.00(Л /лУ СВР — AinYgdpX + dummies
R 2 = 0.82, SE E = 0.10, D -W = 2.31, B-G = 0.87[0.35], J -B = 0.82[0.66], A R C H ( 1) = 1.79[0.18], W H IT E = 12.5[0.13],
A D F = -6.3[0.00], C H O W = 0.63[0.68], T P = 71.43% , sample 1995 :2 - 2 0 0 2 :4 (31 obs.),
where:
ßw ie - country beta ri.sk (Poland) calculated in W dow iński and Wrzesiński (2004), and W dow iński (2004a);
iMM - m oney m ark e t rate, percent per annum , IF S , Line 96460B ...ZF...; ‘мм - in terb a n k ra te (three-m onth m atu rity ), percent per an num , euro area, IF S , Line 16360B.ZF;
Ус,dp - G D P , natio n al currency, bln, P olan d, IF S , Line 96499B ...ZF... deflated w ith P GDP — price deflato r o f G D P incom e, ow n calculations on the base o f G U S d a ta , N ational Accounts and IF S D a ta ;
Yg dp - G D P a t m ark e t price, euro area (changing com position), con stan t prices - E C U /e u ro - mixed m ethod o f adjustm ent, bln o f unit.
T he capital m ark et risk is m easured as a time-varying param eter estim ated in a regression o f the W arsaw Stock E xchange Index W IG on foreign indexes (D JIA , N A S D A Q , D A X and F T SE ). T his co u n try beta risk is an average o f m o n th ly individual beta param eters estim ated fo r daily d a ta in m o n th ly sub-periods in regressions for W IG index on individual foreign stock m a rk e t indexes.
W e have fou nd in W dow iński and W rzesiński (2004) and W dow iński (2004) w ithin a m o n th ly research th a t m o n etary variables as exchange rates and interest rates have relatively m ore pow er th an real variables in explaining the co u n try beta m a rk e t risk in P oland. As we can see, w ithin the qu arterly d a ta the relations are sim ilar. T he capital m a rk e t risk also depends on m oney m ark e t interest rate differential to a larger extent th an o n a G D P g row th differential, having considered a size o f respective estim ates and their significance.
N ow let us show the m oney m ark et equ atio n s fo r M l and М 2 m oney supply, m oney m a rk e t interest rate, lending rate, and exchange rates.
W e assum e th a t the m oney m a rk e t is in equilibrium , i.e. M s = M D, w here S and D den o te supply and dem and respectively. T h e equilibrium condition specifies the following relation (e.g. W dowiński and van Aarle 2001):
(2) ms — p = к у — li,
where:
ms - (log of) nom inal m oney supply; p - (log of) price index;
у - (log of) real incom e; i - nom inal interest rate; к, X - param eters.
T h e p aram eter к represents the effects o f tran sactio n dem an d fo r m oney, while X represents speculative dem and for m oney. Below we give estim ation results o f m oney equations.
Money supply M l
(3) Ŕ 2 = 0.98, S E E = 0.01, D -W = 2.41, В - G = 4.29[0.04], J -B = 0.26[0.88], A R C II( 1) = 2.21[0.41], W H IT E = 10.80[0.37],
A D F = -5.80[0.00], C H O W = 0.15[0.86], T P = 33.33% , sample 1997:2 — 2003:1 (24 obs.)
M l - m oney supply M l, bln o f P L N , source: h ttp ://w w w .n b p .p l;
P Cpi - consum er prices, index num bers (1995 = 100): period averages, P oland, IF S , Line 96464..,ZF... Money supply М2 л (4) Ж 2 = 0.99, SE E = 0.01, D -W = 1.76, B-G = 0.38[0.54], J-B = 0.44[0.80], A R C H (l) = 2.15[0.14], W H IT E = 4.83[0.78], A D F = -4.24[0.00], C H O W = 0.35[0.79], T P = 57.14% , sample 1997 :1 - 2003 :1 (25 obs.)
М 2 - m oney supply М 2, bln o f P L N ; source: h ttp ://w w w .n b p .p l/. As expected, the response o f M l - cash dem ands - to changes in G D P and m oney m ark et interest rate is m uch stronger th an in case o f М 2 m oney supply - a b ro a d er definition o f m oney dem ands w ith low liquidity.
л t-stat (1.19) (5.73) (-18.34) where: In — 8.80 + 0.19 In Уgdp,t — 0 .0 0 4 ijv ff + trend t-stat (10.22) (2.42) H . 4 9 ) where:
B
U
t
Money market interest rate
1m m,i = —2.47 + 0.32i h n ú- 1 + 2.63 ßwic.,t + 0.70ißit + dummies
t-stat ( — 5.40)(6.43) (4.89) (15.26)
(5) R 2 = 0.99, S E E = 0.60, B-G = 9.60[0.002], J -B = 0.42[0.81], A R C H ( l) = 5.22[0.02], W H IT E = 11.88[0.16], A D F = -8.86[0.00], C H O W = 0.41[0.91], T P = 42.86% , sample 1995: 1 - 2 0 0 2 :4 (32 obs.)
where:
iD - disco u n t ra te (end o f period), percent per an n u m , P o land, IF S , Line 96460...Z F...
Lending interest rate
= 6.80 + 0.62iLt,_ 1 + 0.31iMMit + trend 4- dummies t-sta t (3.99) (13.78) (9.53)
(6) R 2 = 0.99, S E E = 0.43, B-G = 3.21 [0.07], J -B = 0.55[0.76], A R C H ( l) = 0.23[0.63], W H IT E = 25.11 [0.01], A D F = -5.22[0.00], C H O W = 0.62[0.80], T P = 87.50% , sample 1992: 1 - 2003 :2 (46 obs.), where:
iL - lending rate, percent per annum , P oland, IF S , Line 96460P .. Z F ... In case o f both interest rates we have used A R ( 1) specification. W ith this sim plified ap p ro ach we tried to cap tu re the risk o f the m a rk e t specified by the respective interest rate. W e can see th a t th e estim ate by a lagged interest ra te iMM - (0.32) is m u ch lower th a n its c o u n te rp a rt by a lagged lending ra te iL - (0.62). T his m eans th a t the adjustm ent to w ard s equilibrium after a shock takes m o re time in the credit m ark et. T h e difference in this in ertia m akes the interest rate differential in the credit an d m oney m arkets to narro w very slowly. H ence, the higher the differential, the higher the price o f credit.
We should also no te th a t there is a feedback betw een the m oney m arket (iMM) and the capital m ark e t represented by the co u n try beta risk (ßWIG) (cf. F igure 1). T h e coefficient by ß WIG (2.63) denotes th a t 10 p o in ts increase ceteris paribus in th e capital m ark e t risk gives rise to an increase in m oney m a rk e t ra te by 0.26 pp.
In m odeling exchange ra te s 1 we have used a m o n etary ap p ro ach . T he m o n etary m odel is given as follows (e.g. M cese and RogofT 1983):
(7) ms — p = к у — Я i,
(8) ms* — p* = к* у* — A*i*,
(9) š = p - p*
where:
ms - (log of) nom inal m oney supply; p - (log of) price index;
у - (log of) real incom e; i - n om in al interest rate; J - equilibrium exchange rate; к, Я - p aram eters;
* - denotes respective foreign variables.
S ubstituting (7) and (8) into (9) for prices and u nd er assum p tion th at к = к* and Я = Я*, we o b tain the m o netary m odel o f exchange rate:
(10) š = (m° - ms*) - к (у - / ) + Я(г - /*).
In W dow iński (2005) we have assessed the predictive pow er o f exchan ge ra te q u arte rly purchasing pow er parity and m o n etary m odels. We have fou nd th a t the predictive eccuracy o f the m o n etary m odel is higher than the pow er o f the P P P m odel in case o f exchange rates P L N /U S D and P L N /E U R . Below we present estim ation results o f em pirical exchange rate m odels. Exchange rate P L N /U S D lnS[/sD,r = 14.49 4- 0 .6 7 (ln M 2 -ln M 2us),-0 .2 9 (ln Y GDP — 1пУовр)г- 2 + dummies t-stat ' (18.21) (26.24) (-3.12) (11) R 2 = 0.98, SE E = 0.01, D -W = 2.69, B-G = 3.91 [0.05], J-B = 0.66[0.72], A R C H ( 1) = 0.50[0.48], W H IT E = 9.56[0.39], A D F = — 7.25[0.00], C H O W = 0.002[0.99], T P = 71.43% , sample 1997:1 - 2003 : 3 (27obs.),
where:
Susd - m a rk e t ra te , zlotys per US dollar: period average (rf), national currency p er U S, P o lan d , IF S , Line 96 4 ..R F .Z F ...;
M 2 US - m oney supply М 2, bln o f US dollars: end o f p eriod, U nited S tates, IF S , Line 11159M B .ZF...;
У GDP - G D P (1995 = 100), index num ber, U nited S tates, IF S , Line 11199B V R ZF...
Exchange rate PL N /E U R
In W f = 0.28 + 0 .56(ln M 1 - In M 1£ V 2 - 0.27(ln Y GDP - In Y EGuDP)t _ 2 -
t-stat (0.62) (0.57) (-2.01)
— 0.53 In S^ur/usd t—i + dummies ( - 1 2 .7 4 )
(12) R 2 = 0.94, S E E = 0.02, D -W = 2.27, B-G — 0.54[0.46], J -B = 0.30[0.86], A R C H ( l ) = 1.75[0.19], W H IT E = 8.50[0.67], A D F = — 5.51 [0.00], T P = 70.00% , sample 1998 : 2 - 2003: 3 (22obs.),
where:
Se u r ~ P L N /E U R - fixing N B P (m onthly average) since 1996, until
1996 EC B reference exchange rate, US dollar/eu ro, 2:15 pm (C .E .T .), against E C U up to D ecem ber 1998 x P L N /U S D - fixing N B P (m onthly average);
M l EU - eu ro area, gross stocks, central governm ent and M F Is (with EC B ) [G plus U] repo rtin g sector - m o netary aggregate M l , all currencies com bined - eu ro area c o u n terp art, o th er residents and o th er general govnt. (2120 & 2200) sector, denom inated in euro, d a ta w orking day and seasonally adjusted , bln o f euro;
Seur/usd - n a tio n a l currency p er US d o lla r, eu ro a re a , IF S , Line 16 3..R F .Z F ...
Nominal effective exchange rate o f the zloty
^ --- ) = 5.84 + 0 .2 3 In ( ---) = 0 .8 0 In /" ---^ + d u m m i e s
N EER.tJ \ S v S D .t J \ SeVR.i/
(13) Ŕ 2 = 0.99, SE E = 0.01, D -W = 1.65, B-G = 1.30[0.25], J -B = 0.81 [0.67], A R C Ii( 1) = 1.08[0.30], W H IT E = 10.58[0.10],
A D F = — 5.23[0.00], C H O W = 0.61[0.82], T P = 100% , sample 1 9 9 3 : 2 - 2 0 0 3 : 2 (4 lob s.),
where:
Sn e e r ~ nom inal effective exchange rate, index n u m bers (1995 = 100):
period averages, P oland, IF S , Line 964..N E C Z F ...
T h e results show a sim ilar response o f exchange rates to changes in m oney supply and incom e differentials. We should also note a very significant effect o f changes to the exchange ra te E U R /U S D on the exchange rate P L N /E U R . T h e sam e effect in case o f the exchange ra te P L N /U S D turned o u t to be insignificant. In both eq uations (11) an d (12), th e influence of short-term interest rates was insignificant. T his effect seems to be stronger w ith higher frequency d a ta (m onthly or daily).
E stim atio n results o f the N E E R exchange rate show th a t the weight of P L N /E U R ra te was m uch higher th an the weight o f P L N /U S D ra te over the analyzed period, i.e. Q2, 1993 - Q2, 2003.
N ow let us tu rn to foreign trad e relations which acco u n t fo r a p a rt o f th e real side o f the m odel. W e need to point o u t th a t d u rin g the last decade a significant change in international trad e relations could be observed in P oland. In particu lar, trad e relations with the E U 15 and C E E C s have developed rem arkably. B oth im port and expo rt stru ctu re has changed during tran sitio n . T h e m em bership in the E U will have even stro n g er im pact on the tra d e balance o f Poland and o th er countries which jo ined the E U . F oreig n tra d e is a very im p o rtan t factor o f econom ic g row th in those countries. H ow ever, their dynam ics o f im ports used to exceed the dynam ics o f exports. We can expect th a t high dynam ics o f im p orts will persist m ainly due to (i) ongoing tran sitio n process and m o d ern izatio n o f the econom y, which calls fo r high investm ent and interm ediate goods im ports, (ii) abolishing o f tra d e barriers after joining the E U and with the rest o f the w orld within W TO , (iii) inflow o f F D I which creates dem and for im p o rts and (iv) ap p reciatio n o f the zloty as a result o f F D I and po rtfolio investm ents in P o lan d. T o im prove the trad e balance it is necessary to increase exports by c o rp o ra te restru ctu re, cost optim ization and seeking fo r new m arkets. It is th en necessary to pursue such econom ic policy, w hich will allow for raising the rates o f investm ent outlays to low er costs an d im prove the qu ality o f p ro d u ctio n . W ith o u t continuou s changes in th e level o f com petitiveness o f th e Polish econom y it is n o t possible to im prove the trade balance. T h e com petitiveness, how ever, should be viewed by gaining a com
parativ e ad v an tag e in a variety o f com m odities by cost o ptim izatio n and quality im provem ent and not by policy o f currency depreciation. A n im portant favourable facto r o f exports grow th is F D I inflow and ow nership restructure in the econom y (cf. W ysokińska 1999).
E conom ic g row th in Poland depends on foreign tra d e to a large extent. T h e tra d e o f P oland has been divided in the m odel into three regions: EU 15, C E E C s and the rest o f the world (RW ). T h e latter has been calculated in the follow ing way:
r j ' R W — _j_ • j C E E C ^
where: T - den o tes either im ports to or exports from P oland an d W stands for W O R L D .
T h e estim ates o f foreign tra d e eq uations are presented in T ab le 1. Table 1. Income and price elasticities o f imports and exports by country regions
Foreign trade
Elasticity
income price
short-term long-term short-term long-term
Imports EU 1.01 X -0.23 X CEEC 1.03 X -0.24 X RW 1.07 X -0.64 X Exports EU 2.14 3.45 -0.57 -0.92 CEEC 0.26 1.00 -0.21 -0.81 RW 1.00 X -1.11 X
W e observe a very sim ilar short-term response o f regional im p orts to G D P incom e changes and a sim ilar relative price effect in the case o f E U 15 and C E E C s. T h e price effect is m uch stronger in case o f R W region. T he results show then a sim ilar p a tte rn o f P o la n d ’s trad e w ith the E U 15 an d C E E C s, while m ore flu ctu atio n s can be observed in im p o rts w ith R W countries, m ainly d u e to price shocks.
In case o f exports we can see a different picture. B oth incom e2 and price elasticities are m ore diversified. T he highest income effect we can see in case o f the E U 15, while the strongest price effect again in case o f R W region.
2 We have used different income indicators in regional exports from Poland, i.e. for the EU - GD P plus imports (total absorption), for CEECs - CEECs exports in US dollars, for RW region - RW exports in US dollars defined as a difference between world exports and a sum of EU exports and CEECs exports.
C o m p arin g the results for exports and im po rts we can conclude th at ex p o rt stru ctu re is m ore likely to change due to incom e and price shocks th an im p o rt structure.
Finally, we will show PPI and CPI equations as prices play an im p o rtan t role in the m odel.
Producer price index
ln Pppij = 1.63 4- 0.26 In + 0.14 In W , + 0.03 In Pfuel,t- 2 + 0-29 In Penergy 1 - 1 +
t-stat (5.96) (6.26) (3.22) (3.41) (6.13) + 0.003(i'L — A ln P CP/) ,_ 2 + 0.141n(l/S w£M>f_ 2) + d u m m i e s (3.72) (3.76) (15) R 2 = 0.99, SE E = 0.008, D -W = 1.93, B-G = 0.05[0.83], J -B = 0.43[0.81], A R C I I ( l) = 1.06[0.30], W IIIT E = 9.19[0.87], A D F = — 8.25[0.00], C H O W = 0.85[0.44], T P = 20% , sample 1 9 9 5 : 4 - 2 0 0 3 : 2 (31 obs.), where:
Pppi - p ro d u cer prices: indu stry, index num bers (1995 = 100): period averages, P o lan d , IF S , Line 96463...Z F...;
P% - im p o rt price, index 1995 = 100, calculated on the base o f regional im p o rt price indexes from E U 15, C E E C and RW , ow n calculations;
W - gross average wages in sector o f enterprises, P L N , G U S - Polish Statistical Office;
P f v e l - fuel pro d u cer prices, P oland, T ab le 13, G U S - Polish Statistical
Office Prices in the national economy,
Pe n e r g y - energy p roducer prices, P oland, T ab le 13, G U S - Polish
Statistical Office Prices in the national economy.
Consumer price index
ln Pcpi,t = —1.89 + 0.33 ln P ppi,t + 0.53 InP pooD.t + 0.11 In УСВр ,_ з +
t-stat (-7.32) (4.24) (9.77) (4.60) + 0.12 lnM2 t _ 3 — 0.0021ММ , + dummies (3.51) (-3.16) (16) Я 2 = 0.99, SE E — 0.003, D - ^ = 2 . 3 1 , B-G = 1.58[0.21], J -B = 1.02[0.60], A R C H ( 1) = 0.04[0.83], W H IT E = 12.85[0.38], A D F = — 5.78[0.00], T P = 57.14% , - sample 1997 :4 - 2003: 2 (23obs.),
where:
Pfood - f ° ° d prices, P oland, T ab le 23: consum er prices, G U S - Polish S tatistical Office Prices in the national economy.
W e can see th a t p ro d u cer prices are determ ined to a large extent by im p o rt prices (P%) and energy pro d u cer prices (Penercy)- T h e effects of wages (VF), fuel p ro d u cer prices (P FUel), and nom inal effective exchange rate (S NEER) are less pronounced. A positive influence o f the real lending interest ra te is highly significant.
C on su m er prices follow p roducer prices and are highly influenced by food prices (P Food)• T he incom e and m o netary effects are w eaker. It seems th a t co st factors played a d o m in an t role over m o n etary facto rs in the price setting m echanism in the period 1995-2003. T his is d u e to stru ctu ra l price changes th a t take place in the econom y as p a rt o f a tran sitio n process and E U pre-accession stru ctu ra l price adjustm ents.
F inally, statistical properties o f estim ated equation s should be considered. W e observe th a t all equations are economically relevant in term s o f coefficient signs an d posses good statistical properties. T h e R 2 coefficient is high, we d o n o t reject the null o f norm ality and in m ost cases no au to co rrelatio n and no heteroscedasticity o f residuals is present, while estim ates are stable over tim e. We should also p oint o u t a relatively high ability o f the m odel eq u atio n s to trace changes to tendency in endogenous variables as given by tu rn in g points statistic:
т р _ Щ А у М > О л A y , - A f t . , > 0 | A y M ^ O ) , m A < „ „ N i A y f i y , - ! < 0)
where Ay, and A y, den o te changes in endogenous variables у and their predictors ý, respectively. T h e T P statistic (e.g. W elfe and Brzeszczyński 2000) m easures a percentage o f a num ber o f m atch ed tu rn in g points to tendency in у and ý in a n u m b er o f all tu rn in g p o in ts in y.
Since the purpose o f our study is to evaluate econom ic effects o f financial shocks to interest rates and exchange rates o n th e perfo rm an ce o f the Polish econom y, in Section 3 we present sim ulation exercises.
3. FINANCIAL SHOCKS AND ECONOMIC GROWTH IN POLAND - SIMULATION RESULTS
In this section we give ex-post sim ulation results o f financial shocks in the period Q2, 1998 - Q4, 2002. We have studied three scenarios. Scenario 1 denotes a 5 pp. shock to a dom estic disco u n t interest ra te , Scenario 2 denotes a 10% shock to the exchange rate E U R /U S D , i.e. a depreciation o f th e eu ro ag ain st the dollar, and finally, in Scenario 3 we have p u t
a shock to a sh o rt-term E U interest rate by 5 pp. W e have applied b oth an im pulse and a sustained shock.
Before ru n n in g scenario analyzes, we carried o u t static and dynam ic base sim ulations on the m odel. We observed good fit to em pirical d ata and no significant differences betw een static and dynam ic sim ulations were o btain ed. T his stands for a p ro per dynam ic specification o f the m odel. T he e rro rs 3 are given in T ab le 2.
S im ulation results are given in graphs in A ppendix. In T ab le 3 we present m ultipliers in a sustained shock obtain ed in the three scenarios.
The analysis in Scenario 1 (cf. T able 3 and figures in A ppendix) has shown th a t a 5 pp. shock to a dom estic discount rate gives rise to an increase in the capital m a rk e t risk and in tu rn to an increase in m oney m ark e t an d lending rates. R ising interest rates give rise to a d ro p in m oney supply M l and М 2, which brings a nom inal appreciation o f the zloty. T his d ro p in e.g. P L N /U S D exchange rate is sharp enough to lower both im ports and exports expressed in US dollars. E x p o rts decreases m ore th an im ports and as a result we observe a d eterio ratio n o f the to tal trad e balance. H igher in terest rates bring also a significant d isinflation (as m easured by C PI) and a low er G D P inum e (via lower private consum ption and trade balance deficit), which in tu rn gives rise to an increase in unem ploym ent rate.
In general we can conclude th a t a 5 pp. positive sustained shock to a d isco u n t ra te gives rise in the end to a 5.39% app reciation o f P L N /E U R exchange rate, 2.38% ap preciation o f P L N /U S D exchange rate, 2.04% d isin flation in consum er prices and 2.58% decrease o f G D P . T h e unem p loym ent ra te goes up by roughly 0.8 pp.
N ow let as proceed to Scenario 2. We have p u t a 10% positive shock to E U R /U S D exchange rate. T he shock denotes a d epreciatio n o f the euro against the dollar. W e can see th a t this shock is ab so rb ed by the capital m a rk e t risk an d interest rates and dies ou t in those variables over the sam ple period. T h e shock influences directly the exchange ra te P L N /E U R and we observe its appreciation. T his, in tu rn , lowers exports, which in the end, via low er G D P , deteriorates the trad e balance. M oreow er, we observe disinflation in C PI prices and a higher un em ploym ent rate.
G enerally speaking, a depreciation o f the euro vs. the dollar is transm itted into the Polish econom y via the m onetary an d then a real channel. We can see th a t a sustained 10% positive E U R /U S D exchange ra te shock gives rise to a 5.31% appreciation o f P L N /E U R exchange rate and a very slight 0.12% ap p reciatio n o f P L N /U S D exchange rate. In the end C PI prices are lower by 0.41% and G D P goes dow n by 1.02% . In tu rn , the unem ploym ent ra te increases by 0.29 pp.
Table 2. Ex-post simulation errors
Variable
MAE RMSE MAPE (%) Theil TP (%)
static dynamic static dynamic static dynamic static dynamic static dynamic
Capital market risk 0.06 0.06 0.08 0.07 39.50 51.83 0.1112 0.1092 54.55 36.36
Real money supply M l 654.37 784.51 741.66 1067.87 1.12 1.37 0.0064 0.0092 25.00 25.00
Real money supply М2 1521.78 1590.46 1982.95 2141.35 1.00 1.04 0.0064 0.0069 60.00 80.00
Money market rate 0.54 0.49 0.67 0.61 3.51 3.25 0.0215 0.0194 33.33 33.33
Lending rate 0.30 0.54 0.44 0.67 1.66 2,98 0.0119 0.0183 50.00 100.00
Exchange rate PLN /U SD 0.05 0.05 0.06 0.06 1.26 1.31 0.0075 0.0077 63.64 27.27
Exchange rate PLN/EUR 0.03 0.05 0.05 0.06 0.87 1.16 0.0057 0.0076 66.67 66.67
NEER 0.77 1.11 0.89 1.39 0.95 1.38 0.0056 0.0086 85.71 71.43
CPI index 0.55 0.67 0.69 0.86 0.30 0.36 0.0019 0.0024 40.00 60.00
PPI index 0.71 0.75 0.85 0.89 0.46 0.50 0.0028 0.0029 25.00 50.00
Unemployment rate 0.14 0.31 0.18 0.36 1.00 2.21 0.0061 0.0124 33.33 66.67
F inally, let us analyze Scenario 3 in which we p u t a 5 pp. positive shock to a short-term EU interest rate. T his shock is tran sm itted into the Polish econom y directly th ro u g h the capital m ark et. 1 hen the shock feeds interest rates and exchange rates and is furth er tran sm itted into the real .sector. W e observe a d ro p in capital m ark et risk, which lowers b o th m oney m a rk e t and lending interest rates. Lower m oney m ark e t interest rate gives rise to an increase in m oney supplies M l and М 2. T h is results in higher exchange rates P L N /E U R and P L N /U S D which in tu rn b o o st exports and im prove the trad e balance. As a consequence, we observe G D P increase and a very m o d era te d ro p in unem ploym ent rate.
In general, we should note th a t a 5 pp. rise in E U interest rate lowers the capital m a rk e t risk by roughly 11 points. T h e m oney m ark et and lending rates d ro p by 0.44 and 0.35 pp., respectively. B oth exchange rates, i.e. P L N /E U R and P L N /U S D , increase by 0.44% and 0.19% , respectively, w hich m eans a nom inal depreciation. T his depreciation im proves the trade balance, which in turn gives rise to a slight G D P grow th by 0.21% . M oreover, we can see a rise in C PI prices by 0.16% and a very sm all d ro p in unem ploym ent rate by 0.06 pp.
W e conclude th a t the effects in Scenarios 2 and 3 (foreign) are m uch w eaker co m p ared to S cenario 1 (dom estic). M o reo v er, th e results in S cenario 1 arc opposite to Scenario 3 but in the form er they are m uch stronger.
4. CONCLUSIONS AND POLICY IMPLICATIONS
In this paper we have show n the estim ation and sim ulation results o f the q u arterly econom etric m odel. T he m odel has been positively verified in econom ic term s. T he estim ates o f the m odel tu rn ed o u t to be statis tically significant and stable over time. N o au to co rrelatio n and norm ality o f residuals has n o t been rejected and predictive pow er o f relations was relatively high. N o outliers in the static and dynam ic base sim ulations were observed.
In the sim ulation exercises we have focused on the three scenarios. In S cenario 1 we have applied a 5 pp. shock to a dom estic d iscou nt interest rate, S cenario 2 d enoted a 10% positive shock to th e exchange rate E U R /U S D , and finally, in Scenario 3 we have applied a shock to a short-term E U interest rate by 5 pp. W e have applied both impulse and sustained shocks.
T h e results have show n th a t dom estic m o n etary policy has a strong influence on the perform ance o f the Polish econom y as m easured by e.g. G D P incom e grow th and unem ploym ent rate.
Table 3. Multipliers in Scenario 1, 2 and 3 in a sustained shock
Variable Increase of domestic discount rate by 5 pp. Scenario 1
Increase o f EUR /U SD exchange rate by 10% Scenario 2
Increase o f EU interest rate by 5 pp. Scenario 3
Nominal money supply M l Nominal money supply М2 Exchange rate PLN/USD Exchange rate PLN/EUR NEER
CPI index PP1 index GDP
Capita] market risk Money market rate Lending rate Unemployment rate
1 year 2 years 3 years 4 years end of
period 1 year 2 years 3 years 4 years
end of
period 1 year 2 years 3 years 4 years
end of period Percent -8.71 -3.39 -2.28 -4.46 3.80 -1.19 -0.05 -1.80 -9.98 -4.48 -2.58 -5.32 4.56 -1.72 -0.47 -2.37 -10.31 -5.12 -2.42 -A.62 5.45 -1.96 -0.55 -2.40 -11.96 -5.34 -2.47 -4.87 5.26 -2.00 -0.57 -2.49 -12.92 -5.32 -2.38 -5.39 4.88 -2.04 -0.61 -2.58 -0.58 -0.33 -0.07 -5.30 3.92 -0.23 -0.53 -0.68 -0.75 -0.49 -0.11 -5.34 4.06 -0.32 -0.59 -0.88 -0.83 -0.59 -0.11 -4.56 4.76 -0.38 -0.62 -0.92 -0.95 -0.62 -0.10 -4.79 4.58 -0.39 -0.63 -0.92 -1.08 -0.65 -0.12 -5.31 4.26 -0.41 -0.65 -1.02 0.72 0.27 0.18 0.36 -0.29 0.09 0.00 0.14 0.83 0.36 0.20 0.43 -0.35 0.14 0.04 0.19 0.86 0.41 0.19 0.37 -0.42 0.16 0.04 0.19 1.00 0.43 0.20 0.39 -0.40 0.16 0.05 0.20 1.08 0.43 0.19 0.44 -0.37 0.16 0.05 0.21 Percentage points 0.1172 5.5589 3.9292 0.3258 0.1135 5.5695 4.4224 0.5928 0.1131 5.5674 4.4930 0.7145 0.1132 5.5672 4.5027 0.7608 0.1158 5.5703 4.5031 0.7636 -0.0009 -0.0001 0.0035 0.1459 -0.0007 -0.0001 0.0016 0.2239 -0.0010 -0.0010 0.0008 0.2679 -0.0011 -0.0018 0.0000 0.2833 0.0002 0.0007 0.0003 0.2892 -0.1133 -0.4362 -0.3083 -0.0058 -0.1130 -0.4370 -0.3470 -0.0469 -0.1129 -0.4368 -0.3525 -0.0566 -0.1130 -0.4368 -0.3533 -0.0603 -0.1132 -0.4370 -0.3533 -0.0605
W e have foun d th a t a 5 pp. sustained positive shock to a dom estic disco u n t ra te lowers G D P by 1.8% after a year and by 2.5% after 4 years and increases unem ploym ent rate by 0.3 pp. and 0.8 pp. respectively over the sam e perio d. T h e effects in Scenario 1 (dom estic) tu rn ed o u t to be m uch stro n g er th an in Scenario 2 and 3 (foreign).
W e have also found th a t e.g. a 10% dep reciation o f th e euro against the d o llar gives rise to an ap preciation o f the zloty against the euro by 4.8% afte r 4 years and against the do llar by 0.1% . T h is shock brings also a d ro p in G D P by 0.7% after a year and by 0.9% after 4 years, while an increase in unem ploym ent ra te is 0.3 pp. after 4 years.
T h e policy im plication would be to pursue an econom ic policy o f sm oothing the asym m etric shocks in Poland against th e E U 15 econom y as we m ight expect th a t large differentials in e.g. interest rates, inflation rates and incom e grow th rates affect the capital m a rk e t risk and exchange rates to a large extent. H ence, the stability o f the financial m a rk e t an d exchange rates is an im p o rta n t grow th factor o f the Polish econom y.
01400 0.1200 0.1000 0.0800 0.0600 0.0400 0.0200 - 0.0000 -0.0200 0.0060 0.0050 0.0040 0.0030 m 0 2 03 0, o s o 6 07 0 .o o o io o ,io i2 o ,3 o u o i5 o i6 0 i7 o J ^ о, 02 оз о. 05 об о, * о о о ю о — о н о ^ б о ^ е о , , о, 02 оз о , 05 os 07 o . os о м c m o tt0 4 o n o is tm o ,ro ,« o 4 --- . Г™«- . n . . . . __ . I Щ impulse □ sustained j
I impulse □ sustained | impulse □ sustained]
Fig. A l. Capital market beta risk
6.0000 5.0000 4.0000 3.0000 -2.0 0 0 0 - 1,0000- 0.0000-- 1.0 0 0 0 ' 0.0150 -0 .0050-[II __________________________ Q, 02 03 O* 05 06 07 08 09 0,0 01, 0120130,40,5 0,60,7018019 ' o l Q 2 0 3 Q * Q 5 06 Q7 0BQ9 0,00,,0,20,301.0,5 0 * 0 , ^ ^ ' 0, 02 03 O, 05 06 07 06 0 . 0,0 01,0,20,30«0 , 5 0 « 0 ^ 0 » r = “ --- r—-i ľ ľ ľ ~ ľ n I ■ imoulse П sustained
И impulse □ sustained | impulse □ sustained |
5.0000 4.5000 4.0000 3.5000 3.0000 2.5000 2.0000 1.5000 1.0000 0.5000 0.0000 Q1 Q2 Q3 04 Q5 Q6 07 08 09 010 011012Q13Q14Q15 Q16Q17018Q19 I impulse □ sustained 0,0060 0.0050 0.0040- 0.0030 - 0.0020 - 0 .0 0 1 0 - 0.0000 -0.0010 -0.0020 J U 01 02 03 04 05 06 07 06 09 010 011012013014015016 017018019 0.0000 -0.0500 -0.1000 -0.1500 -0.2000--0.2500 -0 ,3000-- 0.3500 - 0.4000 01 02 03 04 05 06 07 08 09 010 011012013014015016017018019
I impulse □ sustained I impulse □ sustained
Fig. A3. Lending rate
2 .00% 0,00% -2.00% - 4.00% -6 .00% - 8 .00%- -10,00% - -12.00% - - 14.00% 01 02 03 04 05 06 07 08 09 010 011012013014015 016017018019
I ■ impulse □ sustained I I И impulse □ sustained |
01 02 03 04 05 Q6 07 08 Q9 010 011012013QUQ15 016Q17Q18Q19 I impulse □ sustained I
0.00% - 1,0 0 % - - 2.00% - - 3.00% - - 4,00% - 5,00% - 6,00% Ц Ql 02 Q3 04 0 5 Q6 Q7 08 09 010 011012013014015 0 16017018019 I ■ impulse □ sustained I 0 . 10% 0,00% - 0,10% - Ш - - 0,30% - - 0,40% - - 0.50% - - 0,60% - - 0,70% * T J y i 01 0 2 0 3 04 05 06 07 08 09 Q10011012013 QUQ15Q16Q17Q18Q19 [~Й impulse □ sustained | 01 02 03 04 05 06 07 06 09 Q10 Q11Q12Q13Q14Q15Q16Q17Q18Q19 I impulse □ sustained I
Fig. A5. Money supply М2
0,50% 0,00% - 0.50%- - 1.00%- - 1,50% - 2,00% ■ - 2,50%- - 3,00% 01 02 03 04 0 5 06 07 08 09 010 011012013014015 0 16017018019 0,02% 0.00% - 0.02%- - 0.04% - -0 .06% - -0 .08% - -0.10% - -0.12%- -0 ,14% - 0,16%
-in
01 02 03 04 05 0 6 07 08 09 0Ю 011Q12Q13Q14Q15Q16Q17Q18Q19I impulse □ sustained 1 I impulse □ sustained
01 02 03 04 05 06 0 7 08 09 01001101 2 0 1 3 0 1 4 0 1 5 Q16Q17Q18Q19
I impulse □ sustained!
0,00% -1.00% - 2.00% - 3,00% -4 ,00% - 5,00% -6.00% 1.00% 0 .00% - 1.00% -2,00% - 3.00% - 4.00% - 5.00% -6 .00% Q1 0 2 0 3 0 4 0 5 0 6 Q7 0 8 0 9 ОЮ 011012013 Q14Q15 01 6 0170 18 01 9 01 0 2 0 3 0 4 05 0 6 07 08 0 9 Q10Q11Q12Q13Q14Q15Q16Q17Q18Q19 01 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 Ю Q11012Q13Q14Q15 Q16Q17Q18019
I impulse □ sustained I impulse □ sustained I И impulse □ sustained |
Fig. A 7. Exchange rate PLN/EUR
1.20% 1.00% - 0.80% - 0.60% - 0.40%- 0.20% 0.00% -0.20% - 0.40% -0 .60% - -0 ,80% - -1.00%
r n
01 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 Q100 1 1 0 1 2 0 1 3 0 1 4 0 1 5 Q16017Q18Q19 I impulse □ sustained 01 0 2 0 3 0 4 0 5 0 6 07 0 8 0 9 Q10Q11Q12Q13Q14Q15Q16Q17Q18Q19 [ ■ impulse □ sustained |ш * ,
01 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 Q10 Q11Q12Q13Q14Q15 Q16Q17Q18019 I ■ impulse □ sustained I2 .00% 1,50% 1.00% 0.50% 0.00% -0.50% - 1,00% - 1,50% - 2,00% - 2.50%
TFT
0.50% 0 .00% -0 .50% - 1.00% - 1.50% -2.00% - 2.50% - 3,00% - 3.50% - 4,00% -4 .50% - 5.00% Q1 Q2 0 3 О * 0 5 0 6 Q7 0 8 0 9 0 1 0 Q11Q12Q13Q14Q15 016Q17Q18Q19 01 0 2 0 3 0 4 0 5 0 6 Q7 0 8 0 9 Q10Q11Q12Q13Q14Q15Q16Q17Q18Q19I impulse □ sustained I impulse □ sustained I impulse □ sustained I
Fig. A9. Total exports to the world (in USD)
01 0 2 0 3 04 0 5 0 6 0 7 0 8 0 9 Q10 0 1 1012013 014015 01 6 Q17Q18 019 01 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 Q 1 0 01 10 12 0 1 3 0 1 4 0 1 5 0 1 6 0 1 7 0 1 8 0 1 9 01 0 2 0 3 04 0 5 0 6 0 7 0 8 0 9 Q10Q11Q12Q13Q14015Q16Q17Q18Q19
I impulse □ sustained I impulse □ sustained I impulse □ sustained I
01 02 03 04 05 06 Q7 08 09 Q10011Q12Q13Q14Q15Q16Q17018Q19 01 02 03 04 05 06 07 08 09 Q10 011Q12Q13Q14Q15Q16Q17Q18Q19 01 02 03 04 05 06 07 08 09 010Q11Q12Q13Q14Q15Q16Q17Q18Q19
I impulse □ sustained I impulse □ sustained I impulse □ sustained
Fig. A l l . Consumer price index
I impulse □ sustained I I impulse □ sustained | I impulse □ sustained I
0.50% 0 .00% - 0.50% - 1.00% ■ - 1.50% - - 2 .00% - - 2.50% 3,00% -F ljT I impulse □ sustained Q1 02 03 04 05 Об Q7 00 09 Q10 011012013 Q14Q15 016 Q1701B 019 01 02 03 04 05 06 07 OB 09 Q10 Q11Q12Q13Q14Q15Q16Q17Q18Q19 I impulse □ sustained 0 1 0 2 0 3 0 4 0 5 0 6 07 06 09 010 011Q12Q13Q14Q15 Q16Q17Q18Q19 [ 1 impulse □ sustained]
Fig. A 13. Gross domestic product
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Piotr Wdowiński
RYNKI FINANSOWE A WZROST GOSPODARCZY W POLSCE: ANALIZA SYMULACYJNA W OPARCIU O MODEL EKONOMETRYCZNY
(Streszczenie)
W artykule przedstawiliśmy analizę symulacyjną rozwoju gospodarki Polski w oparciu o kwartalny model ekonometryczny. Model ten składa się z 22 równań stochastycznych, które opisują związki rynku finansowego z sektorem realnym gospodarki. Celem badania jest zaprezentowanie wpływu zmian krajowych i zagranicznych stóp procentowych oraz kursu walutowego E U R /U SD na wzrost gospodarczy w Polsce w okresie Q2, 1993-Q2, 2003.
