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 182, 2004 A ntonin Rusek*
T O W A R D T H E M E M B E R S H IP IN T H E E U R O P E A N U N IO N :
P O L IS H E C O N O M IC P E R F O R M A N C E 1 9 9 3 -2 0 0 2
1. In trod u ction
The D ecem ber 2002 summ it o f the European Union (EU ) in C openhagen, D enm ark, closed a significant chapter in the m odem E uropean history. 10 Eastern and C entral European countries - Poland, H ungary, the Czech R epublic, Slovakia, Estonia, Latvia, Lithuania, Slovenia, M alta and the Greek part o f C yprus - were invited to join the European U nion. A ssum ing that conclusions o f the C openhagen summit are approved by all existing m em ber countries (w hich is expected) and by the candidate countries (w hich is expected as well), the EU expansion should form ally take place by M ay - June 2004.
The expected 2004 EU enlargem ent differs substantially from the previous ones - and, indeed, it is entirely different than the last enlargem ent in 1996. C ountries which jo in ed in 1996 (A ustria, Sweden and Finland) had the average G D P per capita above w hat was then the EU average. All three countries had a long tradition o f a functioning m arket econom y, their legal structures were alm ost identical to E U ’s and their m onetary and fiscal policies by and large conform ed to EU standards. Finland and A ustria joined E uro area from its inception in January 1999.
C ountries slated for 2004 entry are substantially different. T heir G D P per capita is only 44% o f to d ay ’s EU average. Except for the G reek part o f Cyprus and M alta, their m odern m arket econom y traditions are recent (post 1990) and their legal and adm inistrative structures and econom ic policies not only still differ relatively significantly from today’s EU standards, but often display persistent w eaknesses.
And, indeed, countries now invited to join EU are not hom ogenous. They differ am ong them selves in population and size, by the level o f econom ic developm ent and by econom ic dynam ics. Poland is a large country both size wise and population wise - bigger than all other invited countries together. The Czech R epublic and Hungary are o f a medium size (roughly 10 m illion people each), w hereas all other candidate countries are very small.
These differences notw ithstanding, future challenges are com m on to all “new ” EU countries. They are as follow s (N oyer 2001):
1) Real convergence, 2) Inflation developm ents,
3) M onetary and Exchange rate strategies, 4) C apital account liberalization,
5) Financial sector structure and functioning.
O f these, the real convergence is probably the m ost im portant, and, at the same time, probably the most difficult to ach iev e1.
The com m onality o f challenges, however, does not elim inate the fact that individual accession countries are different, with different past dynam ics and level o f perform ance. Therefore, their response to challenges will be necessarily different, reflecting the conditions and up to date achievem ents o f the each individual new entrant.
T hese differences imply that each country has to be analyzed individually. T his paper will concentrate on the econom ic perform ance o f Poland in the pre-accession period 1993-2002'.
The general overview o f the Polish econom y’s perform ance is provided in the next part. Part III then analyzes the factors determ ining the Polish econom ic grow th by using the V A R approach. Part IV concludes and provides some evaluations o f the Polish econom ic dilemmas.
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1 To quote Christian Noyer (2001): “Sustainable rates o f G DP growth will be the key challenge for accession countries in years, and even decades, to com e. [...] The degree o f real convergence with the Euro area, that is, the catching up o f the per capita incom e and price levels o f accession countries with those o f the euro area, has remained limited. [. . . ] The size o f the gap, com bined with the lim ited growth differentials, suggests that the process w ill be a very slow one [. . .]”.
2 The rationale behind the choice o f the period for the analysis is tw ofold. On the one side it is the availability o f data (pre 1993 data are not available in quarterly frequency in all instances). And, on the other side, the 1993 is the earliest when w e can consider Poland to be a functioning market econom y.
2. T h e Polish E con o m y 1 9 9 3 -2 0 0 2
T he dynam ics o f the Polish econom y in the period 1993-2002 is described in Tables 1 and 2.
T able 1 indicates that during the most o f this tim e the Polish econom y experienced rather rapid econom ic growth (certainly by European standards), albeit slow ing down after 2000. R egarding the real convergence to EU, the Polish econom ic grow th exceeded the EU average by more than 125% during the last ten years. H ow ever, the recent econom ic slow dow n - especially the grow th recession in 2001, when the Polish rate o f grow th was below EU average the first tim e in m ore than a decade - should be a reason for som e concern. On the other side, it should be noted that in the long run the Polish growth perform ance is clearly superior to the fellow accession countries H ungary and the C zech R epublic.
Table 1. Econom ic Growth in selected areas Real GDP: 1 9 9 3 -2 0 0 2
Year USA EU Japan Czech Poland Hungary
1993 2.7 - 0 .4 0.4 - 1 .0 3.8 - 0 .6 1994 4.0 2.8 1.0 2.6 5.2 2.9 1995 2.7 2.4 1.6 5.9 7.0 1.5 1996 3.6 1.6 3.5 4.8 6 .0 1.3 1997 4.4 2.5 1.8 - 1.0 6.8 4.6 1998 4.3 2.9 -1. 1 - 2 .2 4.8 4.9 1999 4.1 2.8 0.7 - 0 .3 4.1 4.2 2000 3.8 3.4 2.4 4.9 4.0 5.2 2001 0.3 1.5 0.1 3.3 1.0 3.8 20 0 2 (est.) 2.3 0.9 - 0 .6 2.3 2.5 2.5 Average 1 9 9 3 -2 0 0 2 3.22 2.04 0.98 1.95 4 .5 2 3.03
S o u r c e s : A ll data are in constant 1995 prices. Data for U S A , European Union (E U ) and Japan were obtained from EUR OSTAT Web page (http://europa.eu.int/com m /eurostat), part General statistics. Data for the Czech Republic, Poland and Hungary are from PLANECON REPORT, Developm ents in the E conom ies o f Central Europe and Russia, Data Supplement, V olum e X VIII, Number 18, Novem ber 2002.
M ore detailed inform ation about the Polish econom ic dynam ics in the 1993-2002 period is provided in Table 2.
As far as “accession challenges” other than the real convergence are concerned, the Polish perform ance is mixed. By 2001 the inflation was brought below 2% annually, well in line with the EU average. H ow ever, the budget deficit, reasonably under control till 2000, risen over 4% o f G D P annually in 2001 and 2002. D om estic debt is recently rising as well.
Equally m ixed were developm ents in the area o f productivity and labor markets. U nem ploym ent (historically always rather high in Poland) declined to ju st above 10% in 1998, but started to rise again subsequently. U nem ploym ent accelerated especially in 2001 and 2002, reaching 18.1% (w ell above the EU level) in 2002. H ow ever, w hereas the real wages were rising rather rapidly, 27% above its 1995 level in 2002, productivity in the sam e period increased yet faster (42% ). Increases in productivity may explain som e o f the recently rising unem ploym ent, but in the long run these bode very well for the Polish econom ic dynam ic, especially in the all important area o f a real convergence to EU. Finally, the Polish currency (zloty) appreciated by about 9% in real term s in 2002 com pared to 19953. H ow ever, this may actually entail very small if any loss o f international com petitiveness, given the overall productivity dynam ics.
Table 2. Poland Basic Indicators: 1 9 9 3 -2 0 0 2
Year G DP BS CU CA RINT REX INF PROD RW UNPL
1993 3.8 - 2 .0 - 2 .7 0.7 -3 .1 1.10 37.1 0 .9 6 0 .9 6 16.4 1994 5.2 -2 .1 - 1 .0 2.1 1.1 1.09 27.9 0.91 0.98 16.0 1995 7.0 - 1 .9 - 1 .8 2.4 3.0 1.00 19.0 1.00 1.00 14.9 1996 6.0 - 2 .0 - 1. 1 3. 8 6. 7 1.01 11.8 1.04 1.06 13.2 1997 6.8 - 1 .3 - 3 .7 4.2 8.5 1.01 11. 0 1.08 1.12 10.3 1998 4.8 - 1 .0 - 4 .3 6.9 7.1 0.98 4.9 1. 13 1. 15 10.4 1999 4.1 - 0 .8 - 7 .6 5.4 4.8 0.98 7.5 1.20 1.21 13.1 2000 4 .0 0.3 - 6 .2 4.8 7.5 0.85 5.5 1.29 1.22 15.1 2001 1.0 - 4 .2 - 4 .0 1.7 7.0 0.82 0.9 1.34 1.26 17.4 2002 (est.) 2.5 - 4 .5 - 3 .6 2.5 4.0 0.91 1.5 1.42 1.27 18.1 Va r i a b l e s :
GDP - annual rate o f growth o f real G DP in %, BS - ratio o f budget surplus to GDP in % (is deficit), CU - ratio o f current account surplus to G DP in % (is deficit), CA - ratio o f capital account surplus to G DP in %,
RINT - real interest rate (calculated as nominal interest rate m inus expected inflation,
REX - real exchange rate index (calculated as Zloty/Euro nominal exchange rate m ultiplied by the ratio o f EU and Polish producer price indexes and normalized to 1995),
INF - annual producer price inflation, PROD - productivity index (norm alized to 1995), RW - real w age index (norm alized to 1995), U N PL - unem ploym ent rate.
S o u r c e s : A ll data are in constant 1995 prices where relevant. Data w ere obtained from PLANEC ON REPORT, various issu es, 1995, 1996, 1998, 2 0 0 0 , 200 2 ; N ational Bank o f Poland W eb site, the Statistical O ffice o f Poland W eb site and the IM F’s International Financial Statistics.
3 Real exchange rate index is calculated as Zloty/Euro nominal exchange rate m ultiplied by the ratio o f EU and Polish producer price indexes and normalized to 1995.
D ynam ics o f real interest rates appears to be independent o f the growth perform ance o f GDP, indicating that the main targets o f Polish m onetary policy during the analyzed period rem ained inflation (and to a lesser degree the real exchange rate). C urrent account deficits increase when econom y accelerates. Finally, T able 2 indicates som e positive correlation betw een gross capital inflows and G D P growth.
Overall, Tables 1 and 2 indicate that in 1993-2002 period the Polish economic perform ance was reasonably good in many areas, albeit far from stellar.
H ow ever, to get a better understanding o f the factors determ ining the Polish econom ic perform ance in the last 10 years, a more detailed and form alized approach is necessary. Such an approach is provided in the next part.
3. D eterm in an ts o f th e Polish E conom ic (Jrow th
3.1. VAR Model
M acroeconom ic m odeling o f national and later international econom ies has a long tradition, going back to works o f Frisch and T inbergen before W W II. The purpose o f such a m odeling is threefold. On the basic level, any econom ic model strives to contribute to our knowledge of how an econom y w orks - both in general and in particular for individual econom ic structures. O ther tw o purposes o f the econom ic m odeling are more practical - to evaluate policy options and to forecast.
At present m acroeconom ic m odels in use range from sim ple ones (B ryant 1988, chapt. 2; K rugm an 1999) to very sophisticated ones which em ploy several thousands o f equations (FRB model, M IT-Penn). T he state o f art in econom ic and econom etric m odeling is well described by O bstfeld (2001), A rnon and Young (2002), H allet and M cA dam (1999) and others.
H ow ever, the em pirical use o f m acroeconom ic m odels to explain the actual econom ic dynam ics often encounters difficulties.
Even sim pliest m acrom odel requires several equations and a num ber o f variables w hich quickly exhausts the available degrees o f freedom , casting doubts on the reliability and hence the explanatory pow er o f estim ated coefficients. A stability o f underlying behavioral assum ptions is often doubtful as well, especially in em erging m arket econom ies. And, indeed, sim ple models require ex ante choices o f relationships to be included - in essence im posing an ex ante theoretical concept on the evolving reality.
All these issues becom e m agnified in the analysis o f the em erging m arket econom y like Poland. T he country ’s statistical data (even in the quarterly
frequency) are difficult to obtain prior to 1997. G oing back to 1993 is possible - but it still reduces the m axim um num ber o f available quarterly observations to 40. Given large structural changes observed during the transition from the central planning to m arket econom y, the basic structural relationships like money dem and functions cannot be reliably identified (R usek 2001). And, indeed, there is a larger question o f an appropriate theoretical structure for an em erging m arket econom y.
In those circum stances the vector autoregressive approach - VAR m odeling - constitutes an alternative. VAR model - often interpreted as a generalized reduced form - seeks statistical relationships which may ex ist am ong observed variables and provides an alternative structure to test hypothesis regarding the im pact o f changes o f som e variables on the dynam ics o f other variables in the system . As a such, VAR is a suitable approach for the investigation o f relationships betw een the governm ent econom ic policy and the extent o f econom ic activity and is used in this paper4.
VAR technique was developed in the late 7()’s as the alternative to the estimation o f large structural models. Christopher A. Sims (1980) pointed out that the m ajor advantage o f VAR approach is that it did not postulate often ad hoc formulated restrictions o f structural models, yet under relatively weak conditions it could be interpreted as a set o f reduced form equations “within which tests of economically meaningful hypothesis can be executed” . By im plication the VAR technique can be applied in situations where no structural model exists.
Technically speaking, VAR model is the set o f linear dynam ic equations, w here each variable is specified as a function of equal num ber o f lags o f itself and all other variables in the system. The lag structure is considered a proxy designed to account for the role o f expectational dynam ics, adjustm ent and transaction costs and persistent random shock disturbances (K eating 1990).
All variables in the model are treated as endogenous. T he set o f hypothesis testable by V A R m odels is, however, rather limited. N evertheless, it is sufficient for the purpose o f this paper. To begin with, the V A R approach can be interpreted as a m ultivariate version o f G ranger-Sim s causality tests, used to determ ine the causality structure am ong variables. T his, however,’ has its lim itations. M ost o f VAR practitioners use the approach to analyze th e ’response o f the system to a particular initial shock and to infer from there the im pact o f the dynam ics o f individual variables on the historical evolution o f system , using variance decom position and impulse response functions (both discussed later in the context o f em pirical results).
The use o f VA R m odeling as a tool o f the econom ic inquiry is. indeed, somewhat controversial. Darnell and Evans (1990) criticize its atheoretical nature and argue that by lim iting itself to analysis o f statistical correlations without specifying an underlying theoretical structure, VAR does not advance our understanding o f how and why an econom y works.
The purpose o f this paper is to model the historical dynam ics o f the Polish econom y - i.e. the relationship betw een the econom ic policy stance, exogenous (w orld econom y) variables and the dynam ism o f econom ic activity.
An periods lagged, the four variables VAR model is specified:
1)
GDP, = Cons+
£ a ™pGDPM + Z t f DPBSl4 + Zy™ PRI,4 + S 8 ° w’C l/f_1 + u?DP
/=1 /»I /«I /= i
BS,
= Cons + la ^ G D P ,., + I ß ? 5 BS,., + 2 y f s RI,4 + 1 S ? S C U
, . x+ и "
/»i /*i /«i i=i
RI, = Cons + t
a?' GDP,_, + £ ß" BS,_, + t y f Rl,_, + £ 8f' CU ,_x + u f
1=1 1=1 /= 1 /= 1
2
)3)
4) CU, = Cons + X a f u GDP,4 + t ^ B S , . , + t y f u RI,_, + £ s с,и C U + u ™
i=i i = t i = i <=i
w here G D P stands for the real gross dom estic product, the BS stands for the real budget surplus (negative is a budget deficit), RI is the real interest rate and CU is ^ ^ t h e real current account surplus (negative indicates a current account deficit).
u j , j = G D P, BS, RI, CU, are random errors.
T he choice o f variables in this model stems from several considerations. On fiscal policy side the budget surplus (or its negative, the budget deficit) best reflects the com bined im pact o f governm ent spending and taxation on the aggregate dem and.
As far as m onetary policy is concerned, several m onetary and m onetary policy related variables w ere tested ( Ml , М 3, m onetary base, various nominal and real interest rates). H ow ever, given the large structural changes associated with the econom ic transition a stable dem and for m oney is difficult to determ ine for any m onetary aggregate (this characteristic is com m on to alm ost all em erging m arkets). And, indeed, the nominal interest rate over 10 years period reflects m ore the dynam ics o f inflation and inflationary expectations rather than the m onetary policy itself. G iven all these considerations, the real interest rate is the best indicator o f the m onetary policy stance.
The choice o f G D P as the indicator o f an overall econom ic activity is self- explanatory, even if it limits the usable data frequency to quarterly observations.
Several variables may reflect the im pact o f the rest o f the w orld on the Polish econom y. Econom ic dynam ics o f the dom inant trade partner - EU - define the foreign dem and for the Polish output. The real exchange rate reflects the Polish international com petitiveness. And balance o f paym ents elem ents - current account and/or capital inflow - determ ine the availability o f resources beyond dom estic constraints.
All these variables w ere tested in the m odel, but only one - current account - was found statistically significant.
Data used in the estim ation were acquired from the Plan Econ R eports and from the Polish N ational B ank and the Polish Statistical O ffice Internet pages. All data are real based on the 1995 price level and en ter the model in quarterly frequency and in levels5. Both D ickey-Fuller and augm ented D ickey-Fuller tests indicate the absence o f unit roots for all variables except the real GDP. The estim ation period covers the interval between IQ 1993 and 4Q 2002. N um ber o f lags in the estim ation procedure was determ ined by likelihood ratio tests as 4.
3.2. F^stimation Results
The first results inferred directly from the estim ation o f the VAR model are generalized Granger-Sim s causality tests. The Table 3 reports F-statistics and their marginal significance levels constructed under the null hypothesis that the lagged values o f coefficients on a given variable in each equation are jointly zero.
Table 3. Multivariate Granger Causalities (F-Tests)
F-Tests, D ependent Variable R1 Variable F-Statistic S ign if
BS 1.7920 0 .1 7 6 9 9 3 8
Rl 7.0045 0 .0 0 1 5 9 8 4
CU 0 .6 9 2 0 0.607 5 9 5 5
GDP 1.9338 0.1 5 0 9 6 4 8
F-Tests, Dependent Variable GDP Variable F-Statistic S ign if
BS 2.4937 0 .0 8 1 8 4 2 5
Rl 2.0301 0 .1 3 5 6 3 1 0
CU 3.2343 0 .0 3 8 0 7 5 2
GDP 11.4470 0 .0 0 0 1 0 8 2
F-Tests, Dependent Variable BS Variable F-Statistic S ign if
BS 1.7936 0 .1 7 6 6 7 0 6
Rl 0 .5 8 0 3 0.68 0 9 5 6 9
CU 1.6642 0 .2 0 4 4 6 8 4
GDP 5 .4 6 6 4 0 .0051238
F-Tests, Dependent Variable CU Variable F-Statistic Sign if
BS 0.6223 0.652 8 6 9 2
Rl 1.4434 0 .2 6 2 8 0 7 0
CU 1.1805 0 .3 5 4 5 3 0 4
GDP 0 .3 1 7 6 0 .8 6 2 2 4 2 9
S o u r c e : Own calculations.
5 The use o f log levels is precluded by the fact that budget surplus (B S) has both positive and negative observations.
N one o f the variables G ranger causes either CU o r RL Budget surplus BS is caused by the G D P dynam ics. However, there is no detectable G ranger causality from BS to GDP. Finally, the hypothesis that CU G ranger causes G N P cannot be rejected at the conventional 5% significance level, even if there is no detectable G ranger causality from G D P to CU.
Inferences from F-tests, indicative about the structure o f relationships am ong variables as they are, have only a limited validity. G enerally speaking, even if the hypothesis that x G ranger causes у is rejected for the i-th equation, x still can influence у indirectly, through other equations in the system.
T o gain better insights into the dynam ic properties o f the estim ated VAR model, the responses o f the system to particular initial shocks can be analyzed by using variance decom position technique and im pulse response functions. Both techniques require a triangularization of variance-covariance m atrix of residuals, lest possible contem poraneous correlations am ong innovations distort the true im pact o f shock in one variable on others. (Sim s, 1980). This was achieved via C holeski factorization6.
The variance decom position m easures the percentage share o f each particular shock to the one step ahead forecast errors variance o f dependent variable. H ence, it provides an indication o f how relatively im portant individual shocks are in determ ining the variations o f a variable. T he variance decom position was calculated over 8 periods ahead for each variable and results are reported in T able 4. It show s several interesting results.
W hereas o ver 60% o f the forecast erro r in G D P is exp lain ed by its own innovations in the short term (2 periods), this share drops to 35% o ver longer term (8 periods). T he im pact o f innovations in BS on G D P ’s forecast error rem ains rath er sm all throughout (13.5% in 5 th period and below 11% in the period 8). T he im pact o f R I’s innovations on G D P ’s forecast e rro r rem ains rather sm all as w ell, reaching ju st above 7% in the period 8. F inally, the im pact o f innovations in CU on the G D P dynam ics rises to alm ost 50% in period 3 and then d eclines som ew hat subsequently, but rem ains at 47% after 8 periods.
A lm ost 75% o f variance decom position for BS series is determ ined by its own innovations after 3 periods, but it subsequently declines to ju st above 42% after 8 periods. T he im pact o f G D P and Rl rem ains rather smal even after 8 periods - 12.3% and 7,5% respectively. However, the im pact o f CU, smal at the beginning, risis to alm ost 40% after 8 periods.
6 The results o f both variance decom position and impulse response function are sensitive to the variable ordering in the estim ation when Choleski factorization is used. Various orderings were tried and no substantial differences in results were found. The results reported in this paper correspond to the ordering indicated by 1-4).
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CN Table 4. D ecom p osition o f Variance
D ecom p osition o f Variance for Series BS Decom position o f Variance for Series Rl
Step Std Error BS Rl CU G DP Step Std Error BS Rl CU G DP
1 114.0541861 100.00000 0.0 0 0 0 0 0 .0 0 0 0 0 0 .0 0 0 0 0 1 0 .9 7 9 5 7 6 1 0 3 10.39162 89.60838 0 .0 0 0 0 0 0 .0 0 0 0 0 2 1 47.7511102 7 6 .9 6 7 4 5 1.35909 10.36349 11.30996 2 1.645835831 14.71192 82.01741 1.42640 1.84426 3 1 5 0 .1 1 0 2 3 1 6 7 4 .9 5 3 9 0 3.73263 10.35607 10 .95740 3 1.906003519 14.95192 74.10122 5.11308 5.83 3 7 7 4 182.9 1 1 6 9 3 9 52.96661 2.87991 3 6 .1 2 8 1 0 8 .0 2 5 3 8 4 2 .1 2 4 1 6 3 9 5 9 24 .8 9 6 5 8 62.26549 4.35 4 2 5 8.48368 5 184.9414401 5 1 .8 1 3 9 5 3.94 4 5 5 3 5 .6 8 3 1 5 8.55 8 3 5 5 2 .3 1 0 9 0 1 2 3 8 3 4 .3 2 6 0 4 52.76472 3.67898 9 .2 3 0 2 6 6 192.8814581 4 8 .0 6 5 5 3 3 .6 2 7 1 9 3 5 .1 6 5 9 4 13.14134 6 2 .4 0 0 7 6 6 9 3 4 3 5 .8 6 6 9 0 49 .0 4 6 3 8 4.72 1 0 8 10.36563 7 2 0 2 .0 3 9 7 9 4 4 4 3 .9 3 4 9 5 4 .6 3 9 2 9 3 9 .2 5 3 7 4 12.17202 7 2 .4 7 6 7 9 4 3 4 4 3 3 .8 5 5 7 2 46 .4 7 6 9 2 7.39149 12.27587 8 206.0 5 6 8 8 2 1 4 2 .2 7 4 2 6 7 .4 1 0 5 7 3 8 .0 1 8 2 0 1 2 .29696 8 2.540439771 32 .4 6 3 9 8 44 .2 2 2 2 8 10.06882 13.24493
D ecom p osition o f Variance for Series CU D ecom position o f Variance for Series G DP
Step Std Error BSQ Rl CU G DP Step Std Error BS Rl CU GDP
1 0 .8 5 3 8 6 8 3 3 0 0 .4 9 3 1 7 2.28168 9 7 .2 2 5 1 5 0 .0 0 0 0 0 1 0.653037691 7 .7 5 8 1 0 2.1 3 8 0 6 9 .2 6 5 8 6 8 0 .8 3 7 9 8 2 1.003308232 7 .3 7 9 4 6 11.02368 8 1 .5 8 8 2 8 0 .0 0 8 5 7 2 0 .7 7 8 8 5 1 9 5 0 6 .1 2 7 2 6 2 .6 5 5 1 8 29 .9 1 1 2 8 61 .3 0 6 2 8 3 1.113 1 0 4 2 9 0 10 .8 2 9 2 0 10.09805 7 7 .9 5 9 8 0 1.11295 3 0 .9 4 2 4 2 6 8 1 3 4 .8 1 8 2 5 3.67 2 2 5 4 9 .6 1 0 3 4 41 .8 9 9 1 5 4 1 .219994106 9.0 1 5 8 5 8 .6 3 8 5 0 80 .9 4 1 2 2 1.40442 4 0.976306631 4 .8 2 7 3 3 3 .8 1 0 0 8 5 2 .0 7 6 5 5 39 .2 8 6 0 3 5 1.240608657 8 .7 2 1 6 8 9 .4 1 3 3 4 80 .5 0 1 3 9 1.36359 5 1.271707230 13.51361 2.26 0 6 3 36 .3 2 4 1 5 47 .90161 6 1.281043473 8 .6 3 7 0 6 11.77025 7 8 .2 0 7 8 2 1.38487 6 1.370450402 12.27880 1.96339 4 0 .87221 4 4 .8 8 5 6 0 7 1.360550705 12.65694 13.21337 69 .7 2 9 7 3 4 .3 9 9 9 7 7 1.524016218 11.08943 4 .3 3 2 9 8 4 8 .2 8 0 5 9 3 6 .2 9 7 0 0 8 1.411648065 14.51295 14.36447 6 4 .8 0 8 6 8 6 .3 1 3 9 0 8 1.559344581 10.83799 7 .1 0 4 5 6 4 6 .9 9 3 4 9 3 5 .0 6 3 9 5 A n to n in R u se k
R esponses to Shock in BS R esponses to Shock in Rl Entry BS Rl CU G DP Entry BS Rl CU GDP 1 114.0541 - 0 .3 1 5 7 - 0 .0 5 9 9 - 0 .1 8 1 8 1 0 .0 0 0 0 0.9 2 7 2 0 .1 2 8 9 0 .0 9 5 4 2 - 6 1 .5 9 4 9 -0 .5 4 6 6 - 0 .2 6 5 8 - 0 .0 6 3 9 2 17.2248 1.1669 0.3071 0.0 8 3 5 3 9 .3 3 4 2 -0 .3 8 0 3 - 0 .2 4 4 7 -0 .0 7 5 0 3 -2 3 .3 3 1 9 0.6857 0.1 1 8 9 0 .1 2 8 4 4 -2 8 .8 3 4 8 -0 .7 6 1 6 0 .0 0 4 0 - 0 .0 5 6 7 4 -1 1 .0 6 5 4 0.3427 - 0 .0 5 8 8 0.0608 5 - 1 .1 0 7 2 -0 .8 4 2 4 0 .0 0 6 7 - 0 .4 1 5 3 5 -1 9 .6 3 7 8 0.0911 - 0 .1 2 7 7 0 .0155 6 12.6429 - 0 .4 8 3 8 0 .0 8 6 6 - 0 .1 0 9 8 6 0.5 1 3 8 -0 .0 9 5 4 -0 .2 1 9 7 0 .0 1 5 5 7 7.2343 -0 .0 9 8 1 0 .3 0 4 2 -0 .1 6 4 1 7 23.3 3 0 8 - 0 .1 5 5 7 -0 .2 2 6 7 0.2 5 2 5 8 -3 .8 9 0 5 0 .1 3 5 2 0 .2 3 4 3 - 0 .0 7 7 2 8 35.3938 - 0 .0 5 3 8 -0 .2 0 4 0 0.2 6 8 5
R esponses to Shock in C U Responses to Shock in GDP
Entry BS Rl CU G DP Entry BS Rl C U G DP 1 0 .0 0 0 0 0 .0 0 0 0 0 .8 4 1 9 -0 .1 9 8 7 1 0 .0 0 0 0 0 .0 0 0 0 0.0 0 0 0 0.5871 2 ^ 7 .5 6 4 5 0.1965 0.3 3 5 3 -0 .3 7 6 7 2 49.6891 0.2 2 3 5 -0 .0 0 9 2 0.1 6 4 7 3 8.4 3 5 0 0.3835 0 .3 8 0 3 - 0 .5 0 9 0 3 0 .1 7 6 4 0 .4 0 2 4 -0 .1 1 7 0 -0 .0 1 5 6 4 - 9 8 .7 6 0 9 0.1035 0 .4 8 8 6 -0 .2 3 6 1 4 -1 4 .6 9 6 4 0.4133 - 0 .0 8 4 3 0 .0 4 8 2 5 -1 0 .8 4 2 5 0.0005 0.1851 -0 .3 0 1 7 5 15.5632 0 .3 3 1 8 -0 .0 0 9 1 0 .6 3 2 6 6 -2 9 .6 3 1 8 -0 .2 7 5 0 0 .2 1 0 8 -0 .4 2 4 4 6 44 .2 9 1 8 0 .3 2 3 2 - 0 .0 4 1 7 0 .2 6 1 3 7 - 5 4 .2 2 6 6 - 0 .4 2 5 8 0 .0 8 5 5 -0 .5 9 4 7 7 8.9231 0 .3 9 4 4 - 0 .2 4 2 3 -0 .0 0 5 6 8 -1 0 .9 0 4 5 -0 .4 4 3 1 0 .0 2 6 6 - 0 .1 4 5 9 8 -1 5 .8 9 3 1 0 .3 1 8 9 -0 .2 1 0 6 0.0 9 7 7 T o w a rd th e Mem be rsh ip in th e E u ro p ea n U n io n .
Alm ost 65% o f variations in CU is explained by ow n innovations after 8 periods. The role o f other variables never exceeds 15%. T hese results confirm the results from F-test (m ultivariate G range C ausality) reported above - namely that the current account CU is exogenous. That is, current account dynam ics do not react to either changes in dom estic econom ic dynam ics or to changes in m onetary policy stance (i.e. changes in real interest rate R l) or to changes in fiscal policy, m easured by the budget surplus BS.
Almost 75% o f the forecast error in Rl is explained by own innovations over short term (3 periods). H ow ever, this share declines rather fast. It is only 44.22% after the period 8, w hereas the share o f BS innovations rise to over 35% after 6 periods. This im plies the sensitivity o f the m onetary policy to the inflationary potential o f a fiscal expansion stance in a longer term.
O ver all, the variance decom positions indicate that fiscal policy (BS), m onetary policy (R l) and capital account (CU) appear to be independent on G D P perform ance. M onetary policy (R l) responds to a fiscal stance (B S) in the long run, as does the fiscal surplus to current account dynam ics. And whereas neither fiscal policy (BS) nor m onetary policy (R l) have a detectable im pact on the econom ic dynam ic (G D P) the current account dynam ics im pacts G D P very strongly.
Lastly, the im pulse response function (Tab. 5) show s responses o f the system to the one period standard deviation shock in single variable. The results show negative im pact o f the shock to BS (reduction in budget deficit) on the Rl - confirm ing that m onetary policy reacts to the inflationary potential o f a fiscal expansion. But, perhaps m ore im portantly, there is a significantly negative impact o f a shock in CU on the G D P dynam ics - i.e. the im provem ent in current account reduces G D P and vice versa. M oreover, this shock appears to have a protracted im pact, dam pening very slowly even after 8 period s7.
4. Final rem arks
Several findings em erged from the analysis in this paper. Polish econom ic perform ance in the 1993-2002 period was mostly driven by internal factors. In addition, it was positively influenced by capital inflows w hich financed current
7 In evaluating results reported in Tab. 5 it is important to keep in mind the statistical significance and relative importance derived from F-test and variance decom position. Therefore only relevant results are reported in the text whereas Table 5 provides a full information about the estimation output, including numbers which are statistically insignificant (i.e. the hypothesis that those numbers are in reality zero cannot be rejected at 5% significance).
account deficits. On the other side the fiscal position (budget surpluses and/or deficits) and the m onetary stance (real interest rates) had no identifiable impact the on econom ic growth.
This dynam ics im plies that for the Polish econom y, the way ahead - even inside the EU - will be com plicated.
High real interest rates are the m ajor tool the Polish m onetary policy uses to bring dow n inflation to EU level, to stabilize the nom inal exchange rate (the latter is required by the Polish intention to jo in the E uro area), and to counteract possible inflationary im pulses stem m ing from an expansion o f budget deficits. These high real interest rates did not seem to deter dom estic econom ic grow th in the past.
However, the rising budget deficits in the last tw o years are the cause for concern. They do not contribute to econom ic grow th, but in 2001 and 2002 budget deficits exceeded 4%. This certainly forms a serious obstacle for Poland to join the Euro area.
C urrent acco unt deficits (financed by capital inflow s) ap p ear to be exogenous in a sense that they are not determ ined by the ob serv able dom estic econom ic dynam ics. B ut these deficits - or rather the capital inflow s used to finance them - app ear to be an im portant elem ent driving the econom ic grow th.
But this again raises the question o f a real convergence and the grow th oriented dom estic econom ic policies. Rusek (1996) dem onstrated clearly that with an open capital account a fiscal policy in general cannot be used as the engine o f an econom ic growth. M onetary policy is a successful tool o f nominal convergence and cannot play the dual role.
Feasible grow th oriented policy in the future is tw ofold. On the one side it is a preservation o f capital inflows - with no financial crisis such inflow s often lead to. That im plies the adoption of Euro at the earliest.
On the other side it is a com bination o f policies prom oting the dom estic savings and investm ents, expansion o f m arkets on m icrolevels and expansion o f education, research and developm ent.
But this is only a conjecture. Indeed, the m ore research in the area is needed.
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Antonin Rusek
DĄŻENIE DO C Z Ł O N K O S T W A W UNII EURO PEJSK IE J: D O Ś W IA D C Z E N IA PO LSK IE J G O S P O D A R K I LAT 1 9 9 3 -2 0 0 2
Kraje przystępujące ostatnio do Unii Europejskiej, wśród których znajduje się Polska, różnią się m iędzy sob ą pod w zględem liczby ludności, poziom u rozwoju ekonom iczn ego, jak i jego dynamiki. Polska jest najw iększym spośród tych krajów, zarówno pod w zględem powierzchni jak i liczby ludności. C elem artykułu jest próba określenia sytuacji ekonom icznej Polski w okresie przedakcesyjnym, tj. w latach 1 9 9 3 -2 0 0 2 na tle Unii Europejskiej jako całości, U SA , Japonii, Czech i Węgier.
A naliza czynników określających rozwój gospodarczy Polski zostala przeprowadzona przy zastosow aniu m odeli VA R. W części końcowej wskazuje się czynniki sprzyjające, jak i utrudniające w ejście Polski do unii monetarnej.
