MINSOO LEE, MUDZIVIRI NZIRAMASANGA,AND SUNG K. AHN
Transformation Strategy andEconomic Performance
Hungary and Poland
Minsoo Lee is senior lecturer in the Commerce Division of the Economics Depart-ment of Lincoln University, Canterbury, New Zealand. Mudziviri Nziramasanga isassociate professor in the Economics Department, College of Business and Econom-ics, Washington State University. Sung K. Ahn is professor of statistics in the Depart-ment of Management and Decision Sciences, Washington State University.
ABSTRACT: We use monthly time series data for Poland and Hungary toassess the impact of differences in the pace of implementation of economicreforms. The selected policy variables are a measure of reforms in both thedomestic and external sectors of the economy, and they also indicate the ini-tial level of distortions. We use impulse response analysis to measure the effectof changes in the interest rate, the exchange rate, and the share of exports tothe European Union on each other and on industrial production. Our resultsindicate that a faster rate of implementation results in a system that quicklyadjusts to a new equilibrium. The exception for Poland is the impact of theinterest rate on production, indicating that domestic reforms may not yet becomplete. Our results show that, when compared with Hungary, faster reformimplementation gives Poland more policy options in one sector with less de-stabilization in another.
Transition economies in Central and Eastern Europe have moved to a market-oriented economy; however, each country has its own unique policy mix, tran-sition strategy, and initial conditions. A key aspect of transition is the develop-ment of markets and market institutions.
26 EASTERN EUROPEAN ECONOMICS
Some believe that the correct approach is shock therapy (Sachs 1993),whereby the economy is liberalized at once and a tight monetary policy force-fully applied. Others argue for a slower and more deliberate method (Kornai1993), whereby markets are introduced gradually and the state control isallowed to coexist with market sectors. Aghion and Blanchard (1994) theo-retically analyze the pace of transition, arguing that the rapid restructuring ofstate firms may not be desirable and that in the initial phase of adjustmentpriority should be given to private-sector job creation.
Transition is a process entailing several tradeoffs between short-run costsand long-run benefits. Coricelli (1998) argues that policies and outcomesshould be assessed not only by short-term macroeconomic indicators butalso by their impact on the development of markets. Certain policies maysustain output growth in the short run but will hamper long-run growth. Forinstance, fast liberalization of the international sector may adversely affectoutput in the short run while still increasing the long-run growth potential ofthe economy. The short-run negative impact that liberalization of the inter-national sector has on growth can be explained either by a decline in com-petitiveness of domestic products or by an adverse change in the share offinal imported goods in favor of final consumption goods and against im-ports of intermediate inputs. Hoekman and Djankov (1997) show that thecomposition of imports from the European Union (EU) to Albania, Bulgaria,Hungary, Poland, and Romania for 1990 and 1995 increased while the shareof intermediate goods imports has decreased significantly (Hoekman andDjankov 1997: figure 1).
Many politicians in Eastern Europe argue that rapid economic reformcauses the disruption of the economy and leads to falling output (Lazear1995). Przeworski (1991) identifies unemployment as a main source of po-litical difficulties during the transition. The nonlinear path of output andunemployment determines the dynamics of political support. In his analy-sis, radical reform is characterized by a larger initial fall in output and ahigher unemployment rate; nevertheless, radical reform brings a faster re-covery than a gradual program. There is, however, little evidence to supportthis claim.
Most East European and Baltic countries share similar economic charac-teristics. They are equipped with a well-trained workforce and thus haverelatively high quality human capital stock considering the level of per capitaGDP (EBRD 1997). Poland and the Czech Republic have had the most suc-cessful experience in Eastern Europe during the past decade and have adoptedthe most rapid pace of economic reform. On the other hand, Hungary is anexample of how gradual economic reform can encourage growth.
JANUARY–FEBRUARY 2004 27
Role of Initial Conditions
Studies have used cross-country data to assess the impact of initial conditionson short-term as well as long-term growth prospects (for a comprehensivebibliography, see World Bank 1996). The World Bank (1996) classifies initialconditions into two groups. The first consists of initial distortions, includingfactors such as the existence of high black market rates, repressed inflation,and other policy effects associated with highly regulated economies. Thesecond group, termed initial institutions, measures the initial institutionalenvironment, such as familiarity with market mechanisms. This is measuredby the number of years under socialism. The World Bank studies find thatpolicy measures become dominant as reforms proceed. Countries with similarpolicies have similar growth paths regardless of the initial conditions and evenafter allowing for the possibility that policies might be endogenous and corre-lated with the initial institutional environment (World Bank 1996: 15).
Campos and Coricelli (2002) find that the level of internal liberalization atthe beginning of the transition and a membership in the Council for MutualEconomic Assistance (CMEA) explained 80 percent of the variance in thegrowth rate among East European countries. The former assigned a negativeweight to initial liberalization and a positive one to initial conditions. Eight oftheir measures are dummy variables that would be of little practical use in timeseries analysis of a single country. Their analysis is essential if we are to under-stand how initial conditions relate to degrees of distortion over time. Regressionresults also show that initial institutional differences explain 41 percent of thedifferences in growth among twenty-six countries in Eastern Europe, a notinsignificant share. In another study, de Melo, Denizer, and Gelb (1996) showthat the number of years of regional tension, another initial condition, is sig-nificant in explaining the initial contraction in output so common during thefirst five years of reform.
Cross-country results do not reflect the full effect of the interaction be-tween initial conditions and policy changes within a country and over time.They do not show the impact, for example, of the absence of market familiar-ity and a gradual reform process, or a big bang approach. This interaction canbest be captured through a time series approach and the use of impulse re-sponse analysis to reflect the effect of changes in the policy approach on thegrowth rate and the impact of the initial conditions. In the following analysiswe use measures that reflect both the initial distortions and institutional envi-ronment as defined by the World Bank.
We analyze and contrast two transition economies, Hungary and Poland,with regard to the impact of the reform strategy on the behavior of such macro
28 EASTERN EUROPEAN ECONOMICS
variables as the GDP growth rate, employment, exports, imports, and generalprice levels. The GDP in both economies fell by roughly 20 percent during theinitial phase of transformation. However, there were significant differences inthe timing and magnitude of the decline and recovery. In Hungary, the largestdecline came in 1991 and the turnaround in 1994. However, GDP in 1996 wasstill below the 1989 level. In Poland, the largest decline occurred in 1990 andthe turnaround began in 1992. By 1996, GDP was above the 1989 level. Maxi-mum declines in industrial output were 17 percent in Hungary and 29 percentin Poland. In each country the expansion of the service sector has mitigatedthe depressed performance of industry.
Likewise, there were differences in the price trends as measured by theconsumer price index (CPI). Poland used strict monetary controls to combatthe combination of repressed inflation and price-liberalization-induced openinflationary pressures. Hungary had freed its prices earlier and more gradu-ally over the years. It did not need shock therapy to bring inflation to man-ageable levels as additional prices were decontrolled. Over the transitionperiod, however, prices declined more rapidly in Poland. By 1995 it hadlower inflation rates.
Comparative trends in the unemployment rate show further importantsimilarities as well as differences in economic policies. One similarity isthat declines in employment have been considerably smaller than declines inGDP. Policy makers in Hungary have allowed unemployment to rise, andtheir policies on bankruptcy have probably contributed to the trend. The higherunemployment rate in Poland is explained in part by the rapid increase of newentrants into the labor force relative to the shrinking state sector.
If we use the black market premium to measure the level of external distor-tions, we find that Poland had more effective measures relative to Hungaryduring the initial years of reform. In 1988, the premium in Poland was 9.5times higher than that in Hungary. By 1989, it was only 1.4 times higher. Theblack market premium in Poland then declined by 94 percent during the firstfull year of reforms (1990) compared to about 27 percent for Hungary. Thepremium then declined monotonically in both countries and had disappearedby 1999.
Given the initial conditions we can conclude that the relative positions atthe end of 1996 were largely the result of the faster pace of implementation ofthe reform package in Poland.
In 1989 the reform-minded government in Hungary introduced a three-yearprogram of economic stabilization, whose key elements were tight monetaryand prudent fiscal policies, which meant a government budget close to balance;controls on wage increases in the state sector; and a modestly appreciating
JANUARY–FEBRUARY 2004 29
real exchange rate. Between 1989 and 1992, a number of key macroeconomicindicators—inflation rate, exports, the balance of payments, and the inflow offoreign investment—showed impressive improvements. Monetary and fiscalpolicy remained somewhat restrictive. Gross domestic savings remained con-stant in real terms.
The relative situations in both countries in 1989 are relevant in explainingperformance during 1990–96. As would be expected, Hungary was in a betterposition by virtue of its earlier start with the reform process. It was more out-ward oriented, as can be seen in the share of exports and total trade in GDP.However, the patterns of trade were similar. Almost 33 percent of Poland’sexports went to the former centrally planned economies and 51 percent toWestern Europe, compared with 34 percent and 50 percent, respectively, forHungary. By 1996 exports to the former centrally planned economies consti-tuted 21 percent of the total from each country but Hungary got there by amore circuitous route. By 1993, exports to Western Europe constituted 70percent of total Polish exports, compared to 53 percent for Hungary. Yet by1996, the two were almost equal—69 percent for Poland and 71 percent forHungary.
In 1989 the Polish economy was relatively more destabilized, as can beseen by the changes in the producer price index (PPI), the negative real inter-est rate, and higher general government balance. Wages grew faster than GDP,creating a monetary overhang, whereas the reverse was true in Hungary (deMelo, Denzier, and Gelb 1996). Nevertheless, by 1994 the liberalization in-dex was virtually the same in both countries (Hoekman and Djankov 1997).Hungary achieved a higher per capita GNP ($6,810 at 1989 prices) than Po-land ($5,150). Yet the average GNP growth rate was negative over the nextseven years (1990–97) in Hungary, as compared with a positive 3.9 percentin Poland. Part of the explanation can be found in the level of foreign directinvestment (FDI) (Lee and Tcha 2002). FDI was negligible in both countriesin 1989, but the 1996 level in Poland was more than double that in Hungary.
By 1992 domestic savings could not finance the growing budget deficit.The real interest rate became unusually high: the nominal rate was around30–35 percent, which the CPI temporarily stabilized around 20 percent, andthe PPI around 10 percent. This meant that businesses had to pay a 20 percentreal rate of interest, which constrained expansion and economic growth.
The transition in Poland began in January 1990. It involved freeing all buta small number of prices, allowing full internal convertibility of domestic cur-rency, eliminating all quantitative restrictions on imports and nearly all thoseon exports and setting some of the world’s lowest import tariffs. Lending rateswere raised sharply, as were bank reserve requirements. Once the immediate
crisis was past, the banks reverted to largely accommodating normal creditdemand at the normal rates.
Fiscal policy was intended to be restrictive and disinflationary, with de-clining government expenditures and sharp cuts in budget deficits. The ini-tial price liberalization brought a jump of more than 100 percent in CPI andPPI in 1990. Inflation then stabilized at between 2 percent and 3 percent permonth. By 1996 both producer prices and consumer price increases werebelow 20 percent annually.
Methodology and Data
Our basic premise is that the industrial production output (yt) in two transitioneconomies, Hungary and Poland, is related to three variables: the real effec-tive exchange rate (xt), real lending rates (rt), and the share of exports going tothe EU (mt). The share of exports going to the EU is a proxy for the initialinstitutional condition of market memory. The real effective exchange rate andindustrial productivity growth rate are related through the Balassa-Samuelsoneffect, which postulates that cross-country productivity differentials betweentradable and nontradable sectors will lead to changes in real costs and the priceof tradable goods relative to the nontradable goods. Real lending rates influenceindustrial production indirectly through the cost of capital. It would have beenideal to include the growth rate of imports of intermediate and capital goods toincorporate their impact on productivity and output. However, monthly data areavailable only for total imports, and the inclusion of imports of consumer goodswould distort the estimates. All of the above-mentioned variables are amongthose most affected by reform policies. To investigate the effects of the variableswe estimate the following empirical model:
∆yt = β0 + β1∆x t + β2 ∆rt + β3∆m t + ε t, (1)
where ∆ is the first difference operator.We utilize seasonally adjusted monthly data for Hungary, January 1993 to
December 2000, and for Poland, July 1993 to December 2000. In this respectwe face the problem of short time series familiar to those who study transitioneconomies; however, seven to ten years is enough to observe short-term changesalong the long-run trend. Industrial production, real effective exchange rate,lending rate, and CPI are from International Financial Statistics, September2002, and the share of exports going to the EU is from the Vienna Institute forInternational Economic Studies. Table 1 describes the means and standarddeviations of each time series.
JANUARY–FEBRUARY 2004 31
There are no monthly data on the black market premium or annual data forthe years 1991 through 1995. We assume that there is a close relationshipbetween declines in the premium just described and the observed gradual de-cline in the value of the local currency. This is a reasonable assumption giventhe fact that both currencies were overvalued at the beginning of the reforms.
First, we performed the augmented Dickey-Fuller (1979, 1981) test todetermine the order of integration of data of each time series. If we assumethat the data were generated from the AR(p) process,
,1∑
=−− ε+φ+α=
p
itititt YY
then we can rewrite the process in an error correction form,
∑−
=−−− ε+∆φ++α=∆
1
11
p
ititittt YcYY , (2)
where
The error correction form in the above is convenient because only one term,Yt – 1, is an integrated process of order one, I(1), under the unit root hypothesis,and the rest of the terms are stationary. The regression “t-ratio” of the estima-tor of c to its “standard error” from OLS regression of (2) is used to test thenull hypothesis of a unit root. For both Hungary and Poland, the test statisticsand the corresponding p-values of the variables in levels and in first differ-ences (Tables 2A and 2B) indicate that we cannot reject the null hypothesis ofa unit root in each series in levels. However, we reject the null hypothesis in
Table 1
Descriptive Statistics for Variables
Hungary Poland
Variable mean standard deviation mean standard deviation
y t 2.06 0.100 2.05 0.090x t 2.02 0.015 2.03 0.040r t 1.31 0.130 1.39 0.110mt 1.83 0.045 1.83 0.025
.1,...,1for)...(and1, 11
1 −=φ++φ−=φφ+−=−=∆ +=
− ∑ picYYY pii
p
iittt
32 EASTERN EUROPEAN ECONOMICS
each differenced series; that is, all variables are nonstationary in levels andstationary in first differences.
We further test the cointegration relationship among four variables basedon the maximal eigenvalue and trace statistic tests. We consider a four-dimensional VAR(p) model for Zt = (y t, xt, r t, m t) ′ ,
(3)
where δ is a 4 × 1 vector of constant term, Φi is a 4 × 4 matrix of parameters,and εt is a white noise with positive definite covariance matrix Σε.
We rewrite equation (3) as a vector error correction model (VECM) to ex-amine the existence of cointegration relation among the variables,
Table 2A
Augmented Dickey-Fuller Unit Root Tests (Hungary)
Level form First difference form
lag ADF test lag ADF testVariable length statistics P-values length statistics P-values
The long-run behavior of Zt is concentrated in the coefficient matrix Φ. If therank of Φ is zero, then each component of Zt is I(1). Insofar as there is no sta-tionary long-run equilibrium relationship among the variables, we use thestandard vector autoregressive (VAR) model without the second term in theright-hand side of equation (4) for the estimation. If the rank of Φ is four,then each component of Zt is stationary. If the rank of Φ is between zero and4, that is, 0 < r = rank(Φ) < 4, then Zt is cointegrated with cointegrating rank rand Φ contains the stationary long-run equilibrium information. Therefore, therank of the coefficient matrix Φ is examined for the long-run equilibrium infor-mation.
We need to determine the appropriate rank of the coefficient matrix Φ aswell as the AR order of the model. For both Hungary and Poland, we choosean appropriate AR order based on partial canonical correlation analysis (Ahnand Reinsel 1988), and AR(6) is chosen. We further choose the cointegratingrank of the four variables based on Johansen’s test of cointegration. Both maxi-mal eigenvalue and trace test statistics using the AR(6) model are summarizedin Tables 3A and 3B for Hungary and Poland, respectively. The null hypothesisthat the cointegrating rank is at most r is tested against an alternative that thecointegrating rank is four using the trace test statistic and against an alternativehyothesis that the cointegrating rank is r + 1 using the maximal eigenvaluestatistics. The cointegrating rank r is chosen as the smallest value among thevalues where the null hypothesis is not rejected. The critical values in Tables 3Aand 3B are for a level of significance of 0.05 and are taken from Johansen andJesulius (1990: Table A.1). Both maximal eigenvalue and trace tests indicatethat we fail to reject the null hypothesis of no cointegration among four vari-ables in both Hungary and Poland.
Therefore, we estimate a standard VAR model with first differenced seriesin the following model,
where Wt = Zt – Zt – 1, δ is a 4 × 1 vector of constant term, Φi is a 4 × 4 matrix of
(4)
(5)W Wt i t ii
t= + +−=
∑δ εΦ1
5
W Z Zt t t i i kk i
p
i
p
= − =− + =−−>=
∑∑1 41
, , , andΦ Ι Φ Φ Φ*
W Z Wt t i t ii
p
t= + + +− −=
−
∑δ εΦ Φ11
1* ,
34 EASTERN EUROPEAN ECONOMICS
parameters, and εt is a white noise with positive definite covariance matrix Σε.Parameter estimates are available upon request.
Impulse Response Analysis
The responses and interactions among the variables to an unpredicted policychange, which will lead to a new long-run equilibrium, are helpful in examining
*Critical values are from M. Osterwald-Lenum, “A Note with Quantiles of the AsymptoticDistribution of the Maximum Likelihood Cointegration Rank Test Statistics,” Oxford Bul-letin of Economics and Statistics 54: 461–72.
*Critical values are from M. Osterwald-Lenum, “A Note with Quantiles of the AsymptoticDistribution of the Maximum Likelihood Cointegration Rank Test Statistics,” Oxford Bul-letin of Economics and Statistics 54: 461–72.
JANUARY–FEBRUARY 2004 35
short-term macroeconomic fluctuations and long-run adjustment toward thenew equilibrium. Impulse response analysis of vector autoregressive systemsallows us to examine the interrelationships among the variables in dynamicmodels (Lütkepohl and Reimers 1992; Mellander, Vredin, and Warne 1992).We will trace the effects of a one standard-deviation shock to one of the inno-vations on current and future values of the variables.
To do this, we consider the stationary four-dimensional VAR model of equa-tion (5) and rewrite it as an infinite moving average (MA) representation
(6)
where ψ = I5 and
.for0with...,2,1,1∑ = − >=φ=φψ=ψ j
k iikj pkj
The (k, l) elements of the ψj represent the impulse response of the kth compo-nent of Zt to a unit change in the lth component of the shock εt, j time periodsafter the change occurred.
We will examine the orthogonalized impulse responses of the system, andthe errors are orthogonalized by Cholesky decomposition so that the covari-ance matrix of the resulting innovations is diagonal.
jtjjt eZ −
∞
=∑ Θ+µ=0
, (7)
where Θj = ψ j P, et = P–1εt, mtt IeeE =′)( , PP′ = Σε and P is assumed to be alower triangular matrix with positive diagonal elements. The elements of theΘj are impulse responses, and Lütkepohl and Reimers (1992) explain that aone-time impulse may have a permanent effect on the dynamic system, whichwill lead to a new long-run equilibrium.
Figures 1, 2, and 3 depict the impulse responses of industrial production inHungary and Poland to a one standard deviation shock in the share of exportsgoing to the EU, real lending rates, and real exchange rates, respectively. Fig-ure 4 shows the response of the share of total exports to the EU to a onestandard deviation shock to real lending rates. Although we use monthly data,we cover a long enough sample period to observe relatively long-term effects.
Generally the results for Poland show a quick dissipation of the response toan impulse for most of the variables. We can deduce that the economy with atransformation from shock therapy now adapts quickly to any disturbance. Onthe other hand, in Hungary the positive results of an external or internal shockseem to linger on even after four years. The amplitudes of responses of outputand the external sector to changes in the lending rate are larger and tend to
persist over a longer time in Hungary. Monetary effects do linger for a longerperiod than in Poland, in spite of the fact that the CPI and the lending rates inPoland in 1989 were much higher and more volatile than in Hungary. Distor-tions in the external sector, measured by the relative shares of exports to theEU, were similar. The lower rates in Hungary reflect a lesser degree of initialdistortions that can be attributed to previous attempts at partial reforms. Animplication of our results is that a reform strategy dominates the impact ofinitial distortions.
The results for Hungary show that the lending rate and inflation have alarger negative impact on the domestic sector than on exports. The impact ontotal production is almost double that on the share of exports to the EU, andthe gap is widening even after four years. The obvious explanation is that theimpact on the external sector is ameliorated by the response of the exchangerate to domestic inflation. In Poland these monetary effects on the externalsector are quickly dissipated. The impact on domestic production persistsafter four years but at a lower level than in Hungary. The external sectorreforms in both countries seem to be more complete than in the domesticsectors. The lingering response of output to changes in the interest rate isevidence of the incomplete domestic reforms. The magnitude is much greaterin Hungary, and we attribute this to the slower pace of reform.
Conclusion
The major concern for transition economies transforming from central plan-ning to a competitive market economy is how to create a successful marketeconomy. Economic analysis has largely covered the necessary componentsfor a successful market economy. However, relatively little research has beendone on the correct transition strategy, and on the pace and method of intro-ducing the necessary components to transition economies.
We examined the two most advanced transition economies with differenttransition strategies in Eastern Europe. We used time series techniques to dis-tinguish the outcomes on industrial output growth from two economies adopt-ing different transition strategies. To do this we selected variables that reflectedthe initial distortions within the two countries and were are also influenced bypolicy decisions. Our analysis indicates that, for Poland at least, a more rapidimplementation of reforms will yield a faster adjustment to the new long-runequilibrium industrial output; a more competitive sector, as measured by theresponse to export opportunities; and earlier price stability. The downside hasto do with a slower employment response. Results from the impulse responseanalysis further support the time trends. More aggressive policy implementation
JANUARY–FEBRUARY 2004 41
in Poland mitigated the negative effects on exports of the dissolution of theCMEA. Interest rate stability occurred sooner, and industrial performance wasbetter under Poland’s strategy.
The results indicate that a strategy involving faster reforms will over-whelm the effect of initial conditions. Poland’s economy had a greater levelof initial distortions than Hungary, but was able to stabilize much faster inthe case of the external sector and no less rapidly in the domestic sector. Thepolicy implications are that Poland can use monetary policy within reason tocurb domestic inflation, for example, without destabilizing the trade sectorfor a long period. As already stated, the partial reforms are such that theimpact of this monetary policy on output is likely to persist for a long timebecause of the incomplete domestic reforms in both countries. Likewise,Poland can use the real exchange rate to stimulate trade without unduly de-stabilizing the domestic nontradable sector. The same cannot be said forHungary. The country with a more market-oriented economy ends up withbetter policy control than one whose system is predicated on more interfer-ence in market outcomes.
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