Chapter

10 Disinflation in Transition Economies: The Role of Relative Price Adjustment

Author(s):
Carlo Cottarelli, and Gyorgy Szapary
Published Date:
July 1998
Share
  • ShareShare
Show Summary Details
Author(s)
Sharmini Coorey, Mauro Mecagni and Erik Offerdal 

Although most of the former centrally planned economies experienced very high rates of inflation at the beginning of their transition, many have succeeded in lowering inflation to intermediate levels of about 20-40 percent a year. However, there has been limited success in reducing inflation to relatively low levels, say, in the single-digit ranges.1 In some cases, inflation has declined to low monthly rates, but these reductions have, so far, rarely been sustained.

Are there features special to transition economies that constrain the rapid achievement of low inflation? In particular, does inflation in these economies reflect the ongoing adjustment of relative prices—a necessary aspect of the transition to a market economy—or does it stem from the traditional factors of insufficiently tight financial policies and wage pressures? This paper attempts to answer these questions by analyzing the empirical evidence relating to the determinants of inflation in a group of 21 transition economies. It considers whether relative price adjustments take place over a prolonged period—even following rapid liberalization—and contribute to a period of moderate inflation, perhaps initially through an increase in velocity and, depending on exchange rate policy, over time through an increase in the money supply via the balance of payments. Some factors that could underlie the marked real appreciation experienced by many transition economies are also examined.

If relative price adjustments are important, it would suggest, other things being equal, a worsening of any short-run trade-off—if one exists—between reducing inflation and increasing growth compared with a situation without significant relative price shocks. For a given relative price increase, rapid disinflation would be associated with greater output loss to the extent that economic agents (whose prices have not increased) resist the downward adjustment of their own prices. In these circumstances, the downward adjustment would normally be forced through unemployment and recession or, in fast-growing economies, through a temporary slowdown in the rate of growth. Because greater relative price variability is associated with structural transformation, an important additional consideration applies to transition economies: in view of the potential short-term conflict between relative price adjustment and disinflation, it is necessary to ensure that achievement of low inflation does not come at the cost of delaying structural reforms. If it does, the apparent reduction in inflation is likely to be short lived, as the economic pressures in partially reformed economies spill over to renewed bouts of inflation—for instance, because artificially low prices for public services require unsustainable fiscal subsidies.

The paper is organized as follows. The second section briefly reviews the literature on the determinants of inflation, particularly that relating relative price variability to overall inflation, and provides a broad analytical framework for the subsequent empirical work. The third section analyzes the characteristics of the distribution of price changes in 21 transition economies using disaggregated data for the consumer price index (CPI) to obtain some insight into the relationship between relative price variability and inflation.2 The results of econometric estimates of a semireduced-form inflation model using panel data for the 21 countries are examined in the next section, while the penultimate section takes a closer look at some issues related to relative price adjustment in five countries—Czech Republic, Estonia, Moldova, Poland, and Russia—selected to cover a range of progress with regard to stabilization and structural reform as well as different policy regimes. The concluding section summarizes the main findings of the paper and draws policy implications for the design of disinflation programs in transition economies.

Review of the Literature and Analytical Framework

The literature suggests four broad groups of variables that could explain the stickiness of inflation in transition economies after the initial monetary overhang has been dissipated: money growth fueled by fiscal obligations, often reflecting delayed structural reforms; wage increases out of line with productivity gains; underlying pressures for an appreciation of the real exchange rate coupled with a policy of stabilizing the nominal exchange rate; and relative price adjustment combined with downward price rigidities or, more generally, asymmetric price responses. The last three variables may be associated with unanticipated capital inflows and endogenous money growth through the balance of payments.

Fiscal Obligations and Money Growth

At the beginning of the transition, most centrally planned economies faced both a stock and a flow macroeconomic disequilibrium. The former took the form of a monetary overhang that dissipated relatively quickly following an initial burst of inflation when prices were liberalized. The flow disequilibrium—mainly due to the monetization of explicit and implicit fiscal obligations—however, has been a driving force behind the persistence of inflation in many countries (Bruno, 1993; Fischer, Sahay, and Vegh, 1996). The weakening of the ability to expropriate enterprise surpluses and the collapse in output often contributed to a sharp decline in government revenue, while subsidies and transfer payments increased. In many cases, fiscal deficits were financed through bank borrowing; however, even when these deficits were relatively small, banking system credit to public enterprises often increased sharply and fueled rapid money growth. Indeed, in transition economies, the measured fiscal deficit vastly understates the true extent of fiscal obligations, which mainly arise from unreformed institutional relationships, particularly with regard to public enterprises and the banking system (Dornbusch, 1992; McKinnon, 1992).

An additional variable influencing the persistence of inflation even when some degree of monetary control has been established is the credibility of the fiscal adjustment, which could contribute to shifts in velocity. Public perceptions of the sustainability of a fiscal and credit tightening are influenced by, for example, progress on fiscal reform—particularly social safety net and pension reform and the adoption of an inflation-resilient tax system—public enterprise restructuring and privatization, and the health of the banking system (Bruno, 1993).

Wage Pressures

Wage policies can contribute to the stickiness of inflation in several ways. First, wage increases in excess of productivity gains can directly place upward pressure on prices. Second, higher wage bills are often responsible for the expansion of credit, and hence money, to state enterprises and to the government (Sahay and Vegh, 1995). Third, explicit or implicit wage indexation can contribute to significant inflation inertia. Fourth, the lack of relative wage flexibility at both the sectoral and the enterprise level can raise the output cost of reducing inflation and weaken the eventual economic recovery, thus making continued inflation a more politically acceptable alternative (Edwards, 1992). Although the empirical evidence is mixed on whether exogenous wage increases have driven inflation in transition economies, there are indications that large wage increases in reaction to an initial inflation shock have sustained and fueled inflationary pressure in a number of countries (Citrin and Lahiri, 1995; and Pujol and Griffiths, Chapter 9 in this volume).3

Real Exchange Rate Appreciation and Capital Inflows

Many transition economies have experienced strong upward pressure on their real exchange rates.4 However, real appreciation can have a positive or negative impact on inflation depending on the exchange rate regime. On the one hand, in countries that maintain a relatively stable nominal exchange rate, real appreciation would be accompanied by capital inflows, monetary expansion, and a higher rate of inflation than that of trading partners. On the other hand, in countries with flexible exchange rates, real appreciation would be associated with nominal appreciation and downward pressure on the overall rate of inflation. The literature identifies at least three factors that could lead to real appreciation during transition.

(1) Initial undervaluation of the real exchange rate relative to its equilibrium level. In transition economies, undervaluation usually arises when the nominal exchange rate of new currencies is initially set at excessively low levels (often to minimize risks to competitiveness or international reserves) or when the nominal exchange rate is influenced by temporary distortions in asset markets.5 Undervaluation may be manifested in different ways: first, the domestic prices of tradable goods may be lower than comparable goods in world markets because the arbitrage of traded goods prices takes place only gradually.6 Second, even after traded goods prices have equalized, real product wages may be lower than indicated by labor productivity in traded goods; these low wages would also be reflected in prices of services that are lower than in countries with comparable levels of per capita GDP adjusted for purchasing power parity.7 Evidence of very low prices of services has been found for Russia (De Masi and Koen, 1995) and the Baltics (Richards and Tersman, 1995). Although undervaluation is likely to has been significant in the early years of the transition (Saavalainen, 1995), there is little clear-cut evidence that it persists several years after liberalization, particularly when international differences in productivity in traded goods are taken into account.

(2) Differential productivity growth between the tradables and nontradables sectors (Balassa, 1964; Samuelson, 1964): higher productivity growth in tradables relative to nontradables may raise real wages and lead to an increase in the prices of nontradables relative to tradables and, hence, to a real appreciation. Although such productivity growth differentials have been observed in market economies,8 and suggested for the Baltic countries (Richards and Tersman, 1995), hard empirical evidence for transition economies is scant. Moreover, it is unclear whether productivity growth differentials in favor of tradables should be expected in transition economies given that productivity gains in the relatively underdeveloped service sector (for example, financial services, communications, and retailing and wholesaling) could be substantial during transition.

(3) Demand pressures associated with a perceived shift to a higher level of permanent income: the move to market-determined prices may increase permanent income in transition economies; while potential output takes time to expand, private consumption may adjust more rapidly through external borrowing. Similarly, an increase in investment financed by foreign savings may temporarily raise the demand for domestic resources.9 These increases in domestic absorption could give rise to a temporary appreciation of the equilibrium real exchange rate during transition. However, increases in private consumption or the fiscal deficit in excess of levels that would be supported by a higher permanent income could give rise to excessive real appreciation and capital inflows that would eventually be reversed.

Relative Price Adjustment

Since price liberalization and structural reform in transition economies continue to cause the realignment of relative prices, under what conditions could this realignment, as reflected by relative price variability, contribute systematically to inflation?

Theoretical Approach

Classical theory suggests that while in the long run inflation is determined by nominal money growth, relative price adjustment reflects real factors and would not affect the increase in overall prices. However, the empirical association in market economies between inflation and relative price variability—which can be measured in different ways—has been noted since the 1920s. The theoretical basis for this association is quite varied, particularly with regard to the implied direction of causality between inflation and variability—an important consideration for empirical work.

Approaches where causality runs from relative price variability to inflation are based on assumptions of downward price inflexibility (Fischer, 1981, 1982;Frenkel and Giavazzi, 1982) or some other type of cost to adjusting prices. Ball and Mankiw (1995) show rigorously that if firms face a cost to adjusting prices (“menu costs”), a skewed distribution of relative price shocks—such as occurred during the OPEC shocks—results in an increase in the overall price level. Large shocks have a disproportionate effect on the price level because firms adjust to large shocks, but not to small shocks, when price adjustment is costly. In transition economies, the adjustment of relative prices to a new market-determined structure can be interpreted as a series of skewed real sectoral shocks that, when combined with menu costs and, over time, an accommodative monetary policy stance can lead to higher inflation.10Ball and Mankiw (1994) also show that with trend inflation and menu costs, a higher variance of relative price shocks results in an increase in the price level because shocks that raise firms’ desired prices trigger larger price responses than shocks that lower desired prices. This is because trend inflation causes firms’ relative prices to decline automatically between adjustments; hence, positive shocks are more likely to induce price adjustment than negative shocks, and the positive adjustments that occur are larger than the negative adjustments.

Another approach—widely used in empirical work as the basis for regressing relative price variance on inflation—comprises stochastic rational expectations models with imperfect information where agents cannot distinguish between general and relative price changes (Lucas, 1973; Barro, 1976; Hercowitz, 1981). Normality in the distribution of goods prices is important to the derivation of results from these models. However, Cukierman (1979) has pointed out that the interpretation of the direction of causality as running from inflation to relative price variability is erroneous: the direction of causality is in fact ambiguous because the variance of relative price changes and the unanticipated change in inflation (as well as the time variance of inflation) are determined simultaneously and depend on the variance of unanticipated aggregate and relative demand shocks.

Models where inflation or unexpected inflation causes relative price variability generally assume that inflation is exogenous. Sheshinski and Weiss (1977) show that when firms face menu costs, higher inflation leads to higher nominal price adjustments in each period. If the timing of price adjustments among firms is independent, higher inflation results in higher relative price variance because not all firms raise their prices simultaneously. Ball and Mankiw (1994) note that price setting is likely to be staggered within rather than between sectors, so that staggered adjustment cannot explain why inflation is associated with relative price variability at the sectoral level. Also, in these models, the change in relative prices is temporary because all firms eventually adjust their prices to restore the previous configuration of relative prices. In transition economies, the administrative costs of adjusting prices of public services (for example, rents, utilities, and transport) have a similar effect—in terms of making prices sticky—as menu costs. Thus, when inflation rises, relative price variance could increase because administered prices are not immediately adjusted in line with market conditions.

These analytical approaches to the relationship between inflation and relative price variability have two implications for empirical work. First, although much of the existing empirical evidence is based on simple bivariate correlations between inflation and relative price variability the association between the two variables needs to be considered in a multivariate setting that controls for aggregate shocks. Second, because causality can, in principle, run in either direction, it is important to examine the factors underlying increases in relative price variability.11

Evidence from Transition Economies

What does the existing empirical evidence suggest about the link between relative price adjustment and inflation in transition economies? Evidence for Russia and Kazakhstan confirms that price liberalization entails a measured increase in the variability of relative prices (De Broeck, De Masi, and Koen, 1995; and De Masi and Koen, 1995). Notably, in Russia, although price variability subsided following a relatively rapid and comprehensive initial liberalization, it persisted at high levels in comparison with market economies. In addition, in both countries, variability is positively associated with inflation (and changes in inflation), although this finding is based on a simple correlation that does not control for common shocks to both variables. In Poland, monthly inflation is highly correlated with the standard deviation and skewness of the distribution of sectoral price changes (see Chapter 9 in this volume). In addition, skewness is shown to capture lasting relative price changes that appear to have contributed significantly to Polish inflation from 1989 to mid-1995.

The persistence of relative price variability in transition economies following even comprehensive initial price liberalization could be explained in terms of the unavoidably limited speed of structural reforms and the changing structure of output and demand associated with the gradual move to a market economy Another explanation, which also has implications for the appreciation of the real exchange rate, is the cost-recovery hypothesis, which argues that the adjustment of certain capital-intensive prices of services (housing, utilities, and transport) must take place more gradually than the adjustment of other prices, particularly tradables, which are subject to international competition (Zavoico, 1995; Saavalainen, 1995). These services are distinguished by a capital stock that not only was inherited, with little or no associated debt, from the pretransition era, but also is large relative to the per capita income of these countries, adjusted for purchasing power parity. Initially when consumer wage levels are low, such service prices would be set to cover only current costs, even in a fully liberalized environment, because there are no associated debt-service costs. Maintenance costs may not be covered because it is optimal initially to consume the excessively large capital stock. As real incomes rise and the capital stock that can be supported by these incomes also rises,12 the prices of these services will be raised, at first to cover maintenance costs and then to cover (future) capital costs, until they reach a level at which new investment can take place.

The gradual nature of the capital stock adjustment and cost-recovery process suggests that some service prices will continue to adjust over several years following even comprehensive price liberalization.13 It also implies that price levels in such economies would be lower than indicated by international comparisons of GDP adjusted for purchasing power parity, not due to undervaluation, but because of the pricing of capital.14 Thus, the real exchange rate may also be expected to appreciate more steeply as real incomes rise (and the prices of these services are increased to permit new investment) than may normally be expected for market economies.15 Any attempt to bring about a more immediate adjustment in the relative prices of cost-recovery items—if successful—is likely to entail a substantial contraction in demand or—if unsuccessful—higher inflation.

Empirical Evidence on Relative Price Behavior

The preceding discussion suggests that the shape of the distribution of individual inflation rates of goods and services comprising a price index can provide important insights into factors underlying the relationship between inflation and relative price adjustment. This section, therefore, briefly reviews the main results of a detailed analysis16 of the characteristics of the inflation distributions (based on the CPIs) of the 21 transition economies included in the study.17 The sample of quarterly CPI data covers 1991-92 to the third quarter of 1995 for most countries and typically has a level of disaggregation varying from 10 to 70 categories of goods and services (Table A1).

The analysis was based on four indicators characterizing the sample distributions of individual price changes, weighted by their contribution to the CPI or unweighted, for each time period and country. The results are broadly in line with findings for market economies and indicate that

  • the sample distributions tend to shift substantially over time within countries, indicating the presence of substantial relative price changes throughout the transition period—even well beyond comprehensive initial liberalization. This finding was confirmed by the lack of significant time persistence, in all but a few cases, in the different relative price variability measures.18 The evidence also suggests variations in the degree and nature of relative price adjustment across countries.19

  • the distributions also show frequent and significant departures from both normality and symmetry, providing prima facie evidence against a Barro-Lucas-type model where inflation and relative price variance are determined simultaneously. The rate of rejection of normality and symmetry increases noticeably for weighted price changes, indicating that the weighting system exerts a significant influence on asymmetry.

  • when asymmetry prevails, the direction of skewness is frequently positive. Thus, a small number of large relative price increases led the inflationary process and coexisted with a large number of small relative price reductions. This is consistent with real relative price shocks and asymmetric price responses a la Ball and Mankiw, suggesting a direction of causality from relative price variability to inflation (Table 1).

  • a decomposition of variance indicates that most (some 65-75 percent on average) of the total variation in relative prices stems from within tradables, and to a lesser extent (about 15-25 percent) from within nontradables; the contribution from variance between tradables prices and nontradables prices is relatively minor.20

Table 1.Share of Total Sample of Quarterly Observations with Positive Skewness(In percent)
Region/CountryUnweighted Commodity Price ChangesWeighted Commodity Price Changes
Share of total sample skewedOf which, positively skewedShare of total sample skewedOf which, positively skewed
Eastern and Central Europe
Albania73829379
Bulgaria386391100
Czech Republic68857993
Hungary32676892
Poland91908695
Romania1009310093
Slovak Republic87468083
Slovenia81546370
Baltics
Estonia777092100
Latvia92759275
Lithuania9210010092
Commonwealth of Independent States
Armenia3610010091
Azerbaijan100100100100
Belarus87100100100
Georgia431008667
Kazakhstan748610090
Kyrgyz Republic100100100100
Moldova80929386
Russia10093100100
Ukraine769288100
Uzbekistan8310083100
Source: Authors’ estimates.

In addition, in keeping with the literature, the relationship between the average inflation rate and various indicators of relative price variability was examined on a country-by-country basis.21 The main result is that the empirical relationship between inflation and relative price adjustment could be sensitive to the choice of variability indicator, particularly between variance and skewness, suggesting that both measures of relative price variability should be included in the panel regressions. While variance appears to be somewhat positively correlated with inflation, skewness in the distribution of price changes appears to be only weakly associated with the level of inflation, although when significant, it too tends to be positively correlated.22

Empirical Evidence on the Determinants of Inflation

What light does an econometric analysis shed on the sources of inflationary pressure in transition economies? This section discusses the underlying methodology and results of such an analysis for a panel of 21 transition economies. These regressions are intended to capture the impact on inflation of relative price adjustments, including those giving rise to real appreciation, when aggregate nominal shocks such as money and nominal wage growth are controlled for.

The Model for Inflation

The factors explaining inflation discussed in the second section were brought together in a simple, static two-sector model of traded and nontraded goods and money market clearing to derive and interpret an estimated equation for inflation.23 Dynamics were not included because the limited time coverage of the data (on average about 12 quarters a country) permits the estimation of only short-run (mainly within-quarter) effects, with no distinction made between short- and long-run parameters. A semireduced form for inflation was selected for estimation rather than a reduced-form version because of the relevance of the regressors, particularly the real exchange rate, to the policy debate. The specification selected for estimation can be expressed as

and,

γ2>0; γ3>0; γ4<0; γ5>0,

where the γ’s are functions of the structural parameters of the model.24

Estimation Methodology25

With the dependent variable defined as the quarterly end-of-period inflation rate, on the basis of the above equation, the specification initially included (1) the lagged inflation rate, to account for inflation inertia; (2) the growth rate of broad money, both contemporaneous and with up to a two-quarter lag; (3) an indicator of labor cost pressure (unit labor cost growth, when available, or nominal wage growth), both contemporaneous and with a one-quarter lag;26 (4) an indicator of real exchange rate behavior (the differential growth of nontraded and traded goods prices), both contemporaneous and with a one-quarter lag;27 and (5) indicators of relative price adjustment (the Theil variance and skewness). Additive dummies were included to control seasonal effects. The differential impact of the exchange rate regime on inflation was tested through additive and multiplicative dummies (on both the inflation inertia and the real exchange rate terms) for countries and periods where the exchange rate was used as an explicit nominal anchor.28

The equations were estimated by ordinary least squares with corrections for the bias in standard errors (and hence t-statistics) caused by heteroscedasticity, as indicated by diagnostic tests.29 Using a “general to specific” modeling strategy, a more parsimonious final equation was derived from a larger initial set of explanatory variables following a specification search that eliminated statistically insignificant regressors in order of least significance. The final specification estimates were then tested for robustness to different definitions of the most important regressors: liquidity and relative price variance.

On the basis of evidence of parameter instability across regions,30 three regional specifications were estimated separately for Eastern Europe, the Baltics, and the CIS, respectively (Table 2). The robustness of the estimated coefficients was assessed by reestimating the regional specifications by weighted least squares. In addition, the sensitivity of the results to changes in the sample period was examined by reestimating the regional specifications for Eastern Europe and the Baltics, excluding the initial period of liberalization.31 Because consumer expenditure weights can give a distorted view of the relative importance of certain sectors (public services, for instance, tend to have a very small weight in the CPI of many transition economies), the sensitivity of the results to unweighted indicators of relative price variability was also examined.32

Table 2.Sensitivity to Specification of Regional Subsamples(OLS-HCSE estimates; dependent variable: quarterly CPI inflation rate)
VariablePooled SampleEastern and Central EuropeBalticsCommonwealth of Independent States
Constant13.800.926.6443.27
(2.35)**(0.58)(2.07)**(2.41)**
Money growth0.260.05-0.020.24
(2.94)***(0.24)(-0.23)(2.12)**
Money growth, lagged one quarter0.380.520.290.37
(4.08)***(2.16)**(3.53)***(3.21)***
Money growth, lagged two quarters0.090.100.060.08
(1.78)*(0.771(0.87)11.451
Variance of relative prices10.040.030.020.04
(6.54)***(8.82)***(1.86)*(3.24)***
Outlier dummy1,517.31,495.22
(89.15)***(62.16)***
Seasonal dummiesSome significantNot significantSome significantAll significant
R2 corrected0.920.520.600.92
F-statistics (zero slopes)380.4***20.04***7.93***149.51***
Breusch-Pagan test for heteroscedasticity101.49***95.87***1.8836.23***
White test for heteroscedasticity174.68***101.72***78.76***
Jarque-Bera test for normality of residuals3,780.98***169.85***7.67**176.17***
Number of observations26012233105
Source: Authors’ estimates.Note: For the t-statistics reported in parentheses, three asterisks indicate statistical significance at the 1 percent level, two asterisks at the 5 percent level, and one asterisk at the 10 percent (level). A dash indicates that the variable was not included because of lack of significance in the specification search. OLS-HCSE refers to correction of bias in ordinary least squares standard errors and t-statistics using a heteroscedasticity-consistent variance-covariance estimator.

To address potential simultaneity problems, the final regional specifications were reestimated using instrumental variables for the current money and wage growth terms (the real exchange rate appears only as a lagged variable). Available instruments (limited by data availability) were very poorly correlated with the two relative price variability terms. (As noted above, variance and skewness tend to show little time persistence, and so lagged values did not perform well). However, the discussion in the preceding sections suggests that the most likely source of possible simultaneity bias—attributable to causality running from inflation and relative price variability—arises from the presence of price-controlled items in the CPI.33 Hence, the variance and skewness terms were recalculated only on the basket of liberalized goods, excluding price-controlled items to the extent possible.34 The instrumental variable estimation of the regional equations was carried out substituting these new terms for the two contemporaneous relative price variability indicators.

Estimation Results

The specification search yielded equations with high explanatory power (an adjusted R2 of over 0.9 for the pooled sample of 21 countries and the CIS and about 0.7 for the other two regions) and significant, and generally plausible, parameter estimates (Table 3).35 Variations in inflation in the post-liberalization period in Eastern Europe and the Baltics proved more difficult to capture and the corresponding equations have somewhat lower explanatory power (an adjusted R2 of 0.5-0.6). The estimations for all three regions were robust to the correction of standard errors for bias caused by heteroscedasticity and to reestimation using weighted least squares.36 The results for Eastern Europe and the Baltics were generally robust to estimation by instrumental variables, although the statistical significance—but not the size—of the coefficient on wage growth tended to diminish. For the CIS, the coefficient on wage growth increased somewhat and that on money growth became statistically insignificant, although the sum of the coefficients on current and lagged money growth remained similar. This tendency for statistical significance to diminish while coefficient estimates remain roughly unchanged may reflect the quality of the instruments. The difficulty in instrumenting for these variables may itself reflect the exogenous nature of nominal wage shocks in Eastern Europe and money growth, stemming from discretionary credit expansion, in the CIS.

Table 3.Final Specification: Pooled and Regional Estimates(Dependent variable; quarterly CPI inflation rate)
VariableEastern and Central EuropeBalticsCommonwealth of Independent States
Pooled SampleFull samplePost-liberalizationFull samplePost-liberalization
OLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSE
Constant13.800.361.181.564.1857.71
(2.35)**(0.29)(1.24)(0.96)(4.80)***(3.61)***
Multiplicative dummy for exchange rate anchor effects on inflation inertia-0.150.03
(-1.44)(0.26)
Inflation rate, lagged0.230.410.250.09
(3.30)***(4.68)***(3.27)***(1.36)
Money growth0.260.20
(2.94)***(2.14)**
Money growth, lagged one quarter0.380.320.210.320.230.30
(4.08)***(2.29)**(1.99)**(3.82)***(4.77)***(2.94)***
Money growth, lagged two quarters0.09
(1.78)*
Nominal wage growth0.210.130.21
(3.21)***(1.91)*(2.34)**
Nominal wage growth, lagged one quarter0.08-0.01
(2.72)***(-0.15)
Real exchange rate change, lagged one quarter-0.15-0.26
(2.08)**(-5.19)***
Variance of relative prices10.040.020.01
(6.54)***(5.65)***(0.57)
Skewness of relative prices10.900.89
(2.59)***(2.93)***
Skewness of relative prices, lagged one quarter15.40

(1.96)
*
Seasonal dummiesSome significantSome significant
Outlier dummy1,517.31,489.27
(89.15)***(82.19)***
R2 corrected0.920.660.580.730.530.94
F-statistics (zero slopes)380.4***34.07***20.50***30.05***12.04**187.46***
Breusch-Pagan test for heteroscedasticity101.49***105.59***75.50***5.95*9.55***37.18***
White test for heteroscedasticity174.68***80.60***53.36**9.506.2577.11***
Jarque-Bera test for normality of residuals3,780.98***407.26***91.84***0.668.84**52.72***
Number of observations2601221003331105
Source: Authors’ estimates.Note: For the t-statistics reported in parentheses, three asterisks indicate statistical significance at the 1 percent level, two asterisks at the 5 percent level, and one asterisk at the 10 percent level. A dash indicates that the variable was not included because of lack of significance in the specification search. OLS-HCSE refers to correction of bias in ordinary least squares standard errors and t-statistics using a heteroscedasticiry-consistent variance-covariance estimator.

The specification search also revealed collinearity between nominal wage growth and relative price variance in the pool and the CIS bloc (the correlation coefficient in the two samples is almost 0.8), so that both terms could not be individually significant at the same time. Although the pooled sample results are driven mainly by the CIS, the procedure followed in the specification search resulted in the elimination of the wage cost term from the pooled sample (and the retention of the Theil variance) and vice versa for the CIS, Hence, alternative specifications were derived retaining the wage term in the pool but eliminating it in the CIS (Table 4).

Table 4.Relative Price Indicators: Alternative Specifications in Pooled Sample and the Commonwealth of Independent States(Dependent variable; quarterly CPI inflation rate)
Pooled SampleCommon wealth of Independent States
Final specificationAlternative specification: including nominal wage growth1Final specificationAlternative specification: excluding nominal wage growth2
Constant13.8017.4757.5159.80
(2.35)**(2.79)***(3.61)***(3.24)***
Additive dummy for exchange rate anchors-5.64
(-2.19)**
Money growth0.260.40.200.23
(2.94)***(3.05)***(2.14)**(2.03)**
Money growth, lagged one quarter0.380.320.300.40
(4.08)***(4.10)***(2.94)***(3.08)***
Money growth, lagged two quarters0.090.090.12
(1.78)*(1.68)*(2.20)**
Nominal wage growth0.160.21
(2.90)**(2.34)**
Variance of relative prices30.040.020.04
(6.54)***(1.68)*(4.37)***
Variance of relative prices, lagged one quarter3-0.02
(-2.66)***
Skewness of relative prices, lagged one quarter35.407.57
(1.96)*(2.39)**
Seasonal dummiesSome significantSome significantSome significantAll significant
Outlier dummy1,517.31,512.051,489.271,465.4
(89.15)***(96.41)***(82.19)***(60.42)***
R2 corrected0.920.930.940.93
F-statistics (zero slopes)380.4***358.88***187.46***139.77***
Breusch-Pagan test for heteroscedasticity101.49***114.04***37.18***43.57***
White test for heteroscedasticity174.68***206.18***77.11***83.62***
Jarque-Bera lesl for normality of residuals3,780.98***2,364.69***52.72***152.58***
Number of observations260260105105
Source: Authors’ estimates.Note: For the t-statistics reported in parentheses, three asterisks indicate statistical significance at the 1 percent level, two asterisks at the 5 percent level, and one asterisk at the 10 percent level. A dash indicates that the variable was not included because of lack of significance in the specification search. OLS-HCSE refers to correction of bias in ordinary least squares standard errors and t-statistics using a heteroscedasticity-consistent variance-covariance estimator.

What light do the results shed on the sources of inflationary pressure in transition economies, particularly the role of relative price adjustments? Do the estimates suggest significant regional differences in these sources and whether their relative influence may shift over time? The main messages that emerge from the empirical analysis can be summarized as follows:

(1) Inflation is strongly and positively correlated with broad money growth and displays a relatively rapid response to a monetary shock. Contemporaneous and lagged money growth has an elasticity of about 0.5-0.7 in the pooled sample and the CIS and about 0.3 in the other two regions (Table 3).37 Evaluated at the sample mean, it contributes on average about one-half of inflation in the pool and over one-third in each of the regions despite the very different rates of inflation (Table 5). In Eastern Europe and the CIS, the relative contribution of money growth to inflation is higher in 1995 (even though the rate of inflation is significantly lower) than in the sample mean. The money variable may reflect accommodation—either exogenously through credit creation or endogenously through capital inflows and reserve accumulation—of wage and relative price shocks, including real appreciation. This suggests that better monetary control, including by allowing nominal appreciation, could help bring about greater disinflation.

Table 5.Inflation Decomposition at Sample Mean and Final Year, 1995(In percentage points of inflation)
VariablePooled SampleBalticsCommonwealth of Independent States
Final specificationAlternative specificationEastern and Central EuropeFinal specificationFinal specificationAlternative specification
Final specification
I. Sample mean
Actual inflation42.042.09.49.690.090.0
Constant and dummy variables15.69.8-0.21.635.724.4
Lagged inflation rate2.63.6
Money growth224.221.23.54.232.148.7
Nominal wage growth26.22.517.8
Real exchange rate change2-0.4
Variance of relative prices12.24.81.510.7
Skewness of relative prices20.34.56.2
II. 1995
Actual inflation11.711.73.96.320.120.1
Constant and dummy variables1-5.4-3.0-2.23.0-2.78.6
Lagged inflation rate1.21.9
Money growth212.210.72.82.112.821.1
Nominal wage growth22.11.45.3
Real exchange rate change2-0.1
Variance of relative prices4.91.90.81.0
Skewness of relative prices2-0.64.76.6
Source: Authors’ estimates.Note: Final specification from Table 3, full sample period; alternative specification from Table 4. A dash indicates that the variable was not included because of lack of significance in the specification search.

(2) Nominal wage pressures appear to have a significant impact on inflation, with an elasticity of about 0.2-0.3, accounting on average for about one-fifth to one-fourth of quarterly inflation in Eastern Europe and the CIS; wage pressures do not appear to be a significant factor in the Baltics (Tables 3 and 5). However, since these labor cost indicators capture only pressures arising from monetary remuneration, the estimated coefficients may understate pressures arising from nonwage benefits (most likely monetized and, hence, reflected in money growth), which were considerable, especially in the CIS. In Eastern Europe, the relative contribution of wage growth to inflation is higher in 1995 than in the sample mean.

(3) Overall, the results suggest that relative price adjustment has a significant impact on inflation, although the size of this effect and the indicator capturing it vary by region and over the sample period. Because the estimations reflect only the partial impact effects on inflation during a quarter (holding other factors constant), the size of the estimated effect may be understated to the extent that pressures on inflation stemming from relative price adjustments are accommodated by money growth and are thus captured by the money variable in the equation.38

(4) In the pooled sample and the CIS, variability is associated with nominal wage shocks. In the pool, relative price variance is estimated to contribute slightly less than one-third of inflation (Tables 3 and 5). Because of collinearity in the data, the estimated contribution declines when nominal wage growth is included in the specification (Tables 4 and 5). Similarly, in the CIS, when wage growth is included, the estimated contribution from variability appears small, on average, although it picks up quite substantially in 1995; when the wage term is excluded, the estimated contribution—from both variance and skewness—rises to about one-fifth of inflation.39

(5) In Eastern Europe, variance contributes, on average, about one-sixth of inflation (Table 5). The impact of variance becomes insignificant in the post-liberalization period, although the unweighted skewness suggests a small but significant relative price effect (Tables 3 and 6). Similarly, in the Baltics, variability is estimated to make only a small contribution to inflation. The limited estimated impact of relative price adjustment on inflation—despite evidence of substantial variability even in the post-liberatization period—suggests that monetary accommodation of price shocks may be quite rapid in the small open economies in these two regions. The significance of skewness rather than variance following liberalization in Eastern Europe and the Baltics (which may be considered more advanced reformers with lower inflation rates), and the marked increase in the contribution of skewness when inflation declined sharply in the CIS in 1995, suggests that asymmetric price responses may be more of a factor at intermediate ranges of inflation and in the later stages of transition.

Table 6.Sensitivity to Relative Price Indicators: Unweighted Indicators(Dependent variable: quarterly CPI inflation rate)
VariableEastern and Central EuropeBalticsCommonwealth of Independent States
Pool
Full sampleFull samplePost-liberalizationFull samplePost-liberalizationFull sample
OLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSEOLS-HCSE
Constant12.110.760.981.504.3858.09
(2.05)**(0.84)(1.06)(0.87)(5.00)***(3.92)***
Multiplicative dummy for exchange rate anchor effects on inflation inertia-0.130.02
(1.38)(0.28)
Inflation rate, lagged0.210.440.250.07
(3.16)***(5.45)***(2.97)***(1.06)
Money growth0.220.20
(2.72)***(2.72)***
Money growth, lagged one quarter0.350.260.190.320.210.29
(3.99)***(2.55)**(2.08)**(3.44)***(4.27)***(3.91)***
Money growth, lagged two quarters0.10
(1.81)*
Nominal wage growth0.170.140.21
(2.88)***(2.03)**(8.03)***
Nominal wage growth, lagged one quarter0.070.004
(2.18)**(0.08)
Real exchange rate change, lagged one quarter-0.16-0.24
(2.57)***(-5.20)***
Variance of relative prices10.030.02
(5.14)***(3.88)***
Skewness of relative prices10.410.710.86
(2.23)**(2.02)*(3.09)***
Skewness of relative prices, lagged one quarter11.87
(0.43)
Seasonal dummiesAll significantAll significant
Outlier dummy1,490.33495.4
(92.77)***(87.01)***
R2 corrected0.920.730.600.710.520.93
F-statistics (zero slopes)379.86***47.04***21.30***27.41***11.62***182.96***
Breusch-Pagan test for heteroscedasticity109.03***57.68***75.02***6.03**9.37***40.23***
White test for heteroscedasticity166.46***95.68***39.53***11.959.1071.63***
Jarque-Bera test for normality of residuals3,031.40***44.03***85.61***0.499.16**46.59***
Number of observations2601221003331105
Source: Authors’ estimates.Note: 1For the t-statistics reported in parentheses, three asterisks indicate statistical significance at the 1 percent level, two asterisks at the 5 percent level, and one asterisk at the 10 percent level. A dash indicates that the variable was not included because of lack of significance in the specification search. OLS-HCSE refers to correction of bias in ordinary least squares standard errors and t-statistics using a heteroscedasticity-consistent variance-covariance estimator.

(6) The empirical significance of the impact of relative price adjustment is sensitive to the indicator used to measure variability—particularly between variance and skewness—and to the sample period. Except in the CIS, the results are generally robust to the substitution of unweighted variance and skewness for the corresponding Theil measures (Tables 3 and 6). In particular, as indicated above, although both the Theil and unweighted variance are significant in the full-sample estimation for Eastern Europe, they become statistically insignificant in the post-liberalization period; the unweighted skewness, in contrast, captures some effect of relative price variability on inflation during this period.

(7) The results do not show a significant impact of real appreciation on inflation except in Eastern Europe, where it has a negative elasticity of about 0.2 and, evaluated at the sample mean, shows a small dampening effect on inflation for a given money growth (Tables 3 and 5). The negative impact is consistent with nominal appreciation (see equation (1)), although the small estimated effect may reflect the tendency for countries in the sample to resist nominal appreciation through intervention and endogenous increases in money through the balance of payments. Hence, as in the case of relative price variability, some of the impact of real appreciation may be captured by the money growth term. Because strong real appreciation is an important feature of many transition economies, a few related issues are examined in the next section.

(8) Inflation inertia—reflecting backward indexation or backward-looking expectations in wage and price formation—may become more important as moderate levels of inflation persist, suggesting that the output costs of reducing inflation may tend to increase at these levels. Inertia (as measured by lagged inflation) appears to have contributed about one-fourth to one-third of the inflation in Eastern Europe and the Baltics, but is not significant in the CIS countries where the level of inflation is on average much higher (Tables 3 and 5). In the post-liberalization period, however, the experiences of Eastern Europe and the Baltics diverge, with inertia effects becoming stronger in Eastern Europe, but insignificant in the Baltics.

(9) Explicit exchange rate anchors appear to have only a marginal—and statistically weak—dampening effect on inflation. This does not, however, necessarily imply that exchange rate anchors are ineffective because they can contribute to lower money growth and nominal wage pressure by disciplining financial policies and dampening inflation expectations. While in the alternative specification for the pool an exchange anchor enters as an additive dummy, in Eastern Europe it is manifested as a multiplicative dummy on the lagged inflation term, suggesting a reduction in inertia through a beneficial effect on the formation of expectations.40 An exchange regime effect could not be observed in the Baltics, most likely reflecting the somewhat similar experiences and policy actions of Estonia, which maintained a formal peg, and Latvia, which did not.41

Relative Price Adjustment in Five Transition Economies

To complement the econometric results, this section examines the evidence from five selected countries—Czech Republic, Estonia, Moldova, Poland, and Russia—to obtain more insight into the role of relative price adjustment. The analysis focuses on two issues: (1) What factors underlie variability in relative prices as measured by the variance and skewness of the price distributions? (2) Does the analysis of relative price adjustment shed some light on the factors that could explain the marked real appreciation in transition economies?

The five selected countries have all achieved an initial macroeconomic stabilization and have liberalized and adjusted relative prices to some extent. Nevertheless, they represent a range of progress in these areas, particularly with regard to inflation reduction, and also reflect some diversity in macroeconomic and structural policies. The timing of their initial liberalization varies, and they also adopted somewhat different strategies. The Czech Republic, Poland, and Estonia followed a “big-bang” approach, undertook extensive liberalization early, and used an explicit exchange rate anchor, while Moldova and Russia adopted a gradual approach to both stabilization and structural reform and relied on a more flexible exchange rate policy.

Factors Underlying Relative Price Variability

A common feature of the present sample is the periodic sharp peaks in the measured variance of relative prices, concurrent with peaks in inflation, particularly in the early stages of transition (Figure 1). For all five countries, these peaks largely coincide with relative price shocks: episodes of trade and price liberalization, increases in wages and administered prices, tax reform, and terms of trade shocks, in some instances accompanied by monetary accommodation (particularly in Russia). This suggests that spikes in variance largely reflect exogenous relative price shocks stemming from structural change, at times accommodated by money growth. In terms of the models of relative price variability discussed earlier, these results would suggest either a simultaneous effect or a direction of causality running from relative price variability to inflation.42

Figure 1.Inflation and Relative Price Variance

Although variance declines sharply following the initial bouts of price liberalization in all five countries, it appears to remain high relative to market economies. Comparisons of variance across countries need to be interpreted with caution because the measures also reflect the weights and level of disaggregation of the CPI data. Nevertheless, as a rough indication, a comparison of the Theil variance and unweighted variance for 1995 with corresponding indices for Argentina, Greece, Italy, and the United States suggests that relative price variance in these transition economies—with the exception of the Czech Republic—is substantially higher than in the market economies (see Coorey, Mecagni, and Offerdal, 1996). In addition, the contribution from variance within tradables tends to be somewhat greater in the transition economies, although this may reflect the relatively low weight given to nontradables in the CPI (particularly for Moldova and Russia).

Can an analysis of skewness reveal any insights about factors—such as the cost-recovery hypothesis—that could explain a prolonged period of relative price adjustment? A comparison of inflation rates of cost-recovery items with overall inflation indicates that prices of these items tend to be adjusted discontinuously rather than smoothly (Figure 2). This may reflect the administrative and political costs of changing such prices that induce the authorities to recover the deterioration of these relative prices (during periods when prices are not changed) by periodically raising them well in excess of average inflation.43 Given this pattern of periodic price adjustments, goods for which cost recovery is a consideration may be expected to dominate as outliers in quarters when the distribution of prices is positively skewed. Moreover, if these prices increase in relative terms on a sustained basis as argued by the cost-recovery hypothesis, rather than simply being adjusted periodically to keep up with average inflation, they will also tend to dominate the distribution of prices when inflation rates are calculated on a cumulative basis.44

Figure 2.Consumer Price Inflation

(In percent)

The evidence suggests that in three countries—Czech Republic, Estonia, and Poland—cost-recovery items indeed dominate the distributions of cumulative inflation rates, indicating sustained relative price gains (Figure 3). In addition, on average, they frequently rank among the 10 most extreme outliers in periods when the distributions of quarterly inflation rates are positively skewed (see Coorey, Mecagni, and Offerdal, 1996)—a pattern that is evident in both the early and the later years of the transition.45 In Russia, cost-recovery items are less dominant, although this relates to the much higher degree of disaggregation of the CPI data in which items with strong price seasonality (that is, fruits and vegetables) appear individually.46 In Moldova, cost-recovery items dominate the distribution of cumulative inflation rates in the early years, but are strikingly absent from the later years—suggesting that these prices, which are largely administratively set, were not adjusted during 1994-95 when overall inflation declined markedly.

Figure 3.Cumulative Relative Price Changes

Note: Bars indicate the ratio of individual inflation rates to the mean unweighted inflation rate, both calculated on a cumulative basis.

Some Factors Underlying Real Appreciation

All five countries have experienced considerable real appreciation since the beginning of the transition, although the measured degree of appreciation is sensitive to the choice of index (Figure 4).47 Undervaluation is frequently cited as an explanation for this appreciation, even in the later stages of transition. Although international price comparisons are often used as evidence, direct comparisons can be misleading if differences in GDP adjusted for purchasing power parity are not taken into account. A price comparison for 1993 suggests that price levels in all countries except Poland were significantly lower, relative to a comparator Western European country (Austria) than would be indicated by differences in adjusted GDP (Table 7). The discrepancy is especially marked for Moldova and seems surprisingly large for the Czech Republic.

Figure 4.Indicators of Real Exchange Appreciation

(Index: First observation = 100)

Note: Starting period coincides approximately with the period of initial price liberalization, except for Russia, where data are not available for 1992.

1Relative price of nontradables to tradables.

2Real exchange rate based on CPI relative to trading partner CPIs.

3U.S. dollars per unit of local currencies.

Table 7.Price Level Comparisons
1993
Czech RepublicEstoniaMoldovaPolandRussia
Commodity price level (in percent of corresponding Austrian price level)
Food, beverages, and tobacco3628144726
Clothing and footwear3623104928
Household equipment and operation3931146025
Gross rents, fuel, and power15134228
Medical care1977226
Transport and communication4318145617
Of which
Purchased transport services33884611
Communication32843610
Recreation and education201972811
Miscellaneous goods and services292595129
Overall price level (in percent of overall Austrian price level)261993516
Predicted price level (in percent of Austrian price level)14542293836
Memorandum items:
GDP adjusted for purchasing power parity (in percent of Austrian GDP (EPCP))24511242027
GDP adjusted for purchasing power parity (in percent of Austrian GDP (WEO))33833162826
19944
Czech RepublicEstoniaMoldovaPolandRussia
Commodity price level (in percent of corresponding Austrian price level)
Food, beverages, and tobacco5356
Clothing and footwear426721
Household equipment and operation484617
Gross rents, fuel, and power163836
Transport and communication301925
Recreation and education353926
Miscellaneous goods and services2910339
Overall price level (in percent of overall Austrian price level)5425142
Predicted price level (in percent of Austrian price level)1382922
Memorandum item:
GDP adjusted for purchasing power parity (in percent of Austrian GDP (WEO))3292217

Undervaluation can be reflected in international price differences in tradables if there is only gradual arbitrage in traded goods prices. Price comparisons suggesting that traded goods prices are often much lower relative to those in industrial countries than can be accounted for by transportation costs have sometimes been used as evidence of undervaluation (for instance, in Table 7, traded goods prices in 1993 in all five countries are typically less than half the levels in Austria).48 Moreover, the tendency for the real exchange rate measured on the basis of relative CPIs to appreciate more than the ratio of nontraded to traded goods in the Czech Republic, Estonia, and Poland is consistent with the gradual convergence of domestic traded prices to those of trading partners (Figure 4).49

Nevertheless, while undervaluation may explain the sharp real appreciation at the initial stages of transition, gradual arbitrage in traded goods prices is not very plausible in small open economies like the Czech Republic, Estonia, and Poland. However, to the extent that tradable goods prices incorporate a substantial nontradable element, and the pricing of capital pushes nontradables prices (which are dominated by capital-intensive services) below levels predicted for market economies, a more plausible explanation may be offered by the cost recovery hypothesis. Since cost recovery appears to be a factor at least in the Czech Republic, Estonia, and Poland (Figure 3), part of the real appreciation and gradual convergence of tradables and nontradables prices to market economy levels may be driven by cost-recovery considerations rather than by undervaluation per se.

An alternative explanation of real appreciation in the later stages of transition, particularly in the Baltics, is the Balassa-Samuelson effect based on faster productivity growth in tradables than in nontradables. However, numerical examples based on the observed real appreciation (as measured by the change in prices of nontradables relative to tradables in the CPI) and some plausible assumption on total factor productivity growth in tradables in the five countries imply highly implausible rates of total factor productivity growth in nontradables, particularly when real appreciation is large, as in Estonia, Moldova, and Russia (Table 8). For the entire sample period, the observed real appreciation is large enough to imply sizable negative total factor productivity growth in nontradables in almost all cases.50 For the last year of the sample, plausible rates of productivity growth in nontradables obtain only in the Czech Republic and Poland, where real appreciation is much more moderate.

Table 8.Real Exchange Rate Appreciation and Implied Productivity Growth Consistent with the Balassa-Samuelson Model(In percent)
Czech RepublicEstoniaMoldovaPolandRussia
Whole period1
Total real appreciation
Relative consumer price index57.0173164121.0327
Price of nontradables relative to price of tradables28.08842589.0754
Implied annual productivity growth, nontraded goods sector; Case I2-0.5-15-35-7.0-56
Implied annual productivity growth, nontraded goods sector; Case II30.4-14-34-6.0-55
Later period4
Total real appreciation
Relative consumer price index9.019103.052
Price of nontradables relative to price of tradables-0.418100.138
Implied annual productivity growth, nontraded goods sector; Case 25.0-8-25.0-19
Implied annual productivity growth, nontraded goods sector; Case II36.0-7-16.0-18
Source: Authors’ estimates.Note: The implied productivity growth is calculated as: (PN˙PT)=(ααT)ΘTΘN, where a “^” denotes rate of change; derived by assuming linear homogenous production functions in the traded (T) and nontraded (N) goods sectors:Yi=ΘiKi(1αi)Liαj;i=T,N (Asea and Corden, 1994). Assuming α√αT=k (a constant), the formulation for discrete changes is (PN˙PT)=[(1+kΘT)/(1+ΘN)1]. The implied productivity growth in nontradables will be higher than that in tradables if there is a real depreciation or if k is sufficiently larger than unity.

Conclusions

In the context of the concerns over the persistence of intermediate inflation, this paper has analyzed the empirical evidence regarding the sources of inflation in 21 transition economies, focusing in particular on the role of relative price adjustment. An examination of disaggregated CPI data shows that inflation distributions in transition economies display a high degree of variance and frequent positive skewness, indicating that significant relative price adjustments take place throughout the transition period even well beyond comprehensive initial liberalization. Evidence of positive skewness shows that a small number of large price increases have often led the inflationary process. It suggests the presence of significant relative shocks and asymmetric price responses consistent with theoretical approaches that draw a causal link from relative price variability to inflation.

A closer look at the factors under lying relative price variability in five representative case studies indicates that variability arises from different sources and is mainly associated with relative, rather than aggregate, shocks. First, sharp increases in relative price variance (which are frequently concurrent with spikes in inflation) early in the transition tend to coincide with periods of intensive structural change: trade and price liberalization, increases in wages and administered prices, tax reform, and terms of trade shocks, at times accompanied by monetary accommodation. Second, sustained relative price changes underlie the positive skewness in inflation disributions. Increases in relative prices of capital-intensive services (housing, utilities, and transport) where cost-recovery considerations are important are particularly evident in countries more advanced in the transition. In addition, sectors that experienced the largest cumulative relative price increases also tend to dominate as outliers in periods when the distribution of inflation rates is positively skewed. These findings further support models that derive a positive impact on inflation from relative price variability. Models that draw a reverse causal link from inflation to variability cannot explain sustained relative price changes at the sectoral level.

The cost-recovery hypothesis may also provide some insight into the marked appreciation of the real exchange rate—an important relative price—experienced by many transition economies. The gradual nature of cost recovery in transition economies keeps nontradables prices below levels predicted for market economies. Furthermore, to the extent that tradable goods prices incorporate a substantial nontradable element in the form of capital-intensive services, the cost-recovery hypothesis offers a plausible explanation for the apparent undervaluation of the real exchange rate.

A regression analysis of relative price variability and inflation, controlling for nominal shocks, indicates that variability has a statistically significant impact on inflation, although—more than in the case of the other explanatory variables—the size of the effect differs by region and over the sample period. In CIS countries, relative price variability is associated with wage shocks and has a substantial impact on inflation. The estimated impact is generally small in Eastern Europe and the Baltics, although variance has a sizable effect on inflation during the initial liberalization period in Eastern Europe. The estimations do not show a significant impact of real appreciation on inflation, except for a small dampening effect (for a given money growth) observed for Eastern Europe.

Why, when there is strong evidence of substantial relative price variability, including real appreciation, would there not be a larger quantitative impact on inflation, particularly in the moderate-inflation countries of Eastern Europe and the Baltics? The explanation is likely to lie in the relatively rapid (that is, within one quarter) monetary accommodation of relative shocks—generated through credit expansion or official intervention in the face of foreign exchange inflows. Evidence from countries with fixed or preannounced exchange rate regimes in Eastern Europe and the Baltics suggests that monetary expansion through foreign exchange inflows can be quite rapid and substantial in these small open economies (particularly in the Baltics). The regression estimates indicate that, even in the relatively short period of one quarter, nominal money growth plays a dominant role in explaining inflation in all regions. Strikingly, monetary growth accounts for a similar proportion of inflation in all three regions, even though Eastern Europe and the Baltics have, on average, much lower inflation rates than the CIS countries.

One of the main policy implications that can be drawn from the results in this paper is that relative price adjustment does not set a “floor” on inflation, provided there is a willingness to use monetary policy sufficiently aggressively.51 The empirical significance of money growth—whatever its source—suggests, other things being equal, that tighter monetary control, including through nominal appreciation, could help lower inflation in the presence of relative price adjustments. If a gradual reduction of inflation from intermediate levels is envisaged, increased exchange rate flexibility—through either a switch to a money-based anchor or a widening of an exchange rate band—may be needed. If a more rapid reduction of inflation is targeted, a strong and credible commitment would be needed to limit the extent of foreign exchange intervention, thus controlling money growth and allowing nominal appreciation. This is especially important if ambitious structural reforms that imply large relative price changes are envisaged.

Nevertheless, the design of disinflation programs and the choice of anchor strategy should anticipate that significant shifts in velocity, and hence instability in the demand for real balances, may accompany large relative price adjustments, particularly in the short run. If an exchange rate anchor strategy is chosen—and there may be good reasons for not abandoning such a strategy once it is in place—or if firm commitments cannot be made with regard to permitting nominal appreciation, inflation targets should reflect the likelihood that moderate inflation will persist. Although inflation may eventually decline, other factors such as inertia are likely to entail output costs at this later stage. The regression results indicate that inertia becomes a more significant influence at lower levels of inflation and in the later stages of transition in Eastern Europe, suggesting that output costs of reducing inflation increase at these levels. In addition, the significant impact of nominal wage pressures on inflation in the context of both high and intermediate inflation indicates the need for vigilance in the area of wage growth, particularly also with regard to backward indexation, which would add to inertia. However, other research suggests that authorities may not be able to control nominal wage pressures effectively (see Schadler and others, 1995), so that it may be difficult in practice to use nominal wages as a secondary anchor.

Appendix. Background Tables

The following tables show the structure of the sample of 21 countries discussed in this paper.

Table A1.Sample Characteristics of the CPI Data
Region/CountryObservation Period, First and Last QuarterBreak Points Occur1Number of Categories Before/After Break Points2CPI Weights Available in
Central and Eastern Europe
Albania1992:Q1-1995:Q31993:Q48/241992
Bulgaria1990:Q3-1995:Q31992:Q411/111990,1993
Czech Republic1991:Q1-1995:Q31993:Q430/101991,1994
Hungary1991:Q1-1995:Q31992:Q47/71991,93, 94, 95
Poland1990:Q1-1995:Q2331990,91, 92, 93, 94, 95
Romania1992:Q1-1995:Q31993:Q469/1611992,1994
Slovak Republic1992:Q1-1995:Q3341992
Slovenia1992:Q1-1995:Q4171992, 93, 94, 95
Baltics
Estonia1992:Q3-1995:Q3231992
Latvia1992:Q3-1995:Q3511992, 1994
Lithuania1992:Q3-1995:Q4791992, 1994
Commonwealth of Independent States
Armenia1993:Q1-1995:Q391993, 1995
Azerbaijan1991:Q1-1995:Q3421991, 92, 93, 95
Belarus1992:Q1-1995:Q3331992
Georgia1994:Q1-1995:Q3161994
Kazakhstan1991:Q1-1995:Q3181991
Kyrgyz Republic1992:Q1-1995:Q31994:Q432/331992, 1995
Moldova1992:Q1-1995:Q31993:Q453/721995
Russia1992:Q1-1995:Q31992:Q4153/3821992, 93, 94, 95
1993:Q4382/392
1994:Q4392/288
Ukraine1991:Q1-1995:Q11992:Q48/881991, 92,93, 94
1993:Q48/39
Uzbekistan1994:Q1-1995:Q2151994, 1995
Table A2.Sample Size
Full Sample
PeriodNumber of quartersPost-Liberalization
PeriodExchange Rate Anchor
Central and Eastern Europe
Albania1992:Q2-1995:Q3141993:Q1-1995:Q3No
Bulgaria1991:Q3-1995:Q3171992:Q2-1995:Q3No
Czech Republic1992:Q3-1995:Q3131992:Q3-1995:Q3Yes
Hungary1991:Q2-1995:Q3181993:Q1-1995:Q3Yes, since March 1995
Poland1990:Q2-1995:Q2211991:Q2-1995:Q2Yes
Romania1992:Q3-1995:Q3131993:Q4-1995:Q3No
Slovak Republic1992:Q3-1995:Q3131992:Q3-1995:Q3Yes
Slovenia1992:Q3-1995:Q3131992:Q3-1995:Q3No
Baltics
Estonia1992:Q4-1995:Q3121993:Q1-1995:Q3Yes
Latvia1992:Q4-1995:Q3121993:Q1-1995:Q3Yes, since February 1994
Lithuania1993:Q3-1995:Q391993:Q3-1995:Q3Yes, since April 1994
Commonwealth of Independent States
Armenia1993:Q2-1995:Q310n.a.No
Azerbaijan1992:Q3-1995:Q313n.a.No
Belarus1992:Q3-1995:Q313n.a.No
Georgia1994:Q2-1995:Q36n.a.No
Kazahkstan1992:Q3-1995:Q313n.a.No
Kyrgyz Republic1993:Q1-1995:Q311n.a.No
Moldova1992:Q3-1995:Q313n.a.No
Russia1993:Q2-1995:Q310n.a.Yes, since June 1995
Ukraine1992:Q3-1995:Q111n.a.No
Uzbekistan1994:Q2-1995:Q25n.a.No
References

    Asea, P., and W.Corden,1994, “The Balassa-Samuelson Model: An Overview,”Review of International Economics, Vol. 2 (October), pp. 191200.

    Balassa, B.,1964, ‘The Purchasing-Power Parity Doctrine: A Reappraisal,”Journal of Political Economy, Vol. 72 (December), pp. 58496.

    Ball, Laurence, and N. GregoryMankiw,1994, “Asymmetric Price Adjustment and Economic Fluctuations,”Economic Journal, Vol. 104 (March), pp. 24761.

    Ball, Laurence, and N. GregoryMankiw,1995, “Relative Price Changes as Aggregate Supply Shocks,”Quarterly Journal of Economics, Vol. 110 (February), pp. 16293.

    Barro, Robert J.,1976, “Rational Expectations and the Role of Monetary Policy,”Journal of Monetary Economics, Vol. 2 (January), pp. 132.

    Blejer, M., and L.Leiderman,1982, “Inflation and Relative-Price Variability in the Open Economy,”European Economic Review, Vol. 18 (July), pp. 387402.

    Bruno, Michael,1993, “Stabilization and the Macroeconomics of Transition: How Different Is Eastern Europe?”Journal of Economics of Transition, Vol. 1 (January), pp. 519.

    Citrin, Daniel A., and Ashok K.Lahiri,1995, Policy Experiences and Issues in the Baltics, Russia, and Other Countries of the Former Soviet Union, IMF Occasional Paper No. 133 (Washington: International Monetary Fund).

    Coorey, Sharmini, MauroMecagni, and ErikOfferdal,1996, “Disinflation in Transition Economies: The Role of Relative Price Adjustment,”IMF Working Paper 96/138 (Washington: International Monetary Fund).

    Coorey, Sharmini, MauroMecagni, and ErikOfferdal,1997, “Designing Disinflation Programs in Transition Economies: The Implications of Relative Price Adjustment,”IMF Paper on Policy Analysis and Assessment 97/1 (Washington: International Monetary Fund).

    Cukierman, Alex,1979, “The Relationship between Relative Prices and the General Price Level: A Suggested Interpretation,”American Economic Review, Vol. 69 (June), pp. 44447.

    De Broeck, M., P.De Masi, and V.Koen,1995, “Inflation Dynamics in Kazakstan,”IMF Working Paper 95/140 (Washington: International Monetary Fund).

    De Gregorio, J., A.Giovannini, and H.C.Wolf,1993, “International Evidence on Tradables and Nontradables Inflation,”NBER Working Paper No. 4438 (Cambridge, Massachusetts: National Bureau of Economic Research).

    De Masi, P., and V.Koen,1995, “Relative Price Convergence in Russia,”IMF Working Paper 95/54 (Washington: International Monetary Fund).

    Dornbusch, R.,1992, “Lessons from Experiences with High Inflation,”World Bank Economic Review,”Vol. 6 (January), pp. 1331.

    Edwards, S.,1992, “Stabilization and Liberalization Policies for Economies in Transition: Latin American Lessons for Eastern Europe,” in The Emergence of Market Economies in Eastern Europe, ed. by C.Clague and G.C.Rausser (Cambridge, Massachusetts: Blackwell).

    Faruqee, Hamid,1995, “Long-Run Determinants of the Real Exchange Rate: A Stock-Flow Perspective,”Staff Papers, International Monetary Fund, Vol. 42 (March), pp. 80107.

    Fischer, Stanley,1981, “Relative Shocks, Relative Price Variability, and Inflation,”Brookings Papers on Economic Activity: 2, Brookings Institution, pp. 381141.

    Fischer, Stanley,1982, “Relative Price Variability and Inflation in the United States and Germany,”European Economic Review, Vol. 18, (May-June), pp. 172208.

    Fischer, Stanley,1993, “The Role of Macroeconomic Factors in Growth,”Journal of Monetary Economics, Vol. 32 (December), pp. 485512.

    Fischer, Stanley, RatnaSahay, and CarlosVegh,1996, “Stabilization and Growth in Transition Economies: The Early Experiences,”IMF Working Paper 96/31 (Washington: International Monetary Fund).

    Frenkel, Jacob, and FrancescoGiavazzi,1982, “Comments on ‘Relative Price Stability and Inflation in the United States and Germany,’ by S. Fischer,”European Economic Review, Vol. 18 (May/June), pp. 198208.

    Froot, K., and K.Rogoff,1991, “The EMS, the EMU, and the Transition to a Common Currency,”NBER Working Paper No. 3684 (Cambridge, Massachusetts: National Bureau of Economic Research).

    Hercowitz, Zvi,1981, “Money and the Dispersion of Relative Prices,”Journal of Political Economy, Vol. 89 (April), pp. 32856.

    Heston, A., D.Nuxoll, and R.Summers,1994, “The Differential Productivity Hypothesis and Purchasing Power Parities: Some New Evidence,”Review of International Economics, Vol. 2 (October), pp. 22743.

    International Monetary Fund, World Economic Outlook: A Survey by the Staff (Washington, various issues).

    Kravis, I.B., and R.E.Lipsey,1982, “Towards an Explanation of National Price Levels,”NBER Working Paper No. 1034 (Cambridge, Massachusetts: National Bureau of Economic Research).

    Lipschitz, Leslie, and DonoghMcDonald,1991, “Real Exchange Rates and Competitiveness: A Clarification of Concepts and Some Measurements for Europe,”IMF Working Paper 91/25 (Washington: International Monetary Fund).

    Lucas, R.E.Jr.,1973, “Some International Evidence on Output-Inflation Trade offs,”American Economic Review, Vol. 63 (June), pp. 32634.

    McKinnon, R.,1992, “Taxation, Money, and Credit in a Liberalizing Socialist Economy,” in The Emergence of Market Economies in Eastern Europe, ed. by C.Clague and G.C.Rausser (Cambridge, Massachussets: Blackwell).

    Micossi, S., and G.M.Milesi-Ferretti,1994, “Real Exchange Rates and the Prices of Nontradable Goods,”IMF Working Paper 94/19 (Washington: International Monetary Fund).

    Phillips, S.,1994, “Note on Administered Price Increases in the CIS” (unpublished).

    Richards, A., and G.Tersman,1995, “Growth, Nontradables, and Price Convergence in the Baltics,”IMF Working Paper 95/45 (Washington: International Monetary Fund).

    Rogoff, K.,1996, “The Purchasing Power Parity Puzzle,”Journal of Economic Literature, Vol. 34 (June), pp. 64768.

    Saavalainen, T.,1995, “Stabilization in the Baltic Countries: A Comparative Analysis,”IMF Working Paper 95/44 (Washington: International Monetary Fund).

    Sahay, R., and C.Vegh,1995, “Inflation and Stabilization in Transition Economies: A Comparison with Market Economies,”IMF Working Paper 95/8 (Washington: International Monetary Fund).

    Samuelson, P.,1964, “Theoretical Notes on Trade Problems,”Review of Economics and Statistics, Vol. 46 (May), pp. 14554.

    Sarel, M.,1996, “Nonlinear Effects of Inflation on Economic Growth,”Staff Papers, International Monetary Fund, Vol. 43 (March), pp. 199215.

    Schadler, Susan, and others,1995, Conditionality: Experience Under Stand-By and Extended Arrangements, Part II: Background Papers, IMF Occasional Paper No. 129 (Washington: International Monetary Fund).

    Sheshinski, E., and Y.Weiss,1977, “Inflation and Costs of Price Adjustment,”Review of Economic Studies, Vol. 44 (June), pp. 287303.

    Theil, Henri,1967, Economics and Information Theory (Amsterdam: North Holland).

    Zavoico, Basil,1995, “A Brief Note on the Inflationary Process in Transition Economies” (unpublished; Washington: International Monetary Fund).

Note: The authors would like to thank Susan Schadler, Gerard Beianger, Jack Boorman, Hugh Bredenkamp, Carlo Cortarelli, Louis Dicks-Mireaux, Stanley Fischer, Michael Keane, Kalpana Kochhar, Jorge Marquez-Ruarte, and Don Mathieson for valuable comments and suggestions; Kadima Kalonji and Fernanda Gusmao for excellent research assistance and document preparation; colleagues in EU1 and EU2 departments at the IMF for help in assembling the database; and Derek Bills and Angeliki Economopoulos for technical assistance.

Until recently, there was little consensus in the literature regarding the desirability of the objective of single-digit inflation. However, a growing body of evidence from large industrial and developing country samples suggests that inflation above the single-digit ranges is detrimental to long-term growth (Fischer, 1993;Sarel, 1996).

The 21 countries include transition economies in Eastern and Central Europe (referred to as “Eastern Europe” in the paper), the Baltics, and the Commonwealth of Independent States (CIS). The structure of the sample is shown in Tables Al and A2 in the appendix. Transition economies in Asia and the countries of the former Yugoslavia (except Slovenia) are not included in the analysis. Tajikistan and Turkmenistan are also excluded because of data problems.

In a number of IMF-supported programs in the CIS, nominal wage growth substantially exceeded program expectations and turned out significantly higher than the corresponding inflation targets (Citrin and Lahiri, 1995).

Measured either Ln terms of the relative price of traded and nontraded goods (the definition used in most of the analytical literature) or in terms of relative CPIs (the definition commonly used in empirical work).

For instance, with negative real interest rates on bank deposits and no other liquid inflation hedges, foreign exchange can become the most important form of liquid wealth holding and can drive the exchange rate far from its purchasing power parity level (Bruno, 1993).

While price differentials in tradables could arise from trade barriers, quality differentials, and the embodiment of a nontradable component in the form of distribution costs, some have argued that these factors alone may not explain the large deviations from international prices of traded goods found, for instance, in Russia (De Masi and Koen, 1995) and Latvia (Richards and Tersman, 1995).

An important implication of the Balassa-Samuelson model is that cross-country differences in the prices of nontradables (that is, wages and prices of services) are explained by differences in productivity in traded goods. Thus, in principle, price levels would be comparable only among countries that have similar levels of per capita GDP, as adjusted for purchasing power parity.

For instance, higher productivity growth in tradables in Japan and Western Europe has been found to explain a significant part of the downward secular trend in the postwar U.S. dollar real exchange rate (Faruqee, 1995;Rogoff, 1996). The evidence, however, is mixed for comparisons across countries in the European Monetary System (EMS) and the Organization for Economic Cooperation and Development (OECD) (De Gregorio, Giovannini, and Wolf, 1993; Froot and Rogoff, 1991; Micossi and Milesi-Ferretti, 1994).

A related consideration is the change in the relative size of the public sector that would affect the real exchange rate because public expenditure tends to fall mainly on nontradables in comparison with private expenditure (Froot and Rogoff, 1991; De Gregorio, Giovannini, and Wolf, 1993). However, because of the drastic shifts in the composition of public revenues and expenditures that typically occur during transition, the direction of this effect is difficult to gauge.

IMF staff have argued that “administered price increases” have been a major factor behind inflation performance in the CIS (for example, Citrin and Lahiri, 1995). However, while such price increases may contribute to inflation volatility, they cannot be considered a fundamental determinant of inflation over a sustained period if these prices are periodically restored to the same relative value; in such a case, administered prices would contribute to lower inflation during periods when they are not being raised (Phillips, 1994). Hence, administered price increases may be considered a determinant of inflation only if they are part of a process of relative price adjustment and other prices are sticky downward. In a statistical sense, the upward adjustment of a particular administered price during a period in which other nominal prices are not adjusted does contribute to inflation in the short run.

This is done for five case studies in the penultimate section. Causality tests are not feasible in the current sample because of the short observation period for each country. In any case, such tests can capture only temporal precedence rather than logical causality. For market economies, causality tests find no clear pattern of leads and lags between inflation and relative price variability (see Coorey, Mecagni, and Offerdal, 1996, Appendix I).

Real incomes could rise because of general productivity growth, whatever its source. Unlike the Balassa-Samuelson effect, this does not require differential productivity growth between traded and nonfraded goods.

In practice, many prices for which cost recovery is a consideration are government controlled in most transition economies and may involve a subsidy element as well. Nevertheless, the point of the cost-recovery hypothesis is that even if these administered prices are set according to market principles (that is, involve no net subsidy), they would initially be substantially lower than in market economies—where such capital-intensive service prices largely reflect the cost of capital—and would rise sharply as real income grows and creates a demand for new investment. This phenomenon has been observed in Estonia, where there is little or no budgetary subsidy on public services and some items such as housing have been privatized (Zavoico, 1995). Also, in Poland, utility and rental price inflation have substantially exceeded overall CPI inflation (see Chapter 9 in this volume).

The undervaluation argument outlined above involves an element of disequilibrium, whereas the gradual adjustment of service prices described here is an equilibrium phenomenon, which does not necessarily involve market distortion, inefficiency, or excess profits.

The Balassa-Samuelson model implies that the ratio of nontraded to traded goods prices is positively related to per capita real GDP. This proposition has been empirically supported across a broad group of high-income and low-income countries based on the United Nations International Comparison Program (ICP) data. However, the robustness of this result among industrial countries as a group and developing countries as a group is less clear (Heston, Nuxoll, and Summers, 1994;Rogoff, 1996).

The results in this section are reported in detail in Coorey, Mecagni, and Offerdal (1996), Appendix 1.

The structure of the sample is given in Table A1. For a formal definition of the different measures of relative price variability, see Coorey, Mecagni, and Offerdal (1996), Appendix I.

A distinction is made in this paper between relative price variability, which refers to the volatility of relative prices and may be measured by variance or skewness, and relative price variance, which refers to measures reflecting the width of the distribution (or dispersion) of individual inflation rates comprising the CPI.

Comparisons of the characteristics of price distributions across countries should be interpreted with caution because such differences can also reflect differing weights and levels of disaggregation in the CPI data.

The decomposition was based on a measure of relative price variance, commonly used in the literature, referred to in this paper as the “Theil variance” (from Theil, 1967). These average proportions are similar to those reported for Mexico (Blejer and Leiderman, 1982), although the period-to-period fluctuations are much greater for transition economies. These patterns may, however, reflect the dominance of tradable goods, in terms of both weights and the number of commodities, in the CPI baskets.

These results are only tentative because diagnostic tests reveal the likelihood of mis-specification (and, hence, the need for multivariate estimation) and because the sample size for each country is small.

As the panel regressions reported in the next sections show, skewness becomes more significant in a multivariate estimation.

This model is presented in greater detail in Coorey, Mecagni, and Offerdal (1996), Appendix II.

The variables are as follows: π = overall inflation rate; (π(t-1)) = inflation lagged one quarter; m = nominal money growth; w = nominal wage growth; (πNTT) = rate of change of the real exchange rate (that is, the change in the ratio of prices of nontradables to tradables); TVAR = Theil variance; TSK = Theil skewness. The last two variables are measures of relative price variability (see Coorey, Mecagni, and Offerdal (1996), Appendix I, for definitions).

The structure of the regression sample is given in Table A2. The sample coverage, methodology, and results are reported in greater detail in Coorey, Mecagni, and Offerdal (1996), Appendix III.

Nominal unit labor costs are used for Eastern Europe (except Albania) and nominal wages are used for the Baltics and the CIS. Hence, for Albania, the Baltics, and the CIS, no allowance is made for wage growth accounted for by productivity growth. However, to the extent that productivity growth could often be negative in these countries (because of labor hoarding, negative output shocks, and so on), it is difficult to establish, a priori, whether the estimated coefficient would overstate or understate true labor cost pressures.

This indicator reflects the definition used in most of the analytical literature more closely than it does the more commonly used (and more easily available) measure based on relative CPIs.

A dummy variable was also included for an extreme outlier (in the data for Armenia), which resulted in a highly normormal distribution of residuals and made tests of statistical significance (F- and t-tests) uninterpretable.

The residuals of the estimated equations were examined for, but did not reveal, in most cases, evidence of autocorrelation.

The predictive performance of the pooled model in different regional subsamples suggested that it was being driven by the subsample corresponding to the CIS; the pooled model performed less well for the Eastern European and Baltic regional blocs. Formal testing of parameter instability through standard Chow/F-tests and recursive procedures was made difficult by heteroscedasticity and nonnormality of the residuals.

A similar analysis could not be made for the CIS because the delayed and gradual nature of price liberalization in many countries limited the sample period excessively.

Relative price variability can be measured in many ways. A choice has to be made whether price changes should be weighted by their contribution to the CPI or be unweighted and, if the former, how the weights should enter into the definition of variability. Measured variability thus depends on the characteristics of the sample, particularly the degree of disaggregation of the price data—which influences the dispersion of the weights—and the accuracy of the weights. Hence, any observed empirical relationship between inflation and relative price variability is likely to be sensitive to the choice of indicator and the characteristics of the sample.

With price-controlled goods, an increase in inflation would automatically increase relative price variance if such prices were not immediately raised in line with market conditions.

The basket of liberalized goods was defined by eliminating all public services (rents, utilities, transport, and so on) and any commodity whose price did not change for three consecutive quarters. Although this would not necessarily yield a basket of liberalized goods for every country, it should eliminate price-controlled goods from the sample in most cases.

Although the specifications for Eastern Europe and the Baltics include a lagged dependent variable, long-run elasticities should not be inferred from the estimates, because dynamic relationships are not sufficiently well captured in these panel regressions where much of the sample variation is cross-sectional.

Some caution may be called for in the interpretation of F- and t-statistics since diagnostic tests reveal nonnormal residuals, although the large sample sizes (over 100 observations) may help in this regard.

Estimations over the pooled sample suggest this result is robust to a change in the definition of the regressor from broad money to domestic credit (of the banking system) because of the high correlation between these two variables, which reflects the limited capacity of commercial banks in most transition economies to lend or borrow abroad. However, inflation appears more responsive to a broad concept of money, which includes foreign currency deposits, than to a narrow concept, which excludes them (the estimated elasticity is nearly halved in the latter case), consistent with evidence for market economies.

For Poland, lagged inflation is statistically significant in explaining future money growth 3-12 months (but not 1 month) ahead, suggesting monetary accommodation of shocks to inflation (see Chapter 9 in this volume). In fixed or preannounced exchange regimes, such as the Czech Republic, Estonia, and Poland, monetary accommodation occurs mainly through official reserve accumulabon. During 1992-95, this accommodation was rapid and significant—frequently at annual rates in excess of 20 percent a quarter—despite substantial sterilization in the Czech Republic. In CIS countries, on the other hand, monetary accommodation has taken place mainly through discretionary credit expansion (Coorey, Mecagni, and Offerdal, 1996).

The negative sign on the coefficient of the lagged variance is consistent with the partial reversal of the initial (within-quarter) positive impact of relative price shocks on inflation.

The dummy reflects only formal anchors—rather than a policy of resistance to nominal appreciation—for given nominal money and wage growth. Although the t-statistic indicates a lower than standard level of significance, the elimination of this dummy is rejected by F- and χ2 tests and worsens the performance of the estimated equation, suggesting some overall significance. The insignificance of the dummy in the post-liberalization period in Eastern Europe is consistent with a diminishing signaling effect for long-standing anchors. A multiplicative exchange regime dummy was introduced on the real exchange rate term, but turned out to be insignificant in the pool and in each of the regions.

An exchange regime dummy could not be introduced in the CIS bloc because no country maintained a formal peg during the sample period (except Russia in the third quarter of 1995).

If causality tends to run from inflation to variability, spikes in the two variables should coincide with aggregate shocks (for example, relaxation of financial policies) and not just with relative price shocks (for example, episodes of intensive liberalization and wage shocks); an exception is the fourth quarter of 1994 in Russia, which seems to be mainly related to a relaxation of financial policies (see Figure 1).

Services for which cost recovery is a consideration (rents, utilities, transport, and communication) tend to be publicly owned in most of these countries. This type of step adjustment would be consistent with “menu cost” models proposed by Ball and Mankiw (1994) to derive an asymmetric price response endogenously and by Sheshin-ski and Weiss (1977) to derive staggered relative price adjustment. However, the evidence showing sustained relative price increases in these items supports the presence of large sectoral shocks and relative price variability causing inflation, as suggested by Ball and Mankiw (1995). As discussed earlier models of Staggered relative price adjustment where causality runs in the reverse direction envisage only temporary changes in relative prices.

Outliers in the quarterly distribution of individual inflation rates may reflect seasonal and other factors that are not necessarily related to a sustained change in relative prices. However, if inflation rates are calculated over a given period on a cumulative basis, outliers would indicate goods that experienced a sustained change in their relative price.

Unweighted CPI data were used for this analysis because the very small weight typically given to cost-recovery items in consumer expenditures biases these price changes downward. Because these items are also intermediate inputs and affect the final prices of other goods, the use of CPI weights would distort the significance of these relative price changes.

Based on quarterly inflation data. A cumulative inflation distribution cannot be constructed for Russia because the commodity classifications change annually.

The weighting in the CPI plays an important role in the divergence in the two measures. In Moldova and Russia, nontradables received a very small weight in the overall CPI; hence, for a given real appreciation (defined as an increase in the prices of nontradables relative to tradables), the relative CPI-based measure would be lower than the ratio of nontradables to tradables prices.

Using differences in traded goods prices as evidence of undervaluation, however, is of questionable validity given that a sizable body of empirical evidence demonstrates that international differences in price levels of similar traded goods are large and persistent even across industrial countries (Rogoff, 1996). Kravis and Lipsey (1982) argue that international price differences for tradables are large enough to suggest a substantial nontradable element.

The two measures yield similar results if the ratio of nontradables to tradables prices in trading partners is relatively stable and there is close price arbitrage in traded goods; that is, tradables prices increase at similar rates domestically and abroad (De Gregorio, Giovannini, and Wolf, 1993; Lipschitz and McDonald, 1991), If domestic tradables prices rise faster, consistent with gradual price arbitrage, the relative prices of nontraded to traded goods need not change, but the CPl-based measure would show a real appreciation.

A generous assumption of an annual total factor productivity growth in tradables of 5 percent was made to bias the implied productivity growth in nontradables upward. If productivity growth in tradables is lower, the implied productivity growth in nontradables will be lower as well.

For a more detailed discussion of policy implications for the design of disinflation programs see Coorey, Mecagni, and Offerdal (1997).

    Other Resources Citing This Publication