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Relative Price Convergence in Russia

Author(s):
International Monetary Fund. Research Dept.
Published Date:
January 1996
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High open inflation appeared in 1991 in Russia as a result of partial price reforms and the de facto loosening of price controls.1 Following the January 2, 1992, comprehensive price liberalization and the associated price jump, monthly inflation rates remained in the double digits during most of the next three years.2 By the end of 1994, consumer prices had increased by almost 2,000 times compared to December 1990 (Figure 1, top panel).

Eliminating controls allowed prices to become market determined. It is commonly accepted that relative prices were highly distorted under central planning and that liberalization prompted major shifts in the price structure. Supportive evidence typically consists of selected examples of goods (and more rarely services) for which the relative price change has been particularly conspicuous. However, to our best knowledge, no systematic empirical analysis of the realignment of relative prices has yet been undertaken showing to what extent and how fast prices in Russia have converged to some market economy benchmark.

Figure 1.Price Levels and Relative Prices

(December 1990=100, log scale)

Sources: Goskomstat of the Russian Federation; and authors’ calculations.

a Relative to the overall CPI, linking the hybrid CPI (1991–92) and the expanded CPI (1993–94).

b Excluding alcohol and tobacco.

This paper explores this question for consumer prices, using several large data sets ranging from 1980 to 1994.3 Price convergence can be thought of along several dimensions. Section I examines the realignment of average nationwide domestic relative prices in the wake of the freeing of prices and the associated removal of subsidies; it also documents the increasing synchronization of price-setting as agents adapt to a high inflation environment. Section II offers alternative measures of the movement of the overall price level in Russia toward international heights. Section III discusses the evolution of regional price disparities within Russia as a way to assess market integration. Section IV summarizes the main findings of the paper and outlines areas for further research.

I. Realignment of Domestic Relative Prices

At any level of disaggregation of the overall consumer price index (CPI) and at any frequency, it is immediately apparent that inflation rates varied a lot across items or groups of items, implying that relative domestic consumer prices changed considerably over time. This section analyzes the timing, direction, and permanence of these shifts in the structure of relative prices, and identifies a number of long-run changes and trends. In addition, some insights are offered on the short-run dynamics of open inflation.

Pre-Versus Post-Liberalization Prices

The evolution of individual relative prices suggests that during the 1980s—i.e., even before prices were liberalized—the structure of domestic administered prices was not completely frozen. For example, the relative price of vodka surged between 1985 and 1990 in connection with the antialcohol campaign launched in the early stages of perestroika. The April 1991 retail price adjustments translated into large increases in the relative price of a number of items (e.g., meat and meat products, butter, sugar, bread, potatoes, and many electrical appliances) and large drops in the relative price of others (e.g., vodka and construction materials). The January 1992 liberalization led to very significant changes, including large increases for some items (such as meat, canned fish, butter, cheese, sugar, refrigerators, washing machines, and construction materials), and large declines for others (such as eggs, bread, vodka, many electronic entertainment goods, watches, sewing machines, and bicycles). As a result, by 1992, the relative price of many goods had changed considerably compared with 1980 (Figure 2).

Figure 2.Relative Price Change for Selected Goods in Stores. 1992 versus 1980

(Percent)

Sources: Goskomstat of the Russian Federation: and authors’ calculations.

During the 1980s and even more so in 1991, food prices in city markets, which had been free all along, typically increased faster than prices in stores for those items that were sold through both channels, reflecting repressed inflation. In 1992, following price liberalization, food prices rose much less in city markets than in stores. While by 1991 prices in city markets were typically two to four times higher than in stores, prices in the two types of outlets broadly converged in 1992.4

Table 1.Cross-Correlations of Price Structures Prices in Stores
All goods1985199019911992Dec. 1992June 1993
19800.980.990.980.960.620.63
19851.000.990.950.940.550.55
19901.000.980.950.610.61
19911.000.960.680.68
19921.000.750.75
Dec. 19921.000.99
Foodstuffs1985199019911992Dec. 1992June 1993
19800.990.980.990.950.940.82
19851.000.990.990.950.930.79
19901.000.970.910.880.74
19911.000.950.940.79
19921.000.980.90
Dec. 19921.000.87
Nonfood goods1985199019911992Dec. 1992June 1993
19800.980.990.970.940.590.59
19851.000.990.930.910.500.51
19901.000.970.920.560.57
19911.000.940.630.64
19921.000.740.74
Dec. 19921.000.99
Prices in City Markets
Foodstuffs1985199019911992Dec. 1992June 1993
19800.970.950.930.930.920.96
19851.000.980.980.980.960.94
19901.000.990.970.980.92
19911.000.990.990.88
19921.000.970.86
Dec. 19921.000.88
Sources: Goskomstat of the Russian Federation; and authors’ calculations.
Sources: Goskomstat of the Russian Federation; and authors’ calculations.

It is difficult, however, to compare the overall magnitude of relative price shifts without some summary measure. One such indicator is the correlation between price structures over time (or space).5 The cross-period correlation coefficients shown in Table 1 confirm that relative prices changed moderately during the 1980s, that they shifted more significantly in 1991, and that the largest changes took place in 1992. The cross-correlations also suggest that the structure of relative prices in city markets was much less affected by price liberalization than that of prices in stores.6

As already noted, seasonality may distort comparisons involving a given month and a yearly average. Using end-1990, end-1991, end-1992, and end-1993 prices for a similar (albeit slightly different) set of goods, analogous cross-correlations controlling for potential seasonal biases corroborated the above conclusions.7 Furthermore, the correlations suggest that the bulk of the relative price changes had taken place by end-1992, especially for nonfood goods. They also highlight continuing changes in the structure of food prices in 1993, probably as a result of adjustments in the structure of subsidies.

Although the above correlations between price structures are informative global measures of relative price changes, they suffer from two shortcomings. First, the sample under consideration excludes services, the prices of which behaved very differently from that of goods. Second, the sample is fairly small and items are unweighted, which might produce misleading results.8

At the most aggregate level, the prices of “paid services” increased much less than that of goods in April 1991 and January 1992 (Figure 1, bottom panel).9 However, a very rapid catch-up began after the early 1992 jump in the overall price level. By late 1992, the relative price of services had returned to its December 1990 level, and by late 1994, it had surged to about five times that level. In part, this process reflected the commercialization of a number of services such as child and health care that were previously provided for a nominal fee. It also reflected the adjustment of cost recovery ratios from a very low basis, for example in the case of housing, with rents rising by almost 500 times between end-1992 and end-1994, compared to a 30-fold increase in the overall CPI. A similar U-curve pattern for the relative price of services has been observed in many other countries of the former Soviet Union.10 It is also reflected in the evolution of the share of services in household expenditures, which fell through 1992 but then rebounded, although by 1994 it was still extremely low compared to market economy standards (Figure 3).11

Whereas the trends in service prices are invariant to the choice of the price index, the evolution of food prices depends on which measure of consumer prices is selected. Based on the “hybrid CPI,” the price of food relative to the overall CPI declined rapidly after a spike associated with the January 1992 price jump and hovered around 85 percent of its December 1990 reference level between mid-1992 and end-1994 (Figure 1, bottom panel); based on the “urban CPI,” however, the relative price of food fell less after January 1992 and remained at about 120 percent of its December 1990 level through 1994.12

Further insights into the shifts in relative prices emerge from a more disaggregated analysis. Data for the full decomposition of the CPI were obtained for July 1993 and July 1994,13 and prices covering a bit more than half of the CPI were reconstructed for January and July 1992.14 The trends described above are reflected in the evolution of individual prices.15

The magnitude of the relative price changes confirms that the broadbased liberalization that took effect on January 2, 1992, did not instantaneously bring about a new stable relative price structure, not least because a large number of prices temporarily remained subject to federal or local price controls before they were freed. Specifically, the relative price of those items that were free of controls early on changed little from mid-1992 onward: for example, the prices of potatoes, apples, and eggs moved broadly in line with the overall CPI.16 The prices of some food items and of some medicines rose substantially more than the overall CPI once subsidies were cut. For example, the relative price of milk rose a lot during the first half of 1992 as subsidization was reduced, and grew further between mid-1993 and mid-1994 for the same reason. The relative price of bread doubled between mid-1993 and mid-1994, reflecting the sharp reduction in subsidies in the fall of 1993. At the same time, the relative price of aspirin and other analgesics rose tremendously as a result of import subsidy cuts, termination of humanitarian aid in kind, and decontrol measures. The price of electricity rose much less than the overall CPI through mid-1993 but much faster thereafter, reflecting a deliberate policy to raise cost recovery ratios.17 A similar price path was registered for many other services.

Figure 3.Structure of Household Consumption: International Comparison

(Percent)

Sources: Goskomstat (Russia): GUS (Poland): National Statistical Institute (Portugal): INSEE (France): Bureau of Economic Analysis (United States); and authors’ calculations.

aIncluding utilities.

Other reasons underlying the instability of relative prices after January 1992 include sheer uncertainty (see below) and sectoral or aggregate demand and supply shocks causing shifts in the equilibrium relative price structure. For example, the ten-fold real exchange rate appreciation between January 1992 and mid-1994 heightened import competition and contributed to the significant relative price declines recorded for some foodstuffs (such as sugar, vegetable oil, vodka, and tea) and some nonfood items (including a number of consumer durables).

Short-Run Open Inflation Dynamics

Although inflation declined in the first half of 1992 following the price jump associated with generalized decontrol, macroeconomic stabilization failed and a regime of chronic high inflation set in. One way to analyze the trajectory of the price level in this context would be to relate inflation to the evolution of the potentially relevant monetary and credit aggregates, as done by Koen and Marrese (1995). A somewhat different and less conventional perspective on the dynamics of inflation involves the analysis of the link between relative price variability and overall inflation. In principle, these variables could be positively or negatively correlated, or display no stable relationship whatsoever.18 In practice, the results offered by the empirical literature on this subject vary depending on the country, the period, and the level of disaggregation.

For Russia, monthly inflation rates for 66 food items and 87 nonfood goods have been published by Goskomstat (1994) for the period 1992–93. Based on 1993 weights, these items cover 75 percent of the overall CPI (88 percent of the food, beverages, and tobacco component and 66 percent of the nonfood goods component).

The measure of relative price variability used here is analogous to the indices that are traditionally used in the literature, and can be described as a weighted variance:

with

where ωi and πi denote the weight and monthly percent change in price associated with item i. The weights used come from the 1993 CPI, thus reflecting 1992 expenditure patterns, and are normalized to sum to unity.19

Figure 4 illustrates the evolution of relative price variability for all goods as well as for food and nonfood goods separately. The inflation rates shown are the weighted arithmetic averages of the inflation rates for the individual items. January 1992 is excluded because the price changes associated with the one-time jump are orders of magnitude larger and inherently different from subsequent ones.20 The underlying distributions of the inflation rates across all goods in February 1992 and December 1993 for Russia are shown in the top half of Figure 5; for comparative purposes, analogous distributions for France and the United States are presented in the bottom half. Several lessons can be drawn from Figures 4 and 5.

First, while relative price variability subsided in the course of the first half of 1992, it remained very high throughout the period under consideration in comparison with market economies. Specifically, it was more than 20 times larger on average in 1993 than in the United States and France.21 Even the minimum value of relative price variability in the Russian sample (reached for nonfood goods in July 1992) was more than three times higher than the corresponding measure in the United States and France.

Second, relative price variability for food from mid-1992 onward was almost constantly higher than for nonfood goods, the only exceptions being October and November 1992. In 1993, relative price variability for food was on average more than two times larger than for nonfood goods. One plausible explanation for this apparent regularity is that seasonality affects food prices more than nonfood goods prices.22 In this regard, it is worth noting that in the United States and France as well, relative price variability is typically two to three times higher for food than for nonfood goods.

Figure 4.Relative Price Variability and Inflation for Goods

(Monthly inflation rates in percent)

Sources: Goskomstat of the Russian Federation (1994); and authors’ calculations.

Figure 5.Distribution of Inflation Rates for Goods

(Percent)

Sources: Goskomstat of the Russian Federation (Russia): Bureau of Labor Statistics (United States); INSEE (France): and authors’ calculations.

Table 2.Inflation and Relative Price Variability: Regression Resultsa(t-statistics in parentheses)
Regressors
Dependent variable: variabilitybConstantInflationChange in inflationDummyc
Durbin-Watson
All goods264.79.2331.10.851.64
(5.4)(4.1)(-10.5)
328.55.18.2–316.00.892.35
(8.4)(2.8)(3.9)(-12.8)
Food182.27.4–221.90.622.27
(3.2)(2.8)(-5.9)
241.74.35.9–216.20.652.00
(3.9)(1.4)(1.9)(-5.4)
Nonfood goods271.315.0–428.70.502.41
(1.8)(2.6)(-3.8)
465.910.616.1–554.70.432.66
(2.6)(1.5)(1.9)(-4.0)
Sources: Goskomstat of the Russian Federation (1994); and authors’ calculations.

Based on monthly observations for February 1992–December 1993, and using ordinary least squares.

As defined in equation (1).

Dummy equals zero prior to July 1992 and 1 from July 1992 onward.

Sources: Goskomstat of the Russian Federation (1994); and authors’ calculations.

Based on monthly observations for February 1992–December 1993, and using ordinary least squares.

As defined in equation (1).

Dummy equals zero prior to July 1992 and 1 from July 1992 onward.

Third, the average level of relative price variability was much lower in 1993 than in 1992. This is consistent with the earlier finding that most of the relative price changes for goods had taken place by the end of 1992. It is also consistent with the presumption that as agents became more familiar with chronic high inflation, price setting became increasingly synchronized across goods.23

Fourth, relative price variability and inflation display a strong positive correlation, as suggested by Figure 4 and confirmed by the regressions in Table 2.24 For nonfood goods, the April-May 1992 spike in variability, which accounts for the poor correlation of variability and inflation during the first half of the year, is overwhelmingly caused by very large increases in the price of gasoline.25 Apart from this episode, variability and inflation move closely together. Adding the change in inflation among the independent variables suggests that an acceleration in the overall price level is accompanied by greater relative price variability, and vice versa.

The dummy variable introduced in the regressions captures the shift in the relationship between variability and inflation that occurred around mid-1992, and which can be thought of as a regime switch. In the immediate aftermath of the initial price jump, some prices were adjusted downward and others increased substantially as price setters developed a perception of new overall and relative price levels. Some confusion about their true values persisted for several months and entailed significant further relative price adjustments.26 By midyear, however, much of this uncertainty had abated and a new regime of high, chronic inflation set in.

In the longer run, the positive correlation between relative variability and inflation may weaken. Indeed, one would expect agents to compete away an increasing portion of relative price variability as high inflation becomes entrenched, and more vigorously so as inflation rises. Ultimately, price setters are likely to coordinate price adjustments by responding to a visible and unambiguous high-frequency signal such as the exchange rate, and virtually all domestic prices will be moving in line with the latter.27 In the extreme case of a hyperinflation, the variability of relative prices may thus turn out to be quite small.

Among the potential extensions of the regression analysis conducted here would be to relate relative price variability separately to anticipated and unanticipated inflation.28 One hypothesis worth testing in such a framework would be that relative price variability is more closely linked to inflation surprises than to the expected component of inflation.29

II. International Convergence of the Overall Price Level

The previous section analyzed the movements of domestic relative prices following price liberalization. This section examines the extent to which domestic price levels have converged to international levels after the freeing of prices. No attempt is made to compare the gap between domestic and foreign prices before and after January 1992 because information on pre-1992 prices is relatively scanty,30 and because the complex system of multiple exchange rates in place until the end of 1991 would render such a comparison extremely difficult. Exchange rate unification only occurred in mid-1992,31 implying that even the price level comparisons presented below for the first half of 1992 and based on the interbank exchange rate are somewhat perilous and tend to understate the Russian price level.

The Price of Staples

One indicator occasionally referred to in Russia to evaluate the gap between domestic and international prices is the price of a basket of 19 staples considered as a minimum food consumption standard. This basket covers about one half of the food component of the Russian CPI at 1993 weights (excluding alcoholic drinks).32 If the U.S. price of this basket is taken as a benchmark, this measure suggests that Russian prices rose from 4 percent of “international levels” in January 1992 to one fourth in December 1993, and to almost one third in December 1994 (Figure 6, bottom panel). If the price in France is used instead, the measure implies that Russian prices rose from 3 percent of “international levels” in January 1992 to close to one fifth in December 1993 and slightly above one fifth in December 1994.33

Since a number of the staples included in the basket are often subsidized by local governments in Russia, it may seem that the price level ratio derived from this basket should be viewed as a lower bound for the overall price level. While this is a plausible conjecture as far as goods prices are concerned, it is not clear a priori whether it would still hold if service prices are taken into account. As discussed above, the relative price of a number of important services remained extremely low throughout 1992–94. meaning that the overall consumer price level in Russia was lower than what goods prices alone would indicate.

Figure 6.International Comparison of Price Levelsa

Sources: Goskomstat of the Russian Federation; Center for Economic Analysis; INSEE; U.S. Bureau of Labor Statistics; and authors’ calculations.

aUsing the exchange rate quoted on the MICEX.

bP denotes a Paasche, Russian-weighted index, and L, a Laspeyres, French-weighted index.

cBasket of 19 staples.

Broader Price Measures

In order to cover a more representative sample of consumer goods and services, a systematic comparison with contemporaneous French prices was attempted for all the items of the Russian CPI.34 Whenever applicable, the lowest quality variety appearing in the French nomenclature was used so as to account for the likely quality differentials. Not surprisingly, matching failed for many items, mostly because of insufficiently precise specifications or absence of a counterpart. Nevertheless, the coverage was extended significantly compared with the basket of staples.

The Russian data set for January 1992 was more limited than for subsequent dates, mainly because no service prices were available for that month. Two separate comparisons were therefore conducted. The first was for goods only, starting in January 1992, with matches achieved for 74 percent of foodstuffs and 25 percent of nonfood goods, jointly representing 51 percent of the overall CPI (all at 1993 Russian weights). The second comparison pertained to a broader set of goods and services, starting in July 1992, with matches achieved for the same 74 percent of food goods, 29 percent of nonfood goods, and 29 percent of services, altogether covering 54 percent of the overall CPI (also at 1993 Russian weights).

Cross-country price level ratios can be computed in several ways. Since the weights of the main groups of items in household expenditures are dramatically different in Russia from what they are in France (Figure 3), and since domestic relative price structures also differ enormously, one would expect the results to be sensitive to the formula that is selected. One way to measure the distance between Russian and French price levels is to define a Paasche-type index, P, based on Russian weights:

where

with i indexing the items for which matches were achieved, and R denoting Russia and F, France.

An alternative approach involves the use of French rather than Russian weights, and the computation of a Laspeyres-type index, denoted L:

where

There is no compelling reason to prefer domestic or foreign weights in a bilateral price level comparison. If a single point-estimate were to be sought, a measure such as a Fisher-type index (i.e., an equi-weighted geometric average of L and P) would be an agnostic compromise. However, given the data limitations, it may be preferable to think of the Paasche and Laspeyres indices as delineating an estimated range for the price level ratio.

The results of the first comparison, shown in the top left panel of Figure 6, are broadly in line with those obtained above for the basket of 19 staples. The Paasche index for food prices increased from less than 2 percent in January 1992 to 8 percent in mid-1992, 10 percent in mid-1993, and 21 percent by mid-1994.35 It also appeared that the domestic price of nonfood goods relative to France was consistently higher than for foodstuffs but followed a similar path, rising from less than 3 percent in January 1992 to 13 percent in mid-1992, 17 percent in mid-1993, and 35 percent by mid-1994. The use of the corresponding Laspeyres indices produced very similar results.

The results of the second comparison appear in the top right panel of Figure 6. The point estimates of the level of service prices are much more sensitive to the choice of the weights than those for goods. Nevertheless, both the Paasche and the Laspeyres measures indicate that the domestic price of services compared to France started from an extremely low level in mid-1992, and that although it rose faster than that of goods, it remained well below the latter by mid-1994. The inclusion of services into an overall consumer price level comparison therefore brings down the ratio of Russian to French prices. Broadly speaking, consumer prices in Russia rose from about 6–7 percent of the French level in July 1992 (immediately following exchange rate unification) to 20–22 percent in July 1994. This is almost exactly in line with the estimates derived based on the basket of 19 staples, reflecting the offsetting effects of higher relative prices for nonfood goods and of lower relative prices for services.

The gap between domestic and foreign prices thus narrowed between 1992 and 1994, but remained very wide in mid-1994. The relatively swift movement toward international price levels in the early phase of the transition is consistent with the pattern described by Halpern and Wyplosz (1995) in their cross-country study. The persistence of a chasm between the price level in Russia and that in market economies is consistent with the well-known positive correlation between per capita income and price levels.36 The law of one price clearly does not apply to nontradables such as services, but it also fails for tradables insofar as the latter are subject to import or export tariffs or quotas. Even when no restrictions or taxes come into play, the price of highly tradable items embodies a nontradable component in the form of distribution costs. Given the very low dollar wage levels prevailing in Russia, one would expect prices in Russia to be well below those in comparator market economies.

III. Regional Disparities

Geographical price and nominal income dispersion has traditionally been very pronounced in Russia, not least owing to the vastness of the country and the harshness of its climate, which implied substantial distribution costs. Unfortunately, the available data do not allow us to judge whether prices across regions converged or diverged as a result of the transition.37 It is nevertheless possible to examine the evolution of price dispersion measures following the January 1992 price liberalization in order to assess the evolution of market integration.

Table 3.Geographical Price Dispersion for Food and Nonfood Goodsa

(average coefficient of variation, in percent)b

FoodstuffscNonfood goodsd
March 19923728
July 19932525
June 19941717
Memorandum item: Canada 1991e13
Sources: Statistical Bulletin of the Statistical Committee of the Commonwealth of Independent States (various issues); Center for Economic Analysis; Statistics Canada, Consumer Prices and Price Indexes, various issues; and authors’ calculations.

The statistics shown pertain to a sample of 9 cities (Moscow, Chelyabinsk. Ekaterinburg, Kazan, Nizhni Novgorod, Novosibirk, Saint Petersburg, Volgograd, and Voronezh). For March 1992, information was available for an extra 10 cities (Arkhangelsk, Krasnodar, Kemerovo, Pskov, Ryazan, Samara, Smolensk, Stavropol, Tambov, and Vologda) and the dispersion coefficients are 38 percent for foodstuffs and 28 percent for nonfood goods.

For Russia, weighted average of item-specific coefficients of variation, with weights reflecting the share of the items in the CPI.

Representing about half of the weight of food items in the CPI.

Representing about one sixth of the weight of nonfood goods in the CPI.

For Canada, equi-weighted average of item-specific coefficients of variation, based on retail prices for 60 food goods for the first week of January, April, July, and October, 1991, and covering a sample of 25 cities (St. John’s, Charlottetown, Sydney, Halifax, Moncton, Saint John, Chicoutimi, Quebec, Trois Rivieres, Sherbrooke, Montreal, Hull, Ottawa, Toronto, Hamilton, London, Sudbury, Thunder Bay, Winnipeg, Regina, Saskatoon, Edmonton, Calgary, Vancouver, and Victoria).

Sources: Statistical Bulletin of the Statistical Committee of the Commonwealth of Independent States (various issues); Center for Economic Analysis; Statistics Canada, Consumer Prices and Price Indexes, various issues; and authors’ calculations.

The statistics shown pertain to a sample of 9 cities (Moscow, Chelyabinsk. Ekaterinburg, Kazan, Nizhni Novgorod, Novosibirk, Saint Petersburg, Volgograd, and Voronezh). For March 1992, information was available for an extra 10 cities (Arkhangelsk, Krasnodar, Kemerovo, Pskov, Ryazan, Samara, Smolensk, Stavropol, Tambov, and Vologda) and the dispersion coefficients are 38 percent for foodstuffs and 28 percent for nonfood goods.

For Russia, weighted average of item-specific coefficients of variation, with weights reflecting the share of the items in the CPI.

Representing about half of the weight of food items in the CPI.

Representing about one sixth of the weight of nonfood goods in the CPI.

For Canada, equi-weighted average of item-specific coefficients of variation, based on retail prices for 60 food goods for the first week of January, April, July, and October, 1991, and covering a sample of 25 cities (St. John’s, Charlottetown, Sydney, Halifax, Moncton, Saint John, Chicoutimi, Quebec, Trois Rivieres, Sherbrooke, Montreal, Hull, Ottawa, Toronto, Hamilton, London, Sudbury, Thunder Bay, Winnipeg, Regina, Saskatoon, Edmonton, Calgary, Vancouver, and Victoria).

Falling Geographical Dispersion

There are reasons to expect geographical price dispersion to have been high in early 1992 and to have declined thereafter. Uncertainty about actual new relative prices was probably more pronounced in the immediate aftermath of the price jump than one or two years later and may have contributed to price dispersion. In addition, remaining local subsidization or other controls differed across regions depending inter alia on their wealth and on local politics, but presumably declined over time.

The average coefficients of variation presented in Table 3 point to a reduction in cross-regional dispersion both for food and nonfood goods prices.38 Also noteworthy is the fact that the dispersion was initially larger for food than for nonfood goods, probably because of more extensive residual subsidization and trade barriers for the former, but that by mid-1993, the dispersion was of the same order of magnitude for the two categories of goods.

Even by mid-1994, the level of geographic price dispersion remained on the high side compared to market economy standards.39 In Canada—which among industrialized countries comes closest to Russia as far as climate and distances are concerned—the average coefficient of variation for food items was on the order of 13 percent, that is, somewhat lower than the estimate for Russia as of mid-1994.

Residual Subsidization

While information on regional price disparities in general is limited, data have been published on the price of the aforementioned 19 staples basket across a large number of cities from early 1992 onward. The coverage of outlets, however, changed in the second half of 1992, when it was extended to include city markets alongside stores. The impact of this modification on the price dispersion measures shown in Table 4 (coefficient of variation, maximum over minimum ratio, and decile ratio) is a priori ambiguous. Thus, the only relevant comparisons over time pertain to June versus February 1992 on the one hand, and to end-1992, end-1993, and end-1994 on the other.40

In contrast to the result derived above for a set of broadly similar individual food items, the dispersion indicators point to a significant increase in geographical variation from end-1992 to end-1993, possibly owing to an increasing divergence in local subsidization levels. Consistent with the earlier results, however, they show a slight decline between end-1993 and end-1994.41 To a large extent, the discrepancy between the results displayed in Tables 3 and 4 is due to the fact that the sample used in Table 3 was much smaller and did not include cities of the far east or the far north. Controlling for the difference in geographical coverage, as is done in the bottom line of Table 4, helps reconcile the results and suggests that after price liberalization at the federal level in early 1992, local subsidies became relatively more important in the colder and more remote parts of the country.42

Table 4.Geographical Price Dispersion for a Basket of Staplesa
199219931994Memorandum item:
Feb.bJunebDec.cDecDec.cCanada 1991d
Coefficient of variation (in percent)18.518.722.034.130.16.5
Maximum/minimum2.42.73.85.05.11.3
Top decile/bottom decile1.82.02.12.82.41.3
Number of observations999197629825
Memorandum item:
Coefficient of variation for 9 citiese39.418.718.718.617.3
Sources: Goskomstat data published in Delovoy Mir and in the quarterly reports of the Center for Economic Analysis; Statistics Canada. Consumer Prices and Price Indexes, various issues; and authors’ calculations.

The sample of cities includes Abakan, Angarsk, Arkhangelsk, Arzamas, Astrakhan, Barnaul, Belgorod, Berdsk, Birobidzhan, Bryansk, Cherkessk, Chita, Divnogorsk, Dzerzhinsk, Gomo-Altaysk, Ishimbay, Izhevsk, Kaliningrad, Kaluga, Kamyshin, Kazan, Kemerovo, Kirov, Kirovo-Chepetsk, Kopeysk, Kostroma, Krasnodar, Krasnoyarsk, Kurgan, Kursk, Lipetsk, Magadan, Makhachkala, Maykop, Miass, Moscow, Murmansk, Naberezhnyye Chelny, Nalchik, Neftekamsk, Nizhni Novgorod, Nizhni Tagil, Norilsk, Novocheboksarsk, Novosibirsk, Novokuznetsk, Novorossiysk, Novyy Urengoy, Obninsk, Omsk, Orel, Orenburg, Orsk, Penza, Perm, Petropavlosk-Kamchatskiy, Petrozavodsk, Prokolyevsk, Pskov, Rostov-on-Don, Rubtsovsk, Ryazan, Rybinsk, Samara, Severodvinsk, Saint Petersburg, Salekhard, Saransk, Shakhty, Shebekino, Sovetsk, Syktyvkar, Syzran, Taganrog, Tambov, Tayshet, Tolyatti, Tomsk, Tuapse, Tula, Tver, Tyumen, Ufa, Ukhta, Ulyanovsk, Vladikavkaz, Vladimir, Vlagoveshchensk, Volgograd, Vologda, Volgodonsk, Vorkuta, Voronezh, Yaroslav, Yekaterinburg, Yakutsk, Yelets, Yoshkar-Ola, and Yuzhno-Sakhalinsk, but for some dates several observations were missing. The exact dates are February 18, 1992; June 23, 1992; December 8, 1992; December 28, 1993; and December 13, 1994.

Excluding city markets.

Including city markets.

A Canadian basket was constructed replicating the Russian basket of staples. The statistics shown are the averages of the statistics computed for the first week of January, April, July, and October, 1991. The geographical coverage is the same as in Table 3.

Moscow, Chelyabinsk, Yekaterinburg, Kazan, Nizhni Novgorod, Novosibirsk, Saint Petersburg, Volgograd, and Voronezh (same cities as in Table 3).

Sources: Goskomstat data published in Delovoy Mir and in the quarterly reports of the Center for Economic Analysis; Statistics Canada. Consumer Prices and Price Indexes, various issues; and authors’ calculations.

The sample of cities includes Abakan, Angarsk, Arkhangelsk, Arzamas, Astrakhan, Barnaul, Belgorod, Berdsk, Birobidzhan, Bryansk, Cherkessk, Chita, Divnogorsk, Dzerzhinsk, Gomo-Altaysk, Ishimbay, Izhevsk, Kaliningrad, Kaluga, Kamyshin, Kazan, Kemerovo, Kirov, Kirovo-Chepetsk, Kopeysk, Kostroma, Krasnodar, Krasnoyarsk, Kurgan, Kursk, Lipetsk, Magadan, Makhachkala, Maykop, Miass, Moscow, Murmansk, Naberezhnyye Chelny, Nalchik, Neftekamsk, Nizhni Novgorod, Nizhni Tagil, Norilsk, Novocheboksarsk, Novosibirsk, Novokuznetsk, Novorossiysk, Novyy Urengoy, Obninsk, Omsk, Orel, Orenburg, Orsk, Penza, Perm, Petropavlosk-Kamchatskiy, Petrozavodsk, Prokolyevsk, Pskov, Rostov-on-Don, Rubtsovsk, Ryazan, Rybinsk, Samara, Severodvinsk, Saint Petersburg, Salekhard, Saransk, Shakhty, Shebekino, Sovetsk, Syktyvkar, Syzran, Taganrog, Tambov, Tayshet, Tolyatti, Tomsk, Tuapse, Tula, Tver, Tyumen, Ufa, Ukhta, Ulyanovsk, Vladikavkaz, Vladimir, Vlagoveshchensk, Volgograd, Vologda, Volgodonsk, Vorkuta, Voronezh, Yaroslav, Yekaterinburg, Yakutsk, Yelets, Yoshkar-Ola, and Yuzhno-Sakhalinsk, but for some dates several observations were missing. The exact dates are February 18, 1992; June 23, 1992; December 8, 1992; December 28, 1993; and December 13, 1994.

Excluding city markets.

Including city markets.

A Canadian basket was constructed replicating the Russian basket of staples. The statistics shown are the averages of the statistics computed for the first week of January, April, July, and October, 1991. The geographical coverage is the same as in Table 3.

Moscow, Chelyabinsk, Yekaterinburg, Kazan, Nizhni Novgorod, Novosibirsk, Saint Petersburg, Volgograd, and Voronezh (same cities as in Table 3).

Looking at the ranking of specific cities, certain patterns emerge. The highest prices were consistently registered in areas such as the Far East (e.g., Magadan and Yuzhno-Sakhalinsk), and the lowest ones in areas such as the Volga region (Ulyanovsk and Kazan), partly reflecting differences in climate and transportation costs, but also local price policies.43 Notwithstanding the relative ordinal stability of the extrema, the overall cardinal ranking of cities changed substantially over time, particularly during the first half of 1992 (Table 5). In the course of 1993, significant further shifts occurred, which, as evident from Table 4, resulted in higher geographical price dispersion. During the third year following price liberalization, the ranking changed much less, as attested by the high correlation coefficient between end-1993 and end-1994 prices. The evolution over time of the relative price of staples across regions is presumably largely determined by changes in relative subsidization and administrative control levels, which in turn are conditioned by local policies and budgetary resources.

Table 5.Geographical Price Cross-Correlations for a Basket of Staples
Feb. 1992June 1992Dec. 1992Dec. 1993Dec. 1994
Feb. 19921.000.510.470.350.29
June 19921.000.720.610.62
Dec. 19921.000.670.72
Dec. 19931.000.89
Sources: as for Table 4.
Sources: as for Table 4.

IV. Conclusions

The empirical investigation conducted in this paper confirms that after their decontrol, prices in Russia moved closer to market levels. For goods, most of the permanent realignment in domestic relative prices had taken place by the end of 1992, even though some further shifts occurred in 1993–94. For services, convergence to market levels appears to be a more protracted process; by mid-1994, notwithstanding sharp increases in relative domestic terms, the prices of many important services remained far below advanced market economy levels.

Because of major discontinuities in the exchange rate regime, it remains difficult to pass judgment on the impact of the transition on the gap between the domestic overall price level and the level prevailing abroad. However, it is clear that this gap, which was huge in January 1992, has narrowed substantially. Similarly, while the effect of the transition on geographical price dispersion within Russia cannot be assessed, it was possible to establish that the degree of integration of the domestic goods market, particularly for nonfood items, seems to have increased since early 1992.

It would be hazardous, however, to view these results as more than early, indicative ones. While some of the trends identified in this paper are probably robust to the use of alternative indices and superior samples, others are ambiguous and need further substantiation. In particular, the comparison of international price levels carried out here is extremely tentative,44 as is the analysis of geographical price dispersion.45

Several promising areas for further research can be identified. The first is to expand the samples used in this paper in order to assess the robustness of its main results. In particular, the inclusion of more recent data would reveal whether the incipient trend toward greater synchronization in price setting uncovered looking at 1992–93 inflation rates continues in 1994 and beyond. Longer time series would also permit a potentially interesting investigation of the impact of seasonality on relative price variability.46 Furthermore, it would be worthwhile to examine to what extent the results obtained for Russia can be generalized to other economies in transition.47

A second area for further work would involve extending the analysis to producer prices. Highly disaggregated industrial producer price data exist and could be exploited, albeit taking into account the complication of arrears. The latter have not played a large role for cash-based, retail transactions but have been ubiquitous at the noncash, wholesale level. Based on producer prices, convergence toward international levels may well be more advanced than for consumer prices because of the larger share of nontradables in the CPI than in the PPI.48 Indeed, the speed of convergence has been more rapid for producer prices, which rose almost twice as much as consumer prices in Russia between December 1990 and December 1994, with the bulk of the faster growth occurring in 1991–92. But in the absence of level estimates, this evidence is not sufficient to confirm that the gap between domestic and international prices is narrower for producer prices.

A third set of issues worthy of further research pertains to the pathology of inflation, as opposed to the morphological approach adopted in this paper. As longer time series become available, quantitative work could be carried out on the dynamic interaction of money and credit, arrears, relative consumer and producer prices, and the overall price level. In this context, the neutrality or influence of market structures could also be examined.

REFERENCES

Paula De Masi is an Economist in the Research Department. She holds a Ph.D. from Harvard University. Vincent Koen is a Principal Administrator at the OECD. At the time of writing, he was an Economist in the IMF’s Research Department. He holds a Ph.D. from MIT. Suggestions and other inputs from Gerard Belanger, Andrew Berg, Aleš Bulíř, David T. Coe, François Lequiller, Bogdan Lissovolic, Anthony Richards, and Bryan Roberts are gratefully acknowledged.

Previous episodes include the hyperinflation of the early 1920s and a period of chronic high inflation in the 1930s and 1940s.

For details, see Koen and Phillips (1993).

The data are presented in De Masi and Koen (1995).

The remaining spread may reflect quality differences or local price controls.

Berg (1994) computes such a measure for Poland.

The relative price structure in city markets was nevertheless affected because some of the items sold in city markets were also sold in stores, and because of nonzero cross-product demand elasticities.

The raw data appear in Goskomstat (1994). For the sake of brevity, the correlations are not reported here.

The weights of individual items in the CPI vary considerably. Vodka by far carries the largest weight (9.34 percent, almost twice as much as the second largest element, sugar). A number of items for which no household budget survey information is available, but which are presumably a small proportion of the CPI, are given the minimal weight of 0.01 percent.

Many services are (or were) public “goods” and therefore do not (or did not) appear in the CPI, hence the qualifier “paid.”

For example, in the Baltic countries, Kazakstan, Ukraine. Armenia. Azerbaijan, and Tajikistan. See De Masi and Koen (forthcoming).

The price of services typically also rises more rapidly than the overall CPI in market economies, but not that much faster. In the United States, for instance, it rose by 15.7 percent between end-1990 and end-1994. compared to an 11.9 percent increase for the overall CPI.

The differences between the “hybrid” and “urban” CPIs are described by Koen and Phillips (1992).

The numbers were directly provided by Goskomstat. The complete list of items appears in Russian in Goskomstat (1993) and in English in Granville and Shapiro (1994).

Based on Goskomstat price tables published weekly by Delovoy Mir and on data provided directly by the Center for Economic Analysis.

See Table A3 in De Masi and Koen (1995).

The comparison with January 1992 is difficult because of seasonality.

See IMF (1995).

See Fischer (1982). Goel and Ram (1993). and the references therein.

An analogous measure based on geometric rather than arithmetic averaging of item-specific price changes was also computed, but none of the results reported below was qualitatively affected.

Relative price variability for all goods was 86 times larger in January than in February 1992, and the average January jump in the price level for goods amounted to 347 percent versus a 24 percent increase in February.

Monthly values for variability measures analogous to those computed for Russia were calculated for the United States, based on a set of 60 food items and 60 nonfood goods (using 1994 price indices from the monthly CPI Detailed Report and 1993 weights from the bulletin on the Relative Importance of Components in the Consumer Price Index, both published by the U.S. Bureau of Labor Statistics), and for France, based on a set of 79 food items and 123 nonfood goods (using 1994 observations and weights as published in the INSEE’s Bulletin Mensuel de Statistique),

Chart 3 in Koen (1994) suggests that seasonal variations are very large for food prices on city markets. The behavior of the price of some individual food items (e.g., apples, carrots, and beets) also points to strong seasonal variability. Some nonfood goods prices are also subject to large seasonal swings (e.g.. some clothing items).

An extension of the analysis to 1994 if and when the necessary data become available would allow a more confident confirmation or refutation of this conjecture.

It could be argued that the regression equation should be specified differently as greater relative price variability may cause greater inflation, for instance because of asymmetric price responses to disturbances (in the form of downward inflexibility). However, the purpose of the regressions in Table 2 is to establish a correlation more than to test for causality.

In April 1992. gasoline alone accounted for67 percent of the variability of relative nonfood goods prices and in May. for 90 percent.

This confusion is reflected in the widely different estimates for the size of the price jump and for inflation in the early months of 1992 associated with alternative retail/consumer price indices, see Koen and Phillips (1993), Table 2.

Symptomatic is the following description of the foreign exchange market in early 1995: “Only about half an hour will pass after the beginning of tenders and thousands of pagers will beep and thousands of telephones will ring announcing the news about the new exchange rate of the dollar. A little more time will pass and the money-changing offices will post new figures on their doors and the announcers on practically all the television and radio stations will interrupt themselves in order to expressively read a couple of four-digit figures …” (Kommersant Daily, February 3, 1995, p. 5).

One way to distinguish between the two components of inflation would be to identify them with the fitted value and the residual respectively from a regression of inflation on lagged money or credit.

Goel and Ram (1993) find that this is indeed the case in the United States.

Particularly on black market prices and volumes.

The basket reflects the minimum food consumption required for a 45-year-old. able-bodied worker as defined by the former USSR State Committee for Labor and Social Problems.

The two measures differ because the price of the basket is higher in France and because of changes in the franc/dollar exchange rate over the period under consideration

Average prices in France arc published in the INSEE’s Bulletin Mensuel de Statistique, France was selected as the comparator country because of the availability of fairly detailed price level data and the familiarity of one of the authors with the empirical content of this information.

Richards and Tersman (1995) find that food prices in Latvia in March 1994 were about 37 percent of the Swedish level.

Rationalized by Balassa (1964) and Samuelson (1964), among others. In this respect, the selection of France influences the point estimates presented above but given the order of magnitude of the price level gap. the same qualitative results would have been obtained using other market economies as a benchmark.

Regional inflation rates have been published but in the absence of information on regional price levels for some base period, it cannot be established whether differential price increases entailed convergence or divergence of price levels across regions.

The data sources and coverage are described in Table 3. The subset of foodstuffs is very similar to the one constituting the basket of 19 staples. No information on local services prices was available.

Some dispersion is observable even in market economies, as noted long ago by Mills (1927) for the United States.

Apart from the change in coverage, seasonality would also render the comparison with February and June 1992 hazardous.

The max/min ratio rises a little but is a less relevant measure of dispersion than the decile ratio, which clearly drops.

Another difference between Tables 3 and 4 is that Table 3 was for midyear rather than end-year data, and was based on averages of individual coefficients of variation rather than coefficients of variation for the price of a basket.

As denoted by its name, Ulyanovsk is Lenin’s birth place. The local authorities took steps to limit exports of agricultural products to other regions in order to ensure local supply at low, controlled prices.

The European Comparison Program results for 1993, due to be released in 1996, should shed some further light on this comparison.

Far more comprehensive data than those we had access to seem to exist at Goskomstat and would permit a more thorough investigation.

In the United States and France, seasonality probably accounts for a quarter or more of the total relative price variability for goods at a 100–200-item level of disaggregation.

Such an investigation is currently under way. see De Broeck, De Masi, and Koen (1995) and De Masi and Koen (forthcoming).

As noted by Froot and Rogoff (1994). this point was made by Keynes in his 1925 pamphlet on The Economic Consequences of Mr. Churchill,

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