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Relative Price Convergence in Russia

Author(s):
Paula De Masi, and Vincent Koen
Published Date:
June 1995
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I. Introduction

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 (Chart 1, top panel).

Chart 1RUSSIA Price Levels and Relative Prices December 1990-December 1994

(December 1990=100, log-scale)

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

1/ Relative to the overall CPI, linking the hybrid CPI (1991-92) and the expanded CPI (1993-94).

2/ Excluding alcohol and tobacco.

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.

This paper explores this question for consumer prices, using several large data sets ranging from 1980 to 1994. Price convergence can be thought of along several dimensions. Section II 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 III offers alternative measures of the movement of the overall price level in Russia towards international heights. Section IV discusses the evolution of regional price disparities within Russia as a way to assess market integration. Section V summarizes the main findings of the paper and outlines areas for further research. A statistical appendix presents some of the raw data.3

II. 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.

1. 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 (Table A1, second panel). For example, the relative price of vodka surged between 1985 and 1990 in connection with the anti-alcoholic 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 leisure goods, watches, sewing machines, and bicycles),1 As a result, by 1992, the relative price of many goods had changed considerably compared with 1980 (Chart 2).2

Chart 2RUSSIA Relative Price Change for Selected Goods in Stores, 1992 versus 1980

(In percent)

Source: Table A1.

During the 1980s and even more so in 1991, food prices on 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 (Table A2). In 1992, following price liberalization, food prices rose much less on city markets than in stores. While by 1991 prices in city markets were typically 2 to 4 times higher than in stores, prices in the two types of outlets broadly converged in 1992.3

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)4 The cross-period correlation coefficients associated with Tables A1 and A2 are shown in Table 1. They 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.5

Table 1.Russia: Cross-Correlations of Price StructuresPrices 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
1991.1.000.950.940.79
19921.000.980.90
Dec.19921.000.87
Non-food 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.

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.1 Furthermore, the correlations suggest that the bulk of the relative price changes had taken place by end-1992, especially for non-food 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.2

At the most aggregate level, the prices of “paid services” increased much less than that of goods in April 1991 and January 1992 (Chart 1, bottom panel).3 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.4 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 (Chart 3).5

Chart 3Structure of Household Consumption: International Comparison

(In percent)

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

1/ Including utilities.

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 (Chart- 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 1994.1

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 1994,2 and prices covering a bit more than half of the CPI were reconstructed for January and July 1992.3 The trends described above are reflected in the evolution of individual prices presented in Table A3. Despite its incompleteness, it allows several interesting observations.

The magnitude of the relative price changes displayed in Table A3 confirms that the broad-based 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 onwards: for example, potatoes, apples, and eggs saw their prices move broadly in line with the overall CPI.4 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.1 A similar price path was registered for many other services.2

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 non-food items (including a number of consumer durables).

Table A3 also illustrates the sensitivity of relative price measures to the level of disaggregation. In some cases, items that might have been thought of a priori as close substitutes for one another display very divergent price movements (e.g., high-fat versus non-fat cottage cheese, or domestic versus imported aspirin).

2. 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.3 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 non-food goods have been published by Goskomstat (1994) for the period 1992-93 (Table A4). 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 non-food 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

Σi=1nωi=1,

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.1

Chart 4 illustrates the evolution of relative price variability for all goods as well as for food and non-food 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.2 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 Chart 5; for comparative purposes, analogous distributions for France and the United States are presented in the bottom half. Several lessons can be drawn from Charts 4 and 5.

Chart 4RUSSIA Relative Price Variability and Inflation for Goods 1/

February 1992 - December 1993

Sources: Table A4; and authors’ calculations.

1/ Monthly inflation rates, in percent.

Chart 5Distribution of Inflation Rates for Goods

(In percent) Monthly Inflation on Horizontal Axis, Proportion of Goods on Vertical Axis

Sources: Table A1 (Russia); Bureau of Labor Statistics (U.S.); INSEE (France); and authors’ calculations.

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.3 Even the minimum value of relative price variability in the Russian sample (reached for non-food goods in July 1992) was more than 3 times higher than the corresponding measure in the United States and France.

Second, relative price variability for food from mid-1992 onwards was almost constantly higher than for non-food 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 non-food goods. One plausible explanation for this apparent regularity is that seasonality affects food prices more than non-food goods prices.1 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.

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.2

Fourth, relative price variability and inflation display a strong positive correlation, as suggested by Chart 4 and confirmed by the regressions in Table 2.3 For non-food 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.4 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.

Table 2.Russia: Inflation and Relative Price Variability, Regression Results1(t-statistics in parentheses)
Dependent variable:Regressors
Variability2ConstantInflationChange in

inflation
Dummy3R2Durbin-Watson
All goods264.79.2-331.10.851.64
(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)
Non-food 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: Table A4; 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 onwards.

Sources: Table A4; 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 onwards.

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 downwards and others increased substantially as price setters developed a perception of new overall and relative price levels (see Table A4). Some confusion about their true values persisted for several months and entailed significant further relative price adjustments.1 By mid-year, 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.2 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.3 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.4

III. International Convergence of the Overall Price Level

The previous Section has 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,1 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-1992,2 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.

1. 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.3 This basket covers about one half of the food component of the Russian CPI at 1993 weights (excluding alcoholic drinks).4 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 (Chart 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 1994.5

Chart 6INTERNATIONAL COMPARISON OF PRICE LEVELS 1/

Sources: Goskomst at of the Russian Federation; Center for Economic Analysis; INSEE; US Bureau of Labor Statistics; and authors’ calculations.

1/ Using the exchange rate quoted on the MICEX.

2/ P denotes a Paasche, Russian-weighted Index, and L a Laspeyres, French-weighted index.

3/ Basket of 19 staples.

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.

2. 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.1 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 non-food 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 non-food 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 (Chart 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

ωjR=pjRqjFΣipiRqiR,

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

ωjF=pjFqjFΣipiFqiF.

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 Chart 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-1994.1 It also appeared that the domestic price of non-food 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 Chart 6. The point estimates of the level of service prices are much more sensitive to the choice of the weights than 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 non-food 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 by 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 (forthcoming) in their cross-country study. The persistence of a large chasm between the price level in Russia and in market economies is consistent with the well-known positive correlation between per capita income and price levels.1 The law of one price clearly does not apply to non-tradeables such as services, but it also fails for tradeables 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 tradeable items embodies a non-tradeable 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.

IV. Regional Disparities

Geographical price and nominal income dispersion has traditionally been very pronounced in Russia, not least due to the vastness of the country and the harshness of its climate, which implied substantial distribution costs. Unfortunately, the available data do not allow to judge whether prices across regions converged or diverged as a result of the transition.2 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.

1. 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 non-food goods prices.1 Also noteworthy is the fact that the dispersion was initially larger for food than for non-food 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.

Table 3.Russia: Geographical Price Dispersion for Food and Non-Food Goods1

(Average coefficient of variation, in percent)2

Foodstuffs3Non-Food Goods4
March 19923728
July 19932525
June 19941717
Memorandum item:
Canada 1991513
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 non-food 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 non-food 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 (Nfld), Charlottetown, Sydney, Halifax, Moncton, Saint John (N.B.), Chicoutimi, Québec, Trois Rivières, Sherbrooke, Montréal, 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 non-food 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 non-food 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 (Nfld), Charlottetown, Sydney, Halifax, Moncton, Saint John (N.B.), Chicoutimi, Québec, Trois Rivières, Sherbrooke, Montréal, Hull, Ottawa, Toronto, Hamilton, London, Sudbury, Thunder Bay, Winnipeg, Regina, Saskatoon, Edmonton, Calgary, Vancouver, and Victoria).

Even by mid-1994, the level of geographic price dispersion remained on the high side compared to market economy standards.2 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, i.e., somewhat lower than the estimate for Russia as of mid-1994.

2. 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 onwards. 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 the end-1992, end-1993 and end-1994 on the other.3

Table 4.Russia: Geographical Price Dispersion for a Basket of Staples1
Memorandum item:
1992199319941994Canada
Feb.2June2Dec.3Dec.3Dec.319914
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 cities539.418.718.718.617.3
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, Gorno-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, Yuzhno-Sakalinksk, 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 basket described in footnote 1. 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, Ekaterinburg, Kazan, Nizhni-Novgorod, Novosibirk, 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, Gorno-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, Yuzhno-Sakalinksk, 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 basket described in footnote 1. 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, Ekaterinburg, Kazan, Nizhni-Novgorod, Novosibirk, Saint Petersburg, Volgograd, and Voronezh (same cities as in Table 3).

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 due to an increasing divergence in local subsidization levels. Consistent with the earlier results, however, they show a slight decline between end-1993 and end-1994.1 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.2

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.3 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.Russia: Geographical Price Cross-Correlations for a Basket of Staples
June 1992Dec. 1992Dec. 1993Dec. 1994
Feb. 19920.510.470.350.29
June 19921.000.720.610.62
Dec. 19921.000.670.72
Dec. 19931.000.89
Sources: same as Table 4.
Sources: same as Table 4.

The level of price dispersion remained high throughout the period under consideration, as suggested by a comparison with similar indicators for Canada (last column of Table 4). By end-1994, the price of the basket stood at around 30 percent of the U.S. level on average across Russian cities, but it amounted to only 15 percent in Ulyanovsk versus 75 percent in Yuzhno-Sakhalinsk.

V. 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.

Due to 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 non-food 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,1 as is the analysis of geographical price dispersion.2

One important policy implication of the empirical analysis of price convergence which transcends potential price measurement errors and which would extend to other transition economies should be highlighted. As pointed out by Richards and Tersman (1995) for the Baltic states, the large gap between domestic and international price levels that remains two or three years after price liberalization implies that convergence, to the extent it proceeds, will be accompanied by real exchange rate appreciation. The latter could take the form of a strengthening of the nominal, exchange rate. However, the relative price of services can be expected to rise significantly in the years ahead, as cost-recovery ratios are still low for many of them. Even if tight financial policies and foreign competition were to contain price increases in the tradeable goods sector, the process of real exchange rate appreciation is thus likely to involve persistently higher measured inflation in Russia than in Western Europe.

Several promising areas for further research can be identified. The first one 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.3 Furthermore, it would be worthwhile to examine to what extent the results obtained for Russia can be generalized to other economies in transition.4

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 non-cash, 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 non-tradeables in the CPI than in the PPI.5 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.

STATISTICAL APPENDIX
Table A1.Russia: Prices of Selected Goods or Groups of Goods in Stores Since 1980Nominal index (1980 = 1)
19801985199019911992Dec. 1992June 1993
Foodstuffs
Meat1.001.031.092.7455121451
Sausage1.001.021.113.4256120637
Canned meat1.001.031.143.7367151532
Fish1.001.041.194.44511191,141
Herring1.000.680.591.2140133438
Canned fish1.000.960.771.7347112545
Butter1.000.991.002.4454108385
Vegetable oil1.000.991.011.9633102254
Cheese1.001.031.032.2267129519
Eggs1.001.011.062.182870211
Sugar1.000.981.032.4465160427
Tea1.001.041.172.4434101375
Bread1.001.030.972.282875186
Flour1.001.031.253.583794200
Groats1.000.980.982.7362159295
Macaroni1.001.021.042.8746106245
Potatoes1.001.082.158.38125123362
Vegetables1.001.031.564.46881791,797
Berries1.000.991.443.6579
Vodka1.001.252.182.432659181
Wine1.001.381.663.6858173286
Brandy1.001.201.623.092781147
Champagne1.001.301.503.0645165298
Beer1.001.041.182.244792476
Non-food goods
Color TV1.000.941.192.493494251
Black and white TV1.000.941.042.1536110275
Radio1.001.051.392.9525
Tape recorder1.001.261.823.322152163
Camera1.001.011.303.7023134145
Refrigerator1.001.161.392.9968273714
Washing machine1.001.081.243.3080206585
Vacuum cleaner1.001.071.395.4190198581
Watch1.000.871.102.001953104
Sewing machine1.001.151.374.0150169448
Motorbike1.001.231.272.3935
Bicycle1.001.031.102.9329145234
Glass1.001.061.261.2623161492
Lumber1.001.051.551.5529124450
Cement1.001.611.611.613081336
Roofing slate1.001.201.221.22231601,302
Roll of metal1.001.581.461.4627
Table A1a.Russia: Prices of Selected Goods or Groups of Goods in Stores Since 1980

Real index (1980 = 100)1

19801985199019911992Dec. 1992June 1993
Foodstuffs
Meat1009892115147145171
Sausage1009794144150144242
Canned meat1009896157181182202
Fish10099101187138144434
Herring100645051108160167
Canned fish100916573127134207
Butter1009484103144130146
Vegetable oil1009485829012396
Cheese100988794179155197
Eggs100968992768580
Sugar1009387103174193162
Tea100999910391122142
Bread100988296769071
Flour1009810515110011476
Groats1009382115165192112
Macaroni100978812112412793
Potatoes100102182353335148137
Vegetables10097132188235216683
Berries10094121154213
Vodka100119184102707169
Wine100131140155156208109
Brandy100114137130749856
Champagne100124126129121198113
Beer1009910095125111181
Non-food goods
Color TV100891001059111495
Black and white TV10090889096132104
Radio1009911712466
Tape recorder100119154140566262
Camera100961101566116155
Refrigerator100110117126183328271
Washing machine100102105139214248223
Vacuum cleaner100102117228243238221
Watch100829384516440
Sewing machine100109116169135204170
Motorbike10011610710193
Bicycle10098931237917589
Glass1001001065363194187
Lumber100991316578149171
Cement100153136688197128
Roofing slate1001141035161193495
Roll of metal1001501236273
Table A1b.Russia: Prices of Selected Goods or Groups of Goods in Stores Since 19802In percent of average monthly wage
19801985199019911992Dec. 1992June 1993
Foodstuffs
Meat0.980.900.640.871.561.311.67
Sausage1.501.351.001.662.441.993.59
Canned meat0.500.450.340.590.970.830.99
Fish0.440.400.310.630.660.581.88
Herring1.100.660.390.431.281.611.80
Canned fish0.440.370.200.240.600.540.90
Butter1.941.701.161.523.012.302.80
Vegetable oil0.910.800.550.570.881.030.87
Cheese1.361.240.840.972.621.932.64
Eggs (10 pieces)0.590.520.370.410.480.450.46
Sugar0.500.430.310.390.930.880.79
Tea4.083.752.873.204.024.575.73
Bread0.200.180.120.150.170.170.14
Flour0.200.180.150.230.220.210.15
Groats0.250.210.140.220.440.440.27
Macaroni0.300.270.190.280.400.350.27
Potatoes0.070.070.090.200.260.100.10
Vegetables0.220.200.210.320.560.441.48
Berries0.590.520.510.691.36
Vodka4.815.306.273.753.663.113.26
Wine1.461.781.451.732.472.801.57
Brandy9.8910.499.619.837.898.875.44
Champagne3.163.632.833.114.125.743.53
Beer0.280.250.200.200.370.280.49
Non-food goods
Color TV374310266300366390351
Black and white TV1401168796145169144
Radio6156515843
Tape recorder139154152149847985
Camera39353046265821
Refrigerator138142115133273417371
Washing machine52493855119118114
Vacuum cleaner23221940605050
Watch171311119107
Sewing machine777863100112144130
Motorbike425460324327428
Bicycle49453246427943
Glass (per m2)0.610.570.460.250.421.101.13
Lumber (per m3)31292915264252
Cement (per ton)19271810171724
Roofing slate (10 tiles)0.510.540.370.200.340.902.47
Roll of metal (per ton)17624515483139
Sources: Goskomstat, Russian Federation in 1992, Statistical Yearbook, Moscow, 1993 and monthly reports; and authors’ calculations.

The numéraire is the overall RPI/CPI (the retail price index through 1990 is linked with the consumer price indices for subsequent periods).

Price per kilo, liter, or piece, unless specified otherwise.

Sources: Goskomstat, Russian Federation in 1992, Statistical Yearbook, Moscow, 1993 and monthly reports; and authors’ calculations.

The numéraire is the overall RPI/CPI (the retail price index through 1990 is linked with the consumer price indices for subsequent periods).

Price per kilo, liter, or piece, unless specified otherwise.

Table A2.Russia: Prices of Selected Foodstuffs in City Markets Since 1980Nominal index (1980 = 1)
19801985199019911992Dec. 1992June 1993
Ratio over price in stores
Meat4.03.74.14.31.31.41.9
Fish2.83.12.21.31.50.8
Butter2.02.42.83.61.11.21.0
Vegetable oil1.61.82.63.91.31.00.9
Cheese2.22.23.34.30.91.20.9
Eggs1.31.11.52.20.91.21.0
Potatoes3.74.13.52.51.12.22.4
Vegetables3.74.44.63.41.11.20.8
Berries2.32.52.73.00.6
Nominal index (1980 = 1)
Meat10.971.132.951943213
Butter11.191.414.413165190
Vegetable oil11.121.684.842868149
Cheese11.031.544.242771197
Eggs10.871.193.702064160
Potatoes11.192.065.583873240
Vegetables11.201.924.032658363
Berries11.041.644.6221
Real index (1980 = 100)1
Meat1009296124505281
Butter100113119186837872
Vegetable oil100107142204748257
Cheese10098130179728575
Eggs10083101156547761
Potatoes1001131742351018891
Vegetables1001141621707070138
Berries1009913919558
In percent of average monthly wage2
Meat3.913.352.653.702.111.873.12
Fish1.110.971.400.870.891.42
Butter3.874.063.265.503.452.782.76
Vegetable oil1.421.411.432.221.141.080.80
Cheese3.052.782.814.172.362.382.25
Eggs (10 pieces)0.750.580.540.900.440.540.45
Potatoes0.270.280.330.490.300.220.24
Vegetables0.820.870.941.070.620.531.12
Berries1.381.271.362.050.86
Sources: Goskomstat, Russian Federation in 1992, Statistical Yearbook, Moscow, 1993 and monthly reports; and authors’ calculations.

The numéraire is the overall RPI/CPI (the retail price index through 1990 is linked with the consumer price indices for subsequent periods).

Price per kilo or liter unless specified otherwise.

Sources: Goskomstat, Russian Federation in 1992, Statistical Yearbook, Moscow, 1993 and monthly reports; and authors’ calculations.

The numéraire is the overall RPI/CPI (the retail price index through 1990 is linked with the consumer price indices for subsequent periods).

Price per kilo or liter unless specified otherwise.

Table A3.Russia: Evolution of Selected Components of the CPI, January 1992-July 1994

(Percent change in relative price)1

July 92/July 93/July 94/
Jan 92Jul 92Jan 92Jul 93Jul 92Jan 92
Food goods
Beef-5113-45-30-21-61
Pork-4716-39-25-13-54
Meat dumplings-3239-5-828-13
Cooked sausage-214413-2212-12
Partially smoked sausage-3239-6-262-31
Fish, live and chilled-32555259331
Herring, salted, smoked, ivasi49098-77785
Fish canned in oil33640-92427
Fish canned in tomato juice4-17-14-12-27-25
Butter-8-23-29-32-47-51
Vegetable oil-32-3-34-10-13-41
Lard133148-33-12-0
Margarine-4-5-8-15-19-22
Milk, fresh519633445119
Sour cream-36-19-48305-33
Yogurt16261784958314
Cottage cheese, high-fat-53-23-645318-45
Cottage cheese, non-fat1794127
Cheese, hard and soft rennet426-7-5-1
Processed cheese-2114-10
Canned tomatoes81221122636
Fruit and berry juices361-5336-11-16287
Eggs-469-42-18-42
Sugar135-8116-58-61-9
Cookies11-13-47-72
Pryaniki9717-20-15-7
Caramels, toffee59-2323-12-328
Tea462989-48-33-2
Salt157-347146-3148
Mayonnaise-122-10
Flour-21-19-373710-13
Rye and rye-wheat bread93-313310038166
Polished rice31-45-28-9-50-34
Seminola-23-29-4638-2-25
Millet-23-16-363815-12
Groats, buckwheat72-3413-29-53-20
Groats, oat and pearl-barley28-58-4729-46-31
Peas and beans-4562-102410111
Macaroni products14-38-30891733
Potatoes27229-1128
Cabbage, fresh, white915017223209236
Bulb onion-1650265112790
Beets102-9832312126
Carrots186-151444725259
Garlic-6224-53-190-62
Apples12-652-57
Mineral water38
Nonalcoholic beverages, domestic-20
Ice cream44
Vodka22-44-32-13-52-41
Cigarettes [papirosy]63-1539-49-57-29
Cigarettes, filter, domestic-8-20-27-36-49-53
Cigarettes, filter, imported-17
Non-food goods
Fabrics, cotton-21
Fabrics, suit, wool or wool blend2
Fabrics, natural silk-26
Fabrics, artificial silk-16
Coat, men15-36-26-19-48-40
Suit, men21-911-15-22-6
Trousers, men3-26-238-20-17
Shirt, men11-65292134
Coat, women, spring/autumn, wool33-39-205-37-16
Dress, women, wool-484344439
Jacket, schoolchildren65-2326-1-2426
Dress, schoolgirl-7-28-33423-5
Shirt, boy29332364080
Bedsheet-24
Women fur headwear-27
Children fur headwear51
Tee-shirt/tank-top, children225893768106
Tights, women34-55-4050-33-10
Socks, men31-31-1022-1610
Socks, children22-31-1553630
Tights, children26-35-1820-22-2
Shoes, leather, men28-167-1-177
Boots, women3594731352
Summer shoes, women88-3817-20-50-7
Summer shoes, children’s119-481367-1389
Detergents77
Soap, household20
Soap, bath44
Perfume45
Shampoo24
Cream, hand or face74
Toothpaste-21
Deodorant26
Razor blade--
Umbrella-16
Toothbrush34
Yarn, wool-3
Thread, sewing, cotton-16
Matches, box-5982-26
Chair20
Sofa-bed-20
Set of bedroom furniture-44
Set of kitchen furniture-16
Carpet-50
Pot, steel, enameled3
Meat grinder, mechanical-2
Frying pan27
Flatware, stainless-49
Dish-18
Glassware2
Wristwatch-20
Alarm clock6
Refrigerator13225191-40-2574
Clothes washer-12
Electric vacuum cleaner-38
Electric iron77-1452-10-2337
Electric lamps-29
School notebook170
Drawing tablet174
Pen, ballpoint, domestic64
Marking pen291
Photographic paper114
Daily newspaper121
Book, fiction, hard-cover48
Skis137
Tape recorder-26
Radio10
Television set, color151430-31-21-10
Piano-30
Guitar9
Plastic toys35
Toy, electromechanical, wind-up-5
Still camera12
Tape recorder cassette (blank)-27
Phonograph records76
Jewelry, gold-31
Round timber, conifer1
Wood particle board-96
Hard fiber board11
Window glass, sheet60
Plywood3
Cement99
Brick14
Prepared roofing paper26
Linoleum-1
Wallpaper159
Ceramic tile11
Bleach40
Cleaning agents for tubs and sinks120
Bicycle, adult-15
Motorcycle-27
Passenger cars-45
Gasoline34-225
Analgesic, domestic335
Analgesic, imported274
Aspirin, domestic-25
Aspirin, imported32
“No-Shpa” medicine991
Coal-24342237
Firewood-24214137
Sewing machine, mechanical-34
Shovel, rake60
Services
Attaching heel taps78
Mending men’s trousers48
Sewing trousers14
Repairing color television sets26
Repairing refrigerators-9
Car maintenance18
Dry cleaning of a coat74
Clothes laundering and ironing107
Painting and wallpapering40
Passport photographs91
Bath in a bathhouse185
Fashion haircut93
Grave digging176
City bus324
Intercity bus69
Streetcar/trolley bus278
Inland water transportation83
Sea transportation289
Commuter train83
Long-distance train-71
Mailing a letter210
Home telephone customer charge110
Municipal rents460
One night’s stay in a hotel89
Residence in a dormitory157
Charge for electricity-18-83-867724922
Charge for water and sewer829
Charge for piped gas-36
Charge for heating524
Charge for hot water supply741
Childcare, municipal center40
Movie ticket106
Theater ticket276
Museum/exhibition ticket171
Boat ride (recreational)189
Bus tour90
Sanatorium, trade union56
Stay in vacation home58
Initial visit to doctor-specialist104
X-ray stomach exploration72
Laboratory tests85
New patient exam by a dentist56
Tooth extraction102
Cosmetic services114
Notarization of a will16
Legal counseling143
Fee for transfer of deposit262
Sources: Goskomstat of the Russian Federation; and authors’ calculations.

Relative to the overall CPI (urban CPI for 1992, expanded CPI thereafter).

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

Relative to the overall CPI (urban CPI for 1992, expanded CPI thereafter).

Table A4.Russia: Monthly Price Increases for a Large Selection of Goods, 1992-93(In percent)
19921993
Item1Weight2JanFebMarAprMayJuneJulyAugSepOctNovDecJanFebMarAprMayJuneJulyAugSepOctNovDec
Food, Alcohol and Tobacco
Beef0.022034545212789173730234132302328272327221285
Pork0.0109353843148913303123224534272231262325211386
Poultry0.0124388-74-215141292736342435302621233326232217117
Cooked sausage0.02315510133617138153531203242352023282728211396
Cocktail sausages0.00436282646151281829272234433419242727311913106
Ham, boiled pork0.0024449894415792029292537362717222427252213117
Partially smoked sausage0.0143320325612914222825243643301923292530211286
Canned beef, pork, mutton0.004824869182532111128262219292618151820211714108
Fish, live and cnilled0.00042766824231325243047363132161116202218192019
Fish, frozen0.005785892217207761316375534333320101071413172521
Fish, salted, marinated0.00093632339211811151216323937222422301620151928222012
Roe, sturgeon, salmon0.00069151168414513353856222522161717151622191311
Fish canned in oil0.00264452472224537132863222518222119191717161712
Butter0.02749131541553018264545393924157771314142018
Vegetable oil0.00502352750291752613493941221717181010151824322717
Margarine0.004373934262361184830584931292012917131318252618
Milk, fresh0.012020962402664571613293428343627201319233024273220
Sour cream0.0082983-7013812-11216533933303728201412152519222920
Cultured milk products0.002120873773110129212023282719394434221419253520242919
Cottage cheese0.0032641-3132614105815424536333532241412142322293725
Cheese, rennet0.004279627101235335223531363828291516151211121214
Canned vegetables0.00021111033115414157241412172022152014202633302811
Tomato paste, juice, sauce0.0005257293413351089214930202422231312131516182118
Canned fruit (except baby’s)0.000738317395749282136121513161518191821191611
Eggs0.0127265-612351-649316920313522173411810815364438
Sugar0.04664132774691783412272419202118191620242517851
Cookies0.00585292013151012131413263123181816161216232526211912
Pryaniki0.00415172314381718121313301423181818171423242423211714
Caramels, toffee0.008357744452310571017212532151514131118222628251616
Honey0.002850670503323131723372322221615101520414327127
Tea0.0040245462317755153155292619191812991011910108
Coffee, ground0.00161020212515106165131528321314107791115129129
Coffee, instant0.001673243411297-156242722161191010181917129106
Salt0.0007332138437132461111102017131920331919252428282218
Mayonnaise0.0021708192115511121020293952292622191416121715151719
Flour0.0067408508222641420681911121298610132140542615
Rye and rye-wheat bread0.0074184941202126159245715911107101224243243394011
Bread and bakery products0.0270302221517128117113263910171210131420263037373614
Polished rice0.002131928372715756103151242218910767911161812
Seminola0.000540271000715332841281114171010810121131403624
Millet0.0003472136513516715514032111321910797910213526
Buckwheat0.00116794340191035141625193218181311a1391414151911
Oat and pearl-barley0.00074206451547812232895201818128510101016243921
Peas and beans0.0001568224071041475135301717112298101313182422
Macaroni products0.00595651620788161516461721101110101015162341382918
Potatoes0.00999412142422253526-663730201516101064347922726
Cabbage0.00298914304934-11-131812251418312332404113025-3-19-32326
Bulb onion0.0046589111092613-2142113716151820196912433168613
Beets0.0006125141619201529-7-22426192617182319306131462321
Carrots0.00081021530162028210-71019142920262724426214142021
Apples0.01191211631181921-12-21-825605934272117306736-20-3253424
Tangerines, oranges0.00095523303647646-6123232114133237433-13203218
Lemons0.000569241735222920-444521312661122743311931259
Ice cream0.002438544951521191825252622223024232130283218171812
Coffee in a cafeteria0.001123918192112791120393014172015181721212328191712
Juice in a cafeteria0.0011239408186141227202991672419222222242416162312
Lunch, public catering0.01822333510121817101518231918272826302429262924201813
Vodka0.093427284621325861925182317911112123324521145
Infusions, other liquors0.00292701999111323520182715149771915202414159
Grape wine0.008332718101138464242242201311101216232021161410
Brandy0.003612823283410712363511131391015171921181310
Champagne0.002430921271948461338825810443411172425221813
Beer0.00565741287231917169162424282821212729232014121512
Cigarettes, filter, domestic0.00352592214186721314327252311109881216251513108
Cigarettes, nonfilter, domestic0.003553328719107183754322815161312108912211913105
Cigarettes, filter, imported0.002818961126121231384930181591277817292313121010
Non-food goods
Fabrics, cotton, dress0.0006302791615-11312283192528271211151414131412
Fabric, wool, dress0.0005156344116201022911112320201110131518172113
Fabrics, suit0.0006156341664000435111121211298101119191912
Fabrics, coat0.00091527021101200241011132719148861118302418
Coat (short coat), men0.0010139421190003312281811141499781222262310
Suit, men0.00361783327520526152920152638221613131216161310
Trousers, wool/blend, men0.00261174217932315102517182826241816151721191912
Trousers, denim fabrics, men0.00331231742137213915161912202016131614141413118
Shirt, men0.01351583428844748272417172928211517191619171614
Coat, winter, women0.0054203282422142310116714242114126892729352613
Coat, spring/autumn, women0.0045137543116523461426301928251611891523241810
Coat (short coat), women0.00541324829223111492212131220201610810152218138
Jacket, women0.004612959341641219121110121719159991521181710
Dress, women0.0010145433210601149121925202934151312151517271915
Skirt, women0.0005944123174123791814132925231715141919201714
Blouse, women0.0011130342511441611173027183024171414141614131212
Winter coat, schoolchildren0.00202695622211414950161099978141642383115
Jacket, schoolchildren0.0068449-6203232371324151312181916131113192722159
Dress, schoolgirl0.00019343282472710851413162426272217201821181514
Men’s fur headwear0.00451365226180248493633201513127512222829221910
Women’s fur headwear0.0063136522618006748303418121411861723272627219
Sweater, adult0.0150832322204221824252418231915121413141718129
Warm-ups, children0.00401786415117351311201917131720191413142020201411
Tank-top, men0.00073693520101222882413192926291720252621241714
Underpants, women0.00131724131226414681833163027201822242124231712
Tights, women0.00192367920232123781814122017151213121727251711
Socks, men0.00201907228585257122023182622221820192828231912
Boots, leather, men0.0038240151820413925544421171414971015293528179
Shoes, leather, men0.008127517317554101730171516202223141314182117149
Boots, leather, women0.006726510101843383357271614161187919294126169
Boots, autumn, women0.0092197151541611827653418111513129815253723158
Summer shoes, women0.00212295315329311412129918272622291713181197
Pumps, women’s, fancy0.008920327402041134111327182522111413131112975
Boots, autumn, children0.0016288109109610420523122101520141210132035432716
Shoes, preschooler0.000928142942501116261620101722321517212528291813
Summer shoes, children0.000919721461746531514162016152636333727282520119
Running shoes, adult0.0076279374432102610111312182023211717192616128
Detergents0.0015304214141653238151115101918231821162531272318
Soap, household0.000491356151629439251822152626201621222438312113
Soap, bath0.000715563222835169151036142021191827242428262214
Shampoo0.001424820231827217122024101920191414131514131411
Cream, hand or face0.00091994327282222421325122119191617131414141515
Toothpaste0.0010116565928621613242952293129342620201716161410
Deodorant0.00071015520252122971419132122191614151517161513
Brassiere0.00101364872421849141331203226242124211921161212
Blade, safety razor0.0001703336163438873257142724181926222318201310
Toothbrush0.000124945513323250326510152733431740262430232019
Yarn, wool0.0013113482192133917172818291714109101518291614
Writing desk0.00063903026112441017142916222328191217182226211315
Dresser0.002639177153038611422633262620171015162422151610
Chair0.0005594311322323281220212624211216162336251816
Sofa-bed0.00313796312123410618343026232819151313212021201412
Set of cabinets (divider)0.0066366511072251412361839232618151111172220161010
Set of soft furniture0.004541217125249161628303120241616111619191715149
Set of bedroom furniture0.002236061830529163321302222151891319191714118
Carpet, wool/synthetic0.00416909202314513461531162213118810141813107
Reversible rug, synthetic0.00137713672340111936393815291499912171818117
Dish0.0009313369186112516132026152427181212141717181712
Wristwatch0.0012124363932865313113124162121131410131416141310
Refrigerator0.0084252833055132101132362614282212101417202112105
Clothes washer0.003768325262032215336324019231811111216171913129
Vacuum cleaner0.00263004227207112172620261521181110156015131286
Electric lamps0.0004145140627217861712242137214623161415131323171712
Electric chandeliers0.001825630301434336111845222722151310142115161414
School notebook0.00113344965188189991091391717171823336379412017
Pen, ballpoint, domestic0.000117047169751013871922172930242833274548291914
Daily newspaper, retail0.00281481783212103998911712015141213292624221918
Weekly newspaper, retail0.00131435481915841630268492421231618342725302014
Bock, fiction, hard-cover0.0022115263464303572491516212524231417222017211817
Skis0.0002511428437216132035121815381254262393812424
Taperecorder0.0025144315033535610251415211610910111614121116
Radio0.0002165187151000147146181817151514261715141310
Television set, color0.011128156121422239364227202116127815151814108
Still camera0.000577413734316361113422015131814121011121412139
Blank taperecorder cassette0.000515662854448827333219302718131113121212128
Lumber0.00036801595-123220141198212523212222253031201513
Brick0.00494845314142014144710221521262319252926343118155
Wallpaper0.0012311551776341716658122117191419181824282218
Bicycle0.004031927321015611101321151126182118232019111285
Motorcycle0.008312361114041372855261918192113152720211388
Passenger cars0.005231911210953943224167450262114171212157236246
Gasoline0.009717601412317510012914113510191611-1564917891411
Aspirin, domestic0.000131883118483627465209787214069482942883936243527
Nitroglycerin0.0001311685538231418425710258474353414264214931
Erythromycin0.0006381-38512661310941136529154413756353724332830
Undevit0.0002302284520101143535813325334293325252428422231
Iodine0.000116291143329477151617686515662232937461843581635
Sources: For rates of change, Goskomstat (1994); and for weights, provided directly by Goskorostat.

For some items, the descriptors shown in this table are less precise than in the original source. The goods listed here cover 75 percent of the total CPI, 88 percent of the food (including alcohol and tobacco) category, and 66 percent of the non-food goods category (using weights reflecting consumption shares in 1992).

Weights in the 1993 CPI, representative of 1992 consumption patterns.

Sources: For rates of change, Goskomstat (1994); and for weights, provided directly by Goskorostat.

For some items, the descriptors shown in this table are less precise than in the original source. The goods listed here cover 75 percent of the total CPI, 88 percent of the food (including alcohol and tobacco) category, and 66 percent of the non-food goods category (using weights reflecting consumption shares in 1992).

Weights in the 1993 CPI, representative of 1992 consumption patterns.

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*Vladimir Sokolin, Deputy Chairman of the Goskomstat of the Russian Federation, and Evgeny Gavrilenkov, First Deputy Director of the Center for Economic Analysis, kindly provided some of the data used in this study. Suggestions and other inputs from Gérard Bélanger, Andrew Berg, Aleš; Buliř, David T. Coe, Timothy Heleniak, Marie Keech, Flemming Larsen, François Lequiller, Bogdan Lissovolic, Anthony Richards, and Bryan Roberts are gratefully acknowledged. However, the authors remain responsible for the full content of the paper.
1previous episodes include the hyperinflation of the early 1920s and a period of chronic high inflation in the 1930s and 1940s.
2For details, see Koen and Phillips (1993).
3The rest of the data are available from the authors on request.
1Prices for December 1992 and June 1993 are also shown in Table Al, but should be interpreted with caution as some of them are subject to strong seasonal variations.
2To put the price changes into perspective, the third panel in Table Al shows the implied evolution of the purchasing power of wages.
3The remaining spread may reflect quality differences or local price controls.
4Berg (1994) computes such a measure for Poland.
5The 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 non-zero cross-product demand elasticities.
1The raw data appear in Goskomstat (1994). For the sake of brevity, the correlations are not reported.
2The 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 small are given the minimal weight of 0.01 percent.
3Many services are (or were) public “goods” and therefore do not (or did not) appear in the CPI, hence the qualifier “paid”.
4For example, in the Baltic countries, Kazakhstan, Ukraine, Armenia, Azerbaijan, and Tajikistan. See De Masi and Koen (in preparation).
5The 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.
1The differences between the “hybrid” and “urban” CPIs are described by Koen and Phillips (1992).
2The 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).
3Based on Goskomstat price tables published weekly by Delovoy Mir and on data provided directly by the Center for Economic Analysis.
4The comparison with January 1992 is difficult because of seasonality.
2While strictly comparable price level information was missing for January and July 1992 for almost all services (hence the blanks in Table A3), partial information collected on the evolution of the components of the CPI in 1992-93 confirms this interpretation.
3See Fischer (1982), Goel and Ram (1993), and the references therein.
1An 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.
2Relative 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.
3Monthly 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 non-food 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 non-food goods (using 1994 observations and weights as published in the INSEE’s Bulletin Mensuel de Statistique).
1Chart 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) in Table Al also points to strong seasonal variability. Some non-food goods prices are also subject to large seasonal swings (e.g., some clothing items).
2An extension of the analysis to 1994 if and when the necessary data become available would allow to more confidently confirm or refute this conjecture.
3It 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.
4In April 1992, gasoline alone accounted for 67 percent of the variability of relative non-food goods prices and in May for 90 percent.
1This 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.
2Symptomatic 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).
3One 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.
4Goel and Ram (1993) find that this is indeed the case in the United States.
1Particularly as regards black market prices and volumes.
3A narrower measure, popularized by The Economist, would be the price of a Big Mac sandwich at Mc Donald’s; see Koen and Meyermans (1994).
4The basket reflects the minimum food consumption required for a 45-year old, able-bodied worker as defined by the former U.S.S.R. State Committee for Labor and Social Problems, and includes (with volumes expressed on an annual basis) rye bread (92 kg), wheat bread (86.7 kg), millet (18.1 kg), vermicelli (7.3 kg), sugar (24.8 kg), vegetable oil (10 kg), butter (3.6 kg), beef (42 kg), boiled sausage (2.2 kg), salami (1.1 kg), milk (184.3 liters), sour cream (4.2 kg), hard cheese (2 kg), eggs (183), potatoes (146 kg), fresh cabbage (29.8 kg), onion (10.2 kg), apples (11 kg), and cigarettes (96 packs).
5The two measures differ because the price of the basket is higher in France and because of changes in the FRF/$ exchange rate over the period under consideration.
1Average prices in France are published in the INSEE’s Bulletin Mensael 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.
1Richards and Tersman (1995) find that food prices in Latvia in March 1994 were about 37 percent of the Swedish level.
1Rationalized 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.
2Regional 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.
1The data sources and coverage are described in Table 3. The sub-set of foodstuffs is very similar to the one constituting the basket of 19 staples. No information on local services prices was available.
2Some dispersion is observable even in market economies, as noted long ago by Mills (1927) for the United States.
3Apart from the change in coverage, seasonality would also render the comparison with February and June 1992 hazardous.
1The max/min ratio rises a little but is a less relevant measure of dispersion than the decile ratio, which clearly drops.
2Another 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.
3As 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.
1The European Comparison Program results for 1993, due to be released in 1996, should shed some further light on this comparison.
2Far more comprehensive data than those we had access to seem to exist at Goskomstat and would permit a more thorough investigation.
3In 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.
4Such an investigation is currently under way, see De Broeck, De Masi and Koen (forthcoming) and De Masi and Koen (in preparation).
5As 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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