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

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

(In percent)

Citation: IMF Working Papers 1995, 054; 10.5089/9781451847468.001.A001

Source: Table A1.

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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

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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

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Structure of Household Consumption: International Comparison

(In percent)

Citation: IMF Working Papers 1995, 054; 10.5089/9781451847468.001.A001

Sources: Goekomstat (Russia); QUS (Poland); National Statistical Institute (Portugal); INSEE (France); Bureau of Economic Analysis (United States); and authors’ calculations.1/ Including utilities.

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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

$\underset{i=1}{\overset{n}{\mathrm{\Sigma }}}{\omega }_i=1,$

where ω_i and π_i 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.

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RUSSIA Relative Price Variability and Inflation for Goods ^1/

February 1992 - December 1993

Citation: IMF Working Papers 1995, 054; 10.5089/9781451847468.001.A001

Sources: Table A4; and authors’ calculations.^1/ Monthly inflation rates, in percent.

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Distribution of Inflation Rates for Goods

(In percent)

Monthly Inflation on Horizontal Axis, Proportion of Goods on Vertical Axis

Citation: IMF Working Papers 1995, 054; 10.5089/9781451847468.001.A001

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

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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)

Sources: Table A4; and authors’ calculations.

¹Based on monthly observations for February 1992-December 1993, and using ordinary least squares.

²As defined in equation (1).

³Dummy equals zero prior to July 1992 and 1 from July 1992 onwards.

Table 2.

Russia: Inflation and Relative Price Variability, Regression Results¹

(t-statistics in parentheses)

Dependent variable:	Regressors
Variability2	Constant	Inflation	Change in inflation	Dummy3	R2	Durbin-Watson
All goods	264.7	9.2		-331.1	0.85	1.64
	(5.4)	(4.1)		(-10.5)
	328.5	5.1	8.2	-316.0	0.89	2.35
	(8.4)	(2.8)	(3.9)	(-12.8)
Food	182.2	7.4		-221.9	0.62	2.27
	(3.2)	(2.8)		(-5.9)
	241.7	4.3	5.9	-216.2	0.65	2.00
	(3.9)	(1.4)	(1.9)	(-5.4)
Non-food goods	271.3	15.0		-428.7	0.50	2.41
	(1.8)	(2.6)		(-3.8)
	465.9	10.6	16.1	-554.7	0.43	2.66
	(2.6)	(1.5)	(1.9)	(-4.0)

Sources: Table A4; and authors’ calculations.

¹Based on monthly observations for February 1992-December 1993, and using ordinary least squares.

²As defined in equation (1).

³Dummy equals zero prior to July 1992 and 1 from July 1992 onwards.

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Table 2.

Russia: Inflation and Relative Price Variability, Regression Results¹

(t-statistics in parentheses)

Dependent variable:	Regressors
Variability2	Constant	Inflation	Change in inflation	Dummy3	R2	Durbin-Watson
All goods	264.7	9.2		-331.1	0.85	1.64
	(5.4)	(4.1)		(-10.5)
	328.5	5.1	8.2	-316.0	0.89	2.35
	(8.4)	(2.8)	(3.9)	(-12.8)
Food	182.2	7.4		-221.9	0.62	2.27
	(3.2)	(2.8)		(-5.9)
	241.7	4.3	5.9	-216.2	0.65	2.00
	(3.9)	(1.4)	(1.9)	(-5.4)
Non-food goods	271.3	15.0		-428.7	0.50	2.41
	(1.8)	(2.6)		(-3.8)
	465.9	10.6	16.1	-554.7	0.43	2.66
	(2.6)	(1.5)	(1.9)	(-4.0)

Sources: Table A4; and authors’ calculations.

¹Based on monthly observations for February 1992-December 1993, and using ordinary least squares.

²As defined in equation (1).

³Dummy 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

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

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INTERNATIONAL COMPARISON OF PRICE LEVELS ^1/

Citation: IMF Working Papers 1995, 054; 10.5089/9781451847468.001.A001

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.

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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

$\begin{array}{cc}{\omega }_j^R=\frac{p_j^R{q}_j^F}{\underset{i}{\mathrm{\Sigma }}{p}_i^R{q}_i^R},& \end{array}$

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

$\begin{array}{cc}{\omega }_j^F=\frac{p_j^F{q}_j^F}{\underset{i}{\mathrm{\Sigma }}{p}_i^F{q}_i^F}\mathrm{.}& \end{array}$

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.

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

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.

¹The 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.

²For Russia, weighted average of item-specific coefficients of variation, with weights reflecting the share of the items in the CPI.

³Representing about half of the weight of food items in the CPI.

⁴Representing about one sixth of the weight of non-food goods in the CPI.

⁵For 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).

Table 3.

Russia: Geographical Price Dispersion for Food and Non-Food Goods¹

(Average coefficient of variation, in percent)²

	Foodstuffs3	Non-Food Goods4
March 1992	37	28
July 1993	25	25
June 1994	17	17
Memorandum item:
Canada 19915	13	…

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.

¹The 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.

²For Russia, weighted average of item-specific coefficients of variation, with weights reflecting the share of the items in the CPI.

³Representing about half of the weight of food items in the CPI.

⁴Representing about one sixth of the weight of non-food goods in the CPI.

⁵For 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).

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Table 3.

Russia: Geographical Price Dispersion for Food and Non-Food Goods¹

(Average coefficient of variation, in percent)²

	Foodstuffs3	Non-Food Goods4
March 1992	37	28
July 1993	25	25
June 1994	17	17
Memorandum item:
Canada 19915	13	…

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.

¹The 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.

²For Russia, weighted average of item-specific coefficients of variation, with weights reflecting the share of the items in the CPI.

³Representing about half of the weight of food items in the CPI.

⁴Representing about one sixth of the weight of non-food goods in the CPI.

⁵For 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

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.

¹The 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.

²Excluding city markets.

³Including city markets.

⁴A 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.

⁵Moscow, Chelyabinsk, Ekaterinburg, Kazan, Nizhni-Novgorod, Novosibirk, Saint Petersburg, Volgograd, and Voronezh (same cities as in Table 3).

Table 4.

Russia: Geographical Price Dispersion for a Basket of Staples¹

						Memorandum item:
	1992		1993	1994	1994	Canada
Feb.2	June2	Dec.3	Dec.3	Dec.3	19914
Coefficient of variation (in percent)	18.5	18.7	22.0	34.1	30.1	6.5
Maximum/minimum	2.4	2.7	3.8	5.0	5.1	1.3
Top decile/bottom decile	1.8	2.0	2.1	2.8	2.4	1.3
Number of observations	99	91	97	62	98	25
Memorandum item:
Coefficient of variation
for 9 cities5	39.4	18.7	18.7	18.6	17.3

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.

¹The 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.

²Excluding city markets.

³Including city markets.

⁴A 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.

⁵Moscow, Chelyabinsk, Ekaterinburg, Kazan, Nizhni-Novgorod, Novosibirk, Saint Petersburg, Volgograd, and Voronezh (same cities as in Table 3).

View Table

Table 4.

Russia: Geographical Price Dispersion for a Basket of Staples¹

						Memorandum item:
	1992		1993	1994	1994	Canada
Feb.2	June2	Dec.3	Dec.3	Dec.3	19914
Coefficient of variation (in percent)	18.5	18.7	22.0	34.1	30.1	6.5
Maximum/minimum	2.4	2.7	3.8	5.0	5.1	1.3
Top decile/bottom decile	1.8	2.0	2.1	2.8	2.4	1.3
Number of observations	99	91	97	62	98	25
Memorandum item:
Coefficient of variation
for 9 cities5	39.4	18.7	18.7	18.6	17.3

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.

¹The 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.

²Excluding city markets.

³Including city markets.

⁴A 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.

⁵Moscow, 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

Sources: same as Table 4.

Table 5.

Russia: Geographical Price Cross-Correlations for a Basket of Staples

	June 1992	Dec. 1992	Dec. 1993	Dec. 1994
Feb. 1992	0.51	0.47	0.35	0.29
June 1992	1.00	0.72	0.61	0.62
Dec. 1992		1.00	0.67	0.72
Dec. 1993			1.00	0.89

Sources: same as Table 4.

View Table

Table 5.

Russia: Geographical Price Cross-Correlations for a Basket of Staples

	June 1992	Dec. 1992	Dec. 1993	Dec. 1994
Feb. 1992	0.51	0.47	0.35	0.29
June 1992	1.00	0.72	0.61	0.62
Dec. 1992		1.00	0.67	0.72
Dec. 1993			1.00	0.89

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.