Journal Issue
Share
Article

Russian Federation: Selected Issues

Author(s):
International Monetary Fund
Published Date:
November 2000
Share
  • ShareShare
Show Summary Details

I. The Recovery in Output

A. Introduction

5. Output has rebounded strongly and is now above the pre-crisis level.1 Following a decline of almost 5 percent in real GDP during 1998, with a particularly sharp decline in the third quarter, output grew by over 3 percent in 1999. Estimates for the first quarter of 2000 suggest that the recovery has since gained further momentum. The output recovery was initially driven by import substitution in response to the large real depreciation. Subsequently, the recovery has become more broadly based as exports are growing and domestic demand, including both investment and, more recently, private consumption, is becoming more buoyant.

6. Inflationary pressure stemming from the ruble depreciation was quickly reigned in and inflation has been brought down to relatively low levels. Following an initial burst of inflation stemming from the depreciation, inflation was reduced by late 1999 to about I percent per month on a seasonally adjusted basis.

7. Both the ruble depreciation and the increase in world energy prices have played important roles in the recovery. Breaking out the contribution of each of these factors is difficult but, the data suggest that the increase in world energy prices has, to date, played a secondary role in the recovery. In this regard, the bulk of the improvement in the external current account during 1999 came from a reduction in imports rather than an increase in energy exports.

8. The strong growth in output has resulted in a decline in unemployment. Despite the existence of important rigidities in the labor market, the unemployment rate fell to 11 percent at end-June 2000.

B. Developments Since the 1998 Crisis

9. Output began recovering in the last quarter of 1998 and has since gained further momentum. In the first quarter of 2000, real GDP stood 8.4 percent above its level one year earlier, almost 3 percent above its previous, end-1997 peak. Further, in a sharp break with pre-crisis experience, the current expansion involves most sectors and almost all regions—84 out of 89 regions experienced growth in industrial output in 1999.

10. Any analysis of the dynamics and causes of this recovery is complicated by severe data limitations. Seasonal adjustment is extremely difficult, both because the data series are very short and unstable, and because there have been significant changes in the structure of the economy (see Box 1).

Box 1.Issues in Seasonal Adjustment

Seasonal fluctuations in Russian real activity are unusual in both magnitude and timing, but the amplitude seems to be diminishing, Box Figure 1 (1 and 2). The seasonal pattern, with a very sharp fall in January, followed by strong growth in subsequent months and a peak in December, differs somewhat from the seasonal pattern normally found in countries with a similar climate and industrial structure. The Russian seasonal pattern partly reflects the orthodox holiday period that falls in January as well as old central planning behavior, in which the desire to fulfil the annual plan led to increased activity towards the end of the planning period. Central planning-based accounting and data-reporting practices artificially exacerbated the pattern; in particular, the output of smaller enterprises, which only reported once every year, was incorporated into the series on a cumulative year-to-date basis during the last period. Over the period 1995–99, the estimated seasonal January decrease in industrial output shrank from 7.8 to 6.7 percent, and the estimated seasonal first quarter decrease in real GDP shrank from 12.7 to 12 percent. This reflects both changes over time in the structure of the economy, and in particular the weakening influence of the old central planning mentality and improvements in statistical practices.

Seasonal adjustment in such a situation must allow the seasonal pattern to change over time and to take into account the impact of shocks, notably the August 1998 financial crisis. Allowing for changes in the seasonal pattern is only feasible if it can be assumed that the changes are sufficiently small and/or smooth. With short time series, a single isolated shock, such as the August 1998 financial crisis, can have a large and misleading impact on estimates of seasonal factors. Box Figure 1 (3) contrasts two seasonally adjusted (SA) time series for real GDP growth. In the first (“SA incl. crisis”), seasonal adjustment is achieved by passing the entire, unadjusted time series through the X-12 filter. In the second (“SA excl. crisis”), the crisis and post-crisis period (1998 Q3 onwards) is ignored when estimating the seasonal factors. The substantive difference is that, in the first time series, the output dynamics stemming from the August 1998 crisis and the post-crisis recovery influence the estimates of the normal seasonal movement. As a result, the procedure will tend to estimate higher SA growth rates for Q3 and lower SA growth rates for Q1, Q2, and Q4.

Controlling for the crisis, Box Figure 1 (4) shows SA growth for real GDP, an “output of basic sectors” index (covering about 60 percent of GDP), and industrial output. The figure suggests that, in 1999 Q1-Q2, growth was very fast, particularly for industrial output. In 1999 Q3, there was a sharp slow-down, although the real GDP and the output of basic sectors series give contrasting indications about the precise magnitude. In 1999 Q4, the growth rate rose again. Use of monthly data, see Box Figure 1 (5), confirms this pattern.

Using instead an ARIMA approach has both disadvantages and advantages. Estimating a simple ARIMA regression with seasonal dummies has two disadvantages: the estimates can be heavily influenced by outliers, and changes in the seasonal pattern cannot be accommodated. The approach does, however, permit the calculation of standard errors of the estimated seasonal factors. Box Figure 1 (6) plots the upper and lower bounds of a 90 percent confidence interval for the estimated SA growth rate, using both the fall sample and the non-crisis period alone to estimate the seasonal factors and their standard errors. There are two key conclusions, which reflect the fact that quarter-on-quarter changes in Russia are large and variable. First, the magnitude of the depicted confidence interval is extremely large; indeed, so large that in 1999 the null hypothesis of zero growth cannot (or can only barely) be rejected for any individual quarter. Second, the magnitude of the depicted confidence interval greatly overwhelms the differences implied by using different estimation methods, for example, including or excluding the crisis period, or using X-12 filters versus an econometric approach. Note though that the standard errors diminish dramatically over periods greater than an individual quarter. Indeed, by definition, the standard error is zero for the year as a whole. On the other hand, the confidence intervals would be even wider if account were taken of the (unknown) measurement error associated with the collection of the underlying, unadjusted data.

Box Figure 1.Russian Federation: Seasonal Factors in GDP and Industrial Production, 1996–2000

Source: Goskomstat and Fund staff estimates.

In addition, key macroeconomic time series are unavailable, internally inconsistent, or of only limited reliability, especially at a quarterly frequency.2

11. The post-crisis recovery was initially led by import substitution, in response to the sharp real ruble depreciation. This first phase began in late 1998 and lasted until the middle of 1999. It was characterized by rapid growth of the external trade-oriented industrial sector, whose output increased on average by over 5 percent per quarter (Text Table 1, Figure 1). Import volumes, seasonally adjusted, fell by 50 percent in the second half of 1998 as a result of the depreciation-related substitution effect as well as an income effect originating from a sharp decline in real wages and consumption demand in the aftermath of the crisis. As for exports, energy export volumes remained broadly flat after the crisis, since the scope for expansion is limited by extraction and transportation constraints (see below). In contrast, non-energy exports (seasonally adjusted) declined by about 15 percent in dollar terms between the crisis and the second quarter of 1999, although customs data suggest that export volumes increased significantly, especially to non-CIS countries.3,4 The resultant dramatic increase in net foreign demand more than offset a decline in domestic demand, in particular in consumption, which fell sharply as real wages declined to three-fifths of their pre-crisis level (Figure 2).

Text Table 1.Key Real Sector Growth Rates(Seasonally adjusted, one-period growth)
199819992000
YearQ1Q2Q3Q4YearQ1Q2Q3Q4Q1
Real GDP−4.7−2.4−0.5−6.00.63.13.43.2−0.31.23.8
Industrial output−2.30.5−2.7−9.15.98.15.73.90.51.53.6
Private consumption−5.0−3.6−1.4−1.6−18.0−15.00.3−1.80.57.32.3
Fixed capital formation−6.7−2.6−2.4−4.6−2.74.50.62.68.611.0
Sources: Goskomstat; and Fund staff estimates.
Sources: Goskomstat; and Fund staff estimates.

Figure 1.Russian Federation: Output and Income, 1995–2000

Source: Goskomstat.

Figure 2.Russian Federation: Wages and Unit Labor Costs, 1992–2000

Sources: Goskomstat; and IMF staff calculations.

12. The recovery appeared to be petering out in the second half of 1999. There was a significant slowdown in growth, with imports stabilizing while domestic consumption remained depressed. Investment rebounded strongly as the depreciation and rising oil prices improved the financial condition of enterprises, albeit from a very low base.

13. Output growth gained new and more broad-based momentum from late 1999. Output growth rates have returned to the levels observed in early 1999 and the expansion is now more broadly based, with a significant increase in domestic demand. In particular, private consumption has been growing sharply reflecting both a 20 percent increase in real wages since August 1999 and the near-elimination of wage arrears (Table 18), in turn linked to the strong financial situation of enterprises. Capital formation remains strong as rising international oil prices have further improved profits, and overall public confidence in economic prospects has strengthened in the wake of the recent elections. Three firms alone (Lukoil and Sifneft in the fuel sector, and Norilsk Nickel in the metal sector, which over the last six months has also experienced a major increase in export prices) have announced capital expenditure plans for 2000 that imply a (combined) increase in fixed capital formation of almost 1 percent of GDP. While such increases occur from a very low base, they do nonetheless represent a major break with the long-running trend decline.5

Table 1.Russian Federation: Selected Indicators of Economic Activity, 1991–99(Annual percentage change)
199119921993199419951996199719981999
Gross domestic product−5.0−14.5−8.7−12.7−4.1−3.40.9−4.93.2
Industrial output−8.0−18.0−14.1−20.9−3.3−4.02.0−5.28.1
Extraction industries−4.4−10.9−9.8−9.7−1.4−2.0−1.2
Processing industries−9.3−19.2−14.8−24.0−3.9−4.62.6
Agricultural output−4.5−9.4−4.4−12.0−8.0−5.11.5−13.22.4 2/
Crops 1/0.4−5.4−2.9−10.4−4.60.37.3−22.39.0 2/
Livestock−7.3−11.9−5.4−13.1−10.4−11.0−5.0−1.8−3.7 2/
Freight transport 3/−7.0−14.0−12.0−14.0−1.0−5.0−3.6−3.55.2
Source: Goskomstat.

Plant growing.

Preliminary data.

Turnover of transport companies (including pipelines).

Source: Goskomstat.

Plant growing.

Preliminary data.

Turnover of transport companies (including pipelines).

Table 2.Russian Federation: GDP by Expenditure, 1991–99
1991199219931994199519961997199819991995–99
Cumulative ChangeChange in GDP: Decomposition
(Annual percentage change at constant prices) 1/
Gross domestic product−4.6−14.6−7.6−11.7−4.5−6.70.9−5.53.2−8.2−8.2
Total domestic demand−4.0−17.0−12.9−11.6−4.9−7.71.3−9.0−1.4−16.1−15.0
Consumption−6.1−5.2−1.0−3.1−2.7−3.13.0−2.3−3.5−5.9−4.2
Households−4.6−3.01.21.2−2.8−4.75.4−3.6−5.3−8.3−4.1
General government−11.3−11.8−6.4−2.91.10.8−2.40.60.9−0.10.0
Non-profit institutions34.5−1.00.2−35.9−30.5−0.5−1.8−1.60.0−3.9−0.1
Gross Investment−2.3−36.9−29.4−31.2−10.8−20.6−3.6−31.39.3−42.5−10.8
Capital formation−15.5−41.5−25.8−26.0−7.5−19.3−5.7−11.22.4−30.8−6.6
Changes in inventory264.1−29.2−37.4−47.1−30.4−27.38.9−55.7
Net exports of goods and services171.4717.123.2−13 03.221.2−8.8111.060.2273.66.8
Memorendum Items
GDP at production basis−5.0−14.5−8.7−12.7−4.1−3.40.9−4.93.2−4.3n.a.
(In percent of GDP at current prices)
Total domestic demand1008592959796979384−13n.a.
Consumption635064707171757769−2.5n.a.
Households4134414449495054501.2n.a.
General government171418231920211915−4.0n.a.
Non-profit institutions4253223330.4n.a.
Gross Investment373628262524221515−10.4n.a.
Capital formation242521222121191716−5.4n.a.
Changes in inventory131174433−2−1−4.9n.a.
Net exports of goods and services0158534371612.8n.a.
Exports goods and services (fob)14643928282523314315.5n.a.
Imports of goods and services (fob)1350312324202123272.6n.a.
Source: Goskomstat and Fund staff estimates.

In last year’s comparable prices.

Source: Goskomstat and Fund staff estimates.

In last year’s comparable prices.

Table 3.Russian Federation: GDP by Sector, 1991–99 1/
199119921993199419951996199719981999
(In percent)
Agriculture 2/14.07.28.26.57.27.36.55.86.9
Industry38.233.734.432.829.029.528.329.031.9
of which: processing industry
Construction9.46.37.99.18.58.47.97.15.9
Wholesale, retail, foreign trade, public catering, procurement12.229.119.018.319.618.317.61922.1
Transportation and communications 3/7.57.48.69.911.912.412.111.110.2
Finance, credit, insurance, real estate operations, science and research, housing, geology, subsoil resources, exploration, meteorology, computer services, others8.78.210.89.69.08.08.99.18.3
Stale administration and defense2.52.13.14.75.25.26.26.74.8
Education, culture and art, health care, physical education & social security, utilities, non-production activities services to households, people’s associations7.56.08.09.19.610.912.512.29.9
Source: Goskomstat and Fund staff estimates.

Unit weight of gross added values generated by economic sectors in basis prices to GDP in basis prices unadjusted by indirectly measured financial intermediary services.

Agriculture, including companies servicing agriculture and forestry.

Transport, communications, road infrastructure.

Source: Goskomstat and Fund staff estimates.

Unit weight of gross added values generated by economic sectors in basis prices to GDP in basis prices unadjusted by indirectly measured financial intermediary services.

Agriculture, including companies servicing agriculture and forestry.

Transport, communications, road infrastructure.

Table 4.Russian Federation: Gross Industrial Output by Sector, 1991–99
199119921993199419951996199719981999
(Annual average percentage changes)
Total−8.0−18.0−14.1−20.9−3.3−4.02.0−5.28.1
Electric power generation0.3−4.7−4.7−8.8–3.2−1.6−2.1−2.50.2
Fuel−6.0−7.0−11.6−10.2−0.8−l.50.3−2.52.4
Ferrous metallurgy−7.4−16.4−16.6−17.39.6−2.51.2−8.114.4
Noaferrous metallurgy−8.7−25.4−14.1−8.92.8−3.66.0−5.08.5
Chemicals and petrochemicals−6.8−21.6−21.8−25.58.0−8.12.0−7.521.7
Machinery−10.0−15.0−15.8−31.0−9.3−4.73.5−7.515.9
Forestry, timber processing, paper and pulp−9.0−14.6−18.7−30.5−0.7−17.50.9−0.417.2
Construction materials−2.4−20.4−16.0−27.3−8.0−17.3−4.0−5.87.7
Light industry−9.0−30.0−23.0−46.0−30.2−22.5−2.4−11.520.1
Food processing−9.5−16.4−9.0−17.5−8.2−4.2−0.8−1.97.5
(In percent of 1991 level)
Total100.082.070.455.753.951.752.850.054.1
Electric power generation100.095.390.882.880.278.977.275.375.5
Fuel100.093.082.273.873.272.172.470.572.2
Ferrous metallurgy100.083.669.757.763.261.662.457.365.6
Nonferrous metallurgy100.074.664.158.460.057.961.358.363.2
Chemicals and petrochemicals100.078.461.345.749.345.346.242.852.1
Machinery100.085.071.649.444.842.744.240.947.4
Forestry, timber processing, paper and pulp100.085.469.448.347.939.539.939.746.6
Construction materials100.079.666.948.644.737.035.533.436.0
Light industry100.070.053.929.120.315.715.413.616.3
Food processing100.083.676.162.857.655.254.853.757.7
Source: Goskomstat
Source: Goskomstat
Table 5.Russian Federation: Employment Labor Productivity and Real Wages in Industry by Sector, 1991–99
1991199219931994199519961997199819991/
(In thousands of people)
Employment 2/
Total20,11720,02018,86417,44016,00614,93414,00913,17312,975
Electric power generation563626666710750790810852868
Fuel815870886860846856821794749
Ferrous metallurguy772795788738727727683673680
Nonferrous metallurgy502532542517549537508469470
Chemicals and petrochemicals1,1151,1431,1091,011968923891858860
Machinery9,0938,7677,9337,0296,1905,6283,2624,8564,681
Forestry, timber processing, paper and pulp1,7251,8131,6411,5351,3831,2611,1381,0341,040
Construction materials1,0671,1361,0951,040973868783713700
Light industry2,1451,8451,6991,6001,3321,1331,006888850
Food processing1,5331,5541,5561,5541,5061,4871,4541,3961,420
Others787939949846782724653640637
(In percent of 1991 levels)
Average Labor Productivity 3/
Total1008275646870767684
Electric power generation1008677666056545049
Fuel1008776707169727279
Ferrous metalurguy1008168606765706674
Nonferrous metallurgy1007059575554616268
Chemicals and petrochemicals1007662505755585667
Machinery1008882646669767792
Forestry timber processing, paper and pulp1008173546054606677
Counuctruction materials1007565504945485055
Light industry1008168393330333341
Food processing1008275625957585962
(In percent of 1991 levels)
Real producer wages 4/
Total1007665543740434646
Electric power generation1009484704650505346
Fuel10011393745154575762
Ferrous metallurguy1009675553947474747
Nonferrous metallurgy10010182644748495560
Chemicals and petrochemicals1008563503740434747
Machinery1006457483235374139
Forestry, timber processing, paper and pulp1007356453333343436
Construction materials1006965553435373733
Light industry1005845292019212221
Food processing1007673593640414340
(In percent of 1991 levels)
Product Unit Labor Costs 5/
Total1009387845558566055
Electric power generation10010910910776889410795
Fuel1001301241067378797979
Ferrous metallurguy100118110915971667263
Nonferrous metallurgy1001441381138588808888
Chemicals and petrochemicals1001111021006473748570
Machinery1007370744950495343
Forestry, timber processing, paper and pulp1009077825561565247
Construction materials100931001117078767561
Light industry1007166756065636651
Food processing1009298956270717264
Source: Goskomstat and Fund staff calculation.

Preliminary data.

The table contains the average payroll fund data.

Measured as the ratio of production to workforce.

Deflated by industrial PPI.

Measured as the ratio of real producer wages to average labor productrtity.

Source: Goskomstat and Fund staff calculation.

Preliminary data.

The table contains the average payroll fund data.

Measured as the ratio of production to workforce.

Deflated by industrial PPI.

Measured as the ratio of real producer wages to average labor productrtity.

Table 6.Russian Federation: Labor Force Turnover, 1993–99 1/
1993199419951996199719981999
(In thousands)
Total number of separations14,28414,59713,06911,37211,01710,65010,274
of which: in industry5,3815,2684,2843,7093,3853,3333,152
Number of newly hired11,96311,07911,4808,9828,9818,98410,128
of which: in industry3,7702,9973,1922,3212,4262,3873,200
(As percent of total employment)
Total number of separations25.127.425.723.924.524.924.2
of which: in industry28.832.028.427.026.827.727.0
Number of newly hired21.120.822.618.919.921.023.9
of which: in industry20.118.221.116.919.219.827.4
Sources: Goskomstat.

Data for large and medium enterprises.

Sources: Goskomstat.

Data for large and medium enterprises.

Table 7.Russian Federation: Employment by Sector, 1991–99 1/
199119921993199419951996199719981999 2/
(In percent of 1991 level)
Total100.097.695.992.790.089.387.586.287.3
Industry100.095.292.982.976.773.066.563.163.9
Agriculture and forestry100.0103.7103.8105.6100.395.488.689.989.1
Construction100.092.984.180.073.169.266.659.558.4
Transportation and communication100.097.994.193.191.490.889.083.885.3
Commerce, food service, material and technical supply, marketing and procurement100.0100.9113.3115.3118.7120.8154.7164.5171.0
Public health, physical training, social security, education, art, culture and science100.098.095.694.993.793.190.589.190.8
Administrative staff, lending and state insurance100.094.2106.0115.5137.6175.2170.4178.0179.7
Other sectors (housing, pub. utilities, nonproduction types of gen. services to the public)100.0100.294.092.093.6101.696.296.799.3
(In percent of total employment)
Total100.0100.0100.0100.0100.0100.0100.0100.0100.0
Industry30.329.629.427.125.924.823.022.222.2
Agriculture and forestry13.514.314.615.415.114.413.714.113.8
Construction11.510.910.19.99.38.98.77.97.7
Transportation and communication7.87.87.67.87.97.97.97.67.6
Commerce, food service, material and technical supply, marketing and procurement7.67.99.09.510.110.313.514.514.9
Public health, physical training, social security, education, art, culture and science19.419.519.419.920.220.320.120.120.2
Administrative staff, leading and state insurance2.92.83.13.54.35.45.55.55.5
Other sectors (housing, public utilities, nonproduction types of general services to the public)6.97.16.86.97.37.97.68.08.1
Memorandum;
Total employment (in thousands)73,80072,07170,85268,48466,44165,95064,63963,64264,500
Source: Goskomstat

Average for the year; does not include students.

Preliminary data.

Source: Goskomstat

Average for the year; does not include students.

Preliminary data.

Table 8.Russian Federation; Indicators of Hidden Unemployment, 1993–99 1/
Shortened Workday 2/Forced Leave 3/
Thousands of personsIn percent of workforceThousands of personsAvg. leave days per

person per quarter
1993
Q19502.8190814.0
Q29242.8281918.1
Q310743.3368223.6
Q415584.9487528.9
1994
Q1327410.6463219.0
Q2434814.2678225.0
Q3485816.0727435.0
Q4504816.7772742.0
1995
Q122444.4246611.0
Q219913.9186811.0
Q319003.8179311.0
Q420514.1240110.0
1996
Q129526.1231611.0
Q232926.8199110.0
Q331846.6179312.0
Q434097.2240810.0
1997
Q123825.2170811.0
Q225525.616889.0
Q324825.5122311.0
Q425965.814949.0
1998
Q123245.4247118.2
Q230607.1409521.0
Q337248.6415533.0
Q4430610.1474238.8
1999
Q121965.3200017.6
Q224445.8248423.8
Q325916.2280428.4
Q427286.5332529.5
Source: Goskomstat.

In industry, construction, transportation, communication, services, science, and scientific support.

For 1993, 1995–99 data include number of people on shortened workday at the end of each quarter; for 1994 data show those on shortened workdays over the course of the period.

Without pay or with partial pay.

Source: Goskomstat.

In industry, construction, transportation, communication, services, science, and scientific support.

For 1993, 1995–99 data include number of people on shortened workday at the end of each quarter; for 1994 data show those on shortened workdays over the course of the period.

Without pay or with partial pay.

Table 9.Russian Federation: Selected Labor Market Indicators, 1992–99
Registered Unemployment
Total Employment 1/Registered VacanciesRegistered JobseekersTotalReceiving BenefitsUnemployment According to ILO Definition
(In percent of labor force)
End-year 1992−2.40.41.30.80.55.2
End-year 1993−1.70.51.51.10.76.1
End-year 1994−3.30.42.62.21.97.8
End-year 1995−3.00.43.53.22.89.0
End-year 1996−0.70.43.83.53.110.0
End-year 1997−2.00.53.02.82.411.2
End-year 1998−1.50.42.92.62.413.3
End-year 19991.30.82.01.71.511.9
Source: Goskomstat.

Annual percentage change.

Source: Goskomstat.

Annual percentage change.

Table 10.Russian Federation: Unemployment Rate by Regions (ILO methodology), 1993–99(In percent of labor force)
1993199419951996199719981999
Northern Region
Karelian Republic7.88.713.211.511.916.615.8
Komi Republic4.99.310.910.413.917.816.1
Arkhangel’sk Oblast6.19.711.012.012.414.914.9
Nenets Autonomous Okug13.311.320.1
Vologodak Oblast4.27.68.88.010.512.711.8
Murmansk Oblast6.59.112.414.718.521.016.3
North-western region
Saint Petersburg8.09.910.610.39.911.311.0
Leningrad Oblast6.79 410.210.012.815.014.8
Novgorod Oblast5.88.310.29.113.515.414.5
Pskov Oblast7.912.412.213.714.216.114.1
Central region
Bryansk Oblast4.78.89.48.212.915.716.7
Vladimis Oblast5.910.013.111.511.612.013.1
Ivanovo Oblast8.413.614.616.516.918.817.7
Kalozhaka Oblast5.15.78.37.811.210.211.6
Kostromska Oblast8.19.59.49.99.411.210.1
Moscow6.57.77.06.34.84.85.6
Moscow Oblast5.17.07.97.68.89.910.7
Orlov Oblast4.56.58.09.69.813.29.2
Ryazan Oblast5.16.66.76.410.17.112.8
Smolensk Oblast6.57.810.211.312.916.414.2
Tver Oblast4.06.78.25.79.911.310.4
Tula Oblast4.16.76.26.910.011.611.6
Yaroslavl Oblast5.68.512.110.88.811.18.8
Volga region
Marii-El Republic4.89.411.811.318.013.110.8
Mordoviya Republic6.38.111.613.112.214.512.8
Chuvash Republic7.110.010.211.113.913.913.9
Kirov Oblast6.19.79.28.911.413.110.1
Nizhegorod Oblast5.26.68.79.09.79.17.7
Central-Chernozem region
Belgorod Oblast4.45.56.16.610.711.313.1
Voronezh Oblast4.45.68.29.28.19.512.5
Kursk Oblast3.86.46.17.48.110.211.5
Lipetsk Oblast5.25.76.36.79.811.111.1
Tambov Oblast5.87.510.611.112.912.714.3
Povolgski region
Kalmykiya Republic9.112.122.214.526.130.825.5
Tatarstan Republic3.66.16.56.57.910.911.4
Astrakhan Oblast7.39.714.712.814.615.914.1
Volgograd Oblast5.67.611.511.250.014.712.5
Penzenak Oblast6.43.913.914.912.018.111.6
Samara Oblast4.66.38.08.79.38.612.4
Saratov Oblast5.98.910.410.515.816.111.2
Ulyanov Oblast4.86.58.38.29.811.19.2
North-Kaukaz region
Adygeya Republic8.013.013.411.112.316.021.1
Dagestan Republic17.518.025.327.727.030.031.2
Ingush Republic43.132.258.231.151.8
Kabardino-Balkar Republic9.614.314.317.117.722.428.2
Karaehaev-Circassian Republic9.611.327.420.818.925.522.4
North Ossetian-Alaniya Republic23.330.122.226.633.4
Chechen Republic
Krasnodarsk Krai7.28.69.310.716.516.215.9
Stavropol Krai6.25.69.49.813.916.319.2
Rostov Oblast5.67.88.58.512.015.718.5
Ural
Bashkortostan Republic4.36.77.87.911.213.412.5
Udmurt Republic6.28.713.112.213.111.6
Kurgan Oblast5.69.58.410.212.513.113.4
Orenburg Oblast3.36.27.55.59.513.414.2
Perm Oblast5.78.49.08.811.113.014.3
Komi-Permyatsk Autonomous Okr17.617.410.5
Sverdlovsk Oblast6.28.28.58.510.210.513.9
Chelyabinsk Oblast6.58.28.28.79.512.412.0
West-Siberia
Altai Republic9.313.59.913.218.418.519.4
Altai Krai6.78.411.110.713.916.013.1
Kemerovo Oblart4.97.26.66.811.212.513.8
Novosibirek Oblast6.78.110.18.910.713.715.0
Omsk Oblast5.47.65.47.013.415.515.0
Tomsk Oblast7.610.27.97.912.814.616.5
Tyumen Oblast5.17.56.99.28.914.011.3
Khanti-Mansi Autonomous Okrug12.514.411.3
Yamalo-Nenetsk Autonomous Okr10.711.210.0
East Siberia
Buryat Republic5.89.815.114.621.322.118.1
Tyva Republic6.511.021.418.122.020.926.0
Khakasian Republic4.66.28.711.613.09.616.1
Krasnoyarsk Krai5.48.39.08.113.316.414.3
Taimyrsk Autonomous Okrug7.015.69.7
Evenkisk Autonomous Okrug3.45.97.2
Irkutsk Oblast6.28.38.911.214.413.715.1
Ust-Ordinsk Buryat Autonomous7.78.414.9
Chitinsk Oblast5.87.19.214.918.520.421.0
Aginsk Buryat A. Okrug28.135.723.5
Far East region
Sakha republic (Yakutiya)3.96.07.16.712.613.613.9
Jewish Autonomous Oblast5.611.717.012.625.123.919.0
Chukotak A. Oblast8.44.79.3
Primorye Krai5.47.510.09.613.314.913.7
Khabarovak Krai6.89.211.412.112.712.414.4
Amur Oblast5.38.713.411.015.616.916.4
Kamchatka Oblast5.69.76.87.012.517.618.2
Koryak Autonomous Okrug6.88.48.9
Magadan Oblast6.310.99.710.413.618.120.6
Sakhalin Oblast8.09.911.310.915.017.120.7
Kaliningrad Oblast7.19.69.213.911.516.715.9
Source: Goskomatat.
Source: Goskomatat.
Table 11.Russia Federation: Unemployment Composition by Duration of Job Search and Age Group, 1996–99
Job search time (months)
Under 11.33.66.99–1212+Avenge
(In percent of total)
Total unemployed, October 19967.410.326.812.310.732.58.2
of which: ages
Under 2010.413.129.215.112.719.66.8
20–247.111.628.013.311.128.87.8
25–298.18.427.410.39.336.68.5
30–347.110.125.512.88.136.38.5
35–396.89.627.011.910.434.38.4
40–445.910.325.812.312.233.58.4
45–496.88.924.911.511.536.48.7
50–545.510.324.812.612.434.48.6
55–596.79.126.710.511.235.78.6
60–6411.712.722.612.33.936.98.0
65–7216.314.335.86.55.521.76.0
Total unemployed, October 19977.815.915.810.711.638.18.8
of which : ages
Under 2011.723.224.110.110.820.16.5
20–249.119.119.910.110.731.17.9
25–298.616.015.110.211.039.18.8
30–347.814.913.910.912.440.19.1
35–396.614.913.211.411.842.29.3
40–446.614.014.311.912.540.69.3
45–495.712.213.211.112.445.49.8
50–545.911.111.712.512.945.910.0
55–597.111.713.78.712.845.99.8
60–646.015.915.36.65.450.79.7
65–725.312.713.34.910.253.610.4
Total unemployed, October 19986.116.015.910.310.840.99.1
of which: ages
Under 207.624.627.49.28.822.46.7
20–247.718.918.510.210.334.48.3
25–296.315.316.512.610.438.99.0
30–345.215.113.310.512.543.49.5
35–395.814.112.910.011.046.29.7
40–445.213.114.49.510.847.19.8
45–495.513.713.410.111.445.99.7
50–544.615.413.98.39.248.69.8
55–596.416.012.59.310.545.39.5
60–644.613.915.913.413.139.19.3
65–726.612.711.37.415.047.010.0
Total unemployed, October 19996.413.613.19.310.647.19.8
of which: ages
Under 2013.022.117.89.912.225.07.1
20–247.917.114.610.810.339.48.8
25–296.112.114.28.411.248.09.9
30–345.313.113.59.610.947.69.9
35–395.711.812.39.010.351.010.2
40–445.211.212.79.010.551.410.3
45–495.213.610.89.310.151.010.2
50–544.510.110.69.210.055.510.8
55–594.79.79.08.710.457.611.0
60–646.110.48.85.88.460.511.0
65–724.45.88.15.68.268.112.0
Source: Goskomstat Statistical Bulletin, various issues.
Source: Goskomstat Statistical Bulletin, various issues.
Table 12.Russia Federation: Unemployment by Reason of Being Unemployed, 1992–99 1/(In percent of total unemployed)
19921993199419951996199719981999
Total unemployed100.0100.0100.0100.0100.0100.0100.0100.0
Those who had a previous job79.981.383.683.283.788.085.980.6
of which: left the previous employment because of:
release, redundancy, liquidation21.022.928.928.329.834.037.134.4
resignation34.840.439.339.438.425.022.220.8
completion of term of temporary, seasonal or co7.05.84.94.84.04.45.34.1
discharge from military1.91.71.31.51.10.91.20.5
other reasons15.310.59.29.210.623.720.220.8
Those who have not had a job before20.118.716.416.816.312.014.119.4
Total unemployed: male100.0100.0100.0100.0100.0100.0100.0100.0
Those who had a previous job80.782.185.484.885.689.086.880.6
of which: left the previous employment because of:
release, redundancy, liquidation14.317.223.823.826.031.134.431.7
resignation40.045.744.543.942.429.525.724.1
completion of term of temporary, seasonal or
contract work7.65.44.64.63.75.25.85.0
discharge from military3.43.02.42.81.81.62.10.9
other reasons15.410.810.19.711.721.718.918.8
Those who have not had a job before19.317.914.615.214.411.013.219.4
Total unemployed: female100.0100.0100.0100.0100.0100.0100.0100.0
Those who had a previous job79.180.481.681.481.586.884.880.7
of which: left the previous employment because of:
release, redundancy, liquidation28.329.234.833.634.237.540.337.5
resignation29.134.533.334.133.619.718.017.1
completion of term of temporary, seasonal or
contract work6.46.35.15.14.33.64.73.0
discharge from military0.20.10.20.00.20.10.10.1
other reasons15.210.28.28.59.225.921.623.0
Those who have not had a job before20.919.618.418.618.513.215.219.3
Source: Goskomstat.

For 1992–1997, data refer to end-October values; for 1998–1999, data refer to annual average.

Source: Goskomstat.

For 1992–1997, data refer to end-October values; for 1998–1999, data refer to annual average.

Table 13.Russia Federation: Distribution of the Unemployed by Job Search Methods, 1992–99(In percent of total)
19921993199419951996199719981999 1/
Oct.Oct.OctOct.Mar.Oct.Oct.
Application to the state employment service28.128.334.436.339.039.937.233
Application to a commercial employment service1.03.13.73.84.22.42.42.4
Placing ads in papers, responding to ads8.713.615.616.917.616.318.619.2
Contacting friends, relatives, acquaintances29.936.737.838.537.055.057.855.7
Directly contacting the management/employer26.330.929.027.925.628.829.531.5
Search for land, machines and equipment, raw materials, financial resources for starting own business, applying for licenses, etc.1.81.91.41.40.91.11.00.8
Other methods9.012.912.015.314.314.715.611.9
Source: Goskomstat.

Annual average.

Source: Goskomstat.

Annual average.

Table 14.Russian Federation: Migration Between the Regions of Russia, 1989–99(In thousands)
198919901991199219931994199519961997199819991992–99
TotalTotal as percent of population 1/
Northern Region−9.5−13.2−39.2−45.6−37.5−40.8−25.3−24.3−30.4−31.7−33.7−269.3−4.5
Karelian Republic0.50.80.40.9−0.71.61.800.2−02−0.33.30.4
Komi Republic−5.6−7.8−15.7−11.9−15.1−22.3−12.1−9.1−11.1−10.6−12.1−104.3−8.3
Arkhangel’sk Oblast−4.8−3.4−9.2−7.6−5.4−3.5−4.8−6−7.6−7.7−8.4−51.1−3.3
Volbgodsk Oblast0−0.21.54.16.34.35.54.232.61.631.62.4
Mumasnsk Oblast0.4−2.6−16.2−31.1−22.6−20.9−15.7−13.4−14.9−18.7−14.4−148.7−12.7
North-western region12.419.1−6.6−3.97.447.840.341.528.234.323.7219.32.8
Central region91.17.8961.5113.2216.2166.2138.5139.3138.8112.21085.93.4
Volga region−8.6−1.54.322.22650.831.621.719.918.714.4208.32.5
Central-Chei-nonm region12.423.226.380.191.8102.462.653.238.837633.6500.268
Povolguld region20.740.133.4104.4131.2167.2104.762.967.359.340.2737.24.6
North-Kaukaz region19.778.6149.5103.1143167.386.435.236.526.726.4624.63.7
Ural−39.4−23.1−4.136.641.3123.674.44966.854.537.7483.82.4
West Siberia6.1−2.2−32−8.226.3112.249.730.464.334.3−5.8303.22.0
East Siberia−25−24.528.6−36.2−22.6−7.33.9−7.7−21.4−20.6−22.6−134.6−1.5
Far East region−0.2−9.6−66.1−150.4−101.1−147.8−102.8−65−69.7−64.6−65.0−766.4−9.5
Sakha republic (Yakutya)1.6−4 5−28.4−27.9−20.4−30.9−18.7−12−17.2−19.7−15.3−1621−13.9
lewish Autonomous Oblast0.30.1−0.1−2.6−1.4−5.5−1.4−1.8−1.8−1.9−2.8−19.2−8.7
Chukotak A. Obiiist−3.6−3.7−9.3−22.2−11.5−13.6−9.3−5.2−4.7−4.0−4.2−74.7−47.2
Primorye Krai7.661.9−7.9−7−5.4−9.4−9.4−11−4.2−7.5−61.7−2.7
Khabarovsk Krai1.2−0.3−2.9−13.7−8.3−14.8−10.9−7.5−5.3−6.3−8.4−75.2−4.7
Amor Oblast−0.4−0.7−4.1−15.2−4−13.6−1.1−3.9−5.7−6.2−6.1−55.8−5.3
Kamchatka Oblast0.10.1−3.6−16.6−16.5−15−11.7−7−7−6.4−6.5−86.7−18.0
Kotyak Autonomous Okrug−0.30−0.5−1.9−2.3−1.6−0.9−0.6−1−1.0−0.8−10.1−24.7
Magadan Oblast−5.2−6.7−18.7−38.1−18.9−26.8−20.4−6.6−5.4−6.0−6.7−128.9−34.4
Sakhalin Oblast−1.80.1−0.9−6.2−13.1−22.2−19.9−11.6−11.6−10.0−7.5−102.1−14.4
Kaliningrad Oblast3.26.35.712.511.118.410.58.21313.03.690.3105
Source: Goskomstat

Total as patent of regional population at end-1991.

Source: Goskomstat

Total as patent of regional population at end-1991.

Table 15.Russian Federation: Consumer Price Inflation, 1992–2000 1/
Overall CPIFood 2/Nonfood 3/Paid Services 4/Overall CPI Seasonally Adjusted
(Percentage changes from December to December)
19922508.82526.22573.42120.5
1993839.9804.9641.82311.2
1994213.7214.2164.8521.6
1995131.4123.5116.4232.8
199621.817.817.848.3
199711.09.18.322.6
199884.596.199.518.5
199936.636.139.033.8
(Monthly percentage changes)
1998Jan1.52.10.51.7−0.4
Feb0.91.20.31.00.3
Mar0.60.70.21.20.6
Apr0.40.30.21.00.7
May0.50.60.11.10.7
June0.10.00.00.60.6
July0.2−0.10.11.20.8
Aug3.72.47.11.26.7
Sep38.439.554.33.439.1
Oct4.53.97.41.64.0
Nov5.77.64.31.34.7
Dec11.617.16.31.810.5
1999Jan8.410.36.24.16.5
Feb4.14.44.03.23.5
Mar2.82.83.21.92.7
Apr3.02.64.03.13.3
May2.22.02.72.12.4
June1.91.71.63.52.4
July2.83.21.93.13.5
Aug1.20.52.41.94.1
Sep1.50.82.72.02.0
Oct1.40.92.22.00.9
Nov1.21.01.51.70.3
Dec1.31.41.10.90.3
2000Jan2.32.22.23.40.4
Feb1.00.51.33.00.4
Mar0.50.11.41.50.5
Apr0.90.31.52.11.2
May1.82.21.11.32.0
June2.63.1
Memorandum items:
1992 weights10044.546.19.4
1993 weights10055.338.95.8
1994 weights10053.540.36.2
1995 weights10052.537.89.7
1996 weights10056.630.113.2
1997 weights10054.429.016.6
1998 weights10051.932.116.0
1999 weights10059.927.212.9
Source: Goskomstat and staff estimates.

The Russian authorities have discontinued the practice of publishing average monthly inflation rates since November 1994. Data reported in this table, since December 1994 are on an end of period basis.

Includes food, beverages, and tobacco.

Includes clothing and footwear, household goods, medicines, recreation, education, culture, and personal care and effects.

Includes rent, water, fuel and power, transport, and communication.

Source: Goskomstat and staff estimates.

The Russian authorities have discontinued the practice of publishing average monthly inflation rates since November 1994. Data reported in this table, since December 1994 are on an end of period basis.

Includes food, beverages, and tobacco.

Includes clothing and footwear, household goods, medicines, recreation, education, culture, and personal care and effects.

Includes rent, water, fuel and power, transport, and communication.

Table 16.Russian Federation: Industrial Producer Prices, 1991–2000
Overall PPI IndexElectricityFuelFetrous MetallurgyChemicalsMachineryConstruction MaterialsLight IndustryFood Industry
(Percentage changes from December to December)
1991236110129237165212215371314
19923,2785,4099,1663,5253,7912,6212,7141,1582,628
19938951,2586341,0868489491,1696811,229
1994233229201242262230212241208
1995175199187185168178171163156
1996263540161824342022
1997791115981012
19982331112629134453
19996714135894450375663
(Monthly percent changes)
1998Jan0.91.21.10.41.10.91.01.00.9
Feb0.51.70.00.5−0.81.20.60.90.3
Mar−0.1−0.3−0.70.8−1.20.40.40.60.4
Apr0.01.7−1.90.5−1.00.40.60.3−0.1
May−0.9−1.8−3.4−1.00.80.70.00.1−0.2
Jun0.01.0−1.60.10.50.40.10.1−0.5
Jul−0.80.1−4.91.00.6−0.10.3−0.2−0.2
Aug−1.2−2.1−5.6−1.7−0.30.10.30.2−0.2
Sep7.41.21.82.48.38.63.610.521.1
Oct5.91.45.32.97.53.82.79.25.1
Nov5.1−0.97.31.94.55.91.08.27.6
Dec4.8−0.54.23.23.94.11.67.311.3
1999Jan6.91.36.06.24.98.63.26.69.2
Feb5.63.83.44.93.25.81.68.38.7
Mar3.90.23.97.63.23.31.95.46.2
Apr3.70.73.94.44.03.61.62.64.2
May3.61.48.25.71.53.31.82.22.6
Jun3.71.36.46.61.82.22.02.52.1
Jul3.10.77.83.24.43.03.51.82.9
Aug4.70.012.16.50.81.93.92.85.4
Sep5.91.715.07.13.62.33.83.54.5
Oct5.50.615.25.12.52.73.03.82.6
Nov3.90.75.84.95.92.34.03.50.9
Dec2.21.21.93.31.42.21.92.50.7
2000Jan4.02.09.65.01.73.82.51.31.0
Feb3.74.25.65.11.43.82.52.30.8
Mar2.64.82.33.43.02.62.81.90.5
Apr1.5
May1.7
Jun2.3
Source: Goskomstat.
Source: Goskomstat.
Table 17.Russian Federation: Wages, Pension and Per Capita Income, 1992–99
19921993199419951996199719981999
(In rubles per month)
Average monthly wages6.058.7220.4472.4790.2950.21,051.01,582.0 1/
Minimum wage0.76.117.642.575.972.783.583.5
Pensions1.619.978.0188.1302.1328.1399.0448.7
Income per capita4.045.2206.3515.4760.0930.0969.91,563.0
(Annual percentage change 2/)
Real wages−40.40.4−7.8−27.913.44.9−13.4−19.0
Minimum wage−78.8−10.6−29.2−18.821.0−16.5−10.0−46.2
Pensions27.6−3.8−18.98.8−5.3−4.7−39.5
Real income per capita−53.215.912.0−16.0−0.16.7−18.3−13.3
Source: Goskomstat and staff calculations

Preliminary data.

CPI deflated numbers.

Source: Goskomstat and staff calculations

Preliminary data.

CPI deflated numbers.

Table 18.Russian Federation: Wage Arrears in Industry, Agriculture, and Construction, 1992–2000
IndustryAgricultureConstruction
Nominal 1/Real 2/Nominal 1/Real 2/Nominal 1/Real 2/
End year 1992153.661.481.9
End year 19933649.22877.21152.9
End year 19942,17017.41,30110.47295.8
End year 19957,73426.82,5728.91,9416.7
End year 199622,14963.05,91316.86,46718.3
End year 199726,60767.17,96520.17,45718.8
End year 199832,47145.29,39813.19,60013.4
End year 199917,05817.47,8598.05,6225.7
1998 Jan28,01170.98,28521.07,98920.2
Feb29,54174.18,39321.07,76919.5
Mar30,74676.68,38820.97,87019.6
Apr31,81279.08,33120.78,02619.9
May33,54282.88,50421.08,36320.7
Jun34,96386.38,84821.88,38720.7
Jul36,47489.89,24022.88,80221.7
Aug39,10692.99,64522.99,46922.5
Sep39,26467.49,90917.010,09517.3
Oct36,87960.510,04016.510,28016.9
Nov35,80755.69,74715.110,18115.8
Dec32,47145.29,39813.19,60013.4
1999 Jan32,12241.29,86612.79,23811.9
Feb30,07837.19,62311.98,94311.0
Mar27,92933.59,34811.28,47110.2
Apr25,94830.29,15910.77,8959.2
May25,22628.79,04710.37,5188.6
Jun23,66526.49,19110.37,0507.9
Jul23,48525.59,30110.17,0327.6
Aug22,29123.99,2579.96,6407.1
Sep21,17422.49,0469.66,6037.0
Oct20,63521.58,8859.36,5336.8
Nov19,83220.58,5668.86,4556.7
Dec17,05817.47,8598.05,6225.7
2000Jan17,49317.47,8067.85,9896.0
Feb17,17016.97,8207.75,7775.7
Mar16,40716.17,7447.65,4655.4
Apr16,10715.67,7427.55,1335.0
Source: Goskomstat.

In millions of rubles.

In constant March 1992 prices, deflated by CPI.

Source: Goskomstat.

In millions of rubles.

In constant March 1992 prices, deflated by CPI.

14. Non-energy exports have grown strongly. In the last quarter of 1999, dollar values were 6 percent above the level one year before, and customs reports suggest that volumes for all major categories of exports (except agriculture and raw hides) were at least 13 percent higher than a year earlier, with much larger increases in some categories, such as textiles and machinery.6 For 1999 as a whole, non-energy export volumes grew by about 15 percent, largely driven by rising exports of metals, fertilizers, and timber to non-CIS countries. While the dollar value of non-energy exports declined further, this reflected a continued fall in dollar prices, especially for exports to the CIS. These figures imply that the growth in exports contributed 3–4 percentage points to output growth in 1999.

15. Import volumes have also begun to recover following a sharp decline in 1999. For 1999 as a whole, customs data imply that imports fell by 31 percent in U.S. dollar terms, of which about one-third can be attributed to a decline in prices. However, this fall partly reflects a post-crisis shift in the composition of imports towards cheaper product categories and, within each category, towards cheaper brands. Such structural changes are not handled well by the present indices, both because they are actually unit-value indices and due to the inherent difficulty in identifying appropriate weights. In the first quarter of 2000, reflecting the recovery in domestic demand, imports grew by almost 5 percent in dollar terms, and about 14 percent in volume terms, relative to the first quarter of 1999. Nevertheless, import volumes remained about 40 percent below their pre-crisis level, in part because real wages remain significantly below their pre-crisis levels.

16. The government sector has made a negative contribution to demand growth in the wake of the crisis. General government consumption at constant prices grew by less than 1 percent in 1999 (Table 2). While data on government investment are not available, enlarged government expenditure as a share of GDP fell by 2 percentage points, and non-interest expenditure declined by almost 4 percentage points (Table 22). With the ratio of enlarged government revenues to GDP increasing by over 2 percentage points, the primary deficit decreased by 6 percentage points (see Chapter II).

Table 19.Length and Depth of Output Contraction(Based on Observations Through 1999)
Duration of contraction (years)Peak yearTrough yearReal GDP at trough as percent of peakReversion to measured output level of
BRO Countries
Armenia41989199335Early 1970s
Azerbaijan919881995371960s
Belarus61989199563Late 1970s
Estonia51989199464Early 1970s
Georgia61988199423Late 1950s
Kazakhstan101988199860Late 1960s
Kyrgyz Republic51990199549Early 1970s
Latvia41989199347Late 1960s
Lithuania519891994591970s
Moldova1019891999311950s/1960s
Russia91989199853Early 1970s
Tajikistan819881996261950s/1960s
Turkmenistan919881997501960s or earlier
Ukraine1019891999361960s or earlier
Uzbekistan51990199586Early 1980s
Selected CEE Countries
Bulgaria91988199763Early 1980s
Czech Republic41989199385Late 1970s
Hungary41989199382Late 1970s
Poland21989199186Mid 1980s
Romania51987199273Mid 1980s
Slovakia41989199375Late 1970s
Sources: IMF, International Financial Statistics and World Economic Outlook; Yearbooks of National Statistical Offices; Statistical Committee of the CIS; CMEA Yearbooks; Fund staff estimates.
Sources: IMF, International Financial Statistics and World Economic Outlook; Yearbooks of National Statistical Offices; Statistical Committee of the CIS; CMEA Yearbooks; Fund staff estimates.
Table 20.Fall in Industrial Output Across Regions During the First Half of the 1990s 12
Countrywide dropCoefficient of variationMaximumMinimumNumber of regions
Russia5225872387
Ukraine5022742926
Kazakhstan523273620
Source: De Broeck & Koen (2000b), Table 5.

During 1990–95 for Kazakhstan, 1990–96 for Russia, and 1990–97 for the Ukraine.

All columns in percent, except for the number of regions.

Source: De Broeck & Koen (2000b), Table 5.

During 1990–95 for Kazakhstan, 1990–96 for Russia, and 1990–97 for the Ukraine.

All columns in percent, except for the number of regions.

Table 21.Accounting for Growth in Transition(Percent per Annum)
Average Across Transition Years 0, 1, and 2Average Across Transition Years 3 and 4
GrowthAccounted for byGrowthAccounted for by
MacroStructuralInitial Conditions & ConstantWarResidualMacroStructuralInitial Conditions & ConstantWarResidual
CEE−10.5−1.09.2−16.5−2.1−0.12.60.913.8−11.8−0.80.5
o/wCzech Republic−7.20.69.5−16.20.0−1.13.71.012.8−6.80.0−3.3
Hungary−6.20.010.6−17.70.00.91.21.514.7−13.10.0−2.0
Poland−5.30.812.3−22.20.03.84.90.114.4−14.20.04.7
Slovak−8.8−0.510.1−15.50.0−2.96.2−0.813.0−5.30.0−0.7
Republic
Baltics−17.12.011.6−30.80.00.12.31.114.5−14.70.01.4
Estonia−10.01.812.8−29.10.04.43.20.815.415.30.02.2
Latvia−16.41.711.0−27.90.0−1.11.30.715.4−12.30.0−2.5
Lithuania−25.02.510.9−35.50.0−3.02.41.612.7−16.40.04.4
Russia−11.90.17.6−17.60.0−2.0−3.24.010.8−17.00.0−1.0
Other BRO−17.3−1.71.8−14.7−2.80.1−3.10.08.4−11.0−0.2−0.5
Sources: Berg et al (1999); author’s calculations.
Sources: Berg et al (1999); author’s calculations.

17. Following an initial surge in the aftermath of the crisis, inflation quickly subsided and has remained modest despite the rapid output recovery. Consumer price inflation spiked sharply in September 1998, but declined to around 3 percent on a monthly basis (seasonally adjusted) between April and August 1999. It dropped further in late 1999, not exceeding 1 percent between October 1999 and April 2000 (Table 15). Inflation (unadjusted) ticked up to almost 2 percent in May and 3 percent in June, in part a reflection of special factors, including in particular sharp increases in the customs duty on sugar, adjustments in administered prices (including those for electricity and gas), and seasonal increases in the price of several foodstuffs. Nevertheless, underlying inflation also likely increased, to about 1.5 percent per month, in part reflecting difficulties in keeping control over the growth of base money in the face of large foreign exchange interventions by the CBR. Industrial producer prices have grown consistently faster than consumer prices since February 1999, largely reflecting the steady increase in prices for fuel and other commodities, in turn linked to changes in world market prices (Table 16).

C. Main Factors Behind the Post-Crisis Recovery

18. The ruble depreciation and the rise in world energy prices have been the most important factors behind the output recovery. It is difficult to disentangle the relative impact of these factors, since both have contributed to increased profitability in the tradables sectors, improvement in financial and liquidity conditions in the economy at large, and progress toward sustainable macroeconomic stability. While both the ruble depreciation and the increase in international energy prices have played important roles in the recovery, the ruble depreciation has, to date, been the primary driving force behind the recovery.

The role of the ruble depreciation

19. The sharp depreciation following the August 1998 crisis led to a significant improvement in the competitiveness of the tradables sector (see Box 2). The CPI-based real effective exchange rate (REER) depreciated by 45 percent in the wake of the crisis, and through April 2000 remained about 40 percent below its pre-crisis level (Figure 3).7 The REER based on relative unit labor costs (ULC) improved even more dramatically, declining some 70 percent after the crisis as real wages collapsed, and remaining about 60 percent below the pre-crisis level as of end-1999. Profitability, as measured by product unit labor costs, improved by over 15 percent following the crisis, with a further small increase since then.

Figure 3.Russian Federation: Real Exchange Rates and Trade Prices, 1994–2000

Sources: Goskomstat; and IMF staff calculations.

Figure 4.Russian Federation: Enterprise Financing, 1998–2000

Source: Goskomstat; The Russian Economic Barometer, Vol. 9, No 2.

1/ Relative to GDP, overdue payables were equivalent to 30 percent of GDP at the end of 1999, down from 46 percent in mid-1998.

Figure 5.Russian Federation: Ruble Interest Rates, 1998–2000

(In Percent)

Source: CBR Bulletin of Banking Statistics.

1/ Interest rates on loans and deposits maturing in 91–180 days.

2/ Rate on longest maturity offered. Through April 1999, equals one month. From May 1999, rate on 3-month deposits.

Figure 6.Russian Federation: Interest Rates on U.S. Dollar Instruments, 1998–2000

(In Percent)

Source: CBR Bulletin of Banking Statistics.

1/ Interest rates on loans and deposits maturing in 91–180 days.

2/ Rate on longest maturity offered. Through April 1999, equals one month. From May 1999, rate on 3-month deposits.

20. The strengthening of external competitiveness and profitability in the tradables sector led to a dramatic improvement in the external trade balance. As discussed above, imports fell sharply in the second half of 1998 and have only staged a slow recovery. There has also been a positive response from exports, although this has been dampened by the economic problems in main CIS partner countries.

21. Increased profitability also stimulated an expansion of investment and a reduction in arrears. Given the underdevelopment of domestic capital markets and the low level of credit to the economy from the banking system, retained earnings have been the main source of investment funds. Hence, the improved profitability in the tradable goods sector eased the financing constraint on enterprises’ capital expenditures. In addition, the improved financial conditions in enterprises stimulated the economic recovery by contributing to a significant reduction in arrears and non-cash payments throughout the economy (Figure 4).8

Box 2.Real Effective Exchange Rates, Competitiveness, and Profitability

The August 1998 crisis led to a dramatic real depreciation of the ruble and improvement in industrial profitability. The CPI-based real effective exchange rate (REER) depreciated by about 40 percent in the wake of the crisis (Figure 3). Through April 2000, the REER was broadly constant. The unit labor cost (ULC) based REER declined even further as real wages collapsed. While this measure may be contaminated by data problems in CIS partner countries, it fell by almost 70 percent in the wake of the crisis, and is still at only about 40 percent of its pre-crisis level. Profitability in industry, as measured by product unit labor costs (PULC), improved by over 15 percent between the second quarter of 1998 and the first quarter of 1999, with a further small improvement since. Increases in productivity, rather than changes in real producer wages, have driven the decline in PULC. Figure 2 and Table 5 depict real producer wages, average labor productivity, and product unit labor costs. Regarding capital costs, nominal interest rates have only recently started to decline, implying that real interest rates rose in the post-crisis period (Figures 5 and 6). The growth in profitability has, however, increased the availability of internally generated investment funds, reducing enterprises’ effective cost of capital.

Overall profitability in the economy has improved markedly after the crisis. As illustrated in the table below, in 1999 net profits as a share of GDP increased by a massive 17 percentage points. Three arguments suggest that this increase in aggregate profits largely reflects the impact of the depreciation on profits in all tradable sectors, as opposed to the effect of the increase in dollar export prices, in particular for oil. First, the increase in net profits amounted to about twice the total fuel sector value added, and an even larger multiple of the change in sectoral value added. Second, over four-fifths of the improvement in economy-wide net profits was accounted for not by an increase in gross profits, but by a reduction in gross losses. Assuming that even in 1998 the fuel sector only accounted for a small share of loss-makers suggests, again, that the increase in profitability largely originated outside the fuel sector. Finally, the increase in net profits in 1999 was roughly equivalent to $30 billion. In contrast, oil export earnings only increased by $4 billion, while the change in total fuel export earnings was even smaller. Further, it is unlikely that profits on domestic fuel sales rose as much as profits on fuel exports, given that, since the crisis, domestic fuel prices have dropped substantially relative to world market prices and the continued existence of targets for domestic deliveries by oil exporters (see Box 3). Even allowing for the reduced effective tax burden on the oil sector, one must largely look outside the fuel sector to account for the increase in overall profitability.

Enterprise Profits
19951996199719981999
(Billions of rubles)
Gross profits288238309358729
Gross losses37114135473152
Net profits251124174−115577
(Percent of GDP)
Gross profits18.711.112.313.316.0
Gross losses2.45.35.417.53.3
Net profits16.35.86.9−4.312.7
Sources: Goskomstat; and Fund staff estimates.
Sources: Goskomstat; and Fund staff estimates.

22. On the other hand, the depreciation led to a collapse in real consumer wages and hence to a sharp fall in consumption. The crisis caused the income distribution to shift dramatically against labor, reflecting the large rise in unemployment. In addition, given some inertia in nominal wages, the post-crisis acceleration in inflation led to a sharp reduction in real wages. The response of real wages to the depreciation involved a substantial under-shooting. Over time, as unemployment has subsequently fallen and inflation decreased, the shift was partially reversed and real wages and consumption have recovered. Real wages (seasonally adjusted) at end-April 2000 are now 17 percent above their end-1998 level but are still more than 20 percent below the end-1997 level.

The role of higher international energy prices

23. The external terms of trade have improved drastically since early 1999, reflecting mainly the increase in international oil prices. Average dollar prices of energy exports declined almost continuously between January 1997 and February 1999, falling by a cumulative 47 percent. Since then they have increased to reach a level about 10 percent above the January 1997 level. With oil exports accounting for about one-fifth of total exports, and other fuel items for roughly another fifth, the overall terms of trade (measured using world market prices to proxy for Russia’s non-energy export prices) declined by about 10 percent between the August 1998 crisis and the start of 1999, but have since increased by more than 50 percent.

24. There are four main channels linking the increase in energy prices with output growth. First, there is a direct supply response of energy output to higher prices. Second, demand by the energy sector for output of other sectors would increase. Third, energy prices may also affect output because of the significant financial linkages between export sectors and the rest of the economy. Finally, high energy prices have helped promote financial stability through their impact on the current account and foreign exchange reserves.

25. In the short term, the direct supply response of energy output to higher prices does not appear to be significant. Overall growth, especially of exports, is limited by capacity constraints at both the extraction and transportation stages. Hence, production of oil and of gas (including gas condensate) increased, respectively, by only 0.3 percent and 4.1 percent in 1999. The fuel and fuel products sector accounts for less than 25 percent of overall industrial production, even assuming that all of the chemical and petrochemical industry is concentrated in oil and gas derivatives (Figure 7 and Table 4). Since industrial production in turn equals just over 30 percent of overall GDP (Table 3), the fuel sector accounts for about 8 percent of Russian GDP. Hence, the change in oil and gas output in 1999 caused a direct impact of only about 0.2 percent of GDP. In addition, the increase in fuel output likely reflected mainly previous years’ investment decisions rather than changes in energy prices. In the medium term, energy prices are likely to have a larger impact on fuel sector growth rates. Increases in the profitability of the fuel sector both increase available funds for investments by fuel companies themselves and attract interest from potential foreign investors. However, economic and political stability are likely to be more important determinants of fuel sector investment decisions than are energy prices, given the long gestation periods associated with such investments and the long life of the assets and infrastructure involved. In addition, the oil companies’ long-term oil price forecast is not significantly affected by short-term fluctuations.

Figure 7.Russian Federation: Structure of Output, 1999

Source: Goskomstat.

26. The increase in energy prices has contributed to an increase in exporters’ margins, and a large fraction of these gains is being spent on capital equipment and other domestic inputs. For instance, higher energy prices have encouraged energy companies to improve their infrastructure, leading in particular to a boom in oil companies’ demand for (domestically produced) oil pipes. In turn, rising incomes for all those linked to the fuel sector result in a second-round growth in aggregate demand. In addition, exporters are using their increased resources not just to expand their traditional operations, but also to diversify, both downstream and horizontally. In particular, some exporters are shifting their focus from natural resource extraction to processing.9 Nevertheless, the economy-wide increase in profitability appears to have been driven less by the increase in energy prices than by the effect of the devaluation on profits in both exporting and import-competing industries (Box 3).

Figure 8.Russian Federation: Consumer and Producer Prices for Utilities and Energy, 1997–2000

(July 1998 = 100)

Source: Goskomstat and Fund staff estimates.

27. The windfall gains in the export sector enabled it to increase payments to suppliers and the budget. In turn, this helped bring about a more generalized reduction in arrears and non-cash payments, including at the level of the federal budget. However, the above evidence on profitability hints, again, at a lesser role for higher energy prices in solving die non-payment crisis, compared to the impact of the devaluation.10 This conclusion is reinforced by evidence on timing: in 1999, total overdue payables fell in every single month, including those months when energy prices were still falling.11

28. The positive effect of high energy prices on financial stability, through their impact on the current account and on foreign exchange reserves, is significant but it has not been as important as the ruble depreciation. The contraction of imports following the August 1998 crisis accounted for a much greater fraction of the turn-around in the trade balance in 1999 than changes in energy prices. Specifically, while the average Urals oil price increased from $11.8 in 1998 to $17.0 per barrel in 1999, the dollar value of Russia’s oil exports rose by only $4 billion, in part due to the fact that the oil price increase occurred in the second half of the year. The change in total fuel exports was even smaller. Indeed, overall dollar exports barely changed relative to their 1998 level. In contrast, the total trade surplus increased by over $20 billion.

Box 3.Administered Prices

In the wake of the August 1998 devaluation, most administered prices were not fully adjusted in line with inflation; this real erosion has not been reversed. As shown in Figure 8, the real (CPI-deflated) consumer prices for utilities (including electricity, gas, heating, water and sewage, and hot water) had been gradually rising over 1997 and the first half of 1998, with a particularly sharp increase for gas prices. This reflected the continuation of a trend reduction in implicit subsidies which had started in 1992. However, the crisis led to a sharp break in this trend. Real utility prices fell by about 40 percent between July 1998 and January 1999, and since then they have been only marginally increased. The decline in dollar terms has been even sharper, reflecting the ruble’s real depreciation. For instance, the cost of electricity per kWh has decreased from about 2.6¢ in July 1998 to just over 1¢ in March 2000. These developments appear to reflect a deliberate attempt both to protect household living standards in the face of a sharp decline in real wages, and to support energy-intensive industrial sectors.

In contrast, real fuel prices fell initially, but have increased sharply since early 1999. In CPI-deflated terms, which are most relevant to gauging the impact on living standards, consumer and producer prices for gasoline fell by about one-third between July 1998 and January 1999. However, by March 2000, they were almost one-third and almost 80 percent, respectively, above their immediate pre-crisis levels. likewise, producer prices for furnace fuel and diesel fuel, after an initial decline, were respectively about 25 percent and 60 percent above then- July 1998 levels. In PPI-deflated terms, which are most relevant to gauging the impact on production costs, even immediately after the crisis none of die above prices declined significantly.

The increases in fuel prices have failed to match changes in the world oil price. When gauging changes in the extent of subsidization, it may be more relevant to deflate energy prices by the world oil price, that is, to look at the ratio of domestic energy prices to world oil prices. For consumer prices for gasoline, this ratio fell by over 70 percent between July 1998 and April 1999. A series of sharp price adjustments then brought the ratio back, by October 1999, to 50 percent of the pre-crisis level. Since then, the ratio has again declined, reflecting the recent oil price swings. Producer prices for fuel have displayed similar swings, although since the crisis they have risen sharply relative to consumer fuel prices.

Specific taxes on the oil sector, like utility prices, have been subject to significant real erosion in the wake of the crisis. Following the ruble devaluation, all taxes set as ruble-denominated flat rates (including gasoline and crude excises, local refining taxes, and local production taxes) fell significantly in dollar terms: total ruble-denominated taxes have declined from the equivalent of around $4/barrel in 1996 and 1997 to $l/barrel in 1999. In particular, crude excises have not changed in ruble terms since the devaluation. Although gasoline excises have been raised twice in ruble terms, they have still declined in dollar terms; the same is true of local taxes.

Notwithstanding the introduction of new taxes, effective taxation rates in the oil sector remain below pre-crisis levels. Crude oil export duties had been scrapped at the beginning of 1996, but were reintroduced (denominated in euros) in February 1999. However, their effective value has remained quite low, relative to world oil prices. Specifically, crude export duties averaged about 80.5/barrel in the first half of 1999, rising to about $l/barrel in the last quarter of 1999, and about 82.5/barrel in the first quarter of 2000. Further, these duties are only charged on around 38 percent of Russian produced barrels (the share which is exported). The result has been that the ratio of oil companies’ tax expenses to total revenues fell substantially between 1997 and 1999 (see table below), although a partial recovery is estimated to have occurred in 2000.

Russian Oil Production and Refining: Tax Burden
1996199719981999
Tax expenses (excluding profit tax) gross revenues, percent44444531
Memo: Tax expenses, US$/barrel10.199.866.424.54
Source: Troika Dialog
Source: Troika Dialog

29. The high world energy prices have enabled the authorities to delay adjustment in the administered prices for domestic utility and energy, providing an implicit subsidy to energy users particularly the industrial sector. However, the magnitude of the implicit subsidy provided by artificially depressed utility prices is likely no greater than the subsidy that used to be provided in the form of acceptance of arrears. 12 Domestic real prices for most utilities, including electricity (the most important source of energy for enterprises) and gas, fell by about 40 percent after the crisis and are still some 30 percent below their pre-crisis levels. On the other hand, domestic real fuel prices (including those for all gasoline types, diesel oil, and furnace oil) fell sharply in the immediate aftermath of the crisis, but were soon adjusted upwards. By July 1999, most fuel prices were already well above their pre-crisis levels, and they have increased significantly since, even though the increases have lagged behind changes in the world oil price. Further, arrears to the energy sector have been shrinking over time, while cash collection rates have been rising. As a result, some estimates suggest that the amount of subsidy extended by the infrastructure monopolies to other sectors of the economy may have remained relatively stable over the years, at about 2–3 percent of GDP.

D. Labor Market Trends

30. Unemployment has started to decline but remains at about 11 percent. Unemployment had increased steadily since the start of transition reflecting considerable excess labor and constraints to lay-offs. Overall, under the ILO definition, the unemployment rate stood at 11 percent just before the crisis. It then rose to over 14 percent in February 1999, before declining to just over 12 percent at end-1999 (Table 9) and to 11.4 percent at end-June 2000. Registered unemployment is much lower, and actually declined from 3 percent at end-1997 to 2 percent at end-1999. The wide discrepancy between estimated and registered unemployment reflects the impact of the limited unemployment benefits, combined with strict eligibility requirements. Unemployment spells have become longer, with the average duration of job search increasing steadily from 9 months at end-1997 to 10 months at end-1999 (Table 11). As the persistence of unemployment has increased, so has the share of long-term unemployed, especially among those approaching retirement age.

31. Regional variation in unemployment rates is extremely high, and shows little evidence of declining (Table 10). For instance, in 1999 unemployment rates of 6–9 percent in Moscow and Orlov contrasted with average rates of over a quarter in the North Caucasus, even excluding Chechnya. Migration flows across regions have so far had only a limited impact on this variation in unemployment, and they show little sign of increasing over time (Table 14). Labor mobility is greatly hampered by rigidities in the housing market and the sheer geographical size of Russia which makes relocation costs prohibitive for many workers.

32. The labor market has become more active but a number of serious rigidities remain. Labor turnover statistics indicate a relatively active labor market, where the annual separation rate and the annual rate of new hires are both around one-quarter of total employment (Table 6). However, the extent of inter-sectoral labor reallocation is slowing down, while formal employment has lagged well behind output movements at the sectoral level (Tables 5 and 7). Enterprises continue to hoard labor for several reasons, including significant political pressures not to lay off workers and legal restrictions on severing labor contracts.13 Labor movement is also constrained by the existence of significant non-wage social benefits provided by firms, the inadequacy of the social safety net, and limited opportunities for geographic mobility.14

ANNEX 1

Russia’s Growth Performance, 1991–97

Stylized facts: output growth in transition economies

33. The transition process was associated with a large output loss. Output collapsed in almost all countries when transition began, and the sharp initial decline was followed by a sometimes protracted “bottoming out” phase. By 1997, growth had resumed in the vast majority of transition countries. These developments are depicted in Figure 9, which presents output paths for the Baltics, Russia and other countries of the former Soviet Union (BRO) and Central and Eastern Europe (CEE), both in standard calendar time and in “transition time” (where output indices for different countries are compared across similar years in the transition process, so as to adjust for differences in the year when transition began).

Figure 9.Economic Transition and GDP Changes, 1989–99

Source: IMF World Economic Outlook database.

1/ Transition year zero is defined as the year in which central planning was decisively abandoned. This is taken to be 1992 for the BRO countries, 1990 for Poland, Hungary and countries on the territory of the former Socialist Federal Republic of Yugoslavia, and 1991 for the remaifting Central and Eastern European countries.

34. While the length of the transitional contraction varied considerably across countries, on average it was much longer and deeper in the BRO than in the CEE (Table 19). In the BRO the duration of the contraction ranged from 4 to 9 or more years, with a median of 6 years; in Russia, it lasted 9 years. In the CEE the contractions generally lasted between 2 and 5 years, with a median of 4 years. Similarly, while the depth of the contraction varied significantly across countries, in general it was distinctly larger in the BRO than in the CEE. In the BRO the average contraction equaled 52 percent of real GDP, ranging from 15 percent in Uzbekistan through 47 percent in Russia to 77 percent in Georgia15 In the CEE the average contraction only amounted to 23 percent.

35. The depth of the contraction also varied substantially across sectors and regions within the same country. In the BRO, the (unweighted) average output dropped by 46 percent between 1990 and 1997. The decline was more pronounced in industry and transport & communications, where production fell by over half, and most dramatic in the construction sector, which shrank to one-third of the level observed in 1990. In contrast, production in agriculture and trade only fell by around one-third. The evolution of output has also varied substantially across regions within the same country, particularly in large and diverse countries such as Russia, Ukraine and Kazakhstan (Table 20). These differences across regions reflect inter alia the diversity in the stance of local policies which, for Russia, have been documented in Berkowitz & DeJong (1999).

Growth accounting in Russia

36. Assuming an aggregate Cobb-Douglas production function, aggregate output growth can be decomposed into labor growth, capital growth, and the residual, total factor productivity (TFP) growth.16,17 TFP growth should not be interpreted as simply an estimate of the rate of exogenous technological progress: it includes any factor affecting the efficiency with which inputs are used.18

37. Most of the output contraction was accounted for by negative TFP growth. Over the period 1991–97, Russian output declined by an average 7.4 percent per year reflecting an average decline in TFP of 5.9 percent per year. For comparison, over 1971–90 average output growth equaled 2.2 percent per annum, while average TFP growth was close to zero. In the early years of the transition, TFP growth was sharply negative, but it then gradually stabilized although it remained negative even after 1995.

38. This approach can be refined in a number of ways. One is to adjust labor input for the number of workers on shortened days and/or compulsory leave, and adjusting capital input for the capacity utilization rate. Even after making such adjustments, one finds that over 1991–96 average TFP growth equaled -4 percent per year, accounting for about half the average output decline of 9 percent per year. Again, even after 1995, average TFP growth was negative. A further refinement involves decomposing aggregate output and inputs into sector-specific output and inputs. Using this approach, average TFP growth over the period 1991–96 equaled -3 percent per year, and again it remained negative even after 1995. Examining the sectoral distribution of inputs, labor shifted away from construction and industry and towards trade; capital shifted away from agriculture and trade and towards services; and resources in general shifted away from the old state firms in construction and industry and towards new small-scale service activities. Perhaps surprisingly, this sectoral input reallocation appears to have-had a negative impact on TFP growth.19 The absolute effect, however, was extremely small: most of the aggregate TFP decline reflected the decline in sector-specific TFPs.

39. Overall, these developments are comparable, and indeed slightly superior, to the average values observed in other BRO countries, but inferior to that of the CEE (Figure 10).20 However, the average for the other BRO is sharply lowered by countries which were torn by internal and external conflict (Armenia, Azerbaijan, Georgia, Moldova, and Tajikistan). The Baltics experienced a substantial decline in productivity at the start of transition, reflecting their high degree of openness and the collapse of trade relations among the BRO, but by 1995 their TFP growth had turned sharply positive and sectoral resource reallocation actually acted to raise their productivity. In Poland, which began its transition in 1989, aggregate TFP growth turned positive in 1992 in tandem with the return to growth of the overall economy, and it averaged somewhat less than 4 percent per year over 1992–98.21 The corresponding figures for Hungary, the Slovak Republic and the Czech Republic were 2.2 percent, 1.2 percent and 0.5 percent, respectively, all significantly above Russian levels.

Figure 10.Economic Transition and Productivity Changes, 1989–99 1/

Sources: De Broeck & Koen (2000b); author’s calculations.

Determinants of the growth performance in Russia

40. One view focuses on initial conditions, and specifically on the degree of pre-transition distortions. It postulates that the transition process involves a breakdown of economic relations among firms; Blanchard & Kremer (1997) call this “disorganization”. The old structures that worked under central planning, including supply networks and trade patterns, are destroyed, and it takes time for new ones to emerge. Russia (like most other CIS countries) suffered relatively more because its economy had been under central planning for the longest time, and was more distorted than in other transition countries. In particular, it suffered relatively more from over-industrialization (although this was partially offset by a lower degree of trade dependency with other countries). On this hypothesis, if and when new market institutions and structures are established, Russian productivity growth should soon and almost automatically rise sharply, so as to equal and possibly exceed the levels observed in the more successful transition economies.

41. Another view suggests instead that cross-country differences in performance are best explained by the structural reforms pursued by different transition economies. In particular, several authors have identified the following factors:

  • Financial development. In Russia, the financial system always engaged in very little intermediation. Banks offered few credits to the production sector, engaging instead in proprietary securities trading. The intermediation has further declined in the wake of the crisis. This has not proved an obstacle to the recent recovery, since existing industrial firms have been able to finance investments from their cash flow. However, these deficiencies in the financial infrastructure constitute a barrier to the entry of new firms and to the emergence of new sectors.
  • Rule of law. Weaknesses in the rule of law discourage investment and create entry barriers for new firms. In Russia, bureaucratic procedures for business registration and regulation, and the need to obtain various permits and authorizations from various different agencies, create vast scope for rent-seeking, as manifested in corruption and (related to it) unpredictable and discretionary levels of taxation. Government authorities, especially at the local level, are especially keen to use their powers, both in enforcing regulations and in awarding contracts, to protect politically influential incumbents (McKinsey Global Institute (1999)).
  • Privatization and general reform enthusiasm. Across Russian regions, economic growth is found to have a close correlation with the formation of new legal enterprises. The latter, in turn, is closely linked to the extent of privatization initiatives, and to the general enthusiasm for reform as proxied by the willingness of electors to support pro-reform parties.
  • Internal and external liberalization. Russia has made significant progress in terms of liberalizing domestic prices, dismantling trading monopolies in domestic markets, and removing trade controls and quotas. However, it still has relatively high tariff rates, and maintains significant foreign exchange restrictions. While these measures may yield short-run benefits, in terms of raising revenue and reducing capital flight, they also represent a large medium-run obstacle to continued productivity growth.

42. A third view centers on macroeconomic conditions. It particular, it views macroeconomic stabilization, as proxied by inflation, as a pre-requisite for sustainable growth. While Russia eventually succeeded in bringing inflation under control, its fiscal deficits were never fully confronted until after the crisis. Since these deficits were seen as likely to be eventually monetized, they had a damaging effect on inflationary expectations, and led to periodic crises.

43. Several studies have tried to test these views using cross-country and cross-regional regressions. 22Berg et al. (1999) analyze a sample of 10 CEE countries, the three Baltic republics, the 12 CIS countries, and Mongolia over a period which spanned their transition. Their key results were as follows.

  • Macroeconomic variables. Increases in inflation have a strong adverse effect on private sector growth. A reduction in the fiscal deficit, however, also has a negative effect on private sector growth. This reflects two factors: first, a fiscal contraction has a negative short-run aggregate demand effect; second, the regression already controls separately for the impact of the fiscal deficit on inflation.
  • Structural variables. Internal liberalization has a positive impact on private sector growth, in line with standard theory. External liberalization initially has a negative impact on the private sector, possibly reflecting the destructive effect of foreign competition on inefficient incumbents. However, as time passes and the easing of import constraints benefits newly emerging private firms, the sign of the effect is reversed. Finally, increases in an index of private sector entry conditions, which measures progress in privatization and financial sector reform, have significant effects after a one-year lag.
  • Initial conditions. Higher trade dependency and over-industrialization have an adverse aggregate effect on the initial output decline. Higher urbanization and a lower share of agriculture are associated with faster initial growth of the private sector. The impact of these initial conditions vanishes over time, but slowly (with a “half life” of about 5 years).

44. These conclusions were refined and qualified by Havrylyshyn et al. (1999). In reviewing the growth experience of 25 CEE and BRO countries in the period 1990–98, they focused not only on the importance of adverse initial conditions and the role of policies on growth and its sustainability, but also on the magnitude of the trade-offs between them. Qualitatively their most important conclusions were as follows.

  • Macroeconomic and structural factors. Financial stabilization is a necessary but not sufficient condition for sustained growth. Macroeconomic stabilization needs to be complemented by comprehensive progress on market-oriented structural reforms for growth to be sustained and to attract foreign direct investment.
  • Initial conditions. Initial conditions, notably over-industrialization, are not without importance but their impact can be readily offset by strong reform efforts, particularly a more rapid pace of structural reform. Indeed, while bold reform is associated with a greater initial output decline, it is also associated with a faster recovery.

45. The insights from these two studies can be combined to account for the path of output during transition and to highlight cross-country differences in the transition experience. In Table 21, the fitted values from the regressions are averaged over time, distinguishing only between two broad time-phases—the earlier and the later transition years. For each phase, the fitted values are shown for Poland, Hungary, the Czech Republic, Slovakia, each of the Baltics, Russia, and the other BRO. There are three key conclusions. First, the model displays a very good fit. Second, a number of countries with “bad” initial conditions (such as Poland, with high degrees of initial trade dependency and overindustrialization), made up for them by reforming faster or having smaller macroeconomic imbalances. Conversely, other countries with relatively good initial conditions often reformed more slowly, partly or wholly offsetting the effect of the initial conditions. Third, Russia suffered from relatively bad initial conditions, including in particular overindustrialization-However, the crucial difference compared with, say, the Czech Republic or the Baltics lay in its failure to reform aggressively. For instance, if Russia had reformed as quickly and thoroughly as Estonia, it might have expected an average growth rate over 1992–96 of about --3.5 percent, or 5 percentage points higher than actually occurred; indeed, Russia would actually have returned to positive growth already in 1995. However, given the relatively few observations available on each country in isolation, all these country-specific results should be interpreted very cautiously.

References

    BergBorenszteinSahay& Zettelmeyer (1999) “The Evolution of Output in Transition Economies: Explaining the Difference,”IMF WP 99/73.

    • Search Google Scholar
    • Export Citation

    Berkowitz& De Jong (1999) “Accounting for Growth in post-Soviet Russia,”mimeo (University of Pittsburgh).

    Blanchard& Kremer (1997) “Disorganization,”Quarterly Journal of Economics112(4):10911126.

    Christoffersen& Doyle (1998) “From Inflation to Growth: Eight Years of Transition,”IMF WP 98/100.

    DeBroeck& Koen (2000a) “The ‘Soaring Eagle’: Anatomy of the Polish Take-off in the 1990s,”forthcoming IMF WP.

    DeBroeck& Koen (2000b) “The Great Contraction in Russia, the Baltics and the Other Countries of the Former Soviet Union: A View from the Supply Side,”forthcoming IMF WP.

    • Search Google Scholar
    • Export Citation

    DeMeloDenizer& Gelb (1996) “From Plan to Market: Patterns of Transition,”World Bank Policy Research WP 1564.

    DeMelo& Gelb (1997) “Transition to Date: a Comparative Overview,”in Salvatore Zecchini,ed.:Lessons from the Economic Transition. Central and Eastern Europe in the 1990s pp. 5978.

    • Search Google Scholar
    • Export Citation

    DeMeloDenizerGelb& Tenev (1997) “Circumstance and Choice: the Role of Mtial Conditions and Policies in Transition Economies,”World Bank Policy Research WP 1866.

    • Search Google Scholar
    • Export Citation

    Dolinskaya (2000) “Explaining the Russian Output Collapse: Aggregate Sources and Regional Evidence”,mimeo (IMF).

    FischerSahay& Vegh (1996a) “Stabilization & Growth in Transition Economies: The Early Experience,”Journal of Economic Perspectives10(2):4566.

    • Search Google Scholar
    • Export Citation

    FischerSahay& Vegh (1996b) “Economies in Transition: the Beginnings of Growth,”American Economic Review Papers & Proceedings:229233.

    • Search Google Scholar
    • Export Citation

    FischerSahay& Vegh (1998a) “From Transition to Market: Evidence and Growth Prospects,”IMF WP 98/52.

    FischerSahay& Vegh (1998b) “How Far is Eastern Europe from Brussels?”,IMF WP 98/53.

    Fischer& Sahay (2000) “The Transition Economies after Ten Years”,IMF WP 00/30.

    HavrylyshynWolfBerengautCastello-Brancovan RoodenMarcer-Blackman (1999) “Growth Experience in Transition Countries, 1990–98” IMF OP 184.

    • Search Google Scholar
    • Export Citation

    JohnsonKaufmann& Shleifer (1997) “The Unofficial Economy in Transition,”Brookings Papers on Economic Activity(2):159240.

    McKinsey Global Institute (1999) “Unlocking Economic Growth in Russia”.

    Shleifer& Vishny (1993) “Corruption,”Quarterly Journal of Economics108:599618.

    Zettelmeyer (1998) “The Uzbek Growth Puzzle,”IMF WP 98/133.

1

Annex I provides a longer-term perspective on output growth in Russia and a comparison with experience in other transition countries.

2

For quarterly data, there are two main problems. First, for export and import volumes and prices, there are no aggregate time series, but only year-on-year growth rates for selected commodities. This is particularly significant since annual customs data suggest that there have been major changes in the prices of both exports and imports that cannot be related to changes in observable world market prices, such as the spot price for oil. Thus, construction of export and import price indices on the basis of world prices is unlikely to provide reliable information on underlying developments. Second, there are no quarterly time series for the expenditure components of real GDP. While proxies are available for bodi private consumption and fixed capital formation, the time series for such proxies are internally inconsistent and are only weakly correlated with the annual national income data.

3

In 1999 Q1, for instance, export volumes for machinery, chemicals, and wood and paper products, which together account for about one-quarter of total exports, were on average some 40 percent above their level one year before. For ferrous and non-ferrous metals, which account for another 22 percent of total exports, the corresponding year-on-year growth rate was almost 13 percent.

4

The counterpart of such volume increases must be large decreases in dollar prices. The latter can only in small part be linked to movements in observable world commodity prices, such as for nickel and other metals. The dollar price declines were especially large for exports to the CIS, which account for about 15 percent of total exports, reflecting the weakening output and the devaluations in some of these countries as well as Russia’s position as a large country for trade with the CIS in some products. In 1999 Q1, for example, average prices for metal exports to CIS and non-CIS countries, respectively, were 55 percent and 29 percent below their values of one year before. For chemicals, the corresponding figures were 55 percent and 37 percent.

5

Data on capital formation in the first quarter of 2000 are difficult to interpret. The official estimate implies a decline of 6 percent, but this conflicts with other data showing a significant increase in construction activity.

6

Year-on-year growth rates for textiles and machinery were, respectively, 55 percent and 41 percent.

7

The real exchange rate relative to the U.S. dollar, though, appreciated by 2.5–3.0 percent per month in May through July 2000.

8

A detailed discussion of the real effects of the non-payment crisis is contained in SM/99/178, 7/14/99.

9

The aluminum industry, which has also benefited from an increase in dollar export prices, is a prominent example.

10

Three additional factors may have contributed to the decline in non-payments. First, liquidity is no longer being absorbed by the GKO market. Second, the federal government has insisted on collecting revenues in cash. Third, confidence may have increased in the ability of the courts to pursue bankruptcy proceedings and protect property rights.

11

Defined as the stock of overdue payables in the nine basic sectors of the economy, deflated by the PPI.

12

This issue is explored in depth in the “1998—2000 Economic Review — Russian Federation” publication of the OECD.

13

Rigidities in the labor market are discussed in more detail in SM/99/178, 7/14/99.

14

The range of social services provided by enterprises has actually been increasing over time, partly reflecting the relatively favorable tax treatment of fringe benefits as opposed to cash wages.

15

The relatively shallow Uzbek contraction has surprised many, given the country’s hesitant and idiosyncratic approach to reform. Zettelmeyer (1998) argues this growth performance reflected a combination of low initial industrialization, significant cotton production, and selfsufficiency in energy.

16

The elasticities of output with respect to labor and capital are set equal to, respectively, 0.7 and 0.3.

17

This section draws on forthcoming work by De Broeck & Koen (2000b) and Dolinskaya (2000).

18

Being a residual, it also includes any bias due to methodological assumptions and measurement errors. However, to the extent that the focus is on contrasting growth before and during the transition, or growth during the earlier and the later transition years, the approach remains valid as long as the computational biases are constant over time. The impact of errors in measuring the capital stock deserves special mention. Estimates of the capital stock are constructed by applying a depreciation rate to the inherited stock, and adding in new investment. The depreciation rate is calculated using the national income capital consumption measures. Especially for the early transition years, these depreciation rates may be under-estimated since they largely reflected the very slow depreciation allowed under the tax system. Given the significant obsolescence which in fact occurred, this imparts an upwards bias to the capital stock. Hence, there is a downward bias in measured TFP growth during the early transition years. However, to the extent that the focus is on contrasting growth across countries at equivalent stages of the transition process, the approach remains valid as long as the bias affected all countries equally.

19

One possible explanation is that value added in trade and services may be underestimated.

20

All comparisons between TFP growth in Russia and other countries are done using the “standard methodology”, unless otherwise stated.

21

De Broeck & Koen (2000b) point out that “During the initial recovery 1992–93,… positive TFP growth in excess of overall growth mainly reflected an increase in capacity utilization rates. In the following years, as renewed growth in input of factors, in particular capital, was recorded, the contribution of TFP growth to overall growth fell back to somewhat less than two-thirds.”

22

Most of these regressions have focused on GDP growth, reflecting considerations of data availability; however, some authors have recently started to analyze TFP growth. De Melo, Denizer & Gelb (1996) and De Melo & Gelb (1997) were the first to quantify and systematically study the role of structural reforms. Fisher, Sahay & Vegh (1996 a, b; 1997) introduced macroeconomic policies. De Melo, Denizer, Gelb & Tenev (1997) studied the role of initial conditions in detail.

Other Resources Citing This Publication