The Selected Issues paper on the Russian Federation discusses the economic growth and future growth potential of the country. After almost a decade of impressive growth performance, Russia suffered a sharp contraction in 2009 with GDP falling by 8 percent. This paper gives an overview of the conceptual issues regarding potential growth and the analytical framework based on an exogenous growth model; growth accounting results for Russia in the past decade; and importance of structural reforms to achieve sustained high growth.

Abstract

The Selected Issues paper on the Russian Federation discusses the economic growth and future growth potential of the country. After almost a decade of impressive growth performance, Russia suffered a sharp contraction in 2009 with GDP falling by 8 percent. This paper gives an overview of the conceptual issues regarding potential growth and the analytical framework based on an exogenous growth model; growth accounting results for Russia in the past decade; and importance of structural reforms to achieve sustained high growth.

I. Russian Federation—Potential Growth: the Past and the Future1

Russia’s fast growth in the past decade was driven mainly by TFP growth. The increased demand for capital was mostly met by heavier utilization of the existing stock. While some moderation of TFP growth is expected in the next decade, the scope for more intense use of capital is limited, implying that investment and capital accumulation should play a bigger role than in the past. Given the unfavorable demographic trend in Russia, this highlights the urgent need for structural reforms to improve the investment climate and labor participation.

A. Introduction

1. After almost a decade of impressive growth performance, Russia suffered a sharp contraction in 2009 with GDP falling by 8 percent. The sharp and costly adjustments during the crisis raise important but hard-to-answer questions: how would Russia’s potential growth in the next decade be compared to that in the past; and what needs to be done to help the Russian economy grow again at the impressive pace during the inter-crisis period.

2. Projecting Russia’s potential growth generally requires a careful examination of the past growth experience. With a clear understanding about the sources of the past growth, one can assess how the underlying forces will change in the future and how the growth path will respond to the changes. Based on a growth accounting approach, this paper will analyze the key sources of Russia’s growth in the last decade and evaluate Russia’s growth potential in the future. Relevant questions include:

  • What are the main forces that drove Russia’s growth in the last decade?

  • How did Russia’s efficiency level evolve in the last decade and how large is the remaining scope for catch-up?

  • What will be the main source of Russia’s growth in the next decade and how will the growth path respond to the different environment?

  • What should be done to raise Russia’s growth potential?

3. The paper is organized as follows. Section B will provide an overview of conceptual issues regarding potential growth and the analytical framework. Section C will present the growth accounting results for Russia in the past decade. Section D will describe an exogenous growth model, which provides the analytical framework for the growth accounting exercise in Section C and simulations in the following section. Section E will evaluate Russia’s potential growth based on the simulation results, and it will highlight the importance of structural reforms to achieve sustained high growth.

B. Potential Growth and Productivity

4. Potential growth in this paper refers to a long-run GDP growth forecast. Potential growth is often used to describe related, but logically distinct, concepts.2 In this study, potential growth means a “steady-state” growth as defined in growth literature, and the optimal transition path toward the steady state. While analyzing the source of Russia’s growth in the past and the future, the paper offers a forecast for Russia’s sustainable long-run growth rate, with a particular emphasis on the transition path under specific assumptions on productivity growth and efficiency enhancement.

5. In assessing Russia’s potential growth, this paper relies on a growth-accounting framework, which has been widely used in growth literature. By linking GDP growth to the changes in production inputs, a growth-accounting framework provides a useful means to decompose GDP growth into the contributions from capital accumulation, changes in labor supply, and a residual factor, commonly known as total factor productivity (TFP). Further, the growth-accounting framework can be used to project potential growth in the longer term, by forecasting the future evolution of labor, capital and TFP.

6. However, it should be noted that growth accounting shows only the source of growth and is not intended to determine the causes of growth. This can be best explained with an example. Consider a country where both capital per worker and factor productivity have increased rapidly. The growth-accounting exercise will show the relative importance of each factor in GDP growth, but it cannot determine whether the productivity growth caused the capital deepening (as suggested by exogenous growth theories) or whether the capital accumulation made additional innovation possible (as suggested by endogenous growth theories). This implies that a simulation-based projection in this study will need an explicit assumption on the causality, which allows us to trace the optimal responses of endogenous variables to exogenous developments.

7. In this study, we follow a Solow-type approach—economic growth is directly linked to efficiency/technological progress and labor supply, which are exogenous in our framework. These exogenous factors determine the optimal paths of all endogenous variables such as consumption, investment, and income growth. The ‘exogenous’ efficiency/technological progress is captured as improvements in TFP, which we view as closely related to structural reforms.

C. Source of Growth in Russia: 2001–11

8. Russia’s GDP grew by about 5 percent annually during 2001–11. However, the investment to GDP ratio remained relatively unimpressive at around 20 percent during this period, and labor growth was not as significant as in other fast growing economies. This implies that factor accumulations were not the main source of growth, which was also suggested by earlier studies by Oomes and Dynnikova (2006) and Tiffin (2009). The relatively solid growth performance in the last decade raised Russia’s PPP GDP per capita from 29 percent of the OECD average in 2001 to 41 percent in 2010.3 However, with Russia’s per capita income level still below the half of the OECD average, large scope for further catch-up remains.

uA01fig01

Russia: GDP growth, labor and investment

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Sources: World Economic Outlook; and IMF staff calculations.
uA01fig02

Russia: PPP GDP per capita

(percent of OECD average)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Sources: World Economic Outlook; and IMF staff calculations.

9. The efficiency of the Russian economy has also improved from 35 percent of its “best-practice” frontier in 2001 to 50 percent in 2011.4 There are five main factors that contribute to an improvement of labor productivity at an aggregated level: (i) improvements in the general efficiency/technology; (ii) variable factor utilization; (iii) resource reallocation across sectors; (iv) widespread imperfect competition and increasing returns; and (v) capital accumulation (Basu and Fernald, 2000). The full decomposition of these factors requires more detailed sectoral data than currently available for Russia. Given this data constraint, the paper focuses on the role of capital utilization and TFP growth in explaining the Russia’s productivity improvement in the last decade.

10. A typical growth accounting assumes that factor utilizations are stable over a longer time period. In this case, the productive use of capital stock and labor would be proportional to the size of capital stock and the number of workers, and thus the growth rate of factor service flows can be proxied by that of the stock of production factors. However, it is well known that factor utilizations vary significantly over a business cycle, and this approximation does not hold in the short to medium run. For this reason, a growth accounting framework is generally recommended to analyze growth experiences over longer-run periods of a decade or more, assuming that factor utilization fluctuates around the mean without showing any trend in the long run.

11. The conventional growth-accounting exercise suggests that about 86 percent of Russia’s growth in 2001–11 was contributed by TFP growth.5 During this period, GDP grew by 4.8 percent per year, while capital stock and labor grew by less than 1 percent per year. This level of TFP contribution is unusually high, although there seem to have been easy technological catch-up opportunities for Russia during this period. The TFP contribution to GDP growth was even higher for the period between 2001 and 2008, implying that investment during this period was just enough to cover the depreciation of capital stock.

uA01fig03

Contributions to GDP growth

(percentage point)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.
uA01fig04

Capacity utilization

(percent)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: Russian Economic Barometer

12. However, many empirical and theoretical studies suggest that capacity utilization in a fast growing economy can exhibit an increasing trend over an extended period. In fact, according to the survey data (Russian Economic Barometer), capacity utilization in Russia increased from 66½ percent in 2000 to 79½ percent in 2007 before falling to 76½ percent in 2008.6 Under this circumstance, failure to reflect the increasing trend of capacity utilization in the growth accounting will lead to an overestimation of the TFP contribution to GDP growth.

13. To address this measurement issue, the following section will propose an exogenous growth model where the level of capacity utilization is determined endogenously. The model will provide an analytical framework to answer the following questions: What was the true growth contribution by TFP? Was the increasing capacity utilization an optimal response to the changes in the exogenous environment or more of an anomaly? How would Russia’s growth path in the next decade respond to any changes in TFP growth?

D. Growth Model with Variable Capital Utilization

14. The special feature of the growth model in this section is that capital utilization is an endogenous variable, and the cost of heavier capital utilization is borne through accelerated depreciation.7 Specifically, the model is a variant of a Ramsey-type growth model with endogenous capital utilization (u) and depreciation (δ):

Qt=(ut.Kt)α(At.Nt)1-αδt=δ(ut)=δο+δ1.ut1+θ
Kt+1=(1-δt).Kt+It

where Q is output, u is the intensity of capital utilization, K is capital stock, N is labor, A is labor augmenting technology (efficiency), I is investment, and δ is depreciation. δo represents the depreciation that is independent of the intensity of capital utilization (also known as “rust and dust”), while δ1ut1+θ stands for the depreciation that increases with capital utilization (known as “wear and tear”).8

uA01fig05

Contributions to GDP growth

(percentage point)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.
uA01fig06

Capital utilization and depreciation rate

(percent)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Sources: Russian Economic Barometer; and IMF staff estimates.

15. The growth-accounting exercise based on variable capital utilization shows that the more intensive use of capital stock contributed significantly to GDP growth in the last decade. With capital utilization and depreciation assumed to vary over time, TFP growth accounted for about 68 percent of GDP growth during 2001–11 and 70 percent of the growth during 2001–08, significantly lower than the TFP contribution derived from the conventional growth accounting.9 The lower TFP contribution is the reflection of the higher growth contribution by capital, estimated at 26½ percent of the total GDP growth in 2001–11. This is significantly higher than the estimate based on the conventional approach (8½ percent), entirely because of the more intense use of capital stock.

16. The simulation of the model also indicates that the increasing trend of capital utilization in the last decade is fully consistent with TFP growth. For the simulation, we first calculate the TFP growth rates based on the actual utilization, investment, implied depreciation, and labor growth. Then, we calculate the optimal path of capital utilization, assuming that the economy faces exogenous shocks to the TFP growth rate, as estimated by the growth accounting.10 As shown in the chart, the predicted path of capital utilization is very similar to the actual utilization.

uA01fig07

TFP growth and capacity utilization

(percent)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Sources: Russian Economic Barometer; and IMF staff estimates.

17. The simulation results suggest that the increasing trend of capital utilization in the last decade was an optimal response to the changes in external conditions.11 With the sharp increase in the TFP growth rate during the first half of the last decade, the production possibility frontier of the Russian economy expanded faster, meaning higher marginal productivity of capital. The increased demand for capital would be met through more intense use of the existing capacity and/or a faster accumulation of capital stock. 12 Especially, when large idle capacity exists due to overinvestment in the past or a large negative TFP shock as at end-1990s in Russia, the increasing demand for capital service flow would be more likely to be met with higher utilization of the existing capacity for an extended period. This also explains why the investment to GDP ratio in Russia remained relatively low in the last decade, despite the jumpstart of economic catch-up.

E. Russia’s Long-Run Growth Path and Economic Catch-up

18. It is difficult to forecast the long-run growth path of an economy, given the complex interlinks among variables that are known as determinants of long-run growth. Further, as the forecasting horizon is getting longer, the future development depends more on what will happen than what has already been in place. Against this caveat, a scenario-based projection—the projected path of endogenous macroeconomic variables given the assumption on the exogenous forces—would be a reasonable alternative to an econometric exercise.

19. Four scenarios are considered, including the staff’s current baseline projections. Scenario 1 assumes that TFP will grow at the annual rate of 3 percent during 2012–20, similar to the average rate during 2001–11. Scenarios 2 and 3 are less optimistic than Scenario 1, assuming that TFP will grow at the annual rate of 1 and 2 percent, respectively. Staff’s baseline scenario does not make an explicit projection on the TFP growth rates. However, for comparison with the other scenarios, we calculate them using the projected investment-to-GDP ratio and GDP growth rates.

20. In all scenarios, labor supply is assumed to be constant throughout the period under consideration. UN projections suggest that the Russia’s population of age between 15 and 64 will decline from about 103 million in 2010 to 89 million in 2030, a decline of about 0.7 percent per year. Given the declining population, it will be challenging to keep labor supply constant in the long run. However, the effect of the projected adverse demographic change on labor supply could be limited in the medium term, as there still remains a significant gap in labor participation between the average upper middle income country and Russia. Pension reforms and more general labor market reforms would help more people remain active in labor, and more immigration from neighboring countries could also ease the pressures.

uA01fig08

Labor participation rate

(percent of total population over 15)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Sources: World Bank; and IMF staff calculations.

21. As expected, the medium to long-term growth rates depend on the underlying TFP growth. When TFP grows at the pre-crisis rate of 3 percent, the Russian economy is expected to grow at 5 percent or more in the next 8 years, very close to the average growth rate will decline to around 2½ percent per year during 2013–11. If TFP growth slows to 1 percent (Scenario 2), the growth rate during 2013–20, converging to the long-run rate of 2 percent. Growth will be very similar to the staff’s baseline projection when TFP grows at 2 percent per year, about ⅔ of the TFP growth rate estimated for the last decade.13

uA01fig09

GDP growth

(percent)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.
uA01fig10

Investment to GDP ratio

(percent)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.

22. Under all scenarios, the efficiency gap between Russia and the frontier is projected to decline. The efficiency frontier is measured as defined in Tiffin (2006, 2009). After the impressive efficiency catch-up from about 35 percent to 50½ percent of the frontier, Scenario 1 suggests a continuing improvement to 69 percent by 2020. The staff baseline and scenario 3 project the efficiency catch-up to around 64 percent of the frontier level. Even in the least optimistic scenario, Russia’s efficiency level is projected to increase to 58½ percent of the frontier. These results suggest that the room for Russia’s efficiency catch-up gains remains substantial.

uA01fig11

Efficiency ratio

(percent of the frontier)

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.

23. However, the simulation results suggest that the composition of the GDP growth in 2012–20 will be significantly different from that of the last decade. TFP growth will account for around 65–69 percent of the projected GDP growth during 2012–20, which is broadly in line with 68 percent in the last decade. However, the composition of the input growth—capital and labor services—is projected to be substantially different from that of the last decade.

uA01fig12

Contributions to GDP growth, variable capacity utilization

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates.
uA01fig13

Contributions to GDP growth, percent of GDP growth

Citation: IMF Staff Country Reports 2012, 218; 10.5089/9781475505047.002.A001

Source: IMF staff estimates

24. In all scenarios, scope for further increase in capacity utilization is limited. This implies that growth in the future will require a faster accumulation of capital stock through higher investment. Unlike the growth experience in the last decade, when the increase of capital services was made possible through higher utilization, growth in the next decade will require a significant increase in the capital stock to meet the demand for capital services.

25. Improving the investment climate will be essential to realize the growth potential. Even with good potential and right economic incentives, policy distortions and unstable macroeconomic environments could hamper the realization of the growth potential, particularly through their negative effects on investment. Capital utilization, which was the main source of capital input growth in the last decade, is generally less sensitive to the investment climate, because it can be easily reversed whenever needed. However, fixed capital investment—the main contributor in the next decade—is well known to be sensitive to the investment climate, including the strength of property right and macroeconomic stability, as it is more costly to reverse the investment decisions.

26. This reinforces the need for steadfast implementation of structural reforms in Russia. There has been no shortage of reform plans, but their effective implementation has been insufficient to change the investors’ perception on the Russian economy. Reforms can help materialize Russia’ growth potential through their direct impact on TFP as well as removing distortions affecting investment decisions. Further, given the significant inefficiency in the state-owned enterprises and considerable state interference in the economy, scope for efficiency gains through resource reallocation seems to remain large. Reforms to reduce the state interference in the economy (including through transparent and more decisive privatization of state-owned companies), improve the labor market flexibility, and ensure a stable fiscal regime for the investment in the new industries will be essential to materialize easy catch-up gains. Russia’s accession to the WTO should be a catalyst for these reforms, making the business environment more predictable and rule-based.

Appendix I.1.: Growth Model with Variable Capital Utilization

1. An economy maximizes the welfare (measured as a function of per capita consumption) over an infinite horizon. The labor supply (or population) and technology growth are determined exogenously. In conventional terms, the optimization problem can be written as follows:

Maxt=0(11+β)t.u(CNtNt),whereu(c)=c1-1η1-1η
subject to Kt+1-(1-δt).Kt=Qt-CNt
Qt=(ut.Kt)α(At.Nt)1-αδt=δ(ut)=δο+δ1.ut1+θ
Nt=No.(1+ηt)t
nt=(1-ρn).nο+ρn.nt-1+Ent
At=Aο.(1+gt)t
gt=(1-ρg).gο+ρg.gt-1+Egt

2. Here, CN is the aggregate consumption, N is population (identical to labor supply), K is capital stock, δ is the depreciation rate of capital stock, which is a function of capital utilization, u, n is the population growth rate, A is the labor-augmenting technology level, and g is the technology growth rate. En and Eg represent random shocks to population and technological growth rates, respectively.

To transform the optimization problem to one with a steady state solution, define:

ctCNtAt.Nt;ktktAt.Nt;ytQtAt.Nt

Then, the optimization problem can be rewritten as follows:

Max t=ογt·ct1-1η1-1η,Where γtAο1-1η.(1+gt)t.(1-1η)(1+β)t
subject to yt=utα·ktα
kt+1·(1+gt+1)·(1+ηt+1)-(1-δt)·kt=yt-ct
nt=(1-ρn)·nο+ρn·nt-1+Ent
gt=(1-ρg)·gο+ρg·gt-1+Egt
δt=δ(ut)=δο+δ1·ut1+θ

The optimal solution of the problem satisfies the following equations, simultaneously.

(1)ct=ct+1[(1+gt+1)(1+nt+1)Rt+1+(1-δt+1)1Γt+1]η
(2)ut=[αδ1(1+θ)ktα1]1θ+1α
(3)δt=δ(ut)=δ0+δ1ut1+θ
(4)nt=(1ρn)n0+ρnnt1+Ent
(5)gt=(1ρg)g0+ρggt1+Egt
(6)yt=utαktα
(7)Γt(1+gt)11η1+β
(8)[kt=11δt(1+gt+1)(1+nt+1)yt+ct]
(9)Rt=αytkt

The model consists of 9 endogenous variables, 2 exogenous variables (shocks to the growth rate of labor and technology, Ent and Egt) and 8 parameters.14

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Among others, the parameter values of the depreciation equation (3) warrants further elaboration. There are few econometric studies on the depreciation parameters. We assume capital stock depreciates by 2 percent per year, independent of the intensity of its utilization (δ0=0.02). The coefficient for the wear-and-tear part of depreciation (δ1) is set to make the total depreciation rate at the actual utilization in 2000 equal to about 5 percent: i.e., δ1 = {x:δ = 0.02 + x. u2.5, where δ = 0.05 and u = 0.67 }.15

References

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  • Tiffin, A. J., 2009, “Russia: Efficiency and Long-Term Growth,” IMF, unpublished manuscript.

1

Prepared by Daehaeng Kim.

2

In addition to the definition used in the paper, there are two other concepts that potential growth often describe. In a short-term macroeconomic context, potential growth refers to the output growth that an economy would have if there were no nominal rigidities but all other (real) frictions and shocks remained unchanged. This concept, often called “trend” growth, corresponds to the older Keynesian notion of potential growth, which is the maximum growth rate that an economy can achieve without causing inflationary pressure. Potential growth sometimes refers to the “optimal rate of growth” without distortionary taxes and other market imperfections. For more details, see Basu and Fernald (2001).

3

Comparing Russia’s output level today with that of the early period is subject to several measurement problems. For a summary, see e.g., Shleifer and Treisman (2005).

4

The efficiency ratio is defined as the ratio between Russia’ actual labor productivity and its efficiency frontier, which is estimated using a stochastic frontier model. The efficiency frontier is the production level when the economy uses all the available inputs in the most productive manner, given the current state of worldwide technology. For details, see Tiffin (2006).

5

Russia’s capital stock is estimated based on a perpetual inventory method, starting from the capital stock in 2000 estimated by Tiffin (2006). The extension uses the actual real fixed capital investment data, with the depreciation of capital stock assumed at 6½ percent per year. Following Oomes and Dynnikova (2006), we assume that the capital share is 0.5.

6

The survey has been conducted by the Institution of World Economy and International Relations of the Russian Academy of Science since 1991. The survey result has been published in the bulletin Russian Economic Barometer. The survey covers around 500 enterprises. For more details, see Oomes and Dynnikova (2006).

7

The labor cost of capital utilization could also be significant at the extensive margin (e.g., a higher wage rate for night shifts). However, the labor cost of capital utilization is not considered in the model, as labor market conditions (wages and unemployment rates) in the last decade indicate limited labor cost pressures associated with more intense use of capital in Russia.

8

Details of the model, optimality conditions, and calibration can be found in Technical Appendix.

9

With the assumption that the production technology is linearly homogenous, and the labor share is 0.5, the TFP contribution to growth should be 50 percent at the steady state. In this regard, the TFP contribution in the last decade estimated for Russia remains very high even after correcting for the increasing trend of capital utilization. There are several possibilities that contribute to an overestimation of TFP growth. First, there could be measurement problems in estimating capital stock and investment. Second, the capital utilization data may not reflect the actual trend of more intense use of capital accurately. Lastly, as noted in Section C, an explicit consideration of resource reallocation and increasing returns to scale would reduce the TFP contribution further.

10

In the simulation, we assume that TFP growth is random walk.

11

While the model shows that an increasing capital utilization, as observed in Russia during 2001–11, is the optimal response to technological catch-up, it has also been argued that it could reflect the decreasing distortions in factor markets (Kwon, 1986) and rent-seeking behaviors (Krueger, 1974).

12

In the equilibrium, the level of capital utilization is determined by the existing capital stock and the anticipated TFP growth rates, and the cost of heavier utilization becomes identical to the value of the depreciated portion of the existing capital stock.

13

The baseline investment to GDP ratio after 2014 is slightly lower than the level projected by the model (Scenario 3), which makes no material difference in the conclusion of this paper.

14

The (forward-looking) Euler equations are solved using the stacked-time algorithm in TROLL.

15

The annual depreciation of 5 percent is commonly assumed in growth accounting studies (e.g., Collins, 2007) and consistent with the depreciation rate implied by Russia’s capital stock and real investment during 1995–97, as estimated in Tiffin (2006).

Russian Federation: Selected Issues
Author: International Monetary Fund