## _cr12218 ## Source details **Canonical URL:** [_cr12218](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2012/_cr12218.pdf) ## Other formats - [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2012/_cr12218.pdf.md) - [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2012/_cr12218.pdf.json) --- ### Appendix I.1 — Growth Model with Variable Capital Utilization: summary of structure and calibration - Model type and objective: - Ramsey-type growth model with endogenous capital utilization (u) and utilization-dependent depreciation. - Representative production function: Q_t = (u_t K_t)^{α} · (A_t N_t)^{1−α}. - Depreciation specification: δ_t = δ_0 + δ_1 u_t^{δ_2}, decomposing “rust and dust” and utilization-dependent “wear and tear”. - Labor supply and labor-augmenting technology (TFP) treated as exogenous; TFP in simulations follows a random walk. - Key conceptual notes: - δ_0: depreciation independent of utilization (“rust and dust”). - Utilization raises depreciation via the δ_1 u^{δ_2} term (“wear and tear”). - Labor cost of higher utilization at the extensive margin not modeled (limited labor cost pressures in the last decade). - Calibration and parameters (values preserved exactly): - Capital stock via perpetual inventory starting from Tiffin (2006) estimate for 2000. - Depreciation assumed at 6½ percent per year for capital stock accounting (contextual note). - Capital share: ߙ = 0.5. - Discount rate: ߚ = 0.02. - Depreciation due to rust and dust: ߜ଴ = 0.02. - Depreciation coefficient for wear and tear: ߜଵ = 0.093. - Elasticity of the marginal rate of depreciation: ߠ = 1.5. - Persistence of labor supply shock: ߩ௡ = 0.999. - Persistence of technology shock: ߩ௚ = 0.999. - Intertemporal elasticity of substitution: ߟ = 1. - Coefficient ߜଵ chosen so total depreciation at actual utilization in 2000 equals about 5 percent (consistent with common growth-accounting assumptions). ### Empirical growth accounting (2001–11) and role of utilization - Aggregate growth outcomes (2001–11): - GDP grew by about 5 percent annually. - More precisely: GDP grew by 4.8 percent per year (2001–11). - Investment to GDP ratio remained around 20 percent. - Capital stock and labor grew by less than 1 percent per year. - Russia’s PPP GDP per capita rose from 29 percent of the OECD average in 2001 to 41 percent in 2010. - Efficiency and frontier: - Efficiency improved from 35 percent of the best-practice frontier in 2001 to 50 percent in 2011. - Conventional growth-accounting attribution: - About 86 percent of Russia’s growth in 2001–11 was attributed to TFP growth (conventional accounting). - Capacity utilization evidence: - Russian Economic Barometer: capacity utilization rose from 66½ percent in 2000 to 79½ percent in 2007, then fell to 76½ percent in 2008. - Measurement caveat: - If factor utilization trends upward during prolonged expansions, failing to reflect variable utilization will overstate TFP’s contribution. ### Quantitative revisions when allowing variable capital utilization - TFP contribution to GDP growth (2001–11): - Conventional accounting: 86 percent of GDP growth. - With variable utilization: about 68 percent of GDP growth (2001–11). - For 2001–08: TFP accounted for 70 percent when allowing variable utilization. - Capital contribution (2001–11): - Conventional approach: capital contributed 8½ percent of total GDP growth. - With variable utilization: capital contributed 26½ percent of total GDP growth. - Interpretation: upward revision reflects more intensive use of existing capital (capital service flows) rather than stock alone. - Model fit: - Model-implied optimal path of capital utilization closely matches observed utilization when calibrated to estimated exogenous TFP shocks. - Increasing utilization in the last decade interpreted as an optimal response to higher TFP growth raising marginal productivity of capital. ### Capital utilization, catch-up, and interpretation of past growth - Mechanism: - Sharp increase in TFP growth in the first half of the last decade expanded the production possibility frontier and raised marginal productivity of capital. - Increased demand for capital services met via higher utilization and/or faster capital accumulation. - When large idle capacity exists (from past overinvestment or negative TFP shocks), increased demand is more likely to be met by higher utilization for an extended period. - Explains why investment-to-GDP ratio remained relatively low despite rapid catch-up. ### Scenario-based projections for long-run growth (2012–20) - Four scenarios considered (staff baseline compared with TFP scenarios): - Scenario 1: TFP grows at an annual rate of 3 percent during 2012–20 (similar to average 2001–11). - Scenario 2: TFP grows at an annual rate of 1 percent. - Scenario 3: TFP grows at an annual rate of 2 percent. - Staff baseline: does not make an explicit TFP projection; implied TFP growth rates calculated using projected investment-to-GDP ratio and GDP growth rates. - Labor supply assumption: - Labor supply assumed constant over the period. - UN projections: population aged 15–64 declines from about 103 million in 2010 to 89 million in 2030, a decline of about 0.7 percent per year. - Growth outcomes: - Scenario 1 (TFP = 3 percent): economy expected to grow at 5 percent or more in the next 8 years, very close to 2001–11 average. - Scenario 2 (TFP = 1 percent): growth declines to around 2½ percent per year during 2013–20, converging to a long-run rate of 2 percent. - Scenario 3 (TFP = 2 percent): growth similar to staff baseline; TFP about ⅔ of last-decade estimate. - Efficiency catch-up (percent of frontier): - 2001–11: improvement from about 35 percent to 50½ percent. - Scenario 1: improvement to 69 percent by 2020. - Staff baseline and Scenario 3: catch-up to around 64 percent by 2020. - Scenario 2: increase to 58½ percent by 2020. - Composition of projected growth (2012–20): - TFP will account for around 65–69 percent of projected GDP growth (broadly in line with 68 percent in the last decade). - Input growth composition differs from 2001–11: past capital services growth driven mainly by higher utilization; in 2012–20 scope for further utilization increases is limited, implying capital accumulation must play a larger role. ### Investment needs, constraints, and policy implications - Investment needs: - With limited scope to raise capacity utilization, future growth requires faster accumulation of capital stock through higher investment. - Fixed capital investment is sensitive to the investment climate: strength of property rights and macroeconomic stability matter. - Policy recommendations to raise growth potential: - Improve the investment climate by: - addressing policy distortions and unstable macroeconomic environments that hamper investment; - strengthening property rights; - ensuring macroeconomic stability to encourage fixed capital formation. - Implement structural reforms steadfastly: - reduce state interference in the economy (including transparent and more decisive privatization of state-owned companies); - improve labor market flexibility; - ensure a stable fiscal regime for investment in new industries. - use Russia’s accession to the WTO as a catalyst for reforms to make the business environment more predictable and rule-based. - Rationale: large inefficiencies in state-owned enterprises and considerable state interference imply substantial scope for efficiency gains via resource reallocation. ### Appendix: model solution and computational notes - Optimal solution satisfies a system of 9 endogenous equations and variables, with 2 exogenous shocks (labor and technology growth) and 8 parameters. - Euler equations solved using stacked-time algorithm in TROLL. - Depreciation calibration: assume 2 percent per year independent of utilization (ߜ଴ = 0.02); wear-and-tear parameter set so total depreciation at actual 2000 utilization ≈ 5 percent. --- ### Central bank operational frameworks prior to the crisis — corridor vs floor systems (overview and implications) - Operational objective pre-2008: - Policy centered on targeted short-term interbank or wholesale money-market interest rates. - Some central banks used an announced OMO rate; expectation that market rates trade close to it. - Standing facilities (SF): - Credit SF: overnight, penal rate, “last resort”. - Deposit SF: not always offered; systems using both SFs called “corridor” systems; heavy reserve balances with little OMO draining imply “floor” systems. - Corridor systems: - Central bank sets upper/lower bounds by SFs; OMOs steer market rates toward middle of corridor. - Practical observation: with active OMOs and no floor rate, short-term market rate often around OMO rate or near zero (the floor), not the midpoint. - Floor systems: - Asymmetric corridor with little OMO at the middle; market rates close to deposit SF. - Causes include weak liquidity management, QE, or policy choice not to drain reserve surpluses. - Determinants of regime: - Structural surplus of reserve money not drained → effective floor system. - Ex ante reserve shortage → corridor system with active OMOs. - What matters is the marginal rate at which the market expects to transact substantially with the central bank. - Temporary shifts during crisis: - Some Advanced Economies temporarily moved from corridor to floor as reserve balances expanded due to QE or weak interbank markets. - Russia (2011): structural shift in market liquidity from April 2011; late September 2011 repo OMO lending regularly impacted MIACR; currency in circulation and net government balances drained about rubles 2.3 trillion liquidity in 2011, facilitating move to corridor with interbank rates closer to overnight repo OMO than to the floor. - India: shift from floor to corridor and operational changes summarized (Working Group, Monetary Policy Statement 2011–12). ### Corridor width: observed practices and consequences - International corridor practice examples (observed): - +/- 25bp: Australia, Canada, Chile, Israel, Malaysia. - +/- 50bp: Egypt, New Zealand, Singapore, South Africa, Sweden, Switzerland, Thailand. - +/- 100bp (pre-crisis): Czech Republic, ECB, Bank of England, US Federal Reserve, Hungary, India, Korea. - More than 100bp: Bolivia, Poland, Azerbaijan, Brazil. - Consequences of too-wide a corridor: - Increased likelihood of credit SF use; if SF penal, banks hoard liquidity; collateral demand rises; secondary market liquidity may be reduced; potential degradation of collateral quality. - Guidance on significance of spreads: - Corridor narrower than +/-25bp is empirically judged too narrow to motivate interbank transactions. - Corridor wider than +/-100bp: central bank should be clear that wider spread will incentivize interbank transactions rather than hoarding. - Example: CBR end-2011 operational rates: - Overnight (up to 7 day) repo OMO rate was 5¼ percent. - This was 125bp above the overnight deposit SF, but 275bp below the higher overnight credit rates, yielding a 400bp wide asymmetric corridor if taken as general indicator. ### Effects of corridor width on market intermediation and collateral - Too-narrow corridor: - Removes incentive for short-term market trades; central bank intermediation becomes default. - Central bank intermediation is collateral intensive → deadweight costs; potential reduction in secondary market liquidity; risk of central bank accepting lower-quality collateral. - Both extremes (too narrow or too wide) discourage interbank trading and dampen market and yield-curve development, weakening interest-rate transmission. ### Recommendations on corridor management - If markets expect regular use of SFs or market is segmented, corridor width matters more. - For Russia: - Uncertain ideal corridor width; country in “learning mode” with structural liquidity shortage and international uncertainty. - Recommended approach: reduce corridor width gradually and monitor market response with regular re-evaluation. - Suggested reduction: a corridor width of around 200bp would be appropriate for Russian markets at the current juncture, subject to cautious implementation and frequent reassessment. - Rationalize (reduce) the number of policy rates and maturities to simplify interpretation of market responses. ### Communication policy transition - Good communication shapes expectations about future policy, market conditions, interest and exchange rates, and inflation. - Central banks moving toward greater transparency; communication can anchor expectations (important for commodity exporters). - Communication items: policy objectives and strategy, rationale for policy decisions, views on current conditions and outlook, outlook for future policy. --- ### CBR communication, financial market developments, liquidity, and banking sector soundness (selected findings) - CBR communication progress: - Annual 3-year monetary policy guidelines provide an adequate sense of inflation objectives. - Monthly inflation reports analyze past and current conditions; post-policy statements explain policy decisions and reveal some outlook information. - Recent statements reference capacity utilization and output gap. - Areas for improvement: - Inflation reports largely backward looking; recommendation to add forward-looking section and inflation projections over a reasonable horizon. - Publish minutes of past policy meetings (initially with long lag, then shorter lags as appropriate). - Ensure mutual consistency across policy communications; coordinate communications with MoF and MoE. - Financial market and liquidity developments: - Asset prices deteriorated since end-2011 but remain well above 2008/09 trough when oil prices were about $40. - 2008/09 systemic liquidity squeeze: bank deposits declined by about 8½ percent; some banks saw 20 percent declines in household deposits in 1–2 months. - Official liquidity response in 2008/09: CBR provided liquidity equal to 10 percent of GDP via easing instruments and new instruments; emergency liquidity assistance now permanent feature of institutional framework. - Since end-2011: external shocks moderate; banks reduced external funding liquidity risks; banks are net foreign creditor; solid customer deposit growth; interbank liquidity broadly maintained. - Official liquidity support in late 2011 aimed to provide sufficient liquidity to corporate sector via banks. - Credit growth and funding (key statistics): - Nominal credit to non-financial private sector grew by 25 percent in 2011 (20 percent in real terms). - Credit-to-GDP ratio increased by 2 percentage points to 47 percent. - Total assets of banks grew by 23 percent in 2011. - Household credit growth: over nominal 40 percent (y/y) in early 2012; household credit = 11 percent of GDP; about 20 percent of household credit is mortgage. - Corporate loans grew nominal 24 percent in 2011. - Exposures to commercial real estate ~6 percent of total loans (some estimate 15–20 percent including on-lending). - Funding: household and corporate deposits >60 percent of banks’ balance sheets; customer loans = 56 percent of balance sheet. - Central bank funding rose to 3.1 percent of balance sheet in March 2012. - Interbank transactions = 10 percent of balance sheet; net borrowing from interbank = 1 percent of assets. - Financial soundness indicators and risks: - ROA recovered to over 2 percent in 2011. - NPL ratio declined from over 10 percent in 2009 to below 7 percent in 2011; caveat: decline driven by rapid credit growth rather than reduction in overdue amounts. - Reported total provisions exceed NPLs; NPL ratio net of provisions to capital ~10 percent (peer median). - Regulatory capital ratio declined to 14.7 percent from above 20 percent in 2009 peak. - With 2.4 percent ROA, Russian banks can increase total and core capital ratios by 2.7 percentage points every year assuming zero dividend payout. - Return on equity = 18 percent (median peer range 13–21 percent excluding Hungary). --- ### Capital adequacy, Basel reforms, financial-soundness statistics, and risks - Basel 2.5 and Basel III introduction starting in 2013: - Expected to reduce capital adequacy further as risk weights tighten and capital definition becomes stricter. - Minimum total capital ratio will continue to be set at 10 percent, so effective minimum capital requirements rise. - CBR requests banks report on local GAAP and IFRS, though regulatory ratios based on local GAAP. - System-level financial soundness indicators (values preserved exactly): - Capital to risk-weighted assets: 15.5 (2007), 16.8 (2008), 20.9 (2009), 18.1 (2010), 14.7 (2011), 14.7 (2012--Mar). - Core capital to risk-weighted assets: 11.6 (2007), 10.6 (2008), 13.2 (2009), 11.1 (2010), 9.3 (2011), 9.2 (2012--Mar). - Capital to total assets: 13.3 (2007), 13.6 (2008), 15.7 (2009), 14.0 (2010), 12.6 (2011), 12.9 (2012--Mar). - Risk-weighted assets to total assets: 85.6 (2007), 81.0 (2008), 75.2 (2009), 77.4 (2010), 85.9 (2011), 87.7 (2012--Mar). - NPLs to total loans: 2.5 (2007), 3.8 (2008), 9.6 (2009), 8.2 (2010), 6.6 (2011), 6.8 (2012--Mar). - Loan loss provisions to total loans: 3.6 (2007), 4.5 (2008), 9.1 (2009), 8.5 (2010), 6.9 (2011), 7.0 (2012--Mar). - Return on assets: 3.0 (2007), 1.8 (2008), 0.7 (2009), 1.9 (2010), 2.4 (2011), 2.4 (2012--Mar). - Return on equity: 22.7 (2007), 13.3 (2008), 4.9 (2009), 12.5 (2010), 17.6 (2011), 18.2 (2012--Mar). - Liquid assets to short-term liabilities: 72.9 (2007), 92.1 (2008), 102.4 (2009), 94.3 (2010), 60.1 (2011), 58.7 (2012--Mar). - Ratio of client's funds to total loans: 94.8 (2007), 84.6 (2008), 99.9 (2009), 109.5 (2010), 105.3 (2011), 102.2 (2012--Mar). - Major risks and resilience: - Oil price shocks are major risk; stress-test showed system-wide capital ratio falling from 18.1 percent to 14.1 percent under oil-price decline scenario. - Direct FX exposures small: net open FX position to capital = 0.6 percent. - Overseas and nonresident investments = 14 percent of total assets (approximate composition: 40 percent interbank exposures, 30 percent loans to nonresident corporations, 14 percent cash, 13 percent securities). - Stress test for top 17 banks (65 percent of system assets) in April 2012: potential losses from higher interest rates very small relative to capital. ### Exchange rate volatility empirical findings (selected) - RUB/USD and RUB/EUR volatility patterns: - RUB/EUR volatility: fairly high early 2000, declined mid-2000s, lower from 2004 until crisis. - RUB/USD volatility: very low in early 2000 under exchange rate targeting, rose mid-2000s, jumped during 2008–09 crisis. - During 2008–09 crisis volatility jumped to 3–5 times pre-crisis averages; post-crisis vs pre-crisis difference significant mainly for RUB/USD. - Oil price volatility explanatory role: - Oil price volatility dominates other global-risk proxies for RUB/USD volatility; simple empirical model explains over 80 percent of RUB/USD volatility movement. - Oil price volatility plays small role for RUB/EUR; EUR/USD volatility explains 30 percent of RUB/EUR movement. - Volatility estimates (period averages, standard deviation in percent — as reported): - USDEUR: 00-04 = 10 33 ; 05-June 08 = 15 15 ; Crisis 2/ = 8 16 1 ; May 09-now = 37 29. - Standard deviation of residuals (Ruble-EUR volatility): 00-04 = 21 ; 05-June 08 = 5 ; May -now = 17. - Standard deviation of residuals (Ruble-USD volatility): 00-04 = 1.6 ; 05-June 08 = 6.4 ; May 09 -now = 9.2. - Interpretation: - Unexplained residual volatility has become more volatile since the global financial crisis, implying increased influence of factors beyond fundamentals and global currency market trends. --- ### Fiscal framework, oil funds, and policy recommendations (selected) - Existing framework and issues: - Two oil funds: Reserve Fund (smoothing large oil-price swings) and National Wealth Fund (save for future generations). - Long-term nonoil deficit target of 4.7 percent of GDP specified in budget code and endorsed by staff as appropriate anchor. - Framework implementation has not been steadfast; Reserve Fund drawn down in 2009–10 leaving smaller buffer. - Options for fiscal anchors: - Nonoil deficit target — Pros: focuses on nonoil balance, delinks economy from oil volatility, ensures intergenerational equity; Cons: harder to communicate and needs periodic reassessment. - Oil-price rule — Pros: easy to communicate; Cons: needs supplementary constraints to ensure sustainability and may lag changes in oil volumes. - Staff assessment and model-based simulations: - Staff view: suspended nonoil deficit target of 4.7 percent remains appropriate anchor. - POIM-real simulation (using April 2012 WEO assumptions): consistent with nonoil deficit ≈ 6 percent of GDP by 2015 under a real-criterion rule. - Stress-testing suggests appropriate nonoil deficit range by 2015 between 4 and 8 percent of GDP; 4.7 percent is conservatively appropriate to rebuild Reserve Fund. - Ministry of Finance rule under consideration may lead to higher nonoil deficit through 2020 and not rebuild Reserve Fund meaningfully. - Sensitivity (POIM-real) — nonoil primary deficit by 2015 (percent of GDP) under parameter variations (values preserved exactly): - Baseline parameters: 6.2. - Long-run Urals oil price (baseline = US$95/barrel): - US$120/barrel: 7.3. - US$70/barrel: 5.2. - 10-year average price (2011-2002, US$55.70/barrel): 4.7. - Long-run gas price (baseline = US$330/tcm): - US$400/tcm: 6.8. - US$260/tcm: 5.7. - 10-year average (US$203.40/tcm): 5.3. - Combined oil/gas shocks: - US$120 and US$400: 7.8. - US$70 and US$260: 4.7. - 10-year averages: 3.7. - Oil reserves (baseline = 100, oil runs out in 2049): - 130 (runs out in 2061): 6.8. - 70 (runs out in 2038): 5.4. - Gas reserves (baseline = 100, runs out in 2091): - 130 (runs out in 2116): 6.3. - 70 (runs out in 2067): 6.0. - Effective oil and gas tax take (baseline = 35%): - +5 ppt: 7.3. - -5 ppt: 5.2. - Long-run real interest rate (baseline r = 4.0): - r = 4.5: 6.5. - r = 3.5: 5.9. - Long-run real growth rate (baseline y = 3.0): - y = 3.5: 6.2. - y = 2.5: 6.3. - Recommended design and governance: - Credibility requires balancing flexibility and commitment; consider procedural rules and explicit revision clauses. - Consistent implementation is more important than specific rule form. - Path to reach 4.7 percent nonoil deficit by 2015 using GIMF simulations: - Alternative: reduce nonoil deficit gradually to 4.7 percent by 2015 (adjustment ≈ 1.5 percent per year starting in 2012) using growth-friendly instruments (reductions in government consumption and transfers). - Table IV.3 — consolidation measures by instrument (percent of GDP) and 4-year totals: - Government consumption: 2012 = 0.229; 2013 = 0.385; 2014 = 0.367; 2015 = 0.319; 4-year total = 1.324; Share of total = 24.4. - General transfers: 2012 = 0.711; 2013 = 1.197; 2014 = 1.139; 2015 = 0.990; 4-year total = 4.075; Share of total = 75.6. - Total: 2012 = 0.940; 2013 = 1.582; 2014 = 1.505; 2015 = 1.309; 4-year total = 5.3; Share of total = 100.0. - Potential measures to achieve 5.3 percent of GDP savings: - Government consumption: reduce civil service wages (2011–13 MTEF envisaged 0.9 percent of GDP), reduce subsidies (1.3 percent of GDP originally in 2010 stimulus, only 0.4 percent included in 2011-13 MTEF), improve regional expenditure efficiency (1.1 percent of GDP per World Bank). - General transfers: phase out poorly-targeted social assistance (1 percent of GDP per World Bank), increase pension age to 65 by 2050 and reduce early pensions (potential savings by 2020 ≈ 2.7–3.7 percent of GDP per simulations), reduce/eliminate tax expenditures (MinFin estimate = 1.5 percent of GDP in 2010). - Credibility scenarios and growth effects (GIMF): - Immediately credible package: agents foresee lower interest rates → immediate boost to consumption and investment. - “Earned credibility”: agents believe consolidation observed each period is permanent; initial contraction muted, medium-term benefits. - Gradual credibility by doing: credibility builds from 2014; larger short-term contraction but positive effects by 2013. - Credibility only after full implementation (in 2016): largest short-term contraction; growth becomes positive starting in 2015 before full credibility achieved. *Italic: IMF staff estimates and analysis as presented in the source document.* ### Appendix I.1. Growth Model with Variable Capital Utilization .................................12 ### Appendix I.1. Growth Model with Variable Capital Utilization ### Introduction - Russia experienced a sharp contraction in 2009 with GDP falling by 8 percent. - Key questions addressed: - What were the main forces that drove Russia’s growth in the last decade? - How did Russia’s efficiency level evolve and what scope for catch-up remains? - What will be the main source of Russia’s growth in the next decade? - What should be done to raise Russia’s growth potential? - The paper is organized to (i) outline conceptual issues and framework, (ii) present growth accounting results for the past decade, (iii) describe an exogenous growth model with endogenous capital utilization, and (iv) evaluate potential growth and policy implications. ### Potential Growth and Productivity (Framework) - Definition used: potential growth = “steady-state” growth and the optimal transition path toward the steady state. - Methodology: growth-accounting framework linking GDP growth to changes in capital, labor, and total factor productivity (TFP). - Modeling approach: Solow-type approach where efficiency/technological progress (TFP) and labor supply are treated as exogenous; TFP is viewed as closely related to structural reforms. - Caveat: growth accounting decomposes sources of growth but does not by itself establish causality between factors (exogenous vs endogenous growth mechanisms). ### Source of Growth in Russia: 2001–11 (Empirical findings) - Aggregate outcomes: - Russia’s GDP grew by about 5 percent annually during 2001–11. - More precisely, GDP grew by 4.8 percent per year (2001–11). - Investment to GDP ratio remained around 20 percent during this period. - Capital stock and labor grew by less than 1 percent per year. - Russia’s PPP GDP per capita rose from 29 percent of the OECD average in 2001 to 41 percent in 2010. - Efficiency and frontier: - The efficiency of the Russian economy improved from 35 percent of its “best-practice” frontier in 2001 to 50 percent in 2011. - Conventional growth-accounting result: - About 86 percent of Russia’s growth in 2001–11 was attributed to TFP growth (conventional accounting). - Capacity utilization dynamics: - Russian Economic Barometer survey: capacity utilization increased from 66½ percent in 2000 to 79½ percent in 2007, then fell to 76½ percent in 2008. - Measurement concern: - If factor utilization trends upward during prolonged expansions, failing to reflect variable utilization will overstate TFP’s contribution. ### Growth Model with Variable Capital Utilization (Model structure and calibration) - Main feature: capital utilization (u) is endogenous and increased utilization raises depreciation (accelerated depreciation / “wear and tear”). - Representative production and depreciation specification (symbolic presentation preserved from source): - Q_t = (u_t K_t)^{α} · (A_t N_t)^{1−α} - δ_t = δ_0 + δ_1 u_t^{δ_2} (model describes decomposition into “rust and dust” and utilization-dependent wear-and-tear) - The model is a Ramsey-type growth model with endogenous u and depreciation. - Conceptual notes: - δ_0 represents depreciation independent of utilization (“rust and dust”). - The utilization-dependent term captures depreciation that increases with u (“wear and tear”). - Labor cost of higher utilization at the extensive margin is not modeled, given limited labor cost pressures in the last decade. - Calibration and data: - Capital stock constructed via perpetual inventory method starting from Tiffin (2006) estimate for 2000. - Depreciation assumed at 6½ percent per year for capital stock accounting. - Capital share assumed at 0.5 (following Oomes and Dynnikova (2006)). - Technical Appendix contains full model details, optimality conditions, and calibration. ### Key quantitative revisions from allowing variable utilization - Growth-accounting with variable capital utilization yields materially different attributions: - TFP growth contribution: - Conventional accounting: 86 percent of GDP growth (2001–11). - With variable utilization: about 68 percent of GDP growth (2001–11). - For 2001–08: TFP accounted for 70 percent when allowing variable utilization (lower than conventional estimate). - Capital contribution: - With variable utilization: capital contributed 26½ percent of total GDP growth (2001–11). - Conventional approach estimated capital contribution at 8½ percent (2001–11). - The upward revision in capital’s contribution reflects the more intensive use of the existing capital stock (capital service flows rather than stock alone). - Model simulation results: - The model-implied optimal path of capital utilization closely matches the actual observed utilization path when the economy faces the estimated exogenous TFP shocks. - The increasing trend of capital utilization in the last decade is consistent with TFP growth and can be interpreted as an optimal response rather than an anomaly. ### Implications for potential growth and policy (from model and simulations) - Main implications: - A substantial fraction of past growth reflected more intensive use of existing capital rather than only accumulation of new capital or purely technological improvements. - Given limited scope for much higher capital utilization going forward, investment (capital accumulation) and structural improvements that raise TFP will need to play a larger role in future growth. - Russia faces unfavorable demographic trends, increasing the urgency for structural reforms to improve the investment climate and labor participation to sustain growth. - Modeling perspective: - Projections of long-run GDP growth and transition paths depend critically on assumptions about future TFP trends and the evolution of capacity utilization; the model provides a framework to trace endogenous responses (consumption, investment, utilization) to exogenous TFP developments. *Source: Appendix I.1. Growth Model with Variable Capital Utilization (excerpt).* ### 17. The simulation results suggest that the increasing trend of capital utilization in ### 17. The simulation results suggest that the increasing trend of capital utilization in ### Capital utilization and past TFP catch-up - The increasing trend of capital utilization in the last decade was an optimal response to changes in external conditions, given a sharp increase in the TFP growth rate during the first half of the last decade that expanded the production possibility frontier and raised the marginal productivity of capital. - Increased demand for capital could be met through: - more intense use of existing capacity (higher utilization), and/or - faster accumulation of capital stock. - When large idle capacity exists (due to overinvestment in the past or a large negative TFP shock at end-1990s in Russia), increased demand for capital service flow is more likely to be met with higher utilization of existing capacity for an extended period. - This dynamic helps explain why the investment to GDP ratio in Russia remained relatively low in the last decade despite rapid economic catch-up. ### Scenario-based projections for Russia’s long-run growth (2012–20) - Four scenarios considered, including staff’s current baseline projections: - Scenario 1: TFP grows at an annual rate of 3 percent during 2012–20 (similar to average 2001–11). - Scenario 2: TFP grows at an annual rate of 1 percent. - Scenario 3: TFP grows at an annual rate of 2 percent. - Staff baseline does not make an explicit projection on TFP growth rates; for comparison, TFP growth rates are calculated using projected investment-to-GDP ratio and GDP growth rates. - Labor supply assumption: - Labor supply is assumed constant throughout the period under consideration. - UN projections suggest 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. - Growth outcomes: - If TFP grows at 3 percent (Scenario 1), the Russian economy is expected to grow at 5 percent or more in the next 8 years, very close to the average growth rate during 2001–11. - If TFP growth slows to 1 percent (Scenario 2), the growth rate will decline to around 2½ percent per year 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 (Scenario 3), about ⅔ of the TFP growth rate estimated for the last decade. - Efficiency catch-up projections (efficiency measured as percent of the frontier): - 2001–11: improvement from about 35 percent to 50½ percent of the frontier. - Scenario 1: improvement to 69 percent by 2020. - Staff baseline and Scenario 3: catch-up to around 64 percent of the frontier by 2020. - Scenario 2 (least optimistic): increase to 58½ percent of the frontier by 2020. - Composition of GDP growth (2012–20 versus 2001–11): - TFP growth will account for around 65–69 percent of projected GDP growth during 2012–20 (broadly in line with 68 percent in the last decade). - Input growth composition (capital and labor services) is projected to be substantially different from the last decade. - In the last decade, increased capital services were driven mainly by higher utilization; in 2012–20, scope for further increase in capacity utilization is limited. ### Investment needs and constraints - With limited scope to raise capacity utilization further, future growth will require faster accumulation of capital stock through higher investment. - Unlike reversable capital utilization, fixed capital investment (the main contributor in the next decade) is sensitive to the investment climate, including: - strength of property rights, - macroeconomic stability. - Capital utilization was the main source of capital input growth in the last decade and is generally less sensitive to the investment climate because it can be easily reversed; fixed capital investment is more costly to reverse. ### Policy implications and recommendations - Improving the investment climate is essential to realize growth potential: - Address policy distortions and unstable macroeconomic environments that hamper investment. - Strengthen property rights and ensure macroeconomic stability to encourage fixed capital formation. - Steadfast implementation of structural reforms is required: - Effective implementation has been insufficient to change investor perception despite numerous reform plans. - Reforms can improve TFP directly and remove distortions affecting investment decisions. - Large inefficiencies in state-owned enterprises and considerable state interference imply substantial scope for efficiency gains through resource reallocation. - Recommended reforms include: - reduce state interference in the economy (including transparent and more decisive privatization of state-owned companies), - improve labor market flexibility, - ensure a stable fiscal regime for investment in new industries. - Russia’s accession to the WTO should act as a catalyst for reforms by making the business environment more predictable and rule-based. ### Appendix I.1 — Growth model with variable capital utilization (model structure and calibration) - Economy maximizes welfare (function of per capita consumption) over an infinite horizon; labor supply (population) and technology growth are exogenous. TFP growth in the simulation is assumed to follow a random walk. - Key elements and definitions: - CN: aggregate consumption. - N: population (identical to labor supply). - K: capital stock. - ߜ: depreciation rate of capital stock, function of capital utilization, u. - n: population growth rate. - A: labor-augmenting technology level. - g: technology growth rate. - En and Eg: random shocks to population and technological growth rates. - The optimal solution satisfies a system of 9 endogenous equations and variables, with 2 exogenous variables (shocks to growth rate of labor and technology, ݊ܧ௧ and ݃ܧ௧) and 8 parameters. The (forward-looking) Euler equations are solved using the stacked-time algorithm in TROLL. - Parameter values: - ߙ = 0.5 — Capital share in the production function - ߚ = 0.02 — Discount rate - ߜ଴ = 0.02 — Depreciation due to rust and dust - ߜଵ = 0.093 — Depreciation coefficient for wear and tear - ߠ = 1.5 — Elasticity of the marginal rate of depreciation - ߩ௡ = 0.999 — Persistence of labor supply shock (near random walk) - ߩ௚ = 0.999 — Persistence of labor-augmenting technology shock (near random walk) - ߟ = 1 — Intertemporal elasticity of substitution - Depreciation calibration note: - Assume capital stock depreciates by 2 percent per year independent of utilization (ߜ଴ = 0.02). - Coefficient for wear-and-tear depreciation (ߜଵ) is set so that total depreciation at actual utilization in 2000 equals about 5 percent (i.e., annual depreciation of 5 percent is commonly assumed in growth accounting studies and consistent with depreciation implied by Russia’s capital stock and real investment during 1995–97). *Italic: IMF staff estimates and analysis as presented in the source document.* ### 4. Central bank monetary policy setting prior to the outbreak of the financial crisis ### _cr12218 - 4. Central bank monetary policy setting prior to the outbreak of the financial crisis ### Operational objective and common practices pre-2008 - Policy was normally centered on the targeted level for short-term interbank or wholesale money-market interest rates. - Some central banks expressed policy as a short-term interbank target (examples given: U.S. Federal Reserve Bank, Bank of Canada, Reserve Bank of Australia). - Others announced policy in terms of an open market operation (OMO) rate at which the central bank would transact, expecting short-term market rates to trade close to this level—perhaps within 5–10 basis points (examples given: ECB, Bank of England, Reserve Bank of New Zealand, and a number of Emerging Market central banks). ### Role and design of standing facilities (SF) - Nearly all central banks make available a standing credit facility (credit SF) for payment-system safety; it is nearly always for an overnight maturity and carries a penalty rate to motivate effective liquidity management. - In some systems a deposit SF is not offered because it is unnecessary from a payment-systems perspective; liquidity can be guided by OMO and reserve requirement averaging (example: the USA prior to October 2008). - Systems using standing credit and deposit facilities to inject and withdraw reserve money are typically called either “corridor” systems or “floor” systems. ### Corridor systems - Definition: central bank sets upper and lower bounds for most overnight wholesale money market transactions by making available standing credit and standing deposit facilities, usually with overnight maturities. - Typical practice: SFs are set at symmetric margins around the announced policy rate; OMO are used to steer actual short-term market rates to the middle of the corridor. - Practical observations: - Pre-crisis expectation: market rates steered within a much narrower band in line with the policy target. - If there is active use of OMO and no floor rate, the short-term market rate is typically around the OMO rate or close to zero (the floor), not the average of SF rates. - U.K. example: - 2004 decision to restructure operational framework to deliver a relatively stable overnight interbank rate in line with the policy target. - Interim narrow corridor introduced; later, with enhanced liquidity management (introduced May 2006), corridor widened from +/-25bp to +/-100bp while maintaining stability. - Enhanced liquidity management included averaging of voluntary contractual reserves over a 4–5 week period, weekly short-term liquidity OMO, and provisions to minimize liquidity risk on the final day of the reserve maintenance period. ### Floor systems - Definition: an asymmetric corridor where upper and lower bounds are set by SFs but there is no OMO (or not enough) at the middle of the corridor; expectation is that market rates will be close to, but somewhat above, the deposit SF. - Causes: - Result of weak liquidity management. - Policy decision not to drain reserve balances surplus to demand. - Policy of Quantitative Easing (QE) or unsterilized exchange rate intervention. - Pre-crisis prevalence: more common in Emerging Market countries, though used in a few Advanced Economies (Norway noted). - India example phases (as observed in the source): - Floor system in 2009 and early 2010, with rates close to or below the floor. - Floor system reacting to periodic shortages from mid-2010 until mid-2011. - Introduction of a corridor system from mid-2011. - Note: overnight market rate can be below the floor if deposit facility is not available until payment system closes. ### Determinants of system type and market behavior - Structural surplus of reserve money not fully drained by OMO → effectively a floor system because banks expect to leave significant reserves in deposit facility. - Ex ante reserve money shortage → tends to be a corridor system with active OMO to keep short-term market rates aligned to policy rate. - Central banks typically view the standing credit facility as “last resort” borrowing and set a penal rate; if markets regularly trade at that level, it would not be penal. - What matters most: the marginal rate at which the market expects to transact in substantial volume with the central bank. - If no OMO, market rates tend to trade around the floor or, in stress, around the ceiling, not around the average of the two. - Regular and substantial use of one SF tends to push the market rate to that boundary (typically the floor). - If use of SFs is expected to be trivial, SF rates are unlikely to impact market rates directly; the OMO rate should guide the market. - Perfect liquidity management would render corridor width irrelevant; in practice, corridor width matters when liquidity cannot be managed perfectly or when a floor system is used. ### Temporary shifts and examples during/after the financial crisis - Some Advanced Economy central banks temporarily moved from corridor to floor systems as reserve money balances expanded substantially due to QE purchases or central bank intermediation when interbank markets were weak (examples: U.S., Euro area, U.K.). - Rationale: financial sector stability demands outweighed benefits for monetary policy transmission and market development of a corridor system; weakened transmission from short-term policy rates to wider economy was acceptable amid weak inflationary pressures and low economic growth. - Russia (2011): - Structural shift in market liquidity began in April 2011 and became clear from late September 2011 when repo OMO lending came regularly and substantially into play, impacting the overnight market rate (MIACR). - Slowdown in official foreign exchange purchases and occasional net sales, plus reduction in net credit to government, drained surplus reserve money balances. - An increase in net government balances with the CBR and an increase in currency in circulation drained some rubles 2.3 trillion liquidity from the market in 2011, facilitating a move to a corridor system with interbank rates trading closer to overnight repo OMO than to the floor. - India: - Two important factors brought the overnight interbank rate into the middle of the corridor: - RBI decision to pull back from exchange rate intervention and sell foreign exchange when dollar funding pressures were high in 2008–09, reducing domestic currency liquidity creation from official FX purchases and moving the market to a structural shortage. - RBI adjusted its operational structure, using OMO to guide market rates to the middle of the corridor and reduce volatility. - RBI institutional changes were formalized by a Working Group on Operating Procedure of Monetary Policy (constituted July 2010, report published March 2011) and the May 3, 2011 Monetary Policy Statement 2011–12 detailing changes. ### Determining corridor width: observed practice and consequences - Global practice varies substantially. Table of Policy Rate Corridors (as observed in the source): - +/- 25bp: Australia, Canada, Chile, Israel, Malaysia - +/- 50bp: Egypt, New Zealand, Singapore, South Africa, Sweden, Switzerland, Thailand - +/- 100bp (pre-crisis): Czech Republic, ECB, Bank of England, US Federal Reserve, Hungary, India, Korea - More than 100bp: Bolivia, Poland, Azerbaijan, Brazil - Consequences of too-wide a corridor: - If liquidity management is difficult and banks face uncertainty, probability of needing credit SF increases. - If the marginal cost of accessing the credit SF is too penal, banks have an incentive to increase liquidity buffers to avoid the cost, reducing market trades (liquidity hoarding). - Example logic: a gain of 50bp in interbank overnight lending every day of the week could be more than offset if the lending bank must access a credit SF at 300bp over the effective policy rate once a week, even ignoring the cost of holding eligible collateral. ### Key findings and implications - The effective operating regime (corridor vs floor) depends on structural liquidity conditions and central bank operational choices. - Regular substantial OMO usage that targets the middle of the corridor supports a corridor system; persistent reserve surpluses with little draining by OMO supports a floor system. - Changes in external flows (e.g., FX intervention, capital outflows) and fiscal movements (e.g., net government balances) can materially shift structural liquidity and thus the feasible operational framework. - Temporary shifts to a floor system can be appropriate during major financial shocks to prioritize stability, but they complicate policy implementation if inflationary pressures later rise before surplus reserves are absorbed. * _cr12218 - 4. Central bank monetary policy setting prior to the outbreak of the financial crisis_ ### 23. Does it matter if the corridor is too narrow, such that the market has no incentive for ### _cr12218 - 23. Does it matter if the corridor is too narrow, such that the market has no incentive for ### Effects of corridor width on market intermediation and collateral - A corridor that is too narrow can remove incentives for short-term market trades, making central bank intermediation the default. - Central bank intermediation is collateral intensive; the central bank will demand collateral from borrowing banks, creating: - a deadweight cost on financial intermediation; - potential reduction in secondary market liquidity of securities accepted as collateral; - a risk that the central bank may accept lower-quality (“second-rate”) collateral, degrading collateral quality across the banking system. - Both corridors that are too narrow and those that are too wide will discourage interbank trading and tend to dampen market and yield-curve development, weakening interest-rate transmission. ### What size of interest rate spread is significant - Standing Facility (SF) rates are often argued to be “penal” to discourage market intermediation via the central bank; the central bank must judge what “penal” implies for its market. - Important normal-market factors to consider: the size of trades, the cost of trading, and the cost of alternatives. - Back-office settlement costs can exceed the return on short-term trades even if credit and liquidity risk are zero; repo settlement costs (including securities depository fees) are greater than for unsecured interbank transactions. - If there is perceived liquidity risk, required returns must be correspondingly higher. - Transacting with the central bank may be cheaper if opportunity cost is low (avoidance of dealing room and middle office costs). - Numerical example from the source: an overnight trade yielding a gain of 25bp on US$1 million equates to a gain of US$6.85. ### Central Bank of Russia (CBR) rate structure and market segmentation - Interbank market segmentation: a small number of large banks deal in large volumes (perhaps several billion rubles) while many small banks transact for a hundred million rubles or less. - A spread penal for small banks may be excessively penal for large banks; central bank design should account for large trades because they have a greater impact on the overall economy. - CBR policy rate structure at end 2011 used several different interest rates for Standing Facility lending, Standing Facility deposit, and Open Market Operations, with a range of maturities and collateralization models. - The multiplicity of official rates complicates assessment of whether corridors are too wide or too narrow and complicates transmission from overnight rates to longer-term market rates. - Overnight (up to 7 day) repo OMO rate was 5¼ percent: - this was 125bp above the overnight deposit SF, - but 275bp below the higher of the overnight credit rates, - yielding a 400bp wide, asymmetric corridor for overnight operations (if taken as the general operational indicator), which is a wide spread by comparison. ### Historical experiences of narrowing corridors (examples) - Since 2007 several central banks temporarily reduced corridor widths to reduce short-term rate volatility when interbank markets weakened; SF rates became more important when market intermediation could not be relied upon. - U.S. Federal Reserve: - cut the spread between its target rate (the Fed Funds Rate) and the credit SF (Primary Credit Facility) from 100bp to 50bp in August 2007, - further reduced it to 25bp in March 2008, - increased back to 50bp in early 2010 as interbank pressures eased. - Note: in the USA at present, 50bp represents the full width of the corridor between the rate paid on excess reserves (25bp) and the rate charged for SF credit (75bp). - ECB: - operated a corridor of +/-100bp from 1999 to 2008, - narrowed to +/-50bp in October 2008, - restored to +/-100bp in January 2009, - narrowed to +/-75bp subsequently as markets failed to sustain recovery. - With fixed-rate, full-allotment OMO tenders introduced in October 2008, the OMO lending rate has in large measure functioned as an SF rate so the effective corridor width is 75bp. - Bank of England: - introduced a narrow corridor of +/-25bp in 2004 prior to reserves averaging in May 2006, - widened to +/-100bp once reserves averaging was introduced, - narrowed to +/-25bp in 2008 in face of strong market volatility, - when policy rate was cut to 50bp in March 2009, the corridor effectively became 25bp wide as all reserves were remunerated at the policy rate (operating as a deposit SF). ### Considerations for floor versus corridor systems - In a floor system the effective gap between the market rate and the credit SF is (almost) the whole width of the corridor rather than half; corridor width should be re-evaluated accordingly. - Since 2007, narrowing the corridor temporarily has been used to reduce short-term rate volatility during market stress, recognizing that wider corridors do not address core causes of interbank dysfunction (credit/liquidity risk perceptions). ### Conclusions and policy recommendations - The importance of corridor width increases if: - (i) market participants expect to use standing facilities more because OMOs or other liquidity tools cannot keep reserve balances within a narrow band, and - (ii) the market is segmented so liquidity-rich banks may not lend to liquidity-short banks. - Interbank transactions are discouraged when the corridor is: - (i) too narrow — benefits for liquidity-rich banks from market dealing do not outweigh benefits of using the central bank as intermediary; - (ii) too wide — opportunity cost of being short reserves motivates hoarding of liquidity. - Empirical guidance from the source: - a corridor narrower than +/-25bp is too narrow to motivate interbank transactions; - if the corridor is to be wider than+/-100bp, the central bank should be reasonably clear that a wider spread will incentivize interbank transactions (or reduce exchange rate pressures), rather than motivating hoarding of liquidity. - For Russia specifically: - it is not possible to be certain ex ante what the ideal corridor width is; Russia is in a “learning mode” with structural liquidity shortage and international uncertainty. - recommended approach: reduce corridor width gradually and monitor market response with regular re-evaluation. - suggested reduction: a corridor width of around 200bp would be appropriate for the Russian markets at the current juncture, subject to cautious implementation and frequent reassessment. - Final recommendation: rationalize (reduce) the number of policy rates and maturities to simplify interpretation of market responses to adjustments. ### Transition to communication policy - Good communication enhances monetary policy effectiveness by shaping expectations about future policy, market conditions, interest and exchange rates, and inflation. - Central banks have moved toward greater transparency over the past twenty years; communication can help anchor expectations, which is especially important for commodity exporters. - Central banks can communicate on: - policy objectives and strategy (e.g., inflation targets like “below, but close to, 2 percent”); - rationale for current and past policy decisions and decision processes (e.g., post-policy statements, press conferences, publication of meeting minutes); - views on current economic conditions and outlook (publication of inflation forecasts, “fan charts”, measures of inflation expectations); - outlook for future monetary policy (easing/tightening biases, projected paths for future interest rates). - Consistent communication allows the public to learn the central bank’s reaction function, increasing predictability and credibility and anchoring inflation expectations. *Source: IMF staff analysis as presented in the supplied content unit.* ### 44. In recent years, the CBR has made important progress in its communication. ### _cr12218 - 44. In recent years, the CBR has made important progress in its communication. ### CBR communication: recent progress - The annually adopted and published monetary policy guidelines have a 3-year horizon and "give an adequate sense of the CBR’s inflation objectives." - Monthly inflation reports "analyze elaborately past and current economic conditions." - Monthly post policy meeting statements "provide an explanation of policy decisions and reveal, to some extent, information about the outlook for future policy." - Recent post policy meeting statements include references to the cyclical position of the economy such as capacity utilization and the output gap. ### CBR communication: areas for improvement and policy recommendations - Inflation projections - Current status: "Thus far the CBR’s inflation reports have been largely backward looking." - Recommendation: "CBR follows through with its plans to add a forward-looking section to the inflation reports." - Further recommendation: "Eventually, this forward looking section should also include inflation projections over a reasonable horizon." - Expected benefits: "Such projections would provide important information to the public...make monetary policy more predictable" and "might help further insulate monetary policy from political influences, thereby strengthening the CBR’s de facto independence." - Minutes - Recommendation: "CBR could also usefully start publishing minutes of past policy meetings of its Board." - Implementation note: "At the start, minutes could be published with a relatively long lag...Going forward the CBR could experiment with shorter lags, depending on experience and usefulness (the Fed, for example, gradually stepped up the speed of the release of its FOMC meeting minutes...)." - Goal: "reinforce and support the policy explanations...and...enhance the CBR’s accountability to the general public." - "Noise reduction" - Recommendation: Ensure mutual consistency across monetary policy communications so they "help guide, and not confuse, the public." - Institutional recommendation: Other government agencies such as the ministry of finance and the ministry of economy should "respect the CBR’s mandate in the area of monetary policy." - Coordination rule: "Any communications by the MoF or MoE on the monetary policy stance or liquidity situation in the banking system will need to be closely coordinated with the CBR." ### Financial market developments and liquidity conditions - Russian financial markets "have been volatile in line with global financial and commodity markets" and "largely follow oil prices." - Asset prices deteriorated since end 2011 but remain "well above the trough recorded in 2008/09 when oil prices declined to $40 levels." - Global market turbulence in 2008/09 triggered a systemic liquidity squeeze among Russian banks and corporate: - Bank deposits declined by about 8½ percent, leading to a decrease in the deposit-to-GDP ratio in 2008. - Some banks experienced about 20 percent declines in household deposits in a matter of 1–2 months. - Interbank market exhibited sharp increases in rates, bid-ask spreads, and interest rate volatility. - Official liquidity response in 2008/09: - The CBR provided liquidity amounting to 10 percent of GDP by easing instruments, introducing new instruments, and reducing counterparty risk. - The CBR initially intervened to maintain Ruble value, easing FX liquidity needs. - The government supported liquidity by placing its deposit in commercial banks. - "Going forward, the CBR has made the emergency liquidity assistance a permanent feature of its institutional framework." - Conditions since end-2011: - External shocks were "moderate so far" with smaller oil price declines and concentrated funding distress in euro area. - Banks reduced external funding liquidity risks; "the stock of foreign borrowing has remained subdued since the last crisis time and banks are now a net foreign creditor." - Banks maintain net FX asset position; their FX assets are mostly liquid with less than 1 year maturity and held vis-à-vis counterparties in major financial centers. - Solid customer deposit growth continued, raising deposit-to-GDP ratio; interbank market liquidity was broadly maintained with low bid-ask spreads and low interest rate volatility. - Official liquidity support in late 2011 aimed at providing sufficient liquidity to the corporate sector through the banking sector. ### Credit growth and funding (key statistics and findings) - Nominal credit to the non-financial private sector grew by 25 percent in 2011 (20 percent in real terms). - Increase in the credit-to-GDP ratio: "2 percentage points to 47 percent." - Total assets of banks grew by 23 percent in 2011. - Household segment: - Household credit growth accelerated to "over nominal 40 percent (year-on-year) in the first months of 2012." - Household credit amounts to 11 percent of GDP. - Within household credit, "about 20 percent is mortgage" and growth has been "equally strong in both mortgages and other types of consumer loans." - Corporate loans: "grew at more modest rate of nominal 24 percent in 2011," with part reflecting substitution away from foreign funding. - Exposures to commercial real estate (construction): "small at about 6 percent of total loans," though some market participants estimate "15–20 percent" once on-lending is considered. - Funding structure: - Household and corporate deposits are "over 60 percent of banks’ balance sheets," while customer loans amount to 56 percent of the balance sheet. - Loan-to-deposit ratios started to rise in 2011. - Central bank funding rose "at the margin" to "3.1 percent of the balance sheet in March 2012." - Main source of wholesale funding is interbank transactions (10 percent of the balance sheet); net borrowing from interbank sources is 1 percent of assets. - Russia’s liquidity indicator scores favorably to other EMs but banks’ maturity gap is marginally rising. ### Financial soundness of the banking sector (key statistics and risks) - Profitability and NPLs: - ROA recovered to "over 2 percent in 2011." - NPL ratio declined "from over 10 percent in 2009 to below 7 percent in 2011." - Caveats: decline in NPL ratio driven by rapid credit growth; amount of overdue and nonperforming loans has not been reduced. - Risks to NPL measurement: (i) overvaluation of foreclosed assets, (ii) transfer of distressed assets to affiliated off-balance sheet entities not subject to consolidated supervision, (iii) doubtful quality of restructured loans. - Provisioning and capital - Reported total provisions (including those for performing loans) "exceeds NPLs." - NPL ratio net of provisions to capital is about 10 percent (median in the peer group). - Uncertainty over adequacy of provisions due to discretionary provisioning ratios and widely varying quality of collateral. - Rapid credit growth is weighing on capital adequacy: - Regulatory capital ratio declined to 14.7 percent from the peak of above 20 percent in 2009 right after state capital injection. - Decline is larger for state-owned banks and foreign banks, with about 4 percentage points decline each in a year since end 2010. - Stock of capital remained constant; declines in capital ratios driven by rapid expansion of credit and some tightening of risk weights. - Peer comparisons and structural notes - With "2.4 percent ROA, Russian banks can increase their total and core capital ratios by 2.7 percentage points every year, assuming zero dividend payout." - Return on equity is 18 percent, about median of the range observed for Russia’s peers (13–21 percent, excluding Hungary with negative profits). - Russia’s NPL ratio "remains one of the highest among the peer group." - Sectoral credit distribution data could be biased due to lack of strict consolidated supervision and monitoring of related party lending. *Source: _cr12218 - 44. In recent years, the CBR has made important progress in its communication.* ### 9.2 percent (Table 1). The introduction of Basel 2.5 and Basel III framework starting in 2013 ### _cr12218 - 9.2 percent (Table 1). The introduction of Basel 2.5 and Basel III framework starting in 2013 ### Capital Adequacy and Regulatory Changes - The introduction of Basel 2.5 and Basel III framework starting in 2013 is expected to reduce capital adequacy further as risk weights will be tightened and the definition of capital will become stricter. - Since the minimum total capital ratio will continue to be set at 10 percent, the changes will effectively raise minimum capital ratio requirements. - The CBR requests all banks to report both on local GAAP and IFRS basis, although regulatory ratios are based on local GAAP. - Note on emerging and developing economies: minimum capital requirements are often set much higher than Basel requirement (8 percent) partly in order to compensate for larger economic and financial volatilities and for regulatory and supervisory weakness. ### Financial Soundness Indicators — Key Statistics and Trends - System-level capital adequacy: - Capital to risk-weighted assets: 15.5 (2007), 16.8 (2008), 20.9 (2009), 18.1 (2010), 14.7 (2011), 14.7 (2012--Mar) - Core capital to risk-weighted assets: 11.6 (2007), 10.6 (2008), 13.2 (2009), 11.1 (2010), 9.3 (2011), 9.2 (2012--Mar) - Capital to total assets: 13.3 (2007), 13.6 (2008), 15.7 (2009), 14.0 (2010), 12.6 (2011), 12.9 (2012--Mar) - Risk-weighted assets to total assets: 85.6 (2007), 81.0 (2008), 75.2 (2009), 77.4 (2010), 85.9 (2011), 87.7 (2012--Mar) - Credit risk measures: - NPLs to total loans: 2.5 (2007), 3.8 (2008), 9.6 (2009), 8.2 (2010), 6.6 (2011), 6.8 (2012--Mar) - Loan loss provisions to total loans: 3.6 (2007), 4.5 (2008), 9.1 (2009), 8.5 (2010), 6.9 (2011), 7.0 (2012--Mar) - Large credit risks to capital: 211.9 (2007), 191.7 (2008), 147.1 (2009), 184.6 (2010), 228.4 (2011), 222.6 (2012--Mar) - Profitability and returns: - Return on assets: 3.0 (2007), 1.8 (2008), 0.7 (2009), 1.9 (2010), 2.4 (2011), 2.4 (2012--Mar) - Return on equity: 22.7 (2007), 13.3 (2008), 4.9 (2009), 12.5 (2010), 17.6 (2011), 18.2 (2012--Mar) - Liquidity and balance-sheet composition (selected): - Highly liquid assets to total assets: 14.5 (2007), 13.3 (2008), 13.5 (2009), 11.8 (2010), 12 (2011), 12 (2012--Mar) - Liquid assets to total assets: 24.8 (2007), 25.9 (2008), 28.0 (2009), 26.8 (2010), 23.9 (2011), 23.2 (2012--Mar) - Liquid assets to short-term liabilities: 72.9 (2007), 92.1 (2008), 102.4 (2009), 94.3 (2010), 60.1 (2011), 58.7 (2012--Mar) - Ratio of client's funds to total loans: 94.8 (2007), 84.6 (2008), 99.9 (2009), 109.5 (2010), 105.3 (2011), 102.2 (2012--Mar) ### Economic Risks and Resilience Going Forward - Oil Prices: Major Risk - Volatile external conditions, especially oil prices, remain the main source of risks for Russian banks. - Stress test scenario examined declines in oil prices (to US$50–70) with corresponding sharp declines in the GDP growth rate. - Credit risks are key for banks; oil prices and the exchange rate (highly correlated with oil prices) are key drivers for credit quality. - Stress-test result: the system-wide overall capital ratio declined from 18.1 percent to 14.1 percent under the considered stress. Given current capital ratio at 14.7 percent (Table 1), similar shocks could make a larger number of banks undercapitalized. - Exchange Rate: Manageable Risk - RUB/USD volatility has risen since the global financial crisis; correlated with fundamentals because oil prices are denominated in U.S. dollars. - Change in CBR’s policy framework away from exchange rate targeting could allow more volatility, which may help absorb macroeconomic and external shocks. - Direct bank exposures to FX risk are small: - Net open FX position to capital: 0.6 percent of capital. - Banks are net FX creditors; ruble depreciation is, on aggregate, beneficial to banks. - Indirect credit-quality impact: - About a quarter of total loans are denominated in FX. - Resident corporations and financial institutions borrow about 20 percent of their loans in FX; many corporations have matching FX income. - Resident individuals have 5 percent of their loans denominated in FX. - FX lending to individuals (resident and nonresident) are just 1 percent of total loans. - Overdue loan ratios by currency indicate relatively better credit quality of FX loans for all borrower types except individuals. - Potential Contagion from Exposures to Europe: Manageable - Overseas and nonresident investments amount to 14 percent of total assets: - Roughly 40 percent is interbank exposures. - 30 percent is loans to nonresident corporations. - 14 percent is in cash. - 13 percent is in securities. - Interbank exposures concentration: - Exposures concentrated in state-owned, foreign and large private banks and major financial centers (U.K. in particular). - State-owned banks’ exposures concentrated in Cyprus (where one major bank has its subsidiary) apart from London. - Foreign banks’ exposures increased vis-à-vis group companies (Austria and Italy) while reducing exposures in U.K., Germany, and other countries. - Securities exposures: CBR estimates about 60 percent of exposures are vis-à-vis ultimately Russian entities (issued via entities incorporated in Luxembourg, Ireland, and Cyprus). - Monetary Tightening in Russia: Manageable - Stress test for top 17 banks (65 percent of system by assets) in April 2012 indicates potential losses from higher interest rates are very small compared to capital. - Transmission from policy rates to other interest rates is seen as relatively limited. - Central bank funding is relatively small at 3 percent of liabilities (Table 1). ### Exchange Rate Volatility — Empirical Findings (Box III.1) - Evolution and drivers: - RUB/EUR volatility: fairly high in early 2000, declined towards mid-2000s, remained lower from 2004 up to the crisis. - RUB/USD volatility: kept at very low levels in early 2000 under exchange rate targeting, rose in mid-2000s, and jumped during the 2008–09 crisis. - During 2008–09 crisis: volatility jumped to 3–5 times pre-crisis averages (differences strongly statistically significant). The post-crisis vs pre-crisis difference is significant only for RUB/USD volatility. - Role of oil price volatility: - RUB/USD volatility is closely linked to oil price volatilities. - A simple empirical model indicates oil price volatility dominates the impact of other global-risk proxies on RUB/USD volatility. - The model (with crisis period dummy) explains over 80 percent of the movement of RUB/USD volatility. - Oil price volatility plays only a small role for RUB/EUR volatility; EUR/USD volatility contributes most to RUB/EUR movement, explaining 30 percent of total movement. - Increasing unexplained residual volatility: - For both RUB/USD and RUB/EUR, the unexplained residual has become more volatile, implying exchange rates have been increasingly driven by factors other than fundamentals or global currency market trends since the global financial crisis. - Volatility estimates (period averages, standard deviation in percent): - USDEUR: 00-04 = 10 33 ; 05-June 08 = 15 15 ; Crisis 2/ = 8 16 1 ; May 09-now = 37 29 - Standard deviation of residuals (Ruble-EUR volatility): 00-04 = 21 ; 05-June 08 = 5 ; May -now = 17 - Standard deviation of residuals (Ruble-USD volatility): 00-04 = 1.6 ; 05-June 08 = 6.4 ; May 09 -now = 9.2 *Source: IMF staff compilation from Central Bank of Russia data and 2011 FSAP stress-testing results as presented in the document.* ### 1. As discussed in Strengthening Russia’s Fiscal Framework ### As discussed in Strengthening Russia’s Fiscal Framework ### Existing budget framework and recent implementation - Russia already has many elements of a budget framework that can help face future challenges, but the framework "has not been implemented in a steadfast way." - Two oil funds exist: - Reserve Fund — a “rainy day” fund to smooth large swings in oil prices. - National Wealth Fund — to save part of the oil wealth for future generations. - The long-term nonoil deficit target of 4.7 percent of GDP is specified in the budget code and has been endorsed by staff as an appropriate anchor. ### Key challenges for oil-producing countries and best-practice responses - Main challenges: - Delink the economy from oil price volatility. - Ensure intergenerational equity (oil wealth enjoyed equally by all generations). - Promote balanced and diversified economic growth. - Best-practice responses suggested: - Save some oil revenue during an oil boom and draw on savings in a (temporary) downturn. - Base spending decisions on a longer-term perspective (credible medium-term fiscal framework). - Focus on nonoil indicators, rather than the overall balance, to assess the true stance of fiscal policy. ### Recent deviations, risks, and fiscal stance issues - Fiscal policy has focused excessively on the overall balance rather than the nonoil balance, leading to procyclical policies (except 2009). - The Reserve Fund was drawn down to finance budget deficits in 2009 and 2010, leaving a much smaller buffer against sudden oil price drops. - The medium-term anchor for fiscal policy was suspended during the crisis. - The Ministry of Finance proposed an oil-price rule starting with the 2013 budget with features: - Ceiling on expenditures defined as total revenue at the “base” oil price, plus all nonoil revenues, plus a net borrowing limit of 1 percent of GDP. - Oil revenues above the “base” oil price saved in the Reserve Fund until it reaches 7 percent of GDP; once at that threshold, at least half of excess oil revenues should go to the National Wealth Fund, with the remainder channeled to the budget for infrastructure and priority projects. - If oil prices are below the “base” oil price, the Reserve Fund would finance the resulting budget deficit. - Starting in 2013, the rule would use a 5-year backward-looking average of oil prices as the base, gradually increasing to a 10-year average by 2018. ### Approaches to long-term management of oil wealth and fiscal risks - Desirability of approaches depends on country circumstances and institutions. - Russia faces looming demographic challenges that imply significant fiscal risks from future pension and healthcare expenditures; need to preserve a share of today’s oil wealth for future generations. - Calls on contingent liabilities (explicit and implicit) can have major fiscal costs. - Best-practice guidelines for fiscal risk disclosure and management: - Fiscal risks should be identified and disclosed. - Fiscal risks should be mitigated in a cost-effective manner. - There should be a clear legal and administrative framework to regulate overall fiscal management and government exposure to fiscal risks. - Fiscal risks should be systematically incorporated into fiscal analysis and the budget process. - Current situation in Russia: - Fiscal risks are not systematically identified and disclosed nor systematically incorporated into fiscal analysis and the budget process. - Example event: failure of the Bank of Moscow in summer 2011 and subsequent $14.2 billion recapitalization operation paid for through the state deposit insurance corporation (DIA) did not entail a cost to the state budget but illustrates the need for better structures. - Including the debt of quasi-sovereigns would increase Russia’s public-debt-to-GDP ratio by an extra 10 percentage points by 2020 (research cited). ### Pros and cons: Nonoil deficit target versus oil-price rule - Nonoil deficit target — Pros: - Focuses on the nonoil deficit relevant for an oil-producing country. - Delinks the economy from oil price volatility. - Ensures both fiscal sustainability and intergenerational equity. - Encompasses changes in both oil prices and volumes. - Nonoil deficit target — Cons: - May be difficult to communicate. - Needs to be reassessed periodically. - Oil-price rule — Pros: - Delinks the economy from oil price volatility. - Easy to communicate. - Oil-price rule — Cons: - Needs supplementation with additional constraints (e.g., expenditure ceiling, “reverse-engineered” oil price) to ensure fiscal sustainability and intergenerational equity, which could make communication harder. - Does not explicitly take account of changes in oil volumes. ### Flexibility of rules and handling structural breaks - Nonoil deficit target could be more effective in delinking the budget from oil price cycles and is forward-looking if reassessed periodically. - Oil-price rules that use past prices (moving average) only reflect permanent shifts in oil prices with a lag; such rules can be expansionary during a shift to permanently lower long-run prices until the moving average adjusts. - Some countries incorporate both past and future oil prices in their oil-price rules to address this lag. ### Staff assessment and model-based simulations - Staff’s assessment: the currently-suspended nonoil deficit target of 4.7 percent remains an appropriate anchor for Russia. - Using assumptions from the April 2012 WEO, a Permanent Oil Income Model (POIM) using a real criterion rule (constant stream of services in real terms) would be consistent with a nonoil deficit of about 6 percent of GDP by 2015, allowing greater upfront consumption but lower consumption in outer years. - Stress testing suggests the appropriate range for the nonoil deficit by 2015 would be between 4 and 8 percent of GDP; 4.7 percent of GDP appears appropriately conservative and would allow the Reserve Fund to be gradually rebuilt out of the resulting overall surpluses. - Staff’s estimates suggest the ministry of finance rule under consideration would lead to a nonoil deficit higher than under a POIM-real rule through 2020 and would not generate sufficient surpluses to rebuild the Reserve Fund meaningfully. ### Sensitivity analysis for POIM-Real Approach — Nonoil primary deficit by 2015 (percent of GDP) - Baseline parameters: 6.2 - Sensitivity tests: - Long-run Urals oil price (baseline = US$95/barrel) - Higher oil prices (US$120/barrel): 7.3 - Lower oil prices (US$70/barrel): 5.2 - 10-year average price (2011-2002, US$55.70/barrel): 4.7 - Long-run gas price (baseline = US$330/tcm) - Higher gas prices (US$400/tcm): 6.8 - Lower gas prices (US$260/tcm): 5.7 - 10-year average price (2011-2002, US$203.40/tcm): 5.3 - Combined shocks to oil and gas prices - Higher oil and gas prices (US$120/barrel and US$400/tcm): 7.8 - Lower oil and gas prices (US$70/barrel and US$260/tcm): 4.7 - 10-year average price (2011-2002, US$55.70/barrel and US$203.40/tcm): 3.7 - Oil reserves (baseline = 100, oil runs out in 2049) - Higher oil reserves (130, oil runs out in 2061): 6.8 - Lower oil reserves (70, oil runs out in 2038): 5.4 - Gas reserves (baseline = 100, gas runs out in 2091) - Higher gas reserves (130, gas runs out in 2116): 6.3 - Lower gas reserves (70, gas runs out in 2067): 6.0 - Effective oil and gas tax take (baseline = 35%) - Higher oil tax take (+5 ppt): 7.3 - Higher oil tax take (-5 ppt): 5.2 - Long-run real interest rate on financial assets (baseline r = 4.0) - Higher r = 4.5: 6.5 - Higher r = 3.5: 5.9 - Long-run real growth rate (baseline y = 3.0) - Higher y = 3.5: 6.2 - Higher y = 2.5: 6.3 ### Recommendations for rule design and governance - To be credible and lasting, fiscal anchors and targets need flexibility to balance the risk of obsolescence and the risk of undermining credibility by excessive discretion. - Practices to consider: - Focus on procedural rules rather than fixed numerical targets (example: Chile — identify fiscal variable and process to determine specific targets). - Rely on a “flexible” guideline instead of a rigid rule (examples: Timor-Leste and Norway). - Include explicit revision clauses (e.g., targets reassessed every four years). - Main lesson: consistent implementation of whichever rule is chosen is more important than the specific form of the rule. ### Path to reduce the nonoil deficit and GIMF simulations - The current 2012–14 medium-term budget would leave the nonoil deficit at about 9 percent of GDP by 2014, nearly double the 4.7 percent of GDP target. - An alternative: reduce the nonoil deficit gradually to 4.7 percent of GDP by 2015 (adjustment about 1.5 percent per year starting in 2012) using growth-friendly instruments (reductions in government consumption and transfers). This would cause a short-term drag on growth but could yield a positive medium-term growth effect. - Table IV.3: Additional budget consolidation measures by GIMF instrument to reach nonoil deficit target (percent of GDP) — aggregate and by instrument over 2012–2015: - Government consumption: - 2012: 0.229 - 2013: 0.385 - 2014: 0.367 - 2015: 0.319 - 4-year total: 1.324 - Share of total consolidation: 24.4 - General transfers: - 2012: 0.711 - 2013: 1.197 - 2014: 1.139 - 2015: 0.990 - 4-year total: 4.075 - Share of total consolidation: 75.6 - Total: - 2012: 0.940 - 2013: 1.582 - 2014: 1.505 - 2015: 1.309 - 4-year total: 5.3 - Share of total consolidation: 100.0 ### Potential measures to achieve 5.3 percent of GDP fiscal savings - Government consumption: - Reduce wages as part of civil service reform (the 2011–13 medium-term budget had envisaged savings of 0.9 percent of GDP). - Further reduce subsidies to support public or private enterprises (1.3 percent of GDP was originally part of the crisis-related stimulus in 2010, of which only 0.4 percent of GDP was included in the 2011-13 medium-term budget). - Improve the efficiency of expenditures at the regional level (1.1 percent of GDP as estimated by the World Bank’s 2011 Public Expenditure Review). - General transfers: - Gradually phase out poorly-targeted social assistance programs (1 percent of GDP as estimated by the World Bank’s 2011 Public Expenditure Review). - Increase the pension age to 65 for both men and women by 2050 and reduce early pensions (potential savings by 2020 would be about 2.7–3.7 percent of GDP based on simulations from Reforming the Public Pension System in the Russian Federation (forthcoming Working Paper)). - Reduce/eliminate tax expenditures (estimated by the Russian Ministry of Finance to be 1.5 percent of GDP in 2010). ### Credibility of consolidation and growth effects (GIMF scenarios) - Credibility scenarios considered: - Immediately credible package: agents perfectly foresee reduction in interest rates and immediately increase consumption and investment, boosting growth. - “Earned credibility”: agents fully believe that the amount of consolidation observed each period is permanent; initial contractionary effects are muted as agents foresee benefits. - Gradual credibility by doing: agents see consolidation as credible starting in 2014; initial impact on growth is more negative than “earned credibility” but becomes positive in 2013 and converges to “earned credibility” subsequently. - Credibility only after full implementation (in 2016): largest short-term contractionary growth effects; impact on growth becomes positive starting in 2015 even before full credibility is achieved. *Prepared by Charleen Gust.* --- _Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2012/_cr12218.pdf_