## 1. GDP Trend and Cycle

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---

### A. Short-Term Estimates and Methodology
- Complementary decomposition methods:
  - HP filter (Hodrey Prescott, 1980) on quarterly data (lambda as suggested by Ravn and Uhlig (2002)).
  - Structural time series model à la Harvey Jaeger (1993) (HJ), adapted to mixed frequencies to estimate monthly trend and cycle.
  - Production function approach using annual data.
- Data frequencies and samples:
  - Quarterly data: 1999Q1–2022Q1.
  - Annual data: 1999–2021.
- Procedural notes:
  - Mixed-frequency HJ provides monthly estimates of trend and cycle, expanding information for monthly policy decisions and reducing temporal aggregation bias.
  - Headwind episodes defined as two or more consecutive negative QoQ growth of real GDP or sharp decelerations in growth following a time variant methodology inspired by Harding and Pagan (2002).

### B. Key Short-Term Findings
- Trend growth trajectory and levels:
  - Trend GDP growth has been decreasing since 2005.
  - Quarterly estimates suggest current annualized trend growth is about 2-2½ percent.
  - Annual data suggests current GDP trend growth is between 2-3 percent.
  - Production function approach shows trend growth slowed to 2.2 percent in 2021.
- Drivers of the decline:
  - Declining contributions of labor and total factor productivity (TFP).
  - Contribution of labor decreasing, likely reflecting lower labor productivity and/or labor market participation.
  - Contribution of TFP has become negative in recent years, suggesting insufficient innovation.
- Model comparisons and selected numerical outputs:
  - Models largely interpret trend and cycle similarly; mixed-frequency HJ shows higher variation in the trend and larger relative amplitude of the cycle.
  - Selected method outputs (annualized unless noted):
    - HJ 1/Quarterly: 3.6, 2.8, 3.5, 2.7, 2.4
    - HJ 1/Monthly: 3.4, 2.6, 3.7, 2.5, 2.2
    - HP 1/2/Quarterly (lambda = 1,600): 4.1, 2.6, 3.4, 2.1, 2.1
    - HP 3/Annual (lambda = 6.25): 4.0, 2.5, 3.3, 3.0, ...
    - HP 4/Annual (lambda = 100): 5.1, 3.9, 3.4, 2.0, ...
    - PF Annual (Production function): 3.5, 2.9, 2.5, 2.2, ...
  - Note abbreviations: "HJ" = Harvey-Jaeger; "HP" = HP filter; "PF" = Production function approach.

### C. Long-Term Estimates, Projections, and COVID-19 Effects
- Projection assumptions and methodological cautions:
  - Various GDP projection vintages presented; all assumed to converge to 4 percent in the long run.
  - HP filter subject to end-point biases; can underestimate high-frequency cycles near end points and may report spurious cycles.
  - Using forecasts in the sample can influence HP filter estimates; production function estimates are systematically higher when projections are included.
- COVID-19 impacts (channels and magnitudes):
  - Labor: short-term disruptions reduced employment and participation.
  - Capital: capital investment fell in construction due to trade disruptions with Russia, weakening productive capacity.
  - TFP: may have declined due to reduced R&D as businesses prioritized health, remote work, and supply-chain issues.
- Long-term implications:
  - COVID-19 may lead to permanent losses in trend levels; unclear whether trend growth will be affected.
  - Trend growth would be affected mainly by demographics and TFP growth.
  - Under the assumption that COVID-19 becomes endemic in the short term, it is not expected to substantially alter fertility, mortality, or migration trends.
  - Long-term TFP could be affected via prolonged school closures and early retirement reducing human capital, but it is too early to assess statistical significance.

### D. The Importance of Structural Reforms
- Endogeneity of TFP and capital accumulation: investment raises labor productivity and fosters technological adoption.
- Convergence and structural weaknesses:
  - Most Caucasus and Central Asia (CCA) economies have stopped converging with emerging Europe; structural and institutional reforms slowed in the early 2000s.
- Recommended second-generation reforms to raise trend growth:
  - Boost export competitiveness and diversify away from oil and commodities.
  - Increase FDI in non-extractive industries.
  - Reduce the state footprint by resuming privatizations and promoting private sector development.
  - Increase education of the workforce and reduce skill mismatches.
  - Strengthen governance and the judicial process to promote fair and swift contract enforcement.
- Priorities highlighted for Kazakhstan (largest payoffs):
  - Reducing the state footprint.
  - Strengthening public and corporate governance.
  - Diversifying trade and the economy away from extractive industry.
  - Promoting technological innovation.
- Policy context:
  - An ambitious program of reforms was recently announced by President Tokayev in several of these areas.

### E. Conclusions and Policy Implications
- Methodological consensus:
  - Annual trend growth in Kazakhstan has declined and is now about 2–3   percent.
  - Trend growth has been decreasing because of reduced contributions from labor and TFP; recent negative TFP contributions suggest insufficient innovation.
- Methodological recommendation:
  - Use mixed-frequency methodology to generate monthly estimates to better inform monthly base rate policy decisions and mitigate temporal aggregation bias.
- Structural policy recommendations:
  - Implement reforms to reduce the state footprint, strengthen governance, diversify the economy and exports away from extractive sectors, and promote technological change to increase future trend GDP growth.

### Methodological appendices (summary)
- Low-frequency trend-cycle decomposition:
  - Observed log real GDP yt decomposed into cycle ψt and trend μt.
  - Trend μt modeled as local linear random walk with drift: μt = μt−1 + φt−1; φt = φt−1 + ξt, with ξt ~ N(0, σξ2).
  - Stochastic cycle ψt modeled by trigonometric set-up with restriction ρ ∈ (0,1) and cycles allowed between 1.5 and 9 years.
  - Four unobserved variables and four structural parameters estimated via the Kalman filter.
- Mixed-frequency extension:
  - Quarterly lows related to monthly highs via an m_t-weighted average rotating among (1,2,3); approximation follows Mariano and Murasawa (2010).
- Production function / growth accounting:
  - Cobb-Douglas: Yt = At Kt^α Lt^(1−α).
  - Firm-level Orbis cross-sectional OLS (2019, sample of 430 firms) yields capital share 0.4 and labor share 0.6.
  - Human capital extension uses r = 0.107.
  - Capital stock initial year K0 = I0/(g + δ) with δ = 0.07.
  - TFP calculated as residual; HP filter with smoothing parameter 100 applied to each factor.

---

### Exports to Russia and Spillovers (Selected empirical results)

### Trade channel: evidence and magnitudes
- Exports to Russia significantly drive Kazakhstan’s growth and even more so for CIS oil importers.
  - A 10-pp increase in bilateral export growth is associated with a 0.27 pp increase in Kazakhstan’s real GDP growth, and a 0.4 pp increase in CIS OI growth.
- Bilateral exports measurement:
  - q-o-q growth of exports to Russia in local currency; growth rates weighted by the share of Russia in total exports and demeaned.
- Selected regression coefficients and diagnostics (Text Table 2):
  - Own Growth (t-1): 0.131; 0.0899; 0.0816; 0.0819; -0.0268; -0.0439; -0.0405; -0.0448
  - Export to Russia growth: 0.0267*; 0.00635; 0.0423***; 0.0276**
  - Export to EU growth: 0.0472***; 0.0593***
  - Export to AE growth: 0.0461***; 0.0413*; 0.0684***; 0.0561***
  - Headline CPI-: -0.281**; -0.318**; -0.326**; -0.324**; -0.0727; -0.113**; -0.119**; -0.118**
  - REER Growth: -0.0263; -0.0239; -0.0245; -0.0237; 0.101**; 0.129***; 0.134***; 0.140***
  - Oil Price Growth: 0.0431***; 0.0363***; 0.0362***; 0.0361***; 0.0715***; 0.0676***; 0.0685***; 0.0669***
  - Constant: 1.416***; 1.458***; 1.511***; 1.501***; 0.837***; 0.858***; 0.865***; 0.827***
  - Observations: 68 68 68 68 33 39 33 39
  - R-squared: 0.3630; 0.3980; 0.3960; 0.3980; 0.1940; 0.2020; 0.2100; 0.220

### Financial channel: limited role with some exceptions
- Overall minimal financial transmission, with some negative association from Russian interbank lending rates:
  - An increase in Russian interbank lending rates is negatively associated with growth in Kazakhstan.
  - Changes in Russia’s equity prices, policy rate, and government bond yields generally do not have a significant effect on Kazakhstan’s cyclical output in reported specifications.
- Selected coefficients (Text Table 3):
  - Own Growth (t-1): 0.0566; 0.0174; -0.00675; 0.0677; -0.0418; 0.0601
  - Russia Equity Price Growth (t-1): 0.0279; 0.0232; 0.0350**; 0.0327**
  - Russia Change in Lending Rate (t-1): -0.291*; -0.348*; -0.336**; -0.149
  - EU Real GDP Growth (t-1): 0.321; 0.166*; 0.177; 0.773***; 0.0526; 0.719**
  - Headline CPI-: -0.337**; -0.287**; -0.360***; -0.0952**; -0.0473; -0.0886**
  - Oil Price Growth: 0.0292**; 0.0500***; 0.0306**; 0.0312***; 0.0686***; 0.0312***
  - Constant: 1.716***; 1.565***; 1.907***; 0.843***; 1.033***; 0.858***
  - Observations: 50 68 50 30 40 30 30
  - R-squared: 0.3650; 0.3920; 0.4200; 0.2050; 0.1730; 0.209

### Quantitative spillover magnitudes and forecast decompositions
- VAR and dynamic panel results:
  - A one-standard-deviation (SD) positive growth shock in Russia (1.8 pp) raises q-o-q growth in Kazakhstan by 0.3 pp in the first quarter and 0.5 pp in the next quarter.
  - A one-SD positive growth shock in the EU (1.9 pp) is associated with a 0.25 pp growth increase in Kazakhstan after two quarters.
- Forecast error variance decomposition (domestic growth fluctuations):
  - Shocks from Russia explain 14 percent of domestic growth fluctuations.
  - Shocks from the EU explain 4 percent.
  - Oil price shocks explain 18 percent.
- Dynamic OLS / panel regression key results:
  - After controlling for non-Russia factors, a one-percentage-point increase in real GDP growth in Russia yields:
    - About 1/3 pp increase in Kazakhstan (country-specific dynamic OLS).
    - About 2/3 pp increase in CIS oil importers (panel estimates for CIS OI).
  - Selected parameter values preserved as reported (examples):
    - Own Growth (t-1): 0.0724; 0.263**; 0.250**
    - Russia Real GDP Growth: 0.487***; 0.323**; 1.015***; 0.883***
    - Oil Price Growth: 0.0166; 0.0294***; 0.0240**; 0.0148; 0.00628; 0.0384***; 0.0361***; 0.00516
    - Observations: 68, 68, 68, 66, 33, 39, 33, 39
    - R-squared: 0.505, 0.449, 0.502, 0.537, 0.377, 0.284, 0.285, 0.381
    - Significance: *** p<0.01, ** p<0.05, * p<0.1

### Country-specific determinants of passthrough
- Estimation approach:
  - Country-specific beta (훽2) measures effect of 1 pp Russia growth on domestic growth, then 훽2i regressed cross-sectionally on country-specific variables (훼i).
- Key cross-sectional findings (Text Table 4 coefficients and standard errors preserved):
  - Global Connectedness - Breadth: -0.0215***; -0.0149* (standard errors: (0.00433); (0.00762))
  - Trade with Russia (% of total trade): 0.0147***; 0.00951* (standard errors: (0.00430); (0.00511))
  - Economic Complexity: -0.128*; 0.114; 0.0903 (standard errors: (0.0707); (0.0838); (0.0849))
  - Government Effectiveness: -0.179***; 0.0818; 0.146 (standard errors: (0.0594); (0.102); (0.112))
  - EU (1 if EU, 0 if otherwise): -0.282** (standard error: (0.107))
  - Current Account Balance (% of GDP): -0.0237**; 0.00111; 0.000444 (standard errors: (0.00975); (0.00970); (0.00971))
  - GDP Per Capita: -1.36e-05*; -1.94e-05*** (standard errors: (6.88e-06); (6.29e-06))
  - Constants and observations vary across specifications; example R-squared values include 0.4590; 0.2860; 0.1010; 0.2450; 0.1690; 0.1930; 0.5470; 0.541

### Stylized facts and policy implications
- Stylized external-linkage facts:
  - In 2019, over a third of Kazakhstan’s total imports were from Russia (representing about 8 percent of GDP).
  - Imports from Russia by product share (2019): consumer goods 41.1 percent, intermediate goods 31.5 percent, capital goods 21.3 percent, raw materials 6.1 percent.
  - Kazakhstan’s exports to Russia declined to about 10 percent of total exports in 2019.
  - Cross-border financial linkages with Russia are small: portfolio investments in Russia by Kazakhstani residents are less than 1 percent of their total portfolio holdings.
  - Kazakhstan receives limited FDI inflows from Russia—representing about 3 percent of GDP.
  - Sovereign bond spreads of Russia and Kazakhstan are closely correlated during major shocks.
- Policy recommendations to mitigate vulnerability:
  - Greater partner diversification to reduce trade-channel spillovers.
  - Improved public governance to limit co-movement of sovereign spreads and amplify resilience.
  - Continued credible macroeconomic policies and maintenance of strong buffers.
  - These policies act both directly and indirectly to contain cross-border spillover effects.

---

### Fiscal Governance Vulnerabilities and Prioritized Recommendations

### A. Budget Structures, Rules, and Fiscal Policy Effectiveness
- Main issues:
  - Budget processes and fiscal policy effectiveness hampered by scattered fiscal responsibilities and ad-hoc decisions.
  - Numerous extra-budgetary funds and quasi-public entities operate outside the direct remit of the budget, undermining assessment of the fiscal impulse and macroeconomic policy coordination.
- Recommended direction:
  - Clarify fiscal responsibilities guided by international standards, starting with boundaries of the general government and public sector.
  - Reform quasi-public sector: bring non-commercial entities under line ministries; proceed with privatization plans for commercially operating entities.
- Quasi-Government Entities (QGE) — key facts:
  - About 7,000 QGE in Kazakhstan.
  - Most QGE fully owned by the government; less than a thousand where the government is a shareholder.
  - Most QGE owned by two national holding companies:
    - Samruk-Kazyna: hydrocarbons account for half of its revenue and three quarters of assets. Samruk-Kazyna’s revenues amounted to 14.0 percent of GDP in 2021, and had accumulated a debt of 11.8 percent of GDP.
    - Baiterek: in 2021, Baiterek’s revenues amounted to 0.3 percent of GDP, and its total debt to 9.8 percent of GDP.
  - QGE oversight distributed across the Ministry of Economy, line ministries, the NBK, and other entities, with scope to streamline governance.
- Budgetary weight of SOEs, 2021 (as presented):
  - General government revenue 14,359 17.1
  - of which: revenue from SOEs 2,490 3.0
  - Revenue of holding companies 11,980 14.3
  - Baiterek 216 0.3
  - Samruk Kazyna 11,764 14.0
  - Budget support to SOEs 550 0.1
  - Holding companies debt 18,146 21.6
  - Baiterek 8,200 9.8
  - Samruk Kazyna 9,946 11.8
  - Memorandum item:
    - Nominal GDP 83,952 ...
- Strengthening budget rules and processes:
  - Use upcoming revision of budget code to make fiscal policy more rules-based; stricter implementation for amending the budget needed.
  - Emphasize the non-oil deficit to non-oil GDP as a key measure of fiscal impulse.
  - Use medium-term fiscal framework to anchor annual budgets; correct deviations in subsequent years or revise plans if warranted.
  - Strengthen reporting provisions: publish accurate and timely mid-year and end-of-year fiscal reports and explain deviations.
  - Support policies to strengthen budget credibility, notably in wage bill policy and management.
- Public wage bill improvements (Box 2 key points):
  - Public wage bill is underestimated (PEFA 2019).
  - Limited information on overall public wage bill for general government; non-central government entities' wage bill not reported.
  - Remuneration rules could be improved; current wage increases largely set by seniority and ad-hoc decisions.
  - Reform plans should introduce a direct link between salary increases and performance.
- Strengthening budget oversight:
  - Consider establishing an independent fiscal council to monitor fiscal outcomes and publish assessments against approved budgets and rules.
  - Note: 51 emerging and advanced economies have established fiscal councils.

### B. Strengthening Fiscal Transparency
- Progress to date:
  - Substantial efforts to improve budget transparency, including digitalization and a new fiscal risks statement (FRS).
  - Progress aligning government finance statistics with the 2014 GFSM; data available online.
  - Progress recognized in the 2021 Open Budget Survey.
- Implications of quasi-public sector restructuring:
  - Reclassification of some SOEs as extrabudgetary general government units will impact fiscal statistics, budget presentations, governance, accounting, and reporting.
  - Distinguish extrabudgetary activities compensated through budget transfers from quasi-fiscal activities not fully compensated; quasi-fiscal activities should be fully compensated and adequately reported.
- Tax expenditures and energy subsidies:
  - Large tax expenditures, including VAT and corporate income tax exemptions.
  - As of 2020, authorities assessed VAT and CIT tax expenditures to represent about 4.5 percent of GDP and 1.7 percent, respectively, against a total collection of 3.6 percent and 3.5 percent.
  - Total removal of these tax expenditures would potentially double their joint level of revenue collection.
  - Pre-tax energy subsidies are implicit subsidies; tackling energy subsidies is important because:
    - (i) size of the subsidies (about 20 percent of GDP) calls for careful planning of tax and price adjustments,
    - (ii) removing energy subsidies will be costly for businesses and households and will require adequate social safety nets,
    - (iii) removing energy subsidies is highly sensitive and requires early and sustained engagement with civil society.
  - First step: disclose level of energy subsidies and their opportunity cost to inform public debate on alternative uses of public resources.
- Public investment and procurement:
  - Authorities have taken steps to improve the public investment framework; upgrading infrastructure quality (especially roads) is critical for diversification, climate challenges, and growth potential.
  - Public procurement represents 7 percent of GDP and 35 percent of government spending; perceptions of corruption in public procurement remain significant.
  - Recent initiatives: new public procurement law, fiscal risks assessments covering PPPs, new web-based procurement platform.
  - New procurement law provisions include greater access to public tenders, promote online procurement, focus on quality over price, and streamline processes.
- Priority procurement improvements:
  - Generalize competitive public tenders: share of uncompetitive procurement contracts remains elevated (about a half of total contracts); QGE have separate procurement processes.
  - Address unfairness where SOEs compete with private firms; consider privatizing SOEs operating on a commercial basis.
  - Give more budget flexibility to procurement contracts to avoid delays and disruptions when economic conditions change.
  - Disclose beneficial owners of public contracts to align with best practices and support AML efforts.

### C. Fostering a Risk Management Culture
- Improving Fiscal Risks Statements (FRS) and Long-Term Fiscal Sustainability (LTFS):
  - Introduction of an FRS and LTFS in the 2023 budget is an important step toward risk-based fiscal policymaking.
  - First FRS focuses on macro-fiscal risks; authorities intend to broaden scope to cover SOEs, PPPs and other risks.
  - Initial LTFS focuses on projections until 2050 and issues related to demographic and climate changes.
  - Uses of FRS and LTFS:
    - Inform PFM reforms and incorporate macroeconomic projections in the budget process.
    - Prioritize SOE and PPP reforms.
    - Develop contingency fiscal plans to reconcile stabilization role of fiscal policy and preserve fiscal space.
    - In the longer term, LTFS will help analyze management of natural resource revenues as part of transition away from fossil fuels.
- Managing fiscal risks from the SOE sector:
  - SOE debt: limited information on debt held by subsidiaries and cross-debts could raise risks for SOEs and the budget.
  - Centralized cash management within holding groups can transmit liquidity or solvency pressures across entities.
  - Shocks to the hydrocarbon sector may simultaneously impact several large SOE entities, potentially creating significant fiscal liabilities.
  - Privatizations would help reduce risks; structural SOE reforms also desirable: simplify governance, place some SOEs under one line ministry, and have the Ministry of Economy supervise cross-cutting fiscal risks.
- Taxpayer compliance and revenue administration:
  - Revenue collection affected by corruption vulnerabilities; entrepreneur perceptions of bribe requests from tax officials are above the median among emerging countries.
  - Time to clear customs: about 9 days.
  - Digitalization by the State Revenue Committee (SRC):
    - E-invoicing strengthened VAT collection and reduced VAT fraud opportunities.
    - One-stop shops for e-filing and e-payments improved taxpayer services.
    - Taxpayer databases enable cross-checking declarations between customs and tax, reducing tax fraud.
    - Reduced face-to-face interactions lowered corruption vulnerabilities.
  - Movement toward risk-based revenue collection:
    - SRC modernized tax administration focusing on compliance risks with highest revenue impact.
    - New IT systems incorporate economic factors to better assess compliance risks.
    - Large Taxpayer Office (LTO) can leverage comprehensive databases to improve voluntary compliance.
    - SRC developing risk-based tax audits.
  - The new tax code expected in 2023 should support efforts to reduce taxpayer compliance risks by streamlining tax incentives and increasing PIT progressivity to improve fairness, voluntary compliance, and revenue administration.

*Source: 1kazea2022009 - 1. GDP Trend and Cycle (Selected Issues Paper), November 18, 2022.*

### 1. GDP Trend and Cycle ___________________________________________________________________ 4

### 1. GDP Trend and Cycle

### A. Short-Term Estimates and Methodology
- Complementary methods used to decompose GDP into trend and cycle:
  - HP filter (Hodrey Prescott, 1980) on quarterly data (lambda as suggested by Ravn and Uhlig (2002)).
  - Structural time series model à la Harvey Jaeger (1993) (HJ), adapted to mixed frequencies to estimate monthly trend and cycle (Appendix I).
  - Production function approach using annual data (Appendix II).
- Data frequencies and samples:
  - Quarterly data: 1999Q1–2022Q1.
  - Annual data: 1999–2021.
- Key procedural notes:
  - Mixed-frequency HJ provides monthly estimates of trend and cycle, expanding information available for monthly policy decisions and reducing temporal aggregation bias.
  - Headwind episodes are defined as two or more consecutive negative QoQ growth of real GDP or sharp decelerations in growth following a time variant methodology inspired by Harding and Pagan (2002).

### B. Key Short-Term Findings
- Trend growth trajectory:
  - Trend GDP growth has been decreasing since 2005.
  - Quarterly estimates suggest current annualized trend growth is about 2-2½ percent.
  - Annual data suggests current GDP trend growth is between 2-3 percent.
  - Production function approach shows trend growth slowed to 2.2 percent in 2021.
- Drivers of the decline:
  - Declining contributions of labor and total factor productivity (TFP).
  - Contribution of labor has been decreasing, likely reflecting lower labor productivity and/or labor market participation.
  - Contribution of TFP has become negative in recent years, suggesting insufficient innovation.
- Model comparisons:
  - Models largely interpret trend and cycle similarly; mixed-frequency HJ shows higher variation in the trend of GDP and larger relative amplitude of the cycle during peaks and troughs.
  - The mixed-frequency approach may be preferred for monthly policymaking due to ability to produce monthly decompositions.

- Selected numerical method outputs (excerpted from model comparisons):
  - HJ 1/Quarterly (Annualized): 3.6, 2.8, 3.5, 2.7, 2.4
  - HJ 1/Monthly (Annualized): 3.4, 2.6, 3.7, 2.5, 2.2
  - HP 1/2/Quarterly (Annualized, lambda = 1,600): 4.1, 2.6, 3.4, 2.1, 2.1
  - HP 3/Annual (lambda = 6.25): 4.0, 2.5, 3.3, 3.0, ...
  - HP 4/Annual (lambda = 100): 5.1, 3.9, 3.4, 2.0, ...
  - PF Annual (Production function): 3.5, 2.9, 2.5, 2.2, ...
  - (Notes: "HJ" for Harvey-Jaeger; "HP" for HP filter; "PF" for Production function approach. 1/ Annualized. 2/ lambda = 1,600. 3/ lambda = 6.25. 4/ lambda = 100.)

### C. Long-Term Estimates, Projections, and COVID-19 Effects
- Projection assumptions and biases:
  - Various GDP projection vintages are presented; all assumed to converge to 4 percent in the long run.
  - HP filter is subject to end-point biases; HP can underestimate high-frequency cycles near end points and may report spurious cycles.
  - Using forecasts in the sample can influence HP filter estimates; production function estimates are systematically higher when projections are included.
- COVID-19 impacts:
  - COVID-19 has had an impact mainly on short-term estimates of trend level and growth through headwinds to labor, capital, and TFP:
    - Labor: short-term disruptions reduced employment and participation.
    - Capital: capital investment fell in construction due to trade disruptions with Russia, weakening productive capacity.
    - TFP: may have declined due to reduced R&D as businesses prioritized health, remote work, and supply-chain issues.
  - Long-term implications:
    - COVID-19 may lead to permanent losses in trend levels, but it is unclear whether trend growth will be affected.
    - Trend growth would be affected mainly by demographics and TFP growth.
    - Under the assumption that COVID-19 becomes endemic in the short term, it is not expected to substantially alter fertility, mortality, or migration trends.
    - Long-term TFP could be affected via prolonged school closures and early retirement reducing human capital, but it is too early to assess statistical significance.

### D. The Importance of Structural Reforms
- TFP and capital accumulation are endogenous; investment raises labor productivity and fosters technological adoption.
- Structural weaknesses and convergence:
  - Most Caucasus and Central Asia (CCA) economies have stopped converging with emerging Europe; structural and institutional reforms slowed in the early 2000s.
- Recommended second-generation reforms to raise trend growth:
  - Boost export competitiveness and diversify away from oil and commodities.
  - Increase FDI in non-extractive industries.
  - Reduce the state footprint by resuming privatizations and promoting private sector development.
  - Increase education of the workforce and reduce skill mismatches.
  - Strengthen governance and the judicial process to promote fair and swift contract enforcement.
- Priorities highlighted for Kazakhstan (largest payoffs):
  - Reducing the state footprint.
  - Strengthening public and corporate governance.
  - Diversifying trade and the economy away from extractive industry.
  - Promoting technological innovation.
- Policy context:
  - An ambitious program of reforms was recently announced by President Tokayev in several of these areas.

### E. Conclusions and Policy Implications
- Consensus from multiple methodologies:
  - Annual trend growth in Kazakhstan has declined and is now about 2–3   percent.
  - Trend growth has been decreasing because of reduced contributions from labor and TFP; recent negative TFP contributions suggest insufficient innovation.
- Policy-relevant methodological recommendation:
  - A mixed-frequency methodology is proposed to generate monthly estimates that can better inform monthly base rate policy decisions and mitigate temporal aggregation bias.
- Structural policy recommendation summary:
  - Implement reforms to reduce the state footprint, strengthen governance, diversify the economy and exports away from extractive sectors, and promote technological change to increase future trend GDP growth.

*Source: 1kazea2022009 - 1. GDP Trend and Cycle (Selected Issues Paper), November 18, 2022.*

### 18.      Structural reforms remain critical to raise future trend GDP growth. COVID-19 has

### 18.      Structural reforms remain critical to raise future trend GDP growth. COVID-19 has

### Key findings on growth, productivity, and COVID-19 effects
- COVID-19 has depressed both trend level and growth in the short term through headwinds to labor, capital, and TFP.
- COVID-19 could also affect long-term trend growth through the destruction of human capital, but it is too early to assess the statistical significance of this effect.
- Productivity growth has been close to zero for the last decade (World Bank (2022).
- Average economic growth in the five years prior to COVID was 2.4 percent, against 8½ percent during 1999–2008.

### Policy priorities and recommendations
- Reduce the state footprint.
- Strengthen public and corporate governance.
- Pursue economic and trade diversification.
- Increase the share of investment, including FDI, in non-extractive industries to promote R&D, innovation, and higher TFP.

### Stylized facts on external linkages (Russia and trade)
- In 2019, over a third of Kazakhstan’s total imports were from Russia (representing about 8 percent of GDP).
- Imports from Russia by product share (2019): consumer goods 41.1 percent, intermediate goods 31.5 percent, capital goods 21.3 percent, raw materials 6.1 percent.
- Kazakhstan’s exports to Russia declined to about 10 percent of total exports in 2019.
- Cross-border financial linkages with Russia are small: portfolio investments in Russia by Kazakhstani residents are less than 1 percent of their total portfolio holdings.
- Kazakhstan receives limited FDI inflows from Russia—representing about 3 percent of GDP.
- Sovereign bond spreads of Russia and Kazakhstan are closely correlated during major shocks.

### Quantitative transmission and empirical results
- VAR and dynamic panel models are used to quantify the impact of Russian cyclical output fluctuations on Kazakhstan and peer economies.
- A one-standard-deviation (SD) positive growth shock in Russia is quantified as a 1.8 pp increase.
  - This one-SD positive growth shock in Russia raises quarter-on-quarter growth in Kazakhstan by 0.3 pp in the first quarter and 0.5 pp in the next quarter.
- The impact of a one-SD positive growth shock in the EU is quantified as a 1.9 pp increase.
  - This EU shock is associated with a 0.25 pp growth increase in Kazakhstan after two quarters.
- Peer comparisons:
  - Armenia and Belarus: spillovers peak three quarters after the initial shock with impacts of 0.8 pp and 0.6 pp, respectively.
  - Ukraine: reaching 1 pp in the first quarter and 0.7 pp in the second quarter.
- Forecast error variance decomposition (domestic growth fluctuations):
  - Shocks from Russia explain 14 percent of domestic growth fluctuations.
  - Shocks from the EU explain 4 percent.
  - Oil price shocks explain 18 percent.

### Dynamic OLS / panel regression results (selected)
- After controlling for non-Russia factors, the impact of a one-percentage-point increase in real GDP growth in Russia on real GDP growth is:
  - About 1/3 pp increase in Kazakhstan (country-specific dynamic OLS).
  - About 2/3 pp increase in CIS oil importers (panel estimates for CIS OI).
- In the baseline dynamic OLS specification, explanatory variables include lagged own growth, Russian growth, EU growth, China growth, headline CPI, REER growth, and oil price growth.
- Selected parameter and specification values preserved from the source:
  - Own Growth (t-1) coefficients reported (e.g., 0.0724; 0.263**; 0.250** across specifications).
  - Russia Real GDP Growth coefficients reported (e.g., 0.487***; 0.323**; 1.015***; 0.883*** across specifications).
  - Oil Price Growth coefficients reported (e.g., 0.0166; 0.0294***; 0.0240**; 0.0148; 0.00628; 0.0384***; 0.0361***; 0.00516 across specifications).
  - Observations: 68, 68, 68, 66, 33, 39, 33, 39 (as shown in table).
  - R-squared values: 0.505, 0.449, 0.502, 0.537, 0.377, 0.284, 0.285, 0.381 (as shown in table).
  - Significance notation: *** p<0.01, ** p<0.05, * p<0.1.

### Methodological notes (models and estimation)
- Low-frequency trend-cycle decomposition:
  - Observed log real GDP yt is decomposed into unobserved cycle ψt and unobserved trend μt.
  - Trend μt modeled as local linear random walk with drift: μt = μt−1 + φt−1; φt = φt−1 + ξt, with ξt ~ N(0, σξ2).
  - Stochastic cycle ψt modeled by a trigonometric set-up with restriction ρ ∈ (0,1) and cycles allowed between 1.5 and 9 years.
  - Four unobserved variables and four structural parameters estimated via the Kalman filter after casting model in state-space form.
- Mixed-frequency extension:
  - Recursive constraint relates quarterly lows to monthly highs via an m_t-weighted average where m_t rotates among (1,2,3) for monthly base frequency and quarterly lower frequency.
  - Approximation follows Mariano and Murasawa (2010) to preserve linearity when using log GDP.
- Production function / growth accounting approach:
  - Cobb-Douglas production function: Yt = At Kt^α Lt^(1−α).
  - Firm-level Orbis cross-sectional OLS (2019 data, sample of 430 firms) used to estimate factor shares with constraint β = 1 − α.
    - Resulting coefficients: capital share 0.4 and labor share 0.6.
  - Human capital extension: Yt = At Kt^α (eS_t r l_t)^(1−α) where S_t is average schooling years and r captures marginal returns to a year of schooling.
    - Parameter r set at 0.107 (Psacharapoulos and Patrinos (2004)).
  - Capital stock initial year K0 = I0/(g + δ), with δ assumed 0.07.
  - Data on output, investment, and employment from IMF WEO database.
  - TFP calculated as residual and HP filter applied to each factor with smoothing parameter of 100; component-specific trends plugged into production function to yield trend output and year-on-year trend growth.

*Source: Republic of Kazakhstan chapter and appendices (structural reform priorities, empirical results on spillovers from Russia, mixed-frequency output decomposition, and production-function growth accounting) from the provided IMF content.*

### 9. Exports to Russia are a significant driver of Kazakhstan’s economic growth. Real GDP

### 9. Exports to Russia are a significant driver of Kazakhstan’s economic growth. Real GDP

### Trade channel: evidence and magnitudes
- Exports to Russia have a significant impact on growth in Kazakhstan and an even stronger impact for CIS oil importers.
- A 10-pp increase in bilateral export growth is associated with a 0.27 pp increase in Kazakhstan’s real GDP growth, and a 0.4 pp increase in CIS OI growth (columns 1 and 5).
- Bilateral exports are measured as the q-o-q growth of exports to Russia in local currency; growth rates are weighted by the share of Russia in total exports and are demeaned.
- Text Table 2 (selected coefficients and diagnostics):
  - Own Growth (t-1): 0.131; 0.0899; 0.0816; 0.0819; -0.0268; -0.0439; -0.0405; -0.0448
  - Export to Russia growth: 0.0267*; 0.00635; 0.0423***; 0.0276**
  - Export to EU growth: 0.0472***; 0.0593***
  - Export to AE growth: 0.0461***; 0.0413*; 0.0684***; 0.0561***
  - Headline CPI-: -0.281**; -0.318**; -0.326**; -0.324**; -0.0727; -0.113**; -0.119**; -0.118**
  - REER Growth: -0.0263; -0.0239; -0.0245; -0.0237; 0.101**; 0.129***; 0.134***; 0.140***
  - Oil Price Growth: 0.0431***; 0.0363***; 0.0362***; 0.0361***; 0.0715***; 0.0676***; 0.0685***; 0.0669***
  - Constant: 1.416***; 1.458***; 1.511***; 1.501***; 0.837***; 0.858***; 0.865***; 0.827***
  - Observations: 68 68 68 68 33 39 33 39
  - R-squared: 0.3630; 0.3980; 0.3960; 0.3980; 0.1940; 0.2020; 0.2100; 0.220
- Note in text: "The impact of bilateral exports with Russia is slightly stronger for CIS oil importers: a 1 pp increase in bilateral exports is associated with a 0.4 pp increase in CIS OI real GDP growth (column 5)."

### Financial channel: limited role with some exceptions
- The role of the financial channel appears minimal overall.
- Changes in Russian interbank lending rates and equity prices are used as proxies for financial transmission variables.
- An increase in Russian interbank lending rates is negatively associated with growth in Kazakhstan.
- Changes in Russia’s equity prices, policy rate, and government bond yields do not have a significant effect on Kazakhstan’s cyclical output in the reported specifications.
- Text Table 3 (selected coefficients and diagnostics):
  - Own Growth (t-1): 0.0566; 0.0174; -0.00675; 0.0677; -0.0418; 0.0601
  - Russia Equity Price Growth (t-1): 0.0279; 0.0232; 0.0350**; 0.0327**
  - Russia Change in Lending Rate (t-1): -0.291*; -0.348*; -0.336**; -0.149
  - EU Real GDP Growth (t-1): 0.321; 0.166*; 0.177; 0.773***; 0.0526; 0.719**
  - Headline CPI-: -0.337**; -0.287**; -0.360***; -0.0952**; -0.0473; -0.0886**
  - REER Growth: -0.0687*; -0.0239; -0.0535; 0.0238; 0.0521; 0.0196
  - Oil Price Growth: 0.0292**; 0.0500***; 0.0306**; 0.0312***; 0.0686***; 0.0312***
  - Constant: 1.716***; 1.565***; 1.907***; 0.843***; 1.033***; 0.858***
  - Observations: 50 68 50 30 40 30 30
  - R-squared: 0.3650; 0.3920; 0.4200; 0.2050; 0.1730; 0.209

### Country-specific factors: fundamentals, diversification, and institutions
- Estimation strategy:
  - Country-specific beta coefficient (훽2) captures the effect of a 1 pp increase in real GDP growth in Russia on domestic real GDP growth, controlling for non-Russian factors.
  - 훽2 coefficients are estimated for a sample of CIS and EU economies with quarterly data; then 훽2i is regressed cross-sectionally on a 14-year average of country-specific variables (훼i).
- Strong macroeconomic buffers contribute to Kazakhstan’s resilience:
  - Vast oil reserves allow Kazakhstan to smooth external shocks.
  - Kazakhstan deviates from the pattern that more complex economies are less sensitive to Russia’s cyclical output fluctuations.
  - Kazakhstan’s relatively strong current account position and low foreign-currency debt share help explain lower sensitivity.
- Partner diversification:
  - Countries with higher partner diversification are less sensitive to Russian cyclical output (strong negative correlation with sensitivity; Figure 6.1).
  - Global Connectedness—Breadth index used as proxy; higher score implies more dispersion or diversification.
  - Analysis shows countries with large export linkages with Russia are more sensitive to Russian output fluctuations than countries with high import dependence from Russia.
  - In Kazakhstan, import dependence does not seem to play a role in cycle transmission (Figure 6.9), even though it exceeds that of other economies.
- Public governance:
  - Countries with higher government effectiveness are less sensitive to the Russian business cycle.
  - Government effectiveness is negatively associated with business-cycle passthrough (Figure 6.7).
  - Better governance may reduce vulnerability to spillovers via risk premia and limit co-movement between Russian and domestic sovereign spreads.
- When combined, diversification and trade intensity with Russia are the strongest determinants of passthrough:
  - Regression specification: 훽2i = 휃1(훼i) + 휖i
  - Greater partner diversification (global connectedness index) associated with weaker spillover effects.
  - Higher trade share with Russia associated with larger effects.

### Cross-sectional determinants and key coefficients (Text Table 4)
- Global Connectedness - Breadth: -0.0215***; -0.0149* (standard errors: (0.00433); (0.00762))
- Trade with Russia (% of total trade): 0.0147***; 0.00951* (standard errors: (0.00430); (0.00511))
- Economic Complexity: -0.128*; 0.114; 0.0903 (standard errors: (0.0707); (0.0838); (0.0849))
- Government Effectiveness: -0.179***; 0.0818; 0.146 (standard errors: (0.0594); (0.102); (0.112))
- EU (1 if EU, 0 if otherwise): -0.282** (standard error: (0.107))
- Current Account Balance (% of GDP): -0.0237**; 0.00111; 0.000444 (standard errors: (0.00975); (0.00970); (0.00971))
- GDP Per Capita: -1.36e-05*; -1.94e-05*** (standard errors: (6.88e-06); (6.29e-06))
- Constant terms and Observations vary across specifications:
  - Constant examples: 1.102***; 0.320***; 0.551***; 0.578***; 0.432***; 0.650***; 1.160***; 0.774***
  - Observations: 31 31 31 30 31 31 30 30
  - R-squared examples: 0.4590; 0.2860; 0.1010; 0.2450; 0.1690; 0.1930; 0.5470; 0.541

### Event analysis and connectedness groups
- Large Russian cyclical output fluctuations defined as periods where Russian real q-o-q GDP growth is one-SD above or below its 2001–19 average.
- Countries grouped by partner diversification into top (High), medium (Medium), and bottom (Low) third percentiles; average responses calculated for Upswings and Downswing periods.
- Kazakhstan is in the medium diversification group but its dynamics over the Russian business cycle are similar to those of the low connectedness group — possibly because large events capture lagged oil price shocks.
- More diversified economies experience weaker cyclical output and bilateral trade fluctuations during large Russian business cycle swings.

### Conclusion and policy implications
- Main findings:
  - Strong economic linkages and business cycle synchronicity exist between Russia and Kazakhstan.
  - Shocks to growth in Russia have a sizable impact on Kazakhstan and play a dominant role in driving its cyclical output fluctuations, including relative to global factors.
  - Spillovers are transmitted primarily through trade, especially exports, and may be amplified by changes in sovereign risk premia.
  - Despite sizable linkages, growth spillovers to Kazakhstan are relatively mild compared to peers due to strong macroeconomic fundamentals.
- Policy recommendations to mitigate vulnerability:
  - Greater partner diversification to reduce trade-channel spillovers.
  - Improved public governance to limit co-movement of sovereign spreads and amplify resilience.
  - Continued credible macroeconomic policies and maintenance of strong buffers.
  - These policies act both directly and indirectly to contain cross-border spillover effects (referenced in Figure 8: Partner Diversification; Public Governance; Macroeconomic Fundamentals; Trade Channel; Risk-premium Channel).

*Source: IMF staff estimates and analysis as presented in "9. Exports to Russia are a significant driver of Kazakhstan’s economic growth. Real GDP" (PDF chapter).*

### 2.      This paper provides an overview of fiscal governance vulnerabilities and prioritized

### This paper provides an overview of fiscal governance vulnerabilities and prioritized recommendations to support the authorities’ reform plans

### A. Budget Structures and Rules, and Fiscal Policy Effectiveness
- Main issues
  - Budget processes and fiscal policy effectiveness are hampered by scattered fiscal responsibilities and ad-hoc decisions.
  - Numerous extra-budgetary funds and quasi-public entities operate outside the direct remit of the budget, undermining assessment of the fiscal impulse and macroeconomic policy coordination (e.g., monetary policy transmission).
- Recommended direction
  - Clarify fiscal responsibilities guided by international standards, starting with the boundaries of the general government and public sector.
  - Reform quasi-public sector to bring entities that do not operate on a commercial basis under the direct supervision of line ministries, while privatization plans for those operating on a commercial basis should proceed.
- Box 1: Quasi-Government Entities in Kazakhstan — key facts
  - There are about 7,000 quasi-government entities (QGE) in Kazakhstan.
  - Most QGE are fully owned by the government; less than a thousand are companies where the government is a shareholder (e.g., Limited Liability Partnerships and Joint Stock Companies).
  - Most QGE are owned by two national holding companies:
    - Samruk-Kazyna: largely involved in the natural resource sector (hydrocarbons account for half of its revenue and three quarters of assets). Samruk-Kazyna’s revenues amounted to 14.0 percent of GDP in 2021, comparable to central government revenues (17.1 percent), and had accumulated a debt of 11.8 percent of GDP.
    - Baiterek: a shareholder of financial institutions. In 2021, Baiterek’s revenues amounted to 0.3 percent of GDP, and its total debt to 9.8 percent of GDP.
  - QGE oversight is distributed across the Ministry of Economy, line ministries, the NBK, and other entities (including holding companies), with scope to streamline governance.
- Budgetary weight of SOEs, 2021 (as presented)
  - (Billions of Tenge)(percent of GDP)
  - General government revenue14,35917.1
  - of which: revenue from SOEs2,4903.0
  - Revenue of holding companies11,98014.3
  - Baiterek2160.3
  - Samruk Kazyna11,76414.0
  - Budget support to SOEs550.1
  - Holding companies debt18,14621.6
  - Baiterek8,2009.8
  - Samruk Kazyna9,94611.8
  - Memorandum item
  - Nominal GDP83,952...
- Strengthening budget rules and processes
  - Use the upcoming revision of the budget code to make fiscal policy more rules-based; stricter implementation of procedural rules to amend the budget is needed.
  - Emphasize the non-oil deficit to non-oil GDP as a key measure of fiscal impulse when elaborating annual budgets.
  - Use the medium-term fiscal framework to anchor annual budgets on medium-term policy objectives; deviations from approved budgets should be corrected in subsequent years or lead to revision of medium-term plans if warranted.
  - Strengthen reporting provisions (e.g., publish accurate and timely mid-year and end-of-year fiscal reports and explain deviations).
  - Support policies to strengthen budget credibility, notably in wage bill policy and management.
- Box 2: Improving the Policy on Public Wage Bill — key points
  - The public wage bill is underestimated (see Public Expenditure and Financial Assessment, PEFA, of 2019).
  - Limited information on the overall public wage bill for the general government; wage bill of non-central government entities is not reported.
  - Rules regarding remuneration of civil servants could be improved; current wage increases are largely set based on seniority and ad-hoc decisions, reflecting current inflation.
  - Current reform plans should introduce a direct link between salary increases and performance.
- Strengthening budget oversight
  - Consider establishing an independent fiscal council to monitor fiscal outcomes and publish assessments of budget implementation against approved budgets and fiscal and numerical rules.
  - Note: 51 emerging and advanced economies have established fiscal councils (Figure 2 referencing counts).

### B. Strengthening Fiscal Transparency
- Progress to date
  - Kazakhstan has made substantial efforts to improve budget transparency, including leveraging digitalization and introducing a new fiscal risks statement (FRS).
  - Progress in aligning government finance statistics with the 2014 Government Finance Statistics Manual (GFSM); data available online through the government platform.
  - Progress recognized in the 2021 Open Budget Survey.
- Implications of restructuring the quasi-public sector
  - Reclassification of some SOEs currently classified as extrabudgetary general government units will impact fiscal statistics, budget presentations, governance arrangements, accounting, and reporting.
  - Distinguish extrabudgetary activities compensated through budget transfers from quasi-fiscal activities that are not fully compensated; quasi-fiscal activities should be fully compensated and adequately reported in the budget.
- Tax expenditures and energy subsidies
  - Kazakhstan provides large tax expenditures, including exemptions on VAT and corporate income tax.
  - As of 2020, authorities assessed tax expenditure for VAT and CIT to represent, respectively, about 4.5 percent of GDP and 1.7 percent, against a total collection of 3.6 percent and 3.5 percent. The total removal of these tax expenditure would potentially double their joint level of revenue collection.
  - Pre-tax energy subsidies are implicit subsidies (i.e., rent not captured by providing energy products below international prices). Figure 3 indicates energy subsidies (2019) components and comparators.
  - Tackling energy subsidies is important for medium- to long-term fiscal policy and is complex for at least three reasons:
    - (i) the size of the subsidies (about 20 percent of GDP) calls for careful planning of tax and price adjustments,
    - (ii) removing energy subsidies will be costly for businesses and households and will require adequate social safety nets,
    - (iii) removing energy subsidies is highly sensitive and requires early and sustained engagement with civil society.
  - First step: disclose the level of energy subsidies and their opportunity cost to help public debate on alternative uses of public resources (e.g., education, health, infrastructure).
- Public investment and procurement
  - Authorities have taken steps to improve the public investment framework; upgrading infrastructure quality (especially roads) is critical for diversification, climate challenges, and growth potential.
  - Public procurement represents 7 percent of GDP and 35 percent of government spending; perceptions of corruption in public procurement remain significant.
  - Recent initiatives to foster transparency and fairness include: preparation of a new public procurement law, development of fiscal risks assessments covering PPPs, and a new web-based procurement platform to foster open and transparent bidding.
  - The new procurement law introduces provisions to: allow greater access to public tenders (including by foreign enterprises); promote greater use of online procurement; focus on quality of delivered goods and services over price; and streamline and accelerate procurement processes.
- Priority improvements to public procurement
  - Generalize competitive public tenders: share of uncompetitive procurement contracts remains elevated (about a half of total contracts); QGE have separate procurement processes.
  - Address unfairness where SOEs compete with private firms; consider privatizing SOEs operating on a commercial basis.
  - Give more budget flexibility to procurement contracts to avoid delays and disruptions when economic conditions change.
  - Disclose beneficial owners of public contracts to align with best practices and support AML efforts.

### C. Fostering a Risk Management Culture
- Improving Fiscal Risks Statements (FRS) and Long-Term Fiscal Sustainability (LTFS)
  - Introduction of an FRS and LTFS in the 2023 budget is an important step toward risk-based fiscal policymaking.
  - The first FRS focuses on macro-fiscal risks; authorities intend to broaden scope to cover SOEs, PPPs and other risks.
  - The initial LTFS focuses on projections until 2050 and issues pertaining to demographic and climate changes.
  - Uses of FRS and LTFS:
    - Inform PFM reforms and incorporate macroeconomic projections in the budget process.
    - Prioritize SOE and PPP reforms.
    - Develop contingency fiscal plans in case risks materialize to reconcile stabilization role of fiscal policy and preserve fiscal space.
    - In the longer term, LTFS will help analyze management of natural resource revenues as part of transition away from fossil fuels.
- Managing fiscal risks from the SOE sector — challenges and exposures
  - SOE debt: limited information on debt held by subsidiaries of holding companies and cross-debts among subsidiaries could raise risks for SOEs and the budget.
  - Cross-SOE financial exposures: centralized cash management within holding groups can transmit liquidity or solvency pressures across entities.
  - Common risk exposures: shocks to the hydrocarbon sector may simultaneously impact several large SOE entities, potentially creating significant fiscal liabilities.
  - While privatizations would help reduce these risks, structural SOE reforms are also desirable: simplify governance structure, place some SOEs directly under supervision of one line ministry, and have the Ministry of Economy supervise cross-cutting fiscal risks.
- Taxpayer compliance and revenue administration
  - Revenue collection is affected by corruption vulnerabilities; entrepreneur perceptions of bribe requests from tax officials are above the median among emerging countries and may be concentrated in specific sectors.
  - Time to clear customs: about 9 days, placing Kazakhstan at the top of the third quartile among emerging countries.
  - Digitalization improvements by the State Revenue Committee (SRC):
    - E-invoicing has strengthened VAT collection and reduced VAT fraud opportunities.
    - One-stop shops for e-filing and e-payments improved taxpayer services.
    - Taxpayer databases enable cross-checking declarations between customs and tax, reducing tax fraud.
    - Reduced face-to-face interactions have lowered corruption vulnerabilities.
  - Movement toward risk-based revenue collection:
    - SRC modernized tax administration focusing on compliance risks with highest revenue impact.
    - New IT systems incorporate economic factors to better assess compliance risks.
    - Large Taxpayer Office (LTO) can leverage comprehensive databases to improve voluntary compliance.
    - SRC is developing risk-based tax audits.
  - The new tax code expected in 2023 should support efforts to reduce taxpayer compliance risks by streamlining tax incentives and increasing PIT progressivity to improve fairness, voluntary compliance, and revenue administration.

*Prepared by Olivier Basdevant.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2022/english/1kazea2022009.pdf_