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### Executive Summary — RA-GAP application to Estonia (2007–12)
- RA-GAP methodology applied to Estonia for 2007–12 using a top-down approach to estimate potential VAT base from statistical value-added by sector.
- Two components:
  - Estimate potential net VAT collections for a given period.
  - Determine accrued net VAT collections for that period.
- Compliance gap = potential net VAT collections − accrued net VAT collections.

### High-level findings on VAT revenue performance
- VAT revenues as a percent of GDP in Estonia have been between 8 percent and 9 percent since 2000.
- 2009 rate changes:
  - Reduced VAT rate for medicines and other products increased from 5 percent to 9 percent in January.
  - Standard rate increased from 18 percent to 20 percent in July.
- Between 2009 and 2012:
  - Nominal GDP and final consumption grew by 25 percent.
  - Actual collections increased by 23 percent.
  - Declarations increased by 16 percent.
  - Eurostat-reported actual VAT collections increased from €1,224 million to €1,508 million.
  - Declared VAT increased from €1,336 million to €1,551 million.
- Discrepancy between economic activity and VAT revenues implies a likely expansion in overall VAT compliance gap.

### Magnitude and evolution of the VAT compliance gap
- RA-GAP estimates show the VAT compliance gap increased over 2007–12, particularly during 2008–11.
- Over 2008–11:
  - The compliance gap rose by nearly 10 percentage points, almost doubling in size.
  - Losses increased by over €150 million (comparison across RA-GAP, CASE, and ETCB estimates).
- Within the overall compliance gap:
  - Assessment gap in Estonia increased from 2009–11.
  - Collections gap grew until 2009 and then decreased after 2010.
  - The decrease in the collections gap followed the introduction of automated management and sanctions of debt in 2010; the collections gap level is now low by international standards.

### Drivers and sectoral observations
- VAT compliance gap is the largest tax gap in Estonia.
- ETCB tax gap analysis indicates Missing Trader Intra-Community (MTIC) frauds are the largest contributor to the VAT compliance gap.
- ETCB evidence and bottom-up analysis show MTIC frauds increased toward 2011.
- C-efficiency:
  - Generally higher than the EU average due to broad VAT coverage, limited reduced rates, and limited exemptions.
  - Decline in c-efficiency ratio after 2008 largely explained by changes in compliance gap.
  - Decomposition: policy gap relatively constant between 2007 and 2012 while compliance gap increased and is approaching policy gap level.

### Methodological notes
- Potential VAT revenues estimated using detailed national accounts for 2007–09 (supply and use tables) and extrapolated to 2012 using published value added growth numbers by sector.
- Actual collections calculated on an accruals basis using tax returns data between 2007 and 2012 provided by ETCB, with accrued collections measured as at May 2013.
- ETCB implemented a major accounting change in 2009; RA-GAP’s accruals method should account for much disruption but timing effects could remain and may over-state the 2009 collections gap (which would under-state the assessment gap).

### Use of tax gap analysis by ETCB
- ETCB has estimated VAT and other tax compliance gaps since 2004; estimates and compliance/risk analysis used to set strategic priorities and identify risks/targets for tactical operations.
- ETCB produces comprehensive tax gap analysis for its annual Basic Strategy Analysis.
- Strategic priority: identify and prevent MTIC frauds, with improved customer service to minimize compliance burdens for compliant businesses.

### Observations and recommended follow-up actions
- Use RA-GAP’s preferred VAT gap model for potential VAT and accrued collections to improve reliability of VAT compliance gap estimates, particularly year-on-year changes.
- Conduct micro-level analysis of trends in VAT declarations and adjustments to monitor risks of taxpayer manipulation to avoid automated debt management and credit risk assessment.
- Increase use of longitudinal data analysis in risk profiles to monitor risks from ETCB’s increasing reliance on automated tax administration.
- Publish annually (nonoperationally sensitive) ETCB tax gap estimates to facilitate public debate on scale of tax compliance losses and counter-measures.
- Where insufficient quantitative data exist for a dividend tax gap estimate, consider qualitative research (structured conversations with tax experts) to determine likely scale.

### The compliance gap by sector
- Over 60 percent of VAT is collected in the wholesale and retail sector.
- Sectors with significant absolute compliance gaps:
  - Agriculture, Forestry and Fishery (sector A)
  - Construction (sector F)
  - Wholesale, Retail and Transportation Services (sectors G and H)
  - Professional Services (sector M)
- These sectors were major positive contributors to the overall compliance gap in 2009.
- RA-GAP sectoral assessments closely match ETCB’s bottom-up analysis and risk assessment.
- Note: ETCB accounting changes in 2009 may leave residual timing effects that could over-state the 2009 collections gap.

### Changes in potential VAT and actual VAT (drivers and measurement)
- Increase in compliance gap after 2009 driven by relatively weak growth of actual VAT receipts compared to potential VAT growth.
- Actual VAT as a percentage of GDP fell from 2009 to 2011, while potential VAT slightly increased.
- Decrease of collections gap: differences between declared VAT and collected VAT narrowed; new debt arising on returns and assessments has been getting smaller year by year.
- Reduction of collections gap followed automated management and sanctions of debt introduced in 2010.
- Wholesale and retail and construction sectors contributed most to growth of potential VAT due to high growth rates and relatively large ratios of potential VAT to value added produced.
- Changes in potential VAT driven primarily by economic forces rather than policy changes.
- RA-GAP treatment: measures accrued collections by reallocating receipts to the periods for which they are paid; cash values are more volatile and can distort compliance-gap trends if used.

### Comparison of RA-GAP results with other measures
- RA-GAP potential VAT estimates generally consistent with ETCB and CASE estimates due to common use of national accounts data.
- RA-GAP compliance gap estimates for 2007–09 are smoother than ETCB and CASE because the latter use cash collections with timing distortions.
- ETCB and CASE VAT gap estimates are more volatile year-to-year, especially in 2007–09, primarily due to timing effects in cash receipts.
- Compliance gap is difference between two large numbers (potential VAT and actual collections); small differences are magnified across sources.
- ETCB simplified VAT gap model (end-consumption/WAR-based) potential biases:
  1. Inconsistency between tax base and applied (average) tax rate.
  2. Timing issue: WAR for year X uses expenditure patterns for year X-2.
  3. Use of purchasers’ prices (including VAT) gives upward bias.
- Net effect of opposing biases appears relatively neutral for 2007–09 but increases uncertainty in year-on-year changes.

### Existing tax gap analysis practices at ETCB
- Intelligence Department produces tax gap analysis to underpin risk management, strategic priorities, operational performance measurement; used with Ministry of Finance for fiscal monitoring.
- Annual Basic Strategy Analysis (December) uses Intelligence Department estimates to determine strategic priorities, business plans, and performance targets.
- Bottom-up analysis identifies targets by behavior and taxpayer; examples include referral of companies declaring nonviable VAT margins for audit.
- Increasing use of ‘soft interventions’ (education visits, pre-return audits), effectiveness evaluated in tax gap terms.
- Performance of ETCB officials evaluated by observed tax gap closure using treated businesses and matching control groups.
- In 2012, VAT compliance gap accounted for about euros (EUR) 200 million of total tax gap losses of €433 million (almost half of overall tax gap).

### Further work required
- Continue complementary bottom-up tax gap analysis given scale of estimated compliance gap.
- ETCB Intelligence Department should continue investing analytical resources to monitor highest-risk taxpayers and identify new risks (VAT credit return risk assessment, anomalous subgroup identification).
- ETCB assesses organized MTIC repayment fraud as largest compliance risk; counter-measures since 2011 have reduced MTIC losses per ETCB and RA-GAP top-down estimates.
- MTIC remains endemic in European VAT regimes; Estonia’s trading patterns make it attractive to organized MTIC fraudsters; further counter measures are necessary and being introduced.

### The very low collection gap — risks and monitoring (section 33)
- Collection gap was already low—around 2–3 percent of net VAT receipts—when automated debt management and late payment sanctions were introduced in 2010.
- Measures reduced collection gap further so that it is now extremely low.
- Two potential compliance risks from very low levels of new debt:
  - Overly burdensome sanctions distorting business cash flow decisions.
  - Taxpayers may avoid sanctions by not filing returns until they can pay, or by filing nil returns and later filing adjusted returns when cash flow allows, leading to:
    - Lower filing compliance as taxpayers ‘game’ the system.
    - Lower receipts if taxpayers file lower returns and fail to file required adjustments until caught.
- Evidence and monitoring:
  - No evidence yet of large-scale abuse, but risk should be monitored.
  - ETCB introduced simplified processes for taxpayers with cash-flow problems.
  - Authorities note increase in filing of zero-returns—possible early indication.
  - Periodic monitoring needed to analyze filing behavior and upward adjustments to previously filed returns.
- RA-GAP and return adjustment findings:
  - Aggregate recent versions of returns show systematic reduction of VAT liabilities relative to originally filed returns.
  - Estonia records corrections and assessments as adjustments to filed returns.
  - ETCB found cases where taxpayers gradually reduce liabilities or increase credit claims by a series of small adjustments (“salami-slicing”) to avoid audits.
  - No evidence yet of large-scale ‘salami-slicing’ to evade risk profiling, but risk needs monitoring.
- Analytical priorities and actions:
  - Carry out tax gap and risk analysis on micro returns data.
  - Examine distribution of adjustments over time to identify persistent upward or downward adjustments and extreme cases.
  - Introduce periodic micro-level monitoring of filing and adjustment risks.
- Implications of e-filing and automation:
  - Increased reliance on e-filing and automation increases need for sophisticated risk profiling and longitudinal analysis.
  - ETCB should periodically review micro-level data for signs of manipulation (bunching around risk thresholds, precise matching to benchmarks).
- Analytical capacity and model recommendations:
  - ETCB has high quality analytical data and quantitative analysts to conduct distributional analyses.
  - ETCB should refine its VAT gap model to reduce impact of simplifying assumptions on year-on-year changes.
  - RA-GAP approach would improve reliability and diagnostic power by decomposing gaps to industrial sectors and using accrued collections.

### Appendix I — RA-GAP model and methodology (key elements preserved)
- Purpose: estimate potential tax revenues from macroeconomic data and measure compliance gap by comparing potential revenues (full compliance under current rules) to actual revenues.
- Top-down approach advantages: covers all compliance losses and allows comparison to tax expenditures; bottom-up useful for identifying drivers.
- RA-GAP preference: use sectoral value added as VAT tax base to reflect VAT determination along production chains and enable sectoral diagnostics.
- Value-added model variables (notation preserved where provided):
  - CPV_s = potential net VAT for a sector.
  - M_s^c, Y_s^c, X_s^c, N_s^c, I_s^c as imports, output, exports, intermediate demand, investment by sector s of commodity c.
  - τ_c = VAT rate that applies to commodity c (zero if zero-rated or exempt).
  - ω_s^c = proportion of input tax credits for commodity c by sector s allowed to be claimed.
  - r_s = proportion of output for a sector produced by registered businesses.
  - e_s = proportion of output for a sector which is exempt output.
- Adjustments for X and M: remove domestic consumption by nonnationals from exports and consumption abroad by nationals from imports; approximate using service categories where necessary.
- Trade sector rates: τ_trade = [∑ (τ_c × margin_c)] / [∑ margin_c].
- Accommodating complex policy structures: use sector-by-commodity tax rate matrix τ_s^c where necessary; transaction-specific treatments noted.
- Measuring actual (accrued) collections:
  - AV_s = C_s + P_s − EC_s − POEC_s.
  - Data needs: customs collections, payments received, excess credit accrued, payments offset by excess credit with date and tax-period linkages.
- Compliance gap measures:
  1. At time of filing (original filing/payment deadline).
  2. At time of estimation (latest available assessed/collection data as of selected date).
- Reporting: (CPV − AV) / CPV and also as percentages of GDP.

### Appendix II — Tax gap methods used by ETCB (highlights)
- Intelligence Department provides comprehensive tax gap analysis; outputs set operational priorities and feed Basic Strategy Analysis.
- Table of heads and model types (summarized):
  - VAT → Top down end-consumption model + bottom-up models for individual compliance risks.
  - Tobacco → Household surveys, administrative data, private sector market research.
  - Alcohol → No robust model; EIER postal survey used as indicative.
  - Customs duty → Structured risk assessment (estimated total risk c. €11 million).
  - Road fuels → Transport survey vs legal clearances; diesel gap estimated between 2½–10½ percent; gasoline gap negligible.
  - Packaging excise → Proxy-based estimate suggests gap of order 90 percent.
  - Dividends tax → No robust method found.
  - Personal income tax → Household survey and bottom-up supplements.
- VAT model caveats:
  - End-consumption WAR-based model excludes intermediate consumption in exempt and government sectors (downward bias).
  - Uses purchaser prices (including VAT) as tax base (upward bias).
  - Receipt series is cash-based and changed in 2009 (single account, earlier recognition of excess credits); 2009 receipts depressed relative to previous years.
- Tobacco duty:
  - Five independent sources estimate tobacco duty gap in range 15–30 percent; gap rose when duty rates increased in 2009.
- Alcohol duties:
  - EIER postal survey used to provide indicative bounds; alcohol duties account for about 3 percent of Estonian tax revenues.
- Packaging excise:
  - Administration difficulty; ETCB estimate indicates very large share of potential tax not paid (order of 90 percent).
- Personal income tax and social security:
  - Chief threat: envelope salaries; tax gap estimate for self-employed: €11.7 million.

### Appendix III — Factors affecting estimated compliance gaps
- Categories: (1) data issues; (2) timing issues; (3) taxpayer planning activity; (4) taxpayer compliance issues.
- Data issues:
  - National accounts generally high quality; tax return data detailed and suitable.
  - Estonia’s open economy: retail/wholesale sectors >60 percent of VAT base; imports and exports each ≈ 100 percent of GDP.
  - Allocation of imports/exports by sector relies on assumptions and limited data; affects sectoral decomposition.
- Timing factors:
  - 2009 accounting change (single account, earlier recognition of excess credits) dramatically reduced stock of carried-forward excess credits and caused processing disruption.
  - RA-GAP accrued collections should be unaffected in principle, but RA-GAP collection gap peaked in 2009 — residual timing impact possible.
- Tax planning activity:
  - Aggressive planning could exploit intra-community rate differentials; no evidence of widespread impact yet.
- Compliance factors and macro events:
  - 2004–2007 strong GDP growth; 2008 receipts dropped sharply due to crisis and cash-flow delays; 2009 receipts above forecast possibly due to firms running down inventories and payment of 2008 arrears.

### MTIC fraud, excess credits, and sectoral incidents (excerpted highlights)
- 2010: ETCB discovered serious MTIC frauds emerging in the fuels sector.
- June 2011: introduction of warrantees tripled net VAT revenues in the fuels sector; annualized implication: prior MTIC losses in fuels sector c. €100 million.
- 2011–April 2012: net VAT receipts from fuels sector fell, suggesting return of MTIC fraud; counter-measures in April 2012 produced a reasonably strong recovery but further erosion occurred since then.
- Overall compliance gap in 2012 fell, though not to 2008/2009 levels; emerging 2013 outturns indicate further revenue recovery.
- MTIC fraud also uncovered in gold and scrap metal trading; MTIC traders in fuels seen moving to Contra trading to disguise fraud.
- ETCB risk-profile test:
  - Lowest performing 10,000 VAT traders by net VAT payments and employees-to-turnover used as proxy for MTIC Contra and Buffer traders.
  - Assumption: paying VAT on 10 percent value added would yield €80 million; observed payments only €8 million → implied tax loss around €70 million.
  - Analysis supports plausibility of MTIC losses and overall compliance gap estimate of €230 million (assumption-driven).
- Excess credit claims:
  - Treated as serious MTIC risk; subject to universal risking and possible audit before release to single accounts; refunds subject to strict deadlines and audit/criminal proceedings.
- Legislative response:
  - Proposed legislation to require taxpayers to submit detailed lists of purchases and sales with monthly VAT returns to enable matching of input credits to suppliers’ output declarations.
  - Design cautions:
    - Transaction-level reporting is strong anti-MTIC measure but risks excessive compliance burden and administrative cost.
    - Not perfect defense; fraud supply chains can be manipulated.
    - ETCB intends to apply risk profiling to focus matching on higher-risk taxpayers.
    - Realistic expectation: process will help contain MTIC rather than eliminate it.

Italic: Source: REPORT: The Value-Added Tax Gap in Estonia — Executive Summary; chapter content and appendices as supplied.

### Executive Summary ......................................................................................................

### Executive Summary

### Overview of RA-GAP application to Estonia (2007–12)
- The RA-GAP methodology was applied to Estonia for the period 2007–12 using a top-down approach to estimate the potential VAT base from statistical data on value-added generated in each sector.
- Two main components of the methodology:
  - Estimate the potential net VAT collections for a given period.
  - Determine the accrued net VAT collections for that period.
- The difference between potential net VAT collections and accrued net VAT collections is the compliance gap.

### High-level findings on VAT revenue performance
- VAT revenues measured as a percent of GDP in Estonia have been between 8 percent and 9 percent since 2000.
- In 2009, the reduced VAT rate for medicines and other products was increased from 5 percent to 9 percent in January, and the standard rate was increased from 18 percent to 20 percent in July.
- Between 2009 and 2012:
  - Nominal GDP and final consumption grew by 25 percent.
  - Actual collections increased by 23 percent.
  - Declarations increased by 16 percent.
  - Eurostat-reported actual VAT collections increased from €1,224 million to €1,508 million.
  - Declared VAT increased from €1,336 million to €1,551 million.
- The discrepancy between trends in economic activity and VAT revenues indicates a likely expansion in the overall VAT compliance gap.

### Magnitude and evolution of the VAT compliance gap
- RA-GAP estimates show the VAT compliance gap increased over 2007–12, particularly during 2008–11.
- Over 2008–11, the compliance gap rose by nearly 10 percentage points, almost doubling in size.
- Over the period 2008–11, losses increased by over €150 million (as observed in comparison across RA-GAP, CASE, and ETCB estimates).
- Within the overall compliance gap:
  - The assessment gap in Estonia increased from 2009–11.
  - The collections gap grew until 2009 and then decreased after 2010.
  - The decrease in the collections gap followed the introduction of automated management and sanctions of debt in 2010; the collections gap level is now low by international standards.

### Drivers and sectoral observations
- The VAT compliance gap is the largest tax gap in Estonia.
- Estonia Tax and Customs Board (ETCB) tax gap analysis indicates Missing Trader Intra-Community (MTIC) frauds are the largest contributor to the VAT compliance gap.
- ETCB intelligence and bottom-up tax gap analysis provide evidence that MTIC frauds increased toward 2011.
- C-efficiency:
  - C-efficiency in Estonia is generally higher than the EU average due to broad VAT coverage, limited reduced rates, and limited exemptions.
  - The decline in the c-efficiency ratio after 2008 can be largely explained by changes in the compliance gap.
  - Decomposition shows a relatively constant policy gap between 2007 and 2012 while the compliance gap increased and is approaching the policy gap level.

### Methodological notes
- Potential VAT revenues were estimated using detailed national accounts data for 2007–09 (when supply and use tables are available) and extrapolated to 2012 using published value added growth numbers for each sector.
- Actual collections were calculated on an accruals basis using tax returns data between 2007 and 2012 provided by ETCB, with accrued collections measured as at May 2013.
- RA-GAP notes ETCB implemented a major accounting change in 2009; while RA-GAP’s accruals method should account for much of the disruption, timing effects could remain and may over-state the 2009 collections gap (which would under-state the assessment gap).

### Use of tax gap analysis by ETCB
- ETCB has estimated VAT and other tax compliance gaps since 2004; these estimates and associated compliance and risk analysis are used to set strategic priorities and identify risks and targets for tactical operations.
- ETCB produces a comprehensive tax gap analysis for its annual Basic Strategy Analysis covering most principal taxes in Estonia.
- ETCB strategic priority for enforcement and compliance: identify and prevent MTIC frauds, with improved customer service to minimize compliance burdens for compliant businesses.

### Observations and possible follow-up actions (recommended improvements)
- Use of RA-GAP’s preferred VAT gap model for potential VAT and accrued collections to improve reliability of VAT compliance gap estimates, particularly year-on-year changes.
- Micro-level analysis of trends in VAT declarations and adjustments to monitor potential risks of taxpayer manipulation to avoid automated debt management and credit risk assessment.
- Increased use of longitudinal data analysis in risk profiles to monitor potential risks from ETCB’s increasing reliance on automated tax administration processes.
- Annual publication of (nonoperationally sensitive) ETCB tax gap estimates to facilitate public debate on the scale of tax compliance losses and appropriate counter-measures.
- In the absence of sufficient quantitative data for a dividend tax gap estimate, ETCB might consider qualitative research (structured conversations with tax experts) to determine the likely scale of this tax gap.

*Source: REPORT: The Value-Added Tax Gap in Estonia — Executive Summary.*

### 13. The assessment gap in Estonia increased from 2009–11, while the collections

### 13. The assessment gap in Estonia increased from 2009–11, while the collections gap grew until 2009

### D. The Compliance Gap by Sector
- Over 60 percent of VAT is collected in the wholesale and retail sector.
- Sectors identified by RA-GAP as having significant compliance gaps (absolute values larger) include:
  - Agriculture, Forestry and Fishery (sector A)
  - Construction (sector F)
  - Wholesale, Retail and Transportation Services (sectors G and H)
  - Professional Services (sector M)
- These sectors were the major positive contributors to the overall compliance gap in 2009.
- RA-GAP sectoral assessments closely match ETCB’s bottom-up analysis and risk assessment.

Key statistics and figures (as presented)
- Figures referenced: Figure 7 (Compliance, Assessment and Collection Gaps, 2008–12), Figure 8 (Declared and Collected Value-Added Tax, 2008–12), Figure 9 (Compliance Gaps by Sector, 2009), Figure 10 (Compliance Gaps by Sector, 2012).

Notes
- ETCB implemented major changes to their accounting in 2009, and to their handling of excess credit returns. Although the accruals method used by RA-GAP should take into account much of the disruption from these changes, it is possible that some timing effects remain in the data and the 2009 collections gap is over-stated (which would mean that the assessment gap is under-stated).

### E. Changes in the Potential Value-Added Tax and the Actual Value-Added Tax
Findings
- The increase in the compliance gap after 2009 is the result of relatively weak growth of actual VAT receipts compared to potential VAT growth.
- Actual VAT, as a percentage of GDP, fell from 2009 to 2011, while potential VAT slightly increased.
- The decrease of collections gap means differences between declared VAT and collected VAT have become narrower; new debt arising on returns and assessments has been getting smaller year by year.
- The reduction of collections gap followed the introduction of automated management and sanctions of debt in 2010.
- Wholesale and retail sector and construction sector contributed most to growth of potential VAT during the period because of high growth rates and relatively large ratios of potential VAT to value added produced.
- Changes in potential VAT come either from changes in the economic tax base or from changes in the policy structure; in this case economic forces were the primary driver.

Methodological points and comparisons
- Potential VAT revenues after 2009 are estimated by using the growth rates of value-added in each sector due to lack of detailed supply-use tables for later years.
- An alternative is to estimate potential VAT using growth rates of demand components (assuming ratios of VAT to components are stable through time).
- Results from the demand-led approach show lower growth of potential VAT than the value-added approach, but the two series converge toward 2012.
- The value-added method is considered to give more reliable results at the sector level but may miss impacts from changes in the proportion of imports and exports; overall the value-added method’s theoretical advantages and consistency with RA-GAP justify its use.

Key statistics and figures (as presented)
- Figure 11: Potential and Actual Value-Added Tax, 2007–12 (Potential VAT and Accrued collection shown as % of GDP for 2007–12).
- Figure 12: Alternative Projections of Potential Value-Added Tax (RA-GAP [value added] vs RA-GAP [demand], million EUR, 2007–12).
- Figure 13: Accrued and Cash Collections, 2007–12.

RA-GAP treatment of collections
- RA-GAP reallocates receipts from the date on which they are paid to the periods for which they are paid (measuring accrued collections rather than cash receipts).
- In the 2008 recession, taxpayers delayed cash payments, reducing cash receipts and accumulating debt; taxpayers also ran down excess credit carry forward balances to pay current liabilities, reducing cash collections relative to accrued collections.
- Cash values show higher volatility than accrued values and can distort underlying compliance-gap trends if gaps are calculated on a cash basis.

### F. Comparison of RA-GAP Results with Other Measures
Findings
- RA-GAP estimates of potential VAT are generally consistent with estimates produced by ETCB and CASE, reflecting common use of national accounts data.
- RA-GAP estimates of the compliance gap for 2007–09 are smoother than ETCB and CASE estimates because ETCB and CASE use cash collections that introduce timing distortions.
- ETCB and CASE VAT gap estimates are more volatile year to year than RA-GAP, especially in 2007–09, primarily due to timing effects in cash receipts.
- The compliance gap is the difference between two large numbers (potential VAT and actual collections); small differences between those numbers are magnified in VAT compliance gap estimates across sources.

Key statistics and figures (as presented)
- Figure 14: Potential Value-Added Tax, 2007–12 (RA-GAP, ETCB, CASE comparison, million EUR).
- Figure 15: Value-Added Tax Gap Estimates, 2007–12 (% of potential VAT).

Assessment of ETCB simplified VAT gap model
- ETCB’s simplified model calculates potential VAT on final consumption by households and NPISH using the Weighted Average Rate (WAR) of VAT from national statistics.
Potential sources of bias in ETCB WAR-based approach:
  1. Inconsistency between tax base and applied (average) tax rate: WAR applies to a detailed classification including intermediate consumption and gross fixed capital formation by exempt sectors; applying WAR to all final consumption by households and NPISH without accounting for these items leads to biases in both directions.
  2. Timing issue: WAR for year X uses VAT rates for year X applied to expenditure patterns for year X-2; during rapid economic change this lag may bias potential VAT estimates.
  3. Use of purchasers’ prices and basic prices: ETCB uses final consumption at purchasers’ prices, which include VAT; inclusion of VAT in the tax base gives an upward bias.

- The net effect of these opposing biases appears relatively neutral for 2007–09, supporting ETCB’s use of their VAT gap model for strategic risk assessments, but the unquantified biases increase uncertainty in year-on-year changes.

### III. EXISTING TAX GAP ANALYSIS FOR ESTONIA
A. Use of Tax Gap Analysis in the Estonian Tax and Customs Board (ETCB)
- ETCB Intelligence Department produces comprehensive tax gap analysis for VAT and other taxes administered by ETCB.
- Tax gap analysis underpins ETCB risk management, strategic priorities, and operational performance measurement; it is used closely with the Ministry of Finance for fiscal monitoring.
- Annual Basic Strategy Analysis (December) uses Intelligence Department tax gap analysis to determine strategic priorities, business plans, and performance targets.
- Bottom-up tax gap analysis and risk assessments identify targets by behavior and by individual taxpayer; examples include referral of companies declaring nonviable VAT margins for audit.
- Increasing use of ‘soft interventions’ (education visits, pre-return audits), with effectiveness evaluated in tax gap terms.
- Performance of ETCB officials and operational teams is evaluated by observed tax gap closure (outcomes), with evaluation methods including monitoring tax receipts from treated businesses against matching control groups to capture direct yields and indirect deterrence/prevention effects.
- ETCB tax gap estimates are used publicly and to frame debate on tax administration and to justify counter-measures against major compliance threats.

B. Basic Strategy Analysis 2013
- The 2013 Basic Strategy Analysis contained tax gap estimates for 2007–12.
- In terms of amount of tax lost in 2012, VAT compliance gap accounted for about euros (EUR) 200 million of total tax gap losses of €433 million, i.e., almost half of the overall tax gap.
- Figure 16: Estonia Tax and Customs Board Estimated Tax Gaps 2007–12 (EUR millions, showing VAT, Social Security, Personal Income Tax, and excises for alcohol, tobacco, fuels, package excise).

### IV. FURTHER WORK REQUIRED
- Given the scale of the estimated compliance gap, complementary ‘bottom-up’ tax gap analysis is appropriate and should continue.
- ETCB Intelligence Department is already investing analytical resources to monitor highest-risk taxpayers and identify new risks through VAT credit return risk assessment and anomalous subgroup identification.
- ETCB assesses organized MTIC repayment fraud as the largest compliance risk, having caused very significant past losses; counter-measures implemented since 2011 have been successful in reducing MTIC losses according to ETCB and RA-GAP top-down estimates.
- MTIC remains endemic within European VAT regimes; Estonia’s extensive international trade and economic structure make it particularly attractive to organized MTIC fraudsters; further counter measures are necessary and are in the process of being introduced by the authorities.

*International Monetary Fund: Estonia — chapter content as supplied*

### 33. The very low level of the collection gap in Estonia creates potential compliance

### 33. The very low level of the collection gap in Estonia creates potential compliance risks that should be monitored

### Current situation and identified risks
- The collection gap in Estonia was already low—around 2–3 percent of net VAT receipts—when automated debt management and late payment sanctions were introduced in 2010.
- These measures have reduced the collection gap further so that it is now extremely low.
- Two potential compliance risks arise from the very low level of new debt:
  - The current very low levels of new debt may be a reflection of overly burdensome sanctions that are distorting business cash flow decisions.
  - Taxpayers may avoid some sanctions by not filing returns until they can afford to pay, or by filing nil returns and later filing adjusted returns when they have the cash flow to meet obligations. This incentive could lead to:
    - Lower filing compliance as taxpayers ‘game’ the system.
    - Lower receipts if taxpayers file lower returns and then fail to file necessary adjustments until caught by audit or other intervention.

### Evidence and monitoring needs
- There is not yet evidence of large scale abuse of filing and enforcement processes, but the risk should be monitored.
- ETCB has introduced simplified processes for taxpayers to manage tax payments when experiencing cash-flow problems.
- Authorities are aware of an increase in filing of zero-returns, which may be an early indication of the filing risk crystallizing.
- Periodic monitoring is needed by analyzing emerging patterns of filing behavior, particularly if taxpayers begin regularly to adjust previously filed returns upwards.

### Findings from RA-GAP and return adjustment analysis
- RA-GAP analysis of detailed VAT returns showed that, in aggregate, most recent versions of returns show a systematic reduction of VAT liabilities relative to the originally filed returns.
- In Estonia, all corrections and assessments against declared liabilities are shown in taxpayer records as adjustments to filed returns.
- ETCB have uncovered cases where taxpayers gradually reduce their liabilities (or increase their credit claims) by a series of relatively small individual adjustments. This deliberate ‘salami-slicing’ of credit adjustments is believed to be an attempt to avoid audits that would be triggered by ETCB’s risk profiles if the credit claim were made in a single amount.
- There is not yet evidence of large scale attempts to get round risk profiling through ‘salami slicing’ VAT credits, but the risk needs to be monitored.
  - Footnote: This refers to the practice of avoiding an audit of a VAT credit return or adjustment by deliberately disaggregating it into several, individually much smaller, credit claims or adjustments, typically all submitted (online) in a short time period. The assumption being made is that each individual claim or adjustment will be too small to trigger risk profile thresholds, and the thresholds are not applied to cumulative changes.

### Analytical priorities and recommended actions
- Tax gap analysis and risk analysis of taxpayer returns and adjustments need to be carried out on the micro returns data.
  - Analysis should examine the distribution of adjustments over time to identify taxpayers persistently adjusting their liabilities up or down, and extreme cases.
  - This is required because:
    - One risk: taxpayers declare less tax than due, then adjust returns upwards when cash flow allows.
    - Opposing risk: taxpayers persistently reduce declared tax liability (perhaps to the point of net credits) for one or more tax periods to avoid risk profiling.
- ETCB should introduce periodic monitoring of the filing and adjustment risks through micro-level data analysis.

### Implications of e-filing and automation for risk profiling
- Increasing reliance on e-filing and more automated payment and administration processes increases the need for sophisticated risk profiling and assessment techniques.
- Automated systems improve efficiency and customer service but increase the risk that determined evaders will manipulate returns to be just within risk profile parameters or to match benchmarks exactly.
- ETCB needs to:
  - Periodically review micro-level returns data for signs of manipulation (for example, bunching of returns around risk profile boundaries or too precise matching to benchmarks).
  - Extend risk profiles to include longitudinal analyses of persistent behavior patterns.

### Analytical capacity and model recommendations
- ETCB have the capacity to use quantitative analytical techniques to further improve their risk profiles and assessments:
  - The authority has high quality analytical data for taxpayer returns and adjustments, and quantitative analysts with the necessary skills and experience to conduct distributional analyses.
- ETCB should consider refining its VAT gap model to reduce the potential impact of its simplifying assumptions on estimated year-on-year changes to the gap.
  - The current VAT gap model is relatively quick and simple to calculate and provides a reasonable assessment of the level of the gap, but its simplified structure implicitly assumes a constant relationship between the relative contributions of individual components of the VAT base to each other over time. In times of economic change, this assumption is unsafe and can distort results.
  - The ETCB method measures collections on a cash basis, creating the risk of timing effects distorting the time series.
- The RA-GAP approach to estimating the VAT gap would improve both the reliability of ETCB’s top-down VAT gap analysis and its diagnostic power:
  - RA-GAP is more complex and requires more analytical resources than ETCB’s current VAT gap model.
  - Because RA-GAP mimics the VAT chains leading to final consumption, it enables the overall gap to be decomposed to individual industrial sectors, improving diagnostic power.
  - Comparing the Statistical Board’s estimates of economic activities used in RA-GAP potential VAT calculation with actual tax returns in sectors with large compliance gaps will provide better insights about further necessary actions.
  - Using accrued collections in place of cash receipts, the detailed form of RA-GAP reduces sensitivity to distortions from economic changes and timing effects.
  - Footnote: The simplified structure of the model is discussed further in Appendix II (below).

*International Monetary Fund — Estonia (excerpt: section 33–41).*

### Appendix I. The RA-GAP Model and Methodology

### Appendix I. The RA-GAP Model and Methodology

### A. Introduction
- Purpose: RA-GAP estimates potential tax revenues from macroeconomic data and measures the magnitude of the compliance gap by comparing potential revenues (under current tax rules with full compliance) to actual revenues.
- Approach: Top-down estimation of total compliance losses by comparing actual VAT collections to potential VAT collections estimated from macroeconomic statistics covering the whole VAT tax base.
  - Advantages of top-down:
    - Should cover all compliance losses, whether or not separately identified.
    - Results can be compared to the costs of tax expenditures and reliefs.
  - Bottom-up approaches (estimating behavioral components individually) may be used to identify drivers of the total gap.
- Sectoral breakdown: RA-GAP decomposes both potential and actual revenues by economic sector to trace trends and identify sector-specific compliance issues.
- Caveats:
  - Macro-statistics approaches have error margins due to modeling simplifications and measurement of the shadow economy.
  - Top-down estimates can overstate potential VAT because tax avoidance or legal interpretation issues that reduce revenue may be included in the compliance gap unless specifically adjusted.

### B. Estimating Potential Value-Added Tax Revenue
- Base concept: Potential tax revenue = sum over sectors/commodities of (potential tax bases × statutory tax rates).
- RA-GAP preference: Use sectoral value added (output minus input) as the VAT tax base to:
  - Reflect how VAT is determined along production chains.
  - Accommodate exemptions and multiple rates by commodity and sector.
  - Enable matching sectoral potential revenues to sectoral tax collections for identification of compliance drivers.
- Alternatives: Consumption-based approaches (e.g., final consumption or household surveys) may be preferable if data quality warrants.
- Limitations: Both value-added and consumption-based approaches are theoretically equivalent but subject to data quality constraints and potential mismeasurement.

- The value-added based potential revenues model (textual description):
  - The model estimates taxable value-added across all sectors using supply-use or input-output tables to compute potential tax on imports by sector + tax on sector output − input tax credits due to the sector.
  - Footnote: alternate structure uses final consumption plus an estimate of VAT borne by exempt businesses; both methods should yield similar results theoretically (see footnote 15).

- Potential revenues model variables (as defined in the source):
  - CPV_s = the potential net VAT for a sector (notation in source: ܸܲ௦)
  - M_s^c = imports by sector s of commodity c (ܯ௖௦)
  - Y_s^c = output by sector s of commodity c (ܻ௖௦)
  - X_s^c = exports by sector s of commodity c (ܺ௖௦)
  - N_s^c = intermediate demand (consumption) by sector s of commodity c (ܰ௖௦)
  - I_s^c = investment by sector s of commodity c (ܫ௖௦)
  - τ_c = the VAT rate that applies to commodity c (zero if zero-rated or exempt) (߬௖)
  - ω_s^c = the proportion of input tax credits for commodity c by sector s allowed to be claimed (ߟ௖௦)
  - r_s = the proportion of output for a sector produced by registered businesses (ݎ௦)
  - e_s = the proportion of output for a sector which is exempt output (݁௦)

- Data sourcing and parameter determination:
  - Y, X, M, N, I: from supply-use or input-output tables; external trade X and M require adjustments (see "Adjustments for Variables X and M").
  - τ_c: obtained from tax rate structure for each commodity (trade services handled specially). For hypothetical/reference tax structure, standard rate assigned to full vector τ_c except internationally typically exempt supplies (margin-based financial services, life insurance, residential rents).
  - ω_s^c: determined by statutory limitations on input tax credits; default value is 1. All values set to 1 for reference tax structure.
  - r_s: estimated with authorities using business licensing data or Customs transactions data (footnote 16).
  - e_s: computed as e_s = [∑_c Y_s^c · 1_{τ_c exempt}] / [∑_c Y_s^c] where 1_{τ_c exempt} distinguishes exempt commodities (footnote 17).

- Adjustments for X and M:
  - Exports must be adjusted to remove domestic consumption by nonnationals.
  - Imports must be adjusted to remove consumption abroad by nationals.
  - If supply-use tables include categories for these flows, adjustments are straightforward; otherwise approximate by removing services typically consumed at place of supply (hotel, restaurant, local transport).

- Trade sector rates:
  - For retail and wholesale trade services, a weighted average statutory rate τ_trade is determined using trade margins by commodity type:
    - τ_trade = [∑ (τ_c × margin_c)] / [∑ margin_c] (textual formula preserved).
    - Where τ_c excludes trade service commodities and margin_c are trade margins for commodity c.

- Accommodating complex policy structures:
  - Sector-specific tax rates:
    - Use a sector-by-commodity matrix of tax rates τ_s^c instead of a single commodity vector τ_c for output and input credit computations; τ_c still applies to imports.
    - e_s calculation replaced with ∑ (Y_s^c × τ_s^c_indicator) / ∑ Y_s^c, where τ_s^c_indicator is a matrix of ones/zeros indicating exempt commodity c for sector s.
  - Transaction-specific treatments:
    - Taxpayer-to-taxpayer transactions:
      - Options: split the commodity into two component commodities based on tax treatment (requires adding commodity to tables and data on transaction values), or ignore them (no net impact on overall gap; only sectoral allocation affected).
    - Taxpayer-to-final consumer transactions:
      - Adjust data side by reducing potential VAT from retail sector by external estimates of the tax expenditure cost.

### C. Measuring Actual Collections
- Goal: Measure actual tax collections from the same activities used for potential revenue estimation by reallocating cash collection data to periods when tax due actually accrued.
- Accrued collections formula (textual representation from source):
  - AV_s = C_s + P_s − EC_s − POEC_s  (notation in source: ܸܣ௦ = ܥ௦ܲ + ௦ܴ − ௦ܱܲ (with sign conventions preserved in definitions))
  - Where:
    - AV_s = accrued VAT collections for the period (ܸܣ௦)
    - C_s = collections at customs in the period (ܥ௦)
    - P_s = payments received for the period (ܲ௦)
    - EC_s = excess credit accrued for the period (ܴ௦)
    - POEC_s = payments offset by excess credit (excess credit carried forward to offset tax due, or excess credit accrued used to offset past periods) (ܱܲ௦)
- Data sources and required items:
  - Collections at customs (C_s): from customs declaration database; need VAT payment value on imports, date of entry, sector of taxpayer.
  - Payments received (P_s): from payments transaction database; need VAT payment value (exclusive of interest/penalties), date of payment, tax period payment is for, taxpayer sector.
  - Excess credit accrued (EC_s): from tax returns database; need value of excess credit, tax period for which excess credit return submitted, date of filing, taxpayer sector (footnote 20).
  - Payments offset by excess credit (POEC_s): applies where taxpayers carry excess credit forward or offset past liabilities; data from tax returns database including related tax period and sector.
- Nuances:
  - It may be necessary to compute excess credit from fundamental return line items (output tax + self-assessed import VAT − VAT on inputs) on a taxpayer-by-taxpayer basis if the reported net tax owing is not suitable (footnote 21).

### D. Measuring and Reporting the Compliance Gap
- Definition: Compliance gap = current potential collections − actual collections (CPV − AV).
- Two standardized static measures to enable comparison over time and across jurisdictions:
  1. Compliance gap at the time of filing
     - Measured at the original filing/payment deadline.
     - For accrued collections, C_s, P_s, EC_s, and POEC_s are filtered to include only payments and returns received before their deadlines.
     - Return data for EC_s and POEC_s are the data as originally submitted by taxpayers (no subsequent assessment actions).
     - This measure does not change over time and provides a baseline for voluntary compliance.
  2. Compliance gap at the time of estimation
     - Measured using the latest available data for returns filed, assessment values, collections and refunds as of a selected date (ideally annually at the anniversary of filing/payment deadline).
     - Payments P_s are filtered to select payments made by that date.
     - Return data for EC_s and POEC_s use current assessed values as of that date (may require compromise where systems do not record all change dates; maintain consistent data extraction anniversary).
     - This measure changes over time and can provide insight into tax administration collection performance.
- Reporting formats:
  - RA-GAP commonly expresses the compliance gap as a percentage of current potential revenues:
    - (CPV − AV) / CPV
  - Also expressed as percentages of GDP to provide common basis for comparison with economic activity and policy gap magnitudes.
- Note: While a raw CPV − AV number shows potential yield, expressing the gap as a proportion of CPV gives better comparative context and an indication of how much of potential revenue might reasonably be gained (footnote 25).

*Source: Appendix I. The RA-GAP Model and Methodology (as provided).*

### Appendix II. Tax Gap Methods Used by the Estonia Tax and Customs

### Appendix II. Tax Gap Methods Used by the Estonia Tax and Customs Board

### Intelligence function and overall approach
- The Intelligence Department of ETCB aims to provide comprehensive tax gap analysis for all the major taxes and categories of compliance risk in Estonia.
- Outputs are used to set operational priorities in tactical compliance risk management and are combined in the annual Basic Strategy Analysis to determine high-level business plans, targets and resource allocation.
- ETCB treats tax gap analysis as assessments or indicators of the relative scale and broad trends of compliance risks rather than precise estimates, since tax gap estimates have unknown, generally biased error terms; changes in estimated gaps are generally more reliable than levels.

### Table of tax gap model types (Head of Duty → Tax gap model)
- VAT → Top down, end-consumption model, with bottom up models for individual compliance risks
- Tobacco duty → Household survey and administrative data, plus private sector market research
- Alcohol duties → No robust model found
- Customs duty → Structured risk assessment
- Road fuels → Comparison of usage from transport survey vs legal clearances
- Packaging excise duty → Comparison of national accounts sector aggregates and tax returns
- Dividends tax → No robust method found
- Personal income tax → Household survey conducted by research agency

### Value-added tax (VAT)
- ETCB uses an end-consumption based VAT model and has estimated the Estonian VAT gap from 2004.
- Potential VAT is estimated based on end consumption by households using data from the WAR Own Resources account compiled by the Estonian Statistics Board.
- ETCB also produces bottom-up components of the total VAT gap to test the aggregate estimate and inform operational decision making; the largest component and most serious growth risk is MTIC fraud (recently Contra variants of MTIC) in the fuels sector.
- Model simplifications and biases:
  - The potential VAT model excludes intermediate consumption in the exempt and government sectors, introducing a downward bias because the tax base is under-stated.
  - The model estimates VAT due on household expenditure at purchaser prices, whereas VAT is levied on prices excluding VAT, introducing an upward bias because the tax base is over-stated.
  - The net effect of these opposing biases appears to largely cancel in the final results, making ETCB potential VAT estimates close to those of CASE and RA-GAP; however, combined biases complicate reliable estimation of underlying changes in the VAT gap.
- Receipts series issues:
  - The receipts series used is cash-based and changed in 2009 with establishment of a single account for all taxes and earlier recognition of excess credits once released to the single account.
  - The accounting change meant 2009 receipts were depressed relative to previous years all else being equal, and ETCB actively reviewed and validated outstanding excess credits, reducing unpaid carried-forward excess credits.
- ETCB tests VAT gap analysis via operational intelligence and bottom-up estimates to provide a reality check and to inform compliance strategy (e.g., use in the annual Strategic Basic Analysis).

### Tobacco duty
- ETCB compares five independent tobacco duty gap estimates:
  - Surveys of discarded cigarette packs by KPMG and AC Nielsen for Philip Morris and Japan Tobaccos (all three Baltic States).
  - Postal survey of prevalence and consumption of illicit cigarettes by the Estonian Institute for Economics Research (EIER) for ETCB.
  - ETCB’s own assessment using external research, operational intelligence and seizures.
  - Research by TNS Emor (Latvia).
- Range and comparisons:
  - The five sources estimate the tobacco duty gap to be in the range of 15–30 percent.
  - The gap rose when duty rates were increased significantly in 2009.
  - EIER estimates are systematically higher than others.
  - The ETCB estimate is broadly consistent with other estimates except for 2009 where ETCB’s estimate is notably lower.

### Alcohol duties
- Robust estimation of the alcohol duty gap is difficult due to market diversity and chronic under-reporting by consumers of illicit alcohol.
- EIER commissioned postal survey: 1,000 households estimating prevalence and consumption of illicit alcohol; lower and upper bounds obtained via respondents’ own consumption and estimates of neighbours’ consumption; an expert panel judges the likely mid-point.
- ETCB accepts the EIER estimate as ‘indicative’ and uses it in absence of alternatives.
- Note: alcohol duties as a whole account for about 3 percent of Estonian tax revenues.
- Observations:
  - EIER estimates a rising illegal market share from about 10 percent to 25 percent, but legal clearances do not reflect this decline; wine duty receipts have increased over four years.

### Customs duty
- Method: Structured assessment of potential scale of individual risks; individual risks are added to provide an upper bound estimate of total at risk.
- This approach likely overstates the total due to double-counting where risks overlap or substitute for each other.
- Estimated total risk: c. €11 million.
- Note: customs duty is collected by ETCB on behalf of the European Commission (EC).

### Road fuels duty
- Method: Transport surveys conducted by the Estonian university and vehicle registrations produce expected fuel consumption from road use, converted to excise duty amounts and compared to actual receipts; intended to include smuggled fuels and misused rebated fuels.
- ETCB believes gasoline duty gap is negligible.
- ETCB estimates diesel gap to be somewhere between 2½–10½ percent.
- Footnote observation: gasoline is typically used in noncommercial vehicles while diesel is more heavily used by road freight transporters with greater incentive to evade; gasoline’s volatility also raises handling risks for informal distribution.

### Packaging excise duty
- Duty introduced to incentivize less packaging and more recycling by taxing packaging for domestic sales and exempting suppliers in approved recycling schemes.
- ETCB finds administration, audit, and control difficult; believes duty has been successful in reducing packaging used and increasing recycling scheme take-up.
- Principal challenge: identifying the potential tax base reliably.
- Using proxies for the tax base, ETCB estimates the packaging excise duty gap to be of the order of 90 percent.
- Estonian national auditors independently estimated that a very large part of the potential tax is not being paid.

### Dividends tax
- No sufficiently reliable way was found to estimate the Estonian dividends tax gap (dividend tax takes the place of Corporation Income Tax in Estonia).
- ETCB examined proxies (e.g., car sales) but found no reliable indicators.
- Modeling such taxes is difficult due to profit shifting, transfer pricing, complexity of tax bases, and distortions in national accounts and survey data from firms’ own definitions.

### Personal income tax and social security contributions
- Top-down estimate: Economic Research Institute produces ETCB’s personal income compliance gap estimate based on a postal survey of perceptions of tax.
- Caveat: postal-survey approach captures low-level forms of tax losses (error, minor evasion) better than egregious avoidance or organized fraud; ETCB assumes the top-down estimate primarily reflects the overall scale of ‘envelope salaries’ only.
- Bottom-up supplements:
  - Regional and trade sector salary benchmarks (excluding management salaries) to test top-down analysis and identify audit cases.
  - Comparison of declared incomes of self-employed entrepreneurs with equivalent salaried workers.
  - Use of third-party information (real estate registers, stock exchange, fishing and forestry permits) to identify undeclared amounts.

### Appendix III — Factors Potentially Affecting Estimated Compliance Gaps in Estonia
- Four main categories that can affect tax gap estimates: (1) data issues; (2) timing issues; (3) taxpayer planning activity; and (4) taxpayer compliance issues.

Data issues
- Two major sources: statistical data issues or tax records issues.
- National accounts data from Estonian statistical agency is generally high standard, timely, detailed, internally consistent, and conforms to Eurostat standards.
- ETCB tax return data provided to the IMF was detailed, internally consistent, timely and in a suitable format for quantitative analysis.
- Estonia’s open trading economy and large neighbors make tax gap estimates sensitive to modeling assumptions:
  - Retail and wholesale sectors account for over 60 percent of the VAT base, unusually high and limiting information from RA-GAP sectoral decomposition.
  - Imports and exports are each equivalent to almost 100 percent of Estonia’s GDP, which is extremely high.
  - VAT treatment of imports/exports may differ from national accounts treatment (e.g., processing goods for re-export, hotel and restaurant services for foreign visitors), requiring adjustments and consistency checks between trade statistics and tax declarations.
  - Allocation of imports and exports for sector tax gaps must rely on limited data and assumptions and account for customs declarations made by agents rather than principals; these adjustments can disproportionately affect sectoral decomposition of potential VAT and VAT gap.

Timing factors
- The major timing factor identified is the 2009 accounting change:
  - Introduction of a single account consolidating liabilities and credits across Heads of Duty.
  - VAT credit returns began to be risk assessed when submitted rather than when refunds were claimed, speeding processing and automating offsetting of excess VAT credits.
  - These changes dramatically reduced the stock of carried-forward excess credits; ETCB suspended repayments for a month during changeover.
  - The RA-GAP calculation of accrued collections should be unaffected in principle, but RA-GAP collection gap peaked in 2009 without affecting overall compliance gap noticeably; a residual timing impact is possible.

Tax planning activity
- Aggressive tax planning is designed to re-characterize activity or timing and can be hard to detect in tax records.
- Potential planning in Estonia could exploit intra-community rate differentials by characterizing activities as occurring in other member states with lower rates, but no particular evidence yet of widespread impact on Estonian VAT revenues.
- Relocation of output to another country is difficult to detect via VAT returns alone; an indicator could be changes in self-assessed trade in services; no evidence yet of such arbitrage impacting VAT revenue.

Compliance factors — VAT and macro events
- Prior to 2010, changes in VAT receipts relative to GDP are largely explicable by changes in the composition of Estonia’s economy:
  - 2004–2007: strong GDP growth following EU accession, fed by strong investment, particularly in housing.
  - 2008: receipts dropped sharply partly due to the economic crisis and possibly firm cash-flow driven delayed payments and firms running down excess credit balances.
  - 2009: receipts came in above forecast; possible reasons include firms running down inventories and payment of 2008 arrears; the 2009 accounting change and disruption of excess credit refunds may have affected reported figures.

*Source: Appendix II. Tax Gap Methods Used by the Estonia Tax and Customs Board*

### 68. In 2010, ETCB discovered serious MTIC frauds emerging in the fuels sector. They

### _cr14133 - 68. In 2010, ETCB discovered serious MTIC frauds emerging in the fuels sector. They

### MTIC fraud in fuels sector — discovery, impact, and trajectory
- In 2010, ETCB discovered serious MTIC frauds emerging in the fuels sector.
- ETCB introduced warrantees as a counter measure in June 2011, and this tripled net VAT revenues in the fuels sector.
- Assuming this step increase reflected the amount of prevented MTIC repayment fraud; on an annualized basis, this suggests MTIC losses in the fuels sector were previously c. €100 million.
- From 2011 to April 2012, net VAT receipts from the fuels sector fell, suggesting the return of MTIC fraud in that sector.
- Further counter-measures taken in April 2012 led to a reasonably strong recovery but further erosion has taken place since then.
- Even so, the overall compliance gap in 2012 fell, though not to 2008/2009 levels.
- Emerging outturns for 2013 receipts indicate a further recovery of revenues.
- MTIC fraud has since been uncovered by ETCB in gold and scrap metal trading.
- In the fuels sector, ETCB have seen MTIC traders moving to Contra trading to disguise MTIC frauds.

### ETCB risk profiling and loss estimation exercise
- ETCB use risk profiles to assess the likely impact of MTIC frauds.
- To test this, ETCB used the lowest performing 10,000 VAT traders in terms of net VAT payments and number of employees relative to turnover as a proxy for MTIC Contra and Buffer traders (or companies at risk of under-declared salaries).
- Assumption applied: If these traders had paid VAT on 10 percent value added (a conservative assumption, as an offsetting bias for bias from genuinely poor performing firms caught in the sample), this sample should have produced €80 million.
- Observed outcome: they only paid €8 million, suggesting a tax loss of around €70 million.
- While heavily assumption driven, this analysis lends plausibility to the estimate of MTIC losses (and an overall compliance gap of €230 million).
- Additional context: According to figures provided by ETCB to the mission, the stock of carried forward excess credits was reduced by about €50 million in each of 2008 and 2009.

### Excess credit claims, refunds, and legislative response
- Excess credit claims are treated as potentially serious compliance (MTIC) risks by ETCB.
- Procedures:
  - Subjected to universal, systematic risking and possible audit interventions before being released to traders’ single accounts.
  - Refunds have to be made within strict deadlines, subject to audit interventions or criminal proceedings.
- Historical practice: Before 2009, excess credit claims were only checked prior to actual payment of the claimed refund.
- Legislative development: Authorities are steering new legislation through the Estonian parliament that would require VAT taxpayers to submit detailed lists of their purchases and sales transactions with their monthly VAT returns.
  - Purpose: allow ETCB to match input tax credits claimed by purchasers to corresponding output tax declarations and payments by suppliers.

### Design limits and operational cautions for transaction-level VAT reporting
- Mandating detailed VAT transaction returns is a strong anti-MTIC measure.
- Risks and limitations:
  - Creates risk of placing an excessive compliance burden on legitimate businesses and administrative burden on the ETCB.
  - Not a perfect defense—supply chains used in fraud can be manipulated to move fraudulent transactions away from obviously high risk taxpayers.
- ETCB mitigation: apply risk profiling before the data matching stage, so that they only check the higher risk taxpayers.
- Realistic expectation: the process will at best contain MTIC rather than stop it completely.

### Tobacco duty — smuggling, market effects, and revenue implications
- Illicit cigarette supply sources:
  - Smuggling across the land border with Russia.
  - Large consignments of nonduty paid cigarettes in commercial vehicles in transit to other EU countries.
  - High retail sales to day trippers on ferries from Finland.
- Household prevalence correlates:
  - Linked with unemployment and income.
  - Positively correlated with degree of householders’ personal ties with Russia (e.g., family and ancestry).
- Forestalling behaviour:
  - Until recently, manufacturers released up to 8–10 months’ sales on the market just ahead of duty rises.
  - Tobacco duty increased in 2008, entirely because of forestalling against a rise at the beginning of 2009.
- Impact of 2009 rate rise:
  - Duty-paid sales decreased by 25 percent, partly from forestalling, partly due to own-price elasticity, but mainly due to an increase in smuggling.
  - Smuggling is now thought to have stabilised, but the lost market share has not been recovered.
- ETCB assessment: the revenue maximisation point for tobacco duty has now been passed (which would mean that the duty escalator is losing money for the Estonian Exchequer).

### Alcohol duties — smuggling, misdescription, and market dynamics
- Illicit alcohol sources and issues:
  - Heavy smuggling across the land border with Russia.
  - Spirits from illegal stills and misdescribed spirits (sold as toiletries despite being drinkable).
  - Example: 60 percent spirit in typically sized spirits bottles sold as mouth wash or men’s fragrance.
  - Counterfeit stamps are now an issue.
  - Heavy smuggling from Estonia to Finland—about one-third of Finnish consumption is believed to be bought in Estonia (including Finnish brands).
- Counter-measures: heavy restrictions on personal allowances for travellers from Russia, and excise stamps.
- Market observations:
  - Illicit market prices appear pegged to duty-paid prices rather than production costs.
  - Believed inverse link between the alcohol gap and GDP, and high correlation with unemployment.
  - Negative correlation in household prevalence with distance from the Russian border.
  - ETCB believe there is a long term trend away from the informal market.
- Research note: EIER research suggests the alcohol duty gap as a percentage of potential tax has been rising at the same time as alcohol duty receipts have been increasing.
  - Possible interpretation: consumption of illicit alcohol could be independent of legitimate consumption (i.e., not substitutional), with some limited support from UK experience indicating opportunistic nonduty paid imports.

### Road fuels duty — smuggling methods and counter-measures
- Main illicit practices:
  - Diesel consignments smuggled from Russia misdescribed, abusing standard tank capacity or using forest roads outside effective customs controls.
  - Heavy use of fuels additives and the misuse of rebated, dyed fuel.
- Counter-measures:
  - Restrictions on frequent border crossings by individual vehicles.
  - Passive cameras on forest roads.
- Effect: Marked reduction in number of repeat crossings and in cross-border traffic overall.
- ETCB gap estimates show step decreases in the road fuels gaps following ETCB counter-measures over the last few years.

### Packaging excise duty — policy implications
- Given the likely scale of the packaging excise duty gap, the precise amount lost is less relevant than the fact that collections are only a small part of the potential tax base.
- Implications:
  - If the packaging duty is to have a revenue raising function, it needs to be re-designed so that it can be administered and controlled more easily.
  - If the tax was introduced primarily to reduce packaging waste, and the tax has actually reduced domestic consumption of packaging (as emerging indications suggest), then the tax is successful in that objective.
  - However, without credible administration and control there is a serious risk that suppliers will evade the tax rather than incur costs to cut down or recycle packaging.

### Personal income tax and social security contributions — envelope salaries and estimated gaps
- Chief threat: cash payments to employees (envelope salaries) not being declared for tax, particularly in sectors using casual labor (construction and hospitality).
- Tax gap estimate for self-employed people in Estonia: €11.7 million, largely from personal income tax and social security contributions.

*Italic: Source — _cr14133 (excerpt) from IMF content provided.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2014/_cr14133.pdf_