## PREFACE — mission, scope, and executive summary (content unit 1svnea2023002)

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### Mission and scope
- A capacity development (CD) mission from the IMF’s Fiscal Affairs Department (FAD) began work with the Slovenian Ministry of Finance (MOF) in January 2022 and visited Ljubljana in October 2022. The October 2022 mission was led by Mr. Eric Hutton of FAD.
- Main purpose: assist in the construction of a tax gap estimate for the Corporate Income Tax (CIT).
- Key SFA interlocutors: Peter Grum, Danuška Bobek Gospodarič, Peter Jenko, Darija Šinkovec, Tomaž Perše, Tomaž Lešnik, Marjan Macek, Dušan Šafarič, Jurij Meze, Dominik Kuzma.
- National accounts office provided data necessary for implementing the analysis.
- Support provided under the EC’s DG REFORM, coordinated by Ms. Elka Ilyova.
- Report structure: Executive Summary; (I) Background; (II) The Estimates; (III) Observations and Next Steps.

### Methodology overview
- Method: IMF RA-GAP (Revenue Administration – Gap Analysis Program) for CIT, top-down approach estimating potential tax base and liability from macroeconomic data.
- Potential CIT base and liability estimated from gross operating surplus (GOS) of non-financial corporations with adjustments for conceptual differences between GOS and the tax base/liability of CIT.
- Coverage: macroeconomic data for non-financial corporations from 2011 to 2020.
- Two approaches to measure potential CIT base:
  - Absolute method: assumes most non-compliance is related to under-declaration of income (deductible expenses declared accurately).
  - Relative method: assumes most non-compliance is from non-reporting (both incomes and expenses may not be declared accurately).
- Final compliance-gap estimate: average of absolute and relative method estimates (the two methods serve as “book ends”).

### Key procedural caveats
- Quality of macroeconomic data and tax records is crucial for estimate quality.
- The potential CIT liability is not a ‘tax capacity’ measure and does not account for behavioral changes under different policies; the model is static.
- The potential CIT base is estimated from national accounts and does not consider cross-border BEPS effects unless national accounts incorporate adjustments for these effects.
- Some assumptions required because national accounts definition of “non-financial corporations” includes some unincorporated enterprises, and tax declaration data may blend operating and capital items.

### Main findings (summary)
- Coverage and period:
  - Analysis period: 2011–2020.
- Assessed CIT and potential CIT trends:
  - Assessed CIT liabilities, measured as a percentage of GDP, dropped from "just a little below one and a half percent of GDP" in 2011 to "one percent" in 2012, and rose thereafter to "a little more than one and a half percent" by 2020.
  - Two potential-CIT estimation methods show similar trends for 2011–2016: a drop from 2011 to 2012, then a steady increase. From 2016 to 2020 the absolute method indicates more potential growth and more volatility.
  - Due to difficulties compiling an accurate measure of accrued net CIT, the report compares assessed CIT to potential CIT (assessment gap) rather than actual CIT to potential CIT (full compliance gap).
- Assessment gap (assessed vs potential):
  - Estimates indicate a possible increase in the assessment gap in 2012 and then a decline back to 2011 levels.
  - Both methods indicate a decline in the gap from 2012 to 2019; results for 2020 diverge broadly.
  - COVID-19 pandemic and related policies (including allowing deferral of CIT payments) may affect 2020 results and increase uncertainty; trends may be volatile until 2023.
- Sectoral concentration:
  - Under either method, the bulk of the assessment gap appears to be in the manufacturing sector.
  - Automotive vehicle and vehicle parts sector shows a general indication of a larger gap.
  - Margin of error for model results probably around 0.4 to 0.5 percent of GDP; sectoral gaps shown are not statistically significant but indicate possible concentration.
- Revenue performance and productivity:
  - Reported CIT collection on a net basis relative to GDP has been lower than the average for European countries for the past decade, around 2 percent of GDP for most years, with a lower level in 2012–2016 and an increase since 2017 following the CIT rate rise.
  - CIT productivity in 2019: 0.37 percent (Slovenia) versus 0.61 percent (European countries average).

### Specific policy and model notes
- CIT rate changes during 2011–2020 (as presented in source):
  - "The rate changed from 20 percent in 2011 to 19 percent in 2012, then dropped to 17 percent in 2013, before being increased back to 19 percent in 2017."
  - Elsewhere the source states: "For 2012 the rate was 18 percent, and it was 20 percent in 2011." (Both statements preserved as presented.)
- Other CIT policy features summarized:
  - Coverage: Legal entities carrying out business in Slovenia are liable to CIT; residents taxed on worldwide income; non-residents taxed on Slovenia-source income.
  - Tax base: Taxable income determined from financial accounting profit/loss with adjustments for permanent and temporary differences; taxable capital gains added.
  - Exemptions: No exemptions; all legal entities liable to CIT.
  - Losses: Tax losses may be carried forward; carryback not allowed; restrictions for change in ownership apply.
  - Threshold: No quantitative threshold for registration.
  - Tax period: Depends on company financial year end; for most companies aligns with calendar year.
  - Advance payments: Monthly advance payments based on a preliminary tax assessment.

### Comments on findings and data limitations
- Significant assumptions necessary for RA-GAP estimation; estimates should be interpreted with caution.
- Mismatches:
  - National accounts “non-financial corporations” includes some unincorporated enterprises, causing imperfect match to CIT base.
  - Tax declaration data do not fully distinguish operating revenues/costs and other revenues/costs; some declaration lines may blend operating and capital costs.
- Uncertainty:
  - 2020 national accounts estimates and taxpayer behavior may have higher margins of error due to COVID-19 disruptions and policy measures (including payment deferrals).

### Work needed to enhance CIT gap estimation (recommendations)
- Improve statistical detail:
  - Obtain GOS data at more detailed sector-of-activity level to improve sectoral estimates of potential and actual bases.
  - Acquire information on the proportion of GOS from non-corporate income tax filers to better estimate the potential base.
- Improve classification:
  - Obtain feedback on classification by Statistics Sweden of business activity codes and institutional sector codes; relative-method estimates are biased upwards due to classification differences.
- Better account for arrears:
  - Improve accounting of accrued tax arrears; simple allocation assumptions could be applied to address this.
- Complement top-down with bottom-up:
  - A bottom-up approach using random/operational audits is recommended to complement the top-down RA-GAP results.
  - Fund staff are producing a bottom-up estimate and analyzing operational data; results will be provided in a follow-up report.
- Use combined evidence:
  - Use both top-down and bottom-up estimates, combined with internal knowledge and operational information, to strengthen compliance risk management.

### GOS gap: definition, trends, and sector concentration
- Definition:
  - The GOS gap = potential GOS (national accounts) − assessed GOS (tax declarations).
  - GOS measures are the foundation for compliance gap estimates; assumption of strong relationship between CIT tax base and GOS.
- Trends (non-financial corporations):
  - GOS gap appears to have declined slightly over the period, as a percent of GDP and as a percent of potential, before a sharp uptick in 2020.
  - Notable decrease from 2013 to 2016; returned to 2013 levels before declining again; uptick in 2020 reflects divergence between assessed and potential GOS during volatile economic changes.
  - GOS gap presented as percent of GDP and percent of potential for 2011–2020.
- Sector concentration:
  - Largely concentrated in manufacturing, with significant contributions from Trade.
  - Particularly concentrated in manufacture sector for motor vehicles and motor vehicle parts (sector code C5).
  - Negative gap in utilities sector (D-E) could be due to misclassification of taxpayers; recommendation to compare revenue authority and national accounts classification.

### Assessed vs Potential CIT and the assessment gap
- Accrued collections not available; assessed CIT used for comparison against potential CIT.
  - Collections compiled on year of collection basis, not true accruals; review of arrears indicates accrual values do not differ significantly from assessed revenue values.
- Assessed CIT for non-financial corporations: overall increasing trend.
- Potential CIT trends:
  - Relative method: relatively flatter up to 2017; generally more volatile series.
  - Absolute method: indicates bigger potential growth after 2017 and shows a spike in 2020.
- Sectoral findings:
  - Sector C5 (vehicles, vehicle parts, other manufacturing) should be producing more revenue than is being assessed — very little assessed CIT from that sector despite economic significance.
  - Assessed CIT here is significantly less than values for CIT collections referenced elsewhere because this analysis concerns assessed CIT for non-financial corporations only.

### Compliance gap definitions and trends
- Definitions:
  - Collection gap = difference between assessed and actual CIT.
  - Assessment gap = difference between assessed and potential CIT.
- Findings:
  - Assessment gap appears to have been falling overall.
  - Both methods show a jump in the gap in 2012 and a roughly declining trend over 2012–2019.
  - 2020 divergence:
    - Absolute method: spike in 2020.
    - Relative method: dip in 2020.
  - 2020 divergence likely distorted by COVID-19 and related policies (e.g., deferment for CIT payments).
  - As a percent of potential, the gap looks to have recovered from the spike it saw in 2012.
- Sectoral composition mirrors GOS gap: dominance in C5 and G; negative gap in D-E likely due to misclassification.
- As a percent of GDP, no single sector at this level of aggregation reaches at least 0.5 percent of GDP; aggregating manufacturing would meet that threshold.

### Observations and next steps
- Observations:
  - Assumptions needed for RA-GAP estimation; interpret CIT gap estimates with caution.
  - National accounts definition of non-financial corporations includes some unincorporated enterprises; imperfect match to CIT base affects level and trend in gap estimates.
  - Recommended cross-check of top-down estimates with bottom-up estimate; bottom-up work underway.
- Next steps (actions necessary to improve current estimates):
  - Obtain more information on the value in national accounts GOS for non-financial corporations coming from entities not required to file or pay CIT.
  - Obtain a more detailed and current breakdown of GOS for non-financial corporations by sector of economic activity.
  - Reconcile sector codes used for tax purposes with national accounts sector codes.
  - Attempt to construct a measure of either accrued CIT or accrued CIT arrears.
  - SFA should work towards making annual updates to the CIT gap estimates to track movements in compliance and inform resource allocation.

### Key data series (selected tables and exact figures from Appendix I)
- Assessed CIT, Potential CIT (relative method), Potential CIT (absolute method) by year:
  - 2011: 1.36, 1.32, 1.78
  - 2012: 0.99, 1.22, 1.40
  - 2013: 1.02, 1.26, 1.45
  - 2014: 1.10, 1.35, 1.52
  - 2015: 1.18, 1.37, 1.57
  - 2016: 1.30, 1.42, 1.62
  - 2017: 1.52, 1.68, 1.94
  - 2018: 1.60, 1.65, 2.06
  - 2019: 1.58, 1.61, 1.93
  - 2020: 1.63, 1.56, 2.26

- Assessment gap (Absolute Method percent of potential, Relative Method percent of potential, Average Result percent of potential; Absolute Method percent of GDP, Relative Method percent of GDP, Average Result percent of GDP) by year:
  - 2011: 23.41, -2.84, 12.21; 0.42, -0.04, 0.19
  - 2012: 28.97, 18.72, 24.19; 0.41, 0.23, 0.32
  - 2013: 29.57, 18.86, 24.59; 0.43, 0.24, 0.33
  - 2014: 27.79, 18.80, 23.56; 0.42, 0.25, 0.34
  - 2015: 24.76, 13.66, 19.59; 0.39, 0.19, 0.29
  - 2016: 19.98, 8.49, 14.62; 0.32, 0.12, 0.22
  - 2017: 21.71, 9.88, 16.21; 0.42, 0.17, 0.29
  - 2018: 22.23, 3.12, 13.72; 0.46, 0.05, 0.25
  - 2019: 18.32, 2.01, 10.91; 0.35, 0.03, 0.19
  - 2020: 27.96, -4.77, 14.62; 0.63, -0.07, 0.28

- CIT to GDP: Slovenia, European countries average, and CIT Rate by year:
  - 2011: 1.65, 2.53, 20
  - 2012: 1.23, 2.61, 18
  - 2013: 1.19, 2.65, 17
  - 2014: 1.40, 2.63, 17
  - 2015: 1.46, 2.63, 17
  - 2016: 1.59, 2.72, 17
  - 2017: 1.78, 2.84, 19
  - 2018: 1.93, 2.91, 19
  - 2019: 1.96, 2.89, 19
  - 2020: 1.99, 2.44, 19
  - 2021: 2.47, 2.96, 19

- CIT Productivity (Slovenia) and Regional Average by year:
  - 2011: 0.33, 0.57
  - 2012: 0.22, 0.59
  - 2013: 0.20, 0.61
  - 2014: 0.24, 0.59
  - 2015: 0.25, 0.57
  - 2016: 0.27, 0.60
  - 2017: 0.34, 0.61
  - 2018: 0.37, 0.62
  - 2019: 0.37, 0.61
  - 2020: 0.38, 0.50
  - 2021: 0.47, 0.61

- GOS, assessed and potential, GOS gap (percent of GDP and percent of potential) by year:
  - 2011: Assessed GOS 13.9, Potential GOS 16.7, GOS Gap 2.1, GOS Gap percent of Potential 13.0
  - 2012: 14.1, 17.1, 2.3, 13.7
  - 2013: 14.7, 17.9, 2.5, 14.7
  - 2014: 15.3, 18.5, 2.5, 14.0
  - 2015: 15.4, 18.3, 2.3, 13.0
  - 2016: 15.6, 18.2, 1.9, 10.9
  - 2017: 16.1, 19.0, 2.2, 12.1
  - 2018: 15.7, 18.7, 2.4, 13.3
  - 2019: 16.0, 18.5, 1.9, 10.4
  - 2020: 15.4, 19.4, 3.3, 17.8

- GOS gap percent of GDP by selected sector (C2, C5, G) across 2011–2020 (selected values):
  - C2: 2011 0.1, 2012 0.1, 2013 0.2, 2014 0.1, 2015 0.2, 2016 0.0, 2017 0.0, 2018 0.1, 2019 0.2, 2020 0.4
  - C5: 2011 1.3, 2012 1.4, 2013 1.5, 2014 1.3, 2015 1.1, 2016 1.1, 2017 1.1, 2018 1.0, 2019 1.0, 2020 1.1
  - G: 2011 0.5, 2012 0.5, 2013 0.7, 2014 0.7, 2015 0.8, 2016 0.9, 2017 0.9, 2018 1.0, 2019 0.5, 2020 0.9

### Method and model (Appendix II)
- RA-GAP top-down framework:
  - Starting point: Gross operating surplus (GOS) of corporations in national accounts used to estimate potential CIT base.
  - Three CIT base concepts used: Current-year net tax base (C-NTB), Current-year tax base (C-TB), Tax base (TB).
  - Conceptual adjustments classified into D1, D2, D3:
    - [D1] differences between GOS and aggregate financial accounting profit (FAP).
    - [D2] differences between aggregate FAP and aggregate current year net tax base (C-NTB).
    - [D3] differences between aggregate C-NTB and aggregate tax base (TB) due to losses and carry-over losses.
  - Sequence: Adjust P-GOS by D1, D2, D3 to estimate potential FAP, potential C-NTB, potential C-TB, potential TB; apply statutory CIT rate and tax credits/additional liabilities to derive potential CIT.
- Scope limitations:
  - Estimates limited to non-financial corporations; financial corporations excluded.
  - Top-down estimates do not attempt to measure tax avoidance or BEPS directly; BEPS captured in national accounts are within scope but profit shifting that reallocates national income across countries is not separately measured.
- Two-method practical strategy:
  - Absolute method (P-TBabs):
    - P-TBabs = P-GOS − (A-GOS − A-TB); uses taxpayer declarations for D1–D3 adjustments; provides an upper limit for compliance gap.
  - Relative method (P-TBrel):
    - Uses ratio of Assessed Current-year Tax Base to Assessed GOS for compliant taxpayers and applies that ratio to P-GOS; assumes compliant taxpayers are representative; P-TBrel adjusted for carried-over losses and deferred profit adjustments.
  - Potential CIT derived by applying statutory CIT rate to P-TB (P-CITabs, P-CITrel); assessment gap = P-CIT − Assessed CIT (A-CIT).
- Interpretive notes:
  - Absolute method tends to be upper bound for assessment gap.
  - Relative method relies on representativeness of compliant taxpayers.
  - Financial corporations excluded.
  - RA-GAP top-down estimates do not separately quantify BEPS or legal profit shifting that reassigns national income across countries.

*IMF Fiscal Affairs Department — PREFACE and Executive Summary (content unit 1svnea2023002)*

### PREFACE ___________________________________________________________________________________________________ 6

### PREFACE

### Preface: mission and scope
- A capacity development (CD) mission from the IMF’s Fiscal Affairs Department (FAD) began work with the Slovenian Ministry of Finance (MOF) in January 2022 and visited Ljubljana in October 2022. The October 2022 mission was led by Mr. Eric Hutton of FAD.
- The mission’s main purpose was to assist in the construction of a tax gap estimate for the Corporate Income Tax (CIT).
- Key SFA interlocutors included: Peter Grum, Danuška Bobek Gospodarič, Peter Jenko, Darija Šinkovec, Tomaž Perše, Tomaž Lešnik, Marjan Macek, Dušan Šafarič, Jurij Meze, and Dominik Kuzma.
- The Slovenian National Accounts office provided data necessary for implementing the analysis.
- Support was provided under the EC’s DG REFORM, with coordination by Ms. Elka Ilyova.
- Report structure: Executive Summary; (I) Background; (II) The Estimates; (III) Observations and Next Steps.

### Methodology overview
- The analysis applies the IMF RA-GAP (Revenue Administration – Gap Analysis Program) methodology for CIT, following a top-down approach that estimates potential tax base and liability from macroeconomic data.
- The potential CIT base and liability were estimated from gross operating surplus (GOS) of non-financial corporations with adjustments for conceptual differences between GOS and the tax base/liability of CIT.
- The RA-GAP approach was applied to available macroeconomic data for non-financial corporations from 2011 to 2020.
- Two approaches to measure potential CIT base:
  - Absolute method: assumes most non-compliance is related to under-declaration of income, so deductible expenses are declared accurately.
  - Relative method: assumes most non-compliance is from non-reporting, so both incomes and expenses may not be declared accurately.
- Final estimate for the compliance gap is produced by averaging the estimates from the absolute and relative methods (the two methods serve as “book ends”).

### Key procedural caveats
- The quality of macroeconomic data and tax records is crucial for estimate quality.
- The potential CIT liability here is not a ‘tax capacity’ measure and does not account for behavioral changes under different policies; the model is static.
- The potential CIT base is estimated from national accounts and does not consider cross-border BEPS effects unless national accounts incorporate adjustments for these effects.
- Some assumptions were required because the national accounts definition of “non-financial corporations” includes some unincorporated enterprises, and tax declaration data may blend operating and capital items.

### Main findings (summary)
- Coverage and period:
  - Analysis period: 2011–2020.
- Assessed CIT and potential CIT trends:
  - Assessed CIT liabilities, measured as a percentage of GDP, dropped from "just a little below one and a half percent of GDP" in 2011 to "one percent" in 2012, and rose thereafter to "a little more than one and a half percent" by 2020.
  - The two potential-CIT estimation methods show similar trends for 2011–2016: a drop from 2011 to 2012, then a steady increase. From 2016 to 2020 the absolute method indicates more potential growth and more volatility.
  - Because of difficulties compiling an accurate measure of accrued net CIT, the report compares assessed CIT to potential CIT (estimating the assessment gap) rather than actual CIT to potential CIT (full compliance gap).
- Assessment gap (assessed vs potential):
  - Estimates indicate a possible increase in the assessment gap in 2012 and then a decline back to 2011 levels.
  - Both methods indicate a decline in the gap from 2012 to 2019; results for 2020 diverge broadly.
  - The COVID-19 pandemic and related policies (including allowing deferral of CIT payments) may affect 2020 results and increase uncertainty; trends may be volatile until 2023.
- Sectoral concentration:
  - Under either method, the bulk of the assessment gap appears to be in the manufacturing sector.
  - In particular, the automotive vehicle and vehicle parts sector shows a general indication of a larger gap.
  - The margin of error for model results is probably around 0.4 to 0.5 percent of GDP, so sectoral gaps shown are not statistically significant but indicate possible concentration.
- Revenue performance and productivity:
  - Reported CIT collection on a net basis relative to GDP has been lower than the average for European countries for the past decade, around 2 percent of GDP for most years, with a lower level in 2012–2016 and an increase since 2017 following the CIT rate rise.
  - CIT productivity in 2019: 0.37 percent (Slovenia) versus 0.61 percent (European countries average).

### Specific policy and model notes
- CIT rate changes during 2011–2020:
  - The report states: "The rate changed from 20 percent in 2011 to 19 percent in 2012, then dropped to 17 percent in 2013, before being increased back to 19 percent in 2017."
  - The report also states elsewhere: "For 2012 the rate was 18 percent, and it was 20 percent in 2011." (Both statements preserved as presented in source.)
- Other CIT policy features summarized:
  - Coverage: Legal entities carrying out business in Slovenia are liable to CIT; residents taxed on worldwide income; non-residents taxed on Slovenia-source income.
  - Tax base: Taxable income determined from financial accounting profit/loss with adjustments for permanent and temporary differences; taxable capital gains added.
  - Exemptions: No exemptions; all legal entities liable to CIT.
  - Losses: Tax losses may be carried forward; carryback not allowed; restrictions for change in ownership apply.
  - Threshold: No quantitative threshold for registration.
  - Tax period: Depends on company financial year end; for most companies aligns with calendar year.
  - Advance payments: Monthly advance payments based on a preliminary tax assessment.

### Comments on findings and data limitations
- Significant assumptions were necessary for RA-GAP estimation; estimates should be interpreted with caution.
- Mismatches:
  - National accounts “non-financial corporations” includes some unincorporated enterprises, causing imperfect match to CIT base.
  - Tax declaration data do not fully distinguish operating revenues/costs and other revenues/costs; some declaration lines may blend operating and capital costs.
- Uncertainty:
  - 2020 national accounts estimates and taxpayer behavior may have higher margins of error due to COVID-19 disruptions and policy measures (including payment deferrals).

### Work needed to enhance CIT gap estimation (recommendations)
- Improve statistical detail:
  - Obtain GOS data at more detailed sector-of-activity level to improve sectoral estimates of potential and actual bases.
  - Acquire information on the proportion of GOS from non-corporate income tax filers to better estimate the potential base.
- Improve classification:
  - Obtain feedback on classification by Statistics Sweden of business activity codes and institutional sector codes; relative-method estimates are biased upwards due to classification differences.
- Better account for arrears:
  - Improve accounting of accrued tax arrears; simple allocation assumptions could be applied to address this.
- Complement top-down with bottom-up:
  - A bottom-up approach using random/operational audits is recommended to complement the top-down RA-GAP results.
  - Work is underway by Fund staff to produce a bottom-up estimate and to analyze operational data; results will be provided in a follow-up report.
- Use combined evidence:
  - It is recommended to use both top-down and bottom-up estimates, combined with internal knowledge and operational information, to strengthen compliance risk management in the tax administration.

*IMF Fiscal Affairs Department — PREFACE and Executive Summary (content unit 1svnea2023002)*

### 7. The GOS  gap is the difference  between the potential GOS, derived  from national

### 7. The GOS gap is the difference between the potential GOS, derived from national accounts, and the assessed GOS, derived from the tax declarations

### Definition and relationship to CIT
- The GOS gap is the difference between the potential GOS, derived from national accounts, and the assessed GOS, derived from the tax declarations.
- The concept and measures of GOS are the foundation upon which the compliance gap estimates are built.
- The underlying assumption is that there is a strong relationship between the CIT tax base and GOS.
- Given this relationship, the trends and levels in the GOS are an important indicator of what might be influencing the trends and levels of the compliance gap.

### Trends in the GOS gap (non-financial corporations)
- The GOS gap, for non-financial corporations, appears to have declined slightly over the period, as a percent of GDP and as a percent of potential before a sharp uptick in 2020.
- The decline has not been smooth:
  - Notable decrease from 2013 to 2016.
  - The gap then appears to have returned to its 2013 levels before declining again.
  - The uptick in 2020 is the result of a divergence in the trend in the assessed GOS and the potential GOS, which may be an artifact of the volatile changes in the nature of many economic activities during this period.
- The GOS gap is presented in the source as:
  - percent of GDP and percent of potential (figures and series spanning 2011–2020).

### Sector concentration of the GOS gap
- The GOS gap appears to be largely concentrated in the manufacturing sector, with significant contributions from the Trade sector.
- Particularly concentrated in manufacture sector for motor vehicles and motor vehicle parts (sector code C5).
- A negative gap in the utilities sector (sector code “D-E”) could be due to misclassification of taxpayers; a comparison of classification used by the revenue authority and national accounts codes should be conducted.

### Assessed vs Potential CIT
- Comparing actual CIT to potential CIT can indicate whether changes in the compliance gap arise from changes in declared/paid tax or from changes in measured economic activity.
- Values for accrued collections of CIT were not available; assessed CIT is used instead for comparison against potential CIT.
  - Collections could only be compiled on a year of collection basis, not a true accruals basis.
  - A review of arrears data indicates that the accrual values do not differ significantly from the assessed revenue values.
- Assessed CIT for non-financial corporations exhibits an overall increasing trend for the period.
- Potential CIT trends:
  - Relative method: relatively flatter up to 2017; generally more volatile series.
  - Absolute method: indicates bigger potential growth after 2017 and shows a spike in 2020.
- Both potential CIT methods show that sector C5 (vehicles, vehicle parts, other manufacturing) should be producing more revenue than is being assessed — very little assessed CIT from that sector despite its economic significance.
- The assessed CIT shown is significantly less than values for CIT collections reviewed elsewhere because the analysis here concerns assessed CIT for non-financial corporations only (collections data referenced elsewhere are for all corporations).

### The Compliance Gap (assessment gap vs collection gap)
- Without data for accrued revenue or accrued arrears, the full compliance gap cannot be estimated; only the assessment gap can be estimated.
- Definitions:
  - Collection gap = difference between assessed and actual CIT.
  - Assessment gap = difference between assessed and potential CIT.
- The assessment gap appears to have been falling overall:
  - Both methods show a jump in the gap in 2012 and a roughly declining trend over 2012–2019.
  - For 2020 there is a stark difference:
    - Absolute method: spike in 2020.
    - Relative method: dip in 2020.
  - The 2020 divergence is likely distorted by unprecedented shifts in economic activity and COVID-19 related policies (e.g., allowing for a deferment for CIT payments).
  - As a percent of potential, the gap looks to have recovered from the spike it saw in 2012.
- Sectoral composition of the assessment gap mirrors the GOS gap:
  - Dominance in sectors C5 (motor vehicle and motor vehicle parts manufacturing) and G (wholesale and retail trade).
  - Negative gap in D-E sector (electricity, water, and other public utilities), likely due to taxpayer misclassification.
  - As a percent of GDP, no single sector at this level of aggregation reaches at least 0.5 percent of GDP; aggregating manufacturing would meet that threshold.

### Observations
- Some assumptions were needed to enable the RA-GAP estimation of potential CIT base and liability; therefore, CIT gap estimates should be interpreted with caution.
- The definition for “non-financial corporations” used in national accounts includes some unincorporated enterprises, so there is not a perfect match to the corporate income tax base. Some assumptions had to be made as to the impact of these differences, which may be affecting both the level and trend in the resulting gap estimates.
- It is recommended that the top-down estimates be cross-checked against a bottom-up based estimate of the tax gap. Work is underway to produce this bottom-up based estimate; the results will be provided in a follow-up report.

### Next steps (actions necessary to improve current estimates)
- Obtain more information on the value in the national accounts GOS for non-financial corporations which is coming from entities not required to file or pay CIT.
- Obtain a more detailed and current breakdown of GOS for non-financial corporations by sector of economic activity.
- Reconcile the sector codes for the main sector of activity being used for tax purposes with the codes being assigned for national accounts purposes.
- Attempt to construct a measure of either accrued CIT or accrued CIT arrears.
- Going forward, the SFA should be working towards making annual updates to the CIT gap estimates to track movements in compliance and inform resource allocation to manage compliance risks.

*Source: Staff calculations based on data from MOF and Slovenia National Accounts*

### Appendix I. Data Tables for Included Figures

### Appendix I. Data Tables for Included Figures

### Key Data Series: Assessed and Potential CIT (Table 1, Table 11)
- Assessed CIT, Potential CIT (relative method), Potential CIT (absolute method) by year:
  - 2011: 1.36, 1.32, 1.78
  - 2012: 0.99, 1.22, 1.40
  - 2013: 1.02, 1.26, 1.45
  - 2014: 1.10, 1.35, 1.52
  - 2015: 1.18, 1.37, 1.57
  - 2016: 1.30, 1.42, 1.62
  - 2017: 1.52, 1.68, 1.94
  - 2018: 1.60, 1.65, 2.06
  - 2019: 1.58, 1.61, 1.93
  - 2020: 1.63, 1.56, 2.26

### Assessment Gap: Percent of Potential and Percent of GDP (Table 2, Table 14)
- Assessment gap (Absolute Method percent of potential, Relative Method percent of potential, Average Result percent of potential; Absolute Method percent of GDP, Relative Method percent of GDP, Average Result percent of GDP) by year:
  - 2011: 23.41, -2.84, 12.21; 0.42, -0.04, 0.19
  - 2012: 28.97, 18.72, 24.19; 0.41, 0.23, 0.32
  - 2013: 29.57, 18.86, 24.59; 0.43, 0.24, 0.33
  - 2014: 27.79, 18.80, 23.56; 0.42, 0.25, 0.34
  - 2015: 24.76, 13.66, 19.59; 0.39, 0.19, 0.29
  - 2016: 19.98, 8.49, 14.62; 0.32, 0.12, 0.22
  - 2017: 21.71, 9.88, 16.21; 0.42, 0.17, 0.29
  - 2018: 22.23, 3.12, 13.72; 0.46, 0.05, 0.25
  - 2019: 18.32, 2.01, 10.91; 0.35, 0.03, 0.19
  - 2020: 27.96, -4.77, 14.62; 0.63, -0.07, 0.28

### CIT Revenue to GDP: Slovenia and Regional Comparison (Table 4, Table 5)
- Slovenia: CIT to GDP by year and European countries average (CIT Rate):
  - 2011: 1.65, 2.53, 20
  - 2012: 1.23, 2.61, 18
  - 2013: 1.19, 2.65, 17
  - 2014: 1.40, 2.63, 17
  - 2015: 1.46, 2.63, 17
  - 2016: 1.59, 2.72, 17
  - 2017: 1.78, 2.84, 19
  - 2018: 1.93, 2.91, 19
  - 2019: 1.96, 2.89, 19
  - 2020: 1.99, 2.44, 19
  - 2021: 2.47, 2.96, 19
- CIT to GDP, Region Average, selected countries (2019, Table 5):
  - Norway: 6.02, 2.89
  - Cyprus: 5.67, 2.89
  - Malta: 5.50, 2.89
  - Belgium: 3.71, 2.89
  - Luxembourg: 6.06, 2.89
  - Netherlands: 3.69, 2.89
  - Ireland: 3.08, 2.89
  - Slovak Republic: 3.06, 2.89
  - Portugal: 3.12, 2.89
  - Sweden: 3.14, 2.89
  - Denmark: 3.15, 2.89
  - Austria: 2.76, 2.89
  - United Kingdom: 2.27, 2.89
  - France: 2.82, 2.89
  - Spain: 2.07, 2.89
  - Czech Republic: 3.32, 2.89
  - Croatia: 2.30, 2.89
  - Bulgaria: 2.30, 2.89
  - Greece: 2.22, 2.89
  - Romania: 2.10, 2.89
  - Slovenia: 1.96, 2.89
  - Italy: 1.95, 2.89
  - Finland: 2.53, 2.89
  - Poland: 2.21, 2.89
  - Lithuania: 1.55, 2.89
  - Hungary: 1.14, 2.89
  - Germany: 2.65, 2.89
  - Estonia: 1.83, 2.89

### CIT Productivity: Slovenia and Regional Average (Table 6, Table 8)
- CIT Productivity (Slovenia), Regional Average by year:
  - 2011: 0.33, 0.57
  - 2012: 0.22, 0.59
  - 2013: 0.20, 0.61
  - 2014: 0.24, 0.59
  - 2015: 0.25, 0.57
  - 2016: 0.27, 0.60
  - 2017: 0.34, 0.61
  - 2018: 0.37, 0.62
  - 2019: 0.37, 0.61
  - 2020: 0.38, 0.50
  - 2021: 0.47, 0.61
- CIT Productivity (2019) selected countries, Region Avg 0.61 (Table 8):
  - Norway: 1.32, 0.61
  - Cyprus: 0.71, 0.61
  - Malta: 1.93, 0.61
  - Belgium: 1.08, 0.61
  - Luxembourg: 1.51, 0.61
  - Netherlands: 0.92, 0.61
  - Ireland: 0.39, 0.61
  - Slovak Republic: 0.64, 0.61
  - Portugal: 0.65, 0.61
  - Sweden: 0.67, 0.61
  - Denmark: 0.69, 0.61
  - Austria: 0.69, 0.61
  - United Kingdom: 0.43, 0.61
  - France: 0.87, 0.61
  - Spain: 0.52, 0.61
  - Czech Republic: 0.63, 0.61
  - Croatia: 0.41, 0.61
  - Bulgaria: 0.23, 0.61
  - Greece: 0.62, 0.61
  - Romania: 0.34, 0.61
  - Slovenia: 0.37, 0.61
  - Italy: 0.47, 0.61
  - Finland: 0.51, 0.61
  - Poland: 0.42, 0.61
  - Lithuania: 0.23, 0.61
  - Hungary: 0.10, 0.61
  - Germany: 0.79, 0.61
  - Estonia: 0.37, 0.61

### Gross Operating Surplus (GOS) and GOS Gap (Table 9, Table 10)
- Assessed GOS, Potential GOS, GOS Gap (percent of GDP), GOS Gap (percent of Potential) by year:
  - 2011: 13.9, 16.7, 2.1, 13.0
  - 2012: 14.1, 17.1, 2.3, 13.7
  - 2013: 14.7, 17.9, 2.5, 14.7
  - 2014: 15.3, 18.5, 2.5, 14.0
  - 2015: 15.4, 18.3, 2.3, 13.0
  - 2016: 15.6, 18.2, 1.9, 10.9
  - 2017: 16.1, 19.0, 2.2, 12.1
  - 2018: 15.7, 18.7, 2.4, 13.3
  - 2019: 16.0, 18.5, 1.9, 10.4
  - 2020: 15.4, 19.4, 3.3, 17.8

- GOS gap percent of GDP by sector (selected sectors, Table 10):
  - C2: 2011 0.1, 2012 0.1, 2013 0.2, 2014 0.1, 2015 0.2, 2016 0.0, 2017 0.0, 2018 0.1, 2019 0.2, 2020 0.4
  - C5: 2011 1.3, 2012 1.4, 2013 1.5, 2014 1.3, 2015 1.1, 2016 1.1, 2017 1.1, 2018 1.0, 2019 1.0, 2020 1.1
  - G: 2011 0.5, 2012 0.5, 2013 0.7, 2014 0.7, 2015 0.8, 2016 0.9, 2017 0.9, 2018 1.0, 2019 0.5, 2020 0.9
  - (Negative gaps presented for D-E, F, H, I in table)

### Assessed and Potential CIT by Sector (Table 12, Table 13)
- Assessed CIT percent of GOS, Potential CIT absolute method percent of GOS, Potential CIT relative method percent of GOS are reported by sector code for 2011–2020. (Detailed sectoral tables provided in source tables.)

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### Appendix II. The Model and Methodology used to Estimate the CIT Gap

### Methodological framework (RA-GAP top-down approach)
- Core methodology:
  - The IMF’s RA-GAP methodology for CIT gap is based on the top-down approach aiming to estimate potential CIT base and liability from existing macroeconomic data and compare estimated results with actual declarations and payments.
  - Basic condition: macroeconomic data must be compiled independently of assessed tax base and liability. In Finland, national accounts are compiled by Finland Statistics using surveys, annual accounts, and administrative data; tax declarations are not the initial source for national accounts measures.

- Theoretical structure:
  - Starting point: Gross operating surplus (GOS) of corporations in national accounts used to estimate potential CIT base.
  - Three concepts of CIT base used in RA-GAP:
    - Current-year net tax base (C-NTB): aggregated current year result reflecting profit-making and loss-making corporations.
    - Current-year tax base (C-TB): aggregated current year result of profit-making corporations only; before deducting carried-over losses.
    - Tax base (TB): aggregated current year result of profit-making corporations only, after deducting carried-over losses from previous years; base for calculating aggregate CIT liability.
  - Conceptual adjustments: differences between GOS and tax base classified into D1, D2, D3:
    - [D1] differences between GOS in national accounts and aggregate financial accounting profit (FAP) of CIT taxpayers
    - [D2] differences between aggregate FAP and aggregate current year net tax base (C-NTB)
    - [D3] differences between aggregate C-NTB and aggregate tax base (TB) due to losses and deductions for carry-over losses
  - Sequence: Adjust GOS by estimates for D1, D2, and D3 to estimate potential FAP, potential C-NTB, potential C-TB, and potential TB; then apply statutory CIT rate and reflect tax credits/additional liabilities to derive potential CIT.

- Scope limitations:
  - Framework limits estimation to non-financial corporations; financial corporations are excluded because their national accounts measures (FISIM, net insurance premiums) can diverge significantly from taxable incomes.
  - Top-down estimates do not attempt to measure tax avoidance or BEPS directly; BEPS activities that are captured in national accounts are within scope, but legal profit shifting that reallocates national income will not be separately measured.

### Practical application: data, limitations, and two-method strategy
- Data and practical constraints:
  - Complete independent data for all D1–D3 adjustments are not available; available statistics may use different definitions and require assumptions.
  - For some adjustments, the only source would be tax declaration data, requiring reconciliation assumptions between tax records and statistical data.
- Two-method approach to reduce assumptions:
  - Absolute method (P-TBabs):
    - Uses difference between Assessed GOS (A-GOS) and Assessed Tax Base (A-TB) derived from taxpayer declarations to adjust Potential GOS (P-GOS).
    - P-TBabs = P-GOS minus the A-GOS—A-TB difference (i.e., uses taxpayer declarations for D1–D3 adjustments).
    - Represents an upper limit for compliance gap and likely over-estimates the gap because it implicitly assumes undeclared operating surplus has no associated costs.
    - Under absolute method, P-CITabs is adjusted by subtracting tax credits claimed by taxpayers.
  - Relative method (P-TBrel):
    - Uses the relative size (geometric mean) of Assessed Current-year Tax Base (AC-TB) to A-GOS for taxpayers with positive AC-TB and positive A-GOS, then scales to sector P-GOS.
    - Adjusts for taxpayers with negative P-GOS by applying ratios from declaration data.
    - Applies deductions for carried-over losses and deferred profit adjustments from declarations to arrive at P-TBrel.
    - Assumes that most taxpayers (particularly larger ones) are compliant; the ratio is driven by compliant taxpayers and applied to P-GOS to estimate what C-TB would be if all reported like compliant taxpayers.
    - Under relative method, P-CITrel is adjusted by the ratio of tax credits claimed to assessed tax payable before credits.
- From P-TB to gaps:
  - Potential CIT (P-CIT) is determined by applying the CIT rate to P-TB (two variants: P-CITabs, P-CITrel).
  - Assessment gap = P-CIT − Assessed CIT (A-CIT).
  - Compliance gap = Assessment gap + Collection gap (collection gap defined as uncollected tax owed for the period on amounts assessed as due against that period’s declarations).

### Assumptions and interpretive notes
- The absolute method tends to provide an upper-bound estimate of the assessment gap.
- The relative method relies on the assumption that compliant taxpayers are representative in the ratio of tax base to A-GOS.
- Financial corporations are excluded from the top-down RA-GAP scope.
- The RA-GAP top-down estimates do not separately quantify BEPS or legal profit shifting that reassigns national income across countries.

*Appendix I and Appendix II data and methodology as presented in the source document.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2023/english/1svnea2023002.pdf_