European Commission, 2016, “The Concept of Tax Gaps,” Report on VAT Gap Estimations by FISCALIS Tax Gap Project Group (FPG/041), Brussels.
European Commission, International Monetary Fund, OECD, United Nations and World Bank, 2009, “System of National Accounts, 2008,” New York.
Hutton, Eric, 2017, “The Revenue Administration – Gap Analysis Program: Model and Methodology for Value-Added Tax Gap Estimation,” IMF Technical Notes and Manuals 17/04, Washington DC, International Monetary Fund.
Internal Revenue Service Research, Analysis & Statistics, 2016, “Federal Tax Compliance Research: Tax Gap Estimates for Tax Years 2008–2010,” Publication 1415 (Rev. 5-2016), Washington DC, Internal Revenue Service.
International Monetary Fund, 2014, “Spillovers in International Corporate Taxation,” IMF Policy Paper, Washington DC, International Monetary Fund.
Mendoza, Enrique G, Assf Razin, and Linda L Tesar, 1994, “Effective tax rates in macroeconomics -Cross-country estimates of tax rates on factor incomes and consumption,” Journal of Monetry Economics 34, pp. 297–323.
OECD, 2015, “Measuring and Monitoring BEPS, Action 11 – 2015 Final Report,” OECD/G20 Base Erosion and Profit Shifting Project, OECD Publishing, Paris.
Pecho Trigueros, Miguel, Fernando Pelaez Longinotti, Jorge Sánchez Vecorena, 2012, “Estimating Tax Noncompliance in Latin America: 2000-2010,” Tax Studies and Research Directorate Working Paper N° 3 – 2012, CIAT.
Poniatowski, Grzegorz, Mikhail Bonch-Osmolovskiy, and Misha Belkindas, 2017, Study and Reports on the VAT Gap in the EU-28 Member States – 2017 Final Report, CASE Network Studies & Analyses Report, No.492/2017.
Rubin, Marcus, 2011, “The practicality of a top down approach to the direct tax gap,” in Plumley, Alan ed. “Recent Research on Tax Administration and Compliance Selected Papers Given at the 2011 IRS-TPC Research Conference,” Washington, DC, pp. 109–127.
The ‘RA-GAP’ stands for ‘Revenue Administration – Gap Analysis Program,’ conducted by the Revenue Administration Divisions of the Fiscal Affairs Department, International Monetary Fund.
The author gratefully acknowledges comments from Michael Keen, and colleagues in the RA-GAP team including Eric Hutton, Martin Knudsen, Michael Thackray, and Juan Toro in Fiscal Affairs Department (FAD), IMF. The feedback from all the countries which have participated in the program is also gratefully acknowledged, while all remaining errors are the author’s.
For European countries, EC (2016) summarizes country cases, and Poniatowski et al. (2017) provide recent updates of the VAT gap estimation by the European Commission. For Latin American countries, see Pecho et al. (2012). Hutton (2017) describes the methodology of the RA-GAP projects for VAT.
The theoretical tax base of the VAT is aggregate value added plus imports minus exports, so that it is straightforward to calculate it from macroeconomic data. But the relationship between the theoretical CIT base and macroeconomic data is more complicated, for various reasons, including the asymmetric treatment for profit-making corporations and loss-making corporations under CIT.
See Rubin (2011) for several methods of the top-down approach to estimate tax gaps for direct taxes, and examples of the results following top-down approach in Latin American countries are introduced in Pecho et al. (2012).
The IRS in the United States uses the results of operational audits for estimating noncompliance of corporation income tax by correcting selection biases. See IRS (2016).
It should be noted, however, that quantifying the policy gap for CIT more difficult because there is no natural reference policy framework for benchmarking the CIT base. This is discussed further in Section V.
In principle, national accounts are expected to measure total economic activities including “non-observed” economy, which are not captured in regular statistical enquiries, being concealed to avoid taxes or complying with administrative procedures. Many countries have had considerable success in compiling estimates of production that cover the non-observed economy as well as the observed economy. See EC, IMF, OECD, UN and World Bank (2009).
11 European Commission (2014) uses net operating surplus (NOS) plus/minus property incomes as the denominator to calculate implicit tax rate of taxes on capital incomes. NOS is calculated by subtracting consumption of fixed capital from GOS.
Some countries allow the offset of losses against profits in previous tax periods by reimbursing taxes paid for those years.
If there are multiple CIT rates, the estimated aggregate base should be separated into different parts to which different CIT rates are applied. For instance, if a reduced rate is applied to small corporations, the base for such corporations should be separated using available distributional data.
It is also possible to show the gap between GOS and ‘declared GOS’, but both GOS and declared GOS may include values not relevant to the CIT tax base, and the ratio of the gap with respect to GOS may be meaningless to understand the impact of non-compliance on the CIT base and collections.
Examples of additional CIT liabilities are minimum tax or alternative tax of which amounts are determined irrelevant of taxable incomes.
However, if there are no reliable data for these it is necessary to use actual declared values to calculate the CIT gaps, and the estimated gap contains the same information as the CIT base gap.
It is, however, difficult to have sector CIT gaps classified into a large number of individual economic activities because of different classification principles between national accounts and the tax administration. National accounts systems usually classify the activities of a single corporation into multiple sectors by using granular business establishment data, while the tax administration commonly classifies a single corporation into a single sector by its primary activity. Therefore, more detailed classification of economic activities for CIT gaps will increase the possibility of mismatches between potential values (based on national accounts) and actual values (based on tax returns) in a single sector.
It should be noted that not all the public corporations under control of the government are categorized in S13; if NPIs engage in the market production, i.e., sales of goods and services at economically significant prices (a ‘50% rule’ – prices representing more than 50 percent of total costs – is applied in SNA2008), such NPIs are classified into S11 or S12.
NPIs producing goods and services at economically significant prices are classified into S11 or S12.
FISIM is measured by the difference between the rate paid to banks by borrowers and the reference rate plus the difference between the reference rate and the rate actually paid to depositors, representing charges for financial intermediation services. Interest payments/receipts at the reference rate is recorded as transactions of property incomes (payments/receipts), which are not recognized as the value-added generated by the financial institutions.
To prevent double taxation, tax credits or allowance for foreign source incomes are given to tax liability/base subject to taxation in the branches’ local jurisdictions.
There are two possible ways to measure actual CIT declarations for calculating the compliance gap: 1) the initial (original) declarations, and 2) the modified declarations as of a certain cutoff date. The initial declarations are measured at the original filing/payment deadline. The former measure will not change over time, and provides a basis for comparison as to how the gap evolves over time as the administration collects on arrears and yields additional assessments. The latter uses the declaration data assessed and/or modified up to a certain cutoff date, which will change according to the choice of cutoff date (though the effects become less important with increasing time between the filing and cutoff dates).
However, standard national accounts tables do not usually include (2), (3), (4) classified by economic activities. Therefore, it is necessary to use individual financial statements and tax return data to classify aggregate values into economic activities.
These are taxpayer identification numbers that have been transferred by algorithm to anonymized numbers that allow records from different data sources (e.g., registration and payment databases) to be linked together for each taxpayer without revealing the identity of the taxpayer to the analyst.
The definition of the policy gap for VAT is provided by Keen (2013), as a difference between the potential VAT if all final consumption were taxed at the current standard rate without any exemptions and the potential VAT given the current policy framework. A graphical chart showing these concepts is provided in Hutton (2017).
CIT efficiency ratio can be calculated for (1) total economy, using total GOS and total CIT revenue (2) S11, using GOS of S11 and CIT revenues of S11 corporations, and (3) S11+S12, using GOS of S11+S12 and CIT revenues of S11 and S12 corporations. The ratio using total GOS is easy to calculate, but may include GOS of S13, S14 and S15 in the denominator, while they are not relevant to CIT base (as discussed in Section III.A), and therefore underestimate the efficiency. Therefore, it is desirable to use S11 or S11+S12 in analyzing CIT revenue performance by using the CIT efficiency ratio.