As the relative tax effort index is the ratio between actual tax collections to the potential tax revenue, this ratio may be greater than 1 for countries with a high tax effort, equal to 1 for countries fully using their potential tax capacity, or less than 1 for countries with a low tax effort. The “relative tax effort” is indicative of how well a country is exploiting its potential tax base. Throughout this paper, “tax effort” refers to the relative tax effort of countries and the countries are grouped on the basis of high, medium and low tax effort. The details of this classification are in Section 7(f).

There have been several empirical cross country analyses using the regression approach to measure a country’s revenue potential and its tax effort. One of the earliest papers on this was by Bahl (1971) who computed the relative tax effort of the _i_ th country using the “tax base proxies” (GDP per capita, agriculture and size of the foreign trade sector) of the _i_ th country and the average practice across the sample of 51 countries. Piancastelli (2001) estimates the tax effort index for a panel of 75 countries for the period 1985-1995 using just GDP per capita to measure the stage of development, the share of agriculture / industry/ services (separately in each regression) as a percent of GDP and trade as a percent of GDP. Using a larger data set of 141 countries over the period 1990-2004, Davoodi and Grigorian (2007) extend this regression based analysis by looking at institutional quality and the shadow economy as predictors of tax collection and tax potential Using a similar approach for 105 developing countries over 25 years, Gupta (2007) also includes tax policy variables (highest marginal tax rates for PIT, CIT and average import tariff rate) that impact revenue efforts. Le, Moreno-Dodson and Rojchaichaninthorn (2008) estimate the tax potential and relative tax effort using structural and institutional quality variables for a panel of 104 countries covering the period 1994-2003.

This study also distinguishes between the revenue potential based on the inherent economic capacity of a country -the “economic revenue potential” - and that based on what the legal and regulatory framework of the country prescribes - “legal revenue potential”. Taking this dual approach, two regressions are run to determine ‘revenue potential (economic)’ and ‘revenue potential (legal)’ using two sets of variables, one corresponding to the intrinsic economic structure and strength of countries, and the other incorporating tax policy, which is an expression of political choice. The “revenue potential (legal)” is the full model specification and the “revenue potential “economic” is a reduced model nested in the full model. Details of the estimation methodology are in Annex B.

The difference between the revenue potential (legal) and the actual revenue collected is commonly understood as the “tax gap”. The difference between the revenue potential (economic) and the actual revenue collected can be termed the “tax space”, i.e., the amount of revenue that a country can afford to collect, given its inherent economic strength, not based on what the parliament has mandated. The difference between the tax gap and the tax space – called “difference”- is discussed in Section 7(a) and 7(c).

# **_3. Components of the study_**

This study empirically investigates the tax effort and tax potential of a group of countries that include countries in the ECA region and the EU, as well as countries in other regions that bear similar characteristics in terms of tax structure. For instance, the countries in this sample have both VAT and social security taxes. In addition, some qualifying countries have been excluded due to lack of relevant tax data which is primarily sourced from WDI, OECD and Eurostat for this study. Accordingly, the sample of countries in this study has been limited to 61 countries. A smaller sample also tends to dampen the effect of the “world-wide average bias” in panel data analysis that may make results not too representative. Interestingly, in robustness checks, when the sample was increased to 88 countries where complete data was available, the results do not change much.

Within the ECA region itself, there is considerable diversity. In addition to Turkey, the other ECA countries can be broadly grouped into the “EU-10+1” (Bulgaria, Croatia, Romania, Czech Republic, Hungary, Poland, Slovak Republic, Slovenia; Estonia, Latvia, and Lithuania); the Balkans comprising Albania, Bosnia and Herzegovina, Kosovo, the former Yugoslav Republic of Macedonia, Serbia, and Montenegro; the Commonwealth of 3