Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

Appendix 1. Variables and Data Source

Ltot is the log of the sum of tax and pension contributions revenue collected by central and sub national governments as percent of GDP. General government revenue was only available for 52 countries; for the remaining 60 countries we used central government revenue. We created a dummy variable (Gov) to distinguish countries that report consolidated revenues (Gov=1) from those that report only revenues from the central government (Gov=0). A caveat is worth mentioning: we did not include social security revenue collected and administered by private institutions, but we did include social security revenue collected by the Government. As a consequence, countries such as the USA and Chile, with an important level of private social security collection might be closer to its maximum tax capacity than what our analysis shows. (Source: World Economic Outlook and official websites.)

Lgd is the log GDP per capita, purchasing power parity constant 2005. (Source: World Bank World Development Indicators (WDI).)

Lgd2 is lgd square, which we include as explanatory variable to capture the presumably non-linear elasticity between tax revenue and per capita GDP.

TR is trade, imports plus exports as percent of GDP, which reflects the degree of openness of an economy. (Source: WDI.)

AVA is the value added of the agriculture sector as percent of GDP. We use this variable to represent how ease (or not) is to collect taxes. (Source: WDI).14

PE is the total public expenditure on education as percent of GDP and represents the level of education.15 (Source: WDI and FAD statistics.)

GINI coefficient measures the extent to which the distribution of income among individuals deviates from the equal distribution. (Source: WDI.)

CPI is the percentage change of consumption price index. (Source: WDI.)

Lcor is the log of the corruption perception index. There are different inefficiencies that can mean that countries do not reach their tax frontier. Among them, corruption, weak tax administrations, government ineffectiveness, and low enforcement. We chose only one to represent inefficiencies: the corruption perception index. (Source: Transparency International.)

Appendix 2. Natural Resource and Non-Natural Resource Countries: Tax Capacity and Tax Effort

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Tax and social contributions as percent of GDP.

Truncated Normal Heterogeneous in Mean and Decay Inefficiency.

Tax capacity (percent of GDP): tax and social contributions divided tax effort.

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1

We are grateful to Michael Keen, Victoria Perry, Edgardo Ruggiero, Serhan Cevik, Daniel Rodriguez, Kazuko Shirono, Jean-Jacques Hallaert, Marco Pani, May Khamis, Amgad Hegazy, Jehann Jack, Bahrom Shukurov, and Alina Luca for their comments and suggestions; and to Kelsey Moser and Dara Veung for help with consolidating the data.

2

The model used in this paper does not allow determining what part of the ‘gap’ is due to inefficiency (say, evasion) and what part is due to policy issues because of the lack of data to represent both causes. For instance, tax rates as explanatory variables of policy issues must be analyzed with tax bases (regime of depreciation, exemptions, and deductions); a country can have a high CIT or VAT rate and a low level of revenue because of the high level of exemptions and deductions. For this reason, only effective rates could be used as explanatory variables. However, effective tax rates are only available for a very small group of developed counties and for a few years. The same happens with inefficiencies: we do not have a variable to represent inefficiencies in collection (of tax administrations): even the level of evasion is only available for a few countries, a few years, and a few taxes (sometimes the VAT, other times the PIT).

3

Half normal and Truncated Normal models differ on the distributional assumption of the ‘u’ term (the ‘v’ term does not change between the two models). While the half normal distribution is a truncated version of a normal random having zero mean and variance σ2u, the Truncated Normal model relaxes an implicit restriction in the normal-half normal model assuming that the mean of the underlying variable is μ.

5

Lambdauivi) provides information of the relative contribution of vit and uit to the total error term and shows in this case that uit or the inefficiency term is relatively large.

6

VAT standard rate is 7 percent in Panama and 10 percent in Paraguay, among the lowest in the world. In Paraguay, tax effort would be lower still if the country refunded the tax collected on the re-export trade (people who cross the border from neighbor countries to make purchases).

7

The relative high level of tax effort in other developing countries can be explained by other factors. For instance, in the case of the Gambia (0.59) and the Kyrgyz Republic (0.78), by the tax collected on re-export trade (people who cross the border from neighboring countries to make purchases).

8

In this group of countries, non-hydrocarbon tax revenues account for about 27.6 percent of total revenues on average (tax and oil revenues).

9

Among natural-resource dependent economies, Bolivia is one of the exceptions: a developing country with also a significant level of tax revenue. In this country revenues from natural resources are significant since 2005, when a new government was elected and changed natural resource policies (revenue from natural resources increased from 1.6 to 7.7 percent of GDP between 2004 and 2008). That is to say, Bolivia had already developed its tax system and reached a relatively high level of tax revenue before collecting a significant level of revenue from natural resources.

10

The maximum difference of 5.6 percent belongs to Guyana, whose level of tax effort changes from 0.73 to 0.67.

11

In a few words, the model adds as explanatory variables the mean of every explanatory variable, which aim to identify the invariant or fixed characteristic of every country).

12

Although some countries, such as Chile and Peru, are not considered in this paper as natural- resource dependent economies (because their mining-sector revenue is lower than 25 percent of total revenue), revenue from this sector is important and, perhaps, this is the main reason why their tax capacities under Mundlack are lower.

13

In this group of countries, non-hydrocarbon tax revenues account for about 27.6 percent of total revenues on average (tax and oil revenues).

14

Due to political reasons, some countries exempt agricultural products from VAT as well as agricultural producers from the income tax. Moreover, this sector is difficult to control particularly when it is composed of small producers.

15

Other variables could reflect better the level of people’s education; however, data sometimes are not available for all countries. On other occasions, some variables are not useful for comparison. For instance, labor force with secondary education (percent of total) was not available for some countries, and secondary education significantly differs among countries.

Understanding Countries’ Tax Effort
Author: Mr. Marco Committeri and Ms. Carola Pessino