South Africa’s Tax Capacity: A Developing Country Analysis

31 May 2002

Ms. Ingrid van Niekerk (EPRI)

EPRI acknowledges that this publication was made possible through support provided by USAID. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the United States Agency for International Development.


This research report analyses how South African tax levels compare to those of other developing countries, controlling for structural characteristics of the economies. Economists have published international comparisons of tax levels using cross-country econometric analysis for more than two decades.

This research provides evidence that South Africa’s average tax rate is relatively low by developing country standards (using a sample of developing countries). This research supports previous analysis documenting how South Africa’s average tax rate is relatively low by international standards (using a sample of developing and industrialised countries), and addresses a concern raised by economists that South Africa should be compared to other developing countries.

Previous international comparisons have documented that South Africa collects a level of taxes about five percentage points of national income lower than expected given the country’s economic fundamentals. This amounts to approximately fifty billion rand per year. This developing country analysis shows that South Africa’s tax collection is approximately seven percentage points of national income lower than that predicted by the nation’s economic characteristics. This amounts to about seventy billion rand per year. South Africa ranks as the fifth most under-taxed developing country, using the tax capacity measure developed in this analysis.

The level of tax revenue collected is a critical determinant of the quantity of real resources a government can mobilise for public initiatives. The Katz Commission points out that "public expenditure is unavoidably constrained by financial considerations," supporting this with an excerpt from the 1995 Budget Speech: "Revenue and deficit targets thus dictate the overall government expenditure levels which the economy and the fiscus can sustain." (1985, pg. 8)

The South African government has committed to maintaining an average tax level of approximately 25% of Gross Domestic Product since the 1995/96 fiscal year (GEAR, 1996 pg. 9). Tax revenue as a percentage of GDP has remained relatively stable for the period 1992/93 to 2000/2001, at between 23,8% to 23,7 % (Department of Finance, 1997 and 2002).

What the optimum level of tax revenue as a percentage of GDP should be in a country is both an ideological and a technical question. Governments of different political persuasion will have different perspectives on the average level of taxation that can be collected in the economy without putting long term economic growth at risk. There are indeed practical limits to the extent that additional tax revenue can be raised. Weiss (1995) agrees that despite all these and other limitations, there is an important tradition in development economics that sees the tax-revenue-to-GDP ratio as a significant element in fiscal policy that can and should be manipulated as part of a development strategy.

This idea of a potential source of tax revenue that can be drawn on by a government has influenced thinking around the idea of ‘taxable capacity’. Tax capacity refers to both the ability of people to pay, and the ability of the relevant government to collect these taxes.

This paper analyses how South African tax levels compare to those of other developing countries, controlling for structural characteristics of the economies. The paper tests the hypothesis that the South African average level of taxation is equal to the expected level, given the economy’s fundamental characteristics. Due consideration is taken of the limitations of such a statistical analysis. The aim is that this international comparison serves as one of the many measures that can be used when investigating the profile of the South African tax system and the ability of the treasury to raise tax revenue from the economy.

  2. Several economists have published international comparisons of tax levels using cross-country econometric analysis for more than two decades. In 1979, Tait, Gratz and Eichengreen published a cogent summary and critique of the theory and methodology employed in these studies. Their research supported the methodology used by Chelliah, Baas and Kelly (1975), who pioneered these techniques. Their main innovative contribution to the debate was to suggest that the international tax comparison indices, which they constructed, should be ranked in order to make useful comparisons. Since then, Newlyn (1985) has argued that the IMF’s ‘taxable capacity’ measure should be used in conjunction with an alternative measure which is based directly on policy-determined discretionary changes in tax structure. He does not however lay out a clear way to this, but the issue is nevertheless critically important for any analysis as it helps define the limitations of such a study.

    Since the late 1980s the application of these various methodologies to the tax systems of developing countries has been critiqued. Bird and Oldman (1990) point out that much variation may be observed in tax ratios in countries with the same level of per capita income. "Considerable efforts have been devoted to explaining this variation in statistical terms, as a rule entirely in terms of economic structure, with no allowance for more political factors." (pg. 5)

    Tanzi (1990) points out that often the problem is associated with the quantitative statistical methods employed that put a disproportionate emphasis on the level of taxation without also investigating the structure of taxation. "The reason is that in developing countries the gap between the statutory tax system and the effective or real tax system may be wide." (pg. 20) He goes on to explain that this wedge may be partly due to explicit and intentional tax evasion, poor and often non-existent accounting, and the timing of the tax payment.

    Much literature has been devoted to the determination or estimation of the capacity to tax in developing countries. Distinctions have often been drawn between taxation in developing countries and taxation in industrialised countries. Even within the developing world there are distinct differences between countries in terms of social and economic characteristics.

    However there are key characteristics, which can be identified that "influence the structure and level of taxation creating a priori expectations for substantial differences in the tax systems of industrial and developing countries." (Tanzi 1992)

    In addition there are important differences in the general characteristics of the tax systems of most developing countries. Amongst those identified by Tanzi (1992) are: fragmentation of tax revenue among a large number of taxes; erosion of the tax base through evasion, incentives, generous tax deductions and exemptions; long collection lags and in particular those associated with periods of high inflation; excessive use of Ad Valorem taxes; use of presumptive and minimum taxes; evasion and enforcement; cost of administrative compliance and the reliance on foreign trade taxes.

    Differences in the ratios of tax-revenue-to-gross-domestic-product can reflect various factors, the most important amongst them being the perceived revenue needs of the country; the desired role of the public sector and non-tax sources of revenue. The first of these – the perceived revenue needs of the country is influenced by both the structure of the economy and the role that the government wants to play in the economy. The larger the role the higher the ratio one would expect to find. Various aspects of the tax system, including the political process, quality of the tax administration and the structure of the economy, can influence the second factor– the desired role of the public sector. The third factor– non-tax sources of revenue, refers to foreign grants, transfers from central bank profits and earnings from government owned resources, that allows governments to sustain long periods of deficit financing. " A full fledged model that tried to explain the variations in the tax ratios across countries would have to take into account these factors. No study yet available has attempted to do so owing to obvious difficulties. Therefore it has been difficult to explain econometrically more than a small proportion of the total variation in tax ratios across countries." (Tanzi, 1992, pg. 6)

    One way of assessing taxable capacity is to relate tax revenue to GDP (the T/GDP ratio) across countries using a simple regression model with explanatory variables that represent elements of taxable capacity. The tax ratio of an individual country can then be compared to the predicted tax ratio for that country from the regression equation. The explanatory variables can be a mixture of demand factors (a government’s wish to tax) and supply factors (a government’s ability to tax).

    Tanzi (1992) developed a model that explained more than half of the variance amongst tax ratios in 1988. His model used agricultural output, per capita income, imports and foreign debt (each as a percentage of GDP) as proxies to explain the variance among tax ratios. Tanzi’s justification for using these variables relates partly to the structure of the economy.

    He points out that the agricultural share is an important independent variable for both demand and supply reasons. On the demand side it can be argued that if an economy is largely agricultural based then there will be less need to spend on government services, as these are often urban-based. As the share of agriculture in GDP rises, the need for total public spending and so the need for tax revenue tends to fall.

    On the supply side, agricultural incomes are normally difficult to tax directly because of the predominance of small-scale producers. Also as many authors have pointed out (Bird 1974 et. al.) the agricultural sector may be heavily taxed through implicit taxes such as import quotas, tariffs, controlled prices for output and overvalued exchange rates. Explicit taxes (export duties and land taxes) on this sector are usually very limited. The difficulty of raising the tax level rises with the increase in share of agriculture. So, from both perspectives the expectation is that agriculture will be negatively associated with a T/GDP ratio.

    Per capita income can also be seen from both a demand and a supply side. It is expected that per capita income will be positively associated with the T/GDP ratio. If government services such as health and education have an income elasticity greater than unity, then rising incomes would create a demand for such services. On the supply side, it is expected that the taxable portion of income (tax base) will rise with the level of income as more activities are brought into the tax net.

    The relationship between the share of imports in GDP and the tax ratio is expected to be positive also. The imports-to-GDP ratio reflects important supply- side influences. It is widely accepted that a high import ratio facilitates the collection of taxes as foreign trade is easier to tax than domestic activity and more so in low income countries.

    The ratio of public debt to GDP is largely associated with demand factors as the need for taxation rises with the share of government debt servicing in GDP. Consequently there is a positive association between public debt to GDP ratio and the T/GDP ratio.

    Despite these criticisms, the quantitative international comparison of taxes remains a popular and useful tool providing an important perspective on an individual country’s tax system relative to those in other countries. As Bird and Oldman conclude: "It is therefore appropriate to begin with a quantitative overview of taxation in developing countries in order to set the stage for the subsequent substantive discussion of the role and nature of taxation…" (1990, pg. 5) Recent studies support this view. In an IMF Occasional Paper, Lachman and Bercuson (1992) utilise international comparisons and conclude that the South African tax rates are not low even by the standards of industrial countries. They qualify this statement, however, pointing out that South Africa’s "effective rate is reduced to a great extent by a variety of tax allowances and exemptions that tend to bring it more in line with those of the majority of the industrial countries." (pg. 30) The Katz Commission (1995) discusses the conceptual basis for international tax comparisons, and indicates that South Africa has a similar tax-to GDP ratio as other countries comparable on a per capita income basis. Harber (1995) quantifies the relationship between tax levels and their determinants using econometric analysis, concluding that South Africa is "undertaxed", but that the degree of "undertaxation" has declined significantly from ten percent of GNP in 1960 to 3,2 percent of GNP in 1993. He acknowledges that part of this high rate could have been due to the longer-term upward trend in tax ratios for sample countries.

    1. Hypothesis

The paper examines whether South African tax levels are greater than, equal to or smaller than those expected, given the economy’s fundamental and structural characteristics. Evidence from cross-country analysis of developing country experience during the 1990’s is used to illuminate this issue. The methodology employed has been frequently adopted by the International Monetary Fund. A measure of the expected tax level is determined, conditional on the characteristics of the individual country that are significant in terms of explaining the level of taxation. Several determinants of tax levels will be evaluated. Chelliah, Baas and Kelly (1975); Tait, Gratz and Eichengreen (1979); Tanzi (1987) and Harber (1995) provide examples of relevant econometric analysis for these and other determinants of tax levels. This paper draws on this literature and uses the following determinants

  1. Openness of the economy;
  2. Sectoral composition of the economy;
  3. Importance of large producers, employers, retail establishments;
  4. Monetisation of the economy;
  5. Literacy;
  6. Degree of urbanisation;
  7. Demand for fiscal resources in the economy.
    1. Data

The data are drawn from several sources: The International Financial Statistics Yearbook (2000) and the Government Finance Statistics yearbook (1999) published by the International Monetary Fund, the World bank’s World Development Report (1999).

Data for the following variables were compiled:

  1. Total Tax Revenue (denoted by T in the equations below);
  2. Gross Domestic Product (Y);
  3. Imports as a percentage of Gross Domestic Product (M), as a measure of openness;
  4. Agriculture as a percentage of Gross Domestic Product (A), as a measure of the economy’s sectoral composition of the economy;
  5. Per Capita Income (YP) as a proxy for literacy and urbanisation;
  6. Industry (I) as a percentage of Gross Domestic Product as measure of the importance of large producers, employers, retail establishments and the sectoral composition of the economy;
  7. Money Supply as a percentage of Gross Domestic Product (Ms), as a measure of monetisation and formalisation of the economy.
  8. Literacy rates (L) as a percentage of Gross Domestic Product, as a measure of literacy and urbanisation
  9. External Indebtedness (Df ), as a measure of demand for fiscal resources in the economy.

The statistical analysis employs cross-sectional data for the set of all countries for which a full set of data is available (approximately 50 countries). The observations are averages of annual data from 1990 to 1998. The process of averaging is used to reduce the possible influence of short-run fluctuations induced by movements in the business cycle. All data are expressed as currency-free ratios (for instance, tax revenue as a percentage of national income) with per capita income measured in a common currency unit (United States dollars).

    1. Statistical Analysis

The paper estimates a multiple regression model using the ordinary least squares (OLS) method. The explanatory variables as outlined above in 3.1 are proxies for the structural characteristics of the economies. The data variables are defined above in 3.2 and ‘E’ represents the residual term. The following equation was estimated:

  1. TG/Y = b o + b 1 M + b 2 Ms +b 3 A +b 4 YR + b 5 L + b 6 Df +b 7 I +b 8 Df + E

A log-log model was estimated using Ordinary Least Squares. As a result, the coefficients represent elasticity: for instance, a 1% increase in money increases a country’s average tax rate by 0.51% (not by 0.51 percentage points of GDP). The coefficients and associated statistics are reported in the table below. The R-squared for the regression is 45%, which is very high for a cross-country regression. The adjusted R-squared is 35%. The calculated F-statistic for the regression--F(7,39) = 4.52— this enables us to reject the null hypothesis that the regression is not significant with a confidence level of 99.9%.


Key findings on the individual co-efficients include:

A number of other specifications were tested, including log-lin models, lin-lin models and lin-log models. All yielded qualitatively similar results, although the log-log model proved significantly better. In addition, various specifications with other combinations of independent variables were tested, also yielding qualitatively similar results.

The tables on the following pages depict the expected and actual tax rates for the countries in the sample. In particular, it is important to note that South Africa’s expected tax rate (measured as the expected value of the tax to GDP ratio conditional on the explanatory variables) is equal to 31.7%, which is 7.8 percentage points of GDP higher than the actual average tax rate of 23.9%. South Africa ranks as the fifth most under-taxed country in the sample, based on this tax effort analysis.

(not included)

GRAPH: EXPECTED VERSUS ACTUAL TAX COLLECTIONS (2nd half of sample) (not included)

(not included)



This paper provides evidence that South Africa’s average tax rate is relatively low by developing country standards. This research supports previous analysis documenting how South Africa’s average tax rate is relatively low by international standards, and addresses a concern raised by economists that South Africa should be compared to other developing countries. The research warrants further attention in a number of directions. First, confidence interval analysis will improve the robustness of the analysis, determining whether the calculated differences between expected tax rates and actual tax rates are significantly different from zero. Second, the analysis will be extended to include industrialised countries, supporting a broader international comparison. Third, dis-aggregated analysis of tax revenue by type of tax (for instance, income tax, value-added tax, etc.) will identify those areas of the tax structure that have taxable capacity.



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