Do government spending and taxation really reduce inequality, or do we need more thorough measurements? A response to the World Bank researchers
‘South Africa can claim to have one of the world’s most redistributive public purses,’ claims Business Day associate editor Hilary Joffe (2015), drawing upon World Bank research findings (Inchauste et al. 2014, Inchauste et al. 2015, World Bank 2014), which were recently reiterated by Woolard et al. (Econ 3x3, October 2015). In response to the question: ‘How much is inequality reduced by progressive taxation and government spending?,’ their answer is that, when they adjust household incomes ‘comprehensively’ for the impact of government revenue and expenditure, the Gini coefficient (which measures income inequality) is reduced from 0.77 to 0.59. This claim is regularly repeated by economists and high-profile commentators, often in support of fiscal austerity (see Bond 2015).
Although I have no easy answer in rebuttal, there is a significant problem. The research ignores large areas of state spending that would probably raise the Gini if included. As a brief glance at the national budget shows, the types of expenditure that the World Bank researchers took into account ignore other categories of expenditure that also have strong distributional effects. Likewise, their selection of taxes omits important components of corporate taxation – including the plethora of tax allowances, credits, loopholes and incentives embedded therein, all of which increase capital gains to holders of company shares. There also are other problems, e.g. regarding the quality of services (see below).
The Bank’s research on this vital matter is not only deficient due to its incompleteness, but is politically biased in a way that largely supports the status quo’s perspective on inequality, namely that there is little fiscal space for further redistribution. Although a key member of the research team has acknowledged the validity of my critical questions and the limitations of the methodology (Lustig 2015), World Bank staff and consultants go on repeating their findings, as in the Econ3x3 article – and most recently in a draft document for a collaborative World Bank project (2016: 22) to assess poverty and inequality in SA.
World Bank researchers acknowledge weaknesses, but . . .
The fiscal tools examined by the Bank researchers (i.e. Inchauste et al.) were only those related to household taxation, social spending, and municipal services – and even there they made assumptions that are dubious in the South African context. To be sure, while repeatedly claiming ‘comprehensive’ coverage, the Bank’s staff and consultants have felt compelled to admit the following data and methodological ‘limitations’:
- the analysis does not take into account the quality of services delivered by the government;
- the analysis excludes some important taxes and spending such as taxes (and tax expenditures/subsidies) on corporate income, international trade and property, and spending such as infrastructure investments, apparently due to the lack of an established methodology for assigning the impact of these outlays across households;
- it does not capture how asset accumulation and returns to capital affect income inequality; and
- there are questions about the lack of adequate information on the income of households at the top of the income distribution (World Bank, 2014: 26; Inchauste et al. 2015: 15).
However, if they fail to address the biases implicit in these shortcomings, it is impossible to conclude that ‘(n)ot only are South Africa’s main fiscal instruments progressive overall, the degree and structure of progressiveness is such that these instruments achieve significant reductions in income inequality’ (Woolard et al., Econ3x3, October 2015: 7). Consider some of these drawbacks (for more detail, see Bond, forthcoming).
Ignoring quality in state spending: the case of education
Education, the single largest budgetary commitment, illustrates how dubious the alleged social spending benefits for recipients can be. Most public schools produce extremely low-quality education, thus locking in inequality with regard to life chances.
The World Economic Forum’s (2015) Global Competitiveness Report 2015–16 rated South African education as the worst of 140 countries in terms of science and mathematics training, and 138th in overall quality. As Spaull (2013: 10) remarks after studying the 1994–2011 outcomes: ‘South Africa has the worst education system of all middle-income countries that participate in cross-national assessments of educational achievement.’ The OECD (2010: 248) notes that ‘in 2008, only 1.4% of working-age Africans held a [university] degree, compared to almost 20% of working-age Whites. This proportion for Africans has hardly increased since 1993, while the proportion for Whites has grown by 5.4%.’
Given these outcomes, it could just as easily be argued that inequality is amplified by the manner in which public education is provided to the low-income majority. This story is fairly typical of maldistributed state resources; similar concerns have been raised regarding the quality of health services to the poor.
As National Treasury senior official Andrew Donaldson acknowledges (in a 2014 Econ3x3 article): ‘In areas such as education, health care and urban transport, service provision tends to evolve in differentiated ways […] the result is a fragmented, unequal structure in which the allocation of resources and the quality of services diverge.’ Combined with semi-privatised systems, such public spending, he admits, ‘entrenches inequality between rich and poor.’
Spending ignored by the World Bank analysts
The social spending items taken into account by the World Bank researchers account for 43% of total government spending (for fiscal year 2010/11). The October 2015 medium-term budget statement anticipates R1.45 trillion in 2016–17 spending, of which R219 billion (15%) is allocated to basic public education subsidies and R170 billion (12%) to public health (with the quality variances across income groups a main caveat for both these types of spending, as discussed above).
But other major areas were not analysed by the Bank researchers, though they have vital distributional implications:
- R184 billion (13%) for ‘Defence, public order and safety,’ which is likely to have a strong bias towards protecting the lives and property of wealthier classes;
- R143 billion (10%) for debt servicing, for which wealthy financiers and other bondholders are the main beneficiaries, taking their gains in deferred income (although a fraction of the working class who are fortunate to have a retirement fund also invests indirectly in debt securities); and
- R129 billion (9%) for aspects of ‘Economic affairs’ – economic infrastructure at R76 billion, industrial development and trade at R32 billion, and science, technology innovation and the environment at R21 billion – items that, arguably, disproportionately benefit corporations and the higher-income groups that own their shares.
No one (myself included) has done the difficult work required to put numbers to the distributive effect of the biases within these spending categories. But, without having done so, Bank staff and consultants should not make expansive claims about a ‘post-fiscal’ Gini coefficient improvement.
Likely regressive state spending: a first look
Although the World Bank (2014: 21) claims to ‘comprehensively assess the distributional impact of government taxation and spending’ using a ‘comprehensive fiscal incidence analysis’ (Inchauste et al, 2015: 9), its researchers ignore major items that appear to subsidise the accumulation of capital gains to wealthier households. Consider the following:
1. State subsidies to capital/corporations/corporate shareholders (‘corporate welfare’):
- Indirect subsidies are enormous, because most of the economic infrastructure created through taxation and user fees – roads and other transport, industrial districts, the world’s cheapest electricity during most of the post-apartheid era, R&D subsidies – is likely to overwhelmingly benefit geographically-proximate corporations and their shareholders. (There may be some job creation, but mega-projects tend to have very low long-term employment multipliers).
- Direct subsidies occur in the form of overt grants or, more often, tax provisions that business can utilise, e.g. accelerated write-offs of capital expenditure, incentives for capital-intensive industry, intended or unintended tax benefits/loopholes (e.g. export processing zones), motor vehicle industry schemes and other industrial development incentives. The direct employment benefits of these schemes are quite limited (as Black showed on Econ3x3).
- To illustrate, the highly-subsidised Medupi and Kusile power plants provide benefits that mainly go to construction companies and subsequent corporate users (three dozen companies consume around 45% of national electricity, at much lower rates than those paid by ordinary firms and households). The same applies to the coal export line from Limpopo to Richards Bay and the Durban dig-out port. The hundreds of billions of rands going to these projects probably have a major distributional effect in favour of upper-income South Africans (and foreign shareholders).
As would be required in properly assessing the value of education and healthcare investment, the Bank and other researchers could estimate the distribution of the benefits from these investments across the income and wealth spectrum.
It is vital for researchers who investigate inequality to assess how much such state subsidies (corporate welfare) add to firms’ longer-term asset bases. This translates into capital gains on shares, a benefit accruing mainly to the rich. Shares on the JSE represent a vast component of household wealth.
2. Other state spending (superficially) considered by the Bank’s researchers includes the provision of household water and electricity, whether by an Eskom or municipalities.
- First, these continue to exhibit serious problems of quality and under-provision, signified by widespread service delivery protests and high levels of disconnection. In 2003, some 275 000 of all households attributed the interruptions of the water supply to cut-offs for non-payment (Muller 2004); this extrapolates to more than 1.5 million people affected that year. Today, while a notional 95% of South Africans have ‘access’ to water, the state concedes that only 65% of households enjoy an actual supply in their taps (Kings 2014).
- Secondly, the 1998 national electricity policy called for the parastatal agency, Eskom, to apply ‘cost-reflective’ tariffs in order to make profits or at least break even. This led to much higher charges for poor people. By the early 2010s, households faced much higher prices and new technologies for disciplining non-paying people, notably the prepaid meter system (which prevents cross-subsidisation). These approaches went counter to the explicit redistributive intentions of the 1994 RDP’s pursuit of ‘lifeline’ electricity and water, based on the progressive principle of cross-subsidisation through block tariffs.
3. Treasury regulations also have significant distributional effects. For example, its deregulatory attitude to transnational corporate profit expatriation has allowed a great deal of income to flow to firms’ overseas financial headquarters (thus supporting future capital gains for wealthy households). Global Financial Integrity estimates the average annual illicit outflows at $21 billion for 2004–2013 (Kar & Spanjers 2015). Such tax laxity towards ‘base erosion and profit shifting’ by multinational corporates is a most important negative-redistributive aspect of fiscal policy not measured by the Bank.
4. Whether fiscal policy favours the wealthy as opposed to the (long-term) interests of the poor also depends on ‘natural capital accounting’, i.e. putting a value on non-renewable resource depletion associated with corporate extraction of minerals. The World Bank (2011: 193) estimated the impact of natural capital shrinkage on South African gross national income in 2005 to be negative 9%. Not to tax mineral wealth is a distributional fiscal policy choice which allows the proceeds of the depletion of non-renewable resources to shift from society as a whole to wealthier shareholders (even though workers in mines, smelters, transport and other downstream beneficiation industries also benefit).
The World Bank researchers have meticulously measured something. But what they have measured is not the whole picture. While selected elements of state taxation and spending have an inequality-reducing effect on a selected component of well-being (household income) – as measured using a selected quantitative measure, the Gini coefficient – this is not a satisfactory basis from which to draw overarching distributional conclusions.
Bank staff and researchers have ignored systemic state-induced inequalities that shape distributions of income and of wealth (including capital gains) and broad human welfare. Indeed, the so-called ‘market distribution’ or ‘pre-fiscal’ distribution of income is already the systemic outcome of an inequality-producing economy that is substantially shaped and supported by state action that has long favoured wealthier people and the corporations in which they invest.
As the influence of the World Bank researchers’ project grew in the past year, I queried the work and received a series of (ultimately bureaucratic) emails from its officials (Bond 2015). Fortunately, upon asking the main consultant, Nora Lustig of Tulane University, why more accurate assessments of the state’s pro-corporate fiscal benefits were not attempted so as to offset the bias from only considering social spending, she took up the challenge with honesty: ‘Your questions are very valid. Regretfully, we have yet to figure out a solid methodological approach to allocate the burden/benefit to households of the list of interventions you list’ (Lustig 2015).
The question is: should Bank staff and allied researchers have been so hasty to publish research findings that had major implications for fiscal and budgetary policy when the methodology is evidently too limited to thoroughly answer the question they have posed? This is especially important in 2016 when even more pressure has risen from financial markets and credit rating agencies to reduce social spending – following the 2015 Budget of Finance Minister Nhlanhla Nene that cut the real value of welfare grants.
Beyond the critical flaws in measurement, the main risk of the World Bank research on ‘post-fiscal’ South African inequality is political bias: it promotes, or can be misused to promote, the budget-cutting agenda of the most regressive faction of corporate capital, i.e. financiers.
To mitigate this damage, the research task ahead for the World Bank and other inequality researchers is surely to attempt to properly measure the distributive impact of all government spending and all taxation (including allowances). That would make a real contribution to the battle against inequality and could inform appropriate tax and expenditure policies and projects (including planned ‘white-elephant’ mega-projects).
Until that research has been accomplished, would it not be better for economists, when asked about the distributional effect of fiscal policy in South Africa, to simply say: we do not yet know enough to answer that question?
Bond P. 2015. Bretton Woods Institution narratives about inequality and economic vulnerability on the eve of South African austerity. International Journal of Health Services 45, 3: 415–42. http://joh.sagepub.com/content/45/3/415.long
--------- forthcoming. South Africa’s pseudo social democracy: Tokenistic nuances within neoliberal nationalism. In: Globalizing Social Democracy: Expectations, Experiences and Alternatives, edited by Ingo Schmidt. London, Pluto Press.
Inchauste G, Lustig N, Maboshe M & Purfield C. & Woolard I. 2014. South Africa Economic Update: Fiscal Policy and Redistribution in an Unequal Society. Presentation, World Bank Group, Pretoria. 6 November.
Inchauste G, Lustig N, Maboshe M & Purfield C. & Woolard I. 2015. The Distributional Impact of Fiscal Policy in South Africa. Policy Research Working Paper 7194. World Bank Group.
Joffe H. 2015. Piketty’s wealth tax fails to solve SA’s inequality riddle. Business Day, 7 October.
Kar, D & J Spanjers 2015. Illicit Financial Flows from Developing Countries: 2004–2013. Washington DC, Global Financial Integrity. http://www.gfintegrity.org/report/illicit-financial-flows-from-developing-countries-2004-2013/
Kings S. 2014. Our water troubles still run deep. Mail & Guardian, 13 February.
Lustig N. 2015. Email correspondence with P. Bond. 20 January.
McDonald D & Pape J eds. 2002. Cost Recovery and the Crisis of Service Delivery in South Africa. London, Zed Books.
Muller M. 2004. Turning off the taps. Mail & Guardian, 26 June.
OECD 2010. Tackling Inequalities in Brazil, China, India and South Africa: The Role of Labour Market and Social Policies. Paris, OECD.
Spaull N. 2013. South Africa’s Education Crisis: The quality of education in South Africa 1994–2011. Centre for Development and Enterprise Working Paper, October.
Van der Berg S. 2009. Fiscal incidence of social spending in South Africa. 2006. Working Paper 10/2009, Department of Economics, Stellenbosch University.
Woolard I, Metz R, Inchauste G, Lustig N, Maboshe M & Purfield C. 2015. How much is inequality reduced by progressive taxation and government spending? Econ3x3, 28 October.
World Bank 2011. The Changing Wealth of Nations. Washington, DC.
World Bank 2014. Fiscal policy and redistribution in an unequal society. South Africa Economic Update 6. Washington DC.
World Bank 2016. South African Poverty and Inequality Assessment. Draft discussion note, Pretoria, January.
World Economic Forum 2015. Global Competitiveness Report 2015–16. Davos.
 The estimate of Van der Berg (2009) for the fall in Gini is even larger: from 0.69 to 0.47.
 A World Bank Group consultation workshop to initiate this project is being held at the University of Johannesburg on 15 February, 2016.
 Capital gains are extremely important in raising the wealth levels of those who are already wealthy. For example, the United States Congressional Budget Office calculated that, in 2011, the share of total income from capital gains enjoyed by that country’s top 1% of earners was 36%; for the bottom 95% it was only 4%. Shares on the Johannesburg Stock Exchange constitute much of household wealth. For aggregate South African households in 2011, wealth was composed of an extremely high 77% in the form of financial assets and 23% non-financial assets (in contrast to India where the ratio was 12% financial to 88% non-financial assets).
 For example, even though minister Ronnie Kasrils decided to implement a free basic water policy in 2001, by that time the commercialisation instinct was thoroughly accepted by municipalities (based in part on World Bank recommendations inordinately hostile to cross-subsidisation). As a result, the right to water ended up being delivered in a tokenistic way, i.e. free for merely the first 6 kilolitres per household per month, with huge price increases beyond 6 kilolitres very common. In the Durban pilot, this led to a doubling of the real price from R2 to R4/kl and in turn, the lowest-income third of the metered customer base cut back their demand from 22 to 15 kl/hh/m from 1997–2004: i.e. a price elasticity of 0.55, compared to 0.11 for the wealthiest third of customers.
 It is the extractive-industry corporations which, by the end of the commodity price super-cycle, were the world’s most profitable firms, according to the UN Conference on Trade and Development. And the intergenerational distribution of mineral wealth – from future low-income South African citizens who no longer have access to such (now-depleted) natural capital – must also be considered, just as the damage from climate change is also now being calculated with more temporal sophistication.
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