Indirect Taxation and Gender Equity: Evidence from South ...sds.ukzn.ac.za/files/South Africa_IT_2009.02.01_1.pdf · been on the incidence of indirect taxes by income group, i.e.

Indirect Taxation and Gender Equity: Evidence from

South Africa

South African Country Paper

January 2009

Daniela Casale

School of Development Studies, University of KwaZulu-Natal

[email protected]

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Note:Part of the work emanating from the project has been accepted for publication in Feminist Economics © 2012 [International Association for Feminist Economics]

CONTENTS

1. INTRODUCTION

2. BACKGROUND AND SOUTH AFRICAN CONTEXT

2.1 Indirect tax incidence studies

2.2 The tax structure in South Africa

3. METHODOLOGY AND DATA

3.1 Indirect tax incidence methodology

3.2 Description of the data sources

3.3 Description of indirect taxes in South Africa

3.4 Identifying the ‘gender’ incidence of indirect taxes

4. RESULTS

4.1 Total indirect tax incidence

4.2 Incidence by urban/rural area and by race

4.3 Incidence by quintile and by presence of children

4.4 Incidence by consumption category

5. SIMULATIONS AND POLICY SUGGESTIONS

6. CONCLUDING REMARKS

7. REFERENCES

8. APPENDIX TABLES

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1. INTRODUCTION

This study is part of a multi-country project on ‘Making Tax Reforms Work for Women:

Mobilizing Taxes for Gender Equality and Women’s Empowerment’. The main objective

of the project is to investigate both explicit and implicit forms of gender bias (see Stotsky

1997a, 1997b) in tax systems in countries of varying levels of development (South

Africa, India, Argentina, Mexico, United Kingdom, Morocco, Ghana and Uganda).

Explicit bias arises due to specific provisions in the tax law that treat women and men

differently. These are typically found in direct taxes. Implicit bias occurs when provisions

of the tax law have a differential impact on women and men due to gendered social or

economic behaviour, even though the tax law contains no explicit bias. This form of bias

is typically found in indirect taxes (i.e. taxes levied on goods and services).

The project focuses on the gendered impact of two main types of taxes: personal income

taxes (which are direct taxes) and indirect taxes (in particular VAT, excises and the fuel

levy). The findings from the personal income tax analysis for South Africa are available

in the country paper by Budlender and Valodia (2007). This paper covers the indirect tax

incidence analysis for South Africa.

The overall findings from the South African case study suggest that the tax reforms of the

past two decades have gone a long way in eliminating both explicit and implicit forms of

bias in the South African tax system. This is particularly the case for the personal income

tax system, while the indirect tax incidence analysis suggests that there may still be some

small room to further eliminate the burden of indirect taxes on poor ‘female’ households.

This paper is organised as follows. In the next section, some background to indirect tax

incidence studies is provided, as well as an outline of the tax structure in South Africa.

Section 3 describes the data and the methodology used, including an explanation of how

we identify the ‘gendered’ incidence of indirect taxes. The results of the incidence

analysis are presented in Section 4, while Section 5 provides some discussion on further

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possible policy changes to the indirect tax system. Concluding remarks are made in

Section 6.

2. BACKGROUND

2.1 Indirect tax incidence studies

There is a large literature, including some studies in developing countries, that examines

the incidence of indirect taxes, i.e. the question of who ultimately bears the burden of

taxes on goods and services (Bird and Miller 1989; Younger 1993; Younger et al 1999;

Ahmad and Stern 1991; Gibson 1998; Rajemison et al 2003; Sahn and Younger 1998;

2003). There have been a few studies in South Africa that have tried to model the impact

of value-added taxes in particular (Fourie and Owen 1993; Alderman and del Ninno

1999; Go et al 2005), and one more extensive study by Woolard et al (2005), which

explored the incidence of indirect taxes using data from 2000 as part of a more general

study of tax incidence for the South African National Treasury.

The focus of most of these studies, however, and certainly in the South African case, has

been on the incidence of indirect taxes by income group, i.e. on the regressivity or

progressivity of the indirect tax system. The goal of this paper and of the broader project

has been to extend this work by exploring the gender impact of indirect taxes, and

particularly the impact on poorer women, and women living with children.

The study of the (gender) implications of indirect taxes is important for a number of

reasons. Indirect taxes make up a large portion of the government’s tax revenue,

especially in developing countries. In South Africa these taxes make up 40 per cent of

total government tax revenue, although this is low by developing country standards

where the share is generally between 50 and 60 per cent (Barnett and Grown 2004). In

addition, there is a global pattern of indirect taxes increasing as a share of total

government revenue, as it has become more difficult to tax companies and individuals

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due to the increased mobility of labour and capital (Khattry and Rao 2002; Barnett and

Grown 2004; Aizenman and Jinjarak 2006).

The indirect tax base is also very wide. While personal income taxes (PIT) and other

direct taxes affect only a small percentage of the population, indirect taxes - because they

are levied on consumption - will affect most people. This point is particularly pertinent to

a gendered analysis of taxes in South Africa. Unemployment rates among women are

currently around 50 per cent, women are far more likely to be engaged in informal work

than men, and even where women are working in the formal sector of the economy, their

earnings are less likely to be above the tax threshold than men’s (Casale and Posel 2005).

Using 2005 labour force data, Budlender and Valodia (2007) estimate that 73 per cent of

employed women compared to 65 per cent of employed men fell outside of the tax net,

and of the PIT paid, women’s contributions accounted for only 30 per cent.

While there is no explicit bias in the indirect tax system (tax authorities don’t have

different VAT rates by group, whereas they often do have different PIT rates by group),

there will be implicit bias as people have different spending patterns and so will bear the

burden of the tax in different proportions. This is particularly relevant in the gender

context, as much research now shows that men and women have different spending

priorities when they control resources.

2.2 The tax structure in South Africa

The structure of taxes in South Africa over the last two decades is shown in Table 1. In

the most recent period, direct taxes form around 60 per cent of total revenue, with

personal income taxes and corporate taxes being the two largest contributors (30 per cent

and 27 per cent of revenue respectively). Indirect taxes make up just under 40 per cent of

total revenue, with the main component, VAT, contributing 26 per cent of total revenue.

VAT, excises and fuel taxes – the indirect taxes that we investigate in this project -

jointly make up 33 per cent of total revenue. Unlike other developing countries, South

Africa does not currently rely heavily on trade taxes for government revenues.

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Some important changes are evident over the decade, especially the shift away from

indirect to direct taxes. This has been driven predominantly by increasing tax revenues

from corporations, especially over the last decade as profit rates rose. Although as a

proportion of total revenue, individual taxes have not increased, tax revenues from PIT

have risen substantially. These changes have been partly due to a marked increase in the

efficiency of the tax authority, the South African Revenue Services (SARS), which has

been able to extend the tax base and improve the collection rate substantially.

Since the political transition, the ANC government has been able to increase the tax/GDP

ratio from 23 per cent in 1993 to 28 per cent in 2007/8 (above the targeted rate of 25 per

cent) (National Treasury, 2008), thereby creating the fiscal space for increased

expenditure. It is worth noting that actual tax collections by SARS have in recent years

exceeded budget projections. In 2007/2008 a budget surplus of 1 per cent of GDP was

recorded and a surplus of 0.8 per cent was projected for 2008/09 (National Treasury,

2008).1

Table 1: Tax Structure, South Africa, 1988-2008 1988/89 1998/99 2007/08

Tax/Source of revenue Revenue % of total Revenue % of total Revenue % of total raised Tax Raised tax raised tax in R'm Revenue in R'm Revenue in R'm revenue

Individuals 14 910 30% 76 400 42% 191 046 30% Companies 11 244 22% 23 330 13% 176 471 27% Other 657 1% 5 558 3% 23 978 4% Total – direct taxes 26 811 53% 105 288 58% 391 495 61% VAT/GST 13 123 26% 43 600 24% 167 028 26% Excise duties 2 508 5% 8 338 5% 22 083 3% Fuel levy 2 555 5% 13 600 8% 26 434 4% Customs duties 2 466 5% 6 200 3% 31 473 5% Other 3 054 6% 4 044,1 2% 3 755 1% Total – indirect taxes 23 707 47% 75 782 42% 250 773 39% Total tax revenue 50 518 100% 181 070 100% 642 268 100% Source: Budlender and Valodia (2007) from National Revenue Accounts, National Treasury, South Africa

1 More detail (also from a gender perspective) on the tax structure and tax reform over the past few decades

can be found in the country paper by Budlender and Valodia (2007) and in the synthesis chapter by

Budlender, Casale and Valodia (2009).

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3. METHODOLOGY AND DATA

3.1 Indirect tax incidence methodology

The methodology most commonly used for calculating the incidence of indirect taxes

involves estimating the amount of tax paid by households indirectly through information

on their spending behaviour. Most countries, including South Africa, conduct household

surveys in which they collect detailed data on households’ expenditure patterns. The

post-tax expenditure values available in these surveys are used with corresponding tax

rate and price information for the year in question to calculate the amount of tax paid by

each household on each consumption item.

Assuming that the tax is shifted forward entirely onto the consumer, the amount of tax

paid per item can be calculated as follows where the tax is ad valorem:

))1/((expend* jijjij rateratetaxpaidV +=

where ratej is the tax rate on item j and expendij is the reported expenditure for household

i on item j. For a unit tax, the amount of tax paid by the household per item is calculated

as:

jjijij dutypricetaxpaidS *)/expend(=

where dutyj is the per unit duty on item j and pricej is the retail price of that item.

Tax incidence is then calculated as the percentage of total household consumption

expenditure spent on the tax for that item, or in total. The convention in the international

literature on tax incidence is to use consumption expenditure rather than income as the

base as it is a better measure of wellbeing if households engage in consumption

smoothing. A more practical reason for using consumption expenditure rather than

income here was that not all countries in the project could access (reliable) income data.

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3.2 Description of the data sources

The expenditure data that we use to calculate the tax incidence for South Africa are

drawn from the Income and Expenditure Survey (IES) of 2000, a household survey

conducted by the national statistical agency, Statistics South Africa (SSA). The IES,

which is predominantly used to update the CPI weights, is conducted every five years

among a nationally representative sample of about 30 000 households. It contains very

detailed information on the spending patterns of households, with data collected on

around 500 expenditure items through face-to-face interviews.2

There has been some concern expressed about the quality of the data from the 2000

survey (see Simkins 2004), but predominantly on the income information collected. We

therefore use only the expenditure data from the IES. We use a cleaned version of the

dataset (prepared by Global Insight) which has had many of the anomalies corrected or

removed, and we also use revised and updated sampling weights based on the 2001

Census provided by Statistics South Africa (which deal with some of the sampling issues

that were of concern).3

The tax rate and price information that we use to calculate the tax incidence per item was

gathered from various government sources: National Treasury Budget Review 2000;

South African Revenue Services VAT Guide for Vendors; and the Statistics South Africa

retail price survey for 2000.4

2 The SSA report on the IES 2000 includes the following definition of the respondent/s: “The person (or

persons) responding in this interview should be a member/members of the household who is/are likely to

do the purchases for the household or know the answers to our questions.” (Statistics SA 2002: 91). 3 The more recent 2005 IES was released in early 2008, but we have chosen not to use the updated survey

information here as some of the expenditure data are not considered reliable (SSA 2008). In particular, the

share of spending on food was found to be much lower than in 2000 across all quintiles in the distribution

(and compared to other countries of similar levels of development), which would effect our incidence

results substantially. 4 The author would like to thank Morné Oosthuizen and Ingrid Woolard who shared their price and excise

duty data.

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3.3 Description of indirect taxes in South Africa

As mentioned earlier, indirect taxes contribute just under 40 per cent of tax revenue in

South Africa. The main component is value-added tax (VAT), which accounts for 25.7

per cent of total tax revenue, with much smaller shares derived from excise duties (3.4

per cent), the fuel levy (4.2 percent) and customs duties (4.7 per cent) (see Figure 1

below). For this study, we analyse the incidence of VAT, excise duties and the fuel levy

only. A brief description of these taxes is provided below (Table 2 contains details).

Figure 1. Composition of tax revenue in South Africa, 2007/08

Other direct3.8% Companies

28.3%

Individuals29.5%

VAT25.7%

Fuel levy4.2%

Excise duties3.4%

Customs duties4.7% Other indirect

0.3%

Source: Own calculations from Budget Review 2007/8, National Treasury

In South Africa, VAT is a multi-stage single-rate tax levied on the consumption of most

goods and services (whether they are produced locally or imported). The VAT rate has

remained at 14 per cent on the value of most goods and services since 1993, although

there are a number of zero-ratings and exemptions. The following goods and services are

zero-rated: 19 basic food items (among them brown bread, eggs, vegetable oil, grains,

rice, milk, fresh fruit and vegetables, dried legumes, canned fish), illuminating paraffin,

goods which are subject to the fuel levy (petrol and diesel), international transport

services, farming inputs, sales of going concerns and certain government grants. The

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zero-rating of basic food items and paraffin/kerosene (used predominantly by the poor as

a fuel for cooking, lighting and heating) was implemented specifically to alleviate the

burden of VAT on poorer households.5

The goods and services which are VAT exempt are residential rental and

accommodation; educational services (including crèches); public road and rail transport;

non-fee related financial services; and medical aid and medicine/medical services

provided by public health institutions. Unlike with goods that are zero-rated, suppliers of

VAT-exempt goods are not able to claim back the input VAT. This implies that, to the

extent that the inputs attract VAT themselves, some of the VAT may be passed on to the

final consumer. An effective rate would be between zero and 14 per cent. However, for

this project, we rate these goods at zero per cent, given that the largest input cost in these

sectors is likely to be labour.6

Specific unit excise duties are levied on sorghum meal, tobacco products, and non-

alcoholic and alcoholic beverages. Details of these duties are provided in Table 2,

although it is important to note here that the taxes on tobacco and alcoholic beverages are

particularly high. The fuel levy is also a unit tax, levied at 110.1 cents per litre of petrol

and 89.4 cents per litre of diesel. For this study, we calculate the incidence of the fuel

levy on petrol and diesel for household use and for private transport only. We do not

estimate the impact of a transfer of the fuel levy onto the consumer where fuel is an input

in other production processes. However, we do make a rule-of-thumb adjustment for the

public transport sector, where it is assumed that the total amount of the fuel levy is

5 Paraffin was only zero-rated in April of 2001. Although our data are from October 2000, we have

calculated tax incidence as if the zero-rating had applied in 2000 i.e. using the spending behaviour

information of households on paraffin from 2000. We do this to get a more realistic picture of the current

incidence on the poor especially. However, this assumption ignores any knock-on effects that an effective

reduction in the price of paraffin would have on other spending patterns. 6 Another way of approaching this would be to estimate the likely effective VAT rate by using a detailed

input-output table for South Africa. This is not only beyond the scope of the project, but would also lead to

a loss of detail (and precision) as the IES has more detailed expenditure categories than the input-output

table for SA and the categories do not correspond exactly with each other.

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passed on to the consumer and that fuel constitutes 30 per cent of input costs in this

sector.

Table 2. Indirect tax rates and specific duties Tax Item Ad valorem

rate/specific duty VAT VAT-rated Most goods and services (incl. imports) 14% Zero-rated goods

-19 basic food items (brown bread, dried mielies and mealie rice, brown bread flour, samp, eggs, fruit, vegetables, dried beans, lentils, maize meal, rice, pilchards in tins or cans, vegetable cooking oil, milk, cultured milk, milk powder and dairy powder blend, edible legumes and pulses of leguminous plants i.e. peas, beans and peanuts) -Paraffin -Exports -Petrol and diesel -Farming inputs -Sales of going concerns -Certain grants by government

0%

Exempt goods -Residential rental and accommodation -Educational services (including creches) -Public road and rail transport -Non-fee related financial services -Medical aid and medicine/medical services provided by public health institutions

Assumed to be 0%

Excise duties Preparations of sorghum for making beverages 33 cents/kg Mineral water and non-alcoholic beverages 8 cents/litre Beer 2239 cents/litre of

absolute alcohol Sorghum beer 745 cents/100 litres Unfortified wine 6790 cents/100 litres Fortified wine 15360 cents/100 litres Sparkling wine 18811 cents/100 litres Spirits 303365/100 litres of

absolute alcohol Cigars 56989 cents/kg Cigarettes 141.5 cents/10

cigarettes Cigarette tobacco 6412 cents/kg Pipe tobacco 3893 cents/kg Fuel levya Petrol 110.1 cents/litre Diesel 89.4 cents/litre Source: Budget Review 2000, Department of Finance, South Africa Notes: a The levy consists of a fuel levy component and a Road Accident Fund component.

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3.4 Identifying the ‘gender’ incidence of indirect taxes

The biggest methodological challenge that we faced in the project was how to estimate

the gender incidence of indirect taxes. This is because sex is an individual attribute, but

expenditure is collected at the household level in most surveys (and often occurs at the

household level, especially where spending is on indivisible/public goods).

It is common practice in the literature which estimates the incidence of indirect taxes on

individuals by race or by income, for example, to simply assume equal sharing in the

household. So if the total amount of indirect tax paid is R1000 a month in a family of

four, individual incidence would be equal to R250 per person. Assuming equal sharing in

the household and calculating an individual incidence on that basis did not seem

satisfactory for a study on the gender impact of taxes, given that intra-household

allocation of resources is not always equal. The project considered adopting different

sharing rules for different classes of goods, but this proved to be highly contentious and

in the end largely arbitrary, as for most countries little case study (or other) research

exists on the intra-household allocation of resources that could inform our choice of

sharing rules.

Instead, it was decided among the project participants to use an alternative approach to

measuring the gender impact of taxes that would also be more feasible for a cross-country

comparative study. This involved classifying households as being either more ‘female’ or

more ‘male’ and then analysing the tax incidence on the individuals within these

households. We use three definitions to classify households as being ‘male-type’ or

‘female-type’ households. The first simply takes into account the presence of male and

female adults in the household; the second and third try to take into account gendered

spending power in the household by adding the dimension of control over resources,

measured through employment status and household headship. Details are provided

below and in Table 3, which shows the distribution of individuals across the various

household types.

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Table 3. Distribution of individuals across household categories and by quintile (%) Quintile All Q1 Q2 Q3 Q4 Q5 Presence of adults Adult male majority 21.9 15.2 17.5 20.7 22.8 23.8 100 Adult female majority 42.0 26.6 24.2 20.4 17.5 11.3 100 Equal number adults 36.1 15 16.7 19.2 21.3 27.8 100 100 Employment status Male breadwinner 26.4 12.2 15.4 20.8 26.7 24.9 100 Female breadwinner 21.6 20.3 22.9 22.7 20.2 13.9 100 Dual earner 24.2 9.8 12.5 18.6 23.1 36 100 No employed 27.8 35.8 28.8 18.5 10.7 6.3 100 100 Headship Male-headed 59.1 14.7 15.9 19.1 22.6 27.7 100 Female-headed 40.9 27.4 26 21.5 16.3 9 100 100 Average p.c. monthly expenditure per quintile R66.26 R140.37 R250.16 R531.38 R2585.30

Source: Own calculations from IES 2000 Notes: Data are weighted.

The first definition, which uses the presence of male and female adults (aged 18 years

and older) to classify households by gender, results in three categories of household:

adult female majority households (where adult females outnumber adult males), adult

male majority households (where adult males outnumber adult females) and equal

number adult households. In South Africa, 42 per cent of individuals live in adult female

majority households, 22 per cent live in adult male majority households with the

remaining 36 per cent living in households where there are an equal number of adult

males and females.

The employment status definition7 classifies households into four categories: ‘female

breadwinner households’ with at least one employed adult female and no employed adult

males; ‘male breadwinner households’ which contain at least one employed adult male

and no employed adult females; ‘dual earner households’ with at least one employed

adult male and one employed adult female, and households with ‘no employed’. In South

7 In the IES 2000, employment status is based on the following question and prompt, “During the past

seven days, did … do any work for pay, profit or family gain? Formal/informal work, working on a farm,

casual/seasonal work, etc”.

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Africa, this latter group consists mostly of households where either pensions and grants

(predominantly through the government’s social welfare programme) or remittances from

migrant workers form the main source of income (87 per cent of these households) (own

calculations from the South African Labour Force Survey of September 2001).

There are more individuals living in male breadwinner households (26.4 percent)

compared to female breadwinner households (21.6 per cent), with another 24.2 per cent

living in dual earner households. It is not surprising in a country with an unemployment

rate of around 40 per cent for the last decade (using an expanded definition that includes

the non-searching unemployed) that the largest proportion of individuals in South Africa

(27.8 per cent) live in households where there are no employed members.

The headship classification categorises households as either male-headed or female-

headed. The following excerpt from the SSA report on the IES 2000 provides the

definition of headship used in the survey:

“At Statistics SA we have a clear definition of a household head. Respondents may have a

different idea of what ‘household head’ means, and you must explain to them what Stats SA

wants. The head is the person in whose name the dwelling is registered. It may be the person

who owns the dwelling, or is responsible for the rent, or gets the dwelling through their work,

or through their relationship to the owner. If two or more persons have equal claim to be head

of the household, or if people state that they are joint heads or that the household has no

head, then choose the eldest as the head.

A head of a household must be a member of the household. If the head of the household is an

absentee head i.e. he/she does not reside at the dwelling unit for at least 4 nights a week, then

choose the spouse of the head. If the spouse is not a household member, choose the oldest

resident person as the head.” (Statistics SA 2002: 90).

It is interesting to note that a large number (41 per cent) of individuals in South Africa

live in female-headed households. This is due to, among other reasons, a high incidence

of labour migration, particularly among men (resulting in the female in the household

being reported as the de facto resident head), and relatively low levels of marriage and

partnership in South Africa.

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Also evident from Table 3 is that the female-type households and those with no employed

tend to be among the less well-off, concentrated in the lower quintiles of the expenditure

distribution. In contrast, the male-type households, the dual earner households, and the

equal number adult households are more heavily concentrated at the upper end of the

expenditure distribution. This means that any tax policy that has positive gender equity

implications, will also result in strong income equity outcomes. The last row of Table 3

shows the average monthly per capita expenditure of households in quintiles 1 to 5.

These figures highlight the very unequal distribution of expenditure in South Africa, with

the relative increase in average expenditure from quintile 4 to quintile 5 being much

larger than the increases across the lower quintiles (a five-fold increase compared two-

fold increases across the lower quintiles).

For South Africa, there is a large overlap across the three gendered household

classifications, evident from the cross-tabulations in Table 4. For example, just over 80

per cent of female-headed households fall into two employment status categories: 40.7

per cent are in the ‘female breadwinner’ category and 40.6 per cent are in the ‘no

employed’ category. The majority of female-headed households, 71 per cent, are in the

category of female adult majority households. About 73 percent of female adult majority

households fall into the categories of ‘female breadwinner’ (36.6 per cent) and ‘no

employed’ households (35.9 per cent). The tax incidence results, which are presented in

the next section, therefore tell a similar story regardless of the gendered household

definition that is used.

Before moving on to the empirical results, it is important to reiterate the key limitation of

our analysis: that we are unable to estimate an individual incidence for men and women

because we do not have individual level information on expenditure or consumption. So

while we refer to implicit bias in favour of or against male-type households, it is

important to recognise that women living in those households will also bear part of the

tax burden. Table 5 below shows the distribution of males and females across household

types. To take one example which illustrates this point: although the majority of women

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live in either female breadwinner or no employed households, 21 per cent and 23 per cent

live in male breadwinner and dual earner households respectively.

Table 4. Cross-tabulations of individuals by household classification a) Employment status by headship Male-headed Female-headed Male breadwinner 39.5 7.4 Female breadwinner 8.4 40.7 Dual earner 33.2 11.2 No employed 18.8 40.6 100 100 b) Presence of adults by headship Male-headed Female-headed Adult male majority 30.3 9.8 Adult female majority 21.3 71.8 Equal number adult 48.4 18.4 100 100 c) Employment status by presence of adults

Adult male majority

Adult female majority

Equal number adults

Male breadwinner 46.3 10.4 32.9 Female breadwinner 9.1 36.6 11.9 Dual earner 22.2 17.1 33.7 No employed 22.4 35.9 21.5

100 100 100 Source: Own calculations from IES 2000 Notes: Data are weighted.

Table 5. Distribution of males and females across household classifications MALES FEMALES Number % Number % Presence of adults Adult male majority 6 795 431 32.82 2 680 544 11.9 Adult female majority 6 099 400 29.46 12 039 943 53.45 Equal number adults 7 812 318 37.73 7 803 523 34.65 100 100 Employment status Male breadwinner 6 733 645 32.52 4 671 982 20.74 Female breadwinner 3 405 791 16.45 5 949 693 26.41 Dual earner 5 188 428 25.06 5 284 704 23.46 No employed 5 379 285 25.98 6 617 633 29.38 100 100 Headship Male-headed 14 085 323 68.04 11 460 892 50.9 Female-headed 6 615 800 31.95 11 055 689 49.1 100 100 Source: Own calculations from IES 2000 Notes: Data are weighted.

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4. RESULTS

4.1 Total indirect tax incidence

The results of the incidence analysis are presented in Tables 6 to 10 and in the Appendix

Tables A1 to A7. Table 6 reports the overall tax incidence for the different household

types using the three gendered definitions of households. Due to the strong correlations

across household categories reported above, the story that emerges from these results is

consistent regardless of which household definition is used. Total indirect tax incidence is

lower in female-type households than in male-type households, by around a full

percentage point on a base of approximately 8 per cent. This result holds for the different

types of taxes as well, i.e. VAT, excise duties and the fuel levy. The pattern of incidence

among households with no employed members is similar to the pattern among female-

type households, while the dual earner and equal number adult households resemble the

male-type households in their tax incidence.

Table 6. Overall incidence by household types (tax as a percentage of expenditure)

Total Tax VAT Excise

Tax Fuel TaxNumber of Households

Headship Male headed *9.06 *7.17 *0.96 *0.94 7013469 Female headed 7.99 7.08 0.44 0.48 4223448 Employment Categories Male breadwinner *9.36 *7.36 *1.12 *0.88 3581869 Female breadwinner 8.14 7.05 0.45 0.64 2366495 Dual earner *9.15 *7.13 *0.89 *1.14 2227405 None employed *7.84 *6.99 *0.49 *0.37 3064381 Household Sex Composition Adult male majority *9.23 *7.29 *1.1 *0.84 3176551 Adult female majority 8.13 7.07 0.47 0.59 4052582 Equal # adult *8.84 *7.12 *0.85 *0.88 4011016 Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. For example, tax incidence in female-headed households is tested against tax incidence in male-headed households.

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While there are statistically significant gender differences for all three types of taxes, the

largest gender differentials are reported for the excise duties and the fuel levy. Most of

the implicit bias against male-type households is being driven by the larger expenditure

in these households on alcohol and tobacco and on fuel for private transport. The gender

difference in the incidence of the fuel levy would have been even more pronounced if we

had not adjusted for the passing on of the fuel levy to consumers in the public transport

sector. This is because female-type households are relatively more intensive users of

public transport, while male-type households are relatively more intensive users of

private transport.

4.2 Incidence by urban/rural area and by race

In this and the following sub-sections only the results for the employment status

categories are presented. The full set of results for the other two definitions is available in

the Appendix in Tables A1 – A7. Table 7 reports on the incidence of indirect taxes within

urban and rural areas.

In both urban and rural areas, total incidence is higher in male-type and dual earner

households compared to female-type and no employed households. In rural areas, this is

the case for all three types of taxes, i.e. VAT, excises and the fuel levy; whereas in urban

areas this result is being driven by the higher incidence of excise taxes and the fuel levy

on male-type and dual earner households. In urban areas, no employed households bear

the highest incidence of the VAT compared to the other household types, while dual

earner households bear the lowest incidence of the VAT. This explains why the incidence

of VAT in female-headed households is higher than in male-headed households in urban

areas, because a large proportion of female-headed households contain no employed

members (see Table A1).

For male-breadwinner, female-breadwinner and no employed households, indirect tax

incidence is higher in urban areas than in rural areas. In dual earner households, tax

18

incidence is higher in rural areas, driven mostly by the higher incidence of VAT and

excise duties on this type of household in rural areas.

Table 7. Incidence by employment status in urban/rural areas (tax as a percentage of expenditure) URBAN RURAL Employment categories

Total Tax VAT

Excise Tax

Fuel Tax # of HHs Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Male breadwinner *9.43 *7.34 *1.1 *1 2601820 *9.22 *7.39 *1.18 *0.65 980049Female breadwinner 8.44 7.2 0.52 0.71 1532255 7.73 6.84 0.35 0.54 834239Dual earner *9.1 *7.03 *0.81 *1.26 1632130 *9.27 *7.33 *1.05 *0.89 595275None employed 8.45 *7.38 *0.59 *0.48 1444043 *7.48 *6.76 *0.42 *0.3 1620338Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. For example, tax incidence in female-breadwinner households is tested against tax incidence in male-breadwinner households within urban and within rural areas.

Table 8 presents the incidence results by race group. In South Africa, the majority of the

population, 78 per cent, is African, with a further nine and ten percent of the population

Coloured (or of mixed race) and White respectively. Just under three per cent of the

population is of Asian or Indian descent. The results suggest that for all four race groups,

male-breadwinner households bear a larger tax burden than female-breadwinner

households, overall, and for the specific types of taxes. However, some of the differences

are not statistically significant, especially for the Indian race group, because of a very

small number of observations in these categories.8

In general, individuals living in Indian and Coloured households tend to have a higher

indirect tax incidence than in African and White households. Coloured male-breadwinner

and dual earner households bear the highest incidence of total indirect taxes in South

Africa, driven largely by the VAT and excise tax incidence. Indian male-breadwinner and

White dual earner households bear the highest incidence of the fuel levy. The findings are

8 There are also some exceptions to this general finding when analysing the results for the other household

definitions. Table A2 in the Appendix shows that Coloured and Indian female-headed households bear a

higher VAT incidence than Coloured and Indian male-headed households. And Indian and White female-

dominated households bear a higher VAT burden than Indian and White male-dominated households, but

these latter differences are not statistically significant.

19

likely to be driven more by the income class that these households fall into than their

race. African households are concentrated at the lower end of the income distribution,

while Indian and especially White households are concentrated at the upper end of the

income distribution. Coloured households tend to fall in the middle of the distribution

and, as we will see in the next section, tax incidence falls most heavily on the middle

quintiles in South Africa, except for the fuel levy, which is highly progressive.

Table 8. Incidence by employment status and race (tax as a percentage of expenditure) AFRICAN COLOURED Employment Categories

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Male breadwinner *9.32 *7.44 *1.13 *0.74 2739562 *10.36 *7.98 *1.63 *0.76 275064Female breadwinner 7.98 7.03 0.39 0.56 1951964 9.57 7.88 1.07 0.62 174504Dual earner *9.11 *7.25 *0.87 *0.99 1211408 *9.99 7.75 *1.32 *0.92 318950None employed *7.7 *6.93 *0.46 *0.31 2558904 *9.44 *8.15 *0.87 *0.42 145776 INDIAN WHITE Employment Categories

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Male breadwinner 9.84 *7.21 0.74 1.9 108193 *8.62 6.3 0.75 *1.58 443013Female breadwinner 9.24 6.85 0.66 1.73 32795 8.56 6.31 0.6 1.65 203127Dual earner 9.07 6.79 0.61 1.67 99553 8.67 6.3 *0.66 *1.71 593096None employed 9.03 *7.52 0.85 *0.66 42520 *8.84 *6.82 0.62 1.41 314173Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. For example, tax incidence in African female-breadwinner households is tested against tax incidence in African male-breadwinner households.

4.3 Incidence by quintile and by presence of children

The results in Table 9 indicate that female-breadwinner households and those with no

employed bear a lower tax incidence than male-breadwinner and dual earner households,

regardless of which expenditure quintile the households are in. This is the case for total

indirect taxes and for the different types of taxes.

For all four of the employment status household categories, total indirect tax incidence

tends to fall most heavily on the middle quintiles, particularly quintiles three and four,

20

with the poorest quintile paying a smaller share of expenditure on tax than the richest

quintile. For VAT and excise duties, the incidence is predominantly on the middle

quintiles, while the fuel levy is strongly progressive.9

Table 9. Incidence by employment status and quintile (tax as a percentage of expenditure)

Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Quintile Male breadwinner Female breadwinner 1 *8.17 *6.98 *0.85 0.35 217382 6.9 6.27 0.29 0.33 3026592 *8.95 *7.4 *1.08 *0.47 333905 8.2 7.27 0.52 0.41 4018293 *9.64 *7.78 *1.24 0.62 571690 8.72 7.59 0.49 0.64 4929504 *9.92 *7.53 *1.31 *1.08 1077101 8.73 7.43 0.53 0.77 6026275 *9.36 *6.97 *0.99 *1.4 1381791 8.08 6.41 0.41 1.25 566430Total *9.36 *7.36 *1.12 *0.88 3581869 8.14 7.05 0.45 0.64 2366495 Dual earner None employed 1 *7.95 *6.73 *0.9 0.33 133016 7 *6.39 *0.39 *0.23 6852632 *9.24 *7.45 *1.23 *0.57 208823 *7.82 *7.12 *0.44 *0.26 7115763 *9.5 *7.7 *1.04 *0.76 343163 *8.56 7.63 *0.59 *0.34 6502514 *10.07 *7.78 *1.01 *1.27 505634 *8.96 *7.67 *0.72 *0.56 5850655 *8.69 6.4 *0.61 *1.68 1036768 *8.72 *6.73 *0.56 *1.43 432227Total *9.15 *7.13 *0.89 *1.14 2227405 *7.84 *6.99 *0.49 *0.37 3064381Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence in female-breadwinner households in quintile one is tested against tax incidence in male-breadwinner households in quintile one

When disaggregated by the presence of children (aged 17 years or younger) in the

household, some differences in the patterns of tax incidence across the quintiles emerge.

These results are presented in Table 10, but the ‘regressivity’/’progressivity’ of the tax is

more clearly visible in Figures 2 to 5 below. For both male-breadwinner and female-

breadwinner households without children, the incidence of excise duties tends to be more

‘regressive’ and the VAT incidence more ‘proportional’ (i.e. the inverted-U shape of the

VAT curves is less pronounced) compared to those households with children. 9 These results are largely consistent with those in Woolard et al (2005). Using the data from the IES 2000,

they find that the VAT and excise incidence falls largely on the middle deciles when expressed as a

percentage of total expenditure. However, when expressed as a percentage of total income, they find the

incidence of these taxes to be regressive. They note that “this appears to be an artifact that is the result of

the large mismatch between income and expenditures in the bottom and top deciles” (Woolard et al 2005:

46). Because of concerns with the reliability of the income data in this survey, we do not try to replicate our

results using income as a base when calculating tax incidence.

21

Figure 2. Total tax incidence by employment status, quintile and presence of children

66.5

77.5

88.5

99.510

10.511

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

Male W Child Male W/O Child Female W ChildFemale W/O Child Dual W Child Dual W/O ChildNone W Child None W/O Child

Figure 3. VAT incidence by employment status, quintile and presence of children

6

6.5

7

7.5

8

8.5

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

Male W Child Male W/O Child Female W ChildFemale W/O Child Dual W Child Dual W/O ChildNone W Child None W/O Child

22

Figure 4. Excise incidence by employment status, quintile and presence of children

0

0.5

1

1.5

2

2.5

3

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

Male W Child Male W/O Child Female W ChildFemale W/O Child Dual W Child Dual W/O ChildNone W Child None W/O Child

Figure 5. Fuel levy incidence by employment status, quintile and presence of children

00.20.40.60.8

11.21.41.61.8

2

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

Male W Child Male W/O Child Female W ChildFemale W/O Child Dual W Child Dual W/O ChildNone W Child None W/O Child

23

Table 10. Incidence by employment status, presence of children, and quintile (tax as a percentage of expenditure)

Quintile Total Tax VAT Excise

Tax Fuel Tax # of HHs Quintile Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Male Breadwinner WITH children Male Breadwinner WITHOUT children 1 *8.13 *6.97 *0.81 0.35 192052 1 9.36 7.25 *1.85 *0.26 25330 2 *8.88 *7.38 *1.01 *0.48 272052 2 *9.77 7.6 *1.85 *0.32 61853 3 *9.61 *7.83 *1.15 0.64 384242 3 *9.82 *7.51 *1.77 0.54 187448 4 *9.77 7.54 *1.12 *1.11 448169 4 *10.22 *7.51 *1.67 1.04 628932 5 *8.83 *6.64 *0.65 *1.53 321974 5 *9.84 *7.26 *1.29 *1.29 1059817 Total *9.14 *7.34 *0.98 *0.82 1618489 Total *9.95 *7.39 *1.51 *1.06 1963380Female Breadwinner WITH children Female Breadwinner WITHOUT children 1 6.87 6.26 0.29 0.32 283696 1 8.36 7.03 0.59 0.74 18963 2 8.2 7.28 0.52 0.4 347570 2 8.18 7.08 0.58 0.51 54259 3 8.78 7.65 0.47 0.66 351347 3 8.36 7.23 0.61 0.52 141604 4 8.83 7.5 0.55 0.78 324200 4 8.41 7.19 0.47 0.74 278427 5 7.87 6.19 0.4 1.28 229069 5 8.37 6.73 0.43 1.21 337361 Total 8.11 7.06 0.45 0.6 1535881 Total 8.37 7.01 0.5 0.86 830614Dual Employed HHs WITH children Dual Employed HHs WITHOUT children 1 *7.94 *6.72 *0.89 0.33 126672 1 8.62 7.07 *1.35 *0.21 6344 2 *9.22 *7.45 *1.19 *0.58 184222 2 *9.72 *7.43 *1.9 0.38 24602 3 *9.48 *7.71 *0.97 *0.8 288317 3 *9.79 *7.67 *1.79 *0.33 54846 4 *10.02 *7.73 *0.95 *1.34 370949 4 *10.35 *8.09 *1.39 *0.87 134685 5 *8.57 6.35 *0.56 *1.66 633080 5 *8.99 6.54 *0.74 *1.71 403688 Total *9.11 *7.14 *0.86 *1.11 1603241 Total *9.39 *7.02 *1.03 *1.33 624164None Employed WITH children None Employed WITHOUT children 1 *6.98 *6.38 *0.37 *0.23 627507 1 *7.66 6.48 0.97 *0.21 57755 2 *7.83 *7.14 *0.43 *0.26 614875 2 *7.76 *6.84 0.72 *0.2 96701 3 *8.56 7.7 0.51 *0.36 418507 3 *8.54 7.34 *0.93 *0.28 231744 4 8.91 *7.87 *0.42 *0.62 180410 4 *9.01 *7.46 *1.04 *0.51 404655 5 *8.76 6.59 0.32 *1.85 42480 5 *8.71 6.77 *0.62 *1.32 389746 Total *7.7 *6.97 0.42 *0.31 1883780 Total 8.58 7.09 *0.85 *0.64 1180601Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence in female-breadwinner households with children in quintile one is tested against tax incidence in male-breadwinner households with children in quintile one.

With few exceptions, the main gender findings hold: regardless of the presence of

children in the household or the quintile, female-breadwinner households and those with

24

no employed members bear a lower incidence than male-breadwinner and dual-earner

households, for total indirect taxes and for the different types of taxes.10

Within each household category, households with children bear a lower total indirect tax

burden than those without children, driven mostly by the differences in the incidence of

excise duties and the fuel levy. There are some exceptions to this when analyzed by

quintile: for example, female breadwinner and no employed households with children in

the middle quintiles have a higher total tax incidence than those female breadwinner and

no employed households without children. This is generally being driven by the VAT and

fuel levy incidence being higher in those quintiles among the households with children.

4.4 Incidence by consumption category

Table A5 reports total indirect tax incidence by consumption category for the

employment status categories (note that this table and the table with the results for the

headship and household composition categories are in the Appendix due to space

constraints here). A comparison of the results for the male- and female-breadwinner

categories only is graphed below in Figure 6. We allocate the large number of

consumption items in the IES into 25 main categories (loosely based on the United

Nations Classification of Individual Consumption According to Purpose or COICOP).

We find that, even though female-type households bear a lower overall indirect tax

incidence, some interesting gender biases do emerge when the data are disaggregated into

consumption categories.

The gender differences that emerge are largely consistent with the broader international

literature on gendered spending patterns. Female breadwinner households bear a greater

10 Two exceptions are that female-breadwinner households without children in the lowest two quintiles bear

a higher incidence of the fuel levy than the other categories of household without children in those

quintiles, and no employed households with children in the highest quintile bear a higher burden of the fuel

levy and VAT than most other household types in that quintile.

25

tax incidence on food (non zero-rated items as well as sugar/confectionary items),

utilities, children’s clothing, personal care items (both necessity and other more non-

essential items), fuel for household use, and education (although education is exempt,

textbooks and stationery attract VAT in this category). Male breadwinner households

bear a greater tax incidence on meals out, non-alcoholic beverages, alcoholic beverages

(particularly beer), tobacco, adult’s clothing, private transport, fuel for transport, medical

expenditure (as private health care attracts VAT), communication and recreation. Again,

dual earner households in the most part resemble the male breadwinner households, and

no employed households resemble the female breadwinner households in their spending

patterns.

Consumption items for which taxes are generally more ‘progressive’ (for all household

types) are housing, meals out, private transport, fuel for transport, communication and

recreation; while items for which taxes are more ‘regressive’ are food, children’s

clothing, personal care necessities, fuel for household use and education. The tax

incidence on non-alcoholic and alcohol beverages and tobacco generally falls most highly

on the middle quintiles. (This is also displayed in Figures 7 to 9 below, which plot tax

incidence by quintile on food, alcohol and tobacco.) It is interesting to note that many of

the items for which the tax is more ‘regressive’ and that might also be considered ‘good’

or necessity items are those consumed more intensively by female breadwinner and no

employed households.

26

Figure 6. Incidence by commodity group: male and female breadwinner

0 0.5 1 1.5 2 2

Housing and utilities

-Housing

-Utilities

Food

-Basic

-Other

-Sugar/confectionary

Meals out

Non-alcoholic beverages

Alcoholic beverages

-Spirits

-Wine

-Beer

Tobacco

Clothing and footw ear

-Adult clothing

-Children's clothing

Personal care

-Necessities

-Baby products

-Other

Fuel for HH use

Furniture, etc

Domestic and household services

Transportation

-Private Transport

-Public/Collective transport

Fuel for transport

Medical exp

Education

Communication

Recreation

Gambling

Misc

Tax/Exp share (%)

.5

Male breadwinner Female breadwinner

Source: Own calculations from IES 2000 Notes: - denotes subcategory

27

Figure 7. Food tax incidence by employment category and quintile

0

0.5

1

1.5

2

2.5

3

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

MaleFemaleDualNone

Figure 8. Alcohol tax incidence by employment category and quintile

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

MaleFemaleDual None

Figure 9. Tobacco tax incidence by employment category and quintile

00.20.40.60.8

11.21.4

1 2 3 4 5

Quintile

Tax/

exp

shar

e (%

)

MaleFemaleDual None

Source: Own calculations from IES

28

When the tax incidence results by consumption item are further disaggregated by

presence of children in the household, the findings from earlier are reinforced (see table

A7 in the Appendix which provides the disaggregated results for the headship category

only). A comparison between male-type households with children and female-type

households with children, finds that male-type households with children bear a higher

incidence of taxes particularly on housing, meals out, alcoholic beverages, tobacco,

adult’s clothing, private transport, fuel for transport, communication and recreation;

while female-type households with children bear a higher burden on food, children’s

clothing, basic personal care items and other non-essential personal care items, fuel for

household use and furniture, equipment and household maintenance items.

Both male-type and female-type households with children bear a lower incidence overall

compared to the households without children, but a higher incidence on certain

consumption items such as: housing, food, children’s clothing, personal care (esp.

necessities and nappies), fuel for household use, furniture etc and education. In contrast,

male-type and female-type households without children bear a higher incidence on meals

out, non-alcoholic and alcoholic beverages, tobacco, other non-necessity personal care

items, adult’s clothing, transport, fuel for transport, (private) medical expenditure,

communication and recreation. These results suggest that, if we had to divide spending

very crudely into ‘good’/necessity items and ‘bad’/luxury items, the presence of women

(with spending power) and children in the household is associated with a greater

proportion of spending on the former basket of goods.

29

5. SIMULATIONS AND POLICY SUGGESTIONS

In this section, we consider the possibility of zero-rating additional items that would

benefit poor female breadwinner and no employed households that contain children in

particular. We estimate the distributional and revenue consequences of zero-rating the

following goods: 1) all other (non-confectionary) food items that are not currently zero-

rated; 2) children’s clothing and footwear;11 3) a basket of basic personal care items

(toilet paper, toothpaste/toothbrushes, soap, tissues, contraception, sanitary towels); 4)

poultry; 5) baby food (milk and grain only); and 6) other fuels for household use

(particularly coal, firewood and candles).

These goods were chosen on the basis that a) they are recurring expenditure items and b)

they make up a larger relative share of the budget of female breadwinner and no

employed households (particularly those with children and in the lower quintiles)

compared to male breadwinner and dual earner households.12 This last criterion by

definition results in strong gender and income distributional outcomes for all of the

policy experiments - we are interested therefore in which policy changes have the largest

relative effect without resulting in unfeasible revenue losses for the fiscus. For

comparison, we also estimate the effect of VAT rating items that are currently zero-rated,

i.e. basic food items and paraffin.

The results of the policy simulations are presented in Table 11. The table shows the

percentage change to the average incidence for that household category following the

policy change, as well as the relative gender and income gains/losses. The findings

suggest that some of the largest income equity gains have already been exhausted through

the government’s current zero-rating of basic food items and paraffin. The zero-rating of

11 All non-confectionary food items and children’s clothing are currently zero-rated in the UK. 12 White bread, white sugar and tea were excluded because of the nutritional implications, although they do

form a larger relative share of the budgets of (poor) female-type households compared to male-type

households.

30

these items has also resulted in substantial gender equity outcomes, benefiting female

breadwinner and no employed households the most in relative terms.

Table 11. Effect on tax incidence and govt. revenue of VAT/zero-rating certain items Base

incidence Effect of VAT-

rating (% change)

Effect of ZERO-rating (% change)

Tax incidence (% of exp)

Basic food

Paraffin Other non-conf. food items

Children’s clothing

Basic personal care items

Poultry Baby food

(milk & grain)

Coal, firewood, candles

Male breadwinner 9.36 23.29 2.03 -20.19 -2.99 -3.21 -4.38 -0.50 -1.23

Female breadwinner 8.14 33.91 2.95 -24.45 -4.42 -4.18 -5.59 -0.71 -1.86

Dual earner 9.15 19.56 1.42 -19.02 -2.95 -2.73 -3.68 -0.50 -1.11 No employed 7.84 45.92 4.34 -25.89 -4.85 -4.72 -6.60 -0.95 -2.67 Ratio female/male % change

1.46 1.45 1.21 1.48 1.30 1.28

1.40

1.51 Q1 7.28 60.03 5.22 -26.37 -5.91 -5.77 -7.29 -1.27 -3.67 Q2 8.36 41.27 4.07 -25.96 -5.26 -4.78 -6.76 -0.89 -2.63 Q3 9.11 29.09 2.74 -24.15 -3.95 -3.95 -5.65 -0.73 -1.77 Q4 9.56 18.83 1.36 -21.44 -2.72 -2.93 -4.07 -0.38 -0.72 Q5 8.82 8.39 0.23 -14.17 -1.59 -1.59 -1.81 -0.15 -0.15 RatioQ1-3/Q4-5 % change 4.79 7.57 2.15 3.51 3.21 3.35

5.43

9.29

Total 8.63 30.13 2.55 -22.25 -3.82 -3.71 -5.00 -0.66 -1.69 Loss/gain to fiscus per year (millions Rands, 2000 prices)

3 876 229 -4 788 -576 -618 -761 -78 -151.2

Source: Own calculations from IES 2000 Notes: Data are weighted.

Of the six policy experiments, the zero-rating of baby food (milk and grain only), other

sources of fuel for household use (i.e. coal, firewood and candles) and children’s clothing

provide the largest relative gender and income equity benefits. However, the percentage

changes to the indirect tax incidence across households due to the zero-rating of baby

food and other sources of fuel for household use are very small, as these two sets of

commodities make up a very small share of the household budget. In addition, for the

31

former there is some concern about the implications for breastfeeding13 , while for the

latter, there are possible environmental consequences. The potential zero-rating of

children’s clothing would therefore would seem to be the most attractive policy

recommendation, as it imposes no obvious negative externalities. Although the income

equity impact of such a policy is not as high as the impact of the zero-rating of basic

foodstuffs or paraffin, the relative gender gains are even higher than for these goods. The

zero-rating of basic children’s clothing and footwear would also be attractive because of

its perfect targeting to households with children.

Although the revenue loss to the fiscus of this policy change (576 million Rands per

annum in 2000 prices) is more than double the loss incurred through the zero-rating of

paraffin, it amounts to a relatively small percentage of the total VAT intake (only 1.2 per

cent, using the budget estimate for 2000). In comparison, the reduction in revenue from

the zero-rating of all other non-confectionary foodstuffs would amount to a loss of over

10 per cent of the total VAT intake. Put another way, the loss of revenue from the zero-

rating of children’s clothing is the equivalent of about 1 per cent of the education budget

for that year and only about half a per cent of the total social services budget (National

Treasury, 2000).

We would not encourage the revenue loss from this policy change to be financed from

within the indirect tax system. Given that it is not possible to accurately estimate the

gender incidence of indirect taxes within the household or to measure any behavioural

change following a tax policy adjustment, a tax increase based on static household

incidence results may have unintentional negative effects. For example, raising the excise

duties on alcohol and tobacco (based on the demerit argument or because the tax

incidence of these goods falls more heavily on male-type households), could result in

13 We assumed that this argument wouldn’t hold in the context of mother-to-child transmission of

HIV/Aids, but we have been alerted to medical evidence which suggests that unless optimal conditions for

the preparation of formula milk exists (such as clean water, access to electricity, etc) breastfeeding is the

less risky option, even for mothers with full blown aids (thanks is due to Nigel Rollins from the WHO for

this information).

32

perverse gender effects within the household if income is substituted away from

‘necessity’/‘female’ goods to finance the inelastic demand for these items.14 Instead, in

the light of the current budget surplus for 2007/08, and the projected budget surplus for

2008/09 (National Treasury 2008), we would argue that there is little need to raise this

relatively small of amount of additional revenue through the tax system.

6. CONCLUDING REMARKS

The findings of this study on the incidence of indirect taxes in South Africa suggest that

there is no implicit bias overall against ‘female-type’ households, those in the lowest

quintiles, and those with children. Instead, the high taxes on alcohol and tobacco and the

fuel levy result in a bias against ‘male-type households’ and those without children. The

zero-rating of basic food items and paraffin, goods which are consumed relatively more

by poor female-type households with children, has helped to protect these households

from carrying a disproportionate share of the indirect tax burden.

Implicit bias against female-type households in the indirect tax system is visible only

when the results are disaggregated into different consumption categories: female-type

households (in the lowest quintile and with children) bear a higher burden on ‘good’ or

necessity items such as food, basic personal care items, children’s clothing and fuel for

household use. Our policy simulations suggest that the zero-rating of children’s clothing

in particular may be a feasible recommendation as it has large gender and income

distributional impacts, it perfectly targets households with children, but has relatively

small revenue implications.

However, any change to the indirect tax system that benefits female-type households

needs to be evaluated against the trade-off of introducing further horizontal inequity (and

14 It is important to note here that although the majority of women (56 per cent) in South Africa live in

female breadwinner or no employed households, 21 percent live in male breadwinner households and 23

per cent live in dual earner households. Therefore any policy that affects these households will of course

also have an impact on the women (and children) living there.

33

complexity) into the indirect tax system. In addition, changes to the indirect tax system

(that are feasible in terms of revenue loss to the fiscus) are likely to have a rather

marginal effect on pre-tax gender and income inequities. Policies to reduce unequal

outcomes for women and children may be better directed from the expenditure side of

budget, particularly through the continued and extended provision of social welfare

grants to those in need.

34

7. REFERENCES

Alderman, H. and del Ninno, C. (1999) “Poverty Issues for Zero Rating Value-Added

Tax (VAT) in South Africa”, World Bank Informal Discussion Paper, No. 19336.

Aizenman, J. and Y. Jinjarak (2006). “Globalization and developing countries - a

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37

8. APPENDIX Table A1. Incidence by headship and household composition in rural/urban area (tax as a percentage of expenditure) URBAN RURAL

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Total Tax VAT

Excise Tax Fuel Tax # of HHs

Headship Male-headed *9.17 *7.16 *0.93 *1.08 4908450 *8.89 *7.19 *1.01 *0.68 2105019Female-headed 8.49 7.36 0.54 0.6 2299781 7.55 6.83 0.34 0.38 1923666Household composition Adult male majority *9.46 *7.36 *1.1 *0.99 2191043 *8.85 *7.16 *1.09 *0.6 985508Adult female majority 8.55 7.27 0.54 0.74 2300099 7.71 6.86 0.4 0.45 1752482Equal # adult *8.98 *7.11 *0.85 *1.03 2719105 *8.6 *7.13 *0.85 *0.62 1291911Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. For example, tax incidence in female-headed households is tested against tax incidence in male-headed households within urban and within rural areas.

38

Table A2. Incidence by headship and household composition and by race (tax as a percentage of expenditure)

Total Tax VAT Excise TaxFuel Tax # of HHs Total Tax VAT Excise Tax Fuel Tax# of HHs

AFRICAN COLOURED Headship Male-headed *8.98 *7.26 *0.96 *0.76 4894946 *10.01*7.74 *1.38 *0.89 623781Female-headed 7.83 7.02 0.38 0.43 3564530 9.81 8.25 1.12 0.44 290160Household composition Adult male majority *9.14 *7.33 *1.1 *0.72 2608230 *10.43 8.13 *1.55 0.75 189899Adult female majority 7.92 7.01 0.4 0.51 3273148 9.72 8 1.05 0.67 321234Equal # adult *8.7 *7.22 *0.82 *0.67 2580459 *9.92*7.67 *1.42 *0.83 403160 INDIAN WHITE Headship Male-headed 9.44 *6.99 *0.72 *1.73 229642 *8.69 6.37 0.68 *1.641242370Female-headed 9.08 7.32 0.55 1.21 53420 8.5 6.37 0.62 1.52 310520Household composition Adult male majority 9.93 6.99 *0.75 2.18 71982 *8.65 6.13 *0.75 *1.77 294971Adult female majority 9.38 7.15 0.63 1.6 74927 8.6 6.48 0.65 1.47 378463Equal # adult *9.08 *7.01 0.7 1.38 136153 *8.69 6.39 0.66 *1.64 879974

Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. For example, tax incidence in African female-headed households is tested against tax incidence in African male-headed households.

39

Table A3. Incidence by headship and household composition and by quintile (tax as a percentage of expenditure)

Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Headship Male-headed Female-headed 1 *7.81 *6.7 *0.8 *0.31 594701 6.87 6.34 0.27 0.26 7424392 *8.76 *7.34 *0.98 *0.44 766405 8 7.2 0.47 0.33 8894483 *9.5 *7.7 *1.13 *0.67 1143779 8.61 7.65 0.47 0.48 9142764 *9.85 *7.55 *1.15 *1.16 1827257 8.97 7.7 0.61 0.66 9423355 *8.97 *6.65 *0.76 *1.56 2681326 8.17 6.49 0.44 1.24 734949Total *9.06 *7.17 *0.96 *0.94 7013469 7.99 7.08 0.44 0.48 4223448Household composition Adult male majority Adult female majority 1 *7.67 *6.68 *0.76 *0.23 245150 7.07 6.4 0.37 0.3 6978062 *8.8 *7.37 *1.01 *0.42 317859 8.1 7.25 0.47 0.38 8030823 *9.52 *7.76 *1.14 *0.62 498443 8.64 7.58 0.52 0.54 8220524 *10.05 *7.58 *1.37 *1.1 903261 9.13 7.64 0.61 0.87 9278525 *9.52 *6.92 *1.09 *1.5 1211838 8.2 6.4 0.42 1.38 801790Total *9.23 *7.29 *1.1 *0.84 3176551 8.13 7.07 0.47 0.59 4052582 Equal # adults 1 *7.49 *6.59 *0.62 *0.28 395363 2 *8.51 7.21 *0.93 0.37 535192 3 *9.41 *7.75 *1.05 *0.62 737560 4 *9.64 7.57 *1.04 *1.03 939314 5 *8.75 *6.56 *0.63 *1.56 1403588 Total *8.84 *7.12 *0.85 *0.88 4011016 Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence in female-headed households in quintile one is tested against tax incidence in male-headed households in quintile one.

40

41

Table A4. Incidence by headship and household composition, presence of children, and quintile (tax as a percentage of expenditure)

Quintile Total Tax VAT Excise

Tax Fuel Tax # of HHs Quintile Total Tax VAT

Excise Tax

Fuel Tax # of HHs

Male-headed WITH children Male-headed WITHOUT children 1 *7.77 *6.69 *0.77 *0.31 522531 1 *8.69 6.89 *1.53 0.26 72170 2 *8.75 *7.35 *0.94 *0.46 624999 2 *8.99 7.25 *1.46 *0.28 141406 3 *9.53 *7.76 *1.06 *0.71 760166 3 *9.31 7.37 *1.52 0.42 383613 4 *9.79 *7.55 *0.99 *1.24 851305 4 *10.01 *7.54 *1.54 *0.93 975952 5 *8.65 6.44 *0.58 *1.63 972121 5 *9.4 *6.94 *1 *1.47 1709205 Total *8.93 *7.17 *0.87 *0.89 3731122 Total *9.52 *7.18 *1.26 *1.09 3282346Female-headed WITH children Female- headed WITHOUT children 1 6.86 6.33 0.27 0.26 706218 1 7.35 6.56 0.42 0.37 36222 2 8 7.21 0.46 0.33 793439 2 8.06 7.04 0.66 0.36 96009 3 8.61 7.68 0.44 0.49 682248 3 8.57 7.47 0.7 0.41 232028 4 9.05 7.79 0.58 0.68 471904 4 8.76 7.49 0.67 0.6 470431 5 8.01 6.29 0.4 1.32 253542 5 8.38 6.75 0.5 1.14 481407 Total 7.92 7.06 0.41 0.45 2907351 Total 8.48 7.17 0.61 0.7 1316096Adult male majority WITH children Adult male majority dominated WITHOUT children 1 *7.63 *6.68 *0.72 *0.23 189815 1 8.14 6.62 *1.24 0.29 55335 2 *8.79 *7.41 *0.95 *0.43 224231 2 *8.86 7.14 *1.38 0.33 93627 3 *9.53 *7.88 *0.97 *0.69 238511 3 *9.48 *7.39 *1.67 0.41 259932 4 *10 *7.66 *1.03 *1.31 203948 4 *10.1 7.5 *1.72 0.87 699313 5 *9.16 *6.61 *0.62 *1.93 156954 5 *9.7 *7.08 *1.33 1.28 1054884 Total *8.99 *7.31 *0.88 *0.79 1013460 Total *9.68 *7.24 *1.5 *0.93 2163091Adult female majority WITH children Adult female majority WITHOUT children 1 7.05 6.4 0.36 0.3 668676 1 7.86 6.78 0.69 0.39 29130 2 8.09 7.25 0.45 0.38 729232 2 8.57 7.38 0.85 0.34 73849 3 8.69 7.63 0.52 0.54 652932 3 8.11 7.06 0.55 0.5 169120 4 9.29 7.72 0.63 0.94 512814 4 8.54 7.37 0.54 0.63 415038 5 8.16 6.25 0.42 1.49 307364 5 8.26 6.63 0.41 1.22 494426 Total 8.1 7.07 0.47 0.56 2871018 Total 8.34 7.01 0.52 0.82 1181564Equal # adults WITH children Equal # adults WITHOUT children 1 *7.46 *6.57 *0.6 *0.28 371437 1 8.75 7.12 *1.42 0.21 23926 2 *8.52 7.23 *0.92 0.37 465254 2 *8.36 6.98 *1.11 0.27 69938 3 *9.45 7.76 *1.03 *0.66 550970 3 *9.21 *7.69 *1.17 0.36 186590 4 *9.58 *7.53 *0.99 *1.06 606965 4 *9.87 *7.69 *1.24 *0.94 332349 5 *8.54 *6.43 *0.59 *1.52 762285 5 *9.22 *6.86 *0.72 *1.65 641302 Total *8.73 *7.09 *0.82 *0.82 2756912 Total *9.33 *7.22 *0.96 *1.15 1254104Source: Own calculations from IES 2000 Notes: Data are weighted. * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence in female-headed households with children in quintile one is tested against tax incidence in male-headed households with children in quintile one.

Table A5. Incidence for main commodity groups by employment status and quintiles (tax as a percentage of expenditure) Male Breadwinner Female Breadwinner

Category 1 2 3 4 5 Total 1 2 3 4 5 Total Housing and utilities 0.55 0.52 0.69 0.73 0.73 *0.67 0.48 0.7 0.84 0.8 0.79 0.72

-Housing 0.04 0.02 0.04 0.07 0.14 0.07 0.03 0.04 0.05 0.08 0.13 0.06-Utilities 0.52 0.51 0.64 0.66 0.59 *0.6 0.45 0.66 0.79 0.72 0.66 0.66

Food 2.6 2.69 2.52 2.26 1.43 *2.22 2.49 2.7 2.64 2.35 1.49 2.4-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.99 2.23 2.18 2.01 1.29 *1.9 1.89 2.22 2.27 2.06 1.33 2.01

-Sugar/confectionary 0.61 0.46 0.34 0.25 0.15 *0.32 0.6 0.48 0.37 0.29 0.16 0.4Meals out 0.01 0.07 0.1 0.14 0.27 *0.14 0.04 0.03 0.07 0.13 0.21 0.09Non-alcoholic beverages 0.36 0.43 0.44 0.4 0.31 *0.39 0.35 0.4 0.39 0.39 0.27 0.37Alcoholic beverages 0.39 0.61 0.7 0.73 0.63 *0.64 0.09 0.23 0.22 0.3 0.17 0.21

-Spirits 0.03 0.06 0.09 0.11 0.17 *0.1 0.01 0.03 0.03 0.05 0.05 0.03-Wine 0.03 0.03 0.03 0.03 0.03 *0.03 0.01 0 0.01 0.02 0.02 0.01-Beer 0.33 0.51 0.58 0.59 0.43 *0.51 0.07 0.2 0.18 0.23 0.1 0.16

Tobacco 0.9 1.02 1.16 1.23 0.85 *1.05 0.31 0.52 0.45 0.47 0.41 0.44Clothing and footwear 0.79 0.88 0.91 0.86 0.68 0.82 0.69 0.87 0.89 0.89 0.66 0.81

-Adult clothing 0.33 0.48 0.59 0.63 0.55 *0.54 0.25 0.42 0.52 0.6 0.46 0.45-Children's clothing 0.45 0.4 0.31 0.23 0.13 *0.28 0.44 0.45 0.37 0.29 0.19 0.36

Personal care 0.74 0.79 0.72 0.63 0.48 *0.65 0.8 0.81 0.81 0.77 0.56 0.77-Necessities 0.43 0.39 0.35 0.28 0.16 *0.3 0.42 0.42 0.36 0.3 0.17 0.35

-Baby products 0.01 0.02 0.01 0.01 0.02 0.01 0 0.01 0.01 0.01 0.02 0.01-Other 0.3 0.38 0.36 0.34 0.3 *0.34 0.37 0.39 0.44 0.46 0.38 0.41

Fuel for HH use 0.41 0.28 0.18 0.12 0.05 *0.17 0.31 0.27 0.23 0.12 0.06 0.21Furniture, HH Equipment and Maintenance 0.66 0.63 0.74 0.69 0.6 0.66 0.6 0.64 0.74 0.77 0.5 0.66Domestic and household services 0 0.01 0.02 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01Transportation 0.01 0.05 0.1 0.22 0.7 *0.26 0.02 0.02 0.06 0.09 0.54 0.12

-Private Transport 0.01 0.05 0.1 0.22 0.7 *0.26 0.02 0.02 0.06 0.09 0.54 0.12-Public/Collective transport

42

0 0 0 0 0 0 0 0 0 0 0 0Fuel for transport 0.34 0.45 0.62 1.07 1.4 *0.87 0.33 0.41 0.64 0.77 1.24 0.63Medical expenditure 0.05 0.07 0.07 0.07 0.1 *0.08 0.04 0.06 0.07 0.07 0.11 0.07Education 0.06 0.05 0.03 0.03 0.03 *0.04 0.1 0.06 0.05 0.05 0.04 0.06Communication 0.12 0.11 0.2 0.26 0.36 *0.23 0.09 0.14 0.22 0.26 0.43 0.21Recreation 0.08 0.11 0.21 0.25 0.48 *0.26 0.04 0.1 0.16 0.24 0.38 0.17Gambling 0.02 0.03 0.03 0.03 0.02 *0.03 0 0.01 0.02 0.02 0.01 0.01Miscellaneous 0.08 0.16 0.21 0.17 0.23 *0.18 0.1 0.21 0.22 0.24 0.2 0.19TOTAL 8.17 8.95 9.64 9.92 9.36 *9.36 6.9 8.2 8.72 8.73 8.08 8.14

Dual earner None employed Category 1 2 3 4 5 Total 1 2 3 4 5 Total

Housing and utilities 0.35 0.5 0.68 0.83 0.8 *0.7 0.48 0.64 0.87 0.94 1.08 0.68

-Housing 0.04 0.06 0.08 0.12 0.19 *0.12 0.03 0.05 0.07 0.08 0.17 0.06-Utilities 0.31 0.45 0.61 0.71 0.61 *0.58 0.45 0.59 0.79 0.86 0.91 0.63

Food 2.55 2.57 2.5 2.32 1.28 *2.03 2.67 2.72 2.67 2.45 1.63 *2.6-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.95 2.12 2.17 2.07 1.15 *1.75 1.93 2.15 2.22 2.13 1.45 *2.04

-Sugar/confectionary 0.6 0.44 0.33 0.25 0.14 *0.28 0.73 0.58 0.45 0.33 0.18 *0.56Meals out 0.07 0.07 0.13 0.15 0.19 *0.14 0.02 0.02 0.1 0.07 0.15 *0.05Non-alcoholic beverages 0.35 0.39 0.39 0.38 0.22 *0.32 0.37 0.41 0.43 0.42 0.27 *0.39Alcoholic beverages 0.35 0.78 0.53 0.49 0.35 *0.47 0.12 0.18 0.28 0.39 0.32 0.21

-Spirits 0.05 0.08 0.08 0.09 0.15 *0.1 0.02 0.02 0.04 0.05 0.13 0.03-Wine 0.02 0.04 0.04 0.03 0.04 *0.03 0.01 0.01 0.01 0.01 0.05 *0.01-Beer 0.29 0.65 0.41 0.37 0.17 *0.33 0.1 0.15 0.23 0.33 0.14 *0.16

Tobacco 0.96 1.13 1.01 1 0.54 *0.85 0.43 0.46 0.59 0.69 0.5 *0.5Clothing and footwear 0.63 0.92 0.97 0.95 0.53 0.77 0.68 0.83 0.8 0.76 0.42 *0.73

-Adult clothing 0.25 0.49 0.59 0.67 0.4 *0.49 0.24 0.36 0.44 0.54 0.35 *0.35-Children's clothing 0.37 0.43 0.38 0.29 0.13 *0.27 0.44 0.47 0.36 0.22 0.07 0.39

Personal care 0.81 0.74 0.77 0.65 0.43 *0.62 0.74 0.8 0.74 0.71 0.5 *0.74-Necessities 0.46 0.38 0.34 0.25 0.12 *0.26 0.42 0.4 0.37 0.32 0.16 *0.38

-Baby products 0 0.01 0.01 0.02 0.03 *0.02 0.01 0.01 0 0.01 0 *0.01-Other 0.35 0.35 0.42 0.38 0.29 *0.35 0.31 0.39 0.37 0.38 0.33 *0.35

Fuel for HH use 0.4 0.32 0.18 0.12 0.04 *0.16 0.29 0.29 0.29 0.19 0.07 *0.27Furniture, HH Equipment and Maintenance 0.64 0.67 0.76 0.72 0.47 *0.62 0.62 0.71 0.71 0.71 0.45 *0.66Domestic and household services 0.02 0.02 0.01 0.01 0.02 *0.02 0.01 0.01 0.01 0.01 0.02 0.01Transportation 0.05 0.05 0.08 0.29 0.87 *0.4 0.01 0.04 0.04 0.17 0.46 *0.07

-Private Transport 0.05 0.05 0.08 0.29 0.87 *0.4 0.01 0.04 0.04 0.17 0.46 *0.07-Public/Collective transport 0 0 0 0 0 0 0 0 0 0 0 0

Fuel for transport 0.33 0.54 0.76 1.24 1.66 *1.13 0.23 0.25 0.33 0.55 1.41 *0.36Medical expenditure 0.1 0.07 0.08 0.07 0.12 *0.09 0.06 0.08 0.08 0.09 0.22 *0.09Education 0.07 0.06 0.05 0.03 0.03 *0.04 0.06 0.04 0.04 0.04 0.05 *0.05Communication 0.09 0.14 0.2 0.3 0.41 *0.28 0.08 0.13 0.17 0.27 0.44 *0.15Recreation 0.07 0.1 0.17 0.28 0.5 *0.3 0.06 0.07 0.13 0.22 0.54 *0.12Gambling 0 0.02 0.04 0.02 0.02 *0.02 0 0.01 0.01 0.02 0.03 *0.01Miscellaneous 0.1 0.16 0.21 0.2 0.19 0.18 0.09 0.14 0.26 0.25 0.17 *0.16TOTAL 7.95 9.24 9.5 10.07 8.69 *9.15 7 7.82 8.56 8.96 8.72 *7.84 Source: Own calculations from IES 2000 Notes: Data are weighted. - denotes sub-category * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence on food in female-breadwinner households is tested against tax incidence on food in male-breadwinner households. 43

Table A6. Incidence for main commodity groups by headship and household composition and by quintiles (tax as a percentage of expenditure)

Male-headed Female-headed Category 1 2 3 4 5 Total 1 2 3 4 5 Total

Housing and utilities 0.47 0.57 0.73 0.79 0.81 0.7 0.48 0.64 0.81 0.84 0.76 0.68-Housing 0.04 0.03 0.05 0.1 0.18 *0.09 0.03 0.04 0.08 0.06 0.09 0.05-Utilities 0.43 0.54 0.69 0.69 0.63 *0.61 0.45 0.6 0.74 0.77 0.67 0.62

Food 2.59 2.66 2.53 2.27 1.37 *2.18 2.61 2.71 2.65 2.43 1.53 2.52-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.96 2.18 2.18 2.02 1.22 *1.84 1.92 2.17 2.25 2.12 1.36 2.04

-Sugar/confectionary 0.64 0.48 0.35 0.26 0.14 *0.33 0.69 0.53 0.4 0.3 0.17 0.48Meals out 0.03 0.04 0.12 0.13 0.22 *0.12 0.03 0.04 0.08 0.12 0.21 0.07Non-alcoholic beverages 0.37 0.42 0.43 0.4 0.26 *0.36 0.35 0.4 0.41 0.39 0.28 0.38Alcoholic beverages 0.3 0.53 0.6 0.6 0.46 *0.51 0.1 0.22 0.23 0.35 0.2 0.21

-Spirits 0.03 0.06 0.09 0.09 0.15 *0.09 0.01 0.02 0.03 0.06 0.06 0.03-Wine 0.02 0.03 0.03 0.03 0.03 *0.03 0 0.01 0.01 0.02 0.02 0.01-Beer 0.25 0.44 0.48 0.48 0.27 *0.38 0.08 0.2 0.19 0.28 0.11 0.17

Tobacco 0.87 0.96 1.09 1.11 0.66 *0.92 0.29 0.46 0.44 0.54 0.43 0.42Clothing and footwear 0.7 0.85 0.87 0.86 0.58 *0.76 0.69 0.87 0.92 0.91 0.65 0.82

-Adult clothing 0.27 0.43 0.54 0.62 0.45 *0.48 0.25 0.4 0.53 0.62 0.47 0.43-Children's clothing 0.43 0.41 0.33 0.24 0.13 *0.28 0.43 0.47 0.39 0.29 0.18 0.39

Personal care 0.78 0.78 0.72 0.64 0.45 *0.65 0.75 0.8 0.8 0.76 0.58 0.76-Necessities 0.45 0.39 0.35 0.27 0.14 *0.29 0.41 0.4 0.37 0.3 0.17 0.36

-Baby products 0 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.02 0.02 0.01-Other 0.32 0.38 0.37 0.36 0.29 *0.34 0.33 0.39 0.43 0.44 0.39 0.39

Fuel for HH use 0.34 0.29 0.21 0.13 0.04 *0.18 0.32 0.29 0.24 0.13 0.06 0.24Furniture, HH Equipment and Maintenance 0.63 0.64 0.74 0.68 0.52 *0.63 0.62 0.7 0.73 0.8 0.51 0.68Domestic and household services 0.01 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01Transportation 0.02 0.05 0.09 0.25 0.78 *0.3 0.02 0.02 0.05 0.11 0.51 0.08

-Private Transport 0.02 0.05 0.09 0.25 0.78 *0.3 0.02 0.02 0.05 0.11 0.51 0.08-Public/Collective transport 0 0 0 0 0 0 0 0 0 0 0 0

Fuel for transport 0.31 0.43 0.66 1.13 1.55 *0.92 0.26 0.32 0.48 0.66 1.22 0.47Medical expenditure 0.06 0.08 0.07 0.08 0.13 *0.09 0.06 0.07 0.07 0.07 0.11 0.07Education 0.07 0.05 0.04 0.03 0.03 *0.04 0.07 0.05 0.05 0.04 0.04 0.05Communication 0.09 0.13 0.19 0.27 0.39 *0.24 0.09 0.13 0.2 0.28 0.42 0.18Recreation 0.08 0.1 0.17 0.26 0.5 *0.26 0.05 0.08 0.16 0.24 0.38 0.14Gambling 0.01 0.02 0.03 0.03 0.02 *0.02 0.01 0.01 0.02 0.02 0.02 0.01Miscellaneous 0.09 0.14 0.19 0.18 0.19 *0.16 0.09 0.18 0.27 0.27 0.26 0.2TOTAL 7.81 8.76 9.5 9.85 8.97 *9.06 6.87 8 8.61 8.97 8.17 7.99

Adult male majority Adult female majority Category 1 2 3 4 5 Total 1 2 3 4 5 Total

44

Housing and utilities 0.56 0.72 0.76 0.76 0.72 *0.71 0.45 0.61 0.8 0.86 0.82 0.67-Housing 0.02 0.04 0.04 0.1 0.12 0.07 0.03 0.05 0.07 0.09 0.14 0.07-Utilities 0.54 0.68 0.72 0.67 0.6 *0.64 0.43 0.56 0.73 0.77 0.67 0.61

Food 2.52 2.62 2.49 2.19 1.39 *2.19 2.63 2.71 2.58 2.38 1.47 2.47-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.87 2.16 2.12 1.93 1.25 *1.84 1.95 2.2 2.2 2.09 1.31 2.01

-Sugar/confectionary 0.65 0.46 0.36 0.26 0.14 *0.35 0.67 0.52 0.38 0.29 0.16 0.45Meals out 0.01 0.06 0.14 0.16 0.27 *0.14 0.04 0.04 0.07 0.12 0.19 0.08Non-alcoholic beverages 0.37 0.41 0.41 0.41 0.33 *0.38 0.35 0.4 0.4 0.39 0.25 0.37Alcoholic beverages 0.2 0.59 0.57 0.74 0.74 *0.59 0.17 0.25 0.22 0.31 0.18 0.22

-Spirits 0.01 0.08 0.08 0.13 0.2 *0.11 0.02 0.03 0.03 0.05 0.06 0.04-Wine 0.02 0.02 0.03 0.03 0.03 *0.03 0.01 0.01 0.01 0.01 0.02 0.01-Beer 0.17 0.49 0.45 0.58 0.51 *0.46 0.14 0.21 0.18 0.25 0.09 0.18

Tobacco 0.91 0.95 1.14 1.31 0.9 *1.05 0.36 0.44 0.51 0.57 0.41 0.45Clothing and footwear 0.71 0.85 0.9 0.92 0.74 *0.83 0.71 0.88 0.9 0.89 0.58 0.81

-Adult clothing 0.29 0.48 0.61 0.72 0.61 *0.56 0.26 0.41 0.51 0.59 0.42 0.42-Children's clothing 0.41 0.38 0.29 0.2 0.13 *0.27 0.45 0.47 0.39 0.3 0.16 0.38

Personal care 0.74 0.76 0.68 0.6 0.47 *0.63 0.76 0.8 0.82 0.76 0.54 0.76-Necessities 0.43 0.39 0.34 0.28 0.17 *0.31 0.41 0.4 0.36 0.29 0.16 0.35

-Baby products 0.01 0 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.01-Other 0.3 0.37 0.33 0.32 0.3 *0.32 0.34 0.39 0.45 0.45 0.36 0.4

Fuel for HH use 0.43 0.27 0.22 0.13 0.05 *0.2 0.29 0.3 0.23 0.12 0.05 0.22Furniture, HH Equipment and Maintenance 0.61 0.61 0.74 0.65 0.58 *0.64 0.62 0.7 0.76 0.76 0.46 0.67Domestic and household services 0 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01Transportation 0.01 0.04 0.08 0.21 0.61 *0.22 0.02 0.03 0.05 0.18 0.65 0.13

-Private Transport 0.01 0.04 0.08 0.21 0.61 *0.22 0.02 0.03 0.05 0.18 0.65 0.13-Public/Collective transport 0 0 0 0 0 0 0 0 0 0 0 0

Fuel for transport 0.23 0.38 0.62 1.09 1.49 *0.83 0.3 0.37 0.53 0.87 1.37 0.58Medical expenditure 0.05 0.07 0.1 0.06 0.1 0.08 0.06 0.07 0.07 0.08 0.11 0.07Education 0.08 0.06 0.04 0.03 0.05 0.05 0.06 0.05 0.05 0.04 0.04 0.05Communication 0.09 0.14 0.2 0.26 0.35 *0.22 0.09 0.14 0.21 0.29 0.42 0.2Recreation 0.06 0.11 0.19 0.28 0.45 *0.24 0.06 0.08 0.15 0.23 0.43 0.16Gambling 0.01 0.02 0.03 0.03 0.03 *0.03 0.01 0.01 0.03 0.02 0.01 0.01Miscellaneous 0.06 0.14 0.22 0.19 0.22 *0.18 0.09 0.21 0.26 0.24 0.21 0.19TOTAL 7.67 8.8 9.52 10.05 9.52 *9.23 7.07 8.1 8.64 9.13 8.2 8.13

Equal # adults Category 1 2 3 4 5 Total

Housing and utilities 0.47 0.55 0.74 0.78 0.83 0.7-Housing 0.05 0.03 0.06 0.08 0.19 *0.09-Utilities 0.41 0.52 0.68 0.71 0.64 0.61

Food 2.61 2.68 2.65 2.35 1.36 *2.23

45

-B asic 0 0 0 0 0 0-Other 1.94 2.16 2.29 2.09 1.22 *1.87

-Sugar/confectionary 0.67 0.52 0.36 0.26 0.15 *0.35Meals out 0.01 0.04 0.1 0.12 0.2 *0.11Non-alcoholic beverages 0.38 0.42 0.45 0.39 0.23 0.36Alcoholic beverages 0.22 0.43 0.62 0.56 0.35 *0.44

-Spirits 0.02 0.04 0.07 0.08 0.14 *0.08-Wine 0.02 0.02 0.03 0.03 0.04 *0.03-Beer 0.18 0.37 0.51 0.46 0.18 *0.33

Tobacco 0.7 0.96 0.96 0.99 0.57 *0.82Clothing and footwear 0.64 0.83 0.87 0.84 0.52 *0.73

-Adult clothing 0.23 0.39 0.52 0.58 0.39 *0.43-Children's clothing 0.42 0.44 0.35 0.26 0.13 *0.29

Personal care 0.77 0.79 0.74 0.65 0.44 *0.65-Necessities 0.45 0.41 0.35 0.27 0.12 *0.3

-Baby products 0 0.01 0.01 0.02 0.03 0.01-Other 0.32 0.38 0.37 0.37 0.29 *0.34

Fuel for HH use 0.34 0.29 0.21 0.14 0.04 *0.18Furniture, HH Equipment and Maintenance 0.64 0.66 0.71 0.72 0.51 *0.64Domestic and household services 0.02 0.01 0.01 0.01 0.02 0.01Transportation 0.01 0.04 0.09 0.22 0.82 *0.3

-Private Transport 0.01 0.04 0.09 0.22 0.82 *0.3-Public/Collective transport 0 0 0 0 0 0

Fuel for transport 0.28 0.37 0.62 1 1.55 *0.87Medical expenditure 0.07 0.08 0.06 0.08 0.14 *0.09Education 0.07 0.05 0.04 0.03 0.02 *0.04Communication 0.07 0.1 0.18 0.27 0.41 *0.23Recreation 0.07 0.1 0.17 0.25 0.52 *0.26Gambling 0.01 0.01 0.02 0.03 0.02 *0.02Miscellaneous 0.11 0.1 0.18 0.19 0.19 *0.16TOTAL 7.49 8.51 9.41 9.64 8.75 *8.84Notes: Data are weighted. - Denotes sub-category * Reports statistical significance in equality of means t-tests with unequal variance at 5% level. Reference category in italics. So, for example, tax incidence on food in female-headed households is tested against tax incidence on food in male-headed households.

46

Table A7. Incidence for main commodity group by headship, presence of children and quintile (tax as a percentage of expenditure) Male-headed with children Male-headed without children

Category 1 2 3 4 5 Total 1 2 3 4 5 Total Housing and utilities 0.47 0.58 0.76 0.86 0.87 ^ *0.72 0.6 0.46 0.6 0.62 0.72 *0.66

-Housing 0.04 0.04 0.05 0.13 0.22 ^ *0.1 0 0.02 0.01 0.04 0.11 *0.07-Utilities 0.43 0.55 0.7 0.73 0.65 0.62 0.59 0.44 0.59 0.59 0.6 *0.59

Food 2.61 2.68 2.52 2.24 1.36 ^ *2.27 2.22 2.43 2.6 2.35 1.37 *1.89-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.97 2.2 2.18 1.99 1.21 ^ *1.91 1.62 1.95 2.18 2.07 1.23 *1.64

-Sugar/confectionary 0.64 0.48 0.34 0.24 0.14 ^ *0.36 0.6 0.48 0.41 0.28 0.14 *0.25Meals out 0.03 0.05 0.13 0.12 0.18 ^ *0.1 0.01 0.02 0.05 0.16 0.27 *0.19Non-alcoholic beverages 0.36 0.42 0.41 0.36 0.22 ^ *0.35 0.44 0.48 0.51 0.5 0.31 0.4Alcoholic beverages 0.29 0.52 0.55 0.49 0.31 ^ *0.43 0.67 0.65 0.87 0.88 0.67 *0.75

-Spirits 0.03 0.07 0.08 0.08 0.13 ^ *0.08 0.08 0.03 0.14 0.13 0.19 *0.16-Wine 0.02 0.02 0.03 0.02 0.03 ^ *0.02 0.04 0.07 0.06 0.04 0.04 *0.04-Beer 0.24 0.43 0.45 0.39 0.16 ^ *0.33 0.55 0.55 0.68 0.71 0.43 *0.55

Tobacco 0.83 0.9 1.02 0.97 0.54 ^ *0.85 1.78 1.62 1.49 1.44 0.83 *1.15Clothing and footwear 0.71 0.86 0.9 0.87 0.53 ^ *0.77 0.48 0.76 0.7 0.84 0.65 0.71

-Adult clothing 0.26 0.42 0.52 0.56 0.36 ^ *0.43 0.32 0.66 0.62 0.77 0.57 *0.63-Children's clothing 0.44 0.44 0.37 0.31 0.17 ^ *0.34 0.16 0.09 0.08 0.07 0.07 0.08

Personal care 0.77 0.77 0.71 0.62 0.44 ^ *0.66 0.86 0.91 0.77 0.7 0.46 *0.6-Necessities 0.45 0.38 0.33 0.24 0.12 ^ *0.3 0.54 0.51 0.43 0.34 0.16 *0.27

-Baby products 0 0.01 0.01 0.02 0.03 ^ *0.02 0 0 0 0 0 0-Other 0.32 0.38 0.37 0.36 0.29 ^ *0.34 0.32 0.39 0.34 0.36 0.3 *0.33

Fuel for HH use 0.33 0.29 0.2 0.13 0.04 ^ *0.19 0.42 0.3 0.22 0.14 0.05 *0.12Furniture, HH Equipment and Maintenance 0.63 0.64 0.77 0.7 0.48 ^ *0.65 0.62 0.65 0.57 0.62 0.56 *0.58Domestic and household services 0.01 0.02 0.01 0.01 0.02 ^ *0.01 0 0 0.01 0.02 0.02 *0.02Transportation 0.02 0.05 0.1 0.31 0.84 ^ *0.27 0.01 0.03 0.04 0.11 0.69 *0.39

-Private Transport 0.02 0.05 0.1 0.31 0.84 ^ *0.27 0.01 0.03 0.04 0.11 0.69 *0.39-Public/Collective transport

47

0 0 0 0 0 0 0 0 0 0 0 0Fuel for transport 0.31 0.44 0.71 1.22 1.62 ^ *0.88 0.26 0.28 0.42 0.92 1.45 *1.07Medical expenditure 0.06 0.08 0.08 0.08 0.12 ^ *0.08 0.04 0.08 0.07 0.08 0.14 0.11Education 0.07 0.05 0.04 0.04 0.04 ^ *0.05 0.11 0.02 0.01 0.01 0.03 *0.02Communication 0.09 0.13 0.21 0.29 0.38 ^ *0.22 0.02 0.11 0.13 0.23 0.41 0.3Recreation 0.08 0.1 0.19 0.27 0.47 ^ *0.23 0.04 0.09 0.11 0.22 0.55 *0.36Gambling 0.01 0.02 0.03 0.03 0.01 ^ *0.02 0.01 0.05 0.01 0.03 0.03 *0.03Miscellaneous 0.09 0.15 0.2 0.19 0.19 ^ *0.16 0.09 0.06 0.13 0.14 0.2 0.16TOTAL 7.77 8.75 9.53 9.79 8.65 ^ *8.93 8.69 8.99 9.31 10.01 9.4 *9.52

Female-headed with children Female-headed without children Category 1 2 3 4 5 Total 1 2 3 4 5 Total

Housing and utilities 0.47 0.64 0.81 0.86 0.81 ^ 0.67 0.67 0.68 0.8 0.77 0.71 0.75

-Housing 0.03 0.04 0.08 0.07 0.13 ^ 0.06 0.01 0.07 0.02 0.03 0.05 0.03-Utilities 0.44 0.6 0.73 0.78 0.68 ^ 0.61 0.67 0.61 0.79 0.75 0.66 0.71

Food 2.62 2.71 2.66 2.4 1.47 ^ 2.56 2.36 2.53 2.64 2.5 1.6 2.25-B asic 0 0 0 0 0 0 0 0 0 0 0 0-Other 1.92 2.18 2.26 2.11 1.31 ^ 2.06 1.83 2.05 2.2 2.17 1.42 1.92

-Sugar/confectionary 0.69 0.53 0.39 0.29 0.16 ^ 0.5 0.53 0.48 0.45 0.33 0.17 0.33Meals out 0.03 0.04 0.08 0.13 0.15 ^ 0.06 0.01 0.02 0.08 0.11 0.27 0.14Non-alcoholic beverages 0.35 0.39 0.4 0.37 0.23 ^ 0.37 0.4 0.42 0.45 0.45 0.33 0.41Alcoholic beverages 0.09 0.22 0.2 0.35 0.19 ^ 0.19 0.15 0.26 0.42 0.37 0.21 0.31

-Spirits 0.01 0.02 0.02 0.06 0.07 ^ 0.03 0 0.02 0.06 0.06 0.05 0.05-Wine 0 0 0.01 0.01 0.02 ^ 0.01 0 0.02 0.03 0.02 0.03 0.03-Beer 0.08 0.19 0.18 0.27 0.1 ^ 0.16 0.15 0.22 0.33 0.29 0.13 0.24

Tobacco 0.28 0.45 0.41 0.51 0.38 ^ 0.39 0.51 0.7 0.63 0.63 0.5 0.59Clothing and footwear 0.69 0.88 0.94 0.95 0.71 ^ 0.84 0.38 0.7 0.77 0.81 0.58 0.7

-Adult clothing 0.25 0.39 0.51 0.59 0.43 ^ 0.4 0.3 0.61 0.68 0.71 0.53 0.62-Children's clothing 0.44 0.49 0.43 0.36 0.28 ^ 0.43 0.08 0.09 0.09 0.1 0.05 0.08

Personal care 0.74 0.79 0.78 0.73 0.48 ^ 0.75 1.23 1.04 0.95 0.85 0.7 0.86-Necessities 0.4 0.39 0.35 0.27 0.14 ^ 0.36 0.57 0.6 0.47 0.38 0.2 0.37

-Baby products 0.01 0.01 0.01 0.02 0.03 ^ 0.01 0 0 0 0 0 0-Other 0.32 0.38 0.42 0.43 0.31 ^ 0.38 0.65 0.44 0.48 0.47 0.49 0.49

Fuel for HH use 0.32 0.29 0.24 0.12 0.07 ^ 0.25 0.34 0.25 0.22 0.14 0.06 0.15Furniture, HH Equipment and Maintenance 0.62 0.7 0.74 0.85 0.51 ^ 0.69 0.52 0.67 0.63 0.66 0.51 0.61Domestic and household services 0.01 0.01 0.01 0.01 0.01 0.01 0 0 0.01 0.01 0.01 0.01Transportation 0.02 0.02 0.04 0.12 0.5 ^ 0.07 0.01 0.02 0.09 0.06 0.53 0.21

-Private Transport 0.02 0.02 0.04 0.12 0.5 ^ 0.07 0.01 0.02 0.09 0.06 0.53 0.21-Public/Collective transport 0 0 0 0 0 0 0 0 0 0 0 0

Fuel for transport 0.26 0.32 0.49 0.68 1.3 ^ 0.44 0.37 0.36 0.41 0.6 1.13 0.69Medical expenditure 0.06 0.07 0.07 0.07 0.1 ^ 0.07 0.02 0.1 0.07 0.08 0.11 0.09Education 0.07 0.05 0.05 0.04 0.04 ^ 0.05 0.07 0.03 0.02 0.02 0.05 0.03Communication 0.09 0.13 0.21 0.28 0.41 ^ 0.17 0.11 0.16 0.13 0.29 0.44 0.28Recreation 0.05 0.08 0.17 0.27 0.35 ^ 0.13 0.15 0.06 0.09 0.19 0.42 0.22Gambling 0.01 0.01 0.02 0.02 0.01 ^ 0.01 0.02 0 0.01 0.02 0.02 0.02Miscellaneous 0.09 0.19 0.28 0.3 0.28 0.2 0.03 0.05 0.15 0.2 0.22 0.18TOTAL 6.86 8 8.61 9.05 8.01 ^ 7.92 7.35 8.06 8.57 8.76 8.38 8.48 Notes: Data are weighted. - denotes sub-category * Reports statistical significance in equality of means t-tests with unequal variance at 5% level within child categories. So, for example, tax incidence on food in female-headed households with children is tested against tax incidence on food in male-headed households with children, and tax incidence on food in female-headed households without children is tested against tax incidence on food in male-headed households without children. ^ Reports statistical significance in equality of means t-tests with unequal variance at 5% level across child categories. So, for example, tax incidence on food in female-headed households with children is tested against tax incidence on food in female-headed households without children, and tax incidence on food in male-headed households with children is tested against tax incidence on food in male-headed households without children. 48