poverty issues for zero rating value-added tax (vat) in...

SOUTH AFRICA: POVERTY AND INEQUALITYINFORM/IAL DISCUSSION PAPEPR SERIFS

19336February 1999

Poverty Issues for Zero RatingValue-Added Tax (VAT)

in South Africa

Harold Alderman and Carlo del Ninno

WORLD BANKCOUNTRY DEPARTMENT IAFRICA REGION

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SOUTH AFRICA: POVERTY AND INEQUALITYINFORMA L DISCUSSION PAPEPR SERIES

* Poverty and Inequality in the Distribution ofPublic Education Spending in South Africa

Florencia Castro-Leal, February 1999

* The Impact of Public Health Spending on Povertyand Inequality in South Africa

Florencia Castro-Leal, February 1999

* Review of Public Expenditures: Efficiency andPoverty Focus

Gurushri Swamy and Richard Ketley, February 1999

* Safety Nets and Income Transfers in South Africa

Harold Aldernian, February 1999

* Poverty Issues for Zero Rating Value-Added Tax (VAT)in South Africa

Harold Alderman and Carlo del Ninno, February 1999

* Violence and Poverty in South Africa: Their Impacton Household Relations and Social Capital

Caroline Moser; February 1999

* Women Workers in South Africa: Participation, Pay andPrejudice in the Formal Labor Market

Carolyn Winter, February 1999

FOREWORD

This paper is one of a series of informal discussion papers on poverty andinequality issues in South Africa, which were produced as contributions to the Povertyand Inequality Report (PIR). The PIR was commissioned by the Deputy President'sOffice of the Government of the Republic of South Africa (and was published in 1998 byPraxis Publishing, South Africa). As these papers were written at different times overthe years 1996-1998, the analysis in each paper covers different periods; however, forease of reference, they are now being disseminated in one series.

A complementary report, which gathers the views of the poor themselves, waswritten by a tearn of South Africans and also published by Praxis Publishing. "TheExperience and Perceptions of Poverty in South Africa" (1998) gives voice to the poor,who describe what poverty is to them, how they get trapped in it, and how they mightescape from it. This study was initiated and funded by the World Bank (through a DutchTrust Fund) and by the Overseas Development Administration of the U.K. Government.

The papers in this series were written under the direction of Ann Duncan (TaskManager) and under the overall guidance of Pamela Cox (Country Director) and RuthKagia (Sector Manager). The series was edited by Barbara Koeppel, and the finalpresentation was managed and executed by Lori Geurts.

Country Department IThe World BankFebruary 1999

Copyright 1999The World Bank1818 "H" Street, N.W.Washington, DC 20433, U.S.A.

This is an informal study by World Bank staff, publishedfor discussion purposes. It is not an official WorldBank document.

ACKNOWLEDGEMENTS

This paper was written by Harold Alderman and Carlo del Ninno. The authors wish tothank Franque Grimard, Richard Ketley, and Ingrid Woolard for helpful comments on an earlierdraft.

The views expressed in this study are those of the authors and should not be attributed tothe World Bank, members of its Board of Executive Directors, or the countries they represent.

ABSTRACT

This study confirms the logic of value-added tax (VAT) exemptions for maize. Based on taxefficiency and equity, this commodity dominates all alternatives: it is well targeted and has ameasurable positive impact on caloric consumption by deficit households. Other value-addedtax exemptions being considered have less to recommend them. In particular, an exemption formeat is not justified, either for equity or nutritional reasons, as it would favor non-poor urbanhouseholds and negatively affect the caloric consumption of rural households.

ABBREVIATIONS AND ACRONYMS

VAT Value Added Tax

NNSDP National Nutrition and Social Development Programme

LSDS Living Standards and Development Survey

CURRENCY EQUIVALENTS

Rand/US$

1990 2.6

1991 2.7

1992 3.1

1993 3.4

1994 3.5

1995 3.6

1996 4.7

1997 4.9

1998 5.9

TABLE OF CONTENTS

I. INTRODUCTION ................................................................1

II. METHODOLOGY ................................................................ 1

III. DATA ................................................................ 4

IV. RESULTS. ............................................................... 5

V. CONCLUSION ................................................................. 7

R eferen ces ................................ ................................................................................................. 9

Appendix

TablesTable 1: Commodities Used in the Demand Analysis and Exempt from VATTable 2: Expenditure and Calorie Shares and Income and Own Price Elasticities by Locations

(and Pooled)Table 3: Relative Social Cost of Tax Reform due to Current VAT ExemptionsTable 4: Relative Social Cost of Tax Reform due to Proposed VAT ExemptionsTable 5: Impact of VAT Exemption on Calorice ConsumptionTable 6: Impact of VAT on Protein Consumption

FiguresFigure 1: Expenditure Patterns for Maize, Bread, Beans and MeatFigure 2: Expenditure Patterns for Milk, Sugar, Oil and KeroseneFigure 3: Relative Social Cost of Tax Reform Due to Current VAT ExemptionFigure 4: Relative Social Cost of Tax Reform Due to Proposed VAT Exemptions

AnnexesTable Al: Demand Elasticities - All ObservationsTable A2: Demand Elasticities - Rural HouseholdsTable A3: Demand Elasticities -Urban and Metropolitan Households

Endnotes

Poverty Issues For Zero Rating VAT in South Africa

I. INTRODUCTION

Value added taxes (VAT) potentially distort consumer behavior less than many forms ofindirect taxes and may therefore be comparatively efficient in generating government revenue. Theymay even be more efficient in an inter-temporal context than some direct taxes.' However, theyinvolve some drawbacks, both in terms of efficiency (Agha and Haughton, 1996) and equity.

With respect to equity, a single rate VAT system--the easiest to administer--is, at best,distributionally neutral. Because of this, VAT systems are often introduced in a way that variesrates or offers exemptions to reduce the impact on low-income consumers. Thus, they often reflecta government's distributional as well as fiscal objectives. However, some observers suggest theyshould be based on efficiency criteria alone, and that equity concerns are better addressed withtargeted income transfers and similar measures.

The introduction of VAT in South Africa in 1991 straddled these two viewpoints. To reducethe impact of the new tax burden on the poor, a safety net program, the National Nutrition andSocial Development Programme (NNSDP), was also introduced in 1991, designed to distributeR400 million annually in community-based food projects (McLachlan and Marshall, 1995). Despitethis measure, maize and brown bread were exempted from VAT shortly after it was introduced; bymid-1993, 19 food commodities were exempted from the VAT (Bailey, no date)."

This paper investigates how well the exemptions have been targeted. It uses findings fromthe 1993 Living Standards and Development Survey (LSDS) to identify how well the exemptionsworked to reduce the tax burdens on various households and to rank a number of commodities interms of tax efficiency and equity. Moreover, the study reviews the impact of the exemptions onhousehold food consumption.

Although it is possible that tax exemptions on non-food commodities may serve equityobjectives, South Africa has concentrated on exemptions on food. Moreover, these exemptions,along with its nutrition program, indicates a specific nutritional consideration in tax design. The listof commodities with current or proposed VAT exemptions includes, for example, maize and beans,which are both plausible candidates for VAT exemptions for equity and efficiency reasons, as wellas for their impact on food nutrient consumption. The list also contains commodities such as bread,which does little to address equity concerns but may have favorable consumption effects, as well asfresh milk and meat, which neither enhance equity and have an arnbiguous impact on nutrition.

II. METHODOLOGY

A tax system always incurs some economic distortions either by changing the price of goodsrelative to the resource cost or by influencing the price of leisure. Thus, when seeking taxefficiency, the goal is to find a tax system that minimizes distortions for a given amount of revenue(Deaton, 1997), and this paper will apply this efficiency criteria. The concept of equity that it adoptsis fairly straightforward: Revenue raised from the poor has different social costs than an equalamount raised from the less poor. Conversely, subsidies or tax exemptions which favor the poor areviewed as more socially desirable than those for the less poor.

Poverty Issues for Zero Rating VAT in South Africa

Much of the information needed to assess the distribution of tax exemptions can be derivedfrom descriptive statistics indicating consumer patterns by income groups. For exarnple, householdsurveys can provide information on the quantities of various goods consumed by different incomegroups. Using this data, one can see commodities consumed in greater amounts by the poor as ashare of total expenditures. These are usually suitable vehicles for progressive exemptions. As arule of thumb, exemptions will represent a larger share of poor households' total expenditures thanfor the general population if the income elasticity on the good to be taxed is less than one. Further,the exemption (or transfer) will be worth more in value per capita terms for the poor than non-poorif the income elasticity is negative. However, income elasticities are not necessary to analyze equityeffects. Indeed, an altemative approach to analyzing equity impacts is to use non-parametricrankings of tax burden over income (Younger et al., 1996).

Nevertheless, the approach we used in this paper employs a matrix of demand parameterssince the price distortions introduced by variable tax rates affect the efficiency as well as the equityof the taxation policy. The efficiency of tax policies varies depending on the existing pricedistortions in the economy, including the presence of other exemptions. The change of a tax rate forone commodity will shift consumption to other commodities through cross-price effects. The netchange on revenue collected will vary depending on whether these commodities have higher orlower tax rates than the average. Thus, the impact of one tax rate depends on what other rates are inplace.

The procedure used in this study to evaluate the altematives for VAT exemptions is basedon Deaton and Grimard (1992) and Ahmad and Stem (1991). For each consumer, any priceincrease for one good, including an increase in a tax, reduces total personal welfare (consumption)in proportion to the amount of the good consumed. Thus, the social costs of an adjustment to taxesare based on the change in the unit cost of the commodity multiplied by a welfare weight (0) whichplaces a relative value on the costs for different individuals. Typically more weight is placed on thecost to the poorest consumers. This is calculated over all households as in equation (1):

S = E 9hqh

where dW is the change of welfare with a change in the tax (t) on the ith commodity and q is thequantity of that commodity consumed.

Moreover, the tax change will also affect government revenue, both in terms of the directrevenue gained (or lost) from the commodity taxed (or exempted from the tax) and the indirect costsdue to shifts in consumer purchases to or from commodities with different tax rates. In someapplications, such different implicit taxation may be due to policy-induced price distortions. Thenet change in revenue is based on the sum over all (k) goods and (h) households as in equation (2):

/1h1kPk(C' hk ) (2)

The ratio of equations (1) and (2) gives a cost benefit ratio to assess commodity-specificexemptions. Since the social benefits of a tax is simply the revenue raised, equation (2) is anexpression of benefits while the numerator is the welfare cost. When all goods are taxed at the samerate, the pretax price reflects resource costs (shadow prices), and all individuals are given the samesocial weight, this ratio will be one. If tax rates differ or if goods are not priced at their shadow

2


price, the ratio may differ from one, even if social weights are the same across individuals. If it islarger than one, the social costs are comparatively high relative to the revenue generated and thecommodity is a good candidate for a reduced tax, Conversely, when it is less than one, thecommodity is a good candidate for a tax, since the tax will lead to higher revenues raised (orreduced economic distortions) than its social cost.

When equity concerns are added one generally compares the relative size of the ratios,rather than comparing the ratio with one. The higher the weight on the poor, the greater the socialcost of taxes on commodities consumed disproportionately by the poor and, hence, the higher thenumerator in the cost-benefit ratio. These goods with higher ratios are candidates for taxexemptions. When all ratios are equal, little scope exists for a reform that would improve socialwelfare yet generate the sarne revenue.

The cross-price effects in the parentheses in equation (2) are central to analyzing if anadjustment in the tax of one commodity is efficient when tax rates differ, since they depend on therates on the other commodities, as well. Consider an increase in the tax on one commodity. If thegoods which are substitutes (complements) have price distortions due to subsidies (taxes), efficiencywill decrease or increase due to changes in the amount of the commodity consumed. This isbecause a cross-price effect that increases the consumption of a good, which is priced below itsresource cost, adds to the overall distortions from optimal consumption and vice versa.

The most critical welfare weights to analyze equity are not directly observed. Thus, moststudies use a grid of alternatives that span from the assumption of no social weight on povertyalleviation to moderate or extreme weight on changes of expenditures at the lowest levels. In theanalysis below, oh is defined by the ratio of a reference level of expenditures over householdexpenditures per adult equivalent taken to the a power, where ax ranges from 0 to 2.

oh =( (3)

When a is 0, the index is the same for all income groups. As a increases, oh increases forhouseholds with incomes below the reference income and decreases for those with higher ones.

Measuring the impact on food consumption requires the same set of price elasticities used toindicate revenue. For example:

1h Yk N(clp)k (!5a ) (4)

where N(/pk is the nutrient (in this study, calorie or protein) content of a unit of the kth commodity.In effect, the analysis is analogous to equation (2), with commodity-specific nutrients substituted forgovernment revenues. Similar examples of calculating the net impact on nutrient consumption dueto price changes are found in Pinstrup-Andersen, Londono and Hoover (1976) and Pitt (1982).

Equation (2) is uninteresting at the margin when all tax rates and economic distortions areequal, as is equation (4), if nutrients per unit expenditure (not per unit weight) are the same acrosscommodities. While the former occurs occasionally, the latter never arises. As is shown below, it is

3

Poverty Issuesfor Zero Rating VAT in South Africa

possible that substitution between commodities leads to rednced nutrient consumption following adecrease in taxes on a single food commodity for either all households or a particular set.

III. DATA

The LSDS survey, which forms the core of our study, was the first household survey ofincome, expenditures and living conditions conducted throughout South Africa. While conceivedas a self-weighted survey, some adjustments were needed later due to differences in the rates ofresponse by income and racial groups.... These weights are used in the analysis.

The demand parameters needed for equation (2) were derived using an Almost IdealDemand System. Two systems of equations were estimated separately using the rural and urbansamples of 4,352 and 4,429 households, respectively. While the analysis requires calculating thetotal change in government revenue, the disaggregation of demand parameters into rural and urban--adding another level of summation in equation (2)--allows for greater flexibility in measuringconsumer response. It does not, however, imply that VAT rates do or should differ in differentlocales: Indeed, if different rates were established, there would probably be a behavioral responsesuch as large-scale purchases and resale near peri-urban areas. Such a response cannot be assessedwith the current household data.

The choice of commodity groupings is based both on the policy options that have been orare currently being considered as well as the aggregations in the expenditure module of the survey.Table I indicates the VAT exemptions as of 1993 as well as others under consideration. The thirdcolumn indicates the 16 commodity breakdown used to estimate demand and the fourth displays thecorresponding commodity breakdown from the survey instrument for all groups except theextensive non-food aggregation.Iv As the LSDS was not designed with analyzing the VAT as anexplicit objective, the commodity groupings in the data collection do not perfectly correspond tothose being considered for VAT exemptions. In particular, the aggregation of brown and whitebread in the survey required a similar aggregation during the analysis.

Two departures in the study from some of the empirical illustrations of tax reform in theliterature are worth mentioning. Unlike Deaton and Grimard (1992), we do not consider qualityshadings; in this analysis, a shift can be made between commodities in response to a price change,but not to a different quality commodity. Although Deaton and Grimard found only relatively smallquality effects in their empirical investigation, along with Ahmad and Stern (1991), they found theexisting price distortions influenced the ranking of commodities in terms of the benefit cost ratios ofequations (1) and (2). While it might be possible to construct a matrix of shadow prices for SouthAfrica as in Ahmad and Stem, we seek to isolate the effects of alternate VAT exemptions from ananalysis of the changing trade environment embodied in the assumptions necessary to constructsuch a matrix. Thus, our study assumes the observed consumer prices correspond closely toresource costs plus taxes.

The reference expenditure used to construct welfare weights is based on the poverty line ofR301 a month (in 1994 rand)--about $80 a month-per adult equivalent: 40% of the households(52.8% of the population) have expenditures below this level. When a>O, the absolute value of theresults is sensitive to a change of the reference expenditure used in equation (3). However, the

4


ranking among altemate tax schemes remains unchanged.' Since the theory focuses on individualand not household welfare, the weights assume that individuals are allocated resources within thehousehold in accord with the scaling used to form adult equivalents. This is open to challenge, butno more so than the assumption that resources are shared equally among household members (as theuse of per capita expenditures requires); unfortunately, household surveys do not obtain the datanecessary to construct individual welfare weights without one or more assumptions on intra-household allocations.

Finally, it is useful to indicate our treatment of non-purchased foods. In general, it isimpractical to tax home-produced goods, and they need to be treated differently in any analysis oftax rates. However, it is unnecessary to add another layer of analysis because, unlike many othercountries, the poor in South Africa produce little of their own food (Carter and May, 1997). Forexample, only 1% of all maize plus mealies consumed was from own production; the figures formilk and meat are 1.5% and 2% respectively.

However, an additional 1 1% of maize, 12% of milk, and 4% of meat were provided either asgifts or as in-kind wages. We presume that most of these were originally purchased and, thus arepotentially taxable. This assumption cannot be directly verified in the data set, although it can beobserved that four times as much mealie meal and maize flour as maize grain was included in thecategory of gifts and wages. Even if these are provided to farm laborers, who, along with domesticworkers are the main recipients of in-kind wages, these particular foods are unlikely to be fromhome production. Still, our estimates slightly overestimate the total revenue possible with VAT forthese three commodities. 7

IV. RESULTS

Table 2 presents the expenditure shares, calorie shares, estimated income elasticities, andown price elasticities derived from the demand systems."" These are presented for households inthe rural and urban areas separately. For illustrative purposes, we also include the income and priceparameters derived from a pooled estimation, although the restrictions needed to pool the results arerejected at the p<.OI level. As the income patterns of demand are not easily indicated by a singleparameter and since the approach does not parameterize income responses, we also illustrate thepattern of consumption of eight key commodities in figures one and two.

While no commodity has a negative income elasticity overall (except for kerosene in therelatively prosperous urban areas), only maize displays a significant negative pattern ofconsumption over a sizable share of the population. Sugar, beans and oils have a flat portion over arange of incomes, while other commodities have an upwards slope in the graph of consumption andtotal expenditure. These figures foreshadow much of the equity impact of VAT alternatives.

Table 3 and Figure 3 illustrate the effects of introducing a 14% VAT on four commodit ygroups currently exempted. These are calculated with other current exemptions assumed to remainin place. The marginal efficiency of tax reform indicates the welfare cost of raising tax revenue;higher values of the marginal efficiency are costly for society. As indicated above, commoditieswith a high value would be a relatively low priority for raising revenue, while those with high

5


marginal welfare costs would be a comparatively high priority for tax exemptions. The results arecalculated for four values of a from equation 3.

Table 4 and Figure 4 illustrate similar calculations for the exemption of one non-food andfour food commodities currently taxed, again with the assumption that the other existing exemptionsremain. The tables also indicate the revenue gains or loss that the change in taxes would entail andthe share of revenue from households defined as poor. As an item of validation, the estimatedrevenue loss from the maize exemption is 23% higher than the revenue loss of 542M Rand for 1994reported by the Department of Inland Revenue (Bailey, no date). The Department estimate,however, is based on an extrapolation of an urban survey that excludes the former homelands.Moreover, it is taken together with all exemptions, while this report is for a scenario that considersonly maize with a zero VAT.

If cx is zero in Tables 3 and 4, there are no distributional benefits and most ratios are close toone. Ratios above one imply that some of the increased revenue from taxing the commodity isoffset by loss of revenue as consumers (whose expenditures are held constant) shift into otherexempt commodities. Conversely, the ratios below one imply that additional revenue is collected asmore consumption shifts to other taxed commodities.VIII

From the standpoint of seeking a commodity for VAT exemption, maize is the dominantchoice at all welfare weights. Even excluding any equity consideration (a=O), the ratio exceeds onein the case of maize as well as with beans and sugar. At higher values of ca, the advantages ofexempting maize are even more apparent. However, when ot is greater than zero, beans and sugarlose their ranking as the two next best choices: When aX > 0, kerosene becomes a better choice forexemption than sugar and beans.

Conversely, no compelling argument exists for exempting meat; indeed, it is a poor choice,even with no equity weights and a worse choice with them. Also, fresh milk and the group of otherdairy products (excluding milk) are poor choices--both on efficiency and equity grounds. Bread liesin the middle of rankings of commodities for exemptions under the range of values for a.

Thus, the ranking of commodities for VAT exemption generally follows from the ranking ofincome elasticities. However, this is less clearly the case when the impact on nutrition isconsidered. Table 5 shows the net change in caloric consumption for the non-poor as well as thepoor. Also, it indicates the change in the percent of households with under 2,000 calories a daywhen the commodities are taxed compared to the consumption that would prevail if thecommodities were not taxed. Usually, a decrease (increase) iri caloric consumption and an increase(decrease) in the number of households below a certain benchmark are expected when a tax is added(eliminated or made exempt). Table 6 presents similar information for protein.

While the poor's caloric consumption with a VAT exemption for maize, beans, bread andoil would increase, the situation is less clear for other commodities. As indicated in Table 5, ifmaize were taxed, the number of households consuming under 2,000 calories per capita per day inrural areas would increase by nearly 1.5% from a base of 43%. While this is partly due to the own-price effect on maize consumption, it also shows that other cereals and beans have a complementaryrelationship with maize. Thus, their consumption also decreases when maize is taxed. While the

6


cross-price effects that lead to increases in calories from some food items when maize prices rise,they do not offset the decline in calories from other commodities for the poorest households.However, for the non-poor, caloric intake actually increases when taxes are levied. Thus, whileoverall caloric consumption would be virtually unchanged, the number of households below thecalorie benchmark used would increase because of the negative impact on the poorer households.

A change in the current VAT exemption for oils would cause as great an increase in thenumber of households with low energy intakes as would a change in the maize exemption.However, this would be driven mainly by the change in the number of calorie deficient householdsin urban areas. A tax on edible oil would have a much higher impact than maize in terms ofpercentage increase in the number of calorie deficit households per billion Rand raised in taxes-7.8% per billion Rand for oil, compared to 2.2% for maize. The increase in the number of caloriedeficient households when a VAT is levied on beans per billion Rand is intermediate between thatof oils and maize, at 4.9%.

The substitution between commodities dominates the impact of taxes on other food items.Thus, for many goods, the VAT has little effect on total calories consumed by the poor or thenumber of households below the benchmark. This is, of course, expected for kerosene, but is alsothe case for sugar, butter and margarine, and fluid milk in rural areas. There, a VAT exemption formeat would increase the number of households below the cutoff point, although it would improveconditions in urban areas. The VAT exemption for bread would increase the calories consumed andreduce the number of households below the threshold of calorie consumption. The net effect of adecrease in taxes for the four foods and one non-food being considered would be a relativelysubstantial drop in urban malnutrition, but virtually no change in rural areas.

In general, households with sufficient energy intakes also have sufficient protein intake.Indeed, in this sample, 99% of the households with low protein consumption also had low caloricintakes. Moreover, those that consume few proteins derive most of them from cereals and beans.Thus, while Table 6 indicates a VAT exemption on meat would favorably affect proteinconsumption of the rural poor (in contrast to its impact on calories), this impact is stillcomparatively small. In addition, as with calories, cross-price effects would cause a decline inprotein consumption if VAT exemptions were introduced for sugar. Indeed, in rural areas, the dropwould be greater than the increase attributed to the VAT exemption for meat. Table 6 also indicatesthat the current exemption for fluid milk has a negligible impact on protein consumption.

V. CONCLUSION

The study confirms the logic of VAT exemption for maize. Based on tax efficiency andequity, this commodity dominates all altematives. Also, tax exemptions for fluid milk or breadhave similar implications as maize for the total revenue foregone, but have less favorable impactson equity. Similarly, while the tax exemption for maize helps improve nutrition in both urban andrural areas, the tax exemptions on fluid milk has virtually no impact on energy or even proteinintake. In contrast to milk, however, the impact on nutrient consumption of a tax exemption forbread is fairly similar to that of maize; the two commodities differ, however, in that a VATexemption for maize has strong estimated equity impacts while it does not for bread.

7

Povertv Issues for Zero Rating VAT in South Africa

Tax exemptions for beans, sugar or kerosene do have favorable rankings from the standpointof equity. Only beans exhibit an appreciable positive impact on energy intake attributed to a taxexemption. Zero rating these three commodities would have comparatively little fiscalconsequence: The amount of revenue lost with zero rating the three commodities is less than iscurrently foregone with the zero rating for fresh milk.

The tax exemption for meat clearly would lead to more revenue lost than with any othercommodity--even if one considers the absolute rather than the relative value of the exemption on thepoor. The VAT exemption for meat saves the poor 325 million Rand (0.18 x 1.8 billion) comparedto 436 million Rand with the zero rating of maize. The leakage in terms of revenue foregone inorder to reach roughly similar tax savings for the poor, however, is quite dissimilar: The result of atax exemption on meat is seven times as great as on maize.

Thus, while the equity and efficiency of commodity taxation may be achieved if exemptionson kerosene and sugar are substituted for those on fluid milk, other changes being considered haveless to recommend them. In particular, a VAT exemption for meat is not justified either in terms ofequity or nutrition: It would favor non-poor urban households and have a negative impact on thecalorie consumption of rural households. Conversely, as is commonly understood, the exemption onmaize is well targeted and has a measurable positive impact on caloric consumption by deficithouseholds.

8


REFERENCES

Agha, Ali and Jonathan Haughton. 1996. Designing VATSystems: Some Efficiency ConsiderationsReview of Economics and Statistics 78(2):303-308.

Ahmad, Ethisham and Nicholas Stern. 1991. The Theory and Practice of Tax Reform forDeveloping Countries. Cambridge: Cambridge University Press.

Bailey, Brandon. No date. The Zero Rating of Foods for VATPurposes. Johannesburg: Land andAgriculture Policy Center. Processed

Carter, Michael and May, Julian. 1997. Poverty, Livelihood and Class in Rural South Africa. StaffPapers Series. Agricultural and Applied Economics. University of Wisconsin-Madison

Deaton, Angus. 1997. The Analysis of Household Surveys: A Microeconometric Approach toDevelopment Policy. Baltimore: Johns Hopkins University Press.

Deaton, Angus and Franque Grimard. 1992. Demand Analysis and Tax Reform in Pakistan. WorldBank. Living Standards Measurement Study Working Paper #85.

LSDS, Living Standards and Development Survey. 1994. Southern African Labour andDevelopment Research Unit (SALDRU) School of Economics, University of Cape Town,South Africa.

McLachlan, Milla and Carol Marshall. 1995. Nutrition in South Africa. A Proposal forTransformation. Midrand: Development Bank of South Africa. Processed.

Newbery, David and Nicholas Stem. 1987. The Theory of Taxation for Developing Countries.Oxford: Oxford University Press.

Pinstrup-Andersen, Per, Norha Ruiz de Londono and Edward Hoover. 1976. The Impact ofIncreasingFood Supply on Human Nutrition. American Joumal of Agricultural Economics58 131-142.

Pitt, Mark. 1983. Food Preferences and Nutrition in Rural Bangladesh. Review of Economics andStatistics. 65: 105-114.

Younger, Stephen, David Sahn, Steven Haggblade, Paul Dorosh. 1996. Tax Incidence inMadagascar: An Analysis Using Household Data. Comell University, mimeo.

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APPENDIX

Table 1: Commodities Used in the Demand Analysis and Exempt from VAT

Exemptions Other Exemptions | Commodity 1 Commodities inas of 1993 Proposed Groups J Questionnaire

Maize Maize MaizeSamp MealieMealieDried MealieBrown Wheaten MealieBrown Bread White Bread Bread Bread (white and brown)

White Flour Other Cereals RiceWheatBreakfast Cereal

Potatoes PotatoesMadumbane

Dried Beans Beans Dried beansLentilsEggs Red Meat Meat Mutton

White Meat ChickenEgg Powder Eggs

Tinned sardines Tinned Herrings Fish Fresh fishl____________ _ lTinned fish

Fresh Milk Milk MilkPowder Milk Margarine Dairy Products Margarine, butterCultured Milk Butter Cheese

Powder milkVegetables Dehydrated Vegetables Fruits and TomatoesFruits Canned Vegetables Vegetables PumpkinLegumes Other fruits and veg.

BananasApple

.___ ___ ___ _ _ CitrusVegetable Oil Oils Oil

__________________ Sugar Sugar SugarOther Foods Jam

Other foodsDrinks Soft drinksMeals Prepared meals outside

____________________ ________ _______ ______ _ ____Prepared m eals insideKerosene Kerosene XKerosene

10


Figure 1: Expenditure patterns for Maize, Bread, Beans and Meat173923 0 p 0 19.19 CO

D, < 0.

0 0 IO

0D Q 0~ 0000000,

000 CP ~ 00 00

00 0 0)

000~~~~~~~~~~~~~~0 0:0

0 ~ ~ ~ ~ ~ ~ ~ ~ ~ I -0

0 ~~~~~~~~003.77932 ~~~~~ ~~~~~ ~ ~~~~0000 0-00000

0 o~~~~~~ 3.77052 1409

3.41359 8.26455 3.41359 8.26455p,, s.pib Th.dterdrr Pr c.pit. rEfflandksr

1. Per capita Maize Expenditure 2. Per capita Bread Expenditure

3.21881 0 , 91.8008 0 00 0 D

0 0 0 0

8 ~~~~~~~~~0.0C 900 0 0 0 0000

00 0O 0 CDA

Cb ~~~~~0032& 0

.333724 -1 0 1.28902

3413359 P-pi8ExpcWit- 8.26455 3.41359 pit. EVdit- 8.26455

3. Per capita Beans Expenditure 4. Per capita Meat Expenditure

Figure 2: Expenditure patterns for Milk, Sugar, Oil and Kerosene3737459 0 6893567 39 4

0~~~~~~~~~~~~~~~~

0 00 IO000

000

0 00 0

C3)b7 0=

.827931 3.13 %o .2653 1.83357 0

3.41~~~~~59 8.26455 ~~~~~~~~3 .41359 8.26455Pc c.pit. E1and6rib Pe, c.pit. Exp.iditrm

S. Per capita Milk Expenditure 6. Per capita Sugar Expenditure

4.71947 o 0 6.57228 0 0

0: 0 00

0 00(ICP oOo 00 0 0

0 00~~~~~~~~~~~~~~~~~ QD 00~~00 ~

o 0 0 0 0

0 0 0~~~~~~~~~~~~~~~~~~~~Q 0 0

0

1 00~~~~~~~~~~1

.675537 0 8245 .246612 0 .245

3.41 359 -i.E dif .653415 A& Atu8245

7. Per capita Oils Expenditure 8. Per capita Kerosene Expenditure

0

Table 2: Expenditure and Calorie Shares and Income and Own Price Elasticitles by Locations (and Pooled)

Rural Metro and Urban PooledBudget shares Elasticities Budget shares Elasticities Budget shares Elasticities N

Expend. Calories Own Price Income Expend. Calories Own Price Income Expend. Calories Own Price Income Z

Maize 12.18 42.84 -0.23 0.31 2.22 14.59 -0.44 0.00 6.91 27.52 -0.60 0.02Bread 5.25 11.47 -0.72 0.99 3.49 16.66 -0.32 0.50 4.32 14.28 -0.64 0.80Cereal 3.61 9.73 -1.03 0.77 1.94 10.12 0.06 0.61 2.73 9.94 -0.77 0.66Potato 1.97 2.92 -0.71 0.61 1.40 4.64 -0.64 0.40 1.67 3.85 -0.68 0.52Beans 1.14 2.13 -1.49 0.90 0.47 1.78 -1.19 0.47 0.78 1.94 -1.39 0.70Meat 8.13 5.50 -0.76 1.29 8.40 12.71 -0.91 0.84 8.27 9.41 -0.82 1.09Fish 1.06 - 0.11 -1.34 1.10 0.96 0.59 -0.87 0.81 1.01 0.37 -1,14 0.97Milk 2.65 1.59 -0.50 0.93 2.45 3.90 -0.52 0.85 2.54 2.84 -0.41 0.87 4Dairy products 1.97 2.49 -0.16 1.23 2.05 6.09 -0.59 0.78 2.01 4.44 -0.36 1.01Fru & Veg 4.63 4.50 -0.61 0.98 3.88 10.54 -1.07 0.77 4.23 7.78 -0,82 0.91Oils 1.55 6.24 -0.54 0.63 0.88 8.29 -0.84 0.45 1.20 7.35 -0.58 0.55Sugar 3.60 9.94 -0.18 0.44 1.36 8.71 -0.39 0.29 2.42 9.27 -0,25 0.28Other 4.00 0.19 -3.11 1.46 2.89 0.57 -1.75 0.69 3.41 0.40 -1.92 1,13Drinks 1.16 0.35 -1.72 1.55 1,33 0.80 -0.80 1.10 1.25 0.60 -1.17 1.38Kerosine 2.37 0.00 -1.37 0.31 1.24 0.00 -1.23 -0.40 1.77 0.00 -1.15 0.11Non Foods 44.73 0.00 -0.96 1.17 65.04 0.00 -0.91 1.17 55.48 0.00 -0.93 1.20

Tot calories 2609.88 2716.04 2666.39HH Expend.(Rand) 974 2,510 1,786PC ixpend.(Rand) 277 880 596Weighed Observat. 4,138 4,643 8,781


Table 3: Relative Social Cost of Tax Reform due to Current VAT Exemptions

Revenue LossTotal per Year From Poor

Alpha 0 0.5 1 2 (Mill. Rand) (Percentage)

Maize 1.07 1.23 1.60 3.74 666,886 65.38Beans 1.11 1.08 1.19 2.07 102,263 42.45Fresh Milk 0.92 0.63 0.55 0.75 621,910 15.32Oil 0.97 0.90 0.98 1.78 179,723 35.89All Together 0.97 0.92 1.05 2.16 1,616,629 40.54

Figure 3: Relative Social Cost of Tax Reform due toCurrent VAT Exemption

4.00-

3.50-

3.00-

2.50 -

2.00-

1.50 -

1 00

0.00

N~~~~ 0

Legend: Values of Alpha

N0 00.5 Q1 *2

13


Table 4: Relative Social Cost of Tax Reform due to Proposed VAT Exemptions

Revenue LossTotal per Year From Poor

Alpha 0 0.5 1 2 (Mill. Rand) (Percentage)

Bread 0.92 0.82 0.85 1.33 664,133 33.4Meat 0.85 0.62 0.55 0.70 1,806,957 18.0Other Dairy 0.89 0.64 0.56 0.72 444,660 18.5Sugar 1.02 1.03 1.21 2.49 260,079 49.2Kerosine 1.00 1.10 1.35 2.90 152,362 66.0

All Together 0.87 0.68 0.66 0.96 3,233,553 24.5

Figure 4: Relative Social Cost of Tax Reform due toProposed VAT Exemptions

3.00

2.50

2.00

1.50l-_.

0.50 W r

| 0. O !

Legend: Values of Alpha

i0 *0.5 ol 32

14


Table 5: Impact of VAT Exemption on Caloric Consumption

Base Run IndividualsAverage Caloric Consumption Consuming Less

Poverty Rate All Non poor Poor than 2000 Kcal(Percent) (Kilocalories per person per day) (Percent)

Rural 73.72 2,443 3,840 1,945 42.75Urban 28.95 2,323 2,674 1,462 38.17

All 52.86 2,387 3,021 1,822 40.61Change in percent

Change in Caloric Consumption consuming LessAll Non poor Poor than 2000 Kca

Elimination of current VAT (Percent) (PercentExemption (Price increase)Maize Rural 0.10 1.93 -1.19 1.46

Urban 0.15 0.71 -2.34 1.41All 0.13 1.17 -1.42 1.44

Beans Rural -0.66 -1.00 -0.42 0.79Urban -0.06 -0.05 -0.07 0.14All -0.39 -0.41 -0.35 0.50

Fresh Milk Rural -0.11. -0.27 0.01 0.12Urban 0.24 0.29 0.05 -1.13All 0.05 0.08 0.02 -0.43

Oils Rural -0.51 -0.51 -0.52 o.esUrban -1.20 -1.18 -1.25 2.37All -0.82 -0.93 -0.67 1.40

Four Foods Rural -1.29 -0.01 -2.20 3.83Urban -0.85 -0.24 -3.59 3.76All -1.09 -0.15 -2.48 3.80

Addition of VATExemption (Price decrease)Bread Rural 1.27 1.54 1.07 -2.36

Urban 0.64 0.56 1.01 -1.70All 0.98 0.93 1.06 -2.07

Meat Rural -0.33 0.04 -0.59 0.70Urban 1.47 1.71 0.39 -2.56All 0.48 1.08 -0.39 -0.73

Butter & Margarine Rural -0.29 -0.34 -0.26 0.29Urban 1.25 1.35 0.81 -2.16All 0.41 0.71 -0.04 -0.79

Sugar Rural -0.59 -1.06 -0.27 0.44Urban 0.09 -0.06 0.76 -1.15All -0.28 -0.44 -0.06 -0.26

Kerosene Rural 0.27 0.27 0.27 -0.36Urban -0.49 -0.54 -0.26 1.11All -0.08 -0.24 0.16 0.28

5 Commodities together Rural -0.18 -0.06 -0.26 0.17Urban 3.57 3.71 2.94 -6.28All 1.52 2.28 0.40 -2.66

Observations (in Thousand)All Non Poor Poor

Rural 21,026 5,525 15,501Urban 18,352 13,039 5,313All 39,378 18,564 20,814

15


Table 6: Impact of VAT on Protein Consumption

Base Run Individuals

Average Protein Consumption Consuming LessPoverty Rate All Non poor Poor than 38.4 Proteins

(Percent) (Proteins per person per day) (Percent)Rural 73.72 63.68 108.62 47.66 23.77Urban 28.95 71.79 85.37 38.45 15.93

All 52.86 67.46 92.29 45.31 20.12

Change in percentChange in Protein Consumption consuming Less

All Non poor Poor than 38.4 ProteinsElimination of current VAT (Percent) (PercentExemption (Price increase)Maize Rural 0.70 2.55 -0.81 4.50

Urban 1.32 1.91 -1.86 0.62All 1.01 2.13 -1.04 3.07

Beans Rural -1.39 - -1.77 -1.09 2.97Urban -0.69 -0.71 -0.55 0.50All -1.04 -1.08 -0.97 2.06

Fresh Milk Rural -0.14 -0.32 0.01 0.48Urban 0.50 0.57 0.12 O.fSAll 0.18 0.26 0.03 0.36

Oils Rural -0.27 -0.45 -0.12 0.26Urban -0.49 -0.53 -0.26 0.18All -0.38 -0.50 -0.15 0.23

Four Foods Rural -1.31 -0.23 -2.18 9.31Urban 0.60 1.18 -2.57 4.30All -0.36 0.68 -2.26 7.46

Addition of VATExemption (Price decreaselBread Rural 1.86 2.21 1.58 -3.39

Urban 0.50 0.37 1.23 -2.27All 1.19 1.01 1.51 -2.98

Meat Rural 1.77 2.87 0.87 -1.57Urban 5.33 5.71 3.24 -8.13All 3.53 4.72 1.38 -3.99

Butter & Margarine Rural -0.06 -0.08 -0.05 0.20Urban 1.28 1.40 0.61 -0.51All 0.60 0.88 0.09 -0.06

Sugar Rural -0.84 -0.96 -0.74 2.19Urban -0.08 -0.05 -0.25 0.08All -0.46 -0.37 -0.63 1:41

Kerosene Rural 0.00 -0.20 0.17 -0.44Urban -0.85 -0.94 -0.39 0.29All -0.42 -0.68 0.04 -0.17

5 Commodities together Rural 2.68 4.01 1.60 -3.23Urban 7.36 7.80 4.92 -12.84All 5.00 6.47 2.32 -6.77

Observations (in Thousand)All Non Poor Poor

Rural 21,026 5,525 15,501Urban 18,352 13,039 5,313All 39,378 18,564 20,814

16

Table Al: Demand Elasticities -All Observations

Commodity W Maize Bread 0. Cereal Potato Beans Meat Fish Milk 0. Dairy Fru Veg Oils Sugar 0. Food S.drinks Keros. Non F. Income

Maize 0.0691 -0.60 0.04 0.18 0.00 0.08 0.16 0.07 0.05 0.01 0.01 -0.03 -0.01 0.00 -0.02 0.05 -0.01 0.02

Bread 0.0432 0.01 -0.64 0.31 -0.02 0.05 -0.47 -0.08 0.07 0.07 -0.20 -0.10 0.08 0.24 -0.09 0.31 -0.34 0.80

0. Cereal 0.0273 0.41 0.49 -0.77 0.10 -0.26 0.13 0.18 -0.37 -0.02 0.11 0.14 0.11 -0.24 0.16 -0.41 -0.42 0.66Potato 0,0167 -0.04 -0.04 0.17 -0.68 0.22 0.08 -0.03 0.09 -0.07 -0.05 0.04 0.09 -0,06 0.06 -0.09 -0.19 0.52

Beans 0.0078 0.63 0.29 -0.90 0.46 -1.39 -0.49 -0.23 -0.13 -0.24 -0.31 -0.12 0.01 0.82 0.31 -0.3B 0.97 0.70Meat 0.0827 0.06 -0.26 0.03 0.01 -0.05 -0.82 0.01 0.03 -0.04 0.08 0.00 0.10 0.00 -0.06 0.11 -0.29 1.09

Fish 0.0101 0.44 -0.36 0.47 -0.05 -0.18 0.06 -1.14 -0.20 -0.32 0.15 -0.31 0.15 0.49 -0.41 0.10 0.13 0.97

Milk 0.0254 0.09 0.12 -0.41 0.05 -0.04 0.13 -0.08 -0.41 0.06 0.12 0.00 -0.34 -0.05 0.12 -0.27 0.03 0.870.Dairy 0.0201 -0.05 0.14 -0.03 -0.07 -0.10 -0.15 -0.16 0.07 -0.36 -0.08 -0.11 0.31 -0.21 -0.13 0.08 -0.17 1.01

Fruits & Veg 0.0423 -0.04 -0.21 0.06 -0.03 -0.06 0.17 0.04 0.07 -0.04 -0.82 0.00 0.02 0.04 -0.08 0.06 -0.09 0.91Oils 0.0120 -0.20 -0.36 0.32 0.05 -0.08 0.04 -0.26 0.01 -0.18 0.00 -0.58 -0.09 0.64 -0.17 -0.02 0.33 0.55Sugar 0.0242 -0.05 0.17 0.13 0.06 0.01 0.41 0.07 -0.34 0.28 0.05 -0.04 -0.25 -0.25 0.12 -0.14 -0.51 0286Other food 0.0341 -0.08 0.29 -0.21 -0.04 0.18 0.00 0.14 -0.05 -0.13 0.05 0.22 -0.20 -1.92 0.16 -0.03 0.48 1.13Soft Drinks 0.0125 -0.23 -0.35 0.34 0.07 0.19 -0.44 -0.34 0.24 -0.22 -0.30 -0.17 0.21 0.44 -1.17 -0.07 0.42 1.38Kerosene 0.0177 0.19 0.79 -0.62 -0.08 -0.16 0.57 0.07 -0.37 0.11 0.17 -0.01 -0.18 0.59 -0.04 -1.15 0.00 0.11

Non Foods 0.5548 -0.08 -0.02 -0.06 -0.02 0.00 -0.04 0.00 -0.02 -0.01 -0.01 0.00 -0.05 0.03 0.01 -0.01 -0.93 1.20

N,

0

cj30'

~n

N

Table A2: Demand Elasticities - Rural Households

Commodity W Maize Bread 0. Cereal Potato Beans Meat Fish Milk 0. Dairy Fru Veg Oils Sugar 0. Food S.drinks Keros. Non F. Income Y

Maize 0.1218 -0.23 -0.05 0.27 0.01 0.09 0.13 0.01 0.13 0.03 -0.06 0.00 0.06 -0.09 0.01 0.03 -0.65 0.31Bread 0.0525 -0.20 -0.72 0.17 0.03 -0.03 -0.30 -0.10 0.05 0.13 -0.07 -0.11 -0.01 0.14 -0.09 0.37 -0.25 0.99 >0. Cereal 0.0361 0.85 0.26 -1.03 0.03 -0.36 0.12 0.23 -0.37 0.00 -0.17 0.17 0.27 -0.40 0.12 -0.57 0.07 0.77 iPotato 0.0197 0.00 0.10 0.07 -0.71 0.27 0.03 -0.05 0.15 -0.03 -0.05 0.02 0.05 -0.31 0.01 -0.20 0.04 0.61Beans 0.0114 0.92 -0.15 -1.16 0.46 -1.49 -0.20 -0.09 -0.22 -0.29 -0.45 -0.06 -0.20 0.56 0.34 -0.37 1.50 0.90Meat 0.0813 0.08 -0.21 0.03 -0.01 -0.03 -0.76 -0.02 -0.04 0.01 0.10 -0.02 0.12 -0.04 -0.09 0.12 -0.52 1.29 sFish 0.0106 0.02 -0.52 0.77 -0.09 -0.10 -0.15 -1.34 -0.16 -0.17 0.22 -0.43 0.52 0.73 -0.77 0.30 0.07 1.10Milk 0.0265 0.52 0.11 -0.60 0.11 -0.10 -0.08 -0.06 -0.50 -0.04 0.20 -0.01 -0.28 -0.05 0.06 -0.38 0.08 0.930. Dairy 0.0197 0.10 0.33 -0.01 -0.04 -0.17 0.03 -0.09 -0.06 -0.16 -0.38 -0.10 0.38 -0.30 -0.13 -0.01 -0.61 1.23Fruits&Veg 0.0463 -0.25 -0.08 -0.14 -0.03 -0.11 0.20 0.05 0.11 -0.16 -0.61 -0.03 -0.05 -0.13 -0.10 0.10 0.25 0.98Oils 0.0155 -0.05 -0.34 0.41 0.02 -0.04 -0.05 -0.29 -0.02 -0.12 -0.08 -0.54 -0.08 0.50 -0.38 0.03 0.41 0.63Sugar 0.0360 0.18 0.02 0.28 0.03 -0.06 0.34 0.16 -0.19 0.23 -0.03 -0.03 -0.18 -0.44 0.16 -0.07 -0.85 0.44Otherfood 0.0400 -0.41 0.16 -0.39 -0.17 0.16 -0.10 0.19 -0.04 -0.15 -0.18 0.18 -0.43 -3.11 0.29 -0.07 2.62 1.46SoftDrinks 0.0116 -0.07 -0.42 0.33 0.00 0.32 -0.63 -0.71 0.12 -0.23 -0.41 -0.62 0.45 1.01 -1.72 -0.22 1.15 1.56Kerosene 0.0237 0.17 0.85 -0.85 -0.16 -0.17 0.48 0.14 -0.41 0.01 0.22 0.02 -0.09 -0.01 -0.09 -1.37 0.94 0.31Non Foods 0.4473 -0.28 0.00 -0.06 -0.02 0.03 -0.06 0.01 -0.02 -0.03 0.03 0.01 -0.10 0.24 0.03 0.01 -0.96 1.17

Table A3: Demand Elasticities - Urban and Metropolitan Households

Commodity W Maize Bread O.Cereal Potato Beans Meat Fish Milk 0. Dairy Fru Veg Oils Sugar 0. Food S.drinks Keros. Non F. Income

Maize 0.0222 -0.44 0.07 0.18 -0.12 0.16 0.24 0.49 -0.16 -0.09 -0.08 -0.03 0.05 0.88 -0.31 -0.06 -0.78 0.00Bread 0.0349 0.04 -0.32 0.10 -0.02 0.09 -0.45 0.05 0.12 0.03 -0.27 -0.06 0.01 0.02 -0.05 0.16 0.03 0.50O. Cereal 0.0194 0.20 0.18 0.06 0.14 -0.10 0.09 -0.14 0.04 -0.22 0.43 -0.01 0.07 -0.11 0.08 0.03 -1.34 0.61Potato 0.0140 -0.20 -0.05 0.19 -0.64 0.09 0.13 0.00 -0.10 -0.13 0.00 0.04 0.06 0.18 0.07 0.00 -0.05 0.40Beans 0.0047 0.73 0.70 -0.41 0.25 -1.19 -0.89 -0.71 0.68 -0.05 0.26 -0.39 0.11 0.50 0.08 0.05 -0.20 0.47Meat 0.0840 0.04 -0.20 0.02 0.02 -0.05 -0.91 0.03 0.06 -0.07 0.06 0.02 0.05 0.03 -0.03 0.09 0.01 0.84Fish 0.0096 1.10 0.19 -0.29 -0.01 -0.35 0.25 -0.87 0.08 -0.62 0.15 -0.19 -0.50 0.23 -0.15 0.13 0.04 0.81Milk 0.0245 -0.16 0.16 0.02 -0.06 0.13 0.19 0.03 -0.52 0.35 -0.27 0.07 -0.07 -0.09 0.16 -0.23 -0.55 0.85O.Dairy 0.0205 -0.11 0.04 -0.21 -0.10 -0.01 -0.28 -0.29 0.42 -0.59 0.32 -0.14 0.06 -0.24 -0.09 0.18 0.26 0.78 oFruits&Veg 0.0388 -0.06 -0.25 0.21 -0.01 0.03 0.13 0.04 -0.17 0.17 -1.07 0.03 0.02 0.10 -0.01 -0.07 0.14 0.77 '

Oils 0.0088 -0.09 -0.22 -0.02 0.06 -0.21 0.23 -0.21 0.19 -0.32 0.15 -0.84 -0.17 0.79 0.09 0.06 0.06 0.45 -o

Sugar 0.0136 0.08 0.03 0.10 0.07 0.04 0.38 -0.35 -0.12 0.11 0.09 -0.11 -0.39 0.47 -0.03 -0.04 -0.61 0.29Otherfood 0.0289 0.66 0.02 -0.08 0.08 0.08 0.10 0.08 -0.08 -0.17 0.14 0.24 0.22 -1.75 0.04 0.02 -0.30 0.69SoftDrinks 0.0133 -0.54 -0.15 0.10 0.07 0.02 -0.22 -0.11 0.28 -0.14 -0.05 0.05 -0.04 0.08 -0.80 0.04 0.29 1.10 x

Kerosene 0.0124 -0.11 0.49 0.06 0.01 0.02 0.71 0.11 -0.42 0.32 -0.18 0.05 -0.03 1.16 0.07 -1.23 -0.63 -0.40 z

Non Foods 0.6504 -0.06 -0.01 -0.05 -0.01 0.00 -0.02 0.00 -0.04 0.01 -0.01 0.00 -0.03 -0.03 0.01 -0.02 -0.91 1.17

mN

:Z

0


ENDNOTES

i The reader is referred to Ahmad and Stem (1991) and Newbery and Stem (1987) for detaileddiscussions of theoretical, administrative and empirical dimensions of taxation.

2 A distinction is made between exempting a commodity from VAT and having it zero rated. Inthe latter case, the producer is able to claim a rebate on taxes on intermediate inputs. However,for convenience of presentation, we use the phrase exemption on commodities which aretechnically zero rated.

I"' The data is available on the Wide World WEB on the following site: www.worldbank.org/html/prdph/lsms/country/za94/za94home.html#top

iv. A much larger matrix of demand parameters can be derived using the Linear Expenditure System(Ahmad and Stem, 1991), but at an unacceptably high cost in flexibility.

v For example, using the median adult equivalent expenditure of 390 Rand instead of the povertyline would increase the reported relative social costs by 29.6% for all commodities when a=l. Thereason why the norrnalization makes a difference is, as mentioned above, when Ua>Q, 0 depends onthe ratio of household income to the reference income.

We do not consider the largely unresearched issue of how in-kind wages respond to changes intaxes.

vii. The corresponding cross-price parameters are available from the authors.

viii. Deaton and Grimard (1992) present another perspective -on the shift of consumption towardstaxed commodities. Since these are consumed below the level that would be the case based onshadow pricing, such a shift increases the attractiveness of the new tax.

20

poverty issues for zero rating value-added tax (vat) in...

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