local government revenue policies and...

LOCAL GOVERNMENT REVENUE POLICIES AND THEIR IMPACTS:

A MODEL FOR TANZANIA AND UGANDA

Zara Sarzin

Water and Urban, East and Southern Africa (AFTU1)

June 2007

ACKNOWLEDGEMENTS

The author would like to acknowledge the valuable contributions and guidance received from Matthew Glasser (Lead Urban Specialist, East and Southern Africa, World Bank) and Uri Raich (Urban Specialist, East and Southern Africa, World Bank), who generously gave of their time to review and edit several drafts of this report. This study would not have been possible without their involvement. The author would also like to thank Paul Francis (Senior Social Scientist, World Bank), Somik Lall (Senior Economist, Finance, Economics and Urban Development, World Bank) and David Savage (Senior Institutional Development Specialist, South Asia Sustainable Development, World Bank) for peer reviewing the paper. Their detailed and insightful comments have been incorporated into the paper. In addition, the study relied on the field work conducted by the DAI Europe team, which included Naomi Humphries, Fiona MacCulloch, Jeremiah Lima and Alfred Etwom. There were many other people who generously contributed their time and expertise and to whom the author is extremely grateful. Their names are listed in Annex A.

1 TABLE OF CONTENTS

Acknowledgements....................................................................................................................................... 2 1 Table of Contents................................................................................................................................... 3 2 Abbreviations and Acronyms ............................................................................................................... 4 3 Executive Summary ............................................................................................................................... 5 4 Introduction ............................................................................................................................................ 8 5 Relevance of a Local Tax Incidence Model ....................................................................................... 11 6 Local Government Revenues in Tanzania ......................................................................................... 14 7 Local Government Revenues in Uganda ........................................................................................... 22 8 How we Developed the Model: Data and Tax Incidence Methodology ........................................... 28

8.1 Collection of Data on the Utilisation of Local Tax Instruments........................................................ 28 8.2 Household Data .............................................................................................................................. 29 8.3 Enterprise Data ............................................................................................................................... 30 8.4 Description of the Model ................................................................................................................. 30

9 Using the Model: Illustrations............................................................................................................. 32 9.1 Local Income Taxes........................................................................................................................ 32 9.2 Land and Property Taxes................................................................................................................ 35 9.3 Automotive Taxes ........................................................................................................................... 38 9.4 Local Sumptuary Taxes .................................................................................................................. 40 9.5 Impact of Local Taxes on Enterprises............................................................................................. 41

10 Summary of Initial Findings and Key Messages ........................................................................... 42 10.1 Key Messages and Initial Recommendations ............................................................................. 43

11 Conclusions And Next Steps .......................................................................................................... 44 12 References ........................................................................................................................................ 47 Annex A: People Met................................................................................................................................... 49 Annex B: Current Local Revenue Instruments in Tanzania .................................................................... 52 Annex C: Tanzania Rates and Charges..................................................................................................... 56 Annex D: Current Local Revenue Instruments in Uganda ...................................................................... 58 Annex E: Uganda Rates and Charges ....................................................................................................... 63 Annex F: Household Survey Data.............................................................................................................. 66 Annex G: Enterprise Data........................................................................................................................... 72 Annex H: Initial Results from the Enterprise Module............................................................................... 75

2 ABBREVIATIONS AND ACRONYMS

AE Adult Equivalent CSL City Service Levy EPRC Economic Policy Research Centre ERB Economic Research Bureau GDP Gross Domestic Product GSU Georgia State University IMF International Monetary Fund KCC Kampala City Council LGA Local Government Authorities (in Tanzania) LGFA Local Government Finances Act of 1982 LGRP Local Government Reform Project LGSP Local Government Support Programme LGU Local Government Units (in Uganda) NBS (Tanzania) National Bureau of Statistics PAYE Pay As You Earn Tax PMO-RALG Prime Minister’s Office Regional Administration and Local Government PSIA Poverty and Social Impact Analysis REPOA Research on Poverty Alleviation TRA Tanzania Revenue Authority UBOS Uganda Bureau of Statistics ULB Unified Local Business Tax VAT Value Added Tax VDC Village Development Contribution

3 EXECUTIVE SUMMARY

Adequate and buoyant local revenues are critical to ensuring the viability and sustainability of local authorities and the quality of services they provide. However, there is often a perception that healthy local revenues are necessarily in tension with economic development or poverty alleviation. This paper will argue that a well designed system of local taxation can reconcile the needs of various stakeholder groups, including local authorities, residents and businesses. And, that it is possible to design a local tax system that is adequate, sustainable and buoyant, and which doesn’t disadvantage the poor or smaller businesses. Accomplishing this requires choosing local tax instruments with an awareness of their impacts on different income classes. Concerns about the equity implications of local revenue policies have led to the abolition of several local taxes in Uganda and Tanzania. These changes have significantly reduced local revenue collections, and minimised the importance of local taxes in the overall intergovernmental fiscal framework. There is significant scope to expand local revenue collections in both countries—in a way that is pro-poor and business-friendly. In general, local taxes should reflect taxpayers’ ability to pay—i.e. tax payers with higher incomes or greater assets should bear a greater share of the tax burden. The central purpose of this study is to encourage evidence-based policy choices on local revenue policy, and to foster debate on new sources of local revenue. A primary output of this study is a simple model of local tax incidence to estimate the relative impact of alternative revenue policies on different income classes. There are many factors that policymakers need to take into account when setting local revenue policy including revenue yield, economic efficiency, administrative efficacy and the equity implications of various local tax options. The tax incidence model focuses on the equity implications (or fairness) of alternative local revenue policies. When policymakers are contemplating changes to the local tax framework, this modelling tool can help to identify which categories of households and firms will end up paying relatively more or less tax. The local tax incidence model can also help policymakers—through the selection and design of local revenue instruments—to shape the incidence of local taxes. Before abolishing or suspending local taxes because they are perceived to be regressive, options should be explored to improve the equity of the tax instrument. The analysis illustrates the steep regressivity of some local taxes, particularly those that are applied as a flat amount irrespective of ability to pay. It is important to recognise that local taxes can be restructured to increase their progressivity, for example by applying exemptions for poorer households, or by implementing a simple system of graduated tax rates. Increasing the equity of a local tax can encourage greater tax compliance, enabling lower rates to be charged. It is important to recognize that the specific design features of a local tax can alter its incidence. The analysis shows that within a family of taxes, individual tax instruments can be regressive or progressive depending on their detailed design. The details are what count. It is therefore important to understand the implications of various design options including the definition of the tax base, the rate structure, and the exemptions that apply. These can significantly alter the incidence of the tax. Beyond equity considerations, there are a number of factors that policymakers need to take into account when setting local revenue policy including revenue yield, economic efficiency and administrative efficacy of various local tax options. The health of the local tax system and the consequent quality of local service delivery is constrained by a number of factors including: (1) the high costs of collection relative to yield for some taxes; (2) low compliance rates for some taxes; (3) the lack of voice felt by taxpayers and negative perceptions of service quality, which affect willingness to pay taxes; (4) the propensity for some local authorities to ignore central government legislation in their search for new revenue sources (a dynamic that was documented following recent tax reforms in Tanzania); and (5) leakage of revenues from privatized tax collection arrangements, which can introduce wide margins between payment by taxpayers and yield to authorities. These constraints need to be considered alongside equity when considering the merits of local revenue policy options.

The paper illustrates how the model can be used to make decisions between different types of local taxes, or to design the details of a particular tax. Initial results from the model are presented, which show the incidence of various local taxes using households survey data from Uganda and Tanzania. These include: (1) personal income taxes; (2) land and property taxes; (3) automotive taxes; and (4) sumptuary taxes. The key findings from the modelling exercise are summarised in the table below.

Table 3.1: Local Tax Incidence Model—Initial Findings Tax Instrument Initial Findings

Personal Income Taxes

• The illustrations show that a flat head tax and a flat household head tax are often regressive for rural and urban households. In Tanzania, the household head tax is slightly less regressive since lower income households typically have larger numbers of adult members than richer households.

• A simple graduated structure can ensure a more progressive incidence across households. However, it can also create some odd discontinuities and can be steeply regressive across some income classes. This arises because of the specific graduations that are chosen.

• It is possible to modify or smooth the incidence of a graduated income tax by changing the income bands and the rates that apply. The larger the number of income bands, the more control policymakers can have over the progressivity or the incidence of the tax. This, of course, needs to be balanced against the ease of understanding and administering the tax instrument.

• A local surcharge on PAYE (the Ugandan national income tax) produces a smooth incidence curve for urban households.

• The impact of a local income tax needs to be considered in the context of central government taxes (e.g. the Graduated Tax in Uganda only applied up to the PAYE threshold).

Land and Property Taxes

• A flat urban property tax (modeled for Tanzania) is highly regressive across household quintiles.

• A basic ad valorem tax (modeled for Tanzania as a percentage of capital improvements) is slightly regressive across urban household quintiles. This suggests that poorer households are relatively asset rich and income poor, and that wealthier households are relatively income rich and asset poor.

• An exemption may be applied to low value properties to reduce administrative costs (without significantly reducing revenue) and/or to introduce a more progressive element into the tax structure. An exemption applied to low value properties results in a discontinuity in the incidence curve.

• An exemption applied to the first TShs X of property value (keeping the tax rate unchanged) results in a smoother incidence curve. Since the rate is applied to a narrower tax base, it may be desirable to increase the rate to generate additional revenues. Increasing the tax rate further increases the progressivity of the tax.

Automotive Taxes • Automotive taxes are typically progressive across household quintiles. • A fuel levy (modeled for Uganda) would be highly progressive, with the burden of

the levy falling on the wealthiest two quintiles

Sumptuary Taxes • The results show that a tax on cigarettes can be either regressive or progressive depending on consumption patterns across households.

• The results for Uganda suggest that a tax on soda or beer is likely to be progressive for both urban and rural households.

The design of the local tax incidence model reflects a trade-off between complexity and ease of use. The expansiveness and complexity of the model also reflects the availability and reliability of data on households and enterprises, which support the distributional analysis. The model can easily be modified to reflect policy changes and can be adapted as new sources of data become available. The concluding section of the paper highlights the strengths and weaknesses of the model and future options for improving or expanding this work.

4 INTRODUCTION

Adequate and buoyant local revenues are critical to ensuring the viability and sustainability of local authorities and the quality of services they provide. In Uganda and Tanzania, local authorities1 account for a significant share of government spending, and therefore play a fundamental role in the implementation of national growth and poverty reduction strategies. In mainland Tanzania for example, LGAs account for approximately one in every five shillings of public spending.2 In Uganda, the share is even greater, with one in every three shillings spent at the LGU level.3 The effectiveness of local service provision relies on adequate and buoyant local revenues, which support sustainable operations and maintenance of local infrastructure and also help to finance staff salaries, councillor emoluments and other administration expenses. Local revenues can help to reduce budget reliance on external sources.4 However, the role of local taxation in the public sector is about more than maximising revenue yield. Local taxation promotes greater community involvement, enhances the accountability of local authorities to their constituents, and helps to reduce vertical fiscal imbalances.5 Throughout East Africa, there is a perception that healthy local revenues are necessarily in tension with economic development or poverty alleviation. On one hand, it is argued that local revenues are needed to support the effective delivery of infrastructure and services. On the other hand, local taxes are often criticised for being inefficient, having an anti-poor bias, affecting resource allocation decisions by distorting relative prices (i.e. by imposing different tax rates on different items), and having a negative impact on local economic outcomes by inhibiting start-up businesses. This paper will argue that a healthy, equitable system of local taxation can ensure adequate revenues without retarding economic development or exacerbating poverty. Accomplishing this requires choosing local tax instruments with an awareness of their impacts on different segments of the population. Concerns about local revenues have led to the abolition of several local taxes in both Uganda and Tanzania. In Tanzania, the abolition of the Development Levy and a variety of nuisance taxes, followed by the virtual abolition of local business licenses as a revenue source, created fiscal stress for many LGAs. In Uganda, similar fiscal pressures have been exerted on LGUs as a result of recent decisions to suspend the Graduated Tax and to amend the Local Government (Rating) Act of 2005. While there were real problems with some of these abolished taxes, not all local taxes share these problems. In fact, there are real advantages to sound local taxes. A well designed system of local taxation can reconcile the needs of various stakeholder groups, including local authorities, residents and businesses. A local authority’s pursuit of strong local revenues is often perceived to be in conflict with the needs of residents and businesses (see Table 4.1. below). However, a healthy system of local taxation can be designed to: (1) provide adequate and buoyant revenues from the point of view of local government, (2) be equitable from the point of view of citizens, especially the poor; and (3) provide incentives for local government to facilitate the formation and growth of enterprises. This requires political will to tax more actively those households and businesses that can afford to pay, in order to provide local authorities with the revenues to deliver public services and maintain local infrastructure.

1 Local Government Authorities in Tanzania and Local Government Units in Uganda. In this paper, when we are speaking about Tanzania, we will use the abbreviation LGA, and when speaking about Uganda, we will use LGU. We will use the term “local authorities” when we intend to refer to both countries. 2 Local Government Fiscal Review (2006), p. 20. 3 Steffensen (2004c), p. 68. 4 Boex Comments. In Tanzania’s MKUKUTA, the Government notes that Tanzania is a low-tax country, and that enhanced revenue mobilization is needed in order for the budget to be less dependent on external sources. Increasing overall revenue mobilisation through improvements in the local revenue system should be an important part of this strategy. 5 Boex (2006), Transformation of the Local Revenue System, p. 3.

Table 4.1: Framework for Local Taxation—Perspectives of Various Stakeholder Groups

Local Authorities Residents Businesses

• Local revenues need to be adequate to meet the cost of the services and infrastructure they are intended to finance.

• Local revenues need to be buoyant—the tax base should grow automatically when prices rise, population grows or the economy expands—to meet expanding demands for service delivery.

• Revenue collections need to be stable and predictable to facilitate planning and budgeting.

• Collection and administration costs need to be minimized.

• Local revenue autonomy and flexibility need to be reinforced.

• Tax instruments need to be politically acceptable.

• The framework for local taxation needs to be simple, transparent and easy to understand.

• The local tax system needs to be fair and equitable in both design and administration. – Everyone should pay

something. – The tax burden should be

proportionate to ability to pay (vertical equity).

– Taxes should be applied consistently for individuals at the same income level (horizontal equity).

– Intensive users of municipal services should pay more (benefits principle).

• Local taxes need to be linked to services provided.

• Local revenues should enhance accountability and strengthen the social contract at the local level.

• Compliance costs for taxpayers need to be minimized.

• The local tax system needs to be fair and equitable in both design and administration. – All enterprises pay

something. – Similarly situated

businesses pay similar taxes.

• Local taxes need to support a conducive business environment. – Taxes should not distort

economic activity (efficiency).

– Taxes should minimize barriers to enterprise development, especially for small and medium-size enterprises.

• Local taxes need to be linked to services provided.

• Compliance costs for taxpayers need to be minimized.

There is significant scope to expand local revenue collections in both Uganda and Tanzania—in a way that is pro-poor and business-friendly. In Tanzania, per capita local revenue collections declined from TShs 1,726 in FY 2002/03 to TShs 1,352 per capita in FY 2005/06.6,7 In Uganda, per capita local revenue collections declined from UShs 3,886 in FY 2002/03 to UShs 2,345 in FY 2005/06 (excluding Graduated Tax compensation).8 There is significant scope to expand own source revenue collections.9 However, any expansion in local revenues needs to happen in a way that is pro-poor and business-friendly. It is therefore important to know which local taxes are regressive, neutral or progressive.

6 Local Government Fiscal Review (2006), p. 29. 7 1 USD = 1,247 TZS on 31 May, 2007. 8 1 USD = 1,692 UGX on 31 May, 2007. 9 According to the IMF, total domestic revenue collections in Uganda have remained stagnant at around 12 percent of GDP, with local revenue collections in the order of 0.7 percent of GDP in 2005. After the suspension of the graduated tax, we estimate that local revenue collections fell to around 0.4 percent of GDP. In Tanzania, local revenue collections were roughly 0.3 percent of GDP in 2005, in the context of total domestic revenue collections of 13.1 percent of GDP.

The central purpose of this study is to encourage evidence-based policy choices on local revenue policy, and to foster debate on new sources of local revenue. Despite common perceptions that local government revenues are regressive and inefficient, there is little quantitative analysis available to assess the incidence and revenue impacts of local taxes, and to formulate appropriate policy recommendations. A key output of this study is a simple model of local tax incidence to estimate the relative impact of alternative revenue policies on different categories of households and firms. The model is geared towards understanding the equity implications of different local taxes. While equity is only one of many considerations when setting local revenue policy, equity issues are often the most divisive when trying to reach a consensus across different stakeholder groups on the most appropriate taxes to apply at the local level. The model can help policymakers—through the selection and design of local revenue instruments—to control the incidence of local taxes. The model is intended as a tool for policymakers to: (1) provide estimates of the distribution of local tax impacts across different categories of households and firms, in order to better understand who bears the burden of local taxes, and whether existing local tax instruments are regressive, neutral or progressive; and (2) provide a tool to test alternative tax policies, to help ensure that local revenue policies have the desired impact. The goal of this analysis is to support a genuine discussion about options and impacts, which should point the way to a constructive synthesis that fully considers, and has the potential to serve, the interests of citizens, local government, taxpayers, the poor, and the private sector. The study builds on the 2005 Poverty and Social Impact Analysis (PSIA) conducted by the World Bank in Tanzania. The 2005 PSIA examined the intended and unintended consequences of the tax reforms implemented between 2003 and 2004 in Tanzania, which included the elimination of the Development Levy, “nuisance taxes”, and business licenses for enterprises below a certain size (and the capping of licenses for larger firms). The PSIA concluded that the impact of the reforms, while varying across different categories of households and firms, was broadly progressive. The 2005 report called for further analytical work to inform the ongoing policy dialogue. Specifically, the study highlighted the need for a simple model of households and enterprises to assess the impact of various local tax alternatives.10 In Tanzania, this study is also intended as a complement to work on local government revenue policy being conducted with donor basket-funding, by Georgia State University (GSU) on behalf of the Ministry of Finance and the Ministry of Local Government. It also supports the work on local revenue enhancement in Dar es Salaam, which is in the initial stages of implementation, as component 2(b) of the Local Government Support Project (LGSP).

10 World Bank (2006), p. 39.

5 RELEVANCE OF A LOCAL TAX INCIDENCE MODEL

The purpose of this work is to promote informed policy choices at the national and local level, and to foster debate on local revenue instruments. The work aims to support a discussion about options and impacts, which can point the way to a synthesis that fully considers the interests of citizens, local government, taxpayers, the poor, and the private sector. The key question for both national and local policymakers is how policies towards local revenues can encourage taxes which meet three important criteria: (1) they should be adequate and buoyant from the point of view of local government; (2) they should be equitable from the point of view of citizens (especially the poor), and (3) they should not pose entry barriers to enterprise development (and perhaps even provide structural incentives for local authorities to facilitate formation and growth of enterprises). The primary output of this work is a modelling tool that enables policymakers to assess how particular taxes impact on households and firms. There are many factors that policymakers need to take into account when setting local revenue policy including revenue yield, economic efficiency, administrative efficacy and the equity implications of various local tax options. The tax incidence model focuses on the equity implications (or fairness) of alternative local revenue policies. When policymakers are contemplating changes to the local tax framework, this modelling tool can help to identify which categories of households and firms will end up paying relatively more or less tax. Regardless of a policymaker’s views on how local tax liabilities should be distributed across different groups of households and firms, it is important that this distribution is determined by choice, and not by chance. The local tax incidence model can help policymakers—through the selection and design of local revenue instruments—to shape the incidence of local taxes. The model is intended as a tool for both national and local policymakers. National policymakers might find the model useful as they decide on the revenue raising powers of local authorities, or as they make decisions in respect of the design of a particular tax. The model can also inform local design choices within whatever freedom of action local policymakers are allowed by national legislation. There are several ways in which the model may be used: • The model can help both national and local governments understand which income classes bear the

burden of local taxes. In this way, the model can inform public debate on who should pay local taxes. • The model can be used to assess the equity implications of proposed changes to the local tax

system. The model can provide estimates of the incidence of the local tax structure before and after the proposed changes and demonstrate whether or not the burden of the tax changes falls disproportionately on particular groups.

• The model can help policymakers make informed choices between different types of taxes to apply. Some families of taxes tend to be less or more progressive than others. The equity implications of tax options can be balanced against other considerations such as revenue yield, economic efficiency and administrative efficacy.

• The specifics of a particular tax, such as the structure of rates and charges and the exemptions that apply, also affect incidence. The model can therefore assist policymakers as they develop the detailed design of a particular tax.

• The model can be used as a starting point for regular tax incidence studies. Regular studies of this kind can help policymakers determine whether trends in the economy or flaws in the design of tax instruments have led to unintended consequences in the incidence of local taxes.

Most policymakers agree that taxes should reflect taxpayers’ ability to pay—tax payers with higher incomes or greater assets should bear a greater share of the tax burden. Progressive and proportional taxes typically satisfy the ability to pay principle. Taxes are progressive when their incidence increases as incomes rise, i.e. higher income taxpayers pay a greater percentage of their income in tax than lower income taxpayers. Proportional taxes are those whose incidence is constant as income rises, and so everyone pays the same percentage of their income in tax. Regressive taxes, on the other hand, are those whose incidence decreases as incomes rise, and so lower income taxpayers end up paying a greater percentage of their income in tax than higher income taxpayers. These concepts are illustrated in Diagrams 5.1 to 5.3 below.

Diagram 5.1: Incidence of a Progressive Tax

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Diagram 5.2: Incidence of a Proportional Tax

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Diagram 5.3: Incidence of a Regressive Tax

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6 LOCAL GOVERNMENT REVENUES IN TANZANIA

Prior to 2003, Local Government Authorities in Tanzania were empowered to define their own local tax structure. The Local Government Finances Act of 1982 (LGFA)—which defines the financial framework for local government authorities (LGAs) in Tanzania—allowed an ‘open list’ or permissive approach to local taxation. This gave LGAs wide powers to impose taxes, levies and fees and set rates within their local jurisdictions. Consequently, the number and type of local taxes, levies and fees varied significantly from one LGA to another and there were also large variations in the rates imposed by LGAs on similar tax bases. Local taxes were criticized for being inefficient—the cost of collection could consume a significant portion of tax revenue for specific taxes; and since LGAs made use of a multiplicity of taxes instead of a few productive ones, a single home or business was frequently and repeatedly bothered for relatively small amounts of revenue. Local taxes were also criticized for being regressive and for creating disincentives for the creation and growth of private enterprises. And a further problem related to the legitimacy of the local tax regime—taxpayers did not feel they had any voice in decisions relating to the setting of tax rates or the expenditure of tax revenues. Despite the large number of revenue instruments in use, 60 percent of local revenues came from three main sources. Prior to 2003, the lion’s share of local revenues came from a combination of just three sources: (1) the Development Levy, which alone accounted for 20 percent of own source revenues; (2) agricultural and livestock taxes; and (3) licenses and fees (including business licenses). Local revenue collections varied significantly across rural and urban LGAs. In rural LGAs, the predominant revenue sources were the Development Levy, the agricultural cess and the livestock levy. In urban LGAs the most productive revenue sources were licences and fees (including business licenses), the City Service Levy (CSL) and property taxes, which together accounted for approximately two-thirds of local revenues for a typical urban LGA. Table 6.4 provides statistics on the relative importance of local revenue sources. Annex B summarises the local tax instruments currently in use in Tanzania, including details on the tax base, rates and exemptions that typically apply.

Box 6.1: Major Local Revenue Sources in Tanzania Prior to 2003: • Twenty percent of own source revenues came from the Development Levy, a flat head tax payable by

adults over the age of 18 (with women and the elderly exempted in some districts). • Agricultural and livestock taxes were major sources of revenue for rural LGAs, levied on the sale of

agricultural produce and livestock, up to a maximum of 5 percent of the farm gate price. • Licenses and fees including business licenses accounted for a significant share of revenue for urban

LGAs. Fees ranged between TShs 60,000 and TShs1,000,000 per licence.11 (Since 2004/05, business licenses are only issued when a business is established and not every year. The maximum license fee is set at TShs 20,000 for all businesses with a turnover exceeding TShs 20 million.)

After the 2002/03 reforms: • Agricultural and livestock taxes continue to be a major source of revenue for rural LGAs. • The relative importance of the City Service Levy has increased since the 2002/03 reforms. It is levied

at a rate of 0.3 percent of enterprise turnover, for those enterprises whose turnover exceeds TShs 20 million per annum.

11 Franzsen and Semboja (2004), p. 33.

Due to the inefficiency and equity impacts of the local tax system, a series of reforms were implemented in 2003 and 2004, which included the abolition of “nuisance taxes” and the Development Levy and the elimination of local business licenses as a revenue source. First, in 2003 the Development Levy was abolished together with a number of minor local revenue sources (the so called “nuisance taxes”). Second, with the objective of improving the business environment, further reforms were implemented in 2004 which reduced license fee collections at both central and local government levels, and effectively eliminated the revenue aspect of local business licenses.12 Finally, the Local Government Finance Act was amended to eliminate all taxes and fees levied by LGAs except those specified in a schedule to the Act. While the rates applicable to these local taxes and fees can in many cases be determined by LGAs, in most cases there is a maximum rate prescribed by the central government.13 The reforms significantly reduced the revenue raising authority of LGAs and minimised the importance of local revenues in the overall intergovernmental fiscal framework. The abolished taxes have not been replaced by sound local revenue sources, and as a result the reforms significantly reduce the revenue raising authority of local government. Prior to the reforms, own revenue sources accounted for approximately 20 percent of local government fiscal resources. By 2005/06, own source revenues accounted for less than 10 percent of total local government finances. This trend has implications for the accountability of LGAs to their constituents. Diagram 6.1 illustrates this consistent decline in own source revenues as a percentage of total local government finances. 14

Diagram 6.1: Composition of Local Government Finances in Tanzania

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12 Under the new system, businesses only apply for a licence on start-up which is then valid for the lifetime of the business. The fee is only applied to businesses with turnovers exceeding TShs 20 million at a maximum rate of TShs 20,000. 13 GSU (2005), p. 4-16 14 Local Government Fiscal Review (2006), p.4.

With the abolition of the Development Levy and other reforms, local governments in Tanzania lost substantial income from own revenue sources. Local revenue collections fell from a high of TShs 57.7bn in 2002 to TShs 42.9 billion in 2004/05. Although the impact was felt across both urban and rural regions, rural districts suffered most. The decline in local revenue collections was partially reversed in FY 2005/06, with collections increasing to TShs 49.3 billion. These trends are illustrated in Diagrams 6.2 and 6.3 below.

Diagram 6.2: Trend in Local Government Revenue Collections15

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15 Local Government Fiscal Review (2006), p. 29. 16 Local Government Fiscal Review (2006), p. 29.

As a result of the reforms, LGAs were forced to rely on fewer local revenue instruments. As a consequence, the relative importance of various categories of local revenues changed significantly, as summarised in Table 6.1.17

Table 6.1: Local Revenue Collections by Source (2002-2005/6)18

2002 2003 2004/05 2005/06 (%) (%) (%) (%) Development levy 20 7 0 0 Property tax 6 6 10 10 Agricultural cesses 16 19 27 22 City Service Levy 16 16 25 24 Land rent 1 1 1 2 Licenses and fees 20 25 13 2 Charges 10 11 15 26 Other revenues 11 15 10 15 Total revenues 100 100 100 100

A 2005 Poverty and Social Impact Analysis conducted by the World Bank found that the impacts of the reforms were broadly progressive for households and firms. While on average, households recorded a very small decrease (0.8 percent) in overall tax payments, the tax burden increased by 14 percent for better-off households, remained about the same for median households, and decreased by 34 percent for poor households. On average, enterprises recorded a 14 percent decrease in tax payments. The tax burden fell by 11 percent for medium enterprises and 36 percent for small businesses. Micro businesses recorded an 11 percent increase in tax payments, which was attributed to their likely non-payment of previous business registration fees, coupled with the wider use of other taxes (such as billboard fees) which were imposed on micro businesses with greater vigour than the defunct licence fees.19 A 2006 FIAS report draws attention to several outstanding problems with the local tax regime in Tanzania, despite the reforms implemented in 2003 and 2004. The report suggests that LGAs are either ignoring the new legislation or finding ways around it to re-introduce new levies and fees. The report also notes that LGAs still levy a large number of taxes, fees, licenses and charges, some of which constrain the commercialisation of smallholder agriculture and the formalisation of small and micro enterprises. The report highlights inefficiencies that arise due to the limited cooperation between the Tanzanian Revenue Authority (TRA) and LGAs. Enterprises provide similar data to several government bodies, which raises compliance costs and increases the overall administrative costs in the public sector. 20

17 GSU (2005), pp. 2-7, 2-8 18 Local Government Fiscal Review (2006). 19 World Bank (2005), p. 37. 20 FIAS (2006), pp. 2, 4, 9. Concerns relate specifically to: (1) multiple taxes (including fees and charges), which make business entry difficult and expensive—levies are perceived as exorbitant, and are often charged up-front irrespective of the size and type of business; (2) the duplication of some local and central taxes; (3) new charges introduced by LGAs to replace abolished nuisance taxes; and (4) a lack of transparency with regard to exemptions; and (5) coercive enforcement, which legitimizes tax resistance and encourages tax evasion. The report also notes that the imposition multiple taxes on smallholders can accumulate up to 20 percent of the farm gate price: small-holders only pays taxes through district (“cess”) levies, other local government taxes and through fuel duty, and according to legislation local governments are only allowed to apply a cess of up to 5%. However, the imposition of other levies and taxes can add up to 20% of farm gate prices in certain crops in some local authorities.

A 2005 study conducted by the Local Government Reform Programme (LGRP) in collaboration with Georgia State University (GSU) identifies property rates and local business taxes as the two ideal mainstays of a local revenue system. The study notes that property taxation has not lived up to its revenue potential, and recommends that improvements be made to the structure and administration of property tax over time—including valuation, assessment, administration, collection and enforcement activities. Specific proposals are made to expand the scope of the property tax by: (1) assigning land rents to the LGA level, and ultimately integrating these into the property tax; (2) encouraging LGAs to levy special assessments (“betterment levies”) to cover the cost of specific infrastructure projects with identified localized benefits; and (3) imposing a rural property tax or simple flat rate on the occupancy of land and huts21. The study also recommends the consolidation of numerous small local business taxes and levies into a single Unified Local Business Tax (ULB). The ULB is envisaged as a broad based tax on business income, based on gross turnover, which would absorb the City Service Levy, the crop and forest produce cess, the guest house levy; and the fish landing or auction levy. Businesses not subject to these taxes would become subject to a tax payment (a fixed charge based on the type, size and location of the business).22 Property and business taxes would be supplemented by revenues from licenses and permits, local fees and charges, and other revenue sources. The LGRP/GSU study also suggests new revenue sources for LGAs including: (1) a formalised village development contribution; (2) a local surcharge on national income tax; (3) a local levy on utility charges; and (4) the assignment of annual motor vehicle fees to the local government level. Firstly, the study notes that personal taxes (something along the lines of the abolished Development Levy) do not appear to be a viable tax at the district level, but that a personal contribution could be feasible at the village level. Currently village LGAs rely on all sorts of informal and “voluntary” village contributions, permitted but not well defined under the current “closed list”, which could be formalised. Secondly, the study proposes a surcharge on the national income tax, which could be levied on the tax base of the national income tax. LGAs could be given discretion to set a flat (proportional) rate within nationally defined minimum and maximum rates. Thirdly, the study proposes a local levy on electricity and other utility charges. And finally, the study proposes assigning motor vehicle annual fees (currently collected by the TRA district offices) to the LGA level. 23 A recent government cabinet paper on local revenue issues draws and builds on the recommendations made in the LGRP/GSU study. The cabinet paper includes proposals for assigning land rents to the local government level, a Unified Local Business Tax, formalising the village development contribution as a local levy, a local levy on utility charges and assigning annual motor vehicle fees to the LGA level. The paper does not include any proposals for a surcharge on the national income tax, which is not considered feasible at this time. The cabinet paper also makes additional recommendations including a proposal for a sumptuary tax on goods such as beer, soft drinks, cigarettes and clothing, which are typically consumed by better off households.24 Table 6.2 summarises some proposals for new sources of local revenues in Tanzania, including proposed tax bases, rates and exemptions.

21 GSU (2005), pp 4-44, 8-16 to 17, 4-33. 22 GSU (2005), pp 4-42, 8-15. 23 GSU (2005), pp. 8-17 to 8-18. 24 Meetings with PMO-RALG and LGRP officials.

Table 6.2: Alternative Local Revenue Instruments in Tanzania

Instrument Tax Base and Exemptions Rate Source

Personal Taxes

Modified Development Levy

Payable by adults 18 years or older resident in the jurisdiction of a local authority. Women and the elderly could be exempted from paying the tax.

The original levy was a flat amount for individuals not employed in the formal sector and a variable rate for those in formal employment (typically 1 percent of salaries, although it seems that this was not commonly applied).25 The modified levy could be structured as: (1) a uniform flat amount per capita, with LGAs given discretion to set the rate between centrally legislated minimums and maximums; or (2) a graduated amount per capita, possibly on the basis of profession or other visible characteristic of taxpayers’ income.

Village Development Contribution (VDC)

Adults of working age.

Simple, three-tiered structure: (1) a standard charge in a pre-determined range (e.g. TShs 100 to TShs 1,000 per person), subject to a maximum of, say, TShs 2,000 per household; (2) a higher rate on wealthy households (e.g. assessed on ownership/use of automobile or motorcycle; children attending a private school; salaried employees above a certain threshold etc.) The higher rate would be set at twice the standard rate (per-household maximum doubled as well); and (3) a zero-rated tier for poor households.

GSU (2005), p 8-17-18.

Local Personal Income Tax Surcharge

Tax base of the central government personal income tax (or personal income tax base). PAYE exemptions are currently granted to individuals not in formal employment and full time students.

LGAs would have discretion to set a flat (proportional) rate within nationally defined minimum and maximum rates, in the order of 2 percent of PAYE income.

GSU (2005), p 4-55.

25 Before it was abolished, the Development Levy in Dar es Salaam was a flat rate of TShs 4,600 per annum for those in formal employment, and TShs 300 per annum for those not formally employed.


Taxes on Land and Property

Modified Property Tax

Betterment levy possibilities—LAs would be encouraged to levy a location specific property rate to cover the cost of specific infrastructure projects with identified localized benefits. Rural property tax—simple flat rate on the occupancy of land and huts should be possible. Exclude low value properties, e.g. residential properties under TShs 5 million.26

GSU (2005), pp. 4-55, 4-33.

Land Rent Assign Land Rent exclusively to the local government level (or shift revenue sharing from the current 80/20 sharing in favour of the Ministry of Lands, to 20/80 in favour of districts).

GSU (2005), p 8-16 to 17

Taxes on Production and Turnover

Modified City Service Levy (CSL)

Introduce a statutory CSL turnover threshold, to ensure that revenues at least exceed the cost of administration and to ensure horizontal equity.

Franzsen, R. and Semboja, J. (2004), p. 31.

Unified Local Business Tax

Tax based on gross turnover. Applied to all businesses and productive enterprises (including those not currently taxed locally) with a turnover exceeding the central government’s VAT threshold (TShs 40 million).

Harmonize effective tax rates.27 This does not imply the same tax rate on turnover for different types of business activity. Flat rate system for small businesses.28 Broadening the local tax base to include smaller businesses would allow the rate structure to be set low.

GSU (2005), pp 4-42, 8-15, A4-14.

Levies on Utility Charges

Local levy on utility charges

Utility charges. Rates could be set by individual LGAs within centrally legislated minimums and maximums.

GSU (2005), p 8- 18

Automotive Taxes

Motor Vehicle Annual Permit Fee29

Assign annual permit fees associated with motor vehicle registration (currently collected by the TRA district offices) to the local government level.

Annual fee of TShs 10,000 for motorcycles and motor vehicles.

GSU (2005), p 8- 18

26 Faber (2004), pp. 21-22. It may make sense to exclude low value properties from taxation, because the cost of identification, valuation, registration, billing and collection can be higher than the revenues collected. This can be done in two ways: (1) exclude properties which are assumed to be under TShs 5 million from the valuation and detailed registration exercise; or (2) give all property owners a deduction on the rateable value of TShs 5 million and exclude properties which are, before deduction, assumed to be under TShs 5 million from the valuation and detailed registration exercise. 27 Currently, tax rates range from 0.3 percent of turnover for the Service Levy and 2 percent for the Stamp Duty to 5 percent for agricultural products. 28 For smaller businesses or businesses that cannot produce turnover information the local government will assess fixed charges according to a centrally legislated schedule that will allow variations by type, size, and location of the business.


Other

Sumptuary Taxes Taxes on beer, soft drinks, cigarettes, hard liquor. Collected from manufacturer, but impact passed through to consumer.

Flat amounts per litre of liquor and soft drink, and per stick of cigarette.

29 GSU (2005), pp. 4-62 to 63. Fees and taxes on motor vehicles in Tanzania include: (1) motor vehicle registration fee collected on the first registration of vehicles, levied at a flat rate of TSh 95,000 per registration for motor vehicles and TShs 32,000 for motor cycles; (2) annual fee of TShs 10,000; (3) fee of TShs 55,000 incurred on the transfer of vehicle ownership, paid by the new owner; (4) Car benefit tax paid by all commercial private companies not involved in transport business at TShs 100,000 per vehicle owned per annum; and (5) foreign motor vehicle permit and transit charges paid by all non commercial foreign motor vehicles temporally imported into Tanzania.

7 LOCAL GOVERNMENT REVENUES IN UGANDA

Own source revenues in Uganda have declined significantly relative to total local government finances. A recent IMF study suggests that local revenues as a percentage of total local government resources has declined from approximately 80 percent in the early stages of the decentralisation process (1997/98) to about 20 percent in 2004/05.30 Two main factors account for this trend. Firstly, the rapid increases in central government transfers to the local level, largely donor financed, which have undermined incentives for own source revenue mobilisation.31 Secondly, recent changes to the framework for local taxation have undermined the revenue raising authority of Local Government Units (LGUs) and have led to a narrowing of the local tax base. Historically, the lion’s share of local revenues in Uganda came from just three sources: Graduated Tax; property rates; and user fees. The 1995 Ugandan Constitution and the 1997 Local Government Act empower LGUs to levy, charge and collect local taxes.32 While the fifth schedule of the Act specifies numerous local revenue instruments33, in practice LGUs depend on a small number of local revenue sources. Historically, the significant share of local revenue came from just three sources: Graduated Tax; property rates; and user fees (market dues and parking fees being the most significant). Before FY 2005/06, Graduated Tax was the most significant source of revenue for LGUs in Uganda, accounting for over 60 percent of own source revenues in rural districts and over 40 percent nationally. Annex D outlines the local tax instruments currently in use in Uganda, including details on the tax base, rates and exemptions that typically apply.

Box 8.1: Major Local Revenue Sources in Uganda

• Prior to its suspension, the Graduated Tax was levied on adult men and those adult women in gainful employment (in practice only women with regular salaries paid the tax). The amount of the Graduated Tax varied across income bands, from UShs 3,000 on incomes below UShs 288,000 per annum up to UShs 100,000 on incomes over UShs 1,560,000 per annum.

• Property taxes in Uganda are payable by the owners of residential buildings in urban areas (from 2006 owner occupiers are exempt), and commercial and industrial building in both rural and urban areas. Property rates typically range from 7 to 10 percent applied to the annual rental value of the property.

• Prior to 2006, market vendors were required to pay daily market dues calculated on the basis of goods brought into or sold in the market. Market fees are now structured as a daily fee for using market facilities.

• Parking fees are payable in many urban jurisdictions for the use of public parking bays.

30 IMF (2006), p. 13. 31 Mahler (2005), p. ii. Transfers from the central government increased by 322 percent from 1997/98 to 2003/04. 32 Article 176 (d) of the Ugandan Constitution establishes the principle that each LGU should have a sound financial base with reliable sources of revenue. Article 191 (1) gives LGUs the power to levy, charge, collect and appropriate fees and taxes in accordance with any law enacted by Parliament. Article 191(2) specifies these rents, rates, royalties, stamp duties, personal graduated tax, cess, on registration and licensing and any other fees and taxes that Parliament may prescribe. Section 80 of the Local Government Act provides for LGUs to levy, charge and collect fees and taxes including rates, rents, stamp duties, personal graduated tax and registration and licensing fees and the fees and taxes that are specified in the fifth schedule of the Act. 33 These include: graduated tax; property rates; fees and fines on licenses and permits in respect of service rendered or regulators power exercised by the LGU; interest on investments; rents from lease of property owned by the LGU; fees and fines imposed by courts administered by the LGU; annual bicycle licenses; parking fees; advertisement fees; cess on production; user charges where applicable; fishing licenses; agency fees; charcoal burning licenses; and any other revenue prescribed by the LGUs and approved by the Minister of Local Government.

Many local taxes were criticised for being regressive and for having a negative impact on economic growth. Local taxes, particularly the Graduated Tax, market dues and business licenses, were criticised for having a negative impact on income distribution due to the “steep regressivity” of tax instruments.34 Moreover, local taxes, particularly market dues, were criticised for having a negative impact on economic growth by distorting the relative prices of goods and services.35 These concerns reinforced the momentum towards modifying or suspending several local taxes. Changes to the framework for Graduated Tax in 2001 and its subsequent suspension from FY 2005/06 significantly reduced own source revenues, particularly in rural areas. Graduated Tax declined significantly following the Presidential election of 2001, when the minimum Graduated Tax payment was reduced from UShs 11,000 to UShs 3,000 per annum.36 As a consequence, most taxpayers insisted they be assessed at this minimum level, and own source revenue fell dramatically from over UShs 103 billion in 1999 to UShs 69.7 billion in 2001. The decision was subsequently taken to suspend the Graduated Tax from FY 2005/06. One of the reasons cited for abolishing the tax was the disproportionate burden of the tax on poorer households. While the Government provided LGUs with compensation of UShs 34 billion in 2005/6, this was not sufficient to fill the funding gap arising from the suspension of the tax, which was in the order of UShs 45 billion in 2004/05.37 In 2006, changes to the framework for property taxes and market fees further increased the fiscal pressure on LGUs. During the 2006 presidential election campaign, candidates argued for changes to the framework for property rates and market fees. Under the 2005 Local Government (Ratings) Act, property taxes are levied on commercial and industrial buildings (in both rural and urban areas) and residential buildings in urban areas. In 2006, the Act was amended to exempt owner occupied residential housing, which accounts for a significant share of residential property in urban areas.38 This amendment significantly undercuts the local tax base, and also removes a key accountability link between taxpayers/voters and their elected councillors. Moreover, in 2006, the framework for market fees was amended so that market vendors are only required to pay a monthly rental. (Previously vendors were charged daily fees calculated on the basis of goods brought into or sold in the market, with rates varying across different types of market goods). Wholesalers bringing in foodstuffs and other items in bulk are only charged a one-off fee each time they supply the market and market vendors buying those items are not required to pay any dues on those items. While these changes mitigate concerns that market fees were regressive and distorted relative prices, the changes also minimise a key remaining source of revenue for LGUs. Significant declines in local revenue raise concerns about the sustainability and viability of the local government system in Uganda. The significant reductions in own source revenues undermine the accountability of LGUs to their constituents and weakens the linkages between local taxes and service delivery. As a consequence of budget shortfalls, local councils are meeting less frequently, are failing to meet their co-financing obligations, have limited resources to finance operations and maintenance costs, and are failing to meet their pension obligations.39 This has obvious implications for the quality of services provided. There is a growing imperative to find alternative sources of local revenue that support the fiscal sustainability of LGUs.

34 For individuals not in salaried employment, an assessment of income was based on property ownership which was not always considered to be fair. Harassment was also reported. 35 Bahiigwa et al (2004), p. vi. 36 Bahiigwa et al (2004), pp. 10-11. 37 There is a significant difference, in decentralisation and political terms, between a LGU’s own source taxes and a transfer from central government, 38 According to the 2006 National Household Survey. 78 percent of Ugandan households are owner occupiers. In Kampala, however, 28 percent of household live in owner occupied housing. 39 Wasike (2007) and Nalugo (2007).

Diagram 7.1: Trend in Local Revenue Collections in Uganda40

-

20,000

40,000

60,000

80,000

100,000

120,000

2001/02 2002/03 2003/04 2004/05 2005/06

Rev

enue

Col

lect

ions

USh

Mill

ions

Other RevenuesUrban Authority PermitsRevenue from deptsUser feeProperty TaxGraduated Tax

Table 7.2: Composition of Local Revenues in Uganda—Rural41

Year 2001/02 2002/03 2003/04 2004/05 2005/06 Graduated Tax 67.1% 64.9% 63.9% 60.5% 0.0% Property Tax 0.0% 0.0% 0.0% 0.0% 0.0% User Fees 10.0% 10.5% 11.6% 15.3% 38.4% Revenue from Departments 3.0% 3.8% 3.8% 4.0% 10.6% Urban Authority Permits 0.6% 0.8% 1.3% 4.1% 10.0% Other Revenues 19.3% 20.0% 19.4% 16.2% 41.0% Total Local Revenue 100.0% 100.0% 100.0% 100.0% 100.0%

Table 7.3: Composition of Local Revenues in Uganda—Urban (including KCC)42

Year 2001/02 2002/03 2003/04 2004/05 2005/06 Graduated Tax 18% 21% 21% 19% 0% Property Tax 30% 26% 20% 17% 19% User Fees 21% 25% 25% 29% 37% Revenue from Departments 0% 0% 1% 3% 4% Urban Authority Permits 12% 14% 19% 15% 22% Other Revenues 18% 14% 14% 17% 18% Total Local Revenue 100% 100% 100% 100% 100%

40 Ministry of Local Government data. 41 Ministry of Local Government data. 42 Ministry of Local Government data.

Table 7.4: Composition of Local Revenues in Uganda—Rural and Urban combined (including KCC)43

Year 2001/02 2002/03 2003/04 2004/05 2005/06 Graduated Tax 41% 44% 44% 41% 0% Property Tax 16% 13% 9% 8% 12% User Fees 16% 18% 18% 21% 38% Revenue from Departments 2% 2% 2% 4% 7% Urban Authority Permits 7% 7% 10% 9% 17% Other Revenues 19% 17% 17% 17% 27% Total Local Revenue 100% 100% 100% 100% 100%

Several recent studies suggest options for expanding local revenue collection by introducing new local taxes or making changes to the tax base for existing local revenue instruments. These proposals are summarised in Table 7.5 below. Four specific proposals currently being considered by the Government of Uganda include: (1) a local service tax to be levied on salaried individuals, practicing professionals and business people; (2) a local government hotel tax to be levied on all room occupants, chargeable per room per night; (3) a local fee on motor vehicles to be paid by motor vehicle owners; and (4) a livestock tax to be levied on all farmers who own livestock.

Table 7.5: Alternative Local Revenue Instruments in Uganda

Instrument Proposed Tax Base and

Exemptions Proposed Rate Source

Personal Taxes

Local government income / service tax

Levied on individuals in employment, deducted from monthly salaries. Exclusions for non-agricultural informal sector and working poor.

Average of UShs 1,000 per month. World Bank Mission

Development levy “Community Development Fund” incorporating strengths and addressing the weaknesses of the Graduated Tax. Revenue to remain at village/parish level and not at sub-county/district level.

Simplify the assessment process and use fewer income bands.

Mahler (2005), p. 68.

Surcharge on PAYE Applied as a percentage surcharge on PAYE base or PAYE collections.44

Surcharge of 10 or 20 percent. Mahler (2005), p. xvii.

43 Ministry of Local Government data. 44 PAYE is an instalment income tax system under which employers are required to deduct tax instalments from their employees' salary or other employment income. Deductions are remitted to the Uganda Revenue Authority (URA) and based on the PAYE tax return lodged by the employer. The total amount deducted from the individual employee is offset against the employees' tax liability upon the lodgement of the annual tax return by the employee at the end of the tax year.

Instrument Proposed Tax Base and Exemptions

Proposed Rate Source


Modify urban property tax

Change the tax base from annual net rental value to capital value of land and improvements (improved capital value). Tax undeveloped urban land. Even if it is decided to keep the rental value system, a mechanism to tax undeveloped land should be introduced, such as taxing it at a percentage of the sale value of the land. Tax all urban properties including owner occupied residential property, which is currently exempt from paying property tax. Allow districts in rural areas to levy a property tax on industrial or residential building as well as commercial buildings. An exemption could be applied to low value properties.

Keep the maximum rate for property taxes at 12 percent of net rental value or its equivalent in terms of capital value (say 1.5 percent), if the tax base is changed to capital value. Each LGU should be left free to set its own level of property tax rates. A simple rate of 6 percent to 8 percent of net rental value appears desirable for KCC or a rate of 0.7 percent to 1 percent of capital value.

Mahler (2005), pp. 39-40.

Rural land tax Tax large holdings of rural land or all rural land at a low rate. For example, rural holdings of 5 or 10 acres or more, irrespective of the quality of the land or what it is used for. Exempt small land holdings on equity or cost of assessment grounds.

Annual land tax in the order of UShs 5,000 or UShs 10,000 per acre.

Mahler (2005), p. 39, 45.

Rural property tax Permit rural districts to levy a property tax on high value industrial or residential buildings (say those with a capital value of UShs 50 million or more or a gross annual rental value of UShs 5 million or more) as well as on commercial buildings.

Mahler (2005), p. 40.


Surcharge on VAT Payable by individuals and firms on value added. Individuals and firms whose business sales turnover is below UShs 50 million are exempt from VAT.

Increase VAT rate by 1 or 2 percent. VAT is currently 18 percent of value added.

Mahler (2005), p. xvii.

Business licenses Broaden coverage of business activities to include services, professions and manufacturing (use model of KCC).

Rationalize licence fee structure to better approximate relative sales volume. Introduce three or four fee brackets for each major category taking account of the size of premises, the location of premises and the number of employees.

Mahler (2005), p. 27.

Instrument Proposed Tax Base and Exemptions

Proposed Rate Source

Replace market fees with user fees earmarked for the maintenance and improvement of market infrastructure.

Daily fees in rural markets. Entrance fees for municipal markets.

Bahiigwa et al (2004), p. 24.

Market fees

Use lower rates for: (1) items consumed mainly by the poor; and (2) high value items (e.g. cattle) to discourage the movement of sales outside the market.

Mahler (2005), p. 19.

Agricultural Cess More extensive use of cess on rural products. Levied as an output tax on agricultural production or livestock, collected at the time of sale or time of transport from the district.

Mahler (2005), p. ix.

Local government hotel tax

Levied on all room occupants residing in hotels, chargeable per room per night.

Average of UShs 2,000 per night. World Bank Mission

Automotive Taxes

Surcharge on vehicles licences and fees

Local fee on motor vehicles to be paid by vehicle owners. Motor vehicles could include trucks, pick-up vans and 4-wheel drives, buses, mini buses, cars, motor cycles, agricultural tractors etc.

Average of UShs 15,000 per annum per vehicle.

World Bank Mission

Excise on petroleum products

Increase specific excise on petroleum products or introduce new LGU tax on petroleum.

UShs 50 per litre Mahler (2005), p. 81

Other

Sumptuary taxes Taxes on beer, soft drinks, cigarettes, hard liquor. Collected from manufacturer, but impact passed through to consumer.

Flat rates per litre of liquor, per stick of cigarette etc.

Cattle or livestock tax

Levied on all farmers who own livestock. Exemptions to apply.

Average of UShs 2,000 per cow per year. Bands to apply.

World Bank Mission

8 HOW WE DEVELOPED THE MODEL: DATA AND TAX INCIDENCE METHODOLOGY

This section describes the approach used to build the local tax incidence model. It is worth emphasising that the primary purpose of this work was to develop a methodology and modelling tool that could be adapted and refined over time as systems for collecting, collating and analysing data improve. There were significant challenges in collecting data for the purposes of the study, and so many of the assumptions and parameters in the model have been estimated based on the limited data that were available. The assumptions and model can be updated and adapted as new and better data become available. However, the model is useful for policy purposes and can spur robust dialogue even with the limited data now available. Much of the impact of the model comes from the way it illustrates the potential of different taxes to be regressive, progressive, or neutral. Data collection for the study was carried out by DAI Europe on behalf of the World Bank. The data collection exercise included: (1) describing the various local tax instruments in use in Uganda and Tanzania; (2) developing a household database including descriptions of representative households (by deciles, differentiating between urban and rural regions); (3) developing an enterprise database including descriptions of representative firms of various sizes; and (4) collecting available data on tax bases including income, asset ownership and expenditure on specific taxed commodities for representative households and firms.

8.1 Collection of Data on the Utilisation of Local Tax Instruments

Several LGAs in both rural and urban areas were visited to collect information on the utilisation of local revenue instruments and to sample the various rates and fees charged. While the framework for local taxation is established by national laws, local authorities have the power to pass by-laws that define the specific rates and fees within their jurisdiction (often within a fixed range defined in the national legislation). Consequently, there is significant variation in the fee structures for various local taxes across individual districts. The fee structures can also be quite complicated, with up to 100 different rates specified for in a single by-law for a particular tax. The research team reported several difficulties that hindered the collection of information on the actual rates and fees charged by local authorities. In many cases, local authorities were unable to provide copies of relevant by-laws since they do not usually maintain central registers of relevant by-laws and government notices. Local officials also indicated that not all by-laws are enforced, and that actual rates are often different from those published in the by-laws. The research team also reported that in many instances, local officials were unable to provide definitive lists of rates for those taxes currently administered or answer simple questions about rates and tax bases. This experience points to serious tax administration issues, which though beyond the scope of this exercise, deserve serious attention. Despite these problems, assumptions were crafted for the purposes of the modelling exercise, which can be updated when better data becomes available. These assumptions are based on: (1) the minimum and maximum rates described in the national legislation; (2) the actual rates and fees specified in the by-laws that the research teams managed to collect; (3) rates and fees documented in secondary literature; and (4) average rates calculated on the basis of revenue collection data. The assumptions and model can be easily updated and adapted as new and more accurate data become available.

8.2 Household Data

Consumption expenditure data, extracted from the Household Surveys for Tanzania (2000/01) and Uganda (2002/2003), are used as a proxy for household income. Tax incidence is estimated by calculating the tax burden and expressing it as a percentage of household income. Consumption expenditure is used as a proxy for household income in this calculation for two reasons. Firstly, households tend to report expenditure more accurately (there is less incentive to hide expenditure from the enumerator and/or family members). And secondly, households typically smooth expenditure over time, and so expenditure data provides a better indication of long-term welfare. 45 Consumption expenditure typically excludes: (1) consumption on large durable items, which is not typical of the household’s usual consumption level; and (2) rent and imputed rent, since imputed rent is typically poorly reported.46 Consumption expenditure data were adjusted for regional and intertemporal price variations and for the number of adult equivalents in the household. 47 An adjustment was made for regional and intertemporal price variations, since household welfare depends on the prices the household pays.48 Consumption expenditure is also adjusted for the number of individuals in the household, since larger households require a higher expenditure to meet their needs than smaller households. 49 In both Tanzania and Uganda, the number of Adult Equivalents in each household is determined according to the following formula:

Adult Equivalent = 1 + 0.7(No. of adults – 1) + 0.5(No. of children) Additional tax base information for households was extracted from the Household Budget Survey. Table 1 in Annex F summarises the data that was extracted from the Tanzania Household Budget Survey 2000/2001 (including the additional data fields computed by ERB and the World Bank) and indicates (in the final column) the extent to which data fields are populated across household entries. In Uganda, data was extracted from the Socio-Economic module of the UBOS National Household Survey, 2002/2003. Some additional data was added from the Labour Force module (also part of the UBOS National Household Survey, 2002/2003). Table 2 in Annex F summarises the data fields that were extracted from the Uganda Household Survey (including the additional data fields computed by EPRC and the World Bank). Household deciles and quintiles were calculated separately for rural and urban districts. Data were sorted: (1) by urban and rural; and (2) into ascending order by Total Household Expenditure per Adult Equivalent. The data were divided into deciles/quintiles so that income categories have equal numbers of adult equivalents scaled up by appropriate household weights.50 Averages were calculated across all data fields for each decile/quintile. For age relate data fields, averages were calculated only for those entries populated with data. For all other data fields, averages were calculated across all entries, counting blank entries as zero.

45 World Bank (1999), p. 307. 46 National Bureau of Statistics Tanzania (2002). Consumption expenditure also excludes expenditure on medical care, education, water and postage, due to the large differences in the frequency and value of payments between the 2000/01 and 1991/92 surveys. 47 In Tanzania, these calculations were performed by the Economic Research Bureau (ERB) at the University of Dar es Salaam on behalf of the National Bureau of Statistics (NBS). In Uganda, these calculations were performed by the EPRC (Economic Policy Research Centre) at Makerere University on behalf of the Uganda Bureau of Statistics (UBOS). Average regional prices were used to determine the value of expenditure on various goods and services. 48 National Bureau of Statistics Tanzania (2002). The expenditure required to meet a given minimum consumption level therefore varies depending on where the household lives, e.g. the price of most foodstuffs is higher in Dar es Salaam than in rural areas. 49 National Bureau of Statistics Tanzania (2002). The adjustment uses an adult equivalence scale, which allows for the fact that children have lower consumption needs than adults. Children count as a fraction of an adult on this scale, the fraction depending on their age. In this way, household size is represented by the number of ‘adult equivalents’ rather than simply the number of individuals. The basic measure of household welfare used in this analysis is then each household’s consumption expenditure per adult equivalent over 28 days. 50 The Multiplier (sampling multiplier) is used to compensate for under- or over-representing certain households in a sample and to allow for extrapolation of sample results to the whole population. Therefore multiplier Mi for the ith Enumeration area (Village/Cell/Ward/LC1 zone) means that the ith Enumeration area (Village/Cell/Ward/LC1 zone) represents Mi people in the population. Scaling up using the multiplier means we are extrapolating the results to the whole population.

8.3 Enterprise Data

The collection of robust enterprise data was constrained. The collection of enterprise data was constrained by several factors including: (1) the limited scope and frequency of enterprise surveys in Uganda and Tanzania; (2) the extent to which access to data sets for existing surveys could be secured; (3) the availability of data on the informal sector; and (4) the reliability of available data, since enterprises are often reluctant to disclose data on turnover and assets. Annex G describes the data sources that were identified in Uganda and Tanzania. The model uses data from the Annual Survey of Industrial Production in Tanzania and the Business Inquiry in Uganda.

8.4 Description of the Model

The model calculates the first incidence of the tax only, and does take into account the secondary impacts of local taxes. The model estimates the statutory incidence of local taxes only, i.e. the distribution of the tax burden based on the legal obligation to pay taxes to the local authority. However, the model does not take into account the second order impact of local taxes. For example, the impacts of levying a tax on a firm is felt either by the households that own shares of the firm, or by their customers and suppliers (through increased product prices or lower factor prices).51 The scope of the modelling exercise does not therefore include an analysis of the ultimate economic incidence of local taxes.52 Table 8.1 provides an outline of the structure of the model (household module) for each family of taxes, including a summary of the data and assumptions that feed into the model’s calculations.

Table 8.1: Local Tax Incidence Model: Data and Assumptions

Family of Taxes Data Assumptions

Personal Taxes • Head Tax • Household Head Tax • Graduated Household Head Tax • Surcharge on National Income

Tax

• Number of adults • Number of adult equivalents • Monthly household expenditure • Expenditure per AE

• Head tax (flat amount per adult) • Household head tax (flat amount

per household head) • Graduated Tax table • Surcharge on national income tax

(percentage of national income tax base)

• National income tax table

Land and Property Taxes • Annual Rental Value • Ad Valorem / Capital

Improvements • Ad Valorem / Capital

Improvements / Low Value Properties Exempt

• Ad Valorem / Capital Improvements / First X Shillings of Value Exempt

• Flat Property Tax • Land Tax

• Fraction of households that are owner occupiers

• Normal market rent per month • Fraction of houses that are

permanent structures (derived from the data)

• Value of fields/land • Value of houses • Number of adult equivalents • Expenditure per AE

• Annual rental value: assessment factor; tax free threshold; rates (rural vs. urban, rental vs. owner occupied)

• Land tax: rates (rural vs. urban) • Capital value: percentage of

properties captured on valuation roll; threshold for exemption for low value properties; first x shillings of value tax exempt; rates (rural vs. urban); minimum tax payable (urban vs. rural).

• Flat rate: fees (urban vs. rural; permanent vs. semi-permanent).

51 World Bank (1999), p. 307. A tax on a firm’s product will be passed onto consumers through a price increase equal to the tax rate. In contrast, a tax on a firm’s profits typically falls on the firm’s owners. 52 For example, if taxes are passed forward to consumers through increases in prices, this affects the relative prices of goods and services, which in turn affects consumption patterns. Taxes can also be passed backwards to suppliers via changes to factor prices. This can affect the relative prices of capital and labour, which in turn can affect the usage of labour and capital.

Family of Taxes Data Assumptions

Automotive Taxes • Annual vehicle fees • Urban parking fees • Local fuel tax surcharge

• Number of motor vehicles • Number of motor cycles • Value of Petrol or diesel

consumed by the household

• Annual vehicle fees: flat amount per motor vehicles and per motorcycle.

• Urban parking fees: Fraction of vehicles using street parking; Average number of days per year that street parking is used; Average number of hours per day; Average rate per hour.

• Local fuel tax surcharge: Percentage surcharge.

Sumptuary Taxes • Beer • Soda • Cigarettes

• Household expenditure on beer • Household expenditure on soda • Households expenditure on

cigarettes and other tobacco • Number of adult equivalents • Expenditure income per AE

• Percentage levy on the price of beer, soda and cigarettes and tobacco.

9 USING THE MODEL: ILLUSTRATIONS

This section illustrates how the model can be used to make decisions between different types of local taxes, or to design the details of a particular tax. Initial results from the model are presented, which show the incidence of various local taxes using households (and enterprise) survey data from Uganda and Tanzania. The results are organized according to the type of local tax.

9.1 Local Income Taxes

The model can analyse three different types of local income taxes. Firstly, the model analyses flat, head or poll taxes, where a uniform or fixed amount is charged per individual. The old Development Levy in Tanzania was essentially a head or poll tax, where flat amounts were charged per adult (often with exemptions for women and the elderly), with higher rates applicable for individuals in formal employment. For example, prior to its abolition, the Development Levy in Dar es Salaam was a flat rate of TShs 4,600 per annum for individuals in formal employment and TShs 300 per annum for those not formally employed. Secondly, the model analyses graduated income taxes, where a fixed amount is charged per individual, perhaps with rates varying across income bands and/or professions. This was the case in Uganda, where prior to its suspension, the Graduated Tax was made up of 17 different rates ranging from UShs 3,000 on incomes up to UShs 288,000 per annum up to UShs 100,000 on incomes over UShs 1,560,000 per annum. The upper limit for the Graduated Tax was the lower threshold for the payment of the central government income tax (or PAYE). In both Uganda and Tanzania, there have been various proposals to introduce some kind of “Community Development Fund” or a formalized “Village Development Contribution” at the village or parish level. These development contributions are envisaged either as simple head taxes or as simplified graduated taxes. Finally, the model looks at the impact of a surcharge on national income tax, which could be applied as a percentage of the national income tax or national income tax base (the model considers the former). Again, there have been various proposals to introduce taxes of this nature in both Uganda and Tanzania. The detailed design of each these local income taxes can vary. The progressivity of a tax can be altered by the specific design features of the tax. For example, the progressivity of a tax can be improved by exempting individuals whose income falls below a certain threshold. Some of these design options are summarized in Table 9.1 below. The bolded items indicate the functionality that has been built into the model. It would not be difficult to modify the model to include any of the design options.

Table 9.1: Local Income Taxes Structures: Design Options

Who is required to pay the tax?

All adults (definition of adults can vary) All heads of households All adult men All adult men and employed women All professions, trades and salaried individuals

Who is exempted from paying the tax?

Individuals whose income falls below a certain threshold Elderly Full time students

What is the structure of the rates and fees charged?

Differential rates applied based on characteristics of the taxpayer, e.g. formal sector versus informal sector workers. Maximum amounts applied per household.

How can the model assist local policymakers to choose between different types of local income taxes, and to improve the equity of local income tax instruments? 1. Consider a formalized “Village Development Contribution” in Tanzania: Diagram 9.2 compares the impact of these contributions across household deciles, assuming three different options: (1) a flat contribution of TShs 500 per adult; (2) a flat contribution of TShs 1,500 per household head; and (3) a simple graduated structure, where the amount of the contribution (per household head) varies across five tiers (the lowest tier being zero rated). The vertical axis measures the impact as a percentage of household income. • The illustration shows that the head tax and household head tax analysed are both regressive for rural

and urban households. The household head tax is slightly less regressive since lower income households in Tanzania typically have larger numbers of adult members than richer households.

• A simple graduated structure ensures a more progressive incidence across household deciles. The larger the number of income bands, the more control policymakers can have over the progressivity or the incidence of the tax. This, of course, needs to be balanced against the ease of understanding and administering the tax instrument.

Diagram 9.2: Scenarios of a Formalized Village Development Contribution in Tanzania

Rural Households

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Head Tax Household Head Tax

Urban Households

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Graduated Household Head Tax

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Graduated Household Head Tax

2. Now consider a Graduated Tax versus a surcharge on national income tax: A surcharge on PAYE has been proposed as an alternative to the Graduated Tax in Uganda. Diagram 9.3 compares the incidence of: (1) a Graduated Tax, using the rate structure that applied prior to the suspension of the Graduated Tax in Uganda (the model attributes household income to the household head); (2) the same tax assuming everyone pays the minimum amount of tax (modelled as both a flat head tax per adult and a household head tax); and (3) a surcharge on the national income tax (applying some rough definitions of assessable income). • The first two graphs illustrate the impact of a flat tax of UShs 3,000 per adult and per household head,

and show that these are regressive for both urban and rural households. • The second set of graphs show the impact of the graduated head tax and the surcharge on PAYE.

While the graduated head tax is less regressive than the flat head taxes, it can also create some odd discontinuities and is actually steeply regressive across some segments. This arises because of the specific graduations that are chosen. More graduations in the rate would produce a smoother curve.

• A surcharge on PAYE produces a smooth incidence curve for urban households (most rural households fall below the PAYE threshold, and so the effective rate of PAYE is very low).

Diagram 9.3: Graduated Tax versus a Surcharge on National Income Tax (PAYE) in Uganda

Rural Households

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Graduated Household Head Tax Surcharge on National Income Tax

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Graduated Household Head Tax Surcharge on National Income Tax

Two points are worth emphasizing here: • Firstly, that it is possible to modify or smooth the incidence of a Graduated Tax by changing the income

bands and the rates that apply. • And secondly, the impact of a local income tax needs to be considered in the context of central

government taxes—since the Graduated Tax in Uganda only applied up to the PAYE threshold.

9.2 Land and Property Taxes

The model can analyse several different types of land and property taxes. These include the following forms of taxes: • Property tax levied on the annual rental value of the property. In Uganda, the property tax is defined in

this way, with rates applied to the gross rental value of the property less an allowance for maintenance costs. There are technical problems modelling an annual rental property tax, since the Uganda household survey only captures imputed rental value for owner occupied housing, but these could be solved with improved data, e.g. from a future household survey.

• Flat rate property tax. Typically a flat amount is charged per building with adjustments for size, location and use of plot. This is the system that currently applies to unvalued urban properties in Tanzania.

• Property tax levied on the capital value of improvements. The property tax is applied to the value of buildings only. This is the system that currently applies to urban properties in Tanzania that are on the valuation roll.

• Tax on land or site value. This is a tax applied to value of unimproved land only. In Tanzania, land rents are collected by LGAs on behalf of the central government, with LGAs entitled to 20 percent of the revenue collected.

• Capital improved value. Here the tax is applied to value of both land and buildings. As with local income taxes, the detailed design of each these property tax instruments can vary. Some of these design options are summarized in the table below. The bolded items indicate the functionality that has been built into the model.

Table 9.4: Land and Property Tax Structures: Design Options

What is the structure of the rates and fees charged?

The rate can be applied either as: (1) a flat amount per property; (2) a uniform percentage (ad valorem) charge; or (3) progressive rates (i.e. increasing with property value). Rates may be differentiated based on one or more of the following parameters: (1) whether the property is in a rural versus urban jurisdiction; (2) owner-occupied versus rental property; (3) the type of structure, e.g. permanent versus impermanent structures; and (4) land versus improvements. Minimum tax rates may be applied. The first X amount of value may be tax exempt.

Possible Exemptions Low value properties or low-income families Vacant property

How can the model assist local policymakers to choose between different types of land and property taxes, and to improve the equity of tax instruments? 1. Consider land and property taxes in Tanzania: Diagram 9.5 illustrates the incidence of a flat urban property tax in Tanzania across household quintiles. As expected, the flat tax is highly regressive.

Diagram 9.5: Flat Rate Urban Property Tax in Tanzania

Urban Households

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Flat Property Tax

Diagrams 9.6a – 9.6d examine the incidence of an ad valorem tax on capital improvements in urban areas, and analyse the impact of an exemption for low value properties, compared with an exemption for the first TShs X of value. • Diagram 9.6a shows the impact of a basic ad valorem tax of one percent on capital improvements,

which is slightly regressive across urban household quintiles. This suggests that poorer households are relatively asset rich and income poor, and that wealthier households are relatively income rich and asset poor.

• Diagram 9.6b illustrates the impact of an exemption applied to low value properties, which may be implemented to reduce administrative costs (without significantly reducing revenue) and/or to introduce a more progressive element into the tax structure.53 The graph shows that the exemption results in a discontinuity in the incidence curve.

• Diagram 9.6c shows the impact of an exemption applied to the first TShs X of property value (keeping the rate unchanged), which results in a smoother incidence curve.

• Since the rate is applied to a narrower tax base, it may be desirable to increase the rate to generate additional revenues. This is illustrated in Diagram 9.6d, which shows how the increased rate further increases the progressivity of the tax.

It is important to note that landlords are likely to shift the tax burden onto tenants in the form of higher rental prices. The analysis of the second order impacts of property taxation is beyond the scope of this study.

53 Bahl et al (1992), p. 100.

Diagram 9.6: Scenarios of an Ad Valorem Property Tax in Tanzania

9.6a: Ad Valorem Tax

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9.6b: Exemption for Low Value Properties

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9.6c: Exemption for first TShs X of Value Urban Households

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9.6d: Exemption for first TShs X of Value

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Ad Valorem / Capital Improvements First TSh X Exempt / Rate x 3

9.3 Automotive Taxes

The model analyses three different types of automotive taxes. These include: • Annual motor vehicle fees. Motor vehicle ownership can be an effective tax base for urban local

authorities. Vehicle ownership often increases at a faster rate than population increases, vehicle ownership is easily taxable, and the relative burden of automotive taxes is likely to fall on wealthier households.54 In Tanzania, vehicle fees are a source of revenue for the central government. Fees are levied at TShs 95,000 per registration for motor vehicles, TShs 32,000 for motor cycles, after which there is an annual fee of TShs 10,000. Proposals have been made to assign annual permit fees, currently collected by the Tanzania Revenue Authority (TRA) district offices, to LGAs. In Uganda, proposals have been made for a local fee on vehicle ownership of around UShs 15,000 per annum per vehicle. These are modelled as a flat amount per motor vehicle and motor cycle, based on data from the household surveys.

• Parking fees. Parking fees are a source of revenue for urban local authorities in both Uganda and Tanzania. These are modelled as a flat amount per hour (TShs 300 per hour in Tanzania, and UShs 200 per hour in Uganda), with simple assumptions for the fraction of vehicles using public parking facilities and the frequency and duration of use.

• Fuel levy. In both Uganda and Tanzania, proposals have been made to increase the specific excise on petroleum products or to introduce new local tax on petroleum. A fuel levy is modelled as a percentage of the value of petrol/diesel consumed by the household, using consumption data extracted from the Uganda Household Survey. 55 Data was not available to model the impact of a fuel levy in Tanzania.

54 Bahl et al (1992), p. 190. 55 This could be modelled as a flat amount per litre if quantities are extracted from the Household Survey.

Diagram 9.7 illustrates the impact of automotive taxes in Tanzania and Uganda. • Automotive taxes are typically progressive across household quintiles. A fuel levy in Uganda would be

highly progressive, with the burden of the levy falling on the wealthiest two quintiles

Diagram 9.7: Automotive Taxes in Uganda and Tanzania

9.7a: Rural, Tanzania

Rural Households

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Annual Vehicle Fees

9.7b: Urban, Tanzania

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Hou

seho

ld In

com

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Annual Vehicle Fees Parking Fees

9.7c: Rural, Uganda Rural Households

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Annual Vehicle Fees Fuel Surcharge

9.7d: Urban, Uganda

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Annual Vehicle Fees Parking Fees Fuel Surcharge

According to the Tanzania Household Survey, only 8 percent of households own either a motorcycle or motor vehicle, and so the analysis is based on relatively few observations in each decile. In Uganda, the household survey only asks if the household owns one or more motor vehicle or motorcycle, and so the analysis does not capture whether or not a households owns more than one vehicle or motorcycle. The results therefore understate the progressivity of these tax instruments, because it doesn’t capture the fact that high income households could own more than one vehicle.

9.4 Local Sumptuary Taxes

The model estimates the impact of local sumptuary taxes on beer, liquor and tobacco. For Tanzania, data is only available on the value of consumption of cigarettes and tobacco. For Uganda, data is available on the value of consumption of soda, beer, cigarettes and tobacco. Diagram 9.8 summarizes the results from this module of the local tax incidence model. • The results show that a tax on cigarettes can be either regressive or progressive depending on

consumption patterns across households. • The results for Uganda suggest that a tax on soda or beer is likely to be progressive for both urban and

rural households. • The progressivity of a local tax on beer could be increased by taxing locally produced liquor at lower

rates than imported brands.

Diagram 9.8: Sumptuary Taxes in Uganda and Tanzania

9.8a: Rural, Tanzania

Rural Households

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9.8b: Urban, Tanzania

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9.8c: Rural, Uganda

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Cigarettes Beer Soda

9.8d: Urban, Uganda

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Cigarettes Beer Soda

9.5 Impact of Local Taxes on Enterprises

The enterprise module of the local tax incidence model is structured around data extracted from the 2003 Tanzania Survey of Industrial Production and a subset of data from the Uganda Business Inquiry. These surveys are of limited scope, both in terms of the number of enterprises surveyed and the information collected. Consequently, the data and assumptions underpinning the enterprise module are far less robust than those used for the household module, which builds on detailed data drawn from national household surveys. The functionality of the enterprise module is limited to those taxes where relevant tax base information is available. Even where tax base information is available, the quality and representativeness of the data is questionable. For example, enterprises are often reluctant to disclose accurate turnover data. Changes in the assumptions relating to tax bases for enterprises can have a significant impact on the model’s results. The initial results from the enterprise module are therefore not robust enough for the purposes of decision making. They are presented and discussed in Appendix H. The functionality of the enterprise module can easily be improved and the results updated as better data become available over time. The Appendix also includes some suggestions for improving the data and assumptions for the model.

10 SUMMARY OF INITIAL FINDINGS AND KEY MESSAGES

The previous section demonstrates how the model can be used to make decisions between different types of local taxes, or to design the details of a particular tax. Initial results from the model illustrate the incidence of various local taxes including: (1) personal income taxes; (2) land and property taxes; (3) automotive taxes; and (4) sumptuary taxes. The key findings from the modelling exercise are summarised in the table below.

Table 10.1: Local Tax Incidence Model—Initial Findings Tax Instrument Initial Findings

Personal Income Taxes

• The illustrations show that a flat head tax and a flat household head tax are often regressive for rural and urban households. In Tanzania, the household head tax is slightly less regressive since lower income households typically have larger numbers of adult members than richer households.

• A simple graduated structure can ensure a more progressive incidence across households. However, it can also create some odd discontinuities and can be steeply regressive across some income classes. This arises because of the specific graduations that are chosen.

• It is possible to modify or smooth the incidence of a graduated income tax by changing the income bands and the rates that apply. The larger the number of income bands, the more control policymakers can have over the progressivity or the incidence of the tax. This, of course, needs to be balanced against the ease of understanding and administering the tax instrument.

• A local surcharge on PAYE (the Ugandan national income tax) produces a smooth incidence curve for urban households (most rural households fall below the PAYE threshold, and so the effective rate of PAYE is very low).

• The impact of a local income tax needs to be considered in the context of central government taxes (e.g. the Graduated Tax in Uganda only applied up to the PAYE threshold).

Land and Property Taxes

• A flat urban property tax (modeled for Tanzania) is highly regressive across household quintiles.

• A basic ad valorem tax (modeled for Tanzania as a percentage of capital improvements) is slightly regressive across urban household quintiles. This suggests that poorer households are relatively asset rich and income poor, and that wealthier households are relatively income rich and asset poor.

• An exemption may be applied to low value properties to reduce administrative costs (without significantly reducing revenue) and/or to introduce a more progressive element into the tax structure. An exemption applied to low value properties results in a discontinuity in the incidence curve.

• An exemption applied to the first TShs X of property value (keeping the tax rate unchanged) results in a smoother incidence curve. Since the rate is applied to a narrower tax base, it may be desirable to increase the rate to generate additional revenues. Increasing the tax rate further increases the progressivity of the tax.

Automotive Taxes • Automotive taxes are typically progressive across household quintiles. • A fuel levy (modeled for Uganda) would be highly progressive, with the burden of

the levy falling on the wealthiest two quintiles

Sumptuary Taxes • The results show that a tax on cigarettes can be either regressive or progressive

depending on consumption patterns across households. • The results for Uganda suggest that a tax on soda or beer is likely to be

progressive for both urban and rural households. The progressivity of a local tax on beer could be increased by taxing locally produced liquor at lower rates than imported brands.

10.1 Key Messages and Initial Recommendations

Before abolishing or suspending local taxes because they are perceived to be regressive or difficult for small businesses, options should be explored to improve the equity of the tax instrument. The analysis illustrates the steep regressivity of some local taxes, particularly those that are applied as a flat amount irrespective of ability to pay (e.g. flat tax per adult, flat household head tax, and flat property tax). It is important to recognise that these sorts of taxes can be restructured to increase their progressivity, for example by applying exemptions for poorer households, or by implementing a simple system of graduated tax rates. Increasing the equity of a local tax can encourage greater tax compliance, enabling lower tax rates to be charged. It is important to recognize that the specific design features of a local tax can alter its incidence. The analysis shows that within a family of taxes, individual tax instruments can be regressive or progressive depending on their detailed design. The details are what count. It is therefore important to understand the implications of various design options including the definition of the tax base, the rate structure that the exemptions that apply. These can significantly alter the incidence of the tax. Beyond equity considerations, there are several factors that policymakers need to take into account when setting local revenue policy including revenue yield, economic efficiency and administrative efficacy of various local tax options. The health of the local tax system and the consequent quality of local service delivery is constrained by a number of factors including: (1) the high costs of collection relative to yield for some taxes; (2) low compliance rates for some taxes; (3) the lack of voice felt by taxpayers and negative perceptions of service quality, which affect willingness to pay taxes; (4) the propensity for some local authorities to ignore central government legislation in their search for new revenue sources (a dynamic that was documented following recent tax reforms in Tanzania); and (5) leakage of revenues from privatized tax collection arrangements, which can introduce wide margins between payment by taxpayers and yield to authorities.

11 CONCLUSIONS AND NEXT STEPS

The design of the local tax incidence model reflects a trade-off between complexity and ease of use. The model is intended to be a practical, living tool that can be used by policymakers to assess the implications of a range of local tax options and to facilitate the design of healthy, progressive local taxes. The model was therefore conceived as a simple spreadsheet-based modelling tool that can be easily used, adapted and maintained by any proficient spreadsheet user. The expansiveness and complexity of the model also reflects the availability and reliability of data on households and enterprises, which support the distributional analysis. Some of the key strengths and weaknesses of this approach are outlined below. Key strengths of the model include its ease of use and the scope of the household module. Key benefits of the model include: • Readily interpretable results. The model provides readily interpretable results in graphic format. The

illustrations allow alternative tax instruments or features to be compared and contrasted. The model enables a “what-if” analysis—the user can modify assumptions, and the results are automatically updated.

• Easy to use, maintain and adapt. The simple spreadsheet based modelling tool is easy to understand and use. The model can easily be modified to reflect policy changes and can be adapted as new sources of data become available.

• Representativeness of household data. The model leverages household data that is captured as part of the regular household surveys in Uganda and Tanzania. The detail of the household data has enabled the construction of household income deciles and quintiles that are broadly representative of households in Uganda and Tanzania. The surveys also provide detailed tax base data, which feed into the tax calculations in the household module.

• Scope of the household module. The expansiveness of the household tax base data has enabled a range of local tax instruments to be modelled in the household module of the local tax incidence model. The scope of the household module includes personal taxes, land and property taxes, automotive taxes and some specific excise and sumptuary taxes.

The simple design of the model also results in several drawbacks. These include: • Depth and scope of enterprise module. While the household module uses data from representative

household surveys, the enterprise module uses data from surveys of limited scope, which are not designed to be representative. This data cannot be generalized to the entire universe of enterprises, and so the model can only provide an illustration of how tax liabilities are distributed across firms of different sizes. Changes in the assumptions relating to tax bases can have a significant impact on the model’s results.

• The model does not consider the final or economic incidence of local taxes. The model therefore gives a less complete picture of the distribution and ultimate burden of local tax liabilities. Households rather than firms ultimately bear the burden of all taxes. For example, the impact of local business taxes can be shifted to households either in the form of higher prices, lower wages or lower returns to capital (in the households’ capacities as consumers, workers and owners of firms). In addition, the household that has the legal obligation to pay the tax is not necessarily the household that actually bears the burden of the tax. For example, taxes levied on the owners of property can be shifted to other households in the form of higher rent. The advantage of the model in its current form is that it avoids many controversial economic assumptions about how the tax burden is shifted from firms to households.56

• The model considers one dimension of equity only. The model considers the distribution of tax liabilities across income classes, i.e. the model assesses income incidence or the burden of the tax relative to a

56 Mazerov, p. 5.

household’s ability to pay. There are other dimensions of incidence and equity that are also relevant but currently outside the scope of the model. These include the incidence of local taxes across: (1) regions or districts; (2) age groups; and (3) sources of income.

There are several directions in which the local tax incidence model might be improved of expanded over time. These include: • Improving the quality of data and refining assumptions. The quality of results from the model is

dependant on the quality of the data and assumptions that feed into the model. As described in the section on data and methodology, there are several issues with the data, particular enterprise data. Many of the assumptions in the model can be refined over time as survey tools are improved, and additional data becomes available.

• Include more taxes in the model. For example, the impact of market fees and agricultural cess, billboard and advertising fees, surcharge on VAT, and additional sumptuary taxes could be explored in future iterations of the model, as additional data becomes available.

• Incorporating the impact of national level taxes. A robust analysis of equity should include the combined impact of central government and local government taxes. For example, local income taxes are often designed to capture revenues below the starting threshold for national income tax.

• Looking at the second order impacts of local taxes. The model could be further developed to incorporate the impact of business taxes that are passed through to households in the form of increased prices, lower returns to capital and lower wages, as well as the second order impact of property taxes. This would require the collection of further data, and would also require the construction of additional assumptions that would determine how tax liabilities are shifted to consumers, workers and owners of capital, and how these resulting tax liabilities are allocated across income classes.

• Estimating revenue yield. The model could be further developed to incorporate a calculation of revenue yield for various tax proposals. This calculation could be done with the available household data, but would require additional enterprise data to be collected.

• Incorporate collection ratios into the assumption set. This would require data to be collected on the efficiency of collections (across income classes) including: (1) coverage ratios (fraction of the potential tax base captured in registers, rolls etc); (2) valuation ratio (extent to which the tax base is undervalued in registers, rolls, application of rates, i.e. the accuracy of the valuations); and (3) collection/compliance ratio (given the tax base covered in registers and rolls, what fraction is actually collected?).57

• Projecting tax liabilities into the future. The impact analysis could be extended by projecting the tax burden, making assumptions about population growth and growth in household incomes. This would allow a more dynamic analysis of the tax burden and its equity implications over time.

What else is needed besides a local tax incidence model? In order for local authorities to perform their decentralised functions effectively, they must: (1) have clarity around their service delivery mandates and sufficient levels of autonomy to decide on expenditure priorities; and (2) they must have adequate levels of financial resources—either transferred from the central government or raised locally. Local taxes are only one element of the intergovernmental fiscal architecture. They therefore need to be understood and considered in relation to other elements including: • Service delivery mandates. The essential starting point for fiscal decentralization is the allocation of

roles and responsibilities across different levels of government. Until there is clarity around the services local authorities are expected to deliver, and the functions they are expected to perform, it is difficult to be intelligent about fiscal issues.

57 The research team attempted to gather data on collection ratios for the purposes of this study but met with several obstacles. In most cases the team gathered data on actual collections relative to budgeted collections. In some cases budgeted collections may reflect revenue potential (e.g. for areas where private collectors are employed, such as market and parking fees) but more often they are extrapolated based on actual collections from the previous year.

• Local taxes. Local authorities should generate a reasonable share of resources locally. Optimizing the equity of local tax instruments can help local authorities to raise more revenue with less pain. A sub-optimal tax incidence (a tax that is less fair) will place undue burden on the poor or smaller enterprises, and will therefore raise less revenue than a tax structure that fits the local income and wealth profile better.

• Intergovernmental transfers. Once local taxes have been optimized, there will still be poor areas with little economic activity and thus little to tax. If, as a matter of national policy, these areas are expected to provide better services or perform more functions than they can afford, then an equalizing transfer system is needed

In this study, we explore issues associated with local taxation only. We do not pretend that an optimised tax structure can solve every problem. For example, the design of a local tax regime cannot always solve the problem of differences in local tax generating capacity across local authorities. Instead, these must be solved either by accepting lower levels of services in poor areas, or by providing equalising transfers, or some combination of the two In addition, there are several other factors that should be considered alongside equity when setting local revenue policy. These include: • Linkage with services and willingness to pay. Local authorities are often perceived to be poor service

providers, which undermines willingness to pay taxes. It is therefore important to sensitise taxpayers on why local taxes are important, show the positive effects of local taxation and demonstrate that revenues are actually used for their intended purpose.

• Capacity of LGAs to administer and collect taxes. There is often a perceived or real concern that local authorities do not have the capacity to manage local revenue sources. Of particular concern is the availability of data for the assessment of tax liabilities, particularly in rural and remote areas.

• Double taxation and the build up of tariffs. Several stakeholders in Tanzania expressed concern over the possibility of double taxation (e.g. the proposal in Tanzania for a national income tax surcharge) and the multiplicity of levies (e.g. the proposal in Tanzania for an excise on utility charges). Others argued that these practices are common in other countries, and that it is a matter of segmenting the taxes and adjusting tax rates accordingly.

• Variation across LGAs. There are significant variations in the ability of LGAs to raise local revenues, due to differences in natural endowments and resource bases. Intergovernmental transfers can address some of these inequalities. Another point is that different local tax instruments may be appropriate in some areas but not others, e.g. a tourism or hotel tax may be useful in some areas of the country but not others.

12 REFERENCES

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Bahl, R. and Linn, J. 1992. “Urban Public Finance in Developing Countries.” Oxford University Press, New York, United States.

Faber, Robbert. 2004. “Draft Final Report on: Data Collection Exercise, Comprehensive Valuation, Revenue Collection and Enforcement Practices.” The United Republic of Tanzania, President’s Office Regional Administration and Local Government, September 2004

FIAS, with DFID. 2006. “Study of the Effective Tax Impact in Five Priority Sectors.” Aide Memoire, Tanzania, January 2006.

Fjeldstad, Odd-Helge. 2001. Taxation, Coercion and Donors: Local Government Tax Enforcement in Tanzania.” The Journal of Modern African Studies 39(2): 289–306.

Fjeldstad, Odd-Helge. 2006. “To Pay or Not to Pay? Citizens’ Views on Taxation in Local Authorities in Tanzania.” REPOA, Special Paper No. 06.18.

Fjeldstad, Odd-Helge., with F. Henjewele, G. Mwambe, E. Ngalewa, and K. Nygaard. 2004. “Local Government Finances and Financial Management in Tanzania: Observations from Six Councils 2002–2003.” REPOA Special Paper No. 16, Dar es Salaam.

Franzsen, R. and J. Semboja. 2004. ‘Analytical Report: The Enhancement of Local Revenues in the City of Dar es Salaam. Sub-component 2(b) of the LGSP’. Washington: World Bank.

Georgia State University. 2005. “Final Report: Development of a Strategic Framework for the Financing of Local Governments in Tanzania.” Andrew Young School of Policy Studies, Atlanta and Dar es Salaam, June 2005.

Government of Uganda/Donor Sub-Group on Decentralisation. 2001. “Fiscal Decentralisation in Uganda – The Way Forward: Final Report,” January 2001.

Heymans, C. and K. Kumar. 2002. “The Scope for Fiscal and Institutional Restructuring in Dar es Salaam as a Component of the Tanzania Local Government Support Project.” World Bank, May 2002.

IMF. 2006. “Uganda: Managing More Effective Decentralization.” IMF Working Paper, Fiscal Affairs Department, December 2006.

Kelly, R. 2000. “Property Tax Reform in East Africa: The Tale of Three Reforms.” Development Discussion Paper No. 753, Harvard Institute for International Development, February.

Kelly, R., and Z. Musunu. 2000. “Implementing Property Tax Reform in Tanzania.” Lincoln Institute of Land Policy Working Paper (WP00RK1).

Local Government Finance Commission. 2004a. “Baseline Survey on Revenue Performance.” April 2004, Kampala.

Local Government Finance Commission. 2004b. “Report of Regional Workshops on Best Practices in Mobilising and Generating Local Revenues.” February 2003, Kampala.

Mahler, Walter. 2005. Options for Financing Local Governments in the Ugandan Context: Final Report.” Duke Center for International Development, Sanford Institute of Public Policy, Duke University, February 4, 2005.

McCluskey, W., R. Franzsen, T. Johnstone, and D. Johnstone. 2003. “Property Tax Reform: The Experience of Tanzania.” RICS Foundation (Royal Institute of Chartered Surveyors, London).

Ministry of Local Government. 2004. “Sustainability of LGs, Coverage of O&M Costs, and Importance Of Local Revenues.” Discussion Paper 5, Joint Annual Review of Decentralisation, November 2004.

Ministry of Local Government. 2006. “Clarification on Payment of Property Taxes”. Letter to District Chairpersons and Mayors, 9 March 2006.

Nalugo, Mercy. 2007. “Poor Funding Slowing Down Decentralisation.” All Africa, 14 March 2007.

National Bureau of Statistics Tanzania. 2002. “Household Budget Survey 2000-01.” Dar es Salaam, July 2002.

Steffensen et al. 2004a. “A Comparative Analysis of Decentralization in Kenya, Uganda and Tanzania: Final Synthesis Report.” Unpublished report.

Steffensen, J., P. Tiderman and E. Mwaimpopo. 2004b. “Country Study Tanzania – A Comparative Analysis of Decentralisation in Kenya, Tanzania and Uganda.” Unpublished report.

Steffensen, J., P. Tiderman and E. Ssewankambo. 2004c., “Country Study Uganda – A Comparative Analysis of Decentralisation in Kenya, Tanzania and Uganda.” Unpublished report.

United Republic of Tanzania. 2004. “Local Government Fiscal Review 2004.” Dar es Salaam, November 2004.

United Republic of Tanzania. 2005. “Local Government Fiscal Review 2005.” Dar es Salaam, December 2005.

United Republic of Tanzania. 2007. “Local Government Fiscal Review 2006.” Unpublished Report.

Wasike, Alfred. 2007. “Local Govt in Revenue Crisis.” New Vision, January 15, 2007.

World Bank. 2006. “Local Government Taxation Reform in Tanzania: A Poverty and Social Impact Analysis (PSIA).” Report on Economic and Sector Work, Report No. 34900-TZ.

ANNEX A: PEOPLE MET

Data Collection Phase—Uganda Name Title Organisation Mr. Yiga Chief Finance Officer, Headquarters Kampala City Council Paul Mungati Registered Surveyor of Uganda Kampala City Council Isaiah Kule Chief Finance Officer Kasese Town Council Mr. Esenku Tax Officer Kumi Town Council Vincent Mpagi Chief Finance Officer Masaka Municipal Council Sauda Namuleme Central Division Accountant Masaka Municipal Council Sandra Nantama Katwe Butego Division Treasurer Masaka Municipal Council Moses Mwesigwa Kakoba Division Treasurer Mbarara Municipal Council Arinaitwe Juliet Kamulinzi Division Treasurer Mbarara Municipal Council Richard Kerere Nyamitanga Division Treasurer Mbarara Municipal Council Steven Kavuma Chief Finance Officer Mukono Town Council Kibirige Dennis Data Manager Multiplex Uganda Limited Chris Musoga Senior Tax Officer Tororo Municipal Council Juliet Okello Western Division Sub-accountant Tororo Municipal Council Seith Mayinza Director of Production UBOS Mr. Waswa Senior Statistician UBOS Emwanu Joseph Senior Statistician UBOS Kasule Ronald Uganda Bus Operators

Association (UTODA) Data Collection Phase—Tanzania Name Title Organisation Mtomaye Regional Local Government

Officer Coast Region

Getrude K. Mpaka Regional Administrative Secretary, Coast Region

Odd-Helge Fjeldstad Chr. Michelsen Institute (CMI) Roy Kelly Duke University John Lubuva Municipal Director Ilala Municipal Council Evans Shemdoe Municipal Treasurer Ilala Municipal Council Urban Mapunda Head of Valuation Section Ilala Municipal Council Eliud Accountant Kibaha District Council Saiwelo J Kumwenda Legal Officer Kibaha District Council Twaib M. Lukwaro Principal Trade Officer Kibaha District Council Simba Property Tax Section Kinondoni MC Simon Lapper Finance Adviser Local Government Reform

Programme Cornel Barnabas Co-ordinator, Revenue

Enhancement Component Local Government Support Project

Mbaruku Acting Director General National Bureau of Statistics Howard Clegg Prime Minister’s Office Regional

Administration and Local Government (PMO-RALG)

Millias Kadebe Principal Accountant PMO-RALG Luanda Deputy Director of Legal Services PMO-RALG Daniel Kobb Public Service Management,

President’s Office

Hussein Ussi Statistician Tanzania Revenue Authority Mr. Nyonyo Systems Administrator Tanzania Revenue Authority Mr. Mbanga Acting Treasurer Temeke Municipal Council Victor Ndonne Property Tax Section Temeke Municipal Council Sifael T. Kulanga Municipal Solicitor Temeke Municipal Council

Consultation Workshop Participants Name Title Organisation Bakari Kingobi City Director Dar es Salaam City Council Ernest Mchanga RE Coordinator Dar es Salaam City Council Magwiza Perride Dar es Salaam City Council Alusaria Swai Revenue Accountant Dar es Salaam City Council Marko Nokkala Embassy of Finland Iina Soiri Counsellor (Governance) Embassy of Finland Max Van Bassdoff Economic Adviser Embassy of Finland Hans Raadschilders First Secretary, Local Governance Embassy of the Kingdom of the

Netherlands Deus Mushema RE Coordinator Ilala Municipal Council Alfred Kabagire LGRP Coordinator Local Government Reform

Programme Mr. J.N. Mallya Outcome Manager, Finance Local Government Reform

Programme George Ntigiti Ministry of Finance James Sauramba PMO-RALG Angelista Kihaga Local Government Finance PMO-RALG E. Mchome Asst. Director, Local Government

Finance PMO-RALG

Mbwana Mkembe Local Government Finance PMO-RALG Wilson Mukama Deputy Permanent Secretary PMO-RALG Richard Musingi Director of Sector Coordination PMO-RALG Michael Mwalukasa PMO-RALG Joye Ndasamburo PMO-RALG Stella Steward Local Government Finance PMO-RALG Cornel Barnabas Revenue Enhancement/O & M

Coordinator, LGSP Component 2 PST, Dar es Salaam City Council

Fred Pondamali CIUP, RE/OM Coordinator PST, Dar es Salaam City Council Cosmas Takule Project Manager, LGSP PST, PMO-RALG Lucas Katera Researcher REPOA Simen Maal Researcher REPOA Salim Kisauji Mayor, Chairman of AMICAALL

Tanzania Tanga City Council

Daniel Machemba Executive Director Tanzania Chamber of Commerce, Industry and Agriculture (TCCIA), Tax Reform Task Force

Tonedeus K. Muganyizi Director Research, Policy and Planning

Tanzania Revenue Authority

Ephrem Asebe Consultant, AFTU1 World Bank Parminder Brar Lead Financial Management

Specialist World Bank

Denyse Morin Senior Public Sector Specialist World Bank Catherine Murphy Consultant, AFTS2 World Bank David Mulongo Urban Specialist World Bank Matthew Glasser Lead Urban Specialist World Bank

Consultation Meetings in Tanzania Name Title Organisation Esteriano Mahingila Chief Executive Officer Business Registrations and

Licensing Agency (BRELA) Geoffrey Mackanja Confederation of Tanzanian

Industries (Member of the Tax Reform Task Force)

Bakari Kingobi City Director Dar es Salaam City Council Alusaria Swai Revenue Accountant Dar es Salaam City Council Iina Soiri Counsellor (Governance) Embassy of Finland Max Van Bassdoff Economic Adviser Embassy of Finland Hans Raadschilders First Secretary, Local Governance Embassy of the Kingdom of the

Netherlands John Lubuva Municipal Director Ilala Municipal Council Deus Mushema RE Coordinator Ilala Municipal Council Mr. J.N. Mallya Outcome Manager, Finance Local Government Reform

Programme Eliakim Maswi Assistant Commissioner for

Budget Ministry of Finance

Shogholo Msangi Section Head for Fiscal Policy Ministry of Finance George Ntigiti Ministry of Finance Amantius C. Msole Principal Economist - Fiscal Policy Ministry of Finance Ms. Maro Executive Director National Bureau of Statistics Sange Mbaruku Director of Operations and

Statistics National Bureau of Statistics

Fadhili Khalfani National Bureau of Statistics Ms. E. Mchome Asst. Director, Local Government

Finance PMO-RALG

Wilson Mukama Deputy Permanent Secretary PMO-RALG Cornel Barnabas Revenue Enhancement/O & M

Coordinator, LGSP Component 2 PST, Dar es Salaam City Council

Cosmas Takule Project Manager, LGSP PST, PMO-RALG Lucas Katera Researcher REPOA Simen Maal Researcher REPOA Erasto Ngalewa Programmes and Operations

Coordinator REPOA

Israel Z. Sekilasa Director General SUMATRA (NOT a member of Tax Reform Task Force!)

Salim Kisauji Mayor, Chairman of AMICAALL Tanzania

Tanga City Council

M. Kabinda IT Manager Tanzania Chamber of Commerce, Industry and Agriculture (TCCIA),

Linda Lifiga Senior CDO (Training) Tanzania Chamber of Commerce, Industry and Agriculture (TCCIA),

Daniel Machemba Executive Director Tanzania Chamber of Commerce, Industry and Agriculture (TCCIA),

Adolf Ndunguru Principal Research Officer Tanzania Revenue Authority Iddi Nyundo Municipal Director Temeke Municipal Council Ephrem Asebe Consultant, AFTU1 World Bank Judy O'Connor Country Director World Bank Zainab Semgalawe Operations Officer World Bank David Mulongo Urban Specialist World Bank

ANNEX B: CURRENT LOCAL REVENUE INSTRUMENTS IN TANZANIA

Instrument Tax Base Rate Exemptions


Property Rates

Property tax is charged on the owners of property within urban jurisdictions. Applies to buildings only. Does not apply to mud houses. Property must be occupied.

Flat Rate System: Although legally the property tax base should be the market value of the property, the LGFA authorizes LGAs to levy a flat amount per building with possible adjustments for size location and use of plot.58 Flat rates tend to be highly differentiated, with numerous ad hoc property categories and even taxpayer-specific rates for valuable properties.59 Valuation-based / Ad Valorem System: The Urban Authorities (Ratings) Act of 1983 authorises urban LGAs to impose an ad valorem property tax on buildings. According to the Act, property should be valued at open market value, or where the property value cannot be ascertained, the depreciated replacement cost approach may be used. The latter is the most commonly used method of valuation due to the lack of market price information and the separation of taxes on land and buildings.60 See Annex C for sample rates.

Property in the personal occupation of the President. Property used for public utility undertakings. Premises used primarily for public worship but excluding property used for residential or social purposes in connection with places of public worship. Public libraries and public museums. Cemeteries and crematoria. Civil and military aerodromes. Property used for sporting purposes or educational purposes. Railway infrastructure. Property owned and used exclusively as office accommodation, laboratories and godowns by the government and its departments. Government residential property used exclusively by government officers and employees. Property used by or reserved for use by a LGA Other property as may be prescribed by the concerned urban local authority.

58 GSU (2005), p. 4-33. 59 McCluskey et al (2003), p. 41. 60 GSU (2005), p. 4-33 and McCluskey et al (2003), p.12. For the purposes of valuation, buildings are categorised into four groups: residential, commercial, industrial and hotels. Within each category there are three sub-categories with an established range of replacement costs per square metre. There are also four categories for depreciation adjustments based on the physical condition, functional obsolescence and remaining economic life of the property. The law provides for a maximum depreciation adjustment of 25 percent. McCluskey identifies several drawbacks to this valuation methodology: (1) approach doesn’t reflect locational value (i.e. two properties that have different locational value might have the same replacement cost value but not the same market value) and the valuation of specialised properties such as filling stations and hotels does not adequately reflect the income producing potential of these properties; (2) replacement cost schedules do not reflect the fact that construction costs vary across regions; (3) methodology is time consuming; and (4) requires regular assessment of tax base to ensure that all subsequent improvements are reflected in the assessed value.

Land Rent (Shared with the Central Government)

The holder of a right of occupancy shall pay an annual rent. Collected by LGAs on behalf of the central government (MOLHSD). LGAs are entitled to 20 percent of the revenue collected.61

The amount of the rent is determined subject to area, use and value. Adjustments are made in special cases pf poverty, infirmity and natural disaster. In urban areas, the rates applied to industrial plots are typically between TShs 75 – 150 per square meter per year. For other uses charges vary depending on the market value of the land in question.62 Rent on residential premises exceeding TShs 500,000 is taxed at 10 percent of the rental value for residents and 15 percent for non-residents. In rural areas, land rent for farmland outside the township is TShs 200 per acre per year, and TShs 3,000 per acre per year within the township.

Land used exclusively for religious worship and/or for burial. Land used for charitable purposes.

Automotive Taxes

Parking Fees

Fee to park a vehicle in a public parking bay. Rates vary across LGA, but are typically in the order of TShs 300 per vehicle per hour.


City Service Levy (CSL)

Applied to all resident business enterprises on the basis of enterprise turnover. In practice the levy is collected from entities registered for value-added tax (VAT), i.e. with an annual turnover exceeding Tshs 20 million, and from a small number of other entities.63

The CSL is payable by corporate entities at a rate not exceeding 0.3 percent of enterprise turnover (net of VAT and excise duty. A rate of 0.1 percent applies to Banks.64

Agricultural Produce and Livestock Cess

Levied in most rural district LGAs on the value of agricultural produce or livestock.65 Levied at the point of sale.66 In some cases, the crop must be produced or sold in the district to attract the tax. In other cases, cesses are charged on goods as they move across the district, or when they arrive at their destination.

The rates imposed vary from one LGA to another and from one crop (or type of livestock) to another, typically charged as a flat amount per unit. Maximum of 5 percent of the farm gate price.67

Cess on sellers. Producers selling directly in the markets within the LGAs do not pay produce cess. Cess on timber products (furniture). Export crops (also VAT exempt).68 All corporate entities, which pay the service levy, are exempted from paying the produce cess69.

61 Faber (2004), p. i. Many LGAs claim that they do not get the specified 20 percent share of this source of revenue. 62 http://www.tic.co.tz/IPA_Information.asp?hdnGroupID=3&hdnLevelID=6.3 63 Franzsen and Semboja (2004), p. 26. 64 Fjeldstad (2006), p. 10.

Forest Produce Cess

Paid by licensed buyers of forest products, on sales of timber, charcoal, logs, mirunda, firewood, poles and fito (thin poles)

The rates imposed vary from one LGA to another and from kind of forest produce to another, typically charged as a flat amount per unit. Maximum of 5 percent of the farm gate price.70

Timber products (e.g. furniture).

Fish Landing or Auction Levy

Fee for use of landing berths etc and other landing facilities provided by Local Authorities.

Five percent of the selling price.

Hotel/Guest House Levy

This levy is based on the value of the rooms based on actual occupancy rates per month. Hotels and guest houses which are registered for VAT are not required to pay this levy.

Levied at the rate of 20 percent of the value of rooms occupied.

Rooms Rate (TShs) 1-10 15,000 11-20 30,000 21-30 50,000 31-50 75,000 51-100 100,000 101+ 150,000

This does not apply to hotels, tourist hotels or camping tents.

Advertising Fees

Billboard and Advertising Fees

For advertisements on bill boards and sign boards a licence is needed. The application is commonly handled by the municipal engineer’s department. After the licence is granted to the advertising firm, a fee is payable.71

Rates are based on size and illumination. Sample rates:

TShs 8,000 - 10,000 per square feet per annum for illuminated billboards and posters TShs 6,000 - 7,000 per square feet for non illuminated billboards and posters

Advertisements: For advertisements made on radio, TV, newspaper, 2 percent of the fees charged by the media can be levied. In practice this is not done. 72

65 The tax is paid by the agricultural crop and livestock buyers. Most of these buyers are large and medium size enterprises, especially those dealing with cash crops like coffee, cashew nuts, cotton etc. There are also those who act as middlemen buying agricultural produce from farmers and sell them to individuals who have shops or stalls in the markets for selling to consumers. 66 Previously, LGAs collected the cess at road blocks which were set up at all major exit points in the district. When nuisance taxes were abolished in 2003, LGAs were also prohibited from setting up road blocks to collect this tax. 67 DAI’s field research suggests that the maximum rate is typically charged due to LGA’s dependence on the cess. 68 According to DAI, the exemption only applied to the quantity exported. 69 http://www.tic.co.tz/IPA_Information.asp?hdnGroupID=27&hdnLevelID=7 70 DAI’s field research suggests that the maximum rate is typically charged due to LGA’s dependence on the cess. 71 Faber (2004), p. 8. 72 Faber (2004), p. 8.

Licenses and Permits Service Fees and Charges

• Business license fee for general merchandizing as prescribed under the Business Licensing act, 1972.

• Commercial fishing license fee • Intoxicating liquor license fee • Taxi registration fee • Private health facility license fee (including pharmacies, drug shops,

private dispensaries and private clinics) • Plying (transportation) fees for commercial vehicles • Central bus stand fees • Licensing fee under section 4(1) of the Surface and Marine Transport

Regulatory Authority Act, 2001 • Vehicle license fees • Fishing vessel license fees • Ferry Licenses • Muzzle loading guns license fees • Forest produce license fees • Hunting licenses fees • Building materials extraction license fee • Scaffolding/hoarding permit fees

• Livestock market fee • Refuse collection service fee • Abattoir charges including slaughter and meat inspection fees • Cesspit emptying fee • Clearing of blocked drains fee • Health facility user charges • Artificial insemination fee • Clean water fee • Sale of seedlings • Livestock dipping fee • Insurance commission fee • Sale of building plans prepared by local government staff • Building permit fee • Land survey fee • Tender fee for procurement activities tendered by the LGA • Building valuation service fee • House rent for LGA housing • Market stalls and slabs dues • Magulio (temporary market) fees • Auction mart fees (minada) • Hire/rent for LGA vehicles, plant and other assets

ANNEX C: TANZANIA RATES AND CHARGES

Table C.1: Sample Property Taxes in Tanzania

Location Ad Valorem Flat Rate Tax Source

Arusha 0.5%, minimum of TShs 10,000 Residential minimum: TShs 10,000 McCluskey et al (2003)

Ilala 0.15% for residential property, minimum of TShs 10,000 0.2% for commercial property, minimum of TShs 10,000

For properties not contained on the valuation roll a flat rating system is applied. Flat rates vary by property use and size across wards, as follows: Min Max Average Residential/Swahili 10,000 10,000 10,000 Residential/Modern 10,000 15,000 14,333 Commercial/Residential 15,000 30,000 23,667 Commercial 12-48 m2 20,000 30,000 28,000 Commercial 48+ m2 25,000 50,000 41,333 Service Trade 25,000 100,000 73,000

Flat rates applying to special properties are as follows: Min Max Bar and restaurant 45,000 75,000 Guest houses and hotels 100,000 300,000 Petrol and filling stations 75,000 250,000 Institutions 500,000 750,000 Commercial complex 300,000 450,000 Industrial complex 400,000 600,000 Industry 100,000 500,000

Ilala Municipal Council (Property Rate) By-laws, 2005

Iringa 0.1% for residential property, minimum of TShs 6,000 0.4% for commercial property, minimum of TShs 20,000

Residential minimum: TShs 3,000

McCluskey et al (2003)

Kinondoni 0.15% for residential property, minimum of TShs 10,000 0.2% for commercial property, minimum of TShs 10,000

For properties not contained on the valuation roll a flat rating system is applied. Flat rates vary by property use and size, as follows: Residential/Swahili Unplanned 10,000 Residential/Swahili Planned 15,000 Residential/Modern 20,000 Residential/Commercial 25,000 Residential/Double Storey 80,000 Commercial Double Storey 90,000

Ilala Municipal Council (Property Rate) By-laws, 2002

Residential/[Above] Two Storey 100,000 Commercial/Above Two Storey 150,000 Service Trade 300,000

Mbeya 0.5%, minimum of TShs 5,000 Residential minimum: TShs 2,000 McCluskey et al (2003)

Mogororo 0.12%, minimum of TShs 6,000 Residential minimum: TShs 3,000 McCluskey et al (2003)

Moshi 0.3%, minimum of TShs 3,000 Maximum for owner occupied residential properties of TShs 6,000

Residential minimum of: Surveyed: 300% of land rent Unsurveyed: TShs 2,000


Mwanza 0.15% for single-storeyed 0.4% for multi-storeyed Minimum of TShs 7,500

Residential minimum of: TShs 7,500 for permanent properties TShs 3,000 for temporary properties


Tabora 0.15%, minimum of TShs 3,000 Residential minimum of: TShs 3,000 for unsurveyed (semi-permanent) properties


Tanga 0.2%, minimum of TShs 2,500 Residential minimum: TShs 2,500 McCluskey et al (2003)

Temeke 0.15%, minimum of TShs 10,000 60 categories of rateable properties (categorised by use, size, location), with ranges as follows: Min Max Residential/Unplanned/Semi-Permanent 10,000 12,000 Residential/Small 10,000 25,000 Residential/Medium 25,000 75,000 Residential/Large 450,000 600,000 Commercial/Unplanned/Semi-Permanent 30,000 45,000 Commercial/Small 23,000 75,000 Commercial/Medium 30,000 750,000 Commercial/Large 150,000 1,500,000 Industrial/Large 300,000 1,125,000

Temeke Municipal Council (Property Rate) By-laws, 2001

Rural Areas 2,000 – 10,000 TShs DAI Europe

Kisarawe Applicable to properties in the Kisarawe urban and trading centres: Permanent residential buildings 3,000 Commercial buildings 10,000 Petrol stations 30,000

Temeke District Council (Property Levy) By-laws, 2004

ANNEX D: CURRENT LOCAL REVENUE INSTRUMENTS IN UGANDA

Local Revenue Instrument

Tax Base Rate Exemptions

Personal Taxes

GTax (GTax)—Suspended

Males over 18 and females over 18 in gainful employment. In practice, the tax was not levied on women unless they had a regular salary. For salaried workers, employers had the obligation to deduct the tax. For individuals not in salaried employment, LGUs assessed income on the basis of property owned (excluding household property).

The amount of the GTax varied across income bands, from UShs 3,000 on incomes under UShs 288,000 per annum up to UShs 100,000 on incomes over UShs 1,560,000 per annum. The upper limit was set at the threshold for the payment of PAYE (the national income tax).73

Income Rate 288,000 and below 3,000 288,000-348,000 6,000 348,000-408,000 9,000 408,000-468,000 12,000 468,000-528,000 15,000 528,000-588,000 18,000 588,000-628,000 20,000 628,000-728,000 25,000 728,000-738,000 30,000 738,000-904,666 40,000

904,666-1,071,333 50,000 1,071,333-1,154,666 55,000 1,154,666-1,238,000 60,000 1,238,000-1,245,142 70,000 1,245,142-1,250,500 80,000 1,250,500-1,375,500 90,000

Above 1,560,000 100,000

Most LGUs also levied a Development Levy or Education Levy in addition to their GTax, typically levied as a flat rate of UShs 1,000 or UShs 2,000. At least one LGU (Nakasongola) levied it as a 20 percent surcharge on GTax.74

Students. Employees of the army and military police. Under the LG Act, Chief Administrative Officers were empowered to exempt people on grounds of poverty arising from old age, infirmity pr disability, or other good causes.

73 Mahler (2005), p. 54. 74 Mahler (2005), pp. 58-59.


Property Tax Property taxes are payable by the owners of: (1) commercial and industrial buildings in both rural and urban areas; and (2) residential buildings in urban areas, excluding owner occupied residential housing. Undeveloped land is assumed to have no rental value. The tax base is the net annual rental value of property.75

Responsibility for levying and collecting rates lies with Urban LGUs. They can legally charge a maximum rate of 20 percent of the rateable value, and can set this rate without the input or approval of the central government. Property rates are typically in the range of 7 to 10 percent76, i.e. 6 to 8 percent for residential property, and 8 to 10 percent for non-residential property.77 For example, average rates in Kampala are in the order of:78, 79

UShs 50,000 to 100,000 p.a. for a small one bedroom house; UShs 100,000 to 200,000 p.a. for a medium two bedroom house; and UShs 300,000 – 450,000 p.a. for a large four to five bedroom house.

Any official resident of the president, and traditional or cultural leaders. A property used exclusively for public worship and as a resident of a religious leader. Properties used for burial or as a crematorium. Properties used for charitable or educational institutions supported only by endowments or voluntary contributions. Property used for outdoor sport or recreation. Properties used for public services (i.e. public utilities, public libraries and museums, civil and military aerodromes, and railway properties). Although Ugandan law does not explicitly exempt government property, the central government in Uganda does not pay any property tax.

Fee paid on the transfer of property (required for property registration)

Persons buying land or property. Fees are administered though the district land board, although they must be deposited into a commercial bank to proceed with the registration process.

Maximum rates are in the range of 5-15 percent of the selling price. The actual rate depends on the size and the distance of the land from the town centre. Typical formula: Land Area/Distance from Centre x Land Value + 1% of Selling Price.80

75 The net rental value for residential buildings includes an adjustment for maintenance costs of approximately 18 to 20 percent. 76 Doing Business, Paying Tax in Uganda. 77 Kayuza (2006) 78 The actual range is quite significant. E.g. a one bedroom house in Kololo (an expensive suburb in Kampala) rents for twice as much as a one bedroom house in Kyebando (a cheaper Kampala suburb). DAI suggests the following assumptions corresponding to household characteristics extracted from the household survey: Hut: Mud and poles wall, grass/papyrus or banana fibre roofing, customary land tenure, owner-occupied UShs 50,000 - 10,000 House 1: Mud and poles wall, iron sheet roofing, customary land tenure / freehold, owner-occupied UShs 10,000 - 20,000 House 2: Brick with cement walls, iron sheet roofing, freehold, owner-occupied UShs 20,000 - 30,000 Tenement 1: Mud and poles walls, iron sheet roofing, rammed earth floor, rented private UShs 30,000 - 50,000 Tenement 2: Burnt bricks with cement walls, iron sheet roofing, rammed earth floor, rented private UShs 50,000 - 100,000 Detached House: Burnt brick with cement walls, iron sheet roofing, cement screened floors, owner-occupied UShs 100,000 - 200,000 79 DAI suggests the following assumptions corresponding to enterprise size: Small: UShs 200,000 p.a.; Medium: UShs 300,000 p.a.; and Large: UShs 500,000 p.a. 80 Data for 2004/05 suggests that the average rate is between UShs 20,000 - 100,000 (although in Mbarara the average rate cited was UShs 500,000). The World Bank Doing Business Survey estimates that for a piece of land worth $13,500 = UGX 25,295,854.50, actual transfer fees are UGX 10,000 in case of leases, perusal fees are UGX 5,000 and other charges which add up to about UGX 20,000. In the case of leases there is a consent fee which is also paid before payment of stamp duty in this case in the land administration section of UGX 10,000. Based on the above sources of information, DAI suggests a flat rate of 50,000 might seem a reasonable assumption for modelling.

Building plans and permit fees

All persons/Landlords developing or building on their land and plans taken to LGUs for approval. The LGs don’t keep information of the plans approved. There is a lot defaulting in this tax because majority of people either don’t approve their plans or bribe LGU officials. This is caused by the bureaucratic procedures at the approving department.

The stipulated charging structure indicates that LGUs are supposed to charge a maximum of 5% of the cost of building but some LGs (mostly rural LGs) charge a flat rate of UShs 50,000. Others charge 2500/- per square metre of the building floor depending on the approved plan. The payment is done once at the commencement of the building exercise Data collected by DAI suggests an average levy of 35,000/ per tax.

Ground Rent Ground Rent is levied on LGU owned property (including commercial, residential or industrial buildings in both rural and urban areas). In some cases, LGUs have offered their land to individuals to develop and pay rent for that land. In this way LGUs benefit from land that would otherwise be idle since they lack finances for development.

Automotive Taxes

Parking fees Fees are based on the number of vehicles parked in public parking bays.

Street parking fees are typically UShs 200 for the first 30 minutes and UShs 200 for each additional hour.81

Taxi and Bus Park Fees

Number of vehicles using taxi and bus park facilities.

Each matatus is required to make a monthly payment of UShs 20,000. Entry to the taxi park is 4,500 per day. Matatus also pay an exit fee each time they leave the park of UShs 1,000for town service, UShs 1,500 to UShs 5,000 for longer destinations. For example, a trip from Kampala to Mukono is UShs 1,500. Matatus also pay an entry fee when they enter the park at their new destination. Collection is typically tendered out to private collectors.

81 DAI met with Multiplex, which manages public parking bays in Kampala. Multiplex did not provide any additional details on the usage of parking slots (disaggregated by personal versus commercial vehicle) or collection ratios.


Business/Trading Licenses, Permits, Fees and Taxes.

All businesses operating within the jurisdiction of an LC3. The Trade Licensing Act regulates businesses (wholesale and retail), commission agents, management consultants, estate agents, motor vehicle repairers, and hawkers. Businesses are required to purchase an annual trade licence from the City, Town, Municipal or District Council and to comply with health and safety requirements during the conduct of their business.

Business licences are typically annual flat amounts, with fees varied according to the different categories of business enumerated in a schedule issued by LGUs. These are not standardised between LGUs. KCC has the most comprehensive coverage including licensing of manufacturers and a wide variety of services and professions.82

Farmers, dairymen, hawkers of fish, poultry, fruit and vegetables, who sell their own produce are not required to have annual trade licences while selling their produce. Professional businesses such as banks, lawyers and insurance companies are also exempted.

Produce Cess of Tax

Produce cess or tax on agricultural production is limited in scope. At present it applies to produce such as milk, fish or charcoal transported to other LGUs. In addition, there exists some taxation of marketed rural outputs in the form of market fees

There is no guidance on rate structure which is in relation to volume of goods transported. According to data collected by DAI, the average rate was around UShs 40,000.

Market Fees Market vendors operating from stalls or operating from open spaces within established and gazetted markets pay a monthly rental charge. Wholesalers bringing in foodstuffs and other items in bulk on lorries and pick-ups are only charged a one-off fee on those items, each time they supply the market and the market vendors buying those items are not required to pay any dues on those items. With regard to weekly and monthly markets in the countryside, the market vendors who operate within the markets continue to pay a market charge on each market day.83

A typical monthly rental charge for Kampala is UShs 20,000. Typical monthly rental charges for other urban councils are between UShs 7,000 and UShs 10,000. Typical monthly rental charges for rural areas are between UShs 3,000 and UShs 5,000 per month. Collection is typically tendered out to private collectors.

82 DAI notes that business licenses are applied haphazardly across different business activities. Differentiation for small, medium and large enterprises is commonly provided for in each major business category. However, the categorisation of businesses and the rate paid is somewhat arbitrary and to the discretion of each local council. The formula based approach (determined through the Trade Licensing Act) has become very outdated, and many governments now avoid it basing current assessments on previous rates and their discretion on whether the business has grown in terms of capital investment leading to a flat rate system. 83 Ministry of Local Government website.

Advertising Fees

Advertising fees and tax on billboards

Flat rates levied on advertisers for signs and billboards.

A flat rate is levied per advertisement/billboard. It is not clear whether this is a one-off fee or whether a monthly/yearly rate is charged. On average, the cost per levy was 160,000. Annex E contains sample rates for Kampala City Council.

ANNEX E: UGANDA RATES AND CHARGES

Table E.1: Business License Rates (DAI Assumptions)

Enterprise Size

Sector Small Medium Large

Agriculture 15,000 25,000 35,000

Mining 50,000 100,000 300,000

Manufacturing 100,000 200,000 400,000

Construction 50,000 100,000 300,000

Wholesale and retail trade 20,000 75,000 100,000

Hotels and restaurants 35,000 100,000 500,000

Business activities 80,000 120,000 300,000

Education 50,000 100,000 1,000,000

Health and social work 60,000 100,000 150,000

Other community 20,000 30,000 50,000 For micro enterprises, DAI suggests the following assumptions:84 Per Annum Fee

‘Basic’ businesses – including agricultural activities, small scale mining activities, local brewing 20,000

Licences for trading simple goods 30,000

Non-complex small-scale manufacturing activities and trading for complex goods (pharmacy/chemist) 50,000

Manufacturing activities involving more sophisticated processing (grinding mills) 70,000

Construction company operational permit 200,000

Butcher 60,000

Milk seller 75,000

Mechanic 40,000

Hawkers permit and hot street food/drinks stalls 25,000

Money lender 160,000

84 The DAI assumptions were developed in consultation with the Business Licensing Reform team on the Regulatory Best Practice Project.

Table E.3: Outdoor Advertising Charges approved by Kampala City Council, 2003

Type of Advert Charges

1. Application forms 10,000/= per site per annum

Class One – Billboards 2. Super sign 3. 24sqm to 487sqm 4. Above size 13sqm to 23sqm 5. Billboard above 1.5sqm but below 13sqm 6. Billboard below 13sqm NB: No commercial board below 1.5sqm

1,000,000 per annum 750,000 per annum 500,000 per annum 400,000 per annum 147,000 per annum

Class Two – Posters 7. Presidential elections 8. Parliamentary, L.C V & L.C III elections 9. Other posters

1,000,000 per candidate 500,000 to wait a new law

Class Three – Wall Adverts 10. Wall adverts

75% of billboard sizes

Class Four – Others 11. Banners & Flags 12. Adverts on reverse side of street furniture 13. Street name adverts 14. Bus/Taxi stop signs 15. Bill copy holders 16. Estate Agents’ Boards 17. Sale of goods 18. Livestock auction 19. Railings 20. Contraction signs 21. Project Boards (Ministries, NGOs etc)

15,000 each day 73,200 per annum 110,00 per annum 100,000 per annum To wait contract terms for CENCO 439,000 per annum 74,000 per annum 200,000 per annum - 500,000 per annum 100,000 per annum

Outdoor Adverts 22. Product Replicas & 3-dimensional signs 23. Display advert clocks 24. Tri-vision signs 25. LCD Boards 26. Litter bins 27. Roof signs 28. Sky signs 29. Kiosks 30. Towers, bridges, pylons 31. Passenger shelters 32. Junction sign 33. Aerial signs 34. Moving billboards/Trailer advertising 35. Vehicular advertising

300,000 per annum 200,000 per annum 500,000 per annum 1,000,000 per annum 20,000 per bin 75% of billboard charges 2,000,000 per annum 200,000 per annum 1,000,000 per annum 250,000 per annum 500,000 per annum 150,000 per day 250,000 as license per annum per unit 1,000,000 per annum per client

Table E.4: Total collections for Central Division of KCC, 2005 Advertising Tool Measurements No Charge (UShs) Amount (UShs)

Billboard 1 Super sign 50 1,000,000 80,000,000

Billboard 2 24sqm to 48sqm 58 750,000 43,000,000

Billboard 3 Above size 13sqm to 23sqm

10 500,000 5,000,000

Suburb Sign Board below 1.5sqm 104 147,000 15,000,000

Copy Bill Holder Board below 1.5sqm 30 147,000 5,586,000

Street Finders Board below 1.5sqm 38 147,000 3,750,000

Bus Shelter 15 250,000 3,750,000

City Clock 20 200,000 4,000,000

TOTAL 161,534,000

ANNEX F: HOUSEHOLD SURVEY DATA

Table F.1: Data Extracted from the Tanzania Household Budget Survey 2000/2001 Source Data Entries

with Data

NBS Household ID 100% NBS Household weight 100% NBS Rural or urban 100% NBS National sample or not 100% NBS Region 100% NBS Stratum (Rural, Dar, Other Urban) 100% 2001 HH Survey (I_S1) Survey month 100% 2001 HH Survey (I_S1) Survey year 100% 2001 HH Survey (I_S2) Adults 100% 2001 HH Survey (I_S2) Children 74% 2001 HH Survey (I_S2) Household members 100% 2001 HH Survey (I_S2Q3) HH head gender 100% World Bank calculation HH head gender (Male = 1; Female =0) 100% 2001 HH Survey (I_S2Q4) HH head age 100% 2001 HH Survey (I_S2Q4) First spouse age 65% 2001 HH Survey (I_S2Q4) Second spouse age 2% 2001 HH Survey (I_S2Q5) HH head marital status 100% 2001 HH Survey (I_S2Q7e) HH head educational attainment 99% 2001 HH Survey (I_S2Q7e) Spouse educational attainment 65% 2001 HH Survey (I_S2Q7e) Eldest daughter educational attainment 43% 2001 HH Survey (I_S2Q7e) Eldest son educational attainment 45% 2001 HH Survey (I_S2Q8) HH head main activity 100% 2001 HH Survey (I_S2Q8) HH head secondary activity 99% 2001 HH Survey (I_S2Q8) Spouse main activity 65% 2001 HH Survey (I_S2Q8) Eldest daughter main activity 44% 2001 HH Survey (I_S2Q8) Eldest son main activity 45% 2001 HH Survey (I_S3.1) Number of buildings owned by HH 100% 2001 HH Survey (I_S3.1Q1) Number of buildings owned by HH 100% 2001 HH Survey (I_S3.1Q10) Wall material 100% 2001 HH Survey (I_S3.1Q11) Roof frame material 100% 2001 HH Survey (I_S3.1Q12) Roof material 100% 2001 HH Survey (I_S3.1Q13) Tenure 100% World Bank calculation Owner Occupiers? (Yes = 1) 100% 2001 HH Survey (I_S3.1Q14) Normal market rent per month (owner occupied housing) 71% 2001 HH Survey (I_S3.1Q15) Actual rent paid per month (rental property) 28% 2001 HH Survey (I_S3.1Q2) Storeys in 1st building 100% 2001 HH Survey (I_S3.1Q2) Storeys in 2nd building 14% 2001 HH Survey (I_S3.1Q2) Storeys in 3rd building 5% 2001 HH Survey (I_S3.1Q2) Storeys in 4th building 1% 2001 HH Survey (I_S3.1Q2) Storeys in 5th building 0% 2001 HH Survey (I_S3.1Q2) Storeys in 6th building 0% 2001 HH Survey (I_S3.1Q2) Storeys in 7th building 0% 2001 HH Survey (I_S3.1Q2) Storeys in 8th building 0% 2001 HH Survey (I_S3.1Q2) Storeys in 9th building 0%

World Bank calculation Average Storeys 100% 2001 HH Survey (I_S3.1Q5) Rooms in 1st building 100% 2001 HH Survey (I_S3.1Q5) Rooms in 2nd building 14% 2001 HH Survey (I_S3.1Q5) Rooms in 3rd building 4% 2001 HH Survey (I_S3.1Q5) Rooms in 4th building 1% 2001 HH Survey (I_S3.1Q5) Rooms in 5th building 0% 2001 HH Survey (I_S3.1Q5) Rooms in 6th building 0% 2001 HH Survey (I_S3.1Q5) Rooms in 7th building 0% 2001 HH Survey (I_S3.1Q5) Rooms in 8th building 0% 2001 HH Survey (I_S3.1Q5) Rooms in 9th building 0% World Bank calculation Average Rooms 100% 2001 HH Survey (I_S3.1Q8) Foundation material 100% 2001 HH Survey (I_S3.1Q9) Floor material 100% World Bank calculation Permanent Structure? i.e. Walls made from burnt bricks or concrete cement

and stone walls (Permanent=1) 100%

2001 HH Survey (I_S3.2Q1) Household main drinking water supply 100% 2001 HH Survey (I_S3.2Q10) Cost of improvements in last 12 months 24% 2001 HH Survey (I_S3.2Q11) Reason for not improving housing condition in last 12 months 64% 2001 HH Survey (I_S3.2Q2) Electricity grid 100% 2001 HH Survey (I_S3.2Q2) Solar electricity 100% 2001 HH Survey (I_S3.2Q3) Major fuel for cooking 100% 2001 HH Survey (I_S3.2Q4) Major fuel for lighting 100% 2001 HH Survey (I_S3.2Q5) Toilet facilities 100% 2001 HH Survey (I_S3.2Q6) Cooling facilities 100% 2001 HH Survey (I_S3.2Q7) Heating facilities 100% 2001 HH Survey (I_S3.2Q8) Garbage disposal facilities 100% 2001 HH Survey (I_S3.2Q9) Did HH improve housing conditions? 100% 2001 HH Survey (II_S5) Amount of instalments paid for durable items and other services acquired

under hire purchase in the last 12 months 9%

2001 HH Survey (II_S5) Amount paid for durable items and other services acquired under hire purchase in the last 12 months

12%

2001 HH Survey (II_S5) Value of purchased durable items and other services at full price in the last 12 months

100%

2001 HH Survey (II_S5Q18) Amount paid for cigarettes and tobacco acquired under hire purchase in the last 12 months

0%

2001 HH Survey (II_S5Q18) Instalments paid for cigarettes and tobacco acquired under hire purchase in the last 12 months

0%

2001 HH Survey (II_S5Q18) Value of purchased cigarettes and tobacco at full price in the last 12 months 16% 2001 HH Survey (II_S6) Total value of household assets 99% 2001 HH Survey (II_S634) Number of fields/land 62% 2001 HH Survey (II_S634) Value of fields/land 62% 2001 HH Survey (II_S635) Number of houses 66% 2001 HH Survey (II_S635) Value of houses 66% 2001 HH Survey (II_S6Q24) Number of vehicles 5% 2001 HH Survey (II_S6Q24) Value of vehicles 5% 2001 HH Survey (II_S6Q25) Number of motor cycles 4% 2001 HH Survey (II_S6Q25) Value of motor cycles 4% 2001 HH Survey (II_S6Q58) Household business 1 50% 2001 HH Survey (II_S6Q58) Household business 2 14% 2001 HH Survey (II_S6Q58) Household business 3 3% World Bank calculation At least one household business? (Yes = 1) 100% 2001 HH Survey (II_S6Q60) Household main source of income 99% World Bank calculation Wage or Salary Earners 100% 2001 HH Survey (II_S6Q60) Any household member operating saving or current account 99%

2001 HH Survey (II_S6Q60) First household member operating saving or current account 15% 2001 HH Survey (II_S6Q60) Second household member operating saving or current account 3% 2001 HH Survey (II_S6Q60) Third household member operating saving or current account 0% 2001 HH Survey (II_S6Q60) Fourth household member operating saving or current account 0% 2001 HH Survey (II_S6Q61) Any household member taken a bank loan during the last 12 months 99% 2001 HH Survey (II_S6Q61) First amount of a bank loan during the last 12 months 1% 2001 HH Survey (II_S6Q61) First household member with a bank loan during the last 12 months 1% 2001 HH Survey (II_S6Q61) Second amount of a bank loan during the last 12 months 0% 2001 HH Survey (II_S6Q61) Second household member with a bank loan during the last 12 months 0% 2001 HH Survey (II_S6Q62) Any household member participate in an informal savings group system 99% 2001 HH Survey (II_S6Q63) Any household member participate in an formal savings group system than

bank 99%

2001 HH Survey (II_S6Q64) Acres of land for farming owned this year 63% 2001 HH Survey (II_S6Q65) Acres of land for farming owned last year 61% 2001 HH Survey (II_S6Q66) Does HH use farmland that it does not own this year? 99% 2001 HH Survey (II_S6Q67) Acres of land for farming used but not owned this year 14% 2001 HH Survey (II_S6Q68) Acres of land for farming used but not owned last year 22% 2001 HH Survey (II_S6Q69) Number of livestock owned by household this year 16% 2001 HH Survey (II_S6Q70) Number of livestock owned by household last year 16% 2001 HH Survey (II_S6Q71) Number of medium sized animals (goats and sheep) owned by the

household this year 28%

2001 HH Survey (II_S6Q72) Number of medium sized animals (goats and sheep) owned by the household last year

26%

2001 HH Survey (II_S6Q77) How often did household have problem of food supply last year 100% 2001 HH Survey (II_S6Q78) Household comparison of economic situation now and one year ago 100% 2001 HH Survey (II_S6Q79) Community comparison of economic situation now and one year ago 100% 2001 HH Survey (II_S6Q80) How does this household compare with others in the community 100% 2001 HH Survey (II_S7) Total household income 98% 2001 HH Survey (II_S7Q6) Imputed rent of owner occupied dwellings 64% 2001 HH Survey (II_S7Q6) Rent received 12% ERB calculation Number of adult equivalents 100% ERB calculation Household expenditure income (CBXCC) 100% World Bank calculation Expenditure income per AE 100% World Bank calculation AE weight 100% World Bank calculation Cumulative AE weight 100% World Bank calculation Cumulative percentage 100% World Bank calculation Decile 100% World Bank calculation Quintile 100%

Table F.2 Data Extracted from the Uganda National Household Survey, 2002/2003

Source Data Entries

with Data

S1A Household ID 100% S1A Region 100% S1A District 100% UBOS Multiplier 100% UBOS *Community status 100% S2Q6 HH head gender 100% S2Q6 *HH head gender (Male = 1; Female =0) 100% S2Q7 *HH head age 100% S2Q7 *HH first spouse age 64% S2Q7 HH second spouse age 1%

S2Q7 HH third spouse age 0% ? HH head employment status 96% HH Head Salaried Worker? (Y=1) 100% ? Kind of activity (Industry) where HH head is usually employed 97% ? HH Spouse(s) employment status 62% HH Spouse Salaried Worker? (Y=1) 100% ? Kind of activity (Industry) where spouse(s) is usually employed 62% ? Age of first working son/daughter 45% ? Age of second working son/daughter 30% ? Age of third working son/daughter 19% ? HH Son/daughter employment status 15% ? Kind of activity (Industry) where son/daughter is usually employed 15% S5AQ1 Type of housing unit 100% S5AQ1 *Hut? (Yes=1) 100% S5AQ2 Occupancy of dwelling unit 100% S5AQ2 *Owner Occupiers? (Yes = 1) 100% S5AQ3 Type of dwelling unit 100% S5AQ4 Number of rooms used for sleeping 100% S5AQ4 *Number of Rooms (Integer) 100% S5AQ5 Land tenure of plot 68% *Freehold, Leasehold or Mailo (Y=1) 100% S5AQ6 Type of material used for construction of roof 100% S5AQ7 Type of material used for construction of wall 100% S5AQ8 Type of material used for construction of floor 100% S5BQ10A Does household own motor vehicle 100% S5BQ10A *Vehicle (at least one = 1) 100% S5BQ10B Does household own motor cycle 100% S5BQ10B *Motorcycle (at least one = 1) 100% S5BQ10C Does household own bicycle 100% S5BQ10C *Bicycle (at least one = 1) 100% S5BQ10D Does household own boat or canoe 100% S5BQ10E Does household own Donkey 100% S5BQ11A Does household own Television 100% S5BQ11B Does household own Radio 100% S5BQ11C Does household own Mobile phone 100% S5BQ11D Does household own fixed phone 100% S5BQ11E Does household own postal address 100% S5BQ11F Does household own Email address 100% S6AQ9 Value of soda from Restaurants consumed from home produce for a period

of 7 days 0%

S6AQ8 Quantity of Beer (measured in a bottle of 500ml) from Restaurants taken from home produce for a period of 7 days

0%

S6AQ7 Value of other alcoholic drinks consumed while away from home for a period of 7 days

7%

S6AQ6 Quantity of other drinks (measured in litres) consumed while away from home for a period of 7 days

2%

S6AQ7 Value of other drinks consumed while away from home for a period of 7 days 2% S6AQ5 Value of Other Tobacco consumed while at home for a period of 7 days 4% S6AQ6 Quantity of other Tobacco (measured in Tobacco leaf) consumed while away

from home for a period of 7 days 1%

S6AQ7 Value of other Tobacco consumed while away from home for a period of 7 days

1%

S6AQ8 Quantity of other Tobacco (measured in Tobacco leaf) consumed from home produce for a period of 7 days

1%

S6AQ9 Value of other Tobacco consumed from home produce for a period of 7 days 1% S6AQ10 Quantity of other Tobacco (measured in Tobacco leaf) received free of

charge for a period of 7 days 1%

S6AQ11 Value of other Tobacco received free of charge for a period of 7 days 1% *Value of Households expenditure on other tobacco at home & away from

home for 7 days 100%

*Quantity other tobacco at home & away from home for 7 days 100% S6AQ5 Value of Households consumption expenditure for 7 days (purchases at

home) 98%

S6AQ7 Value of Households consumption expenditure for 7 days (purchases away from home)

20%

S6AQ9 Value of Households consumption out of home produce for 7 days 67% S6AQ11 Value of free consumption for 7 days 29% S6BQ5 Value of purchased Non-durable consumption for 30 days 100% S6BQ7 Value of Home produced Non-durable consumption for 30 days 6% S6BQ9 Value of free Non-durable consumption for 30 days 76% S6CQ3 Value of purchased semi-durable & durable goods & services for 365 days 97% S6CQ4 Value of semi-durable & durable goods & services got from own household

enterprise stock (for 365 days) 3%

S6CQ5 Value of free semi-durable & durable goods & services for 365 days 18% S6DQ1 *Amount paid as taxes & duties excluding Graduated Tax in the last 12

months 7%

S6DQ2 Amount paid as pension & Social Security contributions in the last 12 months 2% S6DQ3 Amount paid as Remittances, gifts & other Transfers including tithe in the

last 12 months 57%

S6DQ4 Amount paid as Contributions to funerals & other functions in the last 12 months

39%

S6DQ5 *Amount paid as Graduated Tax in the last 12 months 29% S6DQ6 Amount of other contributions in the last 12 months 2% S6bQ5 *Value paid for rented house in a period of 30 days 31% S6bQ5 *Value of imputed Rent of owned house in a period of 30 days 68% S6bQ4 *Quantity of paraffin (Kerosene) in litres purchased in a period of 30 days 90% S6bQ5 *Value of paraffin (Kerosene) purchased in a period of 30 days 89% S6bQ8 Quantity of paraffin (Kerosene) in litres out of home produce in a period of 30

days 1%

S6bQ9 Value of paraffin (Kerosene) out of home produce in a period of 30 days 1% S6bQ5 *Value of Petrol or Diesel in litres purchased in a period of 30 days 4% S6bQ9 Value of Petrol or Diesel received for free in a period of 30 days 0% S6cQ3 Value of purchased electronic equipments (TV. Etc) in a period of 365 days 1% S6cQ4 Value of electronic equipments (TV. Etc) acquired out of household

enterprise stock in a period of 365 days 0%

S6cQ5 Value of electronic equipments (TV. Etc) received for free in a period of 365 days

0%

S6cQ3 Value of purchased Radios in a period of 365 days 12% S6cQ4 Value of Radios acquired out of household enterprise stock in a period of

365 days 0%

S6cQ5 Value of Radios received for free in a period of 365 days 0% S6cQ3 Value of purchased Bicycles in a period of 365 days 5% S6cQ4 Value of Bicycles acquired out of household enterprise stock in a period of

365 days 0%

S6cQ5 Value of Bicycles received for free in a period of 365 days 0% S6cQ3 *Value of purchased Motorcars or pick-ups etc in a period of 365 days 0% S6cQ4 Value of Motorcars or pick-ups etc acquired out of household enterprise

stock in a period of 365 days 0%

S6cQ5 Value of Motorcars or pick-ups etc received for free in a period of 365 days 0% S6cQ3 *Value of purchased Motor cycles in a period of 365 days 1%

S6cQ4 Value of Motor cycles acquired out of household enterprise stock in a period of 365 days

0%

S6cQ5 Value of Motor cycles received for free in a period of 365 days 0% S7Q4 Number of houses 64% S7Q5 Value of the houses 65% S7Q4 Number of other buildings 21% S7Q5 Value of other buildings 21% *Total number of buildings 100% S7 *Total value of buildings 100% S7Q5 Value of other household assets 99% S7Q13 Value of agricultural land owned 64% S7Q14 Value of enterprise land owned 3% S7Q15 Value of land rented-in 12% S7Q16 Value of land rented-out 2% S7Q17 Value of Land provided free of charge 6% S7Q18 Value of Land received free of charge 9% S7Q19 Value of total cultivated land 70% S7 *Value of land owned by the household 100% S7Q20 Value of Enterprise assets 44% Q20 Value of the available household assets 100% S7Q13 Quantity of agricultural land owned 63% S7Q14 Quantity of enterprise land owned 3% S7Q15 Quantity of land rented in 12% S7Q16 Quantity of land rented out 2% S7Q17 Quantity in acres of Land provided free of charge 5% S7Q18 Quantity in acres of Land received free of charge 6% S7Q19 Quantity of total cultivated land 69% *Quantity of land owned by the household 100% S8Q2 Income from crop farming enterprises during the last year 46% S9Q1 Does the household have any non-crop farming enterprise? 100% S9Q1 Non-crop farming enterprise (Y=1) 100% S9Q3 Enterprise sector 61% UBOS UBOS Household categorization 100% UBOS *Adult equivalents 100% UBOS *Total Monthly household expenditures in market prices after adjusting for

regional and intertemporal price variation in 1997/98 100%

World Bank *Expenditure income per AE 100% World Bank AE weight 100% World Bank Cumulative AE weight (rural and urban treated separately) 100% World Bank Cumulative percentage (rural and urban treated separately) 100% World Bank *Decile (rural and urban treated separately) 100% World Bank *Quintile (rural and urban treated separately) 100%

ANNEX G: ENTERPRISE DATA

Table G.1: Enterprise Data Sources in Uganda and Tanzania Country Data

Sources Notes

Tanzania NBS, Survey of Industrial Production 2003, Tanzania Bureau of Statistics.

This data was provided directly from NBS to the World Bank. Survey of 595 manufacturing and mining firms. The report includes the following data summarized by sector and enterprise size:

Number of establishments Number of people engaged Number of employees Total labour costs Wages and salaries Gross output Production costs Value added

NBS agreed to provide additional summaries of data from the 2003 survey of industrial production. Additional data (by industry and enterprise size) was provided as follows:

Receipts from dividends, interests, discounts etc. (to calculate total revenue) Total Income Fuels and lubricants consumed Electricity and water charges Rents paid for the hire of fixed assets Posts and telecommunication services Land (closing balance) Buildings and structures (closing balance) Vehicles (closing balance)

Tanzania World Bank Enterprise Study 2001

Small sample size of 275 manufacturing (including agro-industry) firms. 33 of these entries have no sales or revenue data. For the remainder, sales per annum (for the primary product) vary from TShs 18,000 to TShs 193 billion with a broad and fairly equal distribution within this range. The companies in included in the survey are considerably larger in scale/size than the enterprises captured in the TRA database. The database includes the following data fields:

Region Description of products sold (up to three different product types) Unit in which products are sold Quantity of products sold per year Total sales of products per year Total sales (sum of three products) Type of raw material purchased (up to three types) Unit in which raw materials were purchased Quantity of raw materials purchased Cost of raw materials Value of machinery and equipment in 2002 (limited data) Combined value of land and buildings in 2002 (limited data) Value of vehicles in 2002 (limited data given)

Amount spent on rent of machinery and equipment in 2002 (limited data) Amount spent on rent of land and buildings in 2002 Amount spent on hire of vehicles in 2002 (limited data) Total number of employees in 2002 Total cost of labour in 2000, 2001, 2002

DAI cleaned the dataset to those remove entries where total sales of the primary product and rental of land and buildings was zero (111 data points remained following this process). DAI calculated net revenue as total sales less 2002 costs. DAI summarised the data by industry but did not develop any profiles of enterprises according to scale.

Tanzania TRA Both DAI and the World Bank requested a database of companies registered with a TIN with declared revenue figures and sector classification. However to date a full dataset has not been provided. DAI was given an incomplete database with 8187 entries.85 This data set includes the following fields: (1) TIN; (2) Turnover/income (pre-tax declared to TRA); (3) Sector (ISIC code); and (4) Description of business activity.

Tanzania TRA (2001), Taxation of the Informal Sector.

TRA completed a study of informal firms in 2001 for which we have the report. DAI tried unsuccessfully to get the data set underlying this research.86

Uganda Uganda Business Inquiry (UBI) 2000/2001

The UBI is a national survey of establishments.87 UBOS only agreed to provide a data extract with the following fields:88

Business category (sector) Number of employees Activity code District Region Total income Gross output Cost of staff

Uganda Informal Activities section of the National Household Survey, 2002/2003

This is a survey of 6,411 informal household enterprises. DAI extracted raw data from the Informal Activities Section of the National Household Survey. Relevant data fields captured in the extract include the following:

Sector Number of sole proprietors Amount of wages and in kind payments to regular and casual employees in the last 30 days Value of inputs other than labour in the last 30 days Total costs (computed)

85 Coverage of the database is limited to a small selection of districts (including Dar,and Zanzibar) and within these districts, the data is not complete. The turnover/income given is an annual figure given in annual income in TShs (not in thousands) as estimated in the year 2005. This is the figure before any taxes (including VAT / corporation tax are deducted). Corporation tax is typically 30%, VAT is 20%. 86 DAI notes that they made repeated efforts to get the underlying data for the informal study that was done by the research group at Tanzanian Revenue Authority. 87 While the survey report indicates that 147,160 establishments were surveyed, the dataset provided by UBOS only includes 4,720 entries. 88 The Business Inquiry Survey captures more detailed data on Ugandan enterprises that was not provided by UBOS to the research team. These include: (1) fixed assets including breakdowns for the value of land and buildings, plant and machinery, motor vehicles, work in progress, and other assets; (2) the value of inventories; (3) the value of rent paid on land and buildings; (4) fuel usage; (5) other transport costs; (6) turnover; (7) cost of goods sold; (8) ownership.

Value of enterprises products sold or consumed in one month Income received other than through the sale of products Gross revenue (computed) Net revenue of business income(computed) Value of non household establishment assets Value of establishment land

DAI indicated that they subsequently extracted several additional fields from the survey data, but these were not included in the informal database. Specifically:

Number of people engaged in the enterprise (section 3) Value of purchases (trade) Value of output and transfers (mining) Value of land Value of buildings

DAI did not construct profiles of enterprises according to scale/size, since these firms would be considered ‘micro’ – most of the data in this database is entirely family-run cottage industry / subsistence with some support from casual labour as required.

ANNEX H: INITIAL RESULTS FROM THE ENTERPRISE MODULE

The enterprise module of the local tax incidence model is structured around data extracted from the 2003 Tanzania Survey of Industrial Production and a subset of data from the Uganda Business Inquiry. The Ugandan Business Inquiry 2000/2001 (UBI) is a national survey of 147,160 establishments. The research team was only able to access a limited extract of data from the survey, covering 4,720 establishments and a limited number of data fields (total income, gross output, cost of staff and number of people engaged in the business). The data was categorised by number of employees as follows:

Table H.1: Subset of Uganda Business Inquiry 2000/2001 Data

Less than

10 10-19 20-49 50-99 100-499 500+ Number of data points 2,536 1,042 772 197 139 34 Number of people engaged in the business 4 13 28 66 199 1,475 Labour costs (Ushs '000s) 8,569 39,282 110,706 347,432 927,032 5,517,664 Gross output (Ushs '000s) 40,220 241,634 649,859 2,664,089 7,220,600 25,435,563 Total income (Ushs '000s) 82,873 511,305 972,650 4,586,230 9,041,676 27,440,474

Based on this data, the model applies simple assumptions to determine the burden of business taxes on enterprises of various sizes, including: (1) a flat business license fee; (2) a business tax based on enterprise turnover or income; and (3) a business tax based on number of employees or labour costs. These illustrations are presented in Diagram H.1 to H.3 below. As would be expected, a flat business license fee is highly regressive, with smaller enterprises paying a much greater proportion of their income in tax than larger enterprises. A tax based on enterprise turnover is largely progressive across enterprises of different sizes. The model also illustrates the impact of a simple uniform percentage tax on business income, which has a neutral incidence across enterprises of different size. The progressivity of these taxes could be increased by applying increasing marginal rates across income bands. Finally taxes based on the number of employees or labour costs are not always progressive across enterprises.

Diagram H.1: Flat Business License Fee (Uganda)

Enterprises (Uganda)

0.00%

0.05%

0.10%

0.15%

Less than 10 10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Flat Business License

Diagram H.2: Business tax based on Turnover or Income (Uganda)


0.00%

0.10%

0.20%

0.30%

Less than 10 10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Turnover Tax Tax on Business Income

Diagram H.3: Business Tax based on Employee Numbers and Labour Costs (Uganda)


0.00%

0.05%

0.10%

0.15%

Less than 10 10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Flat amount per employee Tax on Wage and Salary Costs

The model could be improved significantly by expanding the data extract to include the total number of enterprises surveyed and additional data fields. For example, the survey includes questions on the cost of renting land and buildings, which could support the modelling of property rates.

The Tanzania 2003 Survey of Industrial Production is a survey of 595 manufacturing firms. NBS provided data summarized by sector and industry size. This data is presented in Table H.2 and H.3 below.

Table H.2: Average Enterprise by Size from Tanzania 2003 Survey of Industrial Production

Enterprise Size 10-19 20-49 50-99 100-499 500+ Persons Engaged89 17 32 72 226 1,307Employees90 5 8 21 46 284Total Labour Costs91 169,406 252,876 182,151 858,170 2,844,858Wages and Salaries 155,050 215,987 152,682 678,941 2,446,973Production Costs92 740,829 649,970 1,521,348 4,204,009 12,299,575Gross Output93 1,176,072 1,062,063 1,964,002 6,777,976 20,302,521Value Added94 435,243 412,093 442,654 2,573,967 8,002,946Receipts from dividends, interests, discounts 333 4,895 8,530 16,284 12,437Total Income 1,181,836 577,198 1,679,048 5,416,590 16,882,967Fuels and lubricants consumed 14,389 21,669 18,775 164,949 195,164Electricity and water charges 16,020 19,578 33,331 192,053 391,228Rents paid for the hire of fixed assets 124,397 5,707 9,768 32,629 109,336Posts and telecommunication services 7,299 12,887 8,258 25,343 73,418Land (closing balance) 18,442 10,885 359,441 197,254 2,022,381Buildings and structures (closing balance) 672,345 66,072 167,329 590,459 930,141Vehicles (closing balance) 44,254 27,360 34,251 74,361 457,196

Table H.3: Enterprise Turnover by Industry Classification from TRA Extract (Dar es Salaam and Zanzibar)

Industry Classification Number of Enterprises Average Turnover

A. Agriculture, hunting and forestry 34 44,994,270 B. Fishing 5 6,185,598 C. Mining and quarrying 40 9,512,772 D. Manufacturing 407 40,076,743 E. Electricity, gas and water supply 5 7,100,000 F. Construction 203 450,015,967 G. Wholesale and retail trade 2,843 26,059,360 H. Hotels and restaurants 459 11,668,030 I. Transport, storage and communications 2,272 38,500,037 J. Financial intermediation 79 400,751,424 K. Real estate, renting and business activities 1,237 67,604,529 L. Public administration 30 11,610,515 M. Education 29 49,688,705 N. Health and social work 64 178,820,208 O. Other community, social and personal service activities 474 27,875,263 P. Private households with employed persons 5 92,240,000 Q. Extra territorial organisations and bodies 1 14,000,000 Total 8,187 51,149,836

89 All employees, working proprietors and the unpaid workers. 90 All paid workers of the establishment (managerial, technical, clerical and other office workers excluding operatives), directors and others who are in receipt of regular pay. 91 Includes wages and salaries (including overtime payments, commissions and other allowance) paid to employees, employee’s contribution to provident and pension funds, gratuity together with other benefits to employees, either in cash or kind. 92 These are made up of: (1) cost of materials consumed; (2) cost of electricity, fuel, lubricants and Water; (3) cost of re-sales; (4) cost of services received; and (5) other costs of production. 93 Total sales and services plus the net balance of both finished and semi-finished products. Valuation is at ex-factory. 94 This represents the difference between gross output and production costs.

Based on this data, the model applies simple assumptions to determine the burden of business taxes on enterprises of various sizes, including: (1) a flat business license fee; (2) a business tax based on enterprise turnover or income; (3) a business tax based on labour costs; and (4) various types of property taxes. These illustrations are presented for information in Diagrams H.4 to H.7 below. It is difficult to draw any reasonable conclusions from the results due to the small number of data points.

Diagram H.4: Flat Business License Fee (Tanzania)

Enterprises (Tanzania)

0.00%

0.01%

0.02%

0.03%

10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Flat Business License

Diagram H.4: Business tax based on Turnover or Income (Tanzania)


0.00%

0.25%

0.50%

10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Turnover Tax Tax on Business Income

Diagram H.6: Business Tax based on Labour Costs (Tanzania)


0.00%

0.05%

0.10%

0.15%

10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Tax on Wage and Salary Costs

Diagram H.7: Property Taxes (Tanzania)


0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

10-19 20-49 50-99 100-499 500+

Enterprise Size

% B

usin

ess

Inco

me

Land Tax Ad Valorem / Capital Improvements Flat Rate Property Tax

It is clear from these results that there are some significant problems with the underlying data used in the model. It may be possible to make some improvements on this data, by developing some assumptions of property ownership, property values and rentals for enterprises of different sizes with reference to other data sources.

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