Forecasting tax revenues: an overview

1. Forecasting tax revenues:an overview • Webinar for parliamentary budget offices • Rajul Awasthi • Global Tax Team • Europe and Central Asia Lead

2. Acknowledgment: • The content of this presentation is based on the materials provided by Professor Gangadhar P. Shukla, Professor of the Practice of Public Policy at Duke Center for International Development, Sanford School of Public Policy, Duke University. Prof. Shukla is also the Director of the Program on Tax Analysis and Revenue Forecasting (TARF).

3. CONTENTS • Introduction: the role of tax analysis • Objectives of revenue forecasting • GDP based methods • Monthly receipts model • Micro simulation models • GDP based micro simulation model for VAT • National accounts based • Input Output tables based • Micro simulation models for income taxes • Forecasting trade taxes

4. Typical Government Budget in its Simplest Form Expenditures Revenues (1) Administrative Overheads (1) Taxes (2) Recurring Costs (2) User fees, royalties, (Operations & Maintenance) other non-tax revenues (3) Capital Expenditures (3) SOE surplus or deficit (4) Transfers (4) Domestic or foreign (pensions, welfare payment) loan/bonds (5) Money creation (inflation)

5. challenges Hard to reduce administrative costs; reduction in costs of operations and maintenance causes deterioration in public services; transfers are statutory liabilities. In the short run, possible to borrow, sell assets; too much borrowing affects risk rating and inflation is undesirable; so in the long run a properly run tax system needed to raise sufficient revenues. Typical trade-off: Raise taxes Or Reduce capital expenditures (affecting long-term economic growth) and funds for maintenance of assets and operations of services.

6. FUNCTIONS OF A TAX ANALYSIS UNIT/PBO UNIT • Analyze the impact of alternative tax policies in terms of revenue and tax incidence • Analyze the impact of non-tax policies on revenues • Appraise revenue impact from economic changes – GDP growth or recession, inflation, deregulation, devaluation, changing trade patterns • Evaluate effect of changes in economic conditions of major trading partners • Forecast revenues • Measure tax effort

7. OBJECTIVES OF REVENUE FORECASTING • Initiating the Annual Budget Process • Estimating the Budget Deficit • Evaluating revenue impact from economic growth – GDP, productivity, labor force • Assessing Revenue Impacts of Policy Changes • Tax Policies • Non-tax Policies • Structural Changes • Computing effect of inflation on revenues • Measuring tax effort of tax administration

8. FORECASTING TAX REVENUES: overview of techniques • GDP based methods • Monthly receipts model • Micro simulation models • GDP based micro simulation model for VAT • National accounts based • Input Output tables based • Micro simulation models for income taxes • Forecasting trade taxes

9. GDP Based Estimating Models • A method for forecasting aggregate tax revenues • Forecast aggregate tax revenues as a function (dependent variable) of tax bases (independent variable), • First, estimate elasticity of tax revenues with respect to aggregate tax base using regression analysis and then use it for forecasting revenues in the future.

10. Tax Elasticity and Tax Buoyancy  Two important indicators used to estimate the changes in tax revenue with changes in GDP or any other tax base. An elastic system means that the government would be able to meet its expenditure needs over time as its GDP or consumption grows. If a system is buoyant but not elastic, it means we need to adjust the tax system (base, rate) to keep collecting enough revenues. These characteristics of a tax system are also useful in forecasting future tax revenues. If we know elasticity, then multiplying it with projected growth rate of GDP or another tax base will yield revenue forecast.

11. Tax buoyancy Tax buoyancy is the ratio of the percentage change in tax revenues (including changes in tax collection due to changes in tax base or tax rate, referred to as discretionary changes in tax policy) to percentage change in GDP.  To calculate tax buoyancy, the ex-post (including changes in tax rate/ base) percentage change in tax revenue is used.

12. Buoyancy – numerical example If: To = Tax Revenue in Year 2010 ($20 million); T1 = Tax Revenue in Year 2011 ($21 million) Y0 = GDP in Year 2010 ($100 million); Y1 = GDP in Year 2011 ($104 million); %T = (T1 – T0 )/T0 = 5%; Y = (Y1 – Y0 )/Y0 = 4%. Tax Buoyancy = 1.25 It means that for every 1% increase in GDP, the tax revenue would increase by 1.25%.

13. Tax Elasticity Tax elasticity is the ratio of percentage change in tax revenue, without any discretionary changes in tax rate or tax base, to the percentage change in GDP. The impact of a tax rate increase or a change in the tax base should be separated before calculating tax elasticity. As it is difficult to separate effects of changes in tax rate/ base on tax revenue, calculating elasticity is more difficult as compared to buoyancy. Tax Elasticity = %T1/%Y   where %T1 is percentage change in tax revenue if no discretionary changes were made in tax rate or tax base, and %Y is percentage change in GDP.

14. Elasticity – numerical example Numerical Illustration If in the preceding example, %T = 5%, %Y = 4% and the effect of change of tax rate and base on percentage change in tax revenue in the period is 1.20%; then %T1 (i.e. percentage change in tax revenue if no changes are made in the base or the rate) is 3.80% (5%-1.2%). Then, Tax Elasticity = 3.8% / 4% = 0.95

15. Buoyancy/elasticity of direct and indirect taxes Direct Taxes Buoyancy and elasticity of personal income taxes depends upon growth and distribution of income. If wage rates or per capita income are increasing, then the tax is buoyant as more individuals become taxable and move up to higher tax brackets. If high population growth leads to large numbers of low skilled, low wage workers, there is little increase in income tax, and the personal income tax will not be buoyant or elastic. Personal income tax will not be so elastic if there are wage increase restrictions, but inflation without indexing of the tax brackets increases the buoyancy of the personal income tax through “bracket creep.” The elasticity of corporate income tax system depends on whether growing sectors of the economy have been taxed or awarded tax breaks and incentives.

16. Buoyancy/elasticity of direct and indirect taxes Indirect Taxes Their elasticity depends mainly on whether there is a unit or ad valorem tax. As prices increase with inflation, unit tax would remain constant resulting in decrease in the ratio of tax revenue to GDP. In case of ad valorem tax, tax revenues increase in the same proportion as prices. Consumption does not necessarily increase proportionally with income. If family income rises and savings increase, a reduced proportion of this increased income would be spent on consumption of additional goods and services. As proportion of income spent on consumption falls with increasing income, elasticity of indirect taxes is typically les than one.

17. How to make a tax system elastic • Cover growing sectors of economy in tax base • Employ a progressive tax rate structure. • Prefer ad valorem to unit tax rates. • Cover commodities with higher income elasticity of demand. • Ensure the tax system is broad based and simple.

18. Forecasting with the Help of Tax Elasticity Construct data series for each tax for (a) tax revenues; (b) tax bases. Data series of tax receipts obtained from revenue collection agency; tax bases obtained from national accounts or state GDP accounts (wages and salaries for Personal income tax, private consumption for sales tax). Adjust tax revenue series by separating the increases in revenues caused by automatic growth in tax base from the increases that occur due to discretionary changes. (Normally the budget speeches provide estimates of revenue impact of tax policy changes.) Historical data series of tax revenues include both the impact of increases in tax base (income, expenditure) and discretionary changes in tax system (rates, exemptions).

19. Forecasting with the Help of Tax Elasticity, cont…. Identify the best tax base (proxy) for each tax using national accounts, i.e. find which component of tax base corresponds most closely to a particular tax. For personal income tax = f (wages, salary, bonuses, interest, dividend, rents, profits from un-incorporated businesses). In case of Sales Tax (VAT), adjusted revenues (ATn, ATn-1, ...) linked to total consumption expenditures on goods/services (Cn, Cn-1........). If sales tax (VAT) not levied on services, that component of consumption observed directly from the GDP and subtracted from Cn to best reflect the sales tax (VAT) base. If nothing else is available, GDP can be used as second best tax base for all taxes.

20. Forecasting with the Help of Tax Elasticity, cont…. Specify a functional relationship between the adjusted tax data (ATn) and the economic variable (selected proxy for tax base) using regression analysis (OLS): ATi = a + b * Bi where ATi is adjusted tax revenues and Bi is tax base in year i; a, b = constants (intercept and slope) to be estimated. Using this equation, tax elasticity may be estimated.

21. Forecasting with the Help of Tax Elasticity, cont…. Alternatively, same equation may be expressed in log terms, the coefficient of Bi (b1), directly yields tax elasticity: Ln ATi = a1 + b1 * Ln Bi  Sometimes, necessary to introduce dummy variables in the model to account for other relevant events affecting tax collection, e.g. a tax reform or economic downturn. For sales tax (VAT) forecasting, relevant equation would look like: Ln AT sales tax (vat) = a + b Ln Consumption (or GDP) + g D where D represents other relevant event affecting collection (major policy shift or shock like a tax reform, liberalization, drought, elections).

22. Forecasting with the Help of Tax Elasticity, cont…. Use above equation to forecast tax revenues in the future. Tax Revenue Next Year = (1+ Tax Elasticity*Percentage change in base) * Tax Revenue This Year

23. MONTHLY RECEIPTS MODEL Useful for monthly monitoring. A simple yet functional tool to project short-term revenues from major taxes, captures seasonal effect of tax collections and provides relatively accurate results. The model requires primarily monthly tax collection data, and projected GDP growth or other tax base proxy (consumption, imports) growth to forecast collections. The model takes into consideration the actual growth of the year-to-date tax collections as compared with that of the same period in the previous fiscal year and the projected growth of tax base proxies (GDP, private consumption, imports).

24. GROWTH FACTOR IN MONTHLY RECEIPTS MDOEL The growth factor, , is measured by a weighted average of two growth factors: (i) Actual growth of year-to-date receipts in the current fiscal year over that of the same months in the previous fiscal year; and (ii) Expected growth rate g of tax base proxies (e.g. GDP) in the current fiscal year. The weight for the first growth factor  is the fraction of the number of months for which taxes have been collected while the weight for the second growth factor (1-) is the number of remaining months.

25. MICRO-SIMULATION MODELS Micro-simulation Models: Not only provide better revenue estimates but useful for policy (impact) analysis too. VAT: Aggregate or National Accounts Approach Starting from Gross Domestic Product (GDP), VAT base estimated by subtracting exports and adding imports to reflect the domestic consumption (destination principle). Also, consumption-type VAT excludes wages and salaries paid to public servants and allows businesses to have input tax credit for capital investment, so the base is reduced by the amount of fixed gross capital formation. Further adjustments to the base made to account for zero-rated and exempt goods and services; for exempt goods and services, cascading effects also need to be accounted for.

26. GDP BASED MICRO-SIMULATION MODEL FOR VAT To estimate the VAT base under this approach, start with: GDP = Consumption + Gross Capital Formation + Government Expenditures + Exports – Imports Subtract: - Trade Balance (i.e., Exports – Imports) - Gross Capital Formation - Wages and Salaries in Government Sector - Zero-rated Consumption Expenditures - Exempt Consumption Expenditures - Imputed Rents for Owner Occupied houses - Commodity Indirect Taxes Replaced by VAT  Add: - Inputs Purchased by Exempt Sectors - New Residential Construction

27. GDP BASED MICRO-SIMULATION MODEL FOR VAT

28. GDP BASED MICRO-SIMULATION MODEL FOR VAT

29. DISAGGREGATE OR INPUT - OUTPUT APPROACH for vat Starting point is the detailed information available for domestic consumption, obtained by netting the personal and government expenditures abroad from their total expenditures contained in the “final demand matrix” of Input-Output tables. Only those domestic expenditures in the final demand categories that are meant for personal and government use, not those for the further production of goods and services for commercial purposes, are considered as final consumption. Useful in estimating revenues with multiple tax rates which is a common feature of VAT in developing countries. IO table is effectively a detailed breakdown of national accounts. Other data sources include household and industrial surveys.

30. DISAGGREGATE OR INPUT - OUTPUT APPROACH FOR VAT Start with: Domestic consumption expenditure by households on goods & services Subtract: - Zero-rated goods and services - Exempt goods and services - Commodity indirect taxes to be replaced Add: - New Residential Construction - Intermediate goods of exempt business activities This approach provides a useful tool for quantifying revenue implications of various tax policy measures. Also, it can be used to analyze the tax incidence, one-time price effect of introducing VAT and future VAT revenues.

31. DATA REQUIREMeNT FOR I-O MODEL • Main data source is input-output (I-O) tables. I-O tables are generally broken down into three components: • The “make” matrix provides a description of various commodities produced by each industry valued at producers’ prices. • The “use” matrix details total commodity inputs -- including intermediate inputs and primary inputs -- used by each industry to generate its output. • The “final demand” matrix contains commodity details for various final expenditure entities/categories.

32. DATA REQUIREMeNT, Cont. Generally, the other data needed to supplement information are: national accounts (NIA), household income-consumption surveys, trade margins, annual economic growth rates by sector. The expenditure categories include personal expenditures, business investments, government expenditures (current and capital expenditures), exports and imports, and government revenues from the sales of goods/services. Data contained in I-O tables usually expressed in terms of producer prices. The difference between producer and purchaser prices is due to trade margins and taxes. Purchaser Price = Producer Price + Wholesale and Retail Margins + Transportation Costs + Indirect Taxes

33. What is found where? GDP (market price) National Income Accounts (NIA) Trade balance (exports and imports) NIA Capital formation Gross domestic capital formation NIA New residential buildings NIA Capital formation in exempt sectors NIA Exempt sectors Value added of exempt sectors such as Financial sector NIA Add purchases of output from exempt sectors by taxed sectors IO table

34. What is found where? Cont. Government expenditure Government consumption and capital formation Budget, NIA Non taxed Government Expenditures Budget (exempt sectors, wages and salaries) Adjustment F: final private expenditure Exempt expenditures NIA, IO table Taxed inputs in exempt expenditures NIA, IO table Exemption threshold Minus sales of firms below threshold TAX Taxed inputs in above sales TAX Zero-rated Goods/Services TAX Collection leakage (compliance rate) TAX

35. MICRO-SIMULATION MODEL FOR INCOME TAXES Income Taxes: Personal income tax microsimulation models based on annual income tax returns, supplemented by surveys to cover non-filers. A typical taxpayer model calculates the tax liability of a typical individual (student, elderly person, couple with children, single person, or disabled person) or family. Typical taxpayer model follows the logic used to fill out the tax returns to calculate the income tax liability. In addition, this model simulates the impact of proposed policy changes on the tax liability of the individual taxpayer.

36. FORECASTING INCOME TAX REVENUES Forecasting Personal Income Tax (PIT) Revenues:  For revenue forecast, a sample of taxpayers and their tax liability is created using a sampling process and revenues are forecast based on expected growth rate of population, income etc. Corporate Income Tax (CIT): An approach similar to may be applied but CIT forecasting is more complicated due to provisions such as loss carry forward. As a consequence, GDP model may be more suitable.

37. TRADE TAX REVENUES Trade Taxes: There are two steps here: First, the change in revenue from year to year is a function of tax elasticity with respect to the base. In the case of imports, base is the imports and elasticity refers to the Tariff Revenue Elasticity (mr) with respect to the imports. Thus Revenue next year = Revenue this year * (1+mr * %imports). mr is determined by regressing real tariff revenues with respect to real imports in log terms. Second, determination of the rate at which imports will change over time (%imports). Imports being a part of consumption, its rate of change depends upon rate of growth of GDP and varies inversely with price of imports (import price index) compared to price level of GDP (GDP deflator)

38. FORECASTING trade TAX REVENUES %imports = %GDP * gdpm + %Pgdpm * pm where gdpm is elasticity of imports with respect to GDP. pm is import elasticity with respect to prices of imports relative to GDP. GDP is change in GDP and Pgdpm is change in the price of imports relative to GDP deflator.   These two elasticities are estimated by regressing time series of real imports with time series of real GDP and time series of relative prices, i.e. import price index divided by GDP deflator. The regression is done in the log form.

39. Thank you! rawasthi@worldbank.org