1. Jonathan Haughton Suffolk University, Boston Jonathan.haughton@suffolk.edu For the World Bank. May 11, 2011

2. 1. Who bears the burden of taxes? 2. Who benefits from government spending? 3. What are the net effects? 4. Who would gain/lose under different possible tax reform packages, and by how much? May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 2

3.  Central government tax revenue  11.6% of GDP in 2004  Buoyant since 2002  71% of revenue from indirect tax ▪ Vat: 19% rate; but yields just 4.9% of GDP  Income tax: 3.4% of GDP May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 3

6.  Revenue/GDP: 20% to 2000, now 25%  VAT: 7% of GDP (at 10% rate!)  Trade: from 4% to 2% of GDP, despite explosion of imports  All income tax: Peaked at 10% GDP in 2006, but dependent on SOE sector  NB: PIT raises 2% of revenue; surprisingly, not rising

8.  Step 1. Make assumptions about incidence  Statutory incidence ≠ Effective incidence  See Table May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 8

9.  VAT: on consumers  Excises: on consumers  PIT: on earners  Business profits: on earners  Other taxes: ▪ Property transfer; local fees and contributions: on payers. ▪ In this study, CIT, trade taxes, natural resource taxes, not included. Incidence covers half of revenue.

10. quantity supply S(1+t) price demand Pd2 Q1 Q2 P1 Ps2

11. quantity supply S(1+t) price demand Pd2 Q1 Q2 P1=Ps 2 What elasticity?

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13.  Step 2. Quantify the effects  Trace effect of a tax, spending change on every household in a survey  ENNIV 2000. 3,997 households, 19,957 people, LSMS template  NB. Assumes equal sharing within household May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 13

14.  Operationalize the analysis  Excel spreadsheet  Stata dataset and programs. Change spreadsheet; it invokes Stata, returns the results. May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 14

15.  9,189 households, including 4,298 from 2004 round.  Two visits per household; 93% of interviews in June, Sept or Oct.  Some explicit tax information (e.g. business taxes); otherwise has to be inferred (e.g. VAT, PIT).

16.  Socio-economic survey, 2009  47-page data dictionary  139,590 individuals  From 43,844 households ▪ Aside: US 1% IRS file plus non-filers: c. 150,000 filers.

17.  19% rate. Fairly stable since 1992.  Exports zero rated  Exemptions include clothing, rice, milk, fish, vegetables, ed. fees, home consumption, housing  In 2000:  42% of central gov. tax revenue  Collected 7.3% of household expenditure. May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 17

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20. Regressivity probably overstated, if poor are more likely to buy in informal sector  By expenditure/cap: slightly regressive  By income/cap: highly regressive May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 20

21.  Income:  Easy to measure  Widely used in developed countries  Overstates regressivity: “lifetime income”  Expenditure  Less underreporting than income  Closer to “permanent income”  May understate regressivity May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 21

22.  In 2000, summarized:  Alcohol, especially beer (t=27.8% of 84% of rec. prodr. price)  Soft drinks (t=17% ex factory)  Cigarettes (t=37.2%)  New vehicles (t=10%)  Motor fuel ▪ Gasoline (S/.2.90 per gallon) ▪ Diesel S/.2.29 per gallon) May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 22

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25. Expend/cap: Kakwani (>0 = progressive) Income/cap: Revenue as % of all tax revenue Actual revenue as % of estimated Alcohol0.057-0.1103.6213 Soft drinks -0.105-0.2830.6127 Tobacco-0.0030.5170 May 11, 2011 JH: Tax & Expenditure Incidence in Peru Page 25 Note under-reporting of expenditures

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27. Expend/cap: Kakwani (>0 = progressive) Income/cap: Revenue as % of all tax revenue Actual revenue as % of estimated Motor fuel 0.3780.2469.3732 Vehicles0.4120.2881.0225 May 11, 2011 JH: Tax & Expenditure Incidence in Peru Page 27 Notes: Fuel numbers overstate progressivity, because of the “bus and truck problem” Vehicle numbers assume purchases in proportion to ownership, which is awkward Ideal is to run this through an input-output table

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37.  In Vietnam, incidence pattern by expenditure/cap decile similar to that by income/cap  Contrast with Peru  These taxes are progressive overall  Heavier, more progressive, than 1998  VAT is generally progressive – mainly due to home production (1/3 at bottom, 1% at top); not the case in all countries  Excise taxes are progressive – also a bit surprising.

39.  Regional effects  Personal Income Tax  Property Tax  Expenditure incidence  Marginal full incidence  Policy reforms

40.  Higher tax rates in south  Highest rate in South-Central Coast (sampling error?)  Urban/rural gap in burden is surprisingly small

43.  Method: strip out business income tax and PIT, and apply rules of new tax  Revenue: from VND127k to VND21k per person.  New tax highly progressive.  But: excludes foreigners; very small sample size for PIT and for large household enterprises.

44.  Done by General Dept. of Taxation in 2005, using tax rolls  Survey, asking about income, spending  15,500: 3,200 foreign, 7,200 PIT, 5,100 business income tax  11,535 responses (74%); low in HCMC, among foreigners. Results re-weighted.  Anything equivalent in Thailand?

46.  Based on 2009  NB. PIT very elastic  Total revenue: -5% ▪ Foreigners: down by a quarter ▪ Vietnamese: tax payments up  Reconcile with VHLSS data  High-income individuals would pay more  Not-so-high income individuals would pay less, and not be in the tax net as much  Difficult to merge the two; in progress.  Keep: taxes foreigners, adds equity. Enforcement could be better. Perhaps limit top rate to top CIT. Adjust brackets for inflation (as in US).

47.  VHLSS has limited data on property:  Residence; non-agric. real estate  Assume tax would not apply to agricultural property, or to movable property.  1% of capital value; arbitrary

49.  Highly progressive  1% is steep; 7.8% of expenditure, so politically infeasible at this level.  Cash flow concerns  Based on bubble prices?  Introduction of tax would reduce base  Excludes corporate ownership

51.  Applied to education, health, targeted social programs  Step 1: Measure unit subsidies  Step 2: Identify coverage  Step 3: Present results May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 51

52.  In 2000 ▪ 98.8% of children 7-10 were at school ▪ 94% of 14-year-olds were at school ▪ 13% of pupils/students were at private schools  Costs ▪ Pre-K: S/. 583 per child per year ▪ K & primary: S/. 386 ▪ Secondary:S/. 624 ▪ Tertiary:S/.2,506  Assigned based on attendance May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 52

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54. May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 54 “progressive but not well-targeted”

56.  Cost of procedures  Used ENNIV-2000 reported data on cost at private facilities  Adjusted downwards substantially to be consistent with government spending ▪ Cost/consultationS/. 0.75/minute ▪ Cost of hospitalizationS/. 75/night ▪ Cost of an analysisS/. 6.2/item May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 56

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59.  Allocated based on reported usage May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 59

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62.  System seems progressive overall  But ▪ Some taxes not included (e.g. CIT) ▪ Not all spending can be included ▪ Rely on our incidence assumptions May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 62

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65.  Addresses question:  If a tax were raised, and spending increased as a result, what would effect be on incidence?  Step 1: Estimate effect of more tax revenue on spending  Step 2: Simulate effect of higher VAT in Peru May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 65

66.  Estimated using regression of form  i.e. spending/GDP (y) is a function of tax revenue/GDP (x)  Panel Data: 16 Latin American countries, 1980-2002. “Fixed effects” estimates. May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 66

67. May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 67 Note: Low marginal effects for education, health No marginal effect for interest payments High marginal effects for social spending

68.  2000: assume VAT from 18% to 19%  Of extra revenue: ▪ Education takes 7.6% ▪ Health takes 7.3% ▪ Social subsidies take 28.4% ▪ Remaining spending not allocable May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 68

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70.  A higher VAT need not hurt the poor  Result is robust to whether we use expenditure/cap or income/cap to sort households May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 70

71.  Greater disaggregation of spending  Sensitivity to assumptions about incidence  Source of purchases/evasion  Better treatment of transport  Use income tax data  Add social security pensions May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 71

72.  Confidence intervals (bootstrapping?)  Create integrated “calculators”; and do it in-house  Need better access to primary data  Adjust for quality/value of benefits  Theory: why income/cap results differ so much from expend/cap results ▪ Measurement error (Deaton)/permanent income May 11, 2011JH: Tax & Expenditure Incidence in PeruPage 72

77. jonathan.haughton@suffolk.edu