Impact Assessment of Personal Income Tax Reduction in the PhilippinesInstitute for Development and Econometric Analysis (IDEA), Inc.July 2014Executive SummarySenate Bill 2149 seeks to reduce the current income tax brackets from seven down to five and gradually adjust tax rates within the next three years in line with inflation. The lowest income bracket under the proposal will be PhP20,000 (from PhP10,000) with a tax rate of 10 percent and the highest will be PhP1,000,000 (from PhP500,000) with a tax rate of 25 percent by January 2017.

The proposal has been put forward in light of ongoing progress towards greater regional integration and a concern for the outmigration of human resources, with implications economic and competitiveness implications. Neighboring countries such as Malaysia and Thailand are already in the process of reducing income taxes while the Philippines continues to have one of the highest income tax rates in the region.

A countrys tax system plays a key role in determining its competitiveness through the effects of its various aspects on economic decision-making. More than the magnitude of tax changes, there is also the question of who effectively bears the tax burden and how this affects their behavior. Thus, any tax reform proposal needs to properly account for its redistributive and welfare effects on the overall economy.

There are reservations that lowering tax rates would result in significant reduction in government tax revenues. This paper reviews the literature on the economic impact of tax changes and develops a simultaneous equations model to describe how consumption and labor supply react to changes in income taxes using data from merged surveys on the labor force and income and expenditures.

Evaluating the evidence, the emerging consensus is that taxes generally have a negative impact on output growth. The specific mechanisms and channels by which taxes affect the economy are not clear-cut. Income taxes in general, and corporate taxes in particular, have the largest effects on firm and household decisions and are thus more likely to adversely affect economic outcomes. There is evidence that while cutting personal income taxes leads to a fall in tax revenues, it can also stimulate the economy in the short run. Tax cuts also raise employment, consumption and investment, though the evidence is mixed with some studies finding the increases to be insignificant, small, or moderate at best.

Using available household survey data, we analyze the effects of income tax changes on household consumption and labor supply using a simultaneous equations model. We find that the relationships between our variables are in line with economic theory, affirming the progressive nature of the income tax system and the negative effect of income taxes on spending and working hours. On the basis of such results, it appears that a reduction in PIT rates would be beneficial to households in terms of 1) increasing consumption spending as measured by total household expenditures, and 2) increasing labor supply as measured by total hours worked.IntroductionThe Philippines currently has one of the highest personal income tax (PIT) rates among the member states of the Association of Southeast Asian Nations (ASEAN) at 32 percent. Progress towards regional integration through the ASEAN Economic Community (AEC) has prompted some member states to begin lowering income tax rates with the end in view of preserving country competitiveness in the regional marketplace. A countrys system of taxation plays an important role in determining country competitiveness. The Organisation for Economic Co-operation and Development or OECD (2010) notes that various aspects of the tax system such as the taxes raised, the tax mix, the quality of tax administration, the complexity of the tax rules and the tax compliance costsand the broadness of the different tax bases can have an impact on the countrys rate of economic growth.

Any tax reform proposal needs to take into consideration the redistributive effects of tax changes and their welfare effects (Haughton and Khandker, 2009). Income taxes in general, and corporate income taxes (CIT) in particular, have the largest effects on firm and household decisions and are thus more likely to negatively impact welfare outcomes. A tax system that promotes economic growth, therefore, is one that shifts the burden of taxation from income to consumption or residential property, broadens the tax base, and lowers the tax rate (OECD, 2010).

This motivates current moves to amend domestic income tax rates in the Philippines, in view of the expected increase in the mobility of people in the region and the continued growth in the number of overseas Filipino workers.In particular, Senate Bill (SB) 2149 seeks to reduce the current seven-tier income tax brackets of the graduated individual tax rates to five tiers, with tax rates gradually adjusted in the next three years to the current consumer price index. Moreover, the lowest income bracket under the proposal will be PhP20,000 (from PhP10,000) with a tax rate of 10 percent and the highest at PhP1,000,000 (500,000) with a tax rate of 25 percent by January 2017.

There are reservations, however, that lowering the PIT would result in direct reduction ingovernment tax revenues. This paper looks at the case, under certain conditions, when lowering PIT can still incitegrowth in government tax revenues through increased consumption and labor supply.This paper proceeds with the review of the literature on the economic impact of tax changes including that of PIT in particular, as well as the arguments for and against the proposed tax amendments. Cross-country-comparisons, specifically among ASEAN member countries, are presented for benchmarking purposes as applied to the Philippine situation. A simultaneous equation model was developed to describe how consumption and labor supply behaviors react to changes in income tax.The model was tested using data from merged surveys on income and expenditure and labor force. This paper ends with concluding remarks. Review of LiteratureThe issue of taxation and its effects on the economy remains a hotly debated topic and the arguments for and against increasing (or decreasing) taxes are well-known by now. It appears, however, that the consensus is that taxes generally have a negative impact on aggregate economic growth though the evidence on the specific mechanisms and various channels by which taxes affect the economy are not clear-cut. In a comprehensive paper on tax policy reform and economic growth, the OECD (2010) notes that it is income taxes, particularly CIT, that have the most adverse effect on per capita gross domestic product (GDP) growth. This is followed by PIT, consumption taxes, and, lastly, recurrent taxes on immovable property. They conclude that ideal growth-oriented tax reforms are those that shift part of the tax burden from income to consumption or residential property. The motivation behind these findings involves not only the magnitude of the tax changes, but also the question of who effectively bears the taxes and how this affects their behavior. In general, the least harmful taxes are those that have a smaller adverse effect on the economic decisions of individuals and firms. In this sense, indirect taxes are less likely to affect individual economic decision-making and therefore result in smaller welfare losses as compared to direct types of taxation such as income taxes. Following neo-classical economic theory, income taxes are effectively taxes on the factors of production, i.e. labor and capital. They serve as additional costs imposed on the production of goods and services and thereby the creation of income and wealth. Thus, McBride (2012) argues that corporate taxes discourage investment, resulting in lower labor productivity and therefore lower wages. He adds that progressive taxes on labor income not only reduce the incentive to work, but also diminish the returns to education. This has negative implications on the build-up of human capital, as well as on entrepreneurial activity given that high-income earners account for a large share of these activities. The OECD (2012) supports the view that increases in PIT top rates may reduce working hours and productivity by reducing the incentive for work, investment, and innovation.There is considerable empirical evidence on the negative effects of income taxes on the macroeconomy. For a condensed overview of the literature, refer to the summary table (Table 1) by McBride (2012).

Leigh et al (2010) estimate the short-term growth effects of fiscal consolidation using data on advanced economies over the past 30 years. They also employ simulations to investigate its long-term effects. They find that fiscal contraction using tax-based adjustments, i.e. tax hikes, have greater contractionary effects than the use of spending cuts. Their simulation assumes that savings from debt reduction is used to finance reductions in labor income taxes. Such reductions are expected to raise labor supply and output since taxes on labor income discourage workers from supplying labor.

The simulation results suggest that using the savings from fiscal consolidation to reduce income taxes has a beneficial impact on GDP in the long run, more so in the case of CIT over PIT a reflection of capital income taxes strong negative effect on private sector investment. Nonetheless, reducing labor income taxes still results in an average of 1.02 percent increase in global GDP, with the top advanced economies (i.e. the United States, the Euro area, and Japan) benefiting the most.In an attempt to more directly evaluate the effect of taxes on GDP, Romer and Romer (2010) use a new measure that incorporates all legislated tax changes as a percentage of nominal GDP. They find that a tax increase equivalent to one percent of GDP has a consistently negative effect on the path of real GDP. With a maximum effect of a 3.08 percent decrease in output after ten quarters, they conclude that tax increases have a very large, sustained, and highly significant negative impact on output or alternatively, that tax cuts have very large and persistent positive output effects.Furthermore, their work suggests that the output effect of tax changes are tied to the actual changes in taxes rather than to news about planned or future changes. The evidence supports the assertion that the main channel through which tax changes affect GDP is through a sharp fall in investment. When it comes to PIT, in particular, Barro and Redlick (2011) also construct their own time series to measure average marginal income tax rates and reveal evidence that increased tax rates have significantly negative effects on GDP. Specifically, a one-percentage-point (ppt) reduction in the average marginal income tax rate boosts next years per capita GDP by 0.5 percent. They argue that marginal income tax rates have substitution effects, which affect decisions on work versus consumption, the timing of consumption, and investment, among others. In turn, these effects on economic behavior ultimately influence GDP and other macroeconomic aggregates. Mertens and Ravn (2013) find that cuts in personal income taxes lead to a fall in tax revenues while corporate income tax cuts have little impact on the average. Cuts in the former raise employment, consumption, and investment, while cuts in the former boost investment and do not affect private consumption and employment. Notably, a reduction in the average PIT rate stimulate output in the short run: there is a significant increase in economic activity within two-years after the tax cut. More precisely, a one-ppt decrease in the average PIT rate increases output by 1.4 percent in the first quarter after the reduction, up to a 1.8 percent increase three quarters after the tax cut. Others, however, support the view that reducing income taxes are not necessarily beneficial to economic growth. Using simple numerical examples of various tax cuts, Charney (2012) calculates the size of the multipliers needed for a tax cut to grow the economy such that the foregone revenue is more than made up for by increased economic activity. She does the hypothetical estimates for the state of Arizona for individual income and sales taxes. This is in response to common arguments in favor tax cuts that tax cuts will grow the economy and will therefore pay for themselves, with the implication that there will be no corresponding reduction in public services or expenditures. The results show that the multipliers necessary for tax cuts to pay for themselves are extraordinarily high and substantially out of the range of any multipliers computed for the type of sectors in which consumers spend. It is simply not reasonable to believe to tax rate cuts will not reduce the amount of revenue collected by the state. Instead, tax rate cuts will reduce revenues by almost the full amount implied by the rate cut.

This is not to say tax cuts have no impact on the economy, however. Charney (2012) finds a small stimulative effect, but even this is likely to be offset if the negative effects of tax cuts on state spending are taken into account. Thus, if the economic effect of reduced government expenditures exactly offset the stimulative effect of the tax cut, then revenues fall by the full amount of the tax cut. If the effect of reduced government expenditures is greater than the stimulative effect, then revenues will decline by more than the implied amount of the tax cut. In an empirical investigation of the recovery of the United States (U.S.) economy in the 1980s, the Congressional Budget Office (1989) concludes that contrary to popular belief, it was not the tax cuts under the Reagan administration that drove U.S. economic growth during the period. Rather, it was expansionary monetary policy that was behind the economic expansion with corporate tax cuts in 1981 playing a limited role through stimulating business investment. In a similar vein, Hungerford (2012) notes that advocates of lower tax rates argue that reduced rates would increase economic growth, increase saving and investment, and boost productivity while proponents of higher tax rates argue that higher tax revenues are necessary for debt reduction, that tax rates on the rich are too low and that high tax rates on the rich would moderate increasing income inequality. He concludes, however, that analysis of U.S. data since 1945 implies that reducing tax rates on the rich has little association with saving, investment or productivity and that these top tax rates are associated with increasing income concentration at the top of the income distribution. The methodology of the above-mentioned study, however, has been questioned. McBride (2012) criticizes the use of the top statutory marginal tax rate as a measure of taxes as the composition of those who pay the said taxes changes over time. The results also run counter to the evidence from the literature, citing for instance, that the OECD has found that progressivity of income taxes, i.e. shifting the tax burden to high income earners, is associated with lower economic growth. Hungerford (2012), in turn, also cites relevant literature to support his claims. On CIT, he agrees with the consensus that corporate taxes have a negative economic impact, citing Ferede and Dahlby (2012) who find that a higher CIT rate is associated with lower private investment and slower economic growth using Canadian panel data from 1977-2006. Moreover, a one-ppt reduction in the corporate tax rate yields a 0.1-0.2-ppt increase in the annual economic growth rate.Ferede and Dahlby (2012) explain that taxes can affect growth through their impacts on factor accumulation and total factor productivity. In the first channel, taxes raise the cost of capital and thereby reduce the incentive to invest and ultimately dampen economic growth. Citing Feldstein (2006), they also argue that taxes distort factor prices and induce efficiency loss in resource allocation. Moreover, taxes also affect entrepreneurial activity, which is a source of new ideas and innovations.On PIT, Hungerford (2012) refers to the work of Lee and Gordon (2005) who also find a negative association between corporate tax rates and economic growth. They note, however, that the effect of the top PIT rate is insignificant, suggesting that adjustments to the said rate may not significantly affect aggregate economic output growth. This echoes earlier work by Katz, Mahler, and Franz (1983). One criticism for cross-country studies like these, however, is that income tax bases are defined differently across countries and as such the effects of any tax-growth analysis may not be directly comparable. This motivated Ferede and Dahlby (2012) to use Canadian provincial with similar income tax bases in to investigate the effects of tax rates on growth.In sum, it appears that the contention is not whether taxes in general, or even income taxes in particular, negatively impact on growth, but rather the significance of the effect of PIT especially vis--vis other taxes. It becomes clear that most studies find a negative association between CIT and economic growth, but the evidence is more mixed in the case of PIT. Reviewing the literature on PIT, Jappelli and Pistaferri (2010) cite a series of papers by Shapiro and Slemrod that use instant-survey data to measure individual responses to actual or hypothetical tax policies. Analysis of U.S. tax cuts in 1992, 2001, and 2008 reveals that a temporary tax change has, at best, only a moderate effect in terms of increasing household spending. Also citing Johnson et al (2006), they note that an evaluation of the 2001 tax rebates in the U.S. shows that the average household spent 20-40 percent on consumption goods practically the same range of estimates by Shapiro and Slemrod. Johnson et al (2006), however, find that expenditure responses tend to be higher for households with low income or low liquid wealth.In his own review of the evidence on PIT, Rider (2006) explains that while governments use progressive PIT rate structures to address income inequality, there is evidence that high state PIT rates in the U.S. negatively affect business and individual decisions, which in turn dampen state growth rates. An important assumption behind this reasoning is that labor and capital are mobile, and that they respond to tax differentials among states. Moreover, he argues that taxes do not stick where they are legally placed. In response to high PIT rates, individuals may reduce their work effort, migrate to states with lower rates, or exert efforts to reduce PIT liabilities. Firms, in turn, may have to compensate their employees for the higher costs associated with high tax rates with implications for wage rates, consumer prices, and other associated costs. Thus, employees are able to shift out the PIT burden, either in part or in full, to their employers. Economic decision-making by employers or firms are, in turn, affected. Some firms may choose to invest less in high-PIT rate states or simply relocate to states with lower PIT-rates. Rider (2006) also contends that differences in state PIT rates are an important determinant of pre-tax wage differences, which influence location decisions of plants and facilities. In this regard, high state PIT rates negatively affect plant and facilities location decisions, foreign direct investment (FDI), capital investment, firm location, state employment, and personal income.Note, however, that the above analysis applies only to the U.S. where there appears to be a high degree of mobility of labor and capital among the different states. The results of the said analysis do not necessarily apply to different countries or even the member states of ASEAN despite moves towards regional integration. Unlike the U.S., for instance, ASEAN does not operate under a single currency or a single central government that determines common or at least similar governance or regulatory frameworks for various aspects of economic life. With regard to the issue of tax rates and compliance, the evidence is also mixed though the general consensus appears to support the view that higher tax rates reduce compliance. In theory, the basic model of individual choice posits that a higher tax rate decreases disposable income and encourages people to under-declare their taxable income. But such an outcome is also influenced by an individuals risk preference. If an individual exhibits decreasing absolute risk aversion, then the lower income brought about by a higher tax rate decreases the return to cheating on taxes. As a result, such people would rather comply with than under-declare their tax obligations (Allingham and Sandmo, 1972). Yitzhaki (1974) shows that a higher tax rate increases declared income when the penalty rises in proportion to the rate of evaded taxes.The model, however, has undergone numerous refinements and extensions that complicate the analysis and makes it extremely difficult to tease out definite analytical results on the effect of tax rate changes on compliance. In terms of empirical evidence, the evidence favors the negative effect of higher tax rates on compliance with an estimated under-reported income-tax rate elasticity ranging from -0.5 to -0.3 (Alm, 1998). For more on this, see Clotfelter (1983), Crane and Nourzad (1992), Slemrod (1985), etc. There are other studies, however, that depart from the above-mentioned results. Feinstein (1991), for instance,finds no significant relationship between marginal tax rates and non-compliance. Others provide evidence for the role of risk aversion in influencing the relationship between tax rates and compliance. Plumley (1996) shows that the effects of an increase in marginal tax rates differ among income groups. Low-income individuals who are typically more risk-averse become more compliant in response to an increase in marginal tax rates. This is because the penalties for under-reporting their taxable income comprise a greater proportion of their net income rather than those with higher income; in other words, they have much more to lose from being caught cheating on their taxes. In contrast, high-income individuals were found to increase non-compliance by decreasing their reported income and increasing their tax offsets though the effects are only marginally significant. In light of the prevailing knowledge, many countries have decided to cut income tax rates while broadening the tax base, especially for corporate taxes (OECD, 2010). There has also been a shift towards greater adoption and higher rates of VAT, though the same cannot be said for indirect taxes in general. There also appears to be increasing preferential tax treatment for small and medium enterprises (SMEs) and research and development (R&D) activities among OECD members.Lastly, it is worth emphasizing that aside from the economic evidence, one also needs to take political economy considerations into account. As Haughton and Khandker (2009) would pose the question, A tax system with a lower VAT and higher personal income tax might be more equitable than the current arrangements, but why is the current system , rather than a more equitable one, in place? Tax systems are as much a product of political forces as they are of economic motivations. While the prevailing knowledge and evidence may provide broad guides, each country will have to take into account its own unique circumstances and idiosyncrasies and find the best fit. Table 1. Summary of Empirical Studies on the Effects of Taxes on Economic Growth

ReferenceMethod/DataEffectsSummary of Findings

1ErgeteFerede& Bev Dahlby,The Impact of Tax Cuts on Economic Growth: Evidence from the Canadian Provinces, 65 National Tax Journal 563-594 (2012).Canadian provinces (1977-2006)NegativeReducing corporate income tax 1 percentage point raises annual growth by 0.1 to 0.2 points.

2KarelMertens& Morten Ravn,The dynamic effects of personal and corporate income tax changes in the United States, American Economic Review (forthcoming) (2012).U.S. Post-WWII exogenous changes in personal and corporate income taxesNegativeA 1 percentage point cut in the average personal income tax rate raises real GDP per capita by 1.4 percent in the first quarter and by up to 1.8 percent after three quarters. A 1 percentage point cut in the average corporate income tax rate raises real GDP per capita by 0.4 percent in the first quarter and by 0.6 percent after one year.

3Norman Gemmell, Richard Kneller, & Ismael Sanz,The Timing and Persistence of Fiscal Policy Impacts on Growth: Evidence from OECD Countries, 121 Economic Journal F33-F58 (2011).17 OECD countries (Early 1970s to 2004)NegativeTaxes on income and profit are most damaging to economic growth over the long run, followed by deficits, and then consumption taxes.

4Jens Arnold, Bert Brys, Christopher Heady, sa Johansson, CyrilleSchwellnus, & Laura Vartia,Tax Policy For Economic Recovery and Growth, 121 Economic Journal F59-F80 (2011).21 OECD countries (1971 to 2004)NegativeCorporate taxes most harmful, followed by taxes on personal income, consumption, and property. Progressivity of PIT harms growth. A 1 percent shift of tax revenues from income taxes (both personal and corporate) to consumption and property taxes would increase GDP per capita by between 0.25 percent and 1 percent in the long run. Corporate taxes, both in terms of the statutory rate and depreciation allowances, reduce investment and productivity growth. Raising the top marginal rate on personal income reduces productivity growth.

5Robert Barro& C.J. Redlick,Macroeconomic Effects of Government Purchases and Taxes, 126 Quarterly Journal of Economics 51-102 (2011).U.S (1912 to 2006)NegativeCut in the average marginal tax rate of one percentage point raises next years per capita GDP by around 0.5%.

6Christina Romer& David Romer,The macroeconomic effects of tax changes: estimates based on a new measure of fiscal shocks, 100 American Economic Review 763-801 (2010).U.S. Post-WWII (104 tax changes, 65 exogenous)NegativeTax (federal revenue) increase of 1% of GDP leads to a fall in output of 3% after about 2 years, mostly through negative effects on investment.

7Alberto Alesina& Silvia Ardagna,Large changes in fiscal policy: taxes versus spending,inTax Policy and the Economy, Vol. 24 (Univ. of Chicago Press, 2010).OECD countries (fiscal stimuli and fiscal adjustments, 1970 to 2007)NegativeFiscal stimuli based upon tax cuts more likely to increase growth than those based upon spending increases. Fiscal consolidations based upon spending cuts and no tax increases are more likely to succeed at reducing deficits and debt and less likely to create recessions.

8International Monetary Fund,Will it hurt? Macroeconomic effects of fiscal consolidation,inWorld Economic Outlook: Recovery, Risk, and Rebalancing (2010).15 advanced countries (170 fiscal consolidations over the last 30 years)Negative1% tax increase reduces GDP by 1.3% after two years.

9Robert Reed,The robust relationship between taxes and U.S. state income growth, 61 National Tax Journal 57-80 (2008).U.S. states (1970-1999, 5 year panels)NegativeRobust negative effect of state and local tax burden. Multi-year panels mitigate misspecified lag effects, serial correlation, and measurement error.

10N. Bania, J. A. Gray, & J. A. Stone,Growth, taxes, and government expenditures: growth hills for U.S. states, 60 National Tax Journal 193-204 (2007).U.S. statesNegativeTaxes directed towards public investments first add then subtract from GDP.

11Young Lee & Roger Gordon,Tax Structure and Economic Growth, 89 Journal of Public Economics 1027-1043 (2005).70 countries (1980 - 1997, cross-sectional and 5 year panels)NegativeReducing corporate income tax 1 percentage point raises annual growth by 0.1 to 0.2 points.

12Randall Holcombe & Donald Lacombe,The effect of state income taxation on per capita income growth, 32 Public Finance Review 292-312 (2004).Counties separated by state borders (1960 to 1990)NegativeStates that raised income taxes averaged a 3.4% reduction in per capita income.

13Marc Tomljanovich,The role of state fiscal policy in state economic growth, 22 Contemporary Economic Policy 318-330 (2004).U.S. states (1972 to 1998, multi-year panels)NegativeHigher tax rates negatively affect short run growth, but not long run growth.

14Olivier Blanchard & Robert Perotti,An Empirical Characterization Of The Dynamic Effects Of Changes In Government Spending And Taxes On Output, 107 Quarterly Journal of Economics 1329-1368 (2002).U.S. Post-WWII (VAR/event study)NegativePositive tax shocks, or unexpected increases in total revenue, negatively affect private investment and GDP.

15F. Padovano& E. Galli, E.,Tax rates and economic growth in the OECD countries (1950-1990),39 Economic Inquiry 44-57 (2001).23 OECD countries (1951 to 1990)NegativeEffective marginal income tax rates negatively correlated with GDP growth.

16Stefan Folster& Magnus Henrekson,Growth effects of government expenditure and taxation in rich countries, 45 European Economic Review 1501-1520 (2001).Rich countries (1970 to 1995)NegativeTax revenue as a share of GDP negatively correlated with GDP growth.

17M. Bleaney, N. Gemmell& R. Kneller,Testing the endogenous growth model: public expenditure, taxation, and growth over the long run, 34 Canadian Journal of Economics 36-57 (2001).OECD countries (1970 to 1995)NegativeDistortionary taxes reduce GDP growth. Consumption taxes are not distortionary.

18R. Kneller, M. Bleaney& N. Gemmell,Fiscal Policy and Growth: Evidence from OECD Countries, 74 Journal of Public Economics 171-190 (1999).OECD countries (1970 to 1995)NegativeDistortionary taxes reduce GDP growth.

19Howard Chernick,Tax progressivity and state economic performance, 11 Economic Development Quarterly 249-267 (1997).U.S. states (1977 to 1993)NegativeProgressivity of income taxes negatively affects GDP growth.

20Enrique Mendoza, G. Milesi-Ferretti, & P. Asea,On the Effectiveness of Tax Policy in Altering Long-Run Growth: HarbergersSuperneutrality Conjecture, 66 Journal of Public Economics 99-126 (1997).18 OECD countries (1965-1991, 5 year panels)NoneEstimated effective tax rates on labor and capital harm investment, but effect on growth is insignificant. Effective consumption taxes increase investment, but not growth. Overall tax burden levels have no effect on investment or growth.

21Stephen Miller & Frank Russek,Fiscal structures and economic growth: international evidence, 35 Economic Inquiry 603-613 (1997).Developed and developing countriesNegativeTax-financed spending reduces growth in developed countries, increases growth in developing countries.

22John Mullen & Martin Williams,Marginal tax rates and state economic growth, 24 Regional Science and Urban Economics 687-705 (1994).U.S. states (1969 to 1986)NegativeHigher marginal tax rates reduce GDP growth.

23William Easterly & S. Rebelo,Fiscal Policy and Economic Growth: An Empirical Investigation, 32 Journal of Monetary Economics 417-458 (1993).Developed and developing countriesNoneEffects of taxation difficult to isolate empirically.

24Reinhard Koester & Roger Kormendi,Taxation, Aggregate Activity and Economic Growth: Cross-Country Evidence on Some Supply-Side Hypotheses, 27 Economic Inquiry 367-86 (1989).63 countriesNegativeControlling for average tax rates, increases in marginal tax rates reduce economic activity. Progressivity reduces growth.

25Jay Helms,The effect of state and local taxes on economic growth: a time series-cross section approach, 67 Review of Economics and Statistics 574-582 (1985).U.S. states (1965 to 1979)NegativeRevenue used to fund transfer payments retards growth.

26Claudio J. Katz, Vincent A. Mahler & Michael G. Franz,The impact of taxes on growth and distribution in developed capitalist countries: a cross-national study, 77 American Political Science Review871-886 (1983).22 developed countriesNoneTaxes reduce saving but not growth or investment.

Source: Lifted from McBride (2012)

Tax Comparisons Across ASEANIn the ASEAN Tax Guide, KPMG International (2013) notes that differences in taxes become a point of differentiation among the member states of ASEAN as they seek to attract foreign direct investment (FDI). While there may be more pertinent issues that influence investment decisions, e.g. bureaucracy, corruption, infrastructure, etc., the fact is that ASEAN countries have traditionally used tax rates and other financial incentives to compete against each other. This policy preference is likely to persist, notwithstanding efforts towards regional integration.The report notes that corporate taxes in the region have shown a declining trend over the last fifteen years, with a marked fall in rates with the signing of the AEC Blueprint in 2007. More recently, Thailand decided to reduce its CIT rate to 20 percent and its maximum PIT rate to 35 percent effective last year (see Table 2). Malaysia is also set to cut income taxes by one ppteach for PIT and CIT effective on 2015 and 2016, respectively. Nonetheless, there are still significant differences in taxes among member countries and no drastic changes are seen without a concerted regional effort at harmonizing tax regimes. Table 2. Thai Personal Income TaxAnnual Taxable Net Income, THBPersonal Income Tax Rate, 2012New Personal Income Tax Rate, 2013

0 150,000NilNil

150,001 300,00010%5%

300,001 500,00010%10%

500,001 750,00020%15%

750,001 1,000,00020%20%

1,000,001 2,000,00030%25%

2,000,001 4,000,00030%30%

4,000,001 or more37%35%

Source: Lifted from Respondek& Fan (2014)

A cursory look at the comparative taxes in ASEAN reveals that the Philippines has one of the highest PIT rates in the region. The maximum PIT tax rate of 32 percent in the country is higher than Indonesia, Malaysia, Laos, Cambodia, Singapore, and Brunei. Only Thailand, Myanmar, and Vietnam have higher tax rates, though the differences is only three ppts (refer to Table 3). Moreover, the Philippines also has the highest tax rates for withholding tax (on dividends, interest, and royalties) and indirect taxes with a value-added tax (VAT) rate of 12 percent. Table 3. Comparison of ASEAN TaxesCountryStandard Corporate Income Tax RateTop Personal Income Tax RateNon-resident Withholding Tax RatesIndirect Tax (i.e. VAT/GST) Standard RateCapital Gains

DividendsRoyaltiesInterest

Brunei20%No personal tax on individuals.None10%15%No VAT or consumption-based tax systemNo capital gains tax

Cambodia20%20%14%14%14%10%No separate capital gains tax. Capital gains are treated as taxable income, subject to 20% profit tax.

Indonesia25%30%20%20%20%10%Subject to tax

Laos24%24%10%5%10%10%No capital gains tax

Malaysia25%. Reduces to 24% from YA 2016.26%. Reduces to 25% from YA 2015.None (assuming single tier dividend)10%15%Service tax: 6%. Sales tax: Generally 5% or 10%. GST of 6% will be introduced from 1 April 2015No capital gains tax other than on the disposable of interests in Malaysian real property or shares in a Real Property Company.

Myanmar25% - company; 35% - branch20% - employment income; 30% - other income; 35% - non-resident foreignersNone20%15%No standard rate. 5% for services. Between 3% and 100% for goods.Subject to tax at 10% for resident taxpayers and 40% for non-resident taxpayers

Philippines30%32%30%30%30%12%Capital gains on the disposal, sale, or exchange of shares, and land and buildings are subject to tax

Singapore17%20%None10%15%7%No capital gains tax

Thailand20% (for 2 accounting periods beginning on or after 1 January 2013)37%. This is expected to be reduced to 35% from the 2013 tax year.10%15%15%10%, although a reduced 7% rate applies on 30 September 2014No separate capital gains tax. Capital gains are treated as taxable income.

Vietnam25%. This is to be reduced to 22% from 1 January 2014, and 20% from 1 January 2016.35%None for corporate investors. 5% for individual investors10%5%10%Capital gains tax is applied to both corporate and individual investors.

Source: ASEAN Tax Guide (2013)An earlier assessment by Botman et al (2008) calculates effective tax rates in ASEAN and concludes that general effective tax rates are relatively higher in the Philippines though its investment incentives are generally comparable to its ASEAN neighbors. The authors, however, decided to ignore personal income taxation for simplification purposes though they note that, in principle, PIT affects investment and saving behavior, especially taxes on interest, dividends, and capital gains. It is worth mentioning that these taxes vary widely within the region and that rates in the Philippines are among the highest.On a related note, Reside (2007) provides evidence that proxy variables for fiscal incentives, including income tax-related incentives such as income tax holidays, are not good predictors of regional investment in the Philippines. He notes that this is consistent with previous empirical findings and international evidence, i.e. there are other more important factors than fiscal incentives that influence investment decisions.Comparing the tax structure in ASEAN countries, the National Tax Research Center or NTRC (2007) notes that nine out of the ten member countries impose taxes on individual income, with Brunei as the lone exception. All nine countries have schedular income tax structures and make distinction between employment and business income. Cambodia, Laos, and Myanmar all have a separate schedule of tax rates for employment income and business income. Of the nine countries, most have five income tax brackets (Cambodia, Indonesia, Vietnam, and Malaysia), the Philippines and Singapore have seven, Thailand recently added three new income for a total of eight, Laos has nine, and Myanmar has 13.

In terms of the tax base for employment income, the Philippines is most similar to Thailand, Singapore, Indonesia, Myanmar, and Malaysia. These countries, however, allow for more itemized deductions from gross income while the Philippines allows only premiums on health insurance and only up to a certain amount, in addition to personal exemptions. In particular, Malaysia, Thailand, and Singapore have extensive lists of personal allowances and itemized deductions, including special consideration for the disabled and expenses on health and education of children.

Unlike in other ASEAN countries (e.g. Myanmar, Singapore, and Thailand), however, the Philippines allows personal and additional exemption allowances aside from itemized business expenses deducted from gross income of individuals engaged in business or practice of a profession.

Malaysia, the Philippines, Singapore, and Thailand practice the self-assessment system when it comes to tax administration. In Cambodia, Indonesia, Laos, Myanmar, and the Philippines, the employer has the mandate to deduct taxes from its employees income and remit these taxes to authorities. Figure 1. Per Capita income vs. PIT in ASEAN, 2012Source: Latest World Bank (if not available, International Monetary Fund) data as of 2012As for greater outward migration as a possible consequence of ASEANs economic integration, data on the distribution of overseas Filipino workers (OFWs) shows that only a little over 10 percent of OFWs can be found in ASEAN with almost the entire figure accounted for by Singapore and Malaysia. While there has been a diversification in the skills profile of OFWs in general, a good number (30.8 percent) are laborers and unskilled workers while only a small proportion (around 20 percent) are employed in high-paying jobs (professionals, technicians and associate professionals, and managerial positions in government and special-interest organizations. Singapore is known for a large population of Filipino domestic workers. Meanwhile, Malaysia harbors a considerable Filipino population owing to historic and cultural ties that have persisted through backdoor linkages despite crackdowns by Malaysian authorities. Since PIT rates tend to matter more for people with high incomes, and therefore have more to lose from taxes, it would be reasonable to assume that PIT differentials would not by themselves significantly affect outward migration flows to these countries or to the rest of the region. Moreover, while there is evidence that income tax differentials can encourage migration to areas with lower rates (Rider, 2006), we note that this analysis is limited to the context of states within a single country (i.e. the United States) where there is a high degree of labor mobility. ASEAN is not as homogenous or integrated as the U.S. in terms of language, culture, development, economic and political systems, or even ease of transport.Research MethodFrameworkThe Micro-Impacts of Macroeconomic Adjustment Policies (MIMAP) framework developed by Lamberte et al (1991) offers an analytical tool for examining the economic effects of proposed tax amendments. The MIMAP framework looks at the interaction between macroeconomic policies and heterogeneous households, given a countrys particular institutional structure and natural resource endowments. The channels of influence are: the labor market; the goods market; and the delivery of public goods. The framework allows for differential impacts on different groups of households and how affected groups cope with the situation. As such, evaluations of macroeconomic policies should not be limited to macroeconomic aggregates, but also micro-indicators on the impact on household wellbeing.Thus, for purposes of this study, the channels concerned are on the consumption of goods and services, and labor supply.In theory, taxes on labor income such as the PIT are expected to discourage workers from supplying labor, primarily through substitution effects affecting the decisions of individuals on work versus leisure. This response to tax changes is often measured through working hours, though individuals may also adjust other aspects of labor supply such as labor participation, work effort, human capital investment, type of occupation, etc. For instance, OECD (2012), notes that increases in top PIT rates may reduce working hours and productivity by reducing the incentives for work and innovation. There is also evidence that cuts in PIT rates raise employment (Mertens and Ravn, 2013) while others argue that labor income taxes influence decision-making with regard to the accumulation of human capital, e.g. education and training (Ferede and Dahlby 2012). PIT, by definition, directly reduces disposable income available for saving or consumption. Thus, cuts in PIT rates are expected to raise consumption spending and this is also borne out by empirical evidence (Mertens and Ravn, 2013). The magnitude of the expenditure response varies, however. In their analysis of U.S. tax cuts, for example, Jappelli and Pistaferri (2010) find that temporary tax cuts have only a moderate effect in terms of increasing household spending. Moreover, the expenditure response tends to be higher for low-income or low-liquidity households. The decision to work and consume are assumed to be determined by income tax, as well as other taxes and individual and community characteristics. Income tax payment is considered to be affected by individual characteristics. Data

Data from the merged results of the Family Income and Expenditure Survey (FIES) and Labor Force Survey (LFS) is perhaps the most appropriate in studying behaviors related to changes in income tax policy in the Philippines. However, individual behaviors are difficult to observe as income taxes are recorded collectively at the level of the household. Thus, the household is used as the unit of analysis. For this study, the 2009 survey results were utilized. The said data set contains information on the demographic characteristics, income levels, and expenditure patterns of a sample of 38,400 households from all over the country. While the data still provides necessary insights on household behavior, it cannot be denied that the same information is quite aged. However, the data set used is still meritorious, as it characterizes household behavior during times of crisis. Consequently, results obtained in this study may be considered conservative.Regression Models

A regression model was used in order to ascertain the effects of changes in income tax on household consumption and on labor supply (characterized by the total number of hours worked in the past week). Table 4 lists the variables used in the models and their corresponding descriptions, with the first three variables listed being the dependent variables.

Table 4. List of Variables and Definitions

VariableDefinition

ytaxIncome tax paid, per household, in pesos

consTotal family expenditure, in pesos

hrsworkedTotal number of hours worked during the past week

toincTotal family income, in pesos

marriedProportion of married household members

childdepProportion of dependent household members

hhdsexSex of household head, 1 if male, and 0 if female

hhdageAge of household head

memTotal number of household members

ttaxesTotal taxes, per household; computed as sum of income tax; real estate tax; car registration, toll fees, and driver's license; and other direct taxes.

iloanLoans from other families, in pesos

wdrawWithdrawals from savings, in pesos

remitTotal household remittances from abroad, in pesos

urbanUrbanity indicator, 1 if urban and 0 if rural

paytaxTax payment indicator, 1 if paid taxes and 0 otherwise

Notes:In the survey, respondents are asked whether they or their family paid any taxes (such as income, real estate, or other forms) during the period specified in the interview. Responses, however, are coded in terms of the amount of taxes the household paid. As such, it is not entirely clear whether responses coded as zero means that they did not pay any taxes or if they are exempt from paying taxes.The households decision to consume is related to a number of causal factors, which includes income tax and other direct taxes (ytax, ttaxes). The level of income (toinc), the availability of liquid assets (iloan, wdraw, remit), community characteristics (urban), and household characteristics (hhdsex, hhdage, mem) affect this decision. Meanwhile, the decision to supply labor hours is determined by taxes and community and household characteristics, as stated above. Income tax, however, is potentially jointly determined with consumption and labor supply. Thus, income tax payment behavior is also modeled as a function of income and other household characteristics (married, childdep, hhdsex, hhdage, mem).

Equations (1) to (3) exhibit the complete specification for each of the models.(1)

(2)

(3)

Under usual circumstances, equations (1) to (3) are estimated separately using ordinary least squares (OLS). However, since there is interplay in consumption, labor, and taxation behavior, the same equations were treated as simultaneous; that is, the equations were estimated at the same time using three-stage least squares (3sls).

Apart from theory, a more objective approach to determining whether simultaneous models are needed is to conduct a test that compares the estimates obtained from the independent models and the simultaneous equations. The Hausman Test compares the estimates and is used for this purpose.

Households were also divided into five equal groups, or quintiles, and equations were again estimated for each of the quintiles. These quintiles divide the total number of households into five equal groups according to some variable sorted according to magnitude. For the purposes of this study, income quintiles were used.

All tests are performed at a ten-percent level of significance ( = 0.10).

Results and InterpretationBefore proceeding to the results of the models, it is of interest to confirm whether the 3SLS model is more appropriate over the OLS model. As previously mentioned, the Hausman Specification Test was used in order to determine the appropriateness of the 3SLS model. The Hausman Test compares the estimates obtained from the OLS and 3SLS models. If the 3SLS model does not offer any valuable improvement on the OLS model, then the estimates obtained should not be greatly different. However, for the models in this study, the results of the test show that the estimates from the two models are significantly different, and that the 3SLS model should be used. The outputs of the estimation procedures for the 3SLS model are summarized in Table 5 below.Table 5. Estimation Output: Simultaneous Equations Model

Equation (1)Income TaxEquation (2)Family ExpenditureEquation (3)Total Hours Worked

Explanatory VariableCoefficientExplanatory VariableCoefficientExplanatory VariableCoefficient

toinc0.019874*ytax(49.69389)*ytax(0.0114988)*

married(1088.797)*ttaxes49.1486*ttaxes0.0112578*

childdep(2924.388)*toinc0.1762088*urban9.880471*

hhdsex980.777*iloan0.4790175*hhdsex10.04519*

hhdage(6.174742)wdraw0.2801235*hhdage0.1575624*

mem(80.5948)*remit0.4738713*mem10.45288*

intercept182.7682urban57751.03*intercept2.334081

hhdsex(2487.998)

hhdage(135.1811)

mem10047.55*

intercept28112.61*

Notes: Figures in parentheses are negative. Figures noted with an asterisk are significant at = 0.10The estimated modelshows that income tax has an inverse relationship with total family expenditure. Specifically, every peso increase in income tax may, on the average, dictate a decrease of Php49.69 in total family expenditure, while keeping all other variables and factors constant. As such, there is reason to believe that a higher level of income tax may hamper or discourage expenditure at the household level. Similarly, the amount of income taxes paid by a household also has a negative effect on the total number of hours spent working in the past week. Based on the model, on the average, every peso increase in income tax may decrease the total number of hours worked by 0.011 hours, while keeping all other factors constant. In effect, a higher level of income tax may discourage people from working more hours. Note that while the effect is significant, it may be considered minute, which is likely due to the diversity in the incomes and characteristics of the households interviewed. Therefore, perusing the data in terms of income levels would also be noteworthy. A model was also estimated for income taxes paid. Note that total income is a significant determinant of income tax, since, on the average, a peso increase in total income may lead to a Php0.02 increase in taxes paid, while holding other variables constant. Again, the figure is small; however, this may be due to the fact that even at higher income levels, some respondents still pay lesser taxes through some exemption mechanisms. The proportion of married household members and the proportion of dependent children in the household negatively affect income taxes. On the average, an increase in the proportion of married household members leads to a Php1,089 decrease in total taxes paid, while an increase in the proportion of dependent children leads to a Php2,924 decrease in total taxes, keeping other factors constant. These results are to be expected as being married and having children in the household are some conditions for tax deductions. Since it is also of interest to ascertain how the variables would behave at different income level, models were also estimated at each income quintile, results of which are found in Annex 3. Except for quintile 4, models show that income taxes have a negative effect on total family expenditure. That is, every peso increase income taxes paid will, on the average, spur a decrease in total family expenditure. This means that regardless of the amount of total income received, a higher amount of tax tends to discourage households from spending. The same, however, cannot be said for total hours worked. It is only for the fifth income quintile, where the top 20 percent of households (in terms of income) are found, that the amount of income paid would, on the average, translate to a decrease in the total number of hours worked.Results for each income quintile should be approached with caution, however, as the 3SLS models for each quintile have a negative R-squared. This implies that such a model specification is not necessarily an improvement over the OLS models. Concluding RemarksFrom the results of the above analysis, it is worth pointing out some key findings. For one, the relationships between the dependent and independent variables used in the analysis are consistent with the predictions of economic theory. Income taxes paid by households increase with total income, affirming the progressive nature of the income tax system. The magnitude of the estimated coefficient, while statistically significant, is quite small. Tax exemptions and other means of tax avoidance are likely to play a part in diminishing the relationship between the amount of taxes paid and total household incomes (though we cannot also discount other explanations such as limitations with the survey data or outright tax evasion). This is confirmed by the logistic regression analysis where being married and having children as dependents reduce the likelihood of paying taxes as these two are bases for income tax exemptions. The negative relationship between income taxes, on one hand, and, on the other hand, total household spending and total hours worked is also confirmed by our results. In the case of total hours worked, the magnitude of the effect of income taxes is small, but the fact that it is at the top income class where this is most apparent is also consistent with economic theory. Low-income households, a good number of which may be minimum wage earners and are thus exempt from income taxes in the first place, are constrained from reducing their work hours because they cannot afford to do so. This is not the case with high-income households who can afford to substitute work for leisure. Moreover, the type of occupation may also play a part with low-income workers typically under no-work-no-pay arrangements. Workers belonging to the top-income group, meanwhile, tend to enjoy more flexibility or may even be self-employed.On the basis of such results, it appears that a reduction in PIT rates would be beneficial to households in terms of 1) increasing consumption spending as measured by total household expenditures, and 2) increasing labor supply as measured by total hours worked. In particular, a one-peso decrease in income taxes paid increases household expenditure by PhP49.69 and total hours worked by 0.01 hours. The former reinforces progressivity as the increases in expenditure generally decline with higher income. The latter effect, however, is small and is concentrated among the top 20-percent of households in terms of income. The findings appear to run counter to the notion of Ricardian Equivalence where consumers understand that any tax cuts in the present must be balanced out by future tax increases. The implication is that forward-looking, rational consumers would rather save the amount accruing to them from the tax cut in order to pay for higher taxes in the future. Thus, a decrease in government savings owing to the tax cut will be offset by an equivalent increase in private savings. Therefore, the timing of tax cuts ought not to affect to affect the equilibrium real interest rate, as they do not affect overall national savings, and aggregate economic demand.In our case, we do see evidence of short-run effects in the labor and goods markets through changes in work hours and in household spending, running counter to the theorys prediction that tax cuts would have no effect on employment and output. Given the limits of our dataset, however, there remains the question of whether this would persist in the long run. Ricardian Equivalence predicts that aggregate demand in general would remain unchanged, but there are compelling reasons to discount this.

One of the more apparent reasons why Ricardian Equivalence may not hold, however, is that it assumes lump-sum taxation and not proportional or distortionary taxes, which is the nature of income taxes. Another is that the theory assumes fixed government spending, which is not the case. Both of these assumptions do not hold in reality, thus making Ricardian Equivalence unlikely.Moreover, the strict underlying assumptions that are often cited as being crucial for the theory to hold are also questionable. These include altruism in intergenerational linkages, e.g. parents concern for their children who may inherit future tax increases; perfect capital markets where consumers face no borrowing constraints and make consumption decisions based on lifetime expected income; and consumer rationality, that is, consumers can fully anticipate the future tax implication of a deficit-finance tax cut. ReferencesAllingham, M. G. and A. Sandmo (1972), Income Tax Evasion: A Theoretical Analysis. Journal of Public Economics, 1:323-338.Alm, J. (1998), Tax Compliance and Administration. Working Paper No. 98-12, Center for Economic Analysis, Department of Economics, University of Colorado at Boulder. Barro R. J. and C. J. Redlick (2011), Macroeconomic Effects from Government Purchases and Taxes. The Quarterly Journal of Economics (2011), 126. 51-102. Botman, D. A. Klemm, and R. Baqir (2008), Investment Incentives and Effective Tax Rates in the Philippines: A Comparison With Neighboring Countries. IMF Working Paper.Charney, A. H. (2012), Can Tax Cuts Pay for Themselves by Stimulating Growth? The University of Arizona Economic and Business Research Center.Clotfelter, C. T. (1983), Tax Evasion and Tax Rates: An Analysis of Individual Returns. The Review of Economics and Statistics, 65: 559-576.Congressional Budget Office (1989), "Budget Deficits, Tax Incentives and Inflation: A Surprising Lesson From the 1983-1984 Recovery."Crane, S. E. and F. Nourzad (1992), An Empirical Analysis of the Factors that Distinguish Those Who Evade on Their Tax Return From Those Who Do Not Choose to File a Return. Public Finance/Finance Publiques, 49 (Supplement): 106-116.DezanShira& Associates (2013), The 2014 Asia Tax Comparator. Asia Briefing Magazine, November-December 2013.Feldstein, M. (2006), "The Effect of Taxes on Efficiency and Growth." Tax Notes (May 8, 2006).Haughton J. and S. R. Khandker (2009), The Effects of Taxation and Spending on Inequality and Poverty. Chapter 15, Handbook on Poverty and Inequality.The World Bank.Hungerford, T. L. (2012), Taxes and the Economy: An Economic Analysis of the Top Tax Rates Since 1945. Congressional Research Service, September 2012.Jappelli T. and L. Pistaferri (2010), The Consumption Response to Income Changes. The Annual Review of Economics, 2:479-506. KPMG International (2013), ASEAN Tax Guide. KPMG Asia Pacific Tax Centre, November 2013.Leigh, D., P. Devries, C. Freedman, J. Guajardo, D. Laxton, and A. Pescatori (2010), Will it Hurt? Macroeconomic Effects of Fiscal Consolidation. International Monetary Fund, October 2010.McBride, W. (2012), CRS, at odds with Academic Studies, Continues to Claim No Harm in Raising Top Earners Tax Rates. The Tax Policy Blog, Tax Foundation, December 2012.McBride, W. (2012), What is the Evidence on Taxes and Growth? The Tax Policy Blog, Tax Foundation, December 2012.Mertens, Karel, and Morten O. Ravn (2013), "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States." American Economic Review, 103(4): 1212-47.National Tax Research Center (2007), Summary of Significant Features of the Income Tax Structure among ASEAN Member Countries. NTRC Tax Research Journal, Vol XIX, pp. 1-44. July-August 2007.OECD (2010), Tax Policy Reform and Economic Growth, OECD Publishing.OECD (2012), Reducing income inequality while boosting economic growth: Can it be done? Going for Growth: Economic Policy Reforms 2012.Plumley, A.H. (1996), The Determinants of Individual Income Tax Compliance: Estimating the Impacts of Tax Policy, Enforcement, and IRS Responsiveness. Internal Revenue Service, Publication 1916 (Rev. 11-96), Washington, DC.Reside, R. (2007), Can Fiscal Incentives Stimulate Regional Investment in the Philippines? An Update of Empirical Results. UPSE Discussion Paper No. 0705, June 2007. Respondek& Fan (2014), Legal E-Bulletin, Vol. 10, February 2014. Rider, M. (2006), The Effect of Personal Income Tax Rates on Individual and Business Decisions A Review of the Evidence. International Studies Program Working Paper 06-15, April 2006.Romer, C. D. and D. H. Romer (2010), The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks. American Economic Review 100: 763-801, June 2010.Slemrod, J. (1985), The Optimal Size of a Tax Collection Agency. Scandinavian Journal of Economics, 89:183-192.Yitzhaki, S. (1974). A Note on Income Tax Evasion: A Theoretical Analysis. Journal of Public Economics, 3: 201-202. Annex 1Results: Hausman Specification Test

---- Coefficients ---- | (b) (B) (b-B) sqrt(diag(V_b-V_B)) | Reg3OLS Reg33SLS Difference S.E.-------------+----------------------------------------------------------------toinc | .0199538 .019874 .0000799 5.18e-06married | -1118.752 -1088.797 -29.95553 16.54913childdep | -2864.336 -2924.388 60.0517 44.30329hhdsex | 995.4552 980.777 14.67824 6.961727hhdage | -5.944975 -6.174742 .2297674 .2353892mem | -85.44507 -80.5948 -4.850266 2.414634------------------------------------------------------------------------------ b = consistent under Ho and Ha; obtained from reg3 B = inconsistent under Ha, efficient under Ho; obtained from reg3 Test: Ho: difference in coefficients not systematicchi2(5) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 10.98Prob>chi2 = 0.0518

Annex 2 Model Estimation Outputs: Simultaneous Equations ModelThree-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 38400 6 14500 0.1498 6719.71 0.0000

cons 38400 10 136615.3 0.3639 13755.03 0.0000

hrsworked 38400 6 57.08796 0.0482 8820.43 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .019874 .0002455 80.96 0.000 .0193928 .0203551

married | -1088.797 315.0026 -3.46 0.001 -1706.19 -471.4028

childdep | -2924.388 349.653 -8.36 0.000 -3609.695 -2239.08

hhdsex | 980.777 208.475 4.70 0.000 572.1735 1389.381

hhdage | -6.174742 5.72616 -1.08 0.281 -17.39781 5.048325

mem | -80.5948 37.90606 -2.13 0.033 -154.8893 -6.300294

_cons | 182.7682 424.0275 0.43 0.666 -648.3103 1013.847

-------------+----------------------------------------------------------------

cons |

ytax | -49.69389 18.19928 -2.73 0.006 -85.36384 -14.02395

ttaxes | 49.1486 17.56632 2.80 0.005 14.71924 83.57796

toinc | .1762088 .0372419 4.73 0.000 .103216 .2492017

iloan | .4790175 .2003357 2.39 0.017 .0863667 .8716683

wdraw | .2801235 .0747158 3.75 0.000 .1336831 .4265638

remit | .4738713 .0271549 17.45 0.000 .4206487 .5270938

urban | 57751.03 2775.521 20.81 0.000 52311.1 63190.95

hhdsex | -2487.998 5120.983 -0.49 0.627 -12524.94 7548.946

hhdage | -135.1811 198.4714 -0.68 0.496 -524.1779 253.8157

mem | 10047.55 860.8564 11.67 0.000 8360.298 11734.79

_cons | 28112.61 10095.95 2.78 0.005 8324.909 47900.32

-------------+----------------------------------------------------------------

hrsworked |

ytax | -.0114988 .0004415 -26.04 0.000 -.0123642 -.0106335

ttaxes | .0112578 .000418 26.93 0.000 .0104385 .0120771

urban | 9.880471 .5845397 16.90 0.000 8.734794 11.02615

hhdsex | 10.04519 .7322252 13.72 0.000 8.610053 11.48032

hhdage | .1575624 .0217736 7.24 0.000 .1148869 .2002379

mem | 10.45288 .1306903 79.98 0.000 10.19673 10.70903

_cons | 2.334081 1.525574 1.53 0.126 -.6559897 5.324152

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------

Annex 3Model Estimation Outputs: Simultaneous Equations Model, by Income Quintilequintile = 1

Three-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 7680 6 143.0998 -0.0018 69.21 0.0000

cons 7680 10 412519.9 -559.3293 5827.46 0.0000

hrsworked 7680 6 58.10299 -1.1997 1082.83 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .0008525 .0001101 7.74 0.000 .0006367 .0010684

married | 6.30443 4.237272 1.49 0.137 -2.000472 14.60933

childdep | 4.139466 5.127892 0.81 0.420 -5.911016 14.18995

hhdsex | -2.485975 4.413798 -0.56 0.573 -11.13686 6.164911

hhdage | .0522193 .1152639 0.45 0.651 -.1736937 .2781324

mem | -1.487226 .9737731 -1.53 0.127 -3.395786 .4213344

_cons | -36.98796 10.20446 -3.62 0.000 -56.98833 -16.9876

-------------+----------------------------------------------------------------

cons |

ytax | -2935.476 1211.367 -2.42 0.015 -5309.712 -561.2391

ttaxes | 68.74653 36.34254 1.89 0.059 -2.483528 139.9766

toinc | 2.146218 .3627412 5.92 0.000 1.435258 2.857178

iloan | -2.598711 1.848925 -1.41 0.160 -6.222537 1.025115

wdraw | 5.041801 2.300301 2.19 0.028 .5332926 9.550309

remit | -.5079376 .2630781 -1.93 0.054 -1.023561 .0076859

urban | 3747.482 1363.478 2.75 0.006 1075.113 6419.85

hhdsex | -1135.456 2866.114 -0.40 0.692 -6752.938 4482.025

hhdage | -9.117619 79.27526 -0.12 0.908 -164.4943 146.259

mem | 423.1454 637.2561 0.66 0.507 -825.8536 1672.144

_cons | -51065.54 16663.9 -3.06 0.002 -83726.19 -18404.9

-------------+----------------------------------------------------------------

hrsworked |

ytax | .3182577 .0348813 9.12 0.000 .2498916 .3866238

ttaxes | -.0040735 .0011358 -3.59 0.000 -.0062996 -.0018473

urban | .8735021 1.053689 0.83 0.407 -1.19169 2.938694

hhdsex | 9.249672 1.290741 7.17 0.000 6.719867 11.77948

hhdage | .0219587 .0357744 0.61 0.539 -.0481579 .0920752

mem | 6.596929 .2853368 23.12 0.000 6.037679 7.156179

_cons | 16.74874 2.787691 6.01 0.000 11.28497 22.21252

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------

quintile = 2

Three-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 7680 6 204.7407 0.0023 22.39 0.0010

cons 7680 10 51158.25 -6.8259 5178.71 0.0000

hrsworked 7680 6 370.1619 -68.7174 5083.27 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .0001808 .0000971 1.86 0.062 -9.41e-06 .0003711

married | 7.798341 4.49769 1.73 0.083 -1.01697 16.61365

childdep | 5.598024 5.531685 1.01 0.312 -5.24388 16.43993

hhdsex | -5.334613 7.091692 -0.75 0.452 -19.23407 8.564847

hhdage | -.2236622 .1794009 -1.25 0.213 -.5752815 .127957

mem | -4.43036 1.221232 -3.63 0.000 -6.82393 -2.03679

_cons | 29.32174 15.68039 1.87 0.061 -1.411263 60.05475

-------------+----------------------------------------------------------------

cons |

ytax | -252.9726 43.80012 -5.78 0.000 -338.8193 -167.126

ttaxes | 17.94203 4.999348 3.59 0.000 8.143489 27.74057

toinc | .836032 .019374 43.15 0.000 .7980596 .8740044

iloan | .9958752 .0364387 27.33 0.000 .9244567 1.067294

wdraw | .6715349 .0277102 24.23 0.000 .6172239 .725846

remit | -.0992119 .0300253 -3.30 0.001 -.1580603 -.0403635

urban | 5958.747 907.3114 6.57 0.000 4180.45 7737.045

hhdsex | -1153.396 942.197 -1.22 0.221 -3000.068 693.2765

hhdage | -100.3887 27.9373 -3.59 0.000 -155.1448 -45.63258

mem | 960.5542 159.0349 6.04 0.000 648.8516 1272.257

_cons | 10880.32 2314.487 4.70 0.000 6344.01 15416.63

-------------+----------------------------------------------------------------

hrsworked |

ytax | 1.880577 .1550674 12.13 0.000 1.57665 2.184503

ttaxes | -.1116626 .0176654 -6.32 0.000 -.1462861 -.0770391

urban | -21.75144 3.437758 -6.33 0.000 -28.48932 -15.01356

hhdsex | 17.48696 6.702052 2.61 0.009 4.351177 30.62274

hhdage | .8459485 .1811691 4.67 0.000 .4908636 1.201033

mem | 10.8986 1.136938 9.59 0.000 8.670242 13.12696

_cons | -41.00472 13.01626 -3.15 0.002 -66.51611 -15.49333

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------

quintile = 3

Three-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 7680 6 1197.551 0.0191 177.62 0.0000

cons 7680 10 34018.35 -0.6383 3258.62 0.0000

hrsworked 7680 6 71.2834 -0.9499 1648.79 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .0055348 .0008247 6.71 0.000 .0039184 .0071511

married | -96.39574 64.22875 -1.50 0.133 -222.2818 29.49029

childdep | -465.9999 63.42184 -7.35 0.000 -590.3044 -341.6954

hhdsex | 40.42505 44.04868 0.92 0.359 -45.90879 126.7589

hhdage | -6.723978 1.094261 -6.14 0.000 -8.868691 -4.579265

mem | -29.97505 7.32389 -4.09 0.000 -44.32961 -15.62049

_cons | 85.33416 131.8038 0.65 0.517 -172.9966 343.6649

-------------+----------------------------------------------------------------

cons |

ytax | -34.97379 7.155069 -4.89 0.000 -48.99747 -20.95012

ttaxes | 17.79353 4.453161 4.00 0.000 9.06549 26.52156

toinc | .8608525 .0188198 45.74 0.000 .8239664 .8977385

iloan | .7442828 .0456317 16.31 0.000 .6548463 .8337193

wdraw | .5896205 .0436841 13.50 0.000 .5040013 .6752398

remit | -.0942303 .0147769 -6.38 0.000 -.1231924 -.0652682

urban | 9539.629 952.8641 10.01 0.000 7672.05 11407.21

hhdsex | -1108.666 992.1174 -1.12 0.264 -3053.18 835.8485

hhdage | -241.436 38.79588 -6.22 0.000 -317.4745 -165.3974

mem | 1281.165 153.7239 8.33 0.000 979.8719 1582.459

_cons | 8502.592 2881 2.95 0.003 2855.935 14149.25

-------------+----------------------------------------------------------------

hrsworked |

ytax | .0644411 .0129508 4.98 0.000 .0390581 .0898241

ttaxes | -.0259086 .0081011 -3.20 0.001 -.0417865 -.0100306

urban | -8.066674 1.909775 -4.22 0.000 -11.80977 -4.323583

hhdsex | 12.06571 2.267112 5.32 0.000 7.622255 16.50917

hhdage | .6621812 .0806818 8.21 0.000 .5040478 .8203146

mem | 8.693393 .3720991 23.36 0.000 7.964092 9.422694

_cons | -1.37177 4.378193 -0.31 0.754 -9.95287 7.20933

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------

quintile = 4

Three-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 7680 6 3498.645 0.0631 537.32 0.0000

cons 7680 10 36582.51 0.3699 4943.46 0.0000

hrsworked 7680 6 119.3442 -3.2252 1242.51 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .0177113 .0012194 14.52 0.000 .0153213 .0201013

married | -854.6968 176.8859 -4.83 0.000 -1201.387 -508.0068

childdep | -1702.433 181.3376 -9.39 0.000 -2057.848 -1347.018

hhdsex | 44.69675 107.6142 0.42 0.678 -166.2231 255.6166

hhdage | -23.90258 3.23433 -7.39 0.000 -30.24175 -17.56341

mem | -217.1616 19.87326 -10.93 0.000 -256.1125 -178.2108

_cons | 661.8082 337.601 1.96 0.050 .1223274 1323.494

-------------+----------------------------------------------------------------

cons |

ytax | 3.530254 6.759027 0.52 0.601 -9.717195 16.7777

ttaxes | -2.095355 5.885249 -0.36 0.722 -13.63023 9.439521

toinc | .7519506 .0143286 52.48 0.000 .7238671 .7800342

iloan | 1.040866 .0572191 18.19 0.000 .9287191 1.153014

wdraw | .4671525 .0398135 11.73 0.000 .3891194 .5451855

remit | .0682153 .0150146 4.54 0.000 .0387872 .0976434

urban | 11778.57 2122.255 5.55 0.000 7619.03 15938.11

hhdsex | 2839.501 1773.455 1.60 0.109 -636.4064 6315.409

hhdage | -157.0019 66.26541 -2.37 0.018 -286.8797 -27.12407

mem | 1997.138 253.6358 7.87 0.000 1500.021 2494.255

_cons | 12221.03 3530.412 3.46 0.001 5301.551 19140.51

-------------+----------------------------------------------------------------

hrsworked |

ytax | .0777059 .0103523 7.51 0.000 .0574157 .097996

ttaxes | -.0595058 .0090561 -6.57 0.000 -.0772554 -.0417563

urban | -20.07855 3.845203 -5.22 0.000 -27.61501 -12.54209

hhdsex | 28.19095 3.471663 8.12 0.000 21.38662 34.99529

hhdage | .9248591 .1295435 7.14 0.000 .6709585 1.17876

mem | 10.78306 .630388 17.11 0.000 9.547525 12.0186

_cons | -10.2881 6.683545 -1.54 0.124 -23.38761 2.811406

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------

quintile = 5

Three-stage least-squares regression

----------------------------------------------------------------------

Equation ObsParms RMSE "R-sq" chi2 P

----------------------------------------------------------------------

ytax 7680 6 30328.7 0.0843 703.73 0.0000

cons 7680 10 289642.8 -0.4114 2476.93 0.0000

hrsworked 7680 6 69.8405 0.1058 1593.48 0.0000

----------------------------------------------------------------------

------------------------------------------------------------------------------

| Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

ytax |

toinc | .0160276 .0006417 24.98 0.000 .0147698 .0172854

married | -3887.712 1412.221 -2.75 0.006 -6655.614 -1119.809

childdep | -9763.749 1552.567 -6.29 0.000 -12806.72 -6720.774

hhdsex | 4426.006 819.5282 5.40 0.000 2819.76 6032.252

hhdage | -41.2232 28.54655 -1.44 0.149 -97.1734 14.727

mem | -512.6123 160.5408 -3.19 0.001 -827.2666 -197.9581

_cons | 10559.67 2056.437 5.13 0.000 6529.13 14590.21

-------------+----------------------------------------------------------------

cons |

ytax | -61.33875 16.59442 -3.70 0.000 -93.86321 -28.81429

ttaxes | 61.19477 16.09908 3.80 0.000 29.64115 92.7484

toinc | .0740477 .0296534 2.50 0.013 .0159281 .1321674

iloan | -.1252526 .2502314 -0.50 0.617 -.615697 .3651919

wdraw | .166625 .0755445 2.21 0.027 .0185605 .3146895

remit | .3045364 .026245 11.60 0.000 .2530971 .3559757

urban | 89399.92 11616.57 7.70 0.000 66631.86 112168

hhdsex | -9329.782 11966.52 -0.78 0.436 -32783.73 14124.16

hhdage | -1316.624 628.3273 -2.10 0.036 -2548.123 -85.12478

mem | 14805.29 2661.796 5.56 0.000 9588.269 20022.32

_cons | 143042 20851.67 6.86 0.000 102173.5 183910.5

-------------+----------------------------------------------------------------

hrsworked |

ytax | -.0055076 .000726 -7.59 0.000 -.0069306 -.0040846

ttaxes | .0055668 .0006956 8.00 0.000 .0042034 .0069301

urban | 12.65861 1.930491 6.56 0.000 8.87492 16.44231

hhdsex | 16.0726 1.828677 8.79 0.000 12.48846 19.65674

hhdage | -.1136904 .0677951 -1.68 0.094 -.2465664 .0191855

mem | 12.46531 .3624348 34.39 0.000 11.75495 13.17566

_cons | 13.45538 4.179488 3.22 0.001 5.263733 21.64703

------------------------------------------------------------------------------

Endogenous variables: ytax cons hrsworked

Exogenous variables: toinc married childdephhdsexhhdagememttaxesiloan

wdraw remit urban

------------------------------------------------------------------------------