The Growth-Inequality Tradeoff in the Design of TaxStructure: Evidence from a Large Panel of Countries

Yongzheng Liu∗

School of FinanceRenmin University of China

E-mail: yongzheng.liu@ruc.edu.cnFax: +86 10 82509261

Mailing address: No.59 Zhongguancun Street, Haidian District,Beijing 100872, China

Jorge Martinez-VazquezInternational Center for Public Policy

Georgia State UniversityE-mail: jorgemartinez@gsu.edu

Mailing address: 14 Marietta St NW, 5th FloorAtlanta, GA 30303, USA

Abstract

This paper examines the potential tradeoff between economic growth and income in-equality in the design of tax structure using a structural model and a large panel dataset for 150 developed and developing countries covering the period 1970-2009. We findclear evidence of: (1) a tradeoff between growth and inequality for both direct andindirect taxes; (2) heterogeneous growth and inequality effects of tax instruments mea-sured by levels and rates (particularly corporate income tax); and (3) heterogeneouseffects of tax instruments on different definitions of inequality (i.e., gross income, netincome, or expenditure).

Keywords: Growth; inequality; tradeoff; tax structureJEL Classifications: D31, H20, O15, O41, O50

∗Corresponding author. We would like to thank the guest editor (Dr. Yong Wang) and an anonymousreferee for helpful comments and suggestions, which helped improve the paper. We would also like to thankMarika West for helpful research assistance. This research was supported for Liu by the Program for NewCentury Excellent Talents in University (NCET-13-0573) of the Ministry of Education of China and forMartinez-Vazquez by the Spanish Ministry of Economy and Competitiveness under project No. ECO2012-37572.

1. Introduction

Tax systems are complex institutions that countries have devised from time immemorial

to collect adequate revenues for the expenditure needs of the state. But the taxes used to

collect these revenues can have quite different costs to the economy in terms of distortions

or “excess burden losses”, as economic agents change their behaviors when confronted with

the changes in incentives associated with taxes. These excess burdens or efficiency losses

when sustained through time will reduce the rate of economic growth of the economy. Since

there are practically no taxes that at the same time yield significant revenue and are non-

distortionary, the optimal choice of taxes involves those with the lowest efficiency losses, or

in other words, those that can allow the maximum rate of economic growth over time.

Also important from an economic viewpoint, but even more important from a political

economy viewpoint, the same exact revenues can be raised with very different distribution

of final burdens or incidence across different income or other groups of individuals in society.

Even though there is wide acceptance that the distribution of tax burdens should be fair or

just, there is much less consensus on how progressive or redistributive tax systems should be.

And as in the case of efficiency-growth, different taxes have different degrees of effectiveness

in reducing (or increasing) income inequality.

The main challenge in the design of tax structures is that generally there is a conflict

or tradeoff between the objectives of growth and inequality. To put it more concretely,

direct taxes—mainly personal income tax and corporate income tax—are thought to reduce

growth due to the fact that they introduce distortions in the allocation of resources and

reduce economic incentives for work effort and savings and investment. However, these

taxes, especially the personal income tax, are generally accepted to be progressive and can

be effective in reducing income inequality. On the other hand, while higher reliance on

indirect taxes, such as consumption taxes, would reduce the typical workers’ and savers-

investors’ marginal tax rates, increasing their incentive to work and save and invest, and

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thus potentially lead to higher economic growth, indirect taxes are generally considered to

be regressive and so are expected to result in higher real income inequality. This is so

because indirect taxes are ultimately paid by consumers and lower income groups spend a

higher share of their incomes on consumption.

Thus, given a certain amount of tax revenues to be raised, the optimal design of a

country’s tax structure involves a careful consideration of its potential impacts on the tradeoff

between growth and inequality. A number of studies have explored the related impact of tax

structure, but most of them have treated the issues separately—looking either at the link

between tax structure and economic growth (e.g., Kneller et al., 1999; Holmes et al., 2004;

Lee and Gordon, 2005; Arnold et al., 2011; Chang et al., 2011) or at the link between tax

structure and income inequality (e.g., Weller, 2007; Duncan and Sabirianova Peter, 2012).

Neither isolated aspect of the analysis is ultimately useful to policy makers, because when

contemplating tax reform, policy makers need to balance simultaneously the impacts of

alternative tax structures on both growth and inequality.

A related important issue in this literature, but one that has garnered less of a consensus is

the measurement of tax structure. Existing studies have used either tax levels (i.e., revenues

collected), for example Arnold et al. (2011), or statutory tax rates, for example Lee and

Gordon (2005). From a theoretical standpoint, these two measures capture different aspects

of the tax system, but they are also related, as the former is the outcome of the latter along

with many other determinants. Statutory rates tend to capture the marginal effects on

economic behaviors but may not be that decisive in determining efficiency losses or changes

in the income distribution if overall tax collections are low because of other offsetting aspects

of the tax structure, such as exemptions or deductions. Therefore, applying both measures

of tax structure to the same country sample is meaningful and should allow us to identify

whether measurement would matter in exploring the economic impacts of tax structure.

In this paper we present new cross-country evidence for the potential tradeoff between

economic growth and income distribution in the design of tax structure, by using a panel

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dataset for 150 countries covering the period between 1970 and 2009. We contribute to

the literature in four significant ways. First, we utilize a large sample of countries from

both the developed and developing world for the past four decades. This should be more

informative than most other relevant cross-country studies that have focused only on high-

income countries (e.g., Arnold et al., 2011; Muinelo-Gallo and Roca-Sagales, 2011, 2013); in

particular, the inclusion of a large number of developed and developing countries will allow

us to discern whether similar tradeoffs are present in the two sets of countries. Second, we

construct a series of tax indicators for tax structure based on: tax levels and tax rates for

the major tax instruments, an index for the overall tax mix (i.e., the ratio of direct versus

indirect taxes), and an index for tax progressivity. This approach allows us to capture the

most comprehensive aspects of a country’s tax system, some of which have been ignored

in the previous literature. Third, rather than relying on a single reduced form estimation

approach, as has been the norm in past studies, we employ a structural model to explore the

joint impacts of tax policies on both growth and income distribution; this allows us to account

for the potential cross causality between growth and inequality.1 Fourth, depending on the

types of tax instruments, we explore how the inequality effects of different tax instruments

may vary across different definitions of income inequality (i.e., gross income, net income, or

expenditure).

In our empirical estimation we find significant effects of tax structure choices on economic

growth and income distribution. These effects generally support the findings in the previous

literature regarding economic growth with direct taxes, mainly personal income tax and

corporate income tax, retarding growth and with their substitution for indirect taxes, mainly

consumption tax, having positive effects. In contrast, while reliance on progressive personal

and corporate income taxes has a positive impact on income distribution, contributing to

1Muinelo-Gallo and Roca-Sagales (2011, 2013) are notable exceptions in the literature in that theyconduct a similar structural estimation. However, our analysis differs from theirs in several ways. The mostimportant differences are: a larger country sample in our case, which includes both high-income countriesand low-income countries; a more comprehensive measurement of tax structure, which includes not onlydisaggregated tax levels but also tax rates for individual tax categories, overall tax mix and progressivity;and an account for the potential endogeneity problem of the tax variables.

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decreasing inequality, indirect taxes, in particular the consumption tax, have a negative

impact on income distribution, leading to increasing inequality. Interestingly, our results

also highlight that the growth and distributional effects of the corporate income tax are

only statistically significant when measured in rates. Finally, in line with the observation

that direct taxes are more directly related to net income and indirect taxes (particularly the

consumption tax) are more directly related to expenditure, we find supporting evidence that

direct taxes are more effective in reducing net income inequality, while indirect taxes tend

to be more significant in increasing expenditure inequality.

The rest of the paper is organized as follows. In section 2 we provide an overview of the

international trends on changes in tax structure over the last four decades. In section 3 we

review the empirical methodology and data. In section 4 we present the estimation results.

In section 5 we simulate the growth and inequality implications of actual tax policy changes

for our sample countries. In section 6 we conclude.

2. Trends in Taxation: A Look at the Raw Data

Over the last several decades there have been significant changes in the rates and other

elements of the structure of tax systems in both developed and developing countries. Nat-

urally, all these changes in tax policy have had consequences, among other things, on both

economic growth and income distribution. In this section, we provide as background in-

formation an overview of the trends in tax structure at the international level. For our

worldwide sample of 150 countries the average annual tax structure as a share of GDP in

Figure 1 shows the rapid rise of the general consumption tax (GTGS), generally the VAT,

to become one of the most important sources of revenue from the early 1990s, coming to

represent on average 7 percent of GDP in most recent years. Figure 1 also shows the large

importance in the average tax system of payroll and social security taxes (SSCPAY) during

the entire sample period. Personal income taxes (PIT) have remained on average stable

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over the entire period, at about 4.5 percent of GDP and the same can be said for corporate

income taxes (CIT) at 3 percent, though in more recent years we can observe a fast rise in

PIT and a significant drop in the CIT, respectively.2 Also notable are the downward trends

in excise taxes (EXC) and customs taxes (CUST), especially since the early 1990s, and with

a more significant drop in CUST, the result of widespread trade reforms. Property taxes

(PROP) have taken up the lowest share in GDP and have been quite stable at a value around

1 percent of GDP over the period.

[Figure 1 about here.]

A different, more synthetic, way to examine tax trends for their potential effect on eco-

nomic growth and income distribution is to just focus on the direct to indirect taxes ratio.

Direct taxes we define as all income taxes, including PIT, CIT, SSCPAY, and PROP.3 As a

group these taxes all have some negative impact on growth but because of their varying pro-

gressivity tend to have a positive impact on reducing income inequality. On the other hand,

indirect taxes, fundamentally comprising GTGS, EXC, and CUST, are markedly friendlier

toward economic growth but because of their regressivity tend to increase income inequality.

Of course, the behavior or trend of the ratio is determined by that of its components in the

numerator and denominator, which were just examined above.

As shown in Figure 2, over the last four decades the average ratio of direct to indirect

taxes for our sample of countries oscillated around 1.5, with only a significant increase in the

last few years since the current world financial crisis. When the ratio is defined with PROP

as part of indirect taxes (Tax Mix 2), the ratio is smaller but parallels closely the alternate

definition (Tax Mix 1).

[Figure 2 about here.]

2Sample sizes for years 2007, 2008 and 2009 are reduced significantly, so the trend in these three yearsmay not be comparable to the previous years.

3Alternatively, property taxes can be considered as part of the indirect taxes. The data description belowconsiders both possibilities.

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3. Empirical Methodology and Data

Our main empirical strategy is to provide an assessment of the impact of tax structure

on both economic growth and income inequality and, on the way, shed some light on the

various growth-inequality tradeoffs in the design and overall structure of tax systems. To

achieve these goals, we estimate a simultaneous equations model based on the canonical

specifications for economic growth and inequality in the previous literature, and we introduce

a set of tax structure indicators into panel regressions, using a fairly large panel dataset built

with information from 150 countries over the period 1970 to 2009.

3.1. Specification and Estimation Issues

Specification. While the empirical literature on economic growth is vast and ever growing,

the literature to date has reached relatively little consensus on the determinants of income

inequality. The benchmark structural specification we employ here follows Lundberg and

Squire (2003), which is among the first to examine the joint determination of growth and

inequality by a series of other variables. As is also now standard in the literature, the

specification is estimated by transforming the yearly data into five-year intervals, in order

to control for the influence of business cycle fluctuations and the measurement error. More

specifically, we estimate the following structural model for growth and inequality,

Growthit = γGiniit + αTit + Xitβ + uit

Giniit = ϑGrowthit + θTit + Zitδ + εit

(1)

where i indicates country and t denotes five-year intervals (i.e., 1970-1974, 1975-1979,...,

2000-2004, and 2005-2009); Growthit represents the average annual growth rate of GDP per

capita (real); Giniit represents the Gini coefficient that we use as our measure of income

inequality; Tit is a set of variables of interest including a number of tax structure indica-

tors; Xit and Zit are vectors of control variables for the growth and inequality equations

6

respectively, as defined in Lundberg and Squire (2003).

The vector of “growth” variables Xit, which is in turn based on Barro (1991) and Easterly

et al. (1993), captures the best established factors of significance in determining economic

growth, including the initial income level, education level, government consumption, finan-

cial development, trade openness, inflation, and the overall tax burden. The initial income

level, measured as real GDP per capita at the beginning of each five-year period, is included

to capture a catching-up effect in countries with lower initial income. Education is generally

viewed as one of the main engines for economic growth, and it is measured by the average

years of schooling. The share of government consumption to GDP is expected to be neg-

atively associated with per capita GDP growth, as government consumption has no direct

effect on private productivity but lowers saving and growth through the distorting effects

from taxation. Financial development as measured by the ratio of M2 to GDP captures the

link between financial depth and economic growth—a relationship that is still a subject of

great disagreement and controversy among researchers. Trade openness, measured by the

ratio of total trade (imports plus exports) to GDP, aims to capture the exposure of a country

to globalization. An increase in inflation, measured by the annual percentage change in the

consumer price index, may reduce the level of business investment and the overall efficiency

with which productive factors are put to use. Finally, we include the overall tax burden,

measured as the share of total tax revenue in GDP, as an additional variable for controlling

the total tax level in the economy and it helps to control for revenue neutrality when we

analyze the effect of any given tax instrument.

The vector of “inequality” variables Zit, which originally come from Li et al. (1998),

includes education level, a measure of civil liberties, financial development, and a measure of

the distribution of land. Given that educational attainment is related to income and that low

education is highly correlated with poverty, it is expected to find less inequality in societies

with higher levels of education. In addition, a higher level of education also means that the

share of labor income in the total tends to be higher and that labor income tends to be more

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equally distributed than capital income. From a political economy perspective, civil liberties

can be expected to constrain the ability of the rich to influence policy in their favor, and so a

higher level of civil liberties may contribute to a lower level of inequality in society. Financial

development and distribution of land, measured by the ratio of M2 to GDP and the Gini

coefficient of land distribution respectively, are included to capture the access of the poor to

the financial market. A deeper development of the financial sector and a more equal land

distribution are expected to ease the access of the poor to credit and so contribute to a lower

level of inequality in the society. In addition, we include three dummy variables to control

for the differences in the definition and measurement units of the Gini coefficient. The first

dummy variable equals one if the Gini coefficient is based on net income (and zero otherwise);

the second dummy variable equals one if the Gini coefficient is based on expenditures (and

zero otherwise); the third dummy variable equals one if the Gini coefficient is based on

individual data (and equals zero if the Gini coefficient is based on household data). Finally,

distinguishing by the type of direct versus indirect taxes, it is expected that direct taxes,

especially for the personal income tax, will have a more direct impact on inequality measured

by net income; while indirect taxes, especially for the consumption tax, will have a more

direct impact on inequality based on expenditure. To capture these heterogeneous effects,

we include in the specifications an interaction term between direct (indirect) tax instruments

and the net income (expenditure) dummy variable.

We also include uit and εit as error terms. Following Easterly et al. (1993) and Lundberg

and Squire (2003), we assume that there is no correlation in growth rates and in inequality

across periods, while we do allow for country fixed effects in the growth equation so that uit =

ηi + eit. However, as in Muinelo-Gallo and Roca-Sagales (2013), we do not include country

fixed effects in the inequality equation. This is due to the fact that inequality varies much

more across countries than over time, and so this characteristic of the variance of inequality

cannot be examined by techniques that eliminate cross-country effects and focus exclusively

on the within-country relationship (Lundberg and Squire, 2003). In addition, taking out

8

fixed effects in the estimation of inequality is also likely to exacerbate the measurements

error (Banerjee and Duflo, 2003).

Endogeneity. An important potential problem concerns the endogeneity of the tax vari-

ables in estimating the structural model. A country’s tax structure design is very likely to

be affected by the economic business cycle and the social and political conditions that are

related to the country’s overall standing vis-a-vis economic growth and income distribution.

In the most common case, countries with slow growth or in a recession are more likely to

adopt reductions in tax rates as a way to boost the economy through more investment and

increased consumer demand. Countries with high and increasing income inequality may

adopt reforms that rely more heavily on direct taxes. In addition, endogeneity may also

arise automatically because tax collections increase (decrease) with income in an expanding

(shrinking) economy if the tax systems are income elastic.

In order to circumvent the endogeneity issue, we use an instrumental variable approach.

We modify Lee and Gordon (2005)’s approach to instrument our tax structure variable by

using the initial level of the corresponding weighted average of tax structure from neighboring

countries in the sub-period five-year intervals. The validity of these instruments are justified

by the conventional tax competition and tax mimicking literature as it argues that the

design of tax structure in a country will be correlated with the design of tax structure in

the neighboring countries, due to the fact that countries compete or mimic their tax policies

for attracting mobile tax bases. More specifically, the weighs we used for constructing the

instruments are the inverse of distance between two countries and the trade openness of a

country. The first weight reflects the standard practice in the spatial econometrics literature,

which assumes that geographically closer countries interact more strongly with each other;

and the second weight aims to approximate the relative level of exposure to tax competition

of a country (e.g., Devereux et al., 2008). Given that it takes time for a country to respond

to the change in tax policies in other countries, it is logical to expect that a country’s tax

structure is associated with the initial level of tax structure in the neighboring countries.

9

However, average economic growth and/or income distribution in a country in the later years

should virtually have no significant impact on the design of the tax system of the neighboring

countries in the initial year. It is this favorable feature that makes the weighted average tax

structures in neighboring countries in the initial year otherwise a good instrument for tax

structure in the home country.

Estimation approach. Estimation of the system equations (1) requires an effective method-

ology to tackle several econometric issues simultaneously. First, appearance of the growth

variable on the RHS of the inequality equation and vice versa creates the usual endogeneity

problem in the estimation of simultaneous equations, which renders OLS estimators biased.

Thus, we use an instrumental variable (IV) approach to correct this. Since we have only three

explanatory variables in common for the baseline growth and inequality models—education

level, financial development, and overall tax burden, the implicit assumption is that the

other explanatory variables in the growth equation do not affect inequality and so can serve

as instruments for the endogenous growth variable in the inequality equation, and similarly,

the other explanatory variables in the inequality equation do not influence growth and so can

serve as instruments for the endogenous inequality variable in the growth equation. Second,

it is the potential endogeneity issue of the tax structure variables as just discussed above.

We therefore employ the set of variables we laid out before as additional exogenous instru-

ments for the tax structure variables. Finally, the possible omitted variables would affect

both equations, leading to inefficiency caused by the possible correlation of the error terms

uit and εit in the system. Thus, we incorporate the seemingly unrelated regression model

(SURE) to extend the 2SLS to a 3SLS model in order to improve estimation efficiency.

3.2. Data

The data panel we use is unbalanced and variables are derived from various sources.

Our measure of income inequality, the Gini coefficient, is obtained from the UNU-WDIER

World Income Inequality Database. Tax variables in levels are taken from the Government

10

Finance Statistics of the International Monetary Fund (GFS-IMF). Top statutory income

tax rates and measures of tax progressivity are derived from the World Tax Indicators from

the International Center for Public Policy at Georgia State University, which compiled the

data from a combination of multiple sources. The average year of schooling as our measure of

education level is obtained from Barro and Lee (2001). Civil liberties are taken from Freedom

House, while land Gini values are provided by the FAO database. All the other economic

variables are derived from the World Development Indicator database. The data definitions

are presented in Table A1 in the Appendix and the summary statistics are reported in Table

1.

[Table 1 about here.]

Our variables of interest involve the measurement of the structure of tax systems in as

much detail as possible and over as long a period as possible. To do so, we construct a

series of tax structure indicators that capture various dimensions of the tax systems. These

include a set of the most important individual tax categories measured in levels (covering

PIT, CIT, and GTGS), top statutory tax rates for personal income tax (PITRate) and cor-

porate income tax (CITRate), an index evaluating the overall direct to indirect taxes mix

(Tax Mix 1 and Tax Mix 2), and an index reflecting the overall PIT tax progressivity. The

tax mix is measured by the ratio of direct taxes to indirect taxes, with property tax being

considered alternatively as either a direct tax or an indirect tax (Tax Mix 1 and Tax Mix

2). Structural tax progressivity is based on simulations of the countries’ personal income

tax system, including information on statutory tax rates, tax brackets, country-specific tax

legislation, basic allowances, standard deductions, tax credits, national surcharges, and lo-

cal taxes. For the estimations we use the average rate progression (ARP) constructed by

Klara Sabirianova Peter and Duncan (2010), which characterize the structural progressiv-

ity of national tax schedules with respect to the changes in average rates along the income

11

distribution.4

4. Empirical Results

This section discusses the 3SLS estimation results, taking into account the potential

reverse causality between growth and inequality and the endogeneity of the tax variables.

The F-statistics for first stage regression models are reported at the bottom of each table,

indicating the validity of the instruments used for the endogenous tax variables. Below, we

discuss the growth and distributional effects of tax structures measured by levels, rates, and

the overall tax mix and progressivity of the system, respectively. In all specifications, we

consider the inclusion and not the interaction terms between the tax instruments and the

definitions of the Gini index.

4.1. The Impacts of Tax Levels

Tax structure in this subsection is captured by a set of the most important individual

tax instruments, including personal income tax, corporate income tax, and general tax on

goods and services (i.e., the consumption tax). They are all measured in levels relative to

GDP. Table 2 reports the estimation results. Focusing on the tax variables, these results

suggest several main findings.

First, there exists clear evidence of a tradeoff between growth and inequality facing

governments in the design of their tax structures. Column (1) shows a negative coefficient

for the personal income taxes in both growth and inequality equations, indicating that an

increased reliance on personal income tax that is balanced by a decreased reliance on other

taxes tends to cut economic growth but also reduce income inequality at the same time.

4For ARP, Klara Sabirianova Peter and Duncan (2010) derive the progressivity measure as follows.Average tax rates are first computed for each country for each year at 100 different levels of pre-tax income,which are evenly spread in the range from 4 to 400 percent of a country’s GDP per capita. The averagerates (for each country and each year) are then regressed on the log of the 100 income data points that areformed around per capita GDP. A country’s tax structure in a particular year is interpreted as progressive,neutral or regressive if the estimated slope coefficient is positive, zero or negative.

12

In contrast, column (3) shows a positive effect for the greater reliance on the general tax

on goods and services on both growth and inequality, suggesting a shift in the opposite

direction to rely more on indirect taxes—the general tax on goods and services—would

tend to promote economic growth while worsen income inequality. Quantitatively, a one

percentage-point increase in the share of personal income taxes in GDP, on average, reduces

the growth rate by 1.62 percentage points while it lowers the Gini index by 0.40 points; a

one percentage-point increase in the share of the general tax on goods and services in GDP,

on average, increases the growth rate by 0.75 percentage points while it increases the Gini

index by 0.30 points. The opposite effects of these two tax instruments are in line with the

theoretical predictions that a revenue-neutral tax shift to personal income tax (consumption

tax) will reduce (increase) economic incentives for work effort and savings and investment,

resulting in lower (higher) rates of economic growth; while due largely to the progressivity

(regressivity) feature of the personal income tax (the consumption tax), at the same time

it will lessen (worsen) income inequality. These results are also in general consistent with

those that have been found in the previous literature relying on single equation estimations

(e.g., Arnold et al., 2011).

Second, the corporate income tax measured in levels turns out to have no significant

effects on either growth or inequality. Although the distributional effects of the corporate

income tax are theoretically less clear, as the final incidence of this tax on capital or labor

depends among other things on the openness of the economy (Harberger, 1962, 2006), it

would appear that our finding of an insignificant growth effect of the corporate income tax

(when it is measured in levels) is somehow inconsistent with those reported in previous

studies. These previous studies find in general a significant growth-retarding effect for the

corporate income tax based on data from high-income countries (e.g., Arnold et al., 2011;

Muinelo-Gallo and Roca-Sagales, 2011). Our finding of an insignificant growth effect of

the corporate income tax measured in levels may be simply due to the offsetting effects

from the higher provision levels of public service allowed by the associated revenues; these

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offsetting effects may be more pronounced in the case of developing countries, where public

services accessibility appears to be even more heterogeneous. To further investigate this

point, we divide our full sample into groups of developed countries and developing countries,

and re-estimate the structural model. We find that, consistent with the previous literature,

the growth effect of the corporate income tax is negative and significant at the margin

in developed countries, while it is not statistically significant in developing countries.5 In

addition, as we will see immediately below in the next subsection, the story for corporate

income tax is quite different when it is measured in rates which, it can be assumed, better

capture the marginal distortionary effects of the tax on economic behaviors.

Third, we find supporting evidence for the hypothesis that, depending on the type of

tax instrument, the impact on income inequality varies across different definitions of the

Gini index. More specifically, the inequality-reducing effect of the personal income tax is

stronger when the Gini is measured by net income, while the inequality-increasing effect

of the consumption tax is stronger when the Gini is measured on the basis of expenditure.

Looking at column (4) of Table 2, although the coefficient for the PIT in the inequality

equation becomes positive and significant, the estimated coefficient of the interaction term

is significantly negative and larger in magnitude. Taking the partial derivative of the Gini

index with respect to PIT and evaluating it at the mean value of the net income dummy

variable gives us the net effect of PIT on income inequality with a value of -0.10, indicating

that, on average, the net effect of PIT on income inequality remains negative and significant.

Meanwhile, the negative coefficient of the interaction term and its relatively large magnitude

clearly suggest that when inequality is measured by net income (i.e., Dummy netincome=1),

the inequality effect of PIT becomes much stronger (i.e. -0.67). Similarly, the estimated

coefficients of GTGS and its interaction term in column (6) are both positive, suggesting

that the inequality-increasing effect of the consumption tax is reinforced when inequality is

measured on the basis of expenditure. Lastly, the estimated coefficient for the CIT remains

5For space reasons these results on the subsamples of developed and developing countries are not reportedin the paper but are available on request.

14

statistically insignificant when the interaction term is included in the specification, and its

interaction term also has a statistically insignificant coefficient. This is not surprising as it is

not immediately clear how the corporate income tax may affect income inequality differently

on the basis of different definitions of the Gini index.

Concerning the control variables, the results are mostly consistent with those obtained

in the previous literature. For the growth equation, the coefficient for initial GDP per

capita is negative and significant, which is consistent with the assumption of the conditional

convergence of economic growth reported in previous studies (Barro, 1991; Mankiw et al.,

1992). The coefficient for education level is positively related to economic growth, confirming

the predictions of growth theory and consistent with the findings in many previous studies

(Barro, 1991; Mankiw et al., 1992; Arnold et al., 2011). Government consumption is neg-

atively associated with economic growth, as it lowers savings and thus growth through the

distorting effects from taxation. In spite of an unclear theoretical effect, our estimates reveal

a negative relationship between financial development and economic growth. Trade open-

ness and inflation, though having the expected signs, are not always statistically significant.

Last, the overall level of taxes is positively related to economic growth—a result, however, on

which no consensus has been reached in the literature (Arnold et al., 2011). For the inequality

equation, the net income/expenditure dummy variables and household/individual dummy

variable for the measurement of the Gini index are negative and statistically significant, a

result that coincides with that in Barro (2000). The estimated coefficient for overall level

of tax burden shows that it is inequality reducing. As for the rest of the control variables,

the results are broadly consistent with those in Li et al. (1998) and Lundberg and Squire

(2003)—the impacts of education level and financial development on inequality are consis-

tently negative and significant, while the impacts of the land Gini index and civil liberties are

positively related to inequality.6 Lastly, we address the potential reverse causality between

growth and inequality. Our results indicate that income inequality has a negative impact on

6Note that the index of civil liberties is defined from 1 to 7, with 1 assigned to countries with the largestdegree of civil liberties. So higher values of the index refer to lower civil liberties.

15

economic growth; however, this impact is not always statistically significant across different

specifications. On the other hand, economic growth turns out to be consistently negative

and significant associated with income inequality across all specifications, indicating that

an effective pathway to alleviate income inequality is through the promotion of economic

growth.

[Table 2 about here.]

4.2. The Impacts of Tax Rates

In this subsection, we explore the impact of tax structure when it is measured by tax

rates. Given data availability, we only look at the top statutory tax rates for the personal

income tax (PITRate) and the corporate income tax (CITRate), which by far are the two

tax rates that have been analyzed most often in the literature. These two rates also have

been observed to drop considerably over the past decades (see Figure 3).

[Figure 3 about here.]

The estimation results are reported in Table 3. Consistently, columns (1) and (3) reveal

that an increase in the top statutory rate for personal income tax leads to lower rates of

economic growth with a lower level of income equality, and the inequality-reducing effect

of personal income tax rate becomes stronger when the Gini index is measured by net

income. In magnitude, these effects are smaller relative to the corresponding case in levels:

a one percentage-point increase in the top statutory tax rate for the personal income tax

is correlated with a 0.06 percentage point decrease in economic growth rate and a 0.09

percentage point decrease in the Gini index. In contrast to what we found in the previous

subsection for the measurement in levels, columns (2) and (4) show that when the corporate

income tax is measured by the top statutory tax rate, this tax has the expected negative

and significant effect on both growth and inequality. This effect is about two to three times

stronger than that of the personal income tax rate. That is, a one percentage-point increase

16

in the corporate tax rate is associated with 0.20 percentage point decrease in the growth rate

and 0.31 percentage point decrease in the Gini index. We have seen that when the corporate

income tax is measured in levels the economic impact can be mixed and this may be due to

the fact that the higher revenues may allow larger amounts of productive public expenditure

in the country. In contrast, when we use the top statutory rate of the corporate income tax

we are mostly capturing both the degree of progressivity and the (negative) incentive effects

of this tax instrument on economic activity at the margin. Thus, it is this last feature that

likely drives the corporate income tax rate to have a significant effect on both growth and

inequality. These results are consistent with those obtained by Lee and Gordon (2005) for

economic growth. Finally, it is worth noting that, even though it is not entirely clear, the

directions in which the corporate income tax rate may affect income inequality differently

based on different definitions of the Gini index, the positive coefficient of the interaction term

in column (4) of Table 3 suggests that the inequality-reducing effect of this tax instrument

becomes smaller when inequality is measured as net income of individuals or households.

The remaining control variables in both the growth and inequality equations are generally

unchanged, with the exception that the impact of the Gini index on economic growth is now

mostly insignificant.

[Table 3 about here.]

4.3. The Impacts of Tax Mix and Tax Progressivity

Turning to the overall design of tax structure, we focus on two additional indicators—tax

mix and structural tax progressivity. Table 4 presents the estimation results. As shown, the

results generally validate the conjectures that have long stood in the theoretical tax literature

and echo the conclusions of some existing empirical studies based on single equation analysis

such as Martinez-Vazquez et al. (2011) and Duncan and Sabirianova Peter (2012). That

is, given overall tax revenues as constant, a shift from indirect taxes to direct taxes lowers

economic growth but reduces income inequality (columns (1) and (2)), while an increase

17

in the extent of overall tax progressivity leads to a lower level of economic growth but a

more equal distribution of income (column (3)). Quantitatively, however, the overall impact

of the shift from indirect taxes to direct taxes is small. A full one ratio point (equivalent

to 100 percentage points) increase in the ratio of direct to indirect taxes is correlated with

only a 2.21 percentage point decrease in the growth rate and with only 0.96 point decrease

in the Gini index (based on column (1)). This small effect in turn is due largely to the

offsetting of the varied impacts of individual tax instruments we found in subsection 4.1. On

the other hand, a one point increase in the ARP index contributes to a 0.66 point decrease

in the growth rate and to a 0.35 point decrease in the Gini index. Last, consistent with

the preceding results, the inequality-reducing effects for a shift from indirect taxes to direct

taxes and/or an increase of tax progressivity tend to be larger when the Gini is measured

on the basis of net income inequality.7

[Table 4 about here.]

5. Growth versus Inequality Tradeoff: Policy Simulations

From a policy perspective, our results above document the existence of the much discussed

classic trade-off between growth and inequality involved in the design of major tax policy

reforms, including income taxes and general consumption taxes. In order to visualize the

magnitude of the real impact of choices in tax systems around the world, we estimate the

tradeoff as a combination of the estimated marginal effects of each tax instrument and the

actual policy change in the use of that tax instrument. Thus, even though a particular

instrument may be relatively ineffective—having a relatively small marginal impact—this

may be more than offset by a large change in the use of that instrument, and vice versa.

Table 5 summarizes the final effects for each tax instrument having statistically significant

coefficients (based on specifications without considering the interaction term) and allowing

7Similarly, although the estimated coefficient of ARP is positive in column (6) of Table 4, its net impacton income inequality is negative after taking into accounting the effects of the interaction term.

18

a change in the usage of the instruments that is equal to the overall change between 1981

and 2005.8 The results are clearly general averages for a large number of countries and for

a long period of time. However, we believe they represent good summary indicators of the

overall effects of tax policies on both the trends of economic growth and income distribution

worldwide over a quarter century.

[Table 5 about here.]

In summary, the worldwide change in tax structure in recent times has been in the direc-

tion of favoring economic growth, even though both the growth and distributional impacts

of this change in reality, on average, have not been very large. Specifically, the economic

significance (marginal effects) of personal income tax seemed to be offset by the relatively

small changes in its usage (i.e., a decrease of 0.25 percentage point), resulting in an increase

of 0.41 percentage point in economic growth as well as 0.1 percentage point increase in in-

come inequality. The general tax on goods and services increases in size by 1.94 percentage

points led to an increase of 2.38 percentage points in economic growth accompanied by a

0.78 percentage point increase in income inequality. Overall, the net effect of changes in

these major tax instruments worldwide over the period 1981-2005 resulted in an increase in

economic growth of about 2.35 percentage points and an increase in income inequality of

only 0.88 percentage points.

Looking at the effect of changes in the top statutory tax rate for income taxes, the

relative small marginal effects have been augmented by a large drop in their usage, leading

to a modest impact on both growth and inequality. In particular, the top statutory corporate

(personal) income tax rate decreases in size by 12.41 (19.58) percentage points led to a 2.48

(1.18) percentage point increase in economic growth accompanied by a 3.85 (1.76) percentage

point increase in income inequality.

8The selection of the focus on this period is because we have a larger sample of countries in this period,which makes our calculation over the period more comparable.

19

Last, despite the fact that the direct to indirect taxes ratio has experienced a reduction

of about 0.4 ratio points (equivalent to 40 percentage points), it only led to very minor

increases in both economic growth and income inequality (less than 1.3 and 0.6 percentage

points, respectively). This is mostly due to the relatively small marginal effects. Personal

income tax progressivity tends to have a larger effect on economic growth than on income

distribution, and so a modest decrease in the level of tax progressivity (about 0.85 percentage

point) resulted in a 0.56 percentage point increase in economic growth accompanied by a

0.30 percentage point increase in income inequality.

6. Conclusion

In this paper we have examined the potential tradeoff between economic growth and

inequality in income distribution in the design of tax structures by using a large panel data

set of 150 developed and developing countries for approximately the last four decades. While

the literature on optimal taxation does not provide exact guidelines for the design of tax

systems, it is generally understood that optimal tax design requires the use of both direct

and indirect taxes, leaving quite open what the optimal tax mix should actually be. The

recent empirical studies based on endogenous growth models have shown that heavy reliance

on different forms of direct taxation has significant negative effects on the rate of economic

growth. On the other hand, a less plentiful but nevertheless robust literature on the effects

of taxation on income distribution shows that heavier reliance on progressive direct taxes

can have an equalizing effect on income distribution.

In this paper we find evidence of an explicit tradeoff between growth and inequality for

an overall choice of direct versus indirect taxes, level of tax progressivity, and some major tax

categories including income taxes and general consumption taxes. Our empirical results also

highlight the importance of differentiating among the definitions of income inequality (i.e.,

gross income, net income, or expenditure) when exploring the inequality effects of various tax

20

instruments and the importance of differentiating the measurement of the corporate income

tax (i.e., tax level or tax rate) when exploring its economic impacts. Nevertheless, given the

various potential tradeoffs detected, another important finding in this paper is that overall,

from a policy perspective, the impact of the changes in tax structure in reality on economic

growth and income inequality has not been very large—between 1981 and 2005 the average

tax structure change made by countries in our sample implied 2.35 percentage points higher

economic growth but also 0.88 percentage points higher inequality in income distribution

measured by the Gini coefficient.

Also from a policy perspective it is necessary to keep in mind that tax structure choices

can also significantly affect other important economic policy goals for governments. In par-

ticular, the heavier use of direct forms of taxation with significant progressivity also can

contribute to macroeconomic stability via the work of automatic tax stabilizers. Thus from

this perspective, the tradeoff is not only between growth and inequality but also macroeco-

nomic stability. Other economic goals worth pursuing, especially for developing countries,

may include the attraction of foreign direct investment, which may respond positively to

lower relative use of direct taxation, in particular corporate income taxes. Therefore, lower

relative usage of direct taxes may not only lead to faster economic growth but also reinforce

it through the attraction of foreign direct investment. In reality, different countries make

different choices on tax design in large part reflecting the relative importance they give to

different economic goals at their individual stage of development. Thus, it is interesting to

observe that developing countries on average are making considerably heavier use of indirect

over direct taxes. This reveals a higher weight being given in their social preferences to

economic growth over income inequality.

21

Appendix

Table A1: Description of Variables and Sources

Variable Description SourceGrowth Growth rate of real GDP per capita, % World Development Indica-

tors (WDI)Gini coefficient Gini coefficient, % World Income Inequality

Database (WIID)Initial income Initial GDP per capita, 1,000$ WDIEducation Average years of schooling for population aged 25 or order Barro and Lee (2010)Government consumption Government consumption, % of GDP Penn World TablesM2/GDP M2/GDP, % WDIOpenness Import plus export, % of GDP WDIInflation Annual percent change in consumer prices, 1/10,000 WDIDummy netincome =1 if Gini coefficient is based on net income, 0 otherwise WIIDDummy expenditure =1 if Gini coefficient is based on expenditure, 0 otherwise WIIDDummy: individual vs.household

=1 if Gini coefficient is based on individual data, 0 other-wise

WIID

Land Gini Land Gini coefficient, % FAO databaseCivil liberties Index on a scale of 1 to 7, with 1 representing the higher

level and 7 representing the lower level of civil liberties.Freedom house

Overall tax burden Total tax revenues, % of GDP Government Finance Statis-tics (GFS), OECD RevenueStatistics

PIT Personal income tax, % of GDP GFS, OECD Revenue Statis-tics

CIT Corporate income tax, % of GDP GFS, OECD Revenue Statis-tics

SSCPAY Social security and payroll taxes, % of GDP GFS, OECD Revenue Statis-tics

PROP Property tax, % of GDP GFS, OECD Revenue Statis-tics

GTGS General tax on goods and services, % of GDP GFS, OECD Revenue Statis-tics

EXC Excises tax, % of GDP GFS, OECD Revenue Statis-tics

CUST Customs duty, % of GDP GFS, OECD Revenue Statis-tics

PITRate Top statutory tax rate of personal income tax, % World Tax Indicators (WTI)CITRate Top statutory tax rate of corporate income tax, % WTITax Mix 1 Direct (personal and corporate income tax, payroll tax, so-

cial security contributions, property tax) to indirect (taxon goods and services, excise tax, custom duty) taxes ratio

GFS, OECD Revenue Statis-tics

Tax Mix 2 Direct (personal and corporate income tax, payroll tax, so-cial security contributions) to indirect (property tax, gen-eral tax on goods and services, excise tax, custom duty)taxes ratio

GFS, OECD Revenue Statis-tics

ARP Average rate progression up to an income level equivalentto four times countries’ per capita GDP in local currency

WTI

22

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25

Tab

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26

Table 2: Effects of Tax Structure Measured by Levels: 3SLS Estimations

(1) (2) (3) (4) (5) (6)PIT CIT GTGS PIT CIT GTGS

Growth EquationGini index -0.11 -0.13* -0.14** -0.07 -0.11* -0.15**

(-1.53) (-1.74) (-2.09) (-0.98) (-1.74) (-2.26)Initial income -0.24*** -0.14* -0.13** -0.26*** -0.17** -0.15***

(-4.60) (-1.76) (-2.40) (-4.91) (-2.28) (-2.71)Education 0.48*** 0.09 -0.31 0.54*** 0.13 -0.23

(2.86) (0.48) (-1.31) (3.16) (0.72) (-1.03)Government -0.37*** -0.31** -0.31*** -0.38*** -0.29*** -0.31***

(-4.73) (-2.54) (-4.43) (-4.76) (-2.63) (-4.49)M2/GDP -0.04*** -0.02** -0.02*** -0.04*** -0.02** -0.02***

(-3.94) (-2.17) (-3.00) (-4.18) (-2.18) (-2.80)Openness 0.01 0.01 0.00 0.01 0.01 0.00

(1.48) (0.97) (0.46) (1.50) (0.85) (0.38)Inflation -0.12* -0.12 -0.01 -0.11 -0.10 -0.03

(-1.84) (-1.45) (-0.17) (-1.64) (-1.35) (-0.40)Overall tax burden 0.17*** 0.09 -0.04 0.19*** 0.07 -0.03

(3.55) (1.06) (-1.13) (3.95) (0.92) (-0.81)Tax instrumenta,b -1.62*** -0.45 0.75*** -1.84*** -0.29 0.64***

(-3.54) (-0.78) (2.91) (-4.07) (-0.58) (2.59)R-squared 0.143 0.280 0.333 0.088 0.316 0.346Gini EquationGrowth rate -1.17*** -1.31*** -1.19*** -1.09*** -1.39*** -1.22***

(-5.08) (-5.54) (-5.27) (-4.85) (-5.75) (-5.47)Dummy netincome -4.88*** -5.16*** -5.08*** 0.56 -3.22* -4.56***

(-4.74) (-4.95) (-4.99) (0.38) (-1.95) (-4.43)Dummy expenditure -9.94*** -9.13*** -9.81*** -9.09*** -8.96*** -13.28***

(-8.08) (-7.29) (-7.85) (-7.48) (-7.11) (-7.42)Dummy: individual -9.67*** -9.86*** -9.77*** -11.11*** -9.66*** -9.61***

vs. household (-5.31) (-5.27) (-5.41) (-6.17) (-5.16) (-5.38)Education -0.44** -0.66*** -0.64*** -0.62*** -0.63*** -0.67***

(-2.14) (-3.29) (-3.07) (-3.06) (-3.14) (-3.25)M2/GDP -0.02*** -0.02** -0.02** -0.02*** -0.02** -0.02***

(-3.05) (-2.48) (-2.44) (-3.06) (-2.03) (-2.65)Land Gini 0.11*** 0.15*** 0.15*** 0.08*** 0.15*** 0.14***

(3.96) (5.96) (5.96) (2.97) (5.90) (5.75)Civil liberties 1.47*** 1.42*** 1.52*** 1.76*** 1.42*** 1.56***

(3.81) (3.72) (4.06) (4.60) (3.70) (4.20)Overall tax burden -0.15*** -0.22*** -0.29*** -0.09* -0.22*** -0.27***

(-2.64) (-4.58) (-5.52) (-1.73) (-4.47) (-5.07)Tax instrumenta,b -0.40*** -0.00 0.30† 0.33* 0.15 0.03‡

(-3.08) (-0.01) (1.57) (1.70) (0.67) (0.13)Interaction termc -1.00*** -0.73 0.96***

(-5.01) (-1.53) (2.70)F-test for 1st stage 109.15 9.11 23.44 106.52 8.87 23.12Observations 344 357 366 344 357 366R-squared 0.540 0.527 0.542 0.561 0.519 0.552Notes: t-statistics in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. a: Tax instrument represents the corresponding

tax indicator noted on the top of each column. b: Tax instrument is treated as endogenous variable and is instrumentedby distance-weighted average of tax variables and openness-weighted average of tax variables from neighboring countries.c:Interaction term=PIT/CIT*Dummy netincome or =GTGS*Dummy expenditure. † represents significance at the 10% level

under one-tail test. ‡ represents the joint test for the tax variable and its interaction term is significant at the 1% level.

27

Table 3: Effects of Tax Structure Measured by Rates: 3SLS Estimations

(1) (2) (3) (4)PITRate CITRate PITRate CITRate

Growth EquationGini index -0.08 -0.10 -0.06 -0.12*

(-1.29) (-1.55) (-0.96) (-1.80)Initial income -0.30*** -0.20*** -0.30*** -0.20***

(-4.98) (-3.92) (-4.98) (-3.85)Education 0.32 -0.01 0.35 -0.05

(1.11) (-0.02) (1.24) (-0.18)Government -0.29*** -0.18* -0.29*** -0.17*

(-3.69) (-1.95) (-3.68) (-1.87)M2/GDP -0.02*** -0.02*** -0.02*** -0.02***

(-2.62) (-2.80) (-2.58) (-2.88)Openness -0.00 -0.02 -0.00 -0.02*

(-0.38) (-1.61) (-0.38) (-1.68)Inflation -0.10* -0.13** -0.10* -0.14**

(-1.70) (-2.09) (-1.66) (-2.21)Overall tax burden 0.06* 0.03 0.06** 0.03

(1.90) (1.03) (1.99) (1.03)Tax instrumenta,b -0.06** -0.20*** -0.06* -0.22***

(-1.98) (-2.99) (-1.87) (-3.37)R-squared 0.492 0.393 0.503 0.368Gini EquationGrowth rate -1.05*** -1.30*** -0.99*** -1.33***

(-5.08) (-6.18) (-4.80) (-6.39)Dummy netincome -5.97*** -6.82*** -2.60 -10.86***

(-5.58) (-6.65) (-1.14) (-3.59)Dummy expenditure -11.13*** -10.71*** -11.13*** -10.59***

(-8.61) (-8.66) (-8.69) (-8.58)Dummy: individual -11.95*** -10.30*** -12.12*** -10.57***

vs. household (-6.16) (-5.63) (-6.29) (-5.77)Education -0.80*** -0.90*** -0.77*** -0.89***

(-3.79) (-4.35) (-3.67) (-4.34)M2/GDP -0.02*** -0.02*** -0.02** -0.02***

(-2.67) (-3.53) (-2.57) (-3.44)Land Gini 0.14*** 0.14*** 0.14*** 0.14***

(5.92) (5.99) (6.07) (5.91)Civil liberties 0.87** 1.21*** 0.80** 1.17***

(2.35) (3.36) (2.16) (3.24)Overall tax burden -0.31*** -0.25*** -0.32*** -0.26***

(-6.51) (-5.32) (-6.71) (-5.50)Tax instrumenta,b -0.09*** -0.31*** -0.03‡ -0.36***

(-3.19) (-6.37) (-0.69) (-6.01)Interaction termc -0.08* 0.12‡

(-1.68) (1.43)F-test for 1st stage 22.31 9.31 22.33 9.19Observations 321 343 321 343R-squared 0.624 0.595 0.631 0.595Notes: t-statistics in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. a: Tax instrument

represents the corresponding tax indicator noted on the top of each column. b: Tax instrumentis treated as endogenous variable and is instrumented by distance-weighted average of tax vari-ables and openness-weighted average of tax variables from neighboring countries. c:Interaction

term=Tax instrument*Dummy netincome. ‡ represents the joint test for the tax variable and itsinteraction term is significant at the 1% level.

28

Table 4: Effects of Tax Mix and Tax Progressivity: 3SLS Estimations

(1) (2) (3) (4) (5) (6)Tax Mix 1 Tax Mix 2 ARP Tax Mix 1 Tax Mix 2 ARP

Growth EquationGini index -0.12 -0.11 0.01 -0.10 -0.08 0.07

(-1.61) (-1.45) (0.07) (-1.41) (-1.07) (0.83)Initial income -0.13* -0.16*** -0.36*** -0.14** -0.18*** -0.43***

(-1.88) (-2.63) (-4.19) (-2.14) (-2.97) (-4.93)Education 0.12 0.04 0.35** 0.12 0.06 0.37*

(0.71) (0.22) (1.96) (0.72) (0.35) (1.93)Government -0.46*** -0.54*** -0.33*** -0.45*** -0.51*** -0.35***

(-3.99) (-4.02) (-3.82) (-3.91) (-4.04) (-3.68)M2/GDP -0.03*** -0.03*** -0.03*** -0.02** -0.03*** -0.03***

(-2.60) (-2.78) (-3.06) (-2.54) (-2.69) (-3.06)Openness 0.01 0.01 0.02 0.01 0.01 0.02*

(0.67) (1.03) (1.48) (0.78) (1.11) (1.70)Inflation -0.12 -0.12 -0.06 -0.11 -0.10 -0.04

(-1.54) (-1.43) (-0.97) (-1.44) (-1.33) (-0.70)Overall tax burden 0.14*** 0.17*** 0.03 0.13*** 0.16*** 0.04

(2.68) (2.93) (0.97) (2.58) (2.97) (1.32)Tax instrumenta,b -2.21** -3.17** -0.66** -2.01** -2.83** -0.89***

(-2.19) (-2.53) (-2.14) (-2.02) (-2.39) (-3.08)R-squared 0.317 0.241 0.473 0.342 0.303 0.424Gini EquationGrowth rate -1.13*** -1.07*** -1.41*** -1.27*** -1.21*** -1.18***

(-4.78) (-4.56) (-6.17) (-5.35) (-5.19) (-5.46)Dummy netincome -6.07*** -5.87*** -5.79*** -0.76 0.57 2.54

(-5.53) (-5.46) (-5.06) (-0.43) (0.31) (1.42)Dummy expenditure -10.13*** -10.11*** -11.53*** -9.12*** -9.29*** -9.36***

(-7.45) (-7.49) (-8.08) (-6.58) (-6.86) (-6.62)Dummy: individual -8.56*** -8.61*** -11.93*** -8.66*** -9.10*** -12.47***vs. household (-4.20) (-4.23) (-5.81) (-4.26) (-4.51) (-6.31)Education -0.48** -0.56*** -0.49** -0.55** -0.60*** -0.68***

(-2.23) (-2.67) (-2.19) (-2.52) (-2.89) (-3.18)M2/GDP -0.02** -0.02** -0.02*** -0.01 -0.01** -0.01**

(-2.16) (-2.46) (-2.77) (-1.38) (-2.08) (-2.27)Land Gini 0.15*** 0.15*** 0.11*** 0.13*** 0.12*** 0.06**

(5.97) (6.02) (3.92) (4.74) (4.32) (2.11)Civil liberties 1.42*** 1.45*** 0.73* 1.29*** 1.23*** 0.52

(3.57) (3.64) (1.92) (3.22) (3.11) (1.42)Overall tax burden -0.19*** -0.16*** -0.35*** -0.14*** -0.09* -0.26***

(-3.84) (-3.07) (-6.28) (-2.86) (-1.75) (-4.71)Tax instrumenta,b -0.96** -1.46** -0.35* -0.03‡ -0.15‡ 0.71***

(-2.40) (-2.50) (-1.72) (-0.05) (-0.23) (2.71)Interaction termc -2.89*** -4.72*** -1.80***

(-3.81) (-4.28) (-5.93)F-test for 1st stage 27.57 15.79 27.63 26.76 15.35 27.63Observations 330 330 299 330 330 299R-squared 0.546 0.549 0.623 0.542 0.556 0.661Notes: t-statistics in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. a: Tax instrument represents the corresponding tax

indicator noted on the top of each column. b: Tax instrument is treated as endogenous variable and is instrumented by distance-weighted average of tax variables and openness-weighted average of tax variables from neighboring countries. c:Interaction term=Tax

instrument*Dummy netincome. ‡ represents the joint test for the tax variable and its interaction term is significant at the 1% level.

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Table 5: Policy Simulation of the Impact of Tax Policies, 1981-2005

Policy Instrument Estimated Marginal Effectsa Changes between Resulting economic effectGrowth Inequality 1981 and 2005b Growth Inequality

Individual Tax InstrumentPIT -1.62 -0.40 -0.25 0.41 0.10CIT - - -0.07 - -GTGS 0.75 0.30 2.59 1.94 0.78Total effect 2.35 0.88

Top Statutory Tax RatePITRate -0.06 -0.09 -19.58 1.18 1.76CITRate -0.20 -0.31 -12.41 2.48 3.85

Overall Tax SystemTax Mix1 -2.21 -0.96 -0.40 0.88 0.38Tax Mix2 -3.17 -1.46 -0.39 1.24 0.57ARP -0.66 -0.35 -0.85 0.56 0.30Notes: a: Estimated marginal effects are based on 3SLS estimations and are only reported for those tax instrumentshaving statistically significant coefficients. b: The changes are calculated at the difference between the two extremeyears, 1981 and 2005. Excepting changes in Tax Mix 1 and Tax Mix 2, all others are interpreted as changes inpercentage points. Changes in Tax Mix 1 and Tax Mix 2 are the difference between the values of two ratios.

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02

46

8%

of G

DP

1970 1980 1990 2000 2010

PIT CIT SSCPAY PROPGTGS EXC CUST

Figure 1: Average Annual Tax Structure as a Share of GDP: 1972-2009Source: Authors’ calculations; IMF GFS Database; OECD Revenue Statistics.Note: Sample sizes for years 2007, 2008 and 2009 are reduced significantly, so the trend inthese three years may not be comparable to the previous years.

31

 

0.5

11.

52

2.5

Dire

ct to

Indi

rect

Tax

Rat

io

1970 1980 1990 2000 2010

Tax Mix 1 Tax Mix 2

Figure 2: Average Annual Direct to Indirect Taxes Ratio: 1972-2009Source: Authors’ calculations; IMF GFS Database; OECD Revenue Statistics.Note: In Tax Mix 1, property taxes are taken as direct taxes; while in Tax Mix 2, propertytaxes are taken as indirect taxes.

32

 

3035

4045

50To

p St

atut

ory

Tax

Rat

e

1970 1980 1990 2000 2010

PITRate CITRate

Figure 3: Top Statutory PIT and CIT Rates, 1970-2005Source: World Tax Indicators

33