1. Firms, Households, and the Public Sector

Physical output is produced with a constant returns to scale (CRS) technology that uses human capital H and physical capital K as inputs. The technology takes the Cobb-Douglas form:

where ν (u) is the fraction of K (H) devoted to the production of goods. K and H depreciate at the rate δ.

Human capital creation is a non-market activity, and H is produced with a CRS technology that uses both human and physical capital as inputs, as in Rebelo (1991). The production function is Cobb-Douglas: ^1/

where 1 - ν (z) is the fraction of K (H) devoted to the accumulation of human capital. Equations (1) and (2) assume implicitly that “point-in-time technologies” are linear: if a fraction ν of the capital stock is employed in the production of final goods, the “effective capital” is vK. ^2/

The government finances exogenous paths of public expenditures and lump-sum transfers by levying taxes on factor incomes and consumption. For simplicity, we impose a balanced-budget condition:

where G_t is government expenditure, S_t are transfers and T_t is total tax revenue. In every period, the resource constraint of the economy is given by:

where C is private consumption.

The economy is inhabited by identical atomistic agents, who own the factors of production. They accumulate human capital, rent physical and human capital to firms, and choose consumption, investment and the allocation of human and physical capital so as to maximize an intertemporal utility function: ^3/

where ρ is the rate of time preference and 1 is leisure time. The instantaneous utility function u (.) takes a Constant Intertemporal Elasticity of Substitution (CIES) form:

where θ is the inverse of the intertemporal elasticity of substitution. This functional form is consistent with a balanced growth path, as shown by King et al. (1988). Households take the paths of factor returns, transfers and tax rates as given and choose the paths of C, K, H, u, v, z to maximize (5) subject to the constraint on human capital accumulation given by (2) and to the following budget constraint:

where R^K, R^H, τ^K and τ^H are the rates of return and the tax rates on capital and labor income, respectively, and τ^C is a consumption tax. Total tax revenues T are equal to τ^KR^KvK + τ^HR^HuH + τ^C C. Each individual’s time endowment is normalized to one:

Firms rent capital from households at the rate of interest R^K, hire labor at the wage rate R^H and use these inputs to produce output with the technology defined in (1). They hire labor and capital up to the point at which their marginal products equate marginal costs:

2. Balanced Growth Competitive Equilibrium

We focus on competitive equilibria in which the economy exhibits a balanced growth path, along which consumption, physical capital and human capital grow at the common rate γ, while factor allocations (u, ν and z) remain constant. Let r be the after-tax net rate of return on physical capital, r = R^K (1 - τ) - δ. The following equilibrium conditions describe the behavior of the economy along the balanced growth path: ^1/

Equation (11) is the usual condition linking the growth rate to the difference between the return on capital and the rate of time preference, adjusted for intertemporal substitution. Equation (12) determines the net, after-tax marginal product of physical capital r. Equation (13) and (14) reflect arbitrage conditions: (13) equates rates of return between sectors producing goods and human capital, and (14) equates rates of return on physical and human capital in the two sectors. Equation (15) describes equilibrium in the human capital accumulation process--human capital grows at the same rate as consumption and physical capital. Equation (16) reflects the equality between the marginal rate of substitution in consumption and leisure and the real rate of return on human capital. Equation (17) is the aggregate resource constraint.

3. Effects of Taxation on Long-Run Growth and Transmission Channels

The system (11)-(17) determines the values of γ, r, K/H, C/H, u, ν and z as functions of technology parameters and of the exogenous fiscal variables τ^C, τ^H, τ^K and G/K. The following semi-reduced form expression for the growth rate follows from (11)-(14):

where D = (αA)^β [β(1-β)]^1-α [(1-α)β/α(1-β)]^β(1-α) is a function of the technology parameters α, β, A and B.

Inspection of (11)-(17) and (18) reveals that in general all three tax rates affect long-run growth in the benchmark model. The channels through which taxes affect growth are the following:

c. Tax on Consumption:

• (C.1) τ^C affects the labor/education - leisure decision (u + z), which in turn affects the capital/labor ratio in production. The effect on growth is negative.

Following Devereux and Love (1994), one can prove that the overall growth effects of physical and human capital income taxes and consumption taxes in the benchmark model are always negative. Modifications of the model affect some or all of the transmission channels listed above and hence yield different effects for a particular tax change on growth. Consider in particular the following modifications: ^2/

Case A: Physical capital does not enter in the production of H (β = 0), as in Lucas (1990). Here channel H.1 is neutralized and a tax on human capital affects growth only through its impact on the work/leisure decision, thus becoming analogous to a consumption tax.

Case B: Human capital is a market good and its factor income returns are taxed at the same rates as in the final goods sector (Pecorino, 1993 and Stokey and Rebelo, 1993). The semi-reduced form expression for growth becomes:

$\begin{array}{cc}\gamma =\frac{1}{\theta }\text{([}D\text{(}1-{\tau }^K\text{)}{}^{\beta }\text{(}1-{{\tau }^H\text{)}}^{1-\alpha }{\left(u+z\right)}^{1-\alpha }{\text{]}}^{\frac{1}{1-\alpha +\beta }}-\rho -\delta \text{)}& \left(19\right)\end{array}$

In this case all the transmission channels are operative and the overall impact of income taxes on growth is enhanced through the addition of direct effects of taxation on the returns paid on H. When H is a tax-free sector, these adverse growth effects of higher taxes are mitigated by the fact that higher taxes reduce the opportunity cost of education, and not only its future returns. This is no longer true when factor incomes on H are taxed. A comparison of (19) with (18) shows that the exponents on (1 - τ^K) and (1 - τ^H) are larger in (19). Note that if factor incomes in the H sector are taxed, but they are given preferential tax treatment relative to other factor incomes, these additional negative growth effects of taxation are less severe.

Case C: Leisure is quality time/home production (CRS in H and/or K). In this case the term u + z does not appear in equation (13), and the system can be solved recursively with equations (11)-(14) determining γ, r, vK/uH and (1 - v)K/zH (as in Rebelo (1991) and Milesi-Ferretti and Roubini (1994)). Because now the accumulation of human capital increases the utility of leisure, channels K.3, H.2, and C.1 are neutralized and hence the consumption tax has no growth effects. If, in addition, β = 0, K.1 and K.2 exactly offset each other and H.1 is neutralized, so that all taxes have no growth effects. This is because higher income taxes reduce the returns on education and its opportunity cost by the same amount, leaving the choice to invest time in education unaffected.

Case D: No leisure (η = 0). In this case u + z = 1 in equation (13) and the system can be solved recursively as in Case C. This also implies that channels K.3, H.2 and C.1 are neutralized. As above, a consumption tax has no growth effects. The intuition for these results is as follows. Since leisure does not bring utility, total labor supply (in the production and education sectors) is inelastic, and therefore a consumption tax is non-distortionary in the long run. Furthermore, if physical capital does not enter in the production of human capital (β = 0), income taxes do not affect growth for the same reasons as in Case C.

The above discussion shows that, in general, taxes on human and physical capital reduce growth, while the effects of a consumption tax are more ambiguous, and depend in particular on the elasticity of labor supply (i.e. on the specification of the leisure activity). Two other factors also play an important role in determining the quantitative impact of taxes on economic growth: the technology and the tax treatment in the human capital accumulation sector. In particular, the growth effect of taxes on human and physical capital when factor incomes in the H sector are untaxed are proportional to β, the share of physical capital in the production of human capital (the limiting case being no effects on growth if β = 0). Alternatively, when human capital is a “market” sector whose factor income returns are taxed, the growth-reducing effects of capital and labor income taxes are enhanced.

It is also worth noting that most of the channels of transmission that explain the growth effects of taxation affect the ratio of investment on physical capital relative to output. This is important to note because of the important role that the investment rate plays as an explanatory variable in some empirical growth studies. In contrast, in the class of models reviewed here, both investment and growth rates are simultaneously determined by the values of the tax rates and other parameters. In the benchmark model, an increase in τ^K generally reduces the physical investment rate, while an increase in τ^H reduces the investment rate in education. The effect of a higher τ^H on the physical investment rate is, however, ambiguous, as we show in the simulations that follow. Moreover, intuition suggests that rising τ^C reduces the consumption-output share, and thus should increase the investment rate. ^1/ Thus, it is important that empirical analysis takes into account the endogeneity of the investment rate with respect to tax policy.

We conduct next some numerical simulations to illustrate how the quantitative effects of taxes on growth and investment depend on model specification. The simulations are based on parameters calibrated to approximate the “normal” growth rate of large industrial countries, at about 3 percent, and their shares of investment and tax revenue in GDP for the benchmark model in which H is a non-market sector. Tax rates and the share of g in GDP were set to match values for the U.S. economy reported in Mendoza and Tesar (1995). For model specifications other than the benchmark, we adjust the productivity constant of the H sector (B) so as to maintain initial growth at 3 percent in all experiments. We examine the implications for the growth rate and the physical investment rate that follow from reducing τ^K and τ^H, and rising τ^C, one at a time by 10 percentage points and from increasing the share of g in GDP by 5 percentage points.

The results of the simulations are reported in Table 1. For all model specifications, except model v, the largest growth effects follow from a reduction in τ^H, relative to the other taxes. This is because the shares of human capital in both sectors are set higher than the shares of physical capital--the latter are α=β=1/3--and hence the exponents on the terms including τ^H in (18) and (19) are higher than those on the terms including τ^K. Across model specifications, the largest increases in growth induced by income tax cuts are obtained, as expected, in the case that H is a market sector subject to taxation (model iii). In this case cutting τ^H by 10 percentage points increases growth by about 1.5 percentage points. But this case is by far the exception: growth-enhancing effects of income tax cuts are modest in all other models and particularly when leisure is quality time (model iv) and when labor supply is inelastic (model vi). With regard to τ^C, a rise in this tax of 10 percentage points reduces growth by 0.2-0.3 percentage points in models i-iii, and it has no growth effects in models iv-vi, as argued above. Keeping taxes constant, a higher GDP share of government purchases increases growth because it induces agents to substitute work for leisure. ^1/

Table 1.

Quantitative Tax Experiments^*

^*Parameter values: α = β = 0.33; A = 1; η = θ = 2.5; δ = 0.1; ρ = 0.024;

^**Baseline fiscal policy: τ^K = 0.43; τ^H = 0.285; τ^C = 0.05; g = 0.19 Values for B -- Model (i): 0.75; (ii): 0.44; (iii): 1.4; (iv): 0.55; (v): 0.31; (vi): 0.275

Table 1.

Quantitative Tax Experiments^*

		Baseline **	reduce τK 10 pct. pts.	reduce τH pct. pts.	increase τC 10 pct. pts.	increa. g 5 pet. pts.
(i)	Benchmark model
	Growth	0.03	0.032	0.037	0.028	0.033
	Investment/GDP	0.251	0.267	0.253	0.256	0.245
(ii)	Benchmark model, β = 0
	Growth	0.03	0.031	0.034	0.027	0.032
	Investment/GDP	0.125	0.146	0.123	0.127	0.124
(iii)	H-sector taxed
	Growth	0.03	0.036	0.044	0.028	0.033
	Investment/GDP	0.183	0.207	0.178	0.187	0.18
(iv)	Leisure = quality time
	Growth	0.03	0.031	0.032	0.03	0.03
	Investment/GDP	0.239	0.247	0.237	0.249	0.231
(v)	Leisure = quality time, β = 0
	Growth	0.03	0.03	0.03	0.03	0.03
	Investment/GDP	0.079	0.093	0.079	0.079	0.079
(vi)	No leisure
	Growth	0.03	0.031	0.032	0.03	0.03
	Investment/GDP	0.252	0.27	0.263	0.252	0.252

^*Parameter values: α = β = 0.33; A = 1; η = θ = 2.5; δ = 0.1; ρ = 0.024;

^**Baseline fiscal policy: τ^K = 0.43; τ^H = 0.285; τ^C = 0.05; g = 0.19 Values for B -- Model (i): 0.75; (ii): 0.44; (iii): 1.4; (iv): 0.55; (v): 0.31; (vi): 0.275

View Table

Table 1.

Quantitative Tax Experiments^*

		Baseline **	reduce τK 10 pct. pts.	reduce τH pct. pts.	increase τC 10 pct. pts.	increa. g 5 pet. pts.
(i)	Benchmark model
	Growth	0.03	0.032	0.037	0.028	0.033
	Investment/GDP	0.251	0.267	0.253	0.256	0.245
(ii)	Benchmark model, β = 0
	Growth	0.03	0.031	0.034	0.027	0.032
	Investment/GDP	0.125	0.146	0.123	0.127	0.124
(iii)	H-sector taxed
	Growth	0.03	0.036	0.044	0.028	0.033
	Investment/GDP	0.183	0.207	0.178	0.187	0.18
(iv)	Leisure = quality time
	Growth	0.03	0.031	0.032	0.03	0.03
	Investment/GDP	0.239	0.247	0.237	0.249	0.231
(v)	Leisure = quality time, β = 0
	Growth	0.03	0.03	0.03	0.03	0.03
	Investment/GDP	0.079	0.093	0.079	0.079	0.079
(vi)	No leisure
	Growth	0.03	0.031	0.032	0.03	0.03
	Investment/GDP	0.252	0.27	0.263	0.252	0.252

^*Parameter values: α = β = 0.33; A = 1; η = θ = 2.5; δ = 0.1; ρ = 0.024;

^**Baseline fiscal policy: τ^K = 0.43; τ^H = 0.285; τ^C = 0.05; g = 0.19 Values for B -- Model (i): 0.75; (ii): 0.44; (iii): 1.4; (iv): 0.55; (v): 0.31; (vi): 0.275

With respect to investment effects of tax changes, Table 1 shows that a 10-percent cut in τ^K increases the investment rate in all model specifications. In contrast, a cut in τ^H has an ambiguous effect on physical investment, although it would increase overall investment if one included investment in human capital. ^2/ As argued earlier, a rise in τ^C reduces the consumption-GDP share and hence rises the investment rate.

The results of the numerical analysis are consistent with Harberger’s view that tax changes around the current tax structure are likely to affect investment more than growth. Only in the case that human capital accumulation is a taxed market activity, we find that changes in factor income taxes generate growth effects that substantially exceed the 1/10 to 2/10 of a percentage point range predicted by Harberger (1964b). Even then, the simulations assume cuts of 10 percentage points in income tax rates, which arguably may be in the extreme of viable changes around the current tax structure. Furthermore, the simulations are also suggestive of the difficulties that one may find in conducting empirical tests of the link between taxation and long-run growth. First, except for the case in which H is a taxed market activity, the growth effects of even large tax changes are small, so identifying precisely the small contribution of tax rates to the widely variant cross-country growth experience is likely to be difficult, even if tax structure data is properly constructed. Second, there is a potentially serious identification problem to the extent that the magnitude, and in some cases even the direction, of the effects of tax changes on growth may vary across countries because of differences in key parameters (such as the share of physical capital in the production of human capital), the nature of leisure time, and details of the tax codes pertaining to differential tax treatment to the returns on human and physical capital. Thus, theory provides no argument for expecting cross-sectional regressions of growth on tax rates to provide robust results.

1. Computing Macroeconomic Measures of Effective Tax Rates

Computing effective marginal tax rates useful for empirical analysis at a national or international level is a complex task because (a) the myriad of tax exemptions, deductions, and credits that make it difficult to extrapolate the actual tax burden from statutory tax rates, (b) different taxes have equivalent effects on observable variables that could be used to construct tax rate estimates (see Frenkel, Razin, and Sadka 1991), (c) the progressivity and nonlinearity of income tax schedules, which imply that aggregate marginal tax rates estimates require data on the distribution of income consistent with those schedules, and (d) tax systems often include different forms of taxation affecting the same tax base--like individual income taxes levied on wages and social security taxes, both of which are labor income taxes. For cross-country analysis, the situation is complicated even further by differences in the structure of tax systems and limitations of the information available on tax revenues and income distribution.

A strategy for resolving completely all of the above problems is not available, but the method proposed by Mendoza et al. (1994) offers a second-best approach. The intuition of the method is the following. Consider an economy with three goods, consumption (c), labor (l), and capital (k). Household consumption is represented by the vector h=(h_c, h_l, h_k), and government expenditures are denoted by the vector g=(g_c, g_l, g_k). Firms produce c using k and l, and government finances g by levying taxes on consumption and factor incomes. The post-tax price vector facing households is p=(p_c, p_l, p_k) and the producer pre-tax price vector is q=(q_c, q_l, q_k). Tax policy is given by specific tax rates t=(t_c, t_l, t_k) per unit of the respective good. Thus, t=p-q and the vector of ad-valorem tax rates is τ=(τ_c, τ_l, τ_k), where τ_i = t_i/q_i for i = c, l, k. Since price vectors p and q are not readily available in the data, the tax rates estimates are constructed by multiplying t_i and q_i times an appropriate quantity so as to use data on tax revenues and tax bases rather than price data. The appropriate quantity measures are constructed using OECD data from Revenue Statistics (OECD, 1992) and National Accounts: Volume II, Detailed Tables (OECD, 1991a). Revenue Statistics contains tax revenue data on a cash-receipt basis at the general government level organized under a uniform format. Other sources, such as the IMF’s Government Finance Statistics report for several countries central government figures only, thus ignoring state and local taxes, or list budget estimates rather than cash receipts. The detailed tables of the OECD National Accounts are consistent: with the Revenue Statistics data and hence help construct tax-base measures. Of particular importance is the data at the disaggregated level on the “balance sheets” of households, corporate enterprises, and government.

2. Effective Tax Rates and Economic Growth: International Empirical Regularities

We constructed time-series of tax rates extending the computations of Mendoza et al. (1994) for the G-7 by adding three years (to cover the sample 1965-1991) and 11 countries (Australia, Austria, Belgium, Denmark, Finland, the Netherlands, New Zealand, Norway, Spain, Sweden, and Switzerland). Tax rates for other OECD countries could not be computed because some of the variables were not available in OECD sources. The missing tax rates could be approximated with rough estimates, as has been done in other cross-sectional studies (see Easterly and Rebelo 1993a) and (1993b)), but we opted to maintain a high degree of accuracy in the computation of tax measures, in line with the arguments in Harberger (1964b) and Harberger et al. (1967). This, however, restricts the degrees of freedom for econometric analysis, although we minimize the problem by giving some emphasis to panel techniques that exploit time-series and cross-section features of the data. The remainder of this section summarizes basic stylized facts linking taxation, investment, and growth, based on a bivariate analysis in which the cross-country panel is broken down into quinquenial averages for each variable and country, as is done in some of the regressions of the next section.

The tax rates estimates illustrate important features of the structure of tax systems of OECD countries. Table 2 provides summary statistics useful to compare tax structures, including means of quinquenial averages, as measures of average taxes, and the difference between maximum and minimum quinquenial averages, as a good indicator of variability given that there are only five quinquenia for each country and variable in the sample. In line with Mendoza et al. (1994), we find that labor, capital, and consumption taxes have fluctuated sharply, and while capital and consumption taxes have not exhibited a marked trend, the tax on labor income has increased over time in all countries. Two important exceptions are Japan, where the capital income tax did increase sharply from the mid 1960s to the late 1980s, and the Nordic countries (Finland, Norway, and Sweden) where all tax rates displayed upward trends. The Nordic countries have above-average tax rates with respect to all three taxes considered, while continental Europe has above-average taxes on consumption and labor income, and below-average taxes on capital income. The opposite holds for OECD countries outside of Europe (Australia, Canada, Japan, New Zealand, and the United States) and for the United Kingdom. Thus, the data clearly distinguish between three groups of countries: a group where all taxes are high (Nordic countries), a group with high capital income taxes and low consumption and labor taxes (nonEuropean OECD countries and the United Kingdom), and a group with low capital income taxes and high consumption and labor taxes (continental Europe). Note, however, that cross-country differences in tax rates narrowed considerably by the end of our sample period for some countries, particularly in Europe as a result of tax harmonization policies.

Table 2.

Tax Rates, Private Investment and GDP Growth: Summary Statistics from Quinquennial Averages ^1/

^1/The table reports the mean of quinquennial averages and the difference between the maximum and minimum quinquennial averages.

^2/For these countries, OECD data permits calculation of the tax rates only for six years.

Table 2.

Tax Rates, Private Investment and GDP Growth: Summary Statistics from Quinquennial Averages ^1/

		Consumption Tax		Labor	Income Tax	Capital	Income Tax	GDP Growth		Pvt.	Investment
		Mean	Max-min	Mean	Max-min	Mean	Max-min	Mean	Max-min	Mean	Max-min
Australia		8.410	1.853	15.786	6.770	40.769	15.645	1.926	3.100	21.286	1.611
Austria		20.744	2.506	37.390	7.198	21.098	3.591	2.994	3.050	21.147	3.871
Belgium		17.163	1.569	42.855	11.637	35.337	11.416	2.808	4.310	16.977	5.183
Canada		12.519	2.290	23.273	10.601	40.896	5.490	2.844	1.900	19.095	1.930
Denmark		34.553	3.014	42.149	3.801	34.976	2.477	2.020	1.740	17.635	5.617
Finland		25.413	9.725	29.068	12.643	32.941	17.168	3.164	2.620	22.638	4.345
France		20.881	1.140	39.690	12.468	24.079	10.305	2.506	4.350	19.323	4.166
West Germany		15.684	1.371	36.832	10.097	26.852	9.730	2.436	2.790	18.072	1.906
Italy		12.289	2.583	39.086	4.064	26.675	2.805	3.200	5.010	19.479	4.869
Japan		5.190	1.142	21.328	11.017	34.147	28.659	4.852	7.500	23.006	4.741
Netherlands 2/		17.552	1.496	51.642	..	30.413	..	2.242	3.990	17.795	3.041
New Zealand 2/		11.623	9.393	25.767	..	37.584	..	1.059	2.730	15.929	2.129
Norway		33.508	10.370	38.920	1.142	39.725	5.246	3.068	3.400	24.090	4.572
Spain 2/		10.191	4.560	32.792	..	13.942	..	2.976	4.970	20.640	5.646
Sweden		21.553	4.717	46.430	12.674	51.212	23.594	1.812	1.970	17.581	3.300
Switzerland		7.394	1.782	28.398	12.487	23.811	12.229	1.642	3.030	19.016	5.021
United Kingdom		14.578	4.057	25.488	4.107	57.290	18.289	2.356	2.440	12.520	5.323
United States		5.648	1.236	25.360	8.238	42.719	4.159	1.938	1.120	16.399	1.731
	Average	16.383	3.600	33.459	8.596	34.137	11.387	2.547	3.334	19.035	3.834

^1/The table reports the mean of quinquennial averages and the difference between the maximum and minimum quinquennial averages.

^2/For these countries, OECD data permits calculation of the tax rates only for six years.

View Table

Table 2.

Tax Rates, Private Investment and GDP Growth: Summary Statistics from Quinquennial Averages ^1/

		Consumption Tax		Labor	Income Tax	Capital	Income Tax	GDP Growth		Pvt.	Investment
		Mean	Max-min	Mean	Max-min	Mean	Max-min	Mean	Max-min	Mean	Max-min
Australia		8.410	1.853	15.786	6.770	40.769	15.645	1.926	3.100	21.286	1.611
Austria		20.744	2.506	37.390	7.198	21.098	3.591	2.994	3.050	21.147	3.871
Belgium		17.163	1.569	42.855	11.637	35.337	11.416	2.808	4.310	16.977	5.183
Canada		12.519	2.290	23.273	10.601	40.896	5.490	2.844	1.900	19.095	1.930
Denmark		34.553	3.014	42.149	3.801	34.976	2.477	2.020	1.740	17.635	5.617
Finland		25.413	9.725	29.068	12.643	32.941	17.168	3.164	2.620	22.638	4.345
France		20.881	1.140	39.690	12.468	24.079	10.305	2.506	4.350	19.323	4.166
West Germany		15.684	1.371	36.832	10.097	26.852	9.730	2.436	2.790	18.072	1.906
Italy		12.289	2.583	39.086	4.064	26.675	2.805	3.200	5.010	19.479	4.869
Japan		5.190	1.142	21.328	11.017	34.147	28.659	4.852	7.500	23.006	4.741
Netherlands 2/		17.552	1.496	51.642	..	30.413	..	2.242	3.990	17.795	3.041
New Zealand 2/		11.623	9.393	25.767	..	37.584	..	1.059	2.730	15.929	2.129
Norway		33.508	10.370	38.920	1.142	39.725	5.246	3.068	3.400	24.090	4.572
Spain 2/		10.191	4.560	32.792	..	13.942	..	2.976	4.970	20.640	5.646
Sweden		21.553	4.717	46.430	12.674	51.212	23.594	1.812	1.970	17.581	3.300
Switzerland		7.394	1.782	28.398	12.487	23.811	12.229	1.642	3.030	19.016	5.021
United Kingdom		14.578	4.057	25.488	4.107	57.290	18.289	2.356	2.440	12.520	5.323
United States		5.648	1.236	25.360	8.238	42.719	4.159	1.938	1.120	16.399	1.731
	Average	16.383	3.600	33.459	8.596	34.137	11.387	2.547	3.334	19.035	3.834

^1/The table reports the mean of quinquennial averages and the difference between the maximum and minimum quinquennial averages.

^2/For these countries, OECD data permits calculation of the tax rates only for six years.

The data in Table 2 also shed some light on the co-movement between tax rates, GDP growth and private investment rates. This evidence is illustrated more clearly in the scattered diagrams in Figures 1-6 and in the correlation coefficients listed in Table 3. Consider first the link between the investment rate and tax structure. Figures 1 and 2 illustrate a clear and strong negative relationship between factor income taxes and the private investment rate (the correlation coefficients are -0.4 and -0.23 for the capital income and labor income taxes respectively) and Figure 3 shows that the investment rate and the consumption tax are positively, albeit weakly, correlated. These co-movements are consistent with the predictions of the endogenous growth models reviewed in Section II. As the analysis is extended to consider the link between growth and taxation the results are qualitatively similar, but quantitatively less significant. Moreover, if one takes out of the sample the first quinquenial averages for Japan (i.e., the averages for 1966-70), since Japanese growth in that period was clearly an outlier (see Figures 4-6), the correlations between factor income (consumption) taxes and growth are negative (positive) but small.

Table 3.

Tax Rates, Private Investment, and Growth: Simple Correlations for a Panel of Quinquennial Averages

Table 3.

Tax Rates, Private Investment, and Growth: Simple Correlations for a Panel of Quinquennial Averages

		Consumption Tax	Capital Income Tax	Labor Income Tax
Private Investment/GDP		0.196	-0.404	-0.232
	No. of Observations	73	64	64
GDP Growth (Including Japan’s first quinquennial average)		0.027	-0.122	-0.238
	No. of Observations	75	66	66
GDP Growth (Excluding Japan’s first quinquennial average)		0.140	-0.020	-0.149
	No. of Observations	74	65	65

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Table 3.

Tax Rates, Private Investment, and Growth: Simple Correlations for a Panel of Quinquennial Averages

		Consumption Tax	Capital Income Tax	Labor Income Tax
Private Investment/GDP		0.196	-0.404	-0.232
	No. of Observations	73	64	64
GDP Growth (Including Japan’s first quinquennial average)		0.027	-0.122	-0.238
	No. of Observations	75	66	66
GDP Growth (Excluding Japan’s first quinquennial average)		0.140	-0.020	-0.149
	No. of Observations	74	65	65

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Private Investment Rate and the Capital Income Tax

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Private Investment Rate and the Labor Income Tax

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Private Investment Rate and the Consumption Tax

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Growth and the Capital Income Tax

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Growth and the Labor Income Tax

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Growth and the Consumption Tax

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In summary, the evidence from bivariate analysis is in line with Harberger’s hypothesis that although we could expect income taxes to have notable adverse effects on investment, these effects do not result in large growth effects. Figures 4-5 are also in line with similar charts examined in the recent empirical literature on taxation and growth (see Plosser (1992)), which suggest some causality from higher taxes to lower growth. However, as this literature discovered, this result often disappears when other determinants of long-run growth are considered. Thus, either to provide stronger evidence on Harberger’s superneutrality conjecture or to examine whether the Mendoza-Razin-Tesar tax measures improve the results of existing empirical studies of the growth effects of taxation, we need to examine the relationship between growth, investment, and taxes within the multivariate growth regression framework proposed by Barro (1991).

1. Tax Structure and the Investment Rate

As argued above, we examine first the relationship between the tax structure and the investment rate because in the models we reviewed most of the effects of taxation on growth operate directly or indirectly through the rate of investment on physical capital. Thus, while there may be sound theoretical reasons for including investment as an exogenous growth determinant along with tax rates, as is done in several recent empirical studies (see Levine and Renelt (1991), Mankiw, Romer, and Weil (1992), and DeLong and Summers (1991)), it is important to consider that this may induce a simultaneous-equation bias resulting from the fact that the investment rate depends in part on the tax structure. Similarly, as Barro and Sala-i-Martin (1995) argue, it is important to modify the estimation technique so as to consider the fact that investment, tax rates, and growth may exhibit two-way causality.

Table 4 presents the results for the cross-sectional regressions of the private investment rate as a function of the tax rates and the other growth determinants. The table reports results of four regression models, each estimated first using the tax rate indicators constructed in Section II and then using TAXPERS. The model estimated in Columns (1) and (2) is a benchmark case in which tax policy and the convergence factor (GDP1965) are the only growth determinants considered (except for the fact that the regressions, as all other regressions in the paper, include time dummies to capture country-specific time trends and common cross-sectional deterministic trends). The results reflect the intuition derived from the scattered diagrams plotted in Figures 1-3. Both TAXCAP and TAXLAB have strong and significant negative effects on the investment rate, while the effect of TAXCON is significant and positive. A reduction (increase) of 10 percentage points in labor and capital income (consumption) taxes increases the investment rate by 1.8 and 1 percent (1.3) respectively. Interestingly, these estimates are consistent with both the results of the numerical simulations reported in Table 1, particularly for the case of inelastic labor (or no leisure), and with Harberger’s (1964b) calculations for the U.S. economy. The results in Column (2) show that if instead of the Mendoza-Razin-Tesar tax rates we use TAXPERS, the benchmark regression model cannot detect a significant effect of taxation on private investment.

Table 4.

Regressions for Private Investment Rate Panel data, Five-Year Averages (1966-90)

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own first lags; the other variables are their own instruments.

Table 4.

Regressions for Private Investment Rate Panel data, Five-Year Averages (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-3.68 (-3.33)	-4.67 (-4.59)	-5.37 (-4.68)	-6.79 (-5.42)	-3.31 (-2.18)	-5.08 (-6.08)
TAXCON	0.13 (2.59)		0.18 (5.12)		0.28 (5.21)		0.31 (2.89)
TAXLAB	-0.18 (-3.98)		-0.22 (-4.95)		-0.21 (-3.23)		-0.23 (-2.09)
TAXCAP	-0.09 (-2.38)		-0.14 (-3.75)		-0.12 (-2.09)		-0.01 (-2.36)
TAXPERS		-0.04 (-0.97)		-0.01 (-0.17)		0.10 (1.21)		-0.18 (-1.94)
TOT			0.29 (2.55)	0.12 (0.84)	0.05 (0.51)	-0.08 (-0.62)	0.13 (2.00)	0.10 (1.97)
SYR			1.09 (4.18)	0.58 (1.97)	0.62 (1.99)	0.29 (0.88)	1.52 (2.82)	0.84 (2.20)
G/Y					-0.44 (-1.58)	-0.33 (-2.39)	-0.55 (-2.57)	-0.69 (-4.94)
Observ.	60	85	59	81	43	69	61	84
R 2	0.44	0.34	0.57	0.33	0.56	0.31	0.87	0.85

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own first lags; the other variables are their own instruments.

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Table 4.

Regressions for Private Investment Rate Panel data, Five-Year Averages (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-3.68 (-3.33)	-4.67 (-4.59)	-5.37 (-4.68)	-6.79 (-5.42)	-3.31 (-2.18)	-5.08 (-6.08)
TAXCON	0.13 (2.59)		0.18 (5.12)		0.28 (5.21)		0.31 (2.89)
TAXLAB	-0.18 (-3.98)		-0.22 (-4.95)		-0.21 (-3.23)		-0.23 (-2.09)
TAXCAP	-0.09 (-2.38)		-0.14 (-3.75)		-0.12 (-2.09)		-0.01 (-2.36)
TAXPERS		-0.04 (-0.97)		-0.01 (-0.17)		0.10 (1.21)		-0.18 (-1.94)
TOT			0.29 (2.55)	0.12 (0.84)	0.05 (0.51)	-0.08 (-0.62)	0.13 (2.00)	0.10 (1.97)
SYR			1.09 (4.18)	0.58 (1.97)	0.62 (1.99)	0.29 (0.88)	1.52 (2.82)	0.84 (2.20)
G/Y					-0.44 (-1.58)	-0.33 (-2.39)	-0.55 (-2.57)	-0.69 (-4.94)
Observ.	60	85	59	81	43	69	61	84
R 2	0.44	0.34	0.57	0.33	0.56	0.31	0.87	0.85

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own first lags; the other variables are their own instruments.

Columns (3)-(8) extend the first regression model to incorporate additional explanatory variables. Columns (3) and (4) add the terms of trade and the level of enrollment in secondary education at the beginning of each quinquenial unit. TOT and SYR are statistically significant determinants of the investment rate when the Mendoza-Razin-Tesar taxes are used, but not when tax policy is measured with TAXPERS. The new information added by SYR and TOT strengthens both the convergence effect and the effects of the three tax rates and allows to identify these effects with more precision. Overall, the regression in Column (3) explains nearly 60 percent of the cross-sectional variability of the private investment rate. In contrast, Column (4) shows that TAXPERS remains insignificant for explaining private investment and the regression as a whole can only explain about 1/3 of the movements in investment. Columns (5) and (6) add government expenditures and represent results based on instrumental variables, with the first lag of taxes and G/Y as instruments, in order to account for possible simultaneity problems and to address the causality between public revenues and expenditures resulting from the government’s budget constraint. In Column (5), the coefficients of TAXCON, TAXLAB, and TAXCAP, are robust to the addition of G/Y as an explanatory variable and to the change in estimation method--in fact, the investment effect of TAXCON rises from 0.13-0.18 to 0.28 percent. Column (6) shows that TAXPERS still cannot capture the effects of taxation on private investment. Finally, Columns (7) and (8) estimate a fixed-effects model using country dummies. Because the convergence effect captured by GDP1965 is a linear combination of the country dummies, the fixed effects model cannot identify the convergence factor, although it is implicit in the country dummies. Also, the fixed-effects model is estimated with OLS, since instrumental variables reduce sharply the degrees of freedom because it requires to estimate coefficients for 6 time and 18 country dummies and current and lagged values of the explanatory variables. Column (7) shows that the fixed-effects model predicts even stronger investment effects from TAXCON and TAXLAB, but the effect of TAXCAP is reduced sharply. Unable to control for the simultaneity between public revenues and expenditures, a significantly negative effect of higher government purchases on investment absorbs the effect of the capital income tax. The specification based on TAXPERS in Column (8) continues to perform unfavorably, although the coefficient rises from -0.04 in Column (2) to -0.18 and it has a higher t-statistic.

Table 5 reports results for experiments that estimate similar regressions as in Table 4 but based on a full time-series, cross-sectional panel, instead of using quinquenial averages. The implications for the link between tax rates and investment that follow from Columns (1)-(4) of the two tables are essentially the same, which suggests that our estimates of the investment effects of taxation are robust not only to the addition of other explanatory variables, but also to the choice of emphasis between cross-sectional and time-series dimensions of the panel. This result is not at odds with the strong transitional growth effects predicted by neoclassical models. In these models, a sharp tax cut induces transitional investment and output booms, as the capital stock grows from the low level of a heavily distorted economy to the high level of a tax-reformed economy. Thus, the ratio of investment to output may not rise significantly more during the transition compared to the overall change between the long-run equilibria of the two regimes. In contrast, Tables 4 and 5 differ in that Columns (5)-(8) in Table 5 show that in the full panel regressions G/Y absorbs almost completely the investment effects of TAXCAP, even when the regressions are estimated using instrumental variables. The GDP identity suggests that, if the GDP share of consumption does not fluctuate much from year to year, yearly changes in I/Y will be matched in part with changes in G/Y, and in part with changes in the trade deficit-GDP ratio. Thus, there is a natural tendency for G/Y to be negatively associated with I/Y which helps explain why G/Y easily outweighs taxes as an explanatory variable in full panel regressions.

Table 5.

Regressions for Private Investment Rate Annual Data (1966-90)

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. In regressions (5) and (6) the instruments for the tax variables and for G/Y are their third and fourth lag; the other variables are their own instruments.

Table 5.

Regressions for Private Investment Rate Annual Data (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-3.30 (-5.97)	-4.64 (-14.25)	-4.80 (-7.96)	-6.21 (-9.96)	-2.58 (-6.11)	-5.48 (-9.09)
TAXCON	0.14 (5.79)		0.17 (8.07)		0.31 (11.65)		0.17 (3.22)
TAXLAB	-0.20 (-9.50)		-0.19 (-9.53)		-0.08 (-2.17)		-0.16 (-3.35)
TAXCAP	-0.07 (-6.45)		-0.09 (-5.07)		0.00 (0.32)		0.03 (2.00)
TAXPERS		-0.04 (-1.72)		-0.00 (-0.10)		0.11 (2.90)		-0.08 (-1.91)
TOT			-0.02 (-1.07)	-0.03 (-1.19)	-0.03 (-1.42)	-0.02 (-0.77)	-0.03 (-2.49)	-0.03 (-2.80)
SYR			0.78 (5.20)	0.37 (2.69)	0.53 (3.49)	0.26 (1.84)	1.31 (4.11)	0.95 (4.54)
G/Y					-0.77 (-6.29)	-0.35 (-5.64)	-0.91 (-8.51)	-0.77 (-11.76)
Observ.	322	442	311	420	260	372	317	424
R2	0.39	0.32	0.45	0.30	0.50	0.35	0.86	0.84

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. In regressions (5) and (6) the instruments for the tax variables and for G/Y are their third and fourth lag; the other variables are their own instruments.

View Table

Table 5.

Regressions for Private Investment Rate Annual Data (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-3.30 (-5.97)	-4.64 (-14.25)	-4.80 (-7.96)	-6.21 (-9.96)	-2.58 (-6.11)	-5.48 (-9.09)
TAXCON	0.14 (5.79)		0.17 (8.07)		0.31 (11.65)		0.17 (3.22)
TAXLAB	-0.20 (-9.50)		-0.19 (-9.53)		-0.08 (-2.17)		-0.16 (-3.35)
TAXCAP	-0.07 (-6.45)		-0.09 (-5.07)		0.00 (0.32)		0.03 (2.00)
TAXPERS		-0.04 (-1.72)		-0.00 (-0.10)		0.11 (2.90)		-0.08 (-1.91)
TOT			-0.02 (-1.07)	-0.03 (-1.19)	-0.03 (-1.42)	-0.02 (-0.77)	-0.03 (-2.49)	-0.03 (-2.80)
SYR			0.78 (5.20)	0.37 (2.69)	0.53 (3.49)	0.26 (1.84)	1.31 (4.11)	0.95 (4.54)
G/Y					-0.77 (-6.29)	-0.35 (-5.64)	-0.91 (-8.51)	-0.77 (-11.76)
Observ.	322	442	311	420	260	372	317	424
R2	0.39	0.32	0.45	0.30	0.50	0.35	0.86	0.84

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statics, calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. In regressions (5) and (6) the instruments for the tax variables and for G/Y are their third and fourth lag; the other variables are their own instruments.

In summary, the evidence documented so far shows that the Mendoza-Razin Tesar measures of effective tax rates are robust determinants of the investment rate both in a cross-section of quinquenial averages, in which time-series variability is sharply reduced, and in a full panel that allows for substantial time-series variability. Factor income taxes have significant negative effects on the investment rate, while the consumption tax and the investment rate are positively related. These results are in line with Harberger’s (1964b) intuition that the mix between direct and indirect taxation should alter investment patterns, and they are also consistent with the quantitative predictions derived in the numerical simulations of endogenous growth models presented in Section II. In contrast, a more conventional measure of tax policy (the ratio of income tax revenue to GDP) is not statistically significant for explaining the private investment rate. Since in I/Y in the data depends on the tax rates, the analysis of Harberger et al. (1967) applies and we must control for the investment effects of taxes when considering I/Y as an explanatory variable in growth regressions.

2. Tax Structure and GDP Growth

Tables 6 and 7 report the results for regressions relating taxation and growth, organized in a similar manner as Tables 4 and 5. Table 6 refers to a panel based on quinquenial averages, while table 7 refers to the full panel. ^1/ Because according to the theory of Section II, I/Y and GDP growth are jointly determined by taxes and the other exogenous variables of the model, we view our growth regressions as a reduced form of a simultaneous equation system in which I/Y has been solved for. ^2/ These regressions thus identify the overall effects of taxation on growth, including those that operate through the private investment rate. This approach seems reasonable in light of the empirical evidence showing that growth regressions fail to pass robustness tests in part because of the complex mutual feedback between growth and its determinants.

Table 6.

Regressions for Per-Capita Real Output Growth Rate Panel Data, Five-Year Averages (1966-90)

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for PRINV and G/Y in regressions (5)-(8) are their own first lags; the other variables are their own instruments.

Table 6.

Regressions for Per-Capita Real Output Growth Rate Panel Data, Five-Year Averages (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-2.12 (-4.98)	-2.37 (-6.09)	-1.75 (-4.29)	-2.39 (-6.38)	-2.43 (-4.37)	-2.43 (-4.56)
I/Y					-0.08 (-0.94)	-0.00 (-0.06)
TAXCON	0.01 (0.64)		0.03 (1.57)		0.03 (1.30)		-0.02 (-0.26)
TAXLAB	-0.01 (-0.56)		-0.02 (-1.02)		-0.04 (-1.68)		-0.06 (-0.66)
TAXCAP	0.00 (0.52)		0.01 (0.57)		-0.01 (-0.56)		-0.02 (-0.75)
TAXPERS		-0.03 (-1.36)		-0.02 (-0.76)		-0.02 (-0.88)		-0.17 (-2.04)
TOT			0.17 (4.37)	0.17 (4.64)	0.18 (4.21)	0.16 (4.35)	0.17 (4.23)	0.18 (4.41)
SYR			0.06 (0.63)	0.10 (1.20)	0.16 (1.60)	0.13 (1.36)	0.19 (0.79)	-0.19 (-0.87)
G/Y			-0.04 (-0.48)	0.00 (0.07)	-0.02 (-0.22)	0.02 (0.52)	-0.07 (-0.37)	-0.16 (-0.11)
Observ.	60	85	58	81	56	76	59	83
R 2	0.33	0.49	0.45	0.48	0.43	0.47	0.44	0.37

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for PRINV and G/Y in regressions (5)-(8) are their own first lags; the other variables are their own instruments.

View Table

Table 6.

Regressions for Per-Capita Real Output Growth Rate Panel Data, Five-Year Averages (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-2.12 (-4.98)	-2.37 (-6.09)	-1.75 (-4.29)	-2.39 (-6.38)	-2.43 (-4.37)	-2.43 (-4.56)
I/Y					-0.08 (-0.94)	-0.00 (-0.06)
TAXCON	0.01 (0.64)		0.03 (1.57)		0.03 (1.30)		-0.02 (-0.26)
TAXLAB	-0.01 (-0.56)		-0.02 (-1.02)		-0.04 (-1.68)		-0.06 (-0.66)
TAXCAP	0.00 (0.52)		0.01 (0.57)		-0.01 (-0.56)		-0.02 (-0.75)
TAXPERS		-0.03 (-1.36)		-0.02 (-0.76)		-0.02 (-0.88)		-0.17 (-2.04)
TOT			0.17 (4.37)	0.17 (4.64)	0.18 (4.21)	0.16 (4.35)	0.17 (4.23)	0.18 (4.41)
SYR			0.06 (0.63)	0.10 (1.20)	0.16 (1.60)	0.13 (1.36)	0.19 (0.79)	-0.19 (-0.87)
G/Y			-0.04 (-0.48)	0.00 (0.07)	-0.02 (-0.22)	0.02 (0.52)	-0.07 (-0.37)	-0.16 (-0.11)
Observ.	60	85	58	81	56	76	59	83
R 2	0.33	0.49	0.45	0.48	0.43	0.47	0.44	0.37

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for PRINV and G/Y in regressions (5)-(8) are their own first lags; the other variables are their own instruments.

Table 7.

Regressions for Output Growth Rate Panel Yearly Data (1966-90)

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own third and fourth lag; the other variables are their own instruments.

Table 7.

Regressions for Output Growth Rate Panel Yearly Data (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-1.85 (-4.36)	-1.97 (-5.13)	-2.31 (-4.59)	-2.51 (-5.40)	-2.59 (-4.59)	-2.94 (-5.27)
I/Y					-0.08 (-1.06)	-0.02 (-0.39)
TAXCON	0.04 (2.40)		0.05 (2.79)		0.03 (1.25)		0.14 (2.09)
TAXLAB	-0.05 (-2.98)		-0.04 (-2.00)		-0.01 (-0.24)		-0.02 (-0.34)
TAXCAP	-0.01 (-1.50)		-0.01 (-1.22)		0.01 (0.63)		-0.09 (-3.72)
TAXPERS		-0.06 (-2.35)		-0.03 (-1.19)		-0.03 (-0.94)		-0.16 (-2.73)
TOT			0.02 (1.19)	0.02 (1.33)	0.02 (1.01)	0.02 (1.35)	0.01 (0.95)	0.02 (1.55)
SYR			0.28 (2.45)	0.26 (2.46)	0.11 (0.83)	0.25 (2.16)	0.60 (1.41)	0.36 (1.41)
G/Y			-0.05 (0.80)	-0.02 (-0.51)	-0.07 (-0.79)	0.06 (1.34)	-0.35 (-2.07)	-0.14 (-1.37)
Observ.	325	442	317	422	252	363	315	420
R 2	0.36	0.45	0.38	0.41	0.34	0.42	0.44	0.46

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own third and fourth lag; the other variables are their own instruments.

View Table

Table 7.

Regressions for Output Growth Rate Panel Yearly Data (1966-90)

Estimation Method	(1) OLS	(2) OLS	(3) OLS	(4) OLS	(5) INST	(6) INST	(7) FE	(8) FE
GDP 1965	-1.85 (-4.36)	-1.97 (-5.13)	-2.31 (-4.59)	-2.51 (-5.40)	-2.59 (-4.59)	-2.94 (-5.27)
I/Y					-0.08 (-1.06)	-0.02 (-0.39)
TAXCON	0.04 (2.40)		0.05 (2.79)		0.03 (1.25)		0.14 (2.09)
TAXLAB	-0.05 (-2.98)		-0.04 (-2.00)		-0.01 (-0.24)		-0.02 (-0.34)
TAXCAP	-0.01 (-1.50)		-0.01 (-1.22)		0.01 (0.63)		-0.09 (-3.72)
TAXPERS		-0.06 (-2.35)		-0.03 (-1.19)		-0.03 (-0.94)		-0.16 (-2.73)
TOT			0.02 (1.19)	0.02 (1.33)	0.02 (1.01)	0.02 (1.35)	0.01 (0.95)	0.02 (1.55)
SYR			0.28 (2.45)	0.26 (2.46)	0.11 (0.83)	0.25 (2.16)	0.60 (1.41)	0.36 (1.41)
G/Y			-0.05 (0.80)	-0.02 (-0.51)	-0.07 (-0.79)	0.06 (1.34)	-0.35 (-2.07)	-0.14 (-1.37)
Observ.	325	442	317	422	252	363	315	420
R 2	0.36	0.45	0.38	0.41	0.34	0.42	0.44	0.46

^*All regressions include an intercept and time dummies, and are estimated excluding outliers, defined as observations that yield residuals larger than two standard errors of a full sample regression. t-statistics calculated using White’s heteroskedasticity robust standard errors, are reported in brackets. The instruments for the tax variables, PRINV and G/Y in regressions (5) and (6) are their own third and fourth lag; the other variables are their own instruments.