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International Journal of Economics and Financial Issues
Vol. 5, No. 1, 2015, pp.11-22
ISSN: 2146-4138
www.econjournals.com
11
Fiscal Policies and Subnational Economic Growth in Mexico
Arwiphawee Srithongrung
Hugo Wall School of Public Affairs
Wichita State University, USA.
Email: Arwiphawee.Srithongrung@wichita.edu
Isaac Sánchez-Juárez
Department of Social Sciences
Universidad Autónoma de Ciudad Juárez, Mexico.
Email: isaac.sanchez@uacj.mx
ABSTRACT: This study investigates the effects of taxes and public investment on economic growth
of Mexican states. The subnational government finance data were drawn from 32 states during the
period of 1993 to 2011. Correcting for long-term trends and isolating cointegration effects between
economic growth and public finance, the empirical results indicate that taxes have negative effect on
growth and the effect can be seen in both transitory and permanent manners. As predicted by growth
theory, the effects of public investment on subnational growth are statistically significant and positive
in both short and long-runs. On the other hand, we find that educational accomplishment negatively
relates to growth. Foreign direct investment does not have any significant effect on subnational
economic growth. In general, the results imply that an appropriate fiscal policy (equilibrium between
public investment and taxes) is required to boost economic growth in this country.
Keywords: Mexico, economic growth, taxes, public investment, states.
JEL Classifications: O11, O23, O47, R11.
1. Introduction
The role of fiscal policies (i.e., taxes and spending) in subnational economic growth has been
focused in numerous studies around the world, partly because there are mixed results for both impacts
of taxing and spending on growth, depending on model specifications and estimation techniques.
Furthermore, given that subnational governments use both their own revenue sources and the
resources from central government to finance public spending, it is necessary to understand in what
way taxes and spending affect local growth. The purpose of this study is to: 1) to investigate the
partial effects of taxes and public investment on subnational economic growth when the another side
of fiscal policies is alternatively controlled for, and 2) to understand the partial effects of other
exogenous variables in neoclassical growth model including education levels, population and foreign
direct investment when fiscal policies are accounted in the model.
The “partial effect of taxes” refers to the true effect of taxes themselves on economic growth,
holding the partial effect of public spending constant. Conventional beliefs and macroeconomic theory
asserts that the true partial effect of taxes themselves should be negative, given that taxes distort
economic agents’ production and consumption choices and, as a consequence, deadweight loss occurs
in the private markets where taxes are levied. Several empirical studies at the subnational levels in the
United States found negative effects of taxes on growth; and hence; the empirical findings confirm
conventional beliefs. In the case of Mexico there are few studies that have addressed this issue and
from here the originality of this paper.
Theoretically, public investment is expected to exhibit positive effects on growth given that
public infrastructure such as road, bridges, water and sewerage systems and telecommunication
infrastructure are important production factors (see for example, Mankiw et al., 1992; Barro and Sala-
i-Martin, 2004). However, several empirical studies at the subnational levels both in the United States
(for example; Garcia-Mila et al., 1996; Holtz-Eakin, 1993), and elsewhere (see for example, Devarajan
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
12
et al., 1996; Sánchez and García, 2014) found either negative or insignificant effects of public
infrastructure spending or public capital stocks on growth. The wrong and insignificant signs of public
investment coefficients maybe due to several reasons including using inappropriate econometric
approaches to analyze the panel data (Kennedy, 2008).
Previous studies on the effects of public spending on growth, including those of Helms (1985),
Mofidi and Stone (1990); Kneller et al. (1999); Tomljanovich (2004) and Bania et al. (2007) have
addressed the issue of controlling another sides of fiscal policies as described above. However, to our
knowledge, none of these papers has satisfactorily corrected econometric problems especially for
integration problem that can be inherent characteristics of macroeconomic growth data. Cointegration
occurs when each of the time series data including taxes, spending, and economic growth levels
contain strong unit roots and unfortunately all of the data series that have unit roots are simultaneously
correlated; and hence, sharing the same or similar trends. Several studies tried to correct unit roots but
fails to address the cointegration problems (see for example Reed, 2008). Panel Vector Auto
Regression (PVAR) method is recently used by several studies for subnational growth to control for
cointegrated trends in macroeconomic data (see Blanchard and Perotti, 2002 and Srithongrung and
Kriz, 2014). However, the underlying assumption for PVAR method is that all variables in the model
is endogenously determined by the rest of the variables in growth model. Thus, the method is not
appropriate for the model that incorporates some exogenously determined variables such as population
growth and foreign investment.
In this paper, we found that the standard panel data analyses controlling fixed or random
effects are not enough to solve unit roots and cointegration problems in the subnational
macroeconomic growth data. Because we found strong trends in subnational public investment data
and strong cointegrating trends between public spending and growth, we chose Error Correction
Model (ECM) suggested by Kennedy (1998) to correct unit roots and cointegration while estimating
the effects of taxes and public investment on growth. Practically, we could use Panel Vector Auto
Regression (PVAR) method as mentioned above; however given that PVAR assumes that all variables
are endogenously determined by the other variables in the model; the method is not useful to analyze
data in this study. In Mexico, public spending by subnational governments is not completely financed
by state’s own revenue sources; instead the spending is partially financed by Mexico’s central
government. Furthermore, given that other socio-economic variables such as education, population
and foreign direct investment are specified based on exogenous growth model, PVAR is not chosen as
appropriate method in this study. The results from ECM confirm theoretical hypotheses for the effects
of taxes and public investment in both short-and long runs.
The paper is organized as follows. The next section describes theoretical background and
major hypotheses. The third section presents testing model and data. The following section provides
results and discussion. The final section presents conclusion.
2. Research Background
The Effects of Taxes on Subnational Economic Growth
Previous empirical results indicated that tax has a negative effect on growth (Holcombe and Lacombe,
2004; Mark et al., 2000; Reed, 2008). Theoretically, the negative effects may be either a direct effect
of taxing, i.e., directly decreased citizens’ income, or an indirect effect, i.e., tax creates deadweight
loss in private markets.1 However, some of the previous empirical results, especially for the studies
that controlled for the effect of public spending in the same testing models, indicated that taxes had a
positive effect on growth in the long-run (the growth-hills effect) (Bania et al., 2007) and corporate
taxes had a positive effect on per capita real Gross State Product (GSP) (Tomljanovich, 2004). In the
case of Mexico, some studies have found negative impact of taxes over economic growth using an
1 Deadweight loss is the sum of consumers’ and producers’ surplus that disappears after tax prices increase since
taxpayers change their behavior by withdrawing their consumption (in the case of sales taxes), production (in the
case of individual labor and corporate output taxes), and decisions to obtain personal properties (in the case of
property taxes). Christiansen (2007:25) argues that the appropriate way to determine the level of public goods
provision is to evaluate the taxing regime: “taxes levied to finance public goods will inflict a loss of efficiency
on society by inducing behavioral responses that are socially inefficient, even if privately rational. This is a
social cost that must be added to the cost in terms of resources needed to produce the public goods”.
Fiscal Policies and Subnational Economic Growth in Mexico
13
OLS panel data model, but positive with fixed and random effects (Samaniego, 2014 and Caballero
and López, 2012). Canavire-Bacarreza et al. (2013) using time series found that in Mexico “a shock
that increases collection of personal income tax by two standard deviations reduces economic growth
in the short run, with a recovery and even a slight positive effect in the long run (more than 3 years).”
As asserted by Reed (2008), a part of these mixed results is relevant to different research
methodologies. We add to this observation that another part of these mixed results is also relevant to
the different underlying assumptions used in testing economic growth; namely, the “short-run” versus
“long-run” growth.
As discussed by Diamond and Moomau (2003), tax rate affects the investment demand
function by changing after-tax return on capital and the supply function of investment by enhancing
incentives to save more. While the first creates negative effects on growth, the latter creates positive
effects on growth. According to these authors, the partial effect of tax itself is unfortunately still
unclear as to whether the results will be positive or negative because the partial effect of taxes depends
on the increasing level of saving and the decreasing level of investment. This opaque understanding
for the roles of public finance on private investment and economic growth creates such arguments as
whether public spending crowds out private investment (in Mexico see for example Calderón and Roa,
2006). With this line of debating, we expect to choose an appropriate empirical economic growth
model that allows testing of the two sides of government fiscal policies. This attempt is not new given
that several studies, including those by Helms (1985), Mofidi and Stone (1990), Kneller et al. (1999),
Tomljanovich (2004), and Bania et al. (2007) have addressed this issue. However, as mentioned
above, these studies failed to control for cointegration that tends to create the wrong signs in
econometric models (Kennedy, 2008).
Furthermore, in addition to the relevancy to government spending, the net effects of taxes on
growth might depend on the pre-existing condition of the taxing system. According to Christiansen
(2007), there are two cases of an initial taxing system: optimal and sub-optimal systems. The first
asserts that the relationship between tax burden and government revenues is non-linear as portrayed
by an inverted U shape. In this case, the taxing system is optimal in the Pareto efficiency definition,
given that it is impossible to increase the tax rate without making anyone worse off. Under this
optimal case, increasing the tax rate does not change the socially-aggregated utility, and thus, taxes
have no significant impact on private markets. This is because the loss experienced by the group
subject to a higher tax burden would be compensated by the benefits gained by the group receiving the
benefits from public goods.
As Christiansen (2007) has pointed out, the key to understanding why aggregated social utility
does not change when the tax system is efficient is to understand the consequences of having an
efficient tax system at the initial point (or the term “self-selection constraints” defined by
Christiansen). If the taxing system is efficient or optimal in terms of having a broad base2 and being
non-discriminatory,3 then there is no incentive for economic agents to change their behavior in terms
of labor supply or consumption demands to avoid increased taxes. If the tax system is narrow and
discriminatory, as in the latter case of the sub-optimal taxing system, there is incentive for some
groups in the society to avoid a tax burden by withdrawing labor supply or substituting the highly
taxed goods with lower taxed ones. This is where the deadweight loss mentioned previously occurs.
In the suboptimal taxing system, the relationship between tax burden and government revenue
is linear, given that changing the tax burden changes the socially aggregated utility according to the
Pareto inefficiency definition: it is possible to change tax rates to make someone better off without
making anyone worse off (Christiansen, 2007). According to Christiansen (2007), under this sub-
optimal regime, increasing the tax rate alters the socially aggregated benefits in terms of net gain or
net loss; also, there is a different cost in using taxes from different sources to fund the same public
project. That is, some tax sources that have under-exploited since the beginning (or suboptimal
according to the Pareto efficiency definition) can exhibit a social net gain, while some tax sources that
2 A broad-base taxing system means that taxes are applied equally across all activities, goods, and services that
are substitutable in the same classes.
3 A non-discriminatory taxing system means that taxes are applied unequally in terms of effective tax rate to
different income classes in the society.
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
14
have been over-taxed since the beginning can exhibit a social net loss when used to fund the same
public project. It should be noted that the quality of the taxing system has nothing to do with the initial
level of the tax burden; thus, non-linearity in terms of the initial level of the tax does not apply under
this assumption.
Regarding the implications of the above concepts, if the coefficient of taxes is statistically
significant, then the taxing system of a jurisdiction is inefficient at the beginning, thus exhibiting
either positive or negative net effects depending on net-gain or net loss in using such a tax to fund
different types of public spending. If the coefficients of the taxes are insignificant, then the taxing
system of such jurisdiction is efficient since the beginning.
Empirically, Reed (2008) has shown that under a robust estimation by using 5-year interval
differenced data, tax burden exhibited negative effects through all estimation techniques, including
pool OLS with fixed state and time effects, fixed effects, random effects, general moment method, and
dynamic panel data estimation. Testing the long-run effects of taxes on personal income growth, Bania
et al. (2007) found that taxes exhibited positive effects on growth during the initial period, and then
negative effects on growth during the later period. Bania et al.’s (2007) full specification of
government budget constraint omitted productive spending (which consists of all government
spending except health and welfares and other transfers), used average data within five-year intervals
(instead of differenced data which test short-run effects), and used leveled data of tax rate to personal
income augmented by the squared term of tax rate to test “long-run growth hills.” Bania et al. (2007)
concluded that in the long-run, taxes used to fund productive expenditure which were omitted in the
test have a positive net effect but later on exhibit negative net effects, depending on the taxing level
during the beginning stage. Unlike other studies, Bania et al. (2007) used the Barro-type endogenous
growth model, which assumes non-linearity in estimating parameters (instead of variable values) as an
underlying framework to test the endogenous effects of government fiscal policy.
Based on the previous empirical results, we assert that the taxing system at the subnational
levels in Mexico is unlikely to be optimal; thus, the positive or negative net effects of taxes are likely
the case. As Christiansen (2007) puts it, even with well-defined social objectives and well-established
decision-making institutions, failure to achieve an optimal taxing system will occur due to asymmetric
information in the decision-making process, let alone political, institutional, and administrative
constraints. Therefore, for this study, our first hypothesis is that taxing exhibits negative effects on
economic growth both in short and long runs given that there is a social cost in producing public
services and the cost paid by private sector affects saving and investment decisions.
The Effects of Public Investment Spending on Subnational Economic Growth
Regarding capital investment, which is one of the main focuses in this study, the studies in the
U.S. during the early period (Aschauer, 1990; Munnell, 1990; Costa et al., 1986) indicated significant
and positive effects of public infrastructure spending or public infrastructure stocks on subnational
growth. The models in these studies did not control for simultaneous effects between dependent and
independent variables (Aschauer, 1990), state and time fixed effects (Aschauer, 1990; Munnell, 1990),
fixed time effects (Costa et al., 1986), existing public capital stocks (Munnell, 1990; Costa et al.,
1986), or public capital spending levels (Aschauer, 1990). These studies obtained significant and large
effects of public capital on growth (elasticity ranging from 0.15 to 1.96). Furthermore, the adjusted r-
squared in these models was extremely large (about 0.99), which signals autocorrelation due to
uncontrolled unit roots in the time series data. When the flaws in these models were corrected, public
capital stocks or spending exhibited significant but small effects on growth .01 for Holtz-Eakin and
Schwartz (1995), using the Non-linear Seemingly Unrelated technique and .02 for Lobo and Rantisi
(1999), using LSDV or insignificant impacts on growth for Garcia-Mila, McGuire, and Porter (1996),
using the General Least Square method and the Two-Stage Least Square method, and for Moomaw et
al. (2002) using LSDV. However, when a more recent method, such as the Vector Auto Regression
(VAR) technique which corrects simultaneous effects between dependent and independent variables
due to co-integration and persistent trends in the lagged residuals, was used, Pereira and Andraz
(2003) again found that public investment had significant and positive impacts on private output.
For the types of capital spending, Lobo and Rantisi (1999) found that public capital stocks,
total public transportation capital outlays, and total public capital outlays, excluding transportation,
significantly and positively affected wage growth rates in 261 U.S. metropolitan areas during the
period of 1977 to 1992. In the same study, Lobo and Rantisi (1999) found that total public sanitarian
Fiscal Policies and Subnational Economic Growth in Mexico
15
outlays significantly but negatively affected the wage growth rate in the same areas and during the
same time period. Prior to the correction of endogeneity, Garcia-Mila and McGuire (1992) found that
transportation systems, including highways and airports, have larger effects on state economic
productivity relative to education than other types of infrastructure systems. Although these studies
had some empirical flaws, they imply that different funding across infrastructure service function
types yields different effects on economic outputs. Growth theories and empirical evidence (i.e.
Vijverberge et al., 1997; Pinnoi, 1994) explain that public infrastructure increases productivity outputs
by reducing private sector costs in the production process. This implies that different types of public
spending that serve different functions for private production yield different social benefits for private
outputs (for the case of Mexico check the works of Sánchez and García, 2014; Caballero and López,
2012; Hernández, 2010; Nuñez, 2006). Thus, the second hypothesis for this study is that when the
negative effects of taxes and cointegration trends are isolated public investment spending is positively
related to state economic growth in Mexico given that public infrastructure reduces private production
cost. The next section presents testing model and data.
3. Methodology and Data
In their study on the role of government taxing and spending on growth, Kneller et al. (1999)
suggested that a government’s combined tax and service package is only one variable in the growth
model; other non-fiscal variables, such as resource endowment, technological advancement in the
local area, time period, and labor growth rates, are other inputs in the growth equation. Thus, Kneller
et al.’s (1999:174) account of growth is:
1 1
k m
i it j jt t
i j
a BY X u
(1)
Where; Y represents non-fiscal variables, X is a government’s combined tax and spending policy, and
u is error terms. Using the growth account by Kneller et al. (1999), equation (1) is rewritten:
itit
m
j
m
j
iitittiititittiitit tbsboexbntrbcbbkbnblba ,,
1
1
1
1
9,8,7,6,5,4,32,1, lnlnln
………(2)
Where;
it,
ln
is an annual growth rate of real Gross Domestic Product (GDP) year t-1 to year t in state i
∆it
l,
ln is an annual change of labor quality measured by the changes in average level of educational
accomplishment in year year t-1 to year t for state i,
∆it
n,
ln is an annual change in the number of population in year t-1 to year t for state i,
∆it
k,
ln is an annual change in private investment measured by the ratio of foreign direct investment to
GDP in year t-1 to year t for state i,
∆it ,
is annual change in tax burden measured by the ratio of total taxes (including income, sales, and
property) to GDP in year t-1 to year t for state i,4
∆it
c, is annual change in the ratio of public investment (i.e., government capital outlays) to real GDP
in year t-1 to year t for state i,
∆it
ntr ,(omitted) is annual change in the ratio of total non-tax revenue including intergovernmental
revenue and and other central government grants sent to state governments to GDP in year t-1 to year
t for state i,
∆it
oex,(omitted) is annual change in the ratio of annual state government expenditure on operational
spending to real GDP year t-1 to year t for state i,,
4 We followed Reed (2008) in measuring percent of tax and spending to personal income by using the fiscal
variables in year t and personal income variable in year t-1 given that the fiscal data were recorded according to
fiscal year and the personal income data were recorded according to calendar year.
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
16
As shown in the equation description above, we following Kneller et al. (1999)’s budget constraint
model by omitting a category in revenue and expenditure which are ∆it
ntr , and ∆it
oex,, respectively
to avoid perfect collinearity within taxing and spending categories.
Endogeneity, Unit Roots and Cointegration Problems in Panel Data
Endogeneity relationship between dependent variable (annual change in GDP growth) and
independent variables (annual changes in the ratio of tax and public investment to GDP) may exist if
the variables on the left and the right hand sides of the equation come from the same time period. To
control for endogeneity, one-period lagged independent variables are specified to create an overlapped
space between fiscal policies and compound growth of GDP in the subsequence periods. This is
standard approach to deal with endogeneity (e.g. see Garcia-Milla and McGuire, 1992; Tomljanovich,
2004; Dye and Feiock, 1995; Bleaney et al., 2001).
Table 1 presents summary statistics for the data used in this study. Empirical estimations were
carried out using panel data for the period 1993 to 2011 for the 32 Mexican states. All monetary data
are in Mexican Pesos and in constant value based year 1993 to control for inflation effect.
Table 1. Summary Statistics
Variable Total
Observations Mean Std. Dev. Min Max
Gross Domestic Product
(in Million Pesos, Real
Value Based Year 1993) 608 46,700,000 59,400,000 5,859,721 376,000,000
Average Education level
(Year) 608 7.68 1.10 4.53 10.63
Total Population 608 3,127,930 2,675,375 353,348 15,200,000
Foreign Direct
Investment (Pesos, Real
Value Based Year 1993)
608 1,520,000,000 5,200,000,000 1,310,000,000 55,900,000,000
Total Taxes (Pesos, Real
value Based Year 1993) 608 727,000,000 2,000,000,000 2,437,989 17,300,000,000
Total Public Investment
(Pesos, Real value Based
Year 1993) 608 394,000,000 424,000,000 4,904,238 3,500,000,000
Ratio of Total Public
Investment to Total GDP
(in Million Pesos) 608 0.00001 0.00001 0.00000 0.00006
Ratio of Total Taxes to
Total GDP (in Million
Pesos) 608 0.00002 0.00004 0.00000 0.00030
Ratio of Total Foreign
Direct Investment to
Total GDP (in Million
Pesos)
608 0.00002 0.00003 -0.00002 0.00023
Ratio of Total Public
Investment to Total GDP 608 10.6 8.8 1.0 62.0
Ratio of Total Taxes to
Total GDP 608 16.5 43.9 0.0 296.0
Ratio of Total Foreign
Direct Investment to
Total GDP
608 17.1 25.2 -23.0 232.0
Table 2 presents unit root test and cointegration statistics. As presented in the table four of six
variables including GDP, public investment, taxes and education contain unit roots. As presented in
Table 2, cointegration exists for the series of log GDP and public investment, the series of log GDP
and taxes, and the series of GDP and education. To circumvent the unit root and cointegration
problems, we used Kennedy’s (2003) ECM technique, which relies on using differentiation to purge
the serial correlation whereby data in the current year are explained by data in the previous year. To
Fiscal Policies and Subnational Economic Growth in Mexico
17
control for cointegration, which is the relationship between the X variables and Y (i.e., when the X
values increase, Y increases), the ECM model includes an error correction term. The error correction
terms are the difference between dependent variable y and each independent variable X. These error
correction terms catch the effects of cointegration between X’s and Y so that the coefficients of the
main variable take only the effects of unit change within that variable into account, rather than
including the cointegration effects.
Table 2. Levin-Lin-Chu Unit Root and Cointegration Test Statistics
Ho: Panels contain unit roots Number of panels: 32
Ha: Panels are stationary Number of periods: 19
Autoregression parameter: Common
Panel means: Included
Time trend: Not Included
ADF Regressions: 1 lag
LR variance: Bartlett kernel, 8 lags average (chosen by LLC)
Unit Root Test
t
-
statistics
p
-
value
Log GDP 0.286 0.612
Public Investment 1.391 0.917
Taxes 0.804 0.789
Education 3.589 0.999
Foreign Direct Investment -7.264 0.000
Population -4.254 0.000
Cointegration Test
t
-
statistics
p
-
value
Log GDP - ratio of Public Investment to GDP 13.328 1.000
Log GDP - ratio of Taxes to GDP 8.438 1.000
Log GDP - log education 5.315 1.000
Owing to use of the ECM technique, all variables in the model entered regression in difference
values. The ratios of taxes and foreign direct investment, the mean of educational level, and total
number of population are integrated at one level while real GDP value and the ratio of public
investment are integrated two levels. The first difference in tax burden, capital stocks, education and
population and the second difference of public investment and GDP growth are statistically
determined by Bayes Information Criterion (BIC). BIC chooses the length of the difference interval by
judging from the magnitude of increasing R2 and the decreasing sum of squared residuals when one
more lag is added to the regressing lagged dependent variable against the current-year dependent
variable (Stock and Watson, 2007). Due to unit root and cointegration correction, equation 2 is
modified and re-written as shown in equation (3) below.
∆, =+ ∆,+ ∆, + ∆,+ ∆,) +∆,+ (−
1, − ,+(− 1), − ,+(− 1), − ,+∑
+
, + , -------------(3)
Where; , is one period lagged residuals or autocorrelation in the model.
Equation 3 presents the final testing model for this study. In this ECM equation, there are two
sets of the independent variables. The first set comprises the differenced independent variables
(e.g., − , ); the second set comprises the error correction terms (e.g. , − , ) that
are added to restore equilibrium in the econometric model. In the ECM, when the error terms or the
differenced values between dependent and independent variables in the previous period or series are
added into the model, the unit roots of independent and dependent variables are canceled out
(Kennedy, 2003). Meanwhile, the leveled data of these independent variables restore equilibrium lost
due to the use of differenced independent values. The coefficient for the first set of independent
variables, representing the difference between data for the previous and the current period, indicates
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
18
the short-term effect of the independent variables on growth within the equilibrium model. The
coefficients of the second set of independent variables, the error correction terms, were also derived
from the regression models and are available on request. The coefficients of the error correction terms
are significant at the 0.01 level. The significance of the error correction terms indicates that
cointegration does exist in the testing models; however, this was controlled for by adding the error
correction terms and residuals from unit root tests into the test equation. The regression results
reported in the next section reflect the pure effects of fiscal policies on growth, because we control for
unit roots in the time series data and for cointegration problems.
4. Empirical Results and Discussion
Table 3 presents the results from the ECM model. Column 1 of the table presents the results
from the base model in which fiscal variables, taxes and public investment were omitted as the based
case to see the effect of production inputs on GDP. In the short-run, population is significant and has
negative effect on GDP growth; population effect is no longer significant when public investment was
added in to the model as shown in columns 3 and 4. This implies that total number of population
decreases available resources for production inputs; however when public investment is added,
production inputs are increasing and hence the effect of population is diminished. Like population, the
average level of education accomplishment is significant and negatively affect GDP growth; however
when public investment is added into the model, the effect of education becomes positive although
insignificant in the short run, as shown in columns 3 and 4. In the long-run, it may be seen that
educational accomplishment reduces GDP growth which is counter-intuitive finding given that
educated workforce should help instead of hurt an economy. However, when considered that labor
stock quantity and quality are substitutable by capital stock, the long-run negative effect of education
on growth is possible.
Column 2 presents the partial effect of tax on real GDP growth when all production inputs are
controlled for and public investment is omitted. As shown in the column, taxes exhibits negative
effects on growth for both short and long-run. Given that tax variable enters the regression model in a
form of ratio of tax to total GDP while the dependent variable log GDP is entered the model in a form
of million pesos value (i.e., lny * 1,000,000), the interpretation for the coefficient of tax is calculated
by
%.5 As seen in column two, for every percent increase in tax burden, the total GDP drops for
1.03% in the short-run and this effect is carried on as the coefficient of the long-term trend for taxes is
statistically significant at 0.01 level. This result is consistent with the conventional belief and theory
that government tax collection produces a negative effect on growth because the private resources are
transferred through the public and there is a deadweight loss in the free market.
Column 3 presents the partial effect of public investment on real GDP growth when all
production inputs are controlled for and tax variable is omitted. As shown in the column, public
investment exhibits positive effect on growth for both short and long-run. Given that public
investment variable enters the regression model in a form of ratio of public investment to total GDP
while the dependent variable log GDP is entered the model in a form of million Pesos value (i.e. lny *
1,000,000), the interpretation for the coefficient of tax is calculated by
%. As seen
in column three, for every percent increase in public investment, the total GDP increase for 5.27% in
the short-run and this effect is carried on as the coefficient of the long-term trend for taxes is
statistically significant at 0.01 level. These findings correspond with the general belief that public
capital outlay simply spurs the economy.
5 See Stock and Watson (2010:268-269). The coefficient B in Log linear model is calculated such that 100 * B
%. In this study, the ratio of tax to GDP was calculated by dividing total taxes to total GDP; while log GDP is
entered regression model in a million pesos value. Thus the interpretation for the coefficients B for the ratio of
taxes and public investment is divided by 1,000,000 before converting into percentage term.
Fiscal Policies and Subnational Economic Growth in Mexico
19
Table 3. Empirical Results
Base Model
Without
Fiscal
Variables
Taxes Public
Investment
Taxes and
Public
Investment
Dependent Variable: Difference Value of Real GDP,
∆
,
Constant 3.848*** 5.012*** 0.457 2.948***
(0.687) (0.482) (0.874) (0.592)
Change in Education Level,
∆
,
-1.18 -0.982 0.297 0.479
(1.142) (1.14) (0.990) (0.986)
Change in Population Level ,
∆
,
-4.489*** -14.51*** 4.111 3.781
(1.873) (1.861) (2.878) (2.844)
Change in Foreign Direct Investment ,
∆
,
23.581 34.131 -30.825 -22.133
(95.535) (95.33) (91.888) (91.694)
Change in Taxes,
∆
,
--- -103.34** --- -91.491**
(45.302)
(41.82)
Change in Public Investment,
∆
,
--- --- 527.96** 527.094**
(238.52) (237.796)
Long-term trend for education level, -0.576*** -0.572*** -1.130*** -1.113***
,
−
,
(0.094) (0.093) (0.136) (0.134)
Long-term trend for taxes --- -0.446** --- -0.69**
,
−
,
(0.090)
(0.093)
Long-term trend for public investment --- --- 1.045*** 1.029***
,
−
,
(0.149) (0.148)
Model F-Stats (4, 475) (6, 474) (6,474) (7,441)
71.21 60.39 27.53 24.64
Prob > F 0.0000 0.0000 0.0000 0.0000
R-squared:
within 0.428 0.433 0.304 0.031
between 0.081 0.081 0.023 0.024
overall 0.002 0.002 0.007 0.007
corr (u_i, Xb) -0.99 -0.99 -0.98 -0.98
prob > F for the test that all u_i = 0 0.0000 0.0000 0.0000 0.0000
rho_ar
,
-0.449 -0.448 -0.321 -0.316
Fixed Effect Included Yes Yes Yes Yes
Number of Observation 512 512 480 480
Number of Groups 32 32 32 32
*Note: ** refers to .05 statistical significance level and *** refers to .01 statistical significance level
The last column of the table presents the net effect of taxes and public investment on real GDP
growth when all production inputs and fiscal variables are controlled for. As shown in the column,
public investment exhibits positive effect on growth for both short and long-run and tax exhibits
negative effect on growth in both short and long-run. Given that public investment and taxes variables
enter the regression model in a form of ratio of public investment to total GDP and the ratio of taxes to
GDP, respectively, while the dependent variable log GDP is entered the model in a form of million
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
20
Pesos value (i.e., lny * 1,000,000), the interpretation for the coefficient of tax and public investment is
calculated by
% and
%, respectively. As seen in the last column of the table,
for every percent increase in public investment ratio, the total GDP increase for 5.27% in the short-
run and for every percent increase in tax ratio, the total GDP drops for about 0.91 percent in the short-
run. The effects of public investment and taxes are carried on as the coefficients of tax and public
investment variables in the long-term trends are statistically significant at 0.01 level. It should be
noted that the effects of each of the public investment is positive in all cases no matter tax is included
or not included in the models although the coefficient of tax drops slightly from 1.03% to 0.91%
when public investment is included in the model.
5. Conclusions
This paper investigates the effect of taxes and public investment on state economic growth in
Mexico. This paper is different than the previous regional economic growth papers in that the
estimation approach namely: Error Correction Model (ECM) is used to correct unit roots and
cointegration that tends to occur in macroeconomic panel data. The cointegration can generate
spurious correlation between public spending and GDP and taxes and GDP and tends to produce the
wrong signs. Using budget constraint model as an underlying assumption for subnational economic
growth model as suggested by Kneller et al. (1999), the empirical results indicate that tax has negative
impact on GDP growth in both short and long-run, while public investment has positive impacts on
GDP growth in both short and long-runs. The effects of taxes range between -1.03 percent to -0.91%
for every percent increase to total GDP, while the effect of public investment is at about 5.27% for
every percent increase to total GDP. Education accomplishment has negative impact on GDP in the
long-run while has insignificant effect in the short-run. This result suggests that labor quality and
quantity may be able to substitute for other production inputs such as public investment and the effect
of input substitution can be seen only in the long-run.
For policy makers and government practitioners, especially at the subnational level in Mexico,
the results in this study suggest that public finance can be used to stabilize regional growth while
foreign direct investment is not useful in influencing growth. Given that foreign direct investment
depends on the economies outside the Mexican states, it is difficult to intervene to enhance growth.
Instead of focusing on economic development incentives to attract foreign investment, it may be more
worthwhile to spend regional economic development effort by re-allocating public resources,
especially on public infrastructure, into the states where needs are the most to allow the under-
developed states to catch up with developed states and hence the growth is even out across the
country. For literature the results adds to subnational growth literature that public investment is
another inputs in production function. Furthermore, when the cointegration trend is controlled for,
there is no evidence supporting the assumption that public investment crowds out private investment.
References
Aschauer, D. (1990), Why is Infrastructure Important?, in: A. Munnel (Ed.) Is There a Shortfall in
Public Capital Investment, 69-104, Boston, MA: Federal Reserve Bank of Boston.
Bania, N., Gray, J. A., Stone, J. A. (2007), Growth, Taxes, and Government Expenditures: Growth
Hills for U.S. States. National Tax Journal, 60(2), 193-204.
Barro, R., Sala-i-Martin, X. (2004), Economic Growth. (2nd Ed.) Cambridge: MA: MIT Press
Blanchard, O., Perotti, R. (2002), An Empirical Characterization of the Dynamic Effects of Changes in
Government Spending and Taxes on Output. Quarterly Journal of Economics, 117, 1329-1368.
Bleaney, M., Kneller, R., Gemmell, N. (2001), Testing Endogenous Growth Model: Public
Expenditure, Taxation Over the Long-run. Canadian Journal of Economics, 34(1), 36-57.
Caballero, E., López J. (2012), Gasto Público, Impuesto Sobre la Renta e Inversión Privada en
México. Investigación Económica, 71(280), 55-84.
Calderón, C., Roa R. (2006), ¿Existe un Crowding-out del Financiamiento Privado en México?
Análisis Económico, 21(48), 139-150.
Canavire-Bacarreza, G., Martinez-Vazquez, J, Vulovi, V. (2013), Taxation and Economic Growth in
Latin America, Washington: Inter-American Development Bank.
Fiscal Policies and Subnational Economic Growth in Mexico
21
Christiansen, V. (2007), Two Approaches to Determine Public Good Provision Under Distortionary
Taxation. National Tax Journal, 60(1), 25-43.
Costa Da Silva, J., Ellson, R., Martin, R. (1986), Public Capital Regional Output and Development:
Some Empirical Evidence. Journal of Regional Science, 27(3), 419-437.
Devarajan, S., Swaroop, V., Zou, H. (1996), The Composition of Public Expenditure and Economic
Growth. Journal of Monetary Economics 37(2), 313-344.
Diamond, J. W., Moomau, P. H. (2003), Issues in Analyzing the Macroeconomic Effects of Tax Policy.
National Tax Journal, 56(3), 447-462.
Dye, T., Feiock, R. (1995), State Income Tax Adoption and Economic Growth. Social Science
Quarterly, 76(3), 648-654.
Garcia-Mila, T., McGuire, T. (1992), The Contribution of Publicly Provided Inputs to States’
Economies. Regional Sciences and Urban Economics, 22(2), 229-241.
Garcia-Mila, T., McGuire, T., Porter, R. (1996), The Effect of Public Capital in State-Level
Production Functions Reconsidered. Review of Economics and Statistics, 78(1), 177-180.
Helms, L. J. (1985), The Effect of State and Local Taxes on Economic Growth: A Time Series-Cross
Section Approach. Review of Economics and Statistics, 67(4), 574-582.
Hernández, J. (2010), Inversión Pública y Crecimiento Económico. Hacia una Nueva Perspectiva de
la Función del Gobierno. Economía: Teoría y Práctica. 33, 59-95.
Holcombe, R. G., Lacombe, D. J. (2004), Factors Underlying the Growth of Local Government in the
19th Century United States. Public Choice, 120(3-4), 359-377.
Holtz-Eakin, D. (1993), State-specific Estimates of State and Local Government Capital. Regional
Science and Urban Economics, 23(2), 185-210.
Holtz-Eakin, D., Schwartz, A. (1995), Infrastructure in a Structural Model of Economic Growth.
Regional Science and Urban Economics, 25(2), 131-151.
Kennedy, P. (1998). A Guide to Econometrics. (4th Ed.) Cambridge, MA: The MIT Press.
Kennedy, P. (2003). A Guide to Econometrics. (5th Ed.). Cambridge, Massachusetts: The MIT Press
Kennedy, P. (2008). A Guide to Econometrics. (6th Ed.). Cambridge, Massachusetts: The MIT Press.
Kneller, R., Bleaney, M. F., Gemmell, N. (1999), Fiscal Policy and Growth: Evidence from OECD
Countries. Journal of Public Economics, 74(2), 171-190.
Lobo, J., Rantisi, N. (1999), Investment in Infrastructure as Determinant of Metropolitan Productivity.
Growth and Change, 30(1), 106-127.
Mankiw, N.G., Romer, D., Weil, D N. (1992), A Contribution to the Empirics of Economic Growth.
Quarterly Journal of Economics, 107(2), 407-437.
Mark, S.T., McGuire, T.J., Papke, L.E. (2000), The Influence of Taxes on Employment and Population
Growth: Evidence from the Washington, D.C. Metropolitan Area. National Tax Journal, 53(1),
105-123.
Mofidi, A., Stone, J.A. (1990), Do State and Local Taxes Affect Economic Growth? Review of
Economics and Statistics, 72(4), 686-691.
Moomaw, R., Mullen, K., Williams, M. (2002), Human and Knowledge Capital: A Contribution to
Empirics of State Economic Growth. American Economic Journal, 30(1), 48-59.
Munnell, A. (1990), How Does Public Infrastructure Affect Regional Economic performance?, in:
Munnell, A. (Ed.) Is There a Shortfall in Public Capital Investment?, 69-104, Boston,
Massachusetts: Federal Reserve Bank of Boston.
Nuñez, G. (2006), Inversión Pública y Crecimiento Económico en México. Un Enfoque de
Contabilidad del Crecimiento. Perfiles Latinoamericanos, 27, 11-32.
Pereira, A., Andraz, J. (2003), On the Impact of Public Investment: On the Performance of U.S.
Industries. Public Finance Review, 31(1), 66-90.
Pinnoi, N. (1994), Public Infrastructure and Private Production: Measuring Relative Contribution.
Journal of Economic Behavior and Organization, 23(2), 127-148.
Reed, W.R. (2008), The Robust Relationship Between Taxes and U.S. State Income Growth. National
Tax Journal, 61(1), 57-80.
Samaniego, M. (2014), Gasto Publico Productivo y Crecimiento Económico en México, 1993-2011, in
Sánchez, I. L. (Ed.) Reflexiones Sobre Sociedad y Desarrollo en México, 37-76, Ciudad Juárez:
Editorial Tiempo Económico & Lulu.
International Journal of Economics and Financial Issues, Vol. 5, No. 1, 2015, pp.11-22
22
Sánchez, I. L., García R. M. (2014), Producción, Empleo e Inversión Pública en la Frontera Norte de
México. Revista Internacional Administración y Finanzas, 7(7), 111-126.
Srithongrung, A., Kriz, K. (2014), The Impact of Sub-national Fiscal Policies on Economic Growth: A
Dynamic Analysis Approach. Journal of Policy Analysis and Management, 33(4), 912-928.
Stock, J., Watson, M. (2007), Introduction to Econometrics. (2nd Ed.). New York: Pearson education,
Inc.
Stock, J., Watson, M. (2010), Introduction to Econometrics. (3rd Ed.). New York: Addison-Wesley.
Tomljanovich, M. (2004). The Role of State Fiscal Policy in State Economic Growth. Contemporary
Economic Policy, 22(3), 318-330.
Vijverberge, P., Vijverberge, C., Gamble, J. (1997), Public Capital and Private Productivity. The
Review of Economics and Statistics, 79(2), 267-278.
