Download A Cross-Country Analysis

Cross-Sector Tax Discrimination and Economic Performance:
A Cross-Country Analysis
Young Lee*
Hanyang University
Taeyoon Sung**
Yonsei University
Taejong Kim***
KDI School of Public Policy and Management
June 2008
Abstract
Using corporate financial statement data in 70 countries, this paper measures tax
burden in each sector and analyzes the impact of tax burden on the growth of sector
and overall economy. We find that sectors and countries with lower effective tax rates
tend to grow faster. In addition to the level of tax rates we also examine the effect of
cross-sector differences in tax burden within a country, which can be seen as a proxy
for industrial policy through taxation. We find that industrial policy through taxation
hampers the growth of other sectors and fails to promote the economic growth, though
it can promote the growth of the favored sector. We also find that negative effect of
industrial policy is stronger in OECD countries, implying that the room for
government intervention becomes smaller as the economy and the market develops.
Key words: Corporate Income Taxation, Industrial Performance, Economic Growth,
Preferential Corporate Taxation
JEL classification: H21; E62
________________________
* Corresponding Author. Professor Young Lee, College of Economics and Finance, Hanyang
University, Seoul 133-791, Korea. E-mail: [email protected]
** Professor Taeyoon Sung, School of Economics, Yonsei University, Seoul, 130-722, Korea.
E-mail: [email protected]
*** Professor Taejong Kim, KDI School of Public Policy and Management, Seoul, 130-868 Korea.
E-mail: [email protected]
1
I. Introduction
We attempt to measure cross-sector discrimination in corporate income taxation and
analyze its impact on both industry-level performance and overall economic growth.
For this purpose, we utilize a large-scale international panel data of firm-level financial
statements. Given the data set, we can estimate effective marginal tax rates cross
industries, and examine the relationship of the estimated rates with economic
performance. In particular, since we have estimated effective marginal tax rates even at
the industry level, we can examine the implications of cross-sector differences, as well
as the absolute level of corporate tax burden, on economic performance.
The discriminatory application in corporate taxation, such as preferential tax rates,
depreciation rules, and tax credits for investment and R&D expenditures, is a
widely-adopted policy measure across countries. This measure can be interpreted to
represent a kind of industrial policy through taxation. Theoretically, the overall impact
of cross-sector tax discrimination on economic growth is ambiguous. First, the
discrimination policy in taxation can distort resource allocation, and thus hampering
growth.1 On the other hand, the policy may compensate for positive externalities from
tax-favored sectors to the rest of the economy. Thus, in this case, a prerequisite for the
effectiveness of tax favors is the ability of the government to identify appropriate
industries and set tax rates at optimal levels. Thus, figuring out whether the
discriminative tax policy promotes economic growth calls for an empirical
investigation.
In a neoclassical setup, taxes do not have impact on determining the long-term growth as long
as productivity is not affected by taxes, although taxes can change output in the long run.
However, even in the neoclassical model, tax changes can move short-term output growth
along a transitional path to the new steady state. For example, as shown in Hall and Jorgenson
(1967), low effective tax rates on new investment can derive faster short-run growth, due to an
investment increase in response to lower tax rates. Furthermore, in the context of endogenous
growth models, taxes can have long-term effects since they can influence on entrepreneurial
activity, technology, and productivity growth.
1
2
The rest of the paper is organized as follows. In Section 2, we begin by reviewing the
literature on the relationship between taxation and economic growth, and survey
various concepts of the effective tax rate. The review also summarizes the literature on
corporate tax burden and economic growth. Section 3 measures effective marginal tax
rates across sectors for each country. To capture the effective marginal tax rate in each
industry, we estimate coefficient from regressing corporate income taxes on before-tax
earnings of firms in a given sector. For this purpose, we employ the OSIRIS dataset, a
large-scale international longitudinal database of corporate financial statements. 2
Section 4 analyzes how estimated industry-level tax differences affect industry-level
growth. Finally, Section 5 studies their impact on overall economic growth. The
analysis in Section 5 incorporates the impact of statutory tax rates as well as the
estimated effective tax rates. For the analysis in Section 5, we combine the estimated
effective tax rates, the aggregate data from the World Bank's World Development
Indicators, and statutory tax rates coming from the Worldwide Summary of Corporate
Taxes from Price Waterhouse. Section 6 provides concluding remarks.
2. Literature Review
As already mentioned, distortion in taxation can disturb efficient resource allocation,
and thus, hamper capital accumulation and growth in the overall economy (i.e., see
Feldstein, 1974, 1978; Chamley, 1981; Becker, 1985; Judd, 1985; Jones and Manuelli,
1990; Rebelo, 1991). However, if taxation appropriately compensates for positive
externalities from some sectors to the rest of the economy, taxation may contribute to
efficient allocation of resources and economic growth.
Thus, the theoretical perspectives call for empirical investigation on the effect of
2
For the detailed explanation on the database, see Section 3.
3
taxation on growth. However, in literature, empirical studies report mixed results. For
example, King and Rebelo (1990) and Jones, Manuelli, and Rossi (1993) report that
corporate income taxation reduces economic growth. On the other hand, some studies,
such as Lucas (1990) and Stokey and Rebelo (1995), suggest that the effects are either
insignificant or may even work in the opposite direction. They are mostly calibration
studies based on US data.
Ambiguity in calibration results also call for empirical studies that attempt to trace
the impact of taxation in the growth regression framework by using the cross-country
data. These studies include Skinner (1987), Koester and Kormendi (1989), Easterly and
Rebelo (1993), Dowrick (1996), Agell, Lindh, and Ohlsson (1997), Bibbee, Leibfritz, and
Thornton (1997), Mendoza, Milesi-Ferretti and Asea (1997). These studies suggest
either negative or insignificant impact of overall corporate income taxation on
economic growth. More recently, Lee and Gordon (2005) utilized a newly-available
data on statutory corporate income taxes, and find a negative and significant effect of
corporate income tax rates on economic growth. Not only were the results robust to the
inclusion of other growth factors, but also their instrumental variable and fixed effects
estimates confirmed the basic results.
In contrast to the earlier studies on the relationship tax and economic growth, this
paper focuses on effective tax rates and cross-sector differences in corporate income
taxation, and their impact on economic performance. Hence, this study supplements
the existing literature in the sense that corporate taxation may affect overall growth not
just through the aggregate tax rate overall, but also through the preferential treatment
of certain industries. Cross-sector tax discrimination may disturb the equalization of
before-tax rates of return across industries, and thus hamper the efficient resource
allocation and capital accumulation.
4
3. Measuring Industry-Level Tax Burden
The main data analyzed in this paper come from the OSIRIS database provided by
Bureau van Dijk Electronic Publishing. OSIRIS reports financial data for 47,180 business
corporations from 1978 to 2006 from 138 countries. Due to missing values and entry &
exit of firms, the actual number of firms in the data is smaller. For example, the number
of firms with non-missing value of before-tax earnings is around 30,000 in 2005 from
107 countries. By using the financial data of business corporations, we construct
industry-level and country-level variables. We generate four 5-year sub-samples: late
1980's (1986-2000), early 1990's (1991-1995), late 1990's (1996-2000), and early 2000's
(2001-2005). For these four periods, we construct industry-level and country-level
time-series, cross-section data. Our data, industry-level or country-level, is an an
unbalanced panel.
Our key variable, effective tax rate (hereafter, ETR), comes from regressing corporate
income taxes on before-tax corporate earnings. We followed method used in Koester
and Kormendi (1989) which estimate effective marginal tax rates for a country by
regressing government's tax revenue on GDP for a sample of countries. To prevent
outliers from exercising undue influence on our estimates, we adopt median
regressions for our purpose. Reported before-tax earnings are adjusted for possible
loss-carry-forward and loss-carry-backward. When we estimate ETR, we use only
firms with positive (loss-carry-adjusted) earnings and positive tax payments, which
results in around 30% decrease in the number of firms. Using only firms with normal
operation improves the fit considerably.
Our estimated ETR reflect not just statutory marginal tax rates (hereafter, STR) but
also a myriad of provisions such as rules applying to investment and R&D tax credits
5
and special tax exemptions.3 Our estimation is an attempt to capture the overall impact
of statutory tax rates, tax credits and special tax exemptions.
Our country-level estimates of ETR are strongly correlated with statutory corporate
tax rates. The correlation coefficient between ETR and STR is 0.50 with p-value 0.000.
<Figure 1> shows how ETR and STR are related for each country in the 2001-2005
sub-sample. If the estimated effective tax rates coincide with statutory tax rates,
observations come along with the 45-degree. Although there are some cross-country
differences, overall, the estimated ETRs turn out to be consistent with STRs.
Not all the observations appear exactly on the 45-degree line. Some countries appear
above the 45-degree line, while other countries are located below the 45-degree line.
For the countries above the 45-degree line, the estimated effective tax rates are higher
than statutory tax rates. Given that our statutory tax rates are rates by the central
government, we can observe this pattern if local government tax burden on corporate
income is substantial. This pattern is observed in several OECD countries, such as
Norway, Switzerland, Japan, Germany, Italy, and Ireland. We also observed that ETR
is higher than STR in some countries with zero statutory rates, such as Jordan,
Bermuda, Cayman Islands, Saudi Arabia, and Kuwait.
On the other hand, when various tax exemptions are provided, the estimated
effective tax rates can be lower than statutory tax rates. In this case, observations can
appear below the 45-degree line. We observe that ETR is lower than STR by more than
10%p in Egypt, Ecuador, Paraguay, Latvia, Belgium, Taiwan, Sri Lanka, Israel,
3
Our effective marginal tax rates do not reflect differences in depreciation allowance and
interest payment because they are already deducted in the calculation of before-tax earnings. To
reflect effects of depreciation allowance and corporate financial structure on effective tax rates,
one needs to regress corporate income taxes on before-tax earnings plus depreciation and
interest payments. We explore the effect of differences in depreciation and corporate financial
structure on effective tax burden in a separate paper.
6
Philippines, Luxembourg, Austria, and Pakistan.
We examine how effective tax rates changed over time for three groups of countries:
all, OECD countries, and non-OECD countries. Since our data is an unbalanced panel,
we cannot use a simple average of estimated ETR, and need to control for missing
values. Using country-level data, we run simple regressions of estimated ETR on
period dummies and country dummies. <Figure 3> shows that, on average, our
estimated ETR decreased by 8%p from 32% in the late 1980s to 24% in the early 2000s.4
Decrease in effective tax rates is more salient in non-OECD countries. The average ETR
in non-OECD countries dropped by 11%p, while those in OECD countries dropped
only by 5%p. STR also dropped considerably over the same period. One interesting
pattern is that the difference in ETR between OECD and non-OECD countries becomes
much larger than that in STR, suggesting that tax credits and tax exemptions become
used more widely in non-OECD countries over time.
We estimate ETR not just for countries but also for industries in a given country. Our
classification of industry is based on Standard Industry Code (SIC). Starting from
one-digit SIC code, we combine or divide them to have similar numbers of observation
and to have several key industries as a separate category. We classify firms into 16
industries: agriculture, forestry, and fishing (two-digit SIC code between 1-9), mining
(10-14), construction (15-19), other manufacturing (20-27, 31-34), chemical (28-30),
industry machine & transportation equipment (35, 37), electricity (36), transportation
(40-47), communication (48), utility, i.e. electric, gas, and sanitary services (49),
wholesale trade (50, 51), retail trade (52-59), depository (60), non-depository (61-69),
service (70-79, 81-89), and health (80).
<Figure 5> presents ETR at the industry level for three groups of countries: all,
4
<Figure 4> shows that, on average, statutory tax rates also decreased by around 10%p from
7
OECD, and non-OECD. As in the investigation of over-time changes in ETR, we use a
simple regression to examine ETR by industry.5 Those figures are calculated using
estimated coefficients of industry dummies in the regressions of ETR on industry
dummies, period dummies, and country dummies. It is observed that on average,
non-depository, service industries, and communication are less heavily taxed than
construction, wholesale, depository, and utility. There are some differences between
OECD and non-OECD countries. Agriculture and retail are more heavily taxed in
non-OECD, while construction is more heavily taxed in OECD.
Estimating effective tax rates for individual sectors allows us to evaluate the
cross-sector differences in effective tax rates within a country. We use the standard
deviation of ETR across sectors within a country as a measure indicating a kind of
industrial policy through taxation. The choice of the standard deviation as a proxy for
cross-sector tax discrimination merits discussion. If a country decides to lowers (raises)
tax rates for industries with rates higher (lower) than the average rate while preserving
the average tax rates, it would represent a reduction in cross-sector discrimination and
be well captured by a decrease in the standard deviation of ETR. On the other hand, a
country reduces tax rates for each industry by the same %p, the level of ETR will be
lower but standard deviation of ETR will not be changed.
The standard deviation of ETR is especially low in countries such as the U.S. (0.03),
UK (0.06), Denmark (0.07), France (0.07), and Finland (0.07). Among OECD countries,
Norway (0.16), Austria (0.15), and Belgium (0.15) are countries with large standard
deviation of ETR. Note that these countries with higher standard deviation tend to
have higher level of ETR.6 Since we include both ETR and the standard deviation of
37% in the late 1980s to 27% in the early 2000s.
5
Of course, we use industry-level data in the calculation of ETR by industry, while we use
country-level data in the calculation of over-time changes in ETR.
6
The correlation coefficient between ETR and standard of ETR is 0.180 with p-value 0.027.
8
ETR as independent variables in regressions, the standard deviation captures (not
across industry) across country and period variability of ETR after controlling for the
average level of ETR.
5. Preferential Tax Treatment and Industry Growth
Do preferential treatments in taxation promote growth in the favored industries? How
do the preferential treatments affect capital formation and employment in the favored
industries? How do industrial policy through taxation affect the overall growth of
industry? This section provides empirical results to answer these questions.
Industry growth of the following five variables are used as dependent variable:
after-tax earnings, before-tax earnings, net sales, total assets, and employment. The first
two variables measure profits, the third variable measures output, and the last two
variables
measure
inputs.
Since
corporate
income
taxes
are
basically
on
equity-financed capital, it is expected to affect assets much more strongly than
employment. In the calculation of industrial growth, we do not drop firms with
negative earnings, because we are measuring growth of industry not of firms. As
mentioned earlier, we have four 5-year sub-samples. Combined with the classification
of industries into 16 sectors, the maximum number of observation is 4,480
period-industry cells for 70 countries (=4*16*70) in total. Among 4,480 possible cells,
we can estimate ETR and industrial growth for 1,486 cells. Dropping top and bottom
2% observations in the value of growth rate of before-tax profits leave us with 1,411
observations. We did so because there are some observations with extreme values of
growth rates. In median regressions for the whole sample without dropping these
observations with extreme values, we find qualitatively the same results.
9
In addition to ETR and standard deviation of ETR, we added log of initial GDP per
capita to control for the tendency of low-income countries’ growing faster. We also
added industry dummies, period dummies, and country dummies. Our specification
for industrial growth regressions is:
GrijT   0  1 ETRijT   2 sd ( ETR) iT   3 log( GDPpciT )  BInd j  CPerT  DCnt i   ijT
where subscript i indicates country, subscript j industry, and subscript T period,
GrijT is growth rates of industry,
ETRijT is estimated effective tax rates,
sd ( ETR) iT is standard deviation of ETR within a country,
log( GDPpciT ) is log of initial GDP per capita in constant US dollar,
Ind j is industry dummies,
PerT is period dummies, and
Cnti is country dummies.
In addition to pooled OLS, we also use instrumental variable (IV) estimation method.
Surely, one cannot dismiss a possible effect from industry growth to tax rates. It is
possible that high industry growth allows a lower tax rates if the government needs a
fixed amount of tax revenue. We use as instruments the weighted average ETR in other
countries, weighting by the inverse of the distance between the two countries. In a
similar way, we also construct IV for standard deviation of ETR. Lee and Gordon
(2005) use the similar IV in the investigation of the impacts of statutory tax rates on
economic growth. The correlation in the tax rates in nearby countries is remarkably
high in the data.7 Tax competition would make the weighted average of ETR and
7
The correlation between ETR and the weighted average of ETR in other countries is .7434 with
p-value 0.000, while the equivalent correlation for standard deviation of ETR is .6412 with
p-value 0.000.
10
standard deviation of ETR elsewhere a good instrument for the local tax rates and its
standard deviation.
<Table 1> provides summary statistics of the variables for industry-level regressions.
ETR is on average 28%, ranging from 0% to 98%. Standard deviation of ETR within a
country is on avearge 0.095. Growth of before-tax and after-tax earnings are on average
around 20-22%. Among various measures of industry growth, before-tax and after-tax
earnings are most closely correlated with correlation coefficient 0.89. The correlation
coefficient between sales and assets is 0.81, while that between sales and employment
is only 0.28.
<Table 2> presents OLS regression results for investigating the relationship between
ETR and industry growth. We include industry and period dummies in all regressions.
Column (1) shows that industries with lower values of ETR have high growth rates, as
expected. In Column (2), we added standard deviation of ETR within a country to find
that both the level and standard deviation of ETR are significantly negative. In column
(3) we added the log of the initial GDP per capita as an independent variable. In all
regressions with log of initial GDP per capita, it takes the expected sign.
The level of ETR is found to be significantly correlated with various measures of
industry growth except for being insignificant on employment. Our OLS results
indicate that a 10 percent point reduction in ETR would increase growth rates for
before-tax earnings, after-tax earnings, net sales, and assets by 3.07%p, 2.86%p, 2.97%p,
and 2.47%p respectively.
Standard deviation of ETR has a negative coefficient in the regressions for before-tax
and after-tax earnings, implying that more cross-sector differences can hamper
industrial performance in terms of earnings. However, as for net sales, the coefficient
11
turns out to be insignificant, although it is negative. It is interesting to observe that
growth rates of assets are correlated strongly negatively with ETR and standard
deviation of ETR, while growth rates of employment are significantly correlated with
neither ETR nor standard deviation of ETR. This suggests the impacts of corporate
income tax are mostly on capital not on employment.
IV estimation results without country dummies are reported in <Table 3>. ETR and
standard deviation of ETR become larger (in absolute value) and more significant in IV
estimation results. In fact, ETR and standard deviation of ETR become statistically
significant except for regressions for employment. Columns (1) and (3) of <Table 3>
imply that a one-standard-deviation decrease in ETR is associated with around 5.5%
increase in before-tax and after-tax earnings. A decrease in one standard deviation of
ETR by 0.04 is estimated to be associated with around 7.3-9.4% increase in before-tax
and after-tax earnings.
In <Table 4>, we also examine possible differential effects of ETR on growth by
country groups. We find that the level of ETR is significantly negatively correlated
with growth in non-OECD countries, while this correlation is not observed in OECD
countries. This result is consistent with the findings of Lee and Gordon (2005) using the
statutory tax rates. However, more interestingly, the negative impacts of standard
deviation of ETR are estimated to be much larger and more significant in OECD
countries. Perhaps this indicates that the cost of industrial policy becomes larger in
countries with more developed markets. Policy implication of this finding, of course, is
that the industrial policy should be avoided in the developed market economy.
<Table 4> reports regressions results when country dummies are added as
independent variable. Generally, the estimated effects of ETR and standard deviation
of ETR becomes smaller. However, ETR still remains strongly negatively correlated
12
with industry growth, and negative impact of standard deviation of ETR on growth of
earnings remains statistically significant for whole and OECD countries.
6. Cross-Sector Tax Discrimination and Economic Growth
Lower corporate income tax rates are likely to contribute to faster economic growth by
promoting entrepreneurship and investment. In fact, Lee and Gordon (2005) present
evidence that economic growth is faster in countries with lower statutory corporate
income tax rates. Djankov et. Al (2008) find that effective corporate tax rate have a large
adverse impact on aggregate investment, FDI, and entrepreneurial activity. In addition
to the aspect of lower corporate income taxes, this section examines how cross-sector
discrimination in taxation affects overall economic growth. Industry-level tax
discriminations, as measured by dispersion in ETR across industries, are an indication
of cross-sector preferential corporate taxation in a given country.
Industry-level tax favors may in principle promote economic growth when they are
appropriately targeted at industries with positive externalities and benefit of these
positive externalities is larger than the cost from distorting efficient allocation of
resources across industries and between corporate and non-corporate sector. However,
if the targeting of government misses the mark due to either its incompetence or
political pressures or both, the overall impact on economic growth can be negative.
As mentioned before, the country-level data is an unbalanced panel of country and
periods. Our country-level data consists of 161 observations: 28 countries in the late
1980s, 37 countries in the early 1990s, 41 countries in the late 1990s, and 55 countries in
the early 2000s. The dependent variable is the growth rate of GDP per capita within
each period. As independent variables, we include other key determinants of economic
13
growth identified in the literature as well as ETR and standard deviation of ETR. We
include log of the initial GDP per capita, average inflation rates, and average trade
openness. The specification used for the investigation of economic growth is:
GriT   0  1 ETRiT   2 sd ( ETR) iT   3 log( GDPpciT )   4 Inf iT   5TradeiT  BPerT   iT
where subscript i indicates country, and subscript T period,
GriT is growth rate of GDP per capita,
ETRiT is estimated effective tax rates for each country-period,
sd ( ETR) iT is standard deviation of ETR within a country ,
log( GDPpciT ) is log of initial GDP per capita in constant US dollar,
Inf iT is average inflation rate using CPI,
TradeiT is average of (imports+exports)/GDP, and
PerT is period dummies.
<Table 5> reports basic descriptive statistics for variables of the country-level data.
On average, the country grows at 2.8%. The average ETR is 28%, which is virtually the
same as the average ETR in the industry-level data. The average statutory tax rate is
32%.8
<Table 6> reports regression results. Column (1) shows that the raw correlation
between ETR and economic growth is statistically significant and negative. The
correlation between ETR and economic growth becomes 20% smaller when other
determinants of economic growth are added. Estimated coefficients of initial GDP per
capita, inflation rates, and trade openness take the expected sign. Columns (3) and (4)
8
For the explanation on the pattern and possible reason for the discrepancy between ETR and
STR, see section 3.
14
show that using STR instead of ETR produces a very similar result. Interestingly,
explanatory power of ETR in terms of R 2 is larger than that of STR. This is confirmed
in column (5), where ETR is statistically significant but STR is not significant when
both ETR and STR are entered.
Columns (6) through (10) report IV regression results. The estimated coefficients of
ETR and STR become larger in absolute value in IV estimations. When both ETR and
STR are entered in column (8), they are estimated to be significantly negative. Here,
though the estimated coefficient of STR is larger than that of ETR in the absolute value,
t-value of the estimated coefficient of ETR is larger than that of STR. In column (9), we
check differential effect of ETR on economic growth of OECD and non-OECD countries.
As reported in Lee and Gordon (2005), we find that lower corporate tax rates lead to
higher economic growth in non-OECD countries, while this pattern is not observed in
OECD countries.
In column (10) we added the standard deviation of ETR. Here, both ETR and the
standard deviation of ETR are insignificant, contrary to the finding of the strong
negative effect of standard deviation of ETR on industry growth. The reason for
insignificant effect of standard deviation of ETR on economic growth might be a
smaller number of observations and/or omitted variables, such as the share of
corporate sector. Note, however, that we don’t find evidence that industrial policy
through taxation promote economic growth either.
7. Concluding Remarks
This paper uses a firm-level data set of financial statements for a large sample of
corporations around the world to estimate sector-specific ETR in corporate income
15
taxation. We further investigate the effects of effective tax rates on growth of the
favored sectors and of the economy as a whole. The key findings can be summarized as
follows. First, industry and country with lower effective tax rates tend to grow faster.
In the industry-level regression, we find that sectors with low tax rates show a higher
growth of earnings, sales, and assets. Employment, however, is not found to be
significantly associated with the tax rate.
Second, it is found that industrial policy through preferential treatment in corporate
income taxation fails to achieve the desired effect. In the industry-level regressions, we
find that standard deviation of ETR is significantly negatively correlated with sector
growth. In the country-level regressions, we do not find evidence that countries with
larger standard deviation of ETR grow faster.
Our results show that industrial policy through taxation hampers the growth of
other sectors and fails to promote the economic growth, though it can promote the
growth of the favored sector. This might reflect the lack of government capacity to pick
industries appropriate for favors, or high-positive-spillover industries, or the
proneness of the government to succumb to political pressures. In either case,
industrial policy through corporate income taxation would not be an appropriate
policy tool, if the desired outcome is to promote overall economic growth, not merely
the growth of the preferred sectors or industries.
Third, we find that negative effect of industrial policy is stronger in OECD countries,
where the developed markets make government intervention more costly. This implies
that the room for government intervention becomes smaller as the economy and the
market develops.
Fourth, we find a large drop in the effective corporate income tax rates as well as
16
statutory tax rates. Interestingly, the effective tax rates did not drop as much as
statutory tax rates in OECD, while the former dropped more than the latter in
non-OECD. Among various industries, it is observed that on average, non-depository,
service industries, and communication are less heavily taxed than construction,
wholesale, depository, and utility.
Fifth, we observed a negative effect of initial GDP per capita on industry growth,
implying that convergence is observed not only in the country-level data but also in the
industry-level data.
17
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Lucas, Robert E., 1990, "Supply-Side Economics: An Analytical Review," Oxford
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Koester, Reinhard B., and Roger C. Kormendi. "Taxation, Aggregate Activity and
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Ineffectiveness of Tax Policy in Altering Long-Run Growth: Harberger's
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Rebelo, Sergio, 1991, "Long-Run Policy Analysis and Long-Run Growth," Journal of
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Skinner, Jonathan, 1987, "Taxation and Output Growth: Evidence from African
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Stokey, Nancy L. and Sergio Rebelo, 1995, "Growth Effects of Flat-Rate Taxes," Journal
of Political Economy, vol. 103, pp. 519-550.
Yamarik, Steven, 2000, "Can Tax Policy Help Explain State-Level Macroeconomic
Growth?" Economics Letters, vol. 68, pp. 211-215.
19
<Table 1> Summary Statistics for Industry-Level Regressions
Variable
Notation
Obs.
Mean
Std. Dev.
Min
Max
growth rate
for before-tax profits
Ebtgr
1,411
0.203
0.407
-0.642
2.038
1,340
0.223
0.459
-0.852
6.295
1,408
0.149
0.479
-0.694
10.236
1,411
0.144
0.355
-0.677
3.881
901
0.223
0.579
-0.890
4.856
1,411
0.277
0.126
0.000
0.979
1,411
0.095
0.042
0.001
0.296
1,411
15,019
10,370
216
47,281
growth rate
Eatgr
for after-tax profits
growth rate
NSgr
for net sales
growth rate
Assetgr
for total asset
growth rate
Empgr
for employment
effective tax rate
estimated for each
ETR_ijT0
industry
st. deviation of effective
ETRsd_iT0
tax rate across industry
GDP per capita
GDPpcIni
of the initial year
20
<Table 2> ETR and Industry Growth, Baseline Regressions, OLS
(1)
(2)
(3)
(4)
(5)
(6)
(7)
dependent variable
Ebt
Ebt
Ebt
Eat
NS
Asset
Emp
ETR_ijT0
-0.357
(0.088)***
-0.377
(0.090)***
-0.307
(0.090)***
-0.286
(0.105)***
-0.297
(0.106)***
-0.247
(0.076)***
-0.110
(0.167)
-0.521
(0.262)**
-0.629
(0.260)**
-0.669
(0.303)**
-0.048
(0.305)
-0.404
(0.220)*
-0.016
(0.462)
-0.051
(0.009)***
-0.051
(0.011)***
-0.079
(0.011)***
-0.071
(0.008)***
-0.067
(0.019)***
ETRsd_iT0
log of GDPpcIni
Constant
0.332
(0.071)***
0.393
(0.077)***
0.855
(0.113)***
0.932
(0.131)***
1.009
(0.133)***
1.006
(0.096)***
1.265
(0.238)***
Obs.
1,421
1,411
1,411
1,340
1,408
1,411
901
0.014
0.017
0.037
0.031
0.045
0.095
0.078
Adjusted R
2
Standard errors in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
21
<Table 3> ETR and Industry Growth, IV, OECD vs. non-OECD (with OECD dummy)
ETR_ijT0
(1)
Ebt
(2)
Ebt
(3)
Eat
(4)
Eat
(5)
NS
(6)
NS
(7)
Asset
(8)
Asset
(9)
Emp
(10)
Emp
-0.428
(0.122)***
-0.790
(0.201)***
-0.444
(0.144)***
-0.937
(0.238)***
-0.357
(0.143)**
-0.828
(0.236)***
-0.297
(0.103)***
-0.585
(0.170)***
-0.020
(0.231)
-0.520
(0.497)
0.818
(0.257)***
ETR_ijT0 X OECD
-1.741
(0.374)***
ETRsd_iT0
ETRsd_iT0 X
OECD
lnGDPpcIni
Obs.
-2.264
(0.435)***
-0.741
(0.790)
-0.052
(0.009)***
-0.031
(0.014)**
-1.083
(0.706)
0.978
(0.302)***
-0.906
(0.436)**
-1.707
(0.923)*
-0.053
(0.011)***
-0.243
(0.104)**
OECD dummy
Constant
-1.121
(0.612)*
1.032
(0.303)***
-0.040
(0.016)**
-0.316
(0.716)
0.645
(0.217)***
-1.298
(0.315)***
-0.726
(0.925)
-0.081
(0.011)***
-0.183
(0.123)
-0.069
(0.016)***
-0.892
(0.517)*
0.602
(0.565)
0.656
(0.668)
-0.449
(0.667)
-0.072
(0.008)***
-0.257
(0.122)**
-0.056
(0.012)***
-0.468
(1.428)
1.101
(1.658)
-0.066
(0.020)***
-0.202
(0.088)**
-0.118
(0.033)***
-0.115
(0.218)
1.028
(0.121)***
0.916
(0.160)***
1.176
(0.140)***
1.105
(0.186)***
1.137
(0.141)***
1.123
(0.187)***
1.136
(0.102)***
1.059
(0.135)***
1.146
(0.252)***
1.740
(0.403)***
1411
1411
1340
1340
1408
1408
1411
1411
901
901
0.039
0.044
0.084
0.092
0.076
0.078
0.024
0.033
0.009
0.010
Adjusted R
ETR_ijT0 for
0.028
0.095
OECD
[0.865]
[0.618]
[p-value]
ETRsd_iT0 for
-1.862
-2.790
OECD
[0.000]
[0.000]
[p-value]
Standard errors in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
2
22
0.150
[0.432]
0.060
[0.662]
0.082
[0.759]
-1.042
[0.062]
-1.341
[0.001]
0.633
[0.413]
<Table 4> ETR and Industry Growth, IV, OECD vs. non-OECD (without OECD dummy)
ETR_ijT0
(1)
Ebt
(2)
Ebt
(3)
Eat
(4)
Eat
(5)
NS
(6)
NS
(7)
Asset
(8)
Asset
(9)
Emp
(10)
Emp
-0.379
(0.145)***
-0.737
(0.218)***
-0.455
(0.171)***
-0.883
(0.259)***
-0.167
(0.169)
-0.463
(0.255)*
-0.206
(0.119)*
-0.360
(0.179)**
-0.326
(0.275)
-0.690
(0.565)
0.665
(0.293)**
ETR_ijT0 X OECD
-1.048
(0.548)*
ETRsd_iT0
ETRsd_iT0 X
OECD
-0.642
(0.967)
0.783
(0.345)**
-1.835
(0.650)***
-0.721
(1.146)
-0.429
(1.142)
0.549
(0.342)
-0.065
(0.638)
-2.335
(1.361)*
0.096
(1.126)
0.287
(0.240)
-0.660
(0.450)
-0.308
(1.334)
-0.652
(0.794)
0.463
(0.645)
-0.276
(0.946)
-0.041
(0.941)
1.635
(2.667)
-2.337
(2.866)
lnGDPpcIni
-0.495
(0.143)***
-0.521
(0.145)***
-0.443
(0.166)***
-0.450
(0.169)***
-0.069
(0.166)
-0.095
(0.168)
-0.046
(0.117)
-0.062
(0.119)
0.575
(0.306)*
0.578
(0.306)*
Constant
2.796
(0.841)***
2.954
(0.867)***
2.722
(0.976)***
4.931
(1.715)***
0.884
(0.979)
1.054
(1.008)
0.884
(0.691)
0.994
(0.711)
-4.478
(3.094)
-4.496
(3.093)
1,411
1,411
1,340
1,340
1,408
1,408
1,411
1,411
901
901
0.108
0.105
0.085
0.080
Adjusted R
ETR_ijT0 for
-0.072
-0.100
OECD
[0.712]
[0.660]
[p-value]
ETRsd_iT0 for
-1.363
-2.764
OECD
[0.034]
[0.000]
[p-value]
Standard errors in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
0.128
0.125
0.208
0.206
0.250
0.252
Obs.
2
23
0.086
[0.705]
-0.073
[0.648]
-0.227
[0.469]
-0.212
[0.776]
-0.693
[0.188]
-0.702
[0.482]
<Table 5> Summary Statistics for Country-Level Regressions
Variable
Notation
Obs.
Mean
Std. Dev.
Min
Max
GDPpcgr
161
0.028
0.022
-0.017
0.099
ETR_iT0
161
0.281
0.118
0.029
0.986
ETRsd_iT0
152
0.098
0.047
0.001
0.296
Statutory tax rate
STR
161
0.324
0.089
0.000
0.540
Initial GDP per capita
GDPpcIni
161
12,564
10,913
216
37,992
Average inflation rate
using CPI
InfCPIAvg
161
0.068
0.115
-0.013
0.793
161
0.785
0.587
0.171
4.062
growth rate of GDP per
capita
Effective tax rate
estimated for each
country
st. deviation of effective
tax rate across industry
(imports+exports) / GDP TradeGDPAvg
24
<Table 6> ETR and Country-level Growth
(1)
(2)
OLS
OLS
-0.050
-0.039
(0.013)*** (0.013)***
ETR_ijT0
(3)
OLS
(4)
OLS
(5)
(6)
OLS
IV
-0.032
-0.044
(0.014)** (0.015)***
(7)
IV
(8)
IV
-0.031
(0.016)*
(9)
IV
-0.013
(0.021)
ETR_ijT0 X CntOECD
0.010
(0.052)
ETRsd_iT0
-0.050
(0.022)**
STR
lnGDPpcIni
InfCPIAvg
TradeGDPAvg
OECD dummy
Constant
Obs.
Adjusted R
R
(10)
IV
-0.069
(0.018)***
0.078
(0.035)**
2
-0.050
-0.028
-0.080
-0.052
(0.022)** (0.024)
(0.029)*** (0.031)*
-0.004
-0.005
-0.005
-0.004
-0.006
-0.005
-0.006
-0.006
(0.001)***
(0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.002)***
-0.029
-0.024
-0.029
-0.030
-0.025
-0.030
-0.033
-0.032
(0.015)*
(0.015)
(0.015)* (0.015)*
(0.015)
(0.015)* (0.016)** (0.015)**
0.009
0.010
0.009
0.009
0.009
0.008
0.012
0.011
(0.003)***
(0.003)*** (0.003)*** (0.003)*** (0.003)*** (0.003)** (0.003)*** (0.003)***
-0.019
(0.011)*
0.048
0.078
0.050
0.091
0.091
0.080
0.107
0.103
0.081
0.100
(0.006)*** (0.013)*** (0.009)*** (0.017)*** (0.017)*** (0.013)*** (0.020)*** (0.020)*** (0.014)*** (0.018)***
161
161
166
161
161
161
161
161
152
161
0.082
0.169
0.020
0.149
0.171
0.204
2
ETR_ijT0 for OECD
[p-value]
Standard errors in parentheses
+ significant at 10%; * significant at 5%; ** significant at 1%
0.176
0.206
0.191
0.197
0.009
[0.733]
25
.6
.7
STR and ETR, late 1980s
DEU
.4
.5
JPN
CAN
USA
GBRNLDFRA
AUSTUR ZAF
ITAMYS
DNK
SWE
BEL IRL
THA
LUX
ESP
PHL
FIN SGPMEX
CHE
.2
.3
NOR
NZL
0
.1
HKG
0
.1
.2
.3
.4
Statutory Tax Rates
.5
.6
.7
.6
.7
.7
STR and ETR, early 1990s
.6
NOR
.5
JPN
ITA
.3
.4
DEU
.2
CHE
PAK
.1
HKG
ISR
USA
MEX
CAN
BGDZAF
FRA
AUS
GBR
KOR
NLD
TUR
DNK
GHA
IND
NZL
THA PHL
SWE
ESP GRC
MYS
LUX
SGP IDN
BEL
IRL
AUT
COL
0
CHL
0
.1
.2
.3
.4
Statutory Tax Rates
26
.5
.6
.7
STR and ETR, late 1990s
.5
NOR
.3
.4
JPN
.2
BRA CHE
GAB PAK
POL
DEU
USA
KEN
FRA GRC
ARG
AUS
NZL
ISR BGD
NLD
FIN GBR
DNK
TUR
SWE
MEX
ZAF
AUT
PHL
GHA
CHN
SVN PER
SGPMYS IRL
LKA
LVA
IND
.1
HUN
CHL
KORLUX
0
HKG
0
.1
.2
.3
.4
Statutory Tax Rates
.5
.6
.7
.6
.7
.7
STR and ETR, early 2000s
.6
NOR
.3
.4
.5
PNG
BRA
CHE
.2
IRL
HKG
CHL
.1
HUN
JPN ITA
ARG
GRC
USA
COL
PAK
DEU DNK
FRA
ZAF
MEX
KEN MAR
FIN
GBR
PER
AUS
GAB
IND
CHN
ESP
PAN
RUS
KOR
SWE
MYS
BGD
GTM
CZE
CRI
THA
EST AUT BEL
LKA
VEN
SGPSVK
SLV
EGY
HRV
SVN
VNM
0
LVA ECU
0
.1
.2
.3
.4
Statutory Tax Rates
27
.5
.4
STR and ETR, early 2000s, sub-sample with t between 0.2 and 0.4
ARG
GRC
USA COL
DNK
.3
DEU
FRA
PER
ZAF
KEN
FIN GBR
RUS
KOR
SWE
MEX
MAR
AUS
CHN
PAN
GAB
IND
ESP
MYS
GTM
AUT
BEL
.2
CZE
CRI
THA
EST
.2
.3
Statutory Tax Rates
28
.4
29
2
SAU04
EGY14
CHL07
AUS10
PHL06
JPN10
-1
0
e( Ebtgr | X )
1
JPN03
SGP08
BEL08
DEU06
JPN02
BRA04
MEX01THA13
MEX05
DNK08
GRC11
HKG04 SAU13
ZAF15
COL13
ISR04
JPN10
GRC08
ZAF08
MEX00
CHL04
KOR12
RUS03
AUS08
ISR08
ITA05
JAM08
THA05
CAN10
ISR06
IND10
NOR07
MYS02
ITA07
USA05ZAF13
HKG03
TUR03
SAU00
IND14
CHL10
BRA01
ITA05
KOR15 MYS10
ISR14
THA01
MEX03
JPN13
IRL02
ARG08
CHE10
GRC05
CAN06
NZL11
KWT08
ARG14
KWT14
CHL05
AUS00
EGY11
THA11
PAK11
HKG11
LKA00
HKG14
GRC04
NZL09
GBR09
KOR08
MYS14
SGP04
PNG10
CZE04
MEX11
EGY13
KOR06POL04
MEX13
BEL14
IRL07
MYS09
CHN04
BRA03
FIN10
PER01
NZL01
IRL07
ECU02
FRA00
MAR03
ITA02
THA07
USA13
CHL03
COL02
CHE09
IRL04
IND02
NZL11
RUS04
ARG02
USA14
KWT05
THA10
IRL13
FIN14
NOR06
CHN05
LUX03
KWT10
IND13
CHL05
THA07
KWT07 CHN09TUR10
ESP03
PAN13
CAN03
PER07
JPN11
TUR06CZE14
ESP03
NOR02
SWE10
IDN11
ZAF02
DNK06
NZL12
USA00
SWE03
FIN07
SWE05
GRC09
NOR04
NOR05
EGY05
EGY03
ARG09
LVA04
THA08
CHL08
KOR13
KOR07
ITA01
ESP02
NZL14
NOR03
FIN10
JPN09
GRC10
GRC02
KOR03
NZL01
CHE06
NZL07
PER01
SWE05
DNK08
CHE11
SGP05
MEX01
THA10
EGY06
SVN04
DNK13
POL04
CHL03
DNK09
NOR11
JPN00
JPN04
CAN13
MEX06
THA14
ISR02
TUR02
SWE15
THA01
JPN07
SWE11
GRC01
PER04
JPN13
SAU02
AUS13
CHE13
BEL07
ZAF11
AUT06
GRC15
MYS02
CZE09
DNK14
IND03
NOR06
CAN05
CAN09
CAN05
MYS14
CHE11
ZAF13
ZAF13
LKA04
SGP15
THA01
HKG13
SWE02
SGP09
KOR11
THA03
MYS01
GBR15
ECU03
AUT03
CHL13
SWE08
ARG11
GRC14
PHL13
BGD04
TUR06
KOR06
GRC03
PER05
DNK13
DNK07
HKG01
SWE02
MEX10
JPN14
JPN07
GBR08
ESP11
SWE04
ESP01
USA01
JPN10
BEL01
NZL10
CHN07
AUS14
SGP06
EGY08
GRC03
CZE01
USA15
SVN03
ISR02
SGP07
MYS01
USA06
JPN05
MYS04
KOR09
NLD06
CHE04
EGY07
IND09
PAK03
LVA03
SGP11
ITA07
SWE15
CAN15
KOR04
CAN00
NOR01
TUR03
FIN09
CAN15
GRC10
FRA13
ARG09
KOR09
PER13
CHE05
AUS13
ARG11
CAN13
DNK07
IND11
CAN11
PAN02
DEU06
ISR06
TUR03
NZL00
GRC06
SWE06
SWE13
SWE06
USA02
NOR01LUX09
PNG01
NZL00
TUR11
SGP13
GRC01
SWE08
BEL13
LVA10
FRA07
IRL03
FRA14
SWE10
ZAF06
JPN04
THA09
HKG07
COL00
IRL11
KOR06
EGY04
KWT03
BEL07
NOR05
EGY10
NLD14
DNK04
CHE13
FIN04
NZL03
AUT03
CZE03
LTU03
PHL11
MYS03
FRA03
SGP13
SWE13
AUS09
BRA11
DNK06
USA10
VEN09
JPN08
GBR02
KOR14
MYS06
BRA03
DEU08
AUS01
NZL03
NOR05
USA02
AUT01
SWE03
IND00
SWE07
DEU10
KWT13
ISR03
AUS09
GBR05
DNK11
ECU14
HUN04
NOR04
FRA15
NLD12
SWE00
NOR04
NZL13
AUS14
JPN14
SWE13
IRL05
DNK14
LKA00
SGP03
CHE03
DEU07
VEN04
CAN07
HUN08
NOR04
PRT11
FRA02
IND07
SWE02
CHE13
MEX07
PER03
BGD06
BEL03
GRC00
ZAF01
DNK03
NLD04
DEU09
DEU01
GBR13
CAN10
JPN11
SWE09
BEL03
DEU06
DNK02
AUS10
NOR09
HKG11
MEX08
CAN02
NZL09
CRI13
HKG11
SWE09
NZL13
SWE11
MAR08
SGP15
BEL02
PAN00
IRL11
SLV08
IRL04
IRL10
NLD11
MYS00
AUS03
CHN07
SGP13
DNK09
GRC14
MYS07
NLD05
AUS02
SGP11
GRC13
JPN08
SGP04
AUT09
IND04
CAN04
NOR01
EST02
MYS13
ZAF00
IRL14
MYS03
HKG11
NOR07
HKG09
BEL10
USA13
ZAF14
CHN08
USA03
GRC13
IND05
DEU11
HKG05
CHL06
SGP07
KOR05
MYS06
USA01
DNK10
KOR07
PAK05
JPN14
MYS06
NOR14
GBR04
SGP05
KOR05
NOR03
AUS09
GBR14
NLD13
BEL09
PER00
FIN08
CHE04
SGP03
PRT03
PAN11
BEL03
USA04
HKG09
SGP10
HUN03
CHL07
ZAF10
BEL09
GBR01
SAU10
POL03
THA04
DEU15
ESP04
NLD10
SWE07
ZAF03
ITA08
SAU03
HKG08
NLD04
FRA05
GBR08
HKG08
ZAF11
DEU09
DEU07
GBR05
AUS07
NZL04
ITA09
NLD07
LVA02
ITA05
MYS00
PER03
ITA10
AUT09
MYS01
AUT04
SWE09
GBR00
DEU10
AUT06
AUT04
AUS09
GBR05
AUS14
NOR01
SWE13
MEX01
SGP08
AUT06
FIN06
ESP13
MYS11
THA01
NOR02
GTM13
SWE12
JPN09
GBR01
USA10
CHL11
DNK03
SWE11
ARG01
PAK03
CRI03
CHE05
USA14
USA11
LKA11
NLD11
MYS09
DNK00
IDN10
DEU07
ESP08
FIN09
CAN03
HKG02
GRC07
NLD06
CHN05
CHE09
CHE09
FRA06
FRA09
SGP06
CHE06
CAN11
FIN11
LVA09
BEL13
ISR11
IRL10
IRL03
DNK05
IDN05
SGP01
JPN04
SWE01
IRL05
SGP07
NZL07
ZAF07
SGP01
IND04
CHN04
BEL02
CHN01
AUS11
KOR04
USA06
ZAF14
USA13
LUX03
SGP08
SGP05
HKG08
GBR07
ZAF08
AUT11
CAN01
USA02
DEU11
NLD07
HKG14
HKG10
HKG07
IDN03
AUS01
NOR09
AUS01
ZAF03
ITA01
FIN09
SWE03
AUS08
USA11
DEU14
LUX04
PRT09
GBR09
AUT02
SGP10
AUS15
FRA13
NOR08
VEN13
NZL00
CHE06
GBR03
DEU09
HKG06
IRL02
IND07
POL01
THA06
FIN07
SAU14
LKA14
EGY02
CHE10
GBR11
USA04
GBR03
USA11
PER10
USA12
CHL15
AUT04
USA01
GBR06
NOR09
IND09
THA08
SAU08
ESP09
ESP09
NZL08
ZAF01
FRA01
JPN15
DEU04
JPN06
IRL10
CHL11
BRA09
CAN08
PHL03
CHN03
CHL13
ZAF07
ITA09
AUS04
MEX14
USA15
ZAF03
SWE09
ZAF06
HKG13
MEX11
MEX03
ISR11
USA03
MYS13
PHL09
HKG02
IRL10
SGP11
GBR07
KOR13
AUS10
ITA04
JPN03
AUT02
CHE04
NLD13
ESP01
DEU07NLD09 PER08
FRA10
POL06
CHE04
ZAF04
JPN12
HKG09
BRA06
THA03
AUS11
MEX11
GRC14
IND05
HKG10
CHE08
BRA01
GBR04
ISL05
ESP04
PAK05
JPN11
CHL11
USA00
NLD01
USA05
BRA13
JPN05
SGP06
SVK04
FIN09
AUS03
USA09
JPN01
CAN04
PHL03
CHN13
CAN09
ESP01
CHE09
DNK10
NLD02
AUS03
KOR02
DEU03
ZAF09
SVK03
BEL13
AUS05
HUN14
DNK04
BRA04
FRA08
DNK04
DEU03
USA07
HKG07
NZL13
NLD03
CAN09
ISR11
SWE05
GBR09
AUS15
NOR10
GBR04
NLD03
MEX10
DEU15
BGD03
AUS14
DEU04
FRA08
HKG13
CHL09
CZE05
BRA09
NLD07
NLD11
KOR05
NLD02
SGP03
CHE05
GBR13
CHN11
KOR14
ITA13
FIN10
USA09
ECU00
BEL09
NLD04
DNK02
DEU00
CHE05
FRA03
BGD11
HKG07
CHE14
SWE04
SGP14
POL14
CHE03
GBR04
CAN11
JPN03
SGP11
GBR07
MYS03
GBR10
DEU08
THA09
HKG09
IRL11
FIN02
KOR09
CHE03
BEL11
ESP10
HUN09
FRA05
ITA00
MEX03
NLD05
DEU15
AUS12
ITA01
IND06
DEU05
LUX04
COL10
COL09
FIN13
CHE03
CAN09
DEU03
IND09
IND14
SGP15
FRA11
USA03
KOR02
DEU05
USA03
GBR01
MEX04
CHN09
FIN06
ESP14
FRA01
BEL08
FRA02
AUS07
ESP07
ESP08
IRL09
CAN15
MYS06
USA08
USA14
NLD03
ITA09
SWE15
GTM04
COL03
AUT05
NLD10
MYS14
USA04
ITA03
DEU10
ITA04
ECU11
BEL01
COL03
ISR04
GBR02
ITA03
JPN04 DEU09
ISL00
CZE04
FRA15
ZAF11
BEL07
FRA10
ARG13
FIN03
NOR02
NLD03
SLV13
SAU07
ISL05
DEU01
SGP14
NLD14
SGP02
FRA00
NZL03
USA10
BEL05
AUS07
RUS07
IRL03
KOR08
AUS02
PRT02
CHE13
MYS04
GRC03
USA09
FIN03
NZL06
THA03
NOR08
AUS11
MYS11
FRA10
KOR03
AUS03
GBR01
JPN07
AUT06
MYS00
ITA08
NZL08
MEX08
RUS08
DEU10
SVN04
GBR06
IRL03
FRA09
NLD10
SWE03
FRA04
IDN10
USA14
KEN03
IRL14
PHL01
CHE11
USA04
FIN06
CAN11
ARG02
GRC11
THA07
MYS10
MAR09
GRC13
SGP15
BRA10
BRA11
SGP10
SGP03
FRA09
AUS04
THA10
GBR11
GBR03
AUS05
ARG08
ISR08
AUT01
SWE06
HUN01
GBR00
SGP10
FRA02
AUS01
ESP03
CHE14
FRA05
JPN00
SGP08
GBR14
DNK14
PHL03
NLD08
AUS04
USA08
SVK09
DEU04
LVA07
CHL09
CHL03
AUS08
NOR13
DEU11
IDN03
DEU03
BEL04
PHL09
NLD14
PER09
IND08
USA10
THA12
FRA04
ESP05
NOR11
NOR06
IND02
DNK03
BEL04
FRA01
GBR05
FRA11
USA00
GBR10
FRA10
GRC04
CRI07
CHL06
PRT05
SWE02
CZE09
EST09
MYS09
ESP02
FRA11
GBR10
NZL14
MAR10
MYS00
THA11
MEX02
HKG08
DNK04
GBR14
AUT05
BEL10
GRC05
ESP07
NLD01
HKG13
KOR03
FRA06
KOR01
KWT04
FRA09
DNK01
AUS02
IND04
USA06
FRA14
DEU04
GRC10
IND03
GBR03
MYS05
GBR11
DEU14
JPN00
JPN10
SWE01
GBR11
MYS03
CRI04
FRA03
MYS07
MYS04
USA07
AUT10
DNK03
FRA04
CAN07
DEU01
AUS07
JPN08
IND06
ESP09
MYS05
MYS02
AUT13
MYS02
ITA11
BEL04
KOR04
BEL11
DEU14
IND15
CHE07
FIN04
MYS08
USA11
EST08
FIN11
ZAF10
PER11
ITA11
DEU05
NOR07
GBR13
CHN02
ESP14
NZL08
MAR04
ZAF04
SWE11
COL09
THA06
CHE14
KEN07
JPN15
JPN11
SGP05
PHL00
BGD04
FRA13
SGP07
ARG03
USA09
JPN06
BEL10
FRA06
GBR10
MAR03
AUS00
VNM03
CHL08
FRA14
JPN05
LTU06
MYS04
AUS08
ZAF07
HKG14
BEL06
AUS15
ZAF03
FIN13
EGY09
BGD13
ITA11
CAN04
LKA03
CAN14
BRA08
USA05
PHL07
ESP10
GRC02
CHE07
HKG03
FRA05
THA04
DNK10
FRA11
FRA03
DNK07
IND03
DEU13
CAN13
PRT05
ZAF14
NZL11
CAN08
CZE06
GBR02
KOR10
FIN05
NLD02
ITA00
IDN08
NZL06
SWE10
COL03
ZAF02
AUT07
USA08
CAN02
DEU02
HKG10
FRA01
MYS11
IRL13
TUR11
AUT04
BEL03
GBR06
BEL10
ESP05
DEU08
JPN02
CZE01
GBR00
IDN08
CAN05
GRC00
THA15
NZL03
COL11
THA03
DNK09
NLD04
ITA06
CHL04
IRL14
FIN07
BRA12
ZAF00
ZAF13
PHL14
THA14
ESP02
FRA14
HRV03
RUS14
AUT05
THA02
BEL11
CHL00
SVN07
SLV09
MYS08
AUS13
DEU11
FIN04
SWE05
RUS10
CHN10
DEU02
MEX14
ESP04
PHL01
AUT01
HRV14
GRC09
DEU01 MYS09
NOR03
IND00
HKG03
MYS01
ZAF04
CHE08
CHN06
IDN07
ESP11
FRA04
LKA05
BEL01
GBR00
CAN08
DNK06
PHL08
GTM03
EST03
IND05
ZAF07
IRL13
FRA00
AUS10
FIN10
CZE08
PRT04
PAK08
ITA10
TUR05
CAN14
ARG01
IND10
FIN05
ZAF01
FIN03
ESP07
ZAF05
MYS05
BGD05
AUT10
FRA06
DEU05
FIN07
NOR06
ISR10
DNK02
DEU02
FIN08
ISR13
ITA02
MYS08
HUN08
RUS06
AUT02
AUT03
KOR13
HUN03
KOR08
CHE11
ZAF01
CHE10
PER14
PHL07
MAR01
ISR03
ZAF06
ZAF08
ZAF15
SGP04
MYS07
ESP06
CAN03
AUT07
CHL07
DNK05
AUT09
LVA03
THA08
TUR04
GHA03
ITA06
BGD06
IND08
THA13
USA02
AUT13
ESP13
CHN14
FIN11
SGP13
ZAF10
CAN10
BEL11
GRC08
BEL13
HKG14
SWE04
POL03
IND12
IND00
NZL04
CAN13
TUR05
BEL12
BEL09
SLV10
RUS01
GRC15
MAR06
PRT14
ESP13
IRL08
FRA13
AUT02
MAR13
ESP06
CZE00LVA10
PHL13
BEL07
SWE15 ESP14
BEL08
JPN02
HUN14
LKA13
SWE07
ZAF10
BEL06
BEL00
HKG02
ZAF04
AUT13
BEL04
DNK06
NLD10
MAR07
ISR14
IND14
NLD01
IND01
NZL04
LKA07
ESP01
POL10
THA10
ESP11
ESP03
ESP10
PRT13
NZL13
USA13
ESP04
BRA05
MEX05
ESP11
ITA13
THA15
MEX04 RUS05
VEN08
GRC06
ESP02
PHL08
MEX04
PAK13 BGD11
-.4
-.2
0
.2
e( MET_ijT0 | X )
coef = -.30679381, se = .08993343, t = -3.41
30
.4
NLD09
AUT01
.6