What do we Know about Intensive and Extensive
Tax Margins of Business Behaviour?
Ruud A. de Mooij1 and Sjef Ederveen2
Abstract
Corporate taxes exert a variety of effects on business behaviour. A wealth of recent empirical
evidence assesses the magnitude of these behavioural margins of taxation. This articles offers
an up-to-date review and aims to provide common ground by computing for each distortion the
semi-elasticity of the corporate tax base. We pay particular attention to international investment.
It is not a priory clear whether marginal investment decisions or discrete locations are most
important here. Using an extension of the meta data base of De Mooij and Ederveen (2003), we
explore the extent to which existing studies reveal differences in effect size between the
intensive and extensive margins of investment.
1
Erasmus University Rotterdam, CPB, CESifo, Tinbergen Institute and Oxford University Centre for Business Taxation. E-
mail: [email protected].
2
Ministry of Economic Affairs, the Netherlands. E-mail: [email protected].
1
1
INTRODUCTION
Corporate taxes influence business behaviour in several ways. For instance, firms exploit tax
arbitrage opportunities between the corporate and non-corporate organizational form, they
switch between debt and equity finance for their investment, or they reduce investment in
response to tax. Multinational firms can further choose to allocate their income in foreign
affiliates if taxes are lower there or they modify location decisions in response to tax. On the
quantitative importance of each of these behavioural margins of taxation is a wealth of
empirical evidence. There is, however, little common ground for comparing different
distortions. Which effects are most important in quantitative terms? This articles offers an upto-date review of empirical studies on various decision margins and aims to provide common
ground by computing the impact of different margins on a nations’ corporate tax base.
The paper starts by reviewing empirical studies on five decision margins of business tax:
organisational form, corporate financial policy, profit shifting, domestic investment and
international investment. While most studies in the literature – including most literature reviews
– focus on the significance of the statistical relationships, this article concentrates on effect
sizes. The reason is that effect size is particularly relevant for policy makers. Indeed, the sole
conclusion that taxes matter for firm behaviour will not satisfy policy makers who are
responsible to design tax policy. They require information about the (relative) importance of tax
effects as well as the tax parameters that cause these effects.
The paper makes the effect size of different behavioural effects to tax comparable by
computing the semi-elasticity of the tax base at each margin. This indicator measures the
percentage change in the corporate tax base in response to a 1%-point change in the appropriate
measure of tax. Its interpretation is intuitively appealing because it can be related to the revenue
consequences of changes in the corporate tax rate. More specically, if we pre-multiply the semielasticity of the tax base by the current tax rate, it gives the revenue-effect induced by the
behavioural response. For instance, if the tax rate is 25%, a semi-elasticity of − 1 implies that an
ex-ante £ reduction in corporate tax yields only 75 pence of revenue ex-post because of this
behavioural response to the tax.
This article pays special attention to international investment choices. Theory is ambiguous
on whether international investment decisions are driven primarily by the company tax burden
at the margin of new investment or by the average tax burden on company profits, which
applies to e.g. discrete location choice. We extend the meta data base of De Mooij and
Ederveen (2003) to assess the difference between the intensive and extensive investment
margins to tax on the basis of existing studies.
2
2
BUSINESS TAXATION AND FIRM DECISION MARGINS
This section discusses five behavioural responses to business taxation. For each decision
margin, we provide a short comprehensive review of recent empirical studies, sometimes by
referring and extending earlier literature reviews. In discussing empirical studies, we
concentrate on effect sizes. The aim is to arrive at a consensus estimate of the semi-elasticity of
the total corporate tax base for each of the five margins. The semi-elasticity is defined as
(∂B / ∂τ ) / B , where B denotes the corporate tax base and τ the corporate tax rate. While this
gives us a rough idea of the relative size of different behavioural margins, our approach neither
does justice to specific circumstances in practice e.g. in certain countries, sectors or times, nor
does it take away the uncertainty about effect sizes. Moreover, it only captures partial effects,
not taking account (general equilibrium) interactions. The only purpose is to simply translate
existing insights from empirical studies into a policy-relevant indicators measuring the size of
distortions induced by business taxation.
2.1
Organisational form
In most countries, incomes earned in sole proprietorships are subject to the personal income tax.
Incomes earned in (closely or widely held) corporations are first subject to corporate income tax
and are then possibly taxed again at the personal level via taxes on profit distributions or
realized capital gains (whereby sometimes double-tax relief is applied). The different tax
treatment of corporate versus non-corporate income creates arbitrage opportunities. Indeed, if
corporate income would be taxed lighter than non-corporate income, people would have an
incentive to become entrepreneur, while entrepreneurs would have an incentive to incorporate
so as to reduce their tax liability.
Yet, decisions on legal form of business are not only made on the basis of tax. For instance,
some businesses organized in the corporate form may collect substantial non-tax benefits, such
as gains from limited liability or the advantage of attracting capital. Others may incur costs
from incorporation, e.g. due to capital requirements or legal obligations. Non-tax costs and
benefits should therefore be weighed against the net tax advantage of corporate versus noncorporate income. Empirical evidence should guide us on how large the effects of taxation are.
A modest literature has explored the impact of taxes on the choice of legal form. Most of
these studies use statutory corporate tax and top personal income tax rates as proxies for the tax
burden on corporate and non-corporate income. Earlier studies reviewed in e.g. De Mooij and
Nicodeme (2008), find that the effects of taxation are small, suggesting that non-tax factors are
more important in determining legal form. Most of these studies use time series variation to
identify the impact of tax. Goolsbee (2004) criticizes this approach as the variation in tax rates
over time is small, making it difficult to properly identify tax effects. Goolsbee (2004) then uses
3
cross-section data for US States and industries in the retail trade sector in 1992. He explores the
impact of taxes for several indicators on the size of the corporate sector, including the share of
companies, employment and sales. His estimates suggest a larger semi-elasticity of the
corporate tax base with respect to the corporate tax rate than earlier studies. In particular, a 1%point increase in the tax differential between the two legal forms would change the share of
corporate assets (and hence the corporate tax base) by 0.4%. De Mooij and Nicodeme (2008)
use a panel of European data on the corporate share of companies and the corporate share of
employment in different European countries between 1997 and 2003. For alternative
specifications and indicators, they report an even larger semi-elasticity of the tax base of around
− 1.0.3
A semi-elasticity of the total corporate tax base between − 0.4 and − 1 would mean that a
10%-point higher tax rate on corporations ceteris paribus reduces the corporate share of
business by between 4% and 10%. Such an erosion, however, is accompanied by an expansion
of the personal income tax base. The overall revenue implications for the government will
therefore be smaller than the erosion of the corporate tax base suggest. Avoiding arbitrage
through the legal for of business requires that the tax difference between alternative legal forms
is minimised.
2.2
Corporate financial policy
While interest on debt is deductible from the corporate tax base as a cost, the return on equity is
generally not. For national investors, the difference in the tax treatment of debt and equity can
sometimes be partly compensated by taxes at the personal level. Yet, for international investors
there is no such offset. As a result, debt is almost everywhere tax favoured relative to equity. It
induces firms to increase their leverage, thereby causing an erosion of the corporate tax base
and a distortion in asset portfolios. Recent financial innovations − such as the arrival of hybrid
financial products − seem to have increased this financial arbitrage.
The question is how large the impact of corporate taxation is on a firms’ financial policy. On
the one hand, the optimal source of finance generally depends on various non-tax factors, such
as the risk of bankruptcy in case of the high debt ratio, or the importance of financial distress or
agency costs. Moreover, thin capitalization rules may put limitations on the use of debt finance.
On the other hand, taxes may create a substantial advantage of debt over equity, thereby
affecting a firms’ financial policy.
A number of studies aim to identify the impact of taxation on the financial leverage of firms.
Graham (2003) reviews several studies using time series data and concludes that most studies
report only small tax effects. However, an important problem of the earlier empirical literature
3
This effect is still small compared to the evidence in Gordon and Slemrod (2002) who report a semi-elasticity of 3.0 for the
share of personal income in total income.
4
is that identification is difficult in light of the small variation in tax rates over time. More recent
studies using cross-section variation between companies typically report larger effects. For
instance, Gordon and Lee (2001) exploit the variation in statutory tax rates between small and
large companies in the US. Controlling for other factors that possibly explain the difference
between a small and large firms, they find that a 1%-point reduction in the corporate tax rate
reduces the debt/asset ratio at the margin by 0.36%-point.
Thin capitalization also matters for international investment. Headquarters investing in
subsidiaries abroad can choose between debt and equity finance. The tax burden on the income
earned depends on this choice of finance. When financed by debt, the interest is deductible for
the subsidiary in the host country and taxed in the home country of the parent. When financed
by equity, the dividend of the subsidiary is taxed at the rate of the host country and repatriated
dividends are untaxed in the country of the parent if that country uses an exemption system
(which is the case in continental Europe). To minimize the tax liability, a parent company will
therefore prefer debt finance for subsidiaries located in high-tax countries and equity finance for
subsidiaries in low-tax countries. Recent empirical studies explore the impact of taxation on the
financial policies of multinationals, thereby using cross-country variation in tax rates. Altshuler
and Grubert (2003) use data on foreign affiliates of US multinationals and estimate the effect of
tax rates on the debt/asset ratio. They report a semi-elasticity of − 0.4, i.e. a 1%-point higher tax
rate reduces the share of debt by 0.4%. Similarly, Desai et al. (2003) arrive at a semi-elasticity
of − 0.25. These elasticities seem of similar size as the response of debt/asset ratios in the
national context.
Abolishing the discrimination between debt and equity is possible by either allowing a
deduction for the cost of equity (as under the allowance for corporate equity) or by disallowing
a deduction for the cost of debt (as under the comprehensive business income tax). A semielasticity between − 0.25 and − 0.4 means that, if a corporate tax rate is 30%, removing this
discrimination would increase the debt/asset ratio by between 7.5 and 12%-point.
2.3
Multinational profit shifting
Across countries, taxable income of a multinational is divided among its affiliates on the basis
of separate accounting. It means that the accounts of each affiliate terminate at the border (the
water’s edge) and that profits within these borders are taxed according to the rules and the rate
of the country where the subsidiary resides. This allocation of profits on the source basis is
often arbitrary, however. For instance, where should the multinational allocate shared costs and
returns? And how should it value intrafirm deliveries or services? Due to this arbitrariness,
multinationals have opportunities to manipulate this allocation and reduce the overall tax
liability of the company. Separate accounting indeed allows for international tax arbitrage,
which erodes the base of a nation’s corporate tax.
5
One important route for shifting multinational profits is the manipulation of transfer prices.
Following the OECD Transfer Pricing Guidelines, transactions between entities of a
multinational company in different countries should be traded on the basis of arms-length
prices, i.e. prices that would apply to market transactions between unrelated parties. For a
number of goods and services, however, there is no outside market. The uniqueness of many
intangibles, such as brand names and intellectual property rights, makes it impossible to
determine arms-length prices. It leaves the freedom for multinationals to determine their own
prices on a discretionary basis. By charging an artificially low price for goods that are
transferred from high-tax to low-tax countries, a multinational can reduce its overall tax
liability.
There is a rapidly growing literature showing that international profit shifting is an
important phenomenon with big implications for government revenues. The character of these
studies is diverse, which makes it difficult to infer a comparable indicator of the effect size. For
the purpose in this paper, we rely on a handful of studies estimating the impact of statutory tax
rate differentials on aggregate measures of profitability. The results of these studies are usually
interpreted as indirect evidence of profit shifting. The estimates directly measure the
quantitative importance of income shifting for the corporate tax base of a country. De Mooij
(2005) summarizes these studies and reports that, on average, the reviewed studies yield a semielasticity of the tax base of − 2, i.e. a 1%-point higher corporate income tax rate in a country
reduces the reported taxable profits by 2%.
This figure suggests that the behavioural response associated with profit shifting is relatively
large. It may explain why countries compete aggressively over their corporate tax rates, which
caused a steady decline in rates over the last decades (see e.g. Loretz, 2008). As the incentives
for profit shifting are driven by international differences in statutory corporate tax rates, the
only way to eliminate these arbitrage opportunities is through international cooperation, e.g. by
introducing a common (minimum) tax rate.
2.4
Aggregate investment
Neo-classical theory suggests that investment is driven by the Jorgenson concept of the cost of
capital. The idea is that firms accumulate capital as long as the return to investment exceeds the
cost of finance and depreciation. Due to decreasing returns to scale, there is a marginal project
that just breaks even, i.e. which earns a return that precisely matches the cost. In the presence of
taxation, the pre-tax rate of return on the marginal investment project is defined as the cost of
capital.
To determine the effect of corporate taxes on investment, we need to asses: (i) the impact of
the corporate tax on the cost of capital; (ii) the impact of the cost of capital on investment. The
first effect depends on the initial corporate tax system and can be illustrated by a simple
6
example. Assuming equity-financed investment, the cost of capital (c) depends on the corporate
tax (τ) in the following way
c=
1 − τA
(r + δ )
1 −τ
(2.1)
where A denotes the net present value of tax allowances in percent of the cost of an investment
and r+δ is the pre-tax cost of capital. This expression shows that the corporate tax rate exerts no
effect on the cost of capital if A = 1, which is the case under an allowance for corporate equity
or a cash-flow tax. Intuitively, these systems turns the corporate tax effectively into a nondistortionary rent tax. With smaller tax allowances (i.e. A < 1), corporate taxes raise the cost of
capital.
On the second effect, there are two strands of empirical literature. One directly estimates the
elasticity of the cost of capital on investment. Hassett and Hubbard (2002) review this literature
and conclude that an elasticity between − 0.5 and − 1.0 is a good reflection of it. Alternatively,
one can divide the substitution elasticity between labour and capital by the labour income share
in production to infer the investment elasticity of the cost of capital indirectly. Chirinko (2002)
provides a careful assessment of this empirical literature and concludes that a value between 0.4
and 0.7 is most plausible for the substitution elasticity. Assuming a labour income share of
80%, we again obtain an elasticity of investment to the cost of capital between − 0.5 and − 1.
For our purpose, we need to determine the size of the impact of the corporate tax on the cost
of capital. Instead of the corporate tax rate, we measure this impact by the effective marginal
tax rate (EMTR). It is defined as the difference in the cost of capital in the presence and in the
absence of tax, in percentage of the pre-tax cost of capital, i.e. EMTR = (c− r− δ)/c. Hence, as
long as the corporate tax raises the cost of capital in (2.1), the EMTR is positive. The EMTR is
a summary indicator measuring how distortionary the corporate tax system is for marginal
investment decisions. From the definition, we can now derive for the semi-elasticity of
investment (I) with respect to the EMTR.
∆Log ( I ) = α∆Log (c) =
α
1 − EMTR
∆EMTR
(2.2)
where α stands for the investment elasticity of the cost of capital (i.e. the value between − ½ and
− 1). A number of studies have computed EMTRs using information from tax codes. They
usually report positive values for equity-financed investment but negative values for debtfinanced investment, which is due to the deductibility of nominal interest. Hence, the corporate
tax provides a net subsidy to investment financed by debt. The weighted average of the EMTRs
is usually reported to be positive, however, indicating that the corporate tax system reduces
7
investment on balance. Its value is generally small, however. For an EMTR of say 10%, the
semi-elasticity of investment to the EMTR lies in the range of − 0.55 to − 1.1. These
investments only earn a marginal return, however, no economic profit. To the extent that the
corporate tax base consists of economic rents, a 1% increase in capital yields a smaller than 1%
increase in the corporate tax base. For instance, if (quasi)rents would constitute half of the
corporate tax base, the semi-elasticity of the corporate tax base via the channel of marginal
investments would be halved to a range between − 0.3 and − 0.6.
Apart from marginal investment decisions, capital formation may be affected by a firm’s
internal funds in the presence of liquidity constraints. Such constraints may arise from
asymmetric information between creditors and investors. Indeed, banks usually have less
information than firms about the chance that an investment project will yield a sufficiently high
rate of return. Banks will then be reluctant to provide credit. This applies in particular to new
and innovative firms who do not yet have a reputation. These firms therefore rely on retained
earnings (or venture capital) as a source of finance for new investments. A lower average tax
burden on these firms will relax credit constraints by improving their own liquidity position and
allow them to finance increase investment. Empirical evidence provides support for the positive
impact of net internal funds on investments (see Hubbard, 1997, for an overview). Given the
limited number of studies and the large diversity of approaches, we are not able to present a
consensus elasticity of the tax base for this channel.
2.5
Foreign investment
Foreign investment is part of total investment, which we discussed in the previous subsection.
There are some special features, however, that relate in particular to foreign capital and not
domestic capital. This subsection therefore pays special attention to the impact of taxes on
foreign investment.
There are two alternative views on how corporate tax policies affect cross-border
investment. The first view is the neoclassical approach, which follows the same logic as section
2.4. Assuming that capital is mobile across countries, investors will seek the most profitable
investment opportunities across the globe. This ultimately equalizes the after-tax rates of return
in all locations. The relevant tax for investors in deciding about the size of their foreign direct
investment (FDI) is then the EMTR. It applies to, for instance, multinationals that have already
established foreign subsidiaries and who decide on how much to invest in each of these
locations.
The second view considers discrete location choices. It may apply, for instance, to
investments that are lumpy. Alternatively, it can be relevant for multinationals that earn a firmspecific economic rent. For instance, (quasi) rents associated with patents, brand names, knowhow or market power are typically mobile across borders. A firm earning such a rent can decide
8
on the location of its plants based on the total tax bill. For this decision, the average effective
tax rate (EATR) on corporate income matters, not the EMTR. Indeed, the higher is the tax
burden on the income earned in a location, the lower is the probability that a firm will locate its
plant.
These alternative theories are not necessarily conflicting. Indeed, firms may first decide on
the location of their plants and then, conditional on location, determine the amount of
investment. For the first choice, the EATR matters; for the second choice the EMTR matters. It
leaves open the question what we can say about the most relevant decision margin. How
sensitive are the intensive and extensive investment margins to corporate tax? Which part of the
corporate tax system (and, therefore, which indicator of tax) induces the largest behavioural
effects? Empirical evidence should guide us to the most likely answers. We discuss this in
section 3.
3
INTENSIVE AND EXTENSIVE MARGINS OF FOREIGN
INVESTMENT
There is a large literature exploring the impact of corporate taxes on international capital flows.
The typical study in this literature regresses a measure of the company tax burden on a measure
of foreign capital flows or stocks, thereby controlling for other factors that affect investment.
Surveys by Hines (1999), Devereux and Griffith (2002) and De Mooij and Ederveen (2003)
conclude that according to most of this literature, company taxes have a significantly effect on
foreign investment.
The literature is heterogeneous in a number of respects. First, studies adopt alternative
measures of capital: some use aggregate data on FDI (time series, cross section and panels),
others rely on measures for property, plant and equipment (mainly US investment abroad), and
again others adopt count data on the number of foreign locations. Second, studies use different
measures of the tax burden: some use statutory corporate tax rates (sometimes for US states on
inward investment), others rely on the EMTR, the EATR, or average tax burdens computed
from micro or macro data. Finally, studies differ in their way of identifying the tax effect on
investment. For instance, some consider the tax regime in the country where the parent
company resides (credit or exemption), studies differ in the control variables they use, and
researchers use different theoretical specifications and econometric methodologies.
This section uses previous empirical findings to assess the most relevant decision margin for
international firms, i.e. marginal investment versus discrete location. To that end, we use a
previously constructed meta sample on the semi-elasticity of foreign investment (De Mooij and
Ederveen, 2003). The sample is a collection of 351 estimates originating from 25 different
studies in the literature. The semi-elasticities reflect a uniformly defined indicator for the effect
size and measure the percentage change in foreign capital in response to a 1%-point change in
9
the tax rate. Apart from the semi-elasticity, the meta data base contains information about the
underlying primary studies, such as the type of capital data and the type of tax indicator used.
De Mooij and Ederveen (2003) explain the systematic variation in study outcomes on the basis
of a large variety of study characteristics. 4 This paper extends that previous meta analysis in two
directions. First, we add six recent studies to the sample. Second, we concentrate on a particular
classification of studies regarding the use of capital data and the use of tax indicators. This aims
to shed light on the differences in effect size for location choice versus marginal investment
choice.
3.1
The meta data base
Appendix A summarizes how we constructed our meta database. It describes the methodology
followed in De Mooij and Ederveen (2003) and adds information from another six studies.
Overall, the new meta sample contains 449 observations for the semi-elasticity of foreign
investment. As in the previous study, we removed outliers that are outside the range of plus and
minus two times the standard deviation from the mean. It leaves us with a sample of 437
observations. Figure 1 shows the distribution of semi-elasticities in this new meta sample,
where the x-axis shows intervals of values for the semi-elasticity and the y-axis shows the
number of observations in each of these intervals.
Figure 1
Distribution of semi-elasticities in the entire meta sample
140
Series: SEMI_ELASTICITY
Sample 1 500 IF (DUBIOUS=0) AND ((Y2>(@MEAN
(Y2,"1 500 if dubious = 0")-2*@STDEV(Y2,"1
500 if dubious = 0")) AND Y2<(@MEAN(Y2,"1
500 if dubious = 0")+2*@STDEV(Y2,"1 500 if
dubious = 0"))))
Observations 437
120
100
80
60
40
20
0
-30
-20
-10
0
10
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
4
-3.845472
-3.016129
8.802083
-36.70000
5.770081
-1.789084
9.694104
1049.061
0.000000
Meta analysis is not common in economics. In general, it aims to synthesize research results using a statistical approach
towards reviewing and summarizing the literature. For a review of the pros and cons of meta analysis, see e.g. Florax et al.
(2002).
10
We see that the mean value in the sample is − 3.8, i.e. a 1%-point increase in a tax measure in a
certain location reduces foreign capital by 3.8%. The distribution in Figure 1 is somewhat
skewed to the left due to some large negative values. The median is therefore smaller, − 3.0.
The standard deviation of 5.8 suggests that the variation across studies is large. The meta
regressions aim to explain the systematic pattern in this variation with respect to the underlying
characteristics of the primary studies.
An important issue in meta analysis is the quality of the primary studies. This can be quite
different, e.g. because studies differ in the number of observations, the quality of the data or
their identification strategy. One may take into account quality differences in the meta
regressions by weighting observations using an indicator for quality. One such indicator that is
sometimes used in meta analysis is the standard error of the estimated coefficient. The problem
in our meta sample is, however, that the required information to compute standard errors of the
semi-elasticities is often missing.5 As an alternative, we register whether an estimated
coefficient is statistically significant at the 5% confidence level. We then divide our meta
sample into two subsamples: one based on only significant and one based on only insignificant
coefficients. Overall, the number of significant elasticities (218) slightly outweighs the number
of insignificant ones (209). We present the distribution of semi-elasticities from significant
estimates in Figure 2. It shows that the mean value of the semi-elasticity in the sample of
significant estimates is − 5.7, which is larger (in absolute terms) than in the total sample. Again,
the sample is skewed to the left so that the median is smaller: − 4.2. In the meta analysis below,
we will use both the entire meta sample and the sample of significant values to assess the
differences between studies.
Figure 2
Distribution of semi-elasticities in the meta sample of significant estimates
80
Series: SEMI_ELASTICITY
Sample 1 500 IF ((DUBIOUS=0) AND ((Y2>(@MEAN
(Y2,"1 500 if dubious = 0")-2*@STDEV(Y2,"1
500 if dubious = 0")) AND Y2<(@MEAN(Y2,"1
500 if dubious = 0")+2*@STDEV(Y2,"1 500 if
dubious = 0"))))) AND (Y5)
Observations 230
70
60
50
40
30
20
10
0
-30
-20
-10
0
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
5
-5.652328
-4.252294
6.757491
-36.70000
6.312537
-1.954239
9.130685
506.5894
0.000000
We generally need a covariance matrix of the error terms to compute the standard error that belongs to a semi-elasticity.
11
3.2
Specification
We estimate an equation of the form y = βX + ε, where y represents the vector of semielasticities, and X is a matrix of dummy variables reflecting various study characteristics. The
information about study characteristics is contained in the meta database, usually in form of
dummies that indicate whether a certain characteristic applies to an estimate or not. The
parameter β thus measures the systematic impact of each study characteristic on the reported
semi-elasticities in the literature. In the regressions, we control via dummy variables for the
following underlying characteristics of an estimate.6
•
Data characteristics, including type of capital and time;
•
Type of tax used in the regression;
•
Background variables, such as the regime for double-tax relief in the parent country
(exemption or credit) and source of finance (retained earnings or transfers).
6
De Mooij and Ederveen (2003) also look at publication details, theoretical specification and econometric methodology.
12
Table 1 Summary information meta database: study characteristics, observations and significance
Number of semielasticities
Number of significant semielasticities
Foreign direct investment (FDI)
Property plant & equipment (PPE)
207
77
114
48
Number of locations
Number of new plants/plant expansions
71
47
35
19
Number of mergers & acquisitions
Other
24
11
7
7
All
437
230
Type of tax data
Effective marginal tax rate
Approximation average tax
74
35
29
144
36
94
60
14
58
29
67
27
437
230
Retained Earnings
Transfers
Mixed
38
84
315
17
47
166
Exempt
Credit
Mixed
177
118
146
73
67
93
Capital data
Financial data
Count data
Country statutory rate
Statutory rate in US states
Average effective tax rate
Micro tax rate
Macro average tax rate
All
Source of finance
System for double tax relief
Time
Post 1980 data
Post 1990 data
Table 1 summarises our classification of the types of capital data and types of tax measures
contained in the meta sample. It shows the number of semi-elasticities based on certain category
as well as the number of significant semi-elasticities.
With respect capital data, we distinguish between studies using financial data on the amount
of capital invested in each location and studies using count data on the number of locations.
While the former best relates to investment, the latter better measures discrete location
decisions. If the two types of data yield the same effect sizes, the effects of taxation on
investment might be entirely driven by discrete choice. If capital data yield larger elasticities,
however, the amount of capital is responsive to taxes as well. Table 1 shows that the sample
13
contains 143 semi-elasticities based on number of locations and 291 based on financial
investment data.
Among the studies using financial data, we distinguish two categories: data on foreign direct
investment (FDI) and US data on property plant and equipment (PPE). The latter is thought to
be more closely related to real capital investment. The studies using count data are divided into
three categories: those making no distinction as to what type of locations are counted and those
based on either new plants/plant expansions or mergers and acquisitions. For mergers and
acquisitions, the impact of taxes can be very different than for greenfield investment (see e.g.
Scholes and Wolfson, 1990). In particular, a higher tax in the host country can make foreign
ownership more attractive because, in contrast to local owners, foreign owners can be shielded
from the higher tax rate by the credit system in the home country (as e.g. applied in the US and
the UK).
With respect to tax data, we distinguish between estimates based on the EMTR and those
determined by an indicator for the average tax burden.7 The EMTR measures incentive effects
on marginal investment decisions while the others indicators are more closely related to
location choices. Hence, if the EMTR yields systematically higher (lower) elasticities than the
other measures of tax, it would suggest that marginal investment choices are more (less)
important than discrete location decisions. In the meta sample, we have 74 estimates using the
EMTR. Other estimates are based on average tax rate measures.
Among the studies using the average tax, 36 estimates use ex-ante EATR computations
along the lines of Devereux and Griffith (1998). These studies show the highest rate of
significant semi-elasticities (over 80%). In the US context, 144 estimates use State statutory tax
rates, which approximate average effective tax rates in the US rather good due to the common
federal base. Other studies either use either country statutory tax rates (29) or average tax rates
computed from firm accounts (94) or macro data (60).
Apart from differences in capital data and tax measures, we include three other study
differences in our meta regressions. The first is the source of finance (retained earnings versus
transfer of funds), a distinction that was made in earlier studies. The second refers to the system
of double tax relief used in the home country of the investor. Under the exemption system,
foreign income is exempt from taxation in the home country of the parent so that the tax in the
host country matters for the return on the investment. Under the credit system, in contrast, tax
liabilities in the host country of the subsidiary are credited against taxes in the home country of
the parent. In that case, the ultimate tax burden on investment is determined by the tax rate of
the home country of the parent. The tax in the host country is then expected to matter less. In
the meta sample, 177 semi-elasticities apply to countries where the investor is located in an
7
This includes studies that estimate the impact of the cost of capital, from which we derive the semi-elasticity of the EMTR.
14
exemption county, 118 apply to credit countries and for the other estimates the country of the
investor is unknown. The final variable that may affect reported semi-elasticities is time. To the
extend that capital has become more mobile over time, one may expect that taxes exert a larger
impact on international investment. However, time may also reflect the improvement in the
quality of data or econometric techniques to identify the impact of taxes. Although we cannot
distinguish these explanations, we can explore the impact of time on the reported effect sizes.
3.3
Meta regressions
Table 2 shows the outcome of four meta regressions as indicated in the previous subsection.
The coefficients in Table 2 show the effect of particular study characteristics, relative to a
benchmark, referring to a study using FDI data, the EMTR, an unspecified source of finance or
system for double-tax relief and no post 1980 data. For presentational convenience, we have put
a minus sign for all semi-elasticities before doing the regression analysis. Thus, we transformed
most semi-elasticities into positive figures. A positive coefficient for a dummy variable
therefore means a higher elasticity in absolute terms, i.e. the semi-elasticity becomes more
negative. The first two regressions in Table 2 use the entire meta sample, but differ in the study
characteristics included in the regression. The last two regressions use the smaller sample of
significant semi-elasticities, again for a limited and extended set of regressors.
The first two columns in Table 2 show a significant negative coefficient for Number of
locations. Hence, studies relying on count data produce significantly smaller semi-elasticities
than studies relying on FDI. It suggests that not only the decision to locate, but also the decision
on the amount of capital invested is responsive to taxation. The coefficient for Number of
locations is not or only weakly significant if the smaller sample of significant semi-elasticities is
used.
For studies using financial data, PPE tends to produce larger semi-elasticities than FDI data.
This result is significant in the regressions for the entire sample, but not under the smaller
sample with only significant semi-elasticities. One explanation for this result is that PPE better
reflects greenfield investments, which depends on location advantages. In contrast, FDI
contains apart from greenfield investment also investment through mergers and acquisitions on
which higher taxes exert an opposite effect due to the ownership advantage. Another
explanation might be that PPE data only exist for US investment and that capital flows into and
out of the US are relatively sensitive to taxes.
15
Table 2: Meta regression results
Full meta sample
Constant: FDI & EMTR
Sample of significant
(1)
(2)
(3)
(4)
2.82 (0.50)**
2.47 (0.92)**
4.81 (0.61)**
4.28 (0.88)**
2.57 (0.69)**
2.71 (0.82)**
1.47 (0.96)
1.73 (1.18)
− 2.73 (0.76)**
− 3.17 (0.92)**
− 1.50 (1.05)
− 2.04 (1.09)*
Capital data (relative to FDI)
Property Plant Equipment
Count data
Number of locations
Locations – Plants
Locations – M&A
− 1.82 (1.00)*
− 1.86 (1.08)*
− 3.52 (1.64)**
− 2.12 (1.63)
− 11.33 (1.03)**
− 11.4 (1.12)**
− 14.80 (1.78)**
− 13.75 (1.99)**
Tax measures (relative to EMTR)
STR in US states
4.63 (1.04)**
4.27 (1.02)**
6.23 (1.77)**
4.24 (1.62)**
STR in countries
− 1.16 (0.56)**
− 1.72 (0.60)**
− 2.71 (0.78)**
− 3.95 (1.16)**
AETR
2.50 (0.68)**
1.98 (0.78)**
0.47 (0.81)
0.52 (1.00)
Micro ATR
− 0.40 (0.73)
− 1.51 (0.83)*
− 1.25 (0.98)
− 3.45 (1.24)**
Macro ATR
− 0.03 (0.74)
0.48 (0.93)
− 0.53 (1.08)
0.45 (1.41)
Other characteristics of the data (relative to mixed data)
Retained Earnings
-0.22 (1.12)
-0.84 (1.49)
Transfers
-0.96 (0.70)
-0.99 (0.79)
Exemption country
1.40 (0.59)**
4.44 (0.77)**
Credit country
0.14 (0.71)
1.40 (0.90)
Post 1980 data
-0.18 (0.91)
-0.67 (1.11)
Post 1990 data
1.72 (0.53)**
1.31 (0.85)
Regression statistics
Observations
437
437
230
230
Adjusted R-squared
0.45
0.47
0.51
0.57
Durbin-Watson
1.70
1.75
1.24
1.56
a
Semi-elasticities are pre-multiplied by − 1 before regressions were run. Coefficients reflect the difference in semi-elasticity
relative to the benchmark set of study characteristics, which is FDI data and the EMTR. Standard errors between brackets, *
and ** denote statistical significance at 10% and 5% level, respectively. We include a special dummy for investment into
Belgium and for capital data used in Swenson (1994) which is different from the other categories of capital data.
Among the studies using count data, those referring to plants (new plants and plant expansions)
produce semi-elasticities which are larger than those referring to all number of locations,
although this difference disappears in the sample of only significant semi-elasticities. It
provides further support that location choices are relatively responsive to tax. Count data on
mergers and acquisitions yield semi-elasticities with an opposite sign from other semielasticities. It confirms that higher taxes in host countries make it more attractive for capital to
be foreign owned due to the tax shelter provided by credit systems. This effect is significant in
all regressions.
16
The benchmark study uses the EMTR as the indicator for the corporate tax burden. Table 2
reveals whether indicators for the average tax burden produce different outcomes. For the
AETR, the meta regressions with the entire meta sample suggest a positive effect. Hence,
lumpy investment or discrete location choices tend to be more responsive to tax than marginal
investment choices. This result is not confirmed, however, when we use the sample of
significant semi-elasticities. Hence, studies based on the EMTR that do report a significant
semi-elasticity yield a value of equal magnitude as studies using the AETR. Note that a
relatively large number of studies using the EMTR (or cost of capital) produce insignificant
semi-elasticities: 39 out of 74 based on the EMTR and 7 out of 36 based on the AETR are
insignificant.
Studies using country statutory tax rates produce smaller semi-elasticities than studies using
the EMTR. The difference is significant in all four regressions in Table 4. Hence, statutory tax
rates are probably a poor indicator to measure the impact of corporate tax systems on
investment. This does not apply to state statutory tax rates in the US, however. Indeed, the
semi-elasticity from studies using this tax indicator is usually larger than from studies using the
EMTR. It may indicate that differences in state statutory tax rates in the US form a relatively
good approximation for the differences in average effective tax rate. Yet, the result may also be
somewhat misleading. In particular, state statutory tax rates are relatively small as compared to
other measures of tax. The average rate is only 6%. For studies not using a double log
specification, we derive the semi-elasticity by dividing the estimated tax elasticity by the tax
rate. With such a low rate, this considerably raises the value of the semi-elasticity. If we would
evaluate the tax elasticity at a higher rate that would include the federal corporate income tax in
the US, the estimated semi-elasticities obtained from these studies would be considerably
smaller. We should therefore interpret this result with caution.
Table 2 shows that studies based on average tax rates computed from data do not yield
different semi-elasticities from studies using the EMTR. Only in the sample of significant semielasticities do we see that the coefficient for the micro ATR is significant and negative. In
estimating elasticities, however, average tax rates suffer from possible endogeneity problems
while they do not measure the tax burden on future but on past investments. Hence, they are
less appropriate indicators to measure investment incentives.
The coefficient for tax exemption countries is significant and positive in both samples in
Table 2. The coefficient for credit countries is insignificant. It suggests that investment from
exemption countries is more responsive to tax than investment from credit countries, which is
consistent with economic theory. The system of double tax relief therefore does matter for the
investment response to taxation: tax deferral and excess foreign credit do not entirely blur the
distinction.
17
The coefficient for post 1980 data in Table 2 is insignificant. For post-1990 data, we find a
positive coefficient if we use the entire meta sample. It provides weak evidence for a growing
responsiveness of capital to taxation over time.
3.4
Predicted semi-elasticities
From the meta regressions in Table 2, we can infer fitted values for the semi-elasticity of
foreign investment under a particular set of study characteristics. Table 3 presents such
predicted values for two types of capital data and three alternative tax measures. Thereby, we
take the regression results from the second column of Table 2. In computing the predicted
values, we set dummies on credit/exemption and retained earnings/transfer of funds equal to
zero. The post-80 and post-90 dummies are set equal to one. In Table 3, we present semielasticities with their original sign, i.e. no longer premultiplied by − 1.
Table 3
Predicted semi-elasticities using the meta regressions for alternative models
Financial data
Count data on number of locations
Effective marginal tax rate
− 4.0
− 0.8
Effective average tax rate
− 6.0
− 2.8
Country statutory tax rate
− 2.3
0.8
Table 3 shows that the typical semi-elasticity of FDI with respect to the EMTR is − 4. This
response is considerably larger than the estimated semi-elasticity of total investment with
respect to the EMTR (see section 2, where a consensus estimate is reported between − 0.55 and
− 1.1). It suggests that the expansion of the capital stock induced by a lower EMTR is largely
due to an inflow of foreign capital. Indeed, if we use a share of foreign capital of 20% found by
Huizinga and Nicodeme (2003) for a typical European country, the semi-elasticity in Table 3
suggests that the aggregate capital stock via FDI rises by 0.8% (= 0.2 × 4.0) if the EMTR is
reduced by 1%-point. This is precisely the average of − 0.55 and − 1.1. It is consistent with the
assumption of perfect capital mobility. Indeed, if there is no relationship between domestic
savings and domestic investment, all extra capital demand induced by a lower corporate tax
should come from an inflow of foreign capital. In that sense, the outcome in Table 3 can be
reconciled with the semi-elasticity of investment reported in section 2.
The predicted semi-elasticity of the AETR is 50% larger than for the EMTR. It suggests that
the extensive margin of investment is more important than the intensive margin. The relatively
large share of significant semi-elasticities based on the EATR compared to those based on the
EMTR provides further support for this difference. Yet, studies using count data yield smaller
elasticities than studies relying on financial data. Not only location decisions, but also the
amount of capital is thus responsive to tax.
18
It is now tempting to compare our predictions based on meta regressions with very recent
findings in the literature and which are not included in the meta data base. It shows another way
how our meta analysis may be used in assessing new evidence in relation to earlier findings. We
therefore will compare three of such studies.
First, Devereux and Lockwood (2006) estimate the long-run semi-elasticity of investment
using financial data for three alternative indicators of tax. For the EATR the results suggest a
statistically significant semi-elasticity of − 1.5. For the EMTR (derived from the cost of capital
measure), the corresponding value is − 0.5. The coefficient is insignificant though. For the
statutory tax rate, the semi-elasticity is − 0.9, but this coefficient turns insignificant when also
the EATR is included in the regression. The values of these semi-elasticities are relatively low
compared to previous findings. The relatively large value for estimates based on the EATR are
consistent with previous findings.
Bellak and Leibrecht (2008) estimate the semi-elasticity using FDI flows into Central and
Eastern European countries. They consider two alternative tax variables. For the EATR, they
report a significant semi-elasticity of − 4.3. For the statutory tax rate, the result becomes
insignificant and the effect size of the semi-elasticity drops to − 1.9. This comes close to our
predictions from the meta regressions. Bellak et al. (2008) estimate similar equations but
concentrate on the impact of labour costs on FDI. The estimated semi-elasticity of the EATR in
their study lies between − 4.3 and − 4.7.
Bénassy-Quéré et al. (2007) use a panel of FDI and estimate the impact of either the
statutory corporate tax rate or the EATR using a double log specification. Their estimates
suggest a significant semi-elasticity of the statutory corporate tax between − 4 and − 6, which is
relatively large compared to previous findings. The semi-elasticity of the EATR is a bit higher
at a round − 6, which is consistent with previous findings.
The semi-elasticities in Table 3 can be interpreted as consensus estimates for alternative
decision margins. Indeed, we use these values to determine consensus values for the semielasticity of the corporate tax base via the channel of foreign investment. To compute them, we
pre-multiply the semi-elasticities in the first column of Table 3 by the 20% foreign share of
capital. For the EATR, this yields a reasonable prediction of the semi-elasticity of the corporate
tax base since discrete investments carry both a return to capital and an economic rent. The
semi-elasticity of the tax base with respect to the EATR would thus be − 1.2 at the extensive
margin. Marginal investments do not carry an economic rent so that the expansion of the tax
base will be smaller than the expansion of the capital stock. If we take the same assumption as
in section 2 that 50% of the tax base is determined by (quasi) rents, the semi-elasticity of the
corporate tax base with respect to the EMTR would be − 0.4 (= 0.5 × 0.2 × − 4.0).
19
4
CONCLUSIONS
How big is the impact of corporate taxes on various decision margins of firms? By reviewing
and using existing empirical evidence, this paper computes for five different decision margins
the semi-elasticity of the total corporate tax base. Table 4 summarizes our assessment. It
suggests that empirical studies on profit shifting suggest responses that are relatively large
compared to other decision margins. It may explain why countries engage in fierce competition
with their statutory tax rates in order to attract multinational profits. Also studies on discrete
location choice suggest a relatively large tax response. It provides further ground for
governments to engage in tax competition or, alternatively, an argument for tax harmonisation.
A few studies suggest that distortions on legal form might be substantial too. Yet, the revenue
implications of this distortion for the government are smaller as activities in the non-corporate
form are still being taxed under the income tax. The reported semi-elasticities for marginal
investment and financial leverage are likely to be smaller, although not negligible. In fact, the
welfare effects induced by these distortions may be actually large since these behavioural
responses involve real distortions in resource allocations, not simply tax arbitrage.
Table 4
Semi-elasticity of the corporate tax base for five decision margins
Behavioural margin
Relevant tax
Effect size
Remark
1. Organisational form
Corporate vs. personal tax
− 0.4 to − 1.0
Revenue effect smaller
2. Financial policy
Debt/equity discrimination
− 0.25 to − 0.4
Ignores personal tax
Statutory tax rate
− 2.0
Revenue lost to other countries
EMTR
− 0.3 to − 0.6
Based on 50% rent share and an
ATR
n.a.
Due to capital-market imperfections
a. Marginal investment
EMTR
− 0.4
Based on 50% rent share and a
b. Discrete location
EATR
− 1.2
Based on foreign capital share of 20%
3. Profit shifting
4. Investment
a. Marginal investment
EMTR of 10%
b. Inframarginal investment
5. Foreign investment
foreign capital share of 20%
20
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Appendix A The meta data base
De Mooij and Ederveen (2003) review the empirical literature on the impact of taxation on
foreign investment. For each study they found, the marginal coefficient was transformed into a
uniformly defined semi-elasticity (or tax rate elasticity). The semi-elasticity measures the
percentage change in FDI in response to a 1%-point change in the tax rate, e.g. a decline from
30% to 29%. It is defined as ∂ln(FDI)/∂t. With taxes, it is more common to look at semielasticities than normal elasticities as firms are likely to respond to changes in after-tax rates of
return, irrespective of the exact level of the tax. To be able to transform marginal coefficients
from studies into semi-elasticities, information is often required about the mean value of the
FDI variable or the tax rate. Only if this information was available from the paper or from the
authors, an estimate was included in the meta sample.
Computing semi-elasticities makes the results from the various studies comparable in terms
of the effect size. Apart from reporting semi-elasticities, information was collected whether
statistics were significant at the 5% confidence level. To that end, information on standard
errors of the estimated semi-elasticities was collected.
De Mooij and Ederveen (2003) arrive at a sample of 371 elasticities. Excluding some
extreme values from the sample, they arrive at a meta sample of 351 elasticities. Using
regression analysis, they explain the variation in semi-elasticities by the variation in the
underlying study characteristics. For a discussion of the studies contained in the meta data base,
we refer to their study. For a review of the pros and cons of meta analysis, see Florax et al.
(2002). This paper adds 78 new elasticities from six recent studies. We briefly discuss these
studies and their main findings. They are summarized in Table A.1 below.
Buettner (2002) adopts FDI flows financed by transfer of funds in the EU between 1991 and
1998. For alternative tax measures and a log-linear specification that includes public
expenditures, he obtains mixed results for the tax variables. Desai et al. (2004) estimate a model
using outward FDI stocks of US multinationals in the manufacturing sector in 1984 and 1992.
They include both indirect tax variables and direct tax measures in their regression. For both
taxes, they report significant elasticities. Benassy-Quere et al. (2003) use similar data as
Buettner for FDI financed by transfer of funds in the OECD, but using a longer time frame
between 1984 and 2000. For alternative specifications regarding control variables or sub
samples, they report mainly significant elasticities. Stoewhase (2005) uses bilateral FDI data
that are divided between three sectors: agriculture, manufacturing and services. He explains the
share of FDI and exports by alternative tax parameters. Only for the manufacturing and service
sectors does he find significant results. Buettner and Ruf (2004) follow Devereux and Griffith
(1998) to explain the choice of location by German multinationals in other EU countries in the
non-financial sector. Thereby, they use micro data on location choices obtained from the
Bundesbank between 1996 and 2001. Buettner and Ruf use alternative measures of the tax rate,
24
including statutory rates, average rates and average effective taxes. Moreover, they estimate a
linear probability model as well as a logit model and explore alternative sub samples. They find
mixed results regarding significance, while elasticities are small compared to other studies.
Stoewhase (2003) uses count data from German multinationals that choose to locate in a
number of EU countries between 1991 and 1998. Thereby, he concentrates on decisions
regarding profit shifting versus investment by distinguishing between different types of firms.
The results suggest that production firms do indeed respond to effective tax rates, but not to
statutory rates. For companies that are important for profit shifting, statutory tax rates are more
important.
Table A.1
Summary results from six new studies to the meta data base
Semi-elasticity
Mean
Median
No. obs
No. sign
Std. dev.
Stoewhase, 2003
-7.36
-6.82
1.12
5
5
Buttner & Ruf, 2004
-0.42
-0.39
0.35
15
6
Buttner, 2002
-1.52
-1.59
0.58
23
12
Benassy-Quere et al., 2003
-5.37
-4.22
3.21
19
19
Desai, et al., 2004
-0.64
-0.64
0.02
2
2
Stoewhase, 2005
-5.26
-4.30
2.71
14
11
In constructing the new meta sample, we again eliminate some extreme values. In particular, we
remove observations that are outside the range of plus and minus two times the standard
deviation from the mean. In this way, especially the extreme negative values that cause skewed
distributions are eliminated from the sample. We end up with a meta sample of 437
observations used in the analysis of the paper.
25