Effective tax rates and the gç£industrial policy gç¥ hypothesis evidence from malaysia

Journal of International Accounting,
Auditing & Taxation 12 (2003) 45–62
Effective tax rates and the “industrial policy” hypothesis:
evidence from Malaysia
Chek Derashida, Hao Zhangb,∗
a
School of Accountancy, Universiti Utara Malaysia, Sintok, Kedah, Malaysia
b
Accounting and Finance Division, Leeds University Business School, Leeds University, Leeds LS2 9JT, UK
Abstract
Studies on effective tax rates (ETR) and firm size in the non-U.S. context are next to non-existent, with
the Kim and Limpaphayom study (1998) being the sole exception. Moreover, no detailed analysis has
been performed to study the link between industrial sectors and ETR. Based on a hand-gathered sample
of Malaysian firms trading in the Kuala Lumpur Stock Exchange in 1990–1999, this paper examines
the association between ETR and a set of possible factors using a regression analysis. There is evidence
to suggest that manufacturing firms and hotels pay significant lower effective tax in Malaysia between
1990–1999. In addition, it appears that large Malaysian firms do not suffer a “political cost” as indicated
by a negative and significant relation between firm size and ETR. Finally, more efficient Malaysian firms
pay lower effective tax. The results are consistent with the “industrial policy” hypothesis developed in
this paper based on an examination of the Malaysian context. These results from a large developing
country (e.g., Malaysia) can be used to compare with existing results from a large developed country
(e.g., U.S.).
© 2003 Elsevier Science Inc. All rights reserved.
Keywords: Effective tax rates; Industrial policy; Political costs; Sector effects; Firm Size
1. Introduction
The issue of effective tax rates (ETR) paid by firms has generated an ongoing dialogue in
the U.S. in recent years (e.g., Kern and Morris, 1992; Kim and Limpaphayom, 1998; Porcano,
1986; Salamon and Siegfried, 1977; Wilkie and Limberg, 1990; Zimmerman, 1983). Implicit
in these studies is the shared concern that U.S. firms, because of their size, may pay more or
∗
Corresponding author. Tel.: +44-113-233-4471; fax: +44-113-233-4459.
E-mail addresses: chek@uum.edu.my (C. Derashid), hz@lubs.leeds.ac.uk (H. Zhang).
1061-9518/03/$ – see front matter © 2003 Elsevier Science Inc. All rights reserved.
doi:10.1016/S1061-9518(03)00003-X

46 C. Derashid, H. Zhang / Journal of International Accounting, Auditing & Taxation 12 (2003) 45–62
less than their fair share of tax. In contrast, the relation between industrial sector effects and
ETR, while investigated in a number of studies (e.g., Gupta and Newberry, 1997; Kern and
Morris, 1992; McIntyre and Nguyen, 2000; Omer, Molloy and Ziebart, 1993; Zimmerman,
1983) is often treated as a subsidiary issue and an adjustment factor. Given that these studies
are from the U.S. context, the relevant questions for international accounting research are
related to whether U.S.-based ETR findings can be generalized to institutional environments
significantly different from those of the U.S., such as East and Southeast Asia. What factors
explain ETR for non-U.S. firms? Can the results from the U.S. firms be extended to non-U.S.
and, especially, non-western firms?
Studies of sector effects on ETR in the non-western context are non-existent. So are the stud-
ies of size effects on ETR, with the sole exception being the study by Kim and Limpaphayom
(1998). Do ETR differ across industrial sectors and/or according to firm size for non-U.S.
firms? If they differ, what may be the underlying reasons? The Kim and Limpaphayom study
(1998), based on firms from Hong Kong, Korea, Malaysia, Taiwan, and Thailand in the period
from 1977 to 1992, provides initial evidence of a negative relation between ETR and firm size
for firms in East and Southeast Asia. While the Kim and Limpaphayom study (1998) does not
address the issue of sector effects because of data unavailability, it nonetheless identifies it as
“very important” (1998, p. 66) for non-western firms primarily because of the long standing
“industry policy” in these countries to promote certain sectors.
Given the explicit industry policy, it is not surprising that various benefits, including tax
benefits, may be given to “strategic” firms and sectors in order to promote both economic
and social goals including: protecting domestic sectors from foreign competition, increasing
exports, enhancing efficiency or competitiveness, and fostering high-tech development. One
result of the policy is that selected firms and sectors are in a naturally good position to influence
and lobby the government for favorable treatments such as tax treatments. While the merits
of the policy to pick “winners” is subject to debate, such a policy provides the rationale and
the context in which to examine the possible link between ETR and industrial policy, i.e., the
“industrial policy” hypothesis.
This paper contributes to the currently sparse literature on ETR in the non-western context
by investigating the link between ETR and sectors and between ETR and size in Malaysia.
The contribution is relevant to international accounting research in at least three ways. First,
the study of ETR in Malaysia is in fact a part of a collective comparative study because our
Malaysian/non-western results are studied in comparison to the existing U.S./western results.
Second, the comparative component of our investigation is non-trivial because it is based on
a genuine policy difference between developing countries such as Malaysia and developed
countries like the U.S. Specifically, the policy difference in our study takes the form of a
long standing industrial policy in Malaysia to promote large firms as well as firms in the
manufacturing sector (e.g., Alavi, 1996) and, since 1990, in the tourism sector (e.g., Malaysia
Institute of Accountant and Malaysian Institute of Taxation, 1990; Price Waterhouse, 1996).
Third, one implication of the industry policy to foreign investors is the effective tax incentives
provided by the government for investing in the manufacturing sector and, to a lesser extent,
the tourism sector.
Our study should provide insights regarding the possible reasons that may explain ETRs in
Malaysia and other similar developing countries and, more importantly, why these reasons may

C. Derashid, H. Zhang / Journal of International Accounting, Auditing & Taxation 12 (2003) 45–62 47
be different from those for firms in the U.S. A better understanding of the taxation hierarchy
and what it reveals about national economic priorities in Malaysia may also be beneficial to
western firms and investors interested in the region. Finally, it has been found that accounting
policy choice as seen in the form of earnings management can alter or influence ETR (Northcut
and Vine, 1998). Thus, what we know about the implicit link between ETR and the industrial
policy in Malaysia should inform how the choice of accounting policy may be made in this
part of the world.
The rest of the paper is organized as follows. The next two sections provide a review on prior
research on ETR and contrast it with the Malaysian context in the 1990s. The following section
outlines the research design and data. Empirical results are then reported and explained. Finally,
the implications of our findings are explored and conclusions are offered in the last section.
2. Prior research
Prior research on ETR has examined: (1) ETR differences across industrial sectors, and
(2) the neutrality of the corporate tax system with respect to firm size. Typically, sector and
size effects on ETR are adjusted for possible effects from other firm characteristics, including
leverage (the ratio of total debt and total asset), capital intensity (the ratio of net property, plant,
and equipment to total asset), and firm performance measures (usually seen in the form of return
on assets). While the studies of sector effects on ETR (e.g., Harberger, 1959; Rosenberg, 1969;
Siegfried, 1974) actually go further back, attention in recent years has shifted to firm size
(e.g., Kern and Morris, 1992; Kim and Limpaphayom, 1998; McIntyre and Nguyen, 2000;
Porcano, 1986; Salamon and Siegfried, 1977; Wilkie and Limberg, 1990; Zimmerman, 1983).
This development can be explained partially by the concern that the effect tax burden may not
be proportionally equal across firms of different size in the U.S.
2.1. Firm size
There are two different points of view related to the issue of firm size. One point of view is
that large firms are subject to greater public scrutiny and as a result, incur a “political cost” in
the form of a higher ETR (Zimmerman, 1983). Another point of view is that large firms in fact
pay less tax because they can devote more resources to tax planning and political lobbying.
For example, a series of reports published in 1984, 1985, and 1986 by Citizens For Tax Justice
(CTJ) have questioned the tax equity among U.S. firms and argued that the large firms were
not paying their fair share of tax (CTJ, 1984, 1985, 1986).
Studies of U.S. firms on the relation between ETR and firm size (e.g., Porcano, 1986;
Zimmerman, 1983) have produced conflicting results. While Zimmerman (1983) observes a
positive association between ETR and firm size using a cash flows-based ETR proxy, Porcano
(1986) observes a negative association using an income-based ETR proxy. Subsequent studies
have tried to reconcile the conflicting results by using modified proxies, time periods, data
basis, and methodologies (e.g., Gupta and Newberry, 1997; Kern and Morris, 1992; Wilkie and
Limberg, 1990). While the evidence so far appears to be in favor of a positive relation between
ETR and firm size in the U.S., the issue is not yet resolved.

Holland (1998) and Kim and Limpaphayom (1998) are the only non-U.S. ETR studies
so far. While Holland (1998) found mixed results for British firms, Kim and Limpaphayom
(1998) found initial evidence that large firms pay lower effective taxes in countries of East and
Southeast Asia. With the exception of Hong Kong, the ETR paid by large firms in Taiwan,
Korea, Malaysia, and Thailand are lower than small firms. Kim and Limpaphayom do not
go further to explore the underlying reasons but suggest that the industrial policy in these
countries to promote and protect selected firms, particular large ones, and sectors may be a
potential explanation.
2.2. Sector effects
Different sectors may indeed receive different tax treatments and these differences would
lead to different effective tax burdens. For example, Harberger (1959) and Rosenberg (1969)
find that U.S. firms in the farming, textiles, petroleum, coal products, and real estate sectors
paid significantly lower income taxes than firms in other sectors. The reason is related to
capital gains and percentage depletion allowances granted to firms engaged in developing,
extracting, or mining natural resources. Omer et al. (1993) detect a significant difference
between firms in the pharmaceutical sector and firms in the petroleum sector. More recently,
McIntyre and Nguyen (2000) report that in the U.S., ETR varies widely by sector, with oil
companies enjoying the lowest effective tax rate. In the non-western context, the sector effects
on ETR are especially relevant because of the explicit industrial policy adopted by many
governments. Kim and Limpaphayom (1998) readily acknowledge the importance of sector
effects in their article. While data limitations prevent the inclusion of sector effects in their
study, Kim and Limpaphayom suggest that a detailed analysis on the sector level should be done
in future studies in order to better understand ETR behavior in a particular country, especially
given the industrial policy. In this paper, we are able to obtain the necessary data to examine
sector effects on ETR in one country, Malaysia, and how these effects may be explained by
the industry policy of Malaysia.
3. The Malaysian context
3.1. Industrial policy
When Malaysia gained independence from Britain in 1957, it was primarily a producer
of two commodities: tin and rubber. The role of the small manufacturing sector was mainly
to provide services to the tin and rubber sectors. In the subsequent years, it has been the
Malaysian government’s long standing policy to diversify the economy and industrialize the
country.1
While the overall industrialization strategy has shifted from Import Substitution
Industrialization (ISI) in the early years to Export Orientated Industrialization (EOI) in the
1980s–1990s, the development of the manufacturing sector continues to figure prominently in
the government’s industrial policy.
This industrial policy is supported by a number of important acts of Parliament. The Pro-
motion Investment Act (PIA) of 1986 (PIA, 1986) provides various investment incentives to

promote industrialization in the manufacturing sector including provisions such as a reduc-
tion in taxable income and a grant of 100% ownership to foreign manufacturing firms pro-
vided that they are sufficiently export orientated. In the first and second Industrial Master Plan
(IMP) 1986–2005 (Malaysian Government, 1985, 1996), a number of sub-sectors were iden-
tified as “strategic” and given favorable treatments through PIA as well as the 1967 Income
Tax Act (ITA, 1967). These sub-sectors are comprised of electrical and electronic, chemi-
cal, textile and apparel, transport, machinery, and equipment, agro-based and food products.
Among the benefits available from PIA include tax holidays, income exemption, investment
tax allowance in the form of accelerated capital allowance relative to depreciation, special
deductions from income (e.g., double deduction for expenses) and other benefits (e.g., export
allowances).
In the tourism sector, a number of tax incentives are provided under PIA and/or ITA. Among
incentives provided under PIA is the industrial building allowances whereby a hotel operator
couldclaiminitialandannualallowancesforbuildingsusedashotelorholidayaccommodation.
Capital expenditure related to building new and/or modernizing existing buildings would also
qualify for industrial building allowances. Meanwhile, tax incentives available under ITA
include double deduction for overseas expenses incurred in promoting Malaysia as tourist
destination (Malaysian Institute of Accountants and Malaysian Institute of Taxation, 1990)
and income tax exemption on income earned in bringing foreign participants to conferences
held in Malaysia (Price Waterhouse, 1996). Such incentives provide tax advantages for firms
in the tourism business especially in the hotel sector.
3.2. The corporate tax system
The ITA of 1967 governs most aspects of Malaysian corporate taxation. Persons and compa-
nies are liable to tax for income derived in Malaysia, except for banking, insurance, air and sea
transport companies, which are taxed based on worldwide income. Both long- and short-terms
interest payments to finance business activities are tax-deductible, and tax-deduction is allowed
for capital allowances (deprecation). Malaysian firms are taxed based on book income after a
number of adjustments (see, e.g., CCH, 1999 for an extensive discussion). Detail computation
of a firm’s chargeable income is referred to in Appendix A. These adjustments contain tax
benefits (e.g., investment tax allowances, income exemption, accelerated depreciation, special
deduction) available only to selected firms. With regards to business losses, the 1967 ITA al-
lows current year losses to be deducted and if unabsorbed, the deductible losses can be carried
forward without specific time limit. In a fiscal year, operating losses are included in the accu-
mulated losses carried over, which can be set against future tax liabilities. While the methods
of depreciation for Malaysian firms are based on Generally Adopted Accounting Principles
(GAAP), the Inland Revenue Board of Malaysia sets the rates of depreciation for tax purposes
(also known as capital allowances). There is no minimum income tax. All Malaysian firms are
taxed at the same statutory rate. In the 1980s, the corporate tax rate in Malaysian stood at 40%.
A change in government policy reduced it to 35% in 1990. The tax rate was further reduced in
stages and by the 1998 assessment year, the rate stood at 28%.
Given the industrial and tax policies discussed above, we examine the “industrial policy”
hypothesis in the form of two research questions:

Question 1: Given the industrial policy in Malaysia, do the manufacturing sector and the tourism
sector enjoy a lower ETR than other sectors?
Question 2: Given the industrial policy in Malaysia, do large firms enjoy a lower ETR than
small firms?
4. Research design
In order to address both Question 1 for sector effects and Question 2 for size effects (Question
2) on ETR in Malaysia, a multiple variable regression analysis is used. In the analysis, ETR
is used as the dependent variable and sector proxy and size proxy as explanatory variables.
Additional explanatory variables are also included to control for time and other possible effects.
4.1. Data
The data used in this paper are hand gathered from 1990 to 1999 annual reports published
by firms listed in the Kuala Lumpur Stock Exchange (KLSE). This method of data gathering,
while laborious, has at least three benefits. First, KLSE classifies listed firms into sectors based
on core business. Thus, this data set enables the examination of link between sector effects and
ETR in a non-western context of Malaysia not possible previously.
Second,theKLSErequiresallitslistedfirmstoabidebytheKLSElistingrequirements.Para-
graph 9.26 of the listing requirements states that all listed firms should prepare their annual au-
dited accounts in accordance with approved Malaysian Accounting Standards Board (MASB)2
and the Ninth Schedule of the Malaysia Companies Act (1965). Thus, one can be reasonably
confident that the accounting figures from the sample are consistent in accounting standards.
Third, the KLSE requires all its listed firms to abide by its disclosure standards, which
include the requirement that data lodged with the KLSE must be certified by qualified auditors
and made publicly available (the listing requirements of KLSE, 2001). Thus, one can be fairly
confident that the financial information in this data set is consistent in quality.
The sample of firms is obtained from those listed in the Main and Second Boards of the
KLSE. The time period covered is from 1990 to 1999 and all firms listed during that period are
gathered into the original sample. On December 1999, there were 474 firms listed in the Main
Board and 283 firms in the Second Board. These firms are classified into 11 different sectors
according to their core businesses: consumer, manufacturing, mining, finance, and trust/close
end funds, construction, trading/services, infrastructure, hotels, plantations, and properties.
The original sample is reduced by excluding firms falling into the following categories:
(1) Firmswithnetoperatingloss(ornegativecashflow)andnetoperatinglosscarryforward.
Their exclusion is consistent with previous studies.3
These firms have been excluded
because they would introduce confounding effects and the results would be difficult to
interpret (see, e.g., Kim and Limpaphayom, 1998; Wilkie and Limberg, 1990).
(2) Firms whose effective tax rate exceeds one, as consistent with previous studies (e.g.,
Gupta and Newberry, 1997; Kim and Limpaphayom, 1998; Singh, Wilder and Chan,

Table 1
Number of firms and firm-years for Kuala Lumpur Stock Exchange listed firms in the 1990–1999 period
Year ETR1 ETR2 ETR3 ETR4 ETR5
1990 201 222 226 203 207
1991 202 217 222 204 207
1992 216 227 231 218 218
1993 208 227 229 217 219
1994 220 232 234 226 225
1995 222 233 235 225 227
1996 220 231 234 227 224
1997 201 212 216 203 204
1998 155 159 161 135 137
1999 110 112 113 105 103
Total (firm-years) 1955 2072 2101 1963 1971
ETR1 = (tax expenses − deferred tax epxenses)/(operating cash flows); ETR2 = (tax expenses −
deferred tax expenses)/(profit before interest and tax); ETR3 = (tax expenses)/(profit before interest and tax);
ETR4 = (tax expenses)/(pre-tax profit − (deferred tax expenses/statutory tax rate)); ETR5 = (tax expenses −
deferred tax expenses)/(pre-tax profit − (changes in deferred tax/statutory tax rate)).
1987; Stickney and McGee, 1982; Zimmerman, 1983). The effective tax rate of a firm
may be greater than one for a number of reasons. One reason is that, in the process of
consolidation within a group of firms, subsidiaries/associated firms with net operating
profit are combined with those subsidiaries/associated firms with net operating loss.
Zimmerman’s reason (1983) is that tax expense on an asset sold in prior year at a gain
is recognized in the current period with the effect of distorting the numerator of the
effective tax rate but not the denominator.
From this group, firms with negative ETR are also eliminated from the sample. Whenever
firms report either loss/negative income (negative denominator) or tax refunds (negative nu-
merator), ETR will be negative. For both circumstances, the analysis of ETR will be distorted.
Furthermore, when firms experienced book losses as well as tax refunds, ETR will be posi-
tive even though such firms pay no tax. While the majority of researchers exclude firms with
negative income (e.g., Omer et al., 1993; Porcano, 1986; Zimmerman, 1983), there are some
differences in dealing with tax refund of firms. Gupta and Newberry (1997), for example, re-
code companies with tax refund to zero to represent no tax. Wilkie (1988) excludes such firms
from his sample. This study follows Wilkie (1988) by excluding firms with negative tax rate.
A sensitivity analysis is performed by applying Gupta and Newberry (1997) coding scheme to
assess the effects. The results, however, are very similar and hence are not disclosed here.
Thus, each company selected in this sample is a firm listed in the KLSE in 1990 and continues
trading as a sole concern up to 1999. The exact final sample varies according to the ETR proxy
used. Table 1 presents numbers of firms from 1990 to 1999 or number of firm-years used as
the final sample.
We posit that ETR is determined by the following regression:
ETR = a + b1(sector effects) + b2(ln assets) + b3(leverage) + b4(capital intensity)
+b5(inventory intensity) + b6(ROA) + b7(MktBook)
+b8(Gequity) + b9(year effects) (1)

where, sector effects: sector dummy (consumer, manufacturing, mining, finance, construction,
trading/services, hotel, and plantation, with properties being the omitted sector); ln assets:
natural log of total assets; leverage: (total debt)/(total assets); capital intensity: (property and
plants & machinery)/(total assets); inventory intensity: (inventory/total assets); ROA: (pre-tax
profits)/(total assets); Gequity: percentage of government equity ownership; year effects: year
dummy (1990–1999).
Industry effects are the dummy variables denoting different sectors in the sample. The sector
dummies are: consumer, manufacturing, mining, finance, construction, trading/services, hotel
and plantation, respectively (with properties being the omitted sector). ln assets, the proxy for
firm size, is the natural log of a firm’s total asset value. The “industrial policy” hypothesis
suggests that positive and statistically significant coefficients for the manufacturing and hotel
dummies.
Previous studies suggest that the ETR may also be influenced by additional variables.
Gupta and Newberry (1997), Porcano (1986), and Stickney and McGee (1982), all suggest
that a firm’s leverage (or total debt/total assets) and capital intensity ((property and plants
& machinery)/total assets) may reduce its ETR. The reasons are tax-deductible interest pay-
ments and accelerated depreciation relative to actual asset lives. Regarding inventory intensity
(inventory/total assets), Gupta and Newberry (1997) argue that firms with higher invento-
ries are likely to have relatively higher ETR. Spooner (1986) also argues that ETR may
be higher for firms with greater investment opportunities (as measured by Market-to-Book
(MktBook) value) and profitability (as measured by, e.g., return on assets). Thus, additional
variables included are: leverage defined as total debt divided by total assets.4
Capital inten-
sity defined as (property and plants & machinery)/total assets, inventory intensity defined as
inventory/total assets. ROA, a profitability/performance measure, is defined as pre-tax prof-
its/total assets.5
MktBook is defined as (market price of share)/(book value of outstanding
shares).
Finally, two more variables, Gequity and yearly effects, both of which are applicable to
the Malaysian context, are included. Gequity is defined as percentage of government equity
ownership in the firm. Government ownership in a firm may reduce the ETR of the firm
because access to government departments can facilitate effective lobbying and timely tax
planning. Yearly effects are dummy variables denoting time effects from 1990 to 1999 (with
1999 as the omitted variable). In the 10-year period from 1990 to 1999, it is not reasonable
to assume that the underlying parameters remain time-invariant throughout. One prominent
time-variant factor is the gradual phasing in of the reduction in corporate tax (Table 2). The
others include the healthy yearly economic growth during this period (more than 8% per year
from 1990 to 1997) and the financial crisis in the latter years. To adjust for these and other
possible time-variant effects, dummy variables for years 1991 to 1999 are included in this
analysis.
4.2. ETR measures
It has been suggested that there are three major issues in the selection of ETR measures (e.g.,
Callihan, 1994; Omer and Molloy, 1991). These issues are: which taxes, how profit should be
measured, and the robustness of these measures to capture ETR.

Table 2
Malaysian corporate tax rates for 1990–1999
Basis year Rate
1/1/90–31/12/90 35
1/1/91–31/12/91 35
1/1/92–31/12/92 34
1/1/93–31/12/93 32
1/1/94–31/12/94 30
1/1/95–31/12/95 30
1/1/96–31/12/96 30
1/1/97–31/12/97 28
1/1/98–31/12/98 28
1/1/99–31/12/99 28
First, the issue of which taxes to include is relevant because any significant omission can
bias the firm’s overall tax burden. Although few researchers have chosen to ignore deferred
tax (e.g., Gupta and Newberry, 1997; Kim and Limpaphayom, 1998; Porcano, 1986), others
have suggested that an adjustment of deferred tax should be made (e.g., Kern and
Morris, 1992; Omer et al., 1993; Singh et al., 1987; Stickney and McGee, 1982; Zimmerman,
1983). In addition, Omer and Molloy (1991) suggest that if deferred taxes are used in an
ETR measure, the researcher should choose the deferred tax expense (profit and loss item)
rather than changes in deferred tax (balance sheet item) because deferred tax expense will
eliminate systematic reporting differences associated with the change in the deferred tax
liability.
Second, the issue of how profit should be measured arises because of the difference between
accounting (book) income and tax income. This difference suggests that accounting profit
might not represent the actual chargeable income of the firms. In addition, different accounting
policies adopted by firms would result in different incomes. The accounting policy induced
income difference would render financial information incomparable across firms. According
to Zimmerman (1983), the use of cash flow (rather than operating income) would eliminate
the effects of different accounting treatments to income. A number of subsequent researchers
have also used cash flow from operation as an alternative to operating income to calculate ETR
(Gupta and Newberry, 1997; Singh et al., 1987).
Third, it has been suggested (e.g., Omer and Molloy, 1991) that the use of more than one
ETR measure can improve the robustness of results. One reason is that different ETR measures
(either income or cash flows-based and with or without deferred tax) have been found to
produce conflicting results (e.g., Porcano, 1986; Zimmerman, 1983).
To account for the factors discussed above, five different ETRs measures are used. ETR1 is
the well-known measure used by Zimmerman (1983) represented as (tax expenses − deferred
tax expenses)/(operating cash flow). ETR2 and ETR3 are two versions of the measure used by
Porcano (1986): (tax expenses−deferred tax expenses)/(profit before interest and tax) and (tax
expenses)/(profit before interest and tax). ETR 4 is the measure used by Stickney and McGee
(1982)andisgivenas(taxexpenses)/(pre-taxprofit−(deferredtaxexpenses/statutorytaxrate)).
ETR5 is the measure used by Shevlin (1987) and is calculated as (tax expenses − deferred tax
expenses)/(pre-tax profit − (changes in deferred tax/statutory tax rate)).

5. Results
Table 3 shows the descriptive statistics of means, median, standard deviation, minimum
and maximum for all proxies of dependent variables (ETR) and explanatory variables over the
period 1990 to 1999. On the whole, examination of the data suggests no obvious outliers. ETRs
range from the lowest 24.3% (ETR3) to the highest 30.1% (ETR5), while the median range
Table 3
Descriptive statistics of variables used in the sample of Malaysian firms
ETRn ln assets Leverage Capital
intensity
Inventory
intensity
ROA MktBook Gequity
Panel A: ETR1
Mean 0.271 13.122 0.139 0.235 0.093 0.081 3.072 1.692
Median 0.265 13.114 0.062 0.187 0.055 0.067 2.071 0.036
S.D. 0.164 1.587 0.191 0.207 0.109 0.131 6.078 7.126
Minimum 0.000 8.290 0.000 0.000 0.000 −4.570 −90.61 0.000
Maximum 0.990 18.580 0.920 0.930 0.065 1.100 104.67 81.430
Panel B: ETR2
Mean 0.250 13.122 0.142 0.224 0.088 0.082 3.034 1.701
Median 0.258 13.121 0.063 0.169 0.048 0.067 2.030 0.034
S.D. 0.143 1.579 1.932 0.207 0.108 0.077 5.903 7.118
Minimum 0.000 8.07 0.000 0.000 0.000 −0.170 −90.610 0.000
Maximum 0.960 18.58 0.920 0.930 0.650 1.100 104.670 81.430
Panel C: ETR3
Mean 0.243 13.112 0.142 0.225 0.089 0.082 3.027 1.679
Median 0.252 13.109 0.064 0.170 0.049 0.066 2.029 0.034
S.D. 0.140 1.579 0.193 0.207 0.108 0.076 5.866 7.018
Minimum 0.000 8.070 0.000 0.000 0.000 −0.170 −90.610 0.000
Maximum 1.000 18.580 0.920 0.930 0.065 1.100 104.67 81.430
Panel D: ETR4
Mean 0.295 13.133 0.138 0.227 0.089 0.087 3.109 1.719
Median 0.290 13.139 0.061 0.172 0.049 0.069 2.069 0.037
S.D. 0.162 1.573 0.189 0.208 0.108 0.075 5.893 7.151
Minimum 0.000 8.290 0.000 0.000 0.000 0.000 −90.61 0.000
Maximum 0.990 18.580 0.920 0.930 0.650 1.100 104.67 81.430
Panel E: ETR5
Mean 0.301 13.128 0.139 0.226 0.089 0.087 3.099 1.718
Median 0.300 13.127 0.061 0.169 0.049 0.069 2.067 0.036
S.D. 0.158 1.573 0.189 0.208 0.108 0.075 5.882 7.195
Minimum 0.000 8.290 0.000 0.000 0.000 0.000 −90.610 0.000
Maximum 1.000 18.580 0.920 0.930 0.650 1.100 104.67 81.430
deferred tax expenses)/(profit before interest and tax); ETR3 = (tax expenses)/(profit before interest and
tax); ETR4 = (tax expenses)/(pre-tax profit − (deferred tax expenses/statutory tax rate)); ETR5 =
(tax expenses − deferred tax expenses)/(pre-tax profit − (changes in deferred tax/statutory tax rate));
ln assets = natural log of total assets; leverage = (total debt)/(total assets); capital intensity =
(property and plants & machinery)/(total assets); inventory intensity = (inventory/total assets); ROA =
(pre-tax profits)/(total assets); MktBook = (market price of share)/(shareholders equity/number of ordinary
shares outstanding); Gequity = percentage of government equity ownership.

from 25.2% (ETR3) to 30.0% (ETR5). Among the ETR measures, ETR3 has the lowest mean
and median where ETR5 has the highest. ETR1, ETR2, and ETR5 have common numerator
where deferred taxes are excluded as opposed to ETR3 and ETR4 where deferred taxes are
included. ETR1 is the only measures that used cash flows-based income measures while the
rest used book-income based measure. Overall, the results suggest that Malaysian firms’ ETR
are lower than the statutory tax rate (31% on average).
The explanatory variables exhibit similar patterns across different measures of ETR. The
results reveal several important points. The transformation of total assets into natural logarithm
form improves the overall distribution and reduces variability of variances. In general, a lever-
age level is low as only about 14% of the total assets are financed by debt. About 23% of the
total assets are in the form of plant, machinery, and equipment. The proportion of inventory
to total assets is about 9%. In terms of profitability, the rate of return measured by return on
assets is 8–9%. The high ratio of MktBook ratios reflects the fact that the Malaysian economy
has been growing rapidly during the decade of 1990s. Finally, on average, government share of
firms’ equity is less than 2%. The high standard deviation indicates a wide variation in terms
of government direct investment in firms.
Bivariate (Pearson product-moment) correlation among independent variables is presented
in Table 4. The low correlation between independent variables suggests that the problem of
multicollinearity is not serious in the data set. The highest correlation among independent
variables is between ln assets and capital intensity with a value of 0.483.
Results from the regression analysis are presented in Table 5. Both the White Test and
Durbin–Watson Test show no significant problems of heteroscedasticity and autocorrelation.
These results are not surprising because time effects and sectors effects have been adjusted
by year and sector dummies. Indeed, all the coefficients of year dummies for each of the five
ETR measures are highly and statistically significant. This result strongly suggests that the
underlying parameters are not time-invariant and time effects must be adjusted.
Results from the coefficients of sector dummies indicate that sector effects possess a sig-
nificant influence on ETR. Both the manufacturing sector and the hotel sector consistently
Table 4
Correlation of the independent variables
Independent
variable
ln assets Leverage Capital
intensity
Inventory
intensity
ROA MktBook Gequity
ln assets 1.000
Leverage 0.483∗∗
1.000
Capital intensity −0.204∗∗
−0.234∗∗
1.000
Inventory intensity −0.245∗∗
−0.258∗∗
0.158∗∗
1.000
ROA −0.066∗∗
−0.276∗∗
0.055∗
0.160∗∗
1.000
MktBook −0.109∗∗
−0.045∗
−0.072∗∗
−0.035 0.240∗∗
1.000
Gequity −0.070 −0.001 0.008 0.15 0.002 −0.041 1.000
ln assets = natural log of total assets; leverage = (total debt)/(total assets); capital intensity =
(property and plants & machinery)/(total assets); inventory intensity = (inventory/total assets); ROA =
(pre-tax profits)/(total assets); Gequity = percentage of government equity ownership.
∗
Significance at 95% confidence level.
∗∗

Table 5
Multiple regression results of five effective tax rates on the Malaysian firms
Independent variable ETR1 ETR2 ETR3 ETR4 ETR5
Constants 2.795∗∗∗
8.153∗∗∗
7.231∗∗∗
4.675∗∗∗
6.186∗∗∗
Size effects
ln assets 1.351 −4.893∗∗∗
−3.875∗∗∗
−0.254 −1.620∗
Sector effects
Consumer −4.230∗∗∗
0.458 −0.574 −2.437∗∗
−1.988∗∗
Manufacturing −6.772∗∗∗
−3.829∗∗∗
−5.263∗∗∗
−5.113∗∗∗
−4.985∗∗∗
Mining 0.149 −0.075 −0.940 −1.642∗
−1.606∗
Finance −1.742∗
−3.040∗∗∗
−3.220∗∗∗
−0.850 −0.927
Construction 0.517 0.889 −0.697 −3.178∗∗∗
−2.303∗∗
Trading −2.379∗∗
0.138 −1.272 −2.525∗∗∗
−1.487
Hotel −2.528∗∗∗
−2.387∗∗
−2.549∗∗∗
−3.683∗∗∗
−3.810∗∗∗
Plantations −3.378∗∗∗
−1.445 −1.737∗
−3.768∗∗∗
−4.241∗∗∗
Other effects
Leverage −0.154 −3.481∗∗∗
−4.525∗∗∗
−0.756 −2.12
Capital intensity −6.730∗∗∗
−1.646∗
−2.545∗∗∗
−3.595∗∗∗
−2.841∗∗∗
Inventory intensity −1.546 −0.865 −1.535 0.342 0.532
ROA 0.318 −1.977∗∗
−1.840∗
−8.298∗∗∗
−9.733∗∗∗
MktBook 1.292 3.744∗∗∗
3.621∗∗∗
3.347∗∗∗
3.660∗∗∗
Gequity −1.127 0.110 0.713 −0.715 −0.843
Year effects
1990 10.882∗∗∗
10.304∗∗∗
11.940∗∗∗
12.624∗∗∗
11.511∗∗∗
1991 10.645∗∗∗
10.575∗∗∗
11.927∗∗∗
11.259∗∗∗
11.123∗∗∗
1992 10.444∗∗∗
9.176∗∗∗
10.392∗∗∗
11.084∗∗∗
10.726∗∗∗
1993 9.593∗∗∗
9.219∗∗∗
10.374∗∗∗
10.664∗∗∗
10.733∗∗∗
1994 8.730∗∗∗
7.782∗∗∗
9.239∗∗∗
9.818∗∗∗
9.144∗∗∗
1995 9.681∗∗∗
8.841∗∗∗
9.915∗∗∗
9.328∗∗∗
9.249∗∗∗
1996 9.302∗∗∗
8.435∗∗∗
9.227∗∗∗
8.918∗∗∗
9.009∗∗∗
1997 8.870∗∗∗
8.294∗∗∗
9.494∗∗∗
9.828∗∗∗
9.285∗∗∗
1998 9.633∗∗∗
8.551∗∗∗
9.305∗∗∗
10.859∗∗∗
11.024∗∗∗
Observations 1955 2072 2101 1963 1971
Adjusted R-square 0.143 0.131 0.146 0.158 0.161
F-value 14.624 14.027 15.978 16.344 16.747
Durbin–Watson 1.906 1.974 1.976 2.087 2.067
deferred tax expenses)/(profit before interest and tax); ETR3 = (tax expenses)/(profit before interest and
tax); ETR4 = (tax expenses)/(pre-tax profit − (deferred tax expenses/statutory tax rate)); ETR5 =
(tax expenses − deferred tax expenses)/(pre-tax profit − (changes in deferred tax/statutory tax rate));
sector effects = sector dummy (consumer, manufacturing, mining, construction, trading/services, hotel, and
plantation, with properties being the omitted sector); ln assets = natural log of total assets; leverage =
(total debt)/(total assets); capital intensity = (property and plants & machinery)/(total assets);
inventory intensity = (inventory/total assets); ROA = (pre-tax profits)/(total assets); MktBook =
(market price of share)/(shareholders equity/number of ordinary shares outstanding); Gequity = percentage
of government equity ownership; year effects = year dummy (1990–1999).
∗
∗∗
∗∗∗

and significantly pay less effective tax than firms in other sectors. This result is the same
for the five ways ETR is measured. Moreover, while the coefficients for some sector dum-
mies from other sectors are also negative and statistically significant, two characteristics set
the coefficients for the manufacturing sector dummy apart. One is that the coefficient for
manufacturing firms is negative and statistically significant in all five ETRs. The same can-
not be said for other sectors except the hotel sector. Another characteristic is that the co-
efficient for manufacturing firms is most negative both in value and statistical significance,
that is, firms in the manufacturing sector pay less effective tax than firms in any other sec-
tor in Malaysia and this result enjoys higher statistical confidence than results for firms
in other sectors. This result is indicative of the industrial policy adopted by the Malaysian
government and consistent with the “industrial policy” hypothesis. Thus, evidence is strong
and robust that manufacturing firms pay less effective tax than firms from other sectors
(Question 1).
The similar but somewhat less strong result from the hotel sector is also highly indicative
of the Malaysian government’s policies to promote tourism as a vital sector for economic
growth and is consistent with the “industrial policy” hypothesis. In particular, this result can
be explained in terms of the steps taken (beginning in 1990) by the Malaysian government to
promote Malaysia as a tourist destination. It appears that a lower ETR is one of the various
incentives the Malaysian government provides for hotel operators.
The coefficient of ln assets, firm size, is negative and statistically significant when
ETR is measured as ETR2, ETR3, and ETR5. This coefficient is not statistically differ-
ent from zero when ETR is measured as ETR1 and ETR4. Collectively, there is no
evidence to suggest that larger firms pay more effective tax than smaller firms in Malaysia.
In fact, there is strong evidence to suggest that small firms pay more effective tax than
large firms in Malaysia. This evidence is in contradiction to the “political cost” hypoth-
esis but consistent with the “industrial policy” hypothesis and with evidence obtained by
Kim and Limpaphayom (1998), the sole study for non-Western firms. This result suggests
that given the industrial policy in Malaysia, ETR does not disadvantage large firms
(Question 2).
The coefficient for leverage is negative and statistically significant when ETR is
measured as ETR2 and ETR3. This coefficient is not statistically different from zero un-
der ETR1, ETR4, and ETR5. Thus, there is some evidence to support the intuitive notion that
debt financing can be used as a tax shield for Malaysian firms, although the evidence is not
conclusive.
The coefficient for capital intensity is negative and statistically significant for all ETR
measures. Moreover, the statistical significance is uniformly in the 99% confidence level with
ETR2 (at 90%) being the only exception. This evidence supports the notion that higher capital
investment and the resultant higher depreciable costs lead to a lower ETR. This evidence is
consistent with two previous studies in the U.S. context (Gupta and Newberry, 1997; Stickney
and McGee, 1982). The coefficient for inventory intensity, on the other hand, is not statistically
different from zero under all ETR measures.
The coefficient of ROA, the measure for efficiency in performance is negative and signif-
icant when ETR is measured as ETR2, ETR3, ETR4, ETR5, but not statistically different
from zero when ETR is measured as ETR1. These results suggest that more efficient firms

pay less effective tax in Malaysia. While these results are contrary to previous studies, they
are nonetheless consistent with the objective of the industrial policy in Malaysia: efficient
firms are given tax subsidy in the form of lower ETR. The coefficient of MktBook, the ra-
tio of market value shares to book value shares, is positive and statistically significant for
ETR2, ETR3, ETR4, and ETR5 and not statistically different from zero for ETR1. Thus,
it appears that firms with a higher MktBook value ratio pay more effective tax than other
firms.
The coefficient for Gequity, government equity, does not appear to be statistically different
from zero; however, ETR is measured. This result suggests that the effects of government
ownership may lie in areas other than ETR.
6. Conclusions
This paper has examined the relation between ETR and a set of possible factors for Malaysian
firms listed in the KLSE in the 1990–1999 time period. In terms of leverage, capital intensity,
and inventory intensity, the results obtained are consistent with previous U.S. studies and thus
not very remarkable. However, the results here are markedly different in terms of sector, size,
and performance.
First, this is the first study to look at the link between ETR and sector effects in the non-U.S.
context. The results confirm the importance of sectors. After adjusting for size, it is found
that manufacturing firms and hotels still pay significantly less effective tax than any other
firms listed in the KLSE. The results can be explained by the long-standing industrial policy
to protect the manufacturing sector as well as the recent 1990 government policy to promote
tourism. This result is robust under all five ETR measures and consistent with the “industrial
policy” hypothesis.
Second, there is no evidence that large Malaysian firms pay more effective tax than small
Malaysia firms. In fact, the negative association between ETR and firm size is statistically
significant in three out of five ETR measures. The evidence from Malaysia appears to be
consistent with the “industrial policy” hypothesis rather than the “political cost” hypothesis.
The evidence is also consistent with the 1998 Kim and Limpaphayom study on firms in East
and Southeast Asia. While the evidence certainly does not preclude the notion that large firms
carry more clout in Malaysia, the reason for that clout can be explained by the explicit industrial
policy adopted by the Malaysian government.
Third, the results indicate, in addition to sector and size effects, the type of performance
that would enable a firm to pay less effective tax. Not all profitable firms pay more (or less)
effective tax. After adjusting for size and sector effects, firms with high ROA (i.e., efficient
or competitive firms) pay significantly less effective tax. Curiously, firms with high MktBook
ratio (i.e., growth firms) pay significantly more effective tax after size and sector effects are
adjusted. One explanation may be that these firms tend to be profitable firms although the
industrial policy does not favor them. The nature of the industrial policy through ETR appears
to be that it rewards efficient rather than pure growth firms in the period 1990–1999. This
result implies one of the criteria by which the industrial policy to “pick” winners is efficiency
or competitiveness.

6.1. Limitations
One major limitation of this study is that the sector proxies, which are based on KSLE clas-
sification, may not be fine enough because they do not directly capture the official “strategic”
sub-sectorsidentifiedintheIMPof1986–2005.Futurestudiesthatusemorerefinedsectorprox-
ies should provide a better analysis of the “industrial policy” hypothesis proposed in this paper.
Another major limitation, which is common to all ETR studies, is that the ways or processes,
which actually enable certain firms (e.g., manufacturing firms) to pay lower effective tax than
other firms, are not examined. The evidence merely indicates that these firms do pay lower
effective tax and this result is consistent with the stated hypothesis. An interesting issue for
future studies would be to investigate the ways by which a lower ETR is achieved. While beyond
the scope of the current study, one possible way forward would be to study how accounting
choice is adopted in Malaysia and whether there is a material difference in accounting standards
between sectors in Malaysia.
On the whole, the results from this study suggest that significant differences may exist
between firms of developing countries and firms of developed countries in relation to ETR. For
example, evidence from Malaysia (a large developing country) supports the “industrial policy”
hypothesis but not the “political cost” hypothesis, which is developed based on evidence from
theU.S.(alargedevelopedcountry).However,ourpaperalsosuggeststhatthesedifferencescan
be, at least partially, explained by the difference in institutional context across countries. The
Malaysian results, as a case in point, are consistent and in support of the idea that the factors
that may influence ETR are susceptible to analysis and may be informed by the underling
institutional context such as government policies.
Notes
1. See, for example, Alavi (1996) for a more detailed discussion.
2. MASB has developed Malaysian Accounting Standard (MAS) as well as adopted extant
International Accounting Standards (IAS).
3. Wilkie and Limberg (1990), for example, excludes companies with negative ETRs rather
than simply negative tax expense to prevent companies with large negative ETRs from
exerting influence on the results.
4. Wealsousepercentageofinterestpaymenttoincomeasanalternativeproxyforleverage
as suggested by Kim and Limpaphayom (1998). We find no material difference between
these proxies.
5. We also use returns on sales (ROS) as a performance proxy. Sensitivity analysis shows
no material difference between using ROA or ROS as performance proxy.
Acknowledgments
We thank the editor and two anonymous reviewers for their helpful comments and sug-
gestions on the earlier drafts. Financial support from the Universiti Utara Malaysia (Northern
University of Malaysia) is gratefully acknowledged.

Appendix A. Tax computation of Malaysian firms
Profit before taxation as per audited accounts
Add
Non-allowable expenses or payments
General provisions
Deduct
Non-taxable or exempt income or receipts
Incomes, which assessed separately
Special deduction (e.g., double deductions)
Add
Balancing charge (sale of long-term assets for gains)
Deduct
Capital allowances:
Unabsorbed allowances carried forward
Current year allowances
Balancing allowances (sale of long-term assets for loss)
Deduct
Tax incentives (e.g., reinvestment allowances, investment tax allowances, etc.)
Deduct
Losses carried forward from previous years
Add
Other statutory income:
Share of partnership income
Dividends (gross), interest, and discounts
Rents, royalties, and premiums
Add
Other gains or profits
Deduct
Adjusted loss from business
Adjusted loss from partnership
Prospective expenditure (for mining firms)
Non-business deductions (e.g., gifts and donations)
Tax chargeable at 28%
Deduct
Tax on dividends deducted at source
Double taxation relief
Tax payable

References
Alavi, R. (1996). Industrialisation in Malaysia: Import substitution and infant industry performance. London:
Routledge.
Callihan, D. S. (1994). Corporate effective tax rates: A synthesis of the literature. Journal of Accounting Literature,
12, 1–43.
CCH. (1999). CCH Malaysian Master Tax Guide 1999 (16th ed.). Singapore: CCH Asia Pte. Limited.
Citizens for Tax Justice. (1984). Corporate income taxes in reagan years. Washington, DC: Citizens for Tax Justice.
Citizens for Tax Justice. (1985). Corporate taxpayers & corporate freeloaders. Washington, DC: Citizens for Tax
Justice.
Citizens for Tax Justice. (1986). 130 reasons why we need tax reform. Washington, DC: Citizens for Tax Justice.
Gupta, S., & Newberry, K. (1997). Determinants of the variability in corporate effective tax rate: Evidence from
longitudinal data. Journal of Accounting and Public Policy, 16, 1–39.
Harberger, A. C. (1959). The corporate income tax: An empirical appraisal. In Proceedings of the tax revision
compedium (Vol. 1, pp. 231–250). House Ways and Means Committee.
Holland, K. (1998). Accounting policy choice: The relationship between corporate tax burden and company size.
Journal of Business Finance and Accounting, 25, 265–288.
Kern, B. B., & Morris, M. H. (1992). Taxes and firm size: The effect of tax legislation during the 1980s. The
Journal of the American Taxation Association, 14, 80–96.
Kim, K. A., & Limpaphayom, P. (1998). Taxes and firm size in Pacific-Basin emerging economies. Journal of
International Accounting, Auditing and Taxation, 7, 47–63.
KLSE. (2001). Listing requirements of Kuala Lumpur Stock Exchange. Kuala Lumpur: The Kuala Lumpur Stock
Exchange.
Malaysia Companies Act. (1965, amended 1999). Kuala Lumpur: International Law Book Services.
Malaysia Institute of Accountant and Malaysian Institute of Taxation. (1990). Malaysian Budget 1991. Kuala
Lumpur: Malaysia Institute of Accountant and Malaysian Institute of Taxation.
Malaysian Government. (1985). Industrial Master Plan (IMP). Kuala Lumpur: National Printing Department.
Malaysian Government. (1996). The Second Industrial Master Plan (IMP2). Kuala Lumpur: National Printing
Department.
Malaysian Income Tax Act. (1967, amended 1999). Kuala Lumpur: International Law Book Services.
McIntyre, R. S. & Nguyen, T. D. C. (2000). Corporate income taxes in the 1990s. Washington, DC: Institute on
Taxation and Economic Policy.
Northcut, W. D., & Vine, C. C. (1998). Earnings management in response to political scrutiny of effective tax
rates. The Journal of the American Taxation Association, 22, 22–36.
Omer, T. C., & Molloy, K. H. (1991). Measurement of effective corporate tax rates using financial statements
information. The Journal of the American Taxation Association, 13, 57–72.
Omer, T. C., Molloy, K. H., & Ziebart, D. A. (1993). An investigation of the firm size—Effective tax rate relation
in the 1980s. Journal of Accounting, Auditing and Finance, 8, 167–182 [New Series].
Porcano, T. M. (1986). Corporate tax rates: Progressive, proportional or regressive. Journal of the American Taxation
Association, 7, 17–31.
Price Waterhouse. (1996). Malaysian Budget 1997, Price Waterhouse. Kuala Lumpur: Price Waterhouse.
Promotion Investment Act. (1986). Kuala Lumpur: International Law Book Services.
Rosenberg, L. G. (1969). Taxation of income from capital, by industry group. In A.C. Harberger & M.J. Bailey
(Eds.), The taxation of income from capital. Washington, DC.
Salamon, L. M., & Siegfried, J. J. (1977). Economic power and political influence: The impact of industry structure
on public policy. The American Political Science Review, 71, 1026–1043.
Shevlin, T. (1987). Taxes and off-balance-sheet financing: Research and development limited partnership. The
Accounting Review, 52, 480–509.
Siegfried, J. J. (1974). Effective average U.S. corporation income tax rates. National Tax Journal, 27, 245–259.
Singh, D., Wilder, R. P., & Chan, K. P. (1987). Tax rate in small and large firms. American Journal of Small
Business, 22, 41–52.
Spooner, G. M. (1986). Effective tax rates from financial statements. National Tax Journal, 36, 293–306.

Stickney, C. P., & McGee, V. E. (1982). Effective corporate tax rates: The effect of size, capital intensity, leverage
and other factors. Journal of Accounting and Public Policy, 2, 125–152.
Wilkie, P. J. (1988). Corporate average effective tax rates and inferences about relative tax preferences. The Journal
of the American Taxation Association, 10, 75–88.
Wilkie, P. J., & Limberg, S. T. (1990). The relationship between from size and effective tax rate: A reconciliation
of Zimmerman (1983) and Porcano (1986). The Journal of American Taxation Association, 11, 76–91.
Zimmerman, J. L. (1983). Taxes and ﬁrm size. Journal of Accounting and Economics, 5, 119–149.

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