On the effect of the 2006 Norwegian tax reform on cash flows from

Transcription

Master Thesis – GRA 1900
27.08.2012
Halvor Melau Sørensen
Tarje Melau Sørensen
BI Norwegian Business School - Master Thesis
- On the effect of the 2006 Norwegian tax reform on
cash flows from firms to private investors -
GRA 1900 – Master Thesis
Programme:
Master of Science in Business and Economics
Major in Finance
Major in Business Law, Tax, and Accounting
Submission Date:
27.08.2012
Due Date
03.09.2012
Supervisor:
Bogdan Stacescu
Campus – BI Oslo
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CONTENT
ACKNOWLEDGMENTS .............................................................................................................. 4
ABSTRACT ..................................................................................................................................... 5
1.
INTRODUCTION ................................................................................................................. 6
2.
LITERATURE REVIEW ..................................................................................................... 9
2.1 AGENCY PROBLEMS AS A REASON FOR DIVIDEND PAYMENTS .................................................. 9
2.2. EVIDENCE FROM OTHER STUDIES ON TAX REFORMS ............................................................. 10
2.3. CASH HOLDINGS AND AGENCY PROBLEMS............................................................................ 13
2.4. REASONS FOR IMPLEMENTING A NEW TAX REFORM IN NORWAY .......................................... 15
3.
DATA.................................................................................................................................... 16
4.
METHODOLOGY .............................................................................................................. 17
4.1 DATA STRUCTURING AND VARIABLE CREATION .................................................................... 17
4.2 NONPARAMETRIC TEST ......................................................................................................... 21
4.3 PANEL DATA REGRESSION ..................................................................................................... 23
4.3.1 Random effects versus fixed effects panel data regression ........................................... 23
4.3.2 Data structuring to run panel data regressions............................................................ 24
4.4 SEEMINGLY UNRELATED REGRESSION ................................................................................... 25
4.4.1 Seemingly unrelated regression model – theory ........................................................... 25
4.4.3 System of equations ...................................................................................................... 26
5.
RESULTS ............................................................................................................................. 27
5.1 RESULTS OF NONPARAMETRIC TESTS .................................................................................... 28
5.1.1 Effect on cash holdings ................................................................................................. 29
5.1.2 Effect on dividends ....................................................................................................... 29
5.1.3 Effect on ownership ...................................................................................................... 29
5.2 RESULTS OF PANEL DATA REGRESSION .................................................................................. 30
5.2.1 Effects on cash holdings ............................................................................................... 30
5.3 RESULTS OF SEEMINGLY UNRELATED REGRESSIONS.............................................................. 32
5.3.1 Effect on cash holdings ................................................................................................. 32
6.
DISCUSSION....................................................................................................................... 33
6.1 ON THE TAX REFORM AND ITS EFFECT ON CASH HOLDINGS ................................................... 33
6.2 ON THE TAX REFORM AND ITS EFFECT ON DIVIDENDS............................................................ 35
6.3 ON THE TAX REFORM AND ITS EFFECT ON OWNERSHIP STRUCTURE ....................................... 37
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6.4 ON THE TAX REFORM AND ITS EFFECT ON CASH FLOW BETWEEN FIRMS AND PRIVATE
INVESTORS. ................................................................................................................................. 38
7.
CONCLUSIONS .................................................................................................................. 39
REFERENCES .............................................................................................................................. 41
ATTACHMENTS ......................................................................................................................... 44
1. Nonparametric test results - means ................................................................................... 44
2. Nonparametric test results – medians ............................................................................... 47
3. Panel data regression – cash holdings .............................................................................. 50
4. Panel data regression – dividends..................................................................................... 53
5. Panel data regression – ownership ................................................................................... 56
6. Panel data regression – personal ownership .................................................................... 59
7. SUR - Before tax reform .................................................................................................... 61
8. OLS – Before tax reform.................................................................................................... 63
9. SUR after tax reform ......................................................................................................... 65
10. OLS – After the tax reform .............................................................................................. 67
11. SUR – Entire period ........................................................................................................ 69
12. OLS – Entire period......................................................................................................... 71
13. Definition of variables ..................................................................................................... 73
14. Empirical distribution test for cash to total assets and adjusted payout ......................... 74
15. Preliminary master thesis ................................................................................................ 75
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Acknowledgments
We would like to thank Bogdan Stacescu for invaluable guidance, quick feedback
and thoughtful comments in the process of writing this Master thesis. In addition
we are thankful for the data provided by the Centre of Corporate Governance.
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Abstract
With the introduction of the 2006 Norwegian tax reform dividends taxation
increased from zero to 28 per cent. The goal was to increase taxation without
affecting business investments, and to remove the possibility of business owners
reducing their income tax by paying dividends instead of salary. Our thesis focus
on the effects the tax reform has had on cash flows from firms to private investors.
We document a significant reduction in dividends and increase in cash holdings
after the tax reform. Dividends increase prior to the tax reform, then drop sharply
after, while cash to total assets show a more continuous increase over the time
period. We also document a significant reduction in personal ownership and a
significant shift from minority to majority owners. Our results show that the tax
reform has had an impact on cash flows between firms and private investors,
which again might influence business investments.
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1. Introduction
The purpose of this Master thesis is to look at the effects of the Norwegian tax
reform of 2006 on the cash flow from firms to private investors1.
The 2006 tax reform introduced a 28%2 tax on dividend payments made by
companies to private individuals. Dividend payments to a limited liability
company3 are not taxed until they are paid out to the owner of that company.
Thoresen (2010) states that the background for the reform of the tax system was
based on the observation that many people with high income got a lower tax base
through the creation of a public company and getting their income through
dividend payments rather than through salary payments, the latter being taxed
progressively up to 55.3%4 and the former previously at a fixed rate of 28%. After
the reform tax on dividend payments have increased to 48%5, while the
progressive tax on labour was lowered to 47.8%6, effectively evening out the
taxation on dividends and labour.
The intention of the 2006 tax reform, according to Nymoen & Woxholt (2009,
168), was to “increase taxation on high stock market returns without influencing
business investments7.” In our thesis we do not look at business investments, but
we look at cash mobility to private investors. One of the main reasons why we
think it is important to study the effects of the tax reform on cash flow from firms
to investors is to see if the intentions of the reform came through, or if
unintentional effects have occurred that may influence corporate investments. In
1
By private investors we mean minority and majority shareholders of common equity, we do not
look at debt investors.
2
Investors pay the 28% tax rate on profits after deducting a fixed rate determined annually to
protect the equity invested against inflation.
3
Aksjeselskap
4
Thoresen, 2010, p 5.
5
6
7
We have translated the Norwegian text into English.
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the following we outline the questions we set out to discuss, and how we plan to
approach the issue.
Do companies keep more cash on balance sheet after the tax reform? We will
discuss whether any changes of cash on the balance sheet can be due to the tax
reform, or if other forces may influence the development of cash holdings at
companies. Subsequently, we will discuss agency issues related to the effect of a
possible build-up in cash on the balance sheet, with a particular focus on the effect
on minority shareholders.
Has dividend policy changed significantly after the 2006 tax reform? The results
will be tied to a discussion related to the “outcome” model looking at how the tax
reform may affect the ability of minority shareholders to force the majority to give
up control of some of the company’s resources through dividend payments.
Has ownership structure in the companies changed in favour of majority
shareholders as minority shareholders have less access to company cash in the
case of lower dividend payments? Investigating this we try to understand if the
dividend tax reform has shifted the balance of power between minority and
majority interests giving the majority interest more power.
In order to better discuss these issues, we have four hypotheses we would like to
test:

First:
o H0: The tax reform has had no impact on cash flow between firms and
private investors.
o H1: The tax reform has had an impact on cash flow between firms and
private investors.

Second:
o H0: The tax reform has not increased the cash on company balance
sheets.
o H1: The tax reform has increased the cash on company balance sheets.

Third:
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o H0: Dividend policy has not changed significantly after the 2006 tax
reform.
o H1: Dividend policy has changed significantly after the 2006 tax reform.

Fourth:
o H0: Ownership structure in companies has not changed in favour of
majority shareholders as a consequence of the reform.
o H1: Ownership structure in companies has changed in favour of majority
shareholders as a consequence of the reform.
We will do a quantitative analysis to check if companies have made a significant
change in their dividend policies, or in the amount of cash they hold on their
balance sheets as a result of the 2006 Norwegian tax reform on dividends. In
addition we check if the ownership structure has changed. The findings of our
quantitative analysis will then be discussed with a focus on agency problems
between minority and majority shareholders, which again can be of interests in
discussions around efficient capital allocation.
Finding answers to our hypotheses is important in order to better understand if the
2006 tax reform had unintentional consequences that may not be optimal for a
well-functioning capital market. In our thesis we focus on the effects the tax
reform has had on cash holdings, dividend payments and ownership structure in
companies.
Our research may give further needs to discuss and highlight the efficiency of
capital allocation. With more cash on the balance sheet, there is a danger that what
Warren Buffet called the institutional imperative (Hagstrom, 1997) makes
management invest the additional cash in inefficient ways, as marginal investment
opportunities often provide a less satisfactory return. In addition, increased cash
on the balance sheet makes management even more important for the company
and for investments in it.
The paper is organized as follows. Section 2 provides a literature review
highlighting the main points of the articles we found to be most relevant to our
thesis research. Section 3 goes through the methodology we have used to arrive at
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our results. Section 4 gives an overview of the data we have used. Section 5
presents the results of the analysis we have used to find meaningful information
based on the data discussed in section 4 and the methodology in section 3. The
results are discussed and interpreted in section 6. Finally, in section 7 we conclude
our findings to our hypothesis and research questions.
2. Literature Review
2.1 Agency problems as a reason for dividend payments
In order to answer our questions it is important to know something about why
dividends are paid out in the first place. A popular idea is that firms signal future
profitability by paying dividends. The idea seems reasonable since stocks tend to
appreciate after raising their dividend and depreciate after cutting dividends.
However, this theory has failed in research trying to predict the future earnings of
a firm using their current dividend policy. Other theories related to the dividend
puzzle usually address the agency problems between inside and outside
shareholders. Outside shareholders prefer dividends since this gives them the
choice as to how the money should be reinvested. If the money stays within the
firm it could be spent on unprofitable projects or on higher salaries to the insiders.
When dividends are paid out, outside investors can choose whether or not they
believe in the future profitability of new projects in the firm, or if they can get a
higher return elsewhere.
Lopez de Silanes, et. al (2000) has provided further research as to how outside
shareholders get insiders to disgorge cash. They have looked at two frequently
used models, the “outcome” model and the “substitute” model. The “outcome”
model predicts that dividends are paid due to minority shareholders using their
legal rights in order to pressure corporate insiders to disgorge cash. This implies
that shareholders in countries with high shareholder protection are more likely to
prefer a dividend policy that maximizes their return on capital, since the cash is
theirs either way. In countries with low shareholder protection, shareholders will
prefer dividends, since a bird in the hand is worth two in the bush. Good
protection of minority shareholders allows minority shareholders to apply
pressure on insiders and should make dividends higher in such countries. Also, the
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higher the portion of minority shareholders the higher should the dividends be.
The “substitute” model leads to the opposite conclusions. It predicts that firms
distribute dividends in order to build a reputation of treating minority shareholders
well. This reputation will make them able to raise external capital on attractive
terms in the future. In countries with low minority shareholder protection minority
shareholders have little else but reputation to rely on and thus dividends should be
higher in these countries. Lopez de Silanes, et. al (2000) studies a sample of 4000
companies from 33 countries with different levels of minority shareholder rights
and finds consistent support for the “outcome” model. In countries with good
protection of minority shareholders dividends are higher and high growth
companies pay lower dividends than low growth companies. However, when
analysing a large sample of private firms with majority owners in Norway,
Berzins et al (2011) finds support of the substitute model. They find that with a
higher potential for conflict in the ownership structure comes higher payout ratios,
implying that majority owners use dividends to reduce agency costs.
The literature describes two main theories explaining the rationale behind
companies’ dividends policies. Either minority investors pressure majority
investors into paying dividends (outcome model) or companies pay dividends in
order to build a good reputation among minority shareholders. The outcome
model predicts that, with the tax reform affecting dividends negatively, we should
see a shift from minority to majority shareholders. The substitute model on the
other hand predicts no such shift as minority investors trust majority investors to
have an incentive for paying out dividends anyway, their reputation.
2.2. Evidence from other studies on tax reforms
Both Alstadsæter and Fjærli (2009) and Kari et. Al (2008) looks at the effects on
dividends when anticipating changes in dividend taxation and just after
implementation of changes in dividend taxation. Both start their analysis by
looking at the two dominant views in regards to dividend taxation. The so called
“old view”, supported by Harberger (1962), Feldstein (1970) and Poterba and
Summers (1985), predicts that a change in dividend taxation affects both
investments and dividends. It is assumed that the marginal source of financing of
investments is new share issues. According to Harberger (1962, 1966) dividend
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taxation distorts the investment decisions and so might prevent an optimal
allocation of capital. The “new view”, developed by King (1974), Auerbach
(1979) and Bradford (1981), argues that dividend taxation affects share values
only and should be neutral with respect to investment and dividend decisions.
This view assumes that the marginal source of financing is profits and that
dividends are paid of what is left after investments. According to the new view
only temporarily changes in dividend taxation will affect dividend and investment
decisions through the timing of dividends.
Alstadsæter and Fjærli (2009) look at dividend payouts of Norwegian listed firms
in the period 1999 – 2006. In this period they examine the effects of both the
temporary dividend tax in 2001 and the permanent shareholder income tax in
2006. From the table below one can clearly see effects of expected tax reforms on
dividends. In 2000 the first signal of increased future tax on dividends came when
the parliament approved a temporary tax on capital gains and dividends on
respectively 28% and 11% (above a threshold) was applied. After 2001 a
committee was appointed and presented its recommendations in 2003, these were
decided and implemented as of 1. January 2006.
Graph 1: Received dividends by households in Billion NOK, 1993-2007. Source Statistics Norway (Alstadsæter and Fjærli
(2009))
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Alstadsæter and Fjærli (2009) find that the timing of dividends payments is very
sensitive to future changes in taxation and especially in companies with
concentrated ownership. Companies reduce cash and increase borrowing in order
to have dividends taxed at the low levels in 2005 and prior years instead of the
higher rates as of 2006. A reason for a higher sensitivity among companies with
concentrated ownership is said to be the possibility to pay out retained earnings
and then immediately reinvest this money as paid in capital, which can be paid out
at a later point without being subject to taxes.
Another important finding from Alstadsæter and Fjærli (2009) is that dividends
continue to be low in 2007. According to the authors this might be explained to
some extent by the repayment of paid-in capital, which replaces dividends for a
short period. If this is the case dividends should return to “normal” at some point.
Kari et al. (2008) finds similar results when looking at the Finnish corporate
income tax reform of 2005. The Finnish tax reform has some differences from the
Norwegian one. Firstly, the Finnish tax reform uses a partial relief method of
dividend taxation which means that only 70% of dividends are included in the
recipient’s taxable capital income. Secondly, non-listed companies can make taxexempt dividends up to a ceiling of 90 000 euros. Amounts above 90 000 euros
are taxed after the main rule. Before the tax reform Finnish corporations were
paying 29 percentage taxes on capital income and profits while the top marginal
tax rate (MTR) was 55 percentages. After the tax reform companies affected by
the reform paid 40.5 percentages on distributed profits.
Kari et al. (2008) looks at the period 1999-2004 and use the whole population of
firms that pay taxes in Finland. They find that dividend payouts are significantly
increased prior to the reform and as Alstadsæter and Fjærli (2009) they find a
relation between the increased dividends and increased debt. The increase in debt
was only noted in non-listed firms and not in listed firms that may find other ways
to finance their dividends. Another interesting finding from Kari et. Al (2008) is
that the investment activity remained unaffected for both listed and non-listed
firms in general. This is supportive of the “new view” but holds only when
revenue is used as weight. Applying the same weight on all companies however,
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they find statistically negative effects on investments as a consequence of the tax
change. Finally Kari et al (2008) finds evidence of tax planning in the sense that
more companies started distributing dividends up to the maximum level of tax
exempt dividends of 90 000 euros.
Kari et al (2009) does further research on the Finnish tax reform. They collect data
for all Finnish firms paying tax in the period 1999-2006 and use differences- in
differences estimation and matching methods in order to further investigate
dividend and investment responses to the newly implemented tax reform. They
find that dividends tend to be abnormally low after the reform. This however, can
still be the effect of abnormally large dividend distributions in the anticipatory
phase. This leads to further confirmation of the results from Alstadsæter and
Fjærli (2009) and Kari et al (2008) anticipating that tax changes have a large
impact on the timing of dividends.
Korkeamaki et al (2009) has done further research on the Finnish tax reform and
studied the effects on shareholder clienteles and the payout-policy of firms. Since
different investors were affected differently as a consequence of the reform it
gives insight as to how firms change their payout policy after their largest
shareholders wishes and/or how shareholders change their positions.
Further there are still no indications that investments decline more in firms
affected by the new dividend tax. This can be regarded as support to the “new
view” even though the period after the reform is still very short and one should be
careful drawing any conclusions.
Prior research on similar tax reforms find that the temporary effects of a tax
reform is evident. We should see increased leverage and increasing dividends
before the tax reform, and then a significant drop after the tax reform.
2.3. Cash holdings and agency problems
Kalcheva and Lins (2007) look at the link between cash holdings and managerial
agency problems in detail. Whether cash on the balance sheet is a good thing or a
bad thing depends on how it is put to use. They find that minority shareholders (p
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8) “discount the value of firms with a combination of expected managerial
entrenchment and high cash balances or no dividend payments, and that these
discounts are more pronounced in countries where minority shareholder rights are
the weakest.” Investors are uneasy about management controlling a large cash
holding. In fact, Dittmar and Mahrt-Smith (2007) finds that well governed firms
increase 0,88 USD in market cap for every extra USD on the balance sheet, while
poorly governed firms increase with only 0,42 USD.
As Kalcheva and Lins writes, Myers (1984) and Almeida et al (2003) argue that
large cash holdings are necessary in order to ensure that positive NPV projects can
be financed even when cash flow is low without having to turn to expensive
external funding. On the other side the authors show that Easterbrook (1984) and
Jensen (1986) claim that investors will prefer companies not to hold large
amounts of cash due to the danger that managers might be tempted to overinvest
and spend money on projects with unsatisfactory NPV, benefitting the managers
at the expense of shareholders. This attitude is similar to the one stated by Warren
Buffet as part of what he sees as the institutional imperative where he claims that
what often happens in organizations is that (Greenwald et al, 2001, p 179) “just as
work expands to fill available time, corporate projects or acquisitions will
materialize to soak up available funds, [and] any business craving of the leader,
however foolish, will quickly be supported by detailed rate-of-return and strategic
studies prepared by his troops.” With a large cash holding, the return on the
money put to use is likely to drop as capital is invested in increasingly risky or
unprofitable projects. The fact that investors discount large cash holdings at
companies with entrenched management when assessing the value of a company,
indicate that the argument of Easterbrook and Jensen has validity. The argument is
further supported by Blanchard, Lopez-de-Silanes, and Schleifer (1994) and
Harford (1999) (p 2 in Kalcheva and Lins (2007)) both documenting “a tendency
for managers to spend large holdings of cash in an inefficient manner.”
Rettl (2011) however, gives some support to managers doing what is in their
shareholders interest. When looking at patent approvals in the U.S., Rettl find that
companies getting approvals tend to store more cash, in order to take advantage of
future growth opportunities and companies getting their patent application turned
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down tend to disgorge cash. We will in this thesis see if the tax reform increases
the incentives to hold cash on the balance sheet rather than paying it out.
Prior research on agency problems and cash holdings comes to different
conclusions. Some argue that large cash holdings decreases value due to investors
not trusting the management to stay focused on projects with a satisfactory rate of
return. Others mean that companies with large cash holdings can take advantage
of good opportunities even when their cash flow does not provide them with
enough capital, and thus avoid expensive external funding. We can support one of
these theories if cash holdings and ownership is significantly affected by the tax
reform. The first theory predicts a decrease in minority owners given an increase
in cash holdings, while the second predicts the opposite.
2.4. Reasons for implementing a new tax reform in Norway
Before the 2006 Norwegian tax reform there were large differences in the
marginal tax rates on capital and labour income which led business owners to
reclassify labour income into capital income in order to pay less tax. To deal with
this “loophole” in the old tax reform was the main motivation behind the 2006
Norwegian tax reform. Thoresen et al (2010) asks if the 2006 Norwegian tax
reform has had the intended effect and increased redistribution. The data used in
this test is income and tax information for the entire Norwegian population in the
years 2000-2008. The method used allows for a separation of horizontal and
vertical effects, where horizontal equality refer to equal treatment of every person,
while the vertical effect shows that the tax capacity increases disproportionately
with the taxation.
In 2004, 95% of total dividends in Norway were paid out to the 10% richest.
Thoresen et al shows that after the reform a smaller part of total income for the
10% richest is due to dividends. Since a higher percentage of their income now
come from the higher taxed labour income the redistribution increases. The fact
that dividends were timed to be paid out before the reform reduces the effect, but
this will be a single period effect. As expected the reduced surtax has the opposite
effect, but not enough to counteract the effect from the increased tax on capital
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income. To conclude, Thoresen et al (2010) finds that the tax reform has had the
intended effect and reduced the horizontal inequality.
Prior theory suggests that the Norwegian tax reform is successful in closing a tax
loophole and in reducing horizontal inequalities. In our research we acknowledge
the results from Thoresen (2010), and focus our attention on the possible
unintended effects of this reform as the cost of cash mobility increases.
3. Data
The data used in the analysis comes from the Centre for Corporate Governance
Research (CCGR).
We have used several filters to screen the companies in the
database; first, all non-independent firms have been filtered out. Second, filters
have been used to keep only companies with positive revenues and total assets.
Third, companies with negative paid in capital or retained earnings have been
excluded. Finally, companies with negative dividends have been filtered out.
Berzins et al (2007) also show that 99.8% of the firms are non-listed, while 0.2%
is listed companies. The data on the companies go from the year 2000 to 2009.
The amount of firms in the data sample has increased from 121325 in 2000 to
182818 in 2009. The trend is clearly that the total amount of companies in the data
is increasing over time.
In order to check our hypotheses and research questions we have received access
to 20 variables from the CCGR database. These variables are8 (9) revenue, (105)
dividends, (76) bank deposits, cash in hand, etc, (63) fixed assets, (78) current
assets, (109) current liabilities, (19) results of operations, (86) retained earnings,
(82) paid-in capital, (14011) sum % equity held by owner with rank 1, (14019)
aggregated fraction held by personal owners, (219) aggregated fraction held by
personal owners, (11103) industry codes level two, (30) other interest expenses,
(14507) is independent, (14025) Herfindahl, (14029) share owned by owners with
more than 10% share, (80) own shares, and (14012) sum % equity held by owner
with rank 2.
8
The numbers in parenthesis indicate the item number of the variable in the data set.
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4. Methodology
In this section we first describe the data structuring and variable creation we have
done in order to make the data ready for analysis (see attachment 13 for full list of
variables). Second, we discuss the various methodological tools we will use in
order to make sense of the data we have. This is vital to provide output that can be
used to properly check our hypotheses.
Our approach is based on the use of two different tools that provide us a view of
the data from different angles. First, we will check the data using a non-parametric
test of median values. Second, we will use a panel data regression analysis with
random effects to look at the data in order to check our hypotheses. Finally we
will run a seemingly unrelated regression to deal with a possible endogeneity
problem in our results.
4.1 Data structuring and variable creation
We decided to work with a sample of only independent firms. Of our original
sample of 1 955 350 observations of independent firms we have reduced our
working sample to 1 692 911 observations by adding the following two
restrictions. First, 626 observations have been removed by deciding to only look
at companies with a total asset value above 0. That means that all negative and
zero total asset values have been filtered out. Second, by only looking at
companies with positive revenue we have reduced the number of observations by
a further 261 813. We have filtered out all companies with negative revenues. In
order to make the sample as representative as possible for the average Norwegian
company our total sample only contains companies with positive total assets and
revenue.
Dividends variable
Instead of testing changes in dividend directly we have chosen to create a new
variable called adjpayx to look at changes in dividends. In our results we choose
to focus on the adjusted payout variable and not the clean dividends. Prior to the
tax reform companies increased their leverage and paid out dividends. These
dividends were then reinvested in the company as paid in capital. By doing this
companies could pay capital dividends from their paid in capital after the tax
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reform without paying taxes. Our adjusted payout ratio reverses this effect and
focuses instead only on the dividends actually paid out to investors. We mean the
picture shown by our adjusted payout is a better one, since variability is reduced
and it lets us know more about future dividend policies by removing part of the
one-time effect around implementation. The dividends that are paid out, and then
shot back into the company as paid in capital, are in fact only a reclassification of
retained earnings to paid in capital. The new variable is defined as:
Adjpayx = divadj/results of operation
Where the divadj variable is:
Dividend payout + paid in capital at time t - paid in capital at time t+1
In order to get a data set that is as representative as possible of the general
business environment we have excluded all cases with negative dividend
payments or negative paid in capital. We have restricted adjpax variable to only 0
or positive numbers, and capped it at 5 (500%) on the upside. This is done in
order to remove outliers, incorrect data punching, and special cases. This is very
important when we use the variables in the regressions since that method uses the
means in the calculations, and thus outliers with very divergent values may greatly
distort the overall picture. In the nonparametric test of medians the distortions
would not be significant, but since we use the same variables for both methods it
is important that they are feasible for both types of calculations.
We use the adjpayx variable rather than the pure dividend variable for three main
reasons. First, we need a measure which is comparable across firms. Second, we
use adjpayx to account for inflation. Since testing dividends alone would allow for
inflation to inflate later dividends compared to earlier, the adjusted payout ratio
addresses this since both the numerator and denominator now is affected by
inflation cancelling out the inflationary effect. Third, as discussed above we know
that some companies borrowed money and paid dividends to enter it as paid in
capital prior to the tax reform in order to be able to pay it out again after the tax
reform, tax free. In order to adjust for that we assume that a decrease in paid in
capital is really a hidden tax free dividend payment.
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Cash on the balance sheet variable
Checking changes in cash on the balance sheet directly could lead to large firms
with high changes in cash on the balance sheet to singularly distort the results. By
looking at the ratio cash to total assets instead we avoid the problem of large
companies having a too big effect on the outcome.
We use the variable cashtoty, which is created by taking cash to total assets and
capping it at the 95% level, cutting off the top tail of the distribution. We use this
variable to test changes in cash holdings for companies in our sample. This is
done to take out outliers, again with our regressions in mind, but which is not of
great importance in the nonparametric test of medians as discussed above.
In order to have a fixed assets to total assets as an instrumental variable in our
seemingly unrelated regression we create the fixratc variable. This variable is
defined as positive fixed assets over positive total assets and capped at 1. Capping
it at 1 takes out 218 observations which negative current assets, but the sample
size remains very big with over half a million observations.
Year group variable to control for differences within the data
We created a variable – yrg - with the value 1 for the period 2000 to 2005 and a
value 2 for the period from 2006 through 2009. Using that variable it is possible to
check if the dependent variables changed significantly from the first to the second
period.
Ownership structure variables
Looking at ownership structure we only do a couple of minor adjustments. The
first thing we do is to cut out all cases where the ownership variable goes above
100% since no one has over 100% ownership. We do that for both the aggregated
personal ownership variable aggpersy, and for the rank1 variable showing the
ownership of the largest shareholder.
We split the rank1 variable into two variables of rank150A and rank150B where
the first contains all owners with more than 50% ownership, and the latter all the
cases where the largest shareholder holds less than, or exactly, 50% of the shares.
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27.08.2012
The separation is made in order to check if complete control by the biggest
shareholder matter in relation to dividend payments and cash on the balance sheet.
In addition we created dummies for non-personal owners and personal owners
with the variable names dumnonpe and dumpe. Dumnonpe is 1 if yrg equals 2 and
aggpersy is below or equal to 50, while dumpe is 1 if yrg equals 2 and aggpersy is
above 50. This variable is created in order to look for differences after the tax
reform in companies with majority personal owners and minority personal
owners.
Profitability variable
To assess profitability we created the variable roax to look at return on assets. The
variable is defined as:
Roax = (paidinpo + retearpo)/totass
The x in roax is signalling that the variable is capped at the value 1, again in order
to avoid the outliers, special cases and incorrect data handling. Paidinpo and
retearpo are variables for paid in capital and retained earnings respectively, and
both are only looking at values above 0. Totass is the sum of fixed and current
assets.
Leverage variable
The levpo variable is the leverage variable excluding all cases that are negative,
where leverage is defined as:
Leverage = (total assets – paid in capital – retained earnings) / total assets
Variables covering firm size, growth and risk
In order to look at firm size we created a proxy for this which is the log of
company revenue, the variable is called logrev.
The variable growthrev shows the growth in revenue and is defined as:
Growthrev = ((rev – rev(-1)))/rev(-1)
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Additionally, to check for volatile sales we created the variable stdgrey which is
defined as:
Stdgrey = standard deviation of the growthrev variable
We use the stdgrey variable as a proxy for uncertainty and risk.
Industry variables
Finally, we created variables for different industry codes based on categorization
of old and new codes as suggested by excel spread sheet provided by our
supervisor. The table below shows the variables created and the industries they
cover.
Variable
Industry 1
Industry 2
Industry 3
Industry 4
Industry 5
Industry 6
Industry 7
Industry 8
Industry 9
Industry 10
Industry 11
Industry 12
Industry 13
Industry 14
Industry 15
Industry 16
Industry 17
Industry 18
Industry
Basic agriculture
Forestry
Fishing
Mining and oil
Light industry
Heavy industry
Utilities
Building
Retail and wholesale
Transport
Tourism
Publishing, media, IT, telecom
Financials
Real estate
Services
Public administration, health and edu.
Gambling
Extraterritorial
Table 1: Industry overview
In our panel data regression we use the industry variables with more than 10 000
observations
4.2 Nonparametric test
There are three main issues we would like to check. That is if the median
dividends paid out by companies have changed as a consequence of the tax
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reform, if the median level of cash kept on the balance sheet has increased and if
the ownership structure in the companies differ significantly prior to and after the
reform.
We started out thinking that we would do an independent t-test to compare the
means of the two groups. However, the two main assumptions underlying such a
test are that the cases are normally distributed within each group, and that the
groups are unrelated.
First, by doing a quick normality check in Eviews on the variables adjpayx and
cashtoty, we found that the variables are not normally distributed in either case.
This is shown in attachment 14.
Second, we have one group for all firms from 2000 through 2005 and another for
all firms from 2006 through 2009. Some of the companies we look at in group one
will be the same in group two. The amount of companies in the study has
increased by about 26%9 from 2005 to 2009, at the same time some companies
went out of business in the period reducing the cross-over effect further between
the groups. The groups are therefore not completely related, but it is not possible
to claim that the assumption that the groups are unrelated holds.
We therefore decided to discard the independent t test as part of our methodology
and go for a nonparametric test instead. The obvious advantage of the
nonparametric test comparing the medians between two groups is that it does not
assume normal distribution. Comparing medians is also positive in that possible
outliers will not affect the result as opposed to the case of means comparison.
However, the issue of the groups not being completely unrelated remains with the
use of the nonparametric test as well.
We use a 95% confidence interval for the test, ensuring that with 95% confidence
we will not reject H0 incorrectly. In the following we discuss more in depth the
variables we use in the nonparametric tests we run, and why we use them.
9
See attachment on amount of firms in the study over the ten year period.
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4.3 Panel data regression
We have data on several key company characteristics for a set of firms over a time
period of ten years. The data contains both a cross-sectional and a time series
aspect. Panel data regression is a tool developed to handle such data.
According to Dougherty (2007) panel data regressions are being increasingly
used. He mentions several reasons for this, first, (p 408) “it may offer a solution to
the problem of bias caused by unobserved heterogeneity, a common problem in
the fitting of models with cross-sectional data sets.” Second, panel data opens up
greater possibilities to reveal dynamics in the data that is difficult to see when
looking at a cross-section in isolation. Third, the amount of observations in data
sets which are feasible for panel data regressions are usually very large. Finally, (p
408) “because it is expensive to establish and maintain them, such panel data sets
tend to be well designed and rich in content.” Since we are looking to find
differences over time as the tax reform is introduced, the dynamics provided by a
panel data regression is useful.
4.3.1 Random effects versus fixed effects panel data regression
There are two main ways to do panel data regressions. These are known as the
fixed effect and random effect models.
The fixed effect model, according to Torres-Reyna’s Panel Data Analysis
presentation (p 9), should be used “whenever you are only interested in analysing
the impact of variables that vary over time.” The equation for the fixed effects
model can be set up as Brüderl (2005, p 8):
yit = β1xit + vi + εit
Where the elements of the equation are, again following Torres-Reyna (p 10):
 yit – is the dependent variable entity i, at time t
 β1 – is the coefficient of the independent variable
 xit – is an independent variable entity i, at time t
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 vi – is the unknown intercept of each entity i
 εit – is the error term of the equation
Working with fixed effect models can be a problem if the variables in the data set
are persistent, i.e. they do not change much over time. In our data set some of the
variables are fairly persistent. Whether to use the fixed effect models or random
effects model is therefore not clear cut immediately.
When variables are persistent a better approach can be to use the random effects
model. According to Torres-Reyna (p 25) “the rationale behind random effects
model is that, unlike the fixed effects model, the variation across entities is
assumed to be random and uncorrelated with the predictor or independent
variables included in the model.” The equation for the random effects model he
puts up (p 25) is:
yit = β1xit + vi + u it + εit
Where u it is the between entity error and εit is now the within entity error. The
random effects model can only be used if the between entity error, u it, is not
correlated with the independent variables.
4.3.2 Data structuring to run panel data regressions
In order to perform panel data regressions with our data set in Eviews we had to
balance the data and create a panel structure to work with. We did that by
inserting observations where necessary to take away date gaps. Variables are then
getting NA values where observations have been put in. The way we did this was
through the proc/structure/resize current page - and choosing a dated panel with
firm as the cross-section ID series and year as the time series identifier. In
addition we ticked the box for inserting observations where necessary. This is
solely an issue of data structure, and our panel is still unbalanced in the normal
meaning of the word.
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27.08.2012
4.4 Seemingly unrelated regression
When it is hard to determine the direction of causality between the dependent and
independent variables it is important to check for possible endogeneity, and if it is
present, overcoming it. We use the seemingly unrelated regression (SUR) method
together with the ordinary least squares regression (OLS) method to check for
endogeneity. If the two methods provide different results, we can assume that
endogeneity is present. In that case, the most appropriate of the methods we use to
look at the data and corresponding results will be the SUR method.
4.4.1 Seemingly unrelated regression model – theory
In the equation below there are m regression equations, i is the different equations,
and t = 1,…, T is the observation index. In our sample we have many observations
so we can assume that T → ∞, while we keep the m equations fixed.
yit = x´it β1 + εit, i = 1,..., m10
Further, the model can be written in vector form as:
yi = Xi β1 + εi, i = 1,..., m11
When these vectors are stacked on top of each other, Zellner (1962, p349) shows
that the system may be written as follows:
10
Equation is taken from Wikipedia page on seemingly unrelated regression, theory text around
the equations is als drawn from the same page.
http://en.wikipedia.org/wiki/Seemingly_unrelated_regressions
11
Equation is taken from Wikipedia page on seemingly unrelated regression.
http://en.wikipedia.org/wiki/Seemingly_unrelated_regressions
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With the system in place we move on to set up our own particular system of
equations, and discuss the instrumental variables we use.
4.4.3 System of equations
In this paper we look at how dividends, cash holdings and ownership are being
affected by the tax reform. The system of equations that we use is set out below in
a stylized fashion12.
1. Dividends = Ownership + Cash to total assets + Risk + Profitability
Instrumental variables = Revenue growth and industry variables13
2. Ownership = Dividends + Cash to total assets + Risk
Instrumental variables = Firm size and industry variables
3. Cash to total assets = Ownership + Dividends + Risk + Profitability
Instrumental variables = Fixed assets and industry variables
The instrumental variables we choose should be exogenous. That is, they affect
the dependent variables, but the dependent variables should not affect them. We
have used all the industries as instrumental variables as they can affect dividends,
cash holdings and ownership, without the latter three being able to affect the
industries. Identification requires that we have as many instruments as we have
right-hand side variables in each equation. This is the case for all our equations
above.
We need at least one equation specific independent variable to avoid that the SUR
estimation and the OLS estimation are equivalent. The first equation above, where
dividend is seen as the dependent variable we have chosen to use growth of
revenue as an equation specific independent variable. We have used growth of
revenue because, according to Rettl (2011), firms with growth opportunities pay
less dividends in order to pursue these opportunities. In addition, it is an
exogenous variable, since dividends do not affect growth of revenue.
12
See the exact specification of the equations in the attached results from the seemingly unrelated
regression calculation
13
Industry variables we use for all equations are industry 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 16
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The second equation, where ownership is seen as the dependent variable, we use
firm size as an independent variable. This is done following Jensen et al (1992), in
their article they use firm size as an independent variable to look at insiders. We
use the same variable to look at ownership.
The third equation, where cash to total assets are seen as the dependent variable,
we use fixed assets as an independent variable. Again, we have looked to Jensen
et al (1992), as they use fixed assets as an independent variable to look at debt.
We think fixed assets can be a good exogenous instrumental variable to look at
cash to total assets. Fixed assets affects cash to total assets, as an increase in fixed
assets increases total assets and thus reduces the cash to total assets, while cash to
total assets do not affect the fixed assets. For example, software companies with
low fixed assets often have high cash to total assets. Having fixed assets as our
instrumental variable enables us to run the seemingly unrelated regression, which
is necessary to deal with the issue of endogeneity.
5. Results
We start by graphing the development of adjusted pay-out and cash to total assets
over the last ten years. Looking at the adjusted pay-out in a histogram makes it
evident that the tax reform has had an effect on dividends. Even though the tax
reform was implemented in 2006 our data show a drop in 2005, since we are
looking at balance sheet data and not cash flows. The dividends on the balance
sheet in 2005 were paid out in 2006. Another effect amplifying the drop in
dividends after the tax reform is that large companies implemented IFRS in 2005.
According to IAS 10 proposed dividends are to be booked directly against equity
and are not shown as debt.
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Graph 2: Average adjusted pay-out ratio year by year
Looking at the average cash to total capital, it is clear that this rises over the
period and especially in 2006 to 2009.
Graph 3: Average cash to total assets ratio year by year
5.1 Results of nonparametric tests
The nonparametric tests of means and medians checks if there are significant
differences in the means and medians between the years prior to the tax reform
and the years after the tax reform.
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Equality of Medians
Variables
Cash to total assets
Adjusted pay-out
Largest owner own more than 50%
Coefficient
Median before
Equality of Means
Median after
Coefficient
Mean before Mean after
55,21 (0,00)
0,1750
0,2178
-58,23 (0,00)
0,2434
147,53 (0,00)
0,0000
0,0000
159,47 (0,00)
0,2362
0,0671
100,0000
100,0000
-3,64 (0,00)
85,6219
89,5950
63,76 (0,00)
0,2781
Largerst owner own 50% or below
5,35 (0,00)
42,8600
45,0000
-71,82 (0,00)
40,1428
40,3084
Aggregate personal ownership
46,99 (0,00)
100,0000
100,0000
73,69 (0,00)
88,9410
83,7005
Table 2: Results of a nonparametric test summarized (Attachments 1 and 2)
5.1.1 Effect on cash holdings
Based on our results we reject H0 in our second hypothesis – the tax reform has
increased cash on company balance sheets. We see from table 1 that both means
and medians are significantly changed. Before the tax reform the median cash to
total asset ratio was 17,5%, while after the tax reform this was increased to
21,78%.
5.1.2 Effect on dividends
Based on our results we reject H0 – which states that dividend policies has not
changed significantly after the 2006 tax reform. The table above shows that both
medians and mean are changed significantly after the tax reform, with the mean
pay-out ratio before the tax reform on 23,62% and after the reform on 6,71%.
5.1.3 Effect on ownership
Based on our results we reject H0 in our fourth hypothesis – which states that
ownership structure in companies has not changed in favour of majority
shareholders as a consequence of the reform. All our ownership variables in the
table above show a significant change from the years prior to the tax reform to the
years after the tax reform. Both variables focusing on the largest owner show a
significant increase in ownership of the largest owner. Average ownership, where
the owner owns more than 50% increased from 85,62% before the tax reform to
89,59% after the tax reform. The effect on the minority owners is smaller, but
show the same trend, the median owner has increased its ownership form 42,86%
to 45% after the tax reform Both variables show a shift towards majority owners.
The aggregate personal ownership is reduced from an average of 88,94% before
the tax reform to 83,70% after the tax reform.
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5.2 Results of panel data regression
We ran a panel data regression on adjusted payout, cash to total assets and
different ownership variables. When choosing independent variables we focus on
what we believe effect the dividend payments of a company such as risk, firm
size, growth, profitability, liquidity and ownership, and we control for industry
specific results.
5.2.1 Effects on cash holdings
Based on our panel data results we also reject H0 – the tax reform has increased
the cash on company balance sheets.
Independent variables
Rank 150B
Rank 150A
Aggpersy
Adjusted pay-out
0,0306 (0,000)
0,0312 (0,000)
0,0307 (0,000)
Revenue growth
-1,98E-05 (0,587)
Return on assets
0,2329 (0,000)
0,2196 (0,000)
0,2224 (0,000)
0,2228 (0,000) 0,2228 (0,000)
Leverage
-0,1710 (0,000)
-0,1466 (0,000)
-0,1545 (0,000)
-0,1514 (0,000) -0,1514 (0,000)
Log revenue
-0,0041 (0,00)
-0,0050 (0,000)
-0,0045 (0,000)
-0,0046 (0,000) -0,0046 (0,000)
Standard deviation of revenue growth
-0,0057 (0,007)
-0,0060 (0,000)
-0,0053 (0,000)
-0,0053 (0,000) -0,0053 (0,000)
Year group
0,0270 (0,000)
0,0301 (0,000)
0,0298 (0,000)
0,0156 (0,000) 0,0313 (0,000)
-
-0,0002 (0,000)
-
-
-5,96E-05 (0,459)
-
-
-
-
-
0,0001 (0,000)
Dumpe
Dumnonpe
0,0309 (0,000) 0,0309 (0,000)
-7,42E-06 (0,880) -1,10E-05 (0,712) -1,08E-05 (0,716)-1,08E-05 (0,717)
Personal ownership > 50%
Personal ownership =< 50%
0,0157 (0,000)
-0,0158 (0,000)
Table 3: Panel data regression results on cash to total assets (attachment 3)
From the results shown in the table above we see that the cash to total assets ratio
is significantly correlated to the year group variable with a positive coefficient,
meaning that the cash holdings are significantly higher after the tax reform than
before. Another interesting finding is that the cash on balance sheet has increased
more in companies with majority personal ownership than in companies with
minority personal ownership.
changed significantly after the 2006 tax reform.
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27.08.2012
Adjusted pay-out
Rank 150B
Rank 150A
Aggpersy
0,3258 (0,0000)
0,3038 (0,000)
0,3110 (0,000)
Revenue growth
-0,0001 (0,043)
-0,0003 (0,006)
-0,0002 (0,001)
Return on assets
0,2794 (0,000)
0,1943 (0,000)
0,2223 (0,000)
Leverage
0,5213 (0,000)
0,5349 (0,000)
0,5294 (0,000)
Log revenue
-0,0002 (0,858)
-0,0116 (0,000)
-0,0074 (0,000)
-0,0509 (0,000)
-0,0462 (0,000)
-0,0477 (0,000)
Year group
-0,2296 (0,000)
-0,2357 (0,000)
-0,2331 (0,000)
-
-0,0005 (0,000)
-
6,14E-05 (0,700)
-
-
-
-
0,0004 (0,000)
Table 4: Panel data regression results on adjusted pay-out (attachment 4)
From the results shown in the table above we see that the adjusted pay-out ratio is
significantly correlated to the year group variable with a negative coefficient,
meaning that the dividends are significantly lower after the tax reform than before.
We also find, as Alstadsæter and Fjærli (2009), that the sensitivity is higher
among companies with highly concentrated ownership.
Based on our results we reject H0 – which states that ownership structure in
companies has not changed in favour of majority shareholders as a consequence
of the reform.
Largest owner > 50%
Largest owner =< 50% Agg. personal ownership
-0,5091 (0,000)
-0,0790 (0,466)
Adjusted pay-out
-0,1997 (0,000)
-0,0682 (0,027)
0,9028 (0,000)
Revenue growth
0,0044 (0,272)
0,0012 (0,509)
-0,0066 (0,061)
Return on assets
0,0436 (0,759)
0,7718 (0,000)
1,0790 (0,000)
Leverage
-0,8394 (0,000)
0,8841 (0,000)
-1,7333 (0,000)
Log revenue
-0,6099 (0,000)
-0,4322 (0,000)
-0,8853 (0,000)
Standard deviation of revenue growth -0,2802 (0,052)
-0,3953 (0,000)
-0,3514 (0,015)
Year group
0,9465 (0,000)
-7,1033 (0,000)
3,0034 (0,000)
1,5571 (0,000)
Table 5: Panel data regression results on ownership variables (attachments 5 and 6)
We find that both among companies where the largest owner are larger than 50%
and in companies where the largest owner is smaller than 50% the ownership
variable is significantly positively correlated with our year group variable. This
shows us that the largest owner in companies is even larger after the tax reform. In
addition we find that the aggregated personal ownership of a firm is significantly
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negatively correlated to the year group variable, meaning that the aggregate
personal ownership in the companies is significantly reduced after the tax reform.
5.3 Results of seemingly unrelated regressions
In order to control for endogeneity, as discussed in the methodology, we ran
seemingly unrelated regressions on dividends, cash to total assets and aggregated
ownership.
5.3.1 Effect on cash holdings
Based on our results we reject H0 – that the tax reform has not increased the cash
on company balance sheets.
Adjusted pay-out
Return on assets
Fixed assets ratio
Year group
C/A (before)
OLS
SUR
0,0536 (0,000) 0,0814 (0,000)
0,1816 (0,000) 0,1681 (0,000)
-0,3442 (0,000) -0,3390 (0,000)
0,0010 (0,000) 0,0118 (0,000)
-0,0002 (0,000) -0,0003 (0,000)
C/A (after)
OLS
SUR
0,0483 (0,000)
0,0860 (0,000)
0,1916 (0,000)
0,1843 (0,000)
-0,3845 (0,000) -0,3820 (0,000)
-0,0052 (0,000) -0,0045 (0,000)
0,0002 (0,000)
0,0003 (0,000)
C/A (together)
OLS
SUR
0,0512 (0,000)
0,0811 (0,000)
0,1854 (0,000)
0,1742 (0,000)
-0,3611 (0,000) 0,1742 (0,000)
0,0029 (0,000)
0,0043 (0,000)
-7,94E-06 (0,449) 5,81E-05 (0,000)
0,0359 (0,000)
0,0416 (0,000)
Table 6: Seemingly unrelated regression results on cash to total assets (attachments 7 – 12)
The table above shows that cash holdings are significantly, and positively,
correlated with the year group variable, meaning that cash holdings are higher
after the tax reform. We also find that our data had endogeneity problems, since
the coefficients are different using OLS and SUR.
changed significantly after the 2006 tax reform.
Revenue growth
Return on assets
Year group
Adjusted pay-out (before)
Adjusted pay-out (after)
OLS
SUR
OLS
SUR
0,3721 (0,000) 0,5846 (0,000) 0,0982 (0,000)
0,1630 (0,000)
-0,0007 (0,000) -0,0007 (0,000) -7,96E-05 (0,043) -8.10E-05 (0,039)
0,4539 (0,000) 0,3909 (0,000) 0,1948 (0,000)
0,1760 (0,000)
-0,093 (0,000) -0,0932 (0,000) -0,0197 (0,000) -0,0191 (0,000)
0,0011 (0,000) 0,0022 (0,000) -0,0003 (0,000) -0,0004 (0,000)
Adjusted pay-out (together)
OLS
SUR
0,2385 (0,000)
0,3847 (0,000)
-0,0002 (0,000) -0,0002 (0,000)
0,3497 (0,000)
0,3070 (0,000)
-0,0557 (0,000) -0,0552 (0,000)
0,0003 (0,000)
0,0007 (0,000)
-0,2101 (0,000) -0,2126 (0,000)
Table 7: Seemingly unrelated regression results on adjusted pay-out (attachments 7 – 12)
The results found on dividends are similar. Dividends are negatively correlated
with the year group variable, meaning that dividends are significantly lower after
the tax reform. We also find that before the tax reform a higher aggregated
personal ownership led to lower dividends, while after the tax reform higher
personal ownership leads to lower dividends.
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Based on our results we reject H0 – which states that ownership structure in
companies has not changed in favour of majority shareholders as a consequence
of the reform.
Adjusted pay-out
Log revenue
Year group
Agg. Pers. own (before)
Agg. Pers. own(after)
OLS
SUR
OLS
SUR
-2,0570 (0,000) -3,2098 (0,000) 3,3154 (0,000)
6,3761 (0,000)
3,1358 (0,000) 4,7126 (0,000) -1,9766 (0,000) -3,7951 (0,000)
-0,8908 (0,000) -0,9151 (0,000) -0,6892 (0,000) -0,7372 (0,000)
-0,4673 (0,000) -0,3537 (0,000) -0,04807 (0,000) -0,5034 (0,000)
Agg. Pers. own (together)
OLS
SUR
0,3040 (0,056)
0,9452 (0,000)
2,1253 (0,000)
3,1817 (0,000)
-0,8057 (0,000) -0,8442 (0,000)
-0,4849 (0,000) -0,4461 (0,000)
-4,8672 (0,000) -4,6990 (0,000)
Table 8: Seemingly unrelated regression results on ownership variables (attachments 7 – 12)
6. Discussion
In the following we will discuss our results in relation to the hypotheses we had
initially and in relation to prior theory on the subject.
6.1 On the tax reform and its effect on cash holdings
Our H0 was that cash on balance sheet had not changed from before to after the
tax reform. Based on our results above we have to reject that hypothesis, since
companies hold more cash after the tax reform. There may be several explanations
for why this is the case.
After the tax reform dividends and capital gains are taxed equally and the benefit
of paying dividends instead of salary is to a large extent removed. In other words,
no matter how you want your money out of the company it will get taxed. For this
reason it is hard to see why companies would hold more cash after the tax reform.
Dividends are more expensive, but so are all alternatives, and sooner or later
investors will want their money. In order to find out whether the increase seen in
cash on balance sheet is due to the tax reform we will look for alternative
explanations.
When looking at the development in the cash holdings it is also important to keep
the results from Bates et. al (2009) in mind. They find that the cash to assets ratio
has increased significantly from 1980 to 2006. The reason for the increase is
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according to the authors mainly due to firm characteristics and their business
environment. Along with time companies have needed to hold more cash since
inventories are reduced, cash flow risk has increased, capital expenditures have
decreased and R&D expenditures have increased.
Another possible reason for the build-up in cash in the years after the tax reform
could be the leveraging that was done in the years prior to the tax reform. When
signing loan agreements companies often have to satisfy some debt covenants in
order to get the loan at the cheapest possible interest rate. Often these covenants
can specify a minimum liquidity needed from the company in order to obtain the
specified interest. This could force companies to hold more cash than they would
have held without the debt covenants, and as such strengthen our results.
However, the build-up in cash holdings on the one side and the reduction of
minority investors on the other supports the argument of Bates and Dittmar-Mahrt
(2007) that minority investors value USD 1 cash holdings on the company’s
balance sheet at less than USD 1 in their pocket. This is explained by Easterbrook
(1984) and Jensen (1986) in Kalcheva and Lins (2007), where they argue that
investors fear management overspending and falling into the institutional
imperative discussed by Warren Buffet. The result of such action may be suboptimal capital allocation and subsequently unsatisfactory returns, making
minority investors look elsewhere for opportunities.
Additionally, our results show that first, high growth in revenues has no
significant effect on the cash to total assets ratio. From earlier theory we would
expect a positive relation here, since growth can be seen as risk reducing leading
companies to hold less cash. However, past revenue growth may not be a good
measure for future growth. Opler et. Al (1997) uses the market to book ratio to
signal future growth opportunities and Rettl (2011) uses patent approvals, both
find a positive relation between cash on balance sheet and growth opportunities.
Second, the effect of firm size on cash to total assets is however in line with
Grullon et al (2002) as smaller companies hold more cash.
34
27.08.2012
6.2 On the tax reform and its effect on dividends
As mentioned, dividends has become more expensive, but so have the
alternatives, and investor will want their money at some point. In the short term
we expected to see companies adjust their dividends to plan their tax effectively.
Our results clearly support a short term effect on dividends.
Alstadsæter and Fjærli found a higher sensitivity among companies with high
concentrated ownership and meant that the reason could be that these companies
could more easily pay dividends then reinvest the money back in as paid in
capital and pay untaxed dividends at a later point in time. They used the same
argument for why dividends don’t turn back up in 2007. We control for the effect
of paying money back in as paid in capital by looking at the adjusted pay-out
ratio, but find the same results as Alstadsæter and Fjærli (2009). We can therefore
conclude that the effects described by Alstadsæter and Fjærli cannot solely be
explained by the increased paid-in capital.
Still, to draw a conclusion on the long term effect is difficult. In our timeframe the
dividends are significantly lower after the tax reform, but the question remains
whether or not our timeframe is enough to say anything about the long term
effects. We will go through some alternative explanations as to why the dividends
are still lower than before the tax reform.
In our panel data regression we find that profitability in the period after the tax
reform is significantly reduced. Dividends were positively correlated with
profitability and thus the change in dividends could be an effect of the reduced
profitability as well as the tax reform.
The short term tax planning that was done the last couple of years before the tax
reform led to artificially high dividends. It is possible that after the tax reform,
companies had less buffer then they actually were comfortable with and used the
income to pay off debt and store more cash. In addition to this effect dividends
can have been artificially high in all years prior to the tax reform. Before the
reform many large owners, also working in the company, didn’t get a salary, but
got dividends instead. This means that before the tax reform part of the dividends
35
27.08.2012
were in fact salary expenses. After the tax reform these owners are better off if
they pay a certain level of salaries, ref. a recent calculation from accountant Tor
Danielsen14.
Due to the short time period we are hesitant to say anything about the long term
effect and then subsequently whether the “old view” supported by Harberger
(1962), Feldstein (1970) and Poterba and Summers (1985) or “new view”
supported by King (1974), Auerbach (1979) and Bradford (1981) is the correct
one. We do however believe that the effect of salary now being paid as salary and
not dividend will reduce the dividends slightly in the long run, and as such give
some support to the “old view”.
The data show us furthermore that first, there is a positive relationship between
cash to total assets and adjusted payout. It is only reasonable to expect that the
liquidity of companies plays a role in their decision to pay out dividends.
Second, the payout ratio is positively correlated with leverage. One could think
that higher leverage leads to higher risk and thus companies should keep cash on
their balance sheet as a buffer. Our results show the opposite, higher leverage
leads to a higher payout ratio. This could be due to the fact that companies were
leveraging up in the years prior to the tax reform in order to pay out as much
dividend as possible, or it could be more fundamental and show that companies
switch from equity to debt financing when the cost of equity increases. Articles
focusing on periods of a tax reform get the same result as we do, ref. Kari et al
(2008) and Altstadsæter and Fjærli (2009).
Third, our results show that large companies pay out less cash. Our result is in
conflict with several articles on this subject. Grullon et.al (2002) find dividends to
increase with firm size due to the reduced operational risks as the company grows
larger. Another reason for dividends to increase with firm size is according to
Redding (1995) that companies should act in the interest of their owners. The
owners of large companies are often large institutional investors who invest in
14
http://tordanielsen.no/index.php/aktuelt/21-lonn-eller-utbytte
36
27.08.2012
large companies to reduce their transaction costs. Large institutional investors
often prefer dividends for tax and fiduciary reasons, while smaller individual
investors don’t necessarily prefer dividends due to the associated tax penalties.
Our period is however a bit special, since there is a tax reform in the middle of it.
Before the tax reform smaller firms with concentrated ownership paid dividends
instead of salary due to the discussed tax benefits. This effect is much larger on
smaller firms, both because it is easier in small firms with high concentration of
ownership, but also since the salary of one employee being paid out as dividend is
a much larger part of the total income in a small firm than in a big one. It seems
that this effect is larger than the effects described by Grullon et.al. (2002) and
Redding (1997).
Fourth, our results support the idea that large variability in revenues make it
harder to plan ahead and make companies more careful when it comes to paying
out dividends.
Finally, the results show that the size of the largest owner is negatively correlated
with dividend payments. This can be seen as support of the outcome model,
discussed in the literary review, since the minority shareholders pressuring
corporate insiders to disgorge cash have less power if the majority shareholder is
large. The effect is bigger on companies where the largest shareholder own more
than 50% than in companies where the largest shareholder own 50% or less. This
follows theory in regards to the outcome model.
6.3 On the tax reform and its effect on ownership structure
We can reject our H0 of no changes in ownership after the tax reform. We have
found that the size of the largest owner increase after the tax reform, that
aggregated personal ownership decreases and those companies with majority
personal ownership hold more cash on balance sheet than others.
The increase in ownership of the largest owner can be seen as support to the
outcome model. With dividends being more expensive minority owners find it
harder to pressure the majority into disgorging cash, and thus sell their shares to
the majority owner. Again, we will look at alternative explanations of our results.
37
27.08.2012
One very likely reason for the increase in majority ownership is the prior taxation
model called “delingsmodellen”15. “Delingsmodellen” dictated that owners
owning more than 2/3 of a company were to be taxed of their part of the company
income. To avoid this tax many owners decided to divide the ownership of their
company among family members and friends. After the tax reform
“delingsmodellen” was no longer valid and ownership was returned back to the
“real owner”.
We find that the aggregated personal ownership is reduced after the tax reform. A
likely reason for this is that more shell companies are established in order to
postpone the taxation of dividend payments to whenever the person behind the
company feels like taking the money out.
Another interesting finding is that companies with majority personal ownership
hold more cash on their balance sheet after the tax reform than companies with
minority personal ownership. This is also in support of the outcome model
6.4 On the tax reform and its effect on cash flow between firms and private
investors.
Based on our discussions above on hypothesis 2, 3 and 4, it becomes clear that the
cash reform has had an effect on the cash flows between firms and private
investors. Dividends have decreased significantly, cash on the balance sheet has
increased, and the ownership structure is significantly changed as an effect of the
tax reform. To determine whether or not the effects are a result of short term tax
planning or if this is a long term effect one would have to have a larger time
period after the tax reform. Some changes are however likely to be long term.
Dividends should continue to be lower than before the tax reform, at least since it
is now good for companies with concentrated ownership to pay some of what
were earlier dividends as salaries. We also believe that the effects seen on
15
http://www.regjeringen.no/nb/dep/fin/dok/nouer/2003/nou-2003-9/10/2.html?id=381907
38
27.08.2012
ownership will last. Aggregated personal ownership will remain lower and the
majority owner will remain larger than before the reform, due to increased use of
shell companies, the removal of “delingsmodellen” and maybe also due to the
effects put forward by the outcome model.
7. Conclusions
This paper describes the effects of the Norwegian tax reform of 2006 on cash
flows from firms to private investors. The tax reform is also a good case to study
agency problems, since we can see how owners react when facing an upward shift
in cash mobility costs.
A similar study has been done by Alstadsæter and Fjærli in 2009. In our research
we have three additional years after the tax reform to consider and we are thus
better able to conclude on the long term effects of the tax reform. Our research
differs further by looking at the adjusted pay-out ratio instead of dividends to get a
better picture of transactions between firms and private investors. Also, we focus
on changes in ownership as a consequence of the tax reform.
Our most important finding is the sharp drop in dividends after the tax reform that
lasts through 2009. Our research adds to Alstadsæter and Fjærli by showing that
the reduced dividends cannot solely be explained by investors after the tax reform
paying out paid in capital instead of dividends. In addition our research looks at
changes in cash holdings and ownership structure. We find that the tax reform has
affected ownership. We find a reduction in aggregate personal ownership and also
a shift from minority owners towards majority owners. Our results can thus be
seen as support to the outcome model. Minority owners sell their shares due to the
higher cost of paying dividends making it even harder to get majority owners to
disgorge cash. Lastly we find an increase in cash holdings after the tax reform.
We show that cost of cash mobility affect capital allocation decisions, firms pay
less dividends and hold more cash, again affecting ownership structure in firms.
With more cash on the balance sheet chances are that managers will find positive
NPV projects and fall into what Warren Buffet describes as the institutional
imperative.
39
27.08.2012
However, we cannot conclude on whether the government goal of introducing the
tax reform without affecting business investments has been successful or not.
Further research can be done on whether the effects seen on dividends, cash
holdings and ownership after the tax reform affect investment decisions in
companies.
40
27.08.2012
References
Alstadsæter, A., and E. Fjærli. 2009. "Neutral taxation of shareholder income?
Corporate responses to an announced dividend tax." International Tax and Public
Finance no. 16 (4):571-604.
Bates, T.W., K.M. Kahle, and R.M. Stulz. 2009. "Why do US firms hold so much
more cash than they used to?" The Journal of Finance no. 64 (5):1985-2021.
Berzins, J., Ø. Bøhren, and P. Rydland. 2007. "Corporate finance and governance
in firms with limited liability: Basic characteristics." Center of Corporate
Governance Research.
Berzins, J., Ø. Bøhren, and B. Stacescu. 2011. "Dividends and Stockholder
Conflicts: A Comprehensive Test for Private Firms." Centre for Corporate
Governance Research. Working Paper no. 5/2011
Brüderl, J. 2005. "Panel data analysis." University of Mannheim, viewed no. 25
(02):2009.
Dougherty, C. 2007. Introduction to econometrics: Oxford University Press, USA.
Finandepartementet Meld. St. 11. 2010-2011 “Evaluering av skattereformen
2006”
Greenwald, B.C.N., J. Kahn, P.D. Sonkin, and M. Van Biema. 2004. Value
investing: from Graham to Buffett and beyond: John Wiley & Sons Inc.
Grullon, G., R. Michaely, and B. Swaminathan. 2002. "Are Dividend Changes a
Sign of Firm Maturity?*." The Journal of Business no. 75 (3):387-424.
Hagstrom, R.G. 1997. The Warren Buffett way: Investment strategies of the
world's greatest investor: Wiley.
41
27.08.2012
Jensen, G.R., D.P. Solberg, and T.S. Zorn. 1992. "Simultaneous determination of
insider ownership, debt, and dividend policies." Journal of financial and
Quantitative analysis no. 27 (2):247-263.
Kalcheva, I., and K.V. Lins. 2007. "International evidence on cash holdings and
expected managerial agency problems." Review of Financial Studies no. 20
(4):1087-1112.
Kari, S., H. Karikallio, and J. Pirttilä. 2008. "Anticipating Tax Changes: Evidence
from the Finnish Corporate Income Tax Reform of 2005*." Fiscal Studies no. 29
(2):167-196.
Kari, S., H. Karikallio, and J. Pirttilä. 2009. The Impact of Dividend Taxation on
Dividends and Investment: New Evidence Based on a Natural Experiment:
CESifo, Center for Economic Studies & Ifo Institute for economic research.
Korkeamaki, T., E. Liljeblom, and D. Pasternack. 2010. "Tax reform and payout
policy: Do shareholder clienteles or payout policy adjust?" Journal of Corporate
Finance no. 16 (4):572-587.
Lopez de Silanes, F., R. Vishny, and A. Shleifer. 2000. "Agency problems and
dividend policies around the world." Journal of finance no. 60 (1):1-33.
Nymoen, J. and Woxholt, B. K. 2009. “Aksjonærmodellen” Verdt å vite 08/09:
168 - 171
Opler, T., L. Pinkowitz, R. Stulz, and R. Williamson. 1997. The determinants and
implications of corporate cash holdings. National Bureau of Economic Research.
Redding, L.S. 1997. "Firm size and dividend payouts." Journal of Financial
Intermediation no. 6 (3):224-248.
Rettl, D.A. 2011. "Growth Opportunities, Cash Holdings and Payout Policy."
http://www.danielrettl.com/Rettl_GrowthCash_2011.pdf
42
27.08.2012
Thoresen, T.O. Bø, E.E. Fjørli, E. Halvorsen, E. 2010 “Skattereformen 2006 – har
skattesystemet blitt mer omfordelende?”
Torres-Reyna, O. 2011. "Panel Data Analysis Fixed & Random Effects."
Princeton University, Data and Statistical Services presentation.
Zellner, A. 1962. "An efficient method of estimating seemingly unrelated
regressions and tests for aggregation bias." Journal of the American statistical
Association:348-368.
43
27.08.2012
Attachments
1. Nonparametric test results - means
Test for Equality of Means of RANK1A50
Categorized by values of YRG
Date: 07/20/12 Time: 11:03
Sample: 2000 2009 IF DUMMY=1
Included observations: 413676
Method
df
Value
Probability
413674
390380.9
(1, 413674)
(1, 390381)
-71.82429
-72.85239
5158.729
5307.471
0.0000
0.0000
0.0000
0.0000
df
Sum of Sq.
Mean Sq.
Between
Within
1
413674
1588871.
1.27E+08
1588871.
307.9967
Total
413675
1.29E+08
311.8368
Mean
85.62194
89.59497
87.28381
Std. Dev.
18.16837
16.65149
17.65890
Std. Err.
of Mean
0.037037
0.040030
0.027456
df
Value
Probability
239269
199080.0
(1, 239269)
(1, 199080)
-3.635673
-3.614646
13.21812
13.06567
0.0003
0.0003
0.0003
0.0003
df
Sum of Sq.
Mean Sq.
1
239269
1571.686
28450025
1571.686
118.9039
t-test
Satterthwaite-Welch t-test*
Anova F-test
Welch F-test*
*Test allows for unequal cell variances
Analysis of Variance
Source of Variation
Category Statistics
YRG
2000-2005
2006-2009
All
Count
240640
173036
413676
Test for Equality of Means of RANK150B
Date: 07/20/12 Time: 11:05
Method
t-test
Anova F-test
Welch F-test*
Source of Variation
Between
Within
44
Total
27.08.2012
239270
28451597
118.9100
Mean
40.14277
40.30843
40.20850
Std. Dev.
10.78134
11.08864
10.90459
Std. Err.
of Mean
0.028379
0.035988
0.022293
df
Value
Probability
652628
498523.9
(1, 652628)
(1, 498524)
73.68915
71.07510
5430.091
5051.670
0.0000
0.0000
0.0000
0.0000
df
Sum of Sq.
Mean Sq.
Between
Within
1
652628
4336230.
5.21E+08
4336230.
798.5557
Total
652629
5.25E+08
805.1987
Mean
88.94095
83.70046
86.79127
Std. Dev.
25.72782
31.54379
28.37602
Std. Err.
of Mean
0.041469
0.060965
0.035125
df
Value
Probability
649927
614385.3
(1, 649927)
(1, 614385)
159.4735
176.0851
25431.79
31005.97
0.0000
0.0000
0.0000
0.0000
Category Statistics
YRG
2000-2005
2006-2009
All
Count
144333
94938
239271
Test for Equality of Means of AGGPERSY
Date: 07/20/12 Time: 11:05
Method
t-test
Anova F-test
Welch F-test*
Source of Variation
Category Statistics
YRG
2000-2005
2006-2009
All
Count
384918
267712
652630
Test for Equality of Means of ADJPAYX
Date: 07/20/12 Time: 11:06
Method
t-test
Anova F-test
Welch F-test*
45
27.08.2012
Source of Variation
df
Sum of Sq.
Mean Sq.
Between
Within
1
649927
4501.991
115051.5
4501.991
0.177022
Total
649928
119553.5
0.183949
Mean
0.236240
0.067063
0.166762
Std. Dev.
0.500188
0.268388
0.428893
Std. Err.
of Mean
0.000808
0.000519
0.000532
df
Value
Probability
630977
532078.5
(1, 630977)
(1, 532078)
-58.22754
-57.59241
3390.446
3316.886
0.0000
0.0000
0.0000
0.0000
df
Sum of Sq.
Mean Sq.
Between
Within
1
630977
184.0798
34258.07
184.0798
0.054294
Total
630978
34442.15
0.054585
Mean
0.243388
0.278138
0.257578
Std. Dev.
0.227182
0.241205
0.233635
Std. Err.
of Mean
0.000372
0.000475
0.000294
Category Statistics
YRG
2000-2005
2006-2009
All
Count
383014
266915
649929
Test for Equality of Means of CASHTOTY
Date: 07/20/12 Time: 11:06
Method
t-test
Anova F-test
Welch F-test*
Source of Variation
Category Statistics
YRG
2000-2005
2006-2009
All
Count
373324
257655
630979
46
27.08.2012
2. Nonparametric test results – medians
Test for Equality of Medians of RANK1A50
Date: 07/20/12 Time: 11:07
Method
df
Value
Probability
1
1
1
1
1
63.75787
72.31012
0.000000
2.48E-06
4065.066
5228.753
7677.944
0.0000
0.0000
1.0000
0.9987
0.0000
0.0000
0.0000
Median
100.0000
100.0000
100.0000
> Overall
Median
0
0
0
Mean Rank
196800.2
220798.6
206838.5
df
Value
Probability
1
1
1
1
1
5.350004
5.580541
89.75836
89.67919
28.62254
31.14244
901.5214
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
Median
42.86000
45.00000
44.00000
> Overall
Median
70658
48356
119014
Mean Rank
119023.3
120567.5
119636.0
Wilcoxon/Mann-Whitney
Wilcoxon/Mann-Whitney (tie-adj.)
Med. Chi-square
Adj. Med. Chi-square
Kruskal-Wallis
Kruskal-Wallis (tie-adj.)
van der Waerden
Category Statistics
YRG
2000-2005
2006-2009
All
Count
240640
173036
413676
Mean Score
-0.141969
0.027435
-0.071109
Test for Equality of Medians of RANK150B
Date: 07/20/12 Time: 11:08
Method
Med. Chi-square
Kruskal-Wallis
van der Waerden
Category Statistics
YRG
2000-2005
2006-2009
All
Count
144333
94938
239271
Mean Score
-0.057515
-0.047117
-0.053390
Test for Equality of Medians of AGGPERSY
Date: 07/20/12 Time: 11:08
47
27.08.2012
Method
df
Value
Probability
1
1
1
1
1
46.99993
58.73252
0.000000
1.58E-06
2208.993
3449.509
10430.78
0.0000
0.0000
1.0000
0.9990
0.0000
0.0000
0.0000
Median
100.0000
100.0000
100.0000
> Overall
Median
0
0
0
Mean Rank
335456.4
313172.6
326315.5
df
Value
Probability
1
1
1
1
1
147.5322
199.9709
39130.43
39129.24
21765.74
39988.35
45990.25
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
Median
0.000000
0.000000
0.000000
> Overall
Median
121313
28476
149789
Mean Rank
353627.1
283835.8
324965.0
df
Value
Probability
1
1
1
55.21012
55.21057
2171.696
2171.457
3048.158
0.0000
0.0000
0.0000
0.0000
0.0000
Med. Chi-square
Kruskal-Wallis
van der Waerden
Category Statistics
YRG
2000-2005
2006-2009
All
Count
384918
267712
652630
Mean Score
-0.022912
-0.142085
-0.071798
Test for Equality of Medians of ADJPAYX
Date: 07/20/12 Time: 11:09
Method
Med. Chi-square
Kruskal-Wallis
van der Waerden
Category Statistics
YRG
2000-2005
2006-2009
All
Count
383014
266915
649929
Mean Score
0.223693
-0.129779
0.078528
Test for Equality of Medians of CASHTOTY
Date: 07/20/12 Time: 11:09
Method
Med. Chi-square
Kruskal-Wallis
48
van der Waerden
27.08.2012
1
1
3048.207
3036.099
0.0000
0.0000
Median
0.175000
0.217765
0.191489
> Overall
Median
177547
137913
315460
Mean Rank
304972.5
330729.1
315490.0
Category Statistics
YRG
2000-2005
2006-2009
All
Count
373324
257655
630979
Mean Score
-0.054744
0.085292
0.002439
49
27.08.2012
3. Panel data regression – cash holdings
Dependent Variable: CASHTOTY
Method: Panel EGLS (Cross-section random effects)
Date: 07/20/12 Time: 11:15
Periods included: 9
Cross-sections included: 50636
Total panel (unbalanced) observations: 179627
Swamy and Arora estimator of component variances
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RANK1A50
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
-0.000152
0.031253
-7.42E-06
-0.146578
-0.005004
0.219645
-0.005988
0.030067
0.003893
0.066332
0.065507
-0.048532
-0.058059
0.063353
0.069186
-0.019032
-0.004701
0.006847
-0.005585
0.378584
3.53E-05
0.000749
4.93E-05
0.002473
0.000538
0.002332
0.001662
0.000857
0.003621
0.004594
0.003669
0.006910
0.003380
0.002196
0.003662
0.004032
0.003803
0.002448
0.002059
0.008486
-4.291596
41.73559
-0.150403
-59.27806
-9.302312
94.19058
-3.601919
35.08347
1.075147
14.43877
17.85251
-7.023740
-17.17626
28.84704
18.89484
-4.719745
-1.236222
2.797017
-2.712420
44.61477
0.0000
0.0000
0.8804
0.0000
0.0000
0.0000
0.0003
0.0000
0.2823
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2164
0.0052
0.0067
0.0000
Effects Specification
S.D.
Cross-section random
Idiosyncratic random
0.168675
0.131724
Rho
0.6212
0.3788
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.094170
0.094075
0.134630
982.7385
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.107986
0.144103
3255.441
1.374536
Unweighted Statistics
R-squared
Sum squared resid
0.168953
8756.958
Mean dependent var
Durbin-Watson stat
0.308879
0.522036
Date: 07/20/12 Time: 11:16
Periods included: 9
50
27.08.2012
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RANK150B
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
-5.96E-05
0.030553
-1.98E-05
-0.171046
-0.004127
0.232871
-0.005657
0.027017
0.017704
0.067748
0.067807
-0.014543
-0.066875
0.072068
0.092111
-0.009857
-0.014296
0.004908
-0.007570
0.373021
8.05E-05
0.000954
3.65E-05
0.003361
0.000712
0.003124
0.002089
0.001043
0.004645
0.005399
0.004229
0.013273
0.004018
0.002811
0.004799
0.004391
0.004438
0.003021
0.002598
0.011135
-0.740852
32.03779
-0.543940
-50.89185
-5.800157
74.54019
-2.708787
25.90843
3.811671
12.54860
16.03319
-1.095724
-16.64583
25.64205
19.19458
-2.244875
-3.221365
1.624603
-2.913409
33.50020
0.4588
0.0000
0.5865
0.0000
0.0000
0.0000
0.0068
0.0000
0.0001
0.0000
0.0000
0.2732
0.0000
0.0000
0.0000
0.0248
0.0013
0.1043
0.0036
0.0000
S.D.
0.163957
0.120539
Rho
0.6491
0.3509
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.109149
0.108980
0.123232
642.5930
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.100928
0.132928
1513.277
1.412089
R-squared
Sum squared resid
0.189693
4399.604
Mean dependent var
Durbin-Watson stat
0.301354
0.498966
Date: 07/20/12 Time: 11:34
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
AGGPERSY
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
0.000119
0.030736
-1.10E-05
-0.152479
-0.004457
0.222443
-0.005310
1.34E-05
0.000588
2.98E-05
0.001980
0.000429
0.001861
0.001343
8.944387
52.23628
-0.368701
-77.00009
-10.39459
119.5395
-3.955226
0.0000
0.0000
0.7124
0.0000
0.0000
0.0000
0.0001
51
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
0.029779
0.008252
0.065056
0.063149
-0.043208
-0.061868
0.063705
0.073662
-0.014056
-0.008322
0.004680
-0.006581
0.351244
27.08.2012
0.000660
0.002896
0.003577
0.002811
0.006088
0.002610
0.001744
0.002954
0.003030
0.002938
0.001926
0.001624
0.006411
45.12356
2.849858
18.18523
22.46625
-7.096865
-23.70481
36.52142
24.93301
-4.639199
-2.832103
2.430358
-4.052427
54.78353
0.0000
0.0044
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0046
0.0151
0.0001
0.0000
S.D.
0.166243
0.128807
Rho
0.6249
0.3751
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.097616
0.097555
0.131660
1588.947
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.103071
0.140889
4837.693
1.369028
R-squared
Sum squared resid
0.174129
13180.54
Mean dependent var
Durbin-Watson stat
0.306179
0.511390
52
27.08.2012
4. Panel data regression – dividends
Dependent Variable: ADJPAYX
Date: 07/20/12 Time: 11:11
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
AGGPERSY
CASHTOTY
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
0.000381
0.311062
-0.000215
0.529416
-0.007464
0.222316
-0.047650
-0.233121
-0.036043
-0.051311
0.006231
0.119587
0.033369
0.012631
-0.017238
-0.002117
0.026539
0.005910
0.013021
0.199077
3.67E-05
0.004396
6.69E-05
0.005000
0.000870
0.005354
0.002101
0.001926
0.005468
0.006522
0.005533
0.012352
0.005448
0.003809
0.005499
0.005720
0.005613
0.004003
0.003650
0.013553
10.36493
70.76800
-3.207765
105.8832
-8.576773
41.52379
-22.68204
-121.0589
-6.592073
-7.867823
1.126258
9.681832
6.125308
3.315571
-3.134915
-0.370013
4.728076
1.476284
3.567315
14.68892
0.0000
0.0000
0.0013
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2601
0.0000
0.0000
0.0009
0.0017
0.7114
0.0000
0.1399
0.0004
0.0000
S.D.
0.113996
0.458615
Rho
0.0582
0.9418
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.140984
0.140926
0.466009
2410.735
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.223537
0.501871
60606.76
1.927890
R-squared
Sum squared resid
0.146176
64536.53
Mean dependent var
Durbin-Watson stat
0.261023
1.810991
Date: 07/20/12 Time: 11:13
Periods included: 9
53
27.08.2012
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RANK150B
CASHTOTY
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
6.14E-05
0.325849
-0.000168
0.521362
-0.000262
0.279476
-0.050992
-0.229609
-0.025374
-0.044079
-0.007642
0.120748
0.051816
0.002259
-0.046642
0.003252
0.035209
0.010297
0.023465
0.103475
0.000160
0.007532
8.34E-05
0.008550
0.001469
0.009196
0.003443
0.003134
0.009179
0.010297
0.008636
0.027955
0.008567
0.006225
0.009329
0.008741
0.008820
0.006482
0.005944
0.023414
0.384759
43.26080
-2.019423
60.97920
-0.178293
30.39152
-14.81238
-73.25328
-2.764350
-4.280651
-0.884869
4.319404
6.048420
0.362854
-4.999769
0.371965
3.992094
1.588399
3.947767
4.419360
0.7004
0.0000
0.0434
0.0000
0.8585
0.0000
0.0000
0.0000
0.0057
0.0000
0.3762
0.0000
0.0000
0.7167
0.0000
0.7099
0.0001
0.1122
0.0001
0.0000
S.D.
0.122653
0.448467
Rho
0.0696
0.9304
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.137937
0.137772
0.456696
839.1898
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.223237
0.490981
20783.93
1.957337
R-squared
Sum squared resid
0.146051
22413.17
Mean dependent var
Durbin-Watson stat
0.264214
1.815978
Date: 07/20/12 Time: 11:14
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RANK1A50
CASHTOTY
GROWTHREV
LEVPO
-0.000550
0.303861
-0.000300
0.534928
6.93E-05
0.005402
0.000110
0.006189
-7.933213
56.24598
-2.723282
86.42749
0.0000
0.0000
0.0065
0.0000
54
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
-0.011572
0.194291
-0.046151
-0.235692
-0.040149
-0.054208
0.011206
0.114895
0.022713
0.017747
0.000534
-0.003578
0.019729
0.005670
0.008648
0.351099
27.08.2012
0.001096
0.006605
0.002634
0.002455
0.006782
0.008354
0.007183
0.013888
0.007045
0.004800
0.006793
0.007503
0.007223
0.005057
0.004613
0.017457
-10.55555
29.41431
-17.52365
-95.99938
-5.919491
-6.488776
1.560205
8.272899
3.224184
3.697149
0.078584
-0.476807
2.731200
1.121284
1.874662
20.11263
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.1187
0.0000
0.0013
0.0002
0.9374
0.6335
0.0063
0.2622
0.0608
0.0000
S.D.
0.111659
0.463580
Rho
0.0548
0.9452
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.142551
0.142461
0.470180
1571.567
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.225194
0.506865
39705.62
1.908747
R-squared
Sum squared resid
0.147156
42111.08
Mean dependent var
Durbin-Watson stat
0.259207
1.800340
55
27.08.2012
5. Panel data regression – ownership
Dependent Variable: AGGPERSY
Date: 07/20/12 Time: 11:18
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
CASHTOTY
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
1.557103
0.902819
-0.006579
-1.733271
-0.885312
1.079009
-0.351370
-7.103292
3.277618
2.130696
-0.690351
4.885802
-1.790684
2.641517
3.569242
1.462166
2.656405
6.543517
3.946051
109.6879
0.245473
0.085040
0.003517
0.270310
0.052513
0.265515
0.144541
0.092368
0.347212
0.418152
0.343614
0.724411
0.321187
0.220744
0.350224
0.366943
0.356450
0.238672
0.208329
0.771244
6.343271
10.61646
-1.870651
-6.412167
-16.85894
4.063838
-2.430935
-76.90168
9.439807
5.095509
-2.009091
6.744514
-5.575199
11.96641
10.19131
3.984721
7.452401
27.41642
18.94144
142.2220
0.0000
0.0000
0.0614
0.0000
0.0000
0.0000
0.0151
0.0000
0.0000
0.0000
0.0445
0.0000
0.0000
0.0000
0.0000
0.0001
0.0000
0.0000
0.0000
0.0000
S.D.
15.82458
19.14114
Rho
0.4060
0.5940
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.028946
0.028880
19.61936
437.8448
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
43.11866
21.97937
1.07E+08
1.653682
R-squared
Sum squared resid
0.015993
1.77E+08
Mean dependent var
Durbin-Watson stat
89.38916
1.012492
Dependent Variable: RANK150B
Date: 07/20/12 Time: 11:18
Periods included: 9
56
27.08.2012
Variable
Coefficient
Std. Error
t-Statistic
Prob.
CASHTOTY
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
-0.079024
-0.068249
0.001195
0.884108
-0.432160
0.771837
-0.395314
0.946457
0.193240
0.863403
-1.680413
-0.842815
-1.530191
-0.448890
-0.967697
-0.041470
-0.143969
0.476678
0.886246
45.53725
0.108282
0.030816
0.001811
0.117156
0.028523
0.106585
0.109989
0.034287
0.185882
0.234781
0.165636
0.550190
0.161885
0.109199
0.198141
0.170627
0.174030
0.118152
0.097171
0.423846
-0.729803
-2.214723
0.659941
7.546439
-15.15126
7.241538
-3.594136
27.60423
1.039585
3.677489
-10.14519
-1.531862
-9.452332
-4.110742
-4.883888
-0.243044
-0.827268
4.034444
9.120440
107.4381
0.4655
0.0268
0.5093
0.0000
0.0000
0.0000
0.0003
0.0000
0.2985
0.0002
0.0000
0.1256
0.0000
0.0000
0.0000
0.8080
0.4081
0.0001
0.0000
0.0000
S.D.
9.399431
3.757148
Rho
0.8622
0.1378
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.012164
0.011976
3.791503
64.58419
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
7.996273
4.738267
1432504.
1.111449
R-squared
Sum squared resid
0.026242
10563965
Mean dependent var
Durbin-Watson stat
40.84087
0.168675
Dependent Variable: RANK1A50
Date: 07/20/12 Time: 11:24
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
CASHTOTY
ADJPAYX
GROWTHREV
LEVPO
LOGREV
-0.509122
-0.199708
0.004425
-0.839382
-0.609873
0.143747
0.043631
0.004028
0.152224
0.036914
-3.541780
-4.577213
1.098337
-5.514119
-16.52140
0.0004
0.0000
0.2721
0.0000
0.0000
57
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
0.043675
-0.280205
3.003375
0.349458
0.777175
-0.469081
2.625291
0.644581
0.259821
1.035093
-0.317076
-0.067262
0.381249
0.191578
92.10424
27.08.2012
0.142381
0.144293
0.050282
0.257401
0.341375
0.252449
0.515839
0.234613
0.147220
0.266885
0.280140
0.263446
0.168327
0.134658
0.541392
0.306749
-1.941925
59.73118
1.357641
2.276602
-1.858126
5.089359
2.747425
1.764854
3.878423
-1.131849
-0.255316
2.264925
1.422698
170.1249
0.7590
0.0521
0.0000
0.1746
0.0228
0.0632
0.0000
0.0060
0.0776
0.0001
0.2577
0.7985
0.0235
0.1548
0.0000
S.D.
15.88874
7.435490
Rho
0.8203
0.1797
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.029217
0.029115
7.441596
284.5050
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
19.47465
10.17921
9946160.
0.872702
R-squared
Sum squared resid
0.020345
55751144
Mean dependent var
Durbin-Watson stat
86.72700
0.168359
58
27.08.2012
6. Panel data regression – personal ownership
Date: 07/20/12 Time: 11:20
Periods included: 9
Variable
Coefficient
Std. Error
t-Statistic
Prob.
DUMNONPE
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
-0.015846
0.030918
-1.08E-05
-0.151398
-0.004630
0.222782
-0.005337
0.031335
0.007938
0.064765
0.062825
-0.043237
-0.062408
0.063317
0.073285
-0.014282
-0.008572
0.004430
-0.006811
0.362527
0.001285
0.000588
2.98E-05
0.001983
0.000429
0.001860
0.001343
0.000682
0.002895
0.003578
0.002810
0.006084
0.002609
0.001744
0.002954
0.003029
0.002938
0.001925
0.001623
0.006252
-12.33582
52.58163
-0.362760
-76.35090
-10.79882
119.7620
-3.975194
45.93089
2.742414
18.10302
22.35654
-7.107221
-23.91642
36.30490
24.80837
-4.715572
-2.918198
2.301599
-4.196239
57.98649
0.0000
0.0000
0.7168
0.0000
0.0000
0.0000
0.0001
0.0000
0.0061
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0035
0.0214
0.0000
0.0000
S.D.
0.166290
0.128788
Rho
0.6251
0.3749
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.097809
0.097748
0.131624
1593.714
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.103001
0.140866
4838.952
1.369488
R-squared
Sum squared resid
0.174316
13187.78
Mean dependent var
Durbin-Watson stat
0.306188
0.511419
Date: 07/20/12 Time: 11:21
Periods included: 9
59
27.08.2012
Variable
Coefficient
Std. Error
t-Statistic
Prob.
DUMPE
ADJPAYX
GROWTHREV
LEVPO
LOGREV
ROAX
STDGREY
YRG
IND10
IND11
IND12
IND13
IND14
IND15
IND16
IND5
IND6
IND8
IND9
C
0.015701
0.030917
-1.08E-05
-0.151392
-0.004630
0.222791
-0.005339
0.015641
0.007933
0.064756
0.062818
-0.043234
-0.062422
0.063304
0.073279
-0.014283
-0.008583
0.004425
-0.006817
0.378231
0.001277
0.000588
2.98E-05
0.001983
0.000429
0.001860
0.001343
0.001252
0.002895
0.003578
0.002810
0.006084
0.002609
0.001744
0.002954
0.003029
0.002938
0.001925
0.001623
0.006357
12.29340
52.58103
-0.363521
-76.34588
-10.80078
119.7656
-3.976215
12.49484
2.740825
18.10074
22.35417
-7.106602
-23.92169
36.29683
24.80615
-4.715830
-2.921920
2.298867
-4.199610
59.49577
0.0000
0.0000
0.7162
0.0000
0.0000
0.0000
0.0001
0.0000
0.0061
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0035
0.0215
0.0000
0.0000
S.D.
0.166289
0.128788
Rho
0.6251
0.3749
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.097806
0.097745
0.131624
1593.660
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.103001
0.140866
4838.980
1.369487
R-squared
Sum squared resid
0.174307
13187.92
Mean dependent var
Durbin-Watson stat
0.306188
0.511416
60
27.08.2012
7. SUR - Before tax reform
System: SYS01
Estimation Method: Seemingly Unrelated Regression
Date: 07/20/12 Time: 10:51
Sample: 2000 2009 IF DUMMY=1 AND YRG=1
Total system (unbalanced) observations 832191
Linear estimation after one-step weighting matrix
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
Coefficient
Std. Error
t-Statistic
Prob.
-0.080364
0.002180
0.584611
-0.093189
-0.000706
0.390948
0.007589
0.044539
0.043439
0.023324
-0.026903
-0.104331
-0.050828
-0.016712
0.069008
-0.032217
-0.055041
103.5638
4.712604
-3.209805
-0.353688
-0.915149
0.001057
-0.288500
3.820899
1.679307
-0.367731
-0.088542
-4.570366
-4.860641
-6.895054
-1.063018
-0.257313
0.337833
0.081426
-0.000271
0.168104
0.011819
-0.338969
-0.038362
-0.047995
-0.027869
-0.074893
0.033773
0.098395
0.052733
0.047370
0.010839
0.053902
0.005819
5.08E-05
0.005256
0.002350
0.000178
0.005494
0.006109
0.006188
0.004426
0.003827
0.006046
0.006500
0.006248
0.023681
0.006544
0.004129
0.006699
0.457916
0.085069
0.187987
0.085492
0.030353
0.224595
0.227915
0.159133
0.133791
0.219794
0.233555
0.224711
0.788241
0.220171
0.143097
0.245418
0.001730
0.000698
1.50E-05
0.001674
0.000714
0.001317
0.001894
0.001903
0.001328
0.001140
0.001847
0.002005
0.001940
0.006621
0.001853
0.001210
-13.81085
42.89301
111.2271
-39.64966
-3.958652
71.15644
1.242275
7.198043
9.814685
6.095159
-4.449998
-16.05121
-8.135216
-0.705708
10.54456
-7.801909
-8.216004
226.1634
55.39755
-17.07466
-4.137074
-30.14995
0.004705
-1.265820
24.01072
12.55173
-1.673065
-0.379105
-20.33883
-6.166442
-31.31678
-7.428668
-1.048470
195.2776
116.6794
-18.09114
100.3959
16.54180
-257.4269
-20.25923
-25.22620
-20.97830
-65.70068
18.28559
49.06520
27.17556
7.154900
5.848889
44.53693
0.0000
0.0000
0.0000
0.0000
0.0001
0.0000
0.2141
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.4804
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.9962
0.2056
0.0000
0.0000
0.0943
0.7046
0.0000
0.0000
0.0000
0.0000
0.2944
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
61
C(50)
0.108036
Determinant residual covariance
27.08.2012
0.002071
52.15402
0.0000
5.109549
Equation: ADJPAYX = C(1) + C(2)*AGGPERSY + C(3)*CASHTOTY + C(4)
*STDGREY + C(5)*GROWTHREV + C(6)*ROAX + C(7)*IND5 + C(8)
*IND6 + C(9)*IND8 + C(10)*IND9 + C(11)*IND10 + C(12)*IND11 +
C(13)*IND12 + C(14)*IND13 + C(15)*IND14 + C(16)*IND15 + C(17)
*IND16
Observations: 214293
R-squared
0.078015 Mean dependent var
0.282534
Adjusted R-squared
0.077946 S.D. dependent var
0.545731
S.E. of regression
0.524031 Sum squared resid
58841.96
Durbin-Watson stat
1.890055
Equation: AGGPERSY = C(18) + C(19)*ADJPAYX + C(20)*CASHTOTY +
C(21)*STDGREY + C(22)*LOGREV + C(23)*IND5 + C(24)*IND6 +
*IND12 + C(30)*IND13 + C(31)*IND14 + C(32)*IND15 + C(33)*IND16
R-squared
90.68700
Adjusted R-squared
23.28166
S.E. of regression
1.68E+08
Durbin-Watson stat
0.415245
Equation: CASHTOTY = C(34) + C(35)*ADJPAYX + C(36)*AGGPERSY +
C(37)*ROAX + C(38)*STDGREY + C(39)*FIXRATC + C(40)*IND5 +
C(41)*IND6 + C(42)*IND8 + C(43)*IND9 + C(44)*IND10 + C(45)*IND11
+ C(46)*IND12 + C(47)*IND13 + C(48)*IND14 + C(49)*IND15 + C(50)
*IND16
R-squared
0.249533
Adjusted R-squared
0.228674
S.E. of regression
11133.75
Durbin-Watson stat
0.641820
62
27.08.2012
8. OLS – Before tax reform
System: SYS01
Estimation Method: Least Squares
Date: 07/20/12 Time: 10:53
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
C(50)
Coefficient
Std. Error
t-Statistic
Prob.
0.056676
0.001141
0.372060
-0.093086
-0.000695
0.453911
-0.000882
0.039925
0.048032
0.021489
-0.028874
-0.093645
-0.035446
-0.005755
0.049490
-0.016366
-0.037523
103.2997
3.135880
-2.056985
-0.467343
-0.890804
0.044301
-0.163575
3.947554
1.758991
-0.359896
-0.226578
-4.624813
-4.821277
-6.725719
-1.047567
-0.241405
0.338590
0.053587
-0.000202
0.181597
0.009777
-0.344212
-0.037955
-0.046567
-0.026366
-0.074590
0.034483
0.098077
0.052910
0.048469
0.013430
0.054831
0.109216
0.005835
5.10E-05
0.005280
0.002355
0.000179
0.005509
0.006120
0.006199
0.004435
0.003835
0.006057
0.006512
0.006259
0.023740
0.006561
0.004138
0.006711
0.458373
0.085155
0.188062
0.085531
0.030384
0.224671
0.227992
0.159193
0.133846
0.219873
0.233643
0.224795
0.788614
0.220278
0.143157
0.245501
0.001734
0.000701
1.50E-05
0.001677
0.000716
0.001322
0.001896
0.001905
0.001331
0.001142
0.001850
0.002008
0.001943
0.006634
0.001857
0.001212
0.002074
9.713586
22.39412
70.46586
-39.52935
-3.874115
82.39274
-0.144169
6.440908
10.83097
5.603440
-4.767236
-14.38119
-5.663288
-0.242408
7.543298
-3.954778
-5.591330
225.3614
36.82548
-10.93782
-5.464023
-29.31805
0.197180
-0.717460
24.79732
13.14187
-1.636839
-0.969763
-20.57344
-6.113606
-30.53289
-7.317596
-0.983316
195.3106
76.42436
-13.46048
108.2638
13.66294
-260.2986
-20.01713
-24.44051
-19.81485
-65.31453
18.64173
48.83714
27.22894
7.305986
7.232101
45.22703
52.65168
0.0000
0.0000
0.0000
0.0000
0.0001
0.0000
0.8854
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.8085
0.0000
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.8437
0.4731
0.0000
0.0000
0.1017
0.3322
0.0000
0.0000
0.0000
0.0000
0.3255
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
63
27.08.2012
5.238464
*IND16
R-squared
0.282534
Adjusted R-squared
0.545731
S.E. of regression
58296.46
Durbin-Watson stat
1.905784
R-squared
90.68700
Adjusted R-squared
23.28166
S.E. of regression
1.68E+08
Durbin-Watson stat
0.408583
*IND16
R-squared
0.249533
Adjusted R-squared
0.228674
S.E. of regression
11075.79
Durbin-Watson stat
0.608330
64
27.08.2012
9. SUR after tax reform
System: SYS02
Date: 07/20/12 Time: 10:55
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
Coefficient
Std. Error
t-Statistic
Prob.
0.044843
-0.000440
0.162975
-0.019120
-8.10E-05
0.175958
-0.013187
0.010653
0.010751
0.003467
-0.009222
-0.014236
0.002515
0.031151
0.012252
0.017918
0.003760
89.02461
-3.795052
6.376104
-0.503428
-0.737162
3.453430
5.691787
10.26786
7.675979
6.048355
4.291570
-0.012420
8.653037
0.345013
5.108869
6.821427
0.344274
0.085979
0.000345
0.184353
-0.004580
-0.381977
-0.041938
-0.044111
-0.026657
-0.084323
0.026044
0.097745
0.059164
0.007662
0.010207
0.057472
0.003188
2.25E-05
0.002879
0.001210
3.92E-05
0.003277
0.003885
0.004106
0.003012
0.002803
0.003839
0.004035
0.003789
0.007188
0.003633
0.002862
0.003836
0.702876
0.243876
0.275450
0.118529
0.045576
0.384988
0.407446
0.290190
0.268186
0.375573
0.389360
0.366808
0.601948
0.338058
0.271125
0.370972
0.002138
0.001623
1.48E-05
0.002158
0.000812
0.001671
0.002629
0.002732
0.001971
0.001855
0.002537
0.002706
0.002541
0.004088
0.002296
0.001856
14.06441
-19.54801
56.60478
-15.80824
-2.064273
53.70098
-3.393848
2.594842
3.568878
1.237049
-2.402569
-3.527977
0.663693
4.333472
3.372682
6.260702
0.980190
126.6577
-15.56139
23.14798
-4.247293
-16.17424
8.970221
13.96944
35.38318
28.62181
16.10433
11.02210
-0.033859
14.37505
1.020573
18.84323
18.38799
161.0196
52.97496
23.35680
85.41584
-5.643626
-228.5862
-15.95292
-16.14758
-13.52619
-45.44468
10.26479
36.12699
23.28515
1.874251
4.446192
30.96855
0.0000
0.0000
0.0000
0.0000
0.0390
0.0000
0.0007
0.0095
0.0004
0.2161
0.0163
0.0004
0.5069
0.0000
0.0007
0.0000
0.3270
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.9730
0.0000
0.3075
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0609
0.0000
0.0000
65
C(50)
0.109839
27.08.2012
0.002540
43.24906
0.0000
2.590226
*IND16
R-squared
0.072324
Adjusted R-squared
0.278844
S.E. of regression
13039.56
Durbin-Watson stat
1.619745
R-squared
85.44732
Adjusted R-squared
29.84899
S.E. of regression
1.87E+08
Durbin-Watson stat
0.850382
*IND16
R-squared
0.284740
Adjusted R-squared
0.242572
S.E. of regression
8426.128
Durbin-Watson stat
0.575268
66
27.08.2012
10. OLS – After the tax reform
System: SYS02
Date: 07/20/12 Time: 10:56
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
C(50)
Coefficient
Std. Error
t-Statistic
Prob.
0.045670
-0.000280
0.098161
-0.019681
-7.96E-05
0.194807
-0.014479
0.010661
0.011276
0.002996
-0.008917
-0.009086
0.010807
0.029719
0.008065
0.024751
0.010503
88.96572
-1.976601
3.315472
-0.480681
-0.689248
3.390393
5.676666
10.30906
7.651950
6.094226
4.517994
0.363770
8.682220
0.200330
5.431759
7.180477
0.361627
0.048274
0.000159
0.191584
-0.005246
-0.384499
-0.041909
-0.042869
-0.024572
-0.083223
0.027010
0.098746
0.059727
0.010404
0.010987
0.059543
0.112045
0.003190
2.25E-05
0.002884
0.001210
3.93E-05
0.003279
0.003887
0.004107
0.003014
0.002804
0.003840
0.004037
0.003790
0.007194
0.003635
0.002863
0.003838
0.703202
0.243923
0.275547
0.118543
0.045600
0.385025
0.407485
0.290220
0.268214
0.375609
0.389400
0.366848
0.602022
0.338095
0.271154
0.371006
0.002140
0.001626
1.48E-05
0.002160
0.000812
0.001674
0.002630
0.002733
0.001972
0.001856
0.002538
0.002707
0.002542
0.004091
0.002297
0.001857
0.002541
14.31546
-12.41422
34.04045
-16.26587
-2.023207
59.41875
-3.725157
2.595596
3.741643
1.068403
-2.322076
-2.250801
2.851171
4.130872
2.218896
8.643825
2.736678
126.5152
-8.103374
12.03235
-4.054920
-15.11519
8.805642
13.93098
35.52153
28.52925
16.22492
11.60244
0.991609
14.42178
0.592524
20.03204
19.35406
169.0061
29.68860
10.75229
88.69486
-6.461140
-229.6771
-15.93628
-15.68636
-12.46221
-44.82805
10.64114
36.48365
23.49756
2.542874
4.783186
32.06893
44.10055
0.0000
0.0000
0.0000
0.0000
0.0431
0.0000
0.0002
0.0094
0.0002
0.2853
0.0202
0.0244
0.0044
0.0000
0.0265
0.0000
0.0062
0.0000
0.0000
0.0000
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.3214
0.0000
0.5535
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0110
0.0000
0.0000
0.0000
67
27.08.2012
2.630900
*IND16
R-squared
0.072324
Adjusted R-squared
0.278844
S.E. of regression
12998.56
Durbin-Watson stat
1.624999
R-squared
85.44732
Adjusted R-squared
29.84899
S.E. of regression
1.86E+08
Durbin-Watson stat
0.851130
*IND16
R-squared
0.284740
Adjusted R-squared
0.242572
S.E. of regression
8398.656
Durbin-Watson stat
0.565249
68
27.08.2012
11. SUR – Entire period
System: SYS03
Date: 07/20/12 Time: 11:01
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
Coefficient
Std. Error
t-Statistic
Prob.
0.312474
0.000687
0.384697
-0.055228
-0.000200
0.306960
-0.002456
0.028345
0.028922
0.016838
-0.019031
-0.062790
-0.027841
0.030417
0.044164
-0.009816
-0.027272
-0.212552
105.1844
3.181728
0.945164
-0.446112
-0.844202
0.797510
1.341473
5.660452
3.299288
1.427530
0.892995
-3.496952
2.203090
-4.752926
0.593591
1.916178
-4.699017
0.274713
0.081052
5.81E-05
0.174196
0.004306
-0.357062
-0.039858
-0.046132
-0.027125
-0.078776
0.031220
0.098652
0.056241
0.015295
0.003926
2.72E-05
0.003145
0.001364
5.72E-05
0.003417
0.003869
0.004002
0.002872
0.002566
0.003825
0.004081
0.003869
0.009622
0.003841
0.002699
0.004016
0.001418
0.398410
0.086802
0.158870
0.070456
0.025881
0.200143
0.206899
0.144110
0.125866
0.195462
0.206072
0.195999
0.437560
0.184927
0.131468
0.205681
0.075854
0.001549
0.000647
1.05E-05
0.001326
0.000536
0.001035
0.001527
0.001558
0.001091
0.000972
0.001482
0.001603
0.001526
0.003321
79.58781
25.29299
122.3125
-40.49258
-3.503133
89.82570
-0.634748
7.082866
10.07078
6.562647
-4.974744
-15.38432
-7.196753
3.161338
11.49948
-3.636743
-6.791505
-149.8997
264.0103
36.65509
5.949300
-6.331786
-32.61895
3.984700
6.483709
39.27875
26.21280
7.303346
4.333408
-17.84166
5.034941
-25.70161
4.515096
9.316244
-61.94787
177.3804
125.2632
5.548611
131.3869
8.034394
-344.8694
-26.10386
-29.60489
-24.86242
-81.03516
21.06200
61.55741
36.86569
4.605396
0.0000
0.0000
0.0000
0.0000
0.0005
0.0000
0.5256
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0016
0.0000
0.0003
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
69
C(50)
C(51)
C(52)
C(53)
0.009782
0.056220
0.109637
0.041609
27.08.2012
0.001408
0.001007
0.001574
0.000576
6.946747
55.84897
69.66550
72.19739
0.0000
0.0000
0.0000
0.0000
4.672875
*IND16 + C(18)*YRG
R-squared
0.188203
Adjusted R-squared
0.458255
S.E. of regression
72961.24
Durbin-Watson stat
1.783727
C(35)*YRG
R-squared
88.57835
Adjusted R-squared
26.24992
S.E. of regression
3.55E+08
Durbin-Watson stat
0.901373
*IND16 + C(53)*YRG
R-squared
0.263869
Adjusted R-squared
0.235070
S.E. of regression
19598.49
Durbin-Watson stat
0.659831
70
27.08.2012
12. OLS – Entire period
System: SYS03
Date: 07/20/12 Time: 11:02
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
C(7)
C(8)
C(9)
C(10)
C(11)
C(12)
C(13)
C(14)
C(15)
C(16)
C(17)
C(18)
C(19)
C(20)
C(21)
C(22)
C(23)
C(24)
C(25)
C(26)
C(27)
C(28)
C(29)
C(30)
C(31)
C(32)
C(33)
C(34)
C(35)
C(36)
C(37)
C(38)
C(39)
C(40)
C(41)
C(42)
C(43)
C(44)
C(45)
C(46)
C(47)
C(48)
C(49)
C(50)
Coefficient
Std. Error
t-Statistic
Prob.
0.373869
0.000293
0.238483
-0.055712
-0.000197
0.349660
-0.006804
0.027339
0.032819
0.016802
-0.018345
-0.052774
-0.013526
0.032537
0.032456
0.004229
-0.012083
-0.210138
105.1706
2.125345
0.304031
-0.484944
-0.805695
0.753817
1.381775
5.725011
3.311653
1.427427
0.890709
-3.367967
2.328219
-4.715580
0.743408
2.077327
-4.867227
0.293565
0.051244
-7.94E-06
0.185367
0.002879
-0.361088
-0.039672
-0.044946
-0.025462
-0.078195
0.031793
0.098639
0.056257
0.017095
0.011326
0.003931
2.72E-05
0.003155
0.001365
5.74E-05
0.003422
0.003872
0.004006
0.002875
0.002569
0.003829
0.004085
0.003872
0.009637
0.003846
0.002703
0.004020
0.001419
0.398543
0.086828
0.158892
0.070464
0.025890
0.200162
0.206918
0.144125
0.125880
0.195482
0.206094
0.196020
0.437624
0.184952
0.131484
0.205701
0.075862
0.001551
0.000649
1.05E-05
0.001327
0.000536
0.001039
0.001528
0.001560
0.001092
0.000973
0.001484
0.001604
0.001527
0.003326
0.001410
95.10126
10.76942
75.59173
-40.80717
-3.429679
102.1815
-1.757202
6.824588
11.41439
6.540400
-4.790399
-12.91769
-3.492957
3.376162
8.439168
1.564975
-3.006138
-148.0669
263.8878
24.47777
1.913440
-6.882113
-31.11988
3.766034
6.677874
39.72245
26.30794
7.302099
4.321857
-17.18175
5.320140
-25.49627
5.653984
10.09876
-64.15898
189.2978
78.92309
-0.757460
139.6534
5.366799
-347.6871
-25.96026
-28.81738
-23.31387
-80.33943
21.42884
61.49682
36.84453
5.139790
8.032623
0.0000
0.0000
0.0000
0.0000
0.0006
0.0000
0.0789
0.0000
0.0000
0.0000
0.0000
0.0000
0.0005
0.0007
0.0000
0.1176
0.0026
0.0000
0.0000
0.0000
0.0557
0.0000
0.0000
0.0002
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.4488
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
71
C(51)
C(52)
C(53)
0.057323
0.110959
0.035854
27.08.2012
0.001008
0.001575
0.000577
56.88209
70.44579
62.15471
0.0000
0.0000
0.0000
4.764614
*IND16 + C(18)*YRG
R-squared
0.188203
Adjusted R-squared
0.458255
S.E. of regression
72520.72
Durbin-Watson stat
1.786690
C(35)*YRG
R-squared
88.57835
Adjusted R-squared
26.24992
S.E. of regression
3.55E+08
Durbin-Watson stat
0.898119
*IND16 + C(53)*YRG
R-squared
0.263869
Adjusted R-squared
0.235070
S.E. of regression
19516.03
Durbin-Watson stat
0.637790
72
27.08.2012
13. Definition of variables
Variable
Definition
adjpayx
aggpersy
Cashtoty
dumnonpe
dumpe
growthrev
Levpo
logrev
Paidinpo
rank150A
rank150B
Retearpo
Roax
stdgrey
Totass
yrg
Adjusted pay-out ratio
Aggregated personal ownership
Dummy equal 1 if yrg=2 and aggpersy is below or equal to 50
Dummy equal to 1 if yrg=2 and aggpersy is above 50%
Revenue growth
Leverage (only positive values included)
Log revenue
Paid in capital (only positive figures)
Largest owner owns less than or equal to 50%
Retained earnings (only positive figures)
Return on assets
Total assets
Dummy variable with the value 1 in the period 00-05 and the value 2 in the period 06-09
73
27.08.2012
14. Empirical distribution test for cash to total assets and adjusted payout
74
27.08.2012
15. Preliminary master thesis
Halvor Melau Sørensen 0904431
Tarje Melau Sørensen 0912899
BI Norwegian Business School - Preliminary Thesis Report
- On the effect of the 2006 Norwegian tax reform on
private investors -
GRA 1900 – Preliminary Thesis Report
Programme:
Master of Science in Business and Economics
Major in Finance
Major in Business Law, Tax, and Accounting
Submission Date:
13.01.2012
Due Date
15.01.2012
Supervisor:
Bogdan Stacescu
Campus – BI Oslo
75
27.08.2012
Acknowledgments
We would like to thank Bogdan Stacescu for invaluable guidance, quick feedback
and thoughtful comments in the process of writing this master thesis. In addition
we are thankful for the data provided by the Centre of Corporate Governance.
Abstract
1. Introduction
The purpose of this Master thesis is to look at the effects of the Norwegian tax
reform of 2006 on the cash flow from firms to private investors16.
The 2006 tax reform introduced a 28%17 tax on dividend payments made by
companies to private individuals. Dividend payments to a limited liability
company18 are not taxed until they are paid out to the owner of that company. In
order to avoid the tax on dividends a lot of investors have created shell companies
where they collect the dividend and reinvest it, rather than receiving the money
privately. The effect of the reform has been that the cost of cash mobility has gone
up. We would like to see how this change affects the capital allocation decisions
of firms, and how those decisions influence private investors.
Thoresen (2010) states that the background for the reform of the tax system was
based on the observation that many people with high incomes got a lower tax base
through the creation of a public company and getting their income through
dividend payments rather than through salary payments, the latter being taxed
progressively up to 55.3%19 and the former previously at a fixed rate of 28%.
After the reform tax on dividend payments have increased to 48%20, while the
16
As we go along specify more clearly what we mean by private investors, do we look at all
private investors or only minority/majority or debt investors?
17
Investors pay the 28% tax rate on profits after deducting a fixed rate determined annually to
protect the equity invested against inflation.
18
Aksjeselskap
19
20
76
27.08.2012
progressive tax on labour was lowered to 47.8%21, effectively evening out the
taxation on dividends and labour.
The intention of the 2006 tax reform, according to Nymoen & Woxholt (2009,
168), was to “increase taxation on high stock market returns without influencing
business investments22.” One of the main reasons why we think it is important to
study the effects of the tax reform on cash flow from firms to investors is to see if
the intentions of the reform came through, or if unintentional effects have
occurred that do influence corporate investments. In the following we outline how
we plan to approach the issue.
We have two main hypotheses.
First:
H0: The tax reform has had no impact on cash flow between firms and private
investors.
H1: The tax reform has had an impact on cash flow between firms and private
investors.
Second:
H0: The tax reform has not increased the cash on company balance sheets.
H1: The tax reform has increased the cash on company balance sheets.
We will do a quantitative analysis to check if companies have made a significant
change in their dividend policies, or in the amount of cash they hold on their
balance sheets as a result of the 2006 Norwegian tax reform on dividends. The
findings of our quantitative analysis will then be discussed with a focus on agency
problems between minority and majority shareholders, and issues of efficient
21
22
We have translated the Norwegian text into English.
77
27.08.2012
capital allocation. The discussion will be based around our findings related to our
hypotheses and our two main research questions outlined below.
We will discuss the effects of our results on the efficiency of capital allocation.
With more cash on the balance sheet, there is a danger that what Warren Buffet
called the institutional imperative (Hagstrom, 2005) makes management invest the
additional cash in inefficient ways, as marginal investment opportunities often
provide a less satisfactory return. In addition, increased cash on the balance sheet
makes management even more important for the company and for investments in
it.
The two research questions we ask are, first, has dividend policy changed
significantly after the 2006 tax reform? The results will be tied to a discussion
related to the “outcome” model looking at how the tax reform may affect the
ability of minority shareholders to force the majority to give up control of some of
the company’s resources through dividend payments.
Second, we ask if the ownership structure in the companies have changed in
favour of majority shareholders as minority shareholders have less access to
company cash in the case of lower dividend payments. Investigating this we try to
understand if the dividend tax reform has shifted the balance of power between
minority and majority interests giving the majority interest more power.
Finding an answer to our hypothesis and corresponding research questions is
important in order to better understand if the 2006 tax reform had unintentional
consequences that may not be optimal for a well-functioning capital market. In
our thesis we focus on the effects related to capital allocation efficiency and the
power of minority shareholders vis-à-vis majority shareholders.
The paper is organized as follows. Section 2 provides a literature review
highlighting the main points of the articles we found to be most relevant to our
thesis research. Section 3 goes through the methodology we have used to arrive at
our results. Section 4 gives an overview of the data we have used. Section 5
presents the results of the analysis we have used to find meaningful information
78
27.08.2012
based on the data discussed in section 4 and the methodology in section 3. The
results are discussed and interpreted in section 6. Finally, in section 7 we conclude
our findings to our hypothesis and research questions.
2. Literature Review
In order to answer our questions it is important to know something about why
dividends are paid out in the first place. A popular idea is that firms signal future
profitability by paying dividends. The idea seems reasonable since stocks tend to
appreciate after raising their dividend and depreciate after cutting dividends.
However, this theory has failed in research trying to predict the future earnings of
a firm using their current dividend policy. Other theories related to the dividend
puzzle usually address the agency problems between inside and outside
shareholders. Outside shareholders prefer dividends since this gives them the
choice as to how the money should be reinvested. If the money stays within the
firm it could be spent on unprofitable projects or on higher salaries to the insiders.
When dividends are paid out, outside investors can choose whether or not they
believe in the future profitability of new projects in the firm, or if they can get a
higher return elsewhere.
La Porta, et.al (1999) has provided further research as to how outside shareholders
get insiders to disgorge cash. They have looked at two frequently used models, the
“outcome” model and the “substitute” model. The “outcome” model predicts that
dividends are paid due to minority shareholders using their legal rights in order to
pressure corporate insiders to disgorge cash. This implies that shareholders in
countries with high shareholder protection are more likely to prefer a dividend
policy that maximizes their return on capital, since the cash is theirs either way. In
countries with low shareholder protection, shareholders will prefer dividends,
since a bird in the hand is worth two in the bush. Good protection of minority
shareholders allows minority shareholders to apply pressure on insiders and
should make dividends higher in such countries. Also, the higher the portion of
minority shareholders the higher should the dividends be. The “substitute” model
leads to the opposite conclusions. It predicts that firms distribute dividends in
order to build a reputation of treating minority shareholders well. This reputation
will make them able to raise external capital on attractive terms in the future. In
79
27.08.2012
countries with low minority shareholder protection minority shareholders have
little else but reputation to rely on and thus dividends should be higher in these
countries. La Porta et al. (1999) studies a sample of 4000 companies from 33
countries with different levels of minority shareholder rights and finds consistent
support for the “outcome” model. In countries with good protection of minority
shareholders dividends are higher and high growth companies pay lower
dividends than low growth companies.
Both Alstadsæter and Fjørli (2009) and Kari et. Al (2008) looks at the effects on
dividends when anticipating changes in dividend taxation and just after
implementation of changes in dividend taxation. Both start their analysis by
looking at the two dominant views in regards to dividend taxation. The so called
“old view”, supported by Harberger (1962), Feldstein (1970) and Poterba and
Summers (1985), predicts that a change in dividend taxation affects both
investments and dividends. It is assumed that the marginal source of financing of
investments is new share issues. According to Harberger (1962, 1966)23 dividend
taxation distorts the investment decisions and so might prevent an optimal
allocation of capital. The “new view”, developed by King (1974), Auerbach
(1979) and Bradford (1981), argues that dividend taxation affects share values
only and should be neutral with respect to investment and dividend decisions.
This view assumes that the marginal source of financing is profits and that
dividends are paid of what is left after investments. According to the new view
only temporarily changes in dividend taxation will affect dividend and investment
decisions through the timing of dividends.
Alstadsæter and Fjærli (2009) look at dividend pay-outs of Norwegian listed firms
in the period 1999 – 2006. In this period they examine the effects of both the
temporary dividend tax in 2001 and the permanent shareholder income tax in
2006. From the table below one can clearly see effects of expected tax reforms
on dividends. In 2000 the first signal of increased future tax on dividends came
when the parliament approved a temporary tax on capital gains and dividends on
23
Taken from the article by Alstadsæter, the info on who is behind the new and old view is taken
from Kari et. Al (2009)
80
27.08.2012
respectively 28% and 11% (above a threshold) was applied. After 2001 a
committee was appointed and presented its recommendations in 2003, these were
decided and implemented as of 1. January 2006.
Received dividends by households in Billion NOK, 1993-2007. Source Statistics
Norway (Alstadsæter)
Alstadsæter and Fjørli (2009) find that the timing of dividends payments is very
sensitive to future changes in taxation and especially in companies with
concentrated ownership. Companies reduce cash and increase borrowing in order
to have dividends taxed at the low levels in 2005 and prior years instead of the
higher rates as of 2006. A reason for a higher sensitivity among companies with
concentrated ownership is said to be the possibility to pay out retained earnings
and then immediately reinvest this money as paid in capital, which can be paid out
at a later point without being subject to taxes.
Another important finding from Alstadsæter and Fjørli (2009) is that dividends
continue to be low in 2007. According to the authors this might be explained to
some extent by the repayment of paid-in capital, which replaces dividends for a
short period. If this is the case dividends should return to “normal” at some point.
81
27.08.2012
Kari et al. (2008) finds similar results when looking at the Finnish corporate
income tax reform of 2005. The Finnish tax reform has some differences from the
Norwegian one. Firstly, the Finnish tax reform uses a partial relief method of
dividend taxation which means that only 70% of dividends are included in the
recipient’s taxable capital income. Secondly, non-listed companies can make taxexempt dividends up to a ceiling of 90 000 euros. Amounts above 90 000 euros
are taxed after the main rule. Before the tax reform Finnish corporations were
paying 29 percentage taxes on capital income and profits while the top marginal
tax rate (MTR) was 55 percentages. After the tax reform companies affected by
the reform paid 40.5 percentages on distributed profits.
Kari et al. (2008) looks at the period 1999-2004 and use the whole population of
firms that pay taxes in Finland. They find that dividend pay-outs are significantly
increased prior to the reform and as Alstadsæter and Fjørli (2009) they find a
relation between the increased dividends and increased debt. The increase in debt
was only noted in non-listed firms and not in listed firms that may find other ways
to finance their dividends. Another interesting finding from Kari et. Al (2008) is
that the investment activity remained unaffected for both listed and non-listed
firms in general. This is supportive of the “new view” but holds only when
revenue is used as weight. Applying the same weight on all companies however,
they find statistically negative effects on investments as a consequence of the tax
change.
Finally Kari et al (2008) finds evidence of tax planning in the sense that more
companies started distributing dividends up to the maximum level of tax exempt
dividends of 90 000 euros.
Kari et al (2009) does further research on the Finnish tax reform. They collect data
for all Finnish firms paying tax in the period 1999-2006 and use differences- in
differences estimation and matching methods in order to further investigate
dividend and investment responses to the newly implemented tax reform. They
find that dividends tend to be abnormally low after the reform. This however, can
still be the effect of abnormally large dividend distributions in the anticipatory
phase. This leads to further confirmation of the results from Alstadsæter and Fjørli
82
27.08.2012
(2009) and Kari et al (2008) anticipating that tax changes have a large impact on
the timing of dividends.
Korkeamaki et al (2009) has done further research on the Finnish tax reform and
studied the effects on shareholder clienteles and the pay-out policy of firms. Since
different investors were affected differently as a consequence of the reform it
gives insight as to how firms change their payout policy after their largest
shareholders wishes and/or how shareholders change their positions.
Further there are still no indications that investments decline more in firms
affected by the new dividend tax. This can be regarded as support to the “new
view” even though the period after the reform is still very short and one should be
careful drawing any conclusions.
Kalcheva and Lins (2003) look at the link between cash holdings and managerial
agency problems in detail. Whether cash on the balance sheet is a good thing or a
bad thing depends on how it is put to use. They find that minority shareholders (p
1) “discount the value of firms with a combination of expected managerial
entrenchment and high cash balances or no dividend payments, and that these
discounts are more pronounced in countries where minority shareholder rights are
the weakest.” Investors are uneasy about management controlling a large cash
holding. This attitude is similar to the one stated by Warren Buffet as part of what
he sees as the institutional imperative where he claims that what often happens in
organizations is that (Hagstrom, 2005) “just as work expands to fill available time,
corporate projects or acquisitions will materialize to soak up available funds,
[and] any business craving of the leader, however foolish, will quickly be
supported by detailed rate-of-return and strategic studies prepared by his troops.”
With a large cash holding, the return on the money put to use is likely to drop as
capital is invested in increasingly risky or unprofitable projects.
However, as Kalcheva and Lins writes, Myers (1984) and Almeida, Campello,
and Weisbach (2003) argue that a large cash holding is necessary in order to
ensure that positive NPV projects can be financed even when cash flow is low
without having to turn to expensive external funding. On the other side the authors
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show that Easterbrook (1984) and Jensen (1986) claim that investors will prefer
companies to not hold large amounts of cash due to the danger that managers
might be tempted to overinvest and spend money on projects with negative NPV,
benefitting the managers at the expense of shareholders. The fact that investors
discount large cash holdings at companies with entrenched management when
assessing the value of a company, indicate that the argument of Easterbrook and
Jensen has validity. The argument is further supported by Blanchard, Lopez-deSilanes, and Schleifer (1994) and Harford (1999) (p 2) both documenting “a
tendency for managers to spend large holdings of cash in an inefficient manner.”
We will in this thesis see if the tax reform increases the incentives to hold cash on
the balance sheet rather than paying it out, and discuss the effects on probable
investment return for companies and shareholders.
Before the 2006 Norwegian tax reform there were large differences in the
marginal tax rates on capital and labour income which led business owners to
reclassify labour income into capital income in order to pay less tax. To deal with
this “loophole” in the old tax reform was the main motivation behind the 2006
Norwegian tax reform. Thoresen et al (2010) asks if the 2006 Norwegian tax
reform has had the intended effect and increased redistribution. The data used in
this test is income and tax information for the entire Norwegian population in the
years 2000-2008. The method used allows for a separation of horizontal and
vertical effects, where horizontal equality refer to equal treatment of every person,
while the vertical effect shows that the tax capacity increases disproportionately
with the taxation.
In 2004, 95% of total dividends in Norway were paid out to the 10% richest.
Thoresen et al shows that after the reform a smaller part of total income for the
10% richest is due to dividends. Since a higher percentage of their income now
come from the higher taxed labour income the redistribution increases. The fact
that dividends were timed to be paid out before the reform reduces the effect, but
this will be a single period effect. As expected the reduced surtax has the opposite
effect, but not enough to counteract the effect from the increased tax on capital
income. To conclude, Thoresen et al (2010) finds that the tax reform has had the
intended effect and reduced the horizontal inequality.
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3. Methodology
We will use panel data regression analysis to answer our research questions.
4. Data
The data used in the analysis comes from the Centre for Corporate Governance
Research (CCGR). Berzins, Bøhren, & Rydland (2008) outline the filters used to
screen the companies in the database; first, all non-limited liability firms have
been filtered out. Second, filters have been used to keep only companies with
positive sales and assets. Third, companies that do not pass non-negativity on
different accounting items have been filtered out. Fourth, consistency restrictions
between a sum and its components have been used. Finally, and most importantly,
filters to take away companies without employees reduced the sample size by
about 30%.
Berzins, Bøhren & Rydland (2008) also show that 99.8% of the firms are nonlisted, while 0.2% is listed companies. The data on the companies go from the
year 2000 to 2009. The amount of firms in the data sample has increased from
121325 in 2000 to 182818 in 2009. The trend is clearly that the total amount of
companies in the data is increasing over time.
In order to check our hypotheses and research questions we have received access
to 20 variables from the CCGR database. These variables are24 (9) revenue, (105)
dividends, (76) bank deposits, cash in hand, etc, (63) fixed assets, (78) current
assets, (109) current liabilities, (19) results of operations, (86) retained earnings,
(82) paid-in capital, (14011) sum % equity held by owner with rank 1, (14019)
aggregated fraction held by personal owners, (219) aggregated fraction held by
personal owners, (11103) industry codes level two, (30) other interest expenses,
(14507) is independent, (14025) Herfindahl, (14029) share owned by owners with
more than 10% share, (80) own shares, and (14012) sum % equity held by owner
with rank 2.
24
The numbers in parenthesis indicate the item number of the variable in the data set.
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5. Results
6. Discussion
7. Conclusions
References
Attachments
86

On the effect of the 2006 Norwegian tax reform on cash flows from

Transcription

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