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1 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: Due Date Supervisor: Bogdan Stacescu Campus BI Oslo 1

2 CONTENT ACKNOWLEDGMENTS... 4 ABSTRACT INTRODUCTION LITERATURE REVIEW AGENCY PROBLEMS AS A REASON FOR DIVIDEND PAYMENTS EVIDENCE FROM OTHER STUDIES ON TAX REFORMS CASH HOLDINGS AND AGENCY PROBLEMS REASONS FOR IMPLEMENTING A NEW TAX REFORM IN NORWAY DATA METHODOLOGY DATA STRUCTURING AND VARIABLE CREATION NONPARAMETRIC TEST PANEL DATA REGRESSION Random effects versus fixed effects panel data regression Data structuring to run panel data regressions SEEMINGLY UNRELATED REGRESSION Seemingly unrelated regression model theory System of equations RESULTS RESULTS OF NONPARAMETRIC TESTS Effect on cash holdings Effect on dividends Effect on ownership RESULTS OF PANEL DATA REGRESSION Effects on cash holdings Effect on dividends Effect on ownership RESULTS OF SEEMINGLY UNRELATED REGRESSIONS Effect on cash holdings Effect on dividends Effect on ownership DISCUSSION ON THE TAX REFORM AND ITS EFFECT ON CASH HOLDINGS ON THE TAX REFORM AND ITS EFFECT ON DIVIDENDS ON THE TAX REFORM AND ITS EFFECT ON OWNERSHIP STRUCTURE

3 6.4 ON THE TAX REFORM AND ITS EFFECT ON CASH FLOW BETWEEN FIRMS AND PRIVATE INVESTORS CONCLUSIONS REFERENCES ATTACHMENTS Nonparametric test results - means Nonparametric test results medians Panel data regression cash holdings Panel data regression dividends Panel data regression ownership Panel data regression personal ownership SUR - Before tax reform OLS Before tax reform SUR after tax reform OLS After the tax reform SUR Entire period OLS Entire period Definition of variables Empirical distribution test for cash to total assets and adjusted payout Preliminary master thesis

4 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. 4

5 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. 5

6 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 investors 1. The 2006 tax reform introduced a 28% 2 tax on dividend payments made by companies to private individuals. Dividend payments to a limited liability company 3 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 investments 7. 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 Thoresen, 2010, p 5. 6 Thoresen, 2010, p 5. 7 We have translated the Norwegian text into English. 6

7 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 H 0 : The tax reform has had no impact on cash flow between firms and private investors. o H 1 : The tax reform has had an impact on cash flow between firms and private investors. Second: o H 0 : The tax reform has not increased the cash on company balance sheets. o H 1 : The tax reform has increased the cash on company balance sheets. Third: 7

8 o H 0 : Dividend policy has not changed significantly after the 2006 tax reform. o H 1 : Dividend policy has changed significantly after the 2006 tax reform. Fourth: o H 0 : Ownership structure in companies has not changed in favour of majority shareholders as a consequence of the reform. o H 1 : 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 8

9 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 9

10 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 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 10

11 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 In this period they examine the effects of both the temporary dividend tax in 2001 and the permanent shareholder income tax in 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 Graph 1: Received dividends by households in Billion NOK, Source Statistics Norway (Alstadsæter and Fjærli (2009)) 11

12 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 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 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 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 euros. Amounts above 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 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, 12

13 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 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 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 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 13

14 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 14

15 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 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 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 15

16 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 The amount of firms in the data sample has increased from in 2000 to in 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 are 8 (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. 16

17 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 observations of independent firms we have reduced our working sample to 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 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 17

18 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. 18

19 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 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. 19

20 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) 20

21 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 Industry 1 Basic agriculture Industry 2 Forestry Industry 3 Fishing Industry 4 Mining and oil Industry 5 Light industry Industry 6 Heavy industry Industry 7 Utilities Industry 8 Building Industry 9 Retail and wholesale Industry 10 Transport Industry 11 Tourism Industry 12 Publishing, media, IT, telecom Industry 13 Financials Industry 14 Real estate Industry 15 Services Industry 16 Public administration, health and edu. Industry 17 Gambling Industry 18 Extraterritorial Table 1: Industry overview In our panel data regression we use the industry variables with more than 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 21

22 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 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 H 0 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. 22

23 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 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): y it = β 1 x it + v i + ε it Where the elements of the equation are, again following Torres-Reyna (p 10): y it is the dependent variable entity i, at time t β 1 is the coefficient of the independent variable x it is an independent variable entity i, at time t 23

24 v i is the unknown intercept of each entity i ε it 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: y it = β 1 x it + v i + u it + ε it Where u it is the between entity error and ε it 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 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. 24

25 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 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. y it = x it β 1 + ε it, i = 1,..., m 10 Further, the model can be written in vector form as: y i = X i β 1 + ε i, i = 1,..., m 11 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. 11 Equation is taken from Wikipedia page on seemingly unrelated regression. 25

26 With the system in place we move on to set up our own particular system of equations, and discuss the instrumental variables we use 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 fashion Dividends = Ownership + Cash to total assets + Risk + Profitability Instrumental variables = Revenue growth and industry variables 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 26

27 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 Another effect amplifying the drop in dividends after the tax reform is that large companies implemented IFRS in According to IAS 10 proposed dividends are to be booked directly against equity and are not shown as debt. 27

28 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 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. 28

29 Equality of Medians Equality of Means Variables Coefficient Median before Median after Coefficient Mean before Mean after Cash to total assets 55,21 (0,00) 0,1750 0, ,23 (0,00) 0,2434 0,2781 Adjusted pay-out 147,53 (0,00) 0,0000 0, ,47 (0,00) 0,2362 0,0671 Largest owner own more than 50% 63,76 (0,00) 100, ,0000-3,64 (0,00) 85, ,5950 Largerst owner own 50% or below 5,35 (0,00) 42, , ,82 (0,00) 40, ,3084 Aggregate personal ownership 46,99 (0,00) 100, , ,69 (0,00) 88, ,7005 Table 2: Results of a nonparametric test summarized (Attachments 1 and 2) Effect on cash holdings Based on our results we reject H 0 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% Effect on dividends Based on our results we reject H 0 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% Effect on ownership Based on our results we reject H 0 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. 29

30 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 Effects on cash holdings Based on our panel data results we also reject H 0 the tax reform has increased the cash on company balance sheets. Cash to total assets Independent variables Rank 150B Rank 150A Aggpersy Dumpe Dumnonpe Adjusted pay-out 0,0306 (0,000) 0,0312 (0,000) 0,0307 (0,000) 0,0309 (0,000) 0,0309 (0,000) Revenue growth -1,98E-05 (0,587) -7,42E-06 (0,880) -1,10E-05 (0,712) -1,08E-05 (0,716)-1,08E-05 (0,717) 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) Largest owner own more than 50% - -0,0002 (0,000) - - Largerst owner own 50% or below -5,96E-05 (0,459) Aggregate personal ownership - - 0,0001 (0,000) - Personal ownership > 50% 0,0157 (0,000) Personal ownership =< 50% -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 Effect on dividends Based on our results we reject H 0 which states that dividend policies has not changed significantly after the 2006 tax reform. 30

31 Adjusted pay-out Independent variables Rank 150B Rank 150A Aggpersy Cash to total assets 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) Standard deviation of revenue growth -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) Largest owner own more than 50% - -0,0005 (0,000) - Largerst owner own 50% or below 6,14E-05 (0,700) - - Aggregate personal ownership - - 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 Effect on ownership Based on our results we reject H 0 which states that ownership structure in companies has not changed in favour of majority shareholders as a consequence of the reform. Independent variables Largest owner > 50% Largest owner =< 50% Agg. personal ownership Cash to total assets -0,5091 (0,000) -0,0790 (0,466) 1,5571 (0,000) 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 3,0034 (0,000) 0,9465 (0,000) -7,1033 (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 31

32 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 Effect on cash holdings Based on our results we reject H 0 that the tax reform has not increased the cash on company balance sheets. C/A (before) C/A (after) C/A (together) OLS SUR OLS SUR OLS SUR Adjusted pay-out 0,0536 (0,000) 0,0814 (0,000) 0,0483 (0,000) 0,0860 (0,000) 0,0512 (0,000) 0,0811 (0,000) Return on assets 0,1816 (0,000) 0,1681 (0,000) 0,1916 (0,000) 0,1843 (0,000) 0,1854 (0,000) 0,1742 (0,000) Fixed assets ratio -0,3442 (0,000) -0,3390 (0,000) -0,3845 (0,000) -0,3820 (0,000) -0,3611 (0,000) 0,1742 (0,000) Standard deviation of revenue growth 0,0010 (0,000) 0,0118 (0,000) -0,0052 (0,000) -0,0045 (0,000) 0,0029 (0,000) 0,0043 (0,000) Aggregate personal ownership -0,0002 (0,000) -0,0003 (0,000) 0,0002 (0,000) 0,0003 (0,000) -7,94E-06 (0,449) 5,81E-05 (0,000) Year group 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 Effect on dividends Based on our results we reject H 0 which states that dividend policies has not changed significantly after the 2006 tax reform. Adjusted pay-out (before) Adjusted pay-out (after) Adjusted pay-out (together) OLS SUR OLS SUR OLS SUR Cash to total assets 0,3721 (0,000) 0,5846 (0,000) 0,0982 (0,000) 0,1630 (0,000) 0,2385 (0,000) 0,3847 (0,000) Revenue growth -0,0007 (0,000) -0,0007 (0,000) -7,96E-05 (0,043) -8.10E-05 (0,039) -0,0002 (0,000) -0,0002 (0,000) Return on assets 0,4539 (0,000) 0,3909 (0,000) 0,1948 (0,000) 0,1760 (0,000) 0,3497 (0,000) 0,3070 (0,000) Standard deviation of revenue growth -0,093 (0,000) -0,0932 (0,000) -0,0197 (0,000) -0,0191 (0,000) -0,0557 (0,000) -0,0552 (0,000) Aggregate personal ownership 0,0011 (0,000) 0,0022 (0,000) -0,0003 (0,000) -0,0004 (0,000) 0,0003 (0,000) 0,0007 (0,000) Year group -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. 32

33 5.3.3 Effect on ownership Based on our results we reject H 0 which states that ownership structure in companies has not changed in favour of majority shareholders as a consequence of the reform. Agg. Pers. own (before) Agg. Pers. own(after) Agg. Pers. own (together) OLS SUR OLS SUR OLS SUR Cash to total assets -2,0570 (0,000) -3,2098 (0,000) 3,3154 (0,000) 6,3761 (0,000) 0,3040 (0,056) 0,9452 (0,000) Adjusted pay-out 3,1358 (0,000) 4,7126 (0,000) -1,9766 (0,000) -3,7951 (0,000) 2,1253 (0,000) 3,1817 (0,000) Log revenue -0,8908 (0,000) -0,9151 (0,000) -0,6892 (0,000) -0,7372 (0,000) -0,8057 (0,000) -0,8442 (0,000) Standard deviation of revenue growth -0,4673 (0,000) -0,3537 (0,000) -0,04807 (0,000) -0,5034 (0,000) -0,4849 (0,000) -0,4461 (0,000) Year group -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 H 0 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 The reason for the increase is 33

34 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

35 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 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

36 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 Danielsen 14. 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

37 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 H 0 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

38 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

39 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 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 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

40 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

41 References Alstadsæter, A., and E. Fjærli "Neutral taxation of shareholder income? Corporate responses to an announced dividend tax." International Tax and Public Finance no. 16 (4): Bates, T.W., K.M. Kahle, and R.M. Stulz "Why do US firms hold so much more cash than they used to?" The Journal of Finance no. 64 (5): Berzins, J., Ø. Bøhren, and P. Rydland "Corporate finance and governance in firms with limited liability: Basic characteristics." Center of Corporate Governance Research. Berzins, J., Ø. Bøhren, and B. Stacescu "Dividends and Stockholder Conflicts: A Comprehensive Test for Private Firms." Centre for Corporate Governance Research. Working Paper no. 5/2011 Brüderl, J "Panel data analysis." University of Mannheim, viewed no. 25 (02):2009. Dougherty, C Introduction to econometrics: Oxford University Press, USA. Finandepartementet Meld. St Evaluering av skattereformen 2006 Greenwald, B.C.N., J. Kahn, P.D. Sonkin, and M. Van Biema Value investing: from Graham to Buffett and beyond: John Wiley & Sons Inc. Grullon, G., R. Michaely, and B. Swaminathan "Are Dividend Changes a Sign of Firm Maturity?*." The Journal of Business no. 75 (3): Hagstrom, R.G The Warren Buffett way: Investment strategies of the world's greatest investor: Wiley. 41

42 Jensen, G.R., D.P. Solberg, and T.S. Zorn "Simultaneous determination of insider ownership, debt, and dividend policies." Journal of financial and Quantitative analysis no. 27 (2): Kalcheva, I., and K.V. Lins "International evidence on cash holdings and expected managerial agency problems." Review of Financial Studies no. 20 (4): Kari, S., H. Karikallio, and J. Pirttilä "Anticipating Tax Changes: Evidence from the Finnish Corporate Income Tax Reform of 2005*." Fiscal Studies no. 29 (2): Kari, S., H. Karikallio, and J. Pirttilä 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 "Tax reform and payout policy: Do shareholder clienteles or payout policy adjust?" Journal of Corporate Finance no. 16 (4): Lopez de Silanes, F., R. Vishny, and A. Shleifer "Agency problems and dividend policies around the world." Journal of finance no. 60 (1):1-33. Nymoen, J. and Woxholt, B. K Aksjonærmodellen Verdt å vite 08/09: Opler, T., L. Pinkowitz, R. Stulz, and R. Williamson The determinants and implications of corporate cash holdings. National Bureau of Economic Research. Redding, L.S "Firm size and dividend payouts." Journal of Financial Intermediation no. 6 (3): Rettl, D.A "Growth Opportunities, Cash Holdings and Payout Policy." 42

43 Thoresen, T.O. Bø, E.E. Fjørli, E. Halvorsen, E Skattereformen 2006 har skattesystemet blitt mer omfordelende? Torres-Reyna, O "Panel Data Analysis Fixed & Random Effects." Princeton University, Data and Statistical Services presentation. Zellner, A "An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias." Journal of the American statistical Association:

44 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: IF DUMMY=1 Included observations: Method df Value Probability t-test Satterthwaite-Welch t-test* Anova F-test (1, ) Welch F-test* (1, ) *Test allows for unequal cell variances Analysis of Variance Source of Variation df Sum of Sq. Mean Sq. Between Within E Total E Category Statistics Std. Err. YRG Count Mean Std. Dev. of Mean All Test for Equality of Means of RANK150B Categorized by values of YRG Date: 07/20/12 Time: 11:05 Sample: IF DUMMY=1 Included observations: Method df Value Probability t-test Satterthwaite-Welch t-test* Anova F-test (1, ) Welch F-test* (1, ) *Test allows for unequal cell variances Analysis of Variance Source of Variation df Sum of Sq. Mean Sq. Between Within

45 Total Category Statistics Std. Err. YRG Count Mean Std. Dev. of Mean All Test for Equality of Means of AGGPERSY Categorized by values of YRG Date: 07/20/12 Time: 11:05 Sample: IF DUMMY=1 Included observations: Method df Value Probability t-test Satterthwaite-Welch t-test* Anova F-test (1, ) Welch F-test* (1, ) *Test allows for unequal cell variances Analysis of Variance Source of Variation df Sum of Sq. Mean Sq. Between Within E Total E Category Statistics Std. Err. YRG Count Mean Std. Dev. of Mean All Test for Equality of Means of ADJPAYX Categorized by values of YRG Date: 07/20/12 Time: 11:06 Sample: IF DUMMY=1 Included observations: Method df Value Probability t-test Satterthwaite-Welch t-test* Anova F-test (1, ) Welch F-test* (1, ) *Test allows for unequal cell variances 45

46 Analysis of Variance Source of Variation df Sum of Sq. Mean Sq. Between Within Total Category Statistics Std. Err. YRG Count Mean Std. Dev. of Mean All Test for Equality of Means of CASHTOTY Categorized by values of YRG Date: 07/20/12 Time: 11:06 Sample: IF DUMMY=1 Included observations: Method df Value Probability t-test Satterthwaite-Welch t-test* Anova F-test (1, ) Welch F-test* (1, ) *Test allows for unequal cell variances Analysis of Variance Source of Variation df Sum of Sq. Mean Sq. Between Within Total Category Statistics Std. Err. YRG Count Mean Std. Dev. of Mean All

47 2. Nonparametric test results medians Test for Equality of Medians of RANK1A50 Categorized by values of YRG Date: 07/20/12 Time: 11:07 Sample: IF DUMMY=1 Included observations: Method df Value Probability Wilcoxon/Mann-Whitney Wilcoxon/Mann-Whitney (tie-adj.) Med. Chi-square Adj. Med. Chi-square E Kruskal-Wallis Kruskal-Wallis (tie-adj.) van der Waerden Category Statistics > Overall YRG Count Median Median Mean Rank Mean Score All Test for Equality of Medians of RANK150B Categorized by values of YRG Date: 07/20/12 Time: 11:08 Sample: IF DUMMY=1 Included observations: Method df Value Probability 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 > Overall YRG Count Median Median Mean Rank Mean Score All Test for Equality of Medians of AGGPERSY Categorized by values of YRG Date: 07/20/12 Time: 11:08 Sample: IF DUMMY=1 Included observations:

48 Method df Value Probability Wilcoxon/Mann-Whitney Wilcoxon/Mann-Whitney (tie-adj.) Med. Chi-square Adj. Med. Chi-square E Kruskal-Wallis Kruskal-Wallis (tie-adj.) van der Waerden Category Statistics > Overall YRG Count Median Median Mean Rank Mean Score All Test for Equality of Medians of ADJPAYX Categorized by values of YRG Date: 07/20/12 Time: 11:09 Sample: IF DUMMY=1 Included observations: Method df Value Probability 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 > Overall YRG Count Median Median Mean Rank Mean Score All Test for Equality of Medians of CASHTOTY Categorized by values of YRG Date: 07/20/12 Time: 11:09 Sample: IF DUMMY=1 Included observations: Method df Value Probability Wilcoxon/Mann-Whitney Wilcoxon/Mann-Whitney (tie-adj.) Med. Chi-square Adj. Med. Chi-square Kruskal-Wallis

49 Kruskal-Wallis (tie-adj.) van der Waerden Category Statistics > Overall YRG Count Median Median Mean Rank Mean Score All

50 3. Panel data regression cash holdings Dependent Variable: CASHTOTY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:15 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. RANK1A E ADJPAYX GROWTHREV -7.42E E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: CASHTOTY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:16 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances 50

51 Variable Coefficient Std. Error t-statistic Prob. RANK150B -5.96E E ADJPAYX GROWTHREV -1.98E E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: CASHTOTY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:34 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. AGGPERSY E ADJPAYX GROWTHREV -1.10E E LEVPO LOGREV ROAX STDGREY

52 YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat

53 4. Panel data regression dividends Dependent Variable: ADJPAYX Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:11 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. AGGPERSY E CASHTOTY GROWTHREV E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: ADJPAYX Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:13 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included:

54 Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. RANK150B 6.14E CASHTOTY GROWTHREV E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: ADJPAYX Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:14 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. RANK1A E CASHTOTY GROWTHREV LEVPO

55 LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat

56 5. Panel data regression ownership Dependent Variable: AGGPERSY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:18 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. CASHTOTY ADJPAYX GROWTHREV LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 1.07E+08 F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid 1.77E+08 Durbin-Watson stat Dependent Variable: RANK150B Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:18 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included:

57 Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. CASHTOTY ADJPAYX GROWTHREV LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: RANK1A50 Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:24 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. CASHTOTY ADJPAYX GROWTHREV LEVPO LOGREV

58 ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat

59 6. Panel data regression personal ownership Dependent Variable: CASHTOTY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:20 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations: Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. DUMNONPE ADJPAYX GROWTHREV -1.08E E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat Dependent Variable: CASHTOTY Method: Panel EGLS (Cross-section random effects) Date: 07/20/12 Time: 11:21 Sample: IF DUMMY=1 Periods included: 9 Cross-sections included: Total panel (unbalanced) observations:

60 Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. DUMPE ADJPAYX GROWTHREV -1.08E E LEVPO LOGREV ROAX STDGREY YRG IND IND IND IND IND IND IND IND IND IND IND C Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat

61 7. SUR - Before tax reform System: SYS01 Estimation Method: Seemingly Unrelated Regression Date: 07/20/12 Time: 10:51 Sample: IF DUMMY=1 AND YRG=1 Included observations: Total system (unbalanced) observations Linear estimation after one-step weighting matrix Coefficient Std. Error t-statistic Prob. C(1) C(2) E 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) E 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)

62 C(50) Determinant residual covariance 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: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(18) + C(19)*ADJPAYX + C(20)*CASHTOTY + C(21)*STDGREY + C(22)*LOGREV + C(23)*IND5 + C(24)*IND6 + C(25)*IND8 + C(26)*IND9 + C(27)*IND10 + C(28)*IND11 + C(29) *IND12 + C(30)*IND13 + C(31)*IND14 + C(32)*IND15 + C(33)*IND16 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 1.68E+08 Durbin-Watson stat 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 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

63 8. OLS Before tax reform System: SYS01 Estimation Method: Least Squares Date: 07/20/12 Time: 10:53 Sample: IF DUMMY=1 AND YRG=1 Included observations: Total system (unbalanced) observations Coefficient Std. Error t-statistic Prob. C(1) C(2) E 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) E 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)

64 Determinant residual covariance 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: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(18) + C(19)*ADJPAYX + C(20)*CASHTOTY + C(21)*STDGREY + C(22)*LOGREV + C(23)*IND5 + C(24)*IND6 + C(25)*IND8 + C(26)*IND9 + C(27)*IND10 + C(28)*IND11 + C(29) *IND12 + C(30)*IND13 + C(31)*IND14 + C(32)*IND15 + C(33)*IND16 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 1.68E+08 Durbin-Watson stat 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 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

65 9. SUR after tax reform System: SYS02 Estimation Method: Seemingly Unrelated Regression Date: 07/20/12 Time: 10:55 Sample: IF DUMMY=1 AND YRG=2 Included observations: Total system (unbalanced) observations Linear estimation after one-step weighting matrix Coefficient Std. Error t-statistic Prob. C(1) C(2) E C(3) C(4) C(5) -8.10E E 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) E 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)

66 C(50) Determinant residual covariance 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: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(18) + C(19)*ADJPAYX + C(20)*CASHTOTY + C(21)*STDGREY + C(22)*LOGREV + C(23)*IND5 + C(24)*IND6 + C(25)*IND8 + C(26)*IND9 + C(27)*IND10 + C(28)*IND11 + C(29) *IND12 + C(30)*IND13 + C(31)*IND14 + C(32)*IND15 + C(33)*IND16 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 1.87E+08 Durbin-Watson stat 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 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

67 10. OLS After the tax reform System: SYS02 Estimation Method: Least Squares Date: 07/20/12 Time: 10:56 Sample: IF DUMMY=1 AND YRG=2 Included observations: Total system (unbalanced) observations Coefficient Std. Error t-statistic Prob. C(1) C(2) E C(3) C(4) C(5) -7.96E E 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) E 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)

68 Determinant residual covariance 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: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(18) + C(19)*ADJPAYX + C(20)*CASHTOTY + C(21)*STDGREY + C(22)*LOGREV + C(23)*IND5 + C(24)*IND6 + C(25)*IND8 + C(26)*IND9 + C(27)*IND10 + C(28)*IND11 + C(29) *IND12 + C(30)*IND13 + C(31)*IND14 + C(32)*IND15 + C(33)*IND16 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 1.86E+08 Durbin-Watson stat 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 Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

69 11. SUR Entire period System: SYS03 Estimation Method: Seemingly Unrelated Regression Date: 07/20/12 Time: 11:01 Sample: IF DUMMY=1 Included observations: Total system (unbalanced) observations Linear estimation after one-step weighting matrix Coefficient Std. Error t-statistic Prob. C(1) C(2) E C(3) C(4) C(5) E 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) 5.81E E C(39) C(40) C(41) C(42) C(43) C(44) C(45) C(46) C(47) C(48) C(49)

70 C(50) C(51) C(52) C(53) Determinant residual covariance 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 + C(18)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(19) + C(20)*ADJPAYX + C(21)*CASHTOTY + C(22)*STDGREY + C(23)*LOGREV + C(24)*IND5 + C(25)*IND6 + C(26)*IND8 + C(27)*IND9 + C(28)*IND10 + C(29)*IND11 + C(30) *IND12 + C(31)*IND13 + C(32)*IND14 + C(33)*IND15 + C(34)*IND16 + C(35)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 3.55E+08 Durbin-Watson stat Equation: CASHTOTY = C(36) + C(37)*ADJPAYX + C(38)*AGGPERSY + C(39)*ROAX + C(40)*STDGREY + C(41)*FIXRATC + C(42)*IND5 + C(43)*IND6 + C(44)*IND8 + C(45)*IND9 + C(46)*IND10 + C(47)*IND11 + C(48)*IND12 + C(49)*IND13 + C(50)*IND14 + C(51)*IND15 + C(52) *IND16 + C(53)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

71 12. OLS Entire period System: SYS03 Estimation Method: Least Squares Date: 07/20/12 Time: 11:02 Sample: IF DUMMY=1 Included observations: Total system (unbalanced) observations Coefficient Std. Error t-statistic Prob. C(1) C(2) E C(3) C(4) C(5) E 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) -7.94E E C(39) C(40) C(41) C(42) C(43) C(44) C(45) C(46) C(47) C(48) C(49) C(50)

72 C(51) C(52) C(53) Determinant residual covariance 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 + C(18)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Equation: AGGPERSY = C(19) + C(20)*ADJPAYX + C(21)*CASHTOTY + C(22)*STDGREY + C(23)*LOGREV + C(24)*IND5 + C(25)*IND6 + C(26)*IND8 + C(27)*IND9 + C(28)*IND10 + C(29)*IND11 + C(30) *IND12 + C(31)*IND13 + C(32)*IND14 + C(33)*IND15 + C(34)*IND16 + C(35)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 3.55E+08 Durbin-Watson stat Equation: CASHTOTY = C(36) + C(37)*ADJPAYX + C(38)*AGGPERSY + C(39)*ROAX + C(40)*STDGREY + C(41)*FIXRATC + C(42)*IND5 + C(43)*IND6 + C(44)*IND8 + C(45)*IND9 + C(46)*IND10 + C(47)*IND11 + C(48)*IND12 + C(49)*IND13 + C(50)*IND14 + C(51)*IND15 + C(52) *IND16 + C(53)*YRG Observations: R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat

73 13. Definition of variables Variable Definition adjpayx Adjusted pay-out ratio aggpersy Aggregated personal ownership Cashtoty Cash to total assets dumnonpe Dummy equal 1 if yrg=2 and aggpersy is below or equal to 50 dumpe Dummy equal to 1 if yrg=2 and aggpersy is above 50% growthrev Revenue growth Levpo Leverage (only positive values included) logrev Log revenue Paidinpo Paid in capital (only positive figures) rank150a Largest owner own more than 50% rank150b Largest owner owns less than or equal to 50% Retearpo Retained earnings (only positive figures) Roax Return on assets stdgrey Standard deviation of revenue growth Totass Total assets yrg Dummy variable with the value 1 in the period and the value 2 in the period

74 14. Empirical distribution test for cash to total assets and adjusted payout 74

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