Corporate income tax rate changes and firm performance:
The moderating effect of firm size and tax loss offset rules
Evidence from European market
Student number: S3091899 Name: Qiaoyu Zhang
Study Programme: MSc IFM Supervisor: Dr. R.O.S. Zaal
Second Accessor: Dr. P.P.M. (Peter) Smid
Abstract
This paper examines how corporate tax affect corporate risk-taking by investigating the firm’s performance under the tax rate increase and the tax rate cut. The major results suggest firm will reduce risk-taking activities in response to the tax rate changes, either rise or cut. Moreover, firm size has the moderating effect on the main relationship only when there is a tax increase. There is no statistically significant moderating effect of found when firms are facing the tax cut. Finally, tax loss-offset rule has a negative impact on the main relation.
1 / 35
1. Introduction
Taxation, as one of the most important tools that government uses to measure the countries’ economy, is always a controversial topic that being continuously discussed. From many aspects, such as individual income, savings, consumptions, etc., that tax can influence the economic activities. In this paper, I mainly focus on the influence of taxation on the corporate risk-taking, since as one of the key component played in the economy, corporations are deeply affected by the tax rate. Meanwhile, firm’s risk-taking is essential for both firms and economies to grow in the long run (Solow, 1956).
After Donald John Trump became the 45th president of USA, he claims to raise the tariff
for importing goods and slash the corporate tax rate in the USA, and that is what exactly he is doing, which contrasts with the main voice of globalization in the past decades. Due to the prevalence of American protectionism and great influential brought by US’s superpower, it can be foreseen that in the following years the tax policies of each country will be greatly challenged and may lead to relatively frequent changes. Therefore, it is worthwhile to study the impact brought by the tax changes on the corporate risk-taking. Thus, in this paper, how corporate income tax affects the corporate risk-taking is tested.
2 / 35 risk-taking: when the tax rate increases, a risk-neutral investor will require a higher pretax expected return on a project as risk increases, to offset the resulting increase in expected tax payments.
On the other hand, studies like Ljungqvist al. (2017) believe when income taxes increases, corporate risk-taking is discouraged since the asymmetry in firm’s payoffs is induced, resulting in a higher profit fall for risky projects. Although in the reality, the governments have policies that allow firms to offset their losses, only part of losses will be covered. The most extreme case that offset all the losses is nonexistent.
Many previous studies have focused on the tax effect on corporate risk-taking in US samples (Cullen and Gordon 2007, Ljungqvist al. 2017, Graham 2003), or take developed western countries as the whole (Langenmayr and Lester 2015), rarely has any study focus on the European countries exclusively. Different from the situation in US or UK, countries in Europe have different law systems which may lead to different impact on firms, and the results could differ from the studies mentioned above.
Based on the arguments and the gap identified above, the main research question is developed:
“What is the impact of the corporate income tax changes on the corporate risk-taking for European firms?”
Additionally, many studies (i.e., Langenmayr and Lester 2015, Dressler and Overesch 2010, Auerbach and Poterba 1987 etc.) show the impact of tax loss offset rules, in which governments allow firms to recoup part of their operating losses incurred by either reducing prior or future taxable income, on the firm’s risk-taking behavior. Therefore, I also investigate the impact of the tax loss offset rules on the relationship between corporate income tax and corporate risk-taking, which lead to the first sub research question: “What is the impact of the tax loss offset rule on the relationship between corporate income tax changes and firm’s risk taking?”
3 / 35 nowadays regarded as a critical element to the firm’s performance and the moderating effect of firm size has never been studied before, which leads to the second sub-research question: “How is the firm size influence the relationship between corporate income tax and firm’s risk taking?”
For answering these research questions, this paper is organized in the following way: the next section will provide the main theoretical background and opposing views and results. During the introduction of the literature review, different hypotheses are developed. Thereafter, the methodology and data are described. In the followed section, I will present the results of the multivariate regressions. The results will be discussed and concluded in the last part, together with limitations and future research opportunities.
2.
Literature review and Hypothesis building
2.1 Tax rate changes and corporate risk takingThe opinion on how corporate taxation affect the corporate risk-taking varies between literature.
4 / 35 expected profit of project B falls faster than project A. As you can see from the table 1, the difference between payoffs of the project become larger (rise from € 1 to € 3) when the tax rate rise from 10% to 30%. The difference stems from the fact that government shares in the corporate profits but not in the loss. Therefore, firms will prefer the safe project to the risky project, especially when the tax rate increases. Moreover, even if taking tax loss-offset into consideration, the most extreme case is the losses are completely written off by the past or future profits. Yet in practice, the government only allow a part of losses to be offset. Thus, an increase in tax rate will ultimately lead to low expected profit and firms are expected to respond by reducing risk-taking activities.
Table 1
Effect of tax rate changes
Project A Project B
Good Scenario € 40 € 100
Bad Scenario € 40 € -20
Payoffs with No tax € 40 € 40
Payoffs with Tax rate 10% € 36 € 35
Payoffs with tax rate 20% € 32 € 30
Payoffs with tax rate 30% € 28 € 25
Note: This table gives an example of how tax rate changes affect the final payoffs. The payoffs of each project are calculated as follow: Payoffs (A) = Good Scenario * 50% * (1-Tax Rate) + Bad Scenario * 50% * (1-Tax Rate); Payoffs (B) = Good Scenario *50% * (1-Tax Rate) + Bad Scenario * 50%.
Hence, I come up with the hypothesis 1a:
Hypothesis 1a. Corporate income tax rate is negatively related with the corporate risk-taking.
5 / 35 systems differences between countries. For instance, code law system is more common among European countries, the capital resource of firms in those countries are relatively more from banks, governments and public institutions, thus the increase of the tax rate can increase the risk shared with government by the increase of the tax shield raised by interest. Therefore, management may even adopt more risky behavior.
So here comes the hypothesis 1b:
Hypothesis 1b. Corporate income tax rate is positively related with the corporate risk taking.
2.2 Firm-level moderator: Firm size
6 / 35 disclosure may be a means of achieving this. Souissi and Khlif (2012) also suggest that larger firms have stronger motivations to disclose more information, thus conclude larger firms have relatively less asymmetric information than smaller firms. Furthermore, it is argued by Farooq and Jibran (2017) that small firms contain more asymmetric information with low and volatile returns that make debt borrowings more costly and therefore more difficult for them to share their risk in the capital market. Conversely, large firms have better access to the debt market due to less asymmetric information, so they deploy debt with less cost comparatively. Watson et al. (2002) also confirm that for larger firms, especially listed firms, have easier access to direct financing due to the large number of their financial disclosures, which assists in the reduction of the level of uncertainty regarding the firm’s performance. Thirdly, based on the legitimacy theory that it is easier for large firms to decrease regulations pressures from governments (political costs) and from environmentally conscious organizations due to their disclosures (Watson et al., 2002). Firth (1979) finds out in the research that large firms attract more attention by the public organizations and government bodies, thus they will try to enhance their reputation and public image by disclosing more information. Higher disclosure allays public criticism and government intervention in their corporate affairs.
However, many researchers find out that firm size is positively related with the board diversity (Arnegger et al. 2014, Harrison and Klein 2007, Child 1972), which is negatively related with the firm risk-taking behavior (Bernile et al., 2018).
In conclusion, general better performance, easier access to the capital market and good relationship with the stakeholders make larger firms are more flexible to the risk brought by the tax rate changes, but it is also possible that due to the larger diversity in the board, large firms will make more conservative behavior in responding to the change of tax rate.
Therefore, I propose my 3rd hypothesis:
7 / 35 corporate risk taking.
Hypothesis 2b. Firm size weaken the relationship between tax rate changes and corporate risk taking.
2.3 Country-level moderator: Tax loss offset rules
Many countries allow firms to recoup part of their operating losses incurred by either reducing prior or future taxable income. The tax loss offset rules, however, significantly differ across countries: only some countries grant a loss carryback option and a loss carryforward is always possible (Dressler & Overesch, 2010). In appendix you can see different loss offset policies in 24 OECD European countries. But in general, the asymmetric treatment of tax losses is an attribute common to all corporate income tax systems (Cooper & Knittel, 2006). To be more specific, under a loss carryback case, if the tax loss is offset against prior taxable income, the government will compensate the firm by return a part of the tax that firm paid in the previous period. Similarly, countries with loss carryforward policy, firms can use their current losses to offset their future taxable income. However, firms under tax loss offset policies will not receive a refund equal to the tax value of its loss. Instead, firms must carry their losses backward or forward to offset prior or future payments of tax.
8 / 35 loss offset provisions affect investment decisions when firms expect potential losses someday in the future and the result shows that existence of tax loss offset rules has a positive influence on investments, which is even stronger for firms with a relatively high probability.
Therefore, I come up with the hypothesis 3a:
Hypothesis 3a. Tax loss carryback/carryforward strengthen the association between corporate income tax and corporate risk taking.
However, it is still possible that tax loss carryback or carryforward will weaken the relationship between corporate income tax and risk-taking. Auerbach and Poterba (1987) in their paper suggest that firms that are currently taxable (without loss carryforwards) have a substantially greater incentive for equipment investment than firms with loss carryforwards. This happens when the costs of postponed depreciation benefits exceed the benefits from reduced tax liabilities through a deduction for tax loss carryback/carryforwards.
Based on the arguments provided, the hypothesis 3b as follow:
9 / 35
3. Description of measurements
3.1 Dependent variable
Measure of risk taking
This paper considers the impact of tax rate changes on the firm’s risk-taking behavior. According to Faccio, Marchica and Mura (2011), I calculate the corporate risk-taking (RISK1) as the standard deviation of the firm profitability (Return on assets) over 3-year overlapping periods from 2007 and ends in 2017 (i.e., 2007-2009, 2008-2010 etc.). ROA is computed as the ratio of firm’s earnings before interest, tax and depreciation (EBITA) to its total assets.
𝑅𝐼𝑆𝐾𝑖,𝑡 = σ (𝑅𝑂𝐴𝑖,(𝑡,𝑡+2))
3.2 Independent variable
3.2.1 Measure of effect of corporate income tax rate changes
Each country has its own statutory rate for us to have a general idea as the first benchmark of taxation, but the picture will be more accurate if we look into the effective corporate tax rate, which represents the real value of tax burden of the company (Vintilă, Gherghina, and Păunescu, 2018). Therefore, in this paper, I follow Ljungqvist al. (2017)’s method that approximate the geographic distribution of firm’s liability by using the data of local income for their subsidiaries, branches and plants to against the total sales of the firm, as the weights of local tax changes. The effective tax rate changes are the sum of all the weighted tax changes. Moreover, to investigate the impact of tax raise and tax cut separately, the corresponding effective tax raise and effective tax cut are calculated individually.
∆𝑡𝑎𝑥 𝑟𝑎𝑡𝑒𝑖,𝑡 = ∑(
𝑖
𝑠𝑎𝑙𝑒𝑠𝑖,𝑠,𝑡
10 / 35 Where
𝑆𝑎𝑙𝑒𝑠𝑖,𝑠,𝑡 = firm i’s sales in state s in year t
𝑆𝑎𝑙𝑒𝑠𝑖,𝑡𝑜𝑡𝑎𝑙,𝑡 = the corresponding firm total across all selected countries in year t
∆𝑇𝑠,𝑡 = the change in the corporate income tax rate in state s in year t
3.2.2 Moderator
Measure of tax loss carryback/carry forward rules
Most countries have loss-offset rules. We measure the loss-offset rules by the length of the statutory loss carryback (LCB) or loss carryforward (LCF) period in a firm's home country s in year t. According to Langenmayr and Lester (2015), for countries with an indefinite loss carryforward period, the LCF is set in 20 years. In this research, I follow the same way.
Measure of firm size
Firm size is calculated by the natural log of the total assets. Large firms are less risky since large firms have more power in maintaining stable incomes and are normally equipped with better risk management skills and higher standards.
3.3 Control variables
To test the relative relationship between the corporate risk-taking and corporate income tax rate changes and moderating effects of the firm size and tax loss offset rules, several controls are incorporated. I adopt the following firm characteristics as descriptive variables: book leverage, stock return (measured by price earnings ratio) and return on equity. Furthermore, in order to control for the unobserved factors, industry fixed effects and year fixed effects are included in the model as well.
11 / 35 Bonaccorsi di Patti et al. (2015)). Kim et al. (2017) suggest higher leverage is accompanied by the increasing possibility of financial distress including events. Thus, managers will decrease the risk-taking behaviors due to the increasing financial failure brought by the leverage. On the other hand, the rise of the debt will increase the cost of capital, which leads to a higher expected return by investors. Management will make risk-preferred decisions to meet the investors’ requirements.
The second control variable I use is the price-earnings ratio, as one of the price multiple parameters, measure the stock’s valuation of the firm. Price multiples serve an important purpose in providing a static and forward glance at a stock's valuation. When there is an expectation of greater earnings potentials in the future, investors tend to bid up share prices, which increases the price-earnings multiple. To respond the high expectation of the investors, corporate managers are incentive to take more risks. Thus, a positive relationship is expected in the final regression results.
The third control variable I use is the return on equity, which indicates the past profitability of the firm. Previous researchers (Ilgen 1971; Lane and Gibbons 2007; Mahto and Khanin 2015) have shown that past financial performance proclivity influence firms’ goal setting and future performance expectations. Mahto and Khanin (2015) argue that if owners or managers of family firms are satisfied with their past financial performance, they will level up their expectation in the future firm performance, in another word, they will adopt more risk-taking activities in the future. However, based on the strategic reference points (SRP) framework (Fiegenbaum, Hart, and Schendel 1996) when firms’ performance rises above their strategic reference point, managers set less ambitious goals and adopt more risk-averse strategies. In this case, either positive or negative relationship is expected in this paper.
As shown in table 2, all used variables and their definitions are summarized.
Table 2
12 / 35
Variables Explanation
RISK Measuring the risk taking of the firm, calculate as the
standard deviation of the 3 years’ ROA
ETR Effective tax rise measures the increase in the firm’s
effective corporate tax rate
ETC Effective tax cut measure the decrease in the firm’s
effective corporate tax rate
TLO Tax loss offset, measuring the length of the statutory
loss carryback (LCB) or loss carryforward (LCF) period in a firm's home country
SIZE Firm size, compute as the natural logarithm of total assets
LEV Firm’s leverage level, measure as the ratio of the
long-term debt over the book value of assets
ROE Net income returned as a percentage
of shareholders’ equity
PM Price-earnings ratio, Market value per Share
/ Earnings per Share
13 / 35
4. Methodology
In this paper, I am going follow Ljungqvist al. (2017) to examine whether the association between changes in corporate income tax rate and firm’s risk taking is influenced by tax offset rules and leverage level by implementing pooled multivariate regression framework, where the regression is:
RISK𝑖,𝑗,𝑠,𝑡 = 𝛼 + 𝛽∆𝑇𝑖,𝑡++ 𝛾∆𝑇𝑖,𝑡−+ 𝛿𝐿𝐶𝑠,𝑡+ 𝜃𝑆𝐼𝑍𝐸𝑖,𝑡+ 𝜇𝑋𝑖,𝑡−1+ 𝜑𝑗,𝑡+ 𝜀𝑖,𝑗,𝑠,𝑡 (1)
Where:
i, j, s and t = firm, industry, country and year RISK𝑖,𝑗,𝑠,𝑡 = measure of firm i’s risk taking
∆𝑇𝑖,𝑡+ = measure of effect of corporate income tax rate increase ∆𝑇𝑖,𝑡− = measure of effect of corporate income tax rate decrease
𝐿𝐶𝑠,𝑡 = length of tax loss carryback/carry forward period in firm’s home country s in year t
𝑆𝐼𝑍𝐸𝑖,𝑡 = size of firm i in year t
𝑋𝑖,𝑡−1 = firm-level control variables measured as of t-1
𝜑𝑗,𝑡 = industry fixed effects in year t 𝜀𝑖,𝑗,𝑠,𝑡 = error term
The coefficient of ∆𝑇𝑖,𝑡+ (𝛽) or ∆𝑇
𝑖,𝑡− (𝛾) determines whether the corporate income tax
rate increase or decrease has positive or negative impact on the firm’s risk-taking decision-makings. The significance of the coefficient determines whether this association empirically exists.
In order to investigate the moderating impact of tax offset rules, we run the following regression:
RISK𝑖,𝑗,𝑠,𝑡 = 𝛼 + 𝛽1∆𝑇𝑖,𝑡++ 𝛽2∆𝑇𝑖,𝑡−+ 𝛾𝐿𝐶𝑠,𝑡+ 𝛿1( ∆𝑇𝑖,𝑡+∗ 𝐿𝐶𝑠,𝑡) + 𝛿2( ∆𝑇𝑖,𝑡−∗ 𝐿𝐶𝑠,𝑡) +
14 / 35 In the regression above, term ∆𝑇𝑖,𝑡+ ∗ 𝐿𝐶
𝑠,𝑡 and ∆𝑇𝑖,𝑡− ∗ 𝐿𝐶𝑠,𝑡 interacts the loss
carryback and loss carryforward variables with the length of tax loss offset period. The coefficient (𝛿1 𝑎𝑛𝑑 𝛿2 ) indicates whether the tax loss offset rules can strengthen or weaken the relationship between corporate income tax changes and firm’s risk-taking behavior. The significance of the coefficient indicates the interaction effect empirically exists.
Similar regressions will be operated as for the firm size. The regressions are shown as following:
RISK𝑖,𝑗,𝑠,𝑡 = 𝛼 + 𝛽1∆𝑇𝑖,𝑡++ 𝛽2∆𝑇𝑖,𝑡−+ 𝛾𝐿𝐸𝑉𝑖,𝑡+ 𝛿1( ∆𝑇𝑖,𝑡+∗ 𝑆𝐼𝑍𝐸𝑖,𝑡) + 𝛿2( ∆𝑇𝑖,𝑡− ∗ 𝑆𝐼𝑍𝐸𝑖,𝑡) +
𝜇𝑋𝑖,𝑡−1+ 𝜑𝑗,𝑡+ 𝜀𝑖,𝑗,𝑠,𝑡 (3)
5.
Data preparation
15 / 35 Table 4
Sample distribution by industries
Industry Obs %
0100-0999 Agriculture, Forestry and Fishing 27 1.14%
1000-1499 Mining 134 5.66%
1500-1799 Construction 59 2.49%
2000-3999 Manufacturing 1189 50.25%
4000-4999 Transportation, Communications, Electric,
Gas and Sanitary service 178 7.52%
5000-5199 Wholesale Trade 102 4.31%
5200-5999 Retail Trade 101 4.27%
7000-8999 Service 576 24.34%
Total 2366 100.00%
Table 3
Sample distribution by countries
16 / 35
6. Results
6.1 Sample analysis
Table 6 shows the descriptive statistics of each variables, including mean, median, maximum/minimum value, standard deviation and 25th/50th/75th percentile of samples.
The sample size of the sample contains 2366 observations, which come from the selected public listed firms from 24 OECD European countries.
Table 5
Sample distribution by year
Year Obs % 2007 446 18.85% 20.41% 18.85% 18.05% 14.24% 2.58% 2.45% 4.56% 2008 483 2009 446 2010 427 2011 337 2012 61 2013 58 2014 108 Total 2366 100.00% Table 6 Correlation Coefficients
RISK ETR ETC PM LEV ROE SIZE TLO
RISK 1 ETR -0.021 1 ETC 0.041 0.012 1 PM 0.087 -0.001 0.002 1 LEV 0.176 -0.042 0.111 0.041 1 ROE -0.162 0.015 -0.054 0.014 0.124 1 SIZE -0.212 0.101 -0.228 0.013 -0.409 0.254 1 TLO 0.075 0.023 -0.014 -0.005 0.046 -0.097 -0.161 1 Note: This table contains the correlation coefficients of all variables used in this paper:
17 / 35 Table 7 presents the correlation coefficients of all variables used in the analysis. The aim is to prove there is no multicollinearity among variables. As you can see from the table, there is no correlation coefficients larger than 0.7. 0.7 is the critical value adopted in this paper to judge the multicollinearity, any variable that has a correlation higher than 0.7 is unnecessary. The largest coefficient is between solvency ratio and firm size and has a value of 0.409.
6.2 Regression results
I develop different models to test all the hypothesis mentioned in chapter 2. Models in Table 6 show the results from multivariate regressions for the main relation and the interaction effects of corporate risk taking and effective tax rate changes.
6.2.1 Main relationship
Model 1 shows the relationship between control variables and dependent variables. According to Model 1, the results show all control variables have the statistically significant relationship with firm risk-taking, all the three control variables are below significance level of 0.01. More precisely, profit-earnings ratio has a positive relationship with the firm risk-taking, which is in line with my expectation that firms with high expectation on firms’ earning potentials will encourage managers to take
Table 7 Summary Statistics Mean Median Max Min Std
18 / 35 more risky activities. The return on equity is negatively related with the risk-taking, which could be explained by the strategic reference points (SRP) framework that when firms’ performance rises above their strategic reference point, managers set less ambitious goals and adopt more risk-averse strategies. The relationship between firm’s leverage level and the risk-taking is positive, which could be explained by the view that the rise of the debt will increase the cost of capital, which leads to a higher expected return by investors and management will make risk-preferred decisions to meet the investors’ requirements.
Model 2 investigates the main relationship between effective tax rate changes (include effective tax rate rise and effective tax rate cut) and corporate risk-taking, which I use to inspect hypothesis 1a and 1b.The result shows the relationship between effective tax rate rise and corporate risk taking are statistically significant at 0.05 significant level. The rise on the effective tax rate will have a negative impact on the corporate taking with β of -0.061, which is in line with the hypothesis 1a that corporate risk-taking is negatively related with the effective tax rate.Moreover, the result also shows a statistically significant positive relationship between effective tax rate cut and corporate risk-taking.In another word, firms will take conservative actions when they are facing a decrease in the effective tax rate. The more the effective tax rate decrease, less risk-taking activities they will obtain. The result is in line with the hypothesis 1b that corporate risk-taking is positively related with the effective tax rate. Overall, I conclude the result mentioned above that: when firms are facing effective tax rate rises, the relationship between firm risk-taking and the effective tax rate is negatively related; when firms are facing cuts on their effective tax rate, the effective tax rate and corporate risk-taking is positively related.
6.2.2 Moderating effect of firm size
19 / 35 effective tax rate and firm risk-taking differs. The result shows the coefficient of interaction term is positive and significant regarding effective tax rate rise, but negative and insignificant to effective tax rate cut. To fully understand the effect of the interaction term ETR*SIZE and ETC*SIZE on the dependent variable SMP, a textual example is provided and supplemented with a visualization in Figure 1. The example takes 2 random individuals: one individual with large firm size (e.g. log of total assets equal to 8) and another one with relatively smaller firm size (e.g. log of total assets equal to 3). In order to distinguish the effect of SIZE on tax rise and tax cut, two extreme conditions will be analyzed separately: one condition only happens tax rise (Condition 1) and another condition only happens tax cut (Condition 2). Assume that both individuals are completely equal with respect to ETR, ETC, PM, ROE and LEV, a direct comparison could be made. Under Condition 1, if ETR=1 and SIZE=8, a 1-unit increase in ETR results in -0.896 + 1.512 * 8 = 11.2. If ETR=1 and SIZE=3, a 1-unit increase in ETR results in -0.896 + 1.512 *3 = 3.64. From the comparison we can see, for larger firms, a unit increase in ETR cause a larger increase in the firm risk-taking than a 1-unit increase in ETR for a small size firm. In another word, the relationship between ETR and RISK is weakened when firm size increase. Referring to the practical, large firms will reduce relative less risk-taking activities compare to the small firms when facing effective tax rise. Under Condition 2, if ETC=-1 and SIZE=8, a 1-unit decrease in ETC results in -0.171 + (-0.027 * 1 * 8) = -0.387. If ETC=-1 and SIZE=3, a 1-unit decrease in ETC results in -0.171 + (-0.027 * 1 * 3) = -0.252. From the comparison we can see, for larger firms, a 1-unit decrease in ETC cause a larger risk-taking drawback than a 1-unit decrease in ETC for a small size firm. In another word, the relationship between ETC and RISK is weakened when firm size increase. However, the moderating effect of SIZE on the ETC and RISK is insignificant.
20 / 35 (hypothesis 2b).
6.2.3 Moderating effect of tax loss offset
The moderating effect of the tax loss offset is being tested in model 5 and model 6. Regression results show both tax loss offset and interaction terms are significant in the model. The coefficient of interactor for tax loss offset and effective tax rate rise is negative and the coefficient of interactor for tax loss offset and effective tax rate cut is positive. Both coefficients are significant at 0,05 significant level. I repeat the example did in section 6.2.2 which is used to test the moderating effect of firm size. Assume that both individuals are completely equal to each other with respect to ETR, ETC, PM, ROE and LEV, a direct comparison could be made. Under Condition 1, if ETR=1 and TLO=20, a 1-unit increase in ETR results in 0.249 + -0.16 * 20 = -2.951. If ETR=1 and TLO=10, a 1-unit increase in ETR results in 0.249 + -0.16 * 10 = -1.351. From the comparison we can see, for the firm with longer tax loss offset period, a 1-unit increase in ETR cause a larger risk-taking drawback than a 1-unit increase in ETR for the firm with shorter tax loss offset period. In another word, the relationship between ETR and RISK is strengthened when tax loss offset period get longer when firm facing tax rise. Under Condition 2, if ETC=-1 and TLO=20, a 1-unit decrease in ETC results in -0.172 + (0.01 * 1 * 20) = 0.028. If ETC=-1 and TLO=10, a 1-unit decrease in ETC results in -0.172 + (0.01 * 1 * 10) = -0.072. Therefore, from the result we see for the firm with a longer tax loss offset period, a 1-unit decrease in ETC cause a larger risk-taking than a 1-unit decrease in ETC for the firm with relatively shorter tax loss offset period. In
Figure 1 Moderating effect of firm size on the association between effective tax rate changes and risk-taking. - 5 - 4 - 3 - 2 - 1 F IRM RIS K -T A KIN G
EFFECTIVE TAX CUT
Large firm Small firm
1 2 3 4 5 F IRM RIS K -T A KIN G
EFFECTIVE TAX RAISE
21 / 35 another word, the relationship between ETC and RISK is strengthened when tax loss offset period increases if firm facing tax cut. In conclusion, the tax loss offsets strengthen the association between effective tax rate changes and firm risk-taking, hypothesis 3a is fully supported.
- 5 - 4 - 3 - 2 - 1 F IRM RIS K -T A KIN G
EFFECTIVE TAX CUT
Long TLO Short TLO
1 2 3 4 5 F IRM RIS K -T A KIN G
EFFECTIVE TAX RAISE
Long TLO Short TLO
22 / 35 Table 6
Multivariate regression results
M1 M2 M3 M4 M5 M6 M7 C -0.069*** (0.001) -0.066*** （0.002） 0.257*** （0.000） 0.275*** (0.000) -0.128*** (0.000) -0.140*** (0.000) 0.203*** (0.002) ETR -0.061** （0.042） -0.011 （0.643） -0.896*** (0.001) -0.069** (0.028) 0.249** (0.045) -0.472* (0.054) ETC 0.024** （0.031） 0.019 （0.203） 0.171 (0.214) 0.028** (0.018) -0.172* (0.053) -0.086 (0.473) PM 0.007*** (0.000) 0.007 （0.000） 0.008*** (0.000) 0.008*** (0.000) 0.007*** (0.000) 0.007*** (0.000) 0.008*** (0.000) ROE -0.105*** (0.000) -0.104*** （0.000） -0.084*** (0.000) -0.083*** (0.000) -0.102*** (0.000) -0.102*** (0.000) -0.081*** (0.000) LEV 0.364*** （0.000） 0.361*** （0.000） 0.267*** (0.000) 0.264*** (0.000) 0.358*** (0.000) 0.360*** (0.000) 0.268*** (0.000) SIZE -0.055*** (0.000) -0.058*** (0.000) -0.057*** (0.000) SIZE*ETR 1.512*** (0.001) 1.468*** (0.001) SIZE*ETC -0.027 (0.181) -0.036* (0.081) TLO 0.004*** (0.000) 0.004*** (0.000) 0.003*** (0.001) TLO*ETR -0.160** (0.013) -0.204*** (0.000) TLO*ETC 0.010** (0.027) 0.016*** (0.006) R2 7.47% 7.49% 8.50% 8.56% 7.72% 7.75% 8.75% Country
dummy No No No No Yes Yes Yes
Year dummy Yes Yes Yes Yes Yes Yes Yes
Industry
dummy Yes Yes Yes Yes Yes Yes Yes
Obs 2366 2366 2366 2366 2366 2366 2366
Note: The table presents the results from cross-section regressions used to test all the hypothesis. 1 star (*) indicates significance at 10%. 2 stars (**) indicates significance at 5% and. 3 stars (***) indicates significance at 1%
6.2.4 Industry analysis
23 / 35 basis. I have picked 3 industries: Manufacturing, Service, Communications, electric, gas and sanitary service, which together represent 82.11% of all firm-year observations. Table 7 represents the summarized information of regression for each individual industry. As for manufacturing industry, which accounts for 50.25% of all observations, has a statistically significant negative result on the coefficient of effective tax rise to risk-taking, which indicates that the manufacturing firms are sensitive to the tax increase and will reduce the risk-taking behaviors in response to the changes. However, there is no significant result that firms will respond on the tax cut. For the moderating effect, it is statistically significant that firm size will strengthen the association between effective tax rate rise and firm risk-taking, which means that larger firms will reduce more risk-taking activities rather than smaller firms when the tax rate increase. The corresponding moderating effect cannot be observed significantly in the relationship between the tax cut and firm risk-taking. For the moderating effect of the tax loss offset, it is constant with the results in the multivariable regression.
For service sector, the main relationship between tax changes and firm risk-taking is similar as the manufacturing sector. The negative relationship between tax rise and risk taking is statistically significant but not for the relation of the tax cut and risk-taking. The interaction term between effective tax rise and firm size is significantly positive, indicating strengthen moderating effects on the main relationship. Yet for the interaction term between effective tax cut and firm size is negatively significant, which tells a weaken moderating effects on the relationship between the tax cut and risk-taking. Moreover, the moderating effects of tax loss offset only positively significant on the relationship between tax rise and firm risk taking.
24 / 35
Table 7
Industry-by-industry results
Manufacturing Service Communications, Electric, Gas and Sanitary service
25 / 35 TLO*ETC 0.005 (0.141) 0.017 (0.173) 0.033* (0.060) R^2 10.00% 12.15% 10.62% 9.08% 9.70% 9.21 15.99% 20.80% 16.48% Obs 1189 1189 1189 576 576 576 178 178 178
26 / 35
7. Conclusion
The aim of this section is to summarize the main findings in this paper, interpret the results and discuss their possible practical implications, as well to review the limitation and further possible research directions.
7.1 Conclusion and implications
In this paper, I have investigated the effects of the corporate income tax rate changes, including effective tax rise and effective tax cut, on the firm’s risk-taking behaviors. Different from the sample of the previous study (Cullen and Gordon 2007, Ljungqvist al. 2017, Graham 2003, Langenmayr and Lester 2015), in total 2366 firm-year observations from 24 OECD European countries have been analyzed. Furthermore, the moderating effects of firm size and tax loss offset rules are tested in this paper as well. The findings of this paper contribute to give investors who are interested in the European market and firm managers who are working for portfolio strategy planning a guidance to respond to the corporate income tax changes in the future.
Confronted with controversial arguments on the relationship between corporate income tax changes and corporate risk-taking, my finding suggests that when firms are facing rises on their effective tax rate, the relationship between firm risk-taking and the effective tax rate is negatively related; when firms are facing cuts on their effective tax rate, the effective tax rate and corporate risk-taking is positively related. To be more specific, firms will reduce risk-taking in response to the tax rate changes, either rise or cut. My findings give a 3rd lemma that different from Ljungqvist al. (2017)’s study that
the average firm reduces risk in response to a tax increase but does not respond to a tax cut and Domar and Musgrave (1944)’s study that tax rate has a positive effect for the firm’s risk-taking. The difference could be explained by the following reasons:
27 / 35 paper are defaulted that firms have potential incentives to use the tax loss offset rules.
2. Stability is the fundamental for firms to establish effective planning and efficient compliance (Piper, 2015). Changes (either rise or cut) in tax rate may cause difficulties or unpredictable consequences. In order to ensure the steady operation of the company, management may shift their interest form risky projects to relative conservative projects.
3. The different data resource may lead to different research results. As can be seen from section 6.2.4 industry analysis, different industries respond differently on the tax rate changes. For instance, the manufacturing industry respond negatively to the tax rate increase on their risk-taking, but do not show significant relationship to the tax rate cut.
I also test the moderating effect of firm size and tax loss offset rules. The results show that firm size weaken the relationship between corporate tax rate and firm risk-taking when firms are facing a tax rise, the moderating effect of firm size is not statistically significant when there is a tax cut. The economic interpretation for the findings regarding to the moderating effect of firm size is that large firms can endure more risks than smaller firms due to their easier access to the capital market and the benefits brought by the large economic scale. For the tax loss offset rules, a positive effect is found on the association between corporate tax rate and firm risk-taking. This finding is in line the previous study that tax loss offset rules moderate firms’ sensitivity to the taxes that tax loss offset rules increase the firm’s tax burden and reduces its willingness to take risk (Ljungqvist al., 2017).
7.2 Limitation and future research
29 / 35
Reference
Akinyomi, Oladele John, and Adebayo Olagunju, 2013, Determinants of capital structure in Nigeria, International Journal of Innovation and Applied Studies 3, 999– 1005.
Arnegger, M., Hofmann, C., Pull, K., Vetter, K., 2014. Firm size and board diversity. Journal of Management & Governance, Vol. 18 Issue 4, p1109-1135.
Auerbach, Alan J., Poterba, James M., 1987. Tax-Loss carryforwards and corporate tax incentives. In Feldstein, Martin ed.: The Effects of Taxation on Capital Accumulation. 305-338. Chicago: University of Chicago Press
Bernile, G., Bhagwat, V., Yonker, S., 2018. Journal of Financial Economics. Vol. 127 Issue 3, p588-612. 25p
Bonaccorsi di Patti, E., A. DIgnazio, M. Gallo and G. Micucci, 2015. The role of leverage in firm solvency: Evidence from bank loans. Italian Economic Journal 1(2), 253–286
Child, J., 1972. Organizational structure: reply to tyler. Sociology, Sep73, Vol. 7 Issue 3, p447-447
Cooper, M. and Knittel, M., 2006. Partial Loss Refundability: How are Corporate Tax Losses Used?. National Tax Journal, 59, 651–63.
Cullen, J. B., Roger H. G., 2007, Taxes and entrepreneurial risk-taking: Theory and evidence for the U.S., Journal of Public Economics 91, 1479–1505.
David, A. H., Katherine, J. K., 2007. What’s the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review 2007, Vol. 32, No.4, 1199-1228
30 / 35 Quarterly Journal of Economics, 58: 388-422.
Dressler, D. and Overesch, M., 2010, Investment Impact of Tax Loss Treatment – Empirical Insights From A Panel of Multinationals. Discussion Paper 10-097, Centre for European Economic Research (ZEW)
Faccio, M., Marchica, M., Mura, R., 2011. Large shareholder diversification and corporate risk-taking. Review of Financial Studies, 24(11): 3601-3641
Farooq, U., Ali, Qamar J., 2017, Firm Size as Moderator to Non-Linear Leverage-Performance Relation: An Emerging Market Review, Binus Business Review 8, 99.
Fiegenbaum, A., S. Hart, and D. Schendel, 1996. Strategic Reference Point Theory. Strategic Management Journal 17, 219– 235
Firth, M., 1979. The Impact of Size, Stock Market Listing and Auditors on Voluntary Disclosure in Corporate Annual Reports. Accounting and Business Research, Vol. 9, No. 36, pp. 273-280
Gentry, William M., Hubbard, R. Glenn, 2004. Success taxes, entrepreneurial entry, and innovation. NBER Working Paper, vol. 10551
Graham, John R., 2003, Taxes and Corporate Finance: A Review, Review of Financial Studies 16, 1075–1129.
Graham, John R., 2006. “A Review of Taxes and Corporate Finance.” Foundations and Trends in Finance 1, p573–691.
Jason P., 2015. Stability in tax. Unpubilished work, Think Ahead ACCA, London
Kim, K., Patro, S., Pereira, R., 2017. Option incentives, leverage, and risk-taking. Journal of Corporate Finance, Vol. 43, p1-18
31 / 35 Lane, D. J., F. X. Gibbons, 2007. Social Comparison and Satisfaction: Students’ Reactions after Exam Feedback Predict Future Academic Performance1. Journal of Applied Social Psychology 37(6), 1363–1384
Leftwich, R., 1981. Evidence of the Impact of Mandatory Changes in Accounting Principles on Corporate Loan Agreements. Journal of Accounting and Economics, Vol. 3, No. 1, pp. 3-36
Ljungqvist A., Zhang L, and Zuo L., 2017. Sharing risk with the government: How Taxes Asset Corporate Risk Taking. Journal of Accounting Research, Vol.55, No.3
Ilgen, D., 1971. Satisfaction with Performance as a Function of the Initial Level of Expected Performance and the Deviation from Expectations. Organizational Behavior and Human Performance 6, 345–361.
Niresh J.A., & Velnampy, T., 2014. Firm Size and Profitability: A Study of Listed Manufacturing Firms in Sri Lanka. International Journal of Business and Management, 9, (4) 57-64
Ozgulbas, N., Koyuncugil, A. S., Yilmaz, F., 2006. Identifying the Effect of Firm Size on Financial Performance of SMEs. The Business Review, Cambridge, 6(1), 162–167.
Raj V. Mahto, Dmitry Khanin, 2015. Satisfaction with Past Financial Performance, Risk Taking, and Future Performance Expectations in the Family Business. Journal of Small Business Management, 53(3), pp. 801–818
Solow, Robert M., 1956. A Contribution to the Theory of Economic Growth. Quarterly Journal of Economics 70, 65–94.
Souissi, M., & Khlif, H., 2012. Meta-analytic review of disclosure level and cost of equity capital. International Journal of Accounting and Information Management, 20(1), 49-62.
32 / 35 Effective Corporate Tax Rate and Its Influential Factors: Empirical Evidence from Emerging European Markets. Emerging Markets Finance and Trade 54, 571–590.
33 / 35
Appendix
Country 2007 2008 2009 2010 2011 2012 2013 2014 Austria Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Belgium Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Czech Republic 5 5 5 5 5 5 5 5 Denmark Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Estonia 0 0 0 0 0 0 0 0
Finland 10 10 10 10 10 10 10 10 France Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Germany Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Greece 5 5 5 5 5 5 5 5
Hungary Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Iceland 10 10 10 10 10 10 10 10 Ireland Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Italy 5 5 5 5 5 Infinite Infinite Infinite Latvia 5 5 5 8 8 8 Infinite Infinite Luxembourg Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Netherlands 9 9 9 9 9 9 9 9
Norway Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Poland 5 5 5 5 5 5 5 5
Portugal 6 6 6 6 4 5 5 12
Slovakia 5 5 5 7 7 7 7 4
Slovenia Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Spain 15 15 15 15 15 18 18 18
Sweden Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite
Switzerland 7 7 7 7 7 7 7 7
34 / 35 Figure 4 Statutory Loss Carryback Periods
