Corporate governance, insider ownership and risky investments in R&D projects: developed and emerging markets

In developed countries proportion of independent directors negatively influence R&D investment intensity. 1% increase in proportion of independent directors leads to decrease in R&D investment intensity by 0,003 points. The coefficient is significant on 5% significance level. Standard error is equal to 0,001. That shows that coefficient deviation is not very high.

The table shows the effect of the factors on R&D investments intensity in the developed markets. The second column reports the results using OLS linear model, the third column represents the results of regressions with robust errors, the fourth column shows results of median regression, the last column shows results of model with robust errors and Huber Iterations. Number of observations, regression R² are given in the last three rows. ***, **, * shows significance 1%, 5%, 10% respectively.

Table III Main results in the developed markets

VARIABLES	Linear Model	Robust Regression	Median Regression	Robust Regression with Huber Iterations
PERC_IND_DIR_DC	-0.003**	-0.003**	-0.002	-0.002**
	(0.001)	(0.001)	(0.001)	(0.001)
CEO_DUALITY_DC	-0.016	-0.016	-0.046	-0.037
	(0.034)	(0.037)	(0.039)	(0.029)
SCIEN_CON_DC	0.053	0.053	0.037	0.035
	(0.033)	(0.035)	(0.038)	(0.028)
INS_OWN_DC	-0.002	-0.002	-0.002	-0.002
	(0.002)	(0.002)	(0.002)	(0.002)
WACC_DC	0.01*	0.001	0.003	0.01**
	(0.005)	(0.006)	(0.006)	(0.004)
FCF2013_DC	-3.68e-08	-3.68e-08	1.13e-06	-1.07e-06
	(2.50e-06)	(1.30e-06)	(2.84e-06)	(2.62e-06)
EBITDA_VAR_DC	0	0	0	0
	(0)	(0)	(0)	(0)
BIOTECH_DC	0.027	0.027	0.124***	0.066**
	(0.034)	(0.039)	(0.0399)	(0.029)
USA	0.357**	0.357***	0.246	0.242**
	(0.145)	(0.106)	(0.165)	(0.121)
Constant	0.057	0.057	0.06	0.046
	(0.134)	(0.084)	(0.152)	(0.111)
Observations	258	258	258	257
R-squared	0.085	0.085		0.117
Pseudo R-squared			0.084
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

The table shows the effect of the factors on R&D investments intensity in the emerging markets. The second column reports the results using OLS linear model, the third column represents the results of regressions with robust errors, the fourth column shows results of median regression, the last column shows results of model with robust errors and Huber Iterations. Number of observations, regression R² are given in the last three rows. ***, **, * shows significance 1%, 5%, 10% respectively.

Table IV Main results in the emerging markets

VARIABLES	Linear Regression	Robust Regression	Median Regression	Robust Regression with Huber Iterations
PERC_IND_DIR_EC	0.00012*	0.00012*	0.00014*	6.97e-05
	(8.48e-05)	(8.53e-05)	(7.97e-05)	(5.83e-05)
CEO_DUALITY_EC	0.002	0.002	0.001	0.003*
	(0.002)	(0.002)	(0.002)	(0.002)
SCIEN_CON_EC	0.006**	0.006***	0.005**	0.005***
	(0.002)	(0.002)	(0.002)	(0.002)
INS_OWN_EC	-2.22e-05	-2.22e-05	-4.00e-05	-5.51e-05
	(5.60e-05)	(5.34e-05)	(5.26e-05)	(3.84e-05)
WACC_EC	0.001**	0.001*	0.001	0.001
	(0.001)	(0.001)	(0.001)	(0.0004)
FCF2013_EC	2.08e-08	2.08e-08	9.54e-09	3.35e-08
	(6.83e-08)	(2.30e-08)	(6.42e-08)	(5.87e-08)
EBITDA_VAR_EC	0	0***	0	0
	(0)	(0)	(0)	(0)
PHARMA_EC	0.002	0.002	0.005	0.005*
	(0.004)	(0.005)	(0.004)	(0.003)
BIOTECH_EC	0.003	0.0036	0.007	0.009**
	(0.005)	(0.006)	(0.005)	(0.004)
CHINA	0.009	0.009**	0.009	0.006
	(0.007)	(0.004)	(0.006)	(0.006)
INDIA	0.018**	0.018***	0.014*	0.008
	(0.007)	(0.006)	(0.007)	(0.006)
Constant	-0.013	-0.013*	-0.012	-0.006
	(0.009)	(0.007)	(0.009)	(0.007)
Observations	214	214	214	213
R-squared	0.183	0.183		0.176
Pseudo R-squared			0.1134
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

CEO duality has a negative coefficient (-0,016), but it is not significant. Standard error is rather high (0,034). That shows that the variance among the fir is very high.

Scientific connections have a positive coefficient (0,053), but they are not significant in developed countries.

Insider ownership is also not significant. The coefficient is negative (-0,002) and have high standard error (0,002).

Concerning other control variables, the model shows that WACC and dummy for USA matters for companies' R&D investment intensity. WACC have positive connection with R&D investment intensity (coefficient is equal to 0, 01 for linear regression, 0,001 for robust regression), but the standard error is quite high (0,005 for linear regression, 0,006 for robust regression).

Dummy for USA coefficient is positive (0,357) and significant on 5% level for linear model and 10% level for robust model. There is no significant influence of Free Cash Flow for 2013, EBITDA variance and industry dummy for biotech companies.

As the R&D investment distribution is asymmetric (Appendix V and Appendix VI), the median regression is useful for analyzing the effect of investigated factors. In contrast to ordinary least squares method that approximates the conditional mean, median regression approximates the conditional median. For the developed countries sample Median regression shows that percentage of independent directors is not significant on 10% significance level. But it is important to note that percentage of independent directors is significant on 15% significance level (p-value= 0.145). Considering median regression, coefficient for dummy variable for biotech industry is extremely significant (p-value=0.002) and equal to 0.124.

Regression with Huber Iterations provided results that are similar to described above. The only difference is significance of dummy for biotech industry. Coefficient for biotech dummy variable is equal to 0,066 and significant on 5% significance level. That can be explained by the fact that after weighting down all the outliers biotechnological companies in developed countries invest significantly more in R&D.

Results for the emerging countries are presented in Table IV.

Regressions build on the emerging countries sample is significant (p-value =0.004). For linear and robust regressions R² is equal to 18,3%, for median regression R² comprise 11,3%, for robust regression with Huber Iterations R² is equal to 17,6 %. This results show that explanation power of the model is higher in the emerging markets.

Linear and robust model results are close.

Proportion of independent directors positively influences R&D investment intensity in the emerging markets. 1% increase in proportion of independent directors leads to increase in R&D investment intensity by 0,00012 points. The coefficient is significant on 10% significance level. Standard error is rather high concerning low coefficient for proportion of independent directors.

CEO duality positively influences R&D investment intensity (coefficient is equal to 0,002), but the connection is not significant. Standard error is rather high (0,002).

Scientific connections have sufficient effect on R&D investment intensity in the emerging markets. The coefficient is equal to 0,006 and significant on 1% significance level.

Insider ownership does not significantly influence R&D investment intensity in the emerging countries.

Concerning other control variables, the model shows that WACC and dummy for countries have significant effect on corporate R&D investment intensity. As in developed countries, in emerging countries WACC have positive connection with R&D investment intensity (coefficient is equal to 0,001), but the standard error is quite high (0,001).

Dummy for India have positive coefficient (0,018) and it is significant on 5% level for linear and robust model. In the robust model, dummy variable for China also matters (coefficient is equal to 0.009; standard error is equal to 0,004). There is no significant influence of Free Cash Flow for 2013, EBITDA variance and industry dummy for biotech companies.

Median regression shows the results similar to OLS regression. Percentage of independent directors and scientific connection is significant on 1% significance level. CEO duality and insider ownership have no significant influence on R&D investment intensity.

Regression with Huber Iterations provided results that are similar to described above. The difference can be found in WACC significance and significance of dummy for biotech and pharmaceutical industries. The reason of the WACC non-significance after weighting down the outliers can be due to the fact that the most risk-loving and the most risk-averse companies' influence was eliminated. As WACC is used as proxy for companies' risk appetite, the weighting could mitigate the risk appetite influence.

Coefficient for pharmaceutical industry dummy is equal to 0,005 and significant on 10% significance level. Coefficient for biotech industry dummy is equal to 0,009 and significant on 5% significance level. That can be also explained by the fact that after weighting down all the outliers biotechnological and pharmaceutical companies in developed countries invest significantly more in R&D.

As a whole, regression results shows that corporate governance characteristics have different influence on R&D investment intensity in the developed and the emerging markets. Proportion of independent directors is associated with lower R&D investment intensity in the developed markets and higher R&D investment efficiency in the emerging markets. CEO duality and insider ownership is not significant regardless the development stage. Control variable shows the same effect both in the developed and in the emerging markets.

Robustness of Main Results

In order to check the stability of main results we build several models (linear models, model with Huber Iterations, median model) that have showed similar results.

We additionally checked these models on different parts of the sample to make sure that the identified relationship is not occasional. Regressions build on different sample's part shows the stability of our results.

3. Potential Explanation of Our Main Results

Why do independent directors have different influence on R&D investment intensity in developed and emerging markets?

Our empirical results show that proportion of independent directors negatively influence corporate R&D investments in developed countries and positively influence risky R&D investments in emerging countries. As the governance mechanisms are used in order to improve companies' efficiency the question of optimal R&D investment arises. Summary statistics shows that not only the R&D investment intensity is higher in emerging countries, but also absolute volume of R&D investments is higher. Such results can be explained by the fact that such huge investments are excessive and corporate governance decreases them to more optimal level. Such explanation is in line with recent research, conducted by Chan, Lin and Wang (2015). They studied the effect of R&D investment cuts in USA and found out that R&D investment cuts positively influence corporate performance and stock price. Scholars conclude that empirical results show that overinvestment in R&D exists and R&D investment cuts resolve the problem of non-optimal resource allocation.

Such results are in line with the explanation that in developed countries companies pay extra attention to R&D and they excessively invest in it. We distinguish the possible reasons of overinvestment in R&D in developed countries and underinvestment in R&D in emerging countries.

A. Life Cycle Issue

Companies have different potential of R&D projects on different stage of their life cycle. Young companies in biotech and pharmaceutical industries often do not have commercial-stage products, but have sufficient growth potential. Thus for young companies it is essential to make significant R&D investments. For mature companies that have approved products it can be more rational to have stable moderate R&D. This explanation is in line with Lambertini and Mantovani (2010) and Chan, Lin and Wang (2015). In USA and Japan there are a lot of stable healthcare companies that have a lot of commercialized products. Such companies can have excess R&D investments and R&D investment reduction can be the optimal strategy. Thus, improvement of corporate governance can lead to more optimal strategy. Concerning incentives of management to underinvest, in developed markets such negative effect can be mitigated by optimal reword system such as stock based compensation. Managers are personally involved in company's operations and independent director' opinion can be extremely useful for objective R&D projects' evaluation.

In emerging markets, young companies with high growth potential prevail. High risk and high information asymmetry leads to investment distortion. Risk-averse managers try to protect their position and reputation and underinvest in R&D projects. Empirical evidence of such effect in the emerging markets was proposed by Hasan, Raymer and Song (2015). Scientists claim that management discretion is higher in the emerging markets and superior corporate governance mitigates this problem.

B. Corporate disclosure matters

Biotech and pharmaceutical companies are concerned about investors' attitude to them. As such companies commonly attract investors' funds to finance their projects, they want to make signal of their future prospects. According to Chan et al. (2015), R&D investments are perceived as positive signal that indicates future development and benefits for investors. The difference of developed and emerging markets appears because of different corporate disclosure level.

In developed countries the level of disclosure is higher and investors pay extra attention to companies' investments in R&D (Chan, Lin, and Wang 2015). Managers try to establish favorable reputation and signal to investors that their company is high-tech by increasing of risky innovative investments. That leads to excess R&D expenditures. Independent directors are often not tightly connected with all the chain of corporate processes including the investor relations. They would rather concern about investment efficiency that about signaling function of R&D expenses.

In emerging countries the disclosure level is not high and investors evaluate rather the idea and scientific perspectives than financial statements. Moreover, companies in emerging markets have fewer opportunities to raise additional capital. Such effect was described by Harvey, Lipson, and Warnock (2008). In case companies have tight budget constraints, managers are even more risk-averse. They will think that in case of failure they will lose their bonuses and even their position. Independent directors in the board will be more adequate in projects' evaluation in such case. Thus, the increase of independent directors' proportion can cause higher R&D investment intensity.

C. Institutional environment

Company's investment strategy can be also connected with external governance. Institutional environment is very important in decision-making process. In developed countries a lot of external incentives to make innovations exist. There is an established mechanism of getting grants or subsidies from the government. That is why the decision making process in companies is adapted to the fact that government encourage innovations. In emerging countries the system of innovation incentives also exists. But it is not steady yet, and firms have not adopted the positive government's attitude toward R&D investment.

However, in weak institutional environment the effect of corporate governance mechanisms is more significant. The reason of such pattern is the substitution effect between external and internal governance. Similar concept was investigated by Hasan et al. (2015). Scientists studied 13 countries in emerging markets and showed that the relationship between corporate governance and corporate R&D investments is stronger in countries with weak country governance.

Thus, the different effect of independent directors in developed and in emerging markets can be explained. We suppose that our results are due to the fact that there is overinvestment in R&D in developed markets and underinvestment in R&D in emerging markets. Higher proportion of independent directors decreases that investment distortion.

It is not matter whether a CEO is also Chairman of the Board

The effect of CEO duality on corporate R&D investments is not significant regardless the type of the market. This finding is in line with the literature that propose that the leadership type do not influence investment process and corporate performance (Daily and Dalton, 1997; Dahya and McConnell, 2005). The effect of concentration power by CEO can have different effect on company's performance depending on CEO characteristics. Considering risky R&D investments the most important characteristics is CEO risk preferences.

Existing literature proposes empirical evidence of different CEO attitude towards risk. Aggarwal and Samwick (2006) research shows that CEO duality negatively influence investment process as CEO is risk-averse and avoid additional responsibilities of investment project choice. Malmendier and Tate (2005) show that CEO is personally involved in company's development and often overconfident about his abilities. Overconfident CEO can overestimate his abilities to increase the enterprise value and undertake too many risky projects.

We claim that both effects exist and the prevalence of one of them depends on CEO personal characteristics. Our empirical findings can be the result of two scenarios: 1) rather risk-neutral CEO that does not distort corporate risky R&D investments; 2) heterogeneous CEOs that have different attitude toward risk. Risk-averse CEO would rather underinvest in risky R&D projects. Overconfident CEO is rather risk-lover and such type of executive managers would rather overinvest in the projects that can bring innovations to the company. Risk-neutral CEO would not distort corporate R&D investment level.

The second explanation appears to be more probable because existing literature revealed that CEO duality does matter for particular markets and industries (Daily and Dalton, 1992; Pi and Timme, 1993; Baliga, Moyer and Rao, 1996; Bertrand and Mullainathan, 2003; Aggarwal and Samwick, 2006).

However, we suppose that the prevalence of risk-neutral CEO is also possible. Despite general heteroscedasticity of economic agents, CEO of pharmaceutical and biotechnological companies can be of one risk neutral type. The potential reason of such situation is self-selection. Risk-averse managers can be in the Board, but they unlikely will be CEO in such risky and volatile industries. Too risk-averse managers would negatively influence company's result and shareholders would rather change such CEO. We expect that managers in pharmaceutical and biotechnological companies are rather risk-loving, but in such case the CEO-Chairman separation would rather be significant.

Another possible explanation is the same attitude toward risk of both CEO and Chairman of the Board. In such case the CEO-Chairman separation will have limited effect. Our empirical results that show non-significance of CEO duality advocate in favor of this hypothesis.

Regardless the significance, it is interesting that CEO duality tend to have negative effect on R&D investments in developed markets and positive effect in emerging markets. That means that power concentration tend to decrease risky R&D investments in USA and Japan and increase risky R&D investments in China, India, Indonesia and Malaysia.

Insider ownership does not significantly influence R&D investments

Our regression analysis shows that proportion of insider ownership does not significantly influence corporate risky R&D investments both in developed and in emerging markets.

Insider ownership accounts for both managerial ownership and ownership of beneficial owners. That is why we cannot conclude on the effect of managerial ownership separately. The data of proportion of shares hold by managers is not available for emerging markets and we could not conduct more deep analysis.

The main result shows that increase of proportion of large shareholders in companies and increase of managers' stake do not positively influence R&D investments.

Existing literature propose that higher stake of beneficial owners have positive relationship with corporate performance (Pant and Pattanayak, 2007; Selarka, 2005). However, we should also account for specific features of pharmaceutical and biotechnological industries. Management of such companies requires specific knowledge, and shareholders cannot monitor the decisions or interfere company's operations. Even if a shareholder has stake more than 10% of the company, he does not significantly influence management process and strategy.

We should note that all the insider ownership that comprises both managerial and beneficial owners' ownership is not the best indicator for analysis. We cannot make any conclusion on the effect of proportion of stocks hold by managers. That fact does not allow us to clarify whether managerial ownership reduce agency problem or entrenchment effect prevails.

Overall, the results demonstrate that corporate governance do matter in investment process. CEO duality has no significant effect on corporate risky R&D projects while proportion of independent directors is supposed to decrease the investment distortion. In developed markets, where overinvestment in R&D is common, higher proportion of independent directors is associated with lower R&D investments. In emerging markets, where underinvestment in R&D is supposed, higher proportion of independent directors leads to higher R&D investments.

Independent directors improves scientific connection in emerging markets

It is essential to understand whether corporate governance influence collaborations with scientific institutions. That gives the understanding whether independent members in the Board and CEO-Chairman separation widen the innovation collaborations or not. Existing theory proposes two different effects concerning the number of independent directors: improving of operations because outside directors can objectively evaluate the projects (Osma 2008; Dong and Gou 2010) and deterioration due to the fact that they can be not aware of all the firm-specific information (Hoskisson et al, 2002). Within this research, it is important to precisely understand how collaboration with universities is linked to corporate governance.

In developed markets corporate governance and scientific connection are not correlated (correlation between scientific connection and percentage of independent directors is equal to -0.02, correlation between CEO duality and scientific connection is equal to 0.06). That means that corporate governance do not influence scientific collaboration potential.

In emerging markets moderate correlation (0.19) between proportion of independent directors and scientific connection exists. Correlation of CEO duality and scientific connection is small (-0.01).

For further analysis of the effect of corporate governance we build the regression of scientific connection on proportion of independent directors and CEO duality.

Regression results are presented in Table V. Regression is significant (p-value = 0.02), but model explanation power is not very high (R²=4%). Despite this fact we can conclude that higher proportion of independent directors positively influence scientific collaborations in the emerging markets. Graph I shows fitted values of scientific collaborations depending on proportion of independent directors.

Possible explanation of such results is based on the fact that companies in developed markets operate for a long time and have long established connections with different Research Institutes and Scientific Universities. Proportion of independent directors and CEO-Chairman separation might potentially improve that connections, but our model do not fix it because we account only for existence of collaboration (dummy variable).

The table shows the effect of corporate governance characteristics on scientific collaborations. The linear regression was used. Number of observations, regression R² are given in the last three rows. ***, **, * shows significance 1%, 5%, 10% respectively.

Table V. Scientific connection regression results in emerging markets

VARIABLES	Linear regression
Independentdirectors	0.006***
	(0.002)
CEOduality	-0.015
	(0.067)
Constant	0.276***
	(0.088)
Observations	216
R-squared	0.04
Standard errors in parentheses ***p<0.01, **p<0.05, *p<0.1

Graph I. Scientific connections and percentage of independent directoes

In emerging markets we analyze mainly young companies and we suppose that period of investigation fixed the period of establishing communications with scientific connections. In such conditions better corporate governance positively influence scientific collaborations.

Do superior R&D investments positively influence performance?

We determined that proportion of independent directors positively influence risky R&D investment intensity and emerging markets and negatively influence R&D investment intensity in developed markets. In understanding that findings it is important to understand the effect of R&D investments on corporate performance.

We studied the effect if R&D investment intensity on companies' performance. We used proxy of Q-Tobin to account for corporate performance. We assume perfect markets and we believe that market can estimate companies' future perspectives.

In developed markets corporate R&D investment intensity do not significantly influence Q-Tobin. The regression is not significant (Appendix VII), p-value = 0.6. That can be explained by the fact that in developed countries there are a lot of commercial-stage companies, and their Q-Tobin is determined rather by commercial success of their existing products than by their scientific progress.

In emerging markets we observe a different result. Corporate R&D investment intensity significantly influences Q-Tobin. The regression results are presented in Table VI. The regression is highly significant (p-value=0), Graph II shows 95% confidence interval for Q-Tobin dependence on corporate R&D investment intensity.

Such results show that market pays more attention to R&D in emerging markets. That can be explained by clinical stage of the majority of the pharmaceutical and biotechnological companies in emerging markets.

The table shows the effect of R&D investment intensity on Q-Tobin The linear regression was used. Number of observations, regression R² are given in the last three rows. ***, **, * shows significance 1%, 5%, 10% respectively.

Table VI. Q-Tobin regression results in emerging markets

VARIABLES	Linear regression
R_D_INTENSITY_EC	36.054***
	(8.557)
Constant	2.555***
	(0.236)
Observations	202
R-squared	0.08
Standard errors in parentheses ***p<0.01, **p<0.05, *p<0.1



Graph II. Q-Tobin and R&D investment intensity

4. Discussion

Obviously, we determined that corporate governance matters in investment decision-making process and higher proportion of independent directors is associated with higher risky R&D investment intensity. We also revealed that CEO duality and insider ownership have no significant effect on R&D investment intensity. However, we should not overinterpret such results.

We believe that the positive relationship between proportion if independent directors and risky R&D investment intensity can be the result of the non-observed firm quality characteristics. Such difference may appear as a result of experience or better human resources. As a result «more experienced firms» have better corporate governance and lower (in case of overinvestment) R&D investments in developed market. In emerging markets «better firms» have better corporate governance and higher R&D investment intensity. But we believe that even if such effect exists, the influence of proportion of independent directors on R&D investments exists. The effect can be lower than the coefficients in our models, but rational explanation together with empirical results propose that corporate governance does matter for firm operations.

Considering insider ownership, insignificance can be the result of bad approximation. One variable for both managerial and large shareholders ownership implies comprises different effects that can offset empirical results.

Conclusion

In this paper we examined how corporate governance and insider ownership influence corporate R&D investments in developed and emerging markets. We analyzed the data from pharmaceutical and biotechnological industries because R&D investments are extremely important in this sector.

Our empirical results revealed that the examined factors have different effect on risky R&D investments in developed and emerging markets.

In developed markets proportion of independent directors negatively influence R&D investment. As R&D investment volume is very large in such countries, we suppose that overinvestment can exist and better corporate governance decrease investment to make them closer to optimal. In emerging markets higher proportion of independent directors is associated with higher R&D investments. We suppose that such effect appear due to mitigating of the agency problem.

CEO - Chairman of the Board separation does not significantly influence corporate R&D investment intensity. The effect of this measure depends on the personal characteristics of managers and can be special in every firm. Considering pharmaceutical and biotechnological industries, we suppose that the attitude toward risk is similar for CEO and Chairman of the Board and that is the reason of insignificance of separation.

Insider ownership is also insignificant factor in determining of R&D investments. In can be due to the fact that not all the insiders can influence investment process. Moreover, beneficial owners can have no industry specific knowledge that allow them to monitor the process.

The research also shows in the emerging countries companies with higher proportion of independent directors have more scientific connections. In developed countries these factors are not connected.

The study revealed that higher R&D investments lead to higher expectations of investors. In developed markets there are no such relations.

An analysis of relationship between risky R&D investments ownership concentration is good subject for further research. People with special preferences invest in risky industries, and possibly they want to get high return on their investments. However, if they have large stake in a company they bear extremely high risk. It would be interesting to understand whether high ownership concentration leads to decrease of risky investments in order to decrease volatility of the business.

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Appendix I

Variables description

The table presents the description of the variables used in the analysis. The first column shows abbreviation used in regression, the second column shows variable description.

Table I. Variables description

SCIEN_CON	Dummy variable that registers whether a company has connection with Research University or Scientific Institute (1-collaboration exists, o-collaboration do not exist), 2014 data
PERC_IND_DIR	Percentage of independent directors in the Board, 2014 data
CEO_DUALITY	Dummy variable that indicates whether CEO-Chairman separation exists (1-no separation, 0-separation exists), 2014 data
ASSETS	Total assets of the company, 2015 data
EBITDA_VAR	Variance of EBITDA, calculated for 2011-2015 period
FCF2013	Free Cash Flow to the firm, 2013 data
WACC	Weighted Average Cost of Capital, 2015 data
INS_OWN	Percentage of stock outstanding held by insiders and beneficial owners, 2014 data
Q_TOBIN	Q-Tobin, ratio between a physical asset's market value and its replacement value, 2015 data
RESEARCH	Total expenditures on R&D activities, 2015 data
R_D_INT	The ratio of R&D expenditures to total assets, 2015 data
CAPEX	Total expenditures on R&D activities, 2015 data
BIOTECH_DC(EC)	Dummy variable that registers whether a company is biotechnological (1- biotechnological , o-other), 2015 data
PHARMA_DC(EC)	Dummy variable that registers whether a company is pharmaceutical (1- pharmaceutical , o-other), 2015 data

Appendix II

Normality tests

Normality test for developed countries' sample

Skewness/Kurtosis tests for Normality

Variable Obs Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2

R_D_INTENS 259 0.0000 0.0001 49.92 0.0000

PERC_IND_D 259 0.0000 0.0000 0.0000

CEO_DUALIT 259 0.0000 0.0000 0.0000

WACC_DC 259 0.0001 0.0000 28.42 0.0000

INS_OWN_DC 259 0.0000 0.0000 0.0000

FCF2013_DC 258 0.0000 0.0000 0.0000

EBITDA_VAR 259 0.0000 0.0000 0.0000

Normality test for emerging countries' sample

Skewness/Kurtosis tests for Normality

Variable Obs Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2

R_D_INTENS 218 0.0000 0.0000 59.51 0.0000

PERC_IND_D 218 0.0000 0.0007 24.57 0.0000

CEO_DUALIT 218 1.0000 0.0005 0.0000

EBITDA_VAR 215 0.0000 0.0000 0.0000

FCF2013_EC 218 0.0180 0.0000 0.0000

WACC_EC 218 0.0516 0.0396 7.49 0.0236

INS_OWN_EC 218 0.0000 0.7437 26.36 0.0000

Appendix III

Testing of regression for heteroscedasticity

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

Ho: Constant variance

Variables: fitted values of R_D_INTENSITY_DC

chi2(1) = 3.36

Prob > chi2 = 0.0668

Testing of regression for multicollinearity

vif

Variable VIF 1/VIF

FCF2013_DC 9.23 0.108307

EBITDA_VAR~C 6.26 0.159777

USA 3.39 0.294956

PERC_IND_D~C 1.77 0.563801

BIOTECH_DC 1.19 0.840040

WACC_DC 1.15 0.867669

INS_OWN_DC 1.11 0.903962

CEO_DUALIT~C 1.10 0.912280

SCIEN_CON_DC 1.04 0.957319

Mean VIF 2.92

Appendix IV

Testing of regression for heteroscedasticity

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

Ho: Constant variance

Variables: fitted values of R_D_INTENSITY_EC

chi2(1) = 29.84

Prob > chi2 = 0.0000

Testing of regression for multicollinearity

vif

Variable VIF 1/VIF

INDIA 7.40 0.135145

CHINA 7.01 0.142644

PHARMA_EC 1.76 0.569364

BIOTECH_EC 1.72 0.580259

PERC_IND_D~C 1.31 0.764650

EBITDA_VAR~C 1.21 0.823507

WACC_EC 1.15 0.873277

SCIEN_CON_EC 1.05 0.954550

FCF2013_EC 1.03 0.968551

INS_OWN_EC 1.03 0.969149

CEO_DUALIT~C 1.03 0.974364

Appendix V

R&D investment intensity distribution in developed markets

Appendix VI

R&D investment intensity distribution in emerging markets

Appendix VII

Q-Tobin regression results in developed markets

The table shows the effect of R&D investment intensity on Q-Tobin. The linear regression was used. Number of observations, regression R² are given in the last three rows. ***, **, * shows significance 1%, 5%, 10% respectively.

Table II. Regression is not significant (p-value=0.6)

VARIABLES	Linear regression
R_D_INTENSITY_EC	1.413
	(2.68)
Constant	4.513
	(1.05)
Observations	259
R-squared	0.001
Standard errors in parentheses ***p<0.01, **p<0.05, *p<0.1

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