Using the data of Chinese listed companies from 2012 to 2014, this paper empirically tests the relationship between managerial overconfidence and corporate R & D investment in the context of financing constraints by the method of multiple regression analysis, and further tests the impact of ownership type on the relationship. We find that: 1) Compared with the companies with weak financing constraints, the positive relationship between managerial overconfidence and corporate R & D investment in the companies with strong financing constraints is stronger; 2) In the context of strong financing constraints, compared with the state-owned companies, the positive relationship between managerial overconfidence and corporate R & D investment in the non-state-owned companies is stronger.
With China’s economic growth into the new normal, the “factor-driven” development model with a large amount of resource consumption has been unable to adapt to the trend of the times and economic transformation is imperative, so “innovation driven” will be the only way for China’s economic development. Firms are the main body of innovation and the factors that drive their innovation are various, among which two kinds of important factors are: managers and capital. Managers as the strategy makers directly determine whether the firms will pursue innovation activities with high income and high risk. With the development of behavioral finance, more and more scholars begin to pay attention to the influence of managerial irrational behavior on corporate innovation activities, especially managerial overconfidence. In addition, innovation activities have the characteristics of high income, high risk and long cycle, and the entire process requires a large amount of fund to support. But the capital market of our country starts late and develops slowly; there are many imperfections, such as the problem of information asymmetry and so on; all these will lead to differences between corporate internal and external financing cost, so that domestic companies are facing strong or weak financing constraints. Scholars have already studied the influence of managerial overconfidence and financial constraints on R & D investment respectively and obtained a more consistent conclusion. But there are no scholars to link the three together to study. Financing constraints can change the financing environment of R & D investment, which affects managerial R & D decision-making. But when managers are overconfident and in the face of financing constraints, what is the impact of their unique “irrational” psychological effects on R & D decision-making process? This is a question worth pondering. Therefore, the main question discussed in this paper is the relationship between managerial overconfidence and R & D investment in the context of financing constraints.
The rest of the article is organized as follows: the second part is theoretical analysis and research hypothesis; the third part is research design, including data sources, samples, models and variables explanation. The forth part is analysis of empirical result. And the fifth part is research conclusion.
Overconfidence is when people evaluate their ability or judge the probability of success, they will overestimate their actual level (sometimes called as “optimistic”). The studies of psychology suggest that humans (including experts) will show overconfidence in many aspects, but there are individual differences in the persistence and strength of confidence. Compared with ordinary people, managers are more prone to be overconfident. Managers are corporate strategy makers and their overconfident “irrational” psychology will have a significant impact on all aspects of companies. In R & D investment, the psychological effects of overconfidence can be summarized as follows:
1) Self-motivation. Innovation activities have high returns, but also have high risk and uncertainty, and the cycle is relatively long. Rational managers tend to avoid risks and will not take the initiative to pursue innovation activities. In order to avoid this “short-sighted behavior” of managers, a certain external incentive is needed, e.g. managerial incentives (monetary compensation incentive or equity incentive). However, managers who are overconfident tend to overestimate the benefits of innovation and underestimate the risks, and believe that they will succeed in the end, which creates an intrinsic self-motivation to actively pursue innovation. Galasso and Simcoe (2010) measure CEO overconfidence with stock option execution and empirically examine the relationship between managerial overconfidence and corporate innovation. They find that overconfident CEOs overestimate the benefits of innovation and underestimate the risks. They will pursue more innovation and are more likely to lead the company to a new technology direction, especially in the competitive industry [
2) Innovation motivation. Before the “innovation-driven” development strategy is formally put forward, innovation has always been regarded as an important indicator of a company’s competitiveness and potential. The success of innovation not only will bring high returns, but also bring a good reputation to the company. For managers, it is a manifestation of ability and vision. Galasso and Simcoe (2010) show that CEOs may show their ability of controlling the market through innovation [
3) Agency costs. Rational managers give up innovation activities for their own interest and thus violate the long-term interest of the shareholders, which will increase the cost of the principal agent. But overconfident managers are not. Fairchild (2005) finds that overconfident managers work harder, which will help alleviate agency problems [
In summary, managerial overconfidence can indeed promote corporate R & D investment, i.e. the relationship between the two is significantly positive. But when considering the factor of financing constraints, there will be any difference? Financing constraints are that in the imperfect financing market, due to large differences between internal and external financing costs, companies cannot pay external high financing costs, resulting in inadequate financing, which will cause that investment decisions are too dependent on internal fund and the investment level is below the optimal level [
H1: Compared with the companies with weak financing constraints, the positive relationship between managerial overconfidence and corporate R & D investment in the companies with strong financing constraints is stronger.
China is constructing a socialist market economy with Chinese characteristics. It can be said to be a combination of planned economy and market economy. Although the government has always stressed the importance and irreplacement of the market mechanism, the country’s economic development is still more subject to government’s intervention, which is an indisputable fact. This creates special difference between the state- owned companies and the non-state-owned companies: In the process of economic transformation, the state-owned listed companies need to assume the government’s social functions and will get some special care from the government. Managers in the state-owned company will pay more attention to the short-term performance and the political objectives. In addition, compared with the non-state-owned companies, the state-owned companies are more easily access to internal fund and external fund. This is because the state-owned companies have abundant assets and rich government relation resources, so they have more financing channels and bargaining power. When financing constraints are weak, two kinds of companies are easier to obtain fund from outside and the challenges of R & D investment are relatively weak, so the special difference between companies will not be reflected and there is no significant difference in the relationship between managerial overconfidence and corporate R & D investment. But in the context of strong financial constraints, compared with the non-state-owned companies, the state-owned companies can use some special financing channels to obtain financial support, and the R & D risk is not entirely taken by themselves, the government accordingly bear some of the risk. More importantly, the state-owned companies need to pay more attention to political objectives and the government will give some corresponding protection measures to allow them to survive in the fierce competition environment. So they will not be too persistent pursuit of innovation, when the fund is scarce, they can correspondingly reduce R & D investment. But the non-state- owned companies are not so lucky, even in the case of strong financial constraints, they can only rely on their own efforts to survive and in the rapidly changing Internet era innovation is an important way out. At this time, compared with the state-owned companies, the challenges the non-state-owned companies face in the R & D investment are more serious. But this also inspire overconfident manager’s “difficult effect” and they will be more determined to carry out R & D investment. To sum up, the following hypothesis is made:
H2: In the context of strong financing constraints, compared with the state-owned companies, the positive relationship between managerial overconfidence and corporate R & D investment in the non-state-owned companies is stronger.
This paper takes all the A-share listed companies from 2012-2014 in Shenzhen and Shanghai Stock Market as the initial research objects. Then adopting the following screening process: 1) excluding financial and insurance listed companies; 2) excluding the companies whose data is missing and abnormal; 3) excluding Special Treatment and Particular Transfer companies. After the above screening process, a total of 6615 observations are obtained finally. The data mainly comes from CSMAR and WIND. The data is collected and integrated by EXCEL to ensure the efficiency and accuracy.
In order to test H2, we divide the whole sample into two subsamples according to the company’s attributes, i.e. the state-owned company group and the non-state-owned company group. When the listed company’s attribute is state-owned, state holding, collective enterprise or government agency, then it is identified as a state-owned company. When the listed company’s attribute is private enterprise, Sino-foreign joint venture, wholly foreign-owned enterprise or other, it belongs to non-state-owned company. According to this standard, after the classification of 6615 observations, 4189 state- owned company observations and 2426 non-state company observations are finally obtained.
According to previous studies, we use the multiple linear regression model with cross-term to test the hypotheses. The multiple regression model is shown below:
RD = β 1 + β 2 OC + β 3 FC + β 4 OC ∗ FC + β 5 SIZE + β 6 LEV + β 7 TBQ + β 8 ROA + Β 9 SHARE + β 1 0 DUA + ε
1) R & D intensity (RD). The indicators of R & D investment are divided into two types: absolute indicator and relative indicator. The relative indicator is adopted by most scholars. So drawing on previous studies, this paper also selects R & D intensity as the dependent variable, which is measured by the ratio of R & D expenses to the corporate main business income.
2) Managerial overconfidence (OC). The independent variable in this paper is managerial overconfidence. Although managerial overconfidence in recent years has received more and more scholars’ attention, it is still very difficult to measure it reasonably and accurately. There are many methods of measuring overconfidence in the academic community, but it is difficult to find a consensus one. After the comprehensive consideration of various methods and the availability of data, we use the method of Hao Ying, Ye Bei and Rongwu Zhang [
3) Financing Constraints (FC). We introduce financing constraints as an important dummy variable into the model and examine whether the relationship between managerial overconfidence and R & D investment is significantly different under different levels of financing constraints. There are many ways to measure financial constraints in the empirical research, including univariate indicator and multivariate index. Similarly, it is difficult to find an agreed-upon approach to measure financial constraints.
Hadlock and Pierce (2010) collect a random sample from 1995-2004 and refute the validity of the KZ index in measuring financial constraints by empirical tests [
SA = − 0. 737Size + 0.0 43Size2 − 0.0 4 0 Age
When the SA value is positive and greater, it indicates that financing constraints are weaker. Many scholars have begun to recognize this method. So in this paper, the SA index is used to measure the level of financing constraints the company faces. The reasons are as follows: First, the SA index does not contain endogenous financial variables. In addition, the SA index is relatively robust, as the other scholars have said, the financial constraints levels classified according to the SA index are consistent with those classified according to the WW index and investment-cash flow sensitivity. Because the variable of finance constraints is dummy, we first calculate the SA index of all the observations and then find the mean of them. If the SA index of a observation is less than the mean, it is defined as strong finance constraints and FC equals 1. Otherwise, it is defined as weak finance constraints and FC equals 0.
4) According to the existing studies to choose the control variables, including: firm size, asset-liability ratio, Tobin q, return on assets, ownership concentration and duality (chairman and general manager). Chang X, Fu K and Low A [
Using SPSS to carry out descriptive statistics of the sample data, exploring the quantitative relationship between the variables. All the samples were divided into overconfident group and non-overconfident group. From
Variables | Code | Definitions |
---|---|---|
R & D intensity | RD | R & D expenses/corporate main business income |
Overconfidence | OC | If the number of shares held by the executive team in this year is more than that in the previous year, OC equals 1; otherwise OC equals 0 |
Financing constraints | FC | If the SA index of a observation is less than the mean of all observations, FC equals 1. Otherwise FC equals 0. |
Firm size | SIZE | Natural logarithm of total assets |
Asset-liability ratio | LEV | Total assets/Total liabilities |
Tobin q | TBQ | Market value of assets/The book value of assets |
Return on assets | ROA | Net profit/Average total assets |
Ownership concentration | SHARE | The proportion of the first largest shareholder |
Duality | DUA | If the chairman and general manager are the same person, DUA equals 1; otherwise DUA equals 0 |
Overconfident Group (N = 2430) | Non-overconfident Group (N = 4185) | Mean T test | |||||
---|---|---|---|---|---|---|---|
Mean | Median | Std. Dev. | Mean | Median | Std. Dev. | T value | |
RD | 0.0483 | 0.0375 | 0.0457 | 0.0232 | 0.0235 | 0.0168 | 31.998*** |
SIZE | 21.653 | 21.437 | 1.1331 | 21.942 | 21.762 | 1.2724 | −9.266*** |
LEV | 0.3467 | 0.3226 | 0.2021 | 0.4525 | 0.4508 | 0.2141 | −19.784*** |
TBQ | 0.0626 | 0.0569 | 0.0551 | 0.0409 | 0.0336 | 0.0762 | 12.303*** |
ROA | 2.5631 | 2.0281 | 2.1661 | 1.9041 | 1.4961 | 1.5991 | 14.135*** |
SHARE | 0.3421 | 0.3272 | 0.1401 | 0.3679 | 0.3554 | 0.1538 | −6.828*** |
DUA | 0.3461 | 0 | 0.4758 | 0.2327 | 0 | 0.4226 | 10.034*** |
***, **, *Significant at the 0.01 level, 0.05 level and 0.10 level.
Weak Financing Constraints Group (N = 1631) | Strong Financing Constraints Group (N = 799) | Mean T test | |||||
---|---|---|---|---|---|---|---|
Mean | Median | Std. Dev. | Mean | Median | Std. Dev. | T value | |
RD | 0.0556 | 0.0417 | 0.0514 | 0.0336 | 0.0286 | 0.0253 | 11.435*** |
SIZE | 21.043 | 21.058 | 0.5274 | 22.898 | 22.621 | 1.0136 | −59.318*** |
LEV | 0.2816 | 0.2509 | 0.1782 | 0.4795 | 0.4887 | 0.1816 | −25.557*** |
TBQ | 0.0629 | 0.0592 | 0.0526 | 0.0621 | 0.0511 | 0.0599 | 0.4069 |
ROA | 2.9792 | 2.3744 | 0.0599 | 1.7137 | 1.3054 | 1.4944 | 14.067*** |
SHARE | 0.3279 | 0.3092 | 0.1287 | 0.3707 | 0.355 | 0.1569 | −7.143*** |
DUA | 0.4101 | 0 | 0.4921 | 0.2152 | 0 | 0.4112 | 9.6648*** |
***, **, *Significant at the 0.01 level, 0.05 level and 0.10 level.
(0.0375) of R & D intensity in strong financing constraints group are both greater than those in weak financing constraints group, and the mean T test also shows a significant difference in the means of these two groups, suggesting that in the context of financing constraints the positive impact of managerial overconfidence on corporate R & D investment is more obvious. Although the above analysis results cannot prove the causal relationship between variables, to a certain extent this can reflect the possible relationship between variables, which is the evidence of the theoretical derivation of this paper.
In order to examine the impact of financing constraints on the relationship between managerial overconfidence and corporate R & D investment after comprehensive consideration of various related factors, next we will use STATA to carry on the multiple regression analysis. Since this paper uses unbalanced panel data, we first need to identify the effect model used for the regression, i.e. the random effect model or the fixed effect model. According to the conventional method, the selection of the effect model is determined by the Hausman test. The result is shown in
The multiple regression results of the fixed effect model are shown in
Chi-Sq. Statistic | Chi-Sq. d.f | Prob | |
---|---|---|---|
The effect model | 721.17 | 14 | 0.0000 |
Dependent Variable = RD | Suest test | |||
---|---|---|---|---|
(1) | (2) | (3) | ||
OC | 0.00195*** (2.84) | 0.00104** (1.00) | 0.00307*** (4.07) | |
FC | −0.00128* (−1.27) | −0.00204* (−1.43) | −0.00031* (−0.24) | |
OC*FC | 0.00309*** (3.56) | 0.00697*** (6.08) | 0.00268*** (2.17) | 0.0036 |
SIZE | 0.00602*** (8.38) | 0.00523*** (4.94) | 0.00715*** (8.44) | |
LEV | −0.01513*** (−6.25) | −0.01375*** (−4.13) | −0.018799*** (−5.88) | |
ROA | −0.02182*** (−6.44) | −0.01772*** (−4.16) | −0.04001*** (−7.04) | |
TBQ | −0.00042*** (−2.39) | −0.00038* (−1.66) | −0.00035* (−1.39) | |
SHARE | −0.00897** (−1.82) | −0.00628 (−0.82) | −0.00961* (−1.82) | |
DAULITY | 0.00041 (0.53) | 0.00073* (0.70) | −0.00033 (−0.35) | |
R2 | 0.0543 | 0.0318 | 0.1645 | |
N | 6615 | 4189 | 2426 |
***, **, *Significant at the 0.01 level, 0.05 level and 0.10 level.
the regression coefficient of the cross-term (OC*FC) is 0.00309 and the significant level reaches 1%. The results show that compared with the companies with weak financing constraints, 1% increase of managerial overconfidence can more increase the R & D investment by 0.309%, which proves that in the context of financing constraints the positive relationship between managerial overconfidence and corporate R & D investment is stronger and Hypothesis 1 is verified.
The second is the regressions of the state-owned company group and the non-state- owned company group. The results in the second and third column of
We have used the SA index to measure the financial constraints and verified the hypotheses in the previous chapter. In order to make the research results more reliable, we use the univariate indicator (the dividend payout ratio) as the proxy variable of the financing constraints in the robustness test section to verify the hypotheses again. Since the higher the dividend payout ratio is, the weaker the financing constraint faced by the firm are, so we first calculate the mean of the dividend payout rate of all the observations. Then we define the observation whose dividend payout rate is below the mean as strong financing constraints and define the observation whose dividend payout rate is above the mean as weak financing constraints. The results of multiple regression using this proxy variable are shown in
This paper uses the data of A-share listed companies in Shenzhen and Shanghai Stock Market during the period of 2012-2014 to empirically test the relationship between managerial overconfidence and corporate R & D investment in the context of financing constraints, measuring managerial overconfidence by the change of the number of shares held by the manager and measuring the financing constraints by the SA index. The results show that compared with the companies with weak financing constraints,
Dependent Variable = RD | Suest test | |||
---|---|---|---|---|
(1) | (2) | (3) | ||
OC | 0.00071** (0.95) | 0.00095** (0.85) | 0.00044*** (0.68) | |
FC | −0.00228* (−1.05) | −0.00188** (−1.12) | −0.00027** (−0.21) | |
OC*FC | 0.00249** (2.52) | 0.00234*** (1.67) | 0.00114** (1.89) | 0.0104 |
SIZE | −0.00136* (−1.45) | −0.00414** (−3.02) | 0.00332*** (3.77) | |
LEV | −0.01671*** (−5.60) | −0.01843*** (−4.44) | −0.01274*** (−3.99) | |
ROA | −0.02891*** (−4.92) | −0.03859*** (−4.61) | −0.01059** (−1.82) | |
TBQ | −0.00043** (−1.89) | −0.00057* (−1.98) | 0.00081** (2.28) | |
SHARE | −0.01666** (−2.76) | −0.03505* (−3.76) | 0.00386* (0.74) | |
DAULITY | 0.00118* (1.32) | 0.00155* (1.21) | 0.00048* (0.56) | |
R2 | 0.1711 | 0.1011 | 0.0947 | |
N | 5915 | 3912 | 2003 |
***, **, *Significant at the 0.01 level, 0.05 level and 0.10 level.
the positive relationship between managerial overconfidence and corporate R & D investment in the companies with strong financing constraints is stronger. In addition, we further test the impact of ownership on this relationship and find that in the context of strong financing constraints, compared with the state-owned companies, the positive relationship between managerial overconfidence and corporate R & D investment in the non-state-owned companies is stronger. In the robustness test, the dividend payout ratio is used as the proxy variable of financing constraints and then the regression test is carried out again. The research hypotheses are also supported and the conclusion is consistent.
The results of this paper show that the “irrational” psychology of managerial overconfidence has a positive side in corporate R & D investment. When corporate R & D investment faces more severe challenges (such as strong financing constraints), the psychological effect of overconfidence will be more prominent and thus its promoting effect on corporate R & D investment is also more obvious. And this effect will be affected by ownership. It is an indisputable fact that China’s capital market starts late, develops slowly and has many imperfections. It is difficult to improve these shortcomings in a short time, so companies will face serious financial constraints, especially small and medium companies, which will further affect companies’ innovation activities. In recent years, the government has paid more and more attention to corporate innovation activities, introducing many related policies to stimulate corporate innovation investment. And with the process of economic globalization, the pressure of competition among companies is increasing, which highlights the importance of innovation. Therefore, in addition to external motivation, the companies should be based on their own situations and appropriately employ some overconfident managers, so that these managers can play an active role in innovation activities. However, as mentioned earlier, because managerial overconfidence cannot be directly observed, it is relatively difficult in the academic community to measure it accurately. So in reality, how to identify whether a manager is overconfident? One possible approach is to use personality test questionnaire to determine whether managers are overconfident. In order to ensure the quality of the questionnaire, we should seek the help of professional psychologists to design a sufficient professional psychological questionnaire.
The contribution of this paper is to introduce the variable of financing constraints, focusing on studying the relationship between managerial overconfidence and corporate R & D investment in the context of financing constraints. Financing constraints are very suitable for the current situation of China’s capital market. In this context the research on the relationship between managerial overconfidence and corporate R & D investment has great practical significance. The main drawback of this paper is that it only studies the effect of managerial overconfidence on R & D investment in the context of financial constraints and does not study its impact on R & D output and subsequent performance. These problems can be further explored in the future.
Liang, T.Y. and Mo, X.T. (2017) Research on the Relationship between Managerial Overconfidence and Corporate R & D Investment in the Context of Financing Constraints. Open Journal of Business and Management, 5, 22-33. http://dx.doi.org/10.4236/ojbm.2017.51003