Does Board Size Affect Initial Public Offering Underpricing?

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Introduction

Investors are interested in the post-IPO performance of companies, and they consider various factors when making a pre-IPO judgment about investing in new stocks. When IPO is finished, firms may encounter a situation referred to as underpricing, which means that the stock price of the issuing firm declines after the first-day closing. The board structure is one of the determinants of post-IPO performance.

The characteristics of the firm’s board include the number of board members, independent directors, experience, presence of woman directors, and others. In the current study, the number of board directors is considered and its effects on IPO underpricing are investigated. There have been many types of research, as discussed in the literature review, which gives conflicting results regarding the impact of board size on IPO underpricing that is also explored in this study. The research question set for this study is: does board size affect IPO underpricing?

Literature Review

Initial Public Offering (IPO) is the first-time launch of a firm’s stocks on an exchange to institutional and retail investors. The IPO is underwritten by a financial institution and its pricing is based on the financial valuation of the firm (Dolvin & Kirby, 2016). IPO underpricing refers to the situation when the stock price falls below the first-day level in the post-IPO period (Dolvin & Kirby, 2016). If a firm experiences underpricing, then it can adversely affect shareholders’ confidence and there could be a flight of capital.

The theoretical framework of the current study is drawn from the signaling theory that states that firms need to send positive signals to market participants, including investors, to show their worth and prospects. A firm with a small board size is viewed positively by investors because they believe that decision-making in such a company is easier and quicker, which is necessary for business growth (Sriram, 2018).

On the other hand, Johl, Kaur, and Cooper (2015) concluded that a larger board is viewed positively by investors as they see it as a way of acquiring more resources. As noted earlier, the signaling theory is suggestive of a positive association between board size and IPO underpricing based on the underlying assumption that the board size represents or “signals” a firm’s quality to investors. A general perception can be established that a large board size would have a positive influence on the IPO underpricing.

However, empirical evidence does not support this assumption in every case. The researchers have also concluded a negative association between board size and IPO underpricing. Thus, the relationship between the board size and IPO underpricing has been identified by researchers in the past as both negative and positive.

Sahoo (2014) argued that a large board size and board committees facilitate better monitoring and reporting of business activities that reduce information asymmetry. The result of their study of 176 Indian IPOs concluded that the relationship between board size and IPO underpricing is positive, which implies that investors view firms with a large board size to be using significant resources that might hinder business growth. Furthermore, firms’ board size was found to have a positive relationship with post-listing price volatility and rate of subscription.

Moreover, Singh and Maurya (2018) argued that board size is an independent measure of corporate governance. The study conducted by Malafeev (2018) focused on understanding the impact of board size on IPO underpricing and came up with a conclusion that there exists a negative relationship between them.

Another study by Anand and Singh (2019) provides a comprehensive understanding of the nature of the relationship between board size and IPO underpricing. It conducted that there is a negative relationship between the two variables. Similar conclusions have been reached by Dolvin and Kirby (2016) in their study as they found an inverse relationship between the number of directors on the firm’s board and IPO underpricing.

Apart from these findings, there are a few studies in the past that could not determine a significant association between these two variables. Kubicek, Stamfestova, and Stouhal (2016) carried out their research to understand how board ownership and IPO returns are linked with each other. In doing so, they were able to conclude an insignificant relationship between board size and IPO underpricing. A study by Kubíček, Strouhal, and Štamfestová (2017) hypothesized a negative relationship between board size and IPO underpricing and failed to find evidence for it among a sample of 75 IPOs in Central Europe.

Other studies, in this regard, were conducted by Mehorta (2016) and Mishra and Kapil (2017). They studied the relationship between IPO and board governance and considered board size among other variables. The test between the variables was based on the data of IPO firms operating in India. The researchers noted in their study that IPO firms do not have access to the necessary resources and also face problems in establishing their brand name in the market which is critical to the success of their operations.

In this context, the researchers referred to the resource dependence theory based on the rationale that IPO firms are relatively new in the market and have a significant dependency on the resources available in the market. Loughran, Ritter, and Rydqvist (2016) have noted that having a larger board size results in low underpricing and it is considered favorable in the long run for IPO firms. Furthermore, the study by Mahatidana (2017) concluded a negative association between the variables, and they noted that when the board size of a firm is large, underpricing can be expected to be lower.

Hypothesis Development

There has been a lot of research including Sriram (2018) and Dolvin and Kirby (2016) indicating that small board size is favorable and has a positive impact on the post-IPO performance of firms. However, others, including Johl et al. (2015) and Sahoo (2014), suggest that large board size is favorable. The literature discussed in this section provides three different views about the impact of board size on IPO underpricing including (1) inverse relationship; (2) direct relationship; and (3) no relationship. The current study focuses on the first view that there is an inverse relationship between the two variables. The hypothesis drawn from the review of previous studies, including Malafeev (2018), is presented in the following:

H: IPO underpricing is negatively associated with the board size.

It implies that the expected outcome of the statistical test is a negative coefficient of the slope between board size and IPO underpricing. The significance of this relationship is also assessed by comparing the p-value with the alpha value of 5% at the assumed confidence level of 95%.

Research Method

The current study follows the positivist paradigm to carry out quantitative research that aims to test the relationship between board size and IPO underpricing. The deductive approach used in this study sets up a hypothesis for testing this relationship through mathematical validation. The study performs multivariate regression analysis to develop a model that predicts changes in the values of the dependent variable affected by four variables.

Formula

Where, ε1 = Error Term

The dependent variable is LNUNDERPRICING which is the natural logarithm of underpricing fraction which is calculated as follows:

Formula

The independent variable is LNBSIZE which is the natural logarithm of the number of board members in a firm. There are three control variables also included in the model, which are LNASSETS, BIGN, and AUDCOM. LNASSETS is the natural logarithm of total assets value recognized on the proforma balance sheet of an IPO firm. AUDCOM is a dummy variable representing the absence (0) or presence of an audit committee (1). BIGN is also a dummy variable that has two values 0 and 1 representing the non-employment and employment of an external auditor from Big 4 accounting firms.

The sample size is 50, which is selected by using a random sampling technique (Creswell & David, 2017). The sample includes firms belonging to different industries, excluding financial and real estate sectors. These firms launched their IPOs on the Australian Securities Exchange (ASX) during five years from 2009 to 2013. The data of these companies is shown below.

Table 1. IPOs on the Australian Securities Exchange.

YEAR Company Code Listing date Issue price Closing price at the end of first day of trading Underpricing fraction LNUNDERPRICING BIGN Boardsize LNBSIZE Audit Committee Total Assets LNASSETS
2009 AUC 12/16/09 0.2 0.22 0.1 0.09531018 0 4 1.386294361 1 7,533,823.00 15.83491317
2009 SMR 12/9/09 0.2 0.4 1 0.693147181 0 5 1.609437912 0 10,655,248.00 16.1815631
2009 MMI 12/4/09 0.25 0.185 -0.26 -0.301105093 0 4 1.386294361 0 12,341,260.00 16.32845868
2009 PSC 12/4/09 0.2 0.195 -0.025 -0.025317808 0 4 1.386294361 0 3,876,459.00 15.17043267
2009 THD 11/12/09 0.2 0.17 -0.15 -0.162518929 0 4 1.386294361 0 2,719,097.00 14.8158104
2009 OXX 11/6/09 0.3 0.35 0.17 0.157003749 0 3 1.098612289 1 92,233,000.00 18.33982854
2009 GES 10/27/09 0.2 0.16 -0.2 -0.223143551 0 4 1.386294361 1 4,655,789.00 15.35362195
2009 MSE 10/16/09 0.2 0.235 0.18 0.165514438 0 3 1.098612289 1 8,477,532.00 15.95292993
2009 TON 8/14/09 0.2 0.215 0.075 0.072320662 0 5 1.609437912 0 11,196,247.00 16.23108919
2009 PKO 12/2/09 0.35 0.53 0.51 0.412109651 0 4 1.386294361 1 12,990,137.00 16.37970094
2010 UNV 12/10/10 0.26 0.26 0 0 0 5 1.609437912 0 27,380,756.00 17.12535099
2010 RNU 12/15/10 0.2 0.225 0.13 0.122217633 0 5 1.609437912 1 10,717,573.00 16.18739529
2010 SUH 1/5/10 0.25 0.38 0.52 0.418710335 0 6 1.791759469 0 19,658,569.00 16.79402388
2010 SHH 2/18/10 0.2 0.17 -0.15 -0.162518929 0 4 1.386294361 1 8,556,112.00 15.96215644
2010 VKA 5/12/10 0.3 0.275 -0.083 -0.086647807 0 4 1.386294361 1 13,972,915.00 16.45263137
2010 DAU 8/23/10 0.5 0.56 0.12 0.113328685 0 3 1.098612289 1 23,668,729.00 16.97966528
2010 HE8 10/20/10 0.2 0.22 0.1 0.09531018 0 3 1.098612289 0 2,266,000.00 14.63352672
2010 ANW 10/21/10 0.2 0.21 0.05 0.048790164 0 3 1.098612289 1 6,384,849.00 15.6694384
2010 SGQ 11/16/10 0.2 0.235 0.18 0.165514438 0 3 1.098612289 0 4,020,976.00 15.20703522
2010 EPW 12/10/10 1.75 1.81 0.034 0.033434776 1 6 1.791759469 1 748,033,000.00 20.43295765
2011 BCK 11/1/11 0.2 0.23 0.15 0.139761942 0 5 1.609437912 1 1840174 14.42537069
2011 BID 27/1/11 0.2 0.22 0.1 0.09531018 0 3 1.098612289 0 5,463,884.00 15.51367045
2011 AGE 3/2/11 0.2 0.225 0.13 0.122217633 0 5 1.609437912 0 20,267,289.00 16.82451877
2011 CXO 11/2/11 0.2 0.21 0.05 0.048790164 0 3 1.098612289 0 8,213,324.00 15.92126827
2011 TGM 7/4/11 0.2 0.23 0.15 0.139761942 0 4 1.386294361 1 5,774,810.00 15.56901591
2011 AZY 20/4/11 0.2 0.205 0.025 0.024692613 0 5 1.609437912 1 10,897,320.00 16.20402745
2011 INF 15/4/11 0.2 0.35 0.75 0.559615788 0 3 1.098612289 0 3,163,104.00 14.96706438
2011 AHK 9/5/11 0.2 0.23 0.15 0.139761942 0 5 1.609437912 1 5,593,866.00 15.5371812
2011 GLN 8/6/11 0.2 0.22 0.1 0.09531018 0 3 1.098612289 0 2,703,299.00 14.80998344
2011 IKW 19/7/11 0.2 0.215 0.075 0.072320662 1 3 1.098612289 1 32,298,680.00 17.29053692
2012 IVZ 19/1/12 0.2 0.24 0.2 0.182321557 0 4 1.386294361 0 10,225,297.00 16.14037531
2012 CHK 1/2/12 0.2 0.22 0.1 0.09531018 0 3 1.098612289 0 2,845,029.00 14.86108382
2012 AJQ 26/4/12 0.5 0.44 -0.12 -0.127833372 0 6 1.791759469 1 81,287,013.00 18.21349682
2012 AHQ 29/5/12 0.2 0.12 -0.4 -0.510825624 0 4 1.386294361 1 10,197,000.00 16.13760412
2012 ATU 24/7/12 0.2 0.18 -0.1 -0.105360516 0 4 1.386294361 0 8,447,455.00 15.94937577
2012 AQI 19/9/12 0.2 0.21 0.05 0.048790164 0 3 1.098612289 0 2,438,163.00 14.70675544
2012 VIC 9/10/12 0.2 0.195 -0.025 -0.025317808 0 4 1.386294361 1 4,445,139.00 15.3073217
2012 BAT 29/10/12 0.2 0.23 0.15 0.139761942 0 3 1.098612289 0 5,629,980.00 15.54361645
2012 TGN 17/12/12 0.2 0.205 0.025 0.024692613 0 4 1.386294361 1 10,861,504.00 16.20073535
2012 AME 20/12/12 0.2 0.19 0.05 0.048790164 0 5 1.609437912 1 11,631,820.00 16.269255
2013 SXA 12/3/13 0.3 0.35 0.166666667 0.15415068 0 4 1.386294361 1 32150894 17.28595082
2013 IPB 30/4/2013 0.5 0.35 -0.3 -0.356674944 0 5 1.609437912 1 9808133 16.0987225
2013 CLZ 24/5/2103 0.2 0.13 -0.35 -0.430782916 0 4 1.386294361 0 3636938 15.10665268
2013 ZEL 19/8/2013 3.75 3.23 -0.138666667 -0.149273703 1 7 1.945910149 1 1905000000 21.36774785
2013 RGS 19/9/2013 0.25 0.264 0.056 0.054488185 0 5 1.609437912 1 16733000 16.63289338
2013 DME 22/10/2013 0.2 0.2 0 0 0 4 1.386294361 1 4313000 15.27714428
2013 MEZ 29/10/2013 1 0.94 -0.06 -0.061875404 1 9 2.197224577 1 7737400000 22.76933155
2013 MCY 10/5/13 2.5 2.17 -0.132 -0.141563564 1 7 1.945910149 1 5784700000 22.47848234
2013 TOU 9/4/13 0.5 0.53 0.06 0.058268908 0 4 1.386294361 1 44398653 17.60871969
2013 RLE 12/12/13 0.25 0.22 -0.12 -0.127833372 0 3 1.098612289 1 7031274 15.76587847

Results and Discussion

Table 2 indicates that the mean value of underpricing fraction is 0.062, which means that the selected IPOs were underpriced by 6.2%. The median is less than the mean value, which implies that the data is right-skewed. The standard deviation (SD) is high which means there is a significant dispersion in the sample data. The sum of LNUNDERPRICING is 1.838 which implies a high level of underpricing recorded in the sample data. The minimum and maximum values are -0.40 and 1.0, which indicates that the range is 1.40. The mean value of board size is 4.260, and its standard deviation is also high.

Table 2. Descriptive Statistics.

Underpricing fraction LNUNDERPRICING BIG Board size LNBSIZE Audit Committee Total Assets LNASSETS
Mean 0.062 0.037 0.100 4.260 1.412 0.600 336414682 16.456
Standard Error 0.034 0.030 0.043 0.178 0.038 0.070 193658393 0.258
Median 0.053 0.052 0.000 4.000 1.386 1.000 10002567 16.118
Mode 0.100 0.095 0.000 4.000 1.386 1.000 #N/A #N/A
Standard Deviation 0.243 0.215 0.303 1.259 0.269 0.495 1369371632 1.822
Sample Variance 0.059 0.046 0.092 1.584 0.072 0.245 1875178666099030000 3.319
Kurtosis 4.757 2.086 5.792 3.115 0.208 -1.900 22 4.852
Skewness 1.519 0.268 2.750 1.467 0.632 -0.421 5 2.161
Range 1.400 1.204 1.000 6.000 1.099 1.000 7735559826 8.344
Minimum -0.400 -0.511 0.000 3.000 1.099 0.000 1840174 14.425
Maximum 1.000 0.693 1.000 9.000 2.197 1.000 7737400000 22.769
Sum 3.093 1.838 5.000 213.000 70.601 30.000 16820734113 822.816
Count 50.000 50.000 50.000 50.000 50.000 50.000 50 50.000

The goodness of fit is weak as the value of R-square is just 0.055, which implies that the model only explains 5.5% of the total variations given in Table 3.

Table 3. Regression Results.

Regression Statistics
Multiple R 0.234824309
R Square 0.055142456
Adjusted R Square -0.028844881
Standard Error 0.218237988
Observations 50
ANOVA
df SS MS F Significance F
Regression 4 0.125081471 0.031270368 0.656556783 0.625355927
Residual 45 2.143251871 0.047627819
Total 49 2.268333342
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -0.002988727 0.489586269 -0.006104598 0.995156249 -0.989066092 0.983088637
LNBSIZE -0.084463378 0.158072292 -0.534333862 0.595740762 -0.402837318 0.233910561
LNASSET 0.013105743 0.036014703 0.363899798 0.717637069 -0.059431593 0.085643079
BIG -0.088534243 0.179898271 -0.492135039 0.625016306 -0.45086796 0.273799475
Audit Committee -0.07967028 0.067920869 -1.172986767 0.246972891 -0.216469933 0.057129372

The regression equation obtained from the analysis is given below:

  • LNUNDERPRICING = -0.002988727 -0.084463378 * LNBSIZE + 0.013105743 * LNASSET -0.088534243 * BIGN – 0.07967028 * Audit Committee

The coefficient of the slope between LNUNDERPRICING and LNBSIZE is negative, which implies an inverse relationship. However, the p-value is not less than α = 0.05, which means that this relationship is not found to be significant. Furthermore, the coefficient of the correlation between LNUNDERPRICING and LNASSET is positive that implies a direct relationship. This relationship is also not found to be significant. The coefficients of the correlation between LNUNDERPRICING and BIGN and Audit Committee are also negative that implies indirect relationships between them which are found to be insignificant.

Conclusion

The current study empirically investigated the effects of board size on IPO underpricing by statistically estimating the coefficient of the relationship between them. The results confirm that there is an inverse relationship between board size and IPO as the coefficient of the slope is negative. It implies that firms with large board sizes experience a decline in their post-IPO stock price.

Therefore, the hypothesis set out for this relationship is accepted. This finding also supports conclusions of previous studies, including Sriram (2018) and Dolvin and Kirby (2016). In this way, the robustness of the current study’s results is asserted. However, the relationship between board size and IPO underpricing is not significant, as the p-value was less than the alpha value at the confidence level of 95%.

Moreover, the results show that the size of a firm positively affects IPO underpricing, which is similar to the findings of studies including Mahatidana and Yunita (2017). The existence of an audit committee in the firm launching an IPO on the capital market and its accounts being verified and submitted by one of the Big 4 accounting firms have a negative relationship with IPO underpricing. These findings are inconsistent with studies by Green and Homroy (2018), Mahatidana and Yunita (2017), and Singh and Maurya (2018).

Limitation of Study and Future Research

A key limitation of the regression model implemented in this study is that the values of R-squared and Adjusted R-squared are very low that could imply poor predictability of the dependent variable based on the changes in the values of independent variables. The outcome is that no significant relationship between variables was found. There are several possible reasons for this outcome including a highly diverse sample of selected IPOs, a small data sample, and the presence of data outliers. It could be improved in future studies by selecting IPOs in the same sector and analyzing a larger sample of data.

References

Anand, R., & Singh, B. (2019). Do firm- and board-specific characteristics corroborate underpricing? A study on the Indian IPOs. Management and Labour Studies, 44(1), 86-102.

Creswell, J., & David, J. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: Sage Publications.

Dolvin, S. D., & Kirby, J. E. (2016). The impact of board structure on IPO underpricing. The Journal of Private Equity, 19(2), 15-21.

Green, C., & Homroy, S. (2018). Female directors, board committees and firm performance. European Economic Review, 102, 19-38.

Johl, S. K., Kaur, S., & Cooper, B. J. (2015). Board characteristics and firm performance: Evidence from Malaysian public listed firms. Journal of Economics, Business and Management, 3(2), 239-243.

Kubíček, A., Strouhal, J., & Štamfestová, P. (2017). Impact of board structure on IPO underpricing in Central Europe. International Advances in Economic Research, 23, 129-130.

Kubicek, A., Stamfestova, P., & Stouhal, J. (2016). Cross country analysis of corporate governance code in the European Union. Economics& Sociology, 9, 319-337.

Loughran, T., Ritter, J. R., & Rydqvist, K. (2016). Initial public offerings: International insights. Contemporary Finance Digest, 2(1), 165-199.

Mahatidana, M. R. A., & Yunita, I. (2017). An examination factors influencing underpricing of IPOs in financial and manufacturing industries on the Indonesia Stock Exchange over the period of 2011- 2016. International Journal of Scientific and Research Publications, 7(11), 457-502.

Malafeev, A. (2018). Relationship between characteristics of board of directors and IPO underpricing. Web.

Mehorta, S. (2016). Accentuating role of board for corporate governance in listed Indian companies. International Journal of Business and General Management, 3(2), 47-56.

Mishra, R., & Kapil, S. (2017). Effect of ownership structure and board structure on firm value: Evidence from India. Corporate Governance: The International Journal of Business in Society, 17(4), 700–726.

Sahoo, S. (2014). The impact of corporate board structure on the pricing performance of initial public offerings. The IUP Journal of Applied Finance, 20(4), 22-47.

Singh, A. K., & Maurya, S. (2018). Corporate governance, ownership structure, and IPO underpricing: Evidence from the Indian new issue market. Journal of Research in Capital Markets, 5. 7. Web.

Sriram, M. (2018). Board characteristics and firm performance: A study of S&P BSE Sensex in India. Afro-Asian Journal of Finance and Accounting, 8(3), 336-349.

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