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Corporate Governance and Stock Market Liquidity: The case of Australia and New Zealand
Ameena Hassa Mona Yaghoubi
1University of Canterbury
Department of Economics and Finance
Current Draft: 26th November, 2020
1The corresponding author is Mona Yaghoubi, [email protected].
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Abstract
This study analyses the relationship between corporate governance and stock market liquidity using listed firms on the New Zealand’s Exchange (NZX) and the Australian Securities Exchange (ASX) from 2014 to 2019. We employ an Ordinary Least Squares model with industry and year fixed effects; our results indicate that there is no significant relationship between governance and stock liquidity within our sample firms.
Keywords: corporate governance, stock liquidity, illiquidity, information asymmetry
1. Introduction
In this paper, we examine the effect of corporate governance on stock market liquidity using a sample of Australian and New Zealand firms from 2014-2019. Although the relationship between stock market liquidity and corporate governance has addressed in previous studies like Chung, Elder and Kim (2010) and Chung et al. (2011), to our knowledge, our paper is the first to examine this relationship in Australia and New Zealand.
Effective corporate governance minimises the conflict of interest between managers and different groups of stakeholders to help maximise the firm value. Operational and financial transparency can be improved as a result of effective governance. Strongly governed firms have more oversight on managers, they prevent incompetent or opportunistic managers to conceal information, and enhance transparency by reducing information asymmetry (Chung et al. (2010)). Therefore, we conjecture that there is a positive relationship between corporate governance and stock liquidity.
As every country has a different approach to corporate governance, the effect of corporate governance on stock liquidity can be different from one country to another. Therefore, we re- examine this relationship, using listed firms on the New Zealand’s Exchange (NZX) and the Australian Securities Exchange (ASX).
The New Zealand stock exchange (NZX) is a small exchange (Chen, Blenman and Chen 2008), which as of July 2020 has a total of 178 listed securities with a combined market capitalisation of USD 106 billion. In New Zealand, the number of individual investors has increased considerably over the recent years (McCaw, 2001 and Tan and Keeper, 2008), particularly with the public offerings of former state or local government-owned businesses such as Contact Energy and Auckland International Airport. The listed firms on the New Zealand Exchange include long- established heritage companies and several overseas companies. The New Zealand market is less liquid than the Australian market, which means that on an average day some companies might not trade at all. On the other hand, Australia makes a perfect setting for the study. The Australian stock market has a market capitalisation of USD 1.3 trillion as of July 2020. Although the Australian Securities Exchange is bigger than the NZX, it is still smaller by world standards, for example New York Stock Exchange market capitalisation is USD 21.04 trillion and London Stock Exchange market capitalisation is USD 3.23 trillion as of July 2020. ASX currently has over 2,000 listed firms. Due to its larger size, the Australian Stock Exchange offers more investment opportunities.
As both countries have different reforms implemented for corporate governance, the effect of
5 governance can be different in these two markets. Therefore, we first focus on a combined sample of these two market and then study each market separately.
To measure the governance quality of a firm, we create a governance index following Prommin et al. (2014). Although governance standards are recommended by the Australian Securities and Investments Commission (ASIC) and the Financial Market Authority (FMA), they are not required. Therefore, due to the limited governance data availability, we employ the five most common governance standards used in Australia and New Zealand to measure our corporate governance index. Two standards were chosen relating to the board of directors, the remaining three standards are chosen from the audit, executive compensation and board nomination. The construction of this index is similar to that of Prommin et al. (2014), where they examine the relationship between corporate governance and liquidity in Thailand.
Liquidity, by its very nature, is difficult to define and even more challenging to estimate. Kyle (1985) states that “liquidity is a slippery and elusive concept, in part because it encompasses a number of transactional properties of markets. These include tightness, depth and resiliency,”
(p. 1316). To measure liquidity, we use two widely used measures of liquidity, the bid-ask spread used by Chung et al. (2010) and the Amihud measure of illiquidity (Amihud, 2002).
We employ an Ordinary Least Squares model with industry and year fixed effects to test the hypothesis of this study. Unlike, Chung, Elder and Kim (2010) and Chung et al. (2011), we do not find a statistically significant and positive relationship between corporate governance and liquidity using a sample of Australian and New Zealand firms.
This paper proceeds as follows. Section 2 reviews the literature and develop the hypothesis.
Section 3 outlines the data, methodology and reports the summary statistics of the variables.
Section 4 tests the effect of corporate governance on stock market liquidity. Section 5 concludes.
2. Literature Review and Hypothesis Development
A number of prior studies focus on various factors across different countries and analyse the effect of corporate governance on liquidity. For example, the study of Bacidore and Sofianos (2002) demonstrates that stocks of US companies listed on the New York Stock Exchange display higher liquidity in the stock market when compared to the stocks of companies outside the USA. Another study by Brockman and Chung (2003) shows that, among the companies listed on the Hong Kong Stock Exchange, the firms of Hong Kong have smaller spreads and thicker depths when compared to Mainland China2. Thus, they interpret the finding as evidence that poor liquidity is a result of poor stockholder protection.
In contrast to the current literature, that looks into the differences in corporate governance in civil law versus common law countries, this paper focuses on two markets with similar legal system – both Australia and New Zealand are common law countries. There are several studies that argue that internal governance and liquidity are related to each other. One of the earliest studies in this field was conducted by Coffee (1991) He states that firms with large investor support measures improve their internal corporate governance and stock market liquidity.
Gompers, Ishi and Metrick (2001) show that listed firms on NYSE and NASDAQ with effective governance have higher stock market liquidity.
A study by Chung et al. (2010) on US companies state that “firms with better governance have narrower spreads, higher market quality index, smaller price impact of trades, and lower probability of information-based trading,” (p. 265). Additionally, research conducted by Prommin, Jumreornvong and Jiraporn (2014) on Thailand shows that liquidity of firms improves with better governance measures in those firms. Despite the above arguments, there is no evidence of the effect of corporate governance on stock market liquidity in Australia and New Zealand.
Better governance is always associated with disclosure rules. Welker (1995) states that a firm disclosure policy reduces any information asymmetry and leads to higher stock market liquidity. In addition, Brown (2007) finds that there is a positive relationship between disclosure of reports and information asymmetry.
Information asymmetry is the fundamental factor that connects the corporate governance of a firm to the liquidity of its shares. Shares with less information asymmetry are traded at a higher
7 price when compared to shares with higher information asymmetry (Easley, Kiefer, O’Hara and Paperman, 1996). Good governance measures reduce agency conflict, and information asymmetry. Effective governance provisions bring in financial transparency by reducing the management’s ability to disclose any less credible information (Leuz, Nanda and Wysocki, 2003).
There are various governance provisions that firms follow which may improve financial transparency by curbing the management’s ability to misrepresent any information. Take, for instance, provisions related to the Audit Committee: the committee is responsible to oversee the financial reports and disclosures of the firms; the committee is also responsible to inspect the auditing performed by the internal team in the firm. Ajinkya, Bhojraj and Sengupta (2005) in their study show that the frequency and quality of information that gets released is enhanced when the board monitors the management effectively. Hence, strong corporate governance ensures that the organisation policies and procedures are placed correctly, which helps in creating long-term shareholder value, thus, improving the operational transparency of the firms.
To have an impact on stock returns and prices, there must be an association between governance provisions, disclosure requirements and the information available to investors. Research conducted by Shen and Lin (2010) shows that organisations with better governance have a stronger relationship between fundamental signals4 and stock returns. Bebchuk, Cohen and Ferrell (2008) show that shareholders’ interest is protected by various governance provisions, as these provisions limit the extent to which managements can reduce the firm’s value through negligence, risk aversion and consideration. Diamond (1985) shows when there is reduced information, asymmetry between the traders and the management leads to smaller speculative positions amongst informed traders. Additionally, stocks of poorly governed firms face greater adverse selection problems and are often associated with wider spreads and smaller depths (Glosten and Milgrom, 1985). Similarly, Kyle (1985) finds that as a result of adverse selection, the price impacts of trades tend to be greater for the stocks of companies with poor governance structure.
Recent studies have been conducted in different countries that show a significant relationship between governance and liquidity within firms. Biswas (2020) has shown in his study that an illiquidity in a firm decreases by 55.97% when the standard deviation of the governance quality increases by a single unit. Sidhu and Kaur (2019) have also conducted a similar study on the Indian economy. Their study shows that effective corporate governance in firms can improve
8 financial disclosures by boards of directors there by enhancing stock market liquidly. Similarly, Ali, Liu and Su (2017) in their study show that trading with small price impact, lower cost of trading and higher frequency of trading are associated with better governed firms, thus improving stock liquidity.
Thus, theory and prior literature, suggest that corporate governance may have an impact on stock liquidity. Therefore, this study examines the effect of corporate governance on stock market liquidity using an index of governance measures in Australia and New Zealand.
Therefore we test:
Hypothesis 1: Firms with better corporate governance have higher stock market liquidity.
In this paper we study the impact of corporate governance on stock market liquidity in Australia and New Zealand. Though both countries have developed economies, there could be a major difference on how corporate governance would impact the liquidity of stocks, as both countries have different reforms implemented for corporate governance. In our knowledge, this paper is the first to test the relationship between corporate governance and liquidity in Australia and New Zealand.
3. Data, Methodology and Summary Statistics
3.1 Data
Our sample consists of 121 firms listed on the NZX, and 478 firms listed on ASX for the period 2014 - 2019. The 121 firms from New Zealand are members of the NZX ALL index, constructed by the New Zealand Exchange and consisting of securities quoted on the NZX main Board (NZX). The 478 firms of Australia are members of ASX all ordinaries, constructed by the Australian Securities Exchange (ASX) using market capitalisation. The data for this study is obtained from Bloomberg, Thomson-Reuters DataStream database, and sample firms’ annual reports. The data was obtained in daily value and then was averaged out to get the values on yearly basis. The governance data is collected from the Thomson-Reuters DataStream database and, for the firms where the governance data was not available, it has been collected manually from the annual reports.
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3.2 Corporate Governance Index
The corporate governance measures chosen for the study were considered based on the most common governance standards between Australia and New Zealand. Both the Australian Securities and Investments Commission (ASIC) and the Financial Markets Authority (FMA) have set governance principles to be followed by firms. However, in New Zealand, considering that firm size is mostly medium to small, the FMA gives firms the flexibility to take up other governance arrangements, though this needs to be disclosed by the firms. Following Prommin et al. (2014), we construct a corporate governance index (henceforth also referred as Gov-Index) based on five standards. Two standards were chosen relating to the board of directors, the remaining three standards are chosen from the audit, executive compensation and board nomination.
The five standards are chosen from four main categories listed in table below. These categories are Board of Directors, Audit Committee, Nomination Committee, and Compensation Committee.
For instance, the Audit Committee in a firm reviews the audit conducted by the internal committees. It also evaluates the appropriateness and effectiveness of internal auditing, and of financial and accounting controls. In so doing, the Audit Committee encourages effective supervision and thus prevents any misreporting of results by the management. This improves the governance standards in a firm as it brings in transparency both in financial and operational matters. The Nomination Committee is also one of the important committees in a firm, because this committee examines the skills and characteristics required for the board of directors. The Nomination Committee assures that the firm is managed by the right set of people and also helps to bring diversity within the firm. By doing this, the Nomination Committee maintains the effectiveness of the board, which would improve operational efficiency and reduce any conflicts, as the board of directors of the firm would be an unbiased choice.
Including the Board as one of the measures is important as the measure will assist in analysing the governance quality of the firm. The composition of the board helps in determining the effectiveness of the board. For example, separation of the chairman and CEO roles increases the independence of the board from management and thus leads to better monitoring and oversight.
Similarly, the Compensation Committee is responsible for deciding the remuneration of the top executives. Apart from remuneration, Compensation Committee is also liable towards the legal responsibility of the shareholders. The committee ensures the protection of shareholders rights, and also plays a role in improving the financial and operational transparency of the firm.
The table below represents a detailed description of the five governance standards, based on which the governance score is calculated. These standards play an important role in the management and investor protection. Similar to Prommin et al. (2014), a governance score is calculated by awarding one point when the firm meets any of the five standards. The governance score can vary between one to five, based on the standards the firm follows. The higher the score the higher is the firm’s governance quality.
Category Standards
Board of Directors a) One-third of the directors are independent directors.
b) Separation in the role of CEO and chairman
Audit Committee c) Audit Committee exists in firm
Nomination Committee d) Nomination Committee exists in firm Compensation Committee e) Compensation Committee exists in firm
For example, consider firm “A” with the following governance score, a) one-third of firm “A”’s directors are independent directors (+1), b) In firm “A”, there is no separation in the role of CEO and chairman (0), c) audit committee exists in firm “A” (+1), d) nomination committee does not exist in firm “A” (0), and e) compensation committee exists in firm “A” (+1), therefore firm “A” meets 3 out of 5 criteria, and its Gov-Index=3.
3.3 Illiquidity Measures
The data to create the liquidity variables were obtained from Bloomberg and Thomson-Reuters DataStream database for both Australian and New Zealand firms. The data is downloaded in USD. The data file includes ticker symbol, date, bid price, asking price, and last price for all
the observations. Following Chung et al. (2010), we dropped observations with missing or negative ask and bid prices. We construct two liquidity measures as follow.
We first follow Amihud (2002) and construct an illiquidity measure that price changes per unit volume. We construct:
Amihud
𝑖𝑦= 100 ∗ 1
𝐷
𝑖𝑦
𝑡−1 𝐷𝑖𝑦|𝑅
𝑖𝑦𝑑|/𝑉𝑂𝐿𝐷
𝑖𝑦𝑑where
𝑅
𝑖𝑦𝑑 is the return on stock i on day d in year y,𝑉𝑂𝐿𝐷
𝑖𝑦𝑑 is the dollar trading volume of stock i on day d in year y, and𝐷
𝑖𝑦is the number of trading days for stock i in the year y.Then, we follow Chung et al. (2010) and construct our Quoted Spread measure, which also measures the illiquidity of a stock. Quoted Spread is one effective method of measuring the illiquidity and trading cost, the difference between the asking and the bidding price. We construct:
𝑄𝑢𝑜𝑡𝑒𝑑 𝑆𝑝𝑟𝑒𝑎𝑑
𝑖𝑦= 100 ∗ 1
𝐷
𝑖𝑦
𝑡−1 𝐷𝑖𝑦(𝐴𝑆𝐾
𝑖𝑦𝑑− 𝐵𝐼𝐷
𝑖𝑦𝑑)/𝑀
𝑖𝑦𝑑where,
𝐴𝑆𝐾
𝑖𝑦𝑑 is the ask price for the stock 𝑖 on day d of year y ,𝐵𝐼𝐷
𝑖𝑦𝑑 is the bid price for the stock 𝑖 on day d of year y, 𝑀
𝑖𝑦𝑑 is the mean of𝐴𝑆𝐾
𝑖𝑦𝑑 and𝐵𝐼𝐷
𝑖𝑦𝑑,
and𝐷
𝑖𝑦 is the number of trading days for stock 𝑖 in the year y. The quoted spread is calculated for each year from 2014 to 2019.3.4 Methodology
We follow the existing literature and control for Return Volatility, Trading Volume, Firm Size, Assets Tangibility and Price (1/price) (Stoll, 2000 and Chung et al., 2010).
Cohen et.al (1976) shows that Return volatility explain liquidity as deep markets are less volatile than narrow markets, and market depth can be explained by Volume (Pagano,1989;
Brennan and Subrahmanyam, 1995). Besides, Stoll et al. (1983) show that bid-ask spread is affected by Size of a firm and Benston et.al (1974) finds that bid-ask spread and risk can be explained by Price of a stock.
Chung et al. (2010) show return volatility positively affects the liquidity, whereas trading volume negatively affects liquidity. The return volatility is measured by the standard deviation
of daily stock returns, and the trading volume is calculated using the average daily trading volume in dollars for each year. We also control for firm size and asset tangibility to control for the effect of information asymmetry on liquidity as larger firms have more information available than the smaller firms. Firm size is measured by the book value of the total assets and asset tangibility is the ratio of net property, plants and equipment (PPE) to the book value of the total assets. We also use the reciprocal of the share price as a control variable as an additional proxy for risk.
To test the effect of corporate governance on liquidity, we employ an Ordinary Least Squares model with industry and year fixed effects and the following empirical specification:
𝐼𝑙𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦𝑖,𝑦 = 𝛼 + 𝛽1𝐺𝑜𝑣 − 𝐼𝑛𝑑𝑒𝑥 + 𝛽2𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖,𝑦+ 𝑆𝐼𝐶 + 𝑌𝑒𝑎𝑟 + ℇ𝑖,𝑦 (1) where Illiquidityi,y is one of the two liquidity measures, Amihud or Quoted Spread; Gov- Indexi,y is the governance index and is obtained by assigning one point for each governance standards that a firm meets; 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖,𝑦 is a matrix of control variables, Return Volatility, Trading Volume, Firm Size, Assets Tangibility and 1/price. SIC and Year represent the industry and year fixed-effects, respectively.
3.5 Summary Statistics
Table 1 reports the summary statistics of the dependent and control variables of this study.
Panels A, B and C use a combined sample of ASX and NZX listed firms, a sample of ASX listed firms and a sample of NZX listed firms, respectively.
insert Table 1
Table 1 shows the average Gov-Index score for the combined sample of ASX and NZX listed firms is 4.42, with a minimum of 1 and maximum of 5. This score, indicate that on average most firms have good governance standards in place. The average Gov-Index score for ASX listed firms is slightly higher than the NZX listed firms, 4.74 vs. 4.23. The table also shows than on average, ASX firms are larger than NZX firms – $ 6.97 B vs. $ 6.20 B book value of assets. The mean and value of the Quoted Spread and Return Volatility for the Australian sample is 0.02, which is close to the mean value of the Quoted Spread and Return Volatility reported by Ali, Liu and Su (2016) using a sample of Australian firms. Panel C of the table shows an average of 0.02 for NZX firms Return Volatility which is close to the mean value of
13 Return Volatility reported by Poskitt et al. (2011). Besides, Panels B and C of Table 1 indicate that on average ASX stocks are more liquid than NZX stocks as the average of Quoted Spread and Amihud measures of illiquidity are higher in NZX than ASX. The table also show that on average New Zealand firms have more tangible assets than the Australian firm. In addition, as can be seen from the table, on average the Price of ASX stocks are much higher than the NZX stocks.
Table 2 reports the correlation coefficients between the illiquidity measures and the explanatory variables. As expected, the table shows a positive correlation between the Amihud and Quoted Spread measures of illiquidity. Table 2 correlation analysis shows that Amihud and Quoted Spread measures of illiquidity and are negatively correlated to Gov-Index, with Amihud having a relatively smaller correlation coefficient with Gov-Index, implying that the higher the Gov- Index, the higher the liquidity (lower the illiquidity). Furthermore, consistent with the literature, Amihud and Quoted Spread are negatively correlated to both Volume and Size. Return Volatility shows a positive correlation to Amihud and Quoted Spread. Consistent with previous studies, Price shows a positive correlation with both Amihud and Quoted Spread. Table 2 also shows a positive correlation between Volume and Size, indicating higher trading volume for larger firms.
insert Table 2
4. Results
Our main findings are reported in Table 3 using Equation (1) and a combined sample of ASX and NZX firms in Panel A, a sample of ASX listed firms in Panel B and a sample of NZX listed firms in Panel C, from 2014 to 2019. Our dependent variables are Amihud and Quoted Spread measures of illiquidity and our variable of interest is Gov-Index. Columns (1), (3) and (5) illustrate the findings using the Amihud measure of illiquidity and Columns (2), (4) and (6) reports the findings using the Quoted Spread measure of illiquidity.
insert Table 3
As can be seen from Table 3, none of the coefficients associated with Gov-Index in columns (1) through (6) are significant. Indicating that inconsistent with the existing literature, we do not find a statistically significant relationship between corporate governance and stock market
14 liquidity in Australia and New Zealand. Examples of studies that find effective corporate governance leads to higher liquidity are Chung et al. (2010) using US data, Chung et al. (2012) using a combined sample of 25 countries data and Prommin et al. (2014) using Thailand data.
Although Australian and New Zealand firms’ data were included in Chung et al. (2012) combined dataset, to our knowledge this paper is the first to study country-level effect governance on liquidity using ASX and NZX data.
In addition, consistent with the literature, the coefficients associated with most control variables are statistically significant with the predicted signs. Table 3 shows a positive and statistically significant relationship between return volatility and illiquidity measures. Firms having high return volatility have lower stock market liquidity when compared to firms having lower return volatility. Besides, as expected, the table illustrates the coefficients associated with Volume are negative and statistically significant. This relationship signifies that firms with higher trading volumes have higher stock market liquidity than firms with lower trading volumes, which are comparatively smaller in size and will have lower market liquidity. Thus, this could be the reason why a significant relationship was not determined for NZX All firms as most of the firms in New Zealand are small to medium sized (Med 2007 and Shangqin et al., 2009). The total assets and the 1/price are positive and significantly related to the liquidity measures of this study, which is consistent with prior studies.
We also test if our findings is robust to adding additional control variable, GDP. The annual growth rate of gross domestic product (GDP) is used as a control variable. High GDP can increase the liquidity of the stock market, therefore we add GDP to our control variables and our main findings remain unchanged.
5. Conclusion
This study sheds light on stock market liquidity by analysing how corporate governance of a firm affect stock market liquidity in Australian and New Zealand firms. Prior studies indicate that firms with good corporate governance are characterised by higher liquidity (Chung et al., 2010). Although this relationship has been tested in the previous literature, to our knowledge, this is the first study to examine the relationship between corporate governance and liquidity in Australia and New Zealand. We find no statistically significant relationship between governance and liquidity using ASX and NZX listed firms. Our result do not support the
15 positive relationship between liquidity and governance reported in studies like Glosten &
Milgrom (1985), Chung et al. (2012) and Prommin et al. (2014).
In this study, we consider the most common governance standards between Australian and New Zealand listed firms to analyse their effect on stock liquidity of the listed firms. Fives standards were chosen based on ASIC and FMA principles of Australia and New Zealand. A corporate governance index was constructed based on the chosen standards, where one point was awarded when the firms meet a specific governance standard, and if the firm fails to meet that standard, a zero score was awarded. The total governance index is the sum of individual standards scores.
In addition, we construct two widely used illiquidity measures.
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20 Table 1: Descriptive Statistics
This table reports the summary statistics of the variables of this study for the period 2014-2019.
The Gov-Index indicates the firm’s governance index constructed in Section 4.2. Amihud and Quoted Spread are our illiquidity measures constructed in Section 4.3, Return Volatility is the standard deviation of daily stock returns, Volume is the average daily trading volume in billion US dollars, Assets Tangibility is measured by the ratio of net property, plants and equipment (PPE) to the book value of total assets, Size is the book value of the total assets in billion US dollars, and 1/Price is the reciprocal of the share price.
Percentile
Variable Observations Mean SD. Min Max 25th Median 75th Panel A : A combined sample of ASX All Ordinaries and NZX All firms
Gov-Index 2417 4.42 1.14 1.00 5.00 4.00 5.00 5.00
Amihud 2417 0.00 0.04 0.00 1.62 0.00 0.00 0.00
Quoted Spread 2415 0.03 0.05 -0.24 1.11 0.01 0.02 0.03
Return volatility (%) 2417 0.02 0.02 0.00 0.60 0.01 0.02 0.03
Volume 2417 12.60 2.63 0.00 17.13 11.69 12.99 14.26
Asset Tangibility 2416 0.79 0.26 0.00 1.56 0.67 0.91 0.99
Size 2416 6.82 2.20 0.00 13.79 5.64 6.75 8.10
1/Price 2396 3.49 42.08 0.00 1000.00 0.14 0.32 0.75
Panel B : ASX All Ordinaries
Gov-Index 1933 4.47 1.18 1.00 5.00 5.00 5.00 5.00
Amihud 1933 0.00 0.05 0.00 1.62 0.00 0.00 0.00
Quoted Spread 1933 0.02 0.02 -0.24 0.36 0.01 0.02 0.03
Return volatility (%) 1933 0.02 0.02 0.00 0.60 0.01 0.02 0.03
Volume 1933 12.96 2.63 0.00 17.13 12.18 13.39 14.49
Asset Tangibility 1933 0.78 0.26 0.00 1.56 0.64 0.90 0.99
Size 1933 6.97 2.15 0.00 13.79 5.86 6.84 8.21
1/Price 1886 1.20 5.42 0.00 172.16 0.12 0.29 0.68
21 Table 2 continued:
Percentile
Variable Observations Mean SD. Min Max 25th Median 75th Panel C: NZX All
Gov-Index 484 4.23 0.95 1.00 5.00 4.00 5.00 5.00
Amihud 484 0.01 0.03 0.00 0.42 0.00 0.00 0.00
Quoted Spread 482 0.04 0.10 0.00 1.11 0.01 0.01 0.03
Return volatility (%) 484 0.02 0.02 0.00 0.31 0.01 0.01 0.02
Volume 484 11.14 2.07 0.00 15.46 9.63 11.35 12.87
Asset Tangibility 483 0.84 0.22 0.00 1.04 0.75 0.95 0.99
Size 483 6.21 2.30 0.00 13.79 4.84 6.29 7.74
1/Price 483 12.44 92.12 0.03 1000.00 0.21 0.40 0.94
22 Table 2: Correlation Coefficients
This table reports the pairwise correlation coefficients between the variables of this study, using a combined sample of ASX and NZX firms for the period 2014-2019. The Gov-Index indicates the firm’s governance index constructed in Section 4.2. Amihud and Quoted Spread are our illiquidity measures constructed in Section 4.3, Return Volatility is the standard deviation of daily stock returns, Volume is the average daily trading volume in billion US dollars, Assets Tangibility is measured by the ratio of net property, plants and equipment (PPE) to the book value of total assets, Size is the natural logarithm of book value of the total assets, and 1/Price is the reciprocal of the share price.
Correlations (1) (2) (3) (4) (5) (6) (7) (8)
(1) Gov-Index 1
(2) Amihud -0.052* 1
(3) Quoted Spread -0.209*** 0.240*** 1
(4) Return volatility -0.116*** 0.181*** 0.351*** 1
(5) Volume 0.278*** -0.090*** -0.340*** -0.019 1
(6) Asset Tangibility -0.043* 0.040 -0.021 0.065** 0.017 1
(7) Size 0.280*** -0.079*** -0.324*** -0.340*** 0.494*** 0.127*** 1
(8) 1/Price -0.107*** 0.154*** 0.346*** 0.235*** -0.003 0.054** -0.171*** 1
* p < 0.05, ** p < 0.01, *** p < 0.001
23 Table 3: Summary of Results
This table shows the estimation results of Equation below:
𝐼𝑙𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦𝑖,𝑦 = 𝛼 + 𝛽1𝐺𝑜𝑣 − 𝐼𝑛𝑑𝑒𝑥 + 𝛽2𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖,𝑦+ 𝑆𝐼𝐶 + 𝑌𝑒𝑎𝑟 + ℇ𝑖,𝑦 where Illiquidityi,y is one of the two liquidity measures, Amihud or Quoted Spread; Gov- Indexi,y is the governance index and is obtained by assigning one point for each governance standards that a firm meets; 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖,𝑦 is a matrix of control variables, Return Volatility, Trading Volume, Firm Size, Assets Tangibility and 1/price. SIC and Year represent the industry and year fixed-effects, respectively. Clustered standard errors by firm are shown in parentheses.
Panel A: Combined Panel B: ASX Panel C: NZX
(1) (2) (3) (4) (5) (6)
VARIABLES Amihud Quoted Spread Amihud Quoted Spread Amihud Quoted Spread
Gov-Index
-0.000188 -0.000724 0.00001 -0.00003 -0.00172 -0.00765 (0.000946) (0.000757) (0.00111) (0.000373) (0.00122) (0.00610) Return volatility
0.348*** 0.430*** 0.0793 0.0751*** 1.189*** 1.891***
(0.0506) (0.0343) (0.0628) (0.0186) (0.0434) (0.139) Asset Tangibility
0.00353 -0.00947 0.00502 -0.00426 0.000365 -0.0428 (0.00473) (0.00587) (0.00594) (0.00267) (0.00485) (0.0313) Volume
-0.00294*** -0.00926*** -0.00386*** -0.00648*** -0.000113 -0.0143***
(0.000661) (0.000849) (0.000861) (0.000396) (0.000632) (0.00376) Size
0.000996 0.000391 0.00146* 0.000982*** 0.00158*** -0.00186 (0.000621) (0.000779) (0.000795) (0.000352) (0.000580) (0.00407) 1/Price
0.000130*** 0.000244*** 0.00101*** 0.00170*** 0.00002* 0.0001
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
Year dummy
Yes Yes Yes Yes Yes Yes
Industry dummy
Yes Yes Yes Yes Yes Yes
Country dummy
Yes Yes No No No No
Adjusted R-squared
0.0603 0.2992 0.0363 0.4355 0.7189 0.468
Observations
2,368 2,366 1,886 1,866 482 480
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
25
