قدرت بازار محصول و نقدینگی بازار سهام

Theory predicts that since a firm with market power has more stable cash flows because of its ability to set prices in the product market, its stock price is less sensitive to order flow (Peress, 2010), which results in greater stock liquidity. We test this prediction on a large sample of firms and find that stock liquidity increases with market power because market power reduces return volatility. Further, consistent with theoretical predictions, the impact of market power on liquidity is more pronounced when information asymmetry is more severe, that is, for smaller firms and for firms with less analyst coverage. Our findings are robust to different measures of liquidity, market power, volatility, and alternative econometric model specifications.

Better stock liquidity should result in higher market value because higher liquidity implies a lower cost of capital (e.g., Amihud and Mendelson, 1986, Pastor and Stambaugh, 2003 and Acharya and Pedersen, 2005). In a noisy rational expectations model, Peress (2010) shows that greater product market power improves stock liquidity. A firm with greater market power has a greater ability to set prices and pass on productivity shocks to its customers, which lowers the volatility of its cash flows and stock returns. The lower volatility of cash flows and returns gives investors more precise information about the stock price and also makes it less sensitive to order flow. As a result, firms with greater market power have lower price impact and therefore better stock liquidity. Using a large sample of firms, we empirically test this theoretical prediction of Peress (2010) and provide evidence that product market power enhances stock liquidity by lowering the variability of cash flows and returns. In addition, we show that the severity of information asymmetry affects the impact of market power on liquidity. Specifically, we find that market power has a larger effect on liquidity when firms are smaller and also when they are followed by fewer analysts. Peress (2010) develops a rational expectations framework in which there is imperfect competition in the product market but perfect competition in the stock market. Imperfect competition in the product market means that each firm has some ability to set prices for its product (i.e., demand is not perfectly elastic). Firms receive productivity shocks that determine their output and the information asymmetry in the model arises due to risk-averse investors observing private but noisy signals about each firm’s productivity shock. Investors condition their asset demands on their private signals and stock prices; and exogenous noise trades ensure that stock prices only partially reveal private signals. When faced with a negative (positive) productivity shock that lowers (raises) output, a firm with product market power is able to increase (decrease) its product price and insulate its profit from the shock. Therefore, product market power lowers the firm’s cash flow volatility and, consequently, also its stock return volatility. As market power increases, expected cash flows and returns become more certain; and this improves the precision of investors’ information about the stock price. As a result, the firm’s stock price becomes less sensitive to uninformative order flow. Thus, firms with greater market power have lower price impact and therefore better stock liquidity (Peress, 2010, Proposition 6). The theoretical framework of Tookes (2008) also implies a positive relation between market power and liquidity, although she arrives at this conclusion by employing different mechanisms. In Tookes’ model, wealth-constrained, risk-neutral informed traders prefer to trade in the stocks of weaker product market competitors since the values of such stocks are more sensitive to private information. Thus, as product market power decreases, informed trading increases, which dampens liquidity because of adverse selection. In our empirical analysis, we measure product market power by the Lerner index, or the price–cost margin (Gaspar and Massa, 2006 and Peress, 2010), and market share; and measure liquidity by Hasbrouck’s (2009) estimate of percentage spread, Amihud’s (2002) price impact measure, quoted spread, and effective spread.2 We first examine changes in liquidity in seven industries (air transport; banks and thrifts; entertainment; natural gas; telecommunications; trucking; utilities) that experienced significant deregulation between the late-1970s and mid-1990s. Deregulation provides an intuitive setting to examine the impact of market power on liquidity since it removes barriers to entry that foster product market power. Comparing average price–cost margin and market share in the 12-year period before and after the deregulation year, we document statistically significant reductions in both measures of market power across many industries. Consistent with the predicted positive relation between market power and liquidity, the decline in market power is associated with a statistically significant drop in liquidity in many industries. Using Hasbrouck’s estimate of percentage spread, we document decreases in liquidity after deregulation for four of the seven industries, three of which are statistically significant at conventional levels. The results are stronger and more pervasive with Amihud’s price impact measure; we observe decreases in liquidity for six of the seven industries. We build on the results from the deregulation analysis by testing the predicted relation between market power and liquidity on a panel data set of 12,695 firm-year observations from 1984 to 2003. We sort our sample independently on size and market power to examine the relation between market power and liquidity while controlling for size effects. In each size-sorted quartile, we find that liquidity improves from the lowest market power quartile to the highest market power quartile, which is consistent with the market power hypothesis. The positive relation between market power and liquidity obtains whether we use price–cost margin or market share to measure market power. We then estimate multivariate regressions to analyze the relation between market power and liquidity. Since the theoretical model of Peress (2010) predicts that higher market power improves liquidity by reducing volatility, we decompose our market power measure into the component that is related to volatility (MPV) and the orthogonal residual component unrelated to volatility. If market power improves liquidity as hypothesized, then MPV should be positively related to liquidity. The findings from our regression analysis show that this is indeed the case. The positive relation between market power and stock liquidity obtains (i) for all liquidity measures— Hasbrouck’s (2009) percentage spread, Amihud’s (2002) price impact, quoted spread, and effective spread; (ii) for alternative measures of market power—price–cost margin, market share or industry-adjusted price–cost margin; (iii) whether we construct MPV using cash flow volatility or stock return volatility; and (iv) in Fama-MacBeth regressions with first-order autocorrelation correction and fixed effects regressions that control for unobserved firm hetereogeneity. 3, 4 Using estimates from our regression analysis, we are able to quantify the impact of market power on liquidity. When MPV is constructed from price–cost margin, we show that an one standard deviation increase in MPV reduces Hasbrouck’s (2009) percentage spread from 1.6% to 1.5%, quoted spread from 1.8% to 1.7%, and effective spread from 1.3% to 1.2% for the average firm in our sample. In the case of the Amihud (2002) price impact measure, for a $1 million daily volume, an one standard deviation increase in MPV reduces the price impact for an average firm from 9% to 7%. When MPV is constructed from market share, the improvements in liquidity are nearly identical for all four liquidity measures. The Peress (2010) framework also sheds light on how information asymmetry affects the positive relation between market power and stock liquidity. The underlying intuition in Peress’ framework is that investors have better information about firm performance when information asymmetry is less severe. Therefore, their estimate of future stock price is more precise even without the volatility-dampening effect of market power. Conversely, as information asymmetry becomes more severe, the stabilizing effect of market power becomes more important to investors in estimating stock prices. Thus, more severe information asymmetry strengthens the predicted relation between market power and liquidity, and vice versa. We test whether the degree of information asymmetry affects the relation between market power and liquidity by interacting the volatility measure MPV with proxies for information asymmetry. In keeping with the literature (e.g., Bharath et al., 2009 and Chang et al., 2006), we select firm size and analyst coverage as information asymmetry proxies since investors tend to know more about larger firms and about firms with greater analyst coverage. Our regression results are consistent with the prediction that as information asymmetry becomes less severe, the positive relation between market power and liquidity becomes weaker. Since we use illiquidity measures as dependent variables in our regressions, the positive coefficient on the interaction between MPV and analyst coverage implies that as analyst coverage increases (and information asymmetry becomes less severe), market power has a smaller impact on liquidity. When we use firm size as the information asymmetry proxy, we obtain similarly strong results. 5 While both Peress (2010) and Tookes (2008) predict a positive relation between market power and liquidity, the different mechanisms in the two papers suggest opposite relations between liquidity and turnover. In Peress (2010), greater market power increases certainty about cash flows and returns, which makes risk-averse informed traders more willing to trade with noise traders, thereby stabilizing prices and improving liquidity. Thus, Peress’ model implies that trading volume is positively related to liquidity. In Tookes’ model, informed traders are risk-neutral, wealth-constrained and prefer to trade in the stocks of lower product market power firms since the returns to information are greater in these stocks. Thus, as product market power decreases, informed trading and trading volume increase but liquidity decreases as there is greater adverse selection. Hence, the Tookes (2008) model predicts a negative relation between liquidity and turnover. Since both models link liquidity and trading volume through market power, we decompose market power into the component that is related to turnover (MPT) and the orthogonal residual component unrelated to turnover, after controlling for the influence of volatility. The Tookes (2008) model predicts a negative relation between liquidity and MPT, whereas Peress (2010) predicts a positive relation. Our regression analyses show greater support for a negative relation between MPT and liquidity. With price–cost margin as the market power measure, we find a negative relation between MPT and liquidity across all liquidity measures. With market share as the market power measure, the relation between MPT and liquidity is negative when we use the Amihud price impact measure, but positive when we use either quoted or effective spread. Our study contributes to the literature that links product and financial markets by providing empirical evidence on how the interactions between product and financial markets affect the relation between volatility and stock liquidity. Peress (2010) presents a model, which predicts that firms with greater market power have greater trading volume, more informative stock prices, and better stock liquidity and that greater information asymmetry strengthens these relations. The panel regressions on a data set spanning 1996–2005 in Peress (2010) show that market power is positively and significantly related to turnover, corporate insider trading activity, and stock price informativeness. He also shows that these relations are more pronounced for smaller firms where information asymmetry is more severe. Using intraday transactions data, Tookes (2008) shows that, consistent with informed trading in rivals’ stocks around quarterly earnings announcements, order flows and returns of product market rivals’ stocks have an impact on the returns of the announcing firm. In addition, in the pre-announcement period, the impact of such trading is stronger if the rival has a smaller market share relative to the announcer and if competitive information is expected to be announced. These studies, however, do not empirically test the predicted relation between market power and stock liquidity, nor do they test the impact of information asymmetry on this relation. The contribution of our paper is, therefore, in providing strong empirical evidence in support of both these predicted relations. Empirical studies including Gaspar and Massa (2006), Chun, Kim, Morck, and Yeung (2008), and Irvine and Pontiff (2008) document an inverse relation between product market power and return volatility. We build on this research and, using a large panel data set of firms, provide evidence that supports the Peress (2010) prediction that market power improves liquidity because of the inverse relation between market power and return variability. There is a large literature that examines the relations between product market competition and various aspects of corporate finance including capital structure, risk management, ownership structure, payout policy, and mergers and acquisitions.6 Other researchers have used product markets to understand issues in asset pricing and investments.7 We add to this literature by focusing on the effect of the market power aspect of product markets and the liquidity of equity securities in financial markets. We show that stock liquidity is increasing in market power and, therefore ceteris paribus, firm value (cost of capital) should also be increasing (decreasing) in market power.8 By identifying market power as a significant determinant of liquidity, our study also adds to the literature that examines how firm decisions and characteristics affect stock liquidity. Prior studies examine the influence of capital structure decisions, mergers and acquisitions, stocks splits, IPO underpricing, insider trading, ownership structure, advertising, and credit ratings on liquidity (Heflin and Shaw, 2000, Lesmond et al., 2002, Pham et al., 2003, Cao et al., 2004, Grullon et al., 2004, Odders-White and Ready, 2006, Lipson and Mortal, 2007, Rubin, 2007 and Chang and Yu, 2010).9 We extend this literature by showing that product market power also has an impact on stock liquidity. The rest of the paper proceeds as follows. Section 2 describes our sample selection procedure, defines variables, and reports summary statistics. In Section 3, we use univariate and multivariate regression analyses to show that market power affects stock liquidity via its impact on volatility. We also present evidence indicating that greater information asymmetry strengthens the market power–liquidity relation. In Section 4, we check the robustness of our results. Section 5 concludes the paper.

In this paper, we empirically test for a positive relation between a firm’s product market power and its stock liquidity, as predicted by the theoretical model of Peress (2010, Proposition 6) . Consistent with theory, we find that product market power enhances stock liquidity by lowering the variability of cash flows and returns. If higher liquidity is associated with a lower cost of equity as suggested by recent research (e.g., Acharya and Pedersen, 2005 ), then our result implies that market power positively affects firm value through improving liquidity. This indirect channel complements the traditional view that market power affects firm value because firms with market power have greater ability to influence their cash flows. We also test a second hypothesis implied by the model of Peress (2010) , namely that the relation between market power and liquidity strengthens as information asymmetry becomes more severe, and vice versa. We find support for this hypothesis using a variety of information asymmetry proxies employed in the literature. To the best of our knowledge, we are the first to provide empirical support for these hypothesized relationsOur findings are robust to different measures of liquidity, market power, and volatility. In addition, our finding remains intact when we control for unobserved firm effects (using panel data regressions) and make reasonable changes in the research design. Our study contributes to the literature on the interactions between product markets and finance. Much of the existing research in this area focuses on the interactions between product market competition and various aspects of corporate finance. Other researchers have used product markets to understand issues in asset pricing and investments. In contrast to these articles, we focus on the relation between product market competition(as measured by product market power) and the trading characteristics of equity securities. By identifying market power as a significant determinant of liquidity, our study also adds to the extant literature that examines how firm decisions and characteristics affect stock liquidity