2022美国代写网站Financial Strength and Product Market Behavior: The RealEffe
Financial Strength and Product Market Behavior: The RealEffects of Corporate Cash Holdings
This paper shows that large cash reserves lead to systematic future market share gainsat the expense of industry rivals.I. The SettingWhile much effort has recently been devoted to studying the determinants of firms’cash policies, evidence on the real implications of firms’ cash reserves remains relativelyscarce.6In particular, prior empirical work has paid little attention to the potential effects offirms’ cash holdings on their actions and performance in the product market. Yet, from anintuitive as well as a theoretical viewpoint, the idea that firms’ cash reserves might affectproduct market outcomes is of long standing. For instance, Tesler (1966) and more recentlyBolton and Scharfstein (1990) argue that deep-pocketed firms may increase their output todrive down industry prices. To the extent that rivals face difficulties in accessing funds, thedecrease in output price may induce losses for financially weak firms and drive them out ofthe market.Consequently, limited access to external funds can hinder a cash-poor firm’sability to compete vigorously in the product market, which may in turn prompt financiallystrong rivals to adopt “predatory” behaviors. http://www.ukassignment.org/dxessay/Chevalier and Scharfstein (1996) also suggestthat cash-poor firms may be less inclined to invest in building market share. In their model,firms directly decrease product prices as a means to secure long-term market share instead ofmaximizing short-term profits. More generally, cash holdings may be used to fund strategicpractices other than predatory pricing. Examples of such policies include decisions aboutcapital outlays, research and development expenses, the location of stores or plants,distribution networks, the use of advertising targeted against rivals, the recruitment of moreproductive workers, or the acquisition of key suppliers or business partners (Campello (2006)).Overall, this line of research suggests that cash-rich firms can use their war chests to financecompetitive strategies that may, in turn, enhance their performance in the product market.
II. Methods and DataA. Measuring the Impact of Cash on Product Market OutcomesTo explore the interplay between cash holdings and product market outcomes, Iinvestigate the link between cash and market share growth. I argue that irrespective of themechanism at work, if cash holdings include a valuable strategic component, they willultimately be reflected in firms’ performance in their product markets. I therefore examinewhether firms with large cash reserves expand their market shares more than their industryrivals. To do so, I follow Campello (2003, 2006) and specify the following baseline model:where the subscripts i and t represent, respectively, the firm and the (end of the) year. Thedependent variable, ΔMarketShares, is sales growth minus its industry-year average, so thatthis variable measures a firm’s sales growth in relation to that of its competitors, orequivalently, is a proxy for market share growth.10To reliably gauge the effects of cashholdings on market share dynamics, I need to characterize a firm’s cash position compared toits rivals. For that purpose, I follow MacKay and Phillips (2005) and standardize the ratio ofcash to total assets within each industry-year. Specifically, I compute zCash by subtractingfrom the cash-to-asset ratio its industry-year mean and divide the difference by the industry-year standard deviation. The motivation for z-scoring cash is as follows. Imagine that a firmhas 5% more cash than its average rival.
Table VIThe Impact of Cash on Firm Value and Operating PerformanceThis table presents results of panel regressions examining the effect of relative-to-rivals cash holdings on firmvalue and operating performance. In columns 1 and 2, the dependent variable is the (industry-adjusted) Market-to-Book ratio at time t. In columns 3 and 4, the dependent variable is the (industry-adjusted) return on assets(ROA) at time t. All variables are defined in the Appendix. The sample period is 1973 through 2006. IVestimations display diagnostic statistics for instrument overindentification restrictions (p-values for J-statisticsreported). All regressions contain firm and time fixed effects. The estimations correct the error structure forheteroskedasticity and within-firm error clustering. I report t-statistics in brackets.**and*denote statisticalsignificance at the 1% and 5% level, respectively.