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Erschienen in: Review of Managerial Science 2/2017

30.11.2015 | Original Paper

The interaction between stock prices and corporate investment: is Europe different?

verfasst von: Houdou Basse Mama

Erschienen in: Review of Managerial Science | Ausgabe 2/2017

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Abstract

I find limited evidence of firm learning from stock prices in Europe and uncover multifaceted complementarities between firm informational and operating environments in determining investment sensitivity to stock prices. Specifically, European firms seemingly do not shift away from their own (peer) stock prices even in instances in which their peers’ (own) stock prices become relatively more informative about firms’ fundamentals. This is consistent with European managers adopting more conservative strategies relative to their U.S.-based peers, and stock prices being less revealing in Europe than in the U.S. Furthermore, while a firm may attach equal weight to both its own stock prices and peer price innovations when peer firms are relatively smaller, investment responds more positively to peers’ price shocks than to that firm’s own stock prices when peers are relatively larger. Interestingly, investment sensitivity to peers’ stock prices decreases in peers’ market share, operating performance, and capital intensity. The decrease is accentuated when peer firms have more informative stock prices and are industry leaders or more capital intensive, thereby signaling perceived reduced growth opportunities. Broadly, these results imply that the specifics of the interaction between stock prices and firm behavior in the U.S. do not necessarily generalize to Europe. More important, these different learning patterns are partly attributable to differences in the amount of internal information, which in turn depends on country-level institutional infrastructures.

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1
While there are good reasons to make an argument for the allocational role of secondary markets (Fama and Miller 1972; O’Hara 1997; Chung et al. 2012), there can be limitations, including manipulation by uninformed traders, which are inherent in this role of secondary financial markets (Goldstein and Guembel 2008). Moreover, the financial crisis of 2007–2009 led to a challenge to the idea that finance promotes real efficiency (Bai et al. 2013). In a more recent study, Goldstein and Yang (2014) characterize the conditions under which market efficiency and real efficiency may be (mis)aligned.
 
2
Another force used in the literature is the level and tone of media attention (e.g. Liu and McConnell 2013).
 
3
Because firms do not operate in a vacuum and stock prices are far from being fully revealing, it is surprising that existing research has largely neglected the role of peer firms’ stock prices in shaping firm behavior. This neglect runs counter to, e.g., the perceived ubiquity of “accounting-based market multiples” in the reports and recommendations of financial analysts and in investment bankers’ fairness opinions (Bhojraj and Lee 2002). Analyzing the retail brokerage industry, Kock (2005) notes that excessively high stock market valuations assigned to firms in the new segment (online brokerage) caused traditional incumbent brokerage houses to offer online services. Servaes and Tamayo (2014) also show empirically that a (stock market valuation-driven) hostile takeover attempt for one firm in an industry alters the investment and financing behavior of industry peers. This evidence suggests that the real effects of stock markets are potentially underestimated when peer effects are not accounted for.
 
4
I thank two anonymous referees for suggesting that the discussion be restricted to this learning setting.
 
5
The marginal effect of managerial private information on investment sensitivity to firm j’s stock prices depends on the parameter values of the amount of informed trading in peer stocks. See Eq. (15) in Foucault and Frésard (2014, pp. 561–562) for more details.
 
6
Recent empirical evidence suggests that executives exert significant discretionary powers over a range of firm policies including the allocation of capital (see Bertrand 2009, for a review). Most of that research addresses the role of managers in firm policies by exploring the relationship between firm outcomes and manager-specific characteristics, their innate preferences and beliefs (e.g. Bertrand and Schoar 2003; Galasso and Simcoe 2011).
 
7
Mixed results produced by studies outside the U.S. that examine the correlation between investment and stock prices reinforce the conjecture of heterogenous learning dynamics in the U.S. and in other markets. Analyzing firm-level data from India, Jordan, South Korea, Malaysia, and Thailand around the liberalization date, Chari and Henry (2008) report a significant predictive power of stock prices for investment even after controlling for current and expected future sales growth. In turn, Porter (1992) finds that stock prices generally have limited predictive power for capital choices in Japanese firms. In stark contrast with the above, Wang et al. (2009) report that prices formed on Chinese stock markets have no impact on corporate investment through the information channel. They interpret their results to mean that this is because stock prices in China probably contain little information about future operating performance. Li et al. (2011) attain similar results using firm-level data of Australian firms over the period 2004–2007. Finally, using a sample of 83 firms listed in five Arab countries (Egypt, Jordan, Morocco, Saudi Arabia and Tunisia), Bolbol and Omran (2005) provide evidence that stock prices play no role in informing corporate investment decisions. A general result is that whether or not stock prices have real effects may depend on the current maturity and other microstructure features of the market (Mullins and Wadhwani 1989). Note, however, that these studies do not address the specifics of learning as this paper does.
 
8
The list of firms is available upon request and the list of industries is given at the bottom of Online Appendix 1.
 
9
The main results are from instrumental variables (IV) estimations, correcting the error structure for heteroskedasticity and within-firm error clustering akin to Petersen (2009). I use the first and second lagged values of idiosyncratic returns to instrument stock prices and correct for simultaneity bias and measurement errors (Leary and Roberts 2014). As shown in Sect. 4, these instruments are both highly relevant and valid as denoted by the Sargan test statistic reported at the bottom of each table.
 
10
This measure is computed as follows: [capex + R&D + acquisitions − (sales of PPE + depreciation)]/total assets.
 
11
Proxy effects are driven by similar behavior arising from similar firms having similar individual characteristics or facing similar institutional environments (Manski 1993).
 
12
In all the specifications above, peer stock prices per se do not matter for firm investment spending, rather their innovations do. While the coefficients on peer “raw” stock prices are negative, they are consistently insignificant.
 
13
In general, measures of residual stock price informativeness, per se, bear no explanatory power for investment, but their interaction with stock prices may matter. Rather surprisingly, however, Table 5 shows that the primary effect on investment of peer price informativeness is significantly positive (7.99 %) when peers have lower analyst following. The opposite holds true when more analysts follow peer stocks (−7.50 %).
 
14
Financial analysis is admittedly not without its drawbacks. The pitfalls of excessive analyst coverage (such as persistent stock mispricing) pertain to both investment banking economic incentives and analysts’ self-interests. However, this is not the focus of the current study.
 
15
The KZ4 index used in this study is similar to the prominent index introduced by Kaplan and Zingales (1997). The difference between the modified index used here and the original measure is that I exclude the average Tobin’s Q from the computations. In addition, I purposely bypass the discussion about the ability of this index to capture financing constraints (a dedicated discussion can be found in Hadlock and Pierce 2010).
 
16
As an ancillary result, I observe a substantial increase in the unconditional effect of peer price innovations. In this specification, a one standard deviation increase in peer stock price innovations is associated with an 8.72 % increase in investment, which represents an increase of about 75 % relative to the unconditional effect shown in Table 4 (4.99 %). In contrast, the sensitivity of investment to firms’ own stock price experiences no material alteration, and lies at 3.47 %.
 
17
When I split the sample using the industry-year median market share as telltale sign, I find consistent evidence that investment sensitivity to innovations in peer stock prices decreases in market share. For firms with lower market share a one standard deviation increase in peer stock price innovations is associated with a 6.72 % increase in investment spending. As the market share of the firm becomes more substantial (i.e. lies above the median within the peer group), I document decreasing propensity of firms to learn from peer firms, but the response remains positive (2.14 %) and marginally significant. Reputational models predict that less successful agents will pay more attention to the characteristics and actions of their more successful peers (Scharfstein and Stein 1990). Against this prediction, I find that the median firm’s investment spending responds more to peer firms’ stock price shocks when peers show below median market share. In this case, a one standard change in peers’ stock price shocks propels the median firm to change its investment spending by 6.86 % in the same direction. In contrast, there is no significant response of investment to innovations in peer firms’ stock prices when peers have higher market share. Furthermore, market share does not help to explain cross-sectional variations in investment sensitivity to firms’ own stock price. It is positive and statistically significant, and lies between 3.01 and 3.92 %. The results are available upon request.
 
18
An earlier version of this study uses the sample split approach rather than the interaction variable approach used in the current version of the paper. The preference for the interaction variable approach resides in the desire to guarantee the power of the tests, as sample splits significantly decrease sample size. I also have tested for the robustness of the inferences using the investment definition developed by Richardson (2006); the inferences are qualitatively similar.
 
19
The main effects of residual price informativeness are trivial. However, market share and capital intensity appear to have a dampening effect on the learning propensity of firms. Profitability (ROA) and sales growth of peer firms induce firms to (unconditionally) increase investment even though moderation occurs depending on the level and informativeness of peer stock prices.
 
20
An interesting finding of the current study is that learning from stock prices in Europe is dynamic. While Mullins and Wadhwani (1989) find that stock prices have no explanatory power in informing corporate investment outside the U.S., I report weak evidence for it. Moreover, European firms learn from stock prices because of informational and strategic motives.
 
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Metadaten
Titel
The interaction between stock prices and corporate investment: is Europe different?
verfasst von
Houdou Basse Mama
Publikationsdatum
30.11.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Review of Managerial Science / Ausgabe 2/2017
Print ISSN: 1863-6683
Elektronische ISSN: 1863-6691
DOI
https://doi.org/10.1007/s11846-015-0187-3

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