Shenglan Chen,Hui Ma

aSchool of Economics and Management,Inner Mongolia University,China

bSchool of Accountancy,Shanghai University of Financial and Economics,China

Peer ef f ects in decision-making:Evidence from corporate investment

Shenglan Chena,*,Hui Mab

aSchool of Economics and Management,Inner Mongolia University,China

bSchool of Accountancy,Shanghai University of Financial and Economics,China

ARTICLE INFO

Article history:

We show that peer e ff ects in fl uence corporate investment decisions.Using a sample of China’s listed fi rms from 1999 to 2012,we show that a one standard deviation increase in peer fi rms’investments is associated with a 4%increase in fi rm i’s investments.We further identify the mechanisms,conditions and economic consequences of peer e ff ects in fi rms’investment decisions.We fi nd that peer e ff ects are more pronounced when fi rms have information advantages and the information disclosure quality of peer fi rms is higher,or if they face more fi erce competition.When fi rms are industry followers,are young or have fi nancial constraints,they are highly sensitive to their peers fi rms.We also quantify the economic consequences generated by peer e ff ects,which can increase fi rm performance in future periods.

?2016 Sun Yat-sen University.Production and hosting by Elsevier B.V.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

1.Introduction

It is common for corporations to interact with peer f i rms in decision-making,such as signing strategic cooperating agreements and developing marketing strategies.Previous studies show that peer f i rms play an important role in shaping a variety of corporate policies,such as product pricing(Bertrand,1883)and advertising (Stigler,1968),but the ef f ect of peer-f i rm behavior on corporate f i nancial policy is often ignored in empirical research,or at most assumed to operate through an unmeasured ef f ect on f i rm-specif i c determinants.Recent studies examine whether the characteristics or behavior of peer f i rms af f ect corporate capital structure(Leary and Roberts,2014),mergers and acquisitions(Bizjak et al.,2009)and tax avoidance(Li et al.,2014).

Investment decisions are important and determine corporate development.Most studies that examine peer e ff ects in corporate investment suggest that managers can gain useful information from the stock price of peer fi rms.Edmans et al.(2012a,2012b)and Bond et al.(2012)point out that stock prices include information that is helpful in guiding a fi rm’s investment policy,such as industry growth opportunities,external environment, competitor strategy and consumer demands.Valuing the stock price of peer fi rms can therefore capture useful information to help reduce investment uncertainty.Ozoguz and Rebello(2013)f i nd that f i rms’investment policy reacts appropriately to volatility in a peer f i rms’stock price.Using U.S.listed f i rms from 1996 to 2008, Foucault and Fresard(2014)f i nd that the valuation of peers matters for a f i rm’s investment:a one standard deviation increase in a peers’valuation is associated with a 5.9%increase in corporate investment.Fracassi (2012)and Dougal et al.(2012)provide similar empirical results.However,few studies investigate whether managers directly mimic the investment behavior of peer f i rms.In this study,we predict that f i rms’investment behavior is inf l uenced by peer f i rms’investment decisions,and provide empirical evidence to support the prediction.

In the stock markets of developed counties,stock prices aggregate diverse corporate decisions and ultimately ref l ect an accurate assessment of f i rm value.However,China has only slowly developed a legal framework for its stock market,and has a weak law enforcement record.Consequently,the idiosyncratic information of f i rms is def i cient,and stock prices are highly synchronous(Morck et al.,2000;Zhu et al., 2007).In this undeveloped stock market,stock prices are not the most useful source of information when real decisions are taken.Firms are more likely to directly mimic the strategies and decisions of their peers.Liu and Chen(2012)f i nd that it is common for f i rms to imitate their peers’behavior in the industry cluster,and this imitation can increase the performance of both a f i rm and its peers.Focusing on corporate mergers and acquisitions,Chen and Lu(2013)argue that the acquisition premium is signif i cantly af f ected by peer f i rms.This evidence shows that managers have strong incentives to learn from peer f i rms,enabling them to maximize f i rm value or avoid the potential risk of failure(Ren,2002;Zhuang,2003;Li et al.,2011).

We examine the ef f ect of the investment policy of peer f i rms on a f i rm’s investment.Information imperfection and investment uncertainty are the main reasons behind the learning behavior of a peer group(Lieberman and Asaba,2006).Any investment decision involves risk and uncertainty.Managers may be unsure of the likelihood of possible outcomes,and may have fundamental difficulties recognizing cause and ef f ect relationships and the full range of potential consequences(Milliken,1987).In environments of uncertainty and ambiguity, managers are particularly likely to imitate the investment activities of peers.This imitation,though still highly imperfect,can signif i cantly reduce the investment risk and the possibility of falling behind rivals.Peer f i rms therefore have a strong inf l uence on managerial perceptions and beliefs.For example,Mongolia Yili Industrial Group Co.,Ltd.,a large dairy enterprise,produces‘‘breakfast milk”and attaches importance to a nutritional breakfast.Mengniu Dairy,the biggest competitor of Yili,then actively rolls out‘‘Mengniu breakfast milk.”‘‘JinDian(金典)milk”produced by Yili and‘‘TeLunsu(特侖蘇)milk”produced by Mengniu are also good examples of the learning ef f ect in product development.While specif i c cases of f i rms learning from their peers can be identif i ed,it is unclear whether the learning ef f ect is widespread in investment policies.

The challenge in examining learning from a peer group is to identify the set of f i rms that can use the investment policies of peers to guide their own investment decisions.Generally,this group will include f i rms that have several similar characteristics(e.g.,industry,size,diversif i cation,business complexity and f i nancing constraints),so the behavior of these f i rms is similar within the same market.The more similarities a f i rm has with its peers,the more likely it is to mimic their investment decisions to reduce the potential failure risk.Considering all these characteristics simultaneously is not practical,however,as peer groups may be made up of too few f i rms,which would be noisy when f i ltering external shocks.Following Albuquerque(2009)and Leary and Roberts(2014),we specify peer f i rms as those in the same industry and in upper and lower size quartiles(0.75 times to 1.25 times a f i rm’s total assets)in relation to the f i rm.After specifying the peers of each f i rm,we examine whether peer f i rms inf l uence the investment behavior of the f i rms,and f i nd that they play an important role in shaping corporate investment decisions.Speci fi cally,we fi nd that a one standard deviation increase in peer fi rms’investment is associated with a 4%increase in fi rm i’s investment.Investment can generally be divided into two categories:(1)investment in property,plant and equipment(PPE)and(2)investment in intangible assets such as R&D,and we test the peer e ff ect in these two types of investment.The results show that both types are sensitive to the investment policies of peer fi rms,while the peer e ff ect is more pronounced in PPEinvestment.Specif i cally,a one standard deviation increase in PPE investment by peer f i rms leads to a 14.4% increase in the PPE investment of f i rm i.

To ensure the robustness of the empirical results,we specify peer f i rms according to dif f erent criteria and reexamine the peer ef f ect in corporate investment policy.In robustness tests,we specify the f i rms in the same registering city and industry,and in the upper and lower size quartiles(0.75 times to 1.25 times a f i rm’s total assets)to the f i rm as provincial-level peer f i rms.We def i ne f i rms as national-level peer f i rms if their assets are in the range of 0.9-1.1 times the assets of the f i rm and in the same industry.The inferences are robust to these dif f erent measures.We replace the lagged control variables with contemporaneous controls to address the concern that investment policy af f ects f i rm-specif i c and peer f i rm characteristics with a lag.Again,we see little change in the results,suggesting that model misspecif i cation in the control variables is unlikely to be behind our results.

Evidence is,however,insufficient to conclude that peer f i rms inf l uence the f i rm’s investments as the relation can covary,due to ref l ection problems(Manski,1993;Shue,2013).Ref l ection problems arise when a researcher observing the distribution of behavior in a population tries to infer whether the average behavior in a group inf l uences the behavior of the individuals that comprise the group.In the current context,this problem is recreated by identifying peer f i rms in same industry.Firms from the same industry face similar institutional environments,investment opportunities and consumption demands,and are more likely to make similar investment decisions.The inability to accurately model the relevant factors inf l uencing the f i rms’investment and its peers generates endogeneity bias.Identifying peer ef f ects is therefore an empirical challenge.We use the following tests to further establish the causality of our fi ndings.

First,specifying fi rms in the same industry but not in upper and lower size quartiles of that fi rm as non-peer fi rms,we examine the e ff ect of the investment of a non-peer fi rm on the fi rm’s investment.If our fi ndings are driven by the macroeconomic environment,industry factors or market-level factors rather than by learning behavior,then we can predict there is a signif i cant positive relationship between the investment of peer f i rms and that of the f i rm,as non-peer f i rms are still in the same industry.However,if we cannot observe a positive relationship,we can infer that the f i ndings are not driven by the ref l ection problem.Second,we conduct an instrumental variable method to address the possible endogeneity bias,using our measures of peer f i rm equity shocks as instruments for peer f i rm investment policy.The peer f i rms return shocks are serially uncorrelated and serially cross-uncorrelated,and are less likely to be manipulated by managers when compared to other investment determinants,such as prof i tability and cash ratios.The instrument variable selected therefore meets the requirements for instrument relevance and exogeneity.Third,with the inclusion of f i rm f i xed ef f ects in the regression model,we reexamine whether peer f i rms inf l uence the investment behavior of the f i rm.This specif i cation addresses the concern that commonality in a f i rm’s investment policy is due to time-invariant investment determinants over the business cycle.

The alternative explanation of the results is that a f i rm’s investment policies are driven by a response to their peers’characteristics rather than investment behavior.Here,the peer ef f ect in corporate investment arises when f i rms respond to changes in the characteristics of their peers’prof i tability,risk,etc.However,the response to their peers’characteristics is dif f erent from learning behavior.Thus,we provide additional analysis to investigate this distinction.To distinguish between these alternatives,we exploit heterogeneity in f i rms’investment responses to their peers’equity shocks after controlling for their peers’investment.The evidence shows that holding f i xed the peer f i rm equity shock,the investments are strongly positively correlated with investments in the peer f i rms,but investments are unrelated to the peer f i rm equity shock,holding f i xed the peer f i rm investments.Thus,f i rms only change their investment in response to a peer f i rm equity shock if it is accompanied by a change in peer f i rm investment,which provides additional support to our conclusion.

Next,we identify the possible channels through which peer f i rms inf l uence a f i rm’s investment.Lieberman and Asaba(2006)f i nd that f i rms imitate to avoid falling behind their rivals,or because they believe that their rivals’actions convey information.According to information based theory,f i rms disclose large amounts of information,such as their business strategy,f i nancial performance,expected future outlook,current and future investment outlays,material contracts and business risks,and this information has a strong spillover ef f ect on the decision-making of others(Gigler,1994;Kumar and Langberg,2010).Managers then have an incentive to value information disclosed by peers,which will guide their real decisions.Empirical evidence demonstrates that a f i rm’s disclosures can have positive externalities.For example,using a private f i rmcontext,Badertscher et al.(2013)examine the externalities of public fi rm presence on the investment decisions of private fi rms,and fi nd that public fi rm presence reduces uncertainty in a speci fi c industry and increases the investment efficiency of private fi rms in that industry.Beatty et al.(2013) fi nd that peers react to high-pro fi le fraudulent reports by increasing their investment expenditure during the fraud period,due to the spillover e ff ect of fraudulent information.We therefore predict that information is an important channel through which peers matter to fi rms in their investment decisions.We test this prediction in two ways.First,following Houston et al.(2014),we use the distance between the registering city of the fi rm and the capital city Beijing to measure the informativeness of the fi rm,and then examine whether the peer e ff ect in corporate investment policy varies with a fi rm’s informativeness.Given that most policies in China are made at conferences in Beijing,it is possible for fi rms close to Beijing to identify potential industry policies and investment opportunities in advance,thus reducing the investment uncertainty and incentive to learn from peers.The results show that closer to Beijing a fi rm is the less sensitive and its investment policy is to peers.Second,we investigate whether the information quality of peers in fl uences the learning e ff ect.Institutional background and regulatory environment di ff erences between mainland China and Hong Kong also lead to a di ff erence in the quality of information disclosure of listed fi rms(Pistor and Xu,2005;Ke et al.,2015).The information disclosed by AH share fi rms is therefore more reliable and valuable.We test this prediction by using AH share fi rms to measure information quality.We fi nd that the learning e ff ect is more pronounced when at least one AH share fi rm is in a peer group.

According to rival-based theory,f i rms’imitation is also a response designed to mitigate competitive rivalry or risk.Firms imitate others in an ef f ort to maintain their relative position or to neutralize the aggressive actions of rivals.Imitation to mitigate rivalry is most common when f i rms with comparable resource endowments and market positions face one another.In a highly competitive environment,suf f ering from a high risk of bankruptcy,f i rms have strong incentives to learn from the strategies of their peer f i rms(Peress,2010; Ozoguz and Rebello,2013).Klemperer(1992)argues that learning from others can to some extent alleviate competitive pressure.Chen and Chang(2012)also provide evidence that f i rm’s cash holdings respond more positively to peers when the product market is highly competitive.Thus,f i rms learn from each other in the introduction of new products and processes,in the adoption of managerial methods and organizational forms and in the entry of certain investments and the timing of the investment.Learning behavior therefore helps fi rms preserve the status quo among their close competitors,even in industries where strong rivalry is maintained.Similar to previous studies(Curry and George,1983;Giroud and Mueller,2011),we use the Her fi ndahl index and the number of fi rms in each two-digit industry to proxy for market competition,and then examine whether the peer e ff ect in investment policy varies with product market competition.The results show that the learning e ff ect in investment policy is more pronounced in a highly competitive market.

To better understand why peer fi rms a ff ect investment policy,we further examine the heterogeneity in peer e ff ects.First,industry leaders are more likely to have the ability to capture the investment opportunities and develop innovative products and techniques than non-industry leaders.Consequently,we predict that the peer e ff ect is less pronounced in the investment policies of industry leader fi rms.Second,lacking sufficient market experience and available resources,young fi rms are more likely to mimic the investment behavior of peer fi rms,to reduce uncertainty and the risk of failure(Petersen and Rajan,1994;Hadlock and Pierce,2010). We predict that the investment of young fi rms is more sensitive to the investment of their peer fi rms.Third, fi nancially constrained fi rms are less sensitive to the behavior of peer fi rms than unconstrained fi rms,as mimicking behavior is assumed to be more costly for fi nancial constrained fi rms,given their high cost of fi nancing. These inferences are supported by empirical results.

Finally,using ROA and Tobin-Q in the next one to three years to measure future corporate performance, we examine the economic consequences generated from this learning behavior in corporate investment policies.Learning behavior in investment is found to benef i t corporate performance.Specif i cally,learning behavior increases corporate performance and f i rm value.The results reveal the importance of the learning ef f ect in investment under an uncertain environment.

Our study contributes to the literature in two ways.First,previous studies suggest that a f i rm’s investment policy is typically assumed to be determined as a function of its growth opportunities,f i nancing constraints, marginal tax rate and external regulations.The role of peer f i rm behavior in af f ecting investment policy is often ignored.Following the research perspective of Ozoguz and Rebello(2013)and Foucault and Fresard(2014),this study’s focus is on the role of a peer fi rm in shaping a fi rm’s investment policy.Using a sample of Chinese listed fi rms from 1999 to 2013,we extend the literature by analyzing the direct relation between a fi rm’s and its peers’investments,which di ff ers from the studies by Ozoguz and Rebello(2013)and Foucault and Fresard(2014).We further address the re fl ection problem and endogeneity bias,identifying the potential channels and mechanisms behind the peer e ff ect in investment,and fi nally con fi rm the economic consequences of these ef f ects.The f i ndings extend our understanding of investment determinants.

Second,peer ef f ects have been mainly applied in psychology and sociology research(Valliant,1995;Dishion et al.,1999;Katz et al.,2001).Many studies have examined the peer ef f ect on corporate real decisions,such as corporate capital structure,merges and acquisitions and corporate governance(John and Kadyrzhanova, 2008;Chen and Chang,2012;Leary and Roberts,2014;Foucault and Fresard,2014).We f i rst examine the role of a peer f i rm in shaping a f i rm’s investment decisions,which extends the literature on peer ef f ects. Lieberman and Asaba(2006)argue that information needs and competition pressure are two channels through which peers inf l uence the behavior of the f i rm.In this study,we empirically test these two predictions and provide evidence to support the theoretical prediction of Lieberman and Asaba(2006),which reveals the mechanism of the learning ef f ect.

The remainder of this paper is as follows.Section 2 reviews the literature.Section 3 develops the hypothesis based on theoretical analysis.Section 4 introduces the sample selection and the variables,and develops the empirical model.Section 5 presents the summary statistics and main empirical results.Section 6 identif i es the potential channels through which peer f i rms af f ect f i rms’investment policies.Section 7 examines the cross-sectional heterogeneity in the ef f ects to better understand the economic mechanisms behind the peer ef f ect.Section 8 presents the economic consequences of the peer ef f ect in investment decisions.Section 9 concludes.

2.Literature review

In economic theory,it is argued that peer f i rms play an important role in shaping corporate decisions, such as through product pricing(Bertrand,1883)and product advertising(Stigler,1968).An increasing number of empirical studies examine the characteristics or behavior of peer f i rms and whether they af f ect a f i rm’s behavior.Using a sample of U.S.listed f i rms,John and Kadyrzhanova(2008)investigate the peer ef f ect in corporate governance.Studies also examine the ef f ect of peer f i rms on corporate capital structure (Leary and Roberts,2014),merges and acquisitions(Bizjak et al.,2009)and tax avoidance(Li et al.,2014). For example,Leary and Roberts(2014)present evidence that a one standard deviation increase in peer fi rms’leverage ratios is associated with a 10%increase in fi rm i’s leverage ratio,an e ff ect greater than that of any other determinants.In corporate investment policies,the behavior of peer fi rms has a strong spillover e ff ect on a fi rm’s investment decisions(Foucault and Fresard,2014),so the possibility of a signi fi cant e ff ect cannot be ignored.

Information-based and rivals-based theories are typically used to explain learning behavior among peer fi rms(Benoit,1984;Lieberman and Asaba,2006).In information-based theories,information imperfection is viewed as the main cause of learning behavior.Managers can learn new information from peer fi rms’stock prices,which can then guide their real decisions.Managers do not have perfect information on every decisionrelevant factor,so learning from peers can help them capture more useful information and reduce investment uncertainty.Conlisk(1980) fi nds that experience or experiment is more costly and time-consuming than imitation,so fi rms whose information is imperfect rationally imitate the strategies of others to reduce the possibility of failure.Under environmental uncertainty,it is difficult for managers to predict the consequences of a particular investment,as it raises the likelihood of undesirable outcomes and the risk of failure(Milliken, 1987).Firms with imperfect information when making investment decisions are therefore more likely to learn investment behavior from peer fi rms,to reduce investment risk(Foucault and Fresard,2014),as they believe that peers’actions convey information about growth opportunities,investment opportunities and industry fl uctuations.

Investment decisions also re fl ect managers’rationally formed expectations,and provide a signal of managers’abilities(Scharfstein and Jeremy,1990).Although decision-makers can make optimal investment decisions by capturing and analyzing as many investment-relevant factors as possible,the risk ofinvestment failure is still signif i cant.Under an uncertain environment,managers are more likely to imitate the investment behavior of other managers,as from the perspective of managers concerned about their reputationinthelabormarket,thismimickingbehaviorisrationalandcostless(Palley,1995; Scharfstein and Jeremy,1990).It is better for the reputations of managers to fail conventionally than to succeed unconventionally.

According to the rivals-based theory,learning behavior commonly acts to defuse rivals and stabilize relative positions in the market.Firms imitate each other in the introduction of new products and processes,the adoption of managerial methods and organizational forms,and the timing and types of investments,as learning behavior is helpful in gaining competitive advantage(Klemperer,1992)and reducing investment uncertainty(Knickerbocker,1973).Firms imitate others in an ef f ort to maintain their relative positions or to neutralize the aggressive actions of rivals.Chen and Chang(2012)f i nd that f i rms also tend to have sizeable cash reserves when their rivals hold high cash holdings.From the perspective of market competition,imitation to mitigate rivalry in important corporate decisions is most rational when f i rms with comparable resource endowments and market positions face each another.

3.Hypothesis development

Imitation processes are most interesting in environments characterized by uncertainty or ambiguity.Few decisions have outcomes that are fully predictable.Managers take actions,the consequences of which depend on the future state of the environment.Managers therefore actively and regularly imitate peers’behavior or actions to overcome information imperfection and protect and enhance managerial reputation.They may also believe that imitation is important in defusing rivalry and reducing risk for their fi rms.Chen and Chang (2012),for example,present evidence that the ratio of cash to total assets is signi fi cantly in fl uenced by peer fi rms’average cash holdings.They argue that fi rms imitate others to reserve cash in an e ff ort to maintain their relative position or to neutralize the aggressive actions of rivals.Chen and Lu(2013) fi nd that peers’merger and acquisition programs are considered and referred to by a fi rm when preparing their own programs to maximize their merger and acquisition performance.Investment policy is important and determines corporate development.Promising investment not only establishes the direction for future development,but also allocates available resources more efficiently,enhancing corporate performance and market value.Firms may suffer enormous fi nancial loss and even the risk of bankruptcy due to errors in vital investments.Consequently, fi rms within the same strategic group may adopt similar behavior to constrain competition and maintain competitive advantages.

In a developed stock market,a fi rm’s stock price provides useful information such as growth opportunities, the state of the economy,the position of competitors and consumer demand.Decision-makers can learn from peer f i rms’stock price and use the information to guide their investment policy,thus reducing uncertainty and failure risk.Foucault and Fresard(2014)present evidence that the investment behavior of a f i rm is af f ected signif i cantly by its peer f i rms’stock prices,as this informs managers about growth opportunities,thereby overcoming information imperfection and enabling them to make optimal investment decisions.However,the Chinese stock market’s legal framework has developed slowly,and law enforcement is weak.Consequently, specif i c f i rm information is lacking,and stock prices are highly synchronous(Morck et al.,2000;Zhu et al.,2007).In emerging economies such as China,stock prices provide less useful information to managers making decisions than in developed countries.Learning directly from the real decisions of peer f i rms rather than from their stock prices is more efficient and prevalent,and the mechanism is dif f erent from that of developed countries.Liu and Chen(2012)f i nd that the learning behavior of Chinese f i rms is common in an industry cluster,and signif i cantly enhances productivity for both a f i rm and its peers.We can therefore infer that a f i rm has strong incentives to mimic the investment behavior of peer f i rms in China,thus reducing the failure risk of investment and mitigating competitive pressure as much as possible.We therefore conduct a statistics test of the following hypothesis:

H1.A f i rm’s investment is signif i cantly inf l uenced by its peer f i rms.

4.Research design,sample selection and summary statistics

4.1.Corporate investment model

Following Richardson(2006),we control for f i rm-level factors relevant to investment decisions and the corporate investment model is set as follows:

where Inv is the measure of corporate investment policy,def i ned as the ratio of capital expenditure to the beginning-of-year book assets;Growth is the measure of growth opportunities,which is calculated as sales growth;Lev is the ratio of total debt over total assets;Cash is the balance of cash and short-term investments def l ated by total assets measured at the beginning of the year;Age is the log of the number of years the f i rm has been listed on stock markets as of the start of the year;Size is the log of total assets measured at the start of the year;and Ret is the stock returns for the year prior to the investment year.Year f i xed ef f ect is a vector of indicator variables to capture year f i xed ef f ects.Industry f i xed ef f ect is a vector of indicator variables to capture industry f i xed ef f ects.

4.2.Baseline empirical model

To examine whether the investment policy of peer f i rms matters in a f i rm’s investment decision,the average investment of peer f i rms is incorporated in the model(1).We also control for peer f i rms’characteristics in the model to mitigate omitted variable bias.

where the indices i,j and t correspond to f i rm,industry and year,respectively.The outcome variable Invijtis the measure of investment.PInv-ijtdenotes peer f i rms’average investment(excluding f i rm i).Firm Specif i c Factorijt-1contains f i rm’s sales growth,leverage,cash ratio,f i rm age,f i rm size,stock return and investment at year t-1.Peer Firms Factors-ijt-1contains peer f i rms’sales growth,leverage,cash ratio,f i rm age,f i rm size,stock return and investment at year t-1.

The challenge in examining how f i rms learn from their peer group is to identify the set of f i rms that can use the investment policy of peers to guide their own investment decisions.The group will typically include f i rms that have several characteristics in common(e.g.,industry,size,diversi fi cation,business complexity and fi nancing constraints),so the behavior of these fi rms is similar in the same market.Firms are more likely to mimic the investment decisions of their peers if they are similar,reducing potential failure risk.Yet considering all the characteristics simultaneously is not practical as it may result in a peer group consisting of too few fi rms,which would be noisy when fi ltering external shocks.Following Albuquerque(2009)and Leary and Roberts(2014),we specify fi rms in the same industry and with upper and lower size quartiles(0.75 times to 1.25 times a fi rm’s total assets)as similar peer fi rms.Table 1 provides de fi nitions of the speci fi c variables.

4.3.Sample selection

We obtain fi nancial data from the China Stock Market and Accounting Research Database(CSMAR) from 1999 to 2013.We drop(1) fi nancial,insurance and utility fi rms,(2) fi rm-years that do not match other fi rms in the same industry and size quartiles,and(3)observations with missing data on any variables.The fi nal sample contains 17,463 observations from 1999 to 2013.To avoid the e ff ect of outliers,we winsorize the top and bottom 1%of the continuous variables.To correct this statistical problem,we use a‘‘clustering”method to adjust the standard error of the estimated coefficient for each company(Petersen,2009).

Table 1Variable def i nitions.

4.4.Descriptive statistics and correlation analysis

Table 2 presents the descriptive statistics.Variables are grouped into two distinct categories:peer f i rm averages and f i rm-specif i c factors.The mean(median)of the corporate investment is 0.062(0.039),and means (medians)of PPE and R&D investment are 0.031(0.012)and 0.005(0.001),respectively.The mean(median) of sales growth is 0.184(0.146).The average cash holding and leverage are 0.485 and 0.190,respectively.The means of f i rm size,age,stock return and lagged investment are 21.332,8.148,0.172 and 0.066.For peer f i rm averages,the mean(median)of the investment is 0.063(0.040),and means(medians)of PPE and R&D investment are 0.043(0.035)and 0.001(0.005),respectively.The latter group includes variables constructed as f i rm i’s value in year t.At this point,we simply note the similarities of many statistics to the former group.

In addition,we also report summary statistics for other variables.The peer f i rm average equity shock is 0.218,and the average log of distance from the registering city of the f i rms to Beijing is roughly 6.505.About 29.1%of f i rms have at least one AH-share peer f i rm in their peer group.The mean of MP is-0.160.The average HHI is 0.935 and 98 f i rms are in the two-digit industry code.Of the sample,about 35.8%of f i rms are industry leaders,and over 75%f i rms are young f i rms in the market.The average for WW index,which measures corporate f i nancing constraints is-0.962.

In Table 3,we present the results of the correlation analysis of the variables.The correlation coefficient of PInv with Inv is 0.262 and is signif i cant at a 5%level,showing that corporate investment is strongly positively correlated with the average investment of peer f i rms.Firm i’s sales growth,leverage ratio,f i rm size,stock return and lagged investment are positively signif i cant at a 5%level.However,its cash ratio and age are negatively correlated with investment.A peer f i rm’s specif i c characteristics also af f ect a f i rm’s investment decision. For example,peer fi rms’growth,size and lagged investment are signi fi cant at 5%level.The correlation coeffi cients of leverage ratio and fi rm age with fi rm i’s investment are-0.046 and-0.031 respectively,and are signi fi cant at a 5%level.

5.The role and implications of the peer ef f ect

5.1.Empirical results for baseline model

Table 4 shows the empirical results for the ef f ects of peer f i rms on corporate investment.When controlling for only the year and the industry f i xed ef f ects in the model,the result is reported in column(1).The coefficientof Pinv is 0.2205,signif i cant at a 1%(t=11.26)level,which indicates that f i rm i’s investment is signif i cantly inf l uenced by peer f i rms.Specif i cally,a one standard deviation increase in the average peer f i rm investment leads to a 14.2 percentage point increase in f i rm i’s investment.Following Richardson(2006),we add f i rmspecif i c characteristics such as sales growth Growtht-1,cash ratio Casht-1,leverage ratio Levt-1,f i rm size Sizet-1,f i rm age Aget-1,annual stock return Rett-1and lagged investment Invt-1as control variables to mitigate the ef f ect of other factors.From the estimates in column(2)of Table 4,we see that the coefficient on the PInv in the regression is 0.0906 and signif i cant at a 1%(t=6.73)level,which is consistent with column(1).We also control for the peer f i rms’specif i c characteristics in the model to mitigate omitted variable bias(Leary and Roberts,2014).Regarding omitted factors,we note the following in column(3)of Table 4.The adjusted R2is 0.398,and the control variables are statistically signif i cant in the expected directions.The coefficient on the PInv is positive and signif i cant at a 1%level,which indicates that a one standard deviation increase in the average peer f i rm investment leads to a 4%(calculation:(0.0618×0.040)/0.062)increase in f i rm i’s investment after controlling for f i rm-specif i c and peer f i rm-specif i c characteristics.This suggests that peer f i rms play an important role in shaping corporate investment policy,which may be a strategy used to reduce investment uncertainty and stabilize the competition position in the market.The above regression results provide evidence supporting our Hypothesis.

Table 2Summary statistics.

Table 3Correlation matrix.

Table 4Ef f ect of peer f i rms on corporate investment.

We then classify investment into tangible and intangible asset investment,and examine the peer ef f ects in both investment types.The results are presented in Table 5.In column(1),the coefficient on PPE is 0.1401, and signif i cant at a 1%level(t=7.09),which indicates that f i rm i’s PPE investment increases 14.4%pointswith a one standard deviation increase in peer f i rms’PPE investment.Regarding R&D investment in column (2),we f i nd that the coefficient is signif i cantly positive,and that a one standard deviation increase in average peer f i rms R&D investment leads to a 5.54%increase in f i rm i’s R&D investment.In summary,f i rms have a strong incentive to mimic their peer f i rms’PPE and R&D investment,but the peer ef f ect is more pronounced in tangible asset investment.Mimicking intangible asset investment policies requires more support,such as corresponding research teams and techniques,making this learning behavior more difficult in the short term.

Table 5Peer ef f ects on dif f erent investment types.

5.2.Robustness tests

The above evidence shows that peer f i rms are important determinants for corporate investment.To avoid peer identif i cation bias due to the current criteria,we specify peer f i rms using new criteria and then test our hypothesis.We not only consider industry and size in identifying peer f i rms,but also consider their registered province,based on spatial competition theory.We specify f i rms in the same registering city and industry,and in the upper and lower size quartiles(0.75 times to 1.25 times of a f i rm’s total assets)to the f i rm as provinciallevel peer f i rms.The results are reported in Panel A of Table 6.The coefficients on PInv are 0.0638 and 0.0918 in columns(1)and(2),respectively.The signif i cantly positive coefficients are consistent with the above f i ndings and provide further support for our hypothesis.Second,we replace provincial-level peer f i rms with national-level peers and re-examine the peer e ff ect in corporate investment.We de fi ne fi rms whose assets are in the range of 0.9-1.1 times the assets of the fi rm and when the industry is the same as national-level peer fi rms.From the estimates in columns(3)and(4),we can see that the coefficients on Pinv measured by nationalpeer f i rms’average investment are positive(0.0939 and 0.1400)and signif i cant(t=7.86;t=10.03).The evidence shows that peer f i rms do inf l uence a f i rm’s investment decision-making.In summary,the inferences are robust to these dif f erent measures.

Table 6Robustness tests.

Furthermore,we replace the lagged control variables with contemporaneous controls to address the concern that investment policy af f ects f i rm-specif i c and peer f i rm characteristics with a lag.The results are tabulated and reported in Panel B of Table 6.As expected,the coefficients on explanatory variables are strongly positive.Again,we see little change in the results,suggesting that model misspecif i cation in the control variables is unlikely to be behind our results.All the robustness tests are consistent with our main results,further strengthening the reasoning on peer ef f ects in corporate investment decisions.

5.3.Ref l ection problem and endogeneity bias

The above evidence is,however,insufficient to establish a causal relationship between the investment of peer f i rms and a f i rm’s investment,as the correlation may be driven by a ref l ection problem.This problem is due to how peer f i rms are identif i ed,in this case as peers in the same industry.Firms from the same industry face similar institutional environments,investment opportunities and consumption demands,so are more likely to make similar investment decisions.Our next challenge is therefore to identify the causality and mitigate the disturbance of the ref l ection problem(Manski,1993;Shue,2013).Specifying f i rms in the same industry but not in the upper and lower size quartiles as the f i rm as non-peers,we then examine whether these nonpeer fi rms can in fl uence corporate investment policies.The test is reasonable and valuable as these non-peer fi rms are still in the same industry and the same regulatory environment,so they can fi lter the e ff ects of their macro-economy,industry policy and market development on investment synchronicity.If our fi ndings are driven by these common factors rather than by a learning incentive,then we can predict that there will still be a signi fi cantly positive relation between non-peers’investment and a fi rm’s own investment.However,the results from column(1)of Table 7 show that the coefficient on NPInv is negative(-0.0048)and insigni fi cant (t=-0.19),which violates the expectation based on the re fl ection problem.The evidence that non-peers in the same industry do not a ff ect corporate investment suppresses re fl ection problem concerns but supports the causality of the peer e ff ect in investment decisions.

To alleviate endogeneity bias,we follow the method of Leary and Roberts(2014)and use peer fi rm equity shocks to instrument for peer fi rm investment policy.Foucault and Fresard(2014) fi nd that stock prices react to corporate investment policy,which shows that equity shock,correlated with investment decisions,meets the requirement of instrumental relevance.The peer fi rms return shocks are serially uncorrelated and crossuncorrelated,and are less likely to be manipulated by managers compared to other investment determinants, such as pro fi tability and cash ratios.This measure is available for a broad panel of fi rms and thus mitigates the statistical power and external validity concerns,when comparing CEO sudden death.While these features do not guarantee exogeneity,they are reassuring as they suggest that peer fi rm return shocks contain little common variation.Regression results using instrumental variables are reported in column(2)of Table 7.When using average peer fi rm investment as the dependent variable in the fi rst stage,instrumental variable is positiveand signif i cant at a 1%level.In the second stage,the coefficient on PInv is still signif i cantly positive,which is consistent with the main results.

Table 7Ref l ection problem and endogeneity bias.

Finally,with the inclusion of f i rm f i xed ef f ects in the regression model,we reexamine whether peer f i rms inf l uence the investment behavior of a f i rm.As shown in column(3),the coefficient on Pinv is 0.0824 and signif i cant at a 1%level(t=5.24).The evidence indicates that commonalities among f i rm’s investment policy are time-invariant investment determinants over the business cycle,but this does not inf l uence the conclusion.All tests conf i rm the f i ndings are robust after removing the ref l ection problem and mitigating endogeneity bias.

While our results establish the presence of signif i cant peer ef f ects,they are subject to limitations.We cannot distinguish between the characteristics and behavior of peer f i rms that af f ect a f i rm’s investment policy.To exclude the alternative explanation,we exploit heterogeneity in a f i rm’s investment change responses to their peers’equity shock,by performing a double sort of the data,based on quintiles of our peer f i rm average equity shocks and peer f i rm investment changes.Within each quintile combination,we calculate the average changes in investment for f i rm i and t-statistics of whether this change is signif i cantly dif f erent from zero.

The results are presented in Table 8,where quintile 1 represents the lowest 20%of the distribution and quintile 5 the highest.For example,the average change in investment among f i rms in the lowest peer f i rmequity shock quintile and the highest peer f i rm leverage change quintile is 0.0859 with a t-statistic of 30.78.We note a monotonic increase in the average investment change across each row.Holding f i xed the peer f i rm equity shock,investment changes are strongly positively correlated with changes in peer f i rm investment. The converse is not true.Average investment changes are largely uncorrelated with the peer f i rm equity shock, holding f i xed peer f i rms’average investment change.In fact,in the last row(5-1),where the dif f erence of average peer f i rm investment changes between rows 1 and 5 is indistinguishable from zero,the cell averages are all economically small and two are statistically insignif i cant.Thus,f i rms only change their investment in response to a peer f i rm equity shock if it is accompanied by a change in peer f i rm investment.These f i ndings reinforce the implication of the regression results and suggest that a fi rm’s investment is more likely a response to peer fi rm fi nancial policies,as opposed to characteristics.

Table 8Removal of alternative explanation.

6.Channels of identif i cation

Lieberman and Asaba(2006)found that information imperfection and market competition are the two main causes of imitation among the peer group.Thus,we empirically examine the channels through which peer ef f ects operate.Based on information theory,f i rms actively learn from peers’decisions as they have imperfect information on decision-making and they believe that peers’actions convey some useful information to guide their real decisions.If f i rms are able to capture information about macroeconomic or industry policy in advance,or if they can identify the prof i table investment opportunities,then we can predict that the f i rms have the advantage in collecting and analyzing information,and thus have less incentive to mimic the investment decisions of peer f i rms.Investment is critical to further development,and f i rms usually take some time to select projects,survey consumer demand,analyze viability and f i nalize projects.The peer group faces similar institutional environments,investment opportunities and consumption demands,and is likely to make similar investment decisions.As such,a f i rm is eager to notice and value the information of peer f i rms so they can overcome information imperfection and reduce uncertainty.Thus,we predict that the information quality of peer f i rms also inf l uences the peer ef f ect in investment.We test these two predictions in two ways.

First,following Houston et al.(2014),we use the distance between the registering city of the f i rm and the capital city Beijing to measure the informational advantage of the f i rm.Most relevant investment policies are made at conferences in Beijing,and f i rms near the city are more likely to identify prof i table investment opportunities in advance,so we predict that the investment of f i rms far from Beijing is more sensitive to that of their peers.As shown in column(1)of Table 9,the coefficient on the interaction term PInv×Dis is 0.0135,and signif i cant at a 10%level(t=1.93),demonstrating that investment is more sensitive to peer f i rms far from Beijing.The evidence for our prediction is strong.

AH companies are Chinese f i rms that have A-shares listed in mainland China and H-shares listed in Hong Kong.They are under the supervision of the Chinese Securities Regulatory Commission(CSRC),and also four Hong Kong regulatory agencies:(1)the Hong Kong Securities and Futures Commission(HKSFC), (2)the Hong Kong Stock Exchange(HKSE),(3)the Hong Kong Institute of Certif i ed Public Accountants (HKICPA)and(4)the Independent Commission against Corruption.The Hong Kong media,analysts andinstitutional investors also play an important role in enforcement.However,China has only recently developed a legal framework for the stock market,and has a weak law enforcement record(Pistor and Xu, 2005).The legal environment has improved in recent years,but it still lags behind Hong Kong in terms of the protection af f orded to minority investors.The market for f i nancial analysts is not well developed and institutional ownership is low(Chen et al.,2013).Institutional investors and brokerage f i rms are often affiliated with the government,so may lack incentives to protect private shareholders.Finally,the media in China are less active than their counterparts in Hong Kong in terms of investigating and publicizing accounting scandals.Government control of the media can prevent full disclosure,as stories are af f ected by political interests. Consequently,the information disclosed by an AH share f i rm is more reliable and valuable(Ke et al.,2015). We def i ne a dummy variable AH to measure the information quality of peer f i rms.Specif i cally,if at least one AH share f i rm is in the peer group,then AH equals one,otherwise zero.The results are presented in column (2)of Table 9.The coefficient on the interaction term PInv×AH is 0.1103,and signif i cant at a 1%(t=3.53) level,which indicates that the peer ef f ect on corporate investment is more pronounced when the peer group includes at least one AH share f i rm.The above evidence provides solid support that sensitivity to peer f i rms’investment varies with the informativeness of both a f i rm and its peers.

Table 9Information-based theory.

Avoiding falling behind rivals is an important incentive for fi rms to imitate each other.Imitation to moderate rivalry is most common when fi rms with comparable resource endowments and market positions face one another.Under a highly competitive market, fi rms are exposed to a higher risk of bankruptcy and continuous operating is uncertain,which leads to severe fi nancing constraints(Povel and Raith,2004).They also pay more attention to resource allocation behavior as they compete for limited resources such as consumers in the highly competitive market(Valta,2012).Chen and Chang(2012) fi nd that the ratio of cash to total assets is signi fi cantly in fl uenced by peer fi rms’average cash holdings.They argue that fi rms imitate others to reserve cash in an e ff ort to maintain their relative position or to neutralize the aggressive actions of rivals.We next examine whether market competition in fl uences the peer e ff ect in corporate investment policy.Similar to previous studies(Curry and George,1983;Giroud and Mueller,2011),we use the Her fi ndahl index and the number of fi rms in each two-digit industry to proxy for market competition.From the estimates in Table 10,we fi nd that the coefficients on the interaction terms are both positive and signi fi cant,which supports our prediction.In summary,the evidence demonstrates that when competitors take similar action,there is less chance that any fi rm will succeed or fail relative to others.Imitation therefore helps preserve the status quo among competitors that follow each other.In a competitive market,these fi rms have strong incentives to learn from the behavior of peer fi rms.

Table 10Rival-based theory.

7.Heterogeneity in peer ef f ect

Given the importance of peer f i rm behavior for f i rms’investment policy,we now turn to why f i rms mimic one another.In this section,we focus on f i rm specif i c characteristics such as industry leader position,f i rm age and corporate f i nancing constraints,and then examine whether some f i rms within the industry are more or less sensitive to their peers’investment policy.

First,we examine whether an industry leader is less sensitive to peer f i rms’investment behavior.In general, industry leaders are more likely to have the ability to identify potentially prof i table investment opportunities and innovate on new products,thus making the imitation to peer f i rms less valuable for industry leader.Leary and Roberts(2014)present evidence showing that industry leaders’ fi nancial policy is less sensitive to its peers’fi nancial policy,though peer fi rms play an important role in shaping corporate capital structure.They argue that small fi rms have stronger incentive to mimic their peers’investment behavior,to reduce investment uncertainty.We categorize fi rms within each industry-year into two groups,industry leaders and followers.We de fi ne these by sorting fi rms within each industry-year into three groups according to their sales share.Industry leaders are those fi rms in the top third of the distribution.From the results in column(1)of Table 11, we fi nd that the coefficient on the interaction term is negative and signi fi cant at a 5%level,which indicates that industry leaders’investment policy is less in fl uenced by their peers compared to followers’investment behavior.The inference is consistent with Leary and Roberts(2014).

Table 11Heterogeneity in peer ef f ect.

Second,previous evidence shows that young fi rms are di ff erent from mature fi rms in many aspects,such as unfamiliarity with the regulatory environment,a poor ability to capture valuable information,and higher capital costs of fi nancing,and that young fi rms lack sufficient operating experience and sufficient available resource to compete with rivals(Petersen and Rajan,1994;Hadlock and Pierce,2010).Relative to mature fi rms,young fi rms are therefore exposed to higher risk of bankruptcy(Dune et al.,1989),and‘‘follow-theleader”behavior is the result of risk minimization.If rivals match each other,none become relatively better or worse o ff.This strategy guarantees that their competitive capabilities remain roughly in balance.We therefore predict that the investment of young fi rms is more sensitive to that of peer fi rms.We also categorize fi rms within each industry-year into two groups,young fi rms and mature fi rms.We de fi ne these by sorting fi rms within each industry-year into three groups according to their age in the listed year.Young fi rms are those in the bottom third of the distribution.The results show that the interaction term is signi fi cantly positive, which is consistent with our prediction.

Firms are de fi ned as more fi nancially constrained by Whited-Wu’s(2006)index.The empirical results are reported in column(3)of Table 11.The coefficient on PInv×WW is-0.1082,and is signi fi cant at a 1%level. The fi nding suggests that fi nancing constraints moderate the learning e ff ect in corporate investment decisions, as mimicking behavior is expected to be more costly for fi nancially constrained fi rms,given their high cost of fi nancing.This evidence indicates that industry leaders,mature fi rms and fi nancially constrained fi rms are less sensitive to their peers’investment policy.

Table 12Economic consequences of peer ef f ect.

8.Economic consequences of peer ef f ect

Finally,using ROA and Tobin-Q to measure corporate performance in the next one to three years,we examine the economic consequences generated from learning behavior.From the estimates in Table 12,we fi nd that the coefficients on the interaction term Inv×Pinv are signi fi cantly positive,which indicates learning behavior in investment bene fi t corporate performance.Speci fi cally,learning behavior can increase corporate performance and fi rm value.The results reveal the importance of the learning e ff ect under an uncertain environment.

9.Conclusion

It is common for corporations to interact with peer f i rms in decision-making,through actions such as signing strategic cooperating agreements and developing marketing strategies.Recent studies examine whether the characteristics or behavior of peer f i rms af f ects corporate capital structure(Leary and Roberts,2014),mergers and acquisitions(Bizjak et al.,2009)and tax avoidance(Li et al.,2014).Investment decisions are important and determine corporate development.Most studies examining the peer ef f ect in corporate investment hold that managers can gain useful information from the stock price of peer f i rms.Edmans et al.(2012a,2012b) and Bond et al.(2012)point out that stock prices contain useful information that is helpful in guiding a f i rm’s investment policy,such as industry growth opportunities,external environment,strategy of competitors and consumer demands.Valuing the stock price of peer f i rms can capture useful information,which can reduce investment uncertainty.However,few studies examine the direct ef f ect of peer f i rms’investment behavior on the fi rm’s investment policy.The aim of this study was therefore to identify whether,how,and why peer fi rm behavior matters for corporate investment policies.

Using a sample of China’s listed fi rms from 1999 to 2012 and following Albuquerque(2009)to de fi ne peer fi rms,we indicate that a one standard deviation increase in peer fi rms’investment is associated with a 4%increase in fi rm i’s investment.Classifying investment into tangible asset investment and intangible asset investment,we then examine the peer e ff ect in these di ff erent types.We fi nd that both are signi fi cantly in fl uenced by the investment behavior of peer fi rms,while the peer e ff ect is more pronounced in tangible asset investment.To establish the causal relationship between a fi rm’s investment and peer fi rms’investment policy,we address the re fl ection problem and endogeneity bias as much as possible.We use the following tests to address these concerns.First,specifying fi rms that are in the same industry but are not in the upper and lower size quartiles as the fi rm as a non-peer group,we examine the e ff ect of the behavior of non-peer fi rms have on the fi rm’s investment policy.Second,we use the instrumental variable method to address the possible endogeneity bias,and predict that the learning e ff ect is still signi fi cant by using two stage least squared regression.Third,we incorporate the year fi xed e ff ect and fi rm fi xed e ff ect into the model,and reexamine the peer e ff ect on investment.The results change little and are consistent with the main fi ndings of the study.

Next,we identify the possible channels through which peer fi rms in fl uence corporate investment policy.We fi nd that peer e ff ects are more pronounced when fi rms have information advantages and when the information disclosure quality of peer fi rms is higher or if they face more fi erce competition.To reveal the potential mechanisms behind peer ef f ects in investment policy,we further explore heterogeneity in the peer ef f ect.When f i rms are industry followers,are young or have f i nancial constraints,they are highly sensitive to their peers f i rms. We also quantify the economic consequences generated by peer ef f ects,which can increase f i rm performance in future periods.

Acknowledgments

This study is the result of research supported by the National Natural Science Foundation of China (71263034,71572087).We acknowledge the executive editor and the anonymous reviewer for their useful comments and suggestions.

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19 September 2014

☆We acknowledge funding for project 71263034 and 71572087 from the National Natural Science Foundation of China.

*Corresponding author.

E-mail addresses:chenshenglan@imu.edu.cn(S.Chen),mahuiacc@126.com(H.Ma).

http://dx.doi.org/10.1016/j.cjar.2016.11.002

1755-3091/?2016 Sun Yat-sen University.Production and hosting by Elsevier B.V.

This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Accepted 25 November 2016

Available online 16 January 2017

Peer e ff ects

Corporate investment

Managerial learning