The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt

Abdel-Khalik, Shimaa Abdel-Moniem; Abulezz, Mohamed E.; Samaan, Ahmed M. Shaker Article The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Abdel-Khalik, Shimaa Abdel-Moniem; Abulezz, Mohamed E.; Samaan, Ahmed M. Shaker (2024) : The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-13, https://doi.org/10.1080/23311975.2024.2371550 This Version is available at: https://hdl.handle.net/10419/326386 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Business & Management ISSN: 2331-1975 (Online) Journal homepage: www.tandfonline.com/journals/oabm20 The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt Shimaa Abdel-Moniem Abdel-Khalik, Mohamed E. Abulezz & Ahmed M. Shaker Samaan To cite this article: Shimaa Abdel-Moniem Abdel-Khalik, Mohamed E. Abulezz & Ahmed M. Shaker Samaan (2024) The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt, Cogent Business & Management, 11:1, 2371550, DOI: 10.1080/23311975.2024.2371550 To link to this article: https://doi.org/10.1080/23311975.2024.2371550 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 27 Jun 2024. Submit your article to this journal Article views: 645 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 Accounting, corporAte governAnce & Business ethics | reseArch Article Cogent Business & ManageMent 2024, VoL. 11, no. 1, 2371550 https://doi.org/10.1080/23311975.2024.2371550 The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia: evidence from Egypt shimaa Abdel-Moniem Abdel-Khalik, Mohamed e. Abulezz and Ahmed M. shaker samaan accounting Department, Faculty of Commerce, Zagazig university, Zagazig, egypt ABSTRACT the purpose of this study is to investigate whether analyst coverage is associated with managerial myopia. Moreover, the effect of the interaction between analyst coverage and investment opportunities on managerial myopia is also investigated. We used data of 100 companies listed on the egyptian stock exchange for the period 2014–2019. the results indicate that analyst coverage exacerbates managerial myopia. this result is consistent with the financial analysts’ pressure role, which indicates that analyst coverage imposes excessive pressure on managers to achieve short-term goals and thereby exacerbates managerial myopia. Furthermore, this study finds that the interaction between analyst coverage and investment opportunities alleviates managerial myopia. this result is consistent with the financial analysts’ monitoring role, which suggests that financial analysts, by acting as effective monitors, mitigate managerial myopia. 1. Introduction the purpose of this study is to investigate whether analyst coverage is associated with managerial myopia. Managerial myopia is the tendency of managers to attempt to induce increases of stock price by boosting current earnings at the expense of long-term objectives (stein, 1988). this implies underinvestment in viable long-term projects, reduction of discretionary expenses (e.g. r&D), or taking exaggerated risks with the objective of achieving short-term goals (Dallas, 2012). As such, managerial myopia may decrease firm value and thereby shareholders’ wealth. extant literature suggests that this relation is rather complex: for it may depend on the particular role financial analysts’ coverage plays. three distinct roles of financial analysts’ coverage are generally identified: monitoring, informational, and pressure roles. First, financial analysts have experience with the businesses they cover in addition to accounting and finance training. Also, they follow firms on a regular basis, which enables them to inspect management behaviors and decisions on a continuous basis. hence, analysts monitor firms’ managers and effectively influence their decision-making (chen et al., 2015; Degeorge et al., 2013; Doukas et al., 2008; irani & oesch, 2013; sun, 2009; Yu, 2008). this is referred to as the financial analysts’ monitoring role. second, financial analysts have the ability to gather, evaluate, and deliver corporates’ information to investors and other stakeholders. hence, they dilute information asymmetry between managers and investors and thereby add value to the financial market and enhance market efficiency (Derrien & Kecskés, 2013; © 2024 the author(s). Published by informa uK Limited, trading as taylor & Francis group CONTACT shimaa abdel-Moniem abdel-Khalik [email protected]om accounting Department, Faculty of Commerce, Zagazig university, Zagazig, egypt. this is an open access article distributed under the terms of the Creative Commons attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the accepted Manuscript in a repository by the author(s) or with their consent. ARTICLE HISTORY received 30 november 2023 revised 26 January 2024 Accepted 17 June 2024 KEYWORDS Managerial myopia; analyst coverage; investment opportunities; the monitoring role; the informational role; the pressure role REVIEWING EDITOR nor shaipah Abdul Wahab, taylor’s university – lakeside campus, Malaysia SUBJECTS Accounting; corporate governance; Finance 2 s. A.-M. ABDel-KhAliK etAl. healy & palepu, 2001). this is referred to as the informational role of financial analysts. consequently, financial analysts’ informational and monitoring roles can encourage long-term investments and thereby mitigate managerial myopia. these two roles can be regarded as the beneficial influence of financial analysts on managerial behavior. Finally, financial analysts create extreme pressure on management to achieve short-term earnings targets and attain analysts’ earnings forecasts, since missing analysts’ earnings forecasts leads to a significant decline in stock prices, a drop in management compensation, and a higher probability of management turnover (graham etal., 2005). hence, management is incentivized to forgo viable long-term investments in order to accomplish short-term goals (clarke et al., 2015; he & tian, 2013; Michenaud, 2008). this is known as the pressure role of financial analysts’ coverage. this role can be viewed as financial analysts’ detrimental influence on managerial behavior. evidence from previous studies on the relation between analyst coverage and managerial myopia is mixed. thus, this relation is not yet fully understood and its nature is still an empirical issue. in the way of understanding this relation, we argue that managerial myopia may be moderated by the availability of investment opportunities. We hypothesize that the availability of good investment opportunities is expected to mitigate managerial myopia. on the other hand, if good investment opportunities are in short supply, the manager will be tempted to invest in short-term propjets. this possibility is not evaluated in prior research and thus the current study could contribute to extant literature, especially as evidence originates in an emerging economy such as egypt. Most prior studies investigate whether analyst coverage is related to firms’ investment in developed countries. given that a country’s institutional factors, such as legal and information infrastructure, could influence the effect of financial analysts on management behavior (chang et al., 2000; Degeorge et al., 2013; elbannan, 2013), the current study examines the relation between analyst coverage and managerial myopia and the moderating effect of investment opportunities on this relation in an emerging economy, namely egypt. Additionally, this study addresses one implication of agency theory by indicating how the interaction between analyst coverage and investment opportunities can improve the information environment through reducing information asymmetry and provide effective monitoring activities. hence, the detrimental impact of moral hazard and adverse selection problems on investment decisions is decreased. our findings indicate that there is a positive effect of analyst coverage on managerial myopia, which supports the pressure role of financial analysts. Moreover, the findings suggest that analyst coverage affects managerial myopia only when the firm has good investment opportunities, which is consistent with financial analysts’ monitoring role. the remainder of this paper is organized as follows: section 2 presents theoretical background. section 3 presents empirical literature review and hypotheses development. section 4 describes the research design, variables measurement, and sample selection. in section 5, empirical results, discussion, and additional analyses are presented. section 6 presents summary and conclusion. limitations and future research ideas are laid down in the final section. 2.Theoretical background in an ideal environment that is free from friction, managers will engage in projects with positive net present values (Modigliani & Miller, 1958). however, in the real world, literature indicates that firms make suboptimal investment decisions. the conflict of interests between managers and shareholders and managers tendency to act in their own interests at the expense of stakeholders’ interests (i.e. agency problem), explain the existence of suboptimal investment decisions (chen et al., 2017; Jensen & Meckling, 1976; stein, 2003). the improvement of firms’ information environment and the effective monitoring exercised by institutional investors, financial analysts, and other stakeholders can lessen both moral hazard and adverse selection problems induced by the separation of ownership and control (chen et al., 2017; Jensen & Meckling, 1976). stein (1989) suggests that managers can behave myopically even in a perfectly efficient market for two reasons: managers primary concern with stock prices and the unobservability of managerial actions and managers’ private information advantage over shareholders. According to stein (1989) model, cogent Business & MAnAgeMent 3 shareholders make predictions of future earnings based on their current earnings. hence, managers are incentivized to manipulate signals to shareholders by exaggerating current earnings to increase anticipated future earnings. the stock market, on the other hand, makes its projections based on anticipating a specific level of earnings growth. Further, Bebchuk and stole (1993) argue that short-term objectives, along with imperfect information, may cause underinvestment or overinvestment in long-term projects based on the observability of the level of investment and its productivity. they provide evidence that underinvestment can occur when investors are not able to observe the level of investment undertaken, whereas overinvestment can occur when investors are able to perceive the level of investment but not its productivity. on the one hand, financial analysts act as effective monitors of managers’ behavior because they have distinctive characteristics (Jensen & Meckling, 1976). hence, analysts can mitigate the moral hazard problem and encourage long-term investment that maximizes shareholders’ wealth and firm value. on the other hand, the capital market punishes companies that do not meet or beat analysts’ forecasts (Mizik, 2010). therefore, managers have incentives to behave myopically and forgo good investment opportunities. 3. Literature review and hypotheses development 3.1. Analyst coverage and managerial myopia the influence of analyst coverage on corporate investment and financing decisions has been investigated in prior studies. Doukas et al. (2008) find that firms increase their investment as a result of increased analyst coverage. Derrien and Kecskés (2013) indicate that a decline in analyst coverage decreases firm investment and financing activities. Furthermore, this result is more significant for smaller firms and those with higher financial constraints. these findings are consistent with the idea that a rise in information asymmetry resulting from a reduction in analyst coverage can increase the cost of capital, which in turn causes a reduction in long-term investment. in other words, management of firms with less analyst coverage tends to become myopic. this stream of literature documents how institutional characteristics of a country affect the role of analyst coverage as external monitors. sun (2009) finds that firms tend to manage earnings less due to increasing analyst coverage. in addition, this relation is more significant for countries with weak investor protection. Degeorge etal. (2013) find that the financial development of a country affects financial analysts’ monitoring role using data from 21 countries. regarding financial analysts’ pressure role, a number of studies indicate that financial analysts, by determining short-term earnings targets to accomplish, impose undue pressure on firms’ managers. Michenaud (2008) finds that firms decrease long-term investment when analysts pressure to increase earnings per share is high. Also, the decline in firms’ investment increases managers’ ability to achieve analysts’ earnings targets. he and tian (2013) show that managers are more likely to decrease firm innovation because of increasing analyst coverage. clarke et al. (2015), on the other hand, find that analyst coverage hinders innovation and thereby exacerbates managerial myopia in firms that are low-quality innovators, whereas analysts encourage innovation in firms that are efficient innovators, implying that analysts have a beneficial role in allocating capital funds to profitable long-term investments by impairing wasteful innovation. guo et al. (2019) indicate that firms decrease r&D expenditures as a result of increasing analyst coverage. in the meantime, analyst coverage may enhance firms’ investment in acquisitions and corporate venture capital, which suggests that the financial analysts’ information and pressure roles differ throughout the numerous policies that a firm invests in. in sum, financial analysts communicate information about firms’ long-term investments to other stakeholders and enable them to realize the real value of such investments by decreasing the information asymmetry between managers and investors. Also, financial analysts, by acting as external monitors for firms’ managers, assist managers in allocating capital funds to the proper long-term investment. consequently, analyst coverage induces managers to engage in long-term investments and thereby decreases the possibility of managerial myopia. 4 s. A.-M. ABDel-KhAliK etAl. An alternative view suggests that financial analysts exercise undue pressure on managers to attain short-term goals. thus, managers are willing to decrease long-term investment and as such exacerbate managerial myopia. According to the prior studies reviewed above, two competing hypotheses are formulated. H1-a: the information and monitoring role: Analysts’ coverage mitigates managerial myopia. H1-b: the pressure role: Analysts’ coverage enhances managerial myopia. 3.2. The moderating effect of investment opportunities on the relation between analyst coverage and managerial myopia the proposed moderating effect of investment opportunities on managerial myopia is a novel addition to the extant literature. the rationale of this proposed moderating effect is that in an environment, with rich investment opportunities coupled with adequate analyst coverage, forgoing profitable investment opportunities grows exceedingly difficult for the manager. As such in this environment, myopia is difficult to expect. in other words, financial analysts, by serving as effective monitors and reducing information asymmetry, encourage managers to increase investments that maximize firms’ value and thereby maximize shareholders’ wealth, given profitable investment opportunities. consequently, the beneficial effect of analyst coverage on managerial myopia will be observed given the existence of investment opportunities. consequently, the next hypothesis is formulated: H2: Investment opportunities moderate the relation between analyst coverage and managerial myopia. 4. Research design 4.1. Model specification the following logistics regression model is estimated in order to examine the effect of analyst coverage and the moderating effect of investment opportunities on managerial myopia: MM COV INVOPP COV INVOPP SIZE ROA it it it it it it =++ + + + ββ β β β β 01 2 3 4 5 * iit it it it it it LEV INST FCF INV Year ind + + + + +∑ +∑ − β β ββ β β 6 7 8 9 1 10 11 ∆uu s r t y it it + ε where MM is managerial myopia; cov is analyst coverage; invopp is investment opportunities; siZe is firm size; roA is return on assets; lev is leverage; inst is institutional ownership; FcF is free cash flow; Δinv is prior year’s change in the firm’s investment. Ɛit is error term. industry and year dummies are included to capture the potential effects related to the industry and the year. 4.1.1. Measurement of dependent variable Firms’ investment in fixed assets is used to capture managerial myopia. investment in fixed assets reduces earnings through increasing depreciation. it is also financed by decreasing cash or increasing debt. hence, the reduction in investment in fixed assets leads to meeting short-term goals (edmans et al., 2017; graham et al., 2005; Kraft et al., 2018). Furthermore, several studies suggest that underinvestment in fixed assets is used as a proxy for managerial myopia. For instance, graham et al. (2005) indicate that managers postpone initiating new investments and delay the maintenance of equipment to fulfill cogent Business & MAnAgeMent 5 short-term objectives. Kraft etal. (2018) examine the managerial myopia hypothesis by investigating how reporting frequency influences capital investment levels. Managerial myopia (MM) is measured as a dichotomous variable that equals one if the change in net fixed assets scaled by total assets at the start of the year is less than or equal to zero, and 0 otherwise. 4.1.2. Measurement of independent variable Following (clarke et al., 2015), analyst coverage (cov) is measured as the natural logarithm of one plus the number of analysts covering the firm. 4.1.3. Measurement of moderator variable investment opportunities (invopp) are measured using tobin’s Q, which equals the market value of equity plus total debt at end of year over the book value of assets at the beginning of the year. 4.1.4. Measurement of control variables First, regarding firm size, larger firms have a better information environment than smaller firms. smaller firms, on the other hand, may suffer cash flow constraints that limit their ability to invest (Bushee, 1998). therefore, managerial myopia is likely to be induced for smaller firms. Firm size (siZe) is measured by natural logarithm of total assets. second, more profitable firms are more likely to encourage long-term investment and thereby mitigate managerial myopia (guo etal., 2019). profitability (roA) is measured by the return on assets. third, Jensen (1986) argues that debt payments force managers to payout cash, and thereby firms may have cash flow shortages that lessen the likelihood of increasing investments. Firms with higher leverage are reported to engage in myopic behavior (cheng et al., 2013; Kraft et al., 2018). We control for leverage (lev), which is measured as the ratio of total debt scaled by total assets. Fourth, institutional investors have an impact on firms’ investment behavior in two different ways. on the one hand, institutional investors who have a high portfolio turnover and engage in momentum trading strategies can induce managers to behave myopically. on the other hand, institutional investors may mitigate managerial myopia by providing a higher degree of monitoring of managerial behavior (Bushee, 1998; Wahal & Mcconnell, 2000). hence, we control for institutional investors (inst), which is measured as the ratio of a firm’s shares held by institutional investors. Fifth, firms with high free cash flow are more likely to increase firms’ investment (Jensen, 1986). Additionally, firms with substantially negative free cash flow have a greater need to raise capital and thus have incentives to behave myopically to increase earnings and achieve short-term goals (Bushee, 1998). We control for free cash flow (FcF), which is measured as cash flow from operations less capital expenditures scaled by total assets. sixth, we control for the prior year’s change in firm’s investment (Δinv), which is measured as firm’s investment in year t-1 minus in year t-2 scaled by total assets. According to Bushee (1998), a reduction in firm’s investment last year increases the probability of reducing investment in the current year. conversely, if the firm cut investment in a preceding year, it becomes costlier to reduce investment in the current year. 4.2. Sample selection and data sources the study’s population comprises all egyptian companies listed on the egyptian stock exchange. Banks and financial services firms are excluded due to their unique financial reporting practices. A sample of 100 nonfinancial, listed egyptian firms with 600 firm-year observations from the period 2014–2019 is selected to examine how analyst coverage influences managerial myopia as well as investigate whether this effect depends on the extent to which investment opportunities exist. this period is selected to avoid time periods witnessing unusual events, including political uprising in egypt preceding the year 2014 that has had an unknown effect on economic stability in addition to the period following 2019 which experienced the coviD-19 epidemic, which has had far reaching impact on the economy. the data are collected from the egyptian stock exchange official website, companies’ websites, and the Mubasher 6 s. A.-M. ABDel-KhAliK etAl. website that are publicly available online. the data are also obtained from egypt for information Dissemination (egiD) in exchange for a charge. 5. Empirical results 5.1. Descriptive statistics and correlation table 1 presents descriptive statistics of the independent, moderator, and control variables that are used in the study. in order to eliminate the outliers effect, all continuous variables included in the study are winsorized at the top 5% and the bottom 95% percentiles of their distribution. the mean of analyst coverage (cov), as measured by the natural logarithm of one plus the number of analysts providing coverage, equals 0.367, which implies that about one analyst is covering the firm on average. the investment opportunities (invopp) range from 0.538 to 3.005, and the mean equals 1.229. the mean of firm size (siZe), as measured by the natural logarithm of total assets, is 20.596, which approximately matches a total assets size of egp 880 million, indicating that the study sample is primarily composed of medium-to large-sized firms. the leverage ratio (lev) ranges from 8% to 82%, and the mean is 43%, which indicates that approximately 43% of the total assets of sample firms are financed by debt, suggesting that sample firms are moderately leveraged. the institutional ownership (inst) varies from 0% to 94%, and the mean is 58.1%. the mean of profitability (roA) is equal to 6%. the free cash flow (FcF), scaled by total assets at the beginning of year, varies from –0.161 to 0.239, with a mean of 0.024. the mean of the prior year’s change in the firm’s investment (Δinv) equals 0.003. the pearson correlation coefficients for all variables in the study are shown in table 2. Analyst coverage, investment opportunities, firm size, return on assets, prior’ year investment, and the interaction variable are negatively correlated with managerial myopia, which tentatively imply that firms with higher analyst coverage, better investment opportunities, higher profitability, a larger previous investment in net fixed assets, and a larger size exhibit less managerial myopia in terms of cutting investment. With the exception of the correlation between the coverage (cov) and the interaction term (cov*invopp), all other correlations between predictor variables range from moderate to low. hence, multicollinearity is not a concern. Table 1. Descriptive statistics. Variables n Mean sD Minimum Maximum COV 600 0.367 0.639 0 2.013 INVOPP 600 1.229 0.612 0.538 3.005 COV*INVOPP 600 0.515 0.989 0 3.466 SIZE 600 20.596 1.347 18.199 23.15 ROA 600 0.060 0.076 −0.068 0.228 LEV 600 0.439 0.219 0.084 0.818 INST 600 0.581 0.286 0.000 0.939 FCF 600 0.024 0.099 −0.161 0.239 ΔINV 600 0.003 0.027 −0.038 0.080 Notes: this table shows the sample’s descriptive statistics. the study sample consists of 600 firm-year observations and spans the years 2014 to 2019. Table 2. Pearson correlation matrix. Variable MM CoV inVoPP CoV*inVoPP siZe Roa LeV inst FCF ΔinV MM 1 CoV −0.166*** 1 inVoPP −0.081** 0.235*** 1 CoV*inVoPP −0.202*** 0.910*** 0.457*** 1 siZe −0.107*** 0.565*** 0.172*** 0.520*** 1 Roa −0.156*** 0.205*** 0.507*** 0.333*** 0.115*** 1 LeV 0.020 0.015 0.051 0.009 0.227*** −0.204*** 1 inst 0.025 0.060 0.204*** 0.077* 0.309*** 0.100** 0.251*** 1 FCF 0.021 0.090** 0.278*** 0.169*** 0.089** 0.545*** −0.171*** 0.081** 1 ΔinV −0.161*** 0.105** −0.026 0.102** 0.017 0.114*** 0.003 0.017 −0.009 1 Notes: this table shows Pearson correlation coefficients of analyst coverage, managerial myopia, investment opportunities, and other control variables. *, **, *** significant relationship at the 10%, 5%, and 1% thresholds. cogent Business & MAnAgeMent 7 5.2. Regression results the maximum likelihood (Ml) estimation method is used to estimate the logistics regression model. gujarati (2003) indicates that having a dummy variable for each category or group leads to perfect collinearity. hence, when the logistics regression model is run, the stAtA omits one industry sector and one year because of collinearity. Also, the stAtA excludes 18 observations, and as a result, the number of observations reduces to 582. to overcome the potential heteroscedasticity and autocorrelation problems, robust standard errors are applied (greene, 2003). Also, the variance inflation factor (viF) is calculated to ensure the absence of multicollinearity. As shown in table 3, the viF for all explanatory variables in the study model is less than 10. hence, there is no significant multicollinearity problem. table 3 also shows the logistics regression results regarding the effect of analyst coverage on managerial myopia as well as the effect of investment opportunities as a moderator variable. it is important to assess the robustness of the study model before interpreting the coefficients of the study variables. the probability of chi2 = 0.0000 is less than the level of significance of 5%. hence, the regression model is statistically significant. the receiver operating characteristic (roc) curve for the study model is shown in Figure 1. hosmer et al. (2013) indicate that a larger area under the roc curve improves the model’s classification Table 3. the effect of analyst coverage and the moderating effect of investment opportunities on managerial myopia. Dependent variable: MM Variables Coefficient z-statistic ViF COV 0.8273* 1.94 8.95 INVOPP 0.3221 1.58 2.17 COV*INVOPP −0.8539*** −3.04 9.87 SIZE −0.1576 −1.55 2.25 ROA −3.8868** −2.15 2.13 LEV 0.0114 0.02 1.55 INST 0.7246** 2.04 1.38 FCF 2.5722** 2.18 1.50 ΔINV −7.4624** −2.19 1.07 Constant 3.4743 1.50 Industry dummy included Year dummy included Observations 582 Wald chi2 (25) 65.53 Prob > chi20.0000 Pseudo R20.0953 Classification 68.38% Area under Roc curve 0.6967 Notes: this table presents logistics regression results of the effect of analyst coverage, the interaction of investment opportunities with analyst coverage, and the control variables on managerial myopia as a dummy variable that equals one if the changes in net fixed assets scaled by total assets at the start of the year are less than or equals zero, and 0 otherwise. *, **, *** represent significance level at 10, 5, 1 % level respectively. Figure 1. the RoC curve.