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Is director industry experience valuable?

We investigate whether investor reactions to the announcement of a new outside director appointment significantly depend upon the director's experience in the appointing firm's industry. Our sample includes 688 outside director appointments to boards of S&P 500 companies from 2005 to 2010. We find significantly higher announcement returns upon appointments of experienced versus inexperienced directors. To alleviate endogeneity concerns, we use the deaths of200 directors holding 280 outside directorships as an identification strategy and find significantly more negative announcement returns associated with the deaths of experienced versus inexperienced directors. However, while our results are robust to accountingfor time-fixed unobservable director and firm characteristics, we still cannot completely rule out endogenous firm-director matching driving our results.

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We investigate whether the industry experience of outside directors on corporate boards affects firm value. Investor interest in industry experience at the board level seems to have increased substantially in the last few years. In particular, in the aftermath of the financial crisis of 2007-2008, the press, shareholder activists, and corporate governance experts at large have expressed increasing concern regarding the lack of sufficient industry experience on corporate boards. (1) In a recent survey of board practices (Deloitte LLP and Society of Corporate Secretaries & Governance Professionals, 2012), 47% of directors indicate that industry experience is the skill most likely to contribute to the success of the board. Widespread belief that director qualifications and experience matter is also reflected in the new amendments to the Securities and Exchange Commission's disclosure rules introduced in December 2009. (2)

Industry expert directors are expected to possess superior knowledge of products, markets, competitors, industry-specific regulations, and standards. Thus, industry experience is expected to affect a director's monitoring capability, as well as the quality of advice provided to senior management (Custodio and Metzger, 2013). In this advisory function, boards set the strategic and operational direction of the company (Armstrong, Guay, and Weber, 2010; Brickley and Zimmermann, 2010). In fact, surveys conducted among directors suggest that directors consider the advisory role and their legal duty to review the corporation's major plans and actions to be of greater importance than the monitoring role (Demb and Neubauer, 1992; Corporate Board Member and PricewaterhouseCoopers LLP, 2008). (3)

Despite the attention director industry experience has received recently, the academic research regarding the value of director industry experience is still scarce. We add to the literature by determining whether board industry experience is perceived as value-relevant by stock market participants. To this end, we investigate whether stockholder reactions to the announcement of a new director appointment significantly depend on the director's experience in the appointing firm's industry. Using a sample of 688 outside directors appointed to the boards of S&P 500 companies from 2005 to 2010, we find that companies that announce the appointment of an industry expert director earn significantly higher announcement returns than companies that announce the appointment of a new director without industry experience (on average about 0.4% to 0.7% larger).4 This finding is not only statistically, but also economically significant relative to the whole sample of 688 new outside director appointments (where the overall average two-day announcement return is approximately 0.08%).

To mitigate concerns that our results are driven by other director or firm-specific variables and in line with previous research, we control for various other director characteristics including gender, age, independence (versus gray outside directors), and whether the director is the chief executive officer (CEO) of another company. We also control for various firm-level variables including size, profitability, growth potential, and the firms' corporate governance structure as measured by board size, board independence, anti-takeover protection, ownership structure, whether the CEO is also Chairman of the board, and whether the CEO sits on the nominating committee, among others.

Our results stay robust to a number of additional tests, for example when applying alternative industry definitions, when measuring industry experience at the segment level, when controlling for generalist skills proxied by education and Ivy League university attendance, when omitting appointments to the boards of financial firms, or when accounting for omitted, but time-fixed variations at the firm level using firm fixed-effects.

A potential concern with our sample is related to US Federal Law (the Clayton Antitrust Act of 1914), which has forbidden individuals from serving as directors of competing companies. Even though the intent of the law was to prevent cartels from developing, rather than preventing conflicts of interest, it has a potential effect on the hiring of outside directors with industry experience. In addition, executives are often asked to sign non-compete contracts when leaving their firms precluding them from subsequent board service for a competitor. (5) There are also common law doctrines against the sharing of proprietary information across companies. All of these will restrict the ability of insiders (directors with industry experience as an inside director) to serve on boards of other companies in the same industry. As a consequence, there may be an indirect screening effect in that our sample of directors with industry experience includes many executives of relatively lower quality (those who never sign non-compete agreements or rise to positions of significant responsibility). (6) However, even if such an effect is at play in our sample and experienced directors are of systematically lower quality than non-experienced directors, this would bias against finding higher announcement returns for experienced directors and is unlikely to be an alternative explanation of our findings.

Director appointments depend on the characteristics and needs of the appointing firms (e.g., the economic situation and governance structure) and the availability, career concerns, and preferences of the newly appointed directors. To alleviate such endogeneity concerns associated with director appointments, we compile a sample of 200 directors who die (unexpectedly) in office while holding a total of 280 outside board seats in listed US companies at the time of their death. These death events of directors still serving on a company's board are plausibly exogenous shocks and free of any selection bias either at the company or director level. Consistent with our findings on director appointments, the announcement returns associated with the deaths of experienced directors are significantly more negative than those of non-experienced directors, and the economic magnitude of the difference is even larger than in the case of director appointments.

However, we caution that using an exogenous shock to board structure resulting from (unexpected) director deaths still does not completely rule out endogeneity concerns as the potential endogeneity of the choice to appoint a particular director may still affect the announcement effects upon an unexpected death event. We attempt to address this concern by using director fixed-effects to account for time-fixed unobservable director characteristics and by splitting the sample by director tenure as the endogenous match between firms and directors is likely to change over time. However, we cannot completely rule out that endogenous firm-director matching drives our results. Therefore, we urge caution when interpreting our results, which establish an association, but not necessarily a causal relation, between director industry experience and firm value.

By systematically investigating the valuation effect of director industry experience, we contribute to different strands of research. Most importantly, our paper adds to the literature relating director characteristics to the announcement returns upon the directors' appointment to the board with the goal to identify the valuation effects of certain director characteristics (Rosenstein and Wyatt, 1990; Fich, 2005; Fahlenbrach, Low, and Stulz, 2010; Adams, Gray, and Nowland, 2012). Our study also contributes to the literature examining the financial expertise of board members in non-financial firms and its effect on various corporate variables (Giiner, Malmendier, and Tate, 2008; Dittmann, Maug, and Schneider, 2010) as well as the literature on the value of financial expertise on banks' boards (Aebi, Sabato, and Schmid, 2012; Minton, Taillard, and Williamson, 2014). We contribute to this literature by not only focusing on financial expertise, but on relevant industry expertise more generally.

Our paper is also related to a recent study investigating the relation between industry experience and acquisition outcomes. Custodio and Metzger (2013) find that acquirer announcement returns in diversifying acquisitions are between two and three times higher when the CEO has experience in the target firm's industry when compared to CEOs with no such experience. We extend the analysis of Custodio and Metzger (2013) by shifting the focus from CEOs to the board of directors, where industry experience is likely to play a crucial role for the effective execution of a board's monitoring and advisory roles.

There are two contemporaneous papers investigating the valuation effect of director industry experience. (7) Masulis, Ruzzier, Xiao, and Zhao (2012) confirm a positive relation between director industry experience and firm value in a standard ordinary least square (OLS) panel analysis. In addition, they investigate the channels through which director industry experience may generate firm value. Their results suggest that industry expertise is associated with fewer earnings restatements, greater cash holdings, higher CEO pay performance sensitivity, higher CEO turnover performance sensitivity, and more patents with more citations. Faleye, Hoitash, and Hoitash (2014) also find a positive relation between director industry experience and firm value. They find board industry expertise to have a positive effect on innovation, but not on acquisition performance. Industry expertise is also significantly related to CEO termination and compensation incentives that encourage innovation investment. Our study differs from these two studies by using an event study framework to evaluate the valuation effect of director industry experience. Our event study setting allows us to introduce an exogenous shock to the firms' board structure through the deaths of corporate directors thereby mitigating endogeneity concerns.

The remainder of the paper is organized as follows. Section I describes the data and variables. Section II presents the empirical main results. Section III reports the results from various robustness tests. Section IV presents the results from an analysis using director deaths as an identification strategy, while Section V provides our conclusions.

I. Data and Variables

A. Sample Selection

We begin our sample collection by reviewing all proxies filed by S&P 500 companies from 2004 to 2011 to gather all new outside director appointments in the calendar years 2005 to 2010. Since utilities companies operate in a regulated industry, we do not consider companies with standard industrial classification (SIC) codes between 4900 and 4942 in our data gathering process. We then identify the precise announcement date for every new director using the Factiva newspaper database. This search results in 1,517 directors who joined the board of directors of a non-utilities S&P 500 company in the calendar years 2005 to 2010.

We apply four filters to these 1,517 outside director appointments to obtain our final sample. First, we exclude 316 appointments that were announced on days with multiple director appointment announcements as these events do not allow an investigation of the announcement effect for each director separately. Additionally, the appointment of several new outside directors may represent a significant strategic realignment of the company (Rosenstein and Wyatt, 1990). We also exclude 495 director appointments that are announced simultaneously with other material company events as these events confound the stock market's reaction to the director appointment announcement. Examples of these confounding events include the announcement of quarterly financial statements or dividends, annual general meetings, or the announcement of a material change to the legal structure of the company (i.e., through a merger, spin-off, or major stake transfer). Moreover, we exclude 14 director re-elections (i.e., elections of directors who, at any time in the past, had already served as directors of the respective company). We also exclude four events without sufficient stock market data to be included in the event study analysis. Applying these four filters reduces our sample to 688 first-time outside director announcements.

B. Measures of Industry Experience

For each of the 688 outside director announcements in our sample, we collect data with a goal of constructing an employment history for each director. We start by collecting biographical information disclosed in the proxy statements where the directors were first introduced and then complement this information by using data from BoardEx, Factiva, LexisNexis, and internet searches. We then use this information to construct an employment history for each director, consisting of the position/job descriptions and the companies they have worked for, as well as the start and end dates of each position. To determine the newly appointed outside directors' industry experience, we assign a four-digit SIC code to each company a director in our sample has worked for throughout his employment history. Overall, the 688 newly appointed directors in our sample have worked for 3,634 different companies. For the industry classification of the 1,377 listed US companies, we use the four-digit SIC code from the Center for Research in Security Prices (CRSP) and Compustat databases. Of the 2,257 companies listed outside the United States and private companies, we retrieve 162 four-digit SIC codes using Amadeus, Compustat Global, and Datastream. We find 1,456 in Factiva's company database, while 639 of the firms are not covered in Factiva or have no SIC code assigned by Factiva. We conduct a second search for the four-digit SIC code of these firms in the LexisNexis database and are able to retrieve the SIC codes for another 250 firms. For 389 firms, we are unable to obtain any industry classification. These firms are omitted in the construction of the employment history of the 655 directors appointed in our 688 sample events. Based on the four-digit SIC codes, we assign every company to the respective Fama-French 12-Industries (FF12) classification industry. We also translate the four-digit SIC codes of our 360 sample firms appointing a new outside director into the FF12 industries. This allows us to compare the industry classification of the appointing firms to those firms in which the newly appointed directors were previously affiliated.

We use this information to construct different measures of industry experience. First, we construct a dummy variable that is equal to one if the newly appointed director has any type of work experience in the FF12 industry of the appointing company [Industry exp. (dummy)]. Next, we construct a variable to measure industry experience in the FF12 industry of the appointing company in days [Industry exp. (days)]. (8) To account for the skewed distribution of this variable, we 8 use the natural logarithm of one plus the number of days of experience. To determine whether the value of industry experience depends upon how close the industry or industries in a director's work history are to the industry of the appointing firm, we also construct a weighted measure of industry experience defined as follows. The variable takes a value of one if the newly appointed director has any type of work experience in the FF12 industry of the appointing company, takes a value of two if the newly appointed director has any type of work experience in the FF48 industry of the appointing company, and is equal to zero otherwise [Industry exp. (FF12/FF48)]. Additionally, we classify experience into different types of industry experience and construct the following three variables: 1) a dummy variable to determine whether the newly appointed director has work experience as an employee/executive without board membership in the same FF12 industry [Exp. employee (dummy)], 2) a dummy variable to determine whether the newly appointed director has work experience as an employee/executive with additional board membership in the same FF12 industry [Exp. inside director (dummy)], and 3) a dummy variable to determine whether the newly appointed director has work experience as an outside board member in the same FF12 industry [Exp. outs, director (dummy)].

We also construct a variable measuring the percentage of directors with industry experience on the board of the appointing firms at the time of the appointment to control for the existing experience on the appointing firms' board. We follow a similar procedure as outlined above to assess the newly appointed directors' industry experience. We first obtain from RiskMetrics the full list of 3,186 different outside directors on the board in all 607 firm-years (of the 360 different companies) in which a new outside director is appointed to the board. We collect biographical information from the proxy statements, BoardEx, Factiva, LexisNexis, and internet searches and use this information to construct an employment history for each director. The 2,201 outside directors have worked for 9,724 companies as of the appointment of the new outside director. We again use CRSP, Compustat, Amadeus, Compustat Global, Datastream, Factiva, and LexisNexis to assign a four-digit SIC code to each company a director in our sample has worked for throughout his employment history. We translate these four-digit SIC codes into FF12 industry codes and compare them to FF12 industry of the appointing firms to determine whether an outside director on the board has work experience in the same industry. We then calculate the percentage of outside directors on the board with any industry experience.

C. Additional Director Characteristics

In addition to the variables related to directors' industry experience, we collect other director-level information for each director appointment from the RiskMetrics Director database. These variables include a director's age, the number of additional directorships a director holds, a dummy to determine whether the director is male, and a dummy indicating whether a director is the CEO of another company (Fich, 2005; Fahlenbrach et al., 2010). We use RiskMetrics to classify all newly appointed directors into independent and gray (or affiliated) directors and construct a dummy variable that is equal to one for independent directors. D. Measures of Corporate Governance and Financial Controls

We also collect information concerning the appointing firms' corporate governance structure. We obtain information on entrenchment (or "E-Index") as proposed by Bebchuk, Cohen, and Ferrell (2009) comprised of the six most empirically important anti-takeover provisions included in the governance index (or "G-Index") of Gompers, Ishii, and Metrick (2003), board size, whether a company has a combined CEO and Chairman, whether the CEO is a member of the nominating committee, the percentage of independent outside directors serving on the board, the percentage of directors older than 72 years serving on the board, the percentage of directors attending less than 75% of board meetings, and a measure of board busyness defined as a dummy variable that is equal to one if the majority of board members hold more than three other directorships. The data to construct all of these variables are obtained from RiskMetrics. In addition, we gather information on institutional ownership from Thomson Financial's CDA Spectrum database.

We also collect firm-level financial variables for the 607 firm-years in which our 360 sample companies appoint new directors. From Compustat, we obtain information on the companies' total assets, return on assets, market-to-book ratio, and research and development (R&D) expenses scaled by sales. A detailed overview of all variables used throughout the paper is provided in the appendix.

E. Descriptive Statistics

Table I reports the number of announcements of outside director appointments by calendar month for the sample period from 2005 to 2010 for the full sample, as well as for subsamples of directors with and without industry experience. Of our 688 director announcements, 374 (54.4%) directors have work experience in the same FF12 industry as the company they are joining. The fraction of experienced directors is relatively stable across our sample years. As for the distribution of announcements across calendar months, there is no clear pattern and the number of announcements is lowest in May and highest in December.

Table II presents the FF12 industry distribution of the companies appointing the 688 directors in our sample. The industries with the most new director appointments are Business Equipment (20.5%), Finance (15.7%), and Manufacturing (13.1%). When we compare the number of director announcements with industry experience to those without industry experience, Table II indicates that there exists considerable heterogeneity across industries. In some industries, the majority of firms appoint directors with industry experience (e.g., Business Equipment and Finance), in some industries the majority of firms appoint directors without industry experience (e.g., Consumer (Non-durables) and Consumer (Durables)), and, in two industries, there are exactly as many appointments of experienced as of inexperienced directors (Manufacturing and Healthcare). To pick up a potential industry effect in our results, we include industry fixed-effects in most of our regressions and provide additional industry-based robustness tests in Section III.

Table III presents means and medians for a selection of financial and corporate governance firm characteristics. In Panel A, we report the variables for the full sample of 607 firm-years in which a total of 688 outside directors is appointed to the boards of 360 S&P 500 firms. Panel B presents the results of tests to determine the equality of means and medians between announcements of experienced and non-experienced directors for these variables. These tests reveal that companies that appoint directors with industry experience tend to be somewhat smaller in terms of market capitalization, report a significantly smaller net income, and are less profitable than firms appointing directors without industry experience. With respect to differences in corporate governance characteristics, we find firms appointing experienced directors to have higher institutional holdings, smaller board sizes, are less likely to have a combined CEO-Chairman position, and have more independent outside directors on the board. Finally, the results in Table III indicate that more experienced boards are significantly more likely to appoint additional outside directors with board experience. Thus, there is some evidence that better governed firms are more likely to appoint directors with industry experience to their boards. Given the results in Table 111, it will be important to control for these and other financial and corporate governance control variables in our multivariate analysis.

Table IV reports director characteristics and director industry experience as of the day of the announcement of the new appointments. Panel A of Table IV presents the director characteristics. The mean (median) age of a director, when appointed to the boards of our sample firms, is 56.75 (57.27) years and they hold an average of 1.18 other directorships. Of the new directors, 81.83% are male, about 23% are CEOs at other companies, and 97% are independent. Panel B provides information concerning the industry experience of the directors with 54.36% having some experience in the appointing firm's industry, 31.10% with industry experience as an employee without board membership, 24.71% as an inside director, and 30.96% as an outside director. The average experienced director has 2,819.61 days of industry experience.

II. Empirical Analysis

A. Descriptive Analysis

We examine investor reactions to the announcement of every new outside director appointment in our sample. We compute cumulative abnormal stock returns (CARs) over the two-day period from the day of the announcement until the day after the announcement. (9) We estimate the market model parameters from t = -220 to t = -21 with t = 0 denoting the day of the announcement. We use the S&P 500 as a proxy for the market return. Individual stock and index return data are from CRSP. We winsorize the two-day CARs at the 1st and 99th percentiles of the distribution to account for outliers. Our results, however, do not change substantially when we omit this winsorization. Table V reports the mean and median (0, 1) CARs for the 688 outside director appointments. In the full sample, including all director appointments, both the mean and the median CARs are small and neither is statistically significantly different from zero. This finding is consistent with earlier studies, such as Rosenstein and Wyatt (1997) and Fich (2005). However, when we compare the CARs across the subsamples of directors with and without industry experience, a r-test and a non-parametric Wilcoxon signed-rank test reveal significantly higher mean and median CARs associated with appointments of industry expert directors. Thus, investors seem to anticipate that directors with industry experience have a better ability to advise managers on strategic issues and to critically monitor executives' decisions. It is important, however, that this result is only univariate and, as such, may be caused by omitted variables that are correlated with both industry experience and the announcement returns.

B. Multivariate Analysis

We address these issues by estimating multivariate regressions of the CARs associated with the announcement of newly appointed outside directors on various director- and firm-specific characteristics. The main variable of interest in this analysis is a dummy variable that is equal to one if the appointee has experience in the appointing company's industry. The results are reported in Table VI. We begin with a univariate regression that only includes this industry experience dummy variable as the explanatory variable. Consistent with the results in Table V, the coefficient on the experience dummy variable is positive and significant, indicating that investors perceive directors with industry experience more favorably when compared to non-experienced directors. In Column 2 of Table VI, we control for various director characteristics, such as the age of the newly appointed director, the number of other directorships the director holds, and dummy variables indicating whether the director is male, whether she is CEO of another company, and whether she is independent. Based on Custodio and Metzger (2013) and the empirical literature on wages, we also include age squared. Most importantly, the inclusion of these control variables does not change our results that the announcement effects of new directors with industry experience are significantly higher than the announcement effects of directors without industry experience.

In Column 3 of Table VI, we include firm-specific characteristics to control for firm size (the log of total assets), firm performance (return on assets), and growth opportunities (R&D expenses scaled by sales and the market-to-book ratio). Including these controls in the regression slightly increases the size of the coefficient on the industry experience dummy variable. The coefficient on size is positive and significant at the 10% level, indicating that larger firms experience, on average, higher CARs upon the announcement of a new director appointment. In addition, the variable measuring the directors' additional board seats (i.e., how busy the directors are) is now significant at the 10% level. Consistent with previous research (Fich and Shivdasani, 2006), we find the announcement effect of busy directors to be significantly lower, possibly due to concerns that they will not devote a sufficient amount of time to this particular directorship. The coefficient on the dummy variable used to determine whether the newly appointed director is male is negative and significant suggesting that shareholders value the addition of female directors more than the addition of male directors. This finding is consistent with Adams et al. (2012).

In Column 4 of Table VI, we control for differences in market reactions that are due to differences in the corporate governance structures of the appointing firms. Due to data restrictions of the RiskMetrics database, our sample decreases from 688 to 650 director announcements in this specification. The coefficient on the industry experience dummy variable remains positive and significant, but both the magnitude of the coefficient and the statistical significance is somewhat reduced when compared to Column 3. Instead of size, ROA is now positive and significant indicating that more profitable firms experience higher CARs, on average, upon the announcement of a new director appointment. With respect to the firm-level corporate governance controls, we find only the dummy variable as to whether the CEO is also Chairman of the board to be significant. The negative coefficient indicates that the market perceives the appointment of new outside directors more negatively (or less positively) if a company has a combined CEO-Chairman position. In Column 5, we reestimate the regression specification in Column 4 and include year and industry dummies as the value of director industry experience may substantially differ across time or industries. The results, however, suggest otherwise and the impact of these additional controls on our results is marginal. (10)

Thus far, we have established that investors seem to consider director industry experience as beneficial to firm value. The economic magnitude of the effect is a two-day announcement return that is, on average, about 0.4% to 0.7% larger for the appointment of directors with industry experience as compared to the appointment of directors without industry experience. This effect is quite sizeable when compared to the average announcement effect associated with the announcement of the 688 new outside directors to the board of approximately 0.08%. For our sample of large S&P 500 firms, this translates into a median (mean) gain of approximately $41 to $72 ($99 to $173) million associated with appointing a director with industry experience as compared to a director without industry experience. While this seems large, it is important to recognize that this is not the absolute value gain associated with appointing a director with industry experience, but the difference between the negative announcement effect associated with appointing a director without experience and the positive announcement effect associated with appointing a director with industry experience, on average. In addition, a corporate decision with the same relative importance, or valuation effect, in any firm has a much larger absolute valuation effect in large firms. In fact, our announcement returns are comparable in size to those reported in other studies investigating the announcement returns of director appointments (Fich, 2005; Fahlenbrach et al., 2010; Adams et al., 2012).

III. Robustness Tests

First, we test the robustness of our results with respect to a narrower and more precise industry classification system than FF12. The disadvantage of using a narrower classification system, however, is that we observe a smaller number of director appointments with industry experience and may end up with too little variation. In particular, in combination with our relatively small sample and the large set of control variables, a low variation in our measure of industry experience will make it difficult to observe any significant results. Therefore, instead of constructing alternative industry experience variables based on the Fama-French 48-industries (FF48) classification, we follow Custodio and Metzger (2013) and construct a weighted measure of industry experience defined as follows. The variable takes a value of one if the newly appointed director has any type of work experience in the FF12 industry of the appointing company, takes a value of two if the newly appointed director has any type of work experience in the FF48 industry of the appointing company, and is otherwise equal to zero. The results from re-estimating Column 5 of Table VI using this alternative measure of industry experience, Industry exp. (FF12/FF48), are reported in Column 1 of Table VII. The coefficient on the measure of industry experience is positive and significant at the 5% level. In addition, the economic magnitude of the valuation effect is larger for the weighted measure using both the FF12 and FF48 industries when compared to the standard measure using only the FF12 industry. (11) Thus, as expected, the value of industry experience is higher when the industry in which the experience was gained is closer to the industry of the appointing firm.

Thus far, we have measured industry experience as either binary [Industry exp. (dummy)} or as a count variable [Industry exp. (FF12/FF48)]. To determine whether more experience, as measured by longer employment in a respective industry, is valued by investors, we replace the experience dummy variable in Table VI [Industry exp. (dummy)} with a variable that measures the length of the respective experience in days [Industry exp. (days)}. The results from this regression are reported in Column 2 of Table VII and indicate that more extensive industry experience is associated with higher announcement returns. Again, the economic magnitude of the results is meaningful. An increase in industry experience in days [Industry exp. (days)} by one standard deviation (4,186 days) is associated with an increase in two-day CARs of approximately 0.1%.

Our sample includes several multisegment or diversified firms. By only using a firm's main industry classification in determining director industry experience, we may miss industry experience acquired in a segment that is active outside of a firm's main industry. To account for the possibility of experience in one or more segments, we collect segment information from the Compustat Segment database. Segment information is available for 537 of the 688 events in our sample. We construct three alternative measures of industry experience that account for experience at the segment level. As the relative importance of individual segments differs widely across firms and segments, we define the first measure as the percentage of segment sales attributed to FF12 industries in which the newly appointed director has work experience [Segment ind. exp. (%)]. To account for the limited data coverage in the Compustat Segment database, we define an alternative measure of industry experience that is identical to Segment ind. exp. (%) for firm-years with data coverage in Compustat Segments. If no segment data is available, the measure is equal to 100% (0%) based on whether the newly appointed director has industry experience in the company's main industry [Segment / main ind. exp. (%)]. The third measure of industry experience is a dummy variable that indicates whether the newly appointed outside director has industry experience in the FF12 industry of at least one segment of the appointing firm or in the firm's main FF12 industry. The results are reported in Columns 3 to 5 of Table VII. The coefficients on all three alternative measures of industry experience are positive and significant confirming a positive relation between industry experience and firm value. Moreover, a higher percentage overlap between the industry portfolio covered by the appointing firms' segments and the industries in which the newly appointed directors have work experience is associated with higher announcement returns. (12)

If appointments of industry expert directors are anticipated differently by the market than appointments of directors without industry experience, the difference in the two-day announcement returns may result from a pre-announcement return picking up part (or all) of the total announcement return in either category. To determine whether our results are affected by differences in anticipation, we proceed as follows. First, we re-estimate Table VI with a pre-announcement abnormal return calculated from day t = -20 to day t = -1 instead of the two-day CAR calculated from day t = 0 to day t = 1 as the dependent variable. The coefficient on the industry experience dummy variable is insignificant in all five specifications. Thus, the 20-day pre-announcement return does not significantly differ across appointments of directors with industry experience and directors without industry experience. Due to limited space, we do not report these results. In addition, we reestimate the results in Table VI and add the pre-announcement abnormal return as an additional explanatory variable. If the two-day announcement return is significantly related to the 20-day pre-announcement return, the coefficient on the latter should pick this up. The results from replicating Column 5 of Table VI, including the pre-announcement abnormal return as an additional explanatory variable, are reported in Column 6 of Table VII. The coefficient on the pre-announcement abnormal return is insignificant, while the coefficient on the experience dummy variable remains qualitatively unchanged. The results from replicating the other four columns in Table VI are also unaffected by the inclusion of pre-announcement abnormal returns and, as such, are not reported due to space limitations. Moreover, as the effect of the pre-announcement abnormal return on the announcement return may depend upon the industry experience status of the newly appointed director, we replicate Table VI by adding the pre-announcement abnormal return and an interaction term between the pre-announcement abnormal return and industry experience. The results confirm that none of the coefficients on the pre-announcement abnormal return or on the interaction term are significant, while the coefficient on the industry experience dummy remains positive and significant in all five specifications. For space reasons, we do not report these results in a table. Overall, we find no evidence that differences in anticipation between the appointments of directors with and without industry experience drive our findings.

Another concern could be that our results are affected by 108 director appointments to the boards of financial firms. Eighty (74%) of these newly appointed directors have industry experience. In the aftermath of the recent financial crisis, lack of financial expertise on banks' boards was often stressed as one of the main reasons for excessive risk taking resulting in poor bank performance and sometimes even collapse (Pozen, 2010). Consequently, we could expect banks to be eager to appoint financial expert directors, and these appointments to be positively perceived by stockholders. Therefore, we reestimate the results in Column 5 of Table VI excluding 97 director appointments to the boards of financial firms with complete controls. The results in Column 7 of Table VII confirm our previous findings.

Next, we extend our standard specification to include year and industry fixed-effects by industry x year interacted fixed-effects in order to control for time-varying factors particular to an industry. The results are reported in Column 8 of Table VII. The results remain virtually unchanged when compared to Column 5 of Table VI.

To rule out concerns that our measures of director industry experience pick up generalist skills rather than experience in the appointing firm's industry, we construct two additional variables. The first variable is the total number of different FF12 industries in which the appointed director was previously employed. The second variable is the number of different companies the newly appointed director worked for throughout his entire work history at the time of the appointment. As both are count variables ranging from 0 to 9 and from 0 to 57, respectively, we use the natural logarithm of one plus the number of industries (firms). Positive and significant Pearson correlation coefficients between industry experience and the two measures of generalist skills of 0.33 and 0.29, respectively, indicate that industry expert directors are also more likely to have more generalist skills or experience. To determine whether our measure of industry experience reflects the effect of generalist skills rather than that of industry experience, we extend our standard regression specification to include either the generalist industry experience measure or both the generalist industry and the generalist firm experience measures. The results in Columns 1 and 2 of Table VIII indicate that the coefficient on the industry experience dummy variable remains positive and significant, while none of the coefficients on the generalist skills variables is estimated to be significant. Our results suggest that it is industry experience and not generalist skills that are associated with higher announcement returns.

As in virtually all empirical corporate governance studies, identification is the biggest challenge in our paper. One source of endogeneity may be director characteristics that are correlated with both industry experience and firm value, but omitted from the analysis because they are unobservable to the researcher (e.g., talent). We attempt to mitigate this omitted variables problem in two ways. First, we use education as a proxy for talent (Abowd, Kramarz, and Margolis, 1999; Graham, Li, and Qiu, 2012). We follow Graham et al. (2012) and define two alternative measures of education. The first variable, Education1, is equal to one for education below a bachelor-level degree, two for a bachelor-level degree, three for non-MBA masters and MBAs, four for doctorates (Ph.D., M.D., and J.D.), and zero otherwise. Education2 is the number of years of education, with education below bachelor-level degree defined as 12 years, a bachelor-level degree as 16 years, non-MBA masters and MBAs as 18 years, and doctoral degrees as 21 years of education. In addition to Education1 and Education2, we construct a dummy variable to determine whether at least one degree of the newly appointed director was obtained from an Ivy League university as Ivy League attendance may also indicate greater ability, a better and more useful education, or both. All three variables are hand-collected from BoardEx, Factiva, LexisNexis, and internet searches. The results from the regressions including Education1 and the Ivy League dummy and Education2 and the Ivy League dummy are reported in Columns 3 and 4 of Table VIII, respectively. None of the education variables is ever deemed significant in these (and additional unreported) tests, while the experience dummy variable remains virtually unchanged. In addition, we use firm fixed-effects to mitigate the problem of omitted, but time-fixed variation at the firm level (e.g., talent). The results from estimating Column 5 of Table VI with firm fixed-effects are reported in Column 5 of Table VIII. Again, we find the coefficient on the experience dummy variable to remain positive and significant corroborating our previous findings.

In the next step of our empirical analysis, we examine to what extent investors value different types of industry experience. In our subsequent analysis, we split our industry experience dummy variable into three dummy variables: 1) a dummy variable to determine whether the newly appointed director has work experience as an employee/executive without board membership in the same FF12 industry [Exp. employee (dummy)'], 2) a dummy variable to determine whether the newly appointed director has work experience as an employee/executive with additional board membership in the same FF12 industry [Exp. inside director (dummy)], and 3) a dummy variable to determine whether the newly appointed director has work experience as outside board member in the same FF12 industry [Exp. outs, director (dummy)]. We estimate the regression specification as reported in Column 5 of Table VIII, including firm fixed-effects, with the standard industry experience dummy variable replaced by the three alternative measures of director experience. The results are reported in Column 6 of Table VIII and indicate that only the coefficient on Exp. inside director (dummy) is positive and significant at the 10% level. The economic magnitude of this effect is much larger than that found in Column 6 and indicates that the appointment of an outside director with industry experience as an inside director is associated with a two-day announcement return that is 2.5% higher than for other appointments. Thus, investors value experience gained as an inside director the highest. (13)

We perform a number of additional robustness tests. First, we investigate whether industry experience gained as a CEO is particularly important. However, we find that experience as a CEO is not more valuable than experience gained as any other inside director. In addition, we attempt to control for the potential effect of retiring/exiting directors. As we cannot directly observe whether a newly appointed director replaces another director, we add a control variable that is equal to one if the number of directors on the board remains unchanged or decreases from the last filing prior to the first filing after the appointment. As decision making processes are presumably easier on boards with an odd number of directors, we additionally construct variables to determine whether the board changes from an odd to an even number or from an even to an odd number. The coefficients on all three of these additional control variables are insignificant in all of the specifications and the coefficients on the industry experience variables are virtually unaffected by their inclusion.

We also consider whether the announcement effect associated with a new outside director appointment and, in particular, with an outside director with industry experience, is significantly related to the appointing firm's past performance. For instance, we could expect that the appointment of an outside director with industry experience is perceived by shareholders as particularly beneficial when the firm performed poorly during the last few years. Alternatively, we might expect that in the case where they have sufficient power, CEOs of poorly performing firms seek to appoint lower quality directors (i.e., without industry experience) to secure their position. In this latter case, the appointment of an inexperienced director would be particularly harmful. Using either the cumulative stock returns over the last 36 months prior to the appointment or the change in profitability (ROA) over the last three years as measures of past performance, we find the coefficient on the interaction term between past performance and industry experience to be insignificant, while the coefficient on industry experience remains positive and significant. Thus, past firm performance does not affect the announcement effect associated with industry experience.

In another test, we construct an alternative set of industry experience variables and consider only experience in listed US firms. Again, we find the results to remain similar. Furthermore, we examine whether our results are robust to using standard errors that cluster at the firm level and standard errors that cluster at the event date level. This may be potentially important as we have some firms in our sample that appoint more than one director to their board. Moreover, we have some dates on which more than one director is appointed to a board (of a different company). Director appointments to the board of one particular firm and appointments taking place on one particular day may not constitute independent observations. However, the results remain virtually unchanged when we cluster at either the firm or the event date level.

Finally, we explore whether knowledge-intensive firms benefit more from directors with industry experience than other firms. To this end, we add an interaction term between industry experience and R&D expenditures scaled by sales to our regressions. We use R&D expenditures as a measure of firms' knowledge intensity. While the coefficient on industry experience remains positive and significant, the coefficient on the interaction term is insignificant. Thus, R&D intensity does not seem to drive our results suggesting that the positive valuation effect of director industry experience is generally observable and not specific to knowledge-intensive firms.

IV. Identification Through Director Deaths

As previously mentioned, one issue potentially plaguing our analysis of director appointments is that the board of directors is an endogenously determined institution (Hermalin and Weisbach, 1988, 1998, 2003). The positive market reaction to the appointment of experienced directors could be driven by the need for change in the appointing firms, not the contribution of industry experience. As such, it might be difficult to empirically identify a causal relationship between director industry experience and firm value. Even though the results of some of our additional tests are not generally consistent with an omitted variable issue driving our results, we aim to alleviate endogeneity concerns related to the appointment of directors by employing an identification strategy based on the deaths of incumbent directors (Nguyen and Nielsen, 2010). Director deaths offer plausibly exogenous identification as to how markets value director industry experience as deaths occur randomly and are likely to be exogenous to current firm and market conditions. While there is a growing literature using CEO and director deaths as identification strategy, it is still surprisingly small given the appeal of this approach. (14)

We start compiling our sample of director deaths by collecting data on departures of S&P 1500 board members from 2005 to 2011. We extend both the stock universe (from the S&P 500 to the S&P 1500) and the time period (from 2005-2010 to 2005-2011) due to the small number of outside director deaths in our original sample (60). For every director departure, we search LexisNexis, Factiva, and SEC filings for information to determine whether the director departure was due to death, retirement, or other reasons. We retain all director departures where the director died in office and use the first date on which we can find a public mention of the death of the director as the event date. Our sample consists of all directorships held by deceased directors on the day of their death with sufficient data on CRSP, resulting in 200 director deaths with 280 directorships in listed US firms. As there is usually a difference between the date on which we find the very first mention of the death of a director (e.g., an industry blog) and the first mention of the death of a director in a media outlet with wider reach (e.g., an obituary published in a newspaper), we use a larger event window (i.e., a seven-day window from day t = -3 to day t = 3) than for the director announcements above where the event date was more easily determined. To determine whether a deceased director had industry experience, we collect biographical information from proxy filings, LexisNexis, and BoardEx in the same spirit as for the director announcements above. One hundred eighty-one directorships are classified as directorships with experience and the remaining 99 as directorships without experience.

We estimate similar cross-sectional regressions as in Table VI for outside director appointments. Again, we begin by regressing the CARs on a dummy variable whether the deceased outside director has industry experience and then extend the set of control variables to include additional director-specific variables, firm-specific financial controls, and year and industry fixed-effects. In contrast to Table VI, we do not include firm-specific corporate governance variables as the set of eight corporate governance variables used in Table VI is available from RiskMetrics for only 198 director death events, while the control variables from Compustat are available for 268 events. (15) The results are reported in Table IX. The only significant variable in all four regression specifications is the experience dummy variable that indicates a sizeable discount associated with the deaths of experienced directors when compared to non-experienced outside directors of about 2.0% to 2.7% over a seven-day event window. By using outside director deaths as an identification strategy to alleviate endogeneity concerns, we corroborate previous findings that director industry experience is valuable.

We provide a number of robustness tests for these results. First, we narrow our death sample by attempting to capture only sudden deaths that were not anticipated by the market. As there is no unambiguously accepted definition of a sudden death in the literature, we follow the previous research (Nguyen and Nielsen, 2010; Falato, Kadyrzhanova, and Lei, 2014) and classify deaths as sudden when the cause of death is indicated to be a heart attack, stroke, or accident and when the specific cause is unreported, but the death is described as unexpected, unanticipated or sudden. In addition to this relatively strict definition of sudden deaths, which results in a relatively small sample of 74 death events (69 events with complete controls), we experiment with alternative specifications. In the first alternative specification, we also classify death events resulting from diseases with low mortality rates (e.g., Lyme disease), diseases that may be deadly for the elderly, but are unlikely to be reported to the public immediately (e.g., pneumonia), or often result in a quick death (e.g., an air embolism) as sudden deaths. In addition, we classify deaths as sudden when the cause of death is indicated to be due to causes incident to age without reference to a specific disease. This somewhat less restrictive definition of sudden deaths results in 105 events (100 with controls). In a second alternative classification of sudden deaths, we reclassify pneumonia and other diseases, which may result from another disease or generally poor health, as expected death events resulting in 91 sudden death events (86 with controls). The results from running the full regression specification, but without year and industry fixed-effects due to the small sample size, are reported in Columns 1 to 3 of Table X with the least restrictive definition of suddenness in Column 1 and the most restrictive in Column 3. The experience dummy variable is negative and significant in all three columns confirming the positive valuation effect of director industry experience. Additionally, both the coefficient and statistical significance increase monotonically from the least restrictive to the most restrictive definition of suddenness. As expected, stricter definitions of suddenness result in stronger announcement effects.

The exogenous shock to the board resulting from (unexpected) director deaths does not completely rule out endogeneity concerns as a company's choice to appoint this particular director was endogenous. Unobserved director characteristics (e.g., talent), which are correlated with industry experience, may drive our results. (16) To address this omitted variables problem at the director level, we estimate a regression with director fixed-effects instead of the necessarily incomplete set of director-level controls. These director fixed-effects account for time-fixed (unobservable) characteristics of the directors, such as talent and ability. This analysis is facilitated by the sample selection applied to the collection of death events that encompasses all board seats, including companies not found in the S&P 1500, held by deceased directors on the day of their death with sufficient data on CRSP. The resulting sample includes 56 directors holding more than one board seat in a listed US firm and a total of 127 death events. (17) The results are reported in Column 4 of Table X. Once again, our results confirm the previous findings that the deaths of experienced directors are associated with lower announcement returns.

V. Conclusion

Is directors' industry knowledge relevant? Despite the importance and timeliness of this issue, academic research has been surprisingly silent on this question thus far. In this paper, we provide systematic empirical evidence to help answer this question and enhance our understanding of the importance of board member characteristics. To this end, we examine market reactions to the announcements of 688 new outside directors at 360 S&P 500 companies from 2005 to 2010. We find, using univariate and multivariate analyses, that investors react significantly more positively to director announcements where the director has previous experience in the industry in which the company issuing the announcement operates. We also provide evidence that investors value industry experience as an inside director more than industry experience as an employee or an outside director. Our results further suggest that it is industry experience and not generalist skills, as measured by the number of firms and industries a director has worked for in the past, that are associated with higher announcement returns. Finally, we investigate a sample of 200 outside director deaths to alleviate endogeneity concerns associated with director appointments. The announcement returns around the deaths of experienced directors are significantly more negative than those of non-experienced directors and the economic magnitude of the difference is even larger than in the case of director appointments.

Given that director industry experience seems to be valuable, the question arises as to why some firms still appoint non-industry experts to their boards of directors. Is there a trade-off between director skills, and does industry experience come at the expense of other, yet unidentified, types of skills? Are industry expert directors in short supply because of the Clayton Antitrust Act or do they demand prohibitively high wages to join corporate boards? Alternatively, if industry experts are better monitors, poorly governed firms may have a preference for non-experts. Also, the importance and public perception of industry experience, and other director characteristics, may have changed significantly during the last few years. As a consequence, firms may have started to optimize board structure and experienced positive market reactions upon perceived improvements. We leave these unresolved questions open for future research.

Appendix: Variable Definitions

                                            Definition

Panel A. Industry experience

Industry Exp. (dummy)        Dummy equal to one if the appointed
                               director has work experience in the
                               same FF12 industry, and zero otherwise.
Exp. Employee (dummy)        Dummy equal to one if the appointed
                               director has work experience as an
                               employee/executive without board
                               membership in the same FF12 industry,
                               and zero otherwise.
Exp. Inside Director         Dummy equal to one if the appointed
  (dummy)                      director has work experience as an
                               employee/executive with additional
                               board membership in the same FF12
                               industry, and zero otherwise.
Exp. Outs. Director          Dummy equal to one if the appointed
  (dummy)                      director has work experience as
                               outside board member in the same FF12
                               industry, and zero otherwise.
Industry Exp. (days)         Natural logarithm of one plus the days
                               of total industry experience in the
                               same FF12 industry of the newly
                               appointed director; adjusted for
                               double counting within one employment
                               category (employee, inside director,
                               and outside director).
Industry Exp.                Measure of industry experience that is
  (FF12/FF48)                  equal to one if the appointed director
                               has work experience in the same FF12
                               industry, equal to two if they have
                               work experience in the same FF48
                               industry, and zero otherwise.
Segment Ind. Exp. (%)        Percentage of segment sales attributed
                               to FF12 industries in which the newly
                               appointed director has work experience.
Segment/Main Ind. Exp.       Percentage of segment sales attributed
  (%)                          to FF12 industries in which the newly
                               appointed director has work
                               experience, but observations without
                               firm coverage in the Compustat Segment
                               database are classified into
                               appointments with/without experience
                               based on the company's main industry.
Main/Segm. Ind. Exp.         Dummy equal to one if the newly
  (dummy)                      appointed outside director has
                               industry experience in the FF12
                               industry of at least one segment of
                               the appointing firm or in the firm's
                               main FF12 industry, and zero otherwise.

Panel B. Director-specific controls

Age                          Age of the appointed director.
Age Squared                  Age of the appointed director squared.
# Add. Directorships         The number of other current
                               directorships held by the appointed
                               director.
Male (dummy)                 Dummy equal to one if the appointed
                                director is male, and zero otherwise.
CEO (dummy)                  Dummy equal to one if appointed director
                               is a CEO of another company at the
                               time of the appointment, and zero
                               otherwise.
Independent (dummy)          Dummy equal to one if the newly
                               appointed director is independent (and
                               not gray), and zero otherwise.
ln(#Industries with Exp.)    Natural logarithm of one plus the number
                               of distinct FF12 industries a director
                               has worked for prior to their
                               appointment.
ln(#Firms with Exp.)         Natural logarithm of one plus the number
                               of distinct firms a director has worked
                               for prior to their board appointment.
Education1                   Count variable equal to one if a
                               director's highest degree is below a
                               bachelor degree, two if the highest
                               degree is a bachelor degree, three if
                               the highest degree is a non-MBA master
                               or an MBA, and four if the highest
                               degree is a doctoral degree (Ph D.,
                               M.D., J.D.).
Education2                   Number of years of education, with below
                               bachelor defined as 12 years, bachelor
                               as 16 years, non-MBA masters and MBAs
                               as 18 years, and doctoral degrees as
                               21 years of education.
Ivy League (dummy)           Dummy equal to one if at least one
                               degree of the newly appointed director
                               was obtained from an Ivy League
                               university.

Panel C. Firm-specific controls

ln(Total assets)             Natural logarithm of total assets.
ROA                          Net income/total assets.
Market-to-Book               Market value equity /book value equity.
R&D/Sales                    R&D expenses/total sales.
E-Index                      Entrenchment index as proposed by Bebchuk
                               et al. (2009).
Institutional Ownership      Percentage ownership of blockholders
                               with >5% ownership.
ln(Board Size)               Natural logarithm of board size.
CEO-Chair (dummy)            Dummy equal to one if the CEO is also
                               Chairman of the board, and zero
                               otherwise.
CEO in Nom. Com.             Dummy equal to one if the CEO is a
  (dummy)                      member of the nominating committee,
                               and zero otherwise.
% Independent Outside        The percentage of independent outside
  Directors                    directors on the board.
% Directors Older than 72    The percentage of directors on the board
                               who are older than 72 years.
Director Non-attendance      The percentage of directors on the board
                               attending less than 75% of the board
                               meetings.
Busy Board (dummy)           Dummy equal to one if the majority of
                               board members holds more than three
                               other directorships, and zero
                               otherwise.
% Directors with             The percentage of outside directors on
  Experience                   the board with work experience in the
                               same FF12 industry.

                                    Source

Panel A. Industry experience

Industry Exp. (dummy)        BoardEx/LexisNexis/
                               Factiva
Exp. Employee (dummy)        BoardEx/LexisNexis/
                               Factiva
Exp. Inside Director         BoardEx/LexisNexis/
  (dummy)                      Factiva
Exp. Outs. Director          BoardEx/LexisNexis/
  (dummy)                      Factiva
Industry Exp. (days)         BoardEx/LexisNexis/
                               Factiva
Industry Exp.                BoardEx/LexisNexis/
  (FF12/FF48)                  Factiva
Segment Ind. Exp. (%)        BoardEx/LexisNexis/
                               Factiva
Segment/Main Ind. Exp.       BoardEx/LexisNexis/
  (%)                          Factiva
Main/Segm. Ind. Exp.         BoardEx/LexisNexis/
  (dummy)                      Factiva

Panel B. Director-specific controls

Age                          BoardEx/RiskMetrics
Age Squared                  BoardEx/RiskMetrics
# Add. Directorships         BoardEx/RiskMetrics
Male (dummy)                 BoardEx/RiskMetrics
CEO (dummy)                  BoardEx/Proxy filings
Independent (dummy)          RiskMetrics/Proxy
                               filings
ln(#Industries with Exp.)    BoardEx/LexisNexis/
                               Factiva
ln(#Firms with Exp.)         BoardEx/LexisNexis/
                               Factiva
Education1                   BoardEx/LexisNexis/
                               Factiva
Education2                   BoardEx/LexisNexis/
                               Factiva
Ivy League (dummy)           BoardEx/LexisNexis/
                               Factiva

Panel C. Firm-specific controls

ln(Total assets)             Compustat
ROA                          Compustat
Market-to-Book               CRSP/Compustat
R&D/Sales                    Compustat
E-Index                      RiskMetrics
Institutional Ownership      CDA Spectrum
ln(Board Size)               RiskMetrics
CEO-Chair (dummy)            RiskMetrics
CEO in Nom. Com.             RiskMetrics
  (dummy)
% Independent Outside        RiskMetrics
  Directors
% Directors Older than 72    RiskMetrics
Director Non-attendance      RiskMetrics
Busy Board (dummy)           RiskMetrics
% Directors with             BoardEx/Lexis
  Experience                   Nexis/Factiva


The authors thank Tim Adam. Yakov Amihud, Manuel Ammann, Marc Arnold, Emanuele Bajo, Tobias Berg, Marco Bigelli, Martin Brown, Ettore Croci, Fabrizio Ferri, Patrick Goettner, Stefan Hirth, Claudio Loderer, Ernst Maug, Daniel Metzger, Alexandra Niessen-Ruenzi, Raghavendra Rau (Editor), Tony Saunders, Friederike Schmid, Alex Stamper, Daniel Streitz, Urs Waelchli, Alexander Wagner, David Yermack, an anonymous referee, and seminar and conference participants at the University of Bern, University of Bologna, University of Hamburg, University of St. Gallen, Humboldt University Berlin, University of Mannheim, 2013 WHU Campus for Finance Conference, and the 2013 Swiss Finance Association Annual Meetings in Zurich for helpful comments and suggestions. Part of this research was completed while von Meyerinck was a PhD candidate at the School of Business of the University of Hamburg and while von Meyerinck, Oesch, and Schmid were visiting scholars at the Stern School of Business, New York University. Von Meyerinck acknowledges financial support from the German Academic Exchange Service and the School of Business of the University of Hamburg. Oesch acknowledges financial support from the Janggen-Pohn Foundation.

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(1) Pozen (2010) argues that in addition to being too large to operate effectively and not devoting sufficient time to board tasks, today's boards frequently lack sufficient expertise in the relevant industry. Similarly, when assessing the most important skills that companies are likely to look for in directors over the next few years, Bertsch (2011) argues that the focus has shifted from director independence toward directors with industry experience.

(2) On December 16, 2009, the Securities and Exchange Commission adopted amendments to its disclosure rules and forms to enhance the information provided to shareholders. These amendments are intended to improve disclosure regarding risk, corporate governance, director qualifications, and compensation. For more details see http://www.sec.gov/rules/final/2009/33-9089-secg.htm.

(3) In this paper, we investigate the valuation effect of director industry experience. We leave the question as to whether any valuation effect is derived primarily from superior monitoring or from better advice provided to top management to future research. Such an analysis requires a panel data structure imposing additional endogeneity concerns that are even harder to address than in our analysis of well-defined director appointment and exit (through death) events.

(4) We focus on the short-term announcement effects as director industry experience, and board composition more generally, are unlikely to remain constant over time. Thus, analyzing the long-term performance changes around the appointment of outside directors with industry experience is a difficult task. Moreover, in an efficient market, short- term announcement returns incorporate the market's estimated long-term impact of adding a new director.

(5) The freedom in the formulation of such non-compete contracts depends upon the states' non-competition laws and, as such, differs across states. However, Garmaise (2009) collects SEC filings of 500 randomly chosen firms included in ExecuComp and finds that 351 (70.2%) use some sort of non-compete contract.

(6) To better understand the type of appointments of industry expert directors in our sample, we provide details of one appointment of an experienced outside director. William D. Perez joined the board of directors of Campbell Soup Co. (standard industrial classification (SIC) Code 2030) on June 1, 2009 after serving as CEO and executive director of WM Wrigley Jr. Co. (SIC Code 2060) for approximately 717 days until Wrigley was sold to Mars. Both firms belong to FF12 industry 1 [Consumer (Non-durables)]. The event reports a two-day cumulative abnormal return (CAR) of 2.97%. Thus, the appointment of directors with relevant industry experience seems possible and not a priori ruled out by non-compete clauses.

(7) Our paper is also related to a recent study on the relation between current industry affiliation and firm performance. Dass, Kini, Nanda, Onal, and Wang (2014) find that a higher proportion of directors from related industries on companies' boards, particularly upstream (supplier) or downstream (customer) industries, are associated with significantly higher firm values.

(8) When calculating a director's industry experience in days, we avoid double counting that arises when a director exerts a role multiple times within the same hierarchical position in the same FF12 industry. This implies that someone can gain more than one day of industry experience when working one day in the same industry, but only if the positions are on a different hierarchical level. The following example illustrates this procedure. Craig Conway, who became an outside director of Advanced Micro Devices Inc., has been an outside director of Salesforce.com from October 6, 2005, until the event date (September 28, 2009) and an outside director of Unisys Corp. from August 15, 2007, until May 28, 2009. As such, the number of experience days for this director is adjusted for the duration of the latter position (652 days) since both positions were within the same FF12 industry as the appointing company (Business Equipment), within the same hierarchical experience category (experience as outside director), and the time period of the second position at Unisys Corp. is fully covered by the position in Advanced Micro Devices Inc.

(9) An inspection of abnormal announcement returns finds that all of the effect takes place on the announcement day and the day after suggesting that these events are measured with high precision. As a consequence, when extending our event window to include three or more days, the signal to noise ratio is expected to decrease. Still, we find our results to hold for a three-day window from day t = -1 to day t = 1, but to be insignificant for event windows of four days or longer. Due to space constraints, we do not report the results from this analysis.

(10) As the announcement effect associated with the industry experience of newly appointed outside directors may depend on the industry experience that already exists on the appointing firms' boards, we reestimate Columns 4 and 5 and include an interaction term between Industry exp. (dummy) and % Directors with experience. However, the coefficient on this interaction term (and on % Directors with experience) is insignificant in both specifications (not reported).

(11) The coefficient estimate of the experience dummy variable in Column 5 of Table VI indicates that the appointment of an industry expert director is associated with an abnormal announcement return and is about 0.5% higher than the appointment of a non-expert director. When differentiating between experience in the same FF12 industry and experience in the same FF48 industry in Column 1 of Table VII, the appointment of a director with experience in the same FF12 industry is associated with announcement returns that are, on average, 0.3% higher as compared to directors without industry experience. Appointments of directors with experience in the same FF48 industry are associated with announcement returns that are, on average, 0.3% higher than those of directors with experience in the same FF12, but not in the FF48 industry and 0.6% higher than those of directors without industry experience.

(12) Segment data are afflicted with many problems (e.g., Berger and Ofek, 1995). For example, the segments' sales values often do not add up to the sales reported at the company level. For some companies, none of its segments' two-digit or even one-digit SIC codes correspond to the SIC code reported for the whole company. Also firms have quite some leeway in reporting segments (e.g., Berger and Hann, 2003). Hence, we report these results based on segment industry reporting as robustness tests only and not in our main analysis.

(13) The positive valuation effect associated with directors with industry experience could also be due to valuable networks, in particular director networks (Fracassi and Tate, 2012), previously established in this industry. However, experience gained as an outside director without any executive position in the industry is the least valuable. Hence, director networks do not seem to drive our findings. As inside directors usually are members of the executive board (often the CEO), this result either indicates that experience in such a high ranked executive position is particularly valuable (Fich, 2005; Fahlenbrach et al., 2010) or that top executive positions facilitate access to valuable personal networks, or both. We do not attempt to empirically differentiate the benefits emerging from personal networks in an industry and other benefits of work experience in an industry, such as for example knowledge of the customer base and / or the suppliers, the main competitors, production details, etc.

(14) Some notable studies include Johnson, Magee, Nagarajan, and Newman (1985) who use 53 sudden deaths of executives to estimate the value of their continued employment and find positive market reactions to the death of founder-CEOs and negative reactions to the death of professional CEOs. Bennedsen, Perez-Gonzalez, and Wolfenzon (2010) determine that CEOs' deaths and deaths in CEOs' families are strongly correlated with declines in firm operating profitability, investments, and sales growth and conclude that CEOs are instrumental to firm performance. Nguyen and Nielsen (2010) use 229 sudden director deaths to investigate the value of director independence and find more negative returns to the announcement of independent director deaths. Fracassi and Tate (2012) use both director deaths and retirements to analyze the valuation effect of CEO-director ties and find that CEO-director ties are associated with weaker monitoring and lower value. Falato, Kadyrzhanova, and Lei (2014) use director and CEO deaths as an exogenous shock to the workload of busy directors on the board to investigate the valuation effect of director busyness.

(15) With the exception of the dummy to determine whether the CEO is also Chairman of the board, which is borderline significant in most specifications reported in Tables VI to VIII, none of the other firm-level governance variables is significant in any of the previous tables. Moreover, in the analysis of director appointments, the inclusion of the CEO-Chairman dummy never affects the coefficient of the experience dummy in a meaningful way.

(16) Another endogeneity concern may be that directors are appointed by companies based on a specific need or requirement. Thus, instead of unobservable director characteristics, director-firm specific factors may drive the results. However, as time evolves, many of these firm-director matches would be expected to deteriorate as companies and their environment change. The average (median) director in our sample is on the board of directors for 10.2 (8.9) years at the time of death. When we split our sample into directors with above and directors with below median tenure, the results are similar in both subsamples even though the firm-director match, on which the appointment decision may have been based, is expected to have deteriorated for most firms in the above median subsample.

(17) We include a dummy to determine whether the newly appointed director is independent as the only director- levelcontrol as this variable is not a fixed director characteristic, but directly related to the respective board seat.

Felix von Meyerinck, David Oesch, and Markus Schmid *

* Felix von Meyerinck is an Assistant Professor of Finance at the Swiss Institute of Banking and Finance, University of St. Gallen in St. Gallen, Switzerland. David Oesch is an Associate Professor of Financial Accounting in the Department of Business Administration, University of Zurich in Zurich, Switzerland. Markus Schmid is a Professor of Finance at the Swiss Institute of Banking and Finance, University of St. Gallen in St. Gallen, Switzerland.

Table I. Distribution of Director Appointments Over Time

The table reports the number of outside directors appointed to the
board of non-utilities S&P 500 companies from 2005 to 2010 after
applying the four filters outlined in Section I.A. The table reports
the total number of outside director appointments (All), the number
of appointments of directors with industry experience (Experience),
and the number of appointments of directors without industry
experience (Non-experience) by calendar year and month. The sample
includes a total of 688 outside director appointments.

                                        Event Month

                              1    2    3    4    5    6    7

Event Year

2005         All              12   10    7    3    7   12    7
             Experience        8    5    5    3    5    5    2
             Non-experience    4    5    2    0    2    7    5
2006         All              10    7   10    5    3    8    9
             Experience        5    4    4    3    1    5    5
             Non-experience    5    3    6    2    2    3    4
2007         All               9    3   13    4    5    5   14
             Experience        6    2    8    2    1    3    6
             Non-experience    3    1    5    2    4    2    8
2008         All              16   22    0    8    5   10   19
             Experience       11   13    0    4    4    7   10
             Non-experience    5    9    0    4    1    3    9
2009         All              10   12   10    6    4   16   14
             Experience        4    3    7    3    3    7    7
             Non-experience    6    9    3    3    1    9    7
2010         All              11   11   10    7    4   15    8
             Experience        6    6    4    3    3   11    2
             Non-experience    5    5    6    4    1    4    6
Sum          All              68   65   50   33   28   66   71
             Experience       40   33   28   18   17   38   32
             Non-experience   28   32   22   15   11   28   39

                                      Event Month

                              8    9    10   11   12   Sum

Event Year

2005         All               8   16    4    8   17   111
             Experience        6    8    2    6    5    60
             Non-experience    2    8    2    2   12    51
2006         All               3   10   12    2   12    91
             Experience        1    2    5    0    8    43
             Non-experience    2    8    7    2    4    48
2007         All               7    7    7    3   20    97
             Experience        4    5    3    0   10    50
             Non-experience    3    2    4    3   10    47
2008         All               8   18   12   12   13   143
             Experience        6   13    6    8    7    89
             Non-experience    2    5    6    4    6    54
2009         All               6   11   12   13   19   133
             Experience        2    8    9    8   10    71
             Non-experience    4    3    3    5    9    62
2010         All               8   13    8    6   12   113
             Experience        5    6    5    4    6    61
             Non-experience    3    7    3    2    6    52

Sum          All              40   75   55   44   93   688
             Experience       24   42   30   26   46   374
             Non-experience   16   33   25   18   47   314

Table II. Distribution of Director Appointments Across FF12
Industries

The table reports the number (Number) and percentage (%) of outside
director appointments across the 12 Fama-French industries for all
director appointments, appointments of directors with industry
experience, and appointments of directors without industry
experience. The sample period is 2005-2010 and includes a total of
688 outside director appointments to boards of S&P 500 firms.
Utilities companies (SIC Codes 4900 to 4942) are excluded from the
sample. As such, there are no observations in Fama-French Industry 8
(Utilities).

                                                 Experienced
                              All Director         Director
                              Appointment        Appointment
                             Announcements      Announcements

Ind.          Name          Number      %      Number      %

1      Consumer               65       9.45%     26       6.95%
         (Non-durables)
2      Consumer               10       1.45%      1       0.27%
         (Durables)
3      Manufacturing          90      13.08%     45      12.03%
4      Oil                    29       4.22%     11       2.94%
5      Chemicals & Allied     31       4.51%      9       2.41%
         Products
6      Business              141      20.49%     89      23.80%
         Equipment
7      Telephone &            22       3.20%      8       2.14%
         Television
         Transmission
8      Utilities               0       0.00%      0       0.00%
9      Wholesale              61       8.87%     27       7.22%
10     Healthcare             66       9.59%     33       8.82%
11     Finance               108      15.70%     80      21.39%
12     Other                  65       9.45%     45      12.03%
Sum                          688     100.0%     374     100.0%

       Non-Experienced
           Director
         Appointment
        Announcements

Ind.   Number      %

1        39      12.42%
2         9       2.87%
3        45      14.33%
4        18       5.73%
5        22       7.01%
6        52      16.56%
7        14       4.46%
8         0       0.00%
9        34      10.83%
10       33      10.51%
11       28       8.92%
12       20       6.37%
Sum     314     100.0%

Table III. Company Characteristics

Panel A of the table reports several company characteristics of S&P
500 firms that announce the appointment of a new outside director to
the board for all outside director appointments in our sample. Panel
B provides the differences in company characteristics between firms
that announce the appointment of experienced directors and firms that
announce the appointment of non-experienced directors. The test for
differences in means is based on a standard 6-test and the test for
differences in medians is a Wilcoxon signed-rank test. The sample
period is 2005-2010 and the sample includes a total of 688 outside
director appointments announced by 360 companies in 607 firm-years.
Definitions and data sources of all of the variables are provided in
the appendix.

Panel A. Company characteristics for all outside director
announcements

                                            Mean        Median      N

Total assets (mill. USD)                 46,443.21    11,111.50    688
Market capitalization (mill. USD)        24,750.51    10,307.07    688
Net income (mill. USD)                    1,249.36       532.48    688
MTB ratio                                     3.43         2.62    688
ROA                                           5.57%        5.95%   688
E-Index                                       2.88         3.00    675
Institutional ownership                      79.58%       82.35%   688
Board size                                   10.59        10.00    651
CEO-Chair (dummy)                             0.65         1.00    651
CEO in nom. com. (dummy)                      0.15         0.00    688
% of independent outside directors on        83.31%       85.71%   651
  the board
% directors with experience                  54.39%       55.05%   688

Panel B. Tests for difference in means and medians of company
characteristics between announcements of experienced and
non-experienced outside director appointments

                                                       Mean

                                              Difference    t-value

Total assets (mill. USD)                      12,334.53     1.20
Market capitalization (mill. USD)             -6,879.41    -2.10 **
Net income (mill. USD)                          -810.34    -2.89 ***
MTB-ratio                                         -1.02    -1.58
ROA                                               -2.53%   -3.41 ***
E-Index                                            0.09     0.81
Institutional ownership                            1.10%    0.89
Board size                                        -0.26    -1.55
CEO-Chair (dummy)                                 -0.07    -1.98 **
CEO in nom. com. (dummy)                           0.03     1.17
% independent of outside directors on the          1.28%    1.78 **
 board
% directors with experience                       20.00%   10.98 ***

                                                      Median

                                              Difference    z-value

Total assets (mill. USD)                      -2,424.64    -1.59
Market capitalization (mill. USD)             -3,174.92    -2.36 **
Net income (mill. USD)                          -276.95    -3.58 ***
MTB-ratio                                         -0.23    -0.79
ROA                                               -1.53%   -2.97 ***
E-Index                                            0.00     0.67
Institutional ownership                            2.94%    2.00 **
Board size                                        -1.00    -1.71 **
CEO-Chair (dummy)                                 -0.00    -1.97 **
CEO in nom. com. (dummy)                          -0.00    -1.17
% independent of outside directors on the          2.88%    1.33
 board
% directors with experience                       22.23%    9.99 ***

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table IV. Director Characteristics and Director Industry Experience

Panel A of the table reports several director characteristics for the
sample of 688 outside directors appointed to the board of S&P 500
firms from 2005 to 2010. Panel B provides information concerning the
directors' industry experience based on a comparison of the
appointing firm's Fama-French 12 industry classification with the
industry classifications of all past employers. The variable
measuring industry experience in working days is adjusted for
double-counting (i.e., if a director's past employment history
includes two simultaneous appointments in the same industry, we count
every such day as just one day of industry experience). Definitions
and data sources of all of the variables are provided in the
appendix.

                                             Mean      Median    N

Panel A. Director characteristics

Age                                           56.75    57.27    688
Number of additional directorships held        1.18     1.00    688
Gender
  male (dummy)                                81.83%            688
  female (dummy)                              18.17%            688
CEO (dummy)                                   22.53%            688
Independent (dummy)                           96.95%            688

Panel B. Director experience based on FF12 industries

Industry exp. (dummy)                         54.36%            688
Exp. employee (dummy)                         31.10%            688
Exp. inside director (dummy)                  24.71%            688
Exp. outs, director (dummy)                   30.96%            688
Industry exp. (days)                       2,819.61     1.00    688

Table V. Cumulative Abnormal Returns Around Outside Director
Appointments

The table reports the mean and median cumulative abnormal returns
(CARs) for the sample of 688 outside directors appointed to the board
of S&P 500 firms from 2005 to 2010, as well as the subsamples of
announcements of outside directors with and without industry
experience. The daily abnormal returns are calculated as the realized
return minus the expected return as estimated by a market model
estimated over a 200-day estimation window from t = -220 to t = -21.
The CARs are calculated over a two-day event window from t = 0 to t =
1. The table reports t-values based on a standard parametric t-test
and z-values based on a non-parametric Wilcoxon signed-rank test.

                                      N    Mean CAR   Median CAR

All outside director appointments    688    0.0834%     0.0195%
Subsamples
  Outside directors with             374    0.3193%     0.0582%
    industry experience
  Outside directors without          314   -0.1976%    -0.1617%
    industry experience
Difference between                          0.5169%     0.2199%
  industry-experienced and
  non-industry-experienced
  outside directors

                                     t-value    z-value

All outside director appointments     0.78       0.12
Subsamples
  Outside directors with              1.94 *     1.20
    industry experience
  Outside directors without          -1.55      -1.14
    industry experience
Difference between                    2.41 **    1.65 *
  industry-experienced and
  non-industry-experienced
  outside directors

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table VI. Cross-Sectional OLS Regressions of CARs on Industry
Experience Dummy Variable

The table reports results from cross-sectional OLS regressions of the
CARs on a dummy variable as to whether the newly appointed outside
director has industry experience in the FF12 industry of the
appointing firm. Column 2 includes a set of director control
variables, Column 3 employs director and firm controls, and Columns 4
and 5 use director, firm, and corporate governance controls. Column 5
also includes year and industry fixed-effects (not reported due to
space limitations). The industry fixed-effects are based on the Fama-
French 12 industry classification. The daily abnormal returns are
calculated as the realized return minus the expected return as
estimated by a market model estimated over a 200-day estimation
window from t = -220 to t = -21. The CARs are calculated over a two-
day event window from t = 0 to t = 1. The sample is comprised of 688
outside directors appointed to the board of S&P 500 firms from 2005
to 2010. Definitions and data sources of all of the variables are
provided in the appendix. The Lvalues are based on White (1980)
heteroskedasticity-robust standard errors and are reported in
parentheses.

                                   (1)           (2)           (3)

Constant                        -0.002         0.026         0.007
                               (-1.548)       (0.780)       (0.199)
Industry Exp. (dummy)            0.005 **      0.006 ***     0.007 ***
                                (2.479)       (2.722)       (3.101)
Age                                           -0.001        -0.001
                                             (-0.786)      (-0.743)
Age Squared                                    0.000         0.000
                                              (1.012)       (0.947)
# Add. Directorships                          -0.001        -0.002 *
                                             (-1.501)      (-1.749)
Male (dummy)                                  -0.005        -0.005 *
                                             (-1.620)      (-1.704)
CEO (dummy)                                    0.003         0.002
                                              (1.277)       (0.863)
Independent (dummy)                           -0.006        -0.005
                                             (-0.722)      (-0.627)
ln(Total assets)                                             0.002 *
                                                            (1.839)
ROA                                                          0.019
                                                            (1.143)
R&D/Sales                                                   -0.013
                                                           (-0.952)
Market-to-Book                                              -0.000
                                                           (-0.572)
E-Index
Institutional Ownership
In (Board Size)
CEO-Chair (dummy)
CEO in Nom. Com. (dummy)
% Independent Outside
  Directors
% Directors Older than 72
Director Non-attendance
Busy Board (dummy)
% Directors with Experience
Year and Industry                  No            No            No
  Fixed-Effects
Observations                       688           688           688
[R.sup.2]                         0.008         0.020         0.033

                                   (4)           (5)

Constant                         0.005         0.018
                                (0.108)       (0.348)
Industry Exp. (dummy)            0.004 **      0.005 **
                                (2.084)       (2.179)
Age                             -0.001        -0.001
                               (-0.473)      (-0.521)
Age Squared                      0.000         0.000
                                (0.699)       (0.711)
# Add. Directorships            -0.001        -0.001
                               (-1.249)      (-0.995)
Male (dummy)                    -0.005 *      -0.005
                               (-1.687)      (-1.543)
CEO (dummy)                      0.004         0.003
                                (1.459)       (1.394)
Independent (dummy)             -0.002        -0.002
                               (-0.282)      (-0.229)
ln(Total assets)                 0.001         0.000
                                (0.729)       (0.218)
ROA                              0.028 *       0.031 *
                                (1.686)       (1.812)
R&D/Sales                       -0.020        -0.021
                               (-1.539)      (-1.375)
Market-to-Book                  -0.000        -0.000
                               (-0.708)      (-0.479)
E-Index                         -0.000        -0.000
                               (-0.435)      (-0.323)
Institutional Ownership         -0.003        -0.005
                               (-0.302)      (-0.458)
In (Board Size)                  0.002         0.000
                                (0.312)       (0.040)
CEO-Chair (dummy)               -0.004 *      -0.004 *
                               (-1.826)      (-1.737)
CEO in Nom. Com. (dummy)        -0.003        -0.001
                               (-0.704)      (-0.222)
% Independent Outside            0.000         0.002
  Directors                     (0.004)       (0.122)
% Directors Older than 72       -0.003         0.002
                               (-0.227)       (0.167)
Director Non-attendance          0.018         0.014
                                (0.478)       (0.348)
Busy Board (dummy)              -0.000         0.000
                               (-0.110)       (0.018)
% Directors with Experience      0.004         0.001
                                (0.962)       (0.182)
Year and Industry                  No            Yes
  Fixed-Effects
Observations                       650           650
[R.sup.2]                         0.038         0.065

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table VII. Robustness Tests--Alternative Measures of Industry
Experience, Differences in Anticipation, Financial Firms, and Time x
Industry Fixed-Effects

The table reports results from cross-sectional OLS regressions of the
two-day CARs on different measures of industry experience of the
newly appointed outside directors. The measure of industry experience
in the first column is equal to one if the appointed director has
work experience in the same FF12 industry, equal to two if she has
work experience in the same FF48 industry, and zero otherwise
[Industry Exp. (FF12/FF48)]. The measure of industry experience in
the second column is the natural logarithm of one plus the number of
days of total industry experience in the same FF12 industry [Industry
Exp. (days)]. The measure of industry experience in Column 3 is the
percentage of segment sales attributed to FF12 industries in which
the newly appointed director has work experience [Segment Ind. Exp.
(%)]. Due to limited data coverage in the Compustat Segment database,
this variable is available only for 504 appointments. The measure of
industry experience in Column 4 is identical to Segment Ind. Exp. (%)
in Column 3, but observations without firm coverage in the Compustat
Segment database are classified into appointments with/without
experience based on the company's main industry [Segment/Main Ind.
Exp. (%)]. The measure of industry experience in Column 5 is a dummy
variable as to whether the newly appointed outside director has
industry experience in the FF12 industry of at least one segment of
the appointing firm or in the firm's main FF12 industry. Columns 6-8
use the standard measure of industry experience from Table VI (i.e.,
the dummy variable as to whether the newly appointed outside director
has industry experience in the same FF12 industry as the appointing
firm). All columns include a set of director, firm, and corporate
governance control variables, as well as year and industry
fixed-effects (not reported due to space limitations). Column 6
includes a 20-day CAR, calculated from t = -20 to t = -1, as an
additional explanatory variable [CAR(-20, -1)]. In Column 7, director
appointments to the board of financial firms (FF12 industry 11) are
excluded from the sample. Column 8 includes year x industry
fixed-effects. The industry fixed-effects are based on the
Fama-French 12 industry classification. The daily abnormal returns
are calculated as the realized return minus the expected return as
estimated by a market model estimated over a 200-day estimation
window from t = -220 to t = -21. The CARs are calculated over a
two-day event window from t = 0 to t = 1. The sample is comprised of
688 outside directors appointed to the board of S&P 500 firms from
2005 to 2010. Definitions and data sources of all of the variables
are provided in the appendix. The t-values are based on White (1980)
heteroskedasticity-robust standard errors and are reported in
parentheses.

                           (1)         (2)         (3)         (4)

Constant                 0.016       0.016       -0.011      0.019
                        (0.316)     (0.321)     (-0.150)    (0.375)
Industry Exp.            0.003 **
  (FFI2/FF48)           (2.192)
Industry Exp. (days)                 0.001 **
                                    (1.990)
Segment Ind. Exp. (%)                             0.005 *
                                                 (1.886)
Segment/Main Ind Exp.                                        0.006 **
  (%)                                                       (2.482)
Main/Segm. Ind. Exp.
  (dummy)
Industry Exp. (dummy)

CAR(-20, -1)

Director, Firm, and        Yes         Yes         Yes         Yes
  Governance Controls
Year and Industry          Yes         Yes         Yes         Yes
  Fixed-Effects
Year x Industry            No          No          No          No
  Fixed-Effects
Observations               650         650         504         650
R-square                  0.066       0.064       0.090       0.067

                           (5)         (6)         (7)         (8)

Constant                 0.020        0.018      0.066       0.028
                        (0.394)      (0.359)    (1.512)     (0.520)
Industry Exp.
  (FFI2/FF48)
Industry Exp. (days)

Segment Ind. Exp. (%)

Segment/Main Ind Exp.
  (%)
Main/Segm. Ind. Exp.     0.005 **
  (dummy)               (2.162)
Industry Exp. (dummy)                 0.005 **   0.004 *     0.005 **
                                     (2.082)    (1.692)     (1.972)
CAR(-20, -1)                         -0.022
                                    (-1.193)
Director, Firm, and        Yes         Yes         Yes         Yes
  Governance Controls
Year and Industry          Yes         Yes         Yes         No
  Fixed-Effects
Year x Industry            No          No          No          Yes
  Fixed-Effects
Observations               650         650         553         650
R-square                  0.065       0.069       0.069       0.H8

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table VIII. Robustness Tests--Generalist Skills, Education, Firm
Fixed-Effects, and Type of Industry Experience

The table reports results from cross-sectional OLS regressions of the
CARs on a dummy variable as to whether the newly appointed outside
director has industry experience in the FF12 industry of the
appointing firm. Columns 1-4 include a set of director, firm, and
corporate governance controls, as well as year and industry dummy
variables (not reported due to space limitations). Column 1 extends
the standard regression specification reported in Column 5 of Table VI
by adding the natural logarithm of one plus the total number of
different FF12 industries in which the newly appointed director was
previously employed throughout his whole work history [ln(# Industries
with Exp.)]. Column 2 includes the natural logarithm of one plus the
number of different companies the newly appointed director worked for
throughout his whole work history at the time of the appointment
[ln(# Firms with Exp.)]. Column 3 includes a count variable,
Education I, which is equal to one for below bachelor, two for
bachelor, three for non-MBA masters and MBAs, and four for doctoral
degrees (Ph.D., M.D., and J.D.), and a dummy variable if at least one
degree of the newly appointed director was obtained from an Ivy
League university [Ivy League (dummy)]. In Column 4, Educationl is
replaced by Education2, which is defined as the number of years of
education, with below bachelor defined as 12 years, bachelor as 16
years, non-MBA masters and MBAs as 18 years, and doctoral degrees as
21 years of education. In Column 5, we replace the year and industry
fixed-effects by year and firm fixed-effects. In Column 6, the dummy
variable as to whether the newly appointed outside director has
industry experience in the FF12 industry of the appointing firm is
split up in three measures of industry experience: 1) a dummy
variable as to whether the newly appointed director has work
experience as an employee/executive without board membership in the
same FF12 industry [Exp. Employee (dummy)], 2) a dummy variable as to
whether the newly appointed director has work experience as an
employee/executive with additional board membership in the same FF12
industry [Exp. Inside Director (dummy)], and a dummy variable as to
whether the newly appointed director has work experience as an
outside board member in the same FF12 industry [Exp. Outs. Director
(dummy)]. Column 6 also includes firm and year fixed-effects and
excludes financial firms for which the relevance of different types
of experience may differ from non-financial firms. The industry
fixed-effects are based on the Fama-French 12 industry
classification. The daily abnormal returns are calculated as the
realized return minus the expected return as estimated by a market
model estimated over a 200-day estimation window from t = -220 to
t = -21. The CARs are calculated over a two-day event window from
t = 0 to t = 1. The sample is comprised of 688 outside directors
appointed to the board of S&P 500 firms from 2005 to 2010.
Definitions and data sources of all of the variables are provided in
the appendix. The Lvalues are based on White (1980)
heteroskedasticity-robust standard errors and are reported in
parentheses.

                                      (1)          (2)         (3)

Constant                            0.017         0.019       0.016
                                   (0.336)       (0.383)     (0.321)
Industry Exp. (dummy)               0.005 **      0.004 *     0.004 **
                                   (2.037)       (1.951)     (2.070)
In(# Industries with Exp.)          0.000        -0.002
                                   (0.155)      (-0.552)
In(# Firms with Exp.)                             0.003
                                                (0.907)
Exp. Employee (dummy)
Exp. Inside Director (dummy)
Exp. Outs. Director (dummy)
Education1                                                   -0.001
                                                            (-1.181)
Education2

Ivy League (dummy)                                            0.001
                                                             (0.509)

Director, Firm, and Governance        Yes          Yes         Yes
controls
Year and Industry Fixed-Effects       Yes          Yes         Yes
Year and Firm Fixed-Effects            No          No           No
Observations                          650          650         648
[R.sup.2]                            0.065        0.066       0.067

                                      (4)          (5)         (6)

Constant                             0.020       0.111       0.080
                                    (0.405)     (0.767)     (0.495)
Industry Exp. (dummy)                0.004 **    0.006 *
                                    (2.085)     (1.771)
In(# Industries with Exp.)
In(# Firms with Exp.)
Exp. Employee (dummy)                                        0.010
                                                            (1.351)
Exp. Inside Director (dummy)                                 0.025 *
                                                            (1.815)
Exp. Outs. Director (dummy)                                  0.002
                                                            (0.253)
Education1

Education2                          -0.000
                                   (-0.992)
Ivy League (dummy)                   0.001
                                    (0.450)

Director, Firm, and Governance        Yes          Yes         Yes
controls
Year and Industry Fixed-Effects       Yes          No           No
Year and Firm Fixed-Effects            No          Yes         Yes
Observations                          648          650         553
[R.sup.2]                            0.067        0.538       0.532

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table IX. Cross-Sectional OLS Regressions of CARs Around Outside
Director Deaths on Industry Experience Dummy Variable

The table reports results from cross-sectional OLS regressions of the
CARs on a dummy variable as to whether the deceased outside director
has industry experience. Column 2 includes a set of director control
variables, Column 3 employs director and firm controls, and Column 4
uses director and firm controls, as well as year and industry fixed-
effects (not reported due to space limitations). The industry fixed-
effects are based on the Fama-French 12 industry classification. The
daily abnormal returns are calculated as the realized return minus
the expected return as estimated by a market model estimated over a
200-day estimation window from t = -220 to t = -21. The CARs are
calculated over a seven-day event window from t = -3 to t = 3.
Definitions and data sources of all of the variables are provided in
the appendix. The t-values are based on White (1980)
heteroskedasticity-robust standard errors and are reported in
parentheses.

                                       (1)           (2)

Constant                             0.013 **     -0.074
                                    (2.522)      (-0.512)
Industry Exp. (dummy)               -0.022 ***    -0.020 ***

                                   (-3.286)      (-2.859)
Age                                                0.002
                                                  (0.549)
Age Squared                                       -0.000
                                                 (-0.527)
# Add. Directorships                              -0.001
                                                 (-1.089)
Male (dummy)                                       0.007
                                                  (0.539)
CEO (dummy)                                       -0.005
                                                 (-0.342)
Independent (dummy)                               -0.003
                                                 (-0.347)
In(Total assets)

ROA

R&D/Sales

Market-to-Book

Year and Industry Fixed-Effects        No            No
Observations                           280           277
R-square                              0.036         0.043

                                       (3)           (4)

Constant                            -0.036        -0.091
                                   (-0.219)      (-0.555)
Industry Exp. (dummy)               -0.020 ***    -0.027 **
                                   (-2.753)      (-2.971)
Age                                  0.002         0.003
                                    (0.444)       (0.715)
Age Squared                         -0.000        -0.000
                                   (-0.424)      (-0.725)
# Add. Directorships                -0.002        -0.002
                                   (-0.844)      (-0.919)
Male (dummy)                         0.007         0.006
                                    (0.551)       (0.394)
CEO (dummy)                         -0.001        -0.000
                                   (-0.069)      (-0.028)
Independent (dummy)                 -0.005         0.003
                                   (-0.528)       (0.318)
In(Total assets)                    -0.004        -0.004
                                   (-1.540)      (-1.406)
ROA                                  0.002         0.009
                                    (0.076)       (0.296)
R&D/Sales                           -0.001        -0.002
                                   (-0.324)      (-0.881)
Market-to-Book                      -0.000        -0.000
                                   (-1.422)      (-1.308)
Year and Industry Fixed-Effects        No            Yes
Observations                           268           268
R-square                              0.052         0.132

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table X. Regressions of CARs Around Outside Director Deaths on
Industry Experience Dummy Variable--Sudden Deaths and Fixed-Effects

The first three columns of the table report results from cross-
sectional OLS regressions of the CARs on a dummy variable as to
whether the deceased outside director has industry experience.
Columns 1 to 3 differ in the definition of death events. In all three
columns, we attempt to capture sudden or unexpected deaths. In
general, we follow Nguyen and Nielsen (2010) and Falato et al. (2014)
and classify deaths as sudden when the cause of death is indicated to
be a heart attack, stroke, or accident. Moreover, we classify a death
as sudden when the specific cause is unreported, but the death is
described as unexpected or unanticipated or sudden. In Column 1, we
additionally classify deaths as events resulting from diseases with
low mortality rates, such as Lyme disease, diseases that may be
deadly for the elderly, but are unlikely to be reported to the public
immediately, such as pneumonia, or often result in a quick death,
such as an air embolism, or when the cause of death is indicated to
be due to causes incident to age or similar without reference to a
specific disease as the sudden deaths. In Column 2, we reclassify
pneumonia and other diseases, which may result from another disease
or a generally poor state of health, as expected death events. In
Column 3, we follow the strict definition as used by Nguyen and
Nielsen (2010) and Falato et al. (2014) to classify deaths as sudden.
The regression specifications in all three columns include a set of
director and firm control variables, as well as time and industry
fixed-effects. Column 4 reports the results from a regression of the
CARs on a dummy variable as to whether the deceased outside director
has industry experience including year and director fixed-effects.
The daily abnormal returns are calculated as the realized return
minus the expected return as estimated by a market model over a
200-day estimation window from t = -220 to t = -21. The CARs are
calculated over a seven-day event window from t = -3 to t = 3.
Definitions and data sources of all of the variables are provided in
the appendix. The Lvalues are based on White (1980)
heteroskedasticity-robust standard errors and are reported in
parentheses.

                                       (1)           (2)

Constant                             0.092        -0.022
                                    (0.321)      (-0.074)
Industry Exp. (dummy)               -0.028 *      -0.035 **
                                   (-1.867)      (-2.147)
Age                                 -0.003        -0.001
                                   (-0.416)      (-0.158)
Age Squared                          0.000         0.000
                                    (0.486)       (0.225)
#Add. Directorships                 -0.000        -0.002
                                   (-0.195)      (-0.978)
Male (dummy)                         0.019         0.060 ***
                                    (0.885)       (3.012)
CEO (dummy)                          0.009         0.004
                                    (0.557)       (0.218)
Independent (dummy)                  0.001         0.006
                                    (0.061)       (0.391)
In(Total Assets)                    -0.000         0.001
                                   (-0.021)       (0.192)
ROA                                  0.023         0.026
                                    (0.699)       (0.733)
R&D/Sales                           -0.000         0.000
                                   (-0.083)       (0.049)
Market-to-Book                       0.001         0.001
                                    (0.868)       (1.026)
Year and Industry Fixed-Effects        Yes           Yes
Year and Director Fixed-Effects        No            No
Observations                           100           86
R-square                              0.058         0.083

                                       (3)           (4)

Constant                            -0.048         0.028
                                   (-0.115)       (0.597)
Industry Exp. (dummy)               -0.047 ***    -0.027 *
                                   (-2.744)      (-1.772)
Age                                  0.000
                                    (0.004)
Age Squared                          0.000
                                    (0.029)
#Add. Directorships                 -0.003
                                   (-1.514)
Male (dummy)                         0.074 ***
                                    (3.612)
CEO (dummy)                         -0.010
                                   (-0.577)
Independent (dummy)                  0.004         0.022
                                    (0.238)       (0.916)
In(Total Assets)                    -0.002        -0.004
                                   (-0.405)      (-0.696)
ROA                                  0.044         0.043
                                    (1.115)       (1.261)
R&D/Sales                            0.000         0.005
                                    (0.174)       (1.581)
Market-to-Book                       0.003        -0.000
                                    (1.587)      (-0.601)
Year and Industry Fixed-Effects        Yes           No
Year and Director Fixed-Effects        No            Yes
Observations                           69            127
R-square                              0.124         0.601

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.
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Author:von Meyerinck, Felix; Oesch, David; Schmid, Markus
Publication:Financial Management
Article Type:Report
Date:Mar 22, 2016
Words:17496
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