1
Human Resource Outsourcing: Performance of Service Providers
Maureen G. Butler Assistant Professor University of South Florida
Carolyn M. Callahan* Doris M. Cook Professor Sam M. Walton College of Business University of Arkansas-Fayetteville Rodney E. Smith Associate Professor California State University Long Beach
11/2/2007
*Please address correspondence to Carolyn M. Callahan, Department of Accounting, Business Building, 401, University of Arkansas, Fayetteville, AR 72701, Phone: (479)575-6126 Fax: (479)575-2863, Email:
[email protected] Please do not quote or distribute without the expressed permission of the authors.
2 Human Resource Outsourcing: Market Performance of Service Providers Abstract: Considerable anecdotal evidence suggests that there is a linkage between an organization's use of outsourcing and organizational performance. However, few empirical archival studies of the outsourcing–performance relationship have been conducted. This paper evaluates the market and operating performance for a rarely studied stakeholder in the outsourcing agreement: the human resource (HR) service providers. Due to their influence on the most important asset of the firm, human capital, we focus on HR providers performing all aspects of HR services, including HR management, HR technology, regulatory compliance, risk management, and payroll. We base our tests on transaction cost economics theory (Coase 1988; Williamson 1979, 1985) which predicts that the performance of the service provider firms should be influenced by the types of services provided and the risks and costs associated with performing those functions. Both experienced and inexperienced providers often undertake HR services that require asset specificity and assume additional risk. We first examine whether the market recognizes and reward the providers’ additional risks. Next we examine whether the risks undertaken by experienced and inexperienced service providers impact subsequent performance. Using a performance-matched sample, we examine our performance predictions in three ways: 1) market reaction to human resource contract announcements, 2) long-run market returns subsequent to those announcements, and 3) operating performance before and after those announcements. In examining one of the fastest growing trends in the business world today, namely outsourcing service providers, we find evidence of positive market reaction to HR service provider contract announcements, and we find some evidence of differential effects on subsequent performance. The results of this study may inform human resource service managers of the possible benefits of releasing outsourcing contract award information and also inform stakeholders of the possible economic ramifications of HR contracts on service providers.
3 I. INTRODUCTION Human resource (HR) outsourcing involves a contractual relationship between an outsourcing firm and a human resource service provider; however, most outsourcing literature investigates this contract from the perspective of the outsourcing or client firm and primarily relies on survey or case study methodologies. Excellent care of employees whose performance determines productivity and ultimately profitability is essential for any organization. The decision to entrust these sensitive and critical functions to an external provider is made cautiously. The selection of an appropriate provider is even more important as their capabilities determine the success of the agreement. This paper examines human resource outsourcing (HRO) and its associated impacts on capital market and operating performance from the perspective of the HR service provider. Human resource service providers perform a broad range of HR tasks, from routine processes to more complex functions. This is a rapidly growing industry. For example, McDougall (2005) reports that Delta Air Lines Inc. and Marriott International each signed seven-year deals to hand off their HR responsibilities to thirdparty service providers. Delta's deal with Affiliated Computer Services Inc. is worth $120 million; Marriott didn't disclose financial terms of its deal with Hewitt Associates. Earlier in 2005 in one of the biggest HR-outsourcing deals to date, British Telecom (BT) signed a 10-year, $575 million expansion of its HR-outsourcing contract with Accenture. The agreement covers a broad range of services for BT's 87,000 employees and 180,000 pensioners, one element of this study. The providers included in this study perform functions such as benefits administration, income and employment verification, workforce management and
4 employee communications, and HR information technology Upon entering into an outsourcing agreement, the client firm may transfer to the service provider the personnel and physical assets formerly used to perform the contracted HR services internally. These newly acquired human and physical assets can then be used by the provider to gain efficiencies in offering services to multiple clients. With few exceptions, academic research on outsourcing as a business strategy generally focuses on the outsourcing client firm rather than the service provider (Jenster and Pedersen 2000) and has relied largely on survey methods. In contrast, this study uses archival data to empirically examine the market wealth and performance effects of human resource outsourcing for HR service providers. Specifically, we examine capital market wealth effects using event study methodology, as well as examining long run returns for one, two, and three years after the outsourcing announcement. HR service providers may not experience immediate improved operating performance because implementation of outsourcing agreements takes time. Providers may incur initial set-up or investment costs that delay the expected increased profits as a result of acquiring a new client. Therefore, the market may have a long run response to outsourcing announcements by HR service providers and experience may have an effect. We find that the market responds favorably to less experienced providers’ HRO contract announcements, suggesting that new service providers entrants to the market may be perceived as bringing new and more efficient HRO solutions. We also examine the effect on operating performance by focusing on the relations between return on assets (ROA), return on sales (ROS), and asset turnover for both provider firms and a set of performance-matched firms. We follow Kothari et al. (2005)
5 to match provider performance against firms in the same industry (2 digit SIC) with similar ROA performance in the year prior to the outsourcing contract announcements. Although the results are mixed, we find some evidence that HR service providers outperform their counterparts, despite apparent losses in operating efficiency (asset turnover). This study is of interest to service providers and to regulators, who desire to understand performance factors to improve profitability and shareholder wealth as well as for monitoring purposes. The results of this research are also of interest to outsourcing or client firms as they evaluate and consider service providers for potential HR outsourcing contracts. Finally, investors may be interested in the buy and hold returns of these firms when evaluating potential investment options. We proceed as follows: in the next section, we provide background on outsourcing and develop theory based hypotheses; in the third section, we describe the research context; in the fourth section, we discuss results, and we then provide conclusions and limitations in the final section. II. BACKGROUND ON OUTSOURCING, THEORY, AND HYPOTHESIS DEVELOPMENT Background on outsourcing Comprehensive human resource outsourcing has its beginnings in the 1999 contract between BP and Exult in which Exult was contracted to assume management, ownership, and accountability of all global transactional and administrative human resource services for BP (Adler 2003). Since then, an industry has developed with firms specializing in more complex human resource services than payroll processing which is a routine service commonly performed by external providers even before 1999. Research
6 and consulting firms promote outsourcing and assist managers desiring to use this strategy. HR service provider firms eager to increase their market share expand their offerings through mergers and acquisitions, with the number of these types of transactions increasing from 64 in 1997 to 108 in 2004 (M & A Market Analysis: Human Resources Outsourcing Gaining Traction Fast 2003). The services offered by these specialized human resource firms is in demand as shown by a 2004 survey by the Society for Human Resource Management which reports that 60% of firms surveyed outsource at least one HR service (Esen 2004). Unlike information systems or logistics outsourcing, which are utilitarian functions, human resource services are critical to the success of an organization in that they uniquely affect firm performance through employee attitudes. Outsourcing HR functions influences employee satisfaction, motivation, productivity, efficiency, and customer service. These aspects of HRO make it uniquely important in understanding the effects of HRO on firm performance. Human resource outsourcing is touted as a cost saving strategy by consultants and providers. It is believed that firms which specialize in HR services offer lower costs than client firms can perform internally because of economies of scale, greater efficiency and higher levels of expertise (M & A Market Analysis: Human Resources Outsourcing Gaining Traction Fast 2003).1 Given that managers of potential client firms consider the
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The human resource services offered by HR service providers cover a wide range of activities including HR management which entails employee handbooks, manuals, compensation, and training; HR technology encompassing HR information systems, reporting, and payroll/benefits integration; regulatory compliance such as labor regulations and Sarbanes-Oxley requirements; risk management covering wellness, OSHA, workers’ compensation, and workplace security; and payroll processing including tax filing and direct deposit. The specific HR services examined in this study include staffing and hiring, benefits administration, income or employment verification, workforce management and employee communications, payroll and tax filing, learning or training, HR information technology, and end-to-end or comprehensive human resource services fall within the parameters of these broad HR service categories.
7 tradeoff between production costs (internal processing costs) and transaction costs (external processing costs) in determining whether to outsource a function (Grossman and Helpman 2002, 2005), HR service providers must also consider these costs in contract negotiations. Specialized human resource firms must either provide these services at a lower cost than the client firm can perform internally, provide a higher level of services to employees with an expected indirect impact on the client firm’s efficiency and profitability, or simply take over administrative functions allowing HR managers to focus on strategic human resource issues that create value for the firm.
Theory Human resource outsourcing announcements provide new information to the market that is quickly incorporated into the stock price according to the efficient markets hypothesis. To the extent that the HR outsourcing contract announcement changes expectations concerning future firm performance or cash flows, a change in stock prices in a short window around the release of this new information can be expected. While market efficiency explains the potential market response to an outsourcing contract announcement based on it providing new information to the market, transaction cost economics clarifies the transaction-specific factors that might influence investors’ expectations of increased cash flows as a result of new outsourcing contracts. Transaction cost economics (Williamson 1979) proposes that the attributes of asset specificity, uncertainty, and frequency2 possessed by an activity are determinants of
2
The attributes of transactions identified by Williamson (1979, 1991) are: Uncertainty – the expected variation in the demand for activities and the inability to monitor activities; Frequency – the volume or rate at which activities are performed; and Asset Specificity – the degree to which an asset can be redeployed to alternative uses and by alternative users without sacrifice of productive value (e.g. site, physical assets,
8 whether a client firm chooses to perform that function in-house or to contract with an external service provider. In part, the volume of human resource services demanded by client firms determines the potential revenue and profits of firms in the HR services industry. However, the particular attributes of the services offered might also influence the profitability of human resource services firms. For example, providing HR services requiring asset specificity could lead to higher profits for the service provider, but the investment required to provide unique services exposes the HR service provider to risks of incomplete contracts.3 HR service providers in this situation have the ability to charge higher service fees to compensate for that added risk and investment leading to higher profits (Grossman and Helpman 2002). Similarly, uncertain or unique human resource functions also provide opportunities for increased revenue for the HR service provider. Uncertain HR functions often vary in activity level or are difficult to monitor, such as meeting staffing requirements during “peak” activity periods of a client firm. Human resource firms might receive higher revenue to compensate for maintaining the level of flexibility to meet the client’s demands. Finally, in performing HR functions which occur frequently, such as payroll processing, human resource service providers can develop efficiencies and in some cases standardize processes across clients to experience economies of scale leading to reduced costs of providing the service. In addition to the factors influencing expected cash flows of human resource service providers based on the transaction cost economics attributes and the information
human assets, specialized training). The uncertainty and frequency definitions are from Widener and Selto (1999). 3 An example of a human resource service requiring asset specificity is a human resource information system that is designed, programmed, and configured to meet the specific needs of the client firm.
9 provided to the market in the form of the contract announcement, many other specialized business and theoretical factors determine whether the market will respond favorably to human resource service providers announcing new outsourcing contracts. HR service providers perform all aspects of human resource management including processes, policies, procedures, programs, and forms that are compliant with regulatory requirements. They are a service industry and offer specialized services that may be bundled or performed by separate providers. The provider is successful if they reduce the administrative burden associated with the HR function, eliminate duplicate processes to better utilize the client’s resources and provide critical data as the client requests so that the client can analyze trends and identify HR cost issues and other concerns. Human resource service providers that operate in this manner have the opportunity to expand their customer base and to command fees commensurate with providing high quality specialized services. Thus, investors have reason to expect increased operating performance after a new outsourcing contract announcement. Outside of the plentiful information systems outsourcing literature, previous accounting research in this area has examined internal audit outsourcing decisions and implications (e.g., Widener and Selto 1999; Caplan and Kirschenheiter 2000; Abbott et al. 2007; Speklé et al. 2007), sourcing in a manufacturing environment (e.g., Anderson et al. 2000), and the outsourcing decision (e.g., Roodhooft and Warlop 1999; Sartorius and Kirsten 2005) but not operating performance effects of outsourcing. Hayes et al. (2000) do examine the market response to information systems outsourcing announcements. Gao (2005) examines both outsourcing firms and providers and finds significant abnormal returns for outsourced service providers around the announcement, but not for a
10 sample of client firms. This paper contributes incrementally to the outsourcing literature by investigating market and operating performance effects using archival financial data on a rarely examined stakeholder in a specific sector of the outsourcing market, the human resource services provider. We provide additional evidence to that found in Gao (2005) by considering human resource services outsourcing specifically, by testing short run and long run returns around the contract announcement, and long run operating performance effects. The results inform investors of the potential outcomes of purchasing shares of HR service providers. Further, the results inform managers of the potential impact of announcing outsourcing contracts on share price. Hypotheses development Human resource outsourcing contract announcements provide new information to investors and in an efficient market should be quickly incorporated into the share price. From the human resource service provider’s perspective, contract announcements not only represent new business to the firm, but also provide additional information to the market concerning the type of services to be performed and the proficiency of the service provider that might influence future profitability. These announcements reduce information asymmetry and signal the market regarding expected future cash flows and should therefore affect the firm’s value and be reflected in the stock price. If investors expect provider performance to improve (decline) as a result of outsourcing human resource services, stock prices should rise (fall). The attributes of the contracted services likely influence expectations about future performance. Human resource service providers might be able to command higher fees for services requiring asset specificity or involving complexity or uncertainty.
11 Furthermore, services that are frequent or uncomplicated might allow the provider to develop efficiencies that reduce the costs of providing the service and thus increase profits. Through the broad range of HR processes, policies, procedures, and programs offered to clients, HR service providers can reduce clients’ costs, improve service to client employees, or relieve the client’s human resources managers of administrative functions enabling them to focus on strategic HR issues that create value. Investors might believe that specialized human resources firms that consistently announce new outsourcing contracts are successful at these tasks and expect these experienced HR service providers to perform well. Gao (2005) examines market response to both outsourcing firms and service providers and does not find significant abnormal returns for the sample of outsourcing firms as a whole. Service providers, however, do experience significant abnormal returns around the contract announcement. These empirical results along with the theoretical expectations founded on market efficiency, transaction cost economics, and the other industry specific factors influencing HR service provider performance suggest the following hypothesis. H1a: Human resource service providers experience positive abnormal returns around human resource outsourcing contract announcements. While market efficiency provides a basis for expecting a short term market response to outsourcing contract announcements by HR service providers, transaction cost economics and other industry specific factors give an explanation for long run market effects and other factors that might influence abnormal returns following a contract announcement. Performing functions that require specific assets has the potential to benefit HR service providers through increased revenues and market share.
12 In a test of Williamson’s (1979) attributes of uncertainty, frequency, and asset specificity, that are used to determine whether a process is outsourced or not, Widener and Selto (1999) find that management control services which deal directly with firm-specific, strategic assets and processes will be retained within the firm. Roodhooft and Warlop (1999) also find that managers consider asset specificity and sunk costs in the outsourcing decision process and perhaps do not make the optimal decision to outsource when they should because of this. Functions involving asset specificity described by Williamson (1979) may require proprietary knowledge that a firm is hesitant to relinquish to an outside provider or may entail specialized equipment or technical expertise that a firm does not possess. For example, human resource information technology requires specialized equipment and software that is configured and programmed to the specific needs of the outsourcing firm. The provider can potentially offer the service at a lower cost than the firm can perform internally, but the outsourcing firm incurs transaction costs which reduce the cost savings. These transaction costs are associated with finding a suitable partner and managing the contract. In the case of outsourcing involving asset specific functions, incentives for the provider to safeguard proprietary information or to meet specification requirements may outweigh the potential cost savings, resulting in increased revenue for the service provider. HR service providers may be able to offer services at lower costs than firms can perform internally, partly because of the collective pooling benefits by combining the uncorrelated demands of various client firms (Williamson 1979). If these functions requiring specific assets are unlikely candidates for outsourcing, then providers that do perform these types of services have the potential to receive higher revenues to some
13 extent because of the incentives received from the client to induce the provider to meet specific requirements or invest in particular assets. The role that asset specificity plays in outsourcing relationships suggests the following hypothesis: H1b: Abnormal returns around outsourcing announcements are increased when human resource service providers perform functions requiring specific assets. Furthermore, the market may reward firms with greater outsourcing experience. These firms have proven themselves to multiple clients. They should be able to leverage that experience to obtain greater profits or greater operating efficiencies. This suggests the following hypothesis: H1c: Abnormal returns around outsourcing announcements are increased when human resource service providers are experienced. While an event study empirically assesses how investors perceive and evaluate risks and shift expectations concerning future cash flows due to the release of new information, this effect may be immediate or long run depending on the business dynamics of the particular industry. If the new outsourcing announcement affects operating performance, and then the stock market, a long run market reaction is expected. The operating performance effect may be delayed because of time required to implement the contract and initial investment and set-up costs incurred by the provider. Consequently, market returns may improve only after the operating impact is realized. To investigate whether HR service providers experience a long run wealth effect, the following hypothesis is tested: H2: Human resource service providers experience positive long run returns following human resource outsourcing contract announcements compared to matched firms.
14 In addition to the potential revenue increase from performing services requiring specific assets, Levy (2005) explains that profits accrue from market share derived through the construction and protection of unique assets and capabilities, branding, and technology. Human resource service providers that can offer unique capabilities and specialized services to clients have the potential to dominate the market in that particular area. The mergers and acquisitions activity among HR service providers may be an indication of the increasing ability of providers to hold a larger portion of the market for a particular service either because of the size of the firm and the ability to provide a greater variety of services to more clients, or because it develops inimitable capabilities through its mergers and acquisitions. Grossman and Helpman (2002) explain that specialized input suppliers can experience greater profitability because their differentiation reduces the equilibrium volume of inputs and enhances the bargaining power of each input supplier in its bilateral relationship with a final producer, or in this case, the outsourcing firm. Moreover, the expected profits of providers decline with entry of other firms like it, because an increase in the number of providers in the market compared to the number of client firms reduces the likelihood of a match for each provider (Grossman and Helpman 2002). In addition to these arguments, other factors might influence the position of a human resource service provider compared to its competitors. HR service providers that are able to successfully reduce the administrative burden of performing HR functions internally, aid clients in improving efficiency and quality in providing HR services to employees, and are responsive to clients’ information needs might develop a reputation that affords them the opportunity to expand its market share. Thus, the nature of the
15 services provided as well as the providers’ experience in those services should affect firm operating performance. This suggests the following hypotheses: H3a: Operating performance subsequent to contract announcements is higher for firms that provide services requiring specific assets. H3b: Operating performance subsequent to contract announcements is higher for firms that are more experienced in providing outsourcing services. III. SAMPLE SELECTION AND EMPIRICAL MODELS Sample Selection A search for outsourcing announcements using Business Wire on LexisNexis yielded a sample of 485 human resource outsourcing announcements. Some HR service providers announce more than one agreement in a single announcement so the total number of announcements represents each provider-client relationship as opposed to each individual announcement. Of the 485 announcements representing the same number of individual outsourcing contract relationships, 201 are for government, privately-held, or other provider firms for which Compustat data is otherwise unavailable, leaving a total of 284 announcements with Compustat data as indicated in Table 1. ---------------------------------Insert Table 1 here ---------------------------------For each of the 284 announcements, we matched on industry and return on assets (ROA) performance in the year prior to the outsourcing announcement following Kothari et al. (2005). We selected matching firms with the lowest absolute percentage difference in ROA if that difference was less than 10%. This process allowed us to match performance for 221 of the 284 announcements. In many cases, each provider firm was
16 involved in multiple announcements, so we collapsed the provider and matching firm information to specific firm-years based on mean values. This collapsing resulted in 86 announcement firm-years with 67 of those with matching information. Panel B of Table 1 describes the number of firm-year announcement observations by calendar year. Although the announcements are distributed throughout the 1994 to 2005 period, many of the firms made multiple announcements in the same general time frame. For the event study, we eliminated every announcement that overlapped with another announcement in either the estimation or event window. We used a 60 day estimation window that begins 70 trading days before each announcement and ends 10 days before the announcement. We used an event window that begins 5 days before the announcement and ends 5 days after the announcement. This process produced 95 events with complete event windows around the announcement. These announcements often involve major contracts and there is little evidence that information leaked prior to the event window. We also ran tests based on longer estimation and event windows. Although those longer windows reduced the number of available, non-overlapping, events, the results were similar. Panels C and D of Table 1 describe the 284 announcements in terms of the industry of the provider firm and the services contracted. As expected, the majority of providers are in the Business Services industry and the Engineering, Accounting, Research, Management and Related Services industry (SIC 87), but other industries are also represented. The announcements specify a variety of HR services, including staffing and hiring, benefits administration, workforce management and employee communications, and payroll and tax filing. Many contracts specify more than one
17 service making the total number of services contracted greater than the total number of announcements and outsourcing firms. To proxy for asset specificity, we classified the services into two groups according to complexity and value-added properties. More complex activities that provide greater value were identified as asset specific (Workforce management and employee communications, learning or training, information technology, comprehensive services). That is, we expect these activities to require a greater investment by the provider to customize services for the client. Less complex and lower value-added activities such as staffing and hiring, benefits administration, income or employment verification, and payroll functions are activities that do not require specific assets but rather assets that are easily transferrable to other clients.4 A summary of the announcements by type of service is shown in Panel D. Table 2 presents the descriptive statistics comparing the HR service providers and the control sample of matched firms. Panel E of Table 2 describes the prior performance characteristics used for matching. The mean difference in performance was approximately 2.3% and the distributions (25th percentile, median, 75th percentile and standard deviation) are virtually identical. Despite the performance similarities, provider firms tend to have greater sales revenue on average than the matched firms. Providers also tend to have higher return on equity (ROE) but lower return on sales (ROS) and asset turnover (Asset_Turn) than matching firms. The lower asset turnover indicates that provider firms are generally less efficient than their counterparts. Perhaps this results
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TPI presents a graphical presentation of HR services and their candidacy for outsourcing based on complexity and value-added properties (TPI 2007).
18 from required investments in specific assets; nevertheless, it runs counter to many of the arguments that provider firms can perform services more efficiently. Event study methodology We examine the effect of human resource outsourcing announcements on stock prices in the short term using event study methodology. We use a single factor market model to estimate abnormal returns. We select short estimation windows as described earlier to maximize the number of non-overlapping events. While estimation periods of 200 days are common in capital markets research, shorter estimation periods are also used (e.g., Affleck-Graves et al. 2002). The daily value-weighted return from the CRSP database approximates the market return and is used to estimate the firm’s expected return had it not announced a new outsourcing contract. The value-weighted market return is used because it more accurately captures the total wealth effects experienced by investors (Fama 1998). The following ordinary least squares regression is estimated. Rit = !i + "iRmt + #it
(1)
where: Rit = !i and "i = Rmt = #it =
daily return for firm i at time t market model parameters for firm i value-weighted market return at time t the unexpected return with a mean of zero and variance!
2 i
where t = days
We estimate abnormal returns for each firm day in the announcement period event window: ARit = Rit – (!i + "iRmt)
(2)
19 We calculate cumulative abnormal returns for each firm over several different event windows: k
CARi # " ARit
(3)
t# j
Statistical tests for the significance of cumulative abnormal returns are based on the standardized prediction error (Patell 1976).5 We then use regression analysis to test the effect of asset specificity and experience on cumulative abnormal returns with the following model: CARit = ! +"1 Sizeit + "2 Prior_ROAit + "3 Experienced_dum + "4 Asset_Specific_dum + "5 Substantial_Amt + "6 RDINT + "7 ADVINT + #itt
(4)
where: CARit = cumulative abnormal returns for firm I and event t Sizeit = Firm market value Prior_ROAit = ROA in year before announcement Experienced_dumit = 1 if firm had previously announced at least three contracts, 0 otherwise Asset_Specific_dumit = 1 if contract requires specific assets, 0 otherwise Substantial_Amtit = 1 if contract specifies a value of $500 million or greater, 0 otherwise RDINTit = R&D expense divided by sales ADVINTit = Advertising expense divided by sales We also estimate Equation (4) with interaction terms (Experienced_dum x Prior_ROA) to see if both experience and prior performance affect market reaction. Additionally, we decompose ROA into ROS and Asset_Turn components to see if a particular performance factor exhibits more influence. 5
We also conducted tests based on the standardized cross-sectional method is used (Boehmer et al. 1991), but there is little cross-sectional overlap in our announcement windows, so results were similar.
20 Long Run Market Performance We compute one, two, and three-year holding period returns (BHRET) assuming that a security is purchased on the day after the outsourcing announcement (Kennedy and Affleck-Graves 2001) as follows: n
BHRETi # $ (1 % rit )
(5)
t #1
where n is 12, 24, or 36 months after the announcement date. We then test the difference in holding period returns for the outsourcing firms and the control sample using paired ttests and wealth relatives (Ritter 1991; Kennedy and Affleck-Graves 2001). Wealth_Rel = 1 + BHRETs of provider firms 1 + BHRETs of control sample firms
(6)
A wealth relative greater than 1 indicates that outsourcing firms outperform the control sample and less than 1, that outsourcing firms under perform the control sample firms. Operating performance Using the well-known DuPont analysis, we examine provider ROA, ROS, and asset turnover around contract announcements in comparison to the matched firm performance for the same period. The DuPont approach expresses return on assets in terms of margins and efficiency as follows: Return on Assets = [Income/Sales] x [Sales/Assets]
(7)
We conduct this comparison in three ways: 1) a univariate analysis of the difference between provider and matched firm performance for the year prior to the announcement and the subsequent four years, 2) a multivariate analysis of the difference between provider and matched firm performance before and after the announcements,
21 and 3) a multivariate analysis of provider performance controlling for matched firm performance around the contract announcements. The multivariate analyses allow us to examine the impact of the type of service and provider experience on subsequent performance. We employ variations of the following model for both analyses: ROAit = ! +"1 Sizeit + "2 Sales_Growth+ "3 Pre_Postit + "4 Asset_Specific_dum + "5 Non_Asset_Specific_dum + "6 Match_ROAit + "7 Experienced_dum + #itt
(8)
where: ROAit = Earnings before extraordinary items divided by assets Sizeit = Natural log of sales Sales_Growthit = Sales in year t divided by sales in year t-1 Pre_Postit = 1 after the announcement, 0 before Asset_Specific_dumit = 1 if contract requires specific assets, 0 otherwise Non_Asset_Specific_dumit = 1 if contract specifies only standard services, 0 otherwise Experienced_dumit = 1 if firm had previously announced at least three contracts, 0 otherwise Match_ROAit = Matching firm ROA IV. RESULTS Event study results Table 3 presents the short window event study results that suggest that human resource outsourcing contract announcements do impact stock price. Panel A of Table 3 shows abnormal returns and corresponding z-statistics by event day from five days before the announcement to 5 days after. Overall, the average abnormal return is significantly positive on the day after the announcement; however, the average abnormal return is significantly negative both 2 days prior to the announcement and 2 days after the announcement. Any activity quickly reverses. For firms providing non-asset specific
22 services, none of the abnormal returns are significantly positive, although the returns are significantly negative two days after the announcement. For firms providing asset specific services, there is a significant 1.1% abnormal return on the day after the announcement and again significantly negative returns two days before and after the announcement. Comparing results for experienced and not experienced firms, the experienced firms show a 1.4% but not significant abnormal return on the announcement day, while the inexperienced firms see a significantly positive 0.8% return on the day after the announcements. The experienced firms suffer significant negative returns two days after the announcement, but the experienced firms do not. These results suggest that inexperienced firms benefit from publicly announcing HRO contracts, but this benefit does not persist as more contract announcements are subsequently made. Firms providing services requiring specific assets, and therefore a greater investment also benefit from announcing HRO contracts immediately the announcement, but as more information concerning the contracts are made available, this positive reaction reverses. ---------------------------------Insert Table 3 here ---------------------------------Panel B of Table 3 shows cumulative abnormal returns over various windows around the announcement dates. In general, the strongest positive cumulative abnormal returns are found over the period from the day before the announcement to the day after. Longer window CARs are generally negative, although the not experienced firms see positive returns over all windows. Together with Panel A, these results provide support for hypothesis H1a. Providers do experience significant abnormal, but temporary, returns
23 immediately around the announcement date. Firms providing asset specific, services do see significant positive returns, but only on the day after the announcement. This provides limited support for hypothesis H1b. Experienced firms do not enjoy positive returns around the announcements contravening hypothesis H1c. The strongest results are for the less experienced firms for which the market reacts positively to HRO contract announcements both on the day after and over the two and three day event windows around the announcement data. These results suggest that perhaps announcements by experienced firms are not considered new information by the market, but announcements by inexperienced firms are new information upon which the market can formulate expectations about future cash flows. Panel C of Table 3 presents results from a regression analysis of cumulative abnormal returns over the 3 days starting one day before the announcements. We collapsed the CAR[-1, 1] values to the mean value for each firm-year, which reduces the number of observations from 95 to 71, but avoids double counting results for the same firm. Column (1) examines only the effect of size and prior performance on cumulative abnormal returns. Size (log of market value) is negatively related and prior ROA is positively related to the 3 day cumulative abnormal return. Column (2) adds features of the contract and the firm’s experience to the model. Neither experience, asset specificity, or the size of the contract, are significant. Column (3) adds interaction terms between provider experience and prior performance.6 The interaction term is significantly negative, suggesting that the market does not reward experienced providers for prior performance, but does reward the less experienced firms. This further suggests
6
We also tested interactions between uncertain contracts and both prior performance and sizes, but none of the interactions were significant.
24 differences in the information environments and market expectations for the two categories of firms. Column (4) decomposes ROA into ROS and asset turnover with similar results. In general, Panel C results contravene hypotheses H1b and H1c; the market does not differentially reward asset specific service providers or experienced providers, but it does appear to reward firms with fewer publicly released HR outsourcing announcements. Long term market returns results Table 4 presents long-term buy and hold returns for provider firms compared to the matched firms. In each case, we accumulated returns for 12, 24, or 36 months beginning at the end of the month of the announcement. We then summarized the data using mean values for each firm-year. In general, while reversals occur, returns are higher for provider firms than for the corresponding matching firms. Mean values for wealth relative are greater than one for all three years, but the median values are not as consistently so. Wealth relative performance tends to be higher for firms undertaking uncertain contracts consistent with hypothesis H1b and for experienced firms consistent with hypothesis H1c. We recognize that the firms are matched on performance not risk, so the differences may be due to differences in risk between the providers and the matched sample. Conversely, the provider firms tend to be larger, which argues that those firms should be lower risk. ---------------------------------Insert Table 4 here ----------------------------------
25 Operating performance results Panel A of Table 5 presents the univariate comparison of provider firm performance against the matched firm performance. For each year around the announcement date, we subtracted matched firm performance from the provider firm performance. Overall, there is little difference in ROA following the announcements. The exception is the performance of the experienced firms, which have significantly higher performance in the one, two, and three years following the announcements. Typically, the provider firms have substantially lower asset turnover than the matched firms. The experienced firms tend to have higher margins to compensate for lower asset efficiency. Since the operating performance of providers in asset specific contracts is not significantly different from the matched firms, Panel A of Table 5 provides no support for hypothesis H3a. There are performance differences for experienced firms, however, so hypothesis H3b is supported. Panel B of Table 5 presents regression results for the difference between provider and matched firm performance for the one year before the announcement to two years after the announcement. Panel C of Table 5 presents similar results with separate observations for provider and matched firms. Panel B shows that firm experience and the asset specific nature of the contract services have little effect on relative performance, contravening both hypotheses H3a and H3b. Conversely, there is some evidence that firms entering contracts for non-asset specific services perform better. Panel C shows similar results. The coefficients on the Experienced_dum and Asset_Specific_dum variables are consistently negative although not significant. Neither experienced firms nor asset specific contracts result in better performance. Furthermore, there is little
26 indication of performance change after the contracts. In summary, the multivariate results do not support H3a or H3b. ---------------------------------Insert Table 5 here ---------------------------------V. CONCLUSION Outsource service providers are rarely the subject of outsourcing research. This study focuses specifically on human resource service providers that perform critical and sensitive functions for client firms. We investigate market response to outsourcing contract announcements for these provider firms in the short term and long run. We examine both experienced and new entrants service providers. We find evidence of positive market reaction to HR contract announcements, and we find some evidence of differential effects on performance. This study first documents the relation between human resource outsourcing contract announcements and the market performance of human resource service providers. The results show that outsourcing announcements temporarily affect share price in the short term and that the market reward less experienced providers announcing HRO contracts. Over the long run, providers generally outperformed matched firms over the subsequent one, two, and three years following the announcements. Experienced firms and those providing asset specific services tend to perform better. The study also examines the impact of contracts on providers’ operating performance relative to matched firms. There is some evidence that performance changes after contract announcements. This may be good news for potential clients. They can
27 assess the performance of candidate suppliers based on their performance before the contract. The results of this study are of interest to HR service providers who want to maximize shareholder wealth and to regulators that monitor outsourcing activities. Based on this sample of HR outsourcing announcements, the market appears to pay attention to this information and responds favorably to the news. The results of this study should be interpreted with caution because the sample sizes are less than 100 observations for some tests. All HR service providers are not publicly traded, so limiting the sample to those with data available on Compustat and CRSP eliminates a large number of firms in the industry. Additionally, the sample contains data only for firms that publicly release human resource outsourcing contract information. Some outsourcing contracts are not publicly released because the client firm does not want it known that they outsource HR services. This type of information might signal an inability to handle HR processing or invoke fear of pending layoffs or other organizational changes. Follow-up studies that examine a larger sample of outsourcing announcements will be more powerful. One way this can be accomplished is by expanding from human resource outsourcing to perhaps, business process outsourcing. Future research can investigate more fully the impact of the particular services offered, perhaps by broad categories of HR management, HR technology, regulatory compliance, risk management, and payroll on the provider’s operating and market performance.
28 TABLE 1 Sample Selection and Distribution of Announcements Panel A: Sample selection Individual announcements All announcements found
485
Less: government/private organizations without Compustat data
201
Total announcements with Compustat
284
Less: announcements with no performance match
63
Total announcements with matched firms
221
Announcement firm-years Total firm-years for announcements with Compustat
86
Less: firm-years with no performance match
19
Total matched announcement firm-years
67
Announcements for event study Announcements with non-overlapping windows and daily returns from CRSP
95
Panel B: Announcements by year Year
Announcements
Matched Firms
Non-Overlapping Events
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
1 1 39 6 14 44 14 14 40 43 20 48
1 1 39 6 14 8 11 13 30 39 20 39
1 1 2 4 4 7 11 9 15 12 9 20
Total
284
221
95
29 TABLE 1 (Continued) Sample Selection and Distribution of Announcements Panel C: Announcements by industry SIC
Industry
48 60 63 64 73 82 87
Communications Depository Institutions Insurance Carriers Insurance Services Business Services Educational Services Management Services
Number of Announcements
Total
1 1 2 2 91 1 186 284
Panel D: Announcements by type of servicea Non-Asset Specific Services Staffing and hiring activities Benefits administration Income or employment verification Payroll and tax filing Total certain services Asset Specific Services Workforce management and employee communications Learning or training Information technology Comprehensive services Total uncertain services ______________________ a
Many contracts specified more than one type of human resources service.
52 57 79 77 265
52 19 31 11 113
30
TABLE 2 Descriptive Statistics Panel A: All Provider Firms Variable
Mean
Std._Dev.
25th percentile
Median
Sales Assets EBEI ROA ROS Asset_Turn Debt_Ratio ROE
2517.159 3467.617 141.446 0.007 -0.022 0.975 0.082 0.082
4342.463 6724.884 285.540 0.122 0.265 0.607 0.108 0.563
104.072 213.990 -0.710 -0.009 -0.011 0.516 0.001 0.018
650.658 941.442 34.536 0.042 0.047 0.921 0.040 0.097
75th percentile 2288.800 3434.702 145.691 0.073 0.092 1.251 0.124 0.162
N 86 86 86 86 86 86 86 86
Panel B: Provider Firms with Matches Variable
Mean
Std._Dev.
25th percentile
Median
Sales Assets EBEI ROA ROS Asset_Turn Debt_Ratio ROE
2940.900 3982.953 172.026 0.013 0.008 1.014 0.081 0.104
4813.509 7486.739 313.056 0.117 0.142 0.642 0.107 0.628
73.832 179.101 -0.710 -0.012 -0.012 0.516 0.001 0.018
798.268 1182.221 37.292 0.041 0.047 0.917 0.042 0.118
75th percentile 2713.137 3958.338 177.021 0.075 0.093 1.271 0.124 0.190
N 67 67 67 67 67 67 67 67
31
TABLE 2 (Continued) Descriptive Statistics Panel C: Matching Firms Variable
Mean
Std._Dev.
Sales Assets EBEI ROA ROS Asset_Turn Debt_Ratio ROE
1088.907 4298.064 199.951 0.021 0.387 1.274 0.169 -0.048
3003.084 25704.340 804.307 0.169 3.067 0.684 0.291 0.508
25th percentile 30.646 41.502 -2.747 -0.068 -0.035 0.703 0.000 -0.203
Median 155.196 98.566 1.425 0.017 0.018 1.232 0.027 0.045
75th percentile 338.380 196.121 17.770 0.104 0.092 1.821 0.218 0.135
N 67 67 67 67 67 67 67 67
Panel D: Combined Provider and Matching Firms Variable Sales Assets EBEI ROA ROS Asset_Turn Debt_Ratio ROE
Mean
Std._Dev.
1887.789 3869.456 163.484 0.011 0.168 1.160 0.108 0.064
3852.867 17669.650 573.334 0.134 2.035 0.885 0.200 0.521
25th percentile 71.902 87.743 -1.954 -0.014 -0.021 0.530 0.000 -0.037
Median 344.318 369.013 10.067 0.033 0.043 1.016 0.030 0.087
75th percentile 1620.978 1916.530 94.277 0.075 0.086 1.505 0.139 0.165
N 153 153 153 153 153 153 153 153
32
Panel E: Performance in Matching Year Variable Mean ROAit-1 Match_ROAit-1 Diff%
0.013 0.013 0.023
Std._Dev. 0.199 0.199 0.028
________________ All statistics for announcement year except performance matching; Sales = Assets = EBEI = ROA = ROS = Asset_Turn = Debt_Ratio = ROE = Match_ROA = Diff% =
total annual revenue (Compustat item 12); total assets (item 6); earnings before extraordinary items (item 18); ebei/total assets; ebei/sales; sales/assets; long-term debt (item 9)/assets; ebei/stockholders’ equity (item 216); ROA for matching firm; absolute value of (ROA – match_ROA)/ROA.
25th percentile -0.003 -0.003 0.003
Median 0.044 0.044 0.007
75th percentile 0.076 0.076 0.045
N 67 67 67
33 TABLE 3 Market Reaction around Human Resource Outsourcing Announcements Panel A: Abnormal returns by day Non_ Asset_ Specificb
Event day
All Firms
-5 -4
0.002 0.000
0.029 0.211
-0.001 0.007
-3
0.002 0.010 0.002 0.008 0.007 0.004 0.001 0.006 0.002
-0.269
-0.002
-3.376 0.864 0.854 2.406
-0.008 0.004 0.008 -0.003
-2.912 0.739
-0.014 0.000
-1.607 0.367
-0.006 0.013
-2 -1 0 1 2 3 4 5 # obs/ day
za
95
za
za
Not Experienced
z
-0.002 0.004
-0.967 0.266
0.004 -0.002
0.794 0.059
-0.240
-0.007
-1.844
0.008
1.101
-0.009 0.001 0.007 0.011
-3.250 0.412 0.419 2.213
-0.011 0.007 0.014 0.005
-2.152 1.203 0.444 0.373
-0.010 0.000 0.004 0.008
-2.603 0.155 0.737 2.763
-0.003 0.003
-2.928 1.331
-0.015 0.017
-4.705 3.259
0.003 -0.009
-0.015 -1.612
-0.005 -0.003
-0.975 -0.223
-0.003 0.003
-1.126 0.593
-0.007 0.002
-1.159 0.003
Asset_ Specificb
0.547 0.784 1.136 0.779 0.882 0.836 0.901 3.799 0.175 1.548 1.647
66
za
Experienced
0.002 -0.004
-0.091 -0.478
0.003
39
36
59
Panel B: Cumulative abnormal returns
CAR
All Firms
[0,1] [-1,1] [0,2] [0,5] [5,5]
0.015 0.017 0.011 0.009 0.005
# obs
95
a
za 2.299 2.375 0.194 -0.071 -0.816
Non_ Asset_ Specificb 0.006 0.010 -0.008 -0.001 -0.001 66
za 1.229 1.510 -1.194 -0.734 -0.780
Asset_ Specific b 0.017 0.019 0.014 0.009 0.002 39
za 1.853 1.751 -0.180 -0.075 -1.154
Experiencedc 0.018 0.025 0.004 0.021 0.012
za
Not Experiencedd
0.563 1.153 -2.261 -0.488 -1.409
36
Z statistic values based on Patell 1976 (see e.g., Eventus User Guide). Some contracts involved both certain and uncertain services. c Experienced indicates events where firms have previously announced more than three contracts. d Not experienced indicates events where firms have not previously announced more than three contracts. brackets indicate event days over which the abnormal returns are accumulated. b
0.012 0.012 0.015 0.001 0.001 59
za 2.478 2.113 2.012 0.291 0.065
34 TABLE 3 (Continued) Panel C: Regression analysis of mean annual cumulative abnormal returns Independent variables Intercept Size ROA
(1) CAR[-1,1]
(2) CAR[-1,1]
(3) CAR[-1,1]
(4) CAR[-1,1]
0.083 (1.93)* -0.010 (1.93)* 0.191 (3.22)***
0.074 (1.87)* -0.011 (2.06)** 0.218 (3.62)*** 0.009 (0.60) 0.013 (0.95)
0.080 (2.24)** -0.013 (2.38)** 0.407 (4.58)*** 0.021 (1.24)
0.073 (1.70)* -0.011 (2.13)**
Experienced_dum Asset_Specific_dum Experienced_dum x ROA Substantial_amt
0.006 (0.58)
-0.365 (2.39)** 0.013 (1.15)
0.048 (0.40) 1.917 (1.08)
0.006 (0.37) 0.280 (3.15)*** -0.196 (2.30)** 0.005 (0.30) 0.053 (1.47) 0.325 (1.67) -0.568 (0.30)
71 0.20
71 0.25
ROS Experienced_dum x ROS Asset_Turn Experienced_dum x Asset_Turn RDINT ADVINT
Observations Adj R-square
71 0.12
71 0.10
-0.043 (1.46)
_______________________________ Robust t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1% CAR[x, y] = cumulative abnormal returns; x and y indicate days over which accumulated (mean value for firm by year); Size = natural log of market value (Compustat item 25 * item 199); ROA = earnings before extraordinary items (item 18)/assets (item 6); Experienced_dum = 1 if firm had previously announced at least three contracts, 0 otherwise; Asset_Specific_dum = 1 if announcement involves asset specific services, 0 otherwise; Experienced_dum x ROA = interaction term; Substantial_amt = 1 if announcement specified that the value of the contract exceeds $500 million; ROS = earnings before extraordinary items (item 18)/sales (item 12); Experienced_dum x ROS = interaction term; Asset_Turn = asset turnover: sales/assets; Experienced_dum x Asset_Turn = interaction term; RDINT = R&D intensity: R&D expense (item 46)/sales (item 12), set to 0 if R&D missing in Compustat; ADVINT = advertising intensity: advertising expense (item 45)/sales (item 12), set to 0 if advertising missing in Compustat.
35 TABLE 4 Annual Buy and Hold Returns following Announcements
All Available Obs Return Variable
Mean
Median
Firms with 3 Years Returns #obs
Mean
Median
#obs
Provider Firms BHRETt+1
-0.039
0.038
59
-0.078
0.028
40
BHRETt+2
-0.019*
0.078
46
-0.017*
0.078
40
0.120
0.182
40
0.120
0.182
40
BHRETt+1
-0.012
0.027
59
-0.036
0.064
40
BHRETt+2
-0.150
0.007
46
-0.137
0.023
40
0.058
0.212
40
0.058
0.212
40
Wealth Relativet+1
1.152**
0.980
59
1.182**
0.889
40
Wealth Relativet+2
1.546***
1.240
46
1.571***
1.186
40
Wealth Relativet+3
1.848***
0.943
40
1.848***
0.943
40
BHRETt+3 Matched Firms
BHRETt+3 Comparison
Certain Contracts Wealth Relativet+1
1.197
0.882
18
1.214
0.914
15
Wealth Relativet+2
1.712**
1.482
16
1.698**
1.197
15
Wealth Relativet+3
1.747
0.850
15
1.747
0.850
15
Wealth Relativet+1
1.165*
1.013
27
1.261*
0.955
16
Wealth Relativet+2
1.798**
1.353
18
1.884**
1.353
16
Wealth Relativet+3
2.510**
1.307
16
2.510**
1.307
16
Wealth Relativet+1
1.198**
1.013
31
1.209*
0.897
24
Wealth Relativet+2
1.451**
0.973
25
1.486**
1.074
24
Wealth Relativet+3
1.757*
0.850
24
1.757*
0.850
24
Wealth Relativet+1
1.102*
0.939
28
1.140
0.805
16
Wealth Relativet+2
1.659***
1.545
21
1.697**
1.504
16
Wealth Relativet+3
1.984**
1.147
16
1.984**
1.147
16
Uncertain Contracts
Not Experienced Firms
Experienced Firms
__________________ Mean and median annual buy and hold returns following announcements summarized by firm announcement year *, **, *** significantly greater than matched firm returns at 10%, 5%, and 1% levels, respectively, using one-tailed ttest using values winsorized 5% to reduce the effect of outliers; BHRET = buy and hold returns (natural log of return + 1) for 1, 2, and 3 years after announcements; Wealth Relative = (provider BHRET + 1) divided by (matched BHRET + 1); Firm-specific subscripts (i) suppressed.
36 TABLE 5 Operating Performance Comparison Panel A: Univariate comparisons Provider Performance minus Matched Firm Performance
All
#obs
Experienced
#obs
Non_ Asset_ Specific
#obs
Asset_ Specific
&ROAt-1 0.000 67 0.000 30 0.000 23 0.000 &ROAt -0.008 67 0.000 30 0.008 23 -0.003 &ROAt+1 0.007 49 0.063 22 ** 0.017 20 -0.006 &ROAt+2 0.003 44 0.097 19 ** -0.017 19 -0.023 0.103 30 ** 0.153 13 ** 0.135 13 * 0.032 &ROAt+3 &ROSt-1 -0.093 67 -0.004 30 -0.235 23 -0.007 &ROSt -0.379 67 0.017 30 -1.048 23 -0.028 &ROSt+1 0.027 49 0.083 22 ** 0.036 20 0.002 &ROSt+2 0.080 44 0.274 19 * 0.007 19 -0.034 &ROSt+3 0.151 30 ** 0.384 13 ** 0.173 13 * 0.038 &Asset_Turnt-1 -0.190 67 ** -0.558 30 *** -0.318 23 * -0.035 &Asset_Turnt -0.377 67 *** -0.772 30 *** -0.529 23 ** -0.169 &Asset_Turnt+1 -0.428 45 ** -1.035 18 *** -0.724 18 * -0.228 &Asset_Turnt+2 -0.591 40 *** -1.271 15 ** -0.717 17 ** -0.658 &Asset_Turnt+3 -0.589 26 *** -0.905 9 ** -0.500 11 * -0.549 __________________ *, **, *** signify significance at 10%, 5%, and 1% respectively, one-tailed t-tests. & indicates difference between provider firm performance and matched firm performance for same year; Year t indicates years of announcements; See table 1 for definitions of variables; Values winsorized 5% to eliminate outliers; Firm-specific subscripts (i) suppressed.
#obs 34 34 23 20 14 34 34 23 20 14 34 34 21 18 13
** *
37 TABLE 5 (Continued) Operating Performance Comparison Panel B: Multivariate analysis of difference between provider and matched firm ROA around announcements Independent Variables Intercept Size Pre_Post Asset_Specific_dum Experienced_dum Non_Asset_Specific_dum
(1)
(2)
(3)
&ROA
&ROA
&ROA
-0.159 (2.06)** 0.017 (1.58) -0.014 (0.46) 0.036 (1.21) 0.058 (1.25) 0.056 (1.46)
-0.254 (3.47)*** 0.034 (3.48)*** -0.021 (0.69) 0.033 (1.39) 0.043 (1.42) 0.048 (1.71)* -0.698 (5.83)***
-0.246 (2.98)*** 0.034 (3.17)*** -0.022 (0.72) 0.033 (1.50) 0.040 (1.29) 0.050 (1.88)* -0.708 (5.92)*** -0.095 (0.31) -1.130 (0.35)
151 0.00
151 0.35
151 0.35
Match_ROA RDINT ADVINT
Observations Adj R-square ____________________________
Robust t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1% & indicates difference between provider firm performance and matched firm performance for each announcement for the year of the announcement and the two following years; summarized (means) by firm year; Firm-specific subscripts (i) and year (t) suppressed; ROA = earnings before extraordinary items (item 18)/Assets (item 6); Size = natural log of sales (item 12); Pre_Post = 0 for year before announcement, and 1 for all 3 years after announcement; Asset_Specific_dum = 1 if announcement involves uncertain services, 0 otherwise; Experienced_dum = 1 if firm had previously announced at least three contracts, 0 otherwise; Non_Asset_Specific_dum = 1 if firm had previously announced less than three contracts; 0 otherwise; Match_ROA = ROA of matching firm; RDINT = R&D intensity: R&D expense (item 46)/sales (item 12), set to 0 if R&D missing in Compustat; ADVINT = advertising intensity: advertising expense (item 45)/sales (item 12), set to 0 if advertising missing in Compustat .
38 TABLE 5 (Continued) Operating Performance Comparison Panel C: Alternate multivariate analysis of provider ROA performance around announcement years Provider Return on Assets (ROA) All Announcements Independent vars Intercept Size Sales_Growth RDINT ADVINT
HRO Pre_Post HRO x Pre_Post
Experienced_dum Asset_Specific_dum Non_Asset_Specific_du m
Observations Adj R-sq
Year t-1 to t+1
Year t-1 to t+2
-0.182 (4.32)*** 0.023 (7.02)*** 0.083 (3.26)*** -0.037 (0.35) -0.655 (0.96)
First Announcements
Year t-1 to t+3
Year t-1 to t+1
Year t-1 to t+2
Year t-1 to t+3
-0.229 (5.85)*** 0.025 (8.30)*** 0.104 (4.30)*** -0.013 (0.13) -0.097 (0.16)
-0.257 (6.93)*** 0.027 (9.58)*** 0.116 (4.94)*** 0.013 (0.13) 0.089 (0.16)
-0.176 (3.89)*** 0.024 (6.54)*** 0.077 (2.72)*** 0.014 (0.12) -0.727 (0.92)
-0.218 (5.26)*** 0.027 (8.05)*** 0.093 (3.54)*** 0.024 (0.21) -0.145 (0.22)
-0.242 (6.24)*** 0.029 (9.48)*** 0.100 (3.99)*** 0.031 (0.29) 0.028 (0.05)
-0.018 (0.86) -0.016 (1.00) 0.005 (0.22)
-0.019 (0.92) -0.020 (1.25) 0.006 (0.26)
-0.019 (0.91) -0.021 (1.34) 0.003 (0.13)
-0.034 (1.45) -0.023 (1.37) -0.001 (0.03)
-0.035 (1.45) -0.023 (1.42) -0.001 (0.05)
-0.033 (1.40) -0.024 (1.53) 0.004 (0.15)
-0.011 (0.87) -0.008 (2.49)**
-0.013 (1.02) -0.006 (2.18)**
-0.007 (0.58) -0.007 (2.25)**
-0.024 (1.31) -0.008 (1.92)*
-0.027 (1.71)* -0.006 (1.68)*
-0.018 (1.22) -0.006 (1.91)*
0.002 (2.11)**
0.003 (3.11)***
0.003 (3.34)***
0.002 (1.97)*
0.003 (3.01)***
0.003 (3.49)***
349 0.22
400 0.24
324 388 429 280 0.21 0.23 0.25 0.19 ___________________________ Robust t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1% Firm-specific subscripts (i) and year (t) suppressed. Analysis based on firm-year performance for providers around the announcement year; Studentized residuals > 3 dropped to reduce the effect of outliers; HRO = 1 if provider, 0 if matched firm; Sales_Growth = sales it year t divided by sales in year t-1; All other variables defined as in Panel B of Table 5.
39
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