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«Elizabeth Blankespoor University of Michigan Stephen M. Ross School of Business blankbe January 2012 Abstract This paper examines the ...»

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Second, I contribute to the information processing costs literature. Many current studies examine the impact of investor processing costs on investor behavior in the markets (Casey 1980, Bloomfield 2002, Miller 2010). I extend the recent stream of literature that examines the impact of investor processing costs on firm behavior (Li 2008, Riedl and Srinivasan 2010) and provide evidence suggesting that firms increase disclosure when faced with anticipated reductions in investors’ processing costs. These findings increase our knowledge of the potential impact of information processing costs on market participants.

Third, I show unintended consequences of the XBRL regulation that are potentially favorable toward investors. The goal of the SEC is to reduce processing costs for those analyzing financial reports, not to alter disclosure; they specifically state in the XBRL mandate that disclosure requirements are not being changed. However, the results of my tests show that the anticipated decrease in investor processing costs spurs firms to provide more disclosure in the footnotes, resulting in a potentially beneficial unintended consequence of the XBRL regulation.

The paper proceeds as follows. The next section discusses the motivation and setting. Section 3 describes the sample and variable definitions, and Section 4 provides the research design and main empirical findings. Section 5 discusses results from additional tests and sensitivity analyses, and Section 6 concludes.

2. Motivation and Setting

2.1 Disclosure Choice and Investor Information Processing Costs To model firms’ disclosure choice, classic theories rely on the assumption of investor response to disclosure and non-disclosure. In a simple disclosure model, a firm weighs the costs and benefits of disclosure when choosing the amount of information to provide, where the benefits can include reduced information asymmetry and thus increased liquidity and decreased cost of capital. These disclosure benefits arise, however, when investors process and incorporate the information into their trading behaviors (Diamond 1985, Diamond and Verrecchia 1991). GE spokesman David Frail describes the disclosure choice as a negotiation between management and investors, alluding to the importance of investors actually acquiring and using the information: “[Disclosure] is a process, and we’ll be listening to everybody. But we have to measure the sheer volume of work against the value to investors of the information.” (Silverman 2002b).6 Disclosure choice can also be described in terms of the costs of non-disclosure. In a simple disclosure model, if firms do not disclose information, investors assume the worst case scenario and adjust price accordingly (Grossman 1981, Milgrom 1981). Anticipating this reaction from investors, firms choose to disclose the information, as long as the cost of investors’ negative reaction (i.e. cost of non-disclosure) outweighs the firm’s cost of disclosure. Thus, investor response is a critical assumption of these models as well.

Essentially, before firms can receive the benefit of disclosure, market participants must respond to the release of information. For investors to respond, though, they must acquire and process the information, and their ability to do so is limited by the extent of processing costs they face. In various contexts, numerous papers highlight that investors can face considerable processing costs that impair their ability to assimilate information in public disclosures (Casey 1980, Grossman and Stiglitz 1980, Merton 1987, Indjejikian 1991, Bloomfield 2002, Hirshleifer and Teoh 2003).

In recent years, there has been concern about high investor processing costs due to the length and complexity of financial reports (Paredes 2003, Li 2008, Miller 2010). More complexity in the information environment impacts market behavior through reduced investor trading (Miller 2010) and delayed impounding of information into price (You and Zhang 2009, Cohen and Lou 2010). In addition, when investors have extra information demands on them (e.g., busy earnings announcement days, Fridays), they do not completely process information (Hirshleifer, Lim, and Teoh 2009, DellaVigna and Pollet 2009). These studies provide evidence that investors rationally weigh the benefits of obtaining firm information against the costs of processing that information when deciding how much to process disclosures; the higher the processing costs, the less investor processing of firms’ disclosures.7 Although detailed financial information is costly to process, it is potentially very helpful for investors’ decision-making. For example, De Franco, Wong, and Zhou (2011) show that investors use information in financial statement footnotes to adjust their beliefs about firm value. Similarly, mosaic theory describes how the joint analysis of many individual information items can provide Payne (1976) provides a specific example of how individuals may decrease their information processing. In his experiment, individuals were given information about various apartments (e.g. rent, noise level, room size, etc.) and asked to choose one apartment. When he varied the number of apartments and pieces of information available for each, he found that participants changed their processing approach. For settings with few apartments and information dimensions, individuals looked at all the available information before deciding. As the number of apartments and information dimensions increased, however, individuals looked at only a subset of the information to make their decision. Following this logic, investors processing detailed and voluminous financial information are more likely to use an approach involving heuristics or summary statistics (i.e. ignore some information) because of the high costs of analyzing the detailed information.





valuable information (Pozen 2005). Individuals with access to detailed information and appropriate tools can use the information to make more informed decisions, as long as the processing costs do not outweigh the benefits of acquiring the information. Therefore, if investors’ costs of processing detailed information are reduced, they are more likely to demand and process detailed information.

The amount of investor processing impacts investor response to disclosure, and thus affects firms’ benefits of disclosure (and costs of non-disclosure), altering firms’ disclosure incentives. Essentially, if processing costs are high, investors will process less disclosure. With less information processing, investors have a muted response to disclosure (Bloomfield 2002) and are less able to identify nondisclosure. Conversely, lower processing costs imply more investor attention to disclosure, and thus higher benefits of disclosure and costs of non-disclosure for firms (Hirshleifer, Lim, and Teoh 2004).

If the impact on disclosure benefit and non-disclosure cost is significant, firms are motivated to increase their disclosure in response.

Increased Attention – Who and How This increased attention to disclosure (and pressure on firms) can come from investors or from any group acting on behalf of investors, such as media, analysts, or regulators. Examples of investor pressure include companies increasing their annual report disclosures in response to investors calling for more openness and transparency in their communications (Bulkeley 2002, Silverman 2002a).

However, analysts, media, and regulators also evaluate and monitor firm disclosure (e.g. Lang and Lundholm 1993, Miller 2006). In the XBRL setting, the SEC specifically highlights the cost-savings XBRL could bring to investors, analysts, and even the SEC itself for analysis of firms’ financial filings (SEC 2009).8 If firms anticipate increased scrutiny of their disclosures by any monitoring Also see http://raasconsulting.blogspot.com/2011/01/why-did-sec-mandate-xbrl.html for an article hypothesizing that the cost-savings for the SEC were a significant motivation for mandating XBRL.

group, they are more likely to increase disclosure in order to avoid the costs of more visible disclosure deficiencies and to receive the increased benefits of disclosure.9 Whether the monitoring parties are investors, analysts, media, or regulators, the disclosure of peer firms can be helpful in identifying incomplete or unusual firm disclosure. In Milgrom and Roberts’ (1986) model of too much relevant information, investors make a fully informed decision by investigating competitors’ disclosures and inferring the worst case scenario for any one firm’s missing information. Comparison to peers is also a way to motivate firms to provide more information. For example, after GE increased the detail of its 10-K footnote disclosures, analysts expressed appreciation and challenged other firms to follow suit: “GE has definitely raised the bar for all corporate reporting.” (Silverman 2002b).10 Peer firm disclosures are particularly relevant in the XBRL setting because XBRL’s standardized structure facilitates comparison across firms. If XBRL reduces the costs of comparing detailed disclosures across firms, investors are more likely to use peer firm disclosures to set expectations for the information firms should disclose. Thus, a reduction in processing costs is likely to lead to additional disciplining of firms and increased firm disclosure.

Current Literature Current studies examine the effect of investor processing costs on market behavior (as discussed above) or the effect of disclosure choice on investor processing costs, whether the choice is the writing style and amount of disclosures (Li 2008, You and Zhang 2009, Miller 2010), the placement of disclosures within financial statements or footnotes (Hopkins 1996, Hirst and Hopkins 1998, Davis-Friday, Folami, Liu, and Mittelstaedt 1999), or the timing of disclosures (DellaVigna and Pollet 2009, Hirshleifer, Lim, and Teoh 2009). Several papers have alluded to the fact that firms can Some practical examples of costs of non-disclosure include the loss of market value due to negative investor assumptions about missing information, loss of reputation for honesty or transparency, or even legal sanctions for newly discovered (real or perceived) deficiencies in disclosure. Examples of the benefits of increased disclosure include improved reputation for transparent disclosure, reduced information asymmetry, increased liquidity, and decreased cost of capital.

Dye and Sridhar (1995) also include peer firm disclosures in their disclosure choice model and provide several examples of herding or cascading disclosure choices among firms.

choose the complexity or presentation of disclosure with investor processing costs in mind. Li (2008) examines whether poorly-performing firms have more complex 10-K’s, and Riedl and Srinivasan (2010) examine firms’ decision of where to disclose special items (financial statements versus footnotes), using both information processing costs and signaling of information relevance as potential drivers of firm disclosure behavior.

However, papers have not directly examined the effect of investor processing costs on the amount of disclosure firms choose to provide, perhaps because it is difficult to disentangle whether investor processing costs altered the amount of disclosure, or the amount of disclosure altered the investor processing costs. To overcome this difficulty, I turn to the implementation of XBRL, which creates a unique setting of an exogenous shock to investor processing costs without changing the amount of required disclosure, providing the opportunity to identify the effect of anticipated investor processing costs on the amount of firm disclosure.

2.2 XBRL Background XBRL is a language used to encode financial information in a format that makes it easier for computer software to automatically acquire, classify, compare, and represent the information.

Essentially, companies use XBRL to identify data items within a financial statement, provide information about each one (such as its name, relevant time period, and currency; e.g. Total Liabilities, 12/31/2010, USD), and highlight relations between items (e.g. Total Liabilities = Current Liabilities + Non-Current Liabilities). Because each data item is “tagged” with this additional information, computer software can process XBRL filings with less human intervention. The information can then be organized in any format useful for analysis, such as across-time comparisons, across-firm comparisons, or detailed disaggregation of an account.

The SEC has long been interested in XBRL and interactive data formats, with the goal of using these technologies to help investors “capture and analyze [financial] information more quickly and at less cost” (SEC 2009). In April 2009, the SEC mandated that all public companies subject to filing requirements in the United States provide XBRL versions of their quarterly and annual financial reports in addition to the standard text or html filing. 11 The rule outlines a three-year implementation in phases. Large accelerated filers with a public common equity float over $5 billion (hereafter Tier 1 filers) begin the first phase of XBRL with filings for fiscal periods ending on or after June 15, 2009.

In the second phase, all other large accelerated filers (i.e. public common equity float over $700 million, hereafter Tier 2 filers) begin providing XBRL filings for fiscal periods ending on or after June 15, 2010, and for the third phase, all remaining filers (hereafter Tier 3 filers) provide XBRL filings for fiscal periods ending on or after June 15, 2011. In addition to the size-based phase-in, the mandate allows firms two years to fully adopt the mandate once they start filing XBRL documents.

For a company’s first year of XBRL filings, the rule only requires tags for quantitative items on the face of the financial statements and tags for each footnote in its entirety (“block tagging”). In the second and subsequent filing years, firms must individually tag all quantitative amounts in the footnotes as well (“detailed tagging”).

2.3 XBRL and Investor Information Processing Costs XBRL data filings can help reduce processing costs for investors by providing information in machine-readable format, facilitating comparison across firms and time, and highlighting contextual information and relations between data items.



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