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R&D INVESTMENTS, BOND RATINGS AND BOND RISK PREMIUMS

A THESIS

SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA

BY

CHARLES SHI

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTORAL OF PHILOSOPHY

Judy Rayburn, Adviser

August 2000

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UMI Number: 9980338

s2 UMI

UMI Microform9980338

Copyright 2000 by Bell & Howell Information and Learning Company All rights reserved This microform edition is protected against

unauthorized copying under Title 17, United States Code

Bell & Howell Information and Learning Company 300 North Zeeb Road

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UNIVERSITY OF MINNESOTA

This is to certify that I have examined this copy of a doctoral thesis by

Charles shi

and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final

examining committee have been made —

C m4 CS

CC,

: Judy Rayburn

Signature of Faculty Adviser

Date

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ACKNOWLEDGEMENTS

I gratefully acknowledge invaluable guidance and critiques from Judy Rayburn (adviser)

and Pervin Shroff Thanks also go to my other committee members: Chandra Kanodia and Matt Mitchell This paper benefited from comments of and discussions with David Aboody, Chun Chang, Charles Lee, Baruch Lev, Dawn Hukai, Anjit Mukherji, Stephen Penman, Bal Radhakrishna, Theodore Sougiannis, Andrew Winton, Peter Woodlock, and

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Abstract

The debate on whether corporate R&D investments should be capitalized as asscts or expensed as incurred begs the question: which effect dominates — the future benetits

from R&D investments or their riskiness? Extant R&D literature focusing on the relation between R&D variables and equity metrics is plagued with the inability of researchers to

address this question This is because both the benefits and riskiness of R&D have the

same directional impacts on the equity valuation of levered firms (Merton 1973, 194)

This study adds another dimension to the literature by assessing the combined effects of the future benefits and riskiness of R&D in the context of the bond market

Option pricing theory stipulates that the mean (expected future benefits) and the

variance (riskiness) of R&D investments play opposite roles in the pricing of bonds Relying on this theoretical framework, | document significant positive associations of

R&D variables with bond default risk and bond risk premium This suggests that, for creditors, the nsk of R&D appears to dominate the future benefits of R&D In other

words, creditors view R&D investments more like risk proxies than assets Since the bond market has remained to be the firms’ most significant external financing channel

(Anderson et al., 1994), and R&D investments have become increasingly important to the U.S economy, this paper generates new evidence for debates on the accounting treatment

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Table of Contents

Acknowledgments Abstract

Table of Contents

Part 1: Overview of R&D Accounting and Literature Review

Chapter |: Accounting for Research and Development Costs: An Overview Chapter 2: Issues in Accounting for Software Development Costs

Chapter 3: Literature Review and Current Debate

Part Il: R&D Investments, Bond Ratings and Bond Risk Premiums

Chapter 4: Introduction

Chapter 5: Contribution of This Study Chapter 6: Research Methodology

Chapter 7: Sample Selection and Descriptive Statistics

Chapter 8: Empirical Results Chapter 9: Conclusion

Part [11: Summary and Future Research Chapter 10: Summary and Future Research

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Appendix I: Summary of R&D Accounting Around the World

Appendix II: Effect of Capitalization on Variability of Software Development

Tables: Table 1: Table 2: Table 3: Table 4: Table 5: Table 6: Table 7: Table 8: Table 9:

Expenditures and Reported Earnings

Sample Composition and Averages of Some Key Variables

Descriptive Statistics for Selected Variables

Pearson Correlations

Results of SUR Estimation: Annual R&D Expenditures

Results of SUR Estimation: Multi-year R&D Constructs

Results of SUR Estimation: Adjusted Model

Results of SUR Estimation: Incremental Effects of Multi-year R&D Constructs over Annual R&D

Results of SUR Estimation: LS Measure

Differential Associations: Long vs Short Useful Life Samples Results of SUR Estimation: LS Measure

Controlling for Other Risk Factors

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Part I: Overview of R&D Accounting and Literature Review

Chapter 1: Accounting for Research and Development Costs: An Overview Accounting for Research and Development Costs

Expenditures devoted to developing a new product or process or to improving an

existing product or process are typically classified as research and development (R&D)

The Financial Accounting Standards Board (FASB) issued Statement of Financial Accounting Standards (SFAS) No 2 in October 1974 The Statement mandates that firms

expense R&D expenditures immediately as they are incurred, and that the aggregate amount of R&D costs’ be disclosed

The disclosure requirement is an important component of SFAS No 2 Many

firms previously did not report R&D expenditures as a separate line item in their financial

statements (Intermediate Accounting, 5" edition, Chasteen et al.), presumably fearing

that the disclosure of the information may reveal crucial proprietary knowledge to their competitors and jeopardize their competitiveness The FASB, supported by respondents

to the Discussion Memorandum, added the disclosure requirement to the Statement based on the belief that the R&D outlays are informative for assessing the firms’ future performance

Prior to the issuance of SFAS No 2, there were diverse practices of accounting

and reporting on R&D Due to the absence of regulatory guidance, firms enjoyed a great

deal of discretion on how to account for their R&D outlays Some firms chose to capitalize a certain portion of the R&D expenditures and to amortize them over some

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arbitrary period (no more than 40 years), while others opted to expense all R&D outlays as incurred According to the Disclosure Journal of Index of Corporate Events (annual edition, May 1973-April 1974), 560 publicly traded firms capitalized their R&D costs

Two factors prompted the FASB to reduce the flexibility allowed in reporting the firms’ R&D activities First, the existing diversity of practices created difficulties for cross-sectional comparative analysis of firms’ performance The FASB believed that a uniform accounting treatment of the R&D outlays would better serve the necds of financial statement users (SFAS No 2, paragraphs 54-55) Second, as R&D became an increasingly important cost component for many firms, the accounting choice of capitalization vs expensing could have a substantial impact on the firms’ financial statements (Vigeland, 1981)

Four alternative accounting methods were considered by the FASB: (1) expensing-all-R&D as incurred, (2) capitalizing-all-R&D as incurred, (3) selective capitalization capitalizing a portion of R&D costs if certain conditions are satisfied and

expensing all other costs, and (4) accumulation of all costs in a special category until the existence of future benefits could be established

The fact that firms invested a significant amount of their resources in R&D

programs suggested that the R&D activities, at least at an aggregate level, provided the

firms with future benefits such as increased revenue streams, high profitability and

market share gains However, there was typically a substantial degree of uncertainty regarding future benefits of individual R&D projects Also, the FASB, at that ume, saw

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typically involved many projects at different stages of completion These projects had

varying degrees of uncertainty about their success rates Hence, it would be difficult to

come up with any meaningful, and verifiable (auditable) amortization schedules if R&D were capitalized on a firm-wide basis These considerations led to the FASB’s disfavor of

the capitalizing-all-R&D option

The alternative proposals of selective capitalization and accumulation of costs in a

special category were rejected because the implementation of both proposals would require the identification of conditions, such as technological feasibility, that allow the

commencement of R&D capitalization The FASB did not believe that the establishment

of these conditions could be objectively and comparably made by all firms (SFAS No 3 p 55)

SFAS No 2 does not apply to R&D activities conducted under a contractual

arrangement or R&D costs specifically reimbursable under the terms of a contract In other words, if a firm performs R&D activities both on their own account and under a

government contract, the firm may capitalize and amortize the costs associated with the

contract but must expense the R&D costs related to its own business

The expensing-all-R&D approach required by SFAS No 2 was viewed by many

as a simple, practical, and conservative way of handling the uncertainty and measurement difficulties embedded in R&D activities More than two decades have passed since SFAS

No 2 was issued The Statement remains the only authoritative pronouncement

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An International Perspective

Expensing all R&D expenditures in the year they are incurred is an uncommon

practice around the world According to a survey compiled by Coopers & Lybrand (1993 see Appendix 1), only the United States, Germany and Mexico, 3 out of 33 listed countries, require immediate expensing of R&D expenditures The high degree of uncertainty involved in estimating the amount and timing of future benefits of R&D

investments, and the lack of a causal association between individual R&D projects and

the respective future benefits form the grounds for the use of immediate expense

recognition

The capitalization approach, an alternative to the expensing rule, is more widely used in the rest of the world Proponents of the capitalization treatment maintain that firms should be allowed to capitalize a portion of R&D costs, if a R&D project is assessed to be highly likely to lead to the successful introduction of a new product or process, and the future benefits flowing from the project can be reasonably estimated Proponents further argue that capitalization has two main advantages over expensing: (1) it provides a better matching between the expense and future revenue; and (2) the related

disclosure of capitalization and subsequent amortization may convey to financial statement users additional value-relevant information, such as the expected success rates

of R&D investments and estimated economic lives of capitalized R&D assets (Eccher

1997; Chambers et al 1998)

As indicated in Appendix I, 30 out of 33 surveyed countries permit capitalization

of varying portions of R&D expenditures if certain conditions are satisfied The

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commercial success of a product or a process under development The requirements are

less stringent for some countries like Italy and Brazil, where the accounting choice is

largely at a firm’s discretion as long as reasonable justification is provided In contrast

Canada, New Zealand, the United Kingdom, and International Accounting Standard (IAS) 9, Research and Development Costs, take the position that research expenditures

should be subject to immediate expensing, while development costs are allowed to be

capitalized conditional on the satisfaction of some pre-specified conditions The rationale is that it is the development process that eventually turns the viable research knowledge into a tangible product or process Since these countries’ criteria for capitalization are very similar to those contained in IAS 9, it is instructive to take a close look at [AS 9

Under [AS 9, all of the following conditions must be met in order for a firm to capitalize

the development costs:

(1) The product or process is clearly defined and the costs attributable to the product or process can be separately identified and measured reliably;

(2) the technical feasibility of the product or process can be demonstrated; (3) the enterprise intends to produce and market, or use, the product or process: (4) a market for the product or process exits or, if it is to be used internally rather than

sold, its usefulness to the enterprise, can be demonstrated; and

(5) adequate resources exist, or their availability can be demonstrated, to complete

the project and market or use the product or process {Paragraph 17, IAS 9]

The primary emphasis of IAS 9 centers around whether a project can pass the technological feasibility test and whether the firm has intentions and resources to complete the project and to make it commercially successful Given the substantial uncertainty inherent in R&D projects and their product markets, the implementation of the rule remains, to a large degree, a discretionary choice

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Chapter 2 Issues in Accounting for Software Development Costs An Exception to SFAS No 2

The software industry was in its infancy when SFAS No 2 was issued in October 1974 The FASB took the position that development of computer software should be

treated as a R&D activity and hence should be expensed as incurred according to SFAS No 2 The majority of software firms, following the issuance of SFAS No 2, expensed

software development costs in the year they incurred

However, many software companies questioned the applicability of the Standard to software creation activities They argued that not all of software development costs fell into the category of R&D expenditures In response to a growing number of complaints from the software industry, the FASB issued FASB Interpretation No 6, Applicability of FASB Statement No.2 to Computer Software in February 1975, and subsequently FASB Technical Bulletin No 79-2, Computer Software Costs in 1978 Interpretations of the two supplements were such that not all costs involved in software creation process are necessarily R&D This left the door open for software companies to capitalize a certain

portion of their development costs

As the software industry grew rapidly, more and more companies chose to capitalize their software development costs During the early 1980s, as many as 12 to 20 percent of software companies capitalized some portion of their software creation costs

(McGee 1988) Even though the FASB issued several pronouncements, such as FASB

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comparability of software companies’ performance In an attempt to curtail the diversity in practice, the SEC announced a moratorium on the capitalization of software

development costs in April 1983, which prohibited public companies from capitalizing software creation costs unless they had disclosed their practice previously The

moratorium remained effective until the issuance of SFAS No 86 in August 1985

The Accounting Standards Division’s Task Force of the American Institute of

Certified Public Accountants (AICPA) met to discuss accounting for the development

and sale of computer software in late 1982 Less than three years later, the FASB adopted SFAS No 86, Accounting for the Costs of Computer Software to be Sold, Leased, or Otherwise Marketed The Statement requires that costs involved in software creation be dichotomized according to the technological feasibility of the project Technological feasibility is typically established upon completion of a detailed program design or

working model All costs prior to the technological feasibility stage must be expensed as

incurred as R&D Software development costs incurred subsequent to the establishment of technological feasibility, labeled as software production costs in SFAS No 86, must be capitalized The capitalized software costs are also required to be revalued against their

net realizable value” on a product-by-product basis at each quarterly balance sheet date

and must be written down to net realizable value if the book value of the capitalized costs exceeds the net realizable value Amortization should be carried out on a product-by- product basis using the greater of revenue-based amortization or straight-line amortization over the remaining estimated economic life of the software

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SFAS No 86 excluded the development costs of software projects for internal use

because it was not perceived as a significant issue in financial reporting at that time

(Statement of Position 98-1, paragraph 1) As software developed for internal use became more common, the AICPA stepped in and issued Statement of Position (SOP) 98-1 Accounting for the Costs of Computer Software Developed or Obtained for Internal Use in March 1998 SOP 98-1 mandates the capitalization of development costs for internal-

use software in the application development stage; furthermore, it requires all software

costs incurred in the preliminary project stage be expensed as incurred The capitalized costs should typically be amortized on a straight-line basis The impairment test is required in accordance with SFAS No 121, Accounting for the Impairment of Long-Lived Assets and for Long-Lived Assets to be Disposed Of

Firm Characteristics of Capitalizers vs Expensers

SFAS No 86 allows flexibility in its implementation A software firm is required

to capitalize development costs only when technological feasibility has been established

and the expected net realizable value of a software product is assessed at higher than the book value of the capitalized costs Since significant subjectivity is involved in evaluating these capitalization requirements, firms have considerable discretion in determining whether to capitalize or expense software development costs

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capitalization usually outweighs the income-deceasing amortization To the extent that

managers may be motivated to choose an accounting method to maximize reported

accounting numbers,” firms have incentives to favor capitalization over expensing On the other hand, capitalizing soft intangibles is generally viewed as a less conservative accounting practice As a result, larger firms would incur higher political costs and are more likely to suffer a reputation loss if they chose the capitalization treatment (Daley and Vigeland, 1983) Concurring with the political cost hypothesis, anecdotal

observations indicate that software heavyweights such as Microsoft, Novell and Borland have consistently expensed their software development costs

Since software firms may self-select their software reporting methods, it is

interesting to determine firm attributes that distinguish software capitalizers from expensers Drawing from the literature on the debate of the SFAS No 86, Aboody and

Lev (1998) evaluated the ability of six firm-specific attributes to discriminate between software capitalizers and expensers: firm size, software development intensity (the ratio of annual software development costs to sales), profitability, profitability change

leverage, and a systematic risk factor Using 163 sample firms during 1987 to 1995, Aboody and Lev (1998) found that firm size, profitability, and software development

intensity are significantly associated with firms’ accounting choice In particular, smaller, less profitable firms with higher software development intensity are more likely to capitalize software development costs in their sample

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Software Firms’ Change of Attitude Toward SFAS No 86

The issuance of SFAS No 86 in 1985 was a result of two factors: overwhelming

support for the capitalization treatment by software companies, and, intensive lobbying

efforts by the then software trade group of - ADAPSO (The Association of Data Processing Service Organizations) The managerial motives to fight for the right to capitalize software development expenditures are quite transparent Capitalization typically results in more attractive financial measures, e.g., higher net income, return on equity, and total assets These apparent benefits from capitalization attracted as many as

12 to 20 percent of software companies to capitalize some portion of their software creation expenditures during the early 1980s, before SFAS No 86 was issued (McGee

1988) After SFAS No 86 became effective in 1986, a majority of the software companies switched to capitalizing a portion of development costs (Aboody and Lev

1998) However, the support for capitalization of software costs has diminished over

time Ironically, the Software Publishers Association, that lobbied for the issuance of

SFAS No 86, filed a petition to the FASB seeking abolition of the Statement in March

1996 What factors could motivate the dramatic reversal of the software firms’ attitude

toward the capitalization rule they supported in the early 1980s?

Aboody and Lev (1998) provide a motive for software producers’ change of

attitude Using software companies’ data from a recent nice-year span (1987-95), they provide evidence that capitalization failed to continuously boost net income and return on

equity by the mid-1990s The income-decreasing amortization eventually exceeded the

income-enhancing capitalization as firms matured (which took place on average in 1995

the motivation for management choice between alternative R&D accounting methods, see Horwitz and Kolodny 1980; Daley and Vigeland 1983)

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based on their sample) Hence, those companies lost their original incentives to continue

capitalizing software development expenditures

I provide one other plausible factor to explain software firms’ change of

preference; the adoption of SFAS No 86 seems to result in an increase in earnings

variability on average The benefits of capitalization (higher reported earnings and returns

on equity) diminish as the software industry matures while costs of adopting the rule,

such as a more volatile earnings stream, still persist When the costs eventually exceed

the declining benefits, firms might have an incentive to abandon their support for the

capitalization rule

To investigate the impact of capitalization of software development costs on earnings variability, | compare the unsigned coefficient of variation of reported earnings under capitalization with that under the as-if expensing rule over a four-year horizon

subsequent to the adoption year of SFAS No 86.* This approach isolates the impact of

other confounding factors on earnings variability Disclosure requirements imposed by SFAS No 86 make it feasible for researchers to undo the capitalization process For

example, as-if earnings under expensing can be calculated as reported earnings under capitalization minus annual capitalized software costs plus annual amortized software

costs Since software development expenses are the only earnings component affected by the Standard, it is instructive to compare the variability of this particular earnings item

under capitalizing vs expensing treatments Findings based on 43 capitalizing firms are

presented in Appendix II

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Panel A of Appendix II shows the effects of capitalization on the variability of

software development expenditures Software expenses under capitalization are equal to

the software development expenditures expensed plus amortization plus occasional write-

offs Software expenses under as-if expensing are the total annual software development outlays (the sum of software development expenditures expensed and capitalized) All variables are normalized by net annual sales The change in variability is measured as the

difference between the dispersion in software expenditures under capitalization and that

under as-if expensing Percentile statistics show that 69% of coefficient of variation differences are greater that zero, implying that, for my sample, software development

expenses under capitalization are generally more variable than under as-if expensing In addition, Wilcoxon Signed-Ranks test shows that the median difference in earnings variability is significant at the level of 0.0009

The effects of software capitalization on variability of reported earnings per share are summarized in Panel B of Appendix II Since scaling by the weighted number of shares may not form a sufficient control for the size effect, the change in variability of earnings is measured as the ratio of dispersion of reported earnings per share under capitalization to adjusted earnings under the as-if expensing rule (this ratio analysis is also used in Francis 1990) Strikingly similar to the results for the change in variability of software expenditures, 62% of earnings dispersion ratios are greater than |, suggesting that most of 43 capitalizing firms’ reported earnings are more volatile than adjusted earnings under expensing Furthermore, the Wilcoxon statistic is significant at the 0.0001

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Taken together, an analysis of 43 capitalizers indicates that capitalization seems to

result in higher earnings variability The increased earnings variability may reflect the

dynamic, risky nature of software development Through capitalization, these risks and uncertainties involved in software development ventures are introduced into reported

earnings, which may consequently lead to higher earnings variability

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Chapter 3: Literature Review and Current Debate

A growing body of empirical accounting research has been devoted accounting

treatments of R&D expenditures since the issuance of SFAS No 2 in 1974 Early studies

examined the economic consequences of the expensing rule A significant portion of the literature, however, has focused on the value-relevance of R&D, that is, a firm's R&D

investments provide future benefits, and hence are reflected in the stock price Unt!

recently, few efforts were made to examine the reliability of R&D accounting The following review of prior research is organized along the aforementioned three lines of

inquiry: economics consequences, value-relevance and reliability

Economic Consequences of SFAS No 2

Following the issuance of SFAS No 2, research was aimed primarily at the impact of the Statement on managerial R&D investment decisions The question was investigated indirectly by (1) testing the capital market reaction surrounding the releases

of the Statement-related events (e.g, Dukes, 1976; Vigeland, 1981, Wasley and

Linsmeier, 1992), (2) surveying potentially affected firms’ managers about their perceived effects of the Statement on R&D investments (e.g., Horwitz and Kolodny, 1980), or directly, (3) by examining changes in the levels of R&D outlays surrounding the adoption of SFAS No 2 for firms which previously capitalized R&D (e.g., Elliott et al., 1980; Horwitz and Kolodny, 1980; and Dukes et al., 1984)

The findings of these studies are mixed Horwitz and Kolodny (1980) reported a

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managerial R&D decisions were detected (Elliott et al., 1980; Vigeland, 1981) Later

attempts to reconcile the discrepancies in the prior studies indicate that the divergent

findings are driven, at least partially, by systematic differences in sample firm size between OTC and listed firms (Dukes et al., 1984; Wasley and Linsmeier, 1992)

Why are small firms’ R&D activities more likely to be adversely affected by the

Statement? When SFAS No 2 was issued in 1974, less than 20% of publicly traded firms

were capitalizing R&D and most of them were small (Barron’s, November 18, 1974)

Several factors have been advanced to explain why the capitalization method was more commonly used by small firms First, small, technology-oriented firms typically grow at a much faster rate than large firms, and their R&D is a major operating expenditure In

general, capitalization results in more favorable reported earnings which last beyond

initial adoption years Furthermore, many firms partially compensate managers based on

reported accounting variables such as earnings As a result, the managers have an

incentive to make an accounting choice which would maximize their bonus rewards Second, when compared with small non-technological firms or large firms, small, high- technology firms have less internal funds and rely more heavily on external financing at their early development stages (National Bureau of Standards [1976, p.18]}) Lower book

value of equity and earnings resulting from a mandatory switch to the expensing-all R&D rule may lead to a higher probability of violation of existing debt covenants or may increase the cost of raising new capital due to higher perceived risk by the market

participants Third, institutional investors tend to have less interest in small firms.” As a

result, a high portion of equity sources of small firms may come from “unsophisticated”

* According to surveys revealed by National Analysts Federation [1977], there was little institutional interest in companies with less than $50-100 million market capitalization

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“unaffiliated” investors It is probable that these investors take the reported numbers at their face value and their evaluation of the firms are influenced by unfavorable impact on

reported numbers.”

To summarize, the extant literature seems to suggest that SFAS No 2 has little impact on large firms’ R&D investments while there is evidence indicating that the R&D levels of small, technological firms may be impacted by the Statement

Value-Relevance of R&D

A central premise underlying the expensing rule is what the FASB believed, at

that time, to be the lack of a direct causal relationship between R&D expenditures and

specific expected benefits (SFAS No 2, paragraph 14).’ This claim has prompted a stream of subsequent research to examine the relationship A common approach ts to

relate R&D information to stock market valuation Hirschey and Weygandt (1985) report

a positive association between a firm’s R&D outlays and its market-to-book ratio Cockburn and Griliches (1988), Hall (1993), Chambers et al (1998), and Lev and

Zarowin (1998) also document that the equity market incorporates R&D into firm valuation Researchers interpret the positive associations between R&D constructs and

equity market metrics as evidence that R&D activities generate future benefits in the

aggregate

Woolridge (1988) and Chan et al (1990) employ a different approach to assess the value-relevance of R&D Using an event study methodology, they find that stock

° Horwitz and Kolodny (1980) surveyed chief financial officers of 168 deferral and 212 expensing firms Approximately 93 percent of the deferral firms as well as 75 percent of expensing firms believed that SFAS No 2 would have a negative effect on the small investors’ evaluation of affected firms

” The FASB was also concerned that the future benefit of R&D are too uncertain and unpredictable to be reliably measured (SFAS No 2, paragraphs 39-40)

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prices respond positively to the announcements of increased R&D expenditures, suggesting that the stock market views R&D as value-enhancing investments Bublitz and Ettredge (1989) report similar evidence by examining the association between cumulative abnormal stock returns and unexpected changes in advertising and R&D spending Their findings suggest that R&D provides long-lived benefits while benefits from advertising

are short-lived

Instead of inferring that R&D benefits from stock prices/returns, Lev and Sougiannis (1996) extract the value of R&D from subsequent reported earnings They

then, adjust reported earnings and net book values by an as-if capitalization treatment They show that information contained in the adjustments is value-relevant to the cquity

market by association of stock prices and returns with the adjusted accounting numbers The potential informational benefits of capitalized R&D expenditures are also reported

by Chambers et al (1998) Applying hypothetical amortization schemes uniformly across the sample years, Chambers et al (1998) document that adjusted earnings and book values are more strongly associated with stock prices than the reported counterparts under the expensing rule They, then, argue that even arbitrary capitalization treatments, having

an advantage of allowing no management's discretion, seem to still improve the “usefulness” of accounting numbers for valuation purposes

The methodologies used in value-relevance studies have two limitations First, the association of security prices/retums with estimates of R&D assets or adjusted accounting variables is also consistent with alternative explanations For example, high

value of R&D estimates may also proxy for the high uncertainty and riskiness inherent in

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Second, the realized security prices are endogenously determined by the information conveyed by the reported numbers One cannot observe what prices would have been if R&D had been capitalized Therefore, implications for alternative reporting practices

drawn from the observed prices under the expensing rule may be problematic

This concern can be mitigated by investigating the software industry where

software firms, under SFAS No 86, are required to capitalize software development costs incurred subsequent to the establishment of technological feasibility Aboody and Lev

(1998) find that capitalized software costs are incorporated in stock prices and returns, hence providing direct evidence that software capitalization is value-relevant to cquity holders

Reliability of R&D Benefits

In contrast to ample studies on the value-relevance of R&D, research regarding the reliability of R&D outcomes is very scarce Kothari et al (1998) gauge the uncertainty/reliability of future benefits from R&D outlays relative to that from property plant and equipment (PP&E) Regressing the standard deviation of future carninys a

proxy for the uncertainty of R&D benefits, against annual R&D expenditures and PP&E they document that the coefficient on R&D is about three times as large as that on PP&E The evidence is consistent with their hypothesis that the future benefits resulting from

R&D activities are more uncertain than that from tangible investments

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models—the expensing-all, the full cost, and the successful efforts methods They show that the successful efforts method appears to win the horse race in providing value-

relevant information when there is no managerial manipulation Then, they allow management to exercise discretion by randomly postponing writing down the R&D assets for unsuccessful projects, and find that the successful efforts scheme still has superior information to the other alternatives if the frequency of delays is modest, even though the

information advantage is dampened by management’s opportunistic actions They conclude that the successful efforts method has the potential to enhance the

informativeness of accounting reporting as opposed to the expensing rule Current Debate

FASB issued the expensing rule in 1974 on the grounds that there was a high

degree of uncertainty about the future benefits of R&D, that there was no direct causal

relationship between R&D expenditures and increased future benefits in terms of sales

profits and share of industry sales, and that comments and feedback submitted by security analysts and bankers indicated that capitalization was not useful in assessing a firm's

earnings potential (SFAS No 2, paragraphs 39-41, 50, 54) Consequently, the FASB concluded that expensing was a better way to reflect the uncertain and risky nature of

R&D activities,

Since SFAS No 2 was issued, the U.S has witnessed a substantial transformation from a traditional manufacturing to an information-based digitalized economy Intangibles have played an increasingly important role in the corporate value creation process Numerous studies assert that the failure of current accounting systems to capture the growing amount of increasingly important intangibles has, in part, contributed to the

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alleged declining usefulness of financial reporting (Rimerman, 1990; Elliott and Jacobson, 1991; Jenkins, 1994; Stewart, 1995; Wallman, 1995; Chang, 1998; Lev and

Zarowin 1998) Moreover, in contrast to the FASB’s belief, subsequent academic

research has provided bountiful evidence that R&D investments are consistently associated with stock prices and retums in the aggregate, suggesting that the benefits of

R&D are long-lived

The debate is not about whether intangibles assets exist, but about how to better measure and disclose them, and about the pros and cons of reporting them even though

they may never be ideally measured Proponents of the expensing rule argue that R&D capital cannot be measured in a meaningful way due to high uncertainty and risk inherent

in the expected benefits of R&D Security analysts like the Association for Investment Management and Research (1993) also contend that the capitalized R&D costs would bear little information relevant to the valuation process due to the lack of correlation

between the R&D costs and subsequent future benefits CFOs of some companies predict

that reporting unreliable and noisy estimates of the intangibles in the financial statements might result in unintended and harmful results, e.g., misled investors and distracted managers (CFO, February 1999, page 30)

Critics of the existing expensing treatment are primarily academics, and, to certain extent, regulators Such critics contend that current accounting models do poorly

in capturing the intangibles, although intangibles constitute a rapidly increasing share of corporate value Thus, it is argued, the value-relevance of existing measurement systems

is deteriorating over time There is a growing need for new methods which better reflect

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the value of the intangibles These calls for better reporting systems have led to actions by regulators and policy makers For example, the SEC held a symposium solely devoted

to financial accounting and reporting on intangible assets in 1996; in September 1998, the International Accounting Standards Committee (IASC) passed a new standard on intangibles (IAS 38), allowing firms to capitalize a wide range of internally developed

intangibles; the Canadian Institute of Chartered Accountants (CICA) has launched the

Canadian Performance Reporting Initiative, and one of its five key projects rcyards intellectual capital management focusing on “experimenting with practices and techniques for managing and measuring intellectual capital”

Although a consensus is emerging that new accounting measurements are needed

in response to the new economy, the process of finding better ways of measuring evaluating and reporting on critical intangible sources of wealth is still at an early stage of development As a result, there have been calls for more research A Brookings

Institute task force, co-chaired by Steve Wallman, a former SEC commissioner, has been convened to tackle broad aspects of intangibles related issues, and make policy

recommendations to reduce or remedy current measuring and reporting deficiencies on

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Part II: R&D Investments, Bond Ratings and Bond Risk Premiums Chapter 4: Introduction

The debate on whether R&D expenditures should be capitalized as assets or

expensed as incurred reflects the trade-off between two asset recognition criteria.’ On one hand, consensuses have emerged that R&D expenditures on aggregate provide firms with

future benefits, such as introduction of new products and increased revenues That ts R&D investments result in value-creating economic assets, which should be recognized in the financial statements On the other hand, the risky and unpredictable nature of R&D

outcomes makes it extremely difficult to quantify the future benefits of R&D.'° Reporting unreliable and noisy estimates of R&D intangibles on the balance sheet would mislead

investors and creditors

The on-going debate begs the question: which effect dominates - the future benefits from R&D investments or their riskiness? '' Extant R&D literature investigating the relation between R&D variables and equity metrics is plagued with the inability of

researchers to address this question This is because both the benefits and riskiness of R&D have the sume directional impacts on the equity valuation of levered firms (Merton 1973, 1974) In other words, the risk and uncertainty of R&D, along with the future

* The Statement of Financial Accounting Concepts No 6, Elements of Financial Statements (1985), asserts that a firm will recognize a transaction as an asset only if (1) the transaction will generate future benefits for the firm, and (2) the future benefits can be quantified with a reasonable degree of precision

'® As the case for tangible investments, capitalization of R&D may be made on a cost basis However, subsequent amortization and revaluation of capitalized intangibles still require the reasonably precise assessment of the outlook of R&D projects For example, the knowledge of a future revenue stream from a pipeline drug would be critical to form a meaningful and informative amortization schedule Moreover the values of R&D intangibles, subject to various technological shocks, often change dramatically over ume while financial statements are not updated in a timely fashion

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benefits of R&D, also contribute to the widely documented positive association between R&D measures and stock prices/returns

This paper adds another dimension to the literature by studying the combined

effects of the future benefits and riskiness of R&D in the context of the bond market The

advantage of taking the perspective of the bondholder instead of equity holder is that, in

contrast to the same directional effects on equity valuation, the future benefits and

riskiness of R&D play opposite roles in the pricing of bonds (Merton 1973, 1974) Therefore, the bond market provides a unique setting enabling me to investigate whether R&D investments are expected to generate future ner benefits and have a more asset-like

nature or whether the risk associated with future benefits is so high that R&D is less asset-like in nature and more useful as a measure of risk

Option pricing theory stipulates that the mean and the variance of future cash

flows from investments have opposite impacts on the value of the firm's debt (Merton

1973, 1974) That is, an increase in the mean of future cash flows arising from the firm's

investments increases the value of its bonds by reducing the probability of default, while an increase in the variance of future cash flows decreases the value of its bonds by increasing the probability of default Relying on this theory, I examine the association

between bond risk measures and R&D investments to determine whether the mean effect

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would imply a stronger variance effect that swamps the mean effect of future benefits

from R&D investments

The sample used in this study consists of 132 new issues of industrial bonds by R&D-intensive firms The bonds were issued between 1991 and 1994 and were rated by Moody’s investment services Two commonly used bond risk measures, Moody's bond ratings and bond risk premium are used as dependent variables Risk premium is

calculated as the difference between a bond’s market yield-to-matunity and the yield on a U.S Treasury bond of comparable maturity on the issuance date The advantage of using

the bond risk premium is that the measure directly controls for the impact of the term structure of interest rates on raw yield to maturity This is particularly important because the sample bonds were issued over four years and the yield to maturity varies with the level of interest rates

This study finds a significant positive correlation of the firm’s annual R&D expenditures with bond default risk (proxied by bond ratings) and risk premium, controlling for other common bond risk determinants This finding suggests that, from the

creditor’s point of view, the adverse effect of high volatility and uncertainty (the variance

effect) of the firm’s R&D activities outweighs the favorable impact of the firm value increments (the mean effect) In other words, even though the expected mean valuc of the firm’s R&D outlays may be positive, it does not overcome the huge variance of the future cash flows Therefore, for creditors, R&D expenditures may reflect less assct-like characteristics but more risk attributes proxying for the excess variance effect over the

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To further test whether the finding depends on the choice of R&D measures, | usc

three other R&D constructs commonly used in the literature'* to estimate R&D “assets”

Specifically, variables are constructed based on the sum of the past five-year R&D expenditures, five-year straight-line depreciation, and industry-specific amortization

schedules, as reported by Lev and Sougiannis (1996, in Table 3, pp 121) All R&D constructs have significantly positive coefficients, indicating that the findings are robust with respect to the alternative measures

I further attempt to identify the R&D variable that is the best risk proxy by comparing the four R&D constructs While the three multi-year measures have comparable explanatory power, they demonstrate incremental power over the naive

variable (annual R&D expenditures) in explaining bond risk premiums This suggests that

these measures are better R&D risk proxies, probably because they are constructed from multiple years of observations, and incorporate the time series variation of R&D expenditures; hence they are more reflective of the firm’s R&D activitics

I also examine whether the Lev-Sougiannis measure (LS measure hereafter) provides more information regarding a firm’s R&D activities than the other proxies In contrast to the other “one-size-fits-all” constructs, the LS measure allows the

amortization schedules to vary across industries, and hence is likely to better capture the

risky and uncertain nature of R&D To test whether the LS measure has discriminative

power of R&D risk, the sample is partitioned by the estimated length of the R&D useful life (partition criteria are elaborated in section III) The partitioned analysis indicates that

'? One may argue that using annual R&D expenditures implicitly assumes that R&D outlays are expensed as incurred, hence the variable may not fully reflect all future benefits accruing from R&D investments and consequently may underestimate the mean effect

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there are significantly differential associations between the bond risk measures and the LS measure across the two samples, implying that R&D investments with longer uscful

lives are associated with higher uncertainty and risk The ability of the LS measure to discriminate varying degrees of R&D risk across the industries indicates that the amortization schedules derived by Lev and Sougiannis (1996) are informative and therefore lend the LS measure an edge over the other competing proxies

This study sheds light on our understanding of the trade-off between the future benefits (relevance) and risk (reliability) related to the financial reporting of R&D expenditures Under the Statement of Financial Accounting Standard (SFAS) No 3, R&D outlays are required to be expensed as incurred Critics of the expensing rule contend that there is a growing body of evidence that R&D on average generates future benefits (E.g., Hirschey and Weygandt 1985; Cockbum and Griliches 1988; Hall 1993;

Lev and Sougiannis 1996) Hence recognizing the value-creating R&D investments as assets will enhance the value-relevance of the financial statements On the other hand

proponents of the expensing rule argue that the outcomes of R&D activities are too

volatile to warrant a capitalization treatment The results in this study show that, from the

perspective of the bond market, the uncertainty of R&D appears to overwhelm the potential increase in the mean of future cash flows from R&D investments This piece of

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in the management’s discussion and analysis to aid the users of financial statements in

assessing the value of R&D activities.'°

The findings of this study may be of interest to policy makers Regulators and policy makers recognize the need for a better method to reflect the risks and value of intangibles.'* Given the dominant importance of debt financing'* and R&D investments to the U.S economy, this paper generates new evidence for debates on the accounting

treatment of intangibles

'’ For example, information regarding the expected useful lives of main products, as typically disclosed by software companies, will help to assess the expected benefits and risk of investments in software products

'* For example, SEC held a symposium solely devoted to financial reporting on intangible assets in 1996

FASB recently reversed an earlier position which would allow the capitalization of purchased R&D trom business combinations and stated “we will probably consider R&D in its entirety at some future date when we have the resources necessary to pursue the issues" (FASB news release, July 28, 1999)

'S Among the three primary extemal financing channels - the issuance of bonds, common stocks, and preferred stocks, the bond market has remained to be the most important source for the firm to raise its external capital For example, the issuance of bond constitutes 87.1 percent of total three offerings in the

1938 - 1941 period, and the share of bond financing continues to be above 80 percent in the 1990 - ¡993

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Chapter 5; Contribution of This Study

Existing value-relevance studies draw inferences from the association between

R&D variables and stock market metrics Option pricing theory states that both the mean and variance of future cash flows from R&D investments impact equity value in the same

direction (Merton 1973, 1974) As a result, the widely documented positive relationship

between R&D constructs and stock prices/retums is attributable to both the mean and

variance effects Stated differently, the risk and uncertainty of R&D also contribute to an

increase in stock prices and returns.'® Recognition of the contribution of R&D risk provides new implications for interpreting the empirical results For example, one cannot

unambiguously infer from the positive relationship that R&D outlays generate net positive expected future cash flows, i.e., net positive mean effect.'’ Second, the positive

association does not necessarily mean that the equity market treats R&D as if it were an

asset because R&D as a risk factor is also consistent with the findings

This paper contributes to the literature by shedding light on a fundamental question underlying the on-going debate on R&D accounting: which effect dominates the future benefits or the riskiness of R&D? The ambiguity in interpretations of the future benefits and riskiness of R&D results from the fact that both mean and variance effects have the same directional impacts on equity valuation In contrast, the two factors

'® Intuition for why the variance of the future cash flow distribution increases equity value stems trom the combination of two factors First, the manager/owners, who have residual claims, benefit from large payoffs if the investments pan out well Second, owners have limited liability and hence may not have to be responsible for the whole loss if the projects turn sour Therefore, the owners are tempted to take on risky projects at the expense of debt holders, resulting in risk shifting (wealth transfer) from the equity holders

(debt holders) to the debt holders (equity holders)

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play opposite roles in bond valuation Therefore, the bond market provides a unique setting to estimate the combined effects | document the positive association between

R&D variables and the bond risk measures, suggesting that the risk and uncertainty of R&D outweigh bond value increment arising from the mean effect, and hence R&D constructs are viewed more like risk proxies than assets by creditors Furthermore, the

positive coefficients on R&D variables may be also due in part to the perception thal

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Chapter 6: Research Methodology

Prior bond studies typically regress bond yields or default risk measures on the

variables of interest and a list of other determinants found important in explaining bond

yields and default risk as control variables (see Reiter 1990 for the literature review) To

investigate the link of R&D constructs to the risk of default and the risk premium, the

following system of two linear equations are examined:

Default Risk ,.; = f (R&D Constructs ,, Other Bond Determinant Set 1) (1)

Risk Premium ,.,; = f (R&D Constructs ,, Other Bond Determinant Set 2) — (2)

The disturbances in equations (1) and (2) contain common unspecified factors For example, macroeconomic shocks such as a government monetary policy change

affect both default risk and risk premium The advantage of estimating the above two

equations simultaneously is that it accommodates the possibility that the error terms of the two equations are contemporaneously correlated and improves the efficiency of

parameter estimates The results from Lagrange multiplier tests, discussed in section V show a significant correlation between the error terms of the two equations, therefore, the

analyses are carried out using the seemingly unrelated regressions (SUR) model in place

of OLS to improve estimation efficiency

Dependent Variables

The dependent variable for equation 1, default risk, is proxied by indicator

variables for bond ratings, with integer values | through 5 representing the ratings of Aaa, Aa, A, Baa, and Ba below.'® Following the classic bond paper by Fisher (1959) and

'* [ lumped bonds with the ratings of Ba and B into category 5 because there are only 11 issues with B ratings Finer decomposition, assigning 5 and 6 to Ba and B issues respectively, does not change the results qualitatively

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recent studies such as Reiter (1991), I gauge the risk premium (PREM, measured in basis

points) as the difference between the yield to maturity on an industrial bond and the daily averages of the constant maturity yield on U.S Treasury Bond of comparable maturity on the issuance date If an industrial bond cannot be matched with a Treasury bond with the exact same maturity, a benchmark Treasury bond yield is constructed by linearly

interpolating the yields of two adjacent Treasury bonds with maturity closest to the

corporate bond maturity.'” Data on bond ratings and yield to maturity on corporate bonds

are collected from Moody’s Bond Survey Information on the constant maturity yield on

U.S Treasury bonds is from the Federal Reserve Board of Governors’ Statistical Release

Subscripts t+land t indicate that dependent variables are one year ahead of independent

variables (accounting variables) because bond premiums and ratings are affected most by publicly available past accounting information (Ederington and Yawitz 1986)."

R&D Constructs

The variable of interest in the current study is R&D I employ four different R&D measures: annual R&D expenditures (RD1), R&D estimates constructed from summation of past five-year R&D expenditures (RD2), five-year straight-line (RD3) and industry- specific amortization schemes (RD4) The first measure is a “flow” variable while the

other three are “stock” variables The sample for this study consists of the same five

R&D-intensive industries as those used by Lev and Sougiannis (1996), hence the

industry-specific amortization schedules are extracted from Table 3 of their paper In particular, the fourth construct for firm / at year ¢, RD4 ; , , is estimated as follows:

" For example, if a corporate bond has an 8 year maturity, a bench mark yield is computed by linearly interpolating the yields of Treasury bonds with maturity of 7 and 10 years

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N-1 k

RD4,, => RD,,_,1- }-d,) (3)

ka0 /=0

where N is the economic useful life of R&D ranging from 5 years in the industry of scientific instruments to 9 years in the chemicals and pharmaceutics industry An amortization scheme is represented by a sequence of d ,, j is from 0 to N-1 Therefore, RD4 is the sum of the unamortized portion of past annual R&D expenditures; it is the

amount of expenditures that are expected to produce current and future earnings over the useful life of the R&D intangibles

Annual amortization of the R&D intangibles is derived accordingly as follows:

RDAMT4,, = yd, RDS,

;z0 (4)

RD3 and RDAMT3 are similarly computed except that they are based on the uniform five year straight-line method which means that N equals 5 and d , is set to be 0.2

for all j, where j is from 0 to 4 To control for size effect, all RD variables are scaled by year-end market value of equity

Other Bond Risk Determinants

The selection of control variables is based on the literature on bond premium and ratings In general, the determinants of bond premium include: (1) default risk variables proxied by accounting information, (2) issue characteristics of maturity, call provision convertibility and subordination status, and (3) macroeconomic conditions such as the effect of the business cycle Particularly, the control variables for the risk premium

equation are defined as below:

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DE = Long term debt-to-equity ratio The higher this ratio, the higher default risk and

bond premium

PROFIT = Net income to net sales Profitability is expected to be negatively correlated with default risk

TIMES = Income before interest expense divided by interest expense Times interest

earned ratio is expected to be inversely associated with default risk and bond premium

LOGASSET = Log of total assets Firm size proxics for default risk and bond marketability Larger firms are expected to have lower default risk and

hence lower risk premium

Issue Characteristics:

LOGMAT = Log of years to maturity The longer years to maturity, the higher interest

rate risk exposure Hence, it is expected to be positively correlated with risk premium

LOGSIZE = Log of issue size It can be viewed as a measure of marketability, and is

expected to be inversely correlated with risk premium That is because, everything else being equal, the larger the size of a bond issue, the

more frequently one should expect the bond to be traded The more frequently a bond exchanges hands, the less uncertain the bond price is

On the other hand, the larger a bond issue size, the higher the debt burden, hence, the higher the probability of default Therefore, the impact of issue size is ambiguous

CALL = Years to first call over years to maturity Call provision exposes bondholders to interest risk Lower call ratio implies a higher level of call protection to

the issuer and hence higher interest risk exposure to bondholders This variable is expected to be negatively associated with risk premium

CONV = | for convertible bonds and 0 otherwise Other things equal, convertible bonds result in lower risk premium

SUBO = | for subordinated bonds and 0 otherwise Subordination status is expected to be associated with higher bond premium.”'

Macroeconomic Conditions:

ECYC = Average yield on Moody’s Aaa bonds for the month of issue less average

* This variable is dropped from PREM (risk premium) equations because it happens to be highly correlated

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