The Value Relevance of Discretionary Capitalization of Research and Development Costs

The Value Relevance of Discretionary Capitalization of Research and Development Costs in the UK

Andrew Bruce Gallagher

Subject area: Finance and Economics

Supervisor: Mr Mark Burridge

Submitted: November 2012

Dissertation submitted to the University of Leicester in partial fulfilment of the requirements for the degree of Master of Business Administration TABLE OF CONTENTS

LIST OF TABLES

Table 1: Breakdown of identified Expensers and Capitalizers 21

Table 2: Pooled descriptive statistics for Capitalizers, Expensers, and the sample 22 as a whole

Table 3: Results of cross-sectional regression analysis of firms that either 24 expense or capitalize R&D costs: regression estimates, t-statistic in parenthesis, and significance levels for models 1-3

Table 4: Result of comparative regressions of models 1 and 3 for the years 25 2005-2007 and 2008-2012 to determine if the global recession affected the value relevance of R&D capitalization: regression estimates, t-statistic in parenthesis, and significance levels.

Table 5: Results of effect of R&D capitalization on subsequent reported 27 earnings: regression estimates, t-statistic in parenthesis, and significance levels

2 KEY TO ABBREVIATIONS

ANOVA Analysis of variance ASE American Stock Exchange EBIT Earnings before interest and taxes EBTCH Average change in operating profit before interest and taxes per share after adding back R&D expenditure and amortisation EPS Earnings per share EPSAD Earnings per share after deducting annual capitalized R&D expenditure FASB Financial Accounting Standards Board FEB Future economic benefit GAAP Generally accepted accounting principles IAS International accounting standards IASB International Accounting Standards Board IFRS International Financial Reporting Standards LGTASS Log of total reported assets excluding R&D assets NASDAQ National Association of Securities Dealers Automated Quotations NICH Average change in net profit after tax per share after adding back R&D expenditure and amortisation NYSE New York Stock Exchange P/E Price-earnings ratio R&D Research and development RDBALPS Capitalized R&D expenditure reported on balance sheet per share RDCAP Change in capitalized R&D expenditure RDEXPCAP Amount in capitalizing firm’s balance sheet that represents amortisation of previous period capitalized R&D RDEXPEXP Change in R&D expenditure by expensers RIM Residual income model SEQPS Shareholders' equity per share SEQPSAD Shareholders' equity per share after deducting annual capitalized R&D expenditure SFAS Statement of financial accounting standards SSAP Statement of standard accounting practice VIF Variance inflation factor

3 ACKNOWLEDGEMENTS

I would like to thank several people, without whom I may never have managed to complete this dissertation. Firstly I would like to God for giving me the means and ability to pursue and complete this degree. I would like to thank my beautiful wife, Sara, for her unending support throughout the course of this dissertation. She has been a constant source of motivation and has kept me focused, even through the seemingly unending early morning and late night study sessions. It would be remiss of me not to mention my gorgeous baby daughter Arielle, my little muse and inspiration who has had to sacrifice her play-time so Dad could go study.

Thanks must also go to my dissertation tutors. Firstly I’d like to thank Professor Chin Bun Tse for all his helpful advice during a large part of this dissertation. Thank you also to Mark Burridge, who picked up the reins after the programme reshuffle and helped me to put the finishing touches on the dissertation.

A big thank you to Lucy Mullins who helped me obtain the capitalization data when all hope seemed lost. Finally, I would like to thank my classmates and study group. We started this journey almost three years ago and back then this day seemed so far away. But we kept persevering, and with only a few pushes and prods, have now made it across the finishing line.

4 EXECUTIVE SUMMARY

In the United States, all research and development (R&D) costs are expensed in the year that they are incurred, but in countries such as the UK, R&D costs maybe be discretionally capitalized as an intangible asset if the commercial feasibility of the asset has been established and it is believed the asset will yield economic benefit. The act of capitalizing R&D expenditure could therefore act as a signal to investors that the company expects near-term economic gains.

This study investigated the value relevance of discretionary R&D accounting policies in a sample of 211 companies traded on the UK’s FTSE All Share Index for the period 2005 to 2011 to determine if capitalizing R&D expenditure as an asset could act as a credible signal of future economic performance. A modification of the Ohlson valuation method was used determine if capitalizing R&D costs was positively associated with market value. A sub-analysis of the dataset was conducted to see if the 2008- 2011 global recession affected the association between market value and capitalizing R&D costs as assets. As current and future value is said to be impounded in the market share price, these regressions provided an indirect measure of whether capitalizing R&D costs could signal future economic value. A direct test for future earnings was also conducted in which the earnings for a period were regressed on several accounting variables including the previous year’s earnings and different R&D variables.

The results showed that over the period 2005-2011 capitalized R&D costs did not have a significant effect on market value and was therefore not value relevant. Prior to the recession however the association between market value and capitalized R&D costs was significant and greater than expensed R&D costs, but during the recession this changed and capitalizing R&D costs was negatively associated with market value. Coinciding with the start of the recession was an increase in the frequency of R&D capitalization and this, together with the results of the regression analysis, suggested that the market suspected earnings management and consequently perceived R&D capitalization as bad news. The findings of the future earnings regressions however showed that even though the market perceived the capitalizing R&D costs negatively, it was still positively associated with future earnings.

This research highlights the difficulties in allowing managers more discretion in financial reporting. On the one hand, discretionary capitalization gives a company a means to convey relevant information to the market about future earnings and in doing so helps to reduce information asymmetry. But the system is open for exploitation and creates opportunity for earnings manipulation through capitalizing ineligible R&D, thus reducing the reliability in reporting. Despite the evidence of earnings management, overall, capitalizing R&D expenditure as an asset was associated with increased future earnings and this is relevant for an investor. Reducing earnings management through tighter corporate governance policies would allow capitalization of R&D expenditure to be a more reliable means of signalling future earnings.

5 1. INTRODUCTION

This dissertation examines the value relevance of the accounting treatment of R&D costs for companies in the UK. There has been a long-standing difference of opinion between accounting standard setters on what is the best accounting policy for R&D costs. In the USA, standard setters require that all R&D costs are expensed immediately, whilst international standard setters provide management more discretion and where the feasibility of the development project has been established and future economic benefit is expected, the R&D costs may be capitalized as an intangible asset. This difference in standards is centred on the trade-off between the relevance and the reliability of the information contained in the annual financial reports.

In the USA, standard setters found that there was little correlation and no causality between R&D costs and future economic benefit due to the high failure rate associated with R&D, which provided them with the motivation to mandate that all development costs be expensed as they are incurred. This approach provides reliable information to an outside investor as it eliminates any potential manipulation, but it fails to convey fully relevant information to an investor as it does not reflect the value of successful R&D.

Many academics feel that this approach is not ideal as capitalizing R&D costs provides a means to convey economically relevant information to the markets and failure to capture this value detracts from the relevance of the annual financial reports (Lev and Sougiannis, 1996). It can also be argued that the immediate expensing of R&D costs goes against the fundamental accounting principle of matching costs with revenues as rarely do the earnings attributable to R&D occur in the same accounting period as the R&D costs are incurred(Lev and Zarowin, 1999).

R&D is responsible for producing some of the most valuable assets of a company, but as R&D tends to involve confidential and proprietary activities, it can be difficult for an outside investor to fully gauge the economic potential of these intangible assets. This may lead to a situation of information asymmetry between the management team of a company and outside investors. It has been suggested that capitalizing R&D expenditure and amortising over its estimated life can reduce this asymmetry by signalling to the market the intangible assets expected value and in doing so, convey information about the company’s future prospects (Aboody and Lev, 2000).

There have been numerous studies that have explored the association between the capitalization of R&D costs and stock market value, as well as investigating if accounting policies can reduce information asymmetry by providing a signal of future economic value arising from the intangible assets. Some of these studies were conducted in the USA where R&D costs that were immediately expensed were converted as if they had been capitalized. Sougiannis (1994) found that R&D investment could convey

6 value relevant information to the market both directly and indirectly, with the indirect method in which value is ascribed through reported earnings attributable to R&D having greater relevance. Lev and Sougiannis (1996) reported that there was a strong association between R&D capitalization, stock price, and returns, demonstrating that capitalization of R&D costs yields value relevant information to investors. Chan et al. (2001) found evidence of stock mispricing in R&D intensive companies with these large distortions caused by expensing rather than capitalizing R&D costs. The work of Chambers et al. (2003) validated the earlier studies and reported that in a large sample of US listed firms, discretionary accounting practises conveyed economically significant information to the market.

There is an equally large body of value relevance research from non-US companies where discretionary capitalization is permitted by accounting standard setters. Abrahams and Sidhu (1998) reported that in a sample of Australian firms the ability to capitalize R&D outlays conveyed value relevant information to the investor. Zhao (2002) reported that in France and the UK, capitalizing R&D costs for successful projects and expensing unsuccessful one had greater value relevance than automatic expensing all R&D expenditure. Oswald and Zarowin (2007) similarly found that R&D capitalization was value relevant and reported that there was a higher association between current-year returns and future earnings in UK firms that capitalized R&D over those who expensed them.

However not all studies have reached the same conclusion. Cazavan-Jeny and JeanJean (2006) found that there was a negative correlation between R&D capitalization and stock-prices, with capitalizers tending to be smaller, less profitable companies. Markarian et al. (2008) reported that rather than using capitalization to reduce information asymmetry, some firms are guilty of using it to smooth their earnings. This opportunistic manipulation of accounting figures can make investors wary and consequently, capitalization of R&D may be perceived as bad news (Attallah and Khazabi, 2005; Chan et al., 2007). In light of this it must be questioned whether a credible signal can be obtained through capitalization of R&D outlays.

The literature shows that capitalizing R&D can be value relevant and provide the market a signal about upcoming economic returns, but in order for a signal to be credible, there must be a cost involved to prevent all parties sending the signal (Dye, 1985). However, as the costs of a false signal are low, companies that derive no benefit from their R&D outlays may also capitalize for reasons of earnings management (Thi et al., 2009). Discretionary capitalization can therefore open the door for opportunistic earnings management and calls into question the whether it remains value relevant (Chambers et al., 2003).

7 This dissertation will explore three research questions.

1. Does the R&D reporting method utilised by a company convey value relevant information to the market?

Whilst there have been many studies that have examined the value relevance of a company’s R&D accounting choice, this study will address a more contemporary dataset and focus only on UK companies. This question will be addressed by examining if there is an association between R&D accounting choice (i.e. capitalizing or expensing R&D costs) and the company’s concurrent market value, represented by its market share price. If capitalization is value relevant a positive association with market value is expected, and capitalized R&D should have a higher correlation than expensed R&D costs. If the market disregards management’s decision to capitalize R&D expenditure or if it suspects earnings management there would be a negative correlation between capitalized R&D costs and market value.

The timeframe of analysis for this study is from 2005, post the implementation of the International Financial Reporting Standards (IFRS) accounting standards in the UK, until the end 2011. This timeframe encompassed the recent global recession. The inclusion of recession data provides an opportunity to examine the robustness of research question 1. Whilst capitalizing R&D may be useful to reduce information asymmetry between the company and outside investors, earnings management may affect the reliability of the information. During times of economic hardship, companies that do not meet the market's expectations may be tempted to manipulate their performance through capitalizing R&D costs to artificially inflate profits or limit losses. The second research question of this dissertation will address this.

2. Did the 2008-2011 global recession have an effect on the value relevance of R&D capitalization?

As in research question 1, this will be addressed by examining if there is an association between R&D accounting choice and the company’s concurrent market value. The dataset from question 1will be subdivided into pre-recession and recession datasets, with the results being compared to each other and the outcome of research question 1.

The market value of a company is believed to reflect not only its present value, but as it accounts for all available information, it should also reflect its future value. Research questions 1 and 2 therefore provide an indirect measure of whether capitalizing R&D expenditure can be used as an indicator of future economic benefit. Research question 3 examines this relationship directly.

3. Is there an association between R&D capitalization and future economic performance of a company?

8 This will be examined by determining if R&D expenditure in a certain period is associated with earnings in subsequent years. By definition assets should provide value and economic benefit to a company. If capitalized R&D is recognised as an asset it is expected that there will be a positive association between it and future period earnings. R&D that is expensed should have no or a negative association with future earnings.

This dissertation is divided into six parts, including this introduction. Chapter 2 will review the pertinent literature for this field of study including the different accounting treatments for R&D costs, the value relevance of R&D, information asymmetry and the interplay between the reliability and the relevance of R&D accounting treatments. Chapter 3 describes the methodological approach taken, the sample, and how data was collected and analysed. Chapter 4 describes the characteristics of the sample and reports the results of the analyses conducted to address the research questions. Chapter 5 concludes the dissertation with a discussion of the theoretical and practical implications of the results, as well as discussing the limitations and future directions for research. Chapter 6 provides a list of references cited in this dissertation.

9 1. LITERATURE REVIEW

1.1 Accounting Treatment of R&D costs Globally there is no set standard for the treatment of successful R&D costs (under all accounting standards unsuccessful R&D endeavours are expensed). In 1974, the USA's Financial Accounting Standards Board (FASB) published the Statement of Financial Accounting Standards No. 2 (SFAS 21) which established new accounting standards for the treatment and reporting of R&D costs. The FASB found that there was little correlation and no causal relationship between R&D expenditure and future economic benefit, and due to the low success rate of R&D activities declared that all R&D costs should be expensed as they are incurred. In addition to mandatory expensing of all R&D costs, SFAS 2 also required that public companies must disclose the total R&D costs expensed in their financial statements.

Other countries however afford companies some discretion in the accounting treatment of R&D costs. The International Accounting Standards Board (IASB) sets different standards for these activities and IAS 382 prescribes the accounting treatment of intangible assets that are not covered in other International Financial Reporting Standards (IFRS). IAS 38 allows an entity to recognise an intangible asset if it is probable that the asset will produce future economic benefit and if the cost of the asset can be reliably measured. A company could therefore recognise R&D costs as intangible assets if the "technical and commercial feasibility of the asset for sale or use have been established" (IAS 38.57). If an intangible item does not satisfy these criteria then companies are required to recognise any costs as an expense as they are incurred (IAS 38.68).

Prior to the 2005 European wide implementation of IFRS, the UK’s Generally Accepted Accounting Principles (GAAP), more specifically the Statement of Standard Accounting Practise (SSAP) 133, also provided management with some discretion over the decision to capitalize R&D costs. Provided the development work has “a reasonable expectation of specific commercial success and of future benefits arising from the work, either from increased revenue and related profits or from reduced costs” then under SSAP 13 a company may capitalize these development costs. As with IAS38, expenditure on early stage pure and applied research is written off as an expense as the costs are incurred.

All financial reports should provide useful information to investors however the different standards have a different emphasis. The USA's FSAB has a clear focus on ensuring that all R&D expenditure is reliably

1 Statement of Financial Accounting Standards No. 2: Accounting for research and development costs; October 1974. Financial Accounting Standards Board, Connecticut. Retrieved from: http://www.fasb.org/pdf/fas2.pdf [accessed: 26/06/2012] 2 International Accounting Standards 38: Intangible Assets; April 2009 revision. International Accounting Standards Board, London. Retrieved from: http://www.iasplus.com/en/standards/standard37 [accessed: 26/06/2012] 3 Statement of Standard Accounting Practice No. 13: Accounting for research and development; January 1989 revision. Retrieved from: http://www.frc.org.uk/images/uploaded/documents/ssap%2013.pdf [accessed 26/06/2012]

10 reported in a company's financial accounts and achieves this by eliminating any opportunity for managers to manipulate the costs of projects. The IASB on the other hand has a focus on relevance by requiring companies to capitalize intangible assets (provided the criteria in IAS38 has been fulfilled) to provide investors with an indication of the value of the asset.

1.2 Value Relevance of R&D Capitalization The FASB’s decision for compulsory expensing of R&D costs was based on the assertion that a “direct relationship between research and development costs and specific future revenue generally has not been demonstrated” (SFAS2). Whilst this approach increases the objectivity and the reliability of the information contained in a company’s financial report, it fails to capture and report the value created through the R&D endeavours. R&D activities conducted by a company produce some of the most valued assets of a company, and it is argued that failure to capture and report this seriously reduces the credibility and relevance of the financial report (Lev and Zarowin, 1999; Healy et al., 2002). The immediate expensing of R&D costs also goes against the fundamental accounting principle of matching costs with revenues, as returns from R&D outlays are typically not realised in the same period that they are incurred (Lev and Zarowin, 1999). There have consequently been a number of academic studies investigating the relationship between company value and R&D investment.

Ben-Zion (1978) commented on the problem of underestimation of true economic earnings that arise from the accounting practice of treating expenditure on intangible capital, such as R&D and advertising, as costs rather than, at least partially, as an investment. Using a market value approach (market value can be used as a proxy for true economic value as it is the true earnings rather than observed earnings that determines market value) he showed that R&D activity had a significant positive effect on a company's market value. Hirschey (1982) also used a market valuation approach to investigate the future economic effects of advertising and R&D on company value. This empirical analysis reported that “advertising and R&D expenditures have positive and significant market value (intangible capital) effects” (page 388).

It has been argued that a company’s tangible and intangible assets are reflected in its market value and these assets have a systematic influence on future profitability (Hirschey and Wichern, 1984). Using Torbin’s Q values (the ratio of a company’s market value to the replacement cost of its assets), Hirschey and Weygandt (1985) demonstrated this by showing a positive correlation between R&D and advertising expenditure on the market value of a company, and owing to the long-lived benefits, suggest that these costs should be capitalized and amortised rather than being expensed when incurred. Bublitz and Ettredge (1989) built on these findings but used an alternative market-based research method that used stock returns and disaggregated earnings data to evaluate the longevity issues of advertising and R&D costs. Their results did not wholly support those of Hirschey (1982) and Hirschey and Weygandt (1985)

11 and they found that whilst R&D outlays of all firms (based on subsamples being pooled) are long lived and should be evaluated as assets, advertising expenditure should be classified as an expense. Cockburn and Griliches (1988), Chauvin and Hirschey (1993), and Hall (1993) similarly reported a positive correlation between R&D expenditure and market value. Woolridge (1988) and Chan et al. (1990) also reported the relevance of R&D expenditure on company value but rather than utilising the above market- based approach, they employed an event methodology in which they examined share-price responses to announcements of increased R&D expenditure. Both parties found there was on average a significantly positive increase in share price following such announcements.

Sougiannis (1994) examined the long-run impact of R&D activity on corporate earnings and market value through the use of two models; one that evaluated the impact of R&D investment on earnings, and another that evaluated the impact of R&D on market value. Sougiannis reported that R&D investment had a direct and indirect effect on market value. R&D investment could directly affect market value when information about R&D was directly conveyed to the market, and indirectly affect market value through reported earnings attributable to R&D. Sougiannis found that the indirect effect was greater than the direct effect, suggesting a greater value relevance to R&D information conveyed through earnings data rather than through the R&D variables themselves.

Lev and Sougiannis (1996) reported that there was a strong association between R&D capitalization and stock prices and returns, demonstrating that capitalization of R&D costs yields value relevant information to investors. As their sample was based on US companies where expensing R&D costs is mandatory, they estimated the R&D capital of the sample companies and adjusted the reported earnings and book values to evaluate the value relevance of R&D capitalization. Similarly constrained by a US-based dataset, Chan et al. (2001) reported stock mispricing in R&D intensive companies with large distortions arising when companies had to expense rather than capitalize R&D costs. They found that this could have a direct effect on investors if they failed to adjust valuation metrics such as price-to-earnings or price-to-book ratios. Chambers et al. (2003) similarly reported that for a large sample of NYSE, ASE and NASDAQ listed firms they found that discretionary accounting practises conveyed economically significant information to the market.

Healy et al. (2002) utilised a different method to examine the value relevance of accounting information. Using a Monte Carlo simulation model of pharmaceutical drug development, the underlying costs, probabilities of success, and economic benefits from drug R&D were used to generate a cash flow model for a pharmaceutical firm. Financial statements were generated to evaluate three scenarios, a cash- expense method where all outlays were expensed as incurred, a full-cost reporting method where R&D outlays were capitalized after initial drug discovery, and lastly, a successful-efforts method where outlays were capitalized after initial drug discovery with unsuccessful projects being written down and successful ones amortised over their expected life. The successful-efforts method was found to be highly correlated

12 with economic returns showing that capitalization was value relevant, especially when there was no room for earnings management.

Whilst SFAS2 does not permit the capitalization of R&D costs, there is an exception in the USA and SFAS864 allows for discretionary capitalization of costs incurred in software development. SFAS86 therefore provides an ideal situation in which to evaluate the effects of accounting treatments of intangible assets in the US context. Aboody and Lev (1998) examined the relevance that capitalizing software development costs had to investors by analysing the associations of financial data with earnings forecasts and other capital market observations. They found a positive association between capitalization of development costs and stock market returns as well as an association with reported earnings indicating that software capitalization conveyed relevant information to investors.

Many of the aforementioned studies however suffer in that they are based on the hypothesised effects of R&D capitalization and rely on adjusted earnings and book values. In contrast, many national as well as the international accounting standards allow for managerial discretion to capitalize and amortise R&D costs, and this allows for more realistic evaluation of the value relevance of R&D capitalization. Abrahams and Sidhu (1998) evaluated the value relevance of capitalizing R&D costs for Australian listed companies and found that selective capitalization was value relevant and there was a significant association between capitalized R&D costs and firm value. This demonstrated that the market believed the capitalized R&D costs to be an asset of the company. Ahmed and Falk (2006) also examined the value relevance of a company’s R&D reporting choice in Australia and found that capitalizing R&D costs was more value relevant and that discretionarily capitalized R&D costs had a higher association with share price than discretionarily expensed costs.

The UK’s accounting practices also allow discretionary capitalization of R&D expenditure. Oswald and Zarowin (2007) examined a sample of UK firms that included both capitalizers and expensers. They reported that there was a greater association between capitalization and stock price informativeness, and concluded that the capitalization of R&D costs can convey information about future performance to the market. Zhao (2002) also found that in countries that allow selective capitalization, such as France and the UK, capitalizing R&D costs for successful projects and expensing unsuccessful one had greater value relevance than automatic expensing all R&D expenditure. Hall and Oriani (2006) compared the value relevance of accounting treatments of several European countries with the Anglo-Saxon countries (UK and USA). They found that the German and French markets valued R&D capital, but not to the same extent as the UK markets did.

4 SFAS86 covers software developed for sale, not purchased or developed for internal use. In order to be eligible for capitalization the technical feasibility should be established; i.e. programme design is complete and that there are no technological uncertainties concerning development issues.

13 Not all studies have however concluded that capitalizing R&D is value relevant. Amir and Lev (1996) examined the value relevance of capitalization for companies in fast-changing, science-based industries, such as the wireless communications industry. They found that on its own, accounting information lacked value relevance and that only when combined with non-financial information does it contribute to the explanation of stock prices. Cazavan-Jeny and JeanJean (2006) tested the value relevance of R&D reporting in a sample of 197 French companies and found that there was a negative correlation between R&D capitalization and stock-prices, whilst Chan et al. (2007) found that, in line with the resource-based view of the firm, the choice of accounting method was not as important as the intensity of R&D, which had a more meaningful influence on firm performance.

There are other criticisms of the value relevance literature and these revolve around methodological short- comings in the research conducted. A large amount of the literature concerning the value relevance of R&D accounting is motivated by accounting standards setting and the inferences that can be drawn from the research. Holthausen and Watt (2001) however are critical of much of this literature and they report methodological weakness in the studies. They argue that unless the underlying theories are "descriptive of accounting, standard setting and valuation" (p.3) then only limited inferences or implications can be drawn from the associations between the accounting numbers and the equity valuations. They found that the value relevance literature focuses exclusively on equity valuation and ignores other roles of accounting and other forces that are important for standard setting. As these roles and forces are not perfectly correlated with the valuation role, key attributes of accounting are not taken into account. Holthausen and Watt argue that these forces are substantive and thereby diminish any inferences that can be made from the value relevance research. Barth et al. (2001) however maintain that the value relevance literature reflects information that is of great importance to equity investors, and since the primary focus of financial statements is equity investment, the current literature is pertinent and relevant.

Ronen (2001) is similarly critical of some value relevance studies (especially Boone and Raman, 2001) and reports that "the empirical association between accounting numbers and price based measures cannot, by themselves, lead to inferences regarding the usefulness of alternative accountings policies" (p.241). He reports a number of flaws in the arguments of these papers. One such flaw is that the usefulness of an accounting treatment cannot be assessed against another treatment solely by means of association with stock prices or measures derived from prices as different equilibrium prices will be observed for the different treatments by the researcher. In order to evaluate the desirability of one treatment over the other, the price equilibria for each specific treatment needs to be compared with respect to an objective function but this is not possible in studies in which the price equilibrium for capitalizing is based on that of expensing. Additionally, stock prices contain not only information about fundamental information but also reflects other factors and "there is no a priori reason to expect that prices reflect fundamental values better than accounting numbers to begin with" (p. 243).

14 1.3 Reducing Information Asymmetry Information asymmetry is associated with all corporate investments as managers are continuously aware of all changes that may affect the value of an asset whilst outside investors only receive periodic updates relating to the asset. Information asymmetries are much more prevalent with intangible assets associated with R&D due to the inherent uncertainties involved in R&D and their proprietary nature. With tangible assets such as property and equipment, it is much easier for outside investors to predict value changes as these tend to be influenced by industry-wide or macroeconomic events; e.g. interest rate changes will affect the value of bonds and stock portfolios of all companies. In contrast, R&D has a high level of uniqueness, and factors that affect one company may not affect others; e.g. a drug failure in a Phase 1 clinical trial is unique to the company developing that drug and it would have no influence on other pharmaceutical companies’ drug development programmes. Information asymmetry is compounded by the uniqueness of R&D investment as it is difficult for outsider investors to fully assess the value of the R&D based on the activities of other companies in the same industry (Aboody and Lev, 2000).

Information asymmetry also arises owing to the lack of organised markets for R&D. With tangible assets, considerable information can be derived as they are directly sold, but with intangible assets, the results from R&D investment are not generally sold directly and therefore there is no price-based information to help outsiders value these intangible assets (Griliches, 1987; Aboody and Lev, 2000).

Accounting rules that require immediate expensing further exacerbate information asymmetry. Tangible and financial assets are marked to market value in quarterly and annual financial reports providing investors with periodic revisions in the value of the assets. When R&D expenditure is treated as an expense, no information on the productivity or value of the R&D can be imparted to the investor (Aboody and Lev, 2000).

This information asymmetry may result in share prices of highly intangible firms not precisely reflecting the firms’ fundamental value. Given the importance of R&D to the productivity of highly intangible firms, it would be expected that investors and analysts would endeavour to acquire as much private information as possible from managers of these firms. This appears to be the case, and Barth et al. (1998) reported significantly more analyst coverage for R&D intensive firms over firms with lower or no R&D. Tasker (1998) similarly found that R&D intensive firms, whose financial statements do not capture all relevant performance and future prospects information, provide more voluntary disclosures in the form of conference calls with analysts.

In order to make sound investment decisions, all investors require relevant and useful information, and financial regulators have a mandate to protect the public interest and ensure a level playing field for all

15 investors (Levitt, 1998). Information asymmetry however allows those with private information to increase their wealth at the expense of the uninformed with adverse economic consequences. Glosten and Milgrom (1985) noted information asymmetry can lead to higher bid-ask spreads as investors with private information can buy stock based on information not available to the market maker, and in order to recoup losses incurred in trading with these investors, larger bid-ask spreads are set. The investor with private information therefore profits at the expense of the market, whilst the market profits at the expense of investors who are motivated by liquidity and are seeking to convert their stock into cash (Copeland and Galai, 1983). Since the market maker is unable to distinguish ex ante between informationally motivated and liquidity motivated traders, market makers not only increase the bid-ask spread, but also decrease the quoted depth (i.e. the number of shares available to trade at a given price) to reduce the maximum loss that they can incur on a single trade (Lee et al., 1993). Boone and Raman (2001) found that these defensive measures taken by market-makers were higher for R&D intensive firms, and that there was a “negative association between market liquidity and the magnitude of off-balance sheet R&D assets” (p. 125) for these firms. This finding rationalises the work of Aboody and Lev (2000) who reported that due to the large information asymmetry in R&D intensive firms, there are substantially more gains by corporate insiders made at the expense of outside investors.

Accounting techniques such as capitalization of R&D expenditure and its subsequent amortised could provide management a means of communicating private information to the market. In Australia where capitalization of intangible assets is routine, analysts expect firms with intangible assets that are likely to provide economic benefit to signal this to the market by capitalizing them as assets. Firms that do this are associated with higher analyst following and lower earnings forecast errors (Matolcsy and Wyatt, 2006). Anagnostopoulou (2010) reported that expensing R&D costs rather than capitalizing them was positively correlated with signed analyst forecast errors, with analysts showing more optimism for companies that expense R&D costs. Ahmed and Falk (2006) also reported on the signalling effect of R&D capitalization in Australia and suggested that “allowing managers to credibly signal their superior information by either capitalizing successful R&D investment or expensing unsuccessful R&D investment would reduce information asymmetry between managers” (p.259).

1.4 R&D Accounting Treatment: Relevance versus Reliability Whilst Matolcsy and Wyatt (2006) and Ahmed and Falk (2006) suggested that Australian analysts prefer capitalization of R&D to signal the market the expected value of R&D endeavours, there are reasons why capitalization may not result in more informative prices - principally due to earnings management.

Earnings management is defined as the "purposeful intervention in the external financial reporting process, with the intent of obtaining some private gain" (Schipper, 1989: p.92). Financial reports are used

16 to convey information on firm performance to outside stakeholders and rely on managers to use their knowledge to select reporting methods, estimates, and disclosures that accurately reflect the economics of the company. However, because managers have discretion, there is opportunity for them to utilise reporting methods and estimates that mislead stakeholders as to the underlying economic performance of the company (Healy and Wahlen, 1999). There are several reasons as to why managers would manipulate their results and these include avoiding losses and earnings declines, smoothing earnings in line with expectations, altering earnings to trigger management bonus schemes, avoiding violating covenants in debt contracts, and equity price manipulation for the benefit of insider trading (Beneish, 2001; Healy et al., 2002). The debate around capitalization of R&D outlays therefore revolves around the trade-off between relevance (i.e. predictive ability) and reliability (the representative faithfulness) of the accounting information.

Sections 2.2 and 2.3 above demonstrate that there has been a lot of empirical research demonstrating that capitalization of R&D costs may provide relevant information to the market and can reduce information asymmetry, but there are few studies that examine the reliability of this information. Kothari et al., (2002) questioned the reliability of R&D capitalization with regards to future economic benefits due to the uncertain nature of R&D. They reported that whilst on average other researchers had found that “the market assigns a statistically and economically significant valuation to corporate R&D activity” (p. 356), they found that there was a much larger degree of uncertainty associated with future earnings from R&D when compared with other items that are typically capitalized, thereby calling into question the reliability of capitalizing R&D costs.

The possibility of earnings manipulation also reduces the reliability of information. Roychowdhury (2006) found evidence to suggest that managers manipulate real activities, such as discretionary spending on R&D, in order to manage earnings, whilst Markarian et al. (2008) reported that rather than using capitalization to reduce information asymmetry, some firms use it to smooth their earnings. They found that firms with lower return on assets were more likely to capitalize R&D costs, and that companies that had improved their performance relative to the previous two years were more likely to expense R&D costs - i.e. the accounting treatment for R&D costs is based on changes in profitability of the firm. The potential to manipulate earnings through capitalizing R&D expenditure can therefore make investors wary and consequently capitalization of R&D may be perceived as bad news (Attallah and Khazabi, 2005; Chan et al., 2007). In light of this it must be questioned whether a credible signal can be obtained through the capitalization of R&D outlays.

A signal in the financial sense is an activity or action performed by a company that conveys information on company health to the outside market, allowing the party receiving the signal to adjust their behaviour accordingly. However, in order for a signal to be credible, there must be a cost involved (Dye, 1985), and the greater the cost the greater the credibility of the signal. In order to prevent everyone sending signal,

17 the costs and benefits of sending the signal have to be distinctly different, and the costs of the signal should increase as the ability of the signaling agent decreases (Spence, 1973). Extrapolating this to the case of capitalizing R&D costs, firms can be categorised into two groups: ones whose R&D activities bring future economic benefits (FEBs) and those where no FEBs can be expected (e.g. due to failed R&D efforts). Firms should be expected to capitalize R&D costs when the benefits of capitalizing exceed those of expensing. In order for capitalizing R&D to be a credible signal, there should only be a net benefit on capitalizing for those firms whose R&D activities bring FEBs. If this is not true then all firms can engage in signaling and an outsider will not be able to discern between a true and false signal. Therefore, if the costs of sending a false signal are low, companies that derived no FEBs from their R&D outlays may capitalize when the benefits of capitalizing exceed those of expensing and the signal will convey no meaningful information (Thi et al., 2009).

Since the true nature of the signal cannot be readily observed, discretionary capitalization can be used as a tool for earnings management and calls into question the value relevance of R&D capitalization (Chambers et al., 2003, Thi et al., 2009). However, it is likely that firms that derived no FEB from their R&D expenditure yet capitalize the costs do so as part of a larger program of earnings management. False signals may therefore be identified by recognising firms that engage in high levels of earnings management.

1.5 Concluding Remarks The debate on the accounting treatment of intangible assets has been around for a considerable period of time. If an intangible asset is reasonably expected or believed on the face of the available evidence to produce economic value it should be recognised on the balance sheet as an asset and reported in the financial accounts. Intangible assets also contribute more significantly in modern times to company value than previously and companies often derive more benefit from intangible assets such as brands, than they do from their physical infrastructure. R&D investments can also help companies to gain competitive advantages over their competitors, further highlighting the value of intangibles (Ehie and Olibe, 2010). In the USA, intangible assets that are purchased can be recognised on the balance sheet, but any intangible asset developed in-house, including all R&D endeavours, have to be immediately expensed. There is a large body of research that claims that intangible assets should be treated as any other tangible asset as they bring value to the company, however due to the perceived uncertainty of future benefits, the lack of alternative uses, and that often they are inseparable from other assets in the firm (i.e. in order to provide value they must be used in conjunction with other assets), some argue that they should not be treated like tangible assets (Cañibano et al., 2000).

18 As demonstrated in this literature review, the majority of the literature suggests that investment in R&D is consistently associated with market value and should be capitalized as an asset. Studies such as those conducted by Lev and Zarowin (1999), Zhao (2002) and Oswald and Zarowin (2007) demonstrate that capitalizing R&D outlays also helps reduce the information asymmetry between corporate insiders and outside investors. These findings are supported by studies that show that professional outsiders, such as financial analysts, find capitalizing R&D costs more informative than expensing them (Matolcsy and Wyatt, 2006; Anagnostopoulou, 2010). Due to the low costs involved in capitalizing R&D costs, there is however scope for capitalization for reasons of earnings management and this reduces the validity of signals that may be given to the outside market of expected future economic gains.

Much of the research that has been conducted in this field analysed data from the early 1990s to 2000s, and since then there have been several economically important global events, not least the implementation of new accounting standards (IFRS) across Europe and the greatest financial recession in recent times. The recent financial crisis highlights the need for transparency in the financial markets and that information asymmetries can be detrimental to a healthy market. This research adds to the body of literature that addresses the value relevance of R&D cost capitalization, assessing it from a UK context where managers can discretionally capitalize R&D costs. It will evaluate this using a more contemporary data set than previously reported and will also examine the robustness of R&D capitalization’s value relevance by examining whether the financial recession had an effect on the relevance of the choice of R&D accounting method.

19 2. METHODOLOGY

2.1 Introduction One of the major concerns over discretionary capitalization of R&D costs is the scope for managerial manipulation which decreases the reliability of the financial reports. Management may be influenced by a variety of consideration and motives such as expensing costs when performance has exceeded a certain level, or conversely capitalizing costs to artificially boost profit levels - i.e. manipulating the earnings so that results are in line with forecasted levels.

This study replicated the approach of Ahmed and Falk (2006) and examined the association between management’s discretionary accounting choice and the firm’s concurrent market value, as represented by share price. Based on historical evidence, it was expected that there would be a positive correlation between capitalized R&D costs and market value, whilst it was expected that there would be no or negative correlation between expensing and market value. Assuming market efficiency and that investors can detect earnings management, a no or negative correlation between capitalizing R&D costs and market value would suggest that the market does not trust managerial judgement or that there are suspicions of earnings management.

2.2 Study Population The study population for this research consisted of firms that had been or were currently listed and traded on the UK’s FTSE All Share index. The sample was divided into two mutually exclusive groups based on their accounting policies for the treatment of R&D costs and classified as either ‘Expensers’ or ‘Capitalizers’. They were classified as Expensers if they had recorded R&D activity in their annual financial reports but with no corresponding reporting of R&D assets on the balance sheet, and classified as Capitalizers if they had at least one balance sheet entry of R&D assets over the study period. Additionally, the financial reports of the Capitalizers were converted as if they had immediately expensed their R&D costs.

2.3 Data Collection Data was collected for the eight-year period from 2005 to 2011 and was sourced using Thomson Reuter's Datastream database. This time frame was selected as prior to 2005 IFRS accounting standards were not utilised by all UK listed companies and comparison between accounting standards could introduce bias to the results.

20 Expensers were identified using Datastream's Worldscope datatype for ‘R&D expense’ (code WC01201). This datatype represents all direct and indirect costs related to the creation and development of new processes, techniques, applications and products with commercial potential. These costs can be categorised as basic research, applied research or the development costs of new products, but excludes any customer or government sponsored research, the purchase of mineral rights for extractive/mining companies, and any engineering expenses. Capitalizers were identified using Worldscope codes WC02504 and WC02505, which respectively represents the net and gross book values of expenses related to the development of new products, i.e. capitalized R&D expenditure. In addition to data relating to the accounting treatment of R&D costs, other descriptive data to evaluate the economic characteristics of the sample companies was collected.

2.4 Data Analysis Data was analysed using SPSS statistical analysis software (versions 18 and 20). Outliers in the sample were identified by their standardised residual value, and standardised residuals with an absolute value greater than 3.29 were identified as possible outliers and were discarded from the analysis set. This value was determined as in a normally distributed sample, 95% of Z-scores should lie between -1.96 and +1.96, 99% between -2.58 and +2.58, and 99.9% between -3.29 and + 3.29% (Field, 2009). The sample was checked to ensure there was no perfect multicollinearity, the residuals at each level of the predictor variables had the same variance (i.e. were homoscedastic), and that the observations between residual terms were uncorrelated (tested using the Durbin-Watson test).

2.5 Regression Models The value relevance of R&D accounting treatment was evaluated using Ahmed and Falk's (2006) adaptation of Ohlson's valuation model (1995). Ohlson's model is a discounted residual income model (RIM) and it equates the value of shareholder's capital to the concurrent sum of the book value of the company and the discounted present value of expected future abnormal (or residual) income. One of the limitations of RIMs is that they do not relate reported financial information to the value of the company. Ohlson overcame this with his introduction of linear information dynamics, which allowed the value of a company to be expressed in terms of reported accounting numbers rather than future expected values (Lee, 1999). Ohlson’s model made use of the weighted average of the current book value and current earnings and it has been shown that when a price multiple is applied to these two items, the result reflects the residual income forecast (Ahmed and Falk, 2006). Some of the most desirable properties of Ohlson’s model for this research is that it provides a formal link between company valuation and accounting numbers and unlike other approaches, it shows links (represented by high R2 values) between value

21 changes and accounting information. These factors give the model a high explanatory power (Lo and Lys, 2000). Ahmed and Falk (2006) adapted Ohlson's model, and building on the work of Penman and Sougiannis (1998), used realised earnings as a proxy for expected earnings.

2.5.1 Research Questions 1 and 2: Share Price Model (Sample as a Whole)

Research question1 examined if capitalizing R&D was value relevant to an outside investor by using a variation of Ohlson's valuation method and related earnings per share (EPS) and shareholder equity to the value of the firm as represented by share price. If R&D capitalization was value relevant, the inclusion of the amount of R&D capitalized in the regression should have more explanatory power (higher R2 value) than regressions without it. This analysis pooled all firm-year observations and treated the sample as a whole.

Three regression models were utilised to examine this: model 1 pertained to Capitalizers, model 2 to Capitalizers whose accounting figures had been converted as if they had immediately expensed and model 3 to Expensers:

1) P90 = α0 + β1EPS(Yrit) + β2SEQPS(Yrit) + β3LGTASS(Yrit) + β4RDBALPS(Yrit) + ε

2) P90 = α0 + β1EPSAD(Yrit) + β2SEQADPS(Yrit) + β3LGTASS(Yrit) + ε

3) P90 = α0 + β1EPS(Yrit) + β2SEQPS(Yrit) + β3LGTASS(Yrit) + ε Where: P90 = firm’s share price

(Yrit) = year indicator; 2004-2011, for firm i EPS = reported earnings per share SEQPS = shareholder equity per share LGTASS = log of total assets, excluding capitalized R&D balance at the end of the year RDBALPS = capitalized R&D expenditure balance per share EPSAD = earnings per share after deducting annual capitalized R&D expenditure SEQADPS = shareholder equity per share after deducting R&D capitalized balance, ε = error term.

In models 1-3 the share price of the company was regressed on R&D per share, EPS, and shareholder equity per share and the results were compared with respect to their power to explain the market value of the company. If R&D capitalization was value relevant, model 1 would have greater power to explain market value when compared with models 2 and 3, which reflect immediate expensing of R&D costs.

All three models made use of data that was publically available and reported in the annual financial reports of the sample companies. Model 2 adjusted the shareholder equity and EPS reported by the Capitalizers as if they had expensed their R&D costs. This adjustment could however affect the validity

22 of the corresponding share prices as these changes were not publically reported and the market would not have accounted for them. The share prices were however considered to remain efficient as investors and analysts could (and potentially do) make the conversion to compare Expensers’ statements with Capitalizers as all the information is freely available in the public domain (Ahmed and Falk, 2006).

The inherent risk level of a firm has been shown to be inversely proportional to its size (Altman, 1968; Falk and Heintz, 1975), and as such total assets were used in this study as a proxy the sample company’s risk position. As it is possible that total assets were correlated with shareholder equity in the analysis, collinearity was checked. The Pearson correlation coefficients between these two variables varied between 0.370 and 0.557 suggesting no perfect multicollinearity.

The dependent variable in the regressions was the firm’s share price. As annual financial reports are normally released three months after the end of the financial year, the stock price at that date rather than the date of financial year end was chosen as it was a truer reflection of value (Penman and Sougiannis, 1998).

To reduce possible heteroscedasticity, the explanatory variables in the regressions were standardised by the number of outstanding shares. This is discussed further in Section 3.6 below.

Research question 2 examined whether the 2008-2011 global recession had an effect on the value relevance of R&D capitalization. The same data and regression models were used as in models 1and 3 above, (model 2 was not included in this sub-analysis) but they were separated into two time frames, 2005-2007 and 2008-2011 and labeled models 1a and 1b, and models 3a and 3b respectively with ‘a’ designating pre-recession and ‘b’ the recession analysis set. If the market suspected firms were capitalizing R&D costs as a means of earnings management, it would be shown through negative coefficients for the R&D capitalization variable, i.e. R&D capitalization would be perceived as bad news by the markets and consequently would be negatively correlated with market share price.

2.5.2 Research Question 3: Future Performance Model

As future expected profits are said to be impounded in the share price, high R2 values, and positive and significant coefficients for the predictor variables in research question 1 would be indicative that the market consider capitalizing R&D spending value relevant and attributed near-term future benefits from it (Ahmed and Falk, 2006). Models 1-3 therefore provide an indirect measure of the future value of capitalized R&D expenditure. The direct association between capitalizing R&D costs and future performance of the firm was further explored using the following four models:

4) EBTCHit = β1EBTCHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit +ε

23 5) NICHit = β1NICHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit + ε

6) EBTCHit+1 = β1EBTCHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit +ε

7) NICHit+1 = β1NICHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit + ε Where:

EBTCHit, EBTCHit-1 and EBTCHit+1 = change in earnings before tax, after adding back R&D expenditures and amortisation, for years t, t-1 and t+1 respectively

RDEXPCAPit-1 = change in R&D expensed and amortised by capitalizers in t-1

RDEXPEXPit-1 = change in R&D expenditure by expensers in t-1

LGTASSit, LGTASSit+1 = log of total assets, excluding capitalized R&D balance, in t and t+1 respectively

NICHit, NICHit-1, NICHit+1 = change in net income, after adding back R&D expenditures and amortisation for year t, t-1 and t+1 respectively ε = error term.

The basis for this analysis revolves around resource utilisation and how it impacts future earnings. The earnings of a company can be divided into two main categories; those that are associated with normal business activities and are expected to recur in future periods, and non-recurring ones that may be above or below the level of the core earnings. These non-recurring earnings are normally related to a change in the level of resource utilisation, and it may be expected that any changes in consumption of resources in time period t-1, such as that spent on R&D, with no corresponding change in income in that period, would affect the income generating power in the next time period (t) as few resources would be available for deployment (Ahmed and Falk, 2006).

EBTCH and NICH represents the change in earnings before interest and taxes and change in net earnings after tax after R&D expenditure and amortisation has been added back respectively and are growth measures of earnings. Negative changes of these variables in a period would reduce income generation potential for future periods, whilst positive increases would provide more resources for reinvestment. It was expected that where EBTCH and NICH were positive, there would be positive coefficients for

EBTCHit-1 and NICHit-1.

RDEXPCAP represents the amortisation and write-down of previous period capitalized R&D on the balance sheet that were expected to provide benefit but did not. This predictor was not expected to contribute significantly to current year income. RDEXPEXP represents resources that had been consumed and subsequently expensed as they were not expected to contribute to future earnings. It was expected that this predictor variable also would not contribute significantly to the model and that its coefficient would be negative or uncorrelated with future earnings. RDCAP was the capitalized R&D costs that were expected to produce future economic benefits for the company and it was expected that this predictor variable would have a positive and significant coefficient in the model.

24 2.6 Standardization and Sensitivity Analysis To reduce possible heteroscedasticity, the predictor variables in regressions 1-7 were standardised by the number of outstanding shares. There has been some debate over standardising variables by the number of outstanding shares. Easton (1998) argues that this approach may lead to invalid results due to the effect of scale and that as management has control over the number of shares in issue, they can change the share price through stock splits without changing the economic characteristics of the firm. This has a direct effect on the scale of any per-share measure of firm attributes so that “a regression of share price on the firm attributes will lead to coefficients that may capture no more than the fact that all variables have the same scale” (Easton, 1998: p.237). To account for this perceived methodological weakness, a sensitivity analysis was conducted in which the predictor variables in regressions 1 and 3 were standardised by book value rather than outstanding shares as suggested by Easton (1998). Rather than using share price as the dependent variable, the market value of the firm was used, and reported earnings were used instead of earnings per share.

1') P’90 = α0 + β1EARNBV(Yrit) + β2SEQBV(Yrit) + β3LGTASS(Yrit) + β4RDBALBV(Yrit) + ε

2') P’90 = α0 + β1EARNBV(Yrit) + β2SEQBV(Yrit) + β3LGTASS(Yrit) + ε

Where:

P’90 = firm’s market value of equity taken 90 days after end of fiscal year

(Yrit) = year indicator; 2004-2011, for firm i EARNBV = reported earnings SEQBV = reported shareholder equity LGTASS = log of total assets, excluding capitalized R&D balance at the end of the year RDBALBV = capitalized R&D expenditure balance ε = error term.

25 3. ANALYSIS AND RESULTS

3.1 Sample A search of Datastream identified 211 companies that reported R&D activity during the period 2005- 2011, corresponding with 927 firm year observations. Of this sample, 125 companies reported an R&D expense with no corresponding balance sheet development assets and had a complete dataset for the regressions (i.e. no missing variables for the regression models), and similarly, 86 companies reported a balance sheet development asset. In certain instances, some companies reported both R&D assets and expenses. In years that development costs were capitalized they were categorised as Capitalizers, and in the years that they expensed R&D with no balance sheet development costs they were classified as Expensers.

Table 1: Breakdown of identified Expensers and Capitalizers

Expensers Capitalizers Total

Number of companies 125 86 211 Number of firm year 594 333 927 observations

Table 2 below provides descriptive statistics of the companies in the sample. There is almost a two-to- one ratio of firm-year observations for Expensers over Capitalizers in the sample. Based on revenues, earnings, total assets, shareholder equity and market capitalization, Expensers are larger than Capitalizers and have on average higher share prices. Capitalizers have higher annual spend on R&D and have a higher R&D intensity (2.7% vs 1.2%), calculated as the ratio between R&D spend and annual revenue.

Expensers have a higher price-earnings (P/E) ratio (1.2 times higher) and higher EPS (1.3 times higher) than Capitalizers, however, had the Capitalizers expensed R&D costs rather than capitalizing them as assets, the gap in EPS would be even larger. This could give added incentive to Capitalizers to improve their accounting ratios through manipulation. If the market suspected such an occurrence, a negative reaction to R&D capitalization would be expected and we would not expect the R2 for model 1 to dominate the R2 of model 3.

26 Table 2: Pooled descriptive statistics for Capitalizers, Expensers, and the sample as a whole Statistic Capitalizers Expensers Total sample (units) N= 333 N = 594 N = 927 Net sales Mean 5,619,428 6,497,738 6,175,879 (£’000s) Minimum 2,279 0 0 Maximum 233,372,550 292,197,171 292,197,171 Median 384,249 776,700 556,907 Std Dev 24,366,973 24,723,490 24,584,037 Net earnings Mean 350,100 574,856 492,189 (£’000s) Minimum -2,410,619 -21,916,000 -21,916,000 Maximum 15,971,779 19,214,609 19,214,609 Median 27,757 40,099 34,617 Std Dev 1,562,280 2,262,573 2,035,232 Total assets (TASS) Mean 5,963,848 8,880,182 7,807,543 (£000s) Minimum 38,943 8,061 8,061 Maximum 188,342,308 219,298,100 219,298,100 Median 412,700 804,494 573,341 Std Dev 22,010,636 25,378,014 24,222,947 Total debt Mean 1,105,975 2,023,775 1,686,204 (£’000s) Minimum 0 0 0 Maximum 29,060,376 39,920,000 39,920,000 Median 59,478 186,056 118,950 Std Dev 3,772,939 4,911,259 4,545,502 Beta Mean 0.983 0.990 0.987 Minimum 0.278 0.314 0.278 Maximum 2.124 2.217 2.217 Median 0.972 0.970 0.972 Std Dev 0.383 0.407 0.398 Market Mean 4,706,671 8,290,668 6,973,078 capitalization Minimum 10,818 8,551 8,551 (£’000s) Maximum 121,883,032 145,839,757 145,839,757 Median 581,751 749,747 691,917 Std Dev 15,547,454 20,916,484 19,187,984

Share price (P90) Mean 5.087 5.611 5.418 (pence) Minimum 0.003 0.054 0.003 Maximum 37.050 42.280 42.280 Median 2.992 3.100 3.054 Std Dev 5.700 6.541 6.247

27 Statistic Capitalizers Expensers Total sample (values in £'000s) N= 333 N = 594 N = 927 Shareholder equity Mean 1,883,690 3,617,879 2,980,037 (£’000s) Minimum -824,000 -3,192,000 -3,192,000 Maximum 67,183,740 103,098,400 103,098,400 Median 177,601 257,200 215,200 Std Dev 7,647,999 12,720,218 11,153,584 Shareholder equity Mean 1.667 2.395 2.127 per share (SEQPS) Minimum -1.082 -0.412 -1.082 (£) Maximum 18.104 38.606 38.606 Median 1.253 1.307 1.290 Std Dev 1.646 3.753 3.165

Earnings per share Mean 0.274 0.359 0.328 (EPS) Minimum -0.917 -4.500 -4.500 (£) Maximum 2.159 4.555 4.555 Median 0.164 0.183 0.170 Std Dev 0.391 0.632 0.557 P/E ratio Mean 13.010 15.120 14.350 Minimum -982.500 -970.000 -982.500 Maximum 486.154 635.000 635.000 Median 15.764 14.752 15.107 Std Dev 66.365 62.193 63.720 R&D capitalized Mean 154,175 NA (£’000s) Minimum 46 Maximum 12,807,228 Median 8,100 Std Dev 974,029 R&D expensed Mean NA 78,453 (£’000s) Minimum 34 Maximum 2,800,344 Median 8,300 Std Dev 288,148

3.2 Results

3.2.1 Research Questions 1 and 2: Share Price Model

It was hypothesised that model 1 should have a higher R2 than the other two models as the inclusion of capitalized R&D costs in the valuation model should provide greater explanatory power for market value of a company. This seems logical as capitalization should be associated with higher share prices as under IFRS standards, only successful projects that will produce future economic value to the company should be capitalized. However, due to the low cost involved in capitalizing R&D, the threat of earnings management may nullify this.

28 Table 3 below shows the results of the regression analysis for models 1-3. These models treated the sample as a whole. The R2 values were quite high for all three models, and were statistically significant at a level of better than 0.001 as tested using ANOVA. The variance inflation factors (VIF) for the models were low and less than 5 indicating there was no strong linear relationship between the predictor variables and hence no multicollinearity (Field, 2009). There was no autocorrelation between residual terms (i.e. independent errors) with the results of the Durbin-Watson test being close to the ideal value of 2 (ranged between 1.791 and 2.015) (Field, 2009).

Table 3: Results of cross-sectional regression analysis of firms that either expense or capitalize R&D costs: regression estimates, t-statistic in parenthesis, and significance levels for models 1-3 Model 1: Capitalizers Model 2: Capitalizers Model 3: Expensers (n=333) (adjusted) (n=337) (n= 594) Constant 2.881** 1.137 -3.837*** (2.966) (1.065) (-3.483) EPS 8.211*** 7.453*** - (17.200) (22.114) EPSAD 7.104*** - - (15.769) SEQPS 1.493*** 0.229*** - (10.822) (4.039) SEQPSAD 1.762 - - (14.831) LGTASS -0.198** -0.014 0.445*** (-2.624) (-0.170) (5.359) RDBALPS 1.813 - - (1.121) 2 R (%) 78.4 76.9 74.8

2 Adjusted R (%) 78.2 76.6 74.6 Model's significance 0.000 0.000 0.000 Highest VIF 1.953 1.561 2.366 Durbin-Watson 1.856 1.791 2.015

Where: * is p<0.05, ** is p<0.01, *** is p<0.001 EPS = earnings per share, EPSAD = earnings per share after deducting annual capitalized R&D expenditure, SEQPS = shareholders' equity per share, SEQPSAD = shareholders' equity per share after deducting annual capitalized R&D expenditure, RDBALPS = capitalized R&D expenditure reported on balance sheet per share, LGTASS = log of total reported assets excluding R&D assets, and VIF = variance inflation factor.

The coefficient of the capitalized R&D costs (RDBALPS) in model 1 was expected to be positive and significant, and the R2 value of model 1 was expected to be higher and provide a better fit for market value than models 2 and 3 in which R&D was immediately expensed. This study found that over the period 2005-2011, the capitalization model did have higher adjusted R2 value than the other two models and RDBALPS had a positive coefficient. The coefficient for RDBALPS however was not significant (p=0.263) and the values of the t-statistic for it was low compared with that of EPS and shareholder

29 equity (t=1.121 for RDBALPS, t=17.200 for EPS, and t=10.822 for SEQPS), indicating that it did not contribute significantly to the model. Whilst R&D capitalization was not significant, its adjusted R2 value did dominate that of model 2 and model 3, however it is difficult to infer value relevance of R&D capitalization based on this as model 1 contained an extra variable in the regression which would automatically lead to an increase in R2 value. The results therefore show that in this model capitalizing R&D costs had no greater association with market value than expensing them.

This finding was not as anticipated based on the reported literature and the reason for this lack of significance becomes apparent when analysing the dataset for research question 2 in which the value relevance of R&D capitalization was examined in the context of the recent global recession. In research question 2, the dataset from research question 1 was analysed after dividing the sample into pre-recession and recession datasets. Table 4 below contains the results of this sub-analysis (for models 1 and 3 only) in which the sample was divided into pre-recession dataset spanning 2005-2007, and the recession dataset spanning 2008-2011.

Table 4: Result of comparative regressions of models 1 and 3 for the years 2005-2007 and 2008-2012 to determine if the global recession affected the value relevance of R&D capitalization: regression estimates, t-statistic in parenthesis, and significance levels. Model 1a Model 1b Model 3a Model 3b 2005-2007: 2008-2011: 2005-2007: 2008-2012: Capitalizers Capitalizers Expensers (n= Expensers (n= (n=103) (n=230) 243) 351) Constant 2.033 3.275 -1.862 -4.673** (1.566) (2.546) (-1.192) (-3.100) EPS 10.336*** 7.646*** 7.976*** 7.213*** (12.501) (13.229) (12.311) (18.349) SEQPS 0.850*** 1.722*** 0.499*** 0.171** (4.160) (9.849) (4.307) (2.619) LGTASS -0.105 -0.240* 0.277* 0.505*** (-0.046) (-2.442) (2.310) (4.485) RDBALPS 3.403* -0.252 - - (2.227) (-0.003) R2 (%) 83.8 77.7 74.8 76.1 Adjusted R2 (%) 83.2 77.3 74.5 75.9 Model's 0.000 0.000 0.000 0.000 significance Highest VIF 2.101 1.920 2.549 2.334 Durbin- 1.925 1.815 2.192 1.960 Watson Where: * is p<0.05, ** is p<0.01, *** is p<0.001. EPS = earnings per share, SEQPS = shareholders' equity per share, RDBALPS = capitalized R&D expenditure reported on balance sheet per share, LGTASS = log of total reported assets excluding R&D assets, and VIF = variance inflation factor.

The R2 values for all the models were significant, and as with research question 1, there was no autocorrelation (Durbin-Watson values ranged from 1.815 to 2.192), and no multicollinearity (VIF values

30 <5). Interestingly, looking at the respective sample sizes, there was a marked increase in the number Capitalizers during the recession. Prior to the recession there were 103 firm year observations, an average of 34 companies per year, but this almost doubled on a per-year basis during the recession to an average of 61 companies per year who capitalized R&D costs. The frequency of Expensers remained comparable prior to and during the recession, with an average 81 per year prior to the recession and 88 per year during the recession.

This large change in frequency of capitalization during the recession is suspicious and could indicate an increased incidence of earnings management whereby managers are attempting to limit the impact of reduced earnings by capitalizing R&D costs to artificially inflate the bottom line. If the market suspected earnings management, R&D capitalization would be received as bad news and rather than being valued positively as an asset, it would have a negative coefficient in the regressions and be associated with a decrease in share value.

Examination of the results of the analysis shows this to be the case. In the period 2005-2007, there was a significant difference between the adjusted R2 values of Capitalizers (model 1a) and Expensers (model 3a), with values of 83.2% and 74.8% respectively. The adjusted R2 value for model 1a was also higher than the 78.4% reported in research question 1 (model 1, for the period 2005-2011). Adjusted R2 values for the Expensers were comparable between the analyses, with 74.8% for model 3a, compared with 74.6% in model 3 (Expensers in the period 2005-2011). Unlike in model 1 where RDBALPS' coefficient was not statistically significant, the pre-recession subset of model 1a was significant with a p-value of 0.028 and the t-statistic showed it made a larger contribution to the model than in model 1 (t-values for the pre-recession subset for EPS, SEQPS and RDBALPS were 12.501, 4.160, and 2.227 respectively compared with 17.200, 10.822 and 1.21 for the original analysis). The coefficient for RDBALPS for the pre-recession dataset was also larger than the original analysis set (3.403 versus 1.813) indicating that money spent on R&D before the recession had a greater positive influence on market value than in research question 1.

During the recession, the adjusted R2 value for Capitalizers (model 1b) had a marked decrease from 83.2% to 77.7%, whilst for Expensers (model 3b) there was an increase from 74.8% to 76.1%. RDBALPS’ coefficient showed it was now negatively correlated with market value, although its p-value fell slightly outside the statistically significant limit of p<0.05 (p=0.082). This negative, non-significant coefficient for capitalized R&D suggests that the market believed earnings were being manipulated by incorrectly capitalizing R&D costs, and as a result R&D capitalization was no longer correlated with market value. This change from R&D capitalization being positively associated with market value prior to the recession, but negatively associated with it during the recession is most likely the reason for the lack of significance when the dataset was examined in research question 1.

31 3.2.2 Research Question 3: Future Performance Model

The future earnings model also used the sample as a whole and the results of the analyses are shown below in table 5. The models were highly significant with p<0.001 for all four models. There was no evidence of autocorrelation (Durbin-Watson values ranged from 1.869 to 2.015), and no multicollinearity as evidence by VIF values < 5 (Field, 2009).

Table 5: Results of effect of R&D capitalization on subsequent reported earnings: regression estimates, t-statistic in parenthesis, and significance levels One year ahead Two years ahead

Model 4: EBTCHit Model 5: Model 6: Model 7:

(n=922) NICHit (n=926) EBTCHit+1 (n=744) NICHit+1 (n=749) Constant -0.165 0.001 -0.023 0.022 (-1.891) (0.053) (-0.213) (0.230)

EBTCHit-1 -0.263*** 0.432*** - - (-8.831) (14.630)

NICHit-1 -0.073*** 0.218*** - - (-3.846) (8.593)

RDEXPCAPit-1 0.190*** 0.051*** 0.419*** 0.417 (14.098) (13.963) (21.598) (0.378) -7 -8 -8 -7 RDEXPEXPit-1 1.6x10 ** 4.0x10 *** 9.2x10 1.8x10 ** (2.969) (4.282) (1.417) (3.204)

RDCAPit-1 0.362*** 0.039*** -0.456*** -0.170** (7.247) (4.342) (-8.239) (-3.418) LGTASS 0.017** 0.001 0.008 0.005 (2.703) (0.725) (1.043) (0.685) R2 (%) 45.7 38.6 73.7 68.9 Adjusted R2 (%) 45.4 38.2 73.5 68.7 Significance 0.000 0.000 0.000 0.000 Highest VIF 4.194 3.047 3.319 3.340 Durbin-Watson 2.015 1.923 1.869 1.933 Where: * is p<0.05, ** is p<0.01, *** is p<0.001.

EBTCHit, EBTCHit+1 and EBTCHit-1 are average change earnings before interest and taxes per share after adding back R&D expenditure and amortisation in years t, t+1 and t-1; NICHit, NICHit+1 and NICHit-1 are average change in net profit after tax per share after adding back R&D expenditure and amortisation in years t, t+1 and t-1; RDEXPCAPit-1 is the amount in capitalizing firm’s balance sheet that represents amortisation of previous period capitalized R&D in year t-1; RDEXPEXPit-1 is the change in R&D expenditure by expensers in year t-1; RDCAPit-1 is the change in capitalized R&D expenditure in year t-1; LGTASS = log of total reported assets excluding R&D assets, and VIF = variance inflation factor. Difference in sample size within each year group is due to incomplete datasets and the removal of outliers.

The explanatory power for earnings before interest and taxes on a per share basis (EBTCH) had greater power than the net earnings after taxes on a per share basis (NICH). As management is in a better position to impact the before taxes earnings, and net earnings can be subject to non-recurring items and events that may be outside of management’s control, this finding is not surprising (Ahmed and Falk, 2006).

It was hypothesised that amortised and written down previous period capitalized R&D (RDEXPCAP) and previous period expensed R&D costs (RDEXPEXP) would not contribute significantly to the model and

32 that of the R&D-related predictor variables, capitalized previous period R&D (RDCAP) would be the most significant indicator of future earnings. RDCAP was significant for all four models, and in the one- year ahead models it had positive and significant coefficients demonstrating that a company's R&D accounting policies could provide a signal to the market about the company's future performance. However, in the two-years ahead models RDCAP's coefficient was significant but negative, indicating it had a negative relationship with future earnings. This finding on its own may appear odd, but when taken in the context of the study as a whole it is understandable. Due to the nature of the analysis, half of the R&D expenditures in model 6 and model 7's analysis set (years 2005-2007) were made in pre-recession conditions, but two-thirds of the data-points in that analysis had corresponding earnings observations that were taken from recession-struck markets (2006's R&D costs corresponded with 2008's earnings and similarly 2007's with 2009's earnings). The remaining R&D and earnings firm-year observations were all made in times of recession in which there would have been a strong downward pressure on earnings. As the majority of the data included recession firm-year observations in which earnings across the board would be down, it is conceivable that this contributed to the negative correlation between R&D and future earnings. It is worth noting that a previous study by Ahmed and Falk (2006) found that the association between capitalization and future earnings decreased as the time between the measurements increased and less importance is consequently attached to the findings of the two-year ahead model than the one-year ahead model.

It was anticipated that both RDEXPCAP and RDEXPEXP would not be significant as these R&D variables represented items that should not contribute to future earnings. They both however had positive values and for the most cases, significant coefficients. This finding was surprising and suggests that in line with the resource-based view of the firm, R&D intensity has an influence on firm performance (Chan et al., 2007).

3.2.3 Sensitivity Analyses

In a study such as this where there is a large difference in size between companies in the data set and the size of the predictor variables, scale could affect outcome of the analysis. To eliminate possible heteroscedasticity, all variables in the regression models were standardised by the number of outstanding shares.

The adjusted R2 values from research question 1 were comparable in size to those reported by Zhao (2002), Ahmed and Falk (2006), and Tsoligkas (2011) who similarly examined the association between share price and capitalized R&D costs. There has however been debate in the literature about the best standardisation method to use. Many authors used the same approach adopted in this study and standardised by outstanding shares, however Easton (1998) feels this method is inappropriate as

33 management has control over the number of shares in issue and this could lead to spurious results. Easton recommends that a more suitable standardisation is to use the company’s book value. A sensitivity analysis was therefore conducted in which regression model 1 and model 3 were standardised by the book value of the company rather than by outstanding shares.

As with the previous regressions there was no evidence of autocorrelation (Durbin-Watson values were 2.071 and 1.975 for model 1' and 3' respectively) and no multicollinearity with the highest VIF between the models being 1.235. Both models were highly significant with p<0.001. Whilst the adjusted R2 values were higher when standardised by book value (adjusted R2 in the sensitivity analysis were 82.7% and 81.2% for model 1' and model 3' respectively, compared with 78.2% and 74.6% in model 1 and model 3), the same dominance pattern existed with model 1' dominating model 3'. The coefficients showed equivalent significance and had the same sign regardless of method used. This finding is in line with that reported by Kothari et al. (2002) and Ahmed and Falk (2006) who conducted similar sensitivity analyses and ratified the decision to standardise by outstanding shares rather than by book value.

This research study utilised pooled data across different time frames in a cross-sectional analysis. With such a method it is possible that autocorrelation may arise. A potential work-around for this is to run the regressions yearly and use the average variable correlation estimates. However, there was an uneven number of firm year observations year-on-year. Autocorrelation was therefore checked using Durbin- Watson tests. In all the models, the Durbin-Watson statistics were close to the ideal value of 2, and were above both the dL value (1.633) of definite autocorrelation, and the dU value (1.715) of probable autocorrelation, based on the sample size and the number of variables in the regression (Durbin and Watson, 1951). It was concluded there was no autocorrelation in the sample. Similarly, the VIF values were all low and so there was no reason to suspect multicollinearity. The pooling of cross-sectional time series data was therefore considered justified and the results credible.

34 4. DISCUSSION

4.1 Summary of Findings This study set out to examine three research questions. The primary research question centred on whether the R&D reporting method utilised by a company could convey value relevant information to the market, i.e. is the capitalization of R&D costs value relevant? This question was further explored by examining whether the recent global recession had an effect on the value relevance of R&D capitalization by looking if there was a change in value relevance during the recession. The final part of this dissertation set out to explore if capitalization of R&D costs could be used as an indicator of future economic performance of a company. This study examined these research questions from a UK perspective. The UK makes an attractive setting for such an analysis as under IFRS accounting standards, management has discretion in whether to capitalize or expense R&D costs.

The study found that for the period 2005-2011, whilst the regression model that included R&D capitalization had a higher adjusted R2 value, the capitalization of R&D did not significantly contribute to the model and no inference of capitalization being more value relevant than expensing R&D costs could be made. It is surmised that this lack of significance was due the global recession. A sub-analysis of this dataset, in which the firm-year observations were divided into pre-recession and recession datasets, showed that prior to the recession the market believed that R&D costs that were capitalized as assets would produce future economic value and consequently, were considered value relevant. During the recession however, there was a large increase in the frequency of R&D capitalization which suggested possible earnings management. This was reflected in a reduction in the adjusted R2 value of the model and a negative and non-significant coefficient for R&D capitalization.

The investigation into the potential of R&D capitalization to act as a signal for future economic performance also produced mixed results. All four models were highly significant, with the models for two-years ahead having higher adjusted R2 values than for one-year ahead. The regressions showed that earnings before interest and taxes (EBIT) had greater explanatory power for future earnings than net profit after taxes. Based on the t-statistic, previous period capitalized R&D likewise had a greater influence on future EBIT than it had on future net profit. The coefficients for capitalized R&D for all the models were highly significant (p-values ranging from p<0.01 to p<0.001) and were positive in the one- year ahead models indicating that capitalized R&D could act as a valid signal for future earnings. In the two-year ahead models however, the coefficients were negative indicating that capitalized R&D was negatively correlated with future earnings and that the R&D assets did not contribute to future value. Since a large amount of the firm-year observations in the two-years ahead models were from the recession time frame, it is believed that this affected the results. Recessions are associated with lower

35 earnings and as half of the R&D expenditure in the analysis set was made in pre-recession conditions, but two-thirds of the earnings observations were taken during the recession, it stands to reason that this had a bearing on the outcome of the analysis. Whilst the one-year ahead model also suffered from having a mix of pre-recession and recession data, the ratio between the two was not as great as the two-years ahead model and the results showed that previous period R&D capitalization contributed positively towards future earnings and could therefore act as a signal to investors of future economic benefit.

4.2 Theoretical Implications The debate around capitalization of R&D costs revolves around the trade-off between reliability and relevance. It has been suggested that capitalizing R&D costs is value relevant to an investor and these intangible assets should be treated in the same way as any tangible asset as they produce economic value for the company. The results of this study highlight this debate as over the seven year period analysed, R&D capitalization was at times value relevant and at other times not, and it was shown to be potentially unreliable due to evidence of possible earnings manipulation. During the pre-recession period, R&D capitalization was positively associated with market value and the act of capitalizing R&D was seen as being more value relevant to an outside investor than expensing the R&D costs. These findings were consistent with those reported by many authors including Abrahams and Sidhu (1998), Ahmed and Falk (2006), Oswald and Zarowin (2007), and Tsoligkas (2011) who similarly found that capitalizing R&D had a higher association with market value than the immediate expensing of R&D costs.

During the recession however there was a change and R&D capitalization was negatively correlated with market value. This implied that investors were distrustful of the act of capitalization, possibly suspecting earnings management, and reacted negatively towards it. During the recession there was also a dramatic increase in the frequency of firms capitalizing R&D costs adding further support to this negative reaction to capitalization. This negative association is similar to what Cazavan-Jeny and Jeanjean (2006) reported for a sample of French companies.

The time frame in which the analysis was conducted provided a good opportunity to explore the robustness of the value relevance literature. Apart from a few studies that included a small amount of data from the tail-end of the savings and loan crisis of the early-1990s, none of the studies identified in the literature examined the value relevance of R&D capitalization in the context of recession hit markets. The results of this study calls into question the findings and recommendations of those studies. Where they reported that capitalize R&D conveyed relevant information to the market, this study found that whilst this was the case in good economic times, the low cost involved in capitalizing R&D leaves it open to exploitation for purposes of earnings management. Other studies have similarly found a lack of value relevance with R&D capitalization (Cazavan-Jeny, 2006, Markarian et al., 2008). These studies were

36 conducted in France and Italy where there is weaker legal enforcement and, as indicated by Leuz (2003), it was suggested that legal enforcement plays a role in value relevance studies, especially where weaker enforcement allows managers to be more opportunistic with respect to earnings management. This study however was conducted on a sample of companies from the UK where there is more rigorous corporate governance and legal enforcement. Whilst it is feasible that the reduced earnings associated with a recession could have contributed to the negative coefficient for capitalized R&D, the concurrent large increase in the frequency of capitalization for the period suggests that the market was also distrustful in the change in accounting policies and consequently assigned less value to the company as represented by its share price.

Going against this finding, the future earnings results did however show that R&D capitalization was associated with higher future earnings. Whilst the recession influenced the two-years ahead aspect of these results, overall, capitalizing R&D was positively correlated with future earnings. This finding mirrored that reported by Ahmed and Falk (2006) and Oswald and Zarowin (2007). With the problems of information asymmetry, which are often associated with the proprietary nature of R&D, it is difficult for a company to convey the value of the R&D to an outside investor. These findings suggest that capitalizing R&D would be a useful means to achieve this. By allowing the management of a company to capitalize and amortise the development work as an intangible asset, an outside investor would gains a means to ascribe value to that asset.

The results of this study introduce some interesting points of discussion for the reliability versus relevance debate. The argument for capitalizing R&D is that it increases the relevance of financial reporting to an outside investor, but the counter-argument is that due to the relative ease for earnings management, such capitalization may not be reliable. This study demonstrated both sides of the argument. It appears that during the recession there was evidence of earnings management and the reaction of the market was to discredit any signal for future value, lending support to immediate expensing argument as put forward by the reliability camp. However, when looking at the results from the future earnings analysis, R&D capitalization was correlated with higher earnings in future periods adding support for the capitalization and value relevant side of the argument.

37 4.3 Practical Implications One of the reasons for conducting empirical research into the relationship between stock market value and different accounting numbers is to assess the use of those numbers in accounting standards. In order to be useful for standard setting the underlying theory must be able to explain and predict the activity they are describing. One of the criticisms of the value relevance literature is that rather than being descriptive of the relationship between stock market valuation and accounting numbers, they tend to highlight only the empirical associations between them and consequently have limited value for standard setting(Holthausen and Watts, 2001; Ronen, 2001). Holthausen and Watts (2001) feel that many of the valuation methods used in the literature have restrictions in their use and this reduces their ability to be widely applied and consequently they provide little or no insight for standard setting. This argument is however countered as the purpose behind value relevance studies is not to be a definitive test that is solely responsible for standard setting, but to rather provide evidence for accounting standard setters to show how accounting numbers are reflected in share prices and can therefore help inform decisions on accounting standards (Barth et al., 2001). Although not the exclusive users of financial reports, equity investors are reliant of a company's financial reports and consequently they should provide relevant information but it should also be reliable.

The results of this study showed that capitalizing R&D does provide information on future value that would be useful to an investor. The reliability of this information is however questionable. To be a reliable signal of future earnings, capitalization of R&D should always be associated with earnings growth and future value. The current accounting standards specify this as well; under IAS38, development costs should only be capitalized as an intangible asset once the "technical and commercial feasibility of the asset for sale or use has been established". It is stipulated like this to increase the reliability of the information in the financial statements. Incidences of earnings management however reduce the validity of R&D capitalization as a signal, and impacts on its ability to reduce information asymmetry. Due to the low cost there is little to discourage a company sending a false signal. Rigorous corporate governance and enforcement should increase the reliability of the signal, but even in the highly regulated UK market this study showed evidence of earnings management with a subsequent loss of reliability in the signal. Whilst not investigated in this body of work, it is feasible that companies that are subject to higher levels of scrutiny do not manipulate their earnings (or do so to a lesser degree), but as an outside investor this is difficult to identify.

It is not easy to provide definitive recommendations based on the findings of this study. On the one hand, the study did show that in general capitalization does provide a credible signal for future earnings. The key point however in this statement is that it is only generally applicable. Unless an investor has a widely diversified portfolio, they may not benefit from using capitalization as an investment signal. If

38 diversified, the investments in the real Capitalizers should out-weigh the poorer investments in companies manipulating their earnings, however if an investor has a smaller portfolio he could conceivably invest exclusively in companies that are guilty of earnings management and the returns would not be as expected. In bull markets the signal from capitalization is more credible than in bear markets and this should be factored into to any investment strategy that utilises intangible assets resulting from R&D.

A final practical implication from this study relates to enforcement of accounting standards and how this can improve the relevance of R&D capitalization. Healy and Wahlen (1999) summarise the conundrum of reliability versus relevance nicely: "Standard setters are expected to consider conflicts between the relevance and reliability of accounting information under alternative standards. Standards that over-emphasize credibility in accounting data are likely to lead to financial statements that provide less relevant and less timely information on a firm's performance. Alternatively, standards that stress relevance and timeliness without appropriate consideration for credibility will generate accounting information that is viewed sceptically by financial report users" (p.366). In order to allow financial reports to convey more credible information on company performance, accounting standards must allow managers some discretion in financial reporting. This however creates opportunities for managers to misrepresent the company's performance as well. Factors that reduce earnings management could increase the value relevance of financial reports, including the role R&D capitalization. Kouki et al. (2011) made several recommendations that could be useful in reducing earnings management and consequently improve the reliability and the relevance of financial reports. Their recommendations focus on corporate governance to enforce accounting standards and include things like the size and composition of the board of directors so that opinions that benefit the manager are not overly represented, independent audit committees to reduce managerial opportunistic earnings management, and separation of function so that company managers cannot also be the company chairman.

4.4 Limitations There are several limitations to this study that reduces its generalizability. This study focused only on a UK data set. Whilst many other countries follow IFRS accounting standards, the cultures in different countries could impact the results as managers may behave differently. The study should therefore be extended to include other countries with different corporate cultures to assess if this has an impact. The analysed sample only included companies on the FTSE All Share Index. Whilst the All Share index captures most of the total market value of all publically traded companies in the UK, there are many micro-cap companies traded on markets such as the FTSE AIM market. Would the findings of this study be applicable to those companies as well considering the vastly different market capitalization, liquidity

39 and investor profile of the respective markets? The sample size was also relatively small. To limit variability due to different accounting standards, data was only collected from 2005 onwards as prior to this the UK did not make use of IFRS accounting standards, and whilst UK GAAP allowed capitalization, there are other differences between the accounting standards that could impact the validity of the results.

4.5 Directions for Future Research The results of this study have introduced a number of questions as to the ability of these findings to be generalised. It is clear that prior to the recession the findings were in line with the majority of the available literature and found that the capitalization of R&D costs was value relevant. During the recession this changed. There are many possible reasons behind this, some of which have been posited as an explanation for these results. It would be interesting to explore this further and investigate if different characteristics of the sample companies had a bearing on the results. For example, does having a larger market capitalization lend itself to a more reliable signal on capitalization? Is there an industry bias towards capitalization or earnings management? Is R&D intensity a factor and are R&D intensive companies less likely to skew their results as they typically have a large R&D spend? Another aspect that would be interesting to explore and which could provide better understanding of these findings is whether other economic downturns similarly experienced a change in frequency of capitalization and other mechanisms of earnings management that would affect the value relevance of accounting standards?

4.6 Reflections and Conclusions This study set out to test whether capitalizing R&D was value relevant, and in doing so, be a means to help reduce the information asymmetry that often exists between inside managers and outside investors, especially in companies with high levels of intangible assets. Intuitively one would think this is the case as in today's high-tech world, intangible assets are often more valuable than tangible ones. The bulk of the published literature also supports this point of view, as do accounting standard setters and under the IFRS accounting standards companies may capitalize development costs once the feasibility of the project has been established and the asset is likely to produce future economic benefit.

The findings of this study do not wholly agree with this. Research question 1 showed that R&D capitalization was not significantly associated with market value and that it provided no more insight into market value than expensing R&D costs. Further examination showed that the recent global recession had a significant impact on these results. Prior to the recession, capitalizing development costs was significantly value relevant and had a higher associated with market value than expensing R&D costs. During the recession this changed and the market appeared to become distrustful of capitalization.

40 Coinciding with the recession was an increase in the frequency of capitalization and at face value it appears that there was opportunistic manipulation of the financial accounts in order to smooth earnings in line with what had been forecast. However, whilst the market was distrustful of capitalization, the act was however associated with higher future earnings over the study period.

Capitalized R&D was associated with higher earnings and, during the bull markets leading up to the recession, was positively associated with market value. This shows that it can be a useful mechanism for reducing information asymmetry. The system appears to have been exploited during the recession; however this does not necessarily detract from its usefulness. It does show deficiencies in the controls that should be in place to eliminate earnings management. R&D capitalization is not the only mechanism utilised in earnings management. Effective corporate governance and stricter controls in the audit system would help eliminate all forms of earnings management, simultaneously improving the reliability and the relevance of financial reporting.

This dissertation presented many challenges, both intellectually and methodologically. As the head of an R&D team in an early stage pharmaceutical company, I am keenly aware of the difficulty in conveying the current and possible future value of development programmes to outsiders. The information is almost always privileged and cannot be made publically available other than on a superficial level. This creates a definite informational imbalance. News flow is also critical for maintaining investor interest, but this is also difficult, often due to the long development times of drugs. My interest in this topic therefore stemmed from this and a desire to identify possible means that could help reduce this imbalance. My knowledge of the field was limited prior to starting this research. This lead to many methodological challenges, but this created opportunities to learn new techniques to enable me to effectively collect, collate and analyse large amounts of financial data. Through the course of this dissertation I have learnt many things, and most importantly, I have gained greater insight into the challenges of not only conveying relevant information to the investor, but also the difficult balancing act facing accounting standard setters as they weigh up the benefits and pitfalls of allowing managers more discretion.

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17. Chambers D, Jennings R, and Thompson II RB (2003). Managerial discretion and accounting for research and development costs. Journal of Accounting, Auditing and Finance; 18 (1): 79-113.

42 18. Chan H, Faff R, Gharghori P, and Ho YK (2007). The relation between R&D intensity and future market returns: does expensing versus capitalization matter? Review of Quantitative Finance and Accounting; 29 (1): 25-51.

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26. Easton PD (1998). Discussion of revalued financial, tangible, and intangible assets: association with share prices and non-market-based value estimates. Journal of Accounting Research; 36 (3): 235-247.

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45 APPENDIX A – DISSERTATION PROPOSAL

The Proposal Template

Your Name, Programme of Study, Student Number, Module Title, Centre & Intake.

Andrew Gallagher, Master of Business Administration, 099025689, Research Methods - The Proposal, Open, February 2010

Specialism

Finance

Dissertation Tutor

Professor Chin Bin Tse. I have discussed my intended research and this proposal with Prof Tse initially at summer school 2011 and then again in 2012 via telephone call. I have also discussed specific aspects relating to methodology and the scope of investigation with Prof Tse through the Blackboard support forums.

The value relevance of discretionary capitalization of R&D costs in a UK context

Abstract

In the United States, all research and development (R&D) costs are expensed in the year that they are incurred, but in countries such as the UK, R&D costs maybe be discretionally capitalized as an intangible asset if the commercial feasibility of the asset has been established and it is believed the asset will yield economic benefit. The act of capitalizing R&D expenditure could therefore act as a signal to investors that the company expects near-term economic benefit. This study aims to investigate the value relevance of discretionary R&D accounting policies in the UK and to determine whether capitalization of R&D costs as an asset can act as a credible signal of future economic performance. Multiple linear regressions will be used to evaluate both the value relevance of R&D capitalization as well as whether there is a relationship between R&D capitalization and future economic performance. Earnings management however threatens the reliability of R&D capitalization as an investment signal and the incidence of it may increase in times of economic hardship. This will be explored by evaluating any change in value relevance pre- and post- the 2008-2012 global recession.

46 Introduction

The asymmetry of information between the management team of a company and investors can create an imbalance and it has been suggested that capitalizing R&D expenditure and amortising over its estimated life can reduce this by signalling to the market the assets expected value and consequently, conveying information about the company’s future prospects.

This will be explored by addressing the primary research question:

Does the R&D reporting method utilised by a company convey value relevant information to the market?

Secondarily it will be investigated:

Is there an association between R&D capitalization and future economic performance of a company?

Capitalizing R&D costs may be relevant for reducing information asymmetry between the company and investors, but due to the possibility of earnings management, the reliability of the information may be questionable. This is especially pertinent during times of economic hardship as companies that do not meet the market's expectations may attempt to manipulate their performance through capitalizing R&D to artificially inflate profits or limit losses. This will be further explored by examining:

Was R&D capitalization more or less value relevant prior to the 2008-2012 global recession?

My interest in this field stems from my work in the pharmaceutical industry where R&D is the single largest expense to the business. Employed at an early-stage pharmaceutical company, news flow is critical to maintain investor interest, but often, much of the information is privileged and cannot be made publically available, creating an informational imbalance between company insiders and the market. My interest therefore lies in techniques that would allow for a reduction in this information asymmetry, which is critical for early-stage pharmaceutical companies that frequently require recapitalization.

Relation to previous research

There is much debate about the treatment of R&D expenditure and globally there is no standardised accounting policy for its reporting. In the USA, it is mandated that for public companies, all R&D outlays should be expensed as they are incurred (SFAS No. 2). It is argued however that capitalizing R&D costs captures “statistically reliable and economically relevant information” and that failure to capitalize these outlays as intangible assets detracts from the relevance of financial reports (Lev and

47 Sougiannis, 1996: p 134). Lev and Zarowin (1999) argue that expensing R&D outlays goes against the fundamental accounting principle of matching costs with revenues as returns from R&D outlays are typically not realised in the same period that they are incurred. With R&D producing some of the most valuable assets of a company, not capturing their value on the balance sheet impacts the credibility of financial reports (Healy et al., 2002). An inability to disclose the value of these intangible assets contributes to information asymmetry between the company and outside investors with consequent economic effects (Abroody and Lev, 2000). Chan et al. (2001) reported stock mispricing in US R&D intensive companies that expensed all outlays, but in countries such as France and the UK, where there is selective capitalization, it was found that capitalizing R&D costs for successful projects and expensing unsuccessful one had greater value relevance than automatic expensing all R&D expenditure (Zhao, 2002). Abrahams and Sidhu (1998) reported a similar pattern in Australian firms and concluded that the ability to capitalize R&D outlays conveyed value relevant information to the investor; a finding echoed by Oswald and Zarowin (2007) who reported that there was a higher association between current-year returns and future earnings in UK firms that capitalized R&D over those who expensed them. However not all studies have reached the same conclusion and Cazavan-Jeny and JeanJean (2006) found that there was a negative correlation between R&D capitalization and stock-prices, with capitalizers tending to be smaller, less profitable companies.

The debate around capitalization of R&D outlays revolves around the trade-off between relevance and reliability due to the potential for manipulation and earnings management. Markarian et al. (2008) reported that rather than using capitalization to reduce information asymmetry, some firms are guilty of using it to smooth their earnings. This phenomenon can make investors wary of manipulation and consequently, capitalization of R&D may be perceived as bad news (Attallah and Khazabi, 2005; Chan et al., 2007). In light of this it must be questioned whether a credible signal can be obtained through the capitalization of R&D outlays.

In order for a signal to be credible, there must be a cost involved to prevent all parties sending the signal (Dye, 1985). Firms should capitalize outlays to signal future benefit; however, as the costs of a false signal are low, companies that derived no benefit from their R&D outlays may also capitalize for reasons of earnings management (Thi et al., 2009). Discretion can therefore introduce bias and calls into question the value relevance of R&D capitalization (Chambers et al., 2003).

The research that will be conducted in this dissertation will explore the value relevance of UK companies’ R&D accounting policies, and whether discretionary capitalization of R&D can be an indicator of future economic performance. The research will evaluate a more contemporary data set than previously reported and will investigate whether the 2008-2012 global recession has impacted on the value relevance of R&D accounting policies.

48 Proposed methods

Companies will be identified and classified as either expensers or capitalizers. They will be classified as expensers if they record R&D activity in their annual financial reports but with no corresponding reporting of R&D assets on the balance sheet, and classified as capitalizers if they have at least one balance sheet entry of R&D assets over the study period. Data will be collected for a ten year period from companies listed on the FTSE All Share Index and will be sourced using databases such as FAME and Thomson-Reuter's DataStream, as well as from annual reports. Expensers will be identified using FAME's R&D report, which will be cross-referenced with DataStream's Worldscope data type for ‘R&D expense’ (code WC01201), which represents all direct and indirect costs related to R&D. Capitalizers will be identified using Worldscope codes WC02504 and WC02505, which represents the net and gross book values of R&D expenditure, i.e. the capitalized R&D expenses. The capitalization data will be cross-referenced to published annual reports where available to verify that the search data relates only to R&D assets and not all intangible assets. In addition to data relating to the accounting treatment of R&D expenditure, other descriptive data to evaluate the economic characteristics of the sample companies shall be collected and will include variables such as market capitalization, book value, sales, earnings, earnings per share, beta, and financial leverage.

The value relevance of R&D accounting treatment will be evaluated using Ahmed and Falk's (2006) adaptation of Ohlson's valuation model (1995). Ohlson's model is a discounted residual income model and it equates the value of shareholder's capital to the sum of the company's book value and the discounted present value of expected abnormal or future residual income. Ahmed and Falk (2006) adapted Ohlson's model and, building on the work of Penman and Sougianis (1998), used realised earnings as a proxy for expected earnings.

The study will examine the value relevance of the R&D accounting treatment from two perspectives. The first will examine the relationship between capitalizing/expensing R&D costs and share price and will treat the sample as a whole by pooling the data across firms and years. The second will examine value relevance by looking at whether the choice of accounting treatment can guide future performance.

The relationship between R&D accounting treatments and share price will be examined using three models: model 1 pertains to capitalizers, model 2 to capitalizers whose accounting figures have been converted as if they had immediately expensed and model 3 to expensing firms:

49 1. P90 = α0 + β1EPS(Yrit) + β2SEQPS(Yrit) + β3LGTASS(Yrit) + β4RDBALPS(Yrit) + ε

2. P90 = α0 + β1EPSAD(Yrit) + β2SEQADPS(Yrit) + β3LGTASS(Yrit) + ε

3. P90 = α0 + β1EPS(Yrit) + β2SEQPS(Yrit) + β3LGTASS(Yrit) + ε

Where:

th  P90 = firm’s share price on 90 day after firm’s financial year end

 (Yrit) = year indicator; 2003-2012, for firm i  EPS = reported earnings per share  SEQPS = shareholder equity per share  LGTASS = log of total assets, excluding capitalized R&D balance at the end of the year  RDBALPS = capitalized R&D expenditure balance per share  EPSAD = earnings per share after deducting annual capitalized R&D expenditure  SEQADPS = shareholder equity per share after deducting R&D capitalized balance,  ε = error term. As annual financial statements are usually released three months after the end of the company’s financial year, the share price at that date (90 days) will be used to give a truer reflection of the firm’s value. To reduce possible heteroscedasticity, the explanatory variables in the regression will be standardised by the number of outstanding shares.

Whilst regressions 1-3 provide a good test on the value relevance for R&D accounting treatment, they do not address directly the association between R&D capitalization and the future performance of the firm. This will be assessed using the following models (Ahmed and Falk, 2006):

50 4. EBTCHit = β1EBTCHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit +ε

5. NICHit = β1NICHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit + ε

6. EBTCHit+1 = β1EBTCHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit +ε

7. NICHit+1 = β1NICHit-1 + β2RDEXPCAPit-1 + β3RDEXPEXPit-1 + β4RDCAPit-1 + β5LGTASSit + ε

Where:

 EBTCHit, EBTCHit-1 and EBTCHit+1 = change in earnings before tax, after adding back R&D expenditures and amortization, for years t, t-1 and t+1 respectively

 RDEXPCAPit-1 = change in R&D expensed and amortized by capitalizers in t-1

 RDEXPEXPit-1 = change in R&D expenditure by expensers in t-1

 LGTASSit, LGTASSit+1 = log of total assets, excluding capitalized R&D balance, in t and t+1 respectively

 NICHit, NICHit-1, NICHit+1 = change in net income, after adding back R&D expenditures and amortization for year t, t-1 and t+1 respectively  ε = error term. As in regressions 1-3, the explanatory variables in the above will be standardised by outstanding shares. There has been some debate over standardising variables by the number of outstanding shares. Easton (1998) argues that this approach may lead to invalid results due to the effect of scale and that as management has control over the number of shares in issue, they can change the share price through stock splits without changing the economic characteristics of the firm. This has a direct effect on the scale of any per-share measure of firm attributes so that “a regression of share price on the firm attributes will lead to coefficients that may capture no more than the fact that all variables have the same scale” (Easton, 1998: p 237). To account for this perceived methodological weakness, a sensitivity analysis shall be conducted in which explanatory variables in regressions 1-3 are standardised by book value rather than outstanding shares as suggested by Easton (1998).

The final aspect of this study will examine whether the 2008-2012 global recession had an effect on the incidence and value relevance of R&D capitalization pre- or post-recession. The same data and regression models will be used as in regressions 1-3 above, but they will be separated into pre- and post- recession datasets for comparative purposes.

51 Reflections

The greatest practical obstacle to the intended research revolves around the collection of data, especially data relating to capitalization of R&D expenditure as often R&D assets are grouped together with other intangible assets. Databases such as FAME and Datastream should provide all the required data in a usable format (assistance has already been sought from both University of Leicester's library and Thomson-Reuter's Datastream help desk to establish the validity of this approach), and several authors report the use of similar methods (for example Oswald and Zarowin, 2007: p 710). Cross referencing with company annual reports will however be conducted to ensure that the search results returned are in fact R&D assets and not other intangible assets. Other practical considerations are missing data fields within the dataset and the treatment of them. Whilst it is possible to employ forecasting techniques to fill any gaps, this would introduce further variation into the data and could impact on the validity of the results. It is anticipated therefore that incomplete datasets would either be omitted, or if required, the regression models may be amended to take into account the available data.

Whilst I have studied some statistics at a university level and made use of various statistical techniques during my post-graduate studies and in my day-to-day work, I have yet to perform linear regressions or use the SPSS statistical software. In my proposed time-table I have set aside 8 weeks (40 working days) to familiarise myself with the techniques that will be required for this research.

Related to the statistical analysis and briefly mentioned in the methods section above, due to differing variability between the explanatory variables in the analysis set, heteroskedastic errors are possible. To reduce possible heteroskedasticity, the explanatory variables will be standardised by the number of outstanding shares. Some authors (Easton, 1998) however have argued against this approach as management has control over the number of shares in issue. Whilst this will be addressed in the dissertation with the variables also being standardised against book value, the final conclusions will be drawn using the per share approach as in general this is the favoured technique reported in the literature.

Other potential theoretical problems relate to the dataset for the pre- vs post-recession analysis. The post- recession analysis will only contain three years data for the sample companies and it may not be possible to draw statistically significant conclusions from the data, especially as it can take five years before returns are evident in the annual accounts. However, changes in trends may be apparent and whilst not statistically significant, they could provide some insight into changing attitudes to the treatment of R&D expenditure during times of recession. Due to the different economic conditions, it may also be necessary when addressing the primary and secondary research questions to exclude data collected during the recession.

52 The research that will be conducted during this dissertation does not involve the study of any human beings, rather relying on secondary information that is freely available in the public domain. As such ethical and political considerations are not pertinent to this body of research.

Conclusion

The aim of this dissertation is to determine if it is value relevant to capitalize R&D expenditure as an asset, and in doing so, provide some guidance to outside investors of possible future economic performance. Whilst it seems logical that this could provide a valid signal to investors of impending profits arising from the asset, the system is open to exploitation through earnings management. In times of financial hardship such as the 2008-2012 recession, analysts and investors may be more critical of R&D capitalization for fear that such an approach has been implemented, and the value relevance will consequently decrease.

Considerable background research has already been conducted during the compilation this research proposal and the next steps will be to further consolidate this literature with papers relating to methodology, as the regressions outlined in this proposal may have to be amended depending on the available data. Further to this, immediate tasks that shall be conducted whilst awaiting feedback on this proposal are to increase my proficiency with SPSS as well as my knowledge of the fundamental principles behind regression analysis to facilitate any troubleshooting once the analysis dataset has been finalised.

53 Timetable

References

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2. Aboody D and Lev B (2000). Information asymmetry, R&D, and insider gains. Journal of Finance; 55 (6): 2747-2766.

3. Abrahams T and Sidhu BK (1998). The role of R&D capitalizations in firm valuation and performance measurement. Australian Journal of Management; 23 (2): 169-183.

4. Ahmed K and Falk H (2006). The value relevance of management's research and development reporting choice: evidence from Australia. Journal of Accounting and Public Policy; 25: 231-264.

5. Atallah G and Khazabi M (2005). A model of R&D capitalization. International Journal of Business and Economics; 4 (2): 107-121.

6. Cazavan-Jeny A and JeanJean T (2006). The negative impact of R&D capitalization: a value relevance approach. European Accounting Review; 15 (1): 37-61.

7. Chambers D, Jennings R, and Thompson II RB (2003). Managerial discretion and accounting for research and development costs. Journal of Accounting, Auditing and Finance; 18 (1): 79-113.

54 8. Chan H, Faff R, Gharghori P, and Ho YK (2007). The relation between R&D intensity and future market returns: does expensing versus capitalization matter? Review of Quantitative Finance and Accounting; 29 (1): 25-51.

9. Chan LKC, Lakonishok J and Sougiannis T (2001). The stock market valuation of research and development expenditures. The Journal of Finance; 56 (6): 2431-2456.

10. Dye RA (1985). Disclosure of non-proprietary information. Journal of Accounting Research; 23 (1): 123-145.

11. Easton PD (1998). Discussion of revalued financial, tangible, and intangible assets: association with share prices and non-market-based value estimates. Journal of Accounting Research; 36 (3): 235-247.

12. Healy PM, Myers SC, and Howe CD (2002). R&D accounting and the tradeoff between relevance and objectivity. Journal of Accounting Research; 40 (3): 677-710.

13. Lev B and Sougiannis T (1996). The capitalization, amortization, and value relevance of R&D. Journal of Accounting and Economics; 21: 107-138.

14. Lev B and Zarowin P (1999). The boundaries of financial reporting and how to extend them. Journal of Accounting Research; 37 (2): 353-385.

15. Markarian G, Pozza L, and Principe A (2008). Capitalization of R&D costs and earnings management: Evidence from Italian listed companies. International Journal of Accounting; 43 (3): 246.

16. Ohlson JA (1995). Earnings, book values, and dividends in equity valuation. Contemporary Accounting Research; 11 (2): 661-687.

17. Oswald DR and Zarowin P (2007). Capitalization of R&D and the informativeness of stock prices. European Accounting Review; 16 (4): 703-726.

18. Penman SH and Sougiannic T (1998). A comparison of dividend, cash flow, and earnings approaches to equity valuation. Contemporary Accounting Research; 15 (Fall): 343-384.

19. Thi TD, Kang H, and Schultze W (2009). Discretionary capitalization of R&D – the tradeoff between earnings management and signalling. AAA 2009 mid-year International Accounting Section (IAS) meeting paper (online). Retrieved from: http://papers.ssrn.com/sol3/papers.cfm? abstract_id=1275785 [accessed: 14 February 2012].

20. Zhao R (2002). Relative value relevance of R&D reporting: and international comparison. Journal of International Financial Management and Accounting; 13 (2): 153-174.