Value-relevance of nonfinancial information: The wireless communications industry

JOURNALOF

ELSEVIER

Journal of Accounting and Economics 22 (1996) 3 30

Accounting &Economics

Value-relevance of nonfinancial information: The wireless communications industry Eli A m i r a, B a r u c h L e v *'b aGraduate School of Business, Columbia University, New York, N Y 10027, USA bHaas School of Business, University of California-Berkeley, Berkeley, CA 94720, USA (Received May 1995: final version received June 1996)

Abstract

We examine the value-relevance to investors of financial (accounting) and nonfinancial information of independent cellular companies and find that, on a stand-alone basis, financial information (earnings, book values, and cash flows) are largely irrelevant for security valuation. Nonfinancial indicators, such as POPS (a growth proxy) and Market Penetration (an operating performance measure), are highly value-relevant. However, combined with nonfinancial information, earnings do contribute to the explanation of prices. The complementarity between financial and nonfinancial data is highlighted in this study.

Key words: Valuation-relevance; Industry analysis; Nonfinancial information; Cellular communication; POPS J E L classification: M41; L63

1. Introduction It has been argued that the financial information of firms in fast-changing, technology-based industries is of limited value to investors. 1 Telecommunications, *Corresponding author. We are grateful to Ray Ball (the editor), Mary Barth, William Beaver, Joshua Livnat, Terry Shevlin, Toshi Shibano, and Brett Trueman for their helpful comments. Seminar participants at University of Alberta, University of California at Berkeley, New York University, Stanford University, SUNY Buffalo, and Tel Aviv University also contributed to this study. KPMG Peat Marwick's financial support is much appreciated. For example: "In times of rapid change, the risk increases that business reporting will fall behind the pace of change, failing to provide what users need to know' (AICPA Special Committee on Financial Reporting, 1994, p. 5). 0165-4101/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved PI1 S0 1 6 5 - 4 101 ( 9 6 ) 0 0 4 3 0 - 2

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E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

biotechnology, and software producers, among other growth companies, invest heavily in intangibles, such as R&D, customer-base creation, franchise, and brand development, yet such investments are either immediately expensed in financial reports or arbitrarily amortized (e.g., the 40-year goodwill amortization common in technology acquisition). 2 Consequently, while significant market values are created in these industries by production and investment activities, key financial variables, such as earnings and book values, are often negative or excessively depressed and appear unrelated to market values. For example, while the total market value of equity of the independent, publicly traded cellular phone companies examined in this study was $34 billion in May 1993 (Table 1), the median earnings and free cash flows of these companies were consistently negative since their inception (mid 1980s), and their book values were so depressed as to yield a median market-to-book ratio of 12 - more than five times the corresponding ratio of industrial companies (Table 2). Such anomalous relations between market values and financial variables, typical to fast-changing, technology-based industries, raise the following questions: 1. What is the value-relevance of reported financial information of fast-changing, science-based companies? While earnings and book values of such companies are typically depressed due to excessive investment expensing, do they still provide relevant (predictive) information for asset valuation? 2. What is the incremental value-relevance of nonfinancial information (e.g., customer penetration rate of cellular companies) over that of financial information? Our main findings, based on a sample of independent cellular phone companies, are: 1. On a stand-alone basis, financial information (earnings, book values, and cash flows) are largely irrelevant for the valuation of cellular companies. However, when combined with nonfinancial information, and after adjustments are made for the excessive expensing of intangibles, some of these variables do contribute to the explanation of stock prices. This finding demonstrates the c o m p l e m e n t a r i t y between financial and nonfinancial information, as well as indicates that the traditional focus of accounting researchers on the former is overly restrictive and may lead to unwarranted conclusions.

ZTheonly exceptionto the uniform R&D expensingin the U.S. is softwaredevelopmentcost (SFAS 86). However,even in this case the capitalization is limited to a certain segment of the software development process (from the establishment of technological feasibility up to the production phase), and is not adhered to by several major softwaredevelopers(most notably Microsoft).

E. Amir, B. Lev/ Journal of Accounting and Economics 22 (1996) 3 30

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2. In the cellular industry, the value-relevance of nonfinancial information overwhelms that of traditional, financial indicators. For reasons explained below, we expect this to be the case in other science-based, high-growth sectors. This indicates the importance, in both practice and research, of significantly expanding the domain of the fundamental variables examined, to include nonfinancial information. Our findings have several disclosure implications, in particular with respect to customer acquisition costs, which are currently expensed by all publicly-held wireless companies. These costs, mainly in the form of commissions paid for new subscribers, are very high (range between $200 and $300 per customer) and are expected to increase, given the intensifying competition in the wireless industry. In such a fast growing industry (over 50 percent annual customer growth rate in the last 10 years), the full expensing of these costs creates an inverse relation between a company's success (growth) and reported earnings and book values. Given that the wireless industry has reached a certain degree of maturity, it appears that customer acquisition costs and other franchise-enhancing expenses, could be capitalized, similar to the mandated capitalization of costs related to the acquisition of insurance contracts (SFAS 60), the capitalization of loan origination fees (SFAS 91), the capitalization of costs related to franchise sales (SFAS 45) and to the acquisition of long-term contracts (FASB Technical Bulletin 90-1). In the wireless industry, the capitalized customer-acquisition costs can be amortized over the expected customer longevity. The capitalization of customer acquisition costs and other value-enhancing expenses may provide an attractive compromise between the full disclosure of fundamental value-drivers and the withholding of proprietary information. For example, cellular companies consider their churn rate (customer turnover) a closely guarded secret. This rate, however, is one of several information items required for the capitalization of customer acquisition costs. Accordingly, such capitalization will enhance financial reporting (improve the expense/revenuematching process and asset presentation), while not requiring a separate disclosure of the competitively-sensitive churn rate. Short of the capitalization of value-enhancing intangible investments, the disclosure of wireless companies could be improved. Current disclosure is inadequate, particularly because it does not distinguish between regular expenses and investment in intangibles. For example, customer acquisition and license application costs are generally lumped with salaries and other expenses in the line item sales, general and administrative expenses. A clear separation between regular expenses and costs which potentially enhance future cash flows will assist investors in the valuation of cellular companies. Differences in the value-relevance of financial variables across life cycle stages of companies have been noted before in the accounting literature. For example, Anthony and Ramesh (1992), using various proxies for growth (e.g., dividend

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E. Amir, B. Lev / Journal o f Accounting and Economics 22 (1996) 3-30

payout, firm age), report that investors' reaction to unexpected sales growth and capital expenditures is higher for growth companies than for stagnant ones. The apparent reason: acquisition of m a r k e t share and capital capacity are highly valued by investors in the early life cycle stage of firms. We do not need growth proxies, since we examine the relative value-relevance of financial and nonfinancial variables in the context of a particularly fast growing, worldwide industry - wireless c o m m u n i c a t i o n s - which is positioned at the cutting edge of technology. As such, this industry appears to represent other emerging high-growth industries. A study of nonfinancial information naturally focuses on an industry, since such information is typically industry-specific (e.g., load factor in airlines, store space of retailers, and n u m b e r of patents granted to pharmaceutical companies). Industry valuation studies, like the current one, are still rare in market-based accounting research, which relies heavily on large, cross-sectional (inter-industry) analysis. 3 In contrast, m u c h of e c o n o m i c research, particularly in the industrial organization area, has shifted years ago from cross-sectional studies to industry or sectoral analysis. 4 There is, of course, a tradeoff in industry studies - sample size and generalizability of findings for specificity of analysis and insights gained. Such a tradeoffis also present in the current analysis, which is based on a 10-year panel data of 14 publicly traded cellular companies. 5 We open (Section 2) with a brief discussion of salient developments and characteristics of the cellular c o m m u n i c a t i o n s industry, followed (Section 3) by a traditional market-based analysis which suggests that financial information is

3To be sure, there are industry studies in accounting - e.g., Lev (1979) and Harris and Ohlson (1990) on oil and gas, Wahlen (1994) and Barth (1994) on the thrift industry. However, market-based research - e.g., Ball and Brown (1968), Ou and Penman (1989), Bernard and Thomas (1989), Lev and Thiagarajan (1993) is typically inter-industry. 4In a comprehensive survey of industrial organization research, Schmalensee (1989, p. 952, emphasis ours) notes: Prior to the seminal work of Bain (1951, 1956), most empirical research in industrial organization involved detailed case studies of particular industries. These were time-consuming, involved a great deal of subjective judgement, and covered only a small sample of industries, in many of which antitrust litigation had made data available. Bain's inter-industry, cross-section approach seemed to make possible rapid and objective analysis of large samples of markets. Research interest accordingly shifted from industry studies to inter-industry work during the 1960s. ... But during this same decade a number of critics effectively challenged the data and methods used in inter-industry research, as well as the conventional interpretation of its findings. Interest shifted to work on the theory of imperfectly competitive markets and, more recently, to econometric industry studies employing formal models of conduct. Inter-industry studies are

now out of fashion. 5There are many more cellular operators in the U.S., but they are either privately-held or nonpublic subsidiaries of large companies, particularly the regional telephone companies ('Baby Bells'). These cellular operators cannot be incorporated in a capital market study such as ours.

E. Amir, B. Lev/ Journal of Accounting and Economics 22 (1996) 3 30

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largely value-irrelevant. Section 4 elaborates on the reasons for these findings, while Section 5 introduces nonfinancial variables and examines jointly the value-implications of financial and nonfinancial information. Section 6 analyzes the relevance of nonfinancial information in the market for corporate control. Section 7 contains concluding remarks.

2. The cellular communications industry Typical to an industry analysis, one has to gain familiarity with the technology and economics of the cellular industry to examine issues of value-relevance, and particularly to identify nonfinancial information items potentially relevant to investors. Cellular telephone service, developed scientifically in 1947 at AT&T's Bell Labs, made its commercial debut in 1983 and proved to be an immediate success. By the end of 1985 there were 340,000 cellular subscribers nationwide, growing in the subsequent eight years (to end of 1993) to 16 million subscribers an average annual growth rate of 62 percent. Cellular revenues have kept pace, increasing at an average annual rate of 48 percent between 1985 and 1993. The cellular customer base is expected to grow nationwide to 70 million subscribers by the year 2000. A similar and occasionally even higher growth in use of cellular phones has been experienced in other developed countries, particularly in Europe and East Asia. 6 Cellular telephone service is vastly superior to the earlier mobile telephone technologies (e.g., the Specialized Mobile Radio used by taxicabs), due to its ability to make more efficient use of the radio spectrum the scarce resource for which there are many competing demands (e.g., television and radio). Cellular technology permits many more simultaneous telephone conversations from the same quantity of radio spectrum than did earlier technologies. This technology, however, requires heavy investment in electronics and computers, making cellular companies very capital-intensive and their financial results particularly sensitive to arbitrary accounting rules, such as the straight-line depreciation of equipment or the 40-year maximum amortization of goodwill from acquisitions of cellular properties. A customer wishing to obtain cellular service acquires hardware (radio telephone) and enters into an agreement with a service provider (operator) who owns and operates cellular systems which furnish the radio link connecting the customer's telephone with the landline network. Alternatively, retail customers can connect with 'resellers' who buy service from operators at wholesale or bulk rates. Cellular service was at first mainly used by businesses, gradually giving up

6Sources:Shew(1994),Donaldson, Lufkin,and Jenrette (1994),Cellular TelephoneIndustry Association (t994).

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E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

market share to personal use. Given the different elasticities of demand between business and personal customers of cellular phones, the increase in the share of personal subscribers has significant effects on prices of service and revenues of providers. Indeed, cellular service prices have declined sharply over the last decade in real and in some aspects even in nominal terms. The fixed resource used by the cellular industry - the radio spectrum - gave rise to regulation by the Federal Communications Commission (FCC) and by the various states in which the service providers operate. The service of connecting customers to the landline telephone system is local and hence the prices charged by operators were regulated by the states. However, recent legislation transfers much of this regulatory power to the FCC. Entry into the cellular market is restricted by the FCC through its authority to license (granted for a maximum of 10 years) the use of radio spectrum necessary to provide cellular service. The main characteristic of the FCC's entry regulation is its authorization of t w o c o m p a n i e s (a duopoly) to provide service in each geographical area, in direct competition with each other. This is obviously a more liberal policy than the 'one provider of service' under the natural monopoly concept, but it falls far short of a free entry policy. The cellular industry was in the mid-1980s rather fragmented, mainly due to the initial lottery allocation of licenses by the FCC. Over time, the industry consolidated through mergers and acquisitions, and is now comprised of a relatively small number of large firms - subsidiaries of telephone companies as well as independent operators. Starting in 1992, the long distance telephone companies, AT&T and Sprint, joined the wireless industry by acquiring large ownership positions in cellular companies. The major strategic objective of acquisitions and partnership formation in the cellular industry is the expansion of c u s t o m e r c o v e r a g e , and in particular coverage of adjacent geographical markets, known as 'clustering'. 7 Clusters offer service providers operational economies of scale, resulting in a less expensive service to customers. Large clusters or service areas of single operators also decrease customers' need to use the services of other operators (called 'roamer' arrangements) when their calls extend beyond a given cluster. Such roamer arrangements, when available, are usually quite expensive. Table 1 presents the composition of the publicly-held U.S. Cellular industry in May 1993. The first group of companies, identified as 'independents', constitutes our sample. The second group includes the cellular subsidiaries of the regional telephone companies (Baby Bells), while the third group includes the cellular activities of other telephone companies. The table reports the market capitalization of each company (note, for telephone companies this reflects total value, not

7For example,of the 116 markets (areas) served by the U.S. Cellular Corporation at year-end 1992, 92 markets were part of a cluster, namely a contiguous area.

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

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Table 1 Major publicly held participants in the cellular telephone market

Company

Stock exchange

Market cap? (millions)

Net POPS b (millions)

Independent operators Associated Communications BCE Mobile Cellular Communications, Inc. Cell. Comm. of Puerto Rico, Inc. Cellular, Inc. Centennial Cellular Corp. Comcast Contel Cellular Inc. LIN Broadcasting Corporation McCaw Cellular Comm., Inc. Rogers Camel Mobile Comm. U.S. Cellular Corporation Vanguard Cellular Systems, Inc. Vodafone Group PLC

OTC TSE OTC OTC OTC OTC OTC OTC OTC OTC OTC AMEX OTC NYSE

748.5 2,014.3 1,587.1 175.5 119.7 158.1 2,876.5 1,524.2 5,014.9 8,857.4 2,018.7 1,454.8 509.3 6,825.4

5.7 15.0 7.8 2.9 2.9 3.9 5.0 24.2 26.9 60.4 22.6 21.7 6.2 57.3

NYSE NYSE NYSE NYSE NYSE NYSE NYSE

19,6(18.9 23,575.1 25,966.2 17,187.8 19,490.2 11,513.1 17,865.3

21.8 34.2 38.7 19.0 33.8 32.6 17.9

NYSE NYSE NYSE NYSE OTC NYSE NYSE N YSE AMEX

4,773.4 1,476.9 1,473.1 33,142.3 447.3 1,314.9 2,251.1 11,181.4 1,921.8

7.7 5.8 2.3 50.8 0.5 1.3 3.3 20.6 17.8

Regional Bell holding companies Ameritech Corporation Bell Atlantic Corporation BellSouth Corporation NYNEX Corporation Pacific Telesis Group Southwestern Bell Corporation US WEST, lnc.

Independent telephone companies ALLTEL Corporation Century Telephone Enterpr, Inc. Cincinnati Bell GTE Corporation Lincoln Telecom Rochester Telephone Southern New England Tel. Sprint Corporation Telephone and Data Systems

Source: Cellular Communications Industry, Spring 1993, by Donaldson, Lufkin, and Jenrette.

aMarket cap. = market value of the company's equity in millions of dollars as of May 1993. For independent operators, Market cap. represents the value of the cellular operations, while for regional and independent telephone companies, Market cap. represents the value of cellular and other operations, mainly telephone. bNet POPS = population coverage in millions, adjusted for percentage ownership. This measure is calculated as the total population in the area in which the company is licensed to operate, multiplied by the company's share of ownership.

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E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

just that of cellular activities), as well as the number of P O P S (i.e., total population in the licensed service area). This nonfinancial measure, reflecting the growth potential of the company, will play a major role in our analysis. For licensing purposes, the FCC divided the U.S. into 301 Metropolitan Service Areas (MSAs) and 428 Rural Service Areas (RSAs). In each area, one license was reserved for the wireline telephone company operating in the area, while the other license was granted to a nonwireline company, s Licenses were awarded to applicants through a combination of an FCC review and lotteries. By May 1986, the total number of applicants for the lottery was 37,650, with most applicants forming partnerships to reduce the risk of losing in the lottery. As of 1993, there were over 1,500 cellular systems on-line. Typical to high-tech sectors, the wireless communications industry is characterized by fast technological developments, calling for large investments with very uncertain and stretched-out payoffs. Currently, the main development is the switch from analog networks, which are reaching capacity limit in some markets, to digital networks which use call-overlapping and compression techniques to expand the number of subscribers eightfold or more (see Calhoun, 1988). This, however, is a very expensive technological advancement, causing the switch over to digital to be rather protracted. Also current is the auctioning off of Personal Communications Service (PCS) licenses by the FCC. The first stage of this auction, which raised over $10 billion, was for a competitive (to cellulars) phone service which also uses radio links but at a higher frequency and requiring less power than cellulars. This leads to smaller cells (coverage area) and allows for more subscribers and cheaper and lighter handsets. PCS will add two operators to the existing two in every region, thereby intensifying competition. Moving from cellular economics and technology to reported financial information, we present in Table 2 several key variables of cellular companies, with comparable ratios for industrial NYSE/AMEX and OTC companies. The data illustrate the problematic nature of financial information in reflecting value and growth of fast-changing and intangibles-intensive industries, like wireless communications. Thus, while considerable market value was created in the last 10 years in the cellular industry (see Market capitalization in Table 1, top panel), the median earnings of the sample companies was negative throughout the examined period (evidenced by the negative E / P ratios in Table 2), and even cash flows from operations (unaffected by depreciation and amortization) were occasionally negative or very low relative to industrial companies. Nevertheless, the negative earnings and low cash flows failed to intimidate investors, as

8This distinction between a wirelineand a nonwirelinecompany operating in an area is now often blurred. In addition, most of the large local wireline companies own some nonwireline licenses outside of their wireline service area.

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Table 2 Median financial ratios of cellular and other industrial companies Variable"

1993

1992

1991

1990

1989

1988

1. EPS/Price

CELL NYSE OTC

- 0.016 0.046 0.027

0.040 0.051 0.032

0.035 0.050 0.030

0.004 0.072 0.046

- 0.010 0.068 0.041

- 0.0l 1 0.076 0.048

2. CFO/Price

CELL NYSE OTC

0.013 0.093 0.028

0.011 0.108 0.036

0.017 0.117 0.047

- 0.005 0.147 0.065

0.002 0.105 0.040

- 0.006 0.108 11.041

3. Market-to-book

CELL NYSE OTC

t2.340 2.070 2.590

6.579 1.823 2.375

9.345 1.667 2.267

I 1.236 1.408 1.768

11.363 1.644 2.016

8.928 1.561 1.863

4. SGA/Sales

CELL NYSE OTC

0.421 0.201 0.271

0.461 0.202 0.276

0.527 0.202 0.275

0.464 0.195 0.269

0.547 0.189 0.265

0.601 0.192 11.269

5. D/PPE

CELL NYSE OTC

0.104 0.065 0.090

0.097 0.065 0.091

0.104 0.065 0.089

0.094 0.066 0.090

0.097 0.065 0.088

11.083 (I.066 0.088

6. D&A/PPE

CELL NYSE OTC

0.154 0.068 0.100

0.152 0.068 0.100

0.157 0.069 0.096

0.128 0.069 0.095

0.104 0.068 0.095

0.100 0.068 0.093

7. Debt/TAS

CELL NYSE OTC

0.568 0.290 0.241

0.618 0.305 0.279

0.458 0.311 0.277

0.604 0.313 0.300

0.488 0.312 0.297

11.449 0.294 /).286

8. FCF/Price

CELL NYSE OTC

- 0.019 0.015 - 0.029

- 0.049 0.020 - 11.025

- 0.081 0.026 - 0.009

- 0.077 0.015 - 0.019

0.054 0.010 - 0.027

0.047 0.013 0.026

Median financial ratios for the period 1988 1993 for three groups of companies: (i) the 14 independent cellular operators listed in Table 1 and denoted here as CELL, (ii) all C O M P U S T A T industrial companies with SIC codes between 2000 and 4999 (excluding cellular companies) listed on the New York and American Stock Exchanges and denoted as NYSE, (iii) all over-the-counter C O M P U STAT industrial companies with SIC codes between 2000 and 4999 (excluding cellular companies) denoted as OTC. aThese variables are defined as follows (annual C O M P U S T A T items in parentheses): EPS/Price primary earnings per share before extraordinary items (58) divided by share price at fiscal year-end (1991, CFO/Price = net cash from operating activities per-share (308/54) divided by share price at fiscal year-end (1991, Market-to-book = share price at fiscal year-end 11991 divided by book value of equity per share (60/251, SGA/Sales = selling, general, and administration expenses (189) divided by net sales (12), D / P P E - depreciation expenses ( 1 4 - 65) divided by gross property, plant, and equipment (7), D&A/PPE = depreciation and amortization expenses ( 141 divided by gross property, plant, and equipment (71, Debt/TAS = long-term debt plus the current portion of long-term debt (9 + 34) divided by total assets (61, FCF/Price = free cash flows per share (308 + 311)/54 divided by share value at fiscal year-end (1991.

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E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

indicated by the median market-to-book ratios of cellular companies (ratio no. 3 in Table 2) which were typically 4 to 6 times larger than those of other industrial companies. Such large market-to-book ratios reflect the high cellular growth expectations of investors, despite the depressed earnings and cash flows. A major reason for the depressed financials of cellular companies is the expensing of intangibles reflected, among others, by the very high ratio of sales, general and administrative expenses (SG&A) to revenues, and by the ratio of depreciation and amortization to property, plant and equipment (variables 4-5 in Table 2). These 'expenses' include the considerable commissions paid for customer acquisition and brand development (more on this in Section 4), as well as writeoffs of goodwill and costs of acquiring operating licenses (note the large difference between ratios 5 and 6 of cellular companies, indicating the size of goodwill amortization). The heavy financial expenses resulting from the large debt assumed in the process of investment in technology and infrastructure are also depressing earnings and book equity values of cellular companies. This is indicated by the relatively large debt-to-asset ratios of cellular companies and by the negative free cash flows reported at the bottom of Table 2. Thus, in the cellular industry, capital market values appear largely unrelated to reported financial variables. An empirical examination of this impression follows.

3. The value-relevance of financial information

We begin the empirical analysis by following the conventional route of regressing stock prices and returns on combinations of reported financial variables, under the assumption that the latter provide investors with valuerelevant information.9 We estimate the following regression from panel data of quarterly financial information of the 14 independent cellular companies listed in Table 1, covering the 10-year period 1984-1993: Rjt = OZ0 + o£1Ejt + o~2AEjt + Ujt,

(1)

Pit = flo + flaBVjt + flzEj, + v~t,

(2)

where R jr

= cumulative, market-adjusted return (raw return minus the corresponding value-weighted CRSP return) of firmj over three alternative periods: (i) a two-day window around quarter t earnings announcement (the day of announcement and the following day),

9In the absence of a clear preferencebetween price and return models,we followKothari and Zimmerman's(1993,p. 34) prescriptionthat '... use ofboth returnand pricemodelshas the potential to yieldmore convincingevidence'.

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

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(ii) a seven-day window centered on the quarterly earnings announcement, and (iii) a three-month window, starting with the beginning of the third month of quarter t and ending two months following it.1 o = stock price of firm j at the end of the second month following P jr quarter t. Ejt, AEjt = quarter t earnings per share (before extraordinary items) and the change in EPS (from the same quarter, a year earlier), respectively; in the returns model, these variables are deflated by beginning of quarter t stock price; in some regressions, EPS are replaced by operating cash flows per share. = book value per share of firm j at end of quarter t. Bvjt Since we are using panel data (same companies in successive quarters), we account in all the regressions for 'fixed firm and time effects', namely we include intercept dummies for each firm and quarter. These fixed effects capture constant firm-specific and time-specific factors, such as financial risk, not explicitly present in expressions (1) and (2). The price regressions include White's (1980) correction. Coefficient estimates of regressions (1) and (2) are reported in Table 3. F r o m panel A it is evident that for the two- and the seven-day return windows both the coefficients of earnings and the change in earnings are statistically insignificant, as are the F-values. The significant F-value of the seven-day regression and the ' r e s p e c t a b l e ' R 2 (0.10) are due to the fixed effects. Without the fixed effects, the F-values of the two- and seven-day regressions are 1.84 (p = 0.16) and 1.68 (p = 0.19), respectively, and the adjusted RZs are 0.006 and 0.005, respectively. For comparison purposes, we estimate regression (1) for telephone companies (SIC codes 4812 and 4813 on C O M P U S T A T ) , using quarterly earnings announcements for the same period as for the cellulars, 1984-1993. Results, reported at the bottom of panel A indicate that the coefficients of both earnings and the change in earnings of telephone companies are statistically significant. Since the significance of these coefficients may be due to the larger sample (713 observations for telephone companies vs. 304 for cellulars), we re-ran regression (1) on telephone companies' data restricting them to the recent period: 1991 93 (265 observations). The data in the bottom row of panel A indicate that even for this smaller sample the coefficient of the level of earnings is significant at the 0.05

1°Shifting the opening date of this window (i.e., to start at the beginning of quarter t, or at the beginning of the second month of quarter t) does not have an appreciableeffecton our findings. The window ending two months into the followingquarter assures that stock returns reflect the complete public dissemination of quarter t financials. We also examinea return window ending fivedays after the quarterly earnings announcement (and starting 65 days before it). Our results do not change materially with this window too.

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Table 3 Panel regressions of narrow-window returns (panel A), quarterly returns (panel B), and share prices (panel C) on combinations of financial variables of independent cellular companies, for the period 1984-1993 (all regressions include fixed c o m p a n y and quarter effects) Panel A: Narrow-window return regressions a EPSt/Pt I

AEPSt/P, 1

Adj. R 2

F-value

N

Two-day window

- 0.073 b ( - 0.60)

0.119 (1.30)

0.03

1.142 (0.24)

307

Seven-day window

- 0.038 ( - 0.20)

0.081 (0.60)

0.10

1.580 (0.01)

304

Telephone cos.: 1984~93 (seven-day window)

0,124 (1.75) 1

0.159 (2.46) 2

0.08

2,10 (0,00)

713

Telephone cos.: 1991 93 (seven-day window)

0.384 (2.38) 2

0.036 (0.22)

0.13

1.29 (0.09)

265

AEPSJPt 1

Adj. R 2

F-value

N

0.29

3.54 (0.00)

325

Panel B: Quarterly window¢ EPS,/Pt I

Cellular companies

- 0.554 ( - 0.90)

0.082 (0.20)

Telephone cos.: 1984 93

1.132 (2.60) 3

- 0.588 ( - 1.79) 1

0.22

2.02 (0.00)

739

Telephone cos.: 1991-93

1.545 (3.01) 3

- 0.154 ( -- 0.44)

0.27

1.730 (0.00)

282

ACFO,/P, a

Adj. R 2

F-value

N

0.042 (1.07)

0.38

4.22 (0.00)

186

CFOt/P,_ I

Cellular companies

- 0.042 (-0.12)

Telephone cos.: 1984-93

0.416 (2.51) 2

0.087 (0.49)

0.25

1.85 (0.00)

395

Telephone cos.: 1991-93

0.618 (3.21) 3

- 0.296 ( - 1.18)

0.26

1.692 (0.01)

228

B VPS

EPS

Adj. R 2

F-value

N

- 0.052 ( - 0.90)

1.612 (1.20)

0.83

25.42 (0.00)

329

2.250 (3.92) 3

0.83

42.96 (0.00)

1,005

Panel C: Stock prices d

Cellular companies

Telephone cos.: 1984-91

0.903 (16.05) 3

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Table 3 (continued)

Telephone cos.: 1991-93

BVPS

EPS

Adj. R z

F-value

0.939 (10.71) 3

1.050 (0.89)

0.86

44.00 (0.00)

N 570

"Narrow return windows include a two-day (day 0 and + 1) and a seven-day (day - 3 to day + 3} window, where day 0 is the day of earnings a n n o u n c e m e n t according to C O M P U S T A T . The dependent variable is cumulative market adjusted returns, calculated by subtracting from raw returns the C R S P value-weighted N Y S E / A M E X index. There are two independent variables: EPS,/Pt ~ = quarterly earnings per-share divided by share price at the end of the preceding quarter, andAEPS~/P, ~ - change in quarterly earnings per share divided by end-of-last-quarter share price. These variables are adjusted for stock splits and stock dividends. bTwo-tailed t-statistics are reported below the regression coefficients: p-values are reported below the regressions" F-statistic; superscript 1,2,3 denote statistical significance at the 0.10, 0.05, 0.01 levels, respectively. ~The quarterly market-adjusted return is computed from the beginning of the third m o n t h of the quarter to the end of the second m o n t h of the following quarter. Cash flows from operating activities per share (CFO) replace earnings per share at the bottom part of the panel. dThe dependent variable is share price at the end of the second m o n t h following quarter t. B V PS is quarter t's book value of equity per share and EPS is quarter t's primary earnings per share. White's (1980) heteroscedasticity-consistent t-statistics are reported in this panel.

level. Thus, the apparent no-reaction of investors to cellular companies' earnings announcements is not a general phenomenon. The two- and seven-day return windows reported in panel A of Table 3 may be too narrow to fully capture investors' reaction to cellular companies' earnings information. Accordingly, we consider in panel B a three-month window which includes the public release of quarter t financial results. Once again, the estimated coefficients of both the level of earnings and their change are statistically insignificant. The relatively large R 2 (0.29) is again due to the fixed firm and quarter effects. Without the fixed effects, the R 2 of the quarterly regressions is 0.001 and the F-value is 1.016 (p-value: 0.36). For telephone companies (period: 1984-93), the earnings level coefficient is positive and significant, though the coefficient of the earnings change is negative and borderline significant, perhaps due to collinearity with the level of earnings (Pearson correlation coefficient = 0.32). For the smaller sample (1991 93), the level of telephone companies' earnings is significant, while their change is not. 11

t~We also estimate the daily variances of the market-adjusted return of cellular stocks around the earnings announcement (from day - 3 to + 3) and compare these "report period' variances with those in other days (days - 23 to - 14 and + 14 to + 23, relative to the earnings announcementt. The return variances in the report period are not significantly higher than in the nonreport period.

16

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

The earnings of cellular companies are often negative; can this account for the seemingly value-irrelevance of earnings? Recent studies have reported an unusual earnings-returns relation when earnings are negative (Satin, 1993; Hayn, 1995). To examine this question, we chose another industry where negative earnings are prevalent - Biotechnology ( C O M P U S T A T SIC code 8731). For the 44 companies in that industry covering the 40 quarters ending in 1993 (a total of 777 observations), 72% of the reported quarterly earnings are negative (the corresponding percentage in our cellular sample is 69.2%). Estimation of regression (1) with the three-month market-adjusted returns as dependent variable (with fixed firm and quarter effects) over this predominantly negative earnings sample, yields a positive and statistically significant coefficient for the earnings change (coefficient = 0.643, t = 2.91) and an insignificant coefficient for the level of earnings (0.148, t = 0.49). Restricting the biotech sample to the recent period (1991-93), reduces the sample size to 453 observations. The coefficient of the earnings change for this subsample is still significant at the 0.10 level. The statistical significance of the earnings change coefficient, but not that of the level of earnings, suggests that while negative earnings may have no value implications (e.g., what price multiple should be applied to them?), the c h a n g e of such earnings (e.g., from very negative to less so) is relevant for securities pricing. Thus, judging from the significance of earnings in the predominantly negative earnings biotech sample, it appears that the frequent losses reported by cellular companies are not the only reason for the value-irrelevance of earnings. 12 Consistent with our findings, financial analysts following cellular companies hardly mention earnings in their industry analyses. However, they do pay close attention to cash flows of cellular companies, since cash flows abstract from the rather ad hoc depreciation and amortization of cellular assets.13 Accordingly, we estimated regression (1), substituting reported cash flow per share from operations for EPS. Estimates of this regression, reported in panel B of Table 3, indicate, once again, that the coefficients of both the level and change of operating cash flows are statistically insignificant. It appears, therefore, that the value-relevance problem does not lie primarily with depreciation and amortization charges, which do not affect cash flows, but rather with the large costs associated with the investment in cellular franchise and in customer-base creation. These costs, which are expensed rather than capitalized, depress both cash

12We also examined software companies (Compustat codes 7372 and 7373), where 33% of the quarterly earnings numbers for the period 1984-1993,were negative. We found that both the level and change of earnings coefficientsare positive and statisticallysignificantat the 0.01 level. 13Fo r example,the Donaldson, Lufkin,and Jenrette,Summer 1994report on the wirelesscommunications industry, does not even mention earnings in its 9 page (pp. 6-15) discussion of the periodic performanceof cellularcompanies. Cash flows,however,are mentioned frequentlyand provide the basis for their 'valuation model'.

E. Amir. B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

17

flows and earnings. It is interesting to note that in cases where cash outflows (e.g., for investment) benefit future periods, accrual accounting is aimed at adjusting such cash flows to better reflect the matching of revenues and expenses. In cellulars' financial reports, however, accrual earnings fail to adjust cash flows, given the excessive expensing of intangible investments. Finally, if stock returns are unaffected by cellular earnings and cash flows, perhaps stock p r i c e s are. Accordingly, we estimate regression (2) - stock prices (at end of the second month following quarter t) regressed on book value-pershare and EPS (model motivated by Ohlson, 1995). Coefficient estimates of this regression, reported in panel C of Table 3, are consistent with the returnsearnings results. Neither the coefficient of book value nor that of earnings are statistically significant (the R 2 of this regression without the fixed effects is 0.04). The corresponding coefficients for telephone companies are, as expected, highly statistically significant. Estimates of the price regression for biotechnology companies, where 72% of the company-quarter earnings observations are negative, yielded a positive coefficient for book value (0.732, t = 4.57), yet a negative coefficient for earnings ( - 1.894, t = - 3.53). The nonsensical coefficient sign of earnings suggests that, similarly to the cellulars' case, the earnings of biotechnology companies are of dubious relevance for securities pricing. 14

4. Why the irrelevance of cellular financials? The accounting measurement and reporting system is ill-equipped to provide value-relevant information in emerging high-tech industries, such as wireless communications. These industries are characterized by heavy investment in intangibles, such as R&D and franchise development, and by substantial spending on the development of customer-base and market share. These investments are largely expensed in financial statements, leading to depressed and often irrelevant earnings and book value figures. Consider, for example, the following comment made on a wireless company (Wall Street Journal, March 28, 1995, p. B6, emphasis ours): 'Nextel Communications Inc.'s loss widened sharply in the fourth quarter and is expected to continue to grow, reflecting the climbing cost o f b u i l d i n g a n e w d i g i t a l w i r e l e s s n e t w o r k . . . . 'It is expected that losses will continue to widen until we can aggressively market the new digital wireless services', a Nextel spokesman said.'

14For the softwaresample described in Footnote 12, the stock price regressionyieldspositiveand statistically significantcoefficientsfor both earnings (coefficient= 2.731, t = 11.47),and book value (coefficient= 1.328, t = 24.57).

18

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

If earnings were measured to reflect a matching of costs with benefits, the 'cost of building a new digital wireless network' surely could not create a 'sharply widening' loss. The only explanation to this contradiction in terms is the existence of a cost/benefit mismatch in currently reported earnings of wireless companies, resulting from a conservative investment writeoff. More generally, consider the ratio of sales, general and administrative (SG&A) expenses to revenues of cellular companies (ratio 4 in Table 2), whose median value varies between 42 to 60% - twice to three times the corresponding ratios of other industrial companies. One suspects that a substantial part of these expenses is in fact an investment, a suspicion confirmed by the MD&As of cellular companies. For example, AirTouch Communications, whose SG&A and depreciation and amortization expenses in 1993 accounted for 72.4 percent of total revenues, comments in its M D & A (emphasis ours): The decrease [in the percentage of SG&A expenses to revenue in 1993] was partially offset by an increase in agent commissions resulting from the increase in new cellular subscribers and the increase in marketing and promotional expenses which commenced in 1992. The 1992 increase similarly reflects commissions paid for new cellular subscribers, expenses associated with new marketing efforts, and other business development initiatives [-all fully expensed] . . . . General, administrative and other expenses primarily consist of... international license application costs .... and increased start-up expenses relating to the development of wireless data services .... The increase in 1992 from the previous year was primarily due to greater costs associated with the Company's pursuit of international license awards and expenses associated with investments in new products and services, ... costs of supportin9 the Company's anticipated growth, including entry into new business opportunities, is expected to cause general, administrative and other expenses to continue increasin9 as a percentage of net operating revenues .... Depreciation and amortization primarily consists o f . . . amortization of intangibles such as FCC license costs and goodwill'. As made clear in the preceding quote, a substantial portion of AirTouch's SG&A expenses as well as amortization costs are, in fact, investments in increasing the customer-base, developing new businesses, and securing domestic and international cellular licenses. Such a mismatch of costs and benefits in the process of earnings calculation is, of course, not unique to AirTouch Communications; rather it is typical to all wireless firms and to varying degrees to other science-based, high-growth companies. To empirically examine the appropriateness of GAAP treatment of cellulars' intangibles, we regressed the three-month market-adjusted returns of the sample companies on the level and change of quarterly earnings (deflated by stock price)

19

E. Amir, B. Lev/ Journal qf Accounting and Economics 22 (1996) 3 30

before S G & A expenses, a l o n g with the level a n d c h a n g e of S G & A expenses (with fixed c o m p a n y a n d q u a r t e r effects). Results, p r e s e n t e d below, s t r o n g l y indicate that r e p o r t e d S G & A expenses are not perceived by investors as c u r r e n t - p e r i o d expenses. Rather, the positive, large, a n d highly significant coefficient of S G & A expenses (coefficient = 7.41, t-value = 3.60) indicates that these items are considered by investors an i n v e s t m e n t h a v i n g a s u b s t a n t i a l positive i m p a c t on future cash flows.1 s

Coefficient estimates of regression (1) SG&A extracted from earnings (t-values in parentheses)

Dependent variable Three-month marketadjusted return

Earnings before SG&A

Earnings change before SG&A

SG&A expenses

Change in SG&A expenses

- 0.149 ( - 0.30)

0.013 {0.00)

7.410 (3.60)"~

1.240 { 0.60}

R2

N

0.32

315

Similar results are o b t a i n e d when the m a r k e t - t o - b o o k ratio of cellular c o m panies, reflecting investors' g r o w t h expectations, is regressed on earnings before S G & A expenses a n d d e p r e c i a t i o n a n d a m o r t i z a t i o n , as well as on the latter two items s e p a r a t e l y (all i n d e p e n d e n t variables deflated by b o o k value). As is evident from the estimates below, the coefficients of b o t h S G & A expenses a n d d e p r e c i a tion a n d a m o r t i z a t i o n costs are positive (clearly inconsistent with their G A A P t r e a t m e n t as expenses), very large a n d highly statistically significant. W h e n c a p i t a l e x p e n d i t u r e s are i n c o r p o r a t e d in the e q u a t i o n , their e s t i m a t e d coefficient is also positive a n d significant.

Coefficient estimates of regression of market-to-book on earnings components (t-values in parentheses) Dependent variable Market-tobook ratio

l/Book

Adjusted earnings over book

SG&A expenses over book

Depr.& amort. over book

2.107 (8.38)3

-- 1.748 ( - 1.25)

31.529 (12.33}3

25.640 (5.64)3

R2

N

0.92

26t

15This result is similar to that obtained when returns are regressed on earnings before R&D expenditures and on R&D expenditures (e.g., Sougiannis, 1994; Lev and Sougiannis, 1996).

20

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

We conclude, therefore, that G A A P is inconsistent with investors' valuation of cellular companies. 16 In the interpretation of these and other results in this study, the possible effects of a survivorship bias should be considered. Specifically, our sample consists of cellular companies that were in operation in 1993. These are, obviously, relatively successful firms, and given the importance of scale economies in this industry (Section 2), they are likely to be 'scale-game winners'. Accordingly, some of our estimates (e.g., the regression coefficients of SG&A expenses in this section) may be biased upward relative to the industry, as a result of the survivorship bias. Finally, it can be argued that the evidence presented above on the deficiencies of financial reporting in the cellular industry is just a manifestation of accounting conservatism, where investors are able to 'sort things out' (as we did in the above regressions by separating SG&A and amortization expenses from earnings). This would be the case if the information provided in cellulars' financial reports were sufficiently rich and detailed to allow investors to undo the excessive conservatism and properly evaluate the performance of cellular companies. However, the information provided publicly is insufficient for this task. In particular, cellular companies typically do not provide breakdowns of reported SG&A expenses to conventional expenses (e.g., salaries, rent) and investments (e.g., commissions paid for customer acquisition). Investors are therefore unable to separate regular expenses from those items which are expected to enhance future cash flows. Furthermore, cellular companies do not disclose their customer churn rate (turnover), without which customer acquisition costs cannot be capitalized and amortized. While the evidence reported above indicates that, on average, investors counteract the conservative investment writeoffs, it is not clear whether without sufficiently detailed information they can make the required adjustments for every firm and time period.

5. The value-relevance of nonfinaneial information The major conclusion from the preceding analysis is that key financial statement variables - earnings, book values, and cash flows - fail to provide

16The inconsistency of GAAP with shareholder value is also reflected in the determinants of management compensation in cellular companies. We have examined the 1993 proxy statements of the 14 sample firms. Of the ten firms which provided information on specificcompensation drivers, six did not mention earnings as a compensation driver. The remaining four companies mentioned earnings along with several nonfinancial drivers. Most determinants of management compensation are nonaccounting, such as subscriber growth, cost per new subscriber, churn rate, reduction in number of subscriber terminations, and market share increase. Shareholder value growth is a common compensation determinant of cellular companies.

21

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

value-relevant information to investors in cellular companies. Could it be that this failure is due to our restriction of the explanatory variables to accounting indicators, and that in a more complete valuation model, including financial as well as nonfinancial variables, the former will be found value-relevant? This question is of particular interest to accounting researchers, since traditional capital market-based analysis is largely restricted to reported accounting information.

5.1. Nonfinancial cellular information Cellular service in the U.S. is organized by geographic areas, where two providers (operators) are licensed in each area to service customers (Section 2). The total population in a service area, therefore, indicates the growth potential of the licensed operator. Population size, abbreviated to POPS in the cellular trade, is obviously an important, forward-looking value indicator. Not all POPS are borne equal: customers in metropolitan areas (particularly businesses) have a higher and less elastic demand for cellular service than customers in rural areas (mostly individuals). Hence, POPS in metropolitan service areas are in general more highly valued by investors than POPS in rural service areas. Operators (cellular companies) generally own licenses in several geographic areas through partnerships and mutual stock holdings. The total POPS value of a company reflects the web of such partial ownerships. For example, in its 1992 financial report, Associated Communications Corporation provided the following breakdown of its total POPS:

Markets

Ownership %

Market population

POPS

Domestic market

Albany, NY Buffalo, NY Pittsburgh, PA Rochester, NY San FranciscoSan Jose, CA

65.83 50.00 35.70 57.14

836,265 1,178,790 2,074,942 1,007,621

550,513 589,395 740,754 575,755

6.00

5,303,496 10,401,114

318,210 2,774,627

30.15

7,100,000

2,140,650

17,501,114

4,915,277

International market

Southeastern MexicoYucatan Peninsula Total domestic and international

22

E. Amir, B. Lev/ Journal of Accounting and Economics 22 (1996) 3-30

Thus, the total population in the markets serviced by Associated Communications as of December 31, 1992 was 17,501,114, while the company's total P O P S figure adjusted for percentage ownership was 4,915,277. Of that figure, 2.77 million P O P S are domestic and 2.14 million are international. While P O P S values reflect the growth potential of the company, the actual realization of this potential is indicated by the number of subscribers. The ratio of subscribers to P O P S is known as the penetration rate, and is an important measure of operating and competitive success. Companies (as well as countries) vary considerably by penetration rates. For example, while M c C a w Cellular's average penetration rate in the first quarter of 1994 was 3.33%, Southwestern Bell's rate was 5.78%. The domestic average penetration rate of all U.S. cellular operators was 3.51% in 1994 (Donaldson, Lufkin, and Jenrette, 1994). Other frequently mentioned nonfinancial measures in the cellular industry are subscribers per cell cite and subscribers per employee. 17 A particularly important indicator of competitive performance is the company's churn rate, which indicates the average length of time customers stay with the cellular operator. The churn rate, however, is not publicly disclosed by cellular companies. Another potentially important performance indicator not regularly disclosed is the cost of adding a subscriber, which reflects the commissions paid to agents for securing subscribers and other customer acquisition costs. The value-relevance of the publicly disclosed nonfinancials of cellular companies is examined below. 5.2. The value-relevance of nonfinancials

F r o m companies' financial statements and analysts' reports we obtained firm-specific quarterly data (for the period 1984-1993) for the following nonfinancials: POPS, the breakdown of total P O P S to those in metropolitan and rural areas, and the number of cellular subscribers from which the customer penetration rate (Subscribers/POPS) can be computed. Obviously, our study understates the value-relevance of nonfinancials, given that we have no access to key data, such as the churn rate and the cost of acquiring a subscriber. H o w should nonfinancial variables be incorporated with financials in a valuation model? Essentially, this task is performed by the accounting system which transforms primitive nonfinancials, such as hours of work and quantities of raw materials, into monetary values of costs, earnings, and assets. In a sense, the accounting system 'prices' nonfinancials relative to each other, so that an hour of employee's work can be added to a square foot of steel plate, resulting in

I 7The area served by an operator is divided into 'cells'. Each cell has a 'cell site' where signals are transmitted to and received from mobile units. The signals are then transmitted to the Mobile Telephone Switching Office(MTSO), a transmission which uses landlines or a microwavelink. The MTSO links the calls to the Public Switched Telephone Network (PSTN).

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

23

a cost of goods sold figure. It is therefore natural to relate the monetized financial information (e.g., earnings and book values) to stock prices and returns, as is done in practice and by accounting and finance researchers. But how should untransformed (primitive) nonfinancials, such as POPS and customer penetration rates, be related to financial variables, such as earnings and book values and ultimately to stock prices and returns? Does one need, for example, to price a penetration rate prior to its incorporation in a valuation model? Should the nonfinancials be transformed to financials by a cost or a production function? Given no theoretical guideline for such model specifications, we proceed by simply combining linearly the financial and nonfinancial variables, while noting that an appropriate combination of financial and nonfinancial indicators (i.e., a complete model of fundamental value-drivers) deserves further consideration. Table 4 provides coefficient estimates from regressions of stock price and market-to-book values on various combinations of cellular companies' financial and nonfinancial variables. The estimates of the price regressions in panel A indicate that POPS (second regression), a measure of growth potential, is positively and significantly associated with stock prices. 18 Notably, when the POPS variable is combined with book value and earnings (third line in panel A), the latter two become statistically significant, in contrast to their insignificance on a stand-alone basis (first line in Table 4 and Table 3). When Penetration rate (PEN = number of subscribers divided by POPS - a measure of operating success) is added to the regression (bottom line, panel A), it is statistically significant, along with the other variables. The coefficient of earnings in regression 4 is, as expected, positive, indicating that once growth potential is accounted for in the price regression (by POPS), an incremental dollar of earnings is appreciated by investors. The negative coefficient of book value appears at first counterintuitive. Recall, however, that the book value of cellular companies reflects the cumulative effect of current and past expensing of intangibles (discussed in Section 4). Accordingly, low book values generally reflect large investment in cellular franchise and customer acquisitions, which should be associated with high prices. Panel B of Table 4 provides coefficient estimates of the market-to-book regressions. Once more (regression 2) the coefficient of POPS, on a stand-alone basis, is positive as expected and highly statistically significant. When POPS is combined with the financial variables (regression 4), earnings-over-book value

lSUnlike earnings, the actual publication date of quarterly P O P S is not easily determinable. To avoid the possibility that for some companies the P O P S value was not publicly available at the time stock price and returns are measured (i.e., end of second m o n t h following quarter t), we ran Table 4 regressions with values of P O P S lagged one quarter. Coefficient estimates of the lagged P O P S variable are close to those reported in Table 4, with somewhat lower t-value (still significant at the 0.05 level). Accordingly, the timeliness of P O P S data does not seem to materially affect our findings.

24

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

Table 4 Coefficient estimates of regressions of share prices (panel A) and market-to-book ratios (panel B) on combinations of financial and nonfinancial fundamentals of cellular companies (all regressions include fixed firm and quarter effects) Panel A: Dependent variable

1.

-

stock pricea

BVPS

EPS

- 0.052 b ( - 0.90)

1.612 (1.20)

2.

--

POPS

PEN

Adj. R 2

N

--

0.83

329

--

4.956 (2.22) 2

--

0.87

329

3.

- 0.390 ( - 4.20) 3

3.780 (2.90) 3

14.560 (4.70) 3

--

0.85

329

4.

- 0.644 ( - 5.73) 3

4.817 (3.79) 3

15.490 (5.00) 3

5.92 (2.72) 3

0.93

225

Panel B: Dependent variable - market-to-book ratio c

1. 2.

1/BVPS

EPS(A)/ BVPS

4.938 (18.00)3

- 12.966 ( _ 9.70)3

.

.

3.

3.190 (13.30) 3

4.

2.160 (8.74) 3

SGA/ BVPS

.

D&A/ BVPS

--

Adj. R 2

N

0.83

263

88.929 (21.98) 3

0.84

263

65.557 (18.96) 3

0.91

263

42.422 (11.020) 3

0.94

263

--

.

--

--

4.171 (2.72) 3

POPS/ BVPS

24.038 (7.18) 3

11.093 (2.88) 3

--

aThe dependent variable is share price at the end of the second m o n t h following quarter t. The independent variables are: BVPS is quarter t's book value of equity per share. EPS is quarter t's primary earnings per share. POPS is quarter t's population coverage calculated as the total population in the company's licensed area multiplied by the finn's percentage ownership. PEN (penetration) is defined as the n u m b e r of actual subscribers (customers) divided by POPS. bWhite's (1980) heteroscedasticity-consistent t-statistics are reported below the regression coefficients in this table. Superscript 1,2,3 denote statistical significance at the 0.10, 0.05, 0.01 levels, respectively. CThe market-to-book ratio is measured using share price at the end of the second m o n t h following quarter t. EPS(A) denotes earnings per share before selling, general, and administrative expenses per share (SGA). D&A denotes depreciation and amortization expenses per share. BVPS and POPS are as described in footnote a above. Observations with negative book value of equity were omitted. becomes

p o s i t i v e a n d h i g h l y s i g n i f i c a n t ( c o e f f i c i e n t = 4 . 1 7 1 , t - v a l u e = 2.72), i n

contrast

with its negative

variables (regression

value when

1). T h e G A A P

the regressors

are restricted

'expenses' - SG&A

tization - are positive and highly significant, indicating

to financial

and depreciation/amorthat investors consider

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

25

these items as enhancing future growth rather than as periodic expenses. Given the sample mean values of SG&A-to-book and D&A-to-book, a dollar of the former contributes, on average, $3.34 to market value, while a dollar of D&A contributes $0.59 to market value. We get mixed results for the return regressions (not reported in Table 4). When the three-months market-adjusted returns (same as those in Table 3) are regressed on earnings and POPS, both the coefficients of the level and change of P O P S are highly statistically significant (coefficients of P O P S level and change: 7.843 (t = 4.10) and 7.156 (t = 2.20), respectively). However, in contrast with the price and market-to-book regressions (Table 4), both the coefficients of the level and change of earnings remain statistically insignificant. The reason for the different performance of earnings may be that in returns regressions investors' expected earnings play an important role and we may have misspecified those expectations. In the price regressions, on the other hand, expected values of current earnings are irrelevant. An important inference from the estimates of Table 4 is that, whereas on a stand-alone basis (the current paradigm in financial accounting research) financial variables appear to be of marginal value-relevance, or irrelevant altogether, in a more complete model including nonfinancials the actual relevance of the accounting data is manifested. Stated differently, the incorporation in the price and market-to-book regressions of the main value-drivers of cellulars - P O P S and Penetration - mitigates the correlated omitted variables problem present in most current valuation models used by researchers, and thereby better highlights the relevance of both the financial and nonfinancial variables. We have so far related fundamental variables (financial as well as nonfin~ncials) to market values. Additional insight into the interaction between financial and nonfinancial variables can be gained by regressing quarterly EPS on various combinations of publicly available nonfinancial indicators. Regression 1 in Table 5 indicates that P O P S and Penetration (both level and change) are negatively and significantly associated with reported earnings. This is consistent with our discussion above, suggesting that due to the excessive expensing of intangibles, the larger the investment in cellular franchise and customer-base, the lower reported earnings. While growth (reflected by P O P S and Penetration) is negatively related to reported earnings, the number of actual customers (SUB in Table 5), is strongly and positively related to earnings. The reason: once the costs of the franchise (POPS) and customer acquisition (PEN) are accounted for, the larger the number of currently paying customers, the higher reported earnings. In the second regression of Table 5 the company's total P O P S are decomposed into P O P S in metropolitan areas (MSA) and those in rural areas (RSA). Both coefficients are negative and highly significant, but that of rural P O P S (RSA) is twice as large as that of metropolitan P O P S (MSA). The reason is that

26

E. Amir, B. L e v / J o u r n a l o f A c c o u n t i n g a n d E c o n o m i c s 22 (1996) 3 - 3 0

I 0

d

r~

I

I

I

I

I

I

I

I

~J = 0

0

0

N 8 0 e~ o

~o oo

g

.~.

~0

I

I

0

~

8

oo

o

o .o

I

t¢'5

o

0

'4=

,-, ~,, ,.~

.~, ~

=

...o

~'r.=

*~

E. Amir. B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

27

the costs per customer of maintaining service in rural areas are higher than in metropolitan areas (e.g., given the relative sparsity of customers in rural areas, more cell cites have to be built and maintained in rural areas than in metropolitan areas). Furthermore, revenues per dollar of investment in rural areas are lower than in metropolitan areas, due to the higher proportion of priceconscious individual customers in the former. Accordingly, the higher costs and lower revenues in rural areas are reflected in a larger negative association with earnings. The main conclusion from the estimates of Table 5 is that within the current GAAP of cellulars, the more successful the company is in securing growth the lower its reported earnings.

6. The market for control of cellulars

The value-relevance of financial and nonfinancial measures in the cellular industry was so far assessed on the basis of stock prices and returns. An alternative value indicator can be obtained from the market for corporate control, namely prices paid in mergers, acquisitions, and leveraged buyouts of cellular operations. This is a particularly relevant value indicator in the cellular industry, given the large number of corporate control changes that have taken place in recent years. For estimation purposes, we identified 41 acquisitions of cellular operations (in many cases resulting in partial ownership) during the period 1990 1993, for which the total price paid and the number of POPS acquired were available.19 Table 6 provides coefficient estimates from various regressions of the total price paid for cellular operations on the number of POPS acquired. The regression estimates indicate that the number of POPS acquired is not only highly statistically significant in explaining acquisition prices, but they provide an almost perfect explanation of the price paid, as indicated by the adjusted R 2 reaching 95% in the first regression. Given that some very large acquisitions in the sample may have exerted undue influence on the regression estimates, we replicated the first regression with a logarithmic transformation of the variables, to reduce the effect of size. Estimates of this regression (second line) are consistent with those of the first regression. Finally, our reading of analyst reports suggested that prices paid for P O P S increased constantly in recent years. This indeed is indicated by the third regression, which includes an intercept time variable (recording the chronological order of the sample transactions) and an interaction variable between time and POPS. The coefficient of the interaction variable is positive and statistically significant.

19Many of these acquisitions were of privately-heldcompanies and we therefore have no financial statement data for them.

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E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3-30

Table 6 Coefficient estimates from regressing total acquisition prices of 41 cellular operations on total n u m b e r of P O P S acquired Dependent variable Acquisition price Log(acquisition price) Acquisition price

Intercept - 48.27 ( - 0.59) b 4.95 (47.89) 3 - 50.22 ( -- 0.32)

Time" -__ 5.70 (0.93)

POPS 165.30 (27.01) 3 __ 92.52 (3.95) 3

Time x POPs

Log(POPS)

-__ 1.90 (3.06) 3

Adj. R 2 0.95

0.965 (16.69) 3 --

0.87

0.96

aThe time variable records the chronological order of the sample transactions. bWhite's (1980) heteroscedasticity-consistent t-statistics, with superscript 1,2,3 denoting statistical significance at the 0.10, 0.05, 0.01 levels, respectively.

The striking finding of this analysis is that, though the conventional financials (e.g., earnings, book values, and cash flows) of the acquired operations are not available to us, they appear largely irrelevant for acquisition prices. What determines cellular values in the market for corporate control is growth potential or franchise value, as reflected by POPS, while other firm-specific attributes are largely immaterial.

7. Concluding remarks The evidence presented in this study indicates that current financial reporting of wireless communications companies - a large, world-wide and technologically leading industry - is inadequate. Specifically, significant value-enhancing investments in the cellular franchise and in expanding the customer-base are fully expensed in financial reports, leading to distorted values of earnings and assets. Investors are cognizant, to some extent, of these accounting deficiencies and therefore rely primarily on nonfinancial (nonaccounting) information. They also appear to undo some of the obviously inappropriate GAAP procedures, but these efforts may be hampered, and are obviously costly, given that cellulars' reports do not provide sufficient information (e.g., on commissions paid for new customers, or on the customer churn rate) to enable investors to distinguish between regular expenses and investments. It is important to note that these reporting deficiencies are not just a temporary inadequacy due to an industry being out of equilibrium. The cellular industry is over 10 years old and, while still growing, reached a considerable degree of domestic and world-wide maturity. Adoption of the new generation of

E. Amir, B. Lev / Journal of Accounting and Economics 22 (1996) 3 30

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wireless technology - P e r s o n a l C o m m u n i c a t i o n s Services ( P C S ) - is already underway. T o what extent are the reporting inadequacies d e m o n s t r a t e d above specific to cellular companies? F u r t h e r research is, of course, required to answer this question, b u t since cellular c o m p a n i e s share several key attributes with other high growth, science-based industries - in particular, large i n v e s t m e n t in i n t a n gibles, fast technological changes - it stands to reason that c o n v e n t i o n a l financial statements are also deficient in m a n y of these increasingly i m p o r t a n t e c o n o m i c sectors. Indeed, our price regressions for b i o t e c h n o l o g y c o m p a n i e s (reported in Section 3) yield an obviously c o u n t e r i n t u i t i v e negative a n d significant coefficient for earning, suggesting inadequacies in the reported earnings of b i o t e c h n o l o g y companies, similar to those of cellular companies. 2°

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2°Relatedly, Kim and Ritter (1996) report that earnings and book values are of limited relevance to the valuation of initial public offerings(IPOs), many of which are high-tech companies.

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