Mark-to-Market Accounting and Valuation: Evidence from UK Real Estate and Investment Companies
Jo Danbolt* and William Rees** *University of Glasgow, Scotland **University of Amsterdam, The Netherlands
Abstract The accounting for British investment vehicles is idiosyncratic, but requires that investment assets are marked to market. This allows us to study valuation relevance of accounting according to industry specific GAAP for real estate and investment companies, which is not historic cost, and estimates for historic cost and mark-to-market accounting. We find that the revaluation of investment assets from cost to market is highly significant in both industries – in contrast to earlier US evidence. For both industries, the valuation impact of earnings, however measured, is low in comparison to that found in earlier studies of non-financial firms. This is as expected, given that profits earned in efficient capital markets are likely to be transient. Of the three earnings measures, the GAAP version, which includes the lowest proportion of transient investment returns, shows the largest coefficient estimates. More important is the apparent over-valuation of investment assets in the companies’ accounts. We find both the real estate and investment companies to typically trade at substantial discount to their markto-market asset values. Our approach to investigating this puzzle is relatively novel, but although we can explain part of the real estate discount, our evidence does not help to explain the discount on investment trusts.
JEL Classification:
M41, G12, G20
Keywords:
valuation models, financial institutions, fair value accounting.
Address for correspondence: Jo Danbolt, Department of Accounting and Finance, University of Glasgow, 65-73 Southpark Avenue, Glasgow G12 8LE; E-mail:
[email protected]; Telephone: +44 (0) 141 330 6289; Fax: 0141 330 4442.
Acknowledgements: We would like to thank the seminar participants at University of Amsterdam and University of Antwerp for helpful comments on earlier versions of this paper. The responsibility for any remaining errors or omissions rests fully with the authors.
Mark-to-Market Accounting and Valuation: Evidence from UK Real Estate and Investment Companies 1.
Introduction We investigate the relationship between accounting variables and valuation for UK real estate
and investment companies, comparing the value relevance of accounting numbers prepared under UK Generally Accepted Accounting Principles (GAAP), as they apply to real estate and investment companies, to those that would have been observed under historic cost and mark-to-market accounting. Under GAAP, the balance sheet of UK investment companies will, at least in part, reflect estimated market values, but the income statement will generally not incorporate the gains and losses on such investment assets – in some instances not even when realised. UK GAAP thus provides a curious hybrid between historic cost and mark-to-market accounting for investment assets. In addition to the reported GAAP income and balance sheet figures, we are able to estimate mark-to-market accounting and historic cost accounting figures for the same set of companies. With these three different sets of accounting numbers, we test the relationship between accounting variables and share prices. Our balanced sample, which includes all three measures of income, consist of 546 real estate and 1,318 investment company firm-years drawn from 1993 to 2002. Our study is pertinent to three issues of academic and practical interest. Firstly, our results bear on the debate concerning the desirability of including fair values in accounting statements. Secondly, we address the applicability of accounting based valuations models. In both these first two aspects our sample represents somewhat extreme circumstances, as there are few other circumstances where the market values of such a substantial portion of the balance sheet are so readily available. However, we view the investigation of the valuation model under these conditions as at least as informative as a study of more usual circumstances – especially given the large number of studies that have already covered the valuation of industrial and commercial firms. The third aspect of our study concerns the investment trust and real estate discount, where we can add to the considerable amount of, unfortunately still inconclusive, evidence regarding investment trusts and to the limited evidence available on real estate firms. Our starting presumptions are that in a model of value that incorporates both equity and income values, the weight attached to these two elements will be driven by a) the permanence of the earnings estimates, and b) the economic relevance of the equity estimates. Where firms are investing in assets traded in efficient markets, we expect the income values to be largely transient – although this is sensitive to the way in which earnings is measured – so the impact of earnings is expected to be low. Where investment assets are marked-to-market, the economic relevance of the equity estimates are expected to be high. We find that income numbers are considerably less important, although often 2
still statistically significant, than equity numbers in an income and equity valuation model – whatever measure of income is used. This is as expected. We also find that the revaluation of investments from cost to market value considerably improves the valuation model and reduces the importance of the income figures. Again both these results are as expected. Our results confirm persistent over-valuation of investment assets in the companies’ accounts, as suggested by mark-to-market equity values almost twenty percent higher than the market capitalisation of the firms involved. While this may be indicative of aggressive accounting, with management overstating asset values, it is more probably associated with the under-valuation puzzle. As is widely discussed in the literature, investment trusts (closed-end mutual funds in the US terminology) tend to trade at a discount to their net asset values (see e.g., Dimson and Minio-Paluello (2002b) for a recent survey). Our results are in line with such prior findings, and we observe similar discounts for the real estate companies. Interestingly, we find that the portion of equity arising from revaluation have a lower value impact than the cost element for real estate firms, but much the same for investment companies. We find the mark-to-market adjustments – as well as other company variables – help explain some of the cross-sectional variation in real estate discounts, but little of that for investment companies. We are thus unable to offer a complete explanation for the apparent overvaluation of investment assets in the balance sheet of British investment and real estate firms. In the following sections we review prior research; the relevant accounting requirements; the research method; the data used in the analysis; our results; and finally the conclusions. 2.
Prior Research
2.1
Value relevance of investment firms. The prior literature analysing the relationship between accounting variables and firm
valuation have tended to exclude non-industrial firms. Rees (1997, p. 1123) explained that “This restriction is conventional as the relationship between value and accounting numbers is thought to be very different for financial firms as opposed to those included in the sample”. However, in recent years, some studies have applied Ohlson-type valuation models (e.g., Ohlson, 1995) to financial firms. These studies have largely focused on the value relevance of ‘fair’ (market) value accounting by US financial institutions. While property revaluations are common in Australia and the UK (Easton et al., 1993), such revaluations are not legal under US GAAP. However, in recent years, US accounting standards have been introduced, allowing fair value accounting for some securities by banks, insurance companies and mutual funds. We review this literature on financial firms next. Analysing the valuation of US banks over the period from 1969 to 1987, Barth, et al. (1990) found earnings before securities trading gains and losses (STGL) to have a significant positive impact on bank values, while the coefficient on STGL fluctuated and was insignificantly different from zero. In a related study using data for US banks over the 1971-1990 period, Barth (1994) found fair value estimates of investment securities to dominate historic cost values in a per share valuation model, with 3
no incremental explanatory power for historic cost values. However, for STGL the incremental explanatory power of fair values were low and were sensitive to the model specification. In a further study of trading gains and losses in the US, Warfield and Linsmeier (1992) examined the market reaction to the disclosure of STGL elements of quarterly accounts for a sample of 143 US firms over 1980-1985. They found that market reactions were related to the expected effect on taxes in the first three quarters of the year, but not in the fourth. Their rationalisation of the fourth quarter results was consistent with Barth et al. (1992) explanation that earnings management effects contaminate the value relevant information in STGL. In an analysis of US banks during 1992-1993, Eccher et al. (1996) found only limited evidence of fair values for financial instruments being value relevant, with the results depending on model specification and year. Also analysing fair value disclosures by US banks during 1992-1993, Nelson (1996) similarly found only limited evidence of fair value disclosures being value relevant. Eccher et al. concluded that while there is some value relevance of fair value disclosures, this is much less than that of the historic cost figures. Switching to a fair value accounting system may therefore be detrimental, as it may eliminate some of the value-relevance of historical cost information. Ahmed and Takeda (1995), however, argued that prior findings of negative or insignificant impact of realised and unrealised gains or losses on securities were due to a missing variable bias. Analysing the impact of securities gains and losses on the valuation of 152 US bank holding companies during 1986-1991, they found – when controlling for interest rates – both unrealised and realised security gains and losses had a significant impact on stock returns for US banks in ‘normal’ periods. However, realised gains had less impact if accounting returns were low or if the company had low capital ratios – circumstances when incentives to manage earnings were high. Barth et al. (1995) similarly found interest rates to be of importance. For a sample of 1,377 cases for US banks over the 1976-1990 period, they found interest income to be more highly valued than other income, and in a way that was consistent with interest rates. Barth et al. (1996) found banks’ fair value estimates of loans, securities and long-term debt all to be value relevant over historic cost book values. Fair value estimates may thus be value relevant, although Ahmed and Takeda suggest the value relevance may be reduced when management have incentives to manage earnings. Beaver and Venkatachalam (1999) also analysed the value relevance of US banks’ fair-value disclosures. They split fair value disclosures into nondiscretionary, discretionary and noise components, and found nondiscretionary disclosures priced approximately one for one in market to book regressions, while discretionary disclosures were priced at more than one for one, consistent with management using discretionary fair value disclosures to signal future company performance. The noise components were not priced. Petroni and Wahlen (1995) found the value relevance of fair value disclosures of investments by 56 US property-liability insurers over the 1985-1991 period to depend on the type of securities 4
held. While fair values were found to be value relevant for securities traded in highly liquid markets (such as US treasury investments), fair values of less liquid investments (such as corporate and municipal bonds) did not add to the explanatory power of the models. Carroll et al. (2002) analysed the value relevance of fair value accounting for financial instruments held by 143 US closed-end mutual funds over the 1982-1997 period. Contrary to the majority of the prior evidence for banks and insurance companies discussed above, Carroll et al. found a significant positive relationship between share prices (and share returns) and fair value securities gains and losses – even when controlling for historic cost figures. Vincent (1999) examined the relationship between accounting variables and share returns for a sample of 138 US real estate investment trusts over the period 1994-1996. Earnings per share, funds from operations, cash from operations and EBITDA (earnings before interest, tax, depreciation and amortization) were all value relevant, although ‘Only EPS provides evidence of greater relative information content’ (p100). Gordon and Vincent (2000) analysed the valuation of property companies in Hong Kong, UK and US during 1994-1997, and concluded “that property companies ... are valued similarly despite differences in accounting practices and required financial disclosures” (p25). However, while the level of share prices were significantly related to both net income and book value on a univariate basis in all three countries, net income was no longer significant for the UK if book value was simultaneously included in the regression. Thus, “book value is valuation sufficient for UK property companies” (p24). On the other hand, they found net income to be valuation sufficient for Hong Kong property firms. These differences were somewhat surprising, given that investment property assets are revalued annually in both Hong Kong and the UK. Danbolt and Rees (2002) applied accounting valuation models to financial firms from six European countries. Based on a sample of 7,714 firm-years from 1,140 companies over the 1989-2000 period, they found that in most countries “the valuation models work as well or better in explaining cross-sectional variations in the market-to-book ratio for financial firms as they do for industrial and commercial firms in the same countries…” (p. 5). However, there were significant differences in the explanatory power of the models in the different countries (high in the UK and the Netherlands, low in Switzerland and Germany, and intermediate in France and Italy) and between the different financial industries. In particular, marking assets to market value reduce the relevance of earnings and increase that of equity. Earnings-based valuation models were found to have higher explanatory power for financial services companies (banks and insurance companies) than for investment holding companies (real estate and investment companies), whose return is predominately accounted for by asset trading in efficient markets. Prior research thus indicates that reported accounting earnings might be relevant for the valuation of financial firms. While prior evidence has generally focused on banks, there is some evidence to suggest that accounting numbers may also be value relevant for other financial firms. We 5
test this proposition in the empirical analysis in section 4. 2.2
Value relevance under different accounting models. However, as indicated above, while this paper test the value relevance of accounting numbers
on a sample of real estate and investment companies, the focus of this study is on the value relevance of accounting numbers prepared under GAAP, mark-to-market and historic cost accounting. A related strand of literature – not restricted to financial firms – is therefore also of relevance to this study. A number of papers have analysed the relative value relevance of accounting numbers under different accounting regimes. A full discussion of this literature is beyond the scope of this paper. However, to the extent that these papers discuss the value relevance of asset revaluations and other fair (market) value disclosures – factors which account for the differences between reported GAAP, mark-tomarket and historic cost figures – we review these papers next. Standish and Ung (1982) analysed the relationship between revaluations and share returns for a sample of 232 UK companies over the period 1964-1973. They found significant positive abnormal returns (of approximately 5%) over the three months leading up to and including the announcement of the revaluation, although the stock market reaction did not appear to be related to the size of the revaluation. Further, the revaluation signal was found to be subordinate to that of earnings and dividends, and the stock market reacted favourably to revaluations only for companies where earnings, dividends and revaluations provided consistent positive signals regarding the company’s performance. Aboody et al. (1999) similarly analysed the value relevance of fixed asset revaluations by UK companies. Based on a sample of 6,633 firm-years for non-financial firms over the period 1983-1995, they found a significant positive relationship between upward revaluations of fixed assets and changes in post-revaluation performance. They further found current revaluations (revaluation balances) to be significantly positively related to annual returns (prices). The relationship between revaluations and prices/future performance was, however, weaker for highly geared firms, for cross-listed firms, and during more volatile economic time periods. Amir et al. (1993) analysed the reconciliations to US GAAP by 101 foreign firms cross-listed in the US (with UK companies constituting 44% of the sample). Overall, they found reconciliation to US GAAP to be value relevant. However, with regard to asset revaluations – which are legal in the UK and Australia, but not in the US – Amir et al. argued “The results suggest that asset revaluations are viewed as value-relevant by the market, and removing these measures in order to reconcile to U.S. GAAP reduces the value-relevance of the accounting data”. (p. 255). Easton et al. (1993), Easton and Eddey (1997), and Barth and Clinch (1998) have similarly found evidence of asset revaluations being value relevant for Australian firms. However, while Amir et al. (1993) found revaluations to be value relevant in both Australia and the UK, they also found some indication of revaluations being less value relevant in the UK than in Australia. In another study of UK and Australian (as well as 6
Canadian) companies’ reconciliations to US GAAP, Barth and Clinch (1996) found that “U.K. revaluations are not positively correlated with information investors use in setting share prices” (p. 137). Indeed, their “evidence suggests that investors discount equity of U.K. firms in a way that is correlated with the write-off of revaluation amounts to conform to U.S. GAAP”. (p. 158). The value relevance of revaluations in the UK thus remains controversial. Despite the amount of prior research in this area, we believe our study makes a valuable contribution to the value relevance literature. We develop and test hypotheses regarding the expected relationship between accounting numbers and company value, based on three fundamentally different accounting systems: reported UK GAAP, mark-to-market accounting, and historic cost accounting. We believe this study is unusual in that we are able to test the value relevance for these three accounting systems on the same set of UK companies. 2.3
Discounts on investment firms It has long been established in the literature that investment trusts (closed-end mutual funds)
tend to trade at a discount to their net asset values (Dimson and Minio-Paluello, 2002b). This anomaly may have implications for the estimated value relevance of the mark-to-market adjustment, as the market-to-book ratio may differ from one even under complete mark-to-market accounting. The investment trust discount puzzle can be summarised by four key findings (Lee et al., 1991): •
Investment trust shares are initially issued at a premium to their net asset value. The premium on issue tends to be up to 10% in the US, and at least 5% in the UK (Dimson and MinioPaluello, 2002b).
•
After listing, investment trusts move to a discount within a few months of trading. For example, Weiss (1989) found US funds to trade at a 10% discount less than six months after issue.
•
The discount on investment trusts varies widely over time. For example, Dimson and MinioPaluello (2002b) found the market-average closed-end fund discount to peak at almost 50% in the UK (40% in the US) during the 1970s, while the discount tended to fluctuate between 5% and 15% during the 1990s in both markets.
•
Discounts shrink when closed-end funds are open ended or liquidated (Brauer, 1984; Brickley and Schallheim, 1985). The discount puzzle is, however, not restricted to investment trusts. Barkham and Ward
(1999), analysing the pricing of 40 UK real estate companies over the period 1993-1995, found the shares to trade at an average of 22.4% discount to the net asset values. Despite numerous studies in this field, the investment trust discount remains a puzzle. Reviewing more than hundred studies trying to explain the closed-end discount, Dimson and Minio-
7
Paluello (2002b) conclude that ‘None provides a full explanation’ (p. 1). Research in this area have tended to focus on either economic explanations for the discount, or on the role of noise traders and limited rationality. Net asset values may be overstated, as the accounts tend not to recognise any capital gains tax that may arise from the realisation of investment gains. In one of the early studies of the discount, Malkiel (1977) found tax effects could at most explain a 6% discount – much less than what has generally been observed in the US. In the US, closed-end funds must distribute to shareholders at least 90% of any gains realised during the year to qualify for exemption from corporation tax. Shareholders pay income tax on dividend income, while capital gains are taxed at the capital gains tax rate (Dimson and Minio-Paluello, 2002b). The tax treatment of investment trusts is, however, very different in the UK. There, the funds are not allowed to distribute capital gains, but must reinvest them. The capital gains tax on investment trusts was abolished in 1980. On the other hand, the funds can retain no more than 15% of any dividend income – the rest must be paid out to the shareholders (Dimson and Minio-Paluello, 2002b). With regard to UK property companies, Adams and VenmoreRowland (1989) found only small reductions in the discounts after UK tax changes in 1980 which reduced contingent tax liabilities, and large discounts existed even on a post-tax basis. Despite the very different tax treatment of closed-end funds in the UK and the US, ‘…UK funds behave remarkably like their United States counterparts, suggesting that the discount cannot be explained by tax factors that are specific to a single country’ (Dimson and Minio-Paluello, 2002b, p. 12). Net asset values may also be overstated to the extent that transactions costs or liquidity problems reduce the realisable gains. However, neither these factors – nor indeed the capital gains tax effect – can explain the empirical evidence of price rises on open-ending (Dimson and MinioPaluello, 2002b). Other economic factors possibly contributing to the discount include agency costs such as management fees (Gemmill and Thomas, 2002); the loss of potentially valuable tax-trading opportunities from idiosyncratic movements in individual shares; and segmentation effects, e.g., for funds investing in overseas shares (Dimson and Minio-Paluello, 2002b). DeLong et al. (1990) and Lee et al. (1991) put forward limited rationality models to explain the discount. They suggested irrational (noise) traders introduce risk into the pricing of closed-end mutual funds. The discount may persist, due to difficulties faced by rational investors in arbitraging this pricing anomaly (Pontiff, 1996; Chen et al., 2002; Gemmill and Thomas, 2002; Jones and Lamont, 2002). However, while Lee et al. find some support for their model in the US market – where mutual funds are predominately held by individual (arguably irrational) investors – it is not clear why a similar discount should be present in the UK, where investment trusts are predominately owned by large institutional (arguably rational) investors. There is, however, evidence from both the US (Lee et al., 1991) and the UK (Minio-Paluello, 1998) of the discount on various funds moving together, and of mean-reversion in the discount (e.g., Thompson, 1978 for the US, and Cheng et al., 1994 and Minio-Paluello, 1998 for the UK). This may suggest the discount is, at least in part, 8
attributable to changing investor sentiments.
Analysing the discount on UK investment trusts,
Gemmill and Thomas (2002) found that ‘noise-trader sentiment, as proxied by retail-investor flows, leads to fluctuations in the discount’ (p. 2571). However, they argued that noise-traders did not cause the discount.
Rather, they argued the
long-term discount was due to limits to arbitrage and
administration expenses. Other studies similarly using multi-factor models have established other regularities in the investment trust discount. Using a model controlling for the Fama-French (1992) 3-factors, an investor sentiment risk factor based on Lee et al. (1991) limited rationality model, mean reversion, price reversal, past performance and the impact of the management group, Dimson and MinioPaluello (2002a) were able to explain 35% of the month-to-month changes in the discount on British investment trusts. Analysing the discount on UK real estate companies, Barkham and Ward (1999) found the discount to be positively related to the companies’ capital gains tax liabilities and company size, but negatively related to company performance or their holding of trading stocks. Administration expenses, gearing, and inside ownership were not found to be significant. However, by far the most significant variable was the sector discount. Including this variable increased the adjusted R2 of the model from 15% to 33%, suggesting there was a significant time-variation in the discount on UK real estate companies, consistent with the investor sentiment hypothesis. Still, the cause of the investment trust and real estate discount remains largely a puzzle. 3.
Accounting for real estate firms and investment companies in the UK. Accounting for real estate firms and investment companies in the UK is curious. Of the two,
the real estate accounting is more conventional, as no special rules apply. SSAP 19 ‘Accounting for investment properties’ governs the valuation of investment properties and this applies to all firms. The impact of these requirements is best illustrated using an example and we have selected, at random, the 1999 annual accounts for Benchmark Group plc. The income for the year includes rental income less relevant costs (GBP 19,503 thousand), the profit on disposal of trading properties (2,491), administration expenses (-3,346) plus profit on disposal of investment properties (1,603). Thus profit before interest, taxation and dividends is 20,251. The distinguishing feature of trading properties is that they were bought for resale and have been carried in the accounts at the lower of cost or net realisable value. However, the investment properties are revalued on an annual basis. The revaluation during the year of property still held at the end of the year is credited to the revaluation reserve (24,081). The unusual feature is that the element of value increase in investment properties, credited to the revaluation reserve in earlier years, for firms sold this year, is not recognised in income, but credited directly to the profit and loss reserve. Thus, income only recognises the profits or losses on investment companies captured in the year of disposal. The result is that the profit on ordinary activities after taxation (13,164) understates conventional historic cost accounting (by 6,444), the amount of revaluation accounted for in earlier 9
years on properties disposed of in this year. GAAP income also understates mark-to-market accounting (by 24,081) – the unrealised increase in value during the year for investment properties still held at the end of the year. It is usual for real estate firms to include a reconciliation of GAAP income to ‘historic cost profits and loses’ and ‘total recognised gains and losses’ as Benchmark does in our selected example. The remaining relevant aspect is that the total capital employed (326,126) includes a revaluation reserve (83,693). It is our view that the accounting practices illustrated by reference to the accounts of Benchmark Group plc for 1999 are typical of those used by our sample companies. The accounting for investment firms is, if anything, more curious than that for real estate firms. The GAAP for these firms is governed by the ‘Statement of Recommended Practice – Financial Statements of Investment Trust Companies’ as well as by general legal and professional requirements. Again the accounting is best illustrated by reference to an example and we use, at random, the 2000 annual accounts of Aberdeen High Income Trust Plc. Here, the income statement ‘Statement of Total Return’ gives results for total return split between revenue and capital. The revenue element incorporates dividend and interest income (GBP 13,623 thousand), less a proportion of the investment management fee (658), other expenses (326), a portion of interest payable (1,689) and tax on ordinary activities (614), to generate a net revenue income figure (10,295). The capital element of income reveals a loss (23,325), which comprises realised (2,339) and unrealised (20,986) elements. Investment management fees (658) and interest payable (1,689) have also been allocated to the capital income. It is usual for firms to simply split the management fees and interest between income and capital by some rule of thumb – here 50:50. A credit for the tax relief on the capitalised expenses (614) is also made. Thus, in this instance, to recreate historic cost income the revenue account must be adjusted by the net realised loss (2,339), the investment management fee (658), interest payable (1,689), less the tax adjustment (614). To further adjust to mark-to-market accounting, the ‘decrease in unrealised appreciation’ (20,986) must be deducted. The balance sheet shows shareholders’ funds (123,970) including capital reserves unrealised (1,073) and capital reserves realised (-12,258). The accounts for Aberdeen High Income Trust Plc (2000) are generally typical of other investment trust reports except that a) before the 1995 SORP most companies did not incorporate a columnar statement of total returns including capital returns, although the same information was typically included in the accounts, and b) 2000 is somewhat untypical as most years up to and including 1999 tended to show positive revaluations. It is also the case that in many instances there may be a transfer between unrealised capital reserves and realised, to account for previously unrealised profits or losses now realised. Thus, neither real estate firms nor investment trusts use conventional accounting. For both, the base level of income reported is usually going to be less than historic cost. Real estate firms include rents, profits from properties bought for resale and this years’ realised profit or loss on 10
investment properties. Investment companies only incorporate the direct yield on investments – dividends and interest payments – and further a proportion of costs are allocated to the capital account. Both realised and unrealised returns on investments are accounted for in the capital element of the total return statement. In shareholders’ equity, real estate firms maintain a revaluation reserve for unrealised appreciation, and as the appreciations become realised they are transferred to revenue, whereas investment trust companies include two reserves separate from the revenue reserve – realised and unrealised reserves. 4.
Research Methods Our analysis is based on the following model (Rees, 1999):
rˆ ∗ w 1 + gˆ + nit w pr t = eqt 1 rˆ - gˆ rˆ - gˆ
(equation 1)
where prt is the price per share at time t, nit is clean surplus net income, eqt is book value of equity and r and g are the expected constant values (expectations denoted ^) for the cost of capital and the growth rate of book value and earnings. w indicates the relative weight (between one and zero) placed on current earnings, as opposed to current equity, as indicators of normal base level earnings from which growth in earnings is predicted. Equity is a feasible indicator of income as, in the absence of better information, the capital invested, equity, times the cost of equity, indicates ‘normal earnings’. The firm subscripts are understood. The model is based on the well-known transformation of the dividend discount model to an accounting based valuation model, and, although we make no use of the linear information dynamics which is an important component of his paper, the model is consistent with Ohlson (1995)1. As an illustrative computation of the coefficients that could be expected from the empirical analysis, let us assume a 12% cost of capital and a growth rate of 5%. If w is one, the coefficient on equity would be 0.71 and on net income would be +15. However, were w to be 0.5 (or 0.2) then the equity coefficient would be +0.14 (+0.66) and the net income coefficient +7.5 (+3). Results from previous studies, all based on non-financial firms, including Collins et al. (1997) for the US, Harris et al. (1994) for Germany, Joos and Lang (1994) for Germany, France and the UK and Rees (1997) for the UK, imply the w is less than one. In all cases the coefficient on net income is less than +15 implied above (with values between 4 and 10 being normal) and the coefficient on equity is positive, as is the intercept term. The hypotheses are tested using the operationalised version of equation 1:
eqHC it pr it ni it + α1 +K = α0 eqHC it eqHC it eqHC it D ∗ ni it rv it α 2 D it + α 3 + α 4 + ε it eqHC it eqHC it 11
(equation 2)
where eqHCit is the reported shareholders equity less any revaluation reserve, Dit is a dummy variable taking the value 1 where net income is negative, D*niit is an interactive term between net income and the negative earnings dummy variable, and rvit is the value of revaluations (the difference between the book value of equity under GAAP and historic cost accounting) for firm i and year t. The rational is as follows: α0 and α1 estimate the coefficients reflecting growth, cost of capital and the weighting parameter, w, for cases where earnings are positive; and the dummy variable and interaction terms allow the weighting parameter to vary for cases that have negative earnings. The assumption is that earnings will have approximately a zero weight (α1≈-α3) when negative, and the weight on equity will increase correspondingly, as reflected in a positive coefficient for α2. The model is initially estimated with α4 set to zero. The inclusion of the rv variable allows us to estimate whether asset revaluations are value relevant, by analysing the relationship between share prices and the size of such revaluations. We estimate the model in equation 2 with ni, D and D*ni based on mark-to-market and historic cost accounting, as well as for the reported GAAP earnings. While some studies have analysed undeflated price regressions (e.g., Barth and Clinch, 1998), such regressions are likely to suffer from heteroscedasticity and spurious regression results due to scale effects (Easton, 1998). It is therefore helpful to scale the variables. While several prior studies have scaled by reported book values, such an approach is not ideal for our analysis, where we are interested in testing the impact of asset revaluations on share prices. We therefore follow the approach of Easton et al. (1993) and scale all variables by the book value of equity, as it would have been under historic cost accounting. This is done by splitting the reported book values of equity (eqGAAPit) into its historic cost (eqHCit) and revaluation (rvit) components.
eqGAAPit = eqHC it + rv it
(equation 3)
Whilst scaled levels equations have been extensively used over the past ten years, they are not problem free and many researchers prefer to use models of returns and/or differences. We have chosen to present our results based on the scaled levels model as this preserves the direct comparison between the estimate of equity and its capitalisation, which would be lost in a returns or differences model. We are also predisposed to use the levels model as in general the results from such a model tend to provide estimates which are generally consistent with theory. The impact of prices leading earnings in a returns or differences model tends to give coefficient estimates that are difficult to reconcile with the economic relationships supposed in the basic model. As a robustness check, we have, however, also estimated the model using first-difference results2.
5.
Data From the Company Analysis database, we identify (over the period 1993-2002) 989 firm-
years for real estate companies, and 2,703 firm-years for investment companies, as detailed in Table 1. However, missing data reduce the samples to 691 and 2,121 firm-years, respectively. Excluding 12
firm-years substantially different in length from a calendar year further reduce the samples to 680 and 1,939 firm-years. After trimming to control for outliers, we are left with a final sample of 645 firmyears for real estate companies, and 1,847 firm-years for investment companies, for the model based on reported accounting numbers under UK GAAP. However, due to missing data for some of our adjustments to either historic cost or mark-to-market accounting, the sample sizes are somewhat lower for these models. We are able to calculate all three models for 546 real estate and 1,318 investment company firm-years. We present results based on this ‘balanced sample’ as they are entirely consistent with the results from the full sample. Table 1 about here The analysis incorporates the following variables: prit/eqHCit
Market-to-Book (Historic Cost), where prit refers to firm i's price per share
for ordinary equity at the accounting year end t3, and eqHCit to firm i's historic cost book value of equity per share at year end t. GAAP book equity is defined as all equity reserves and ordinary share capital, but excluding non-ordinary equity such as preference shares. For real estate companies, we estimate historic cost book equity by subtracting the revaluation reserve (and where available, any unrealised appreciation on investment) from the GAAP figure. For investment companies, we subtract unrealised appreciation on investment (and where available, the revaluation reserve) from eqGAAP. niGAAPit/eqHCit
Net Income to Historic Cost Book Equity, where niGAAPit refers to firm i's
reported earnings per share for year t defined as earned for ordinary after interest charges, extraordinary items and taxation. niHCit/eqHCit
Historic Cost Net Income to Historic Cost Book Equity, where niHCit refers
to firm i's historic cost net income. For real estate companies, we estimate the historic cost net income by adding realised property gains or losses (total revaluations for the year less the increase in unrealised revaluations, as reflected by the increase in the revaluation reserve) to niGAAPit. (Where relevant, we also adjust for realised investment appreciations). For investment companies, we add realised investment appreciation to the reported GAAP income, which is estimated from the change in the realised capital reserves. (Where relevant, we also adjust for any realised property gains or losses). niMMit/eqHCit
Mark-to-Market Net Income to Historic Cost Book Equity, where niMMit
refers to firm i's mark-to-market net income. For real estate companies, we estimate the markto-market net income by adding total property revaluations for the year (less any tax adjustment or foreign exchange translation gains) to niGAAPit. (Where relevant, we also adjust for any appreciations in investment values, as reflected by changes in the realised and unrealised appreciation on investment reserves). For investment companies, we add the change in realised and unrealised appreciation on investment reserves arising during the year to reported GAAP net income (and, where available, any property revaluations for the year). 13
DGAAPit, DHCit, and DMMit
Negative Net Income Dummies, taking the value 1 where
respectively niGAAPit/eqHCit, niHCit/eqHCit, or niMMit/eqHCit is negative. DniGAAPit/eqHCit, DniHCit/eqHCit, and DniMMit/eqHCit
Negative Net Income Interaction
terms. These are interactive terms, combining the negative net income dummy variable with the net income variable, for GAAP, historic cost and mark-to-market accounting, respectively. Accounting policies are not absolutely uniform and the accounting line items available in the database used are not comprehensive. Under these circumstances our figures for historic cost and mark-to-market income should be viewed as estimates. It would be possible to improve the estimates by examining the financial reports of each firm-year in the sample. This is not feasible for samples of 645 and 1,847 cases. We have chosen to maintain sample size and sacrifice some element of accuracy in the estimates of our variables. However, we did conduct an audit of a small sample of firm years. This included a random sample and an investigation of cases where alternative approaches to estimating the variables produced large differences. We found no cases where the values of the reserves were misleading, but minor differences persist in our estimates of historic cost and mark-tomarket earnings. These occur where transactions are debited or credited to the relevant reserve accounts that are not relevant to the revaluation assets or the recognition of realised earnings. This is not uncommon, but usually trivial. However, where share repurchases were conducted by investment trusts they could write off the premium on cancelled shares to the realised capital account. These amounts could be large. We have therefore excluded all investment trust cases from our sample where we have evidence of share repurchase activity. Descriptive statistics for our test variables are presented in panels a) and b) of tables 2 for real estate and investment companies, respectively. As can be seen from table 2, for the balanced sample, the mean (median) price to historic cost book equity ratio for real estate companies is 1.3097 (1.2211). While exceeding one on average (consistent with the hypothesis that traditional historic cost accounting may understate real asset values), the value is below one for 30.59% of the sample. In addition, our real estate companies tend to have substantial revaluation reserves, which on average amounts to 61.69% (49.63%) of the historic cost book value. The market to book ratio – based on the reported book values, including revaluation reserves – averages 0.8276 (0.7841), with 82.05% of our real estate companies having a market to book ratio below one. These results would seem to suggest UK real estate companies under GAAP tend to report aggressive rather than conservative accounting numbers, and that the market does not fully trust the ‘fair’ property values reported by management in the companies’ accounts – or that there are other overvalued assets or undervalued liabilities on the balance sheet. This is consistent with Easton et al. (1993) for Australian industrial and mining companies and Barkham and Ward (1999), who similarly found UK real estate companies to trade at large discounts. Table 2 about here. 14
As one would expect during periods of generally rising property prices, profit levels are higher if unrealised and/or realised changes in property values during the year are included in the profit figures. The average net income ratio under the historic cost convention is 2.05 percentage points higher than that for GAAP at 0.0912 (0.0910), while for the market model the profit figures are more than doubled at 0.1858 (0.1713). However, the profit figures including such property gains and losses are also more volatile. Descriptive statistics for the investment companies are contained in panel b) of table 2. The UK investment companies have exceptionally low market to book ratios. The mean (median) price to historic cost book equity ratio for the balanced sample is 0.9790 (0.9727). The ratio is below one for 53.49% of the companies. Taking into consideration that the investment companies on average have unrealised asset revaluations amounting to 20.51% (18.00%) of their historic cost book equities, the market to book ratio – based on the reported GAAP asset values – would be 0.8100 (0.8398), with 89.23% of the UK investment companies having a market to reported book ratio below one. This is consistent with earlier evidence, as investment holding companies tend to trade at a discount to their net asset values (Dimson and Minio-Paluello, 2002b). Thus recognition of unrealised investment appreciations in the accounts tends to move the market to book ratio away from one rather than towards it. As UK GAAP does not include any asset trading income as part of reported earnings for investment companies, reported net income tends to be low. The scaled mean (median) is 0.0213 (0.0165). Under historic cost accounting, mean (median) earnings would be 0.0634 (0.0765), while under mark-to-market accounting the comparable figures would be 0.0689 (0.0948). Again, earnings incorporating such trading income is also much more volatile than GAAP earnings. A correlation matrix for the variables used in the analysis is provided in table 3. It is perhaps helpful to point out that in general the Pearson and Spearman statistics are similar, suggesting that the parametric results are not being driven by outliers. There are many high correlation statistics between different measures of earnings and/or negative earnings dummies. This is to be expected, but our main results do not combine measures of profit, and correlation with negative earnings dummies is unavoidable and conventional. Table 3 about here. 6.
Results
6.1.
Comparative valuation models. Table 4 contains the results for six different valuation models for each industry. These use
earnings measure in three ways – GAAP, historic cost and mark-to-market – and equity measured in two ways – historic cost and GAAP, which equals mark-to-market. Throughout results are presented using the smaller balanced sample, but the full sample results are very similar. The results have also been tested for sensitivity to alternative estimation techniques – robust MAD regression, which 15
reduces the impact of outliers, and annual regressions, which mitigate the impact of pooling crosssections and time-series. We report in the text wherever significant results are sensitive to alternative estimation techniques4. Real Estate Companies For the basic GAAP model with α4 set to zero, our results are broadly in line with those generally observed for non-financial firms, although the coefficient on earnings (3.8064) is considerably lower, and that on equity (1.0067) somewhat higher than the norm. Both coefficients are clearly significant. The coefficient for the interactive term between earnings and the negative earnings dummy is, at -4.2285, similar to and opposite from that for ni, i.e., α1≈-α3, consistent with expectations. The regression overall is statistically significant and the adjusted R2 is 12.4%. Table 4 about here. If revaluations are included the explanatory power of the model increase significantly – from 12.4% to 43.8%. Two other changes are particularly noteworthy. Firstly, the coefficient on net income falls to 1.9226, although it remains highly significant. Thus, as expected, when assets are stated at market values, equity overall (combining the coefficients for eqHC and rv) becomes more important and earnings less so. The weighting coefficient (w) in equation 1 thus falls, although not quite to zero, as earnings maintain some highly significant explanatory power of the cross-sectional variation in share prices. Secondly, the coefficient is smaller for the revaluation reserve than for the historic cost book value of equity. Thus, while revaluations are taken into account by the market when determining share prices, such unrealised asset gains are valued less highly than other assets on the balance sheet. This suggests investors do not fully trust the ‘fair’ values placed on the properties in the companies’ accounts, or that revaluations are not as valuable as the historic cost portion of assets. We return to this in the final section of our analysis. For the historic cost accounting model, excluding the revaluation reserve, the explanatory power is low, at 6.3%. While we would expect the level of the earnings coefficient under historic cost to be somewhat lower than that for GAAP earnings given the higher level of historic cost than GAAP earnings, the drop in the coefficient – from 3.8064 to 1.6502 – is larger than expected. In addition, the significance of the coefficient is also lower, with the t-statistic of 5.43, compared to 8.40 under GAAP. This suggests that the adjustment from GAAP to historic cost earnings (the inclusion of realised property gains arising during the year) detract from the value relevance of earnings. With earnings less reliable, investors now appear to place more weight on asset values, and both the level (1.1457) and the significance (t-statistic of 28.45) of the coefficient on equity increase compared to that observed under GAAP accounting. Including the revaluation reserve in the historic cost regression restores the explanatory power of the model. The adjusted R2 increase to 41.9%. As before, the revaluation reserve seems to be
16
valued less highly than other assets on the balance sheet, although the coefficient on the revaluation reserve is highly significant. However, with the inclusion of the revaluation reserve in the model, negative historic cost earnings loses its significance. The final section of table 4, panel a), contains the results for the mark-to-market model. Under full mark-to-market accounting, we would expect current earnings to be unhelpful in predicting future earnings, and the coefficient on net income – if completely transient – should approach one. However, while the earnings coefficient for the mark-to-market model, at 1.4250, is lower than that for either GAAP or historic cost accounting, it remains significantly in excess of unity5. This suggests that the mark-to-market net income incorporates some element of permanence, with the companies able to earn some economic rent. The significance level of the coefficient (t-statistic of 10.75) is higher than that for either of the two other models, suggesting the incremental earnings under mark-to-market accounting are value relevant. Thus, asset revaluations – both the total level and the level of revaluations arising during the year – appear to help explain cross-sectional variation in share prices. The explanatory power of the mark-to-market model, even excluding the revaluation reserve, is relatively high, with an adjusted R2 of 18.6%6. Including the revaluation reserve, the explanatory power of the mark-to-market model is little different from that observed for either the GAAP or the HC model (42.8%). While mark-to-market net income remains significant, its level of significance is similar to that for GAAP and HC earnings. Revaluations during the year thus appear to have no incremental explanatory value once the total level of revaluations is controlled for in the model. Investment Companies The regression output from the analysis of the cross-sectional variation in the price to historic cost book equity ratio for the investment companies is contained in panel b) of table 4. For the basic model, GAAP earnings provide relatively low explanatory power. While significant, the coefficient on net income, at 2.9529, is low, both compared to that observed for real estate companies, and to prior evidence for non-financial firms. The controls for negative earnings provide unexpected findings – firstly, we would expect a positive coefficient for the negative net income dummy variable (rather than the observed -0.1245), and the coefficient on the interactive term (at -15.5500) is much larger than expected. The overall explanatory power of the model is low, with the adjusted R2 of 6.2%. The regression is, however, highly significant. The large negative coefficient on negative income is puzzling. To the extent that it exceeds the coefficient on positive earnings it implies a positive valuation impact of losses. This result does not appear to be driven by outliers or by subsets of the sample. The coefficients remain highly significant under robust regression. Under annual regressions the negative coefficients are even larger, although these coefficients are not significant, due to an increase in the standard deviation. We have two possible explanations for the large negative coefficient. This result may either be driven by 17
costs that the market does not interpret as either genuine or persistent, or possibly the negative earnings coefficient, which would not be considered overly large for industrial or commercial firms, is cancelling an income multiple which is not reflected in the earnings coefficient, but might be captured in the equity coefficients. To the extent that this result proves to be robust it is worthy of further investigation. While the balance sheet tends to grossly overstate the value of UK investment companies asset, revaluations are highly value relevant. Including the revaluation reserve in the model improves the explanatory power drastically to 56.8%. In contrast to the real estate sample, we find that the revaluation is valued at a marginally higher multiple than other assets on the balance sheet. Moving to historic cost accounting, the level of the earnings coefficient falls (from 2.9529 to 0.7642), as one would expect given the generally much higher level of historic cost earnings compared to GAAP earnings. The explanatory power of the model overall improves, from 6.2% for to 11.1%. Adjustment to historic cost accounting would thus appear to provide information relevant to investors in UK investment companies. As expected, the significance of the regression increase substantially when we also include revaluations (55.9% vs 11.1%). The overall explanatory power is similar to that of the comparable model under GAAP accounting. Adjustment of earnings to historic cost thus appears to add little to the model when the balance sheet is marked-to-market. The final section of table 4 contains the regression output based on the mark-to-market model. While the earnings coefficient (0.7782) is similar to that observed for historic cost earnings, the level of significance is substantially higher under mark-to-market accounting, indicating that controlling for unrealised as well as realised investment gains and losses significantly improve the explanatory power of the model. This is confirmed by the adjusted R2, which increase to 21.3%. However, once we include revaluations, the explanatory power of the mark-to-market model (55.4%) is similar to that observed for the historic cost model, and mark-to-market earnings are only marginally significant (and not significant under annual estimation). Thus, when the balance sheet incorporate revaluations, the addition of either realised or unrealised appreciations in asset values appears to add little explanatory power over and above what is contained in GAAP earnings. 6.2.
Incremental Value Relevance of Different Accounting Models. A series of models were estimated where the earnings figures from different accounting
models were incorporated. In essence the approach tests the difference in coefficients reported in table 4 and the full results have not been presented in tables7. The basic model is assumed to be the GAAP version and the difference between GAAP earnings and both historic cost and mark-to-market are introduced to the model separately and then jointly, and this is done when the revaluation variable is absent and then when it is present. We find that for the real estate sample the difference between GAAP and historic cost is generally insignificant whilst the difference between GAAP and mark-to-market is typically 18
statistically significant and positive. When mark-to-market earnings are added to GAAP in the absences of the revaluation variable, explanatory power increases from 6.3% to 20.5%. However, when the revaluation variable is included, the increase is small – from 41.9% to 44.6%. For the investment trust sample, the results are somewhat different. Here, the inclusion of the difference between GAAP and historic cost is statistically significant, whereas the difference between GAAP and mark-to-market is only significant in the absence of the revaluation variable. When the historic cost variable is added in the absence of the revaluation variable, the explanatory power increases from 6.2% to 14.2%, and when the mark-to-market variable is added instead, it increases from 11.1% to 24.9%. The increase when either earnings variable is added to the model including the revaluation variable is, however, trivial. These results are relatively easily explained. For real estate companies GAAP, earnings are highly correlated with historic cost earnings (0.705), but are less correlated with mark-to-market (0.423). Mark-to-market incorporates this year’s increase in values on assets disposed of, whereas the change to historic cost only includes previous years, relatively irrelevant, profits on disposals. As the revaluation reserve is significantly correlated with the mark-to-market income when revaluation is included, the earnings differences have little impact. Conversely, the move to historic cost for investment trusts includes this years profits on assets disposed of, and both historic cost and mark-tomarket have low correlations with GAAP earnings – 0.197 and 0.090 respectively. Furthermore, mark-to-market income is highly correlated with revaluations (0.601), so when both are included mark-to-market has little impact. Thus, the different results for the two industries are a function of different GAAP accounting and the relatively short time financial investments are held in comparison to real estate investments. 6.3
The Discount Puzzle The companies in our sample on average trade at a large discount to their mark-to-market
asset values. This is a puzzle – although one that has been addressed before. While this may be aggressive accounting and unreliable ‘fair’ asset values in the accounts, it may also be indicative of market biases in the valuation of such investment holding companies. An example may help illustrate this point. Aberforth Smaller Companies Trust plc – a company chosen at random – had the following very simple balance sheet in their 2000 Annual Report (GBP million): Securities listed on the London Stock Exchange, 286.1; Debtors, 5.4; Cash, 15.1 and Creditors, -5.7, giving a total of shareholders’ funds of 300.9. Note that the company had no debt, and that virtually all the assets had a clearly observable market value. Still, the market capitalisation of the company on the balance sheet date was only 244.4, suggesting a price to book ratio of 0.81 and an under valuation of 56.5 million pounds. It is hard to understand why such large under valuations exist rather than the company being taken over and liquidated. In this instance, six large institutional shareholders held a combined 42.4% stake, and could presumably gain control relatively easily. It is possible that trading expenses (0.8% of net asset 19
value, amounting to 2.2m for the year), potential tax effects from realisation of the gains, or other company characteristics account for these discounts. As discussed in the literature review, several possible explanations have been provided to explain the discount between share prices and net asset values for both real estate and investment companies. In this section we test some of these theories for our sample firms. We run the following model for the real estate companies:
premit = α 0 + α 1
te rv niMM it + α 2 it + α 3 it + K eq it eq it eq it
nip it debt it + α 5 ln(bv it ) + α 6 α4 + υ it eq it ta it
(equation 4)
where: premit
Premium. This is defined as the market to reported (mark-to-market) book
value less one [prit/eqit – 1]. niMMit/eqit
Mark-to-market profit. This is used as a proxy for company performance. It
is hypothesised that companies with better performance (possibly indicative of managerial quality) will trade at a premium compared to other companies (Malkiel, 1995). We scale the profit by the reported (mark-to-market) book equity. rvit/eqit Revaluations. As argued in the literature, net asset values may be overstated to the extent that they fail to take into account potential tax liabilities from the realisation of the appreciation in investments values. These tax liabilities should be related to the size of unrealised appreciations, and we hypothesise a negative relationship between revaluations and the premium. Analysis is also undertaken splitting the observations between companies with negative, medium and high revaluations. teit/eqit
Trading Expenses. This is the cost of running the business. We hypothesise that companies with high trading expenses are likely to trade at a larger discount to their asset values than other firms. Again we scale the variable by book equity.
debtit/eqit
Gearing. As argued by Barkham and Ward (1999), the discount to net asset
value will tend to increase with gearing. For example, if a company with assets of 100 is valued at 80, the discount on the market to book equity ratio will be 20% in the absence of debt, but 40% if the company is financed with 50% debt. We therefore expect an inverse relationship between the premium and company gearing. ln(bvit)
Size. We proxy company size by the natural logarithm of the reported (mark-to-market) book equity. There is no clear prediction as to how company size will affect the discount. While Barkham and Ward (1999) find large companies to trade at larger discounts than smaller firms – possibly due to the difficulties for large firms to rapidly liquidate their holdings, Capozza and Lee (1996) find small real estate firms to have larger
20
discounts. nipit/eqit
Non-Investment Property. While investment properties are marked to market in the companies’ accounts, other assets tend to be stated at their historic cost. To the extent that these historic costs may understate the real asset values, the calculated net asset value – and therefore the discount – may be lower for companies with large proportions of non-investment property assets (Barkham and Ward, 1999). This variable, defined as total assets less investment property assets, as a proportion of total investments, is, however, missing for some of our property companies, and we therefore report regressions both with and without this term.
vit
Residual error term. The same model is used for investment companies, save that non-financial assets replace non-
investment property. nfait
Non Financial Assets. For the investment companies, it is not as easy to identify from the information contained in our database which assets are stated at market value and which are not. Manual checking of a sample of annual reports against the database, suggest that for most companies the variable ‘financial assets’ contain only the company’s investments (which are stated at market value), while for some companies, this variable in addition to the investments contain very small elements of other financial assets. While not ideal, we use this variable to proxy for assets stated at market value, and non-financial assets (total assets less financial assets) to represent assets that may not be stated at their full market value. We scale the variable by total assets. To the extent that historic cost may underestimate fair values, we tentatively predict that companies with high proportions of non-financial assets will trade at a premium to other investment companies. The descriptive statistics for the premium and the independent variables are contained in
tables 5 panels a) and b) for real estate and investment companies, respectively. For the 567 real estate companies for which we have data to undertake the analysis, the mean (median) premium is -15.41% (-21.24%), while for the investment companies, the premium is -10.43% (-12.16%). Table 5 about here. Correlation matrices for the variables included in the analysis of the premium are contained in table 6, panels a) and b), for respectively the real estate and the investment companies. Table 6 about here. Real Estate The regression output from the analysis of the premium for real estate companies is contained in table 7 panel a). In all regressions we observe a highly significant negative constant term, indicating that real estate companies, ceteris paribus, tend to trade at large discounts to their asset values. 21
Table 7 about here. Companies with large mark-to-market earnings are found to trade at a significant premium to other real estate companies. This is consistent with our hypotheses, and suggests that companies recently performing well (possibly indicative of managerial quality) trade at a lower discount than do other firms. We further find a significant negative relationship between the size of the revaluation reserve and the premium. This may be attributable to possible tax effects from the realisation of the unrealised property gains. Further analysis suggests that the negative relationship between revaluations and the premium is attributable to companies with large revaluation reserves, while negative revaluations appear to have no impact on the valuation premium. We do not have full explanations for this result, although it is possible that the potential tax liability from the realisation of the investment gain is only deemed credible for companies with large revaluations or indeed that small revaluations are accounted for via deferred tax whilst large revaluations, which may not be expected to materialise in the foreseeable future so may not be provided for. The mark-to-market adjustments thus help explain a significant proportion of the crosssectional variation in the valuation premium, and thus appears to provide information of relevance to investors. We hypothesise that there would be a positive coefficient on trade expenses – companies with low expenses (which are stated with a negative sign) are expected to trade at a premium relative to other firms. When the proportion of non-investment assets is controlled for, this is what we observe, although the coefficient is not significant. However, when we do not include this variable, trade expenses have a marginally significant negative coefficient, contrary to expectations. As indicated in the correlation matrix, companies with large amounts of non-investment properties tend to have lower trading expenses than other firms (Pearson (Spearman) correlation coefficient of -0.476 (-0.564)). It appears that failure to control for the proportion of assets that are not investment properties may bias the coefficient on trade expenses. Although the coefficient on gearing is negative, as predicted, it is not statistically significant in any of the regressions. Contrary to the findings of Barkham and Ward (1999), but consistent with the findings of Capozza and Lee (1996), we find large companies to trade at a high premium compared to small real estate companies. We do not know the cause of this size effect, although it is possible that larger real estate companies are more closely follows my analysts and ‘sophisticated’ (institutional) investors, and are therefore valued more in line with their asset values. Consistent with expectations, we find a significant positive relationship between the premium and the proportion of non-investment property assets in the balance sheet. Such assets – which include trading properties – are usually stated at historic cost, and may thus be undervalued in the accounts. Including this variable increase the explanatory power of the model (based on total revaluations) from 8.8% to 10.6%. We have also estimated the model incorporating annual intercept dummies and although the 22
explanatory power increases significantly, from 10.5% to 18.2% for the full model, the other results are unchanged so we do not report these results. However, this result does suggest a significant time variation in the valuation premium, consistent with market conditions and investor sentiment affecting the discount to net asset values. Investment Companies For the investment companies, the explanatory power of our models – as reported in panel b) of table 7 – are much lower than what we observed for the real estate companies, and we are only able to explain 2.8% of the cross-sectional variation in the premium. This increase to 4.4% when we include annual intercept dummies in the regressions. We find no significant impact of either company performance or the magnitude of unrealised investment appreciations – whether studied as a continuous variable, or whether we split the sample into observations with negative, medium and high revaluations. Mark-to-market adjustments thus explain little of the cross-sectional variation in the valuation premium. Similarly, we find company size and the proportion of assets that are not financial, do not have a significant impact on the premium. The lack of significance of the revaluation variable may be one of the more significant results we present. It is our understanding of the tax rules that apply to investment trust holdings that gains in investment value are not subject to capital gains tax, whereas gains in investment property values are for real estate firms. This is entirely consistent with significant results on the revaluation variable for real estate and not for investment trusts. In addition to the intercept (which are significant in OLS and robust regressions, but not under annual estimation) and the year dummies, two variables have a significant impact on the premium. Firstly, companies with low trade expenses have significantly higher premia than other firms, consistent with expectations. Secondly, we find companies with large amounts of debt trade at a higher premium than do other firms (although this is not significant under annual estimation). This is contrary to our expectations of the discount being magnified by gearing, which we therefore reject. We do not have a complete explanation of this finding. It may be that shareholders prefer highly geared investment trusts, due to the multiplier effect from any investment gains. Alternatively, high gearing may act as a control on managerial behaviour, and thus help alleviate agency costs (Jensen, 1986).
7.
Conclusions We investigate the importance of using GAAP, historic cost or mark-to-market accounting in
a valuation model for British real estate or investment trust companies. This is an unusual and potentially valuable opportunity to investigate the characteristics of three different accounting approaches. We find that in general income figures contribute little, and we ascribe that to the 23
efficient markets in which the firms trade as this implies that profits and loses will tend to be transient. However, GAAP income figures, which contain a higher proportion of persistent income or expenses, tend to have higher coefficients than do historic cost or mark-to-market earnings. The revaluation element recorded in the balance sheet is highly significant, and in improving the economic relevance of the shareholders equity figure, it reduces the importance of income in the valuation model. These results were as expected. However, we encounter two puzzles that are not yet resolved. Firstly, the negative income interaction term for investment trusts, which is normally expected to simply counteract the positive income coefficient, is much larger than expected – although not larger than would be typical for commercial or industrial firms. We have no robust explanation for this result at this point. Secondly, we find that the value of shareholders equity for both industries typically exceeds that of the market capitalisation of firms by, on average, somewhere between 10 and 20 percent. Further analysis of the discount indicate that real estate companies tend to trade at a lower discount if they perform well (as measured by their mark-to-market profitability), while companies with large revaluations (possibly associated with tax effects) tend to trade at larger discounts. Markto-market adjustments thus help explain some of the cross-sectional variation in the discount. In addition, we find larger real estate companies to trade at a lower discount than smaller firms. For investment companies, we are able to explain very little of the variation in discounts between companies. The cause of the discount to asset values at which British real estate and investment companies trade thus remains a puzzle.
24
References Aboody, D., M.E. Barth and R. Kasznik (1999), ‘Revaluations of Fixed Assets and Future Firm Performance: Evidence from the UK’, Journal of Accounting and Economics, Vol. 26, pp. 149-178. Adams, A. and P. Venmore-Rowland (1989), ‘Property Share Valuation’, Journal of Property Valuation, Vol. 8, No. 2, pp. 147-142. Ahmed, A.S. and C. Takeda (1995), ‘Stock Market Valuation of Gains and Losses on Commercial Banks’ Investment Securities – As Empirical Analysis’, Journal of Accounting and Economics, Vol. 20, pp. 207-225. Amir, E., T.S. Harris and E.K. Venuti (1993), ‘A Comparison of the Value-Relevance of U.S. Versus Non-U.S. GAAP Accounting Measures Using Form 20-F Reconciliations’, Journal of Accounting Research, Vol. 31 (Supplement), pp. 230-264. Barkham, R.J. and C.W.R. Ward (1999), ‘Investor Sentiment and Noise Traders: Discount to Net Asset Value in Listed Property Companies in the U.K.’, Journal of Real Estate Research, Vol. 18, No. 2, pp. 291-312. Barth, M.E. (1991), ‘Relative Measurement Errors Among Alternative Pension Asset and Liability Measures’, The Accounting Review, Vol. 66, (July), pp. 433-463. Barth, M.E. (1994), ‘Fair-Value Accounting: Evidence from Investment Securities and the Market Valuation of Banks’, The Accounting Review, Vol. 96, Iss 1 (January), pp. 1-25. Barth, M., W. Beaver and W. Landsman (1992), ‘The Market Valuation Implications of Net Periodic Pension Cost Components’, Journal of Accounting & Economics, Vol. 15, pp27-62. Barth, M.E., W.H. Beaver and W.R. Landsman (1996), ‘Value-Relevance of Banks’ Fair Value Disclosures under SFAS No. 107’, The Accounting Review, Vol. 71, No. 4 (October), pp. 513-537. Barth, M., W. Beaver and M. Wolfson (1990), ‘Components of Earnings and the Structure of Bank Share Prices’, Financial Analysts Journal, (May-June), pp53-60. Barth, M.E., and G. Clinch (1996), ‘International Accounting Differences and their Relation to Share Prices: Evidence from U.K., Australian, and Canadian Firms’, Contemporary Accounting Research, Vol. 13, pp. 135-170. Barth, M.E., and G. Clinch (1998), ‘Revalued Financial, Tangible, and Intangible Assets: Associations with Share Prices and Non-Market-Based Value Estimates’, Journal of Accounting Research, Vol. 36, Supplement, pp. 119-233. Barth, M. and W. Landsman (1995), ‘Fundamental Issues Related to Using Fair Value Accounting for Financial Reporting’, Accounting Horizons, Vol. 9 (December), pp97-107. Barth, M., W. Landsman and J. Walhen (1995), ‘Fair Value Accounting: Effects on Banks Earnings Volatility, Regulatory Capital, and Value of Contractual Cash Flows’, Journal of Banking and Finance, No. 19, pp577-605. Beaver, W. and M. Venkatachalam (1999), ‘Differential Pricing of Discretionary, Nondiscretionary and Noise Components of Loan Fair Values’, Working Paper. Brauer, G. (1984), ‘‘Open-Ending’ Closed-End Funds’, Journal of Financial Economics, Vol. 13, pp. 491-507. Brickley, J. and J. Schallheim (1985), ‘Lifting the Lid on Closed-End Investment Companies: A Case of Abnormal Returns’, Journal of Financial and Quantitative Analysis, Vol. 20, pp. 107-117. Capozza, D.R. and S. Lee (1996), ‘Portfolio Characteristics and Net Asset Values in REITs’, Canadian Journal of Economics, Vol. 29, No. 2, pp. 520-526. Carroll, T.J., T.J. Linsmeier and K.R. Petroni (2002), ‘The Reliability of Fair Values vs. Historical Cost Information: Evidence From Closed-End Mutual Funds’, Journal of Accounting, Auditing and Finance, Forthcoming. Chen, J., H. Hong and J. Stein (2002), ‘Breadth of Ownership and Stock Returns’, Journal of Financial Economics, forthcoming. Cheng, A., L. Copeland and J. O’Hanlon (1994), ‘Investment Trust Discounts and Abnormal Returns: UK Evidence’, Journal of Business Finance & Accounting, Vol. 21, pp. 813-831. Danbolt, J. and W. Rees (2002), ‘The Valuation of European Financial Firms’, Review of Accounting and Finance, Vol. 1, No. 1, pp. 5-24. 25
DeLong, J.B., A. Shleifer, L. Summers and R.J. Waldmann (1990), ‘Noise Trader Risk in Financial Markets’, Journal of Political Economy, Vol. 98, pp. 703-738. Dimson, E. and C. Minio-Paluello (2002a), ‘A Factor Model of the Closed-End Fund Discount’, Working Paper, London Business School. Dimson, E. and C. Minio-Paluello (2002b), ‘The Closed-End Fund Discount’, Working Paper, London Business School. Easton, P. (1998), ‘Discussion of Revalued Financial, Tangible, and Intangible Assets: Associations with Share Prices and Non-Market-Based Value Estimates’ [by Barth, M.E., and G. Clinch], Journal of Accounting Research, Vol. 36, Supplement, pp. 235-247. Easton, P.D. and D.H. Eddey (1997), ‘The Relevance of Asset Revaluations over and Economic Cycle’, Australian Accounting Review, Vol. 7, pp. 22-30. Easton, P.D., D.H. Eddey and T.S. Harris (1993), ‘An Investigation of Revaluations of Tangible Long-Lived Assets’, Journal of Accounting Research, (Supplement), pp. 1-38. Eccher, E.A., K. Ramesh and S.R. Thiagarajan (1996), ‘Fair-Value Disclosures by Bank Holding Companies’ Journal of Accounting and Economics, Vol. 22, pp. 79-117. Fama, E. and K. French (1992), ‘The Cross-Section of Expected Stock Returns’, Journal of Finance, Vol. 47, pp. 427-465. Gemmill, G. and D.C. Thomas (2002), ‘Noise Trading, Costly Arbitrage, and Asset Prices: Evidence from Closed-end Funds’, Journal of Finance, Vol. 57, No. 6, pp. 2571-2594. Gordon, E.A. and L. Vincent (2000), ‘A Comparison of the Equity Valuation of Property Companies in Hong Kong, the United Kingdom and the United States’, Unpublished manuscript, University of Chicago/Northwestern University. Holthausen, R.W. and R.L. Watts (2001), ‘The Relevance of Value-Relevance Literature for Financial Accounting Standard Setting’, Journal of Accounting and Economics, Vol. 31, pp. 3-75. Jensen, M.C. (1986), ‘Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers’, American Economic Review, Vol. 76, No. 2, pp. 323-329. Jones, C. and O. Lamont (2002), ‘Short Sale Constraints and Stock Returns’, Journal of Financial Economics, forthcoming. Landsman, W.R. (1986), ‘An Empirical Investigation of Pension Fund Property Rights’, The Accounting Review, Vol. 61 (October), pp. 662-691. Lee, C.M.C., A. Shleifer and A.R.H. Thaler (1991), ‘Investor Sentiment and the Closed-End Fund Puzzle;, Journal of Finance, Vol. 46, No. 1, pp. 75-109. Malkiel, B. (1977), ‘The Valuation of Closed-End Investment-Company Shares’, Journal of Finance, Vol. 32, pp. 847-858. Malkiel, B.G. (1995), ‘The Structure of Closed-End Fund Discount Revisited’, Journal of Portfolio Management, pp. 32-38. Minio-Paluello, C. (1998), ‘The UK Closed-End Fund Discount’, PhD Thesis, London Business School. Nelson, K.K. (1996), ‘Fail Value Accounting for Commercial Banks: An Empirical Analysis of SFAS No. 107’, The Accounting Review, Vol. 71, Iss. 2 (April), pp. 161-182. Ohlson, J. (1995), ‘Earnings, Book Values and Dividends in Equity Valuation’, Contemporary Accounting Research, Spring, Vol. 11, No. 2, pp661-687. Petroni, K.R. and J.M. Wahlen (1995), ‘Fair Values of Equity and Debt Securities and Share Prices of Property-Liability Insurers’, The Journal of Risk and Insurance, Vol. 62, Iss 4 (December), pp. 719-737. Pontiff, J. (1996), ‘Costly Arbitrage: Evidence from Closed-End Funds’, Quarterly Journal of Economics, Vol. 111, pp. 1135-1151. Pope, F. and W. Rees (1993), ‘International Differences in GAAP and the Pricing of Earnings’, Journal of International Financial Management and Accounting, pp. 190-219. Rees, W. (1997), ‘The Impact of Dividends, Debt and Investment on Valuation Models’, Journal of Business Finance and Accounting, Vol. 24, No. 7&8, pp. 1111-1140. Rees, W. (1999) ‘Influences on the Value Relevance of Equity and Net Income in the U.K.’, Managerial Finance, Vol. 25, No. 12, pp58-65. Standish, P. and S. Ung (1982), ‘Corporate Signaling, Asset Revaluations and the Stock Prices of British Companies’, The Accounting Review, Vol. 57, Iss. 4 (October), pp. 701-715. 26
Thompson, R. (1978), ‘The Information Content of Discounts and Premiums on Closed-End Fund Shares’, Journal of Financial Economics, Vol. 6, pp. 151-186. Vincent, L. (1999), ‘The Information Content of Funds From Operations (FFO) for Real Estate Investment Trusts (REITs)’, Journal of Accounting and Economics, Vol. 26, pp69-104. Warfield, T. and T. Linsmeier (1992), ‘Tax Planning, Earnings Management, and the Differential Information Content of Bank Earnings Components’, Accounting Review, Vol. 67, No. 3 (July), pp546-562. Weiss, K. (1989), ‘The Post-Offering Price Performance of Closed-End Funds’, Financial Management, Vol. 18, No. 3, pp. 57-67.
27
Table 1. Sample The table explains the derivation of our sample. Data is obtained from Company Analysis. We impose the restriction that both the Financial Times (FT) industrial classification and the standard industrial classification (SIC) classify the company as belonging to the real estate or the investment companies sector, respectively. pr/eqHC refers to the market to book ratio, where the book value of equity is measured on a historic cost basis, rv/eqHC to revaluations (the difference between book equity using GAAP and HC) scaled by historic cost book equity, niGAAP/eqHC to the net income reported under Generally Accepted Accounting Principles scaled by historic cost book equity, niHC/eqHC to the net income under the historic cost convention scaled by historic cost book equity, and niMM/eqHC to the net income under mark-to-market scaled by historic cost book equity.
Initial sample of firms classified as respectively Real Estate Companies or Investment Companies by both FT and SIC, 1993-2002 Missing or unsuitable data: Share price missing Equity at historic cost missing Equity at historic cost zero or negative Accounting year outwith 350-380 days Maximum GAAP sample: Trim top and bottom 1% of pr/eqHC Trim top and bottom 1% of rv/eqHC Trim top and bottom 1% of niGAAP/eqHC Maximum Historic Cost sample: Trim top and bottom 1% of pr/eqHC Trim top and bottom 1% of rv/eqHC Eliminate where niHC/eqHC missing, and trim top and bottom 1% of niHC/eqHC Maximum Mark-to-Market sample: Trim top and bottom 1% of pr/eqHC Trim top and bottom 1% of rv/eqHC Eliminate where niMM/eqHC missing, and trim top and bottom 1% of niMM/eqHC Balanced Sample for all three models: Trim top and bottom 1% of pr/eqHC Trim top and bottom 1% of rv/eqHC Trim top and bottom 1% of niGAAP/eqHC Eliminate where niMM/eqHC missing, and trim top and bottom 1% of niMM/eqHC Eliminate where niHC/eqHC missing, and trim top and bottom 1% of niHC/eqHC
28
Real Estate 989
Investment 2,703
174 116 8 691
69 509 4 2,121
11 680
182 1,939
13 11 11 645
39 22 31 1,847
13 11 100
39 22 497
556
1,381
13 11 82
39 22 520
574
1,358
13 11 11 78
39 22 31 512
21
17
546
1,318
Table 2. Descriptive Statistics The table contains descriptive statistics for three different sets of accounting numbers. pr/eqHC refers to the market to book ratio, where the book value of equity is measured on a historic cost basis, rv/eqHC to revaluations (the difference between book equity using GAAP and HC) scaled by historic cost book equity, ni/eqHC to the net income scaled by historic cost book equity, D to a negative net income dummy variable, and Dni/eqHC to the interactive term between this dummy variable and net income scaled by historic cost book equity. GAAP refers to reported accounting numbers under UK Generally Accepted Accounting Principles, MM refers to numbers using mark-to-market accounting policies, while HC refers to numbers constructed under the historic cost convention.
Mean
Median
Min
Max
Q1
Q3
1.3097 0.6169
1.2211 0.4963
0.5097 0.4774 0.5300 -0.3495
3.1616 2.4362
0.9467 0.2060
1.5832 0.8984
NiGAAP/eqHC DGAAP DniGAAP/eqHC
0.0708 0.0769 -0.0070
0.0718
0.0693
-0.3403
0.2431
0.0421
0.1099
0.0000
0.0341
-0.3403
0.0000
0.0000
0.0000
NiHC/eqHC DHC DniHC/eqHC
0.0912 0.0916 -0.0095
0.0910
0.0968
-0.3157
0.4404
0.0465
0.1406
0.0000
0.0398
-0.3157
0.0000
0.0000
0.0000
NiMM/eqHC DMM DniMM/eqHC
0.1858 0.1154 -0.0124
0.1736
0.1866
-0.4344
1.0184
0.0752
0.2894
0.0000
0.0520
-0.4344
0.0000
0.0000
0.0000
0.9727 0.1800
0.3542 0.1774 0.3037 -0.6275
2.1775 1.8173
0.7555 0.0149
1.1766 0.3745
Panel a – Real Estate (546) Pr/eqHC Rv/eqHC
Panel b – Investment Trusts (1,318) Pr/eqHC 0.9790 Rv/eqHC 0.2058
Std.Dev.
NiGAAP/eqHC DGAAP DniGAAP/eqHC
0.0213 0.1829 -0.0017
0.0165
0.0261
-0.0445
0.1314
0.0026
0.0362
0.0000
0.0055
-0.0445
0.0000
0.0000
0.0000
NiHC/eqHC DHC DniHC/eqHC
0.0634 0.2261 -0.0230
0.0765
0.1241
-0.6051
0.4401
0.0082
0.1330
0.0000
0.0686
-0.6051
0.0000
0.0000
0.0000
NiMM/eqHC DMM DniMM/eqHC
0.0689 0.3475 -0.0692
0.0948
0.2550
-0.8996
1.0416
-0.0673
0.2231
0.0000
0.1412
-0.8996
0.0000
-0.0673
0.0000
29
Table 3. Correlation Matrix The table contains Pearson correlation coefficients (bottom left corner) and Spearman rank correlation coefficients (top right corner) for all dependent and independent variables, based on the balanced sample. All variables are scaled by historic cost book value (eqHC). Panel a – Real Estate pr rv niGAAP D Dni niHC DHC DniHC niMM DMM DniMM pr 0.663*** 0.344*** -0.131*** 0.130*** 0.311*** -0.142*** 0.143*** 0.398*** -0.160*** 0.159*** rv 0.644*** 0.336*** -0.175*** 0.171*** 0.335*** -0.194*** 0.190*** 0.479*** -0.128*** 0.126*** ni 0.295*** 0.268*** -0.462*** 0.462*** 0.780*** -0.405*** 0.404*** 0.394*** -0.298*** 0.299*** D -0.121*** -0.160*** -0.677*** -0.999*** -0.360*** 0.719*** -0.719*** -0.340*** 0.412*** -0.415*** Dni 0.073* 0.067 0.724*** -0.715*** 0.364*** -0.724*** 0.726*** 0.342*** -0.417*** 0.421*** niHC 0.250*** 0.268*** 0.705*** -0.449*** 0.507*** -0.500*** 0.500*** 0.418*** -0.313*** 0.313*** DHC -0.129*** -0.170*** -0.575*** 0.719*** -0.608*** -0.641*** -0.998** -0.345*** 0.382*** -0.382*** DniHC 0.112*** 0.100** 0.562*** -0.555*** 0.745*** 0.660*** -0.754*** 0.347*** -0.391*** 0.391*** niMM 0.387*** 0.424*** 0.423*** -0.324*** 0.292*** 0.405*** -0.324*** 0.307*** -0.553*** 0.555*** DMM -0.121*** -0.075* -0.385*** 0.412*** -0.376*** -0.366*** 0.382*** -0.382*** -0.568*** -0.998*** DniMM 0.037 -0.007 0.304*** -0.282*** 0.383*** 0.281*** -0.256*** 0.357*** 0.533*** -0.663*** Panel b – Investment Trust pr rv niGAAP DGAAP DniGAAP niHC DHC DniHC niMM DMM DniMM pr 0.740*** 0.248*** -0.125*** 0.113*** 0.362*** -0.326*** 0.328*** 0.498*** -0.398*** 0.416*** rv 0.744*** 0.199*** -0.116*** 0.110*** 0.381*** -0.371*** 0.381*** 0.633*** -0.510*** 0.534*** niGAAP 0.177*** 0.125*** -0.670*** 0.674*** 0.270*** -0.306*** 0.310*** 0.134*** -0.126*** 0.153*** DGAAP -0.100*** -0.128*** -0.552*** -0.993*** -0.228*** 0.265*** -0.274*** -0.096*** 0.116*** -0.144*** DniGAAP -0.050* -0.011 0.479*** -0.644*** 0.230*** -0.265*** 0.273*** 0.093*** -0.111*** 0.139*** niHC 0.312*** 0.362*** 0.197*** -0.234*** 0.154*** -0.725*** 0.732*** 0.434*** -0.366*** 0.406*** DHC -0.300*** -0.357*** -0.246*** 0.265*** -0.181*** -0.719*** -0.989*** -0.377*** 0.352*** -0.404*** DniHC 0.216*** 0.303*** 0.194*** -0.227*** 0.126*** 0.786*** -0.620*** 0.389*** -0.363*** 0.422*** niMM 0.454*** 0.601*** 0.090*** -0.109*** 0.040 0.486*** -0.402*** 0.402*** -0.825*** 0.850*** DMM -0.355*** -0.476*** -0.074*** 0.116*** -0.023 -0.371*** 0.352*** -0.301*** -0.767*** -0.971*** DniMM 0.321*** 0.459*** 0.118*** -0.179*** 0.061** 0.480*** -0.425*** 0.499*** 0.819*** -0.672***
30
Table 4. Regression Analysis – Valuation Models The table contains output from OLS regressions of the ratio of the share price to the historic cost book value of equity (pr/eqHC) on historic cost book equity (eqHC/eqHC), the difference between GAAP and historic cost book equity scaled by historic cost book equity (rv/eqHC), net income (ni/eqHC), a negative net income dummy variable (D), and the interactive term between this dummy variable and net income (Dni/eqHC). All variables are scaled by historic cost book equity (eqHC). In the historic cost (mark-to-mark) accounting regressions, the historic cost (mark-to-market) ni, D, and Dni figures are applied. t-statistics are reported in brackets. Coefficients which change sign or lose significance under alternative estimation techniques are reported in italics.
Sample
eqHC/ eqHC
rv/ eqHC
Dni/ eqHC
Adj R2
F-stat
ni/ eqHC
D
3.8064 (8.40)
0.0501 (0.43)
-4.2285 (-4.36)
12.4%
26.64 (0.000)
1.9226 (5.08)
0.1524 (1.64)
-1.4755 (-1.86)
43.8%
107.14 (0.000)
1.6502 (5.43)
0.0015 (0.01)
-1.2109 (-1.40)
6.3%
13.13 (0.000)
0.5654 (2.29)
0.1234 (1.34)
0.4003 (0.58)
41.9%
99.16 (0.000)
1.4250 (10.75)
0.0456 (0.52)
-2.1736 (-4.16)
18.6%
42.49 (0.000)
0.4458 (3.47)
-0.0442 (-0.60)
-0.6283 (-1.40)
42.8%
103.09 (0.000)
2.9529 (6.66)
-0.1245 (-3.63)
-15.5500 (-6.79)
6.2%
29.97 (0.000)
1.8650 (6.17)
-0.0019 (-0.08)
-7.0120 (-4.46)
56.8%
433.30 (0.000)
0.7642 (5.60)
-0.1434 (-4.49)
-0.5125 (-2.34)
11.1%
55.70 (0.000)
0.3436 (3.55)
-0.0215 (-0.95)
-0.5878 (-3.81)
55.9%
417.67 (0.000)
0.7782 (11.29)
-0.0239 (-0.84)
-0.4005 (-3.72)
21.3%
119.59 (0.000)
0.1122 (2.00)
0.0015 (0.07)
-0.2014 (-2.48)
55.4%
409.56 (0.000)
(P-value)
Panel a – Real Estate GAAP
Balanced sample
(546)
1.0067 (23.03)
(546)
0.7996 (21.63)
Historic Cost Balanced (546) sample (546) Mark-to-Market Balanced (546) sample (546)
0.5705 (17.43)
1.1457 (28.45) 0.8805 (25.18)
0.6000 (18.25)
1.0126 (27.86) 0.8847 (28.00)
0.5502 (15.19)
Panel b – Investment Trusts GAAP
Balanced sample
(1,318)
0.9129 (56.20)
(1,318)
0.7540 (64.17)
Historic Cost Balanced (1,318) sample (1,318) Mark-to-Market Balanced (1,318) sample (1,318)
0.8456 (39.22)
0.9512 (51.47) 0.7744 (55.75)
0.8461 (36.52)
0.9060 (50.04) 0.7809 (55.03)
0.8548 (31.71)
31
Table 5. Descriptive Statistics – Analysis of Premium The table contains descriptive statistics for the analysis of the premium – the extent to which the share price exceed the reported book value per share (pr/eq – 1). The other variables are: the mark-to-market profit scaled by reported book equity (niMM/eq); Revaluations scaled by book equity (rv/eq); gearing (debt to book value of equity); size (natural logarithm of the book value of equity); and the proportion of total assets which are not investment and development properties. This last variable is missing for 45 observations for Real Estate Companies, and analysis is undertaken both with and without this variable included.
Panel a Real Estate Full sample (567) Premium NiMM/eq Rv/eq Te/eq Debt/eq Ln(bv) nip/ta (522) Panel b Investment Trusts Full sample (1,318) Premium NiMM/eq Rv/eq Te/eq Debt/eq Ln(bv) nfa/ta
Mean
Median
Std.Dev.
Min
Max
Q1
Q3
-0.1541 0.1094 0.3126 -0.1745 0.9085 4.3315 0.2510 Mean
-0.2124 0.3069 0.1162 0.1022 0.3250 0.2048 -0.0686 0.3670 0.7433 0.7519 4.3424 1.5370 0.1793 0.2193 Median Std.Dev.
-0.6625 -0.4039 -0.5372 -3.4256 0.0000 0.1080 0.0090 Min
2.8103 0.3989 0.7090 -0.0077 7.1372 8.7056 0.9716 Max
-0.3291 0.0508 0.1601 -0.1511 0.4652 3.4013 0.0835 Q1
-0.0563 0.1752 0.4710 -0.0305 1.1533 5.3352 0.3564 Q3
-0.1043 0.0192 0.1118 -0.0121 0.1485 4.2289 0.0716
-0.1216 0.0755 0.1526 -0.0105 0.0661 4.1490 0.0478
-0.9963 -2.1123 -1.6843 -0.0793 0.0000 0.6141 0.0003
1.3172 0.5982 0.6451 0.0015 2.7597 8.1898 0.9190
-0.1938 -0.0643 0.0147 -0.0161 0.0000 3.4057 0.0280
-0.0304 0.1704 0.2725 -0.0056 0.1930 5.0744 0.0814
0.1796 0.2673 0.2617 0.0087 0.2576 1.3001 0.0827
32
Table 6. Correlation Matrix – Analysis of Premium The table contains Pearson correlation coefficients (bottom left corner) and Spearman rank correlation coefficients (top right corner) for all dependent and independent variables, based on variables for the analysis of the valuation premium.
Panel a Real Estate Premium NiMM/eq rv/eq te/eq Debt/eq ln(bv) nip/ta Panel b Investment Companies Premium niMM/eq rv/eq te/eq debt/eq ln(bv) nfa/ta
Premium
niMM/eq
rv/eq
te/eq
debt/eq
ln(bv)
nip/ta
0.133***
-0.181*** 0.228***
-0.111*** 0.060 0.368***
-0.021 -0.089** -0.167*** -0.207***
0.224*** 0.220*** 0.340*** 0.395*** -0.051
0.187*** -0.057 -0.450*** -0.564*** 0.018 -0.206***
0.120*** -0.162*** -0.098** -0.043 0.132*** 0.240***
0.256*** -0.027 -0.230*** 0.199*** -0.048
0.212*** -0.203*** 0.333*** -0.427***
-0.073* 0.257*** -0.476***
-0.138*** -0.024
-0.210***
Premium
niMM/eq
rv/eq
te/eq
debt/eq
ln(bv)
Nfa/ta
0.050* 0.573***
0.222*** 0.208*** 0.385***
0.020 -0.110*** -0.075*** -0.031
0.158*** 0.139*** 0.281*** 0.540*** 0.106***
-0.084*** -0.133*** -0.179*** -0.181*** -0.017 -0.128***
0.027 -0.036 0.002 0.140*** 0.051* 0.091*** -0.070**
0.717*** 0.321*** -0.196*** 0.165*** -0.103***
0.427*** -0.236*** 0.277*** -0.141***
33
-0.141*** 0.470*** -0.270***
-0.060** 0.022
-0.110***
Table 7. Analysis of Premium The table contains output from OLS regressions of the determinants of the valuation premium – the extent to which the share price exceed the reported book value per share (pr/eq – 1). The premium is regressed against: the mark-to-market profit scaled by reported book equity (niMM/eq); Revaluations scaled by book equity (rv/eq) (in addition to analysis of total revaluations, the sample is also split into negative, medium and high revaluations. (in addition to analysis of total revaluations, the sample is also split into negative, medium and high revaluations. Negative revaluations occur in 4.95% (22.74%) of the firm-years for real estate (investment) companies. The positive revaluations are split into two equally sized groups); trading expenses scaled by equity (te/eq); gearing (debt to book value of equity); size (natural logarithm of the book value of equity); and the proportion of total assets which are not investment and development properties (for real estate companies) or financial assets (for investment companies). t-statistics are reported in brackets. Coefficients which change sign or lose significance under alternative estimation techniques are reported in italics. F-stat Sample Constant NiMM rv Negative Medium High te/eq debt/eq ln(bv) nip/ta or Adj R2 (P-value) /eq /eq rv/eq rv/eq rv/eq nfa/ta
Panel a - Real Estate Companies Full sample (567) -0.2580 (-5.52)
Reduced Sample
0.3927 (3.05)
(567)
-0.2566 (-5.08)
0.3737 (2.89)
(522)
-0.3937 (-7.28)
0.3516 (2.61)
(522)
-0.3990 (-6.80)
0.3372 (2.48)
-0.0860 (-3.64)
-0.0508 (-1.94)
-0.0857 (-3.45)
-0.0433 (-1.61)
Panel b – Investment Trusts Full sample (1,318) (1,318)
-0.3804 (-5.72) 0.2238 (0.66)
-0.3333 (-1.99)
-0.4189 (-5.34)
-0.1947 (-2.49) 0.0357 (0.10)
-0.0961 (-0.54)
-0.2038 (-2.19)
-0.0059 (-0.21) -0.0360 (-0.86)
34
-0.0432 (-0.45)
0.0212 (0.53)
-0.0818 (-2.32)
-0.0176 (-1.03)
0.0419 (4.78)
8.8%
11.94 (0.000)
-0.0763 (-2.16)
-0.0166 (-0.97)
0.0440 (4.99)
9.2%
9.20 (0.000)
0.0153 (0.38)
-0.0012 (-0.07)
0.0414 (4.68)
0.3447 (4.73)
10.6%
11.29 (0.000)
0.0143 (0.36)
-0.0013 (-0.07)
0.0424 (4.75)
0.3335 (4.49)
10.5%
8.65 (0.000)
3.1058 (4.44)
0.0408 (2.09)
0.0049 (1.13)
-0.0781 (-1.27)
2.8%
7.32 (0.000)
3.2001 (4.55)
0.0392 (2.00)
0.0043 (0.99)
-0.0774 (-1.26)
2.8%
5.77 (0.000)
Notes 1
The assumptions required to move from value as the present value of expected dividends to equation one above are: that expectations of time series of book value, net income and equity disbursements or increments (usually designated dividends) are governed by the clean surplus relationship - i.e. eqt = eqt-1 + nit + dvt; that both the expectations of the required rate of return and the growth rate of book value and net income can be equated to a constant equivalent; that the expected growth of book value and net income are the same; and finally that a current base level for earnings, from which growth is extrapolated, is a weighting of current net income and current book value of equity times the required rate of return. 2 While the change in GAAP or historic cost earnings have little impact on the change in market-tobook ratios, mark-to-market earnings are highly significant in the absence of revaluations. With revaluations included, the adjusted R2 of the models exceed 17% for all three models for the real estate companies, and 47% for the investment companies. The first-difference results thus confirm the significance of revaluations, as reported below in the scaled levels regressions. The results from the first-difference regressions are available from the authors upon request. 3 Prior evidence (e.g., Barth et al., 1992) indicates that the results are not sensitive to the choice between year end or disclosure date share prices. 4 The results for the full sample analysis, the estimations using robust regressions and annual regressions are available from the authors on request. 5 Given the significantly higher levels of MM earnings than that for either of the two other models, we would in any case expect the level of the coefficient for mark-to-market accounting to be lower than that for either GAAP or HC accounting. 6 The interactive term for negative earnings, while highly significant under OLS and robust estimation, lose significance under annual estimation, suggesting there may be some time variation in the impact of negative MM earnings on the market-to-book ratio. 7 The results for these tests are available from the authors on request.
35
