IMPACT ASSESSMENT OF RECOGNITION VERSUS NOTE DISCLOSURE IN OPERATING L - PDF document

1 IMPACT ASSESSMENT OF RECOGNITION VERSUS
IMPACT ASSESSMENT OF RECOGNITION VERSUS NOTE DISCLOSURE IN OPERATING LEASES Fito, M. Angels1 Universitat Oberta de Catalunya Moya, Soledad Universitat Autònoma de Barcelona Orgaz, Neus Universitat Autònoma de Barcelona Àrea temàtica: Información Financiera y Normalización Contable Keywords Operating leases, international accounting standards, impact assessment, constructive method, factor method 1 Corresponding author. afitob@uoc.edu , Avda. Tibidabo 39-43, 08035 Barcelona, Tel. +34 932 542 139 Fax +34 934 176 495 This study has received financial support from the Spanish Department of Science and Technology (Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica 2010-, Programa de Ciencias Sociales, Económicas y Jurídicas (Economía), (code: ECO 2010- 121a 2 IMPACT ASSESSMENT OF RECOGNITION VERSUS NOTE DISCLOSURE IN OPERATING LEASES Abstract In this paper we have simulated the effect that would be derived from the inclusion in the financial statements of Spanish Companies of the operating leases following the IASB new proposal. We have built on the constructive capitalization method as the basis for our analysis but we have also run the tests with the factor method. Results show how the impact on financial ratios is statistically significant. The ratios on leverage, debt quality, returns and Z Altman score are affected by the inclusion of operating leases in the financial statements. When the sector is considered, retail and energy show to be most affected. This study is an ex ante research and can not go beyond the effect analysis of this new standard. We believe that it is highly probable that, should the standard be implemented, some relevant economic consequences may be derived. Resumen Este trabajo simula el efecto que se derivaría de la inclusión de los contratos

2 de arrendamiento operativo en los estado
de arrendamiento operativo en los estados financieros de las empresas españolas en los términos incluidos en la nueva propuesta del IASB Si bien nuestro análisis se fundamenta sobre el constructive method hemos aplicado el desarrollo estadístico sobre el factor method. Los resultados obtenidos muestran que el impacto sobre los ratios financieros es estadísticamente significativo en los ratios de endeudamiento, calidad de la deuda, rentabilidad y el test de Altman. Cuando introducimos el sector en el análisis, los sectores de comercio al pormenor y energía se muestran como los más afectados. Si bien este estudio es una investigación ex-ante creemos que es muy probable que, si se llega a implementar la propuesta de cambio de registro contable de los arrendamientos operativos se derivaran consecuencias económicas relevantes 3 1. Introduction The International Accounting Standards Board (hereinafter IASB) has issued a new drat on Leases which introduces significant changes in the way operating leases should be recognized and measured in the financial statements. The first draft was issued in August 2010 and at the moment it is under discussion. The IASB pretends that it should be definitely issued by June 2011 although lobbying from companies affected substantially by the new regulation may delay its approval. Up to the moment, operating leases have been generally recognized as an expense in the exercise they are accrued and therefore, no recognition of assets or liabilities has taken place in the statement of financial position under the IAS 1 revised in 2010. However, the draft proposes recognizing those operating leases in the Statement of financial position of companies so that users are provided with a complete and understandable picture of an entity’s leasing activities. Following David Tweedie (the regular president of the IASB) considerations, the current accounting treatme

3 nt for leases omits relevant information
nt for leases omits relevant information about rights and obligations that meet the definitions of assets and liabilities in the boards’ conceptual framework. In Spain, there has been a considerable lobby against the proposed standard. Relevant Spaish quoted companies such as Telefonica, El Corte Inglés or Inditex 2 have shown themselves against IASB proposal as they consider that it may have a negative effect both in the leverage positions of companies and in their net income. Indeed, the implementation of the new draft may affect on the one hand, the level of leverage of companies as it is recognizing as a liability the total payments expected due to the operating lease contracts in force. On the other hand, a change in the net income is expected due to the different recognitions of expenses. The current recognition of the annual lease payment in the income statement would be substituted by the recognition of interests (included in the annual payment) and amortization of the right of use asset which would result in a different amount recognized as an expense. Prior literature on the impact of new accounting standards demonstrates how sometimes they do not only have a significant effect in the main accounting numbers, but they do also have economic consequences related for example with companies’ financial decisions. Papers such as Imhoff and Thomas (1988) showed how the introduction of a new standard 2 These companies are the 1, 7 and 15t in Spain by sales (2010). The main brands of INditex are Zara or Bershka, which are pretty well known around the world. 4 related to the financial lease (where recognition versus disclosure for capital leases was discussed) had an economic impact in financial structure of companies as they found a significant substitution from capital leases to operating ones, a substitution towards non lease financi

4 ng and a significant increase in equity
ng and a significant increase in equity while conventional long term debt diminished. The objective of this study is to determine if the effect of the implementation of this new standard would be statistically significant for the particular case of Spain. If the effect is relevant and financial analysis is affected substantially, some economic consequences may be derived from its implementation. In this first ex ante research (Schipper, 1994) we will only be able to determine if the impact is significant or not but if it is, we will be on guard about the possible economic consequences that arise after the implementation. The data analyzed will be that of public Spanish companies quoted on the 31.12.2009 as they are the ones affected in the first moment by the new draft. The reason to choose Spain as our scenario has been the strong prediction of an important effect due to the important lobby that Spanish companies are doing to change or even cancel the implementation of this new draft as can be derived from the comment letters that those Spanish companies have sent to the IASB in response to the new proposal for lease accounting ( Expected results are a significant change in the accounting numbers of Spanish companies should the draft be issued and, therefore, some possible economic consequences related to the way companies choose their financial resources (not testable for the moment, only based in prior literature on economic consequences derived from new standards implementationWe expect a substantial increase in the level of leverage of companies analyzed and a diminishing of the net income due to the change in the expenses recognition in the income statement. . The paper pretends to contribute to the literature on the impact of the implementation of new standards in European countries and pretends also to warn users of financial statements of the possible change in the predictions of companie

5 s’ performance. The debate on recog
s’ performance. The debate on recognition versus disclosure is important for preparers, auditors, financial analysts and users in general and the literature on how the market captures the former versus the latter provides mixed evidence. Lipe (2001) shows that measures of shareholder risk can be better explained when one includes the financial leverage implicit in unrecorded leases. 5 However, and following Jifri et al. (2009), analysts seem to incorporate efficiently information irrespectively of where it appears in the annual report. The remainder of our paper is as follows: section two includes the main changes incorporated in IASB’s draft. Section three revises previous literature and proposes the hypothesis. Section four explains the data and methodology, section five describes results and finally some conclusions are provided. 2. Regulatory framework Lease is generally considered to be an important source of finance. Therefore, it seems important that lease accounting should provide users of financial statements with a complete and understandable picture of an entity’s leasing activities. The existing accounting models for leases require lessees to classify their leases as either finance or operating leases. However, those models have been criticized for failing to meet the needs of users of financial statements as they do not provide a faithful representation of leasing transactions (IASB, Exposure draft, 2010). In particular, they omit relevant information about rights and obligations that meet the definitions of assets and liabilities in the boards’ conceptual framework. Proponents of this new modification on lease accounting also argue that the model now in force leads to a lack of comparability and undue complexity because of the sharp “bright line” distinction between finance and operating leases. As a result, many users of financial statements adjust t

6 he amounts presented in the statement of
he amounts presented in the statement of financial position to reflect the assets and liabilities arising from operating leases. Accordingly, the IASB and the FASB have jointly developed a draft standard on leases which introduces relevant changes in the way operating leases are measured and recoed in the financial statements. This draft incorporates substantial changes both for lessees and for lessors, although the scope of our study is the impact assessment in the lessees financial statements. The exposure draft proposes that lessees should apply a right-use model in accounting which means that, at the date of commencement of a lease, a lessee shall recognize in the statement of financial position a right of use asset and a liability to make “lease payments”. To measure the liability, the lessee will estimate the present value of the leases payments discounted using the lessee’s incremental borrowing rate or, if it could be readily 6 d, the rate of the lessor charges the lessee. The asset will be valued as the liability plus any direct costs incurred by the lessee. After the date of commencement of the lease, the lessee shall measure the liability at amortized cost using the effective interest method and the right of use asset also at amortized cost. Considering that, up to the moment, IFRSs and US GAAP account for the lease payments arising from operating leases by recognizing them in the period in which they occur, the draft incorporates substantial changes to the current accounting policy. Lessees would be most affected if they have a significant portfolio of assets held under operating leases, especially those with leases of property. We expect that the longer the contracts the bigger the effect, both in the income statement and in the statement of financial position. 3. Literature Review and Hypothesis Development In our paper we are trying to predict what will be the

7 impact for financial statements’ u
impact for financial statements’ users of a change in the leases regulatory framework in Europe. We understand that our study can be considered like ex ante research as described by Schipper in 1994. In her discussion paper, she defines ex ante research by reference to its opposite, ex post research, and states that the former deals with an item that the standard setters are considering while the latter uses results of already promulgated standards as an input to the research analysis. Ex ante leases literature focuses basically on the predicted impact of the new regulation while ex post leases debates on the economic consequences derived from the new regulatory framework. The first studies trying to predict the impact of lease capitalization took place in the US, specifically with Nelson (1963) who demonstrated that, for a sample of eleven US companies, most financial ratios were adversely affected by lease capitalization. Already in 1976, the Financial Accounting Standards Board issued a new Standard (number 13) “Accounting for Leases”. This standard changed the form of capital lease disclosures by requiring all capital Leases to be reported as assets and debt effectively moving them from the footnotes to the balance sheet. Imhoff and Lipe (1988) studied the effect of this new regulation and show how accounting standards can cause relevant effects in companies and therefore have important economic consequences. They found a significant effect due to the implementation of this new regulation. And they found relevant economic such as a decrease in capital lease versus operating lease, decrease in total lease versus other 7 financial resources and decrease in total debt versus equity and leverage. Therefore, the financial structure of companies changed substantially once the standard came into force, corroborating theories supporting the relationship between accounting regulation an

8 d economic decisions. Another paper al
d economic decisions. Another paper also by Imhoff et al. (1993) constructively capitalized operating leases by estimating the present value of operating leases for a sample of 29 airlines and 51 grocery stores. They also found significant effects derived from the capitalization. In Europe, local standards prior to IFRS have also been evolving towards the incorporation of leases in the statement of financial position. Beattie et al. (1998) conducted a study with a prospective analysis of the effects of capitalizing operating leases in the accounts of UK lessees. Results for a sample of listed UK companies show that, on average, the unrecorded long-term liability represented 39% of reported long term debt while the unrecorded asset represented the 6% of total assets. Capitalization had a significant impact on several financial ratios and measures of gearing. Some other country specific studies can be found in Bennet and Bradbury (2003) (2003) for New Zealand, Durocher (2005) for Canada or Fülbier (2008) for Germany. This study examined the potential effects of an on-sheet accounting treatment for operating leases. They identified a significant capitalization impact for a considerable number of companies in general and for certain industry groups (fashion and retail) in particular. They observed changes in financial ratios for the statement of financial position relations but minor effects for profitability ratios and valuation multiples. Moving towards a more ex post approach, there is a broad literature on economic consequences of accounting standards, which has constantly tried to answer to the question of whether accounting standard setters should take account of the effects or cnsequences of the standards they develop. If changes in accounting standards generate significant effects in the financial statement of companies, they may also generate relevant economic effects which can affect the pro

9 cess of decision making. Starting from
cess of decision making. Starting from the paper of Holthausen and Leftwich3 (1981), several studies have tried to determine if the effect of accounting standards is significant, why companies choose one 3 Papers which have been very relevant in the development of economic consequences theories are Watts, R. (1977) or Watts and Zimmerman (1978). In both papers we can find the basis for the theories that explain the link between firms, cash flows and reported accounting income numbers. 8 accounting choice or what is the relationship between lobbying and economic consequs of regulation. They propose a very interesting literature review on the economic consequences theories starting from the assertion that accounting choices have economic consequences if changes in the rules used to calculate accounting numbers alter the distribution of firms’ cash flows or the wealth of parties who use these numbers for contracting or decision making. They main starting hypothesis of economic consequences theories are that if contracting and monitoring is costly, the choice of accounting measurement rules affects firm value and the wealth of parties. Following Holthausen and Leftwich, studies trying to provide empirical evidence on the economic consequences of accounting alternatives can be divided into three categories: a) the choice of accounting techniques, b) the voting and lobbying positions on proposed accounting standards and c) the impact of accounting choices on stock prices The studies of both the choice of accounting techniques and the lobbying have provided the more robust results at the time of measuring the relationship between firm specific characteristics and the reaction to new accounting standards while studies on stock prices have not proved to be so useful so far. As a general statement and derived from previous research in lease accounting

10 , we can observe how on average, lessees
, we can observe how on average, lessees seem to prefer operating lease accounting instead of capital lease accounting and much of the empirical research investigates the implications of unrecorded lease commitments (Lipe, 2001) Staring from this literature review in our study we will try to determine if the effect of the implementation of this new standard would be statistically significant for the particular case of Spain. If the effect is relevant and financial analysis is affected substantially, some economic consequences may be derived from its implementation. We believe that Spanish companies have been counting traditionally on operating leases at the time or performing their business and, from an initial analysis of some of the companies considered in our data set, we have readily observed how the amounts disclosed in the notes to the accounts as corresponding to future leases payments seem to be relevant in respect to accounting variables such as total assets or net income. Therefore, our first hypothesis is: 9 H1: the effect of the implementation of the new standard on operating leases in the Spanish companies, both for static analysis (mainly leverage) and for the dynamic one (returns) will be statistically significant We also believe that the impact is going to be different depending on the sector. We expect that sectors where lease contracts could be longer (non current assets contracts such as property, plant and equipment) should be most affected by the change in the lease standard. The longest the contracts are, the strongest the effect. This would justify why companies such as Inditex (Zara) would be so proactive in the lobby for the cancellation of the standard. Most shops in the retail business are rented and recognizing those amounts as liability is meant to introduce relevant changes in the financial statements. Additionally, prior studies reveal material consequences for leas

11 e-intensive industries such as transport
e-intensive industries such as transport, retail and hospitality (Goodacre, 2003, Gosman and Hanson, 2000 and Lanfranconi and Wiedman 2000). Our second hypothesis therefore will be: H2: the sector is an influencing factor in the impact assessment of the capitalization of operating leases. 4. Data Selection and Research Design 4.1. Data Selection We selected all quoted Spanish firms (consolidated financial statements) in 2009 except for the financial firms that were excluded due to their different regulation. In Spain, only quoted companies can apply IFRS and maybe affected for the new leases regulation. Non quoted companies have to follow Spanish GAAP adapted to IFRS in 2008. The reason why we chose 2009 is that it was the last one available at the moment of the data collection and we wanted to work with the latest possible financial information as the standard is due, the earliest, for June 2011 We worked with an initial population of 112 companies. For each of them, we manually analyzed the notes to the accounts in order to extract information about future minimum lease payments. Only 56 companies disclosed the minimum information required for our analysis so we had to discard the other 56 companies. 10 The operating lease information disclosed by Spanish companies in a note to the financial statements is a schedule of operating lease payments, disclosing separately three different figures: the next year’s payments, the one year up to five payments, and the five more year’s payments As well as the minimum total future operating lease payments, for each company we also extract financial data , both assets and liabilities, some income measures, and other information as the company-specific weighted interest rate for the recognized debt , and the effective tax rate. Other information that would make the capitalization procedure more accurate , as the asset categories rented, the

12 asset life and the lease period, or the
asset life and the lease period, or the weighted average implicit interest rate for each firm’s portfolio of operating leases, between others, were not disclosed by most of the companies selected. Hence the limitation of the availability of public domain date makes necessary to introduce some assumptions. These assumptions are clearly described in the next section as they determine the final output of the capitalization procedure 4.2. Research Design Our procedure is based on the constructive capitalization model of Imhoff et al. (1991;1997) which simulates the effects of operating lease capitalization on assets, liabilities, equity, and the related income statement positions. Prior literature has taken into consideration the constructive capitalization model (Fulbier et al, 2008, Beattie, 1998) due to the fact that it a more developed methodology that the alternative one which would be the factor method. The main difference between them is that the former considers the potential effect in equity and net income while the latter ignores it. The factor method is especially relevant for practitioners due to its simplicity and easy application. The constructive capitalization model is based on some general assumptions such as : (i) at the inception of the lease, the book value of the leased asset is equal to the value of the lease liability, (ii) the capitalized asset and the capitalized liability both equal zero at the end of the lease, (iii) straight-line depreciation is used for all assets, , (iv) lease payments are constant over the lease terms. Under these considerations, we introduce further assumptions in order to calculate the unrecorded lease liabilities, unrecorded lease assets and the variation of the equity position: 11 Assumptions and measurement of the unrecorded lease liabilities: The present value of unrecorded liability (PVL) is calculated as the present value (PV) of the

13 future minimum lease payments (FLP) us
future minimum lease payments (FLP) using the effective-interest method. To obtain the PVL two fundamental assumptions are required: · The interest rate Although the appropriate interest rate could be the weighted average implicit rate for each firm’s portfolio of operating leases, or the implicit rate in the firms’ capital leases (Imhoff et al. 1997), this data is not disclosed by many of the companies analyzThis happens frequently also in other countries’ annual accounts and, in its absence, prior literature generally chooses a fixed discount rate for the complete sample. That is the case of Imhoff et al. (1991) who worked with an interest rate of 10% for all companies, the same as Ely (1995) or Beattie et al. (1998). We believe that working with a constant interest rate for all companies may be too general so we decided to estimate the missing data by means of the weighted interest rate for long-term debt. Information about these interest rates is disclosed by 33 of the 56 companies selected. For the rest of them (23 companies) we use the mean of the rates disclosed weighted by the future lease debt of the companies. We perform additional test with different scenarios (the same weighted interest rate plus one and plus two points) in order to give robustness to our results. · The determination of annual cash flows expired in more than five years As most of the companies do not disclose information about the per-year payments, a pattern assumption in this sense is required. The assumptions are the following: a) For years two to five we assume a geometric decreasing model in which the lease payments decline at a constant rate (Fülbier et al., 2008). In order to annualize the payments aggregated to year two to five, we determine for each company a constant decreasing factor (df) for the five periods: (1) FLPt+1 = FLPt x df Therefore, the unknown FLP2, FLP3, FLP4 and FLP5

14 are a function of the known FLP1 12
are a function of the known FLP1 12 So we can assume that: (2) FLP2 to 5 = FLP1 x df1 + FLP1 x df2 + FLP1 x df3 + FLP1 x df4 And therefore, (3) å1152tFLP b) Once we calculate the peryear payment for two to five year, we assume, as the original model, that the aggregated payment of more than five years is divided in equal annual payments of FLP5 . Unlike most of prior research where a single lease contract is considered, we divide the FLP into five sort of categories, each one with a different remaining lifetime (one year up to five or more years) . We consider that difference between the FLP in two consecutive years is the FLP of those contracts ending in the first of the two expiry date (Fülbier et al. 2008). This conjecture, according to the assumption that lease payments are constant over the lease terms, considers that among the firm’s portfolio of operating leases, contracts expire in different moments. To our understanding, this methodology represents much more faithfully the variety of contracts that can be found in different companies. 4.2.2 .Assumptions and measurement of the unrecorded lease assets: Considering that the present value of the unrecorded asset (PVA) is, at the lease inception, the present value (PV) of the future lease payments (FLP), the relationship between asset value and lease liability at any time during the contract period is a function of PVFLP, the remaining lease life (RL), the total lease life (TL). As the current lease liability is equal to the PV over the remaining life, the ratio of asset to liability can be expressed as: (4) FLPPV Therefore to obtain the PVA a key assumption is also required 13 The total lease life To calculate de PV we calculate the total annual payments corresponding to the remaining life. The assumption about the total life and the proportion between remaining life and total life has an important i

15 mpact on results because depending on wh
mpact on results because depending on which stage is the lease considered the consequences of the capitalization on the current period’s net income would be different. Figure 1 : Total expenses from operating vs capital leases. Based on Figure 2 Imhoff et al (1991) As is shown in figure 1 in the early stages of the lease’s life, the expenses under capitalization (depreciation + interest) are bigger than under non capitalization (lease rental). This difference progressively decreases, and then reverses. Imhoff et al. (1991) assumed that for a company with a stable portfolio of leases, the breakeven point where the periodic capital leases expenses equal the periodic operating lease expenses is 50%. In accordance with this assumption and with other prior studies (Ely 1995, Bennet and Bradbury 2003, Fülbier et al. 2008) we consider that the ratio of RL/TL is 50% and that the lease term matches up with the asset’s estimated life. This assumption entails that the effect on the current period’s income of the constructive capitalization is minimal. Breakeven point expense Interest Lease rental expense Depreciaction + Interest time Lease expiry/end asset’s useful life 14 In order to prove the consistency of this assumption we calculate the impact on results as the difference between the minimum future lease rental of the next year less the straight-line annual depreciation and the next year’s interest expense. The weighted average impact is about the 0,13% over the capitalized assets or the 10.51% over the equity adjustment. 4.2.3 Assumptions and measurement of the equity and deferred taxes adjustments: The difference between the lease asset and liability during the lease contract implies an adjustment of the equity position downwards, due to the accumulated effect of the income reductions in the early years of leases. This reduction in past incomes al

16 so implies an adjustment of deferred tax
so implies an adjustment of deferred taxes. To calculate the adjustment on the net equity position a last assumption is required: · The tax rate To calculate the tax consequences of capitalization we use an average effective tax rate for 2009 by dividing the taxation by the earnings before taxes. Prior studies (Fülbier et al, 2008, Beattie, Eduards and Goodacre, 1998) have also calculated the tax effect using an average effective tax rate, preferring company-specific averages over standardized tax multifactor for the complete sample. Some of these studies have recalculated the results using a general tax multifactor of 40%, the tax used by Inhoff, Lipe and Wright, without identifying significant changes. 15 Figure 2: Illustration of the capitalization method run for INDITEX Company dfst raTax rate23456789Annual payment758.563,00540.842,02385.610,80195.412,49195.412,49195.412,49195.412,49112.204,03(years)(€)(€)diference between 1 and 22,001,00155.231,21diference between 2 and 34,002,00110.677,11110.677,11diference between 3 and 46,003,0079.521,2079.521,2079.521,20diference between 4 and 58,004,00195.412,49195.412,49195.412,49195.412,49195.412,49195.412,49195.412,49195.412,49112.204,0319,151.571.444,26540.842,02385.610,80274.933,69195.412,49195.412,49195.412,49195.412,49195.412,49112.204,032.680.181,312.445.491,30(€)-177.108,15 increase-2.313,38 -752,13 DEF TA-57.581,86 -6.393,69 -2.078,73 decrease-9.941,48 -3.232,20 LIABILITY-12.310,17 -4.002,32 in-146.149,43 -47.516,48 2.445.491,302.445.491,30-177.108,15 -57.581,86 Amounts payable in years REMAINING LIFE RATIO ASSET TO LIABILITYLEASE ASSETTOTAL LIVEEQUITY ADJUSTMENTDEFERRED TAXESLEASE LIABILITY 16 Figure 2 provides an illustration of the capitalization method applied for INDITEX considering its disclosure in respect operating lease contracts. We obtain the unrecorded lease liability, lease liability and the equity adjustm

17 ent running the model described before s
ent running the model described before separately on each basket and aggregating the results. 4.3. Factor model In order to include other capitalization procedures we apply the factor method to the same sample. This method is also based on a capitalization procedure of the minimum lease payments but it considers that the lease asset equals the lease liability, and therefore there is no impact in equity, deferred taxes or net income. Considering that prior evidence finds that measures of shareholder risk can be better explained when one includes the financial leverage implicit in unrecorded leases (Lipe 2001) this method could be a simpler approximation of how capital market participants incorporate the unrecorded operating leases. In our study, once we have calculated the present value of the unrecorded lease liability as described before, we make the unrecorded lease asset equal. Hence no assumptions about the total lease life or the tax rate needs to be done. Results will show how there are not significant differences between both models although the constructive methodology is more complete. The reason is that, under the assumptions already explained for the constructive method, the impact in net income is rather small and that makes that both methods lead to similar conclusions. 4.4. Accounting ratios analyzed To analyze the impact of the lease capitalization on the financial statements and to facilitate comparison with previous studies we calculate nine financial ratios. Based on prior literature we consider four types of ratios: leverage, structure and performance, although we add also the Altman Z score as we consider that the effect of the new standard would be also very relevant if the prediction of failure would be significantly affected. The first four ratios are therefore linked to leverage in order to measure the changes on the companies’ financial leverage position due to the in

18 crease of the lease liability. These are
crease of the lease liability. These are the equity to assets (LEV1), equity to liabilities (LEV2), current liabilities to non-current liabilities (LEVQ) and financial leverage (FINLEV). 17 Ratios related to structural changes in the balance sheet are the liquidity ratio (LIQ) which compares current assets with current liabilities, and the noncurrent assets turnover (NCAT) which divides the non-current assets by the total sales of each company. Although we consider minimal effects of the constructively capitalizing method on the income statement, the impact on the balance sheet could alter the commonly used profitability ratios. We calculate both return on assets (ROA) and return on equity (ROE) as these measures have an important influence on financial analysis. Any alteration in these ratios could affect the diagnosis of a firm performance evolution. Considering the modifications on the balance sheet, the capitalization of operating leases will systematically result in a bigger denominator (total assets) in the case of ROA, and a smaller denominator (shareholders’ equity) in the case of ROE. The impact in the numerator is unclear so in the situation we consider (the ratio of RL to TL is 50%), capitalization has no expected changes in the current net income. Finally we include the Altman ZScore ratio (ALTZ) to explore if the constructively capitalizing methodology improves their bankruptcy prediction model. The inclusion of this ratio, which has not been analyzed in prior literature, is justified by the importance of failure prediction in the present economic environment for the particular case of Spain. Since 2008 the number of companies which have been declared bankruptcy has increased constantly and if this ratio happens to be affected by the proposed change in the standard we should be on guard about it. In table 1 we display the accounting ratio definitions used in the study Table

19 1: Accounting Ratio Definitions Ratio V
1: Accounting Ratio Definitions Ratio Variable Numerator Denominator Leverage 1 LEV1 Total Liabilities Total equity + total liabilities Leverage 2 LEV2 Total Equity Total Liabilities Debt’ s Quality LEVQ Current Liabilities Non current liabilities Financial leverage FINLE Total Assets x EBT Total Equity x EBIT Liquidity LIQ Current Assets Current Liabilities 18 current assets turnover NCAT Noncurrent Assets Total Sales Return on Assets ROA EBIT Total Assets Return on Equity ROE Net Income Total Equity Altman Z ALTZ 1,2(Working Capital/Total Assets) +1,4(Retained earnings/Total Assets)+3,3(EBIT/Total Assets)+0,6(Equity/Total Liabilities)+1(Sales/Total assets) Considering the variations occurred both in assets and liabilities we expect that all ratios would be perceptibly affected by the capitalization method. 5. Statistical Model, Descriptives and Main Results 5.1. Statistical Model Once selected the companies and calculated the ratios before and after the implementation of the proposed standard (predicted calculations) by means of the constructive lease capitalization model, we run the statistical methodology which allows us to determine if this effect, for the particular case of Spanish companies, will be statistically significant. Prior literature on the leases impact like Fülbier, et. al..(2008) following Goodacre (2003) and Lückerath-Rovers and de Bos (2005) indicate that financial ratios do not follow a normal distribution and therefore they use non parametric tests to look for significant statistical differences between the ratios before and after the capitalization. To avoid this problem and working with non parametric tests, we propose the calculation of a comparability index (CI) calculated as the percentage of variation of the ratios before and after. This new variable does follow a normal distribution which allows us to run parametric tests to contrast differenc

20 es in the means This comparability inde
es in the means This comparability index (CI) has been calculated in the following way: 19 úûùêëé=iiiFRbFRa where FRa = Financial Ratio after the capitalization for company i FRb = Financial ratio before the capitalization for company i CI = Comparability Index for company i In addition to the parametric ttest, we have analyzed the impact of two different factors: sector and size. To analyse the impact of the sector, we have divided our set of data in six different sectors following the classification provided by the Madrid Stock Market. The sectors are Energy (Sector 1), Construction and Industry (Sector 2), Retail goods (Sector 3), Retail services (Sector 4) , Financial services (Sector 5) and Technology (Sector 6) For each sector we have run the parametric ttest considering each of the comparability indexes calculated for all ratios. To analyze the impact of size in the change of the ratios between before and after capitalization, we have considered the mean of the total assets. We have created then two different groups of companies and have created a new dummy variable which takes value 1 if total assets is more than 10.000.000€ y takes value 0 otherwise. The influence of size is analyzed for each comparability index by means of contrasting the null hypothesis of constant behavior between different groups running an univariate analysis (ANOVA) in a fixed effects model with a single factor. 5.2. Descriptive Statistics Table 2 shows the descriptive statistics for the variables used in the empirical analysis. In Panel A we include the descriptives for the financial ratios before the capitalization and in Panel B the descriptives for the financial ratios after. In Panel C, we can see the descriptives for the comparability index based in each ratio. 20 Table 2: Sample descriptive statistics Financial Ratios Panel A: Financial Ratios before capitalization (N=56) Me

21 an SD Min Max LEV1b 0,663820 0,194070 0
an SD Min Max LEV1b 0,663820 0,194070 0,2802356 1,126303 LEV2b 0,664126 0,598266 - 2,568427 LEVQb 2,269091 4,091392 0,1749009 28,36426 LIQb 1,369931 0,872590 0,2277514 5,310642 NCATb 1,389343 1,433975 0,0438738 9,807088 ROAb 0,018589 0,108021 - - ROEb - 2,180641 -13,9227 1,119546 FINLEVb 137,8583 1039,457 -513,2215 7758,364 ALTZb 1,532709 1,137901 -1,268462 4,19331 Panel B: Financial Ratios after capitalization (N=56) Mean SD Min Max LEV1a 0,7133834 0,1931514 ,02950753 1,098081 LEV2a 0,5250308 0,4983698 -0,0893203 2,388963 LEVQa 1,874651 3,315319 0,1644568 21,3955 LIQa 1,219958 0,8642309 0,0187928 5,234546 NCATa 1,389343 1,433975 0,0438738 9,807088 ROAa 0,0229306 0,0897571 -0,219458 0,309884 ROEa - ,2213539 1,293032 -8,310007 0,885826 FINLEVa 216,8554 1633,342 -552,7676 12206,91 ALTZa 1,296471 1,024431 -0,8225932 3,469548 21 Panel C: Financial Ratios’ Comparability Index (N=56) Mean SD Min Max LEV1CI 0,0995172 0,2326415 -0,030162 1,130035 LEV2CI - 0,5153843 -3,500051 - LEVQCI - 0,2423282 - 0,0698833 LIQCI - 0,2201342 - - NCATCI 4,504515 24,84191 0,0007645 182,0341 ROACI - 0,2388975 -0,991638 - ROECI 0,015469 0,2939141 -1,366801 0,8648396 FINLEVCI 0,1073825 2,229353 -12,85529 9,122283 ALTZCI - 0,2653823 -1,172007 - The descriptive analysis of the figures obtained after the implementation of the constructive lease capitalization methodology show us the following:: 1. We can see how, in general, the values obtained for the ratios of leverage (LEV1), non current assets turnover (NCAT), return on assets (ROA) and financial leverage (FINLEV) are higher after the operating leases capitalization. Leverage (LEV1) has

22 increased 9,95%, on average and financia
increased 9,95%, on average and financial leverage 10,73%. On the contrary, the quality of debt (LEVQ), liquidity (LIQ), and Altman Z score present lower values after capitalization. The second leverage ratio (LEV) has decreased 21,91% on average due to the impact on equity. Debt quality has also decreased 14,82%, on average due to the impact on non current liabilities. Due to the changes in equity and liabilities, the Z Altman score has decreased 14,64% on average. As expected then, we have found relevant growth for the leverage ratios and the gearing effect is one of the biggest worries of Spanish companies about the leases draft. 2. The comparability indexes that are not too much comparable due to their dispersion (higher standard deviation) are the non current assets turnover and financial leverage. The non current assets turnover has a 24% dispersion 22 Impact assessment of the operating leases’ capitalization In Table 3 we present the effect that would have the new operating leases proposal should it be implemented. We can see how the mean for the non current assets is of 32.764,69. The company with a smaller effect has an impact of 62,48 while the company with the maximum has an effect of 9.694.774,4 so we can see that there is a big dispersion. For non current and current liabilities the mean is 22.096,09 and 8.541,00 respectively which together (30.637,09) results in a higher amount that the impact on assets as expected. Considering the fact that the constructive method calculates the assets always as a proportion of liabilities which are the present value of future operating leases payments, the impact on assets should be always lower that the impact on liabilities. Additionally, there is a negative impact in equity due to the accumulated effect derived from the difference between considering operating leases as an expense or considering as an expense the total sum of intere

23 sts and amortization. Table 3: Impa
sts and amortization. Table 3: Impact of Operating Lease Capitalization on Financial Statement Positions (in Euros) Non Current Assets Non Current Liabilities Current Liabilities Equity Minium 62,84 -94,58 20,00 - Maximun 9.185.201,2 1.471.284,00 -2,99 Mean 32.764,69 22.096,09 8.541,00 -2.201,27 Std Dev 1.541.199,1 1.420.333,1 277.352,04 149.560,3 5.4. Main Results In Table 4 we can find the results after running the ttest. In Panel A we have the results for the complete set of data and in Panel B we present the results classified by sectors. For the whole population, we can observe that six of the nine ratios have significant differences at 1% level. Results show how there are highly significant differences in the 23 leverage (LEV1, LEV2), debt quality (LEVQ), liquidity (LIQ), return on assets (ROA), and the zAltham (ALTZ). For non current assets turnover (NCATC), return on equity (ROE) and financial leverage (FINLEV) we find no statistical significant differences. The ratios of debt quality and Z Altman are the most affected by the capitalization simulation although leverage shows also to have a great impact. Therefore, we can accept our first hypothesis as there are statistically significant differences in the ratios of Spanish companies due to the operating leases’ capitalization. Our results support prior evidence in Europe. Both Fülbier et al. (2008) and Beattie et al (1998) conduct similar analysis for Germany and the UK and they also find significant effects for the financial ratios they analyze, especially for the assets/liabilities relation. Table 4: results t de student Panel A: All the sample T student P value LEV1CI 3,2011 (0,0023)*** LEV2CI - (0,0024)*** LEVQCI - (0,0000)*** LIQCI - (0,0006)*** NCATCI 1,3569 (0,1803) ROACI - (0,0004)*** ROECI 0,3939 (0,6952) FINLEVCI 0,3605 (0,7199) ALTZCI - (0,0001)*** ***Significant at the 0.0

24 1 level (two-tailed): 24 Table 4:
1 level (two-tailed): 24 Table 4: results t de student continued Panel B: Sector SECTOR1 (n=8) SECTOR2 SECTOR3 SECTOR 4 SECTOR 5 SECTOR 6 LEV1IC 2,1964 (0,0641)* 1,2415 (0,2381) 1,9944 (0,0607)* 2,1761 (0,06 - (0,5165) 1,9507 (0,1904) LEV2IC - (0,0170)** - (0,1604) - (0,0925)* - (0,0125)*** - (0,1833) - (0,1248) LEVQIC - (0,1597) - (0,1383) - (0,0202)** - (0,0109)*** - (0,3482) - (0,3116) LIQIC - (0,049)** - (0,1398) - (0,0362)** - (0,0595)** - (0,3816) - (0,0719)* NCATIC 3,0085 (0,0197)** 1,1907 (0,2568) 1,1043 (0,2833) 1,1067 (0,3006) 1,0567 (0,4014) 2,8228 (0 ROAIC - (0,0094 (0,2195) - (0,0422)* - (0,0371)** - (0,3945) - (0,1280) ROEIC 5,3662 (0,0010)*** (0,2587) 0,1103 (0,9134) - (0,6949) 0,4447 (0,7000) 1,3592 (0,3070) FINLEVIC (0,0054)*** (0,3005) 1,0133 (0, - (0,5043) 1,9317 (0,1931) 2,3115 (0,1470) ALTZIC - (0,0091)*** (0,1913) - (0,0247)* - (0,0226)** - (0,1934) - (0,1992) ***Significant at the 0.01 level (two-tailed): **Significant at the 0.05 level (two-tailed); Significant at the 0.10 level (two- When we analyze Panel B we can see how the results change depending on the sector. We have divided all companies analyzed in 6 sectors. The results obtained have to be considered cautiously as the number of companies included in each sector is fairly different. For sector 3 (Retail goods) we have considered 20 companies while for sector 5 (Financial Services) and sector 6 (Technology) we have only 3 companies. Sectors which seem to be most affected by the introduction in the financial statements of the operating leases are energy (Sector 1), Retail goods (Sector 3) and Retail Services (Sector 4). We expected those results for the retail sectors as we can be referring to hotels, restaurants or stores where generally the use of operating leases is quite intensive and we also corroborate prior studies such as Singh, A (2010) who analyzes the impact of operating l

25 eases capitalization for financial ratio
eases capitalization for financial ratios in restaurants and retail firms. 25 Sector 3 includes companies such as Inditex, S.A. and included in sector 4 we have Hotels such as SOL MELIA, S.A. NH Hotles, S.A, and other companies such as the Spanish airline VUELING, S.A which are most affected by the proposed change. When we compare the results obtained by sector we can see how the ratios most affected are the same ones that we already detected in the analysis of the whole data set which gives consistency to our results. The ratios on leverage, debt quality, liquidity and Z Altman score are again significantly affected. We have found no significant effects for Construction (Sector 2), Financial Services (Sector 5) or Technology (Sector 6). We can accept therefore our second hypothesis. We have analyzed also the effect of size in the capitalization of operating leases. In Table 5 we present the results corresponding to the ANOVA test. We can see how the size of the company is a significant variable. We have found statistical significant differences between size and almost all of the ratios analyzed except for non current assets turnover, return on equity and financial leverage. Table 5 Resultats test ANOVA : Factor Size F �ProbF LEV1IC 2,68 0,1076** LEV2IC 3,10 0,0840** LEVQIC 3,18 0,0803** LIQIC 4,30 0,0430*** NCATIC 1,07 0,3054 ROAIC 4,87 0,0 ROEIC 0,01 0,9355 FINLEVIC 0,02 0,8792 ALTZIC 5,09 0,0282*** SIZE= dummy variable equal to 1, if size is higher that 10.000.000€, 0 otherwise ***Significant at the 0.01 level (two-tailed): **Significant at the 0.05 level (two-tailed); * Significant at the 0.10 level (two- 5.5. Sensitivity Analysis We conduct sensitivity analysis to test the robustness of our results. We have considered different scenarios for the assumptions considered and in line with Imfhoff et al. (1991) and Fulbier et al. (2008) we find only slights alteration

26 s. In Table 6, we have included five 2
s. In Table 6, we have included five 26 columns. In the first one (Factor-met) , we present the results corresponding to the factor method instead of the constructive one. The former does not consider the effect in equity and only adjusts both assets and liabilities in the same terms. We can see how the results are quite similar to those derived from the constructive capitalization method. In the second column (Scenario_50_i1) and third (Scenario_50_i2) we have run again the tests under the constructive methodology but considering the interest rate plus 1 and two respectively. In the fourth columns (Scenario_60) and fifth one (Scenario_70) we have considered that the ratio Residual Life/Total Life represents a 60% and 70% respectively. We can see how the results do not change substantially and therefore our results show to be robust. Table 5: Sensitivity analysis for Factor Method, Interest rate considered plus 1 pint, Interest considered plus 2 points, Ratio between Residual Life and Total Life at 60% and Ratio between Residual Life and Total Life at 70% Factor_met ario _50_i2 Scenario _60 Scenario _70 LEV1CI 3,0762 (0,0033)*** 3,1853 (0,0024)*** 3,1701 (0,0025)*** 3,1650 (0,0025)*** 3,1360 (0,0027)*** LEV2CI - (0,0001)*** - (0,0028)*** - (0,0031)*** - (0,0009)*** - (0,0003)*** LEVQ - (0,0000)*** - (0,0000)*** - (0,0000)*** - (0,0000)*** - (0,0000)*** LIQCI - (0,0006)*** - (0,0006)*** - (0,0006)*** - (0,0006)*** - (0,0006) NCATCI 1,3422 (0,1851) 1,3621 (0,1787) 1,36 (0,1771) 1,3521 (0,1819) 1,3485 (0,1830) ROACI - (0,0006)*** - (0,0005)*** - (0,0005)*** - (0,0004)*** - (0,0003)*** ROECI 0,2888 (0,7739) 0,1927 (0,8479) - (0,7162) - (0,3860) FINLEVCI 1,3093 (0,1959) 0,2 (0,7707) 0,2289 (0,8198) - (0,7559) - (0,4575) ALTZCI - (0,0001)*** - (0,0001)*** - (0,0001)*** - (0,0001)*** - (0,0001) ***Significant at the 0.01 level (two-tailed): **Significant at the 0.05 level (twota

27 iled); * Significant at the 0.10 level (
iled); * Significant at the 0.10 level (two- 27 The International Accounting Standards Board has issued a new drat on Leases which introduces significant changes in the way operating leases should be recognized and measured in the financial statements. Up to this moment operating leases have been recorded as an expense and no recognition as an asset or liability has been required. However the IASB’s Exposure Draft (ED/2010) proposes considering operating leases on the same level as capital leases. The recognition of operating leases in the statement of financial position is expected to have an impact both in the structure of the company (assets and liabilities) and in its performance. Depending on the methodology considered to assess the impact of the new standard (constructive capitalization method or factor method) the effects may be different. If the simulation is calculated using the former, total assets and liabilities would be affected (liabilities more than the assets) but also equity would be modified as the effect and results and therefore in equity is considered. If the simulation is calculated with the factor method, there is no impact on equity. In this paper we have simulated the effect that would be derived from the inclusion of operationg leases in the financial statements of Spanish Companies. We have chosen Spain as our particular scenario due to the fact that there has been a very strong lobbying from very relevant Spanish companies trying that the IASB softens or even cancels the proposal. To our best knowledge, no prior studies have been conducted on Spanish companies and we believe it to be a timely study considering the special moment Spain is going through at the moment. . We have run the constructive capitalization method to recognize the operating leases in 56 listed Spanish companies using consolidated data in 2009. Due to the lack of quality disclosed data of t

28 hese companies we have incorporated seve
hese companies we have incorporated several assumptions about the interest rates, the total lease life or the tax rate. Findings are shown to be robust with respect to those assumptions We have chosen the constructive capitalization method as the basis for our analysis but we have also run the tests with the factor method because the IASB seems also to be taking into consideration the option of softening the standard (due to the many pressures received from European companies) and allow for an implementation with no effect in results nor equity (and therefore closer to the factor method). 28 The results found show how the impact on financial ratios of the capitalization of operating leases is statistically significant. The ratios on leverage, debt quality and return are affected by the inclusion of operating leases in the financial statements. This means that the analysis of those companies would be modified should the standard be implemented. We have found also statistical significant for the Z Altman score ratio which we find particularly relevant considering the special economic situation that Spin is going through since 2008. When we run the tests by sector, we can see how the effect differs significantly and therefore sectors of energy, retail goods and retail services are the ones most affected. The ratios that have shown to be most affected when considering the whole data set are again the most affected in the sector analysis. Those results were expected and confirm our hypothesis that the effect of the implementation of the new standard on leases would be relevant. This study is an ex ante research and can not go beyond the effect analysis of this new standard. We believe that it is highly probable that, should the standard be implemented, some economic consequences may be derived. Prior literature has shown how companies modify their financial structures in order to minimize the effects o

29 f new regulations. So we can expect that
f new regulations. So we can expect that Spanish companies will react to the new regulation if they find it to be harmful to their reputation, analysis or performance. 29 Barnes, P., (1987) The analysis and use of financial ratios: A review article, Journal of Business, Finance and Accounting 14, 449- Beattie, V., Edwards, K. and Goodacre, A., (1998) The impact of constructive operating lease capitalization on key accounting ratios, Accounting and Business Research 28, 233- Beatty, A, Liao, S, Weber, J. (2010). “Financial Reporting Quality, Private information, Monitoring and the Lease versus Buy Decision”. The Accounting Review, Vol 85, num 4, pp 1215 Bennet, B, and Bradbury, M., (2003) Capitalizing noncancelable operating leases, Journal of International Financial Management and Accounting 14, 101- Ely, K. (1995) Operating lease accounting and the market’s assessment of equity risk, Journal of Accounting Research 33, 397- Fülbier, R, Lirio, J. Pferdehirt, M. (2008). Impact of lease capitalization on Financial ratios of Listed German Companies. Schmalenbach Business Review, 60, 122- Goodacre, A., (2003), Operating lease finance in the UK retail sector, International Review of Retail, Distribution and Consumer Research, 20, 49- Gosman, M.L, Hanson, E. (2000) The impact of leasing on lenders’ evaluations of firms’ debt levels. Commercial Lending Review, 15, 53- Holthausen, R.W.; Leftwich, R.W. (1983). The economic consequences of accounting choice. Implications of costly contracting and monitoring. Journal of Accounting and Economics 5, 77- Imhoff, E. A. Jr.; Thomas, J.(1988). Economic consequences of accounting standards: the lease disclosure rule change. Journal of Accounting and Economics, 10, 277- Imhoff, E, Lipe, R. and Wright, D., (1991) Operating leases: impact of constructive capitalization. Accounting Horizons 5, 51- Imhoff, E. A. Lipe, R and Wright, D.W. (1993). T

30 he effects of recognition versus disclos
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