Proposed Lease Accounting Changes

Abstract

Regulators have proposed changes to the existing lease accounting rules that will require the capitalization of all operating leases as assets and liabilities. This study investigated the impact of operating lease capitalization on the financial statements and 11 financial ratios in restaurant and retail firms from 2006 to 2008. Significant absolute and relative differences were found across and within the two industries. All 11 financial ratios related to interest coverage, leverage, and profitability will change significantly and dramatically for both industry sectors. The findings indicate that retail firms will be affected to a greater extent than restaurant firms. Within the restaurant industry, small restaurant firms will face significantly higher debt-related ratios than medium or large restaurant firms. Reconciling previous research, this study found firm size to be an important factor in explaining operating lease usage with small firms likely to use more operating leases than large firms. Restaurant and retail firms should evaluate the impact of the proposed standard on debt agreements and executive compensation contracts and plan for operating under the new rules.

Keywords

lease accounting operating leases financial ratios restaurant retail lease capitalization

Introduction

On March 19, 2009, the Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) jointly issued a discussion paper proposing changes to the existing lease accounting rules that would eliminate the current off–balance sheet treatment of operating leases (FASB, 2009). The proposed rules will eliminate the current classification of leases as either finance or operating leases and instead require a single model in which lessees will capitalize all leases as assets and liabilities on the balance sheet at the discounted present value (PV) of the expected lease payments. The leased asset will be depreciated over the shorter term of the lease or the economic life of the asset, whereas the lease payment would be allocated between a reduction in the outstanding principal lease liability and interest expense instead of expensing the entire lease payment.

This article is motivated by the impending changes in lease accounting that will require the capitalization of all operating leases. An exposure draft of the new rules is expected to be issued in 2010 with final implementation in 2012. The proposed changes have raised concerns among companies worried about the potential negative impact on financial statement presentation and certain financial ratios that are widely used in debt agreements and executive compensation plans. Companies are concerned that the proposed changes will dramatically change the amount of debt and assets that is capitalized on the balance sheet and the location and amount of expenses recognized on the income statement. Moreover, the capitalization of operating leases is expected to significantly affect various debt-related ratios such as leverage, times interest earned, and debt-to-equity ratios, among other ratios, that are widely used to evaluate a company’s financial performance and compliance with debt covenants. Management compensation contracts will also be affected if some of these profitability ratios, such as pretax income, are used in designing executive compensation plans. To mitigate the negative impact of the proposed rules, hospitality managers must assess and plan for their implementation because a failure to do so could impose additional financing and executive compensation costs and potentially restrict firm investment and financial policies.

The purpose of this study is to investigate the potential impact of the proposed lease accounting changes on financial statements and the likely changes in the magnitude of various financial ratios in a sample of 234 restaurant and retail firms from 2006 to 2008. Changes in lease accounting rules will likely have a material and significant effect on various corporate risk, credit rating, debt financing, and cash flow decisions of firms that heavily depend on operating leases for growth and expansion. The effects of these changes are best observed through changes in various key balance sheet and income statement ratios before and after operating lease capitalization. Using firm lease disclosure data from annual 10-K reports, this study employs the discounted cash flow (DCF) technique and constructive lease capitalization methodology of Imhoff, Lipe, and Wright (1991, 1997) to convert operating leases to capital leases and estimate the discounted PV of operating leases. Following capitalization, the amounts of assets and liabilities on the balance sheet and various expense accounts on the income statement are adjusted to assess the extent of changes in these amounts. A set of 11 ratios, including interest coverage, debt, and profitability ratios, which are widely used in practice, are then computed and their differences evaluated to determine the magnitude of the changes (absolute and relative) in the financial ratios before and after capitalization. Additionally, the relation between operating leases, firm size, and financial distress is also tested to reconcile and extend prior mixed findings in this area of research. Sensitivity analysis and alternative specifications of the models also provide additional support for the conclusions and robustness of the results. Finally, the potential implications of the findings on corporate policies such as debt agreements and executive compensation are presented and discussed.

The restaurant and retail sectors were chosen for this study to evaluate the impact because of the magnitude and pervasive use of operating leases as a primary source of financing in these two sectors (Imhoff et al., 1997). Unlike other specialized industries such as manufacturing, restaurant and retail firms share similar characteristics in the standardization of their location (stand-alone or located in malls, shopping centers, malls, etc.), which makes it more conducive and attractive for lessors to lease space for retail use (Goodacre, 2003). Furthermore, many restaurant and retail companies are relatively small businesses without access to capital markets or bank financing and so have to rely heavily on operating leases for their growth and expansion.

This study will contribute to the existing literature on leasing in the following ways. First, this study will show how the presentation of financial statements will change dramatically and how the proposed rules will affect the magnitude of various financial ratios that are widely used to assess credit ratings, debt covenants, and executive compensation. Second, this study extends previous hospitality research in leasing by reconciling some mixed findings to provide more conclusive evidence on the relation between operating leases, firm size, and financial distress. Previous research has also been hampered by data availability and limited to small sample sizes. Upneja and Schmidgall (2001) noted the limited number of hospitality-related studies on leasing and the lack of hospitality-specific data on the magnitude of leasing activity and have called for more research in this area. Third, a focus on one or two industry sectors has the advantage of not only increasing the ability to detect an empirical relation but also enabling researchers to perform more intraindustry tests of differences. Comparisons of results from this study and previous research can also provide relevant information on key differences between various industry sectors as well as the magnitude of changes over time. Fourth, incremental new descriptive information is provided on rental expense and site-operating characteristics for both restaurant and retail firms. Finally, this timely and policy-relevant ex ante research as advocated by Schipper (1994), when combined with ex post research, will make a new and significant contribution to the existing literature on leasing as well as the impact of accounting standards on financial statements. Financial statement users, investors, creditors, regulators, and academics will find the information useful and relevant in assessing and evaluating the potential changes and corporate actions of restaurant and retail firms.

Literature Review

The empirical research on lease accounting for U.S. and international firms has generally focused on the impact of capitalizing leases on financial statements and capital structure. Existing industry-specific hospitality-related studies are rather limited in this area with few studies exploring questions on leasing.

Impact on Financial Statements

Imhoff et al. (1991) developed a method for the constructive capitalization of operating leases and used this method to estimate the impact of capitalization on two ratios (return on assets [ROA] and debt-to-equity) for 14 U.S. companies with low and high lease usage. They provided evidence that operating leases had a significant effect on risk and return measures. Using a set of assumptions to constructively capitalize operating leases, they found an average decrease of 34% (10%) in ROA and an average increase of 191% (47%) in debt-to-equity ratios for high lease (low lease) firms. The results of their small sample study indicated that the magnitude of the effect will be different across industries that use off–balance sheet lease financing.

The majority of studies investigating the financial statement impact have generally focused on international firms. Based on an analysis of 232 U.K. firms, Beattie, Edwards, and Goodacre (1998) noted that operating leases not only accounted for an average of 39% of total debt and 6% of total assets but also were 13 times larger than capital leases. Their results showed six of nine ratios (profit margin, ROA, asset turnover, three measures of leverage) were significantly affected by capitalizing operating leases. There was a dramatic increase in the debt-to-equity ratio from 20% to 72% for the sample as a whole and from 24% to 141% in the services sector. Significant interindustry variations indicated a greater impact on the services sector (retail, hotel, media, etc.) relative to other sectors. Furthermore, the relative ranking of companies changed within and across different sectors. This was largely due to the varying levels of operating lease usage among service industry firms such as hotels and retailers. Similar findings have been observed among New Zealand firms (Bennett & Bradbury, 2003), German firms (Fülbier et al., 2006), and the U.K. retail sector (Goodacre, 2003).

Overall, the results of the above studies indicate that capitalization of operating leases will likely have a material impact on the balance sheet with measures such as leverage ratios significantly increased. However, these studies were limited to cross-sectional studies using smaller sample sizes and international firms. Whether these results still hold more than a decade later would certainly provide a meaningful basis for comparison using panel data with larger sample sizes before and after the new rules are implemented.

Impact on Capital Structure

Imhoff and Thomas (1988) documented a significant change in the capital structure of a sample of 158 U.S. firms. After adoption of SFAS 13, a substitution effect occurred with a sharp decline in capital leases and a corresponding increase in operating leases. Most firms employed capital structure changes by increasing their use of nonlease financing evidenced by an increase in equity and a decline in long-term debt. These results suggested that lessees employed various capital structure changes in addition to renegotiating lease contracts to mitigate the impact of the new standard on the overall firm leverage. The findings also suggested that renegotiation of lease contracts was a low-cost alternative relative to other responses that firms employed to potentially reduce the impact of the new standard. Similar capital structure changes are expected to be made by firms prior to and after implementation to the proposed new rules for lease accounting.

Hospitality-Related Leasing Research

A study by Marler (1993) on the nature of leasing in the restaurant industry indicated that restaurant firms preferred operating leases over capital leases with operating leases exceeding capital lease obligations by a ratio of 9 to 1. Despite some mixed and inconclusive evidence on the effect of firm size on leasing, it was observed that restaurants were most affected by liquidity and solvency ratios. However, her results were inconclusive on firm size and she called for further research on the effect of firm size on leases. Upneja and Schmidgall (2001) surveyed hotel financial managers to provide evidence that the majority of lodging firms equipment leases were accounted for as operating leases. Transfer of ownership and bargain-purchase options in lease contracts were the criteria that respondents indicated most likely to trigger capitalization of leases. In another study, Upneja and Dalbor (1999) examined a sample of 95 restaurant firms to determine the association between debt financing and marginal tax rates to explain the capital structure choice of restaurant firms. Although their measure of operating leases was limited because of the unavailability of some lease-operating data in the Compustat database at the time, they nevertheless found that marginal tax rates were significantly and negatively related to operating leases implying that restaurant firms with lower marginal tax rates were more likely to rely on operating leases instead of purchasing assets, whereas firms with high marginal tax rates were more likely to capitalize leases and purchase assets with debt financing. In addition, they documented a positive association between the probability of bankruptcy or financial distress and the use of operating leases suggesting that an increase in the use of operating leases could signal deteriorating financial condition as firms were closer to financial distress. These findings also indicated that firms in strong financial standing (high Altman’s [1968], z score) were less likely to use operating leases. However, this finding was based on a simple regression of the z scores on operating leases without controlling for the effect of firm size on operating leases, which Marler’s (1993) study indicated does exist.

Research in industry-specific studies on operating leases has also been largely limited to small sample sizes and limited data availability prior to 2000. Upneja and Schmidgall (2001) noted the limited number of hospitality studies and the lack of hospitality industry–specific data on the magnitude of leasing in the industry. Using more recent panel data over the 2006-2008 period and a larger sample size of firms in the restaurant and retail sectors, this study will provide a more comprehensive analysis of the magnitude of leasing, its impact on various balance sheet and income statement ratios, and its relation with firm size and financial distress to reconcile and extend previous research in this area.

Method

Research Design

To be consistent with prior research, this study employs the lease capitalization methodology proposed by Imhoff et al. (1991). It differs from previous studies in allowing one or more assumptions to vary by firm. The DCF method is used to estimate the present value of the scheduled minimum future lease payments for operating leases (PVOL) based on lease footnote disclosures in the annual 10-K reports filed by public firms with the Securities and Exchange Commission (SEC). Appendix A provides a sample of the lease footnote disclosures of Darden Restaurants for fiscal year 2009 as required under the existing rules.

The conversion of operating leases into capital leases uses the information in the lease footnote disclosures and requires a set of key uniform assumptions to be made regarding the interest rate and the remaining life of leases beyond 5 years. Employing a uniform set of assumptions ensures that the observed changes and differences can be attributed to differences in the operating leases rather than differences in the assumptions (Imhoff et al., 1991). To implement the DCF technique, this study follows the constructive lease capitalization methodology developed by Imhoff et al. (1991, 1997). In the former study, the researchers developed procedures for estimating the balance sheet impact of capitalizing operating leases, whereas in the latter study, they demonstrated the income statement impact.

Assumptions in Research Design

The following key assumptions are used to implement the DCF technique in this study:

An interest rate of 9% is used to proxy for the average incremental borrowing rate for the portfolio of operating leases for each firm. An analysis of long-term debt disclosures of 69 restaurant companies for 2007 by the author found an overall average interest rate of 9%. Prior studies have used similar rates of 10% (Beattie et al., 1998; Imhoff et al., 1991; Marler, 1993). Furthermore, there were many firms with no reported long-term debt on the balance sheet. For these firms, one has to assume an interest rate in order to perform the necessary computations to estimate the PVOL. In the sensitivity analysis, the incremental interest rate is allowed to vary in order to test the robustness of the results.

It is assumed that all cash flows occurred at year-end and assets are depreciated using the straight-line method of depreciation, whereas the interest payments are computed using the effective interest method consistent with the proposed new rules.

Unlike the uniform assumption of a 15-year remaining lease life used in prior studies (Imhoff et al., 1991; Marler, 1993), the total remaining lease life is allowed to vary by firm in this study.

Consistent with Imhoff et al. (1991), a standard 75% asset to liability ratio is used for all firms in the sample.¹ In the sensitivity analysis, this ratio is allowed to vary by firm. Underlying this assumption, the PV of the asset will be equal to the PV of the lease liability at the inception of the lease but equal to zero at the end of the lease. Imhoff et al. (1991) showed that the book value of the leased asset is lesser than the book value of the liability because the early payments on the lease consisted largely of interest payments with little principal reduction, whereas the depreciation deduction reduced the value of the asset at a much higher rate than the principal reduction of the liability. Therefore, throughout the life of the lease, the lease liability would be greater than the carrying value of the asset.

For simplicity, the effective tax rate for all sample firms is assumed to be the corporate tax rate of 35%.

Based on the above assumptions, the DCF technique using the constructive lease capitalization methodology in this study is demonstrated in Appendix B using Darden Restaurants as an example.

Estimating Impact on Financial Statements and Ratios

The balance sheet effect is determined by increasing long-term debt by the PV of the lease payments, whereas assets are increased by the asset to liability ratio. Following estimation of the asset and liability amounts, the income statement effects are estimated by removing rent expense from selling, general, and administrative expenses (SGA) and replacing it with depreciation and interest expense. Interest expense is calculated by multiplying the 9% interest rate by the average of PV of the lease liability for the current and previous years. Subtracting the interest expense from rent expense in the minimum rent payment schedule for the current year (taken from the previous fiscal year), yields an estimate of depreciation expense. The effective tax rate of 35% is then applied to any difference between the rent expense and the sum of interest and depreciation expense to determine the tax effect. If the PVOL declined (increased) from one year to the next, then the sum of depreciation and interest under capital leases will be less (more) than the current operating rent expense, which will then lead to an increase (decrease) in pretax income and after-tax income.

Following adjustments to the income statement, a set of financial ratios are computed to estimate the impact of operating lease capitalization. These ratios, which include various interest coverage, leverage, and profitability ratios widely used in practice, are computed “before” and “after” lease capitalization. The definitions of these ratios are provided in Appendix C. These ratios are widely used by analysts and credit-rating agencies, commonly cited in accounting and finance textbooks, and have been used in various forms in prior studies (Beattie et al., 1998; Fülbier et al., 2006; Goodacre, 2003). Descriptive statistics, nonparametric tests of differences, and correlation analysis are employed to provide relevant information on the magnitude and significance of changes in various financial ratios before and after capitalization. Finally, the following multiple regression model is specified to test the relation between operating lease usage, firm size, and financial distress to reconcile and extend prior mixed findings on this issue:

{Usage}_{it} = b_{0} + b_{1} z {Score}_{it} + b_{2} {Size}_{it} + b_{3} {Sector}_{it} + ε_{it},

where the usage ratio is a proxy for operating lease usage and measured as the sum of future lease payments over 5 years and scaled by total assets (Imhoff et al., 1991); z score is Altman’s (1968) z Score; Size is the log of total assets to control for firm size; Sector is a dummy variable that equals 1 if the firm is a restaurant firm and zero otherwise.

Sample Selection

The sample for the study was drawn from all active public restaurant firms and retail firms from Standard & Poor’s Compustat database during the most recent three years from 2006 to 2008. This was done to avoid using data for fiscal years prior to 2005 when hundreds of restaurants and retail firms restated their historical financial statements for lease accounting errors. A criteria used in the sample selection process was the need for a firm to have complete financial data for 4 years from 2005 to 2008. Data from 2005 were used only in calculating changes and averages for some ratios. Firms that were subject to bankruptcies, mergers/acquisitions, going private, and lack of complete data were dropped from the sample. From an initial list of 366 firms (112 restaurant firms and 254 retail firms), 132 firms were deleted (48 restaurant firms and 84 retail firms) for the above reasons. The final sample consisted of 234 firms (64 restaurant firms and 170 retail firms) and 702 firm-year observations from 2006 to 2008.

Results

Descriptive Statistics

Data were analyzed for 234 restaurant and retail firms consisting of 702 firm-year observations from 2006 to 2008. Descriptive statistics for the overall sample as well as the two industry sectors are shown in Table 1. Because of the presence of extreme outliers and considerable variation in the data, medians are used to describe the data.

Table 1

Descriptive Statistics (2006-2008)

	Restaurant Firms (64 Firms)				Retail Firms (170 Firms)				Overall Sample (234 Firms)
	n	Mean	Median	SD	n	Mean	Median	SD	n	Mean	Median	SD
Sales	192	1,613	568	3,561	510	9,107	1,741	31,664	702	7,057	1,251	27,251
EBITDA	192	262	53	870	510	696	121	2,240	702	577	98	1,971
EBITDA margin (%)	192	0.11	0.10	0.09	510	0.08	0.07	0.06	702	0.09	0.08	0.07
EBIT	192	189	30	708	510	497	78	1,703	702	412	54	1,504
EBIT margin (%)	192	0.062	0.059	0.091	510	0.048	0.044	0.054	702	0.052	0.049	0.066
Pretax Income	192	139	15	621	510	420	51	1,781	702	343	39	1,557
Pretax Income Margin (%)	192	0.013	0.040	0.227	510	0.034	0.035	0.070	702	0.028	0.036	0.133
Income before extraordinary items	192	92	12	432	510	251	33	1,157	702	208	26	1,014
Total assets	192	1,349	356	3,852	510	4,411	909	14,195	702	3,573	690	12,338
Long-term debt	192	493	76	1,329	510	997	101	3,598	702	859	100	3,152
Total debt	192	517	84	1,370	510	1,095	119	3,838	702	937	111	3,357
Capitalized leases	96	37	12	55	246	114	13	485	342	111	13	415
Total debt/assets (Leverage %)	162	0.42	0.32	0.47	425	0.25	0.21	0.22	587	0.30	0.24	0.32
PVOL	192	386	128	915	510	978	367	1,797	702	816	268	1,626
PVOL/capitalized leases (times)	96	382	14	1,954	246	272	31	978	342	303	25	1,324
PVOL/total assets (%)	192	0.43	0.36	0.28	510	0.46	0.42	0.33	702	.45	0.40	0.32
PVOL/total debt (%)	162	16.5	0.93	82	425	44.9	2.0	434	587	37.1	1.52	372
Adjusted leverage (%)	162	0.58	0.51	0.36	425	0.46	0.45	0.17	587	0.50	0.47	0.25
Average interest rate (%)	192	0.092	0.089	0.032	510	0.098	0.094	0.037	702	0.097	0.093	0.036

Note: PVOL = present value of operating leases; EBIT = earnings before interest and taxes; EBITDA = earnings before interest, taxes, depreciation, and amortization. Expense values are in $ million. EBITDA and EBIT are a non-GAAP measure of profitability. Data are unadjusted for the presence of outliers. Some observations are missing because of the following reasons. Capitalized leases were disclosed by only 32 restaurant firms and 82 retail firms. Ten restaurant firms and 28 retail firms had no debt prior to adjustment for operating leases.

The data show the average sample firm-generated median sales of $1.25 billion, earned income before interest and taxes of $54 million, and before-tax income of $39 million. The net sales and total asset amounts show retail firms to be more than 3 times larger than restaurant firms, an indication that the restaurant sector is composed largely of small firms. However, the restaurant sector is observed to be more effective in converting sales dollars into profits as indicated by the higher profit margins compared with the retail sector. Similar conclusions can be drawn about the amount of debt in both sectors. However, the use of debt as indicated by the leverage ratio (total debt/total assets) is more than one and half times higher for the restaurant sector compared with the retail sector, an indication that restaurants firms are heavy users of debt financing for fixed assets.

Given the widespread and pervasive use of operating leases over capital leases, it is no surprise that few firms in both sectors reported capital leases. The median amount of capital leases is similar across both sectors before capitalization. When operating leases are capitalized, the PV of the off–balance sheet operating lease payments (PVOL) is a median amount of $268 million, an amount higher for the retail sector compared with the restaurant sector. The magnitude of this unreported liability is significant for both sectors. For firms that reported capital leases, the off–balance sheet debt would represent a median of 25 times the reported capital leases, a ratio that is much larger than the ratio of 9 and 13 reported by Marler (1993) and Beattie et al. (1998), respectively. Relative to existing total assets and total debt, the additional debt liability from operating leases would represent a median of 36% and 93% for the restaurant sector and 42% and 200% for the retail sector. Adding this additional operating lease liability to existing debt would almost double the adjusted leverage ratio (after capitalization) from a median of 25% to 47% for the overall sample with similar observations for both sectors. This raises concerns about the relatively large increase in the magnitude of these ratios when the new rules are implemented. The interest rate of 9% used in estimating the PVOL also appears to be reasonable since the average and median rates for all sample firms is between 9% and 10%.

Although these descriptive measure are not strictly comparable with those of previous studies because of the slightly different assumptions and methodologies employed, nevertheless the leverage indicators do provide some direction in the magnitude of the ratios. The median PVOL amount of $128 million for restaurant firms is higher than the figure of $82 million reported by Marler (1993). Similarly, the median PVOL to total debt ratio of 1.52 for the sample is three times larger than the mean ratio of 0.47 reported by Beattie et al. (1998) for U.K. firms.

Table 2 provides incremental new information on store and rental characteristics that is previously unreported in prior research on leasing. These metrics provide some indication of the overall growth and profitability of the restaurant and retail industry. These metrics are also commonly used by analysts to track trends and developments in both sectors. The data show the restaurant sector to be larger than the retail sector in terms of the number of stores, new store openings, and growth in stores. Much of this rapid growth in the restaurant sector has been achieved through franchising to increase future revenues and economies of scale. However, given the high risk of failure in the restaurant sector, the number of stores closed due to impairment, bankruptcy, or weak performance is also higher in the restaurant sector compared with the retail sector. Nevertheless, the numbers of store openings do outpace the store closings over the 3-year period for both sectors, a positive indicator of growth. Reducing the number of nonperforming stores can drive up future profitability. A more closely watched metric in the restaurant and retail industry is the same-store sales or comparable sales figure, which provides information on the percentage change in demand for existing stores that have been opened for at least 12 or 18 months. The comparable sales figure (only for firms that reported this figure) shows that the restaurant sector, in spite of its high risk, still outperformed the retail sector as indicated by the higher operating profitability figures reported in Table 1.

Table 2

Retail Store and Rental Expense Characteristics (2006-2008)

	Restaurant Firms (64 Firms)				Retail Firms (170 Firms)				Overall Sample (234 Firms)
	n	Mean	Median	SD	n	Mean	Median	SD	n	Mean	Median	SD
Number of stores at year end	192	2,306	390	6,215	510	1,097	510	1,518	702	1,428	488	3,533
Growth in stores (%)	121	0.09	0.05	0.24	316	0.05	0.03	0.18	437	0.06	0.04	0.20
Number of stores opened in year	154	83	29	144	415	57	34	72	569	64	33	97
Number of stores closed in year	124	45	14	86	345	36	11	81	469	39	11	82
% change in stores opened	154	0.09	0.07	0.07	415	0.07	.06	0.06	569	0.07	.06	0.06
% change in stores closed	124	0.04	0.02	0.05	345	0.04	.02	0.06	469	0.036	0.02	0.06
Comparable store sales (%)	109	1.47	1.6	4.02	446	0.15	1	6.9	556	0.41	1	6.5
Minimum rent ($ millions)	192	71	25	174	510	178	77	271	702	150	55	253
Contingent rent ($ millions)	154	11	2	38	334	12	3	24	488	12	3	29
Other rent ($ millions)	18	5	2	7	94	21	10	29	112	19	6	27
Total rent expense ($ millions)	192	78	26	203	510	189	84	280	702	159	61	265
Rental income ($ millions)	75	11	1.4	21	164	9	1.9	19	239	10	1.8	20
Net rent expense ($ millions)	192	74	24	202	510	186	84	275	502	155	58	262
Minimum rent/total rent expense (%)	192	0.92	0.95	0.16	510	0.93	.99	0.17	702	0.93	0.98	0.14
Contingent rent/total rent expense (%)	154	0.08	0.05	0.09	334	0.06	.01	0.13	488	0.06	0.02	0.12
Net rent expense/total rent expense (%)	192	0.94	1	0.14	510	0.97	1	0.1	702	0.96	1	0.11

Note: Data are unadjusted for the presence of outliers. Not all characteristics were observed for all firms. For example, rental income was disclosed by 25 restaurant firms and 55 retail firms.

An analysis of the total rental expense shows retail stores incurring higher rental expenses than restaurants. This is expected since retail stores are larger and occupy more leasable space than restaurants. The proportion of minimum rent expense and contingent rental expense relative to total rent expense is largely similar across both two sectors with minimum rental expense accounting for more than 90% of total rental expense. Contingent rent is also higher for restaurant firm compared with retail firms when sales targets are exceeded.

The results of applying the constructive lease capitalization methodology of Imhoff et al. (1991) on the key financial ratios on the overall sample of 234 firms are presented in Table 3. Because of the presence of outliers and the considerable variation in the data, median ratios provide the basis for interpretation. Both interest coverage ratios (earnings before interest and taxes [EBIT]/Interest and earnings before interest, taxes, depreciation, and amortization [EBITDA]/Interest) show a significant decline over 50% after adjusting for the effect of operating leases. On the other hand, debt-related ratios such as the debt-to-EBITDA, leverage, and debt-to-equity ratios show dramatic increases because of the addition of operating leases to existing debt levels. The debt to equity ratio, for example, would increase more than 3 times or 354% from 0.30 to 1.38. Operating profit margins (EBITDA and EBIT) would also increase from the removal of rent expense and its replacement with amortization and interest expense in different locations on the income statement. The impact on pretax income will depend on whether the firm increases or decreases its portfolio of leases and also the life of its leases. A decrease (increase) in the portfolio of leases would increase (decrease) pretax income. Pretax income will also decrease earlier in the lease term because of the front-loading of higher amortization and interest expense, but the reversal would occur later in the lease term. The results in Table 3 also show that the return on invested capital (ROIC) ratio declined with an increase in debt in the denominator of the ratio, whereas the ROA ratio declined on an after-tax basis.²

Table 3

Sample Descriptive Statistics on Capitalization Ratios (2006-2008)

	Unadjusted				Adjusted
	n	Mean	Median	SD	n	Mean	Median	SD
EBIT ICR	630	67	4.78	517	695	3.0	2.22	4.71
EBITDA ICR	630	105.6	8.93	736	695	5.26	4.36	5.18
Total debt to EBITDA	702	1.47	1.06	15	696	1.01	2.74	81.10
Debt to capital	702	0.375	0.267	0.521	702	0.668	0.629	0.428
Debt to equity	702	0.764	0.304	6.37	702	2.70	1.38	12.3
Leverage	702	0.249	0.187	0.311	702	0.509	0.477	0.257
ROIC	702	0.139	0.141	0.237	702	0.124	0.121	0.104
ROA	702	0.025	0.049	0.126	702	0.019	0.034	0.086
EBITDA margin	702	0.086	0.081	0.073	702	0.134	0.129	0.078
EBIT margin	702	0.052	0.049	0.066	702	0.070	0.065	0.065
Pretax margin	702	0.028	0.036	0.133	702	0.028	0.034	0.086

Note: Refer to Appendix C for definitions of variables and ratios.

Comparisons of similar ratios with those of previous studies indicate consistency in the direction and magnitude of the changes. The median change in the EBIT interest coverage ratio, EBIT margin, ROA, and debt to equity ratios in Table 3 are all greater than the mean figures reported by Beattie et al. (1998) for U.K. firms.³ These preliminary findings indicate that implementation of the proposed rules will lead to a decline in interest coverage and profitability ratios and an increase in leverage ratios and operating margins, consistent with the widespread growth and magnitude in the use of operating leases and its subsequent capitalization.

The capitalization impact on the magnitude of the ratios is reported in Table 4. In general, the results show some stability in the absolute median changes in a number of ratios before and after capitalization within the sample and across sectors. The largest median differences appear to be in the interest coverage, ROIC, and ROA ratios prior to the onset of the most recent economic crisis in 2006. On the other hand, capitalization would have a greater impact on debt-to-equity and leverage ratios and EBIT margin for both retail and restaurant firms during the economic crisis in 2008 because of an increase in the magnitude of operating leases and debt financing.

Table 4

Trend in Median Absolute Changes in Financial Ratios From 2006 to 2008

Panel A: Restaurant Firms	2006	2007	2008
EBIT ICR	−2.56	−1.71	−0.77
EBITDA ICR	−4.31	−3.39	−2.29
Total debt to EBITDA	0.884	0.834	1.00
Debt to capital	0.177	0.177	0.180
Debt to equity	0.875	1.04	1.18
Leverage	0.174	0.175	0.198
ROIC	−0.018	−0.014	−0.008
ROA	−0.011	−0.010	−0.005
EBITDA margin	0.042	0.041	0.040
EBIT margin	0.011	0.014	0.019
Pretax margin	−0.003	−0.004	−0.001
Panel B: Retail Firms
EBIT ICR	−3.64	−2.28	−0.98
EBITDA ICR	−5.19	−3.58	−2.38
Total debt to EBITDA	1.16	1.16	1.04
Debt to capital	0.317	0.321	0.307
Debt to equity	0.947	1.11	1.20
Leverage	0.275	0.263	0.281
ROIC	−0.024	−0.017	0.000
ROA	−0.014	−0.011	−0.004
EBITDA margin	0.043	0.043	0.046
EBIT margin	0.012	0.011	0.016
Pretax margin	−0.003	−0.003	−0.000
Panel C: All Firms
EBIT ICR	−3.39	−2.00	−0.83
EBITDA ICR	−4.67	−3.57	−2.38
Total debt to EBITDA	1.09	1.13	1.02
Debt to capital	0.287	0.271	0.257
Debt to equity	0.933	1.08	1.20
Leverage	0.257	0.241	0.249
ROIC	−0.023	−0.017	−0.004
ROA	−0.013	−0.011	−0.004
EBITDA margin	0.042	0.042	0.044
EBIT margin	0.012	0.012	0.016
Pretax margin	−0.003	−0.003	−0.000

Note: Refer to Appendix C for definitions of ratios.

Empirical Findings

Given the nonnormality of the data and presence of extreme outliers in a number of variables, the nonparametric Wilcoxon signed-rank test is employed to assess whether the median differences in the financial ratios are significantly different before and after capitalization. The results in Table 5, Panels A-C are presented for both sectors and the overall sample. The results show significant differences in all 11 ratios at the 1% significance level for both sectors and the sample. Comparisons between sectors in Panels A and B reveal some important differences in the magnitude and relative changes in the ratios. The magnitude of the difference in the median ratios is generally and significantly larger for 7 of 11 ratios in the retail sector in Panel B compared with the restaurant sector in Panel A. Similarly, 9 of the 11 significant ratios in Panel B indicate greater percentage changes in the retail sector relative to the restaurant sector in Panel A. These changes imply that the retail sector would be more significantly affected than the restaurant sector by the proposed rules that will require capitalization of all operating leases. For example, the leverage ratio for restaurants would increase by a median 110%, but the same ratio would be 202% for the retail sector.

Table 5

Changes in Median Financial Ratios by Sector

Ratios
Panel A: Restaurant Firms	Before	After	Diff.	Percentage	z	Spearman
EBIT ICR	4.01	2.12	−1.89	−47.1	−6.696*	.864*
EBITDA ICR	7.63	4.05	−3.58	−46.9	−8.397*	.845*
Total debt to EBITDA	1.54	3.1	1.56	101.3	8.919*	.644*
Debt to capital	0.335	0.648	0.313	93.4	10.262*	.771*
Debt to equity	0.365	1.31	0.945	258.9	10.271*	.713*
Leverage	0.248	0.52	0.272	109.7	11.477*	.761*
ROIC	0.129	0.11	−0.019	−14.7	−4.501*	.960*
ROA	0.047	0.03	−0.017	−36.2	−5.439*	.971*
EBITDA margin	0.101	0.147	0.046	45.5	11.953*	.916*
EBIT margin	0.059	0.079	0.02	33.9	10.559*	.950*
Pretax margin	0.04	0.037	−0.003	−7.5	−5.709*	.979*
Panel B: Retail Firms
EBIT ICR	5.08	2.25	−2.83	−55.7	−12.597*	.830*
EBITDA ICR	9.99	4.49	−5.5	−55.1	−14.737*	.795*
Total debt to EBITDA	0.874	2.61	1.736	198.6	14.653*	.593*
Debt to capital	0.238	0.62	0.382	160.5	18.878*	.610*
Debt to equity	0.283	1.4	1.117	394.7	17.67*	.561*
Leverage	0.155	0.468	0.313	201.9	19.566*	.547*
ROIC	0.144	0.125	−0.019	−13.2	−6.859*	.955*
ROA	0.049	0.037	−0.012	−24.5	−9.976*	.964*
EBITDA margin	0.07	0.121	0.051	72.9	19.49*	.836*
EBIT margin	0.044	0.059	0.015	34.1	18.321*	.936*
Pretax margin	0.035	0.032	−0.003	−8.6	−7.392*	.981*
Panel C: All Firms
EBIT ICR	4.78	2.22	−2.56	−53.6	−14.193*	.841*
EBITDA ICR	8.93	4.36	−4.57	−51.2	−16.921*	.810*
Total debt to EBITDA	1.06	2.74	1.68	158.5	17.14*	.614*
Debt to capital	0.267	0.629	0.362	135.6	21.478*	.659*
Debt to equity	0.304	1.38	1.076	353.9	20.444*	.608*
Leverage	0.187	0.477	0.29	155.1	22.69*	.616*
ROIC	0.141	0.121	−0.02	−14.2	−8.159*	.956*
ROA	0.049	0.034	−0.016	−32.0	−11.319*	.966*
EBITDA margin	0.08	0.129	0.049	61.3	22.856*	.867*
EBIT margin	0.049	0.065	0.016	32.7	21.134*	.943*
Pretax margin	0.036	0.034	−0.002	−5.6	−9.259*	.981*

Note: Spearman is the Spearman rank correlation coefficient before and after capitalization. Reported before and after ratios represent median values. Diff. represents the magnitude of the difference between the median ratios before and after capitalization. Percentage (%) represents the relative difference in the median ratios before and after capitalization. z represents the z value of the Wilcoxon signed-rank test of median differences using a two-tailed test. Refer to Appendix C for definitions of ratios.

p < .01.

To capture the relative performance of the firms before and after capitalization, the Spearman rank correlation is computed for the ranking of firms before and after capitalization. The Spearman rank correlation coefficients are all significant at the 1% level indicating that lease capitalization will significantly affect the relative performance of firms in both sectors. The correlation coefficients range from a low of .547 to a high of .981. The correlation coefficients generally fall into three groups of ratios: low correlations for debt-related ratios, moderate correlations for interest coverage ratios, and high correlations for profitability ratios. In all but one ratio, the correlations are higher for the restaurant sector relative to the retail sector. The lower correlations imply considerable variation in the magnitude and levels of operating leases employed by firms in both sectors. Because much of the unrecognized lease debt is currently held off–balance sheet, capitalization of operating leases would affect the debt structure of retail firms to a greater extent than restaurant firms, consistent with the results using the nonparametric Wilcoxon tests of differences. Companies with no existing debt would have to recognize the additional lease debt on balance sheets, whereas smaller firms with high debt levels would face higher leverage ratios.

Prior research by Marler (1993) found mixed evidence on whether firm size affected the use of operating leases particularly among small firms. To determine if firm size has a considerable impact on the use of leasing and capitalization, the results in Table 5 were further broken down by firm size. Firms were divided into three categories of size based on annual net sales: small, medium, and large firms. Firms with less than $500 million in sales were classified as small firms, whereas those with sales in excess of $1.5 billion in sales were classified as large firms.⁴ Half the restaurant firms were found to be small firms, whereas more than half of the large firms were predominantly retail firms—an indication of the considerable variation in size across sectors. The results of this analysis are presented in Table 6, Panels A-C for both sectors by firm size.

Table 6

Changes in Median Financial Ratios by Sector and Firm Size

	Restaurant (32 firms)				Retail (28 firms)
Panel A, Small Firm Ratios	Before	After	Diff.	Percentage	Before	After	Diff.	Percentage
EBIT ICR	2.285	1.675	−0.610***	−26.7	2.615	1.461	−1.154*	−44.1
EBITDA ICR	6.305	3.663	−2.642*	−41.9	4.541	3.538	1.003*	−22.1
Total debt to EBITDA	0.796	2.971	2.175*	273.2	1.043	3.005	1.962*	188.1
Debt to capital	0.177	0.585	0.408*	230.5	0.234	0.633	0.399*	170.5
Debt to equity	0.128	1.146	1.018*	795.3	0.277	1.381	1.104*	398.6
Leverage	0.126	0.461	0.335*	265.9	0.157	0.515	0.358*	228.0
ROIC	0.076	0.075	−0.001	−1.3	0.080	0.079	−0.001	−1.3
ROA	0.019	0.012	−0.007	−36.8	0.037	0.025	−0.012*	−32.4
EBITDA margin	0.083	0.132	0.049*	59.0	0.045	0.119	0.074*	164.4
EBIT margin	0.038	0.056	0.018*	47.0	0.025	0.041	0.016*	66.7
Pretax margin	0.013	0.009	−0.004*	−31.3	0.027	0.022	−0.005**	−18.1
	Restaurant (20 firms)				Retail (50 firms)
Panel B, Medium Firm Ratios	Before	After	Diff.	Percentage	Before	After	Diff.	Percentage
EBIT ICR	3.312	2.007	−1.305*	−39.4	4.730	1.865	−2.865*	−60.6
EBITDA ICR	5.099	3.707	−1.392*	−27.3	10.778	4.375	−6.403*	−59.4
Total debt to EBITDA	2.526	3.611	1.085*	43.0	0.489	2.501	2.012*	411.5
Debt to capital	0.469	0.671	0.202*	43.1	0.141	0.623	0.482*	341.8
Debt to equity	0.383	1.165	0.787*	204.2	0.124	1.421	1.297*	1046.0
Leverage	0.360	0.570	0.210*	58.3	0.095	0.469	0.374*	393.7
ROIC	0.152	0.112	−0.040*	−26.3	0.124	0.103	−0.021*	−16.9
ROA	0.054	0.031	−0.023*	−42.6	0.037	0.020	−0.017*	−45.9
EBITDA margin	0.123	0.157	0.034*	27.6	0.073	0.131	0.058*	79.5
EBIT margin	0.071	0.084	0.013*	18.3	0.043	0.061	0.017*	41.9
Pretax margin	0.042	0.038	−0.004*	−9.5	0.029	0.026	−0.003*	−10.3
	Restaurant (12 Firms)				Retail (92 Firms)
Panel C, Large Firm Ratios	Before	After	Diff.	Percentage	Before	After	Diff.	Percentage
EBIT ICR	6.784	3.425	−3.359*	−49.5	6.992	2.856	−4.136*	−59.2
EBITDA ICR	9.413	5.758	−3.655*	−38.8	10.674	5.132	−5.542*	−51.9
Total debt to EBITDA	1.582	2.429	0.847*	53.5	1.042	2.520	1.478*	141.8
Debt to capital	0.520	0.710	0.190*	36.5	0.270	0.618	0.348*	128.9
Debt to equity	1.037	2.224	1.187*	114.5	0.336	1.389	1.053*	313.4
Leverage	0.349	0.563	0.214*	61.3	0.182	0.457	0.275*	151.1
ROIC	0.193	0.165	−0.028*	−14.5	0.165	0.144	−0.021*	−12.7
ROA	0.073	0.055	−0.018*	−24.7	0.056	0.046	−0.010*	−17.9
EBITDA margin	0.123	0.158	0.035*	28.5	0.074	0.115	0.041*	55.4
EBIT margin	0.078	0.096	0.018*	23.1	0.049	0.062	0.013*	26.5
Pretax margin	0.072	0.070	−0.002*	−2.8	0.040	0.038	−0.002*	−5.0

Note: Reported before and after ratios represent medians. Diff. represents the magnitude of the difference between the median ratios before and after capitalization. Percentage (%) represents the relative difference in the median ratios before and after capitalization. The two-tailed Wilcoxon signed-rank test is used to test the median differences. Refer to Appendix C for definitions of ratios.

p < .01. **p < .05. ***p < .10.

First, the differences in the ratios before and after capitalization are all significant at the 1% level for firms in both sectors for medium and large firms. Only 8 out of 11 ratios are significant at the 5% level for small restaurant firms in Panel A compared with 10 out of 11 ratios for small retail firms. Second, the impact on the debt-related ratios is significantly higher in both sectors relative to other ratios given the large amount of lease debt that is currently off–balance sheet. Third, unlike the retail sector, most of the ratios before and after capitalization are consistently larger (smaller) for larger (smaller) restaurant firms indicating a potential size effect as indicated by Marler’s (1993) research. Fourth, across all firm sizes, operating margins (EBITDA and EBIT) are observed to be higher for restaurant firms compared with retail firms before and after capitalization.

Within the restaurant industry, the magnitude of the differences and relative changes are generally higher in the interest coverage ratios for larger firms compared with medium and smaller firms. Even more striking is the observation that small firms will be more significantly affected by increases in debt-related ratios relative to medium or large firms. For example, the median leverage ratio for small restaurant firms (Panel A) would increase by a significant 266% compared with 58% and 61% for medium and large restaurant firms (Panels B and C). The lack of access to capital markets or bank financing for many small firms may explain the heavy use of operating leases among small firms. Operating margins (EBITDA and EBIT), on the other hand, will be significantly higher for small restaurant firms (Panel A) relative to medium and large firms (Panels B and C) when rent expense is removed from the income statement. Medium restaurant firms (Panel B) will also face significantly lower ROIC and ROA ratios compared with large firms.

In contrast to the ratios for small restaurant firms (Panel A), medium retail firms (Panel B) will be most affected by lease capitalization. The changes in interest coverage and debt-related ratios for medium retail firms are significantly higher than small or large retail firms. For example, the leverage ratio for medium retail firms will increase by 394% compared with 228% for small firms and 151% for large firms. Consistent with small restaurant firms, small retail firms will also face greater changes in operating margins compared with medium and large retail firms.

Directly comparing firms across sectors and size, it can also be observed that small restaurant firms will face significantly greater changes in debt-related ratios than small retail firms, whereas small retail firms will see larger changes in their operating margins. On the other hand, medium retail firms will be significantly affected to a greater extent than medium restaurant firms. Similar conclusions can be drawn for most ratios for large retail firms compared with large restaurant firms. These results show that the magnitude and changes in operating lease usage varies within sectors and across sectors, consistent with prior research in the United Kingdom (Beattie et al., 1998; Goodacre, 2003). These results also reconcile the mixed finding of Marler (1993) on the size effect to provide further evidence that firm size is an important factor in explaining the use of operating leases with smaller restaurant firms using more operating leases than larger restaurant firms. Although Upneja and Dalbor (1999) provided some evidence that firms with a stronger financial standing were less likely to use operating leases, they nevertheless failed to control for the size effect and thus their measure of financial distress (z score) could have been a proxy for firm size. Therefore, to provide further evidence on this issue, operating lease usage is regressed on firm size and financial distress. No outliers were found in the variables so parametric statistics are reported for this analysis. Five different pooled cross-sectional model specifications were employed in the empirical analysis to investigate the relation between firm size, financial distress, and lease usage. All regressions were estimated with heteroskedasticity robust standard errors. Multicollinearity was also tested and found to be within conventional limits (variance inflation factors < 2 in all regressions). The results of this analysis are presented in Table 7 Panels A and B.

Table 7

Relationship Between Firm Size, Financial Distress, and Lease Usage

	Restaurant			Retail
Panel A, Variable	Mean	Median	SD	Mean	Median	SD
z Score	3.31	2.84	2.93	4.3	3.77	2.77
Usage	0.34	0.28	0.24	0.42	0.39	0.32
Size	5.75	5.88	1.69	6.94	6.81	1.61
Panel B	Model 1	Model 2	Model 3	Model 4		Model 5
Constant	0.934	0.586	0.580	0.577		0.920
	(13.60)*	(6.79)*	(15.55)*	(13.19)*		(13.71)*
z Score	0.000	−0.007	0.01
	(0.00)	(−0.85)	(0.28)
Size	−0.073	−0.039	−0.071
	(−9.22)*	(−3.59)*	(−8.94)*
Sector	−0.174		−1.46	−0.166		−0.167
	(6.83)*		(−5.23)	−6.03)*		(−6.50)*
Distress1			−0.050
			(−1.91)***
Distress2						−0.011
						(−0.51)
Medium			−0.096	−0.102
			(−2.67)*	(−2.82)*
Large			−0.223	−0.230
			(−5.93)*	−6.10)*
Observations	689	192	702	689		702
F ratio	32.4	6.64	15.1	14.5		32
p Value	.000	.002	.000	.000		.000
R ²	.1721	.083	.094	.099		.163

Note: This table presents the results of a multiple regression for 234 retail and restaurant firms (702 maximum observations). Panel A presents descriptive statistics on the key variables used in the regression. Model 2 regression includes only restaurant firms. Usage is the dependent variable measured as the sum of future 5-year rental commitments and scaled by total assets. z Score is Altman’s (1968) proxy for financial distress and obtained from Compustat. z Score is also measured using two dummy variables as an alternative specification in Models 3 and 5. Distress1 is equal to 1 if firms have z scores less than 2.675 indicating that these firms are more likely to face financial distress and equal to zero otherwise. Distress2 is equal to 1 if firms have z scores greater than 4.40 (75% quartile) indicating that these firms are in a strong financial position and less likely to face financial distress and equal to zero otherwise. Size is measured as the log of total assets and proxies for firm size. As an alternative specification, size is also measured as a categorical variable in Models 3 and 4. Firms with sales less than $500 million are classified as small firms and used as a base for comparison. Medium firms are equal to 1 if their sales are between $500 million and less than $1.5 billion and equal to zero otherwise. Large firms with sales greater than $1.5 billion are equal to 1 and zero otherwise. Sector is equal to 1 if firm is a restaurant firm and zero otherwise. All t statistics in parentheses are computed using heteroskedasticity robust standard errors.

p < .01. **p < .05. ***p < .10.

In Table 7, Panel A, descriptive statistics on the key variables show the mean z score of 3.31 for restaurant firms is similar to the mean score of 3.28 reported by Upneja and Dalbor (1999). Further analysis of the data (not reported here) revealed that smaller firms that make greater use of operating leases have lower z scores, whereas larger firms have larger z scores.⁵

The results in Table 7, Panel B, provide further confirmation of the findings. First, the results show that z scores do not explain operating lease usage. This finding is in contrast to the finding of Upneja and Dalbor (1999) that firms with higher z scores were less likely to use operating leases.⁶ Second, firm size is significantly negative in all the five regression indicating that operating lease usage decreases with firm size. In Models 3 and 4, large and medium firms are significantly less likely to use operating leases than small firms consistent with the finding in Model 2 using only restaurant firms. These results indicate that small restaurant firms with heavy operating lease usage will likely face greater changes in financial ratios from operating lease capitalization. Third, the findings on the sector variable indicate that restaurant firms have lower usage of operating leases than retail firms, consistent with the results in Table 5 that retail firms will likely face greater changes in the ratios from the impact of lease capitalization. Finally, the moderately significant and negative coefficient on the distress variable in Model 3 shows that firms facing financial distress (those with z scores less than the cutoff point of 2.675) have lower operating lease usage. Moreover, the results provide no indication that firms in strong financial standing (those with z scores exceeding the 75% quartile of 4.40) are less likely to use operating leases. Further analysis of the data revealed that about a dozen small and medium firms in good financial standing had very high operating lease usage. For example, Rubio’s Restaurants, a small restaurant firm, had z scores exceeding a ratio of 3 over the 3-year period (2006-2008) and an operating lease usage ratio of more than 70%. Similarly, Ark Restaurant Group and Buffalo Wild Wings also had large z scores exceeding a ratio of 5 and operating lease usage ratios around 50%. Medium-sized firms with high z scores and high usage ratios included CEC Entertainment, Panera, Chipotle, California Pizza Kitchen, and P. F. Changs. Large firms with high z scores and high usage ratios included Starbucks and Jack in the Box. These findings provide further conclusive evidence on the impact of firm size on operating lease usage suggesting that future studies on operating leases must control for firms size because lease usage will vary across sectors and within the same industry between small and large firms.

Sensitivity Analysis

Several alternative assumptions were used to test the robustness of the results in Tables 5 and 6. First, the asset to liability ratio of 75% was changed to 70% and 80% and then set equal to the value of the liability. The findings were similar to those in Tables 5 and 6 in terms of the sign, magnitude, and significance of the ratios. When total liabilities is used instead of total long-term debt (and adjusted for deferred taxes), the results on the debt-related ratios remain unchanged. Second, the interest rate used in Tables 5 and 6 was raised from 9% to 10%. The effect of increasing the interest rate is a lower median PVOL of $122 million and $353 million for restaurant and retail firms, respectively, and $257 million for the overall sample. Again, the results are similar to the main findings in Tables 5 and 6.

Third, a 10% interest rate and 15-year total remaining lease life was used to replicate the method used in previous research (Imhoff et al., 1991; Marler, 1993). This resulted in a lower median PVOL of $118 million and $335 million for restaurant and retail firms, respectively, and $246 million for the overall sample. The effect on the magnitude of changes in ratios (absolute and relative) was slightly larger for interest coverage ratios, lower for debt-related ratios, ROIC, and ROA and higher for EBIT margin. More important, the results were again similar to the main findings in Tables 5 and 6 in terms of direction, magnitude, and statistical significance. Fourth, the incremental interest rate of 9% and asset to liability ratio of 75% were allowed to vary by firm. The overall median PVOL was observed to be higher at $266 million ($131 million for restaurants and $349 million for retail firms). The results were again similar to the main findings with one exception. The evidence on the pretax margin for large restaurant firms was weaker (significant at 10% level), whereas the pretax margin for small restaurant firms was positive and insignificant. The sensitivity analysis indicates that the results of this study are robust to changes in assumptions of the constructive lease capitalization methodology.

Finally, if a multiple of 6 times rental expense is used to estimate the lease liability, then the median PVOL would rise to $327 million for the overall sample ($140 million for restaurants and $367 million for retail firms). If the multiples approach commonly used in practice represents a more accurate estimation of the true PVOL, then the estimates using the DCF approach are understated. In this case, the overall median PVOL using the DCF approach in Table 1 would be 82% of the “true” $327 million estimate ($268 million/$327 million) with a higher ratio for restaurants (91%) firms compared with retail firms (77%).

Implications for the Restaurant Industry

The results of this study show that both the restaurant and retail industries will be significantly affected by the proposed changes in the lease accounting standard that will require capitalization of all operating leases. Major implications that arise from the findings of this study include effects on debt covenants, executive compensation plans, and the lease versus buy decision.

Changes in lease accounting rules will affect management compensation policies if management performance and compensation are based on widely used profitability ratios such as EBITDA (a non–generally accepted accounting principles [GAAP] measure), EBIT, and pretax income. Management compensation will increase for measures based on EBITDA margins under the proposed rules.⁷ Executive compensation plans will be affected by the capitalization of operating leases by increasing the incentive compensation that managers will receive. Consequently, restaurant companies should reexamine their compensation plans in light of the proposed changes. One notable exception is P.F. Changs’s China Bistro, which compensates its executives based on ROIC. The company includes rent expense in its measure of income in the numerator and the PVOL in its measure of total invested capital in the denominator [(Restaurant income + rent + interest)/Total restaurant invested capital].⁸

The proposed changes will have a significant effect on leverage ratios that are used to evaluate a company’s financial performance and compliance with loan covenants or other agreements that reference those ratios. This could potentially affect the debt structure policies of restaurant firms and change the mix of debt and equity in the capital structure. The results of this study has also shown that fixed charge coverage ratios or interest coverage ratios (EBIT or EBITDA interest coverage) would significantly decrease, whereas debt-related ratios such as leverage and debt-to-equity ratios would significantly increase. Operating lease capitalization could potentially contribute to a breach of debt covenant restrictions on existing long-term loan agreements for some companies, so firms with leverage ratios closer to the limits of debt covenant violations should reexamine their debt covenants in light of the proposed changes. Failure to do so could lead lenders to impose additional financing costs in the form of higher interest rates that can restrict corporate investment and financing policies.

To avoid the possibility of violating debt covenants, managers should be proactive in anticipating the impact of the proposed changes and review their debt covenants to ensure compliance. If a breach is anticipated, strategies may include renegotiating the existing terms of the credit agreements or loans, refinancing debt, paying off existing loans to reduce existing debt levels, raising more equity, and relying less on debt financing. The proposed changes in lease accounting are not expected to affect debt ratings because credit rating firms such as Standard & Poor’s already make the necessary capitalization adjustments for leases. However, what is uncertain is whether there will be a negative market reaction to the changes in leverage once the standard is implemented. Any negative reaction can potentially lead to a downgrade in debt ratings, increase the cost of capital, and make it more difficult for firms to access the equity or debt markets.

Those companies that are fully leasing their restaurant sites are expected to face declines in fixed charge coverage ratios and higher leverage ratios as more lease debt is added to the balance sheet and higher interest expense reflected on the income statement. Whether these restaurant firms will seek to purchase the real estate and reduce the use of leasing or to continue leasing will be a critical managerial decision for many of these companies. If internal cash is used to acquire property, higher acquisition cost could slow or limit the future growth and expansion of these firms by tying up valuable cash resources. Purchase and ownership of the real estate will certainly increase assets and debt liabilities on the balance sheet. A high fixed cost base will also increase the degree of operating leverage and contribute to volatility in earnings. As such, restaurant managers should carefully weigh all the costs and benefits associated with the lease versus buy decision.

Given the high failure rate of restaurants and the recurring frequency with which restaurant companies increasingly report lease termination costs for poorly performing restaurants, modification of existing lease terms is a very likely outcome under the proposed rules. Managers will probably resort to restructuring existing leases or enter into new leases with shorter terms of 5 or 10 years with no renewal optional period, employ termination clauses and residual value guarantees of the leased property (Goodacre, 2003). The advantage of a shorter lease term over a longer lease term is that the shorter lease term has a lower PVOL when compared with a longer lease term. This also means a lower amount of asset and debt liability recorded on the balance sheet for a shorter lease term. The income statement impact will show a lower amount of interest and depreciation expense for a shorter lease term, which subsequently will result in higher reported income. In these situations, lessees would prefer shorter lease terms under the proposed rules, which would have the effect of transferring the risk from the lessee to the lessor. This means that lessors will bear a greater risk of early lease termination by lessee or failure to exercise a renewal option because of the poor performance of a restaurant or retail location (Goodacre, 2003). Consequently, lessors will incur additional costs in securing new lessees or in disposing of the assets and therefore demand longer lease terms and higher rental compensation or make greater use of termination penalties to compensate for the additional risk involved (Ringer & Unerman, 2000).

Summary and Conclusions

This study investigated the impact of operating lease capitalization on financial statements and financial ratios for firms in the restaurant and retail industries from 2006 to 2008. The results of this study revealed that the magnitude and direction of the impact will be significant for both industry sectors. However, significant absolute and relative differences were also found across industries and within the sectors. If all operating leases are capitalized, all 11 financial ratios related to interest coverage, leverage, and profitability will change significantly and dramatically for both industry sectors. When the results are analyzed by sector and firm size, the findings show that retail firms will be affected by operating lease capitalization to a greater extent than restaurant firms. Within the restaurant industry, smaller firms will face the prospects of significantly higher debt-related ratios than medium or large restaurant firms. In contrast, in the retail sector, medium retail firms will see greater changes in their financial ratios from lease capitalization. This study reconciled previously conflicting results to show that firm size is an important factor in explaining operating lease usage with small firms more likely to use operating leases than large firms. In addition, incrementally new descriptive evidence was provided on retail and restaurant store and rental characteristics.

It will be critical for restaurant companies and managers to immediately assess the impact of the proposed changes on their financial statements and plan for operating under the proposed new rules. If there is a negative impact of the proposed rules, managers can be expected to employ a number of strategies, including among others, shorter rental terms, paying off existing debt, and renegotiating rental terms. Companies that plan proactively in assessing the impact of the proposed leasing rules will not only minimize the added administrative and financial costs of compliance but also stand to gain a competitive advantage. Despite its potential drawbacks for many restaurant companies, the new standard is expected to provide investors and financial statement users with more precise information to assess and value the debt obligations of firms instead of requiring investors to make estimations under the existing standard that is currently imprecise. Incrementally new and valuable information will also enable external users of financial statements to more accurately assess the risks undertaken by the firm.

Limitations of the Research

A number of assumptions were used in this study to capitalize operating leases. These assumptions will differ in practice and across firms, including the incremental interest rates used to capital operating leases, the frequency and periods in which cash flows occur, differences in the asset to liability ratios, and the use of a single effective tax rate for all firms instead of firm-specific effective income tax rates or marginal tax rates. The definitions of financial ratios will also differ in practice across firms, which can result in differences in the amounts capitalized on financial statements. Furthermore, lease contracts will also differ substantially in their features such as purchase or renewal options, residual value guarantees, and length of lease terms. This information is not captured in this study because firms are not required to disclose such information. The nondisclosure and exclusion of these lease features renders the estimations in this study subject to measurement error. To the extent that the proposed rules require the inclusion of contingent rent in lease capitalization, the estimates in this study are also understated.

Future Research

This study will be the first stage of an ongoing research to provide a benchmark for future comparison. The next stage of this research will be to use firm lease data from 2009 to 2010 to examine the magnitude of leasing activity and changes in firm behavior 2 years prior to implementation of the standard. The final stage of this research will be conducted after (ex post) the implementation of the standard in 2011 and thereafter to observe its effect on firm behavior, financial strategies employed by firms to mitigate the impact of the new standard, and to compare the results with the present study. Future research should also investigate the impact of the standard after implementation on capital structure changes and various firm risk and return measures, including equity risk and stock prices.

Footnotes

Appendix A

Appendix B

Appendix C

Notes

Amrik Singh, PhD (e-mail: asingh22@du.edu), is an assistant professor at the Fritz Knoebel School of Hospitality Management, University of Denver, Colorado.

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