The accuracy of valuation methods in predicting the selling price of small firms.

There are many reasons why it is important to estimate the selling price of a small business, yet the literature reports no studies that attempt to verify the accuracy of any valuation technique in terms of its ability to accurately predict how much the sale of a small business will yield. Therefore,

There are a number of situations in which it is necessary to determine the likely selling price of a small business. For example, the buyers of small businesses need a reliable method for determining whether the asking price for a firm is reasonable, as well as an objective basis for establishing an offer price for the business. Similarly, sellers of small businesses need a rational basis for establishing the asking price for their business and an objective basis for considering offers made by potential buyers.

Owners and investors need to know the market value of small businesses to determine the ownership percentage that is appropriate for an equity investment. Also, bankers and lenders are interested in the market value of small firms to help assess the risk involved in extending credit to a small business.

Owners may also be interested in the market value of their small business when considering whether to "harvest" their value in the firm or for estate planning purposes. In addition, market value can provide an important performance measure for management and for employee benefit planning purposes.

It is also necessary to know the market value of a firm for the purchase of key-person insurance and for the development of buy/sell agreements involving a small business. In addition, market value, especially in common law states, is usually an important issue when settling matrimonial or property disputes involving a small business owner.

In today's litigious society, the market value of a small business might be important for reaching an equitable settlement of damage cases. Also, the formation of an Employee Stock Ownership Plan for a small business requires the establishment of the market value of the firm on an annual basis.

These and other reasons indicate a need to identify reliable techniques for calculating the market value of a small business. For the purposes of this article, market value is considered to be the actual selling price of a small business.

Small Business Valuation Theory

Given the need to identify reliable techniques for calculating the value of small businesses, the literature was reviewed to determine whether one or more techniques might be better than the others. Pricer, Vos, and Dixon identify and discuss twelve approaches to business valuation (Pricer, Vos, and Dixon 1987). The first method, book value, is simply the assets of a small business minus its liabilities. The strength of this method, according to the authors, is that information is readily available for valuation calculation, and assets represent a store of business value that may be used for generating future income. The disadvantage of book value is that it does not take into consideration the varying earnings potential of assets or recognize the fact that accounting for assets and for depreciation varies widely among firms.

Another technique described was that of adjusted book value. This method adjusts the book value for obvious discrepancies between it and the market value of assets, also reducing intangible assets to zero. While the adjustments do take into consideration obvious errors in asset valuation, the technique does not allow for fine adjustments. In addition, adjusted book value has the same weaknesses as book value as it doesn't take into consideration the different income generation potential of assets or the varying policies applied to the valuation and depreciation of assets by small businesses.

The liquidation valuation technique is described as the amount of money that could be realized from a "quick sale" of the business. Each asset is reviewed and an estimate made of the amount of money it would sell for in a forced sale situation. The advantage to this method is that it provides a minimum value for a small business - what the business should be worth trader any circumstances. However, as most businesses are not sold quickly, this technique is not of much use when valuing an ongoing small business. Also, the values placed on each asset are only estimates based on a quick review of the balance sheet.

The Corporate Investment Business Broker's Method (CIBB) is a technique that adds the appraised or book value of real estate, equipment, furniture and fixtures, and leasehold improvements. To this is added the cost of inventory, current net profit, and current year owner income and benefits. The theory behind this technique is that small businesses have assets, and this value is reflected in their book value. In addition, for a typical small business, the method assumes that it will take about one year for the customers of the firm to change their commitment from one owner to another. The weakness of the method is that it treats all small businesses the same, whether or not they have growth and increasing profit potential.

Another valuation technique identified is that of replacement value. With this method, the replacement cost of the assets of a small business are added to calculate the firm value. This is a very good approach to use for asset insurance value purposes, and it also provides the cost of replicating assets of a business as an alternative for a potential buyer of that business. The weakness in the technique is that it is not related to the earnings potential of assets or to the market in which they will be used.

The capitalization of earnings method takes the current annual income of the small business being valued and divides it by the required percentage rate of return on the investment in the business, minus the growth rate of the firm. This is a standard valuation technique that is theoretically sound. It takes into consideration both the required return and the growth potential of the business. The weakness in the technique is that it assumes that the growth rate will continue at the same level forever and that the business will operate to infinity.

The holding period valuation is a technique that takes a multiple of earnings from publicly traded companies in the same industry and applies this to projected earnings for the year the current owner(s) intends to exit the firm. This amount is discounted using the required rate of return on investment by the owner and is added to the discounted earnings for each of the years the owner plans to continue with the investment in the firm. This technique provides a good value estimate for owners who know precisely when they want to realize their investment in the business and leave their firms. However, most owners don't know precisely when they will exit their firms, and it is also very difficult to find a public market multiple that realistically applies to closely-held small businesses.

The traditional valuation method applies a market multiple from publicly-traded firms to the projected earnings of a small business to determine value. The strength of this technique is that it relies on a market-determined multiple for earnings, bringing the valuation closer to reality. The problem with the technique is that it is very difficult to find publicly-traded companies that are similar to closely-held small businesses and both high and low multiples can be found and supported for any particular valuation. These techniques form the basis for this study because, surprisingly, there is no information available about which of these methods, or other methods, is the best predictor of the actual small business selling price. In a more general sense, valuation techniques for small businesses fall into three classes: 1) asset valuations; 2) earnings valuations; and 3) cash flow valuations (Stevenson, Roberts, and Grousbeck 1989).

The asset value argument contends that a business's success is reflected in its ability to accumulate assets (Eber 1984). Because it is the assets of a business that allow it to generate income, the assets reflect the true value of a firm. Using this same reasoning, Desmond and Kelly (1980) argue that book value is a good measure of the market value of small businesses. They suggest that since assets are used to generate income, their value should be reduced as their useful life is shortened and that net book value provides a sound basis for estimating firm value.

In contrast, many experts contend that book value is not a good measure of the market value of a small business and argue instead that earnings, either current or projected, are the only real source of business value (Reily 1994; LeClair 1990). They argue that a business with high earnings and low asset value is worth more than a business with low earnings and high asset value. This position is based on the belief that value is derived from the earnings stream generated by a business. Even if this is correct, it is still open to broad interpretation since there are many different methods used to calculate the market value of a firm based on income generation.

For example, some writers argue that an indirect earnings measure, gross sales, provides a sound basis for measuring business value (Desmond and Kelly 1988). Gross sales are thought to provide the best basis for estimating firm value because they indicate the market position that management can use to generate net income. Since such variables as the amount of debt used and expense decisions will have an impact on net profit, it is necessary to use gross sales to fully estimate the potential income of a particular business. This approach to valuation uses some percentage of gross sales as its basis, yet there is no particular agreement about what percentage is actually appropriate.

Another earnings-based approach to valuation is to discount forecasted future earnings back to present value (Ling 1992; Vos 1992; Feinberg 1988). These writers argue that a business represents a mechanism for generating income and that earnings potential is the only way to accurately calculate value. Three-year projected earnings should be used to be certain that expected growth is included in the value determination (Fairchild and Fairchild 1989). Opinions differ about the appropriate discount rate to be used for calculating the present value of future earnings. For example, at times a relatively low discount rate is warranted (Zukin 1993), while at other times a higher rate is recommended (Desmond and Kelley 1988). There are similar disagreements about the appropriate multiple of earnings to use. An article in The Business Owner (1985) recommended that a multiple of 10 times earnings be used to establish future value, while an article in the Small Business Reports (1986) recommended a multiple of five for small firms.

Cash flow valuations are appropriate in circumstances in which the entrepreneur is concerned with a cash-on-cash return on investment (Michel and Shaked 1990). However, as Stevenson, Roberts, and Grousbeck (1989) point out, the time value of money is also important, and timing of cash flow returns has tax implications for the investor. Thus the return to the investor may be a function of the amount and timing of cash flow, terminal value of the firm (sales value), and tax benefits. Still, a different cash flow value is suggested which favors a multiple of cash flow, rather than assets or earnings, as the basis for determining firm value (Thornton 1984).

The literature presents these and other methods for determining firm value (Boykin and Gray 1994; Lippitt and Mastracchio 1993; Vos 1992; Burns and Walker 1991). Methods are usually presented with an explanation of their theoretical soundness and presumed usefulness in practice. For example, the CIBB method of valuation was found to be used by business brokers, suggesting its validity. Similarly, net book value is easy to calculate and understand by both buyers and sellers, and therefore it seemed likely to be a good predictor of value. However, there is no empirical evidence available to give support to the use of any particular valuation method as an estimate of the selling price of a small business. This study seeks to fill this void as it estimates value using twelve standard methods from the literature and then compares these valuations with the subsequent actual selling price of small firms. The study also examines the ability of different techniques to determine whether one or more are better than the others. Pre-sale accounting data were collected for small businesses that had been recently sold, and by comparing the predicted value with the actual selling price, it is possible to determine which method or methods provide the most accurate valuation. Given the limited number of firms involved, conclusions are limited to the present data and methods used for comparison, and no generalizations are warranted without further study. Table 1 provides brief descriptions of the twelve different methods of business valuation that were analyzed for this study.

Methods

A sample of 250 firms which were sold in the previous two years were selected from Dane County, Wisconsin. Only firms with complete financial data at the time of sale were used. This limited the sample to 49 of the original 250 firms. The 49 firms consisted of 23 retailers, 7 manufacturers, 17 service firms, and 2 wholesalers. The sample firms had prior year's sales between zero and $3.5 million. All but seven firms had less than $1.0 million in the prior year's sales. In terms of full-time employees, the sample ranged from 1 to 59, with 39 firms having 15 or fewer employees. The sample of wholesale firms (n = 2) was not considered large enough for perform statistical testing and as a result were dropped from the data set, reducing the sample size to 47.

To estimate the accuracy of a particular method's ability to predict selling price, a measure of the variance in predicted versus the actual selling price was calculated. The percent of variance (VAR) is defined as:

VAR = Actual Selling Price - Predicted Selling Price/Actual Selling Price x 100

As there was no interest in assessing which methods over- or under-predicted sales price, the absolute value of the VAR was used in the analysis. The percent of variance of all subjects on a particular method was then summed and averaged. They were then compared to other methods' average percent of variance.

A series of paired-t tests were used to assess which methods were statistically different from each other in the aggregate sample. A one-factor ANOVA with uneven sample sizes model, using the industry classification as the independent variable and the percent of variance as the dependent variable, was performed on each of the twelve methods separately to determine whether there was an industry effect.

[TABULAR DATA FOR TABLE 2 OMITTED]

Table 3

Descriptive Statistics for Percent of Variation of
Each Valuation Method

Method       Mean      Standard      Minimum     Maximum       n
                      Deviation

NBV         67.97       38.49         9.66        153.52      47
CIBB        68.78       97.12         0.89        381.49      47
HMCE        87.79       77.47         6.86        404.85      47
LMCE        92.25       85.72         0.30        443.68      47
EBIT5      115.16      120.38        15.67        606.78      47
GS40       195.01      391.53         1.73       1630.17      47
DISC5      196.10      357.23         8.59       1530.15      47
EBIT10     228.03      284.92         2.07       1313.57      47
HMFE       241.74      355.97        27.08       1906.38      47
LMFE       259.29      387.50        21.47       2060.72      47
GS75       386.15      762.70         7.51       3144.06      47
DISC10     433.35      738.92        15.79       3160.29      47

Results

Descriptive

Table 2 presents the means, standard deviations, and correlation coefficients for the actual selling price and the estimated selling price based on the twelve different methods.

Many of the methods are highly correlated with each other. This is expected since many are merely scalar multiples of others, and they are all based on some balance sheet or income statement data. Of primary interest is the correlation of actual selling price (PRICE) with the estimated sales price of the 12 methods. The CIBB, HMCE, and LMCE methods were [TABULAR DATA FOR TABLE 4 OMITTED] the only ones to have a statistically significant correlation. NBV was negatively correlated with PRICE (not significantly); this is not surprising since NBV is a measure of the owner's equity in the firm. In a number of cases, the NBV was negative, which is not uncommon in small firms.

Table 3 presents the descriptive statistics for the percent of variance variables associated with the different methods. These data are in aggregate, across all industries. NBV had the lowest mean and standard deviation (67.97 percent, 38.49 percent), followed by CIBB (68.78 percent, 97.12 percent). DISC10 had the largest mean and standard deviation of percent of variation (433.35 percent, 738.92 percent).

Table 4 presents the descriptive statistics for the percent of variation variables by industry classification. In the retail industry, HMCE had the lowest mean percent of variation (75.05 percent) followed by NBV (78.67 percent), and LMCE (79.15 percent). DISC10 had the largest mean (433.35 percent). In the service industry, the lowest mean was NBV (60.58 percent), followed by CIBB (62.47 percent), and HMCE (111.92 percent). The largest mean percent of variation belonged to LMFE (361.27 percent). Among the manufacturing companies, the smallest mean was CIBB (20.17 percent), followed by NBV (50.77 percent), and EBIT5 (65.30 percent).

Statistical Hypothesis Testing, The Aggregate Sample

Figure 1 plots the methods' mean percents of variation on the x-axis and the standard deviations on the y-axis. It is of interest to analyze those methods which have means less than 150 percent (those located in the lower left corner of the plot). The five methods tested were the CIBB, NBV, LMCE, HMCE, and EBIT5. A paired-t test was used to test the null hypothesis that the mean percent of variance values obtained were equal to each other.

Table 5 reflects the results from the paired-t tests of the aggregate data. Descriptively, NBV (67.97 percent) was the best (smallest mean percent of variance) at estimating sale price, followed by CIBB (68.78 percent), HMCE (87.79 percent), LMCE (92.25 percent), and EBIT5 (115.16 percent). The mean for NBV is statistically different from the means of HMCE and CIBB but not from the means for LMCE or EBIT5. The mean for EBIT5 is also significantly different from the means for LMCE, HMCE, and CIBB. The mean for LMCE is statistically different from the mean for HMCE but not from CIBB. Finally, the mean for HMCE is not statistically different from the mean for CIBB.

Table 5

Results from Paired - t Test of Aggregate Data
Paired - t Test Statistics (n = 47)

VAR a/b                  t-value     df      2-tail Sig.

LMCE with HMCE            2.88       46        .006(**)
LMCE with EBIT5          -3.76       46        .000)(**)
LMCE with CIBB            1.62       46        .112
LMCE with NBV            -1.74       46        .089(*)
HMCE with EBIT5          -3.61       46        .001(**)
HMCE with CIBB            1.33       46        .189
HMCE with NBV            -1.54       46        .132
EBIT5 with CIBB           2.81       46        .007(**)
EBIT5 with NBV           -2.54       46        .015(**)
CIBB with NBV            -0.05       46        .958

* p = 0.10
** p = 0.05

Statistical Hypothesis Testing for Industry Effect

A one-factor ANOVA with different sample sizes model was used to test for an industry effect in valuation methods. The industry classification was the independent variable, and the percent of variation was the dependent variable for each of the 12 methods. From Table 6 it is seen that no statistically significant (p = 0.10) industry effect was observed in any of the 12 methods.

Discussion

Except for retail firms, the Corporate Investment Brokers Business method (CIBB) was, on average, consistently among the best predictors of firm sale price. CIBB was also highly correlated with actual sale price (.58, p = 0.05). This method was the only technique tested that included a combination of both asset and earnings data to arrive at a predicted selling price. Where stock is sold at public market, the earnings support for each share is probably an appropriate indicator of value for small businesses. It appears that assets are a store of value and should be included, along with earnings, in determining market value.

Table 6

Results of One-Factor ANOVA(*)

Method             F-score            Significance of F

HMFE                 1.383                    0.261
LMFE                 1.408                    0.255
LMCE                 1.371                    0.264
HMCE                 1.317                    0.278
EBIT5                1.626                    0.208
EBIT10               1.502                    0.234
DISC5                1.267                    0.292
DISC10               1.312                    0.280
CIBB                 1.398                    0.258
GS75                 0.680                    0.512
GS40                 0.571                    0.569
NBV                  1.983                    0.150

* n = 47, df =46 for all tests

The net book value (NBV) method was one of the best predictors in aggregate and across all industries. The fact that smaller firms don't have well-established market positions might partially explain why they would sell for a price similar to their book value. Interestingly, NBV had a weak, statistically insignificant correlation coefficient with sale price (unlike CIBB). Figure 2 plots sale price against the NBV method.

There are several aspects of the relationship between NBV, industry, and selling price which are quite interesting. First, for firms with a positive book value (n = 33), the correlation coefficient between NBV and selling price is 0.40, which is statistically significant at p = .02. Also, for those firms with a book value of 0 or less, most are retailing firms (57 percent, n = 8).

The multiples of the current earnings methods of valuation (LMCE, HMCE) also showed promise of being more accurate predictors than most in the study, particularly in retail industries. Small retail firms may not possess large asset bases, and their value may be in their ability to reach a profitable market through location and a unique product offering, resulting in current earnings.

Sales valuations (GS40, GS75) did not provide good estimates of business selling prices. This may be because revenue does not necessarily measure the earnings or operating profit of a business and therefore is not useful for estimating a firm's market value.

The estimates of value based on future earnings (LMFE, HMFE) provide valuations based on future earnings using both high and low discount rates. It does not appear that discounted future earnings is an accurate predictor of firm selling price. This may be due to the difficulty of accurately estimating future revenue, particularly in smaller enterprises where sales may be highly uncertain.

The multiple of earnings before interest and tax earnings model (EBIT5, EBIT10) did not provide a good estimate of actual selling price. Because levels of debt and tax policy decisions directly effect net income, earnings before interest and taxes provides a realistic view of the actual earnings ability of a given firm. This did not appear in the sales price estimate, and the error may be in the choice of multiple.

The multiples of cash flow method was also a generally poor predictor of actual selling price of firms; the average percent of variance for all types of firms shows that cash flow estimates rank poorly. However, this may be because the actual cash flow of a business depends on its present capital structure. Because new ownership may bring a new capital structure, current capital structure may not be relevant the selling price of a business.

The findings of the study indicate that the CIBB and NBV methods are better predictors of the selling price than other traditional methods. The results also highlight the importance of earnings in establishing the market value of a business.

Limitations, Contributions, and Future Work

This study is exploratory in nature and is not intended as a general evaluation of different valuation methods. It entails many limitations which prevent conclusions beyond the data presented here. First, the number of firms included is small (n = 47), and access to data limited how many different types of firms and valuation methods could be studied. Second, the firms are from a limited geographic area of the United States. Market conditions and prevailing sales practices may vary in other regions. Third, the use of selling price as the standard of comparison ignores a host of adjustments that might be made, such as amount of owner financing, the interest charged, and indirect or nonfinancial perquisites included in the sale.

This research contributes to the study of business valuation by empirically testing the sale price of a business against its theoretical value. It is understood that many variables enter the equation of sale price, but this research suggests that some valuation methods are a better starting point than others at capturing the effects of all possible variables.

Future research is needed to confirm the findings of this study using a larger and more geographically diverse sample of firms. A larger sample will hopefully include more wholesale firms, and allow sample sizes large enough to analyze firms and industries by sales level, for example. Also, the results of future research might be strengthened by calculating the present value of the purchase price including the value of non-compete agreements and previous owner consulting agreements.

Conclusion

The results of this study show that while no single valuation method is superior for estimating the selling price of a particular business, at least for the firms included here, some methods are clearly better than others. In addition, the results suggest that it may be possible to identify a single valuation method which is a reasonable predictor of the likely selling price of a business.

While future research is needed with a larger sample of firms from diverse geographic areas before the findings of this study can be generalized to the entire small business population, this study demonstrates the ability to measure the actual selling price against common valuation technique predictions. Additional research building on this study should lead to increasingly accurate methods for calculating the predicted selling prices of smaller firms. As a result, educators and consultants should be able to provide business sellers and buyers with a reliable estimate of the value of small businesses, thus facilitating the smooth transition of ownership.

Table 1

Description of Valuation Methods

1. Corporate Investment Business Brokers (CIBB)

Book value of assets except inventory; plus inventory at cost; plus earnings' before interest and tax; plus owners' compensation. Owners' compensation includes salary, health and life insurance premiums, auto, rent payments paid on dwelling, and depreciation.

2. Net Book Value (NBV)

Owners' equity of the firm.

3. Gross Sales #1 (G4V)

Forty percent times gross sales.

4. Gross Sales #2 (G75V) Seventy five percent times gross sales.

5. Future Earnings #1 (three years using historical growth rate) (LMFE)

Discount rate of 15 percent for manufacturing and 30 percent for retail, service and wholesale using a multiple often times net earnings.

6. Future Earnings #2 (three years using historical growth rate) (HMFE)

Discount rate of 20 percent for manufacturing; 40 percent for retail, service, and wholesale using a multiple of ten times net earnings.

7. Earnings Before Interest and Taxes #1 (EBIT5)

EBIT at a multiple of five.

8. Earnings Before Interest and Taxes #2 (EBIT10)

EBIT at a multiple of ten.

9. Current Net Earnings at a Multiple of 5 #1 (LMCE)

A discount rate of 15 percent for manufacturing and 30 percent for retail, service, and wholesale.

10. Current Earnings at a Multiple of 5 #2 (HMCE)

A discount rate of 20 percent for manufacturing and 40 percent for retail service, and wholesale.

11. Discretionary Cash Flow (return to owners) #1 (DISC5)

At a multiple of five.

12. Discretionary Cash Flow (return to owners) #2 (DISC10)

At a multiple of ten.

References

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Dr. Pricer is professor of management at The Enterprise Center, University of Wisconsin-Madison. His research interests include failure of small businesses, organizational typologies, and growth of small businesses.

Mr. Johnson is a doctoral student of management. His research interests include organizational typologies, survival strategies, and failure of small businesses.