5 
 
 3 COPY 2 
 
 FACULTY WORKING 
 PAPER NO. 1058 
 
 Cash Flow 
 What Is? 
 
 If It's Not the Bottom Line, 
 
 James A. Gentry 
 Paul Newboid 
 David T. Whitford 
 
 
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 College of Commerce and Business Administration 
 Bureau of Economic and Business Research 
 University of Illinois, Urbana-Champaign 
 
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BEBR 
 
 FACULTY WORKING PAPER NO. 1058 
 College of Commerce and Business Administration 
 University of Illinois at Urbana-Champaign 
 Julv 1984 
 
 Cash Flow — If It's Not The Bottom 
 Line, What Is? 
 
 James A. Gentry, Professor 
 Department of Finance 
 
 Paul Newbold, Professor 
 Department of Economics 
 
 David T. Whitford, Assistant Professor 
 Department of Finance 
 
Digitized by the Internet Archive 
 
 in 2011 with funding from 
 
 University of Illinois Urbana-Champaign 
 
 http://www.archive.org/details/cashflowifitsnot1058gent 
 
ABSTRACT 
 
 A cash based funds flow model is used to discriminate between 
 failed and nonf ailed companies. We discovered cash flow from opera- 
 tions does not provide a reliable signal for classifying companies, 
 which supports recent findings of Casey and Bartczak. Our analysis 
 shows funds flow components or financial ratios provide dependable 
 signals for classifying companies. Finally, we found a combination of 
 funds flow measures and ratios with particular emphasis on dividends, 
 investment and receivables supply management reliable information for 
 judging the condition of a company's financial health. 
 
CASH FLOW— IF IT'S NOT THE BOTTOM LINE, WHAT IS? 
 
 Scientists, astronauts, navigators, meterologists and members of 
 the corporate management team have a common goal of continuously 
 searching for signals that will aid them in predicting what lies ahead. 
 A primary concern of the above professionals is the reliability of the 
 signals being received. For example, corporate management, financial 
 executives, accountants, credit analysts and financial analysts have 
 held the view that past cash flow trends provide reliable signals for 
 predicting a firm's future success or failure. In what may have been a 
 surprising finding, Casey and Bartczak (CB) [2] reported cash flow from 
 operations (CFO) was not a reliable measure for predicting corporate 
 bankruptcy. CB's research found financial ratios provided superior 
 information to CFO for explaining financial failure. They stated there 
 are many other factors that may signal failure, such as company indebt- 
 edness, lack of access to financial markets, low salability of capital 
 assets and a low reservoir of liquid assets. 
 
 In studying the financial explanations of bankruptcy, we selected a 
 broader base of cash flow components than CB. Although our research 
 findings are not directly comparable to CB's due to differences in 
 objectives and experimental design, our eclectic cash flow measures 
 provide unique insights into the prediction of financial failure. 
 
 Cash Based Flows 
 
 We chose a cash based funds flow model to explain corporate failure 
 because integrated cash flow information reflects the outcome of major 
 financial decisions of management. Cash flows are considered to be 
 more sensitive to changes in short term trends than information based 
 on accrual accounting assumptions. Finally, leading valuation theories 
 are based on discounted future cash flows. 
 
-2- 
 
 Previous bankruptcy studies have used financial ratios to predict 
 financial failure, but the theoretical rationale for selecting specific 
 ratios has not been explicitly developed. This ad hoc search process 
 for selecting ratios has resulted in each study finding a unique set of 
 ratios for predicting financial failure. To offset the criticism raised 
 concerning these ad hoc procedures, we selected cash flow components 
 that utilize financial information available in a firm's balance sheets 
 and income statements. Our concern for cash flow measures caused us to 
 decompose cash based accounting information into functionally oriented 
 components. In contrast, CB were only interested in the classification 
 ability of CFO and they utilized the traditional working capital based 
 funds flow model to calculate the CFO measure. 
 
 THE MODEL 
 Rationale 
 
 In an accounting context, cash inflows equal cash outflows. The 
 level and speed of the cash flows reflect managements' operating, 
 investment and financing decisions. The distributions of the com- 
 ponents generating cash inflows and outflows are signals that reflect 
 the resource allocation decisions of management. The trends of the 
 changes in cash inflow and outflow components provide measures for 
 discriminating between financially successful and financially failing 
 firms. 
 
 Components 
 
 The model we use to identify funds flow measures was developed by 
 Erich Kelfert [4], After extensive use of Kelfert's model, we redesigned 
 
-3- 
 
 it to have eight major components. The eight net funds flow components 
 are operations (NOFF), working capital (NWCFF), financial (NFFF), fixed 
 coverage expenses, i.e., interest and lease payments (FCE), capital 
 expenditures (NIFF), dividends (DIV), other asset and liability flows 
 (NOTHER) and the change in cash and marketable securities (CC). The 
 interrelationship among the components is quite complex. Excepting 
 changes in cash and marketable securities, a source (S) would be a 
 positive number and a use (U) would be negative. As a first cut, the 
 following equation presents a formulation of the cash based funds flow 
 model and the most likely source/use classification of each component 
 for a financially healthy firm. 
 
 NOFF + NWCFF + NFFF + FCE + NIFF + DIV + NOTHER - CC = 
 + - + ---- + 
 (S) (U) (S) (U) (U) (U) (U) (U) 
 
 The accounting convention underlying the funds statement results in 
 total net inflow of funds (TNIF) being equal to the absolute value of 
 total net outflow of funds (TNOF). We have simplified the notation by 
 substituting the expression total net cash flow (TNCF) for TNIF and 
 TNOF. Thus by dividing each funds flow component by TNCF, one can 
 determine the percentage each component contributes to the total. 
 
 Example 
 
 An example that compares Deere & Company to Massey-Ferguson (MF) 
 illustrates how the trends of funds flow components aid in determining 
 if a company is financially healthy or weak. Performance trends for 
 the period 1978-1982 of the eight funds flow components are presented 
 in Exhibit 1. 
 
-4- 
 
 The trend of the net operating funds flow components are located 
 in the upper left hand corner of Exhibit 1. The graphic presentation 
 shows that approximately 80% to 90% of Deere 's total net inflow came 
 from operations in three years and only 45% to 55% was generated in the 
 other two years. Although Deere' s operating inflow component was rela- 
 tively erratic, its level was always markedly greater than Massey 
 Ferguson's. Massey's operating flows were 62% of total inf lows in 1979 
 in contrast to being -28% of total outflows in 1982. Net outflows are 
 shown as negative values in Exhibit 1. The trend of the net operating 
 flows was declining for both companies, but is is apparent that Deere, 
 the financially stronger company, received a significantly higher per- 
 cent of their inflows from operations. 
 
 Frequently the largest percentage of a firm's total outflows go to 
 capital investment. However, Exhibit 1 shows the percentage of Deere 's 
 total net outflows going to investment declined from -47% in 1979 to -12% 
 in 1982. For Massey Ferguson the percentage of total outflow going to 
 investment dropped from -24% in 1978 to approximately zero in 1980 and 
 remained at that level through 1982. Graphically, Massey's decline in 
 investment can be related to the shortage of operating inflows 
 available for investment. The decrease in investment at Deere was also 
 related to decline in operating inflows. 
 
 The interdependence among the cash flow components is most evident 
 in the net financing flow component (NFFF), which measures the increase 
 or decrease in total debt and common stock. The path of the net 
 financing flows for Deere in Exhibit 1 reflects an offset to the pat- 
 tern of operating inflows. When net operating flows declined at Deere, 
 
-5- 
 
 the management increased outside financing in order to maintain its on- 
 going operations and dividends. Exhibit 1 highlights Massey's heavy 
 commitment to outside financing in 1979-1980 and a dramatic change in 
 1981. 
 
 The net working capital path has a unique significance for Deere 
 and Massey Ferguson. Although net operating inflows and net investment 
 outflows were declining as a percentage of the total, net working capi- 
 tal at Deere ranged from -15% to -30% of total net outflow in three of 
 the five years. In 1979 it was a small outflow and in 1981 a small 
 inflow . In contrast, at Massey Ferguson net working capital was a 
 major inflow in three of the five years. By disaggregating the five 
 components of working capital a better understanding of the funds flow 
 picture emerges. Exhibit 2 presents the five components of net working 
 capital. Short-term borrowing is included in Exhibit 2, but by defini- 
 tion it is a financing flow. In 1981 when Massey's fixed coverage 
 expenses soared and the short-term borrowing had to be repaid, manage- 
 ment reduced inventory and receivables and they respectively composed 
 71% and 5% of total net inflows. In 1982 receivables composed 66% of 
 total net inflows and inventories 28%. In comparison the change in 
 receivables at Deere were a primary net outflow in each year except 
 1979 and the change in inventories were a small inflow in three of the 
 five years. The key observation is that receivables and inventories 
 were major inflows for Massey when the financial crisis hit. In 
 contrast Deere 's receivables required a major outflow of funds in four 
 of the five years. 
 
-b- 
 
 Exhibit 1 shows dividends at Deere represented between -9% and -16% 
 of the total outflow of funds. In contrast, the dividend outflow as 
 a percentage of the total at Massey ranged from -1% to -9% during the 
 period, which was significantly smaller than the dividend outflow at 
 Deere. Massey was paying dividends to the Canadian government for 
 external financing received throughout the period. 
 
 The percentage of total outflow needed to cover fixed financial 
 obligations highlights a major difference between Deere and Massey 
 Ferguson. The largest outflow of funds for Massey was to meet their 
 fixed coverage expenditures. Exhibit 1 shows fixed coverage ranged 
 from -50% to -88% of the total outflow of funds. Fixed coverage expen- 
 ditures at Deere ranged from -15% in 1979 to about -30% in 1981. 
 
 Research Studv 
 
 Our analysis uses twelve funds flow measures to classify failed 
 and nonfailed companies. We substituted the five working capital 
 components for the single net working capital component, omitted the 
 component CC/TNF to avoid a statistical problem of overidentif ication 
 and added a size measure, total net flows as a percentage of total 
 assets, (TNF/TA). The analyses uses these twelve funds flow components 
 to compare the performance of 33 financially healthy companies to 33 
 bankrupt firms for a period up to three years before failure. The 
 failed companies were selected from the 1981 Standard and Poor's 
 COMPUSTAT Annual Industrial Research File . Initially there were 114 
 failed companies for the period 1970-1981, but only 33 of these failed 
 companies had complete financial data required for this study. Each 
 
-7- 
 
 failed company was matched with a nonfailed company in the same in- 
 dustry and approximately the same size in both assets and sales. Our 
 analysis examined the results for periods of one, two, and three years 
 before failures and an average of the three years. We are reporting 
 the results of one year before failure and the mean of the three years. 
 
 Findings 
 
 The mean and deviation of each cash flow ratio for the 33 failed 
 and nonfailed companies are reported in Exhibit 3. A brief review of 
 the data indicates there is generally a marked difference between the 
 means of the bankrupt companies and the financially nealthy companies. 
 For example using the one year before failure data, the means of the 
 operating inflows are 55.6% of total inflow for the nonfailed companies 
 and 16.3% for the failed companies; the means of the total outflow 
 going to investment are -36.7% and -16.3%, respectively; dividends are 
 -9.2% and -1.8% of the outflow, respectively; and receivables are -16.9% 
 of total ou t f 1 ow for the nonfailed companies and 10.0% of total inflow 
 for the bankrupt companies. The standard deviations are substantially 
 larger for the funds flow components of the failed companies. It is 
 not uncommon, especially among the working capital components, for the 
 mean of the failed companies to be an inflow and the mean of the non- 
 failed to be an outflow. 
 
 A conditional probability model called probit generates coef- 
 ficients from the funds flow components and uses them to predict the 
 probability of failure or nonfailure of the 66 companies. The classi- 
 fication results are reported in Exhibit 4. They show 79% of the failed 
 
companies are classified correctly using data that are either one year 
 before failure or a mean of three years before failure. The model 
 classified 88% of the financially healthy companies correctly using 
 data one year before failure and 79% with the three year average. 
 
 The probit analysis calculates the weight each of these funds flow 
 component contributes to the overall prediction of failure or non- 
 failure. The probit coefficients are similar to the coefficients that 
 compose the Z score developed by Altman [l] and they are reported in 
 Exhibit 5. Using the one year before failure data, we discovered the 
 investment, dividend and receivables components were statistically 
 significant at the 5% level of confidence. Figure 1 provides the 
 distribution of these three funds flow components. The distribution 
 of the percentage of total outflow going to capital investment reveals 
 that financially healthy companies invest a substantially higher per- 
 centage of funds in plant and equipment than the firms that failed. 
 The economic rationale underlying this finding makes it intuitively 
 appealing. 
 
 The distribution of the outflow of funds to dividends are in Figure 
 1 and they are left skewed. For the financially healthy companies the 
 average dividend composed -9.2% of the total outflow and ranged from 
 to -40% with six of the companies paying no dividends. The dividend 
 component for the failed companies ranged between and -25%, and on 
 average was -1.8% of total outflow with 23 of the companies not paying 
 dividends. In general, failing firms tend to experience a shortfall of 
 inflows from operations, thereby causing a reduction in dividend 
 payments. 
 
-9- 
 
 When classifying the performance of accounts receivables, Figure 1 
 shows the financially healthy companies were investing in receivables 
 while the bankrupt firms were reducing the level of receivables in 
 order to generate cash inflows. On average approximately -17% of the 
 outflow went to finance receivables for the nonf ailed firms, while 10% 
 of total cash inflow for failed companies came from receivables. The 
 cash flows related to receivables are vastly different between the 
 financially healthy and failed firms. 
 
 Using a three year mean for each component indicates the dividend 
 component is again significant at the 5% level of confidence in 
 classifying failed and nonf ailed companies. The analysis also found 
 the ratio of total net flow/total assets, a measure of cash flow as a 
 percent of total assets, was statistically significant. The receivables 
 and investment components were not significant because the distribu- 
 tions of the failed companies' ratios were disbursed across a wide range. 
 
 The findings clearly show that regardless of time periods used 
 before failure, dividends are important in classifying failed and non- 
 failed companies. The stability of net cash flow, receivables and 
 investments change dramatically as a company approaches failure. That 
 is, receivables and investment components do not provide reliable 
 signals for classifying failure two or three years before the event, 
 but they become reliable measures one year prior to bankruptcy. 
 
 Our equivalent to CB's cash flow from operations measure includes 
 three cash based funds flow components, namely, operations, working 
 capital and fixed coverage expenses. The probit coefficients in 
 Exhibit 5 for the three equivalent components corroborate CB's finding 
 
-10- 
 
 that CFO does not provide a reliable signal for discriminating between 
 failed and nonf ailed companies. The distribution of these three CFO 
 equivalents are presented in Figure 2. The graphics illustrate that 
 the variance of the operating, working capital and fixed coverage com- 
 ponents for the failed companies is markedly greater than for the finan- 
 cially healthy companies. There are failed companies that have CFO 
 measures quite similar to nonf ailed companies, and there are others 
 that are totally dissimilar. Our findings also indicate it is not pos- 
 sible to use the CFO measures to discriminate between failed and non- 
 failed companies. 
 
 Ratios 
 
 CB found that a set of six accrual accounting based ratios provided 
 more reliable information than CFO for classifying failed and nonfailed 
 companies. Also previous bankruptcy studies have relied totally on 
 financial ratios to predict bankruptcy. In order to determine if finan- 
 cial ratios are a more reliable source of information than the funds 
 flow components, we selected seven ratios that most frequently predicted 
 bankruptcy from fourteen previous studies, 13]. We also included a 
 ratio for size and one for market value. These nine ratios are net 
 income/total assets (NI/TA), total debt/total assets (TD/TA), cash 
 flow/total debt (CF/TD), net working capital/ total assets (NWC/TA), 
 current assets/current liabilities (CA/CL), cash plus marketable 
 securities/current liabilities (C/CL), natural log of total assets 
 (Jin TA), market value of equity/book value of equity (MVE/BVE). 
 
-11- 
 
 When the twelve funds flow components and the nine ratios are com- 
 bined, the probit results show that the dividends component is signifi- 
 cant at the 5% level of confidence and the investment and receivables 
 components are significant at the 10% level. None of the ratios are 
 significant. The data used to calculate the ratios and funds flow com- 
 ponents are from the one year before failure sample. The implication 
 of this finding is that dividend, investment and receivable flows offer 
 reliable information for discriminating between failed and nonfailed 
 companies. They provide dependable signals for analysts and management 
 to identify possible candidates for financial failure. 
 
 A strong discriminating test called the log likelihood statistic 
 was used to determine if ratios provide additional discriminating 
 information when combined with funds flow components or vice versa. 
 We tested the nine ratios and the twelve funds flow components as a 
 group. The results for both the ratios and the cash flow components 
 were significant. When the nine ratios were added to the twelve funds 
 flow measures, the increase in the explanatory power of the combined 
 measures was significant at the 5% level. Adding the funds flow com- 
 ponents to the nine ratios resulted in the combined discriminating 
 power being significant at the 1% level. Although both measures pro- 
 vide additional discriminating information when they are combined, the 
 funds flow components provide a slightly more reliable signal. 
 
 Conclusion 
 
 Our study supports the findings of Casey and Bartczak that cash 
 flow from operations does not provide reliable signals for discriminating 
 
-12- 
 
 between failed and nonfailed companies. CFO is not the bottom line for 
 discriminating between financially healthy and bankrupt companies. We 
 discovered that cash based funds flow model components or financial 
 ratios provide management and analysts reliable signals for classifying 
 failed and nonfailed companies. Our analysis shows when ratios are 
 combined with funds flow measures, or vice versa, the discriminating 
 reliability of the signal improves. However, the confidence level is 
 higher with the addition of funds flow information. We discovered 
 dividend, investment and receivable funds flow measures provide signi- 
 ficant information in classifying failed and nonfailed companies. Thus 
 CFO is not the bottom line, but a combination of funds flow and ratios 
 with particular emphasis on dividends, investment and receivables funds 
 flow components provide reliable information for judging the condition 
 of a company's financial health. 
 
-13- 
 
 REFERENCES 
 
 1. Edward I. Altman, "Financial Ratios, Discriminant Analysis and the 
 Prediction of Corporate Bankruptcy," Jour nal of Fi n ance , Vol. 23 
 (September 1968), pp. 589-609. 
 
 2. Cornelius Casey and Norman Bartczak, "Cash Flow — It's Not The 
 Bottom Line," Harvard Business Review , forthcoming. 
 
 3. James A. Gentry, Paul Newbold and David T. Whitford, "Bankruptcy, 
 Working Capital and Funds Flow," in Gerald H. Lawson and Richard 
 Pike (editors), Manag ement F inance in Working Capital , forthcoming 
 in 1984. 
 
 4. Erich A. Helfert, Techniques of Financial Analysis , Fifth Edition, 
 Homewood, IL: Richard D. Irwin, 1982, Chapter 1. 
 
EXHIBIT 1. TREND OF FUNDS FLOW COMPONENTS 
 FOR DEERE & COMPANY AND MASSEY FERGUSON 1978-1982 
 
 (in percent) 
 
 100 -, 
 
 50 
 
 
 -50 - 
 
 -100 
 
 "I I I I I 
 
 78 80 82 
 NET OPERATING 
 
 100 i 
 
 50 - 
 
 -50- 
 
 -100- 
 
 i i i 
 
 i 
 82 
 
 78 80 
 NET INVESTMENT 
 
 100 -i 
 50 
 
 -50 
 
 -100 -I 
 
 i i i i 
 
 78 80 82 
 NET FINANCING 
 
 100 -i 
 
 50 - 
 
 
 
 -50 - 
 
 -100 - 
 
 inii ii ii 
 
 78 80 82 
 DIVIDENDS 
 
 100 -| 
 
 50 - 
 
 
 
 **-*i 
 
 -50 - 
 
 -100 - 
 
 78 80 82 
 
 NET CHANGE 
 IN CASH 
 
 100 -j 
 50- 
 
 -50 - 
 
 -100 ^ , , 
 
 78 80 
 
 82 
 
 1UU "I 
 
 
 
 50 - 
 n - 
 
 i 
 
 f 
 
 
 <*\\ 
 
 • \ 
 
 -50 - 
 
 
 
 -100 - 
 
 
 i i i 
 
 NET OTHER ASSETS 
 AND LIABILITIES 
 
 100 
 
 50 - 
 
 78 80 82 
 
 NET WORKING 
 CAPITAL 
 
 -50 - 
 
 -100- 
 78 
 FIXED COVERAGE 
 
 i i i 
 80 82 
 
 DEERE & COMPANY 
 MASSEY FERGUSON 
 
EXHIBIT 2. TREND OF SHORT-RUN FUNDS FLOW COMPONENTS 
 FOR DEERE & COMPANY AND MASSEY FERGUSON 1978-1982 
 
 (in percent) 
 
 100 -, 
 
 50- 
 
 -50- 
 
 -100-1 i i i i 
 78 80 82 
 
 RECEIVABLES 
 
 100 -i 
 
 50- 
 
 
 
 -50- 
 
 -100 -I , i , • 
 78 80 82 
 
 INVENTORY 
 
 100-1 
 
 50- 
 
 -50- 
 
 -100-1 , . , , 
 78 80 82 
 
 OTHER CURRENT 
 ASSETS 
 
 100 
 
 50- 
 
 -50- 
 
 -100 - 
 
 i i i 
 
 78 80 82 
 PAYABLES 
 
 100 -. 
 50- 
 
 -50- 
 
 -100-1 
 
 i i 
 
 78 80 82 
 
 OTHER CURRENT 
 LIABILITIES 
 
 DEERE & COMPANY 
 MASSEY FERGUSON 
 
 1UU - 
 
 
 50- 
 
 y. 
 
 
 '••;/ \ / 
 
 n - 
 
 
 u 
 -50- 
 
 ' : ; 
 
 -100- 
 
 • 
 
 -150- 
 
 • " 
 
 -200- 
 
 I I 
 
 -250- 
 
 w m 
 
 «• 
 
 * 
 • 
 
 -300- 
 
 1 1 • 1 
 
 78 80 82 
 
 SHORT TERM 
 BORROWING 
 
EXHIBIT 3 
 
 MEAN NET FUNDS FLOW COMPONENTS /TOTAL NET FLOW 
 FOR FAILED AND NONFAILED COMPANIES 
 
 ONE YEAR BEFORE FAILURE 
 
 Net Funds Flow Component/ 
 Divided by Total Net Flow (TNF) 
 
 Operations 
 Working Capital 
 Other A&L 
 Financing 
 Fixed Coverage 
 Investment 
 Dividends 
 Cash & M.S. 
 Receivables 
 Inventory 
 Other CA 
 Payables 
 Other CL 
 
 Group 
 
 1 
 
 Group 
 
 2 
 
 Failed 
 
 Nonf ailed 
 
 Mean 
 
 S.D. 
 
 Mean 
 
 S.D. 
 
 .163 
 
 .528 
 
 .556 
 
 .247 
 
 .130 
 
 .453 
 
 -.129 
 
 .344 
 
 -.044 
 
 .258 
 
 .047 
 
 .178 
 
 .167 
 
 .490 
 
 .140 
 
 .369 
 
 -.152 
 
 .127 
 
 -.080 
 
 .095 
 
 -.163 
 
 .288 
 
 -.367 
 
 .267 
 
 -.018 
 
 .050 
 
 -.092 
 
 .103 
 
 -.081 
 
 .290 
 
 -.074 
 
 .243 
 
 .100 
 
 .351 
 
 -.169 
 
 .257 
 
 .013 
 
 .485 
 
 -.126 
 
 .246 
 
 .017 
 
 .148 
 
 -.020 
 
 .065 
 
 .170 
 
 .559 
 
 .101 
 
 .393 
 
 -.172 
 
 .680 
 
 .085 
 
 .241 
 
 TNF/TA 
 
 .257 
 
 .140 
 
 .226 
 
 .025 
 
 MEAN OF VARIABLE FOR THREE YEARS BEFORE FAILURE 
 
 Operating 
 Working Capital 
 Other A&L 
 Financing 
 Fixed Coverage 
 Investment 
 Dividends 
 Cash & M.S. 
 Receivables 
 Inventory 
 Other CA 
 Payables 
 Other CL 
 
 288 
 
 .344 
 
 .588 
 
 .228 
 
 007 
 
 .291 
 
 -.102 
 
 .197 
 
 018 
 
 .202 
 
 .029 
 
 .064 
 
 120 
 
 .342 
 
 .090 
 
 .211 
 
 126 
 
 .100 
 
 -.079 
 
 .062 
 
 220 
 
 .170 
 
 -.364 
 
 .211 
 
 002 
 
 .049 
 
 -.093 
 
 .10o 
 
 029 
 
 .145 
 
 -.068 
 
 .108 
 
 013 
 
 .304 
 
 -.151 
 
 .195 
 
 061 
 
 .211 
 
 -.117 
 
 .167 
 
 002 
 
 .022 
 
 -.015 
 
 .032 
 
 147 
 
 .260 
 
 .139 
 
 .212 
 
 089 
 
 .389 
 
 .041 
 
 .250 
 
 TNF/TA 
 
 255 
 
 136 
 
 .219 
 
 .07b 
 
EXHIBIT 4 
 
 CLASSIFICATION MATRICES FOR FAILED AND NONFAILED COMPANIES 
 USING PROBIT MODEL AND TWELVE FUNDS FLOW COMPONENTS 
 
 ONE YEAR BEFORE FAILURE 
 
 Probit (Pr < .5) 
 Failed 
 Nonf ailed 
 Total 
 
 Probit (Pr < .5) 
 Failed 
 Nonf ailed 
 Total 
 
 Number 
 
 Percent 
 
 Percent 
 
 
 Correct 
 
 Correct 
 
 Error 
 
 N_ 
 
 26 
 
 78.8 
 
 21.2 
 
 33 
 
 29 
 
 87.9 
 
 12.1 
 
 33 
 
 59 
 
 83.3 
 
 16.7 
 
 66 
 
 THREE YEAR AVERAGE BEFORE FAILURE 
 
 26 
 
 78.8 
 
 21.2 
 
 33 
 
 2b 
 
 78.8 
 
 21.2 
 
 33 
 
 52 
 
 78.8 
 
 21.2 
 
 66 
 
EXHIBIT 5 
 
 PROBIT COEFFICIENTS 
 
 Net Funds Flow One Year Three Year 
 
 Components Divided Berore Average Before 
 
 by Total Net Flow Failure Failure 
 
 Constant 1.567 -.073 
 
 Operating 1.257 1.630 
 
 Other -1.040 -6.094 
 
 Financing 1.580 -.008 
 
 Fixed Coverage 2.713 -2.041 
 
 Investment 3.678* 4.245 
 
 Dividend 13.133* 17.691* 
 
 Receivables 4.339* 3.b5b 
 
 Inventory 1.253 2.115 
 
 Other CA 2.490 4.532 
 
 Payables 2.086 2.649 
 
 Other CL .56 -.470 
 
 Total Net Flow/ 
 
 Total Assets 0.129 7.362* 
 
 *Asymptotic T ratio was significant at the .05 level of confidence 
 
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