systematic errors in budgeting capital outlays

Systematic Errors in Budgeting Capital OutlaysAuthor(s): Michael GortSource: The Review of Economics and Statistics, Vol. 44, No. 1 (Feb., 1962), pp. 72-75Published by: The MIT PressStable URL: http://www.jstor.org/stable/1926625 .

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SYSTEMATIC ERRORS IN BUDGETING CAPITAL OUTLAYS

Michael Gort

IN recent years, surveys of capital expenditure plans have occupied a prominent place

in forecasting economic activity, and consider- able effort has been devoted to establishing the sources of discrepancies between plans and realized expenditures. This paper deals with systematic errors that arise from the planning process itself. Such errors may be distinguished from discrepancies between plans and realizations that result from changes in the economic environment or from shifts in business expectations about earnings, sales, or other economic variables. More specifically, the discussion focuses on the reasons for consistent tendencies to under- or over-estimate plant and equipment outlays and, in particular, on the alleged relation between size of firm and such tendencies. The suggested hypotheses are tested against data for the electric utility industry.

While discussion of consistent biases in investment forecasts is scattered through a large number of sources, the most detailed studies of the problem were carried out by Friend and Bronfenbrenner I and by Foss and Natrella.2 In both, data from S.E.C. -Department of Commerce surveys of capital expenditure plans were used.

Both pairs of authors found the accuracy of forecasts to be positively correlated with the asset size of firms and with the scale of investment programs.3 (Scale was measured by the volume of planned investment relative to fixed

assets.) Except for firms in the top size class (those with total assets of more than $50 mil- lion), Friend and Bronfenbrenner found a tendency to understate planned relative to realized investment. Foss and Natrella found that large firms overestimated their future investment expenditures, though large firms with plans for only small outlays generally underestimated their outlays. Small and medium- sized firms underestimated their future expenditures when their prospective investment programs were small or moderate-sized but showed no consistent tendency to under- or overestimate when these programs were large.

Friend and Bronfenbrenner regard the tendency to underestimate expenditures as a consequence of omissions from capital budgets of small or contingent items.4 They explain the more accurate predictions of large firms in terms of three factors. First, large firms have many projects with the result that positive errors for some projects cancel out the negative errors on others. Second, large firms are able to allow in their budgets, on the basis of average experience, for such contingent expenditures as those occasioned by breakage. Third, capital budgeting procedures of small and large firms differ: the latter plan further in advance and their budgeting procedures are more for- malized and less flexible - hence, deviations from plans are less likely.

Foss and Natrella agree that variations in capital budgeting procedures have probably contributed to differences in the forecasting performance of large and small firms. How- ever, they conclude that a positive association (present in the period covered by their study) between firm size and size of investment pro- gram was a strategic factor in producing these differences. They also suggest that supply shortages which characterized the post-war economy may have been a central factor in explaining

' Irwin Friend and Jean Bronfenbrenner, "Plant and Equipment Programs and their Realization," Conference on Research in Income and Wealth, Studies in Income and Wealth, XVII (Princeton University Press, I955). Also, "Business Investment Programs and their Realization," Sur- vey of Current Business, XXX (December I950).

2Murray F. Foss and Vito Natrella, "The Structure and Realization of Business Investment Anticipations," Confer- ence of the Universities - National Bureau Committee on Economic Research, The Quality and Economic Significance of Anticipations Data (Princeton University Press, I960).

'On the other hand, Eisner working with data from the McGraw-Hill surveys, found no clear relation between scale of investment plans and accuracy of forecasts. However, he did find a distinct relation between accuracy of forecasts and size of firm. Robert Eisner, "Expectations, Plans, and Capi- tal Expenditures: A Synthesis of Ex Post and Ex Ante Data," in Mary Jean Bowman, Expectations, Uncertainty, and Business Behavior (Social Science Research Council, I958).

'In contrast, Modigliani and Weingartner have attributed the underestimates in the post-war period largely to a failure to project capital outlays on the basis of a rising price level. F. Modigliani and H. M. Weingartner, "Fore- casting Uses of Anticipatory Data on Investment and Sales," Quarterly Journal of Economics, LXXII (February I958).

[ 72 ]



SYSTEMATIC ERRORS IN BUDGETING 73

the tendency of large firms to overestimate their future outlays.

In our own analysis, we start with the proposi- tion that there are two types of errors generally present in capital expenditure projections. Type i errors (underestimates), arise from uncertainty, incomplete plans, and limited planning horizons. These result in the exclusion of some outlays from capital budgets. Type 2

errors (overestimates) arise from the inclusion of contingent expenditures in a budget. The inclusion of some contingent outlays in a budget is a widespread practice (not restricted to profit oriented organizations) that is necessary for financial planning in the sense that provision must be made for adequate funds to meet such cash obligations as may materialize. There is always an implicit cost to both under- and overestimates, but the relative magnitude of these costs varies widely depending upon two variables: namely, the rate of growth in demand and the gestation period for capital goods. In addition, the gestation period imposes cer- tain technical constraints on capital budgeting which, in turn, affect underestimates. Our hypothesis is that for high values of the two variables, firms will tend to have annual expenditure plans that exceed realizations and for low values, the reverse. Thus, the presence of overestimates is not contingent upon circum- stances that are peculiar to a given interval of time, such as post-war supply shortages. Fur- ther, for industries in which the firms are homogeneous with respect to the two variables, the magnitude and direction of forecasting errors of small firms should be substantially the same as for large firms.

A high rate of growth in demand increases expectations of continued growth. This reduces estimates of the risk of long-term commitments in that if requirements for capacity are overestimated and commitments for new capacity prove excessive, continued growth will even- tually eliminate the excess capacity created. Moreover, the higher the rate of growth in demand, the less is the ability of a firm to meet the required increases in output through use of normal reserve capacity. Consequently, po- tential losses from delayed investment outlays are increased. All this leads to a lengthening

of the period for which investment plans are made.5

In some industries most equipment can be purchased from manufacturers' inventories and the time needed for installation is fairly brief. In these industries, there is less risk to deferral of investment decisions, and thus, larger underestimates are more likely. In short, the length of the planning horizon is affected also by the length of the gestation period.

The longer the time required to produce capital goods, the larger the proportion of a given period's capital outlays that is devoted to projects begun in an antecedent period. As the share of new projects in a capital budget is reduced, the scope for underestimates that arise from the omission of uncertain projects is narrowed. For example, if the average gestation period is two years and outlays for projects are evenly distributed over each period, on the average one-half of an annual capital budget will be devoted to projects begun in earlier years. Since omission of uncertain outlays is largely restricted to new projects, firms with an average gestation period of two years will show less tendency to underestimate than those for which the average interval is but one year.

Since both rates of growth in demand and gestation periods for producers' goods vary markedly among industries, significant differences in the tendency to under- or overestimate can be expected among companies in different sectors of the economy.6

To test our hypothesis, data on investment plans in the electric utility industry were used. These data have several special characteristics. First, the electric power industry is highly homogeneous both with respect to the composi- tion of output and the type of capital goods

This hypothesis is consistent with the finding of Foss and Natrella that underestimates are inversely related to the volume of planned outlays, for the latter will generally be correlated with rate of growth in demand.

6 Friend and Bronfenbrenner found that the accuracy of predictions differed among industries. For example, firms in chemicals and in iron and steel, on the whole, did not underestimate their future investment. The authors attribute these differences to variations among industries in the relative numbers of large and small firms. Our hypothesis suggests the converse relationship. That is, differences in the post- I947 period between large and small firms are primarily at- tributable to the fact that large firms fell more frequently into industries characterized by a long production period for capital goods and by faster than average growth.



74 THE REVIEW OF ECONOMICS AND STATISTICS

employed. This facilitates analysis of the relation of size of firm to forecasting errors in that differences among firms in the two strategic variables discussed above are minimal. Second, information for planned and realized investment is available both for outlays measured in money terms and for additions to capacity ex- pressed in physical units.

Except for the early I930's, in the period since I927 the electric power industry has been characterized by relatively steady and rapid growth in demand. Also, it is an industry with one of the longest gestation periods for plant and equipment. In consequence, it would fol- low from our hypothesis that planned outlays for a year in advance should generally be greater than realized investment. Further, as noted above, the electric power industry is highly homogeneous. Thus, if neither size of firm per se nor capital budgeting procedures asso- ciated with size are decisive factors in deter- mining the magnitude of recurrent errors in forecasts, large and small firms will show the same pattern of deviations between plans and realizations.

For industry aggregates in the I927-59 period, Table i shows a comparison of actual capital expenditures with those planned roughly a year in advance.8 The striking fact about the relation between actual and planned expenditures is that the latter exceeded the former in 22 of 29 years. The average deviation between actual and planned expenditures was also larger when plans exceeded realizations than when the reverse was true.

Table i also compares actual additions to generating capacity with those planned a year in advance, and for the post-war period, with those planned two and three years in advance. For the one-year plans, actual additions were less than those planned in 22 of 25 years, and average actual minus planned additions, ex- pressed as a percentage of the former, were -22.5 per cent. As the planning period length-

ens, however, incompleteness in plans appears to more than offset the inclusion of contingent expenditures.

TABLE I. - PLANNED AND REALIZED INVESTMENT

OF ELECTRIC UTILITIES, I927-59

Capital Expenditures a Additions to Capacity b (Millions of Dollars) (Thousands of Kilowatts)

Actual Planned Actual Planned Ahead I year 2 years 3 years

I927 794 958 I928 754 900

I929 853 854

I930 9I9 9I4

I93I 597 894

I932 285 455 1933 129 n.a. I934 I48 n.a. I935 193 201 386 469

I936 290 372 72I 769 I937 456 53I 1,II9 1,273

I938 482 473 I,696 i,8i8

I939 430 4I3 1,285 I,397

I940 597 605 1,693 2,0II

I941 654 724 3,078 3,967 I942 n.a. 70I 2,783 3,6I8

1943 260 n.a. 2,924 3,342

1944 340 234 I,546 I,466

I945 409 663 887 I,297 1946 7I8 895 424 I,462

I947 I1372 I,307 2,203 3,028 3,288

I948 2,078 2,027 4,423 4,409 7,326 I949 2,5i8 2,365 6,926 6,I78 n.a. I950 2,347 2,464 6,o84 6,259 5,9I3

I95I 2,443 2,558 7,I86 7,249 6,396 6,388 I952 2,90I 3,002 6,948 9,o69 8,15I 4,291

1953 3,187 3,28I I0,490 I1,763 11,7I2 7,426 1954 3,I98 3,272 12,269 I3,385 I0,870 8,I69

I955 3,o87 3,I96 12,387 I3,308 1I,346 9,4I3 1956 3,379 3,444 7,304 8,431 7,949 8,229

1957 4,296 4,382 8,752 9,435 7,685 5,189 1958 4,465 4,729 I5,284 I6,663 17,35I 9,117

I959 4,I64 4,402 13,542 I4,265 13,769 13,300

SOURCE: Electrical World (McGraw-Hill Publishing Co.) Annual Sta- tistical Issue, I927-60.

a Data are for private utilities and for state and local publicly owned utilities but not for projects of the U.S. Government nor for rural co- operatives.

b Data are for all private and publicly owned utilities. On the average, privately owned companies contributed roughly three-fourths of total additions.

n.a. Not available.

To sum up, the data show a persistent tendency for one-year investment plans to exceed realizations. This tendency is not restricted to a limited period and, therefore, cannot be ex- plained in terms of supply shortages peculiar to a given interval of time. Further, since data for physical additions show the same general pattern of errors as data for expenditures, the phenomenon cannot be attributed to unexpected movements in construction costs.

For some manufacturing industries in particular, the customarily defined industry boundaries include firms that are highly conglomerate with respect to the two variables.

8 The information is based on surveys conducted each January by Electrical World. The industry coverage in the surveys is high and so is the reliability of the forecasts. In 22 of 26 years, the direction of change from the preceding year in planned outlays corresponded to that for actual expenditures.



SYSTEMATIC ERRORS IN BUDGETING 75

To test the relation between forecasting errors and size of firm, data on an individual company basis were obtained from information published by the Federal Power Commission. For our analysis, data were used for all privately owned electric utilities for which individual company estimates of prospective additions to generating capacity were available.9 The companies were divided into quartiles on the basis of December I954 generating capacity. The January I955 plans for additions to capacity in I955, I956, and I957 were then compared with actual additions for these years. Observa- tions showing neither plans for additions nor actual additions were excluded from analysis.10

TABLE 2. - SIZE OF COMPANY AND ERRORS IN FORECASTING ADDITIONS TO GENERATING CAPACITY, I95 557 a

No. of No. of No. of Actual Less Actual More Exact No. Deviations Deviations Than Planned No. Than Planned No.

Size Class b Forecasts Expected From Actual c Expected (Number) Expected (Number) Expected ( I) ( 2) (3) (4) (5) (6) (7) (8)

I I0 10.3 3I 30.7 I4 I0.2 I 7 20.8 2 8 9-5 30 28.5 9 9.9 2 I 20.I

3 I8 I3-3 35 39.7 II II.5 24 23.5 4 I3 I5.8 50 47.2 I4 I6.4 36 33.6

All 49 146 48 98

Chi-squared: col. (I)-(2) and ()-() = 3.207 col. (5)-(6) and (7)-(8) = 2.786

SOURCE: Based on data in U.S. Federal Power Commission, Electric Power Statistics, Section 3. a The forecasts for 1955, I956, and 1957 were all made in January 1955. b Size based on December I954 generating capacity. The classes are in ascending order of size. The class limits in kilowatts were: 0-I44,679;

I44,680-338,795; 338,796-708,787; 708,788 and over. They were based on a division of all companies into quartiles. c Total number of negative and positive deviations (actual minus planned). d With three degrees of freedom, a chi-square of less than 3.665 is not inconsistent with the null hypothesis at even the .30 level of significance.

Table 2 shows that in the four size classes the distribution of errors (that is, over- and underestimates combined) did not differ significantly from those that could be expected on the null hypothesis. That is, the total of over- and underestimates was independent of company size. Second, the Table shows that the distribution of over- as compared with under-

estimates in the four classes also did not differ significantly from those expected on the null hypothesis. Thus, company size was not asso- ciated with frequency of over- or underestimates of additions to capacity.

Table 2 combines errors in one-year plans with those for the second and third year. For 1955-57 analysis based on comparisons of actual additions with those planned a year in advance (that is, using plans made in January of each of the three years, 1955, I956, and I957, for one year ahead) showed substantially the same results.11

If our analysis is supported by data for other sectors of the economy, much progress toward

correcting forecasts of investment for recurrent errors can be made by adjustments on an industry basis. To the extent that systematic errors in projections of investment depend not on capital budgeting procedures but on an industry's technology and on its rate of growth, we can expect these errors to persist in the future.

9 Many companies were grouped and data were shown by the FPC only on a combined basis.

'0 In consequence, the numbers of observations were un- equal in the four classes. Since the data included three- and two-year forecasts as well as one-year forecasts, the number of instances in which actual additions exceeded those planned was substantially larger than the reverse.

1' For reasons of brevity, data on the latter basis are not shown in this paper. However, using the same four size classes of companies and the same method of analysis, the chi-square for the association of company size with number of over- as compared with underestimates was only 2.593. (With three degrees of freedom, a chi-square of less than 7.8I5 signifies that the results are not inconsistent with the null hypothesis at the .05 level of significance.)



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