Profit maximization—does it matter?

Profit Maxirnization- Does it Matter. ?*

Katherine D. Young C. Richard Shumway

H. L. Goodwin

Comparative hypotheses are statistically tested for a random sample of Texas producers who perceive themselves as profit maxi.mizers and those who do not. Those who assert that they are in the cow-calf business primarily to maximize profits have on average larger herd sizes and acreage, they earn a greater percent of their total net income from farming and ranching, and they place more emphasis on supportive economic motivations and less on social reasons for owning cattle. Off-farm employment status and the qualitative response to changes in price expectations are not unambiguously related to perceived motivations.

One of the fundamental assumptions of the neoclassical theory of the firm is that the behavioral objective of producers is to maximize profits. This assumption is frequently maintained by economists when making both firm-level and policy- related recommendations. 1-4 It is also maintained in much of the contemporary econometric analysis of agricultural production, including direct estimation of production technology5 and dual analysis of technology, output supplies, and/or input demands.e9

*Appreciation is expressed to David Bessler, Richard Conner, and Tom Cartwright for helpful suggestions on earlier drafts of this manuscript.

Katherine D . Young is Executive Assistant for public affairs, Clemson University cformerly a research assistant in agricultural economics, Texas A&M University).

C . Richard Shumway is Professor of Agricultural Economics, Texas A&M University.

H . L . Goodwin is Associate Professor of Agricultural Economics, Texas A&M University.

Agribusiness, Vol. 6, No. 3, 237-253 (1990) 0 1990 by John Wiley & Sons, Inc. CCC 0742-4477/90/030237-17$04.00

238 YOUNG, SHUMWAY, AND GOODWIN

Considerable research has been devoted to determining the true objectives motivating farmers’ decisions. Various procedures have been used including inferential examination of aggregate data6,10 and firm-level inference. I1-l3 Some researchers have concluded that producers’ behavior is essentially consistent with profit maximization. 6910,14 Some have concluded that producers are risk aver- se,11,15 others that producers are motivated by a multiplicity of goals, 16--20 and still others that the evidence is too ambiguous to draw clear c o n ~ l u s i o n s . ~ ~ - ~ ~

The cow-calf industry is one case that has yielded particularly ambiguous results. Cow numbers in the US and in many individual states, including Texas, have grown substantially since 1950 even though documented pre-tax returns to investment in cow-calf production have been low in comparison to crop production and nonagricultural investment^.^^-^^ Such behavior is inconsistent with profit maximization if cow-calf producers really have crop and nonagricultural investment alternatives, if tax effects are approximately the same in all enterprises, and if land appreciation rates are the same for both rangeland and cropland. In a recent survey of Texas cow-calf producers who also raised at least one other commodity, producers’ opinions were directly elicited concerning behavioral objectives that motivated their business decisions. Nearly 90% of the respondents asserted that their primary objective was to maximize pr~fi ts .~O

While the suitability of the profit maximization assumption as a general descriptive property of production agriculture remains ambiguous, it is clear that it is not descriptive of all producers. Consequently, the purpose of this study is to statistically examine the Texas cow-calf survey data to determine fundamental differences between those producers who assert that their primary goal is to maximize profits and those who say it is not.

HYPOTHESES Several hypotheses will be examined in this analysis. They include the following:

(1) Producers who state that they are profit maximizers are more supply responsive to expected price changes than other producers.

(2) Producers who state that they are profit maximizers place more emphasis on economic and less on social reasons for owning cattle than do those who do not perceive themselves as profit maximizers.

profits.

reasons and less on social reasons for owning cattle.

ranching are more likely to seek to maximize profits.

ranching place more emphasis on economic reasons and less on social reasons for owning cattle.

(7) Full-time operators (i.e., those who are not employed off the farm or ranch) are more likely to be profit maximizers.

(8) Full-time operators (i.e., those who are not employed off the farm or ranch) place more emphasis on economic reasons and less on social reasons for owning cattle.

(3) Cow-calf producers with larger herds are more likely to seek to maximize

(4) Cow-calf producers with larger herds place more emphasis on economic

(5) Producers who earn a greater percent of their total income from farming and

(6) Producers who earn a greater percent of their total income from farming and

I

PROFIT MAXIMIZATION 239

The theory of the firm implies that supply responds positively to changes in own price. The first hypothesis goes beyond the specific theoretical implication to assert that supply responsiveness to expected price changes is greater by those seeking to maximize profits than by others. The second hypothesis alleges that if producers really seek to maximize profits, their responses to related questions about their motivations will support their direct claim. The remaining hypotheses are based on the notion that commercial cow-calf operations are more likely to be profit motivated. It is expected that commercial operations are generally larger and tend to concentrate more on agricultural business activities. The third, fifth, and seventh hypotheses deal directly with relationships between the characteristics of the operation and whether or not the producer perceives himself or herself as a profit maximizer. The fourth, sixth, and eighth hypotheses concern relationships between operational characteristics and other economic and social motivations for being in the cow-calf business. No causal relationships are alleged in these hypotheses. It is only asserted that profit-maximizing behavior is positively related to these five variables. No claim is made, for example, whether a producer is large because of being a profit maximizer or is a profit maximizer because of being large.

PROCEDURES Texas cow-calf producers were surveyed by mail in 1986 to elicit their motivations for being in the cow-calf business. The survey was drawn as a stratified random sample of cow-calf producers who also produced at least one other agricultural commodity. Responses from 377 producers (38% of those surveyed) were received and analyzed as to the structural characteristics of their operations and their motivations for owning cattle.30

Evidence clearly revealed that Texas cow-calf producers predominantly perceive themselves as profit maximizers. To evaluate this perception more closely, these data are examined statistically in this article to determine differences between those producers who assert that their primary goal is profit maximization and those who do not. Producers were directly asked in the survey if their objective in raising cattle was primarily to maximize profits. Of the 377 responses, 331 (or 89%) answered positively, 43 answered negatively, and 3 did not respond. Characteristics such as size of operation, income, and employment of the two groups are analyzed in this study for significant differences.

Using chi-square tests and differences-between-means tests of hypotheses, initial evidence of statistically significant differences is determined. For the fourth, sixth, and eighth hypotheses, factor analysis is also performed on the motivational responses. These results identify relationships between the factors and structural characteristics of the operation. Factor analysis is used to specify the minimum number of important combinations of motivations or attitudes that group together. Then comparisons are made on the weighting of the groups (or factors) by producers who claim to be profit maximizers (or have characteristics correlated with asserting to be profit maximizers) and those who do not. Finally, linear regression analysis is used to quantify effects of the economic and social factors on cow numbers. The linear regression analysis relies on ordinary least squares estimation.


RESULTS

Factor Loadings

Several of the survey questions solicited attitudes and reasons for being in the cow-calf business. The questions dealing with economic and social motivations for being in the cow-calf business were analyzed for factor patterns using factor analysis techniques. Survey questions dealing with the attitudes of producers about being in the cow-calf business were also analyzed for factor patterns.

For this analysis it is important to know the value assigned to the response for these survey questions. For example, if a motivational reason for being in the cow-calf business was very important, a value of 1 was assigned to the response. If the reason was very unimportant, a value of 5 was given as the response. In the questions dealing with attitudes, a value of 1 was assigned if the producer strongly agreed with the statement and a 5.was assigned if the producer strongly disagreed with the statement. Thus, the smaller the number, the more important the reason or the more strongly the producer held the stated attitude. Factor analysis was performed separately on the responses to the two sets of survey questions (i. e., motivational reasons and attitudes).

Motivations. In selecting the minimum number of relevant factors, significance tests were used. The large sample chi-square test associated with the maximum likelihood solution is the most satisfactory test from a statistical point of view.31 Using this criterion, three factors were extracted from the 16 observed variables in the first set of questions (those dealing with reasons for being in the cow-calf business). The chi-square test for significance in explaining common variance within the system by these factors was 174.33 with a significance level for reliability of the factors of .OO01.

Of primary importance in factor analysis is the identification and interpreta- tion of factor patterns. Results of the first factor analysis are shown in Table I.

Table I. Factors Identified as Motivations for Being a Cow-Calf Producer.

Factor Loading

Economic Social Profit Variable Motivations Motivations Motivations

Trying to Reduce Risk by Diversification 0.5995 0.1219 0.4204 Make Better Use of Labor Resources 0.5756 0.1987 0.4155 Allow Off-Farm Employment 0.4492 0.2893 0.1755 Generate Cash Flow 0.5571 0.1518 0.3069 Tax Advantages 0.5460 0.3396 0.0707 Alternative Market for Feedstuffs 0.5434 0.1325 0.2896 Pasture Management for Wildlife 0.7112 0.2664 0.1993

Family Tradition 0.1830 0.6336 0.1557 Part of Community Life 0.3887 0.6570 0.1279 Like the Lifestyle of a Rancher 0.1496 0.7642 0.2279

Graze Cropland and/or Timberland 0.5953 0.3099 0.0943

Way to Relax and Exercise 0.2847 0.6891 0.0200 Trying to Maximize Profits 0.1926 0.0563 0.6648

PROFIT MAXIMIZATION 24 1

Only variables which were nontrivial for one of the three factors are presented. Factor 1 was comprised of eight variables which satisfy the criteria of having a

factor loading of at least .40 and being at least .15 greater than all other loadings. Factor loading has the following meaning. Its square is the proportion of the variance of the variable accounted for by the variation in the respective factor. The eight variables comprising factor 1 were all associated with economic reasons for being in the cow-calf business. The reasons were: (1) trying to reduce risk in the entire agricultural operation, (2) make better use of labor resources, (3) allow off-farm employment, (4) generate cash flow, (5) get tax advantages, (6) provide an alternative market for feedstuffs produced, (7) manage pasture for wildlife, and (8) graze crop or timberland. Factor 1 is referred to as “economic motivations”.

Using the same criteria as for factor 1, four nontrivial variables were included in factor 2. These four variables all dealt with social reasons for owning cattle and were as follows: (1) ranching is a family tradition, (2) be part of community life, (3) like the lifestyle of a rancher, and (4) it is a way to relax and get exercise. This factor is referred to as “social motivations”.

Factor 3 consisted of only one variable, that the reason for being in the cow- calf business was to try to maximize profits. Therefore, profit maximization was regarded as a separate factor in making cow-calf production decisions. This unique factor is referred to as “profit motivations’,.

Attitudes. The other factor analysis was performed using the survey data in which a series of attitudinal statements related to the cow-calf business was listed and the respondent ranked the extent to which he/she agreed with each. The chi-square test for significance in explaining common variance within the system by these factors was 60.42 with a significance level for reliability of the factors of .OO01. Results are presented in Table 11. Only variables which were nontrivial for one of the two factors are given.

Table 11. Towards Being a Cow-Calf Producer.

Factors Identified as Attitudes

Factor Loading

Social Economic Variable Attitudes Attitudes

Would Like to See Child Become a 0.6905 0.2214

Important to Ranch for Family 0.8219 0.2063 Satisfaction Gained from Cattle is Enough 0.4241 0.2224

Rancher

Reason to Stay in Business

ture Raising Cattle is above all a Business Ven- 0.2531 0.6621

Producing Efficiently is Always Important 0.2509 0.6265 Profit Maximization is Most Important Con- 0.1342 0.6173

sideration in Making Production Deci- sions


Factor 1 consisted of three variables using the same criteria as for factor 1 of the motivational factors. All three were statements pertaining to the importance of staying in the cow-calf business for personal satisfaction and for providing a certain lifestyle for their children. This factor is referred to as “social attitudes”. Factor 2 of the revealed factor pattern was also made up of three variables. These three variables referred to the importance of raising cattle mainly as a business venture and to operating efficiently. This factor is referred to as “economic attitudes”. Initial results of the factor analysis revealed definite economic and social factor patterns that motivate producers to be in the cow-calf business.

Producer Supply Response

Cow-calf producers whose primary objective is to maximize profits are hypothesized to be more responsive to price changes than other producers. To examine this hypothesis, producers were asked to choose from a list of 20 possible plans any that were applicable to their expected operation in the next five years. Three of the possible plans listed were to: (a) keep the farm or ranch more or less the same, (b) expand the cow herd, or (c) reduce the cow herd. Producers were then asked what action they would take if cattle prices were to remain at the low 1986 levels for the next five years. Four choices were given: (1) expand the operation, (2) sell out, (3) continue the operation as is, and (4) continue, but reduce inputs into the operation.

Of the 83 producers who said they were profit maximizers and who said initially that their future plan was to expand the cow herd, only 33% said they would expand given the low price expectation; 46% said they would maintain their operation as it was, and 20% indicated they would reduce inputs into their operation (Table 111). Of the operators who did not claim to be in the cow-calf business primarily to maximize profits, five initially planned to expand the cow herd. Given the low price expectation, none said they would expand.

Of the producers who asserted they were profit maximizers and initially planned to keep the farm or ranch the same, over one-third said they would continue but with reduced inputs when facing low 1986 prices for the next five years. Of the operators who did not claim to be profit maximizers and who initially planned to keep the farm or ranch the same, 30% changed their plan to continuing with reduced inputs. A chi-square test of independence revealed no significant difference in the change of plans to this alternative scenario between those who claimed to be profit maximizers and those who did not. However, a second chi-square test revealed a significant difference at the 1 % level between the initial plans and the plans with low price expectations for both sets of producers (x2 = 148.84 with a critical

Evidently these producers initially had expectations of higher output prices. When given a price expectation of no increase (assuming everything else constant), most who initially planned to expand changed their plans to not expand and to either maintain their operation or reduce their inputs into the operation. These results show a clear response to price expectations, and both groups were consistent in their responses. However, there was no significant difference in the qualitative response to price between those who stated they were primarily profit maximizers and the others.

= 16.81).


Table 111. by Changes in Possible Plans and by Primary Goal.

Producer Response to Low Price Expectations

New Planb

Initial Plana

~~ ~~~~

Expand the Sell Continue Continue but Operation Out as is Reduce Inputs

Profit Maximizers: Keep Farm/Ranch More

or Less the Same Expand the Cow Herd Reduce the Cow Herd

Not Profit Maximizers: Keep Farm/Ranch More

or Less the Same Expand the Cow Herd Reduce the Cow Herd

(Total) (Frequency) -

22 1 11 4 130 76

83 27 1 38 17 81 0 13 21 47

30 0 0 21 9

5 0 0 4 1 10 0 2 1 7

aProducers could indicate more than one plan. Only producers who listed at least one of these

bIndicated plan if price were to remain at low 1986 levels for five years. initial plans and an alternative plan were reported. No price levels were specified.

Motivational Differences

Producers may take into consideration many objectives when making decisions about the cow-calf operation. 13,28 To verify the response to the direct question on profit maximization in this survey, producers were also asked to rate a set of reasons for being in the cow-calf business by level of importance. Reasons were rated from “very important” to “very unimportant” and are reported in Table IV; several were also noted in the earlier discussion of factor loadings. In addition to seeking to maximize profits, other important reasons reported for being in the cow- calf business included using available resources efficiently and liking the lifestyle of a rancher.30 It is hypothesized, however, that producers who stated that they were profit maximizers place more emphasis on economic and less emphasis on social reasons for being in the cow-calf business than other producers. It is expected that producers whose main objective is not to maximize profits may consider social or family reasons relatively more important. A chi-square test of independence revealed that the relative importance of seven economic reasons and three social reasons was not independent at the 10% level ( x * ~ ~ , ~ = 4.61) of the question on profit maximization (see last column of Table IV).

A mean score for the two groups of producers was also calculated for each reason and is reported in Table IV. Statistical tests were conducted to determine whether the mean scores were significantly higher or lower for any of the reasons. Five of the reasons were more important at the 5% level of significance to those producers who stated they were profit maximizers. All of these reasons relate to the efficient use of resources in the cow-calf operation. Two reasons were significantly less important to the profit maximizers, both of which were social reasons.


Table IV. Ratings on Reasons for Being in Cow-Calf Business and Primary Goal.

Mean Ratings" for Producers with Primary Goal of

Reason Profit Not Profit

Maximization Maximization X Z

Trying to Maximize Profits Trying to Reduce Risk by Diversification Part of Land Usable for Pasture Only Make Better Use of Labor Resources Allows Off-Farm Employment Generate Cash Flow Tax Advantages Alternative Market for Feedstuffs Pasture Management for Wildlife Graze Cropland and/or Timberland Want to Increase Net Worth Family Tradition Part of Community Life Like the Lifestyle of a Rancher Way to Relax and Get Exercise Expertise is in Raising Cattle

1.4b 2.6b 1.9 2.6b 2.9 2.9 2.7 3.1b 3.3 3.4 2. l b

2.3 2.7 2.3" 2.6' 2.0

2.8 3.2 2.2 3.3 3.0 3.3 2.5 3.7 3.5 3.2 2.8 2.1 2.5 1.8 1.9 1.9

110.7' 8%

11.8- 11.5' 3.9 2.2 4.8' 3.9 7.3c 1.6

24.2- 0.8 2.6 5.2' 5.8'

11.6e

"Ratings: 1 = very important, 2 = important, 3 = neutral, 4 = unimportant, 5 = very

bMean rating for profit maximizers significantly less (more important) than mean rating for others

cMean rating for profit maximizers significantly greater (less important) than mean rating for

dTo perform x z tests, rating 1 was combined with 2 and 4 with 5 to provide cell frequencies large

"Significant dependent relationship between reason and primary objective at 5% level of signifi-

'Significant dependent relationship between reason and primary objective at 10% level of

unimportant.

at the 5% level.

others at the 5% level.

enough to approximate the x z distribution.

cance. Critical value of x*05.z = 5.99.

significance. Critical value of zzlo.z = 4.61.

Results of chi-square tests and difference-between-means tests revealed that producers who perceived themselves to be profit maximizers placed more emphasis on economic reasons and less on social reasons than did the others.

To further investigate this hypothesis, factor scores were examined. A score for each factor was computed for each observation by weighting the individual variables by their factor loadings. 32 Mean factor scores were determined across observations for the two groups of respondents, and tests of significance between these mean scores were performed to determine if the factors were weighted differently by those who claimed to be profit maximizers and those who did not. Because of the structure of the data, a lower (including negative) mean factor score implies that the factor is more important.

For producers claiming to be profit maximizers, one would expect smaller means for the economic motivations, profit motivations, and economic attitudes factors. The results shown in Table V confirm this hypothesis. Mean factor scores


Table V. Differences by Factors for Selected Characteristics. a

Results of Testing between Means for Significant

Economic Social Profit Social Economic Characteristic Motivations Motivations Motivations Attitudes Attitudes

Profit Maximization Profit Maximizer

n = 331 Not Profit Maximizer n = 4 3

Number of Cows Less than 100

n = 138 100 or More

n = 239

Percent of Income from Farming and Ranching

25% or Less n = 244

More than 25% n = 133

Off-Farm Employment Not Employed Off-Farm

Employed Off-Farm or n = 180

Retired n = 197

-0.0425

0.2849 ( - 2.39) "

- 0.0724

0.0418 (-1.24)

0. oa4

-0.1191 (1.97)"

0.1462

-0.1336

(3. 13)"

0.0109

-0.2067 (1.20)

-0.1163

0.6716 (-1.90)"

-0.0354

0.0650 (-1.09)

0.1025

-0.0937

(2.12)"

-0.1393 -0.0368 -0.0635

0.9551 0.1730 0.4741 (-8.30)b (-1.44) (-3.43)"

0.1392 -0.0103 -0.0034

-0.0762 -0.0050 0.0019 (2.38)" (0.17) (-0.06)

0.1282 0.1052 0.0446

-0.2352 -0.1930 -0.0818 (4.45)b (3.37)" (1.40)

-0.0898 0.0024 0.0949

0.0820 -0.0022 -0.0867

(- 2.03) (0.05) (2. 10)"

et-test statistics are given in parentheses. "Difference between means of respective variable groupings significant at .05 level. cDifference between means of respective variable groupings significant at . 10 level.

for the economic and profit motivations factors and the economic attitudes factor were significantly lower (i.e., more important) for those who perceive themselves as profit maximizers than for those who do not.

Size of Operation

It is hypothesized that producers with large herds are more likely to seek to maximize profits from the sale of calves than producers with small herds. A great dispersion in size of enterprises is evident in the cow-calf industry in all areas of the US. Neoclassical economic theory implies that in a competitive market sector, only producers with enterprises of the size that yield minimum average total costs will persist in the long run. Considerable evidence indicates that substantial economies of size exist in the cow-calf industry. In the US in 1983, average total economic costs per cow in enterprises of fewer than 100 cows were 37% greater than in operations with more than 500 cows. Further, total economic costs per dollar of cattle sales receipts were 34% higher for herds of fewer than 100 cows than for operations with more than 500 cows.29

YOUNG, SHUMWAY, AND GOODWIN

Since the early 1960s, the trend in Texas (and elsewhere) has been toward larger herds. Even so, 85% of all cattle operations in Texas still had fewer than 100 cows in 1986.33 In this survey, all producers with 500 cows or more said their primary goal was to maximize profits. Of those with herds of 100-499 and 50-99 cows, 89% and 93%, respectively, stated that their main goal in raising cattle was to maximize profits. This compares to 70% of those with less than 50

The mean number of cows was 190 for producers perceiving themselves as profit maximizers and 115 for those not claiming to be profit maximizers (see Table VI). To test the hypothesis that producers with larger herds are more likely to be profit maximizers, the difference between the two means was tested for statistical significance. Results showed that there was a significant difference at the 1% level ( t = 3.69) in average herd sizes for the two groups of producers. We can conclude then that producers with larger herds were more likely to have profit maximization as their primary goal.

Herd size data were grouped corresponding to census classes and are also reported in Table VI. A chi-square test of independence further showed that there was a significant dependent relationship (x2 = 17.14 with critical ~ 2 ~ ~ , ~ = 9.21) between classes of herd sizes and whether or not producers said they were profit maximizers. To perform x2 tests, herd sizes of 100-499 cows and 500 cows or more were combined to provide cell frequencies large enough to approximate the x2 distribution.

Additionally, size of operation in terms of total acreage was significantly larger at the 1% level ( t = 3.35) for those who claimed to be profit maximizers. The percentage of profit-maximizing producers was greater in three of the four largest size categories than was the percentage of those not claiming to be profit maximizers (Table VI).

cows.

Table VI. Herd and Farm Size by Primary Goal.

Primary Goal

Profit Maximization Not Profit Maximization

Size Frequency Percent Mean Size Frequency Percent Mean Size

Number of Cows 1-49 50-99 100-499 500 or More Total

Acreage 1-99 100-219 220-499 500-999 1000-1999 2000 or More Total

30 88

192 21

33 1

4 13 58 72 69

115 33 1

9.0 26.6 58.0 6.4

100.0

1.2 3.9

17.5 21.7 20.9 34.8

100. 0

26.6 71.5

182.7 987.8 190.0

72.3 147.1 333.7 720.6

1436.9 9950.6 3988.4

13 7

23 0

43

4 7 6 5

12 9

43

30.2 16.3 53.5 0

100.0

9.3 16.3 14.0 11.6 27.9 20.9

100.0

19.8 66.4

183.3

115.0 -

73.3 147.4 353.4 764.2

1457.2 3474.4 1302.8


To test the hypothesis that differences in motivations and attitudes of producers are also related to herd size, one would expect smaller means (or heavier weight) for larger herd sizes on the three economic-oriented factors and higher means (or lighter weight) on the two social factors since herd size was related to the profit maximizing goal. Results in Table V show that producers with larger herds (greater than or equal to 100 cows) placed significantly heavier weight on the profit motivations factor and significantly lighter weight (at the 10% level of significance) on the social motivations factor, as expected, than producers with smaller herds. The remaining factors were not significantly related to herd size.

Cow Numbers

The fundamental issue driving this study is the inconsistency of increasing cow inventories in the face of relatively low rates of return to cow-calf operations. Musser et al. l3 found that the average number of cows on farms in Georgia was higher than the profit-maximizing level. They attributed this difference to conspicuous production, which would be consistent with our empirical results. Since cow inventories are a reflection of supply, it is of interest to further examine factors that affect the level of production for the cow-calf producers surveyed.

Linear regression techniques were applied to the data resulting from the factor analysis procedures. This analysis was intended to identify relationships between the number of cows the producer owns, the factor patterns, and other structural characteristics of the operation. Specifically, it was performed to quantify effects of the economic and social factors on the level of production. Separate regression models were formulated for each set of factor patterns. This avoided problems of distinguishing differences in factor patterns from differences in how the survey questions were structured. Both models were estimated using 377 observations. The first regression equation was:

Number of Cows = 85.9890 - 4.2271Fl + 20.4088F2 - lO.4089F3 (21.2558) (10.2399) (9.9207) (11.1305)

+ 1.3484YEARS + 0.0126PAST + 0.5983PERCENT (0.6659) (0.0007) (0.3314) (1)

where F1 is economic motivations, F2 is social motivations, F3 is profit motivations, YEARS is number of years in the cow-calf business, PAST is total acres of pasture in the operation, and PERCENT is percent of net income earned from the cow-calf operation. Standard errors are given in parentheses.

The second estimated regression equation was:

Number of Cows = 81.7448 + 18.4374F4 - 0.2729F5 + 1.3282YEARS (21.5129) (10.4283) (10.7702) (0.6699)

+ 0.0128PAST + 0.8056PERCENT (0.0007) (0.3298) (2)

where F4 is social attitudes, and F5 is economic attitudes. The adjusted R2 for Eq. (1) was .524 and for Eq. (2) it was .523. All estimated

parameters had the expected signs. In Eq. (l), three variables were significant at

YOUNG, SHUMWAY, AND GOODWIN

the .05 level and one variable was significant at the . 10 level in explaining the variation in number of cows in an operation. These variables were social moti- vation, years of experience, acres of pasture, and percent of income earned from the operation, respectively. In Eq. (2), three variables were significant at the .05 level and one was significant at the .10 level in explaining the variation in number of cows in an operation. The four variables were years of experience, total acres of pasture, percent of net income earned from the cow-calf operation, and social attitudes, respectively. The expected relationship of the three structural variables was supported in each case by the parameter estimates. Pasture acreage was expected to be directly related to the number of cows that can be grazed, and years of experience and percent of income earned from the operation were expected to have a positive effect on the number of cows (holding all other variables constant).

In both models the value of the factor score for the social factor (one in each equation) was significant in explaining the number of cows the producer had. The value of the factor score for each economic factor, however, was not significant. Therefore, this regression analysis reinforces the factor analysis findings that the social factors were more clearly related to the herd size decision than were the economic factors. That is, the stronger the social motivations or attitudes, the smaller was the herd size. The stronger the economic motivations or attitudes, the larger the herd size tended to be, but these latter relationships were not statistically significant.

Income

Data on percent of household income earned from farming and ranching are reported for both groups of producers in each herd size class in Table VII. It was expected that producers who earn more of their income from farming and ranching are more likely to perceive themselves as commercial producers and may be more likely to be profit maximizers than those who earn less of their income from the farm. Producers who stated that their primary goal was to maximize profits from the cow-calf operation earned an average of 27.8% of their annual net income from farming and ranching; other producers earned an average of 7.6%

Table VII. Percent of Household Income Earned from Farming and Ranching by Herd Size and Primary Goal.

Primary Goal


Mean Percent of Income Mean Percent of Income Herd Size Frequency from Farm and Ranch Frequency from Farm and Ranch

1-49 COWS 30 15.7 13 5.8 50-99 cows 88 25.7 7 12.3 100-499 COWS 192 29.7 23 8.7 500 Cows or More 21 47.6 0 Total 331 27.8 43 7.6

-


from farming and ranching. A significant difference was found at the 1% level (t = 7.18) in the means of the two groups. Therefore, producers who earned a larger percent of their annual income from the operation were more likely to assert that they are profit maximizers.

A comparison can also be made between herd sizes, the percent of income from farming and ranching, and the question of profit maximization. Producers who primarily seek to maximize profits and have herd sizes of 500 cows or more earned an average of nearly 48% of their total annual income from farming and ranching. Comparatively, producers who had herds of less than 50 cows and did not seek to maximize profits as their primary goal earned less than 6% of their income from the farming operation.

Factor analysis results compared the weights of factor scores between operators who earned 25% or less of their income from the farming or ranching operation with those who earned more than 25% of their income from farming or ranching. Results in Table V indicate that the economic and profit motivations factors were weighted heavier by those who earned more than 25% of their income from the farming operation. One would expect the social attitudes factor to be weighted more heavily by those who earned 25% or less from the farming operation; however, the social attitudes factor was weighted significantly heavier by those who earned more than 25% from farming and ranching. The variables associated with this factor were ones pertaining to the importance of having a ranch as a way of life and a preferred environment for children. This result may imply that producers who earned a greater proportion of their income from the ranch also regarded it as a family way of life because they relied on it more heavily to support a family.

Employment

It is hypothesized that full-time operators (i.e., those who are not employed off the farm or ranch) are more likely to say they are profit maximizers. Depending on the employment status of other members of the household, operators who have other part-time or full-time employment may not be as dependent on farming and ranching for their income as those who do not work off the farm. Producers who have off-farm employment may be more likely to have cattle for other reasons such as tax advantages or simply enjoying the lifestyle of living on a ranch. L a d e ~ i g 3 ~ earlier found that nearly three-fourths of the beef cattle producers he surveyed in two areas of Texas spent 200 days or more in off-farm employment. Of all Texas cattle producers (except feedlots), census data for 1982 revealed that 64% had a principal occupation other than farming.35

In this survey, nearly 50% of the operators who said their primary goal was to maximize profits were not employed off the farm or ranch and 28% were employed full-time off the farm or ranch. For those who did not claim to be profit maximizers, an equal number (15) were not employed off the farm as were employed full-time off the farm. The off-farm employment status data for both groups of producers are reported in Table VIII. A chi-square test of independence (x2 = 2.35 with a critical ~ 2 ~ ~ , ~ = 5.99) showed that whether or not producers perceived themselves as profit maximizers was independent of whether or not they were employed off the farm or ranch. As the employment status of retired producers has no bearing on a comparison of producer goals and off-farm


Table VIII. Employment Status and Primary Goal.

Employment

Primary Goal

Profit Not Profit Maximization Maximization

Frequency Percent Frequency Percent

Not Employed off Farm or Ranch 164 49.5 15 34.9

Employed Full-Time off Farm or Ranch 92 27.8 15 34.9 Employed Part-Time off Farm or Ranch 48 14.5 5 11.6

Retired, 27 8.2 8 18.6

employment, these observations were removed from the data for this x2 test. The survey data revealed that operators with herds of less than 100 cows were

more likely to be employed off the farm than operators with larger herds. It has already been shown that producers with smaller herds were less likely to say they were profit maximizers. For producers who said their primary goal was to maximize profits, chi-square tests performed on the data in Table IX revealed that there was a dependent relationship between small and large herd sizes and whether or not the producer was employed off the farm ( x 2 = 4.34 with a critical x205,1 = 3.84). For those who did not assert that they were profit maximizers, herd size was independent of off-farm employment (x’ = 0.038 with a critical x205,1 = 3.84). To perform the x2 tests, herd size categories were combined into two groups: less than 100 cows and 100 COWS or more; employment categories were also combined into two groups: no off-farm employment and any type of off- farm employment (part or full-time) to provide cell frequencies large enough to approximate the x2 distribution.

It is also hypothesized that producers who are not employed off the farm place more emphasis on profit and economic motivations and less on social motivations for owning cattle than those who are employed off the farm. Results of the comparison of mean factor scores between these two groups of producers indicated that respondents who were not employed off the farm put significantly greater emphasis on the profit motivations factor, but producers who had some type of off-

Table M. Producer Employment Status by Herd Size and Primary Goal.a

Primary Goal


Not Employed Employed Not Employed Employed Herd Size Off-Farm Off-Farm Off-Farm Off-Farm

0-99 cows 47 56 8 10 100 Cows or More 117 84 7 10 Total 164 140 15 20

aExcluding retired producers.


farm employment placed significantly more emphasis on economic motivations and attitudes factors as well as on the social motivations factor (Table V). The economic motivations results may seem contraintuitive; however, producers who have off-farm employment may consider their cattle operation as a way to eE- ciently use the resources that they have. Also, other economic motivations such as tax advantages may be important. The importance of the social reasons could encompass many motivations such as lifestyle or being a long-standing part of the community.

CONCLUSIONS

Commercial cow-calf producers are typically assumed to be in the business to maximize the net returns to their operation even though prior rate-of-return studies raise serious questions about this assumption. In this study of Texas cow- calf producers, nearly 90% of those surveyed stated that their primary reason for being in the cow-calf business was to maximize profits. Comparisons were made between those producers who perceived themselves to be profit maximizers and those who did not. Several significant differences in the two groups were evident. Those who asserted they were in the business primarily to maximize profits had larger average herd sizes and acreages, earned a greater percent of their total income from farming and ranching, and placed more emphasis on supportive economic reasons and less on social reasons for owning cattle. However, it was not clear that either qualitative response to changes in price expectations or full- time f a d r a n c h employment status was related to the producer’s primary goal.

Factor analysis revealed two separate but related factor patterns. One factor pattern identified three general factors as important reasons for being in the cow- calf business. These three factors were profit motivations, economic motivations, and social motivations. The other factor pattern identified two factors as important attitudes of cow-calf producers. These two factors dealt with the importance of staying in the cow-calf business as a way of life for the family and the importance of considering the cow-calf business as a business venture.

Tests were conducted for significant differences in the weighting of these factors based on producer perceptions of themselves as profit maximizers and on herd size, percent of income earned from the farming and ranching operation, and off-farm employment status. Results generally reinforced the previous findings. Those who claimed to be profit maximizers placed significantly more emphasis on the economic motivations for having cattle. Producers with larger herds placed significantly more weight on the profit motivations and significantly less weight on the social motivations for owning cattle. The important relationship between social factors and herd size was further documented by regression analysis. Producers who earned a larger share of their net income from farming and ranching placed significantly more weight on profit and economic motivations and on social attitudes than did those earning a smaller share of net income from the farm. The factor analysis also revealed that producers who were not employed off the farm placed significantly more weight on the profit motivations factor and less weight on both economic and social factors than those employed off the farm.

The weighting of social attitudes by producers earning a larger share of income from farming and ranching and the weighting of social factors by producers not


employed off the farm are counter to our hypotheses and may be indicative of the complex nature of this industry, which has historically accepted unusually low average rates of return on investment. Although the evidence from this multi- faceted analysis generally supports the initial claim of those who say they are in the cow-calf business primarily to maximize profits, it is apparent that goals are not uni-dimensional. Social factors complicate simple classification of these producers. It is possible to suggest economic explanations why some of the social factors played the role they did among our surveyed producers. However, it is also possible that social factors have been responsible for keeping a substantial number of the overall population of cow-calf producers in business when their resources could have earned a greater return elsewhere.

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Profit maximization—does it matter?