Factors Impacting Production and Economic Variability in ... - ASFMRA


Factors Impacting Production and Economic Variability in ... - ASFMRA

Factors Impacting Production and Economic Variability

in Traditional Midwest Swine Enterprises

John D. Lawrence, John Shaffer, Arne Hallam and Thomas J. Baas

Traditional swine enterprises report competitive cost of production for the “top one-third” herds. Further

analysis shows that individual herds are seldom in the most profitable group every year, and nearly all

farms have an occasional good year.While long-run differences exist in cost of production across farms,

the wide variability from year to year in efficiency, costs, and returns provides a greater challenge to

existing swine enterprises.


The U.S. pork industry is changing rapidly, causing

many existing producers to question their ability to

be cost-competitive in the future. Analysis of enterprise

record systems indicated that the average producer

can be cost-competitive, but there is a wide distribution

surrounding the average.In any one year,the

cost of production mean of the high-profit one-third

of producers is consistently 25–30 percent less than

the average cost of the low-profit one-third of producers.

The narrowing profit margins in the pork

industry of the future will not likely be forgiving of

producers with 30 percent higher production cost.

Researchers and extension specialists who have

examined swine enterprise or biological performance

records have often disagreed as to the most important

determinants of profitability in hog operations. Feed

costs are often the focus of attention because they

constitute approximately two-thirds of the total cost

of production. Reproductive performance

(pigs/sow/year, pigs/crate/year, nonproductive sow

days) are also discussed as important determinants of

profit as they impact throughput and overhead cost

per pound of pork produced. More recently, with the

adoption of value-based marketing, carcass merit premiums

and lean growth have garnered more attention.

Many of these studies have either focused on a

single case study farm or have used computer models

to simulate costs and returns under alternative price

and performance scenarios.These studies fail to recognize

that producers adapt their management practices

to fit their available resources, and therefore, different

variables will be important on different farms.

The studies also fail to account for differences in managers

by accounting for a firm variable in addition to

the biological and economic variables. Relatively few

studies have examined a cross-section of farm records

over time using statistical procedures to explain differences

in profitability.

To be competitive in the pork industry, producers

must identify key factors of production that have the

greatest impact on profitability and focus management

attention on them. This paper will examine

swine enterprise records across multiple producers

and multiple years to identify which variables had the

greatest impact on long-run profitability. Second, the

analysis examines whether there is any difference in

profitability that can be attributed to the manager

over and above what is accounted for by performance

and cost variables. Third, it will summarize the variability

in cost of production of an operation over time

to determine if “top-third” producers are consistently

John D. Lawren

John Shaffer

John D. Lawrence is extension livestock economist and associate professor, Iowa State University. He has

a B.S. in animal science and an M.S. in economics from Iowa State University and a Ph.D. in agricultural

economics from the University of Missouri.

Arne Hallam

John Shaffer is a Ph.D. student in agricultural economics, University of Illinois. He received an M.S. in

economics from Iowa State University upon completion of this work.

Arne Hallam is a professor of economics, Iowa State University. He has a B.S. from Brigham Young

University and an M.S. and Ph.D. from the University of California, Berkeley.

Thomas J. Baas is extension swine management specialist and assistant professor in animal science, Iowa

State University. He has a B.S., M.S., and Ph.D. from Iowa State University.

Journal Paper No. J17494, Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project

No. 3358. Supported by Hatch Act and State of Iowa funds.

Thomas J. Baas

Current Research 101

on top.Finally,the variability of returns is examined in

a risk-return analysis and the resulting implications

for credit availability are discussed.


One yardstick that is often used as a measure of the

profitability and viability of pork production is enterprise

records. The Iowa State University Swine

Enterprise Records (ISUSER), begun by Iowa State

University Extension in the early 1970s,are often used

as a benchmark for the competitiveness of traditional

pork operations (average herd size is approximately

120 sows).Typically, 200 to 300 farrow-to-finish operations

participate in the program annually.

Previous studies have examined cost of production

across enterprises and over time to identify which

variables, under the producer’s control, impact profitability

and cost of production. Bruns et al. examined

the performance and cost variability of firms from

year to year within a subset of the record-keepers.

Edwards et al. examined, within-year, cross-sectional

data in consecutive years to identify important factors

that impacted profitability. Boland et al. identified production

variables associated with increases or

decreases in relative profitability over time. While

these studies examined key determinants in annual

profitability and variability in returns, they did not

evaluate longer-run profit determinants or the impact

of specific firm differences on profitability.

This paper examines a subset of producers using the

enterprise records over an extended period of time.

Key variables associated with long-term profitability

are identified as the fluctuation of production and

economic variables of these firms over time.

concludes with a discussion about the implications

for producers, extension personnel and allied industries

using or interpreting enterprise records.

Materials and Methods

The ISUSER are typically divided and reported by

“thirds” based on margin over all cost.The high-profit

one-third of producers each year reports production

costs that are quite competitive–near $36/cwt. since

1990. However, the same producers are seldom in the

high-profit one-third every year (Bruns et al.). Unlike

Boland et al., Bruns et al. found that ISUSER cooperators'

changed rankings from year to year in 11 key

production and economic variables during the late

1980s. Given the increased awareness of the changes

in the pork industry, this study reexamined the Bruns

et al. analysis using more recent data. The records

from 51 farrow-to-finish enterprises that participated

in the ISUSER record program for five years (1990

through 1994) were examined to determine how

their rank changed within the total population from

year to year.

The 1990 through 1994 average cost of production

for these farms was approximately $40/cwt., and the

selling price averaged $46.81, producing a $6.19/cwt.

return to management and profit (Table 1).The range

in variables among producers was as interesting as

the mean values.The five-year average for feed use per

100 pounds of hog produced varied by nearly 90

pounds (approximately 25 percent of the mean); feed

cost differed by $9.06/cwt. (38 percent of the mean);

and total cost differed by $14.70/cwt., or 46 percent

of the mean across the 51 firms. Selling price was less

variable–ranging $4.36/cwt., or less than 10 percent,

across firms.

Regression analysis is used to identify which production,

economic and firm-specific variables are associated

with differences in cost of production.A smaller

group of firms is compared over a longer time period

in a risk-and-return framework to evaluate risk associated

with hog enterprises over time. Finally, the paper

Table 1. Selected Indicators and Summary Statistics for 51 Farrow-to-

Finish Operations: 1990–1994, Five-Year Average Values

Variable Average Maximum Minimum

Net profit and return to management ($) 19,827 123,987 -15,759

Annual percent return on capital (%) 27.5 139.5 -1.2

Average price of market hogs sold ($) 46.81 48.88 44.52

Feed costs per cwt. hog produced ($) 24.60 28.84 19.78

Total cost per cwt. hog produced ($) 39.94 46.32 31.62

Margin over total cost per head sold ($) 6.19 14.51 -0.59

Birth to wean death loss (%) 14.18 25.40 3.41

Female inventory 108 240 27

Pigs weaned per female per year 15.93 20.52 10.70

Pigs weaned per crate per year 63.63 104.38 14.04

Feed efficiency (lb./cwt.) 365 410 321

Cost and performance of individual producers also

varies from year to year. Table 2 ranks variables

numerically and divides them into the appropriate

“third” category. Thus, an upper one-third ranking in

margin overall cost is “good,” but an upper one-third

ranking in total cost is “bad.”A relatively high percentage

of the 51 farms were in the

“desirable” one-third category at

least once during the five years.

More than 70 percent were in

the upper one-third of net profits

and market hog price,and the

lower one-third of feed cost and

total cost at least once in the five

years. A relatively high percentage

of the farms were also in the

least desirable one-third at least

one year. Interestingly, the percentage

of farms in the undesirable

for one-third at least one

102 1998-99 Journal of the ASFMRA

year was lower than the percentage in the desirable

one-third. About one-third of the farms were in the

desirable category three of the five years. Relatively

few farms were in the undesirable category in all five

years, suggesting that firms with multiple years of

poor performance may have exited the business and

were not available for analysis.

There is a large amount of variability in performance

in the hog enterprise over time. This conclusion is

consistent with the earlier study by Bruns et al. and

suggests that the variability exists in spite of increased

competitive pressures within the pork industry.There

are several plausible explanations why farms might

have a particularly bad year (for example, disease outbreak,

labor turnover), but it is less clear why a farm

would have a particularly good year. To examine

whether this variability from year to year is inevitable

or if it differs by firm, a cross-sectional, time-series

multiple regression analysis was performed on 49

farms (two farms had missing data) over five years.To

equalize the influence of price over time, nominal

prices in the individual year’s analysis were converted

to real prices using the GNP deflator for the analysis.

It is possible to develop a regression equation that is

a perfect cost identity,but it would be of little value in

identifying critical management decisions under the

producer’s control. The dependent variable – total

cost of production per cwt. (TCOP) – was regressed

on variables that are either a direct measure of cost.

For example, non-feed variable cost (NFVC) and fixed

cost (FC) per cwt., or a component of cost. For example,

corn price (CP) and supplement price (SP)

impact cost of gain without defining it exactly.

Including feed efficiency as a variable would result in

a near-identity-equation, creating statistical problems.

Management characteristics—such as pigs weaned

per sow per year (PSY), death loss (DL), average

slaughter weight (SW), percent of hogs sold as feeder

pigs (PFP), and hours of labor (LH)—are thought to

impact TCOP.The presence of economies of size within

the data set was examined by including sow inventory

(SI) as a variable. Dummy variables (DY) were

constructed for years Y=1991, 1992, 1993 and 1994,

with 1990 as the base year. Dummy variables (DF)

were also included for each farm (F=1, 2, ..., 48) to

identify significant differences in cost of production

across farms unaccounted for by biological performance

and input prices. The hypothesized regression

equation is



Results and Discussion

The regression results indicate that non-feed operating

costs, fixed costs, death loss, hours of labor, and

feed price are significant in explaining cost of production

differences among these farms. The regression

equation explained 86 percent of the variability

in cost of production (Table 3).As has been found in

other studies (Langemeier and Schroeder, and

Edwards et al.), economies of scale were not present

in these data. The coefficient on sow inventory was

not significant at the 10 percent level. Contrary to

other studies (Edwards et al.),pigs per female per year

was not a significant variable in explaining cost differences.The

hog enterprises in this study have relatively

low fixed cost. Improved reproductive efficiency

reduces overhead, sow feed, and genetic costs by

dividing these items by more pigs, and these costs are

relatively small expenses in this type of operation. In

addition, farms that have higher sow herd performance

may have had greater costs or investment to

achieve it. Average sales weight also did not significantly

affect production cost.

Table 2. Percent of Producers in the Upper (U) or Lower (L) One-Third Ranking for Economic and

Production Variables for One to Five Years, 51 Operations, 1990–1994

Number of Years in Either the Upper or Lower Third Ranking*

1 2 3 4 5

Upper or Lower One-Third Ranking U L U L U L U L U L

Net profit and return to management 76 69 43 47 33 22 24 8 6 0

Annual percent return on capital 69 78 47 57 35 29 18 14 8 2

Average price of market hogs sold 73 67 39 55 27 33 18 14 10 8

Feed costs per cwt. hog produced 55 75 37 49 25 33 16 16 4 12

Total cost per cwt. hog produced 59 71 37 59 24 35 14 20 6 6

Margin over total cost per head sold 69 67 45 45 33 29 14 20 8 6

Birth to wean death loss 69 59 49 33 39 24 33 18 27 4

Female inventory 47 39 39 35 39 33 24 27 12 27

Pigs weaned per female per year 67 61 55 37 39 20 24 16 12 4

Pigs weaned per crate per year 61 47 43 31 39 24 24 20 12 16

Feed efficiency (lb./cwt.) 55 78 35 49 24 37 12 24 2 10

* For example, 76% of the producers were in the upper one-third of the population at least once in five years, and

67% were in the lower one-third at least once in five years. Likewise, only 6% (2 of 51) were in the upper one-third all

five years.

Current Research 103

The dummy variables for individual years were not

significant compared with the base year 1990, suggesting

that year-to-year changes other than prices did

not impact cost. Thus, stressful years, such as 1993

(poor crops and flooding), did not significantly affect

cost nor have producers significantly improved cost

efficiency over time.

Table 3. Multiple Regression Estimates of Costs of Production: 49

Farms, 1990-1994 a

Independent Variable Name Coefficient t-statistic

Non-feed variable cost ($/cwt.)) NFVC 1.0509 b 9.273

Fixed Cost ($/cwt.) FC 1.3151 b 12.320

Selling weight (lbs.) SW 0.0002 0.009

Death loss birth-market (%) DL 0.0485 b 1.952

Female inventory SI -0.0101 -1.261

Pigs/female/year PSY -0.0847 -1.490

Hours of labor/cwt. HL 4.2878 b 5.207

Corn price ($/bu.) CP 5.9772 b 3.509

Supplement price ($/cwt.) SP 0.2718 b 3.073

Percent feeder pigs PFP 3.4476 1.246

Constant 9.2404 1.143

R 2 =.86

a Dependent variable is total cost per cwt. b Significant at the 5% level.

Table 4. Mean for 49 Hog Enterprises, 1990–1994, Grouped by Farms

With Significantly Lower Cost of Production Due to Farm Differences


Lower Cost


Farm-Specific Management Differences

Seventeen of the 49 farm identification variables (DF)

were significant–indicating that, even after accounting

for price and production differences, some farms

have lower costs than others.The farm identification

dummy variables on these 17 farms were significantly

negative at the 5 percent level, indicating that they

had lower cost of production than did the base farm.

These results suggest that there are farm-level management

decisions or characteristics, which impact

cost of production, that are not fully captured in efficiency

or price variables. In Table 4, the mean of variables

of the farms with significantly lower cost of production

is compared to that of the remaining farms,

using the student t-test. In addition to the total cost

variable used to sort the two groups, other variables

were also significantly different.Although the groups

represented similar sized operations (94 and 117

sows), the mean herd sizes were significantly different,

and low-cost herds within this data set had smaller

sow herds. Feed efficiency and feed costs were significantly

lower for the low-cost group.The low-cost

farms had higher investment per female and produced

fewer pigs per crate per year than did the other

group. One explanation may be that the greater

investment was in nursery and/or grow-finish facilities

that improved the efficiency and growth rate of

the market herd (market weights were significantly

higher) rather than the breeding herd.

Not Significantly

Lower Cost


Net profit and return to management ($) 20,051 19,118

Annual percent return on capital (%) 28.62 26.35

Average price of market hogs sold 45.91 46.26

Feed costs per cwt. hog produced ($) 22.86 a 25.46

Total cost per cwt. hog produced ($) 38.57 a 40.83

Margin over total cost per head sold ($) 7.35 5.43

Fixed cost per female ($) 202.45 a 134.82

Average market weight (lbs.) 245 a 242

Birth to wean death loss (%) 14.95 13.82

Female inventory 94 a 117

Pigs weaned per female per year 15.70 15.97

Pigs weaned per crate per year 59.10 a 65.22

Feed efficiency (lbs./cwt.) 354 a 372

a Significantly different at 5% level.

The regression model indicated that variables often

identified as having a large impact on cost of production,

such as sow inventory, sow

productivity, and market hog

slaughter weight, did not significantly

explain the differences in

cost among farms in this study.

However, when firms that were

identified as having significantly

lower costs were compared to

average-cost firms, the low-cost

firms had a smaller average herd

size and higher average slaughter

weight. Feed price, labor

hours, non-feed operating

cost/cwt. and fixed cost were

also significant variables in

explaining differences between

these two groups. Investment,

pig flow and where the dollars

are invested were significant in

separating more intangible cost

differences among firms.

Long-Run Risk and

Return of Swine Enterprises

Although swine enterprises

have a reputation for improving

cash flow on diversified farming

operations, the five-year analysis

indicates that performance and

returns can vary considerably

from year to year for the individual

farm.To examine returns

over a longer time period,

records from 22 farms were

examined over eight years, 1987

through 1994. Although observations

are limited, this analysis

104 1998-99 Journal of the ASFMRA

provides an opportunity to examine the risk-return

profile of these farms. Borrowing from financial theory,

risk is defined as the standard deviation of the rate

of return on capital or an asset (Shapiro).This risk is

compared to the average annual return on capital

over the eight years to identify a two-dimensional

index for the farm.

The risk return profile of the 22 farms is shown in

graphical form in Figure 1. The farms lying to the

north and west in the graph are on the efficient frontier

of this set, producing the highest

return for a given level of risk or the least

amount of risk for a given level of return.

Farms that are inside the efficient frontier

(to the south and east) have less desirable

returns because they have higher risks in

achieveing the same rate of return. Swine

enterprises that produce a low return relative

to the amount of variability in

returns will have greater difficulty attracting

the owners’ capital from other uses. It

will also have difficulty attracting debt


investment and production efficiency. While not

enough is known about these farms to fully explain

the differences in risk and return, noteworthy differences

do exist.

Farm 1 had an average female inventory of 232 head

compared with 65 for Farm 2 and 128 for Farm 3.

Farms 1 and 2 had better feed efficiency, reproductive

performance and lower cost of production than Farm

3. Farms 1 and 3 have similar annual fixed costs and

annual returns on capital but quite different levels of

The average annual return to capital for

these firms was more than 26 percent,but

the range was from 4 to 61 percent over

the eight years. A

measure of the

invested capital is

annual fixed cost

per female, which

averaged $175.95

across all farms and

years. The range

was from $40.94 to


Three individual

farms are identified

in Figure 1 for closer


Farms 1 and 2 are

on the efficient

frontier while Farm

3 has comparable

returns to those of

Farm 1 but more

than twice the variability

in returns.

See Table 5 for a

summary of the

three farms identified

in Figure 1.

These farms differ

in herd size,level of

Table 5. Summary Statistics for Three Selected Hog Farms Over Years 1987–1994.

Mean Std. Dev. Maximum Minimum

Farm 1

Annual return to management ($) 69,119 41,098 144,720 -1,904

Annual percent return to capital (%) 35.87 15.60 60.18 7.70

Total cost of production ($/cwt.) 36.89 3.52 43.87 31.11

Margin per head sold ($) 8.82 5.41 20.65 2.94

Annual fixed cost per female 125.44 22.63 152.15 92.95

Average female inventory 232 11 252 216

Pigs weaned per female per year 16.84 1.14 18.60 15.59

Whole herd feed efficiency 358 17 381 337

Farm 2

Annual return to management ($) 27,391 12,225 43,587 10,628

Annual percent return to capital (%) 61.22 24.53 92.25 28.35

Total cost of production ($/cwt.) 35.56 2.70 39.40 31.85

Margin per head sold ($) 10.91 4.99 19.41 4.05

Annual fixed cost per female 142.51 15.11 163.59 121.49

Average female inventory 65 10 79 49

Pigs weaned per female per year 17.62 3.12 22.46 13.47

Whole herd feed efficiency 341 11 356 324

Farm 3

Annual return to management ($) 22,584 37,695 77,725 -51,890

Annual percent return to capital (%) 35.31 36.07 88.42 -30.02

Total cost of production ($/cwt.) 39.59 4.29 44.45 31.34

Margin per head sold ($) 7.12 7.28 20.87 0.34

Annual fixed cost per female 114.73 13.91 132.60 88.45

Average female inventory 128 18 158 103

Pigs weaned per female per year 15.91 1.99 18.64 11.80

Whole herd feed efficiency 375 24 415 335

Current Research 105

isk. The differences in risk appear to come from a

variety of sources (variability in feed efficiency, reproduction,

inventory) rather than any one factor.

Summary and Implications

Swine enterprises on diversified farms may reduce

total farm income variability compared with specialized

cropping operations. However, a great deal of

variability exists from year to year within swine

enterprises.As a result,farms with comparable returns

on assets may have quite different risk profiles.

Financial markets, including agricultural credit markets,

have favored less risky investments for a given

level of return.The risk return analysis indicates that

farms of quite different sizes can operate on the efficient

risk return frontier. Existing swine producers

have been, and can continue to be, profitable, but the

data indicates that even profitable operations will

occasionally have a bad year. Successful swine enterprises

in the future will be those that can generate

both a profitable and predictable return on investment.


Boland, M.A., K.A. Foster, G.F. Patrick, J.R. Foster, and D.E.

Orr. 1993. “Examining the Linkages Between Productivity

and Profitability in Swine Enterprises.” Journal of the

American Society of Farm Managers and Rural Appraisers


Bruns, M., K. Kliebenstein, J. Lawrence, and E.J. Stevermer.

1992. Iowa Swine Enterprise Return and Production

Variability. 1992 Swine Research Report, Iowa State

University, Ames, IA.

Edwards, W.M., G.T. van der Sluis, and E.J. Stevermer. 1989.

“Determinants of Profitability in Farrow-to-Finish Swine

Producers.” North Central Journal of Agricultural Economics


Langemeier, M.R. and T.C. Schroeder. 1993. “Economies of

Size for Farrow-to-Finish Hog Production in Kansas,” in

Swine Day 1993, Report of Progress 695. Agricultural

Experiment Station, Kansas State University, Manhattan,

KS, November.

Shapiro, Alan C. 1990. Modern Corporate Finance. New York,

NY: MacMillan Publishing.

Critical success factors that determine swine enterprise

profitability are not easily identified as significant

variables and, in this cross-sectional analysis, are

not the popularly discussed variables of market

weight and reproduction. These results suggest that

there is more than one method of profitable pork production.

In addition, firm-specific characteristics

above and beyond production performance and price

variables also influenced profitability.

Extension personnel, farm managers and allied industries

working with producers must focus on the individual

operation, its resource base and unique management

skills of the producer when making management

recommendations. Enterprise evaluation also

requires accurate production and financial records to

confidently diagnose problems and identify solutions.

It is important to evaluate an operation over time

against its past records as well as how it relates to a

common database.The year-to-year variability within

an enterprise may suggest larger problems than a

snapshot ranking of how the enterprise compares to

other operations in any one year.

106 1998-99 Journal of the ASFMRA

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