United States

Department of

Agriculture

Rural Business–

Cooperative

Service

RBS Research

Report 180

Grain Cooperative

Mergers and

Acquisitions, 1993-97
Abstract RBS began keeping detailed statistics on mergers, acquisitions, consolidations, bankruptcies, and other “M/C” activities in 1993. Of the 367 events involving grain cooperatives, most occurred in recent years (53 percent in 1996 and 1997), and among cooperatives having less than $15 million in total sales (63 percent). These cooperatives

were located principally in the heartland. Eighty-seven percent occurred in either the

Corn Belt or the Southern Plains. Almost 70 percent (252 of 367) involved cooperatives merging with another. A small number of cooperatives either merged with (9) or

were acquired by (18) investor-owned-firms.

This report analyzes the operational and financial characteristics of the cooperatives

that were merged or consolidated (M/C) during 1993-97. The report also frames M/C

and surviving cooperatives in the context of agriculture’s economic restructuring.

Lessons learned provide insights to the challenges that lie ahead for grain cooperatives hoping to thrive. 

April 2001
Executive

Summary The goal of this study was to answer some questions about the financial health of

grain cooperatives involved in mergers, acquisitions, and the other related activities.

Compared were cooperatives involved with counterparts and those merged with or

acquired by investor-owned firms (IOFs).

Grain cooperative balance sheets and operating statements were used to construct a

set financial ratios. They were used to compare M/C cooperatives with national averages for grain cooperatives of their same relative size. Selected ratios represent four

general aspects of a business: profitability,liquidity,efficiency, and solvency.

An economic model was also constructed to evaluate the likelihood of a grain cooperative going out of business in the near term given its financial performance record. A

three-variable “best fit” was selected from among the 14 ratios using the score criterion

for each of two size groups. Maximum likelihood estimates, related statistics, and an

interpretation of the ”best fit” model for each group are provided.

This report discusses M/C and surviving cooperatives in the context of agriculture’s

economic restructuring. Lessons learned provided insights to the challenges that lie

ahead for grain cooperatives in an increasingly competitive environment.

i
Contents

i
Contents Executive Summary ...................................................i

Grain Cooperative Characteristics .......................................1

Are Best Co-ops ‘Cherry-Picked?’ ......................................10

Predicting Mergers, Acquisitions .......................................11

Horizontal, Vertical Integration .........................................14

Summary, Conclusions ...............................................15

References ........................................................15

Appendix 1— Score Criterion Results to Select Three-Variable

“Best Fit” Model .........................................16

Appendix 2 — Logistic Regression Results with Diagnostics, 

3-Variable Final, by Size ..................................19

iii
Grain Cooperative Mergers and

Acquisitions, 1993-97

Anthony Crooks

Agricultural Economist

Rural Business-Cooperative Service

U S D A’s Rural Business-Cooperative Service has

kept detailed statistics mergers,1 acquisitions,2 consolidations,3 bankruptcies, and other related (M/C) activities since 1993 (table 1). For the 5-year period 1993-97,

there were 367 M/C events out of an average of 997

grain cooperatives (or 7.3 percent/year). Most (198)

occurred in 1996 and 1997 and among cooperatives

having less than $15 million in total sales (64 percent).

Most activity was located principally in the grain

producing heartland – 87 percent in the Corn Belt and

Southern Plains regions (table 2). Of the 367 cooperatives that were merged and consolidated, 330 had total

sales of at least $5 million and were located in the principle grain producing regions. This report focuses on

the 330 cooperatives.

Figure 1 shows the number of cooperatives

involved in each type of activity. Almost 74 percent

(246 of 330) involved cooperatives that merged with

one another. A limited number of cooperatives were

either merged with (8 of 330) or acquired by (14)

investor-owned firms (IOFs).

Grain Cooperative Characteristics

Storage Capacity — During 1993-97, grain cooperatives with total sales of at least $15 million had an

average storage capacity of just over 4.6 million

bushels (table 3). They conducted business from at

least 4 elevator locations, employed an average 51 fulland part-time workers, and owned at least 1 unit-train

loading facility. While M/C grain cooperatives of the

1

Table 1—Number of Grain Cooperatives In and Out of Business, 1992-97, by Year and Size in Total Sales

Grain cooperative size in Total Sales Grain cooperative size in Total Sales

———————————————---———— —————————————————————

$15 million Between $5 Less than $15 million Between $5 Less tha

Year or more and $15 $5 million ALL Year or more and $15 $5 million ALL

Number of cooperatives “In Business” Number of cooperatives "Out of Business"

1992 419 570 204 1,193

1993 405 537 203 1,145 1993 14 33 1 48

1994 384 495 191 1,070 1994 21 42 12 75

1995 370 463 191 1,024 1995 14 32 0 46

1996 326 408 186 920 1996 44 55 5 104

1997 286 357 183 826 1997 40 51 3 94

Average 354 452 191 997 Total 133 213 21 367

1 Control of different cooperatives (corporations) is vested into a

single one by issuing of stock in the controlling organization in

place of a majority of stock in the other(s) without dissolution of

the consolidating companies.

2 The assets of one cooperative (corporation) are purchased by

another using either cash or other assets.

3 Control of different cooperatives (corporations) is vested into a

single one by issuing of stock in the controlling organization in

place of a majority of stock in the other(s) and the dissolution of

the consolidating companies.
same size operated from the same number of elevator

locations, they had 24 percent less capacity, employed

11 fewer workers, and had 2 load-out facilities. Grain

cooperatives with total sales between $5 million and

$15 million had just over 3.6 percent greater capacity

than those which were merged or consolidated.

Balance Sheet — Grain inventory among all

large cooperatives averaged slightly greater than $3.5

million during the 5 years (table 4) . Farm supply

inventory averaged about $1.7 million. Total inventory

averaged just under $5.2 million. While the large M/C

cooperatives had 9.4 percent more grain inventory,

they carried 40.4 percent less farm supply inventory.

Total inventory averaged $4.8 million, or 6.6 percent

less.

Medium-sized grain cooperatives carried an

average grain inventory valued at $698,428 or 32.8 percent ($927,321) less than their M/C counterparts and

2

Table 2—Number of Grain Cooperatives Out of Business, 1993-97, by Region and Size

Grain Cooperative Size by Total Sales

—————---------------------————————————————

$15 million Between $5 Less than

Region or more and $15 million $5 million ALL

Number of cooperatives "Out of Business"

Corn Belt 102 156 12 270

Southern Plains 8 40 48

Norhtern Plains 15 4 7 26

Pacific Northwest 1 4 5

Other 7 9 2 18

Total 133 213 21 367

Figure 1—Grain Cooperatives “Out of Business,” by Reason, 1993-97

Merged w/Co-op

Acquired by Co-op

Consolidated w/Co-op

Acquired by IOF

Merged w/IOF

Bankruptcy

Unknown Reason

0 50 100 150 200 250

34 246

10

14

8

10

8
13.8 percent less farm supplies. The M/C cooperatives

carried on average one-quarter (25.7 percent) more

total inventory than the national ("in business") average.

Large M/C cooperatives held 7.2 percent fewer

current assets, invested 3.1 percent less in other cooperatives, and held 18 percent less fixed assets than the

national average of large in-business cooperatives. In

contrast, medium-sized M/C cooperatives had 10.4

percent more current assets, 59.6 percent more cooperative investments, and 12.4 percent more fixed assets

than their operating counterparts.

3

Table 4—Grain Cooperative Balance Sheet Statistics: "In Business" and "Merged/Consolidation,” by Size,

5-year Means, 1993-97

Total Sales of $15 million or more Total Sales of between $5 to $15 million

----------------------------------------------------------------------- --------------------------------------------------------------------------------

In Merged/ Percent In Merged/ Percent

Business Consolidated Difference Business Consolidated Difference

Dollars Dollars

Grain inventory 3,524,000 3,856,000 -9.4 698,428 927,321 -32.8

FS inventory 1,670,000 994,880 40.4 415,008 472,429 -13.8

Total inventory 5,194,000 4,850,880 6.6 1,113,436 1,399,750 -25.7

Current assets 7,860,000 7,292,000 7.2 1,944,000 2,146,000 -10.4

Cooperative invest. 1,920,000 1,860,000 3.1 578,346 923,025 -59.6

Fixed assets 3,464,000 2,842,000 18.0 914,538 1,028,285 -12.4

Other assets 193,508 139,273 28.0 44,882 69,245 -54.3

Total assets 13,437,508 12,133,273 9.7 3,481,766 4,166,554 -19.7

Short term debt 2,762,000 2,010,000 27.2 572,039 876,782 -53.3

Patronage refunds 176,614 99,787 43.5 57,259 46,528 18.7

Other current liab. 3,914,000 4,350,000 -11.1 879,664 774,714 11.9

Total current liab. 6,852,614 6,459,787 5.7 1,508,962 1,698,025 -12.5

Long term liab. 1,189,694 788,345 33.7 252,626 316,779 -25.4

Stock 1,366,000 1,708,000 -25.0 455,085 670,003 -47.2

Allocated equity 4,029,177 3,177,119 21.1 1,265,071 1,481,724 -17.1

Unallocated equity 1,938,000 1,496,000 22.8 688,434 635,399 7.7

Total equity 5,395,199 4,885,141 9.5 1,720,178 2,151,750 -25.1

Total L&OE 13,437,508 12,133,273 9.7 3,481,766 4,166,554 -19.7

Table 3—Grain Cooperative Capacity, Locations, Workforce, and Number of Unit Trains, 

5-year Means, 1993-97

Total ales of $15 million or more Total Sales between $5 and $15 million

------------------------------------------------------------------ ---------------------------------------------------------------------

All Grain Cooperatives Merged/Consolidated All Grain Cooperatives

Merged/Consolidated

Cooperatives Cooperatives

No. of Obs. Mean No. of Obs. Mean No. of Obs. Mean No. of Obs. Mean

Elev. Cap 1,376 4,606,000 92 3,512,000 1,288 1,458,000 62

1,407,500

No. Locations 1,457 4 95 4 1,404 2 69 2

Full-time workers 1,454 40 93 32 1,364 11 65 11

Part-time workers 1,309 12 85 7 1,020 4 45 3

Total workforce 1,467 51 96 39 1,400 14 68 13

No. Unit trains 1,389 1 86 2 1,263 0 62 1
Large M/C cooperatives also held current and

long-term liabilities of 5.7 and 33.7 percent less, respectively, than the national average of large in-business

cooperatives. On the other hand, medium-sized M/C

cooperatives held 12.5 percent more current liabilities

and 25.4 percent more long-term liabilities than with

the national average of medium-sized in-business

cooperatives.

The national average of in-business cooperatives

for patronage refunds was greater in both size groups

than in the M/C cooperatives. Large cooperatives paid

43.5 percent more and the medium cooperatives paid

18.7 percent more to their respective membership.

In general, members of medium-sized M/C cooperatives held 25.1 percent more equity than the national average of similar-sized cooperatives still in business but the large M/C cooperatives held less equity.

Medium-sized M/C cooperatives issued almost half

again as much stock (47.2 percent) and held 17.1 percent greater allocated equity than in their surviving

cohorts. Their unallocated equity was 7.7 percent less

than the national average.

In addition, while the large M/C cooperatives

carried one-fourth more stock, they held 21.1 percent

less allocated equity, 22.8 percent unallocated, and

held 9.5 percent less total average equity compared

with the national average.

Operating Statement — These statistics show

the relative strength of the medium-sized M/C cooperatives compared with the medium-sized cooperatives

staying in business, but in a less dramatic fashion

(table 5). Average grain sales and total sales were 8.6

and 5.4 percent less, respectively, for the medium-sized

M/C cooperatives. Moreover, while gross margins

averaged 16.7 percent higher, grain margins wereoff

the national average by more than a fifth (20.6 percent). In terms of non-operating income and total revenue, the M/C cooperatives were particularly strong,

at 17.2 and 98.7 percent more,respectively, than the

national average. However, their total expenses were

also significantly higher (28 percent) than the national

average. Consequently, average M/C cooperative net

income was 27.3 percent lower than the national average for medium-sized grain cooperatives.

4

Table 5—Grain Cooperative Operations Statistics: "In Business" and “Merger/Consolidated”, by Size,

5-year Means, 1993-97

Total Sales of $15 million or more Total Sales of between $5 to $15 million

----------------------------------------------------------------------- --------------------------------------------------------------------------------

In Merged/ Percent In Merged/ Percent

Business Consolidated Difference Business Consolidated Difference

Dollars Dollars

Grain sales 27,460,000 28,700,000 -4.5 7,132,000 6,520,000 8.6

Supply sales 9,434,000 8,650,000 8.3 2,468,000 2,532,000 -2.6

Total sales 36,560,000 37,340,000 -2.1 9,476,000 8,968,000 5.4

Grain margins 986,420 831,479 15.7 286,844 227,876 20.6

Gross margins 2,484,000 1,678,000 32.4 618,433 721,413 -16.7

Other co-ops. income 1,212,000 868,420 28.3 324,463 405,216 -24.9

Patronage received 314,080 314,931 -0.3 86,618 136,298 -57.4

Net interest -269,200 -193,331 28.2 -45,907 -95,338 -107.7

Total non-co-ops.income 72,800 144,677 -98.7 46,208 54,170 -17.2

Total revenue 3,766,000 2,694,000 28.5 987,650 1,176,000 -19.1

Labor expenses 1,404,000 995,605 29.1 388,271 486,536 -25.3

Other expenses 1,700,000 1,374,000 19.2 463,969 596,847 -28.6

Total expenses 3,178,000 2,376,000 25.2 828,002 1,059,928 -28.0

Net income before taxes 588,000 318,000 45.9 159,648 116,072 27.3

Cash paid 178,705 100,877 43.6 59,401 49,554 16.6

Dividends 19,019 1,827 90.4 9,250 15,866 -71.5

Allocated equity 218,054 169,708 22.2 43,074 51,558 -11.9

Unallocated equity 111,652 14,181 87.3 35,320 -8,350 123.6

Income tax 60,570 31,407 48.1 12,603 7,445 40.9
National averages for the large cooperatives also

outperform those of the large M/C cooperatives.

Except for grain sales, total sales and non-operating

income, the national average was more than the M/C

average in all categories. Consequently, the net income

average was 45.9 percent higher than that of the M/C

cooperatives.

Grain Volumes — Total grain volume marketed

for large M/C cooperatives was 16 percent more than

the 5-year national average of in-business cooperatives

(table 6). This figure is consistent with the 4.5 percent

greater average in large M/C cooperative grain sales

reported in the operating statement. Much of the

greater volume is concentrated in the small grains

(wheat and barley) areas.

While the overall grain volume marketed by

medium-sized M/C cooperatives was 5.3 percent less

than the national average of in-business medium-sized

cooperatives, the former traded significantly more

corn and soybeans. M/C cooperative volumes for

these crops were 34.7 and 49.7 more,respectively, than

the national average of in-business medium-sized

cooperatives.

Financial Characteristics

A summary look at balance sheets and operating

statements led to some suggestions about the overall

financial condition of grain cooperatives (M/C or otherwise) in the heartland. Data from individual grain

cooperative balance sheets and operating statements4

were also used to construct a set of financial ratios.

They were used for direct comparisons of the M/C

groups of businesses with those remaining in business

and with CoBank’s benchmarks for good operating

practices.

The financial ratios used are associated with four

general aspects of a business: profitability, liquidity,

efficiency, and solvency. Selected ratios in each of the

four categories were used to compare the M/C cooperatives (by their M/C reason) with their national averages by size to draw inferences about the general

nature and financial condition of these businesses.

Profitability — This describes the cooperative’s

ability to generate net savings. Profitability indicators

generally compare the "returns" of the business (net

income or net savings, from the operating statement)

with another aspect of the cooperative’s business.

Three ratios -- returns to total assets, return to fixed

assets, and return to equity -- compare the firm’s present profitstream with previous years.

National and regional returns to total assets averaged on or slightly less than benchmark levels of 8 percent for large cooperatives, but were 2 to 3 percent off

those levels for medium- sized cooperatives (table 7).

Returns for M/C cooperatives, however, were substantially less. Large M/C cooperatives accrued zero

returns to total assets on average while medium-sized

M/C cooperatives incurred negative returns of -1 percent. Large M/C cooperatives that were involved with

5

Table 6—Grain Cooperative Volume Statistics: "In Business" and “Merged/Consolidation,” by Size, 5-year

Means, 1993-97

Total Sales of $15 million or more Total Sales of between $5 to $15 million

----------------------------------------------------------------------- --------------------------------------------------------------------------------

In Merged/ Percent In Merged/ Percent

Business Consolidated Difference Business Consolidated Difference

Dollars Dollars

Grain sales 27,460,000 28,700,000 -4.5 7,132,000 6,520,000 8.6

Wheat 1,944,000 3,116,239 -60.3 759,475 244,870 67.8

Corn 5,052,000 5,214,000 -3.2 969,355 1,305,638 -34.7

Soybeans 1,826,667 1,096,199 40.0 434,950 651,083 -49.7

Sorghum 1,316,000 1,205,335 8.4 447,049 331,336 25.9

Barley 746,489 1,678,084 -124.8 305,918 32,769 89.3

Other grain 176,114 525,503 -198.4 97,751 18,219 81.4

4 Financial ratios were constructed for each cooperative by using the

five most recently received financial statements. To account for the

impact of the absent M/C cooperatives on overall means, regional

and national means were constructed in a two-step process. First a

5-year rolling average of surviving cooperatives was generated.

The mean of the rolling average for each indicator was taken to

generate the overall result.
another cooperative averaged 1 percent or less, regardless of whether they merged, were acquired, or consolidated. Medium-sized M/C cooperatives performed

almost as poorly.

Return-to-fixed-assets indicates the firm’s rate of

return to property, plant, and equipment. Firms aspire

to a 30-percent rate of return on fixed assets.

Nationally, grain cooperatives remaining in business

for the 5-year period achieved only 27 and 22 percent

return, for large- and medium-sized cooperatives,

respectively. M/C cooperative return-to-fixed-assets

suggests these groups endured low income during the

period or were heavily invested in plant and equipment. Only large cooperatives that merged with an

IOF or went bankrupt approached double digit returnto-fixed-assets (11 and 14 percent, respectively). All

other M/C cooperatives (large and medium-sized)

experienced small or negative return on fixed assets.

Return-to-equity relates the cooperative’s present

profit to its accumulated wealth. Ideally, a firm will

generate profits equivalent to about 10 percent of its

equity a year. By this measure, grain cooperatives with

national average return of 16 and 11percent, respectively,forlarge and mid-sized, must be pleased.

However,return-to-equity among M/C cooperatives

were disappointing, as with the other two indicators.

Patronage received from investments and business in other cooperatives is a vital portion of grain

cooperative income. Unfortunately, apart from patronage received, many grain cooperatives would show

negative income. Therefore, it’s important to distin6

Table 7—Profitability Indicators: National, Regional, and “M/C” Cooperatives By Reason, 5-year Means, by

Size, 1993-97

Total Sales of $15 million or more Total Sales between $5 and $15 million

------------------------------------------------——————————— ------------------------------------------------------————————

Labor Local

Return to Return to Return to Return to Return to Return to Return to Return to

Total Assets Fixed Assets Equity Local Assets Total Assets Fixed Assets Equity Local Assets

In Business 

Cooperatives

National 0.08 0.27 8 00.8 0.39 8

Corn Belt 0.08 0.29 0.18 0.06 0.07 0.26 0.13 0.05 

Southern Plains 0.08 0.30 0.15 0.07 0.06 0.22 0.09 0.05 

Northern Plains 0.06 0.29 0.18 0.05 0.06 0.26 0.14 0.05 

Pacific Northwest 0.09 0.22 0.14 0.08 0.06 0.12 0.08 0.05 

M/C Cooperatives 0.00 0.03 0.00 (0.02) (0.01) (0.03) (0.02) (0.03)

By Reason:

Merged w/

Co-op 0.01 0.03 0.02 (0.02) 0.02 0.05 0.03 (0.01)

Acquired by

Co-op 0.00 0.00 0.00 (0.02) (0.02) (0.06) (0.04) (0.05

Consolidated w/

Co-op 0.01 0.02 0.01 (0.03) 0.00 0.00 0.00 (0.01)

Merged w/ IOF 0.04 0.11 0.06 0.02 (0.01) (0.07) (0.04) (0.05)

Acquired by IOF (0.09) (0.13) (0.18) (0.09) (0.02) (0.06) (0.06) (0.04)

Bankruptcy 0.03 0.14 0.09 0.01

Unknown

Reason (0.02) (0.06) (0.03) (0.03)

Benchmark 0.08 0.30 0.10 0.03 0.08 0.30 0.10 0.03

Return to Total Assets -- Net income / Total assets

Return to Fixed Assets -- Net income / Fixed assets

Return to Equity -- Net income / Equity

Local return to local assets -- Net income (less patronage received) / Total assets (less cooperative investments)
guish the return that is generated from the business’

own activities vis-a-vis those received from investments in other cooperatives, i.e., the share in the profitability of other cooperative managers’ abilities.

Local-return-to-local-assets reports only the

returns that the cooperative generated from its own

activities using its own assets. The importance of the

overall contribution of cooperative patronage income

to a grain cooperative’s bottom line is reflected in the

1or 2 percent difference between the return to total

assets and the local return rate. The prosperity of the

1993-97 period is also reflected in these very robust

rates of local return that arefrom 2 to 4 percentage

points higher than the benchmark.

The importance of patronage received is also

made clear particularly among the M/C cooperatives.

The local-return-to-local-assets for the two groups of

M/C cooperatives were generally negative and ranged

from 1 to 3 percentage points less than their respective

totalreturn. Only large cooperatives that merged with

an IOF (2 percent) or went bankrupt (1 percent)

accrued a positive local return.

Liquidity — Firms, and their creditors, have a

strong preference for a margin of safety against the

uncertainties grain cooperatives face. Liquidity speaks

to a cooperative’s ability to generate cash in the short

term in case of random shocks, extraordinary losses, or

other such uncertainties. Liquidity indicators relate the

current assets of the cooperative to its current liabilities. The more current assets relative to current liabilities, the greater the assurance that a firm’s liabilities

may be paid out of these assets.

The current ratio represents the excess of current

resources over current obligations. The quick ratio also

measures excess current resources over current obligations, after accounting for the firm’s inventory.

In general, grain cooperatives were less diligent

in keeping liquid accounts throughout the period as

their creditors might have preferred (table 8). National

current and quick ratio averages for the large-sized

cooperatives wereoff the 1.5 current ratio benchmark

at 1.32 and fell short of the 0.80 quick at 0.68. The

national average for medium-sized cooperatives was

slightly more liquid, at 1.56 and 0.85, respectively,for

the two ratios.

Among cooperatives going out of business, only

the medium-sized cooperatives that consolidated with

another cooperative held liquid accounts with both

measures exceeding the benchmark. Among the large

M/C cooperatives, however, those that merged with

an IOF held the most liquid accounts during the period and were not far off the desired levels of liquidity

at 1.41 and 0.76 for current and quick ratios, respectively.

W orking capital to sales is a measure of the ability of a firm to meet its short-term obligations in relation to its business volume. Generally, the large cooperatives did not come as close as the medium-sized

ones to meeting the 7 percent ideal. National averages

for the two sizes were 4 and 6 percent, respectively.

Among the cooperatives going out of business,

large cooperatives that merged with an IOF had a

robust working capital to sales rate of 8 percent. All

other M/C groups reported noticeably lower rates

than the benchmark, with medium-sized cooperatives

1 to 2 percentage points higher in all but the one previously mentioned group.

Efficiency — These indicators intend to provide

some measure of how well the firm is managed.

Because there is no direct measure for "management

ability," these indicators serve as a proxy for two

aspects of a manager’s job: holding down costs and

making the best use of the firm’s resources (e.g., facilities and labor).

Ratios that compare expenses, either total or

labor expenses (the largest share of total expenses),

with levels of revenue and/or income provide a measure of the productivity of the workforce. The productivity ratio relates total expenses to total sales. At the

national level, both large and medium-sized grain

cooperative managers successfully held total expenses

below 10 percent of total sales (table 9). On the other

hand, labor expenses exceeded the desired rate of 35

percent of income for both groups. This twin result of

controlled total expenses and slightly higher than

desired labor expenses might reflect not only a rising

wage rate, but also the growing demand among agricultural workers for health care and retirement benefits. It might also reflect the commensurate struggle

among cooperative managers to attract and keep their

best people while trying to limit total costs.

Managers of the M/C cooperatives were somewhat successful in keeping both labor and total

expenses in check. The one exception was that large

cooperatives that merged with an IOF had unusually

large total expenses -- amounting to 15 percent of total

sales.

Efficient use of a business’ facilities involves limiting inventory storage time. Inventory turnover

relates the number of dollars in sales generated per

dollar of inventory and provides a gauge for the coop7
erative’s efficient use of storage facilities during the

accounting period. For most grain cooperatives, this

involves both grain inventory and farm supplies.5

Farm supply turnover rates among all grain

cooperatives would suggest a less efficient use of

inventory (bin, shelf, or tank, etc.) space than might be

called for. The national inventory turnover rate was 8

times for both large and medium-sized cooperatives.

Among the M/C cooperatives, those involved with

another cooperative in merger, acquisition, or consolidation seem to be the most efficient users of farm supply inventory space. Among large cooperatives, each

of these groups averaged or exceeded the benchmark.

Solvency — This is an indication of the cooperative’s long-term financial health. Solvency indicators

include guidelines for a firm’s interest expenses and

liabilities compared with its income and equity.

Times interest earned (TIE) compares the cooperative’s net income to its interest expense. Because

greater interest expense implies a heavier debt load,

interest expense should ideally be no greater than onethird a cooperative’s net income (a TIE ratio of 3 or

more). National averages for both large and mediumsized cooperatives were well over the benchmark for

8

Table 8—Liquidity Indicators: National, Regional and "M/C" Cooperatives, by Reason, 5-Year Means, by

Size, 1993-97

Total Sales of $15 million or more Total Sales between $5 and $15 million

----------------------------------------------------- -------------------------------------------------------

Current Quick Working Current Quick Working

ratio ratio Capital ratio ratio Capital

to Sales to Sales

In Business Cooperatives

National 1.32 0.68 0.04 1.56 0.85 0.06

Corn Belt 1.18 0.48 0.03 1.45 0.56 0.06

Southern Plains 1.40 0.76 0.06 1.65 0.97 0.08

Northern Plains 1.12 0.53 0.03 1.25 0.63 0.05

Pacific Northwest 1.58 0.95 0.05 1.87 1.24 0.06

M/C Cooperatives 1.22 0.62 0.03 1.37 0.68 0.04

By Reason:

Merged w/

Co-op 1.14 0.37 0.03 1.43 0.46 0.06

Acquired by

Co-op 1.16 0.38 0.03 1.31 0.49 0.04

Consolidated w/

Co-op 1.19 0.66 0.02 1.76 1.18 0.04

Merged w/ IOF 1.41 0.76 0.08 1.20 0.55 0.03

Acquired by IOF 1.33 1.33 0.01

Bankruptcy 1.11 0.23 0.01 1.24 0.63 0.04

Unknown Reason 1.29 0.78 0.04

Benchmark 1.50 0.80 0.07 1.50 0.80 0.07

Current ratio -- Current assets / Current liabilities

Quick ratio -- Current assets (less inventories) / Current liabilities

Working capital to sales -- Current assets (less current liabilities) / Total sales

5 Grain inventory turnover rates were computed, but because of

wide variations were considered less than reliable and not

reported. Reporting and regional differences in cooperative annual

reports contribute largely to the variation. These differences

generally involve each cooperative’s choice of fiscal year and

affects grain sales amounts and inventory values. Unfortunately,

in most cases they are irreconcilable.
the period (table 10). This may reflect the relatively

lower interest rates of the period as well as a managerial objective to control interest expenses.

Among the M/C cooperatives, however, uncontrolled interest expenses seemed to be a significant

problem. No M/C cooperatives approached benchmark TIE levels. In fact, all but one group had interest

expenses that exceeded their net income (or a TIE of

less than 1). Interestingly, the group with the highest

TIE (1.36) among the M/C cooperatives were the large

cooperatives that went bankrupt. In some cases, cooperatives reported both negative net income and TIE.

The remaining two solvency indicators suggest

that debt incurred both in and out of business was a

less significant problem among large cooperatives.

National averages approached the benchmark of 0.5

for liabilities to assets and liabilities to equity of 1.0.

M/C cooperatives had similar long-term indebtedness

performance.

Medium-sized cooperatives, on the other hand,

appeared to have less difficulty managing their longterm debt structure. Except for medium-sized and

Northern Plains cooperatives that went bankrupt, both

in- and out-of-business cooperatives held liabilities

well below benchmark levels.

Best Co-ops ‘Cherry-Picked?’

A legend expressed often in the cooperative community is that the most promising ones have or soon

will be purchased by IOFs. This study generally

refutes this belief and will be presented in two ways.

First, while both groups of cooperatives werein

unfavorable financial circumstances, those that merged

with other cooperatives outperformed those that

merged with IOFs. Table 11 compares a simple average

of all financial indicators previously mentioned for

cooperatives that merged with other cooperatives versus those that merged with IOFs, along with national

in- business averages. Large cooperatives that merged

with other cooperatives outperformed those that

merged with IOFs in 11 of 13 indicators. Similarly,

medium-sized cooperatives outperformed their counterparts that merged with IOFs in 12 of the 13.

9

Table 9—Efficiency Indicators: National, Regional, and “M/C” Cooperatives By Reason,

5-Year Means, by Size, 1993-97

Total Sales of $15 million or more Total Sales between $5 and $15 million

----------------------------------------------------------------- ---------------------------------------------------------------

Labor Farm Supply Labor Farm Supply

Productivity Income Inventory Productivity Income Inventory

Ratio Ratio Turnover Ratio Ratio Turnover

In Business Cooperatives

National 0.08 0.37 8 0.08 0.39 8

Corn Belt 0.08 0.38 10 0.09 0.40 8

Southern Plains 0.10 0.38 9 0.11 0.43 7

Northern Plains 0.06 0.37 7 0.06 0.37 8

Pacific Northwest 0.08 0.36 6 0.08 0.37 8

M/C Cooperatives 0.08 0.36 9 0.10 0.39 9

By Reason:

Merged w/ Co-op 0.07 0.40 11 0.10 0.38 9

Acquired by Co-op 0.08 0.34 10 0.10 0.37 8

Consolidated w/ Co-op 0.10 0.39 14 0.08 0.37 10

Merged into IOF 0.15 0.38 3 0.10 0.39 4

Acquired by IOF 0.04 0.25 0.10 0.38 9

Bankruptcy 0.05 0.38 7

Unknown Reason 0.11 0.44 13

Benchmark 0.10 0.35 10 0.10 0.35 10

Productivity ratio -- Total expenses / Total sales

Labor to income -- Labor expenses / Gross revenue 

Farm supply inventory turnover -- Farm supply sales / Farm supply inventory
Second, a very broad measure of the relative

financial health was given to the 330 cooperatives that

went out of business and their merging partners. Firms

that performed no worse than 90 percent of the benchmark level in at least 6 of the 13 indicators were considered healthy. Firms that failed to achieve the 90 percent performance level for seven or more indicators

were considered in poor financial health.

Table 12 summarizes the financial health of the

330 M/C cooperatives and their partners. Sixty-five

percent (82) of the 126 mergers that occurred among

large cooperatives during the 1993-97 period involved

2 firms in poor financial health. Thirty-one percent (39)

occurred among a healthy and a not-so-healthy firm.

And only 4 percent (5) of all large cooperative mergers

during that period involved two healthy firms.

And while a slightly larger percentage of medium-sized cooperative mergers (38 percent or 63 of 204)

involved at least one healthy firm, the implication

remains the same for both groups. Most cooperatives

that went out of business during the period were performing poorly, or at least not as well as their surviving neighbors. In most categories, whether the average

M/C cooperative was involved with a cooperative, or

becoming part of an IOF, its financial indicators were

"weaker" than national averages, and well short of

benchmark values.

Like any other business, when a cooperative

ceased to operate because of financial trouble and

combined with another business, it tended to accept

the terms offered by its benefactor, not dictate them.

Few, if any, were able to negotiate from a position of

strength.

Roughly two-fifths of the 291 cooperatives that

stayed in the "cooperative family" were financially

sound. However, among the 22 cooperatives that

merged with, or were acquired by an IOF,there was

only one solid performer. So, if we look at the best

among a group of relatively weaker cooperatives, and

ask whether they were "picked" or "stayed in the family," the answer is the latter. Of the 121 available "cherry" cooperatives that went out of business during

1993-97, only one was "picked" by an IOF.

10

Table 10—Solvency Indicators: National, Regional, and “M/C” Cooperatives By Reason, 5-year Means, by

Size, 1993-97

Total Sales of $15 million or more Total Sales between $5 and $15 million

----------------------------------------------------------------- ---------------------------------------------------------------

Times Int. Liabilities LT Liabilities Times Int. Liabilities LT Liabilities

Earned to Assets to Equity Earned to Assets to Equity

In Business Cooperatives

National 3.84 0.45 1.17 4.02 0.36 0.80

Corn Belt 2.77 0.50 1.41 3.83 0.40 0.83

Southern Plains 3.91 0.39 0.83 3.66 0.32 0.62

Northern Plains 4.16 0.59 1.84 5.53 0.54 1.44

Pacific Northwest 4.52 0.33 0.61 3.04 0.17 0.31

M/C Cooperatives 0.45 0.44 1.26 (0.30) 0.36 0.96

By Reason:

Merged w/ Co-op 0.30 0.51 1.39 0.76 0.35 0.77

Acquired by Co-op (0.03) 0.53 1.53 (0.56) 0.35 0.92

Consolidated w/ Co-op 0.18 0.37 1.04 (0.07) 0.23 0.56

Merged into IOF 0.42 0.85 (0.69) 0.41 0.97

Acquired by IOF 0.22 1.04 (0.61) 0.40 1.58

Bankruptcy 1.36 0.57 1.68

Unknown Reason (0.65) 0.43 0.98

Benchmark 3.00 0.50 1.00 3.00 0.50 1.00

Times interest earned -- Net income / Interest expense 

Liabilities to assets -- Total liabilities / Total assets

Long-term liabilities to equity -- Long term liabilities / Equity
Predicting Mergers, Acquisitions

A substantial and growing body of literature

exists in support of the economic forecasting of corporate mergers and acquisitions. Most recently, Adesoji et

al., use two mathematical models to explain merger

and acquisition (M&A) activities in the U.S. food manufacturing sector and, in particular,topredict the likelihood of a firm being targeted for M&A (a so-called

target model) and a model to predict the likelihood of

a targeted firm being taken over (a takeover model).

Among others, Adesoji et al., is rooted in the

work of Dietrich and Sorensen, Harris et al., Langetieg,

and Stevens (1973 and 1979). Dietrich and Sorensen

applied logit estimation on financial performance indicators to predict the probability that a given firm will

be a merger target. Harris et al., used probit analysis to

study the financial and product market characteristics

of acquired firms. Langetieg selected from among four

alternative models to employ a three-factor performance index that measured stockholder gains from a

merger. Stevens used multiple discriminate analysis on

financial indicators to distinguish among acquired and

non-acquired firms.

Following this line of inquiry, an economic model

was used to evaluate the likelihood of a grain cooperative going out of business in the near term, given its

financial performance record. A time-series of each of

the 13 financial ratios (table 11) was constructed for

each cooperative in the study.

Each series was regressed on the binary condition

of the associated cooperative’s survival (0) or M/C

condition (1) during the study period. A three-variable

"best fit" model was selected for each size group fro m

11

Table 11—Financial Indicators: National Means and "M/C" Cooperatives, By Size and Type, 5-year Means

with Benchmark

Total Sales of $15 million or more Total Sales between $5 and $15 million

----------------------------------------------------- ----------------------------------------------------

M/C - to a M/C - to an M/C - to a M/C - to an

National Cooperative IOF Benchmark National Cooperative IOF

Profitability

Returns to Total

Assets 0.08 0.01 (0.03) 0.08 0.06 0.00 (0.02)

Returns to Fixed

Assets 0.27 0.02 (0.01) 0.30 0.22 (0.00) (0.07)

Returns to Equity 0.16 0.01 (0.06) 0.10 0.11 (0.00) (0.05)0

Local Returns to

Local Assets 0.07 (0.02) (0.04) 0.03 0.05 (0.02) (0.05)

Liquidity

Current Ratio 1.32 1.16 1.37 1.50 1.56 1.50 1.22

Quick Ratio 0.68 0.47 0.05 0.07 0.06 0.05 0.04

Working Capital to

Sales 0.04 0.03 0.05 0.07 0.06 0.05 0.04

Efficiency

Profitability 0.08 0.08 0.10 0.10 0.08 0.09 0.10

Labor to Income 0.37 0.38 0.32 0.32

Farm Supply Sales

to Inventory 8 12 3 10 8 9 6

Solvency

Times Interest

Earned 3.84 0.15 0.91 3.00 4.02 0.04 (0.65)

Total Liabilities to

Total Assets 0.45 0.47 0.32 0.50 0.36 0.31 0.41

LT Liabilities to

Equity 1.17 1.32 0.95 1.00 0.80 0.75 1.28
among the 13 ratios using the Score Criterion6

(Appendix 1). Maximum likelihood estimates and

related statistics for each size are provided in table 13

(with complete results and diagnostics in Appendix 2).

Each model has, in addition to the intercept, two variables that are significant at the 0.05 level and one that

is not. In other words, the information contributed by

the third variable is less significant than the first two

toward successfully predicting whether a cooperative

will go out of business.

Large grain cooperative M/Cs were most successfully predicted by the three ratios: return-to-totalassets, expenses-to-sales, and labor-to-income. The

negative sign on the variable return-to-total-assets

indicates that the likelihood of a cooperative becoming

an M/C increases as return-to-total-assets decreases.

The result makes sense. Also intuitive are the results

that expenses-to-sales and labor-to-income are positive, that is, the likelihood of a cooperative going out

of business increases with the value of these ratios.

However, the fact that out of all 13 variables,

these three were selected as having the most power for

predicting which large grain cooperatives go out of

business, says a lot about the challenges that confront

cooperatives that remain in the marketplace. That one

variable indicates profitability and the other two, efficiency, speaks to the relentless pressure of a market of

paper-thin margins. Managers are faced with seemingly impossible goals: make every asset a source of revenue while simultaneously reducing the cost of doing

business. The bigger challenge still is to remain in the

game while every player gets bigger and more competitive.

This analysis suggests that merger targets among

large grain cooperatives are likely to have the following financial characteristics: a positive, but relatively

low return-to-total-assets (3 - 4 percent range), expenses-to-sales approaching 10 percent, and labor-toincome significantly exceeding the 35 percent benchmark (40 percent and above). Given these conditions,

another 32 large cooperatives were considered likely

M/C candidates in 2000.

12

Table 12—Financial Health of M/C Cooperatives and Their Partners: National, Regional, and Reason, by

Size and Relative Condition

Total Sales of $15 million or more Total Sales between $5 and $15 million

------------------------------------------------------- -------------------------------------------------------

None One Both None One Both

M/C Cooperatives Healthy Healthy Healthy Total Healthy Healthy Healthy Total

Number of cooperatives Number of cooperatives

National 82 39 5 126 123 63 18 204

Corn Belt 60 37 5 102 102 45 9 156

Southern Plains 6 2 8 13 18 9 40

Northern Plains 15 15 4 4

Pacific Northwest 1 1 4 4

By Reason:

Merged w/ Co-op 46 29 5 80 89 59 18 166

Acquired by Co-op 19 19 15 15

Consolidated

w/ Co-op 10 10

Merged w/ IOF 4* 44 4

Acquired by IOF 5* 59* 9

Bankruptcy 4 4 4 6 6

Unknown Reason 4 4 4 4 4

* No IOF records were reviewed. This characterization reflects only the cooperatives that were involved.

6 The score criterion multiplies values from two data sets, one

containing coefficients (factor scoring or regression coefficient)

and the other containing raw data to be scored using coefficients

from the first data set. This multiplication results in series of linear

combinations of coefficients and raw data values. The Score

Procedure then sorts over the results of each combination to select

and rank them from greatest to least.
Medium-sized grain cooperative M/Cs were

most successfully predicted by the three ratios: localreturn-to-local-assets, expenses-to-sales, and return-tofixed-assets. Again, the negative sign of two of the

variables (local-return-to-local-assets and return-tofixed-assets) indicates that, as these ratios increase, the

likelihood of failure (M/C) diminishes.

Much like their large counterparts, medium-sized

cooperatives must balance profitability and efficiency.

However, while the large cooperatives concern themselves more with efficiency, medium-sized cooperatives must shift their emphasis toward profitability.It

is significant that two of the three most important variables involve return. Particularly important is the contribution of local-return-to-local-assets.

It is well known that many otherwise struggling

local grain cooperatives have managed to survive fro m

one year to the next on patronage received fro m

regional cooperatives. The results of the model suggest, however, that those days are surely ending.

Simply put, local returns are primary to a grain cooperative’s success.

Merger targets among medium-sized grain cooperatives are likely to have these financial characteristics: a local-return-to-total-assets of less than 2 percent,

expenses-to-sales approaching 10 percent, and a

return-to-fixed-assets significantly less than the 30 percent benchmark (18 percent or less). Under these circumstances, another 60 medium-sized cooperatives

were likely targets for consolidation in 2000.

So then, to survive, both large and medium-sized

cooperatives need to be profitable and efficient. But

what does "survival" mean for grain cooperatives in

the context of agriculture’s widespread economic

restructuring? Perhaps what has been learned about

M/C cooperatives will provide some important keys

to the challenges that lie ahead.

Horizontal, Vertical Integration

Even the most cursory look at the M/C cooperatives during the period suggests two predominant patterns: in an attempt to stave off bankruptcy, cooperatives in poor financial health in seeking out a partner

may also discover their potential partner to be struggling financially,or,strong cooperatives seeking out a

strong partner, and/or expanding internally to position themselves strategically for the future.

Inregard to both patterns, historians looking

back on the late 1990s may very easily conclude that

the "farm" crisis of two decades earlier simply moved

further up the food chain. The "family" farm was

essentially shaken out of the industry in the generation

past. Now, even among the largest players remaining

in agriculture, "only the lowest-cost operations will

remain." The buildup of surpluses and declining

export demand have driven prices to their lowest levels in decades. Expectations for their recovery are

equally as bleak. What was once a cost-price "squeeze"

may now be likened to a hammer and anvil.

Paper-thin profit margins and low expectations

are forcing grain cooperatives, along with the rest of

agriculture, to lower operating costs. So a firm must

get larger to spread operating costs over a larger business volume, or gain "scale economies." A merger with

another cooperative is often perceived as a way of

gaining a step on the economic treadmill. By cheaply

13

Table 13—Analysis of Maximum Likelihood Estimates

Parameter Standard Wald Pr >

Variable Estimate Error Chi-Square Chi-Square

Total Sales of $15 million or more

Intercept -3.088 0.813 14.435 0.000

Return to Total Assets- 8.686 2.802 9.613 0.002

Expenses to Sales 12.616 4.401 8.216 0.004

Labor to Income -2.537 2.132 1.416 0.234

Total Sales of $5 to $14.9 million

Intercept -2.119 0.734 8.342 0.004

Local Return to Local Assets -8.853 2.964 8.923 0.003

Expenses to Sales -11.640 5.903 3.888 0.049

Return to Fixed Assets -0.054 0.037 2.147 0.143
acquiring additional assets (e.g., storage facilities, unittrain load-out facilities, etc.), combining two sales

forces or accounting departments and other consolidation measures, firms hope the benefits of size will help

them to cut production costs.

Economists identify this cost-saving behavior

among two or more firms at the same level or "link"

along the supply chain as horizontal integration.

Vertical integration, on the other hand, involves the

forward or backward-linking of two or more firms at

different levels of the supply chain.

While supply chain integration is not a new event

in agriculture,itsincreasing pervasiveness in recent

years is prominent. A supply chain is formed when

one firm, usually a significantly dominant player or

"integrator," works to control (contractually or through

ownership) the activities of firms (groups of firms) at

each level of the production process, up to and including, delivery to the consumer. The purpose of these

chains is control. Integrators assume command of the

production and delivery process to assure themselves:

a) that product quality meets their customers’ specific

needs; b) that costs are driven to the absolute minimum, subject to meeting the quality specifications; and

c) that the associated risks are managed to within

acceptable levels.

Supply chain integration, long a fact of life in the

broiler industry and near completion in the pork

industry, is now underway in the grain industry

(Drabenstott). The grain delivery system is not quite as

complete as the broiler industry. A handful of firms

have yet to completely dominate seed development,

production, processing, and marketing with every

coordinated step up and down the chain.

However,inrecent years, we witnessed the harvest and marketing of herbicid-tolerant corn and soybeans. The so-called "Roundup®-ready" varieties are

just the first of many crops derived from seed stock

that was modified at the genetic level to garner specific properties. Moreover, we also watched as several

alliances of seed corporations with pharmaceutical

firms were formed with the specific interest of developing genetically modified seed stock. And, while

international markets proved to be less than enthusiastic about genetically modified corn and soybeans, at

least during the 1999-2000 marketing year, the die has

been cast. In short, the best available genetics were

combined with the best (i.e., most profitable) production processes to deliver products intended to meet the

needs of an increasingly discriminating consumer.

Summary, Conclusions

This study attempted to frame grain cooperatives

that survived during 1993-97 and those that went out

of business in the context of the widespread economic

restructuring that hit agriculture. Unfortunately, many

more grain cooperatives may be casualties of the latest

wave of economic consolidation. Toretrain employees

and producers who have been left behind remains one

of the many formidable challenges ahead.

Those cooperatives hoping to survive and even

thrive in the current wave of consolidation may face

increasingly greater challenges. First is the unrelenting

pressure of surviving in a market of ever-thinning

margins. Perhaps even more difficult is the challenge

of staying in the marketplace while competition grows

in size and strength.

As the supply chain structure dominates the

grain industry, both cooperatives and their producer

members are faced with a straightforward choice:

build new partnerships or be left behind. Survivors in

the broiler and pork industries successfully adjusted to

a shift in emphasis from "commodity marketing" to

"product delivery." For producers and cooperatives in

the grain industry, this will mean realignment to

become an "integrator" themselves, such as Dakota

Growers Pasta Cooperative of Carrington, ND, or,at

the very least, a reliable supplier to an integrator,for

example, the producers with membership and delivery

rights of corn for Golden Oval Layers in Renville, MN.

14
References

Adesolji, A., R. Nayga, Jr., Z. Farooq, “Predicting

Mergers and Acquisitions in the Food Industry,”

Agribusiness, vol. 15(1): 1-23, 1999.

CoBank, National Bank for Cooperatives, “Analyzing

a Cooperative Business: Designed for

Midwestern Grain or Farm Supply Cooperatives,”

self-published instructional pamphlet for

directors and managers of agricultural cooperatives,

undated.

Drabenstott, Mark “Consolidation in U.S. Agriculture

Leading to New Rural Landscape and

Public Policy Considerations,” Feedstuffs 71:19, May

17, 1999, pp. 33,34,43, and 44.

Dietrich, J. Kimball and Eric Sorenson, “An

Application of Logit Analysis to Prediction of

Merger Targets,” Journal of Business Research, vol.

12 (1984): 393-402.

Hanson, Mark “Grain Co-op Votes in Favor of

Terminal at Sterling; South Central Has

Elevators in Three Towns,” Bismark Tribune, March 21,

1998, Metro Edition, pg. 8.

Harris, R.S., J.F. Sterward, D.K. Guilkey, and W.T.

Carleton, “Characteristics of Acquired Firms:

Fixed and Random Coefficients Probity Analyses,”

Southern Economic Journal, Jul. 1982: 164-184.

Langetieg, Terence C., “An Application of a ThreeFactor Performance Index to Measure Stockholder

Gains from Merger,” Journal of Financial Economics,

6(1978): 365-383.

Merlo, Katherine ”When Cooperatives Combine,”

Rural Cooperatives 65:5, Sept./Oct. 1998, pp. 18-23.

Stevens, Donald L., “Financial Characteristics of

Merger Firms: A Multivariate Analysis,” Journal of

Financial and Quantitative Analysis, vol. 8 (Mar.

1973):149-158.

W adsworth, James J. “Large Cooperatives Unifying: A

Strategic Trend to Monitor,” Rural Cooperatives

66:5, Sept./Oct. 1999, pp. 21-25.

15
Appendix 1— Score Criterion Results to Select

Three-Variable “Best Fit” Model

Score Results — Best Subset

Size 1 — $15 Mil. or More in Total Sales

Logistic Regression

Response Profile

Regression Models Selected by Score

Criterion

Score

In Value Variables Included in

Model

1 20.355 RET_TA

1 20.217 LR_LA

1 19.211 RET_EQ

1 12.836 RET_FA

1 9.493 EXP_SLS

1 4.507 LAB_INC

1 2.174 SALES_FA

1 1.109 WCAP_SLS

1 0.923 GSLS_INV

1 0.782 QUICK

1 0.458 TIE

1 0.259 FSLS_INV

1 0.251 CURRENT

1 0.050 TL_TEQ

1 0.006 TL_TA

2 25.544 RET_TA EXP_SLS

2 24.177 EXP_SLS LR_LA

2 22.976 RET_EQ EXP_SLS

2 22.728 RET_TA TL_TEQ

2 22.518 RET_TA SALES_FA

2 22.125 SALES_FA LR_LA

2 21.996 RET_EQ LR_LA

2 21.673 RET_TA TL_TA

2 21.087 TL_TEQ LR_LA

2 21.065 RET_TA RET_EQ

2 20.951 RET_TA GSLS_INV

2 20.876 TL_TA LR_LA

2 20.803 RET_FA LR_LA

2 20.703 CURRENT LR_LA

3 26.407 RET_TA EXP_SLS LAB_INC

3 26.054 RET_TA EXP_SLS LR_LA

3 26.028 RET_TA GSLS_INV EXP_SLS

3 25.935 RET_TA TL_TEQ EXP_SLS

3 25.743 RET_TA RET_FA EXP_SLS

3 25.735 RET_TA SALES_FA EXP_SLS

3 25.630 RET_TA RET_EQ EXP_SLS

3 25.618 RET_TA FSLS_INV EXP_SLS

3 25.588 RET_TA EXP_SLS WCAP_SLS

3 25.582 RET_TA TIE EXP_SLS

3 25.575 RET_TA CURRENT EXP_SLS

3 25.567 RET_TA TL_TA EXP_SLS

3 25.566 RET_TA QUICK EXP_SLS

3 25.376 RET_EQ EXP_SLS LR_LA

3 24.551 EXP_SLS LAB_INC LR_LA

Regression Models Selected by Score

Criterion

(continued)

Score

In Value Variables Included in

Model

4 26.966 RET_TA TL_TEQ EXP_SLS 

LAB_INC

4 26.932 RET_TA EXP_SLS LAB_INC 

LR_LA

4 26.876 RET_TA CURRENT QUICK 

EXP_SLS

4 26.844 RET_TA GSLS_INV EXP_SLS 

LAB_INC

4 26.717 RET_TA RET_FA EXP_SLS 

LAB_INC

4 26.659 RET_TA TL_TEQ GSLS_INV 

EXP_SLS

4 26.495 RET_TA CURRENT EXP_SLS 

LAB_INC

4 26.492 RET_TA TL_TA EXP_SLS 

LAB_INC

4 26.471 RET_TA FSLS_INV EXP_SLS 

LAB_INC

4 26.456 RET_TA SALES_FA EXP_SLS 

LAB_INC

4 26.450 RET_TA RET_FA SALES_FA 

EXP_SLS

4 26.440 RET_TA RET_EQ EXP_SLS 

LAB_INC

4 26.421 RET_TA EXP_SLS LAB_INC 

WCAP_SLS

4 26.418 RET_TA TIE EXP_SLS

LAB_INC

4 26.409 RET_TA QUICK EXP_SLS 

LAB_INC

5 27.800 RET_TA CURRENT QUICK 

EXP_SLS LAB_INC

5 27.669 RET_TA TL_TEQ GSLS_INV 

EXP_SLS LAB_INC

16
5 27.599 RET_TA RET_FA TL_TEQ 

EXP_SLS LAB_INC

5 27.378 RET_TA TL_TEQ EXP_SLS 

LAB_INC LR_LA

5 27.345 RET_TA CURRENT QUICK

EXP_SLS 

LR_LA

5 27.260 RET_TA CURRENT QUICK TL_TEQ 

EXP_SLS

5 27.232 RET_TA GSLS_INV EXP_SLS

LAB_INC 

LR_LA

5 27.221 RET_TA CURRENT QUICK

EXP_SLS 

WCAP_SLS

5 27.179 RET_TA RET_FA EXP_SLS

LAB_INC 

LR_LA

5 27.168 RET_TA TL_TA GSLS_INV

EXP_SLS 

LAB_INC

5 27.134 RET_TA CURRENT EXP_SLS 

LAB_INC LR_LA

5 27.132 RET_TA RET_FA SALES_FA

EXP_SLS 

LAB_INC

5 27.130 RET_TA TL_TA TL_TEQ EXP_SLS

LAB_INC

5 27.119 RET_TA CURRENT GSLS_INV 

EXP_SLS LAB_INC

5 27.083 RET_TA CURRENT QUICK

GSLS_INV 

EXP_SLS

Score Results — Best Subset

Size 2 — $5 Mil. to $14.9 Mil. in Total

Sales

Logistic Regression

Response Profile

Regression Models Selected by Score

Criterion

Score

In Value Variables Included in Model

1 8.797 LR_LA

1 7.929 RET_TA

1 7.247 RET_EQ

1 5.155 RET_FA

1 1.792 QUICK

1 1.525 EXP_SLS

1 0.912 CURRENT

1 0.729 TL_TA

1 0.635 WCAP_SLS

1 0.562 TIE

1 0.392 TL_TEQ

1 0.270 GSLS_INV

1 0.092 LAB_INC

1 0.010 FSLS_INV

2 12.337 LR_LA EXP_SLS

2 11.111 RET_TA EXP_SLS

2 11.046 RET_EQ EXP_SLS

2 10.461 LAB_INC LR_LA

2 9.320 SALES_FA LR_LA

2 9.130 RET_TA LR_LA

2 9.111 RET_TA LAB_INC

2 9.103 RET_EQ LR_LA

2 9.089 TL_TA LR_LA

2 9.064 GSLS_INV LR_LA

2 9.029 QUICK LR_LA

2 8.934 FSLS_INV LR_LA

2 8.851 LR_LA WCAP_SLS

2 8.825 TL_TEQ LR_LA

2 8.803 TIE LR_LA

3 14.213 LR_LA EXP_SLS RET_FA

3 13.426 RET_EQ SALES_FA EXP_SLS

3 13.147 RET_TA SALES_FA EXP_SLS

3 13.005 RET_EQ EXP_SLS LR_LA

3 12.982 EXP_SLS LR_LA WCAP_SLS

3 12.812 EXP_SLS LAB_INC LR_LA

3 12.718 RET_TA EXP_SLS LR_LA

3 12.487 QUICK EXP_SLS LR_LA

3 12.478 GSLS_INV EXP_SLS LR_LA

3 12.412 FSLS_INV EXP_SLS LR_LA

3 12.412 TL_TA EXP_SLS LR_LA

3 12.401 RET_FA EXP_SLS LR_LA

3 12.344 TIE EXP_SLS LR_LA

3 12.337 TL_TEQ EXP_SLS LR_LA

3 12.337 CURRENT EXP_SLS LR_LA

Regression Models Selected by Score

Criterion (Continued)

Score

In Value Variables Included in

Model

4 14.670 LR_LA RET_FA EXP_SLS

WCAP_SLS

4 15.113 RET_EQ SALES_FA EXP_SLS

LR_LA

17
4 14.661 RET_TA SALES_FA EXP_SLS

LR_LA

4 14.556 TL_TA SALES_FA EXP_SLS

LR_LA

4 14.373 SALES_FA GSLS_INV EXP_SLS

LR_LA

4 14.305 QUICK SALES_FA EXP_SLS

LR_LA

4 14.291 TL_TEQ SALES_FA EXP_SLS

LR_LA

4 14.268 SALES_FA EXP_SLS LAB_INC

LR_LA

4 14.251 SALES_FA FSLS_INV EXP_SLS

LR_LA

4 14.248 RET_FA SALES_FA EXP_SLS

LR_LA

4 14.213 TIE SALES_FA EXP_SLS LR_LA

4 14.213 CURRENT SALES_FA EXP_SLS

LR_LA

4 13.889 QUICK RET_EQ SALES_FA

EXP_SLS

4 13.736 RET_TA RET_EQ SALES_FA

EXP_SLS

4 13.700 RET_EQ EXP_SLS LR_LA

WCAP_SLS

5 15.657 RET_FA RET_EQ SALES_FA

EXP_SLS 

LR_LA

5 15.608 RET_EQ SALES_FA EXP_SLS

LR_LA 

WCAP_SLS

5 15.466 TL_TA SALES_FA EXP_SLS

LR_LA 

WCAP_SLS

5 15.325 TL_TA RET_EQ SALES_FA

EXP_SLS 

LR_LA

5 15.300 RET_EQ SALES_FA GSLS_INV 

EXP_SLS LR_LA

5 15.253 QUICK RET_EQ SALES_FA

EXP_SLS 

LR_LA

5 15.240 RET_TA SALES_FA EXP_SLS

LR_LA 

WCAP_SLS

5 15.173 RET_EQ SALES_FA FSLS_INV 

EXP_SLS LR_LA

5 15.158 RET_EQ SALES_FA EXP_SLS

LAB_INC

LR_LA

5 15.143 QUICK SALES_FA EXP_SLS

LR_LA 

WCAP_SLS

5 15.121 CURRENT RET_EQ SALES_FA 

EXP_SLS LR_LA

5 15.120 RET_TA RET_EQ SALES_FA

EXP_SLS 

LR_LA

5 15.115 TL_TEQ RET_EQ SALES_FA

EXP_SLS 

LR_LA

5 15.114 TIE RET_EQ SALES_FA EXP_SLS 

LR_LA

5 14.968 TL_TEQ SALES_FA EXP_SLS

LR_LA 

WCAP_SLS

18
Appendix 2 — Logistic Regression Results with Diagnostics, 3-Variable Final, by Size

Size 1 — More than $15 Mil. in Total Sales

The LOGISTIC Procedure

Number of M/C observations: 1520

Link Function: Logit

Response Profile

Ordered Binary

Value Outcome Count

1 EVENT 133

2 NO EVENT 1253

WARNING: 134 M/C observation(s) were deleted due to missing values for explanatory

variables.

Deviance and Pearson Goodness-of-Fit Statistics

Pr >

Criterion DF Value Value/DF Chi-Square

Deviance 447 217.6 0.4869 1.0000

Pearson 447 401.0 0.8970 0.9422

Number of unique profiles: 1520

Model Fitting Information and Testing GlM/Cal Null Hypothesis BETA=0

Intercept

Intercept and

Criterion Only Covariates Chi-Square for Covariates

AIC 470.842 459.648 . 

SC 476.020 480.359 . 

-2 LOG L 468.842 451.648 17.195 with 3 DF (p=0.0006)

Score . . 18.456 with 3 DF (p=0.0004)

Analysis of Maximum Likelihood Estimates

Parameter Standard Wald Pr > Standardized Odds

Variable DF Estimate Error Chi-Square Chi-Square Estimate Ratio

INTERCPT 1 -3.0878 0.8127 14.4347 0.0001 . .

RET_TA 1 -8.6858 2.8015 9.6125 0.0019 -0.215383 0.000

EXP_SLS 1 12.6159 4.4013 8.2163 0.0042 0.225033 999.000

LAB_INC 1 2.5367 2.1316 1.4162 0.2340 0.104474 0.079

19
Association of Predicted PrM/Cabilities and M/C observed Responses

Concordant = 64.5% Somers’ D = 0.319

Discordant = 32.6% Gamma = 0.328

Tied = 2.9% Tau-a = 0.027

(71421 pairs) c = 0.659

Parameter Estimates and 95% Confidence Intervals

Profile Likelihood

Confidence Limits

Parameter

Variable Estimate Lower Upper

INTERCPT -3.0878 -4.6966 -1.5101

RET_TA -8.6858 -14.0327 -2.9536

EXP_SLS 12.6159 3.9075 21.2001

LAB_INC 2.5367 1.5595 6.7894

Parameter Estimates and 95% Confidence Intervals

Wald

Confidence Limits

Parameter

Variable Estimate Lower Upper

INTERCPT -3.0878 -4.6807 -1.4949

RET_TA -8.6858 -14.1766 -3.1949

EXP_SLS 12.6159 3.9895 21.2423

LAB_INC 2.5367 1.6412 6.7146

Conditional Odds Ratios and 95% Confidence Intervals

Profile Likelihood

Confidence Limits

Odds

Variable Unit Ratio Lower Upper

RET_TA 1.0000 0.000 0.000 0.052

EXP_SLS 1.0000 999.000 49.774 999.000

LAB_INC 1.0000 0.079 0.001 4.756

20
Conditional Odds Ratios and 95% Confidence Intervals

Wald

Confidence Limits

Odds

Variable Unit Ratio Lower Upper

RET_TA 1.0000 0.000 0.000 0.041

EXP_SLS 1.0000 99.000 54.029 999.000

LAB_INC 1.0000 0.079 0.001 5.161

Estimated Correlation Matrix

Variable INTERCPT RET_TA EXP_SLS LAB_INC

INTERCPT 1.00000 -0.38455 -0.06474 -0.84786

RET_TA -0.38455 1.00000 -0.08578 -0.35677

EXP_SLS -0.06474 -0.08578 1.00000 0.45109

LAB_INC -0.84786 -0.35677 0.45109 1.00000

Size 2 — $5 Mil. to $14.9 Mil. in Total Sales

The LOGISTIC Procedure

Number of M/C observations: 2091

Link Function: Logit

Response Profile

Ordered Binary

Value Outcome Count

1 EVENT 213

2 NO EVENT 1853

WARNING: 26 M/C observation(s) were deleted due to missing values for the explanatory variables.

Deviance and Pearson Goodness-of-Fit Statistics

Pr >

Criterion DF Value Value/DF Chi-Square

Deviance 506 229.0 0.4525 1.0000

Pearson 506 535.5 1.0584 0.1758

21
Number of unique profiles: 510

Model Fitting Information and Testing GlM/Cal Null Hypothesis BETA=0

Intercept

Intercept and

Criterion Only Covariates Chi-Square for Covariates

AIC 449.955 444.441 . 

SC 455.506 466.642 . 

-2 LOG L 447.955 436.441 11.514 with 3 DF (p=0.0092)

Score . . 9.987 with 3 DF (p=0.0187)

Analysis of Maximum Likelihood Estimates

Parameter Standard Wald Pr > Standardized Odds

Variable DF Estimate Error Chi-Square Chi-Square Estimate Ratio

INTERCPT 1 -2.1188 0.7336 8.3416 0.0039 . .

LR_LA 1 -8.8525 2.9636 8.9226 0.0028 -0.216537 0.000

EXP_SLS 1 11.6404 5.9031 3.8884 0.0486 0.188931 0.000

RET_FA 1 -0.0536 0.0366 2.1469 0.1429 -0.314920 0.948

Association of Predicted PrM/Cabilities and M/C observed Responses

Concordant = 61.5% Somers’ D = 0.280

Discordant = 33.5% Gamma = 0.295

Tied = 5.1% Tau-a = 0.014

(88944 pairs) c = 0.640

Parameter Estimates and 95% Confidence Intervals

Profile Likelihood

Confidence Limits

Parameter

Variable Estimate Lower Upper

INTERCPT -2.1188 -3.5345 -0.6604

LR_LA -8.8525 14.4543 -2.8067

EXP_SLS 11.6404 0.4152 23.5797

RET_FA -0.0536 -0.1316 0.0065

22
Parameter Estimates and 95% Confidence Intervals

Wald

Confidence Limits

Parameter

Variable Estimate Lower Upper

INTERCPT -2.1188 3.5567 -0.6810

LR_LA -8.8525 -14.6611 -3.0439

EXP_SLS 11.6404 0.0705 23.2103

RET_FA -0.0536 -0.1253 0.0181

Conditional Odds Ratios and 95% Confidence Intervals

Profile Likelihood

Confidence Limits

Odds

Variable Unit Ratio Lower Upper

LR_LA 1.0000 0.000 0.000 0.060

EXP_SLS 1.0000 0.000 0.000 0.660

RET_FA 1.0000 0.948 0.877 1.007

Conditional Odds Ratios and 95% Confidence Intervals

Wald

Confidence Limits

Odds

Variable Unit Ratio Lower Upper

LR_LA 1.0000 0.000 0.000 0.048

EXP_SLS 1.0000 0.000 0.000 0.932

RET_FA 1.0000 0.948 0.882 1.018

Estimated Correlation Matrix

Variable INTERCPT RET_FA LR_LA EXP_SLS

INTERCPT 1.00000 -0.74868 -0.12166 0.81442

LR_LA -0.12166 0.00321 1.00000 -0.28354

EXP_SLS 0.81442 -0.28293 -0.28354 1.00000

RET_FA -0.74868 1.00000 0.00321 -0.28293

23
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