CREDIT SCORING, LOAN PRICING, AND FARM BUSINESS PERFORMANCE



50 July 1989

Western Journal of Agricultural Economics

Table 1. Credit Scoring and Loan Pricing Model

Variable

Measure

Weight

Range

Score

Solvency

Ratio of debts to total assets

20%

0.00-0.20

0

0.21-0.40

10

0.41-0.60

20

above 0.60

30

Liquidity

Current ratio

20%

above 3.00

0

1.51-3.00

10

1.00-1.50

20

under 1.00

30

Cash Flow

Debt servicing ratio (Interest plus sched-

20%

under 0.15

0

uled principal payments plus 2 5 % of any

0.16-0.25

10

working capital deficit all divided by

0.26-0.35

20

crop and livestock sales)

above 0.35

30

Profitability

Rate of return on assets

20%

above 0.08

0

0.04-0.079

10

0.01-0.039

20

under 0.01

30

Debt exposure

Value of farm production plus nonfarm in-

20%

above 1.20

0

come divided by total liabilities

0.81-1.20

10

0.40-0.80

20

0.00-0.40

30

Credit classification

Scoring range

Interest rate

Class 1

0-7.5 points

8%

Class 2

7.6-15.0 points

10%

Class 3

15.1-22.5 points

12%

Class 4

above 22.5 points

14%

the rate of return on assets; and 5) debt ex-
posure, as measured by gross earnings divided
by total liabilities. The variables, measures,
weights, and resulting credit classes are shown
in table 1.

The borrower’s interest rate on loans is de-
termined by the credit score and classification
procedure. The approach followed here for as-
signing a specific interest rate to each credit
class is to specify a base rate and an interest-
rate range around the base rate. Since four credit
classes are used, the four interest rates are de-
termined by adding and subtracting 5Oo∕o and
1500∕o of the interest-rate range to and from
the base rate. If, for example, the base rate is
11% and the range is 2o∕o, then the set of interest
rates is as follows: Class 1, 8o∕o (11% — 1.5*2);
class 2, 10% (11% - .5*2); class 3, 12% (11%
+ .5*2); class 4, 14% (11% + 1.5*2). This
procedure is easily specified in the simulation
model and allows straightforward changes in
the base rate, range, multiplying factors, and
weights on variables, if desired.

Design of Empirical Analysis

The empirical analysis is designed to show the
effects of the credit scoring and loan pricing
mechanism relative to constant pricing under
different specifications on the initial leverage
position, growth rates, down payment levels,
and liquidity requirements. Extensions of the
analysis also consider the effects of alternative
weightings of the credit scoring variables and
different integer specifications on land pur-
chases. The goals are first to observe the re-
sponse of the firm’s simulated performance to
the adoption of credit-scored pricing. Then the
effects of alternative leverage positions, eco-
nomic conditions, and other variations are
considered.

The adoption of credit-scored pricing is ex-
pected to yield time patterns of performance,
credit classifications, and interest rates that
parallel the changes in the firm’s financial po-
sition arising from its investment, financing,
and debt servicing activities. That is, a growth-
oriented firm starting in a relatively low le-
verage and strong liquidity position should
have a favorable credit rating and relatively
low interest rates. Growth (through land ac-
quisition in this case) will occur relatively rap-
idly and in larger amounts until the increased
financial risk and reductions in liquidity yield
a reduced credit rating, higher borrowing costs,
and thus reduced incentive for further growth.



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