CREDIT SCORING, LOAN PRICING, AND FARM BUSINESS PERFORMANCE



48 July 1989

N + 1

Figure 1. Credit evaluation process and loan
pricing

lender and borrower may modify the plans and
eventually agree on the availability of various
types of credit, the levels of interest rates, col-
lateral requirements, loan maturities, and oth-
er financing terms. The borrower then imple-
ments the business plans, carries on the firm’s
activities over the period, and realizes the re-
sulting performance. The ending financial po-
sition accounts for the combined effects of the
beginning position, the business plans, the
credit terms, and the subsequent outcomes.
Finally, the ending position becomes the be-
ginning position for the next period, in which
the process is repeated, and this sequence con-
tinues until the horizon is reached.

Methodology

The recursive process presented in the preced-
ing section could be implemented using sim-
ulation or optimization procedures. Optimi-
zation offers the opportunity to observe

Western Journal of Agricultural Economics

financial performance, investment patterns,
and financing activities that arise from the
firm’s efforts to push against its resource limits
and operating requirements in order to max-
imize the stipulated objectives. However, a
mathematical programming approach suffers
from difficulties in endogenizing a credit scor-
ing function in which the variables are ex-
pressed by financial ratios and from a less flex-
ible approach for testing the effects of
alternative investment strategies, parameter
specifications, and environmental conditions.

Accordingly, a recursive, multiperiod sim-
ulation model is formulated for use in this study
in order to portray the firm’s financial setting
and business opportunities. The model is for-
mulated, using the LOTUS 123 spreadsheet
software, as a series of annual business deci-
sions and performance results with integer
specifications on major business investments.
The periods are linked together by financial
transfers from one period to the next and by
the credit scoring procedure in which the firm’s
cost ofborrowing is determined by its financial
position at the end of the preceding period
which itself reflects the cumulative effects of
past performance. Thus, the model resembles
the basic approach of other commonly used
simulation models (Richardson and Nixon;
Walker and Helmers; Schnitkey, Barry, and
Ellinger), except for the annual updating of the
credit scoring and loan pricing mechanism, a
deterministic specification, and less empirical
detail on production and marketing compo-
nents.

A deterministic model is specified in order
to highlight the relationships among business
plans, financial performance, the credit score,
and borrowing costs. That is, values for gross
receipts, operating costs, growth rates, and oth-
er parameters are all expressed by single-val-
ued expectations. A stochastic framework
would add further realism, including the pro-
vision for alternative risk attitudes and meth-
ods of responding to risk; however, the added
complexities would obscure the key relation-
ships and might yield performance measures
(e.g., variance of income or wealth, probability
of loss, probability distributions) that are not
directly reflected in credit scoring procedures
used by lenders.

Model Components

The model’s components include the firm’s
initial financial position, operating decisions,



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