Title: On the non-neutrality of scale of agricultural research
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Permanent Link: http://ufdc.ufl.edu/UF00095082/00001
 Material Information
Title: On the non-neutrality of scale of agricultural research
Physical Description: 10 leaves : ; 28 cm.
Language: English
Creator: Hildebrand, Peter E.
Donor: unknown ( endowment ) ( endowment )
Publication Date: 1984
Copyright Date: 1984
 Subjects
Subject: Farms, Small -- Management -- Developing countries   ( lcsh )
Agriculture -- Research -- United States   ( lcsh )
Sustainable agriculture -- Developing countries   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
Spatial Coverage: United States of America
Developing countries
 Notes
Bibliography: Includes one bibliographical reference.
General Note: "1984" penciled in.
General Note: Typescript.
Statement of Responsibility: P.E. Hildebrand.
 Record Information
Bibliographic ID: UF00095082
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 433650358

Full Text







ON THE NON-NEUTRALITY OF SCALE OF AGRICULTURAL RESEARCH

P. E. Hildebrand











Over the last decade, the international agricultural

technical assistance community and many governments have become

concerned about the low productivity of small, limited resource

or low volume farms. Many projects have been initiated to work

with small farmers and several approaches have been used.

Success in increasing productivity has been limited. Even the

much hailed Green Revolution did not have the impact that had

been predicted for it. In the United States, farms have been

growing larger and larger and the number of small farms

declining. Questions have been raised concerning the nature of

agricultural research and whether this research has been

contributing more to larger farms and to the demise of small

farms.



Carter et al., reported in a recent study that most of the

research carried out in the United States was considered by the

research directors involved to be scale neutral, meaning it

should demonstrate the same potential on small as on large farms.

Hence, they argue that the research product was equally adoptable






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on large as on small farms. Yet it has been amply demonstrated

even in the United States, that small farms have not adopted much

of the newer technology and have not been able to compete with

larger farms in the current economic environment.



In this paper, it is argued that the majority of the

research that is conceived as scale neutral by the research

directors responding to the Carter study is, in fact, not scale

neutral and is strongly biased toward large scale, commercial

agriculture and against small, limited resource or low volume

family farms. This is true in the United States but even more

true in developing countries. Three reasons are primarily

responsible for this bias. These reasons are not recognized by

most agricultural researchers and have not entered into the

evaluation criteria regarding scale effect of the research

directors who classified the research reported by Carter, et al.

The reasons, all inter-related, are:



1) The quality of resources on small farms is frequently lower

than on large farms. This has the effect of shifting a small

farm production function downward in comparison with large farms

so that response from a technology on a small farm is less than

on a large farm.



2) Limited quantities of resources, fixed in a higher proportion

for the firm, result in a concave opportunities curv- for the low

volume farm. This results in a reduction in income when






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enterprises are combined. Yet many small farmers are forced

into diversification for subsistence or because they have little

confidence in support from normal market infrastructure.



3) Forced farm enterprise diversification and/or off-farm work,

reduce the quantity if not the quality of management in each

enterprise on the low volume farm. This influences the time

required to learn to use a new technology, shifts the learning

curve to the right and makes learning more expensive. Low volume

output prevents spreading the higher learning costs (loss of

income from not achieving anticipated results) over a sufficient

number of units to make complex learning situations profitable

for the small farm.



The combined effect of these three factors is to make it

unprofitable for the low volume farm to adopt more complex modern

technology. The need under the conditions of low volume is for

technology which is simple, as opposed to complex and uses mostly

resources already fixed on the farm, as opposed to purchased

inputs. This is not the kind of technology being produced by the

research directors polled by Carter, et al., nor by most research

establishments in developing countries.



RESOURCE AND INPUT QUALITY

Not universally, but frequently enough to make it a general

rule, small farmers operate with inputs and resources of inferior

quality compared to large or commercial farmers. It is common to






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see small farms pushed off onto steep or rocky hillsides with

obviously poorer soils. Animals or power equipment, if they

exist at all, are weaker or smaller and do a less effective job

in soil preparation and cultivation. Purchased inputs are more

apt to have been poorly stored or otherwise arrive at the farm

with inferior quality. These and other reasons account for a

lower quality input and resource base on a small farm. Combining

these inputs with a new technology, leads to lower responses than

those achieved on farms with a higher quality resource base and

reduces profit potential from adoption. It is not the size of

the field in which an improved seed is planted that is important.

It is the quality of the soil, the amount of moisture, the

presence or absence of pest and disease control and the losses

between maturity and harvest, when combined with the improved

seed that influence response. Technical innovations that appear

promising with high level production functions are much less so

with lower level response surfaces.



FIXED RESOURCES

Undoubtedly the least understood effect of producing on a

farm with a high proportion of fixed inputs or resources is the

influence of fixed resources on the production possibilities or

opportunities curve. Many economics texts cover the case of

limited resource firms combining products in stage I of the

production function. This produces an opportunities curve that

is concave from the origin, Figure 1, for which specialization,

and not diversification, maximizes income. But even in this






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case, the effect of the resources fixed for the firm but

variable between enterprises is usually ignored. Rather, it is

assumed implicitly that the amount of the X to X fixed factors

in each of the production functions in Figure 1 is equal. This

implies that X to X are not interchangeable between Y and Y

This clearly is not the case with a limited resource firm.



Consider the case of a firm choosing between one or two

products, Y and Y and with four units of a resource X fixed

for the firm but variable between the two enterprises. If one

input X is variable, there will be a family of production

functions related to the levels of the fixed resource with which

it is combined, Figure 2. Implicitly assumed in standard texts

is that there are four units of the fixed resource available for

each of the two enterprise possibilities. However, if rather

than produce only one product, using all four units of the fixed

resource, the farmer produces some of both, then some of the same

four units of the fixed resource must be used in the production

of the second product. The effect is to shift both production

functions downward from X X =4, a consequence not considered

in the standard explanation of enterprise combination. As a

result, production possibilities are represented by a family of

opportunities curves for which the envelope opportunity curve is

again concave, not convex, Figure 2c. This effect exacerbates

even more the consequences of forced diversification.


COST OF LEARNING






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One of the most critical functions of management is learning

to use new technology. Depending on the nature of the

technology, it may take several attempts before its anticipated

potential can be reached. The responses achieved at each

different attempt form what can be called a learning curve. Most

work dealing with learning curves has associated successful

learning with reduction in unit cost. In Figure 3,learning is

related to increase in yield which is frequently the aim of a new

agricultural technology. In this figure, yield potential from

the new technology is very high. However, it takes nearly five

attempts before the full potential is achieved.



Economically, present yield has an associated gross income,

cost and net income, Figure 4. A farmer with a relatively low

level of yield and income is presented with a new technology that

has high gross income potential. However, associated with this

potential high income is usually an increased cost, Figure 5. If

a farmer decides to use the new technology, he invests at the

higher cost level. If he does not achieve the potential response

on the first or second attempt, as shown in Figure 5, net income

can be negative for a period of time. In this figure it takes

three years to break even. In a large volume, commercial

operation, the future, positive income stream can easily pay for

the losses during the early stages of learning. However, on a

small farm with low volume, this is more difficult, especially if

a portion of that low volume is used for subsistence on the farm






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and does not enter the market.



A person who has less time to devote to the learning process

cannot achieve the potential from the new technology as rapidly

as a person who has more time available for learning. Hence, for

a manager of the small-scale, family farm who has many

enterprises to manage, the learning curve shifts to the right and

more attempts will be required before potential is achieved,

Figure 6. On the other hand, technology that is simpler to learn

can shift the curve to the left. Fewer attempts are required

before the full potential is reached. The conclusion is that

simple rather than complex technology is more appropriate for the

small-scale family farmer with little time available for learning

how to use the new technology for each individual enterprise.



However, simpler technology that would shift the learning

curve to the left, usually is associated with a lower potential

benefit and net income, Figure 7. This leads to rejection of the

simpler technology by scientists when evaluating alternative

technologies in favor of more complex technologies with higher

yield and income potential. For the scientist who assumes

instantaneous learning, this is a logical decision. But for the

small, diversified farmer who does not learn instantaneou-ly, the

simpler technology may be more acceptable and more adoptable than

a higher payoff technology that takes several attempts to learn

and may therefore be rejected.






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A rapid rate of learning, a large volume over which to

amortize the learning cost, and a low discount rate would all

enhance the adaptability of a proposed new technology. None of

these are characteristic of a small farm. In their absence, a

particularly high potential profit would be required to entice a

small farmer to try the new technology. But high payoff

technology is usually associated with a high proportion of

purchased inputs requiring cash or credit which the small farmer

does not have and/or increased risk to levels unacceptable to a

person who would be risking his home and not just his business.





SUMMARY AND CONCLUSIONS



Low quality resources on small farms compared with large

farms, shift downward the response surfaces associated with a

technological change making the potential profit from the

adoption of the technology less than for a large farm. Forced

diversification on small farms combined with a high proportion of

fixed resources, reduces income rather than increases it as on a

larger capital base with a higher proportion of variable

resources. Less management time available for each enterprise on

small, diversified farms makes learning more difficult and costly

and further reduces the discounted present value of the response

of a new technology that does not produce anticipated returns the

first year. Any of the effects individually reduces the

acceptability of a high cost or complex technology to the small






Page 9


farmer. When all effects are taken together, as is the case on

most small farms, the result can be overwhelming rejection of

much modern technology. And if small farmers are unable to adopt

new research results (technology) because of these straight

forward economic reasons it is not correct to argue that most of

our agricultural research is scale neutral.



The conclusion is that agricultural research designed for

small farms must result in technology that is simple and not

complex, to reduce learning costs; use mostly resources available

on small farms with a minimum of purchased inputs, to reduce

capital requirements; and be evaluated and tested under the

resource conditions found on the farms of the clientele for whom

they are designed, to reduce inflated estimates of potential

response. It is critical that agricultural researchers

comprehend the economics of small farms if they intend to produce

technology for them. Otherwise, agricultural research will

continue almost inevitably with a bias, albeit unintentional,

toward large, commercial farms and world-wide efforts to aid

small farmers will continue to have only limited effects.







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CITED REFERENCES





Carter, H.O., W.W. Cochrane, L.M. Day, R.C. Powers and

L. Tweeten. 1981. Research and the family farm.

Paper prepared for the Committee on Organization

Policy. Cornell University, Ithaca.




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