The economic returns to institutional innovations in national agricultural research

Material Information

The economic returns to institutional innovations in national agricultural research on-farm research in IDIAP, Panama
Series Title:
CIMMYT economics program working paper
Martínez, Juan Carlos, 1956-
Saín, Gustavo
Place of Publication:
México D.F. México
International Maize and Wheat Improvement Center
Publication Date:
Physical Description:
53 p. : ill. ; 28 cm.


Subjects / Keywords:
Agriculture -- Research -- On-farm -- Economic aspects -- Evaluation -- Panama ( lcsh )
Agriculture -- Research -- Economic aspects -- Evaluation -- Panama ( lcsh )
Agricultural innovations -- Panama ( lcsh )
bibliography ( marcgt )
international intergovernmental publication ( marcgt )
non-fiction ( marcgt )
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Bibliography: p. 51-53.
CIMMYT economics program working paper ;
Statement of Responsibility:
Juan Carlos Martínez, Gustavo Saín.

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Full Text

Juan Carlos Martfnez*
Gustavo Sa in**
CIMMYT Economics Program Working Paper 04/83
Regional Economist, CIMMYT Regional Economics Program for Central America and the Caribbean. The activities of the Regional Program are supported by a grant from the Swiss government. SAgricultural Economist, CIMMYT.

To the Caisan team, for its
personal and professional comitment to the Panamanian Fanrmer.

This work is not a result of our isolated intelectual efforts; it is rather the outcane of our intense interaction with both, our colleagues in CIMYT and IDIAP, and our field experiences in on-farm research operations.
The work has benefited from contents made on an earlier draft. Our thanks for that to Donald Winkelmann, Derek Byerlee, Edgardo Moscardi, David Rohrbach, Larry Harrington, Mike Collinson, Grant Scobie, Lucio Reca and Robert Tripp. We assume full responsability for any remaining limitation of the study.
Last, but not least, we want to extend our recognition to Jose Roman Arauz and his team for their direct involvement in the field work; to Pedro Santamaria for his assistance crunching numbers in the computer, and to Maria Luisa PRodriguez for her patience and craftmanship in typing numerous drafts in the iterative process leading to this final document.

In cooperation with researchers in national agricultural research programs, CIMMYT has sought to develop procedures which help to focus agricultural research squarely on the needs of farmers. The process involves collaboration among biological and social scientists (for the most part economists) in identifying groups of farmers for whom
technologies are to be developed, defining farmer circumstances and problems, screening this information for appropriate research opportunities, and then implementing the resulting research program on experiment stations and in the fields of representative farmers. The process emphasizes fixing priorities in research and identifying
solutions which are appropriate to farmer's circumstances.
The Instituto de Investigaciones Agropecuarias de Panama (IDIAP) was
created in 1975 with the basic goal of reaching Panamanian farmers with technologies appropriate to their specific agroeconomic circumstances. Given this goal, IDIAP agreed with CIMMYT on a cooperative effort in an area-specific, on-farm research program. It was expected that work would generate useful technology and, as well, would serve as a source of methodological and organizational experience in this type of research. The initial program was designed for a maize producing area under the leadership of IDIAP and with technical support from CIMMYT. CIMMYT's constribution drew on the experiences of other countries where national program and CIMMYT staff were jointly engaged in farm-level research.
An earlier report, Institutional Innovations in National Agricultural Research: On-farm Research within IDIAP, Panama, Martinez, Juan Carlos and Jos6 Ron-An Arauz, describes collaborative on-farm research as a needed complement to experiment station research. It concentrates on research in Caisan, a maize producing area, providing details about the surveys and experimentation which led to the introduction of an improved maize technology.
The study by Martinez and Sain presented here examines the benefits and costs of on-farm research. In this paper, Martinez and Sain recognize

that the farming innovations under consideration could have came through station research or through farmer experiments as well as through the on-farm research process described. Each implies a different path through time for development and diffusion of the innovation and for the rate at which increases in productivity are achieved. These differences are a focal point of the analysis. It was not possible to measure the method's contribution to the relevancy of station research, another source of benefits from on-farm work.
Some have been apprehensive about the cost efficiency of such research. Martinez and Sain show a high rate of returns to this investment in on-farm research, largely because the resulting technology was taken up so rapidly by area farmers. The rapid diffusion, in turn, was the result of a research process well tuned to their needs and circumstances.
The Martinez and Sain report on returns to investments in on-farm research is anong the first of its kind. We hope that similar reports will soon be available from other countries so as to add precision to our understanding of the potential from such research.
Donald Winkelmann, Director
Econcmics Program,

I. INRDUCTION ............................................ 1
II. CAIS\IN: PRODUCTSN INUT .................................... 3
III. METHODOLOGXY.................................................. 6
1. Objectives of the Evaluation and the Institutional Point of
View............................................... 6
2. Identification and Characterization of the Products to be
Evaluated ................................................. 8
3. Estimation of the Annual FlcM of Research Benefits ..........10
3.1 Direct Imzpact.. ................................. I...... 10
3.2 Distributional Impacts ................................... 15
3.3 Indirect Impacts ..................................... 15
3.4 The Regional Social Price of Maize ......................... 16
4. Estimation of the Annual Flow of ResearchCosts.............. 18
5. The Benefit/Cost Patio and the Rate of Raturr................. 22
6. Estimation of Adoption Patterns............................ 23
7. The Economic Returns to the Methodological Innovation ........ 26 IVT. RESULI.TS......... *................................... .......... 32
1. Adoption Patterns ....................................32
2. Estimation of the Annual Flow of Net Benefits.............. 36
2.1 Estimation of the Technology Induced Yield Increase ......... 36
2.2 Net Benefits per Unit of Land............................. 3
2.3 The Annual Flow of Net Benefits........................... 39
3. The Annual Flow of Research Costs.......................... 40
4. Benefit Cost Patio and the Pate of Return ............. 40
V. CONCLUSIONS......................................... 42
APPENDIx..................................................... 48

Gustavo Sain
It has been common practice in modeling technological change to consider institutional development as an exogenous variable. Furthermore, these models have usually hypothesized that causality runs from
technological to institutional change (Ruttan,_ 1978). Y The fact that, despite widespread promotion, many new technologies are not used by farmers, has lead to the development of alternative models considering institutional change as endogenous in the model with causality running in both directions (De Janvry,.1978, Ruttan, 1978).
This study deals with the economic evaluation of certain innovative
methodologies for agricultural research, aimed at developing appropriate technologies for target farmers in the near-term. These methodologies were initially implement-ed on a trial basis by a recently. created national research institute in Panama, and later institutionalized within the research organization on the grounds that they significantly contributed to the increased efficiency of public investment in agricultural research. In the past, agricultural research in Panama was conducted by different organizations including the Agricultural Development Ministry (IIDA), the University of Panama, and various public and private enterprises. In general, it was carried in agricultural experimental stations often under conditions quite different from those faced by fa=rners.
At t e same time, there was a general consensus among policy makers
that the existing research structure was generating an insufficient
I/ Follaing Ruttan "an institutional change occurs when there is a
change in (1) the behavior of a particular organization, (2) the relationship between such an organization and its environment, or (3) in the rules that govern behavior and relationships in an organization's environment" (1978, p. 329). In this definition the term organization means a decision unit which exercises control of

amount of appropriate technology to impact effectively the technological structure of the agricultural sector. This deficiency provoked interest in revising traditional research strategies. As a. consequence, the Panamanian Institute of Agricultural Research (IDIAP) was created in 1975 with the main objective of increasing farmers' productivity and income levels with special emphasis on farms of medium and small size.
A guideline of the institution was that of focusing research on specific regions and crops for the development of technologies appropriate to representative farmers in areas defined as high national priorities. Research could thus be concentrated on the most important farmer problems and the scarce resources of IDIAP used to best advantage. Its activities were planned in a sequential pattern to permit methodological adjustments as experience was gained and to provide. a framework for the training of a corp of national on-farm researchers.
In 1978, the first such program began in the area of Caisan with the cooperation of CIVYT and with a former CIMMYT trainee assigned as coordinator of the program. At the same time, the issues which would shape IDIAP's institutional organization were being discussed and Caisan, its first area-specific on-farm research program, was expected to be a source of experience for the development of research procedures for IDIAP.
The Caisan program was planned and carried out strictly within the limits of the human and financial resources normally available to IDIAP. Thus, the cooperation of CIMMYT (development of procedures and in-service training) was designed in such a way as to not exceed normal resource allocation for area-specific programs.
The area of Caisan is located in the northwest side of Panama, involving 10,000 ha of territory and about 300 families. The most important production system is a maize/bean rotation, which led to the inclusion of both maize and beans as target crops for the research program. A complete report of maize results, including surveys and experiments carried between 1978 and 1982 can be found in Martinez and

Arauz (1983), and will not be covered in detail in this paper.
The main objective of the Caisan Project was to increase in the near-term productivity and income of representative area farmers. -Also, Caisan represented a first step in a process which built up from on-farm research actions towards an articulated on-farm research program. In this framework, the methodological implications of the Caisan experience and their spillover effect in terms of the institutionalization of on-farm research within IDIAP -was an important "output" expected fran the Project. Accordingly, the progress of the work was closely followed and intensively discussed by IDIAP researchers and directing staff in national meetings, field days and regional workshops. As a result of these follow-up activities, and given the increasing emphasis in, area specific on-farm research in IDIAP, the institution decided to conduct an evaluation of the cost efficiency of the on-farm research procedures used in Caisan. This evaluation was expected to quantify the social rate of return of IDIAP investment required to implement these on-farm research procedures directed at one of the target crops of Caisan. With this basic goal in mind, an evaluation study was designed and conducted for maize within Caisan program by 1982. -Y This paper reports on the qualitative and quantitative results of this evaluation.
The f lad of basic inputs and outputs of the Caisan Project is described in Figure 1. Two basic types of "outputs" resulted from the implementation of Caisan. The first one is associated with the contribution of Caisan to the institutionalization of on-farm research within IDIAP. This contribution has been obtained through learning-by-doing, in-service training and workshops, all based on Caisan experience. The resulting
2/ On-farm research methodologies used in Caisan are not crop specific
and were equally applied to both target crops (maize and beans).
Although results on beans were less documented and sistematized at the time of the evaluation (mid 1982), the impact of the program in beans production has been at least equivalent, if not superior to the one obtained in maize, being research costs at similar level for
both crops.

Resource Allocation for On Farm Research
Area Specific Research Methodology and
Programs Training
Methodological Experience in OFR New Technological
Learning-by-doing; In-Service Alternatives for
Training; Seminars; Workshops Area Fanners
- Spillover Effect Farner Adoption
- Institutionalization of Direct and Indirect Impacts
On-Farm Research Increase in Yields
- Input Saving Effects

increase in IDIAP's capabilities to inplenent on-farm research procedures in other areas of the country can be considered as an addition to the national stock of knowledge and, hence, as an important positive externality produced by the Project.
The other product is that related to the main objective of increasing, through technology generation, productivity and income of representative area farmers. In this sense, the products are the technological alternatives generated by the program and recommended to farmers. Benefits of these products are valuated through impacts
associated with actual farmer adoption of these alternatives. In other words, the farmer is placed as the final judge of this process of technology generation transfer, and accordingly, adoption is taken as necessary condition for associating positive benefits with the technological alternatives involved. At the time of the evaluation four technological alternatives had been generated by the Program. Two of them, chemical weed control and spatial 'arrangement and density, were of yield increasing nature requiring scme additional resources (costs) per hectare for its adoption. The other two, zero-minimun tillage and no use of fertilizers were basically input (costs) saving per hectare without affecting yields.
On the input side of the Project, two types of inputs can be identified. First, CIMMYT contribution, which has been entirely ccnposed of procedures for on-farm research and training in the use of these procedures. Both elements, research procedures and training have been recently of increasing importance in the CINMYT cooperative work with national research programs. The second type of inputs corresponds to resources reassigned by IDIAP fron the experimental station research to on-farm research in Caisan. 4/ These include human resources, fixed assets (like vehicles and a mini tractor), the rental of a house in the
This cooperative work takes place through CIMYT Regional Programs.
See Juan Carlos Martinez (1982).
On-farm research is understood here as a liasson and needed
complement between the more traditional station research on one
hand and the extension activities on the other.

area, and the different inpuEs (fertilizer, herbicides, insecticides) required for carrying the on-farm experiments.
Figure 2 shows the sequence of decisions followed in the evaluation of the Caisan Project. In the rest of this section the main methodological problems associated with each stage are briefly described and the particular decision taken regarding the case at hand is justified.
1. Objectives of the Evaluation and the Institutional Point of View
Given the nature of the Project, its evaluation could be carried outassuming either a national or international perspective. Whether to follow one or the other will basically depend on the objectives of the evaluation.
The objective of the evaluation was the reasurement of the cost efficiency of the methodology applied in Caisan. Specifically the
national research institution, IDIAP, was interested in knowing the rate of return of the investment required to imrplement area specific on-farm research programs like Caisan as a needed complement to station research. In this sense the objective of the evaluation can be stated as the estimation of the rate of return to the Panamanian society of the resources invested in implementing the OFR methodology used in Caisan.
Assuming an international perspective will imply that benefit and costs will be traced beyond Panamanian borders. In this particular case, on the benefit side spillover effects and increased methodological experience accruing to other countries via CIR1YT international programs should be considered as a positive externality. On the cost side, CINMYT
resources allocated to this type of activities should also be considered, spreading their cost among the various international programs of similar nature implMented with CIMYT cooperation. In other words, assuming an international perspective would imply the evaluation, starting from

Definition of the Objectives of the Evaluation
Definitions of the Institutional point
of View
Identification of Inputs and Outputs to be Evaluated
Estimation of the Estimation of the
Annual Flow of Annual Flow of
Research Benefits Research Costs
Benefit Cost Analysis

Panama, of the international system operating via CIM4YT in the area of on-farm research. This does not appear consistent with the objectives of the evaluation, and would be of little utility for IDIAP decision makers.
Assuming a national perspective has various implications. Spillover effects would be confined within Panama,. while, on the cost side, CIqM4YT could be visualized as part of the international environment faced by the country, from which IDIAP, could occasionally, take elements without any cost. This was the case of the contribution of CIMYT to the program, in terms of OFR rthodologies and training, which accrued to IDIAP without cost for the country. In the words of Kislev and Hoffman evaluating wheat irrprovemnt in Israel: "From the point of view of the Israeli decision maker who has to decide on the allocation of funds to research in the country, free knowledge is part of the environment in which the local research system is operating. The cost of producing this knowledge abroad should not have any effect on his decision." (1978, p.173). In this case the concept is extended to include not only knowledge captured and used directly by Panama, but as well to include the free training and mthodological and professional services which complex rented Panamanian resources.
Since this appears to be more consistent with the specific
objectives of the evaluation, this was performed with a strict national point of view. Accordingly only resources allocated to the Program by IDIAP were considered.
2. Identification and Characterization of the Products To Be Evaluated
Agricultural research may be thought as a production process in which inputs such as previous knowledge, research scientists, laboratories, and research materials to produce certain products.
Definition and characterization of the outputs presents conceptual problems which are, in general, dependant on the correct statement of the objectives and institutional point of view of the evaluation (Scobie, 1979, Schuh and Tollini, 1979). The decision to perform the evaluation

frmn an strict national point of view, clarifies smate of the issues outlined by Scobie and Schuch and Tollini but not all of them. As a result of the research process two types of outputs were identified (see previous section): 1) An addition to the national stock of knowledge through increased capabilities and gain in experiences within IDIAP, and
2) an increase in productivity and income of area farmers through technology generation-adoption.
As recognized in the literature, assigning a value to the first type of product would imply an almost unafordable methodological burden in the evaluation. This is so given that the product defined as a gain in the stock of knowledge is intangible, and also due to the fact that there is neither a market nor other feasible mechanism measuring how much society values this kind of product. By considering only the product related to technology generation it is possible to have an indication of the social returns due to the methodological innovation applied in Caisan. This is feasible if the evaluation is performed taking as a starting point the prevailing technological situation (farer practices) which in turn can be associated with the nore traditional station research. That is,
incremental Benefit-Cost arialysis applied to a case study (Caisan) would serve as a proxi of the social gains of applying OFR methodologies. As every other case of study generalization should be made with care.
In summary, due to methodological difficulties only technological innovations generated by the program would be entered as products in the evaluation. By ccnmparing the benefits generated by this product with that which would have resulted without the program, a reasonable measure of the rate of return accrued from the OFR strategy followed in Caisan can be achieved. In turn, this rate would be a proxi, assuming replicability of the project by the national institution, of the returns to the second type of product: the increased capability within IDIAP to coriduct similar area specific OFR programs in other regions of Panama.
5/ Traditionally the area was covered by the extension service from

3. Estimation of the Annual Flow of Research Benefits
3.1 Direct Impacts
Two main ex-post procedures have been used to evaluate the benefits of agricultural research: the economic surplus (or index number) approach and the production function approach. The choice between both methods rests basically on the quantity and quality of the available data and on the nature of the case at hand.6/
Following Norton and Davis (1981), the production function approach consists essentially in introducing into the production function a variable as proxi for research and extension. Among the studies using this approach at an aggregate level are those of Griliches (1964), Evenson (1967, 1968), Cline (1975), Davis (1976), Kahlon (1977), and Lu, Quance and Li (1978). While Peterson (1960, 1967) and Berdhal (1975) used the approach at the individual product level.
The economic surplus approach, much less data demanding that the previous one, has been widely used to estimate returns to agricultural research in both developed and developing countries. The approach is based on the concept of consumer and producer surplus. An excellent discussion of both concepts can be found in Currie, Murphy and Schmitz (1971), Hertford and Schmitz (1977), and Mishan (1968). A discussion about the surpluses as measures of welfare changes can be found in Boadway (1974). The work of Schultz (1953) and Griliches (1958) are considered as pioneers in using the approach.
Griliches' analysis can be regarded as a special case of a more general scheme presented by Peterson (1967). Figure 3 shows this general case.
There is also a differentiation in terms of marginal and average
rates. In the economic surplus approach what is estimated is an average rate of return to the investment in agricultural research,
the production function approach will provide a marginal rate.

\2 B
0 Q2 1
The displacement of the supply curve froman S1 to S2 due to the vanish ent of the innovation would reduce social benefits (consuner and producer surplus) by an amount equal to the area OAB which is regarded as the net social benefits due to the innovation. The area OAB is in fact the algebraic sum of the area P1P2AB, measuring the change in consumer surplus and the area [(OBP1 '-(OD 2)], measuring the change in producer surplus.
Among other studies which have used the approach are those of Schmitz and Seckler (1970); Hertford and Schmitz (1977); -Y and Kislev and Hoffman (1978). In a recent article, Wise (1981) shows that the surplus method can be derived as a specific case of a more general
The authors showed that linear supply and demand functions provide enough accuracy in the calculations without the complications due to the non-linear specifications. In their words: "However differences in the estimates of benefits provided by the more complicated formulations and those presented here are small for usual values of
the key parameters. The main reason is that in all formulations the critical determinant of the value of the benefits derived from research is simply K.P.Q. or the percentage change in the value of
production attributable to research."

approach measuring benefits. The author also showed the equivalence of both methods: when distributional aspects are introduced, social net benefits can be obtained either as a sum of benefits or as a sum of surpluses.
In order to measure the direct impacts generated by the adoption of the new alternatives, the Wise benefit approach was chosen as the more appropriate. Although the Wise benefit approach and the surplus method have been shown to be equivalent the former was preferred because it adjusts more naturally to the division of the technological alternatives generated by the Program into two groups according to the type of impacts resulting from its adoption.
Before proceeding to the application of the benefit approach, -the structure of regional supply and demand curves must be specified. Because maize acreage affected by the program represents a small percentage of total national maize acreage, it was considered that the project would
have a negligible impact on the national maize market, hence, its evaluation may proceed at fixed prices. This assumes that the region faces a perfectly elastic demand curve. Furthermore, the existence of a minimum support price fixed at the national level provides further
motivation for considering the region as a "price taker", i.e. an increase in regional production due to the Program will not affect the maize price level.
In specifying the supply curve elasticity it should be noted that, because of the nature of the on-farm research methodology, the short-run supply curve should be used in evaluation of the impacts of improved technological components. Although there are no available elasticity estimates, scme empirical evidence, (such as the fact that land and farm labor resources remain fully employed despite short term price variations) supports the hypothesis that the short run supply curve is highly inelastic. Furthermore, the fact that maize is a component of an important regional naize/bean crop rotation, the later being an
important cash crop in the region, would further sustain this hypothesis. A highly inelastic short run maize supply curve would mean itat in the

short run there is not a significant number of farmers leaving or entering the maize production sector. In other words, maize acreage in
the region can be considered as fixed.
Sumnrmarizing, the postulated regional Supply-Demand structure is one
of a perfectly elastic demand curve facing a perfectly inelastic short run supply curve. Within the previous framework, four technological
alternatives generated by the Program will be considerated in terms of their direct impact associated with impact farmer adoption. Table 1 describes them in contrast with farmers' practices prevailing in the
Recom-endation Domain at the initial stage of the Program.
Technological Farmer Practice Technological Alternatives Main Direct Impact
Canponent Through Adoption (Per
Hectare Basis)
Chemical Weed Application of 1 it/ha Application of 1-2 lts/ha
Control of 2,4-D, 30 Days After of Paraquat, 20-30 Days
Planting After Planting
- Application of 1-2 kgs/ha
of Atrazine, 0-10 Days YIELD INCREASING
After Planting
Spacing Arrangement Irregular Spacing 50,000 seeds per ha and Density 40,000 Seeds per ha planted in Rows
at Planting
Zero Minimum Plowing and Harrowing: Manual Chopping of Weeds
Tillage 3 Passes Followed by 1-2 lt/ha of SECOND GROUP
Chemical Fertilizers Application of No Fertilizer Use
200 lbs of 10-30-10
The four alternatives have been classified in two groups according
to the nature of their impact in the production process. The first group includes appropriate chemical weed control and a planting arrangement in rcws with increased density, implying a yield increasing effect and a net addition of resources in order to achieve the higher yields. The second

group, includes zero-minimum tillage and no use of fertilizers which are 8/
associated with an input saving effect without affecting yields. 8- This categorization allows separate treatments for each group in measuring the benefits associated with the alternatives involved. In the case of the alternatives within the first group total benefits for each alternative will be:
B =B1 B2 being
B 1 2
B2 = AC* H-HAS B1, B2, AR, AC>0
BI, is the social value of additional maize production generated with
the diffusion of the new technological alternative involved.
AR, is the yield increase induced by the adoption of the alternative. H, is the net proportion of maize acreage cultivated with the new
HAS, is the total maize acreage within the recommendation domain, which
is assumed to be fixed and estimated in around 1000 hectares.
B2, is the social value of the additional resources necessary to achieve
the increase in production, (AR.H .HAS),
AC, is the net addition in variable cost per unit of land .necessary to
achieve the increase in yields. Recombining previous equation B
could be written as:
B = H.HAS [ LR.Pm AC]
That is, total benefit generated with each technological alternative will be equal to the total maize acreage cultivated with the alternative times the net benefit per hectare associated with its use.
For the particular case of alternatives in the second group, they do not have any significative yield effect hence AR-- 0 and consequently B1 = 0. Because they have an input saving effect, decreasing cost per unit of land, AC 8- For more details see Arauz, Martinez (1983), Chapters 5 and 6.

3.2 Distributional Impact
The distributional aspects of the Program can be assessed by considering the four social groups identified by Wise (1982). -/ Given the nature of the Program these patterns of distributional impact appear to be very simple. Consumer welfare does not change (no production augmenting effect for second group of technologies, no price effect for either group). While benefits of technological development will fully accrue to innovators (adopters) in terms of producer surplus; those who do not adopt the technology remain the same (relevant relative prices are unaffected by the Program). Finally since there is no technological treadmill effect L the number of farmers not adopting the technology and leaving the sector will be negligible.
3.3 Indirect Impacts
The most important secondary impact of the Project is the effect of zero (minimum) tillage on future soil erosion levels and consequently on
the natural fertility of the soil. This impact would be larger for farmers whose maize plots are located on slopes of considerable
Little information is available about potential yield decrease due to the reduction of soil fertility associated with erosion so quantification of this impact is difficult. In this work no attempt is made to measure it. Consequently, benefits are in this respect, underestimated. 11/
9_/ Consumers, producers who do not adopt the technology and leave the sector, producers who do not adopt the technology and stay in the
sector, and producers who adopt the technology.
10/ Cochrane W. (1958) "Farm Prices: Myth and Reality" University of Minnesota Press.
ii/ Following tradition in this type of evaluation when an option is encountered the choice is made such that the associated benefits are
the lowest.

3.4 The Regional Social Price of Maize
Public policy in Panama with respect to maize production has been directed in the last decade ta ,ard the goal of self sufficiency. The main policy instrume-nt used in the attempt to achieve this goal has been the implementation of support prices for this product fixed above the international price. As a consequence domestic production increased from an annual average of 53,800 metric tons during the period 1971-75 to an annual average of 68,600 metric tons during that of 1976-80. Concurrently with this change, imports of maize decreased from an annual average of
19,500 metric tons to 11,400 metric tons during the same periods.
Although there is no direct empirical evidence about the annual balance of the province of Chiriqui, indirect evidence support the 12/
hypothesis that Chiriqui is a net exporter of the product -. The
situation for Panama and for the region is then depicted in Figures 4 and
In a closed economy and in absence of regulations Pe and Qe in figure 4 would be the equilibrium price and quantity for maize at the national level. But Panama confronts a perfectly elastic international supply curve given by P.O. where P. is the international price of maize. Then, in absence of regulations, the relevant supply curve becomes OAO with OQ2 domestically produced, OQ1 domestically consumed and (Q1-Q2) imported. Once a support price P is established, domestic consumption
falls to OQ3, domestic production increases to OQ4 and imports decrease to Q4Q3. The area ADE represents the social loss due to the excess cost of domestic production of the amount Q4Q2, and the area CBF is the loss
12/ Maize production in Chiriqui is reportedly used as follFws- 25.4% is
consumed in the farm, 4% is used as seed, 37.1% is used as feed and the remaining 38% is sold out the farm. Given an annual average total production of 11,661 m.t., it results that 4,431 m.t. are annually sold by farms. Chiriqui urban population was, in 1980, of 91,017, considering an estimated consumption of 18.82 kg/person,
total urban consumption would be of 1,713 m.t. This would leave a net positive balance of 2,178 m.t. Although there are some small mills in the province, the bulk of Panama's mills are located out of the province, hence the excess production over internal consumption
is likely sold out the region for consumption and/or processing.

in consumer' s surplus due to the reduction in consumption of the amount QIQ3
0 D P
r Or
P e
DC s
5 E F 0
D r
0 Q2 Q4 Qe Q3 QI 0 Q2 Q'I
National Level Regional Level
In figure 5, Or and Dr are the regional supply and demand curves,
respectively. Ps is the support price in Panama City and P' = (Ps-TC) is the support price net of transportation costs from the region to Panama City. In this case, OQ1 is the atount produced by the region, QQ2 is the amount consumed within the region and Q2Q1 is the amount the region
Given this situation and assuming that the region surplus production
is entirely exported to and consumed in Panama City n/ the social price of extra units of maize produced by the program will be given by the import price of maize (CIF, Panama City) net of transportation costs from
L3/ Panama City is the most distant point among those of potential
destination for the maize of the region. Hence this assumption implies (via transport costs reduction) the lowest alternative with
respect to pricing the maize.

Caisan to Panama, i.e. p1 = P. -TC. Tis is -so since in absence of m i
distortion in the foreign exchange market this price would reflect the social opportunity cost of extra units of maize without accounting for distortions in the internal market.
Introduction of a support price above the border price increases the social opportunity cost of extra units of maize, hence the society willingness to pay for additional units of maize from Caisan will also increase. In this case the marginal value of extra units of maize from Caisan will be given by the support price net of transportation costs, i.e. p2 = p -TC.
m s
Fran a perspective of general equilibrium and welfare considerations, maize pricing should be done under the assumption of non existence of
regulations and hence Pm should be used. However, social preferences in terms of food security (through import substitution) are well established and politically legitimized as a sustained policy goal which cannot be ignored neither by IDIAP nor by any institution like IDIAP.
In other words, what could be considered with a global perspective as a variable (i.e. agricultural policy) should be and has been considered by IDIAP as a para-ieter, setting the franework within which the institution could display its research policy and institutional strategies. Then when considering hcai efficiently IDIAP has been doing this in the particular case of Caisan the maize price which should be
used is the one provided by P2 as a reflexion of the agricultural policy
framework faced by IDIAP. Accordingly, the resulting rate of return will best reflect, in our view, the efficiency of OFR methodologies implemented by IDIAP in Caisan. In any case, the decision was* taken to conduct the evaluation under both maize pricing options.
4. Estimation of the Annual Flaw of Research Costs
Definition and characterization of inputs to the research process presents similar problems to those described in the case of the products (Scobie, 1979, Schuh and Tollini, 1979). Arong the most cnion problems

are those arising when a particular resource is used to produce multiple or joint products, the case of serendipity in the process, and the correct specification of the knowledge stock participation in the research process. Given the decision to perform the evaluation from a strict national point of view, resources contribute by CI 4YT are considered as free and do not enter the cost side of the evaluation. With respect to resources contributed by IDIAP, Table 2 sha,7s their composition in terms of basic items. The human resources figures
indicate the proportion of man-years used by the program for each of both labor categories, for example during 1979 the program used. 8 man-years of skilled labor and 1.45 man-years of semi-skilled labor. In the case of fixed assets the figures reflect the proportion of the total annual services provided by the asset which is assigned to the program i.e. in 1979, 50 percent of the annual services provided by the rented house is assigned to the Project. Similarly 80 percent of the annual services (hours per annum) provided by a pick-up truck is used by the Project. Finally, as research materials are project specific, the table listed the 14/
amounts of each one of the used in the program.
The economic evaluation of the program requires first that the project be evaluated against the without alternative and that resources used be priced at their respective opportunity cost interpreted as the value of the output the resource would produce in the activity from which the resource is withdrawn.
Application of the with-without criterion requires the identification, as ccrronent of the cost side of the evaluation, of only
14/ While identifying research costs an interesting problem came out in
the discussion. Part of the cost of on-farm experimentation are shared by the farmers (i.e. land, farmer time). Since OFR fits in the production process, that is, it takes place while the farmer production process takes place, these costs will be usually more than outweighted by the benefits resulting from leaving the products of the experimental plot with the cooperator farmer. While this could still leave some doubts in terms of how it should be tested in an evaluation of OFR, it has, from the perspective of research strategy and management, a positive side associated with the fact that a percentage, even though small, of research costs is paid by
those who will be the final recipients of research results.

additional resources necessary to conduct .the program. In the case of fertilizers and pesticides they are program specific resources, hence they are enterely charged to the program (see table 2). With respect to fixed assets, the program used existing equipment and in addition a house was rented. In the case of the equipment it was considered that program accomplishment would require an additional time effort because increasing off station work. As no reliable estimate of this increase existed the total time proportion assigned to the project was taken as a proxi for
each piece of equipment used by the project (see table 2).
1978 1979 1980 1981
A. Human Resources
1. Skilled Labour .40 .8 1.20 1.20
2. Semi-skilled
Labour .20 1.45 1.45 1.45
B. Fixed Assets
(Proportion of Total
Annual Services)
1. Rented House .50 .50 .50 .50
2. Equipment
Pick-up .65 .80 .80 .80
Mini-tractor .50 .50 .50
C. Research Materials
1. Fertilizers a/
Formula 12qq 12qq 12qq
Urea 6qq 6qq 6qq
Superphosphate 10qq 10qq 10qq
2. Herbicides b/
Paraquat 10 Gl 10 Gl
Atrazine 8 kg 8 kg 8 kg
2-4-D 1 G 1 G1 1 Gl
Dinitroaniline 1 Lt
3. Insecticides b/
Carbofurane 45 kg 45 kg 45 kg
a/ One quintal (qq) is equivalent to 45 kg.
The listed amounts refer to comrcial products.

All personnel involved in the project was already working for IDIAP. Application of incremental analysis requires again the identification of
additional thre effort attributable to the program as the coaxonent of the program's labor cost. The same criterion adopted for the equipment was used in this case, the total time proportion assigned to the project by each merrber was taken as a proxi for the additional time effort required by the accomplishment of the Project over the traditional station work.
All resources allocated by IDIAP to the program including labor, fixed assets and fertilizers and pesticides are evaluated at 1981 market prices. This implies that market prices for these resources reflect their
opportunity costs. A brief justification for this procedure follows for each resource category.
i. Labor--There is a general agreement in the welfare economics literature that skilled labor wages approximately reflect the opportunity cost of this type of labor (Irvin 1978). Since the program only used skilled or semiskilled labor, 1981 wages were used to estimate the labor cost incurred by the Caisan Project.
ii. Fixed Assets--Lack of accurate data availability precludes the estimation of the total costs of using the equipment employed by the project. The only data available was that of gasoline expenses. As the gasoline price in Panama reflects its importation costs it was considered that this price properly represented the opportunity cost of using it. Ignoring other user costs would result in underestimation of the true costs of the program. This is partially corrected by increasing the total annual estimated cost by 10%. In the case of the rented house the annual rent was considered as reflecting its opportunity cost.
iii. Pesticides and Fertilizers--The use of market prices was justified in this case on the grounds that there are no subsidies with respect to these resources. As such, domestic prices have historically folloRed world price fluctuations.

5. The Benefit/Cost Ratio and the Rate of Return
In order to calculate the benefit cost ratio and the rate of return
of the project, the methodology employed by Griliches (1958) -also used by Kislev and Hoffman (1977) among others- was adopted. The benefit/cost ratio is estimated as:
(1) B/C=- (PANB+AFnM-AHI4)
PANB, are the past annual net benefits compounded to the base year AFNB, are the annual future net benefits discounted to the base year AJC, are the annual future maintenance costs discounted to the base year, and PARC are the past annual research costs compounded to the base yearGriliches presents the rate of return, r as (1958, p.425):
(2) r= k x B/C
where k is the discount rate used to estimate the B/C ratio. The rate of return r, can be- interpreted as the discount rate at which the stock of costs yields an annual flaw exactly equal to the annual flow of net benefits, alternatively r may be interpreted as the discount factor at which the annual flow of net benefits should be discounted in order to yield a stock exactly equal to that of costs. In other words, a rate of return of say 1.90 (190 percent) would indicate that each dollar spent in the project would generate a future annual f lw of 1.90 dollars of net benefits.
The criterion to judge a given project according to the B/C ratio is that for the project to be acceptable this ratio should be larger or equal to one. Then this last equation says that:
r =k if B/C= 1
That is, if k represents the social rate of time preference between

present and future conscription, then equation 2 states that the average rate of return for each dollar invested in the project (r), will be larger equal or smaller than the social rate of preferences if the discounted benefits are larger equal or smaller than the discounted (at the same rate) costs.
6. Estimation of Adoption Patterns
An im-portant element for measuring the benefits of agricultural research is the estimation of the percentage of farmers (acreage) who have adopted the new technology. The nature of the OFR methodology used in Caisan presumed that appropriate technologies would be available in the near term. This, in turn, would fulfil a necessary condition for farmers' acceptance and accordingly speed up adoption.
A formulation coxmonly used to represent the diffusion of new innovations is the logistic growth function or learning curve. The graph of the function and its generic functional form are shcwn in figure 6.
y= K + exp -(+BXIj
15/ This section draws heavily on Martinez (1973).

Adaptation of this function to a context of technology adoption process is straightforward. Let h (t) be the maize acreage proportion cultivated with the i-th technological alternative in year t. Then the logistic function representing the difussion time pattern is:
h. (t)=K. [1+exp-(A.+B.t) 1
1 1 311
In this equation Ki represents a constant called by Griliches the "ceiling" of the adjustment function. That is Ki is the maximum expected percentage of adoption of the technology. A. is a parameter positioning the curve in the time scale, while B. shcws the rate of growth or rate of acceptance of the innovation.
Martinez conceptualizes the diffusion process along the logistic curve as succesive short-run equilibrium points between the supply and demand for the new technology. In this context the value of the ceiling would be interpreted as the long run equilibrium. Quoting Griliches: "While shift on the supply side determines the origin of the development,
the rate of development is largely a demand or acceptance variable" (Martinez, 1973, p.81).
The rate of acceptance B, therefore, can be interpreted as
sunmTarizing the demand conditions for the technology. As such, the estimated value of B could be used as an indicator of the farmers' degree of acceptability of the technology.
If enough data is available the logistic parameters A and B can be estimated, after the model has been previously linearized, by the least square method. If enough observations are not available, Martinez (op. cit. p. 92) presents a method to obtain a crude estimation of the parameters. The method consists in the simultaneous resolution of the following two equation system:
h i(tl= Ki [1+ exp-(A + Bi t
h (t2)= K. [1+ exp-(A + B.t2)
i2 i24

To solve this system in terms of A and B it is necessary to have information about the maxiumm expected adoption proportion K, and of the adoption proportions in two points in time hi (t) and hi (t2) 16
This has been the procedure followed for estimating the patterns of adoption for each technological alternative generated by the Program. The point hi (tI) was based in the initial formal survey implemented at the planning stage of Caisan for assessment of farmer circumstances. The other point h () was hi (1982); estimated with an especially designed adoption survey carried out in July 1982. The survey methodology used in this case was similar to that used in the assessment of farmer's
circumstances (yet with different objectives). That is, an informal survey (done in May 1982) was carried to design a well focused formal questionnaire. This questionnaire was filled out in June 1982 for a randan sample of 45 farmers within the recommendation domain of the Program.
Finally, the value of the adoption ceiling was estimated based on the knowledge and experience of regional technicians with the acceptability of the alternatives offered, their potential impact in net income and the relative degree of difficulty in their management. For
16/ Once the values of K, h (t ) and h(t2) are known, the system is
reduced to a two equation-wo unknown system which admit a unique
solution. System (3) can be rewriten as:
A + B t1 =C1 A + B t2 =C2
C1 = ln [h(t1)/K-h(tl)]
C2 = ln [h(t2)/K-h(t2)]
The values of A and B which solve the system are calculated as:
A = Clt2 C2tl and B =C2 Cl
t2 tl t2 -t

example, the change from irregular planting to planting in rows is seen by farmers as more complicatede" than the change in the type of weed control. Furthermore, zero and minimum tillage requires the replacement of usually contracted mechanical tillage by hand chopping plus application of herbicides, activities which are usually performed with own farm labor force.
In order to identify farmers who adopted the new technology,
definition of a set of relevant adoption criteria (discriminant variables) for each new technological alternative is necessary. Once these criteria are defined farmers are classified as full adopters if the
technology they are actually using agrees with all these criteria. Similarly, partial adopters are those farmers whose current practices only match sone but not all of these criteria.
Partial adoption may occur if because of lack of information and/or financial or market restrictions the farmer adopts only part of the new technology. This case should not be confused with that of farmers who decide to "test" the new technology. In this case he usually adopts the new technology in full but applies it to only a fraction of his parcel. In this way the farmer is able to compare for himself the "advantages" of the new technology against those of the conventional one.
Table 3 describes the adoption criteria defined for each of the four technological alternatives.
7. The Economic Returns to the Methodological Innovation
As it was stated earlier, one of the objectives of the evaluation is the estimation of the returns accrued to the application of the on-farm methodology into the research process. In order to do so it is necessary that the program be evaluated against the alternative, i.e., against traditional station research, hence an adoption pattern for the traditional approach needs to Ibe assumed.

TA1: Chemnical 1. Chemical Weed Control 1. If the farmer uses
Weed Control chemical weed control
2. Type of Product 2. If the control is
accomplished with
Gesaprim or Gramoxone
3. Application Time 3. i) Gesaprim: 0-15
days after planting
ii) Gramoxone: 0-35
days after planting
4. Doses 4. i) Gesaprim 1-3kg/ha
ii) Gramoxone: 1-3
TA2: Spacing 1. Planting Arrangement 1. If planting is
arrangement and accomplished in rows
2. Density 2. 45,000-60,000
TA3: Zero 1. Tillage system 1. If the farmer does
Tillage not use a mechanical
2. Application of 2. If the farmer
herbicides applies herbicides
prior to planting
TA4: 1. Application of 1. If the farmer does
Fertilization fertilizers not apply fertilizers

Following tradition, a pessimistic assumption which can be made about this pattern, is that station research would be able to identify exactly the sane research opportunities than those identified by OFR. This assumes that, the only advantage of applying the new research methodology is accounted by an extension effect. E_ In other words, the only difference between both research strategies is given by a tire lag in the process of discovery, and dissemination of the same 18/
technological caponents.
Once this assumption is adopted the benefits to be estimated are a function of the differential rates of adoption under both alternatives. Follwing Lu (1981) several alternatives may be considered: these are illustrated in Figure 7.
In order to estimate the incremental benefits due to the application of the on-farm methodology in Caisan the shadow area under both curves needs to be estimated. The problem is that the adoption curve under the station research stragegy (TSR in the figures) is an hypothetical one and cannot be estimated directly. Hence 'it was decided to estimate upper and lower bounds of benefit-cost ratios and rates of returns to the Project by assuming different cut-off points of the benefit flw from the Project. Figure 8 illustrates the approximation method used for the case of a change in the adoption lag.
17/ The process of technological innovation can be decompossed into two
highly interrelated and complementary effects: a research effect dealing with the creation of new technology and an extension effect
dealing with the dissemination of this technology. (Lu, 1981).
18/ In case of complex farming systems, ignoring bioeconomic
interactions may lead to situations in which promising research opportunities remain uncovered. OFR methodology implies the ex-ante assessment of most promising research opportunities minimizing
therefore the probability of missing an important one. Hence the assumption of ignoring the research effect in OFR will certainly
underestimate its contribution within the research process.

i. The only change is in the year of ii. The only change is in the rate
introduction of the new technological of adoption of the new
components. technological components.
Percent of adoption Percent of adoption
t(1) tl(1) t time t(1)=tl(1) t time
iii. The only change is in the iv. The only change is in the adoption
adoption ceilingKof the new lag of the new technological
technological components. components.
Percent of adoption Percent of adoption
I time
t(1)=t(1) t t(1)=t() t t time
OFR= Adoption pattern of new technological components under OFR. TSR= Adoption pattern of new technological component under traditional station research.

,Percent of adoption
I I I _> Time
T m
o t T
Given the estimated OFR curve, and the hypothetical TSR curve then a
cut off point t should be chosen such that the true unknown area ABC would be approximated by the area AD. In order to do not overestimate benefits the area D should be smaller than B plus C. By changing the cut
off point t it is possible to simulate different effects and positions of the TSR curve, leading to upper and lower bounds in the benefits side and hence in the rate of return of the program. The four cut off points simulated in the evaluation are illustrated in figure 9.
The most likely changes between both methodologies (considering only extension effects) would be a combined change in the year of introduction and in the adoption lag of the new technological ccmponents. Hence, the cut off point of 1982 would provide a very unlikely lower bound of the benefits and returns to the OFR ethodology applied in Caisan, while the case of t =1985 would provide a fairly pessimistic estimate of benefits and returns to the program.
A more realistic estimate of the benefits and returns to the OFR methodologies would be given by the cut off point of 1990, in which case some research effects would be also incorporated. Finally, the case of
t = illustrates the upper bound in benefits and returns to the

1. t*=1982 2. t*=1985
Percent of adoption Percent of adoption
h(t) h(t )
11 I
I.I . I I
1980 1982 time 1980 1985
3. t*= 1990 4. t*=w
Percent of adoption Percent of adoption
h(t ) K --.OFRO
O 8 time time
1980 1990 1980

program. As a matter of fact this case is equivalent to remve the assumption that traditional -station research would have been able to identify and effectively work with the same research opportunities identified by the .OFR program in Caisan.
It should be stressed here that the simulation of benefits and returns performed in this work does not imply that there are not benefits to the society after a certain date. Social benefits due to technological innovation are, once adopted, permanent.
1. Adoption Patterns
The initial step in the implementation of the evaluation methodology described in previous section was given by the adoption surveys conducted in 1982. The application of the adoption criteria resulted in the percentage of maize acreage cultivaLed with each alternative. The same procedure was carried for farmer practices from the 1978 survey. Table 4 presents the resulting percentages, as well as the estimates of maximum adoption points (K i). In turn, these values lead to the 'estnimation of logistic adoption functions whose parameters A. and B. are also included in Table 4. The shape of each logistic functions as well as their location in the time scale are shoc.n in Figure 10. TABLE 4. ESTIMATED ADOPTION PARPMTEPS
Alternatives t1 h (t1) h (1982) Ki Ai B i
1.Chemical weed
control 1979 .082 .609 .90 3.3 1.0
2.Seeding arrangement 1979 .207 .627 .80 1.8 1.8
and density
3.1.Zero tillage 1980 0 .188 .50 24.8 2.4
3.2.Minimum tillaqe 1980 0 .042 .25 23.9 2.2
4.No use of fertilizers 1979 .388 .795 .90 1.0 1.0

.0 .0
57 -0 .57
% .4-.4
0 ti Z- -D 5 21=81op(1637~ i
V 0
.9700$2 82 85 87 88 90.9980 82 84 86 8 0
Years Year
0r .4-t):.2t[i-.9 e(p-3.86602.+368t)
197980i 8'. 83 85 8I 89 9 82 84 8

The values obtained for h. (1982) indicate a high percentage. of adoption for the alternatives -after only few years of project operation. This confirms the hypothesis that technologies where appropriate to farmer circumstances prevailing in the recommendation domain. Also, the speed at which adoption took place, reflected by the value of the parameter Bi, is telling us not only that the alternatives generated where agroeconomically viable for representative farmers, but also that they likely represented a solution for an important production problem faced by farrrers and correctly identified as a research opportunity at the planning stage of the Program. 19/ This, as it stands, is an important result of the evaluation. It is still to be seen in the rest of this section whether or not they have been reached efficiently.
In order to proceed towards the estimation of benefits we need to consider the values of hi (t.). The starting point for the diffusion due in
to the Project is placed in different years according to the time of release of the alternative. In this sense, it was considered that there was not. diffusion, hence no adoption due to the Project, of any technological alternative until 1980. We are then interested in clarifying the meaning of the positive values for h (tl) and what role have they play in the quantification of benefits.
The relatively high values for not use of fertilizer (38.8%) and planting arrangement and density (20.7%) could be understood by the fact that in the first case, some farmers were not having access to credit and
consequently not using fertilizer in spite of prevailing recommendations, while the second one was also related to credit programs but in a
different sense, it correspond to farmers which had accepted the fully mecanized services of PROMEC4/A, included in the credit package, and consequently had conventional mechanized land preparation and planting, in which case obviously arrangement, and also density were decided by PRUPMCA which had the same calibration of the' planters for all the services provided. Note that as the Project evolved, conventional
19/ The research hypothesis formulated at the planning stage can be seen
in Martinez and Arauz (1983), Section 4.

necanized tillage and planting decreased as a result of the release of the zero-minimum tillage alternative.
The remaining positive value for h (ti) is a small percentage (8%) in chemical weed control, corresponding to a non-systematic trial and error process folla,7ed by farmers searching for better chemical weed control alternatives. This value reflects the magnitude of the weeds problem identified as a promising research opportunity by the
Project. Finally, the values of h(t1) for zero and minimum tillage were zero, as there were no farmers using at tI these alternatives. In any case, in order to obtain the net annual adoption level due to the Project, whenever a positive value for hi (t ) was found it was discounted from the adoption level reached in each year.
In other words, this net proportion was estimated along the tine scale of the logistic adoption function as H.(t.) = hit.) h (t). Table 5 shows the annual values of H. (ti) for each alternative. Zero values for 1979 reflect the reasonable assumption already established that no adoption due to the Program took place during this year.
Year A L T E R N A T I V E
(j) 1 2 3.1 3.2 4
H I (tj H 2 (ti) H 3.1i (tj H 3.2 (t i) 114 (t i)
1979 0 0 0 0 0
1980 .113 .039 0 0 .1.70
1981 .307 .292 .024 .005 .313
1982 .527 .420 .129 .042 .407
1983 .685 .503 .433 .163 .460
1984 .727 .549 .493 .236 .487
1985 .800 .572 .500 .249 .500
1986 .811 .583 .500 .250 .507
1987 .815 .589 .500 .250 .510
1988 .818 .591 .500 .250 .511
1989 .818 .593 .500 .250 .511
1990 .818 .593 .500 .250 .511
After .818 .593 .500 .250 0
20/ For more details see Martinez and Arauz (1983), Section 4.

The ceiling maximumm adoption) is approximately achieved for every alternative around 1985. The ceiling is continued to perpetuity for all but fertilization. In this case it is ass~ued that due to natural process fertilizer application would start to have significant responses starting in 1990, hence adoption of this alternative was assumed to produce benefits only unLil 1990. 21/
2. Estimation of the Annual Flow of Net Benefits
Net benefits per hectare are estimated for each alternative
subtracting from the change in gross benefits the change in those costs that vary. ( AC) Gross benefits are, in turn, calculated as the product of the increase in yields due to the alternative (ARi), times the social price of maize, (Pm).
This section is organized as follaqs: yield increases are estimated in part 2.1; part 2.2 deals with the. estimation of net benefits per hectare, and the annual flora of net benefits for each technological alternative and for the entire program are calculated in part 2.3.
2.1 Estimation of the Technology Induced Yield Increase'
Although Hertford (1977) stressed some years ago that the most important coponent in measuring the benefits from agricultural research is the production shift parameter K (the parameter measures the relative change in production A Q/Q due to the adoption of the new technology), Dalrymple (1931) pointed out the existence of an imbalance between the relatively sophisticated methcxlology developed to measure the area under the supply-demand curves and the poor data base upon which the method is used.
21/ The Project currently includes fertilizer level trials in continuous
plots to analyze what will happen in the medium run to the natural fertility of the. land as result of adoption by farmers of improved (more intensive) production practices in weed control and. spacial
arrangement and density.

Traditionally two sources of data have been used to measure the relative change in yields: data gathered at experimental level and data from aggregate average farm yields.
While data from aggregate average farm yields has the advantage of being readily accessible; in most developing countries it is a very unreliable estimate of yields at farm level. On the other hand, two reasons are commonly quoted for the existence of an urard bias in the yield gathered at experimental station level when used as farm level yields estimators. The first one given by the fact that the level of non-experimental variables is kept at what is considered an "optimum" one, and the second one given by the existence of marked differentials in managerial factors.
In this work, a third source of data is used to estimate the relative increase in yields at farm level: data gathered in on-farm trials. In this case yield data is free of the first source of bias because the level of non-experimental variables are kept at farmer level. Hence, yield increases reflect more accurately increases due to the change in experimental variables and cannot be partially attributed to the interaction with high intensity use of other inputs. Furthermore experimental yields were adjusted not only to account for agroclimatic and pest related risk factors but also for managerial factors.
In this sense, data used in this work reflects in the most accurate possible way yield gains at farmer level due to the adoption of the technological innovations. It is believed that if this source of data is available (results of OFR experimentation), it should be preferred over alternatives when estimating the gain in yields due to technological innovation.
Estimation of the yield increase induced by the adoption of
technological alternatives belonging to the first group was carried out using the experimental results from all the three cycles of the project. The first two years of experimentation were ccnsidered as normal, while during 1981 yields were adversely affected by an epidemic attack of

Helminthosporium sp. Since epidemic attack of Helninthosporium sp. in the region is estimated to have a very low frequency of approximately one in twenty years, a weighted average of both periods using these frequencies as weights was estimated.
Another adverse factor which should be taking into account is that of lodging. Results from the 1978 survey indicate a high frequency of occurrence with partial crop losses. As there is no information about the magnitude of partial damage, this effect was incorporated into the yields calculation by assuming a total loss imJpact and a smaller occurrence frequency of once every ten years. Adjusted yields are shown in Table 6, where Do and H represent the farmer's practice for seed density and herbicides application respectively where DI and H1 represent the recommended levels in each case.
H H Average
o 1
D 2.901 3.893 3.40
D1 3.682 4.841 4.26
Average 3.29 4.37
Source: Caisan On-Farm Trials 1979/81.
These numbers indicate a yield increase due to chemical weed control
of 1.08 ton/ha, while seed ar-rangement and density raises yields by .86
ton/ha. These impacts should be weighted by a "yield adjustment coefficient" which account for differences between farmers and experimental managerial conditions. In the case of Caisan this coefficient was estimated by Arauz and Martinez (1983) to be 10 percent, hence the final increase in yields to be used in the evaluation are:
- Although a positive interaction effect was identified in some of the
trials, this impact was ignored in the evaluation.

AR= .972 ton/ha
AR2 =.774 ton/ha
for alternative 1 and 2, respectively.
2.2 Net Benefits per Unit of Land
Calculation of the net benefits per unit of land generated by each technological alternative is accormlished by the method of partial budgeting (Perrin et al 1976). Tables 10, 11, 12, 13, and 14 in the appendix 1, provide details of performing this operation, a sumTary of the results under the two pricing alternative is given in Table 7.
TABLE 7. NET BENEFITS PER UNIT OF LAND (DOLARS/fHA, 1981) -TA 1: Chemical TA 2: Spacing TA 3.1: TA 3.2: TA 4:
Social weed control arrangement Zero Minimum FertiliPricing and density tillage tillage zation
1. Without 141.14 104.66 18.75 12.75 39.74
2. With 191.29 145.22 18.75 12.75 39.74
Taken 1981 prices the estimated social prices were:
P = without regulation = $149.50/etric ton., and
p2= with regulation = $201.09/metric ton.
2.3 The Annual Flow of Net Benefits
Once net benefits per unit of land and the total net acreage cultivated with each alternative are estimated, calculation of the annual flow of net benefits proceeds by multiplying both numbers for each alternative. The annual flow for the entire program is procured by adding up the individual flows over the alternatives.
Tables 14-a, 14-b, in the appendix, present these flows for both

social pricing alternatives. The benefits flows shown in these tables correspond to those generated under the upper bound assumption of perpetual flows. Alternative ones are estimated by choosing appropriate cut-off years.
3. The Annual Flow of Research Costs
Annual research costs elapsed from mid 1978 (last 5 months) to 1982. It was assumed that after 1982 there would be a perpetual flaw of
maintenance costs in order to keep yield constant against an adverse nature (Griliches, 1958). A pessimistic annual. estimation of these costs
amounted to 40 percent of the 1982 cost level. Table 8 shows the estimated annual flow of research costs of the program.
1978 1979 1980 1981 1982 After
Annual 3,000 14,300 17,800 17,800 17,800 7,200
4. Benefit-Cost Ratio and the Rate of Return
To estimate the Benefit-Cost ratio (B/C) and the rate of return (r), 1982 was chosen as base year. A discount factor of 15 percent, the same used by USAID in the evaluation of Panamanian agricultural projects of similar length, was employed to carried out the flows to the base year.
The benefit--cost ratio and the rate of return were estimated for the four assummed cut off points of the flow of net benefits under both pricing alternatives. The results of the calculations are summarized in Table 9.

Pricing options t =1982 t =1985 t =1990. t =00
Social prices 3.11 7.86 12.93 16.36
without regulation (47%) (118%) (194%) (245%)
Social prices 4.05 10.30 16.99 21.69
with regulation (61%) (155%) (255%) (325%)
values within parenthesis are rates of return, without
parenthesis benefit-cost ratios.
In all cases, the rates of return substantially exceed the social cost of investment capital. The level of the rates of return will. depend upon the assumption adopted about the true position of the tradition station research curve (see section 3.7) ranging for the first pricing option fran the very unlikely 47 percent in the case of a cut off point of 1982 to 245 percent in the case of a cut off point at infinite.
Using the authors' criteria, the case of t =1982 can be disregarded as very unrealistic. N'ot only it ignores by assumption any "research effect" in the imnpleme~ntation of the on-farm research methodology, but also, it attributes an almost negligible "extension effect" which appears to be inconsistent with the fact that in the past, actions of traditional research and extension have -not resulted in significant changes in technological production patterns in the area, while as shc~n in the adoption patterns, inmrtant technological changes have taken place soon after the OFR starts rendering its first results.
A wrre realistic lower bound would be that of t =1985, while the upper bound would be given by t =.The first case would still represent a purely "extension effect" as the only advantage of on-farmn research over traditional station research strategy. On the other hand, the upper bound would represent a removal of the restrictive assumption that

traditional station would have generated in due time the same technological alternatives as the OFR program. In other words, this cutt off point stress the research effect of OFR by actually assuming that the alternatives generated in Caisan would not have been available should the OFR had not been in operation. The cut off point of t =1990, represents a middle point. It compromises between stressing the "extension effect" in som components like the case of fertilizers and planting arrangement and density where relatively high h(t1) values were found, and stressing the "research effect" in others like herbicides and zero-mninum tillage in which case the survey shows zero or near zero h(t1) values.
Summarizing, the rate of return due to the methodological innovation in Caisan ranges between 118 and 245 percent, with a mst likely value of 194 percent in the case of social prices without regulations and between
155 and 325 percent, with 255 percent as most likely value when regulations are taken into account. The mst likely values of 194 and 255 percent are revealing that each dollar invested up to the base year in imrplementing the on-farm research methodology in Caisan, render a flow of social net benefits of 1.94 and 2.55 dollars per year depending on the pricing option.
In the last five years considerable progress has been acoplished by national agricultural programs in the testing and developing of
operational methodologies for on-farm research, as well as in terms of the amount of resources allocated to this type of activities. As this process evolves, initial methodological and technical problems are resolved and new ones take their place, among them that of the
institutionalization of on-farm research within national research structures.
The starting point for this institutionalization process has been the experience arising from ongoing area-specific, on-farm research programs. These have usually been managed in the initial stage of this process by ad-hoc technical groups from within the research structure.

Fran CIMUT' s perspective, the process builds from basic mthodological ideas, to on-farm research experiences, to the institutionalization of these activities within the national program. In other words, it goes in a bottom up approach, from on-farm research actions to an articulated on-farm research program.
IDIAP and Caisan illustrate this process. The institutional strategy of IDIAP provided the framework for the development of Caisan. The progress of the Project and the methodological experiences arising from it were closely followed by the national directing staff and intensively discussed by researchers and directing staff in national meetings, field days and regional workshops.
This in turn has lead to a reinforcement of the initial orientation of IDIAP towards area-specific, on-farm research. Also, in the methodological dimension, it provided concrete experiences, not only in terms of what to do in on-farm research (surveys, experiments, etc.) but, more important, how to do it, i.e., the informal survey leading to a well-focused formal questionnaire, the prescreening of best-bet technological components based on the assessment of farmer circumstances, the management of experim-ental and nonexperimental variables within the trials, etc.
The present econcic evaluation represents a contribution to this process of institutionalization of on-farm research with som methodological implications in terms of evaluation research; 2_/ which in this case has been adjusted to the particular requirements and institutional circumstances of IDIAP.
An impact evaluation in the more traditional sense (for example impact on yields, impact on production) could represent a necessary, yet not sufficient condition for additional support of this activities on the
part of policy makers. Among other things, meeting sufficient condition
23/ No work of similar nature evaluating on-farm research was found in
the review of the literature on economic evaluation of agricultural

for increasing support also requires dealing with the more controversial issues of the cost efficiency of this methodological innovation in agricultural research. This would be normally considered before the process could be advanced toward the more complex stages of institutionalizing on-farm research within the present national structures. The evaluation has been carried incorporating both elements, impact and cost efficiency, which are sinthetisized in the social rate of return for the IDIAP investment required to implement the Caisan
In terms of economic evaluation methodology, section III showed how the interaction between the "state of the arts" and the particular requirements coming from the nature of on-farm research activities, resulted in certain key decision for the evaluation methodology to be implemented. Farmer adoption,* and consequently actual impact on production, was required for associating any positive benefits to the research process. The same information generated in the on-farm research process was used in the evaluation. This included the initial planning survey of 1978, and the trial results from three production cycles
adjusted by risk factors prevailing in the area. In addition to this, an
adoption survey specially designed to fit the objectives of the evaluation, was implemented in 1982. With all this, the amount and quality of the information used in the evaluation appear to be superior to that used in evaluations of similar nature. 24/ In this sense, it is believed that the information coming from appropriately conducted on-farm experiments will close Dalrynple' s gap between sophisticated evaluation theory and poor data base (see section IV, 2.1).
Meaningful conclusions came out as a result of the evaluation conducted. The level of adoption of the technological alternatives gave indication of the degree in which they fitted circumstances of
24/ For example, the pioneer work of Griliches (1958), in a more
ambitious evaluation (hybrid corn in U.S.), assumes that yield increase associated with the use of hybrids is of 15 percent over pro-innovation yields. The equivalent information in the case of OFR
in Caisan is based in three cycles of on-farm trials, which
incorporates farmer practices as a base for the analysis.

representative farmers front Caisan. On the other hand, the spee at which adoption took place indicated not only that the technologies developed were agro-econaically viable for representative farmers, but' also that they represented a solution to an important problem faced by those farmers. This priority had been correctly identified in assessing research opportunities in the planning stage of the program.
In other words, the results in terms of adoption speaks out of the usefulness of the OFR mthodology for reaching representative fanrers with appropriate technologies in the near term. In assessing "how
useful," the evaluation was required to enter into more quantitative aspects dealing with the specific contribution of the nthodological innovation represented by OFR against the "without alternative"; that is, what would have happened with purely traditional station research. This way of approaching the evaluation is consistent with the conceptual role attached to OFR as a needed complemnt of traditional station research.
Quantitative aspects of evaluating methodological innovations were covered by considering three alternative assumptions about the relative importance of the research effect of OFR over that of TSR.
The first assumption puts a zero weight to this effect attributing an extension effect as the only advantage of OFR over TSR. This provides a lower bound for the economic returns to national investment on
methodological innovations. The assumption is represented by considering that the flow of net benefits attributed to the programs last only to 1985.
In the other extreme of the scale the upper bound of the returns is obtained by strongly weighting the research effect attributable to OFR: technological alternatives engendered by the Project would not have been generated otherwise. In this case, the flow of net benefits are extended to perpetuity.
Finally, an interme-diate case is considered by differentially weighting the research effect by technological components. This provides

a measure of economic returns which appear as the more likely to occur.
In addition, two pricing scenarios for maize were considered. The first one, consistent with a perspective of general equilibrium and welfare considerations, assumed the existence of non regulations; the other, more consistent with the specific objectives of this particular evaluation, takes price policy as a parameter faced by IDIAP. In this scenario, price policy is part of the framework (set of parameters) within which the institution should display its research policy and institutional strategies.
Results indicated that disregarding what pricing scenario is adopted the lowest social benefits generated with the OFR methodology have been comfortably above research costs. This loest bound for the rate of return ranges between 118 and 155 percent, depending on the pricing scenario adopted, 25/ while in the case of the upper bound the rate fluctuates between 245 and 325 percent.
Finally, when the most likely case of a net flow lasting to 1990 is considered, the rate of return ranges between 194 and 255 percent.
'These results reafirm the perception, based on this and other experiences, 6 that the OFR methodologies used in Caisan are costefficient in reaching target farmers with appropriate technologies in the near-term.
Consistently with preceeding results, IDIAP area-specific on-farm. research activities, have gone through considerable expansion since 1978 when the Caisan program begun with only two national researchers. At
- As a reassurance the benefit-cost ratio and rate of return for a
benefit flow lasting only to 1982 (the base year of the evaluation) was calculated. The rate of return ranges in this case between 47% and 61% depending on the pricing scenario. This indicated that even after only less than four years of the beginning of the program, social benefits basically accruing to farmers, outweighted research
26/ For example see Moscardi, E. (1983).

present these activities include five priority areas in agriculture, involving the work of 24 national researchers, and three priority areas in livestock with 21 researchers. As this expansion takes place, a set of issues related to the institutionalization of on-farm research becomes
a matter of primary concern of IDIAP. 27/ As the central management moves to cope with these issues, the institution coms closer to realizing its full potential for the benefit of Panamanian farmrs and the society as a whole.
2 See Martinez and Arauz (1983), Section 5.

without regulation with regulation
1 2
Pm Pm
A. Gross Benefits por ha. (A R x Pm) $ 145.31/ha $ 195.46/ha
B. Net Change in Variable Costs (A C) 4.17/ha 4.17/ha
b.1 Value of Additional Resources
i. 2.0 kg Gesaprin x $8.13/kg 16.26/ha 16.26/ha
ii. 1.0 it Gramoxone x $5.5/lt 5.50/ha 5.50/ha
Weighted average / 6.75/ha 6.75/ha
b.2 Value of Replaced Inputs
i. 1 it. 2-4-D x $2.58/1t. 2.58/ha 2.58/ha
C. Cost of Capital (15% 8 Months) .42/ha .42/ha
D. Net Benefits per ha 140.72/ha 190.87/ha
S The average was weighted by the acreage proportion controlled with
each product (weight for Gesaprim = .1166; weight for Gramoxone
Social price Social price
without regulation with regulation
1 2
Pm Pm
A. Gross Benefits per ha (AR x Pm) $115.71/ha $156.27/ha
B. Net Change in Variable Costs (AC) 11.05/ha 11.05
b.l. Value of Additional Resources i. 3 kg/ha of naize seed x $0.35/kg 1.05/ha 1.05/ha
ii. 2 days/ha of labor x $5.00/day 10.00/ha 10.00/ha
b.2. Value of Replaced Inputs.
C. Cost of Capital (15% 8 months) 1.11/ha 1.11/ha
D. Net Benefits per ha. (A B) 103.55/ha 144.11/ha

TABLE 12. TAs 3.1, 3.2, ZERO TILLAGE AND MINIMUM TILAGE 1/ Zero Tillage Minimum Tillage
A. Gross Benefits por ha. (AR x Pm) B. Net Change in Variable Costs (A C) $ 18.75/ha $12.75/ha
b.1 Value of Additional Resources
i. Two men days/ha x $5.00/day (hand 10.00/ha
ii. 1.5 lt Gramoxone x $5.5/it 8.25/ha 8.25/ha
iii. Two men days/ha x $5.00/day
(application of Herbicide) 10.00/ha 10.00/ha
iv. User cost of back pack sprayer 1.00/ha 1.00/ha
b.2 Value of Replaced Inputs
i. 3 machine hours/ha x $16.00/hour 48.00/ha
ii. 2 machine hours/ha x$16.00/hour 32.00
C. Cost of Capital (15% 8 Months) 1.88/ha 1.28/ha
D. Net Benefits per ha (A-B) 20.63/ha 14.03/ha
1/ Since technological alternatives 3.1, 3.2 and 4.0 are purely input
saving technologies without affecting yields the distinction between
alternative pricing of maize becomes irrelevant and is omitted from
the tables.
A. Gross Benefits per ha (LR x Pm)
B. Net Change in Variable Costs (AC) $39.74/ha
b.1. Value of Additional Resources b.2. Value of Replaced Inputs.
i. 2qq/ha of mixed fertilizer x $17.37/qq 34.74/ha
ii. 1 man day/ha x $5.00/day (application) 5.00/ha C. Cost of Capital (15% 8 months) 3.97/ha
D. Net Benefits per ha. (A-B) 43.71/ha

a) Social Prices without Requlation
Technological 1 2 3 4 Total
yeaf elrnatives Cheical Weed Spatial Arrange- Zero-1,ininirm Fertilization Caisan Control ment and Density tillaqe Project
1980 15,901 4,038 0 7,431 27,370
81 43,201 30,237 565 13,681 87,864
82 74,159 43,491 3,250 17,790 138,690
83 96,393 52,0S6. 11,220 20,107 179,806
84 102,303 56,849 12,457 21,287 192,896
85 112,576 59,231 13,482 21,285 207,144
86 114,124 60,370 13,808 22,161 210,413
87 114,687 60,991 13,822 22,292 211,792
88 115,109 61,198 13,822 22,336 212,465
89 115,109 61,405 13,822 22,336 212,672
90 115,109 61,405 13,822 22,336 210,672
1990 115,109 61,405 13,822 0 190,336
b) Social Prices with Regulation
Technological 1 2 3 4 5
year ternatives Chemical weed Spatial Arrange- Zero-Minimum Fertilization Total Control mewnt and density tillage Caisan
Siembra Project
1980 21,568 5,620 0 7,431 34,619
81 58,597 42,080 565 13,681 114,923
82 100,588 60,526 3,250 17,790 182,154
83 130,746 72,487 11,220 20,107 234,560
84 138,762 79,116 12,457 21,287 251,622
85 152,696 82,431 13,482 21,855 270,464
86 154,796 84,016 13,808 22,161 274,161
87 155,559 84,881 13,822 22,292 276,554
88 156,132 85,169 13,822 22,336 277,459
89 156,132 85,457 13,822 22,336 277,747
90 156,132 85,457 13,822 22,336 277,747
1990 156,132 85,457 13,822 0 255,411

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