Title Page
 Description of the Tunisian ASA...
 The perspective of others on the...
 Experience and insights drawn from...
 Conclusions and implications for...

Group Title: Staff paper - University of Minnesota Department of Agricultural and Applied Economics ; P78-10
Title: Institutional factors affecting the adoption of agricultural sector analysis methodology in LDC's
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00072505/00001
 Material Information
Title: Institutional factors affecting the adoption of agricultural sector analysis methodology in LDC's
Series Title: Staff paper - University of Minnesota Department of Agricultural and Applied Economics
Physical Description: 19 p. : ill. ; 28 cm.
Language: English
Creator: Klein, H
Roe, T
University of Minnesota -- Dept. of Agricultural and Applied Economics
Publisher: University of Minnesota, Institute of Agriculture, Forestry and Home Economics
Place of Publication: St. Paul
Publication Date: 1978
Subject: Agriculture -- Social aspects -- Lesser developed countries   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
non-fiction   ( marcgt )
Bibliography: Bibliography: p. 18-19.
Statement of Responsibility: H. Klein, and T. Roe.
General Note: Cover title.
General Note: July, 1978.
General Note: Minn. doc. no. 78-0594.
 Record Information
Bibliographic ID: UF00072505
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 04239148

Table of Contents
    Title Page
        Title Page
        Page 1
        Page 2
    Description of the Tunisian ASA model
        Page 3
    The perspective of others on the adoption of ASA methods
        Page 4
        Page 5
    Experience and insights drawn from Tunisian efforts
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
    Conclusions and implications for future ASA efforts
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
Full Text
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Staff Papers Series


July 1978


H. Klein and T. Roe

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University of Minnesota
Institute of Agriculture, Forestry and Home Economics
St. Paul, Minnesota 55108

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H. Klein and T. Roe*


Major efforts have been undertaken to both develop and apply large

scale agricultural sector analysis models (ASA) in a number of LDC's.

Well over a dozen LDC's have ASA models either in advanced or final

stages of development including Brazil, Columbia, Egypt, India, Ivory

Coast, Korea, Mexico, Nigeria, Pakistan, Thailand and Tunisia to name

some of these (13). All of these efforts have been funded for develop-

ment and directed by foreign donors with heavy participation by FAO and

the U.S. Agency for International Development. These ASA models have

been developed under a wide variety of circumstances; some have been

devised almost wholely by foreign technicians while others have been

joint efforts between foreign technical advisers and host country


Most of the literature in this area has focused on the theoretical

and analytical problems that have to be confronted in model development.

However, there is very little data concerning the institutionalization

of ASA modelling techniques within governmental decision making and planning

processes (3, p. 35). What little data there is does not look encouraging.

A 1972 USAID study evaluated agricultural sector studies to that date and

concluded that the utilization rates of these ASA efforts was quite low

and, with few exceptions, the resources expended in these efforts were

Staff papers are published without formal review within the Department of
Agricultural and Applied Economics


not justified by their usage. Interestingly, the study concluded that

there did not appear to be any relationship between the utilization rate

and the quality of the ASA effort.(10).

The general purpose of this paper is to consider some issues and

constraints relating to the process of using ASA as an operational

piece in the on-going policy decision making process of a developing

countries host institution. We shall attempt to elaborate from our

experience what some of the constraints on the institutionalization of

ASA techniques appear to be and to introduce some notions on how ASA

efforts might be modified to alleviate or to better deal with these

constraints. These issues are considered in light of (a) the generally

competing need to maintain a sufficient degree of model or technique

isomorphism so as to yield insights into the fundamental directional and

magnitudional impacts of policy instruments on variables (activities)

endogenous to the private sector, (b) the data, resource and human capital

endowments upon which an ASA effort is based and constrained, and (c) the

organizational structure of the institution hosting the effort and/or

the institution in which the effort is based. For our purposes here, we

accept the premise that sector models comprising at least some compre-

hensiveness and detail of the agricultural sector are useful policy

formulation and evaluation tools, among other uses, and that they offer

competitive alternatives to the sole use of other methods in many LDCs.

The plan of the paper is to first briefly, and non analytically,

describe the agricultural sector analysis framework developed in Tunisia


and to identify the principle participants involved in its construction.

The intent of this section is to provide a glimpse of the product in

order to focus the discussion on the constraints and issues considered in

its development. Next, a review of the literature is presented for

purposes of highlighting the concern others share for actually using

these frameworks as a comprehensive policy-decision making tool in LDC's.

Then a discussion of the issues and constraints which appear to effect

the institutionalization of ASA methods in Tunisia is presented.


The sector analysis model was developed in Tunisia. The model is

in the tradition of the Mexican ASA model (5) in the sense that a linear

programming algorithm is used to solve it and in the sense that the

procedures for incorporating nonlinear relationships into a linear

programming format (6, 12) are also included. A statement of the

initial version of the model appears in (11) and a later version in (4).

The present version of the model represents substantial inputs and

efforts by FAO and by our Tunisian counterparts who now have full

responsibility for and control of the model.

The model is static and small by linear programming standards

having about 400 rows and 1800 columns. It is specified so that activities

identify four regions of the country, where traditional modern and government

farms are identified in each region. Within each region, production

activities are specified for the major enterprises of wheat, feed grains,

sheep, cattle, irrigated crops produced in and out of season and tree crops.

Resource transfer activities are also specified and include seasonal labor,

machinery, credit, fertilizer and forage and for traditional farms,

household consumption.

The constraints are specified to capture the regional seasonality of

irrigated land, water, labor, and machinery use. Also included are com-

modity balance equations, and zero balance constraints reflecting livestock

feed activities. A set of convexity constraints also appear and correspond

to the demand functions for wheat, feed grains, legumes, various irrigated

crops, mutton, beef and various fruits. The most recent addition to the

model has been the incorporation of Cobb-Douglas production functions for

four different varieties of wheat.

Other sectors of the economy are included exogenously in terms of the

capital, credit, construction materials and other resources that they

have historically supplied to the agricultural sector.

The points of view of others concerning the use of these techniques

in a policy-decision making environment are presented below.


The literature suggests that over the last five years some attention

has been given to the problem of using ASA frameworks as an operational

tool in the planning process. In an earlier paper by Atkin and Rossmiller

(1), they pointed out that sector analysis and system simulation is a

"... very useful tool in the decision makers toolbox..." but concluded

that it is not a panacea to any of the policy decision makers problem.

In his 1974 paper "General Systems Stimulation Models for Sector Analysis",

Glenn Johnson (8) reflected his concern for the problem of using analytical

frameworks in the policy-decision making processes when he pointed out the

distinction between problem-solving research and disciplinary research. He

pointed out that while the former is designed and focused to find solutions

to problems faced by real world decision makers it is often a difficult

task which does not seem to be well suited to a strict interpretation of

the scientific method. Similarly, Thorebecke (13) concluded "... that a

large gap exists between what the models can deliver and what the users

need and desire for policy formulation purposes." More recently, Bassoco

and Norton (2) demonstrated how the results might be formulated from a

single sectoral model in a manner and form to shed some light on a rather

wide variety of issues of concern to agricultural policy makers. Yet,

difficulty exists in assimilating these techniques into an ongoing policy-

decision making process.

In our opinion, Kornai (9) very incisively lists nine lessons drawn

from his experience in institutionalizing mathematical models developed

for planning purposes. While our summation of this article does not do it

justice, he essentially emphasizes the need for allocating resources to

maintain a continuous dialogue between model builder and planner even at

the expense of decreasing the "mathematical completeness" of a model. In

a similar vane of thought Sherbini (7) was perhaps on the right track when

he suggested that at least part of the problem of institutionalizing sector

analysis efforts into the decision making process is related to behavioral

organization problems such as motivational, structural and communication

constraints. He suggests that using sector analysis to demonstrate how it

can be used to improve policy rather than change it tends to engender

support on the part of central decision making authorities. He points out


that organizations tend to be compartmentalized and self contained, thereby

reducing coordination and that "... feedback communication is invariably

weak and provides poor channels for sector analysis."

These views suggest that the resources, structure and behavior of host

institutions) in developing countries play a critical role in the adoption

and effective use of ASA methodology. Consequently, the extent to which

structural and behavioral factors are considered and incorporated into

the design and use of ASA methods, the more effective these methods may

become in the policy decision making-implementing process.


The background to our efforts in Tunisia that are important to highlight

the issues advance here are: the point in the hierarchical decision making

structure in which the ASA was present, the data, human and other resources

at the disposal of the ASA effort the portfolio of activities assigned to

the effort and briefly the nature of the planning process.

Briefly, taking the above topics in order, Figure 1 approximately

depicts the organagram of the ministry of agriculture. The directions

appearing on the left perform the functions of information supply and to

some extent policy analysis. The offices appearing on the right are

program implementing agencies. The division of regional services refers to

approximately 12 regional offices located throughout the country in

administrative regions referred to as gouvernorats. These regional

offices primarily supply extension services and perform various data

collection and monitoring functions.

The ASA efforts were located in the direction of planning, formally

referred to as the Direction of the Plan, Economic Analysis and Project

Evaluation. The organagram of this bureau appears in Figure 2. This

Direction is composed of the four divisions with a total of about 15

people training through USAID funding to the equivalent level of a U.S.

Masters of Science in Agricultural Economics plus a cadre of people with

various lower levels of college training. The available data base at

the initiation of the sector analysis effort was "meager".

The portfolio of activities ascribed to the ASA effort included the

design of an annual planning system and the development of an initial

version of an agricultural sector analysis model, both to be located in

the Division of Planning (Figure 2). The initial endowment of resources

to undertake this activity included two counterpart Tunisians trained to

the Masters of Science level in Agricultural Economics, a small cadre

of technicians and the right to request data and other special services

from the other Divisions in the bureau, in addition to the use of an IBM

360 computer.

While time and space do not allow the opportunity to discuss in

depth the nature of the planning process some of its important characteristics

can be highlighted. The formal planning process in the Ministry of

Agriculture includes the periodic development of a series of documents

listing publicly supported projects, data describing the recent history

of agricultural production by subsector and its structure, and some subsector

Ministry of Agriculture

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input and crop projections over the period of the plan. Committees

representing the various Directions and offices appearing in Figure 1

partake in this effort which is organized and directed by the Direction

of the Plan (Figure 2).

Now, from this background several constraints to institutionalization

of a sector analyses methodology becomes apparent. First, the Direction

in which the effort is located is not at a pivotal point in the hierarchical

structure so that the composition of the central decision making authority

is not obvious. This increases the difficulty of:

(a) formulating and articulating policy objectives,

(b) identifying policy constraints and the mechanism that

establishes these constraints,

(c) identifying policy instruments (and their dimensions) over

which central authority has discretion and the degree of


(d) developing a dialogue necessary for alternative strategy

evaluations and eventual strategy selection, and

(e) considerable effort and time is required to assess the analyses

underway in other Directions and evaluate their results and

importance relative to the total policy-making effort in

general and the sector analysis in particular.

Another set of difficulties attributed to the structure is the

need for coordination between the Directions on the one hand and the

offices on the other. This implies that a "good" policy strategy

derived from an empirical analysis may be very inefficient when


consideration is given to the Offices capacity to implement, monitor

and control the program implied by the strategy. Thus, inorder to

concentrate the analysis on alternative strategies that are feasible in

a program implementation sense, a dialogue must be maintained with these

offices. Thus, since it is not the discretion of the foreign advisor-

technician to modify the organizational structure to better fit his

sector analysis efforts, ASA efforts must be modified to fit the

structure or at least take into consideration these structural constraints.

With this background the issues considered in developing the

sector framework can be presented chronologically. The strategy followed

in developing the framework was that the maturation and institutionalization

of ASA would be determined by the amount of utility it would provide the

Direction (Figure 2), relative to its cost in terms of personnel and

other resources consumed in its development.

The issues perceived as important included: (a) the need to rely,

as much as possible, on data and sources of data collected and obtained

through normal government channels, (b) the construction of an analytical

framework in a manner which maintained, in the "eyes" of our counterparts,

a progression from field data through manipulative stages and finally,

to model coefficients, (c) the specification of a model and selection

of a technique whose complexity did not exceed the capabilities of our

counterparts, (d) the specification of variables whose resolution, time,

space and form (products, inputs) dimensions were as close as possible

to the very instruments and variables of importance to decision making

by the Direction and the Ministry.


To elucidate the above issues, the need to rely on traditional data

sources in addition to the resources required to collect field data was

primarily to ensure that once the model was constructed, its need for

periodic updating would not be constrained by the need to allocate

resources for purposes of obtaining the needed data. However, recent

events seem to show that this was not a problem as the data collection

capacity and quality have been improved considerably. In the case of

(b) above, the progression from field data to model was important as a

training device in model construction and it also provided for consistency

checks. That is, the raw data were converted into regional budgets. This

allowed for consistency checks with other estimates of regional product

and input supplies and also helped provide our counterparts with a better

initial perspective on the agricultural sector.

The specification of the model to reflect the instruments and

constraints which are within the realm of the policy makers authority to

manipulate, is, in retrospect, perhaps one of the most important considerations

determining the eventual complete institutionalization of the method in

the policy-decision making process. It also is perhaps the most difficult.

While the Tunisian ASA model is decomposed regionally and subsectorally,

further decomposition would yield additional utility to the Direction.

This follows because the program implementing functions of several of

the offices rely on instruments and resources that are more decomposed

than those appearing in the model. Furthermore, some of the variables

appearing in the model are not at the discretion of the ministry of

agriculture to-manipulate. For instance, agricultural product prices


and the prices of imported agricultural inputs are instruments at the

discretion of the Ministry of National Economy and the Ministry of Finance.

Consequently, policy analysis based on these instruments tended to engender

little interest on the part of the Ministry of Agriculture officials.

On the other hand, instruments that were later discovered to be at the

discretion of the ministry, such as storage and transportation services,

do not presently appear in the model. This obviously suggests directions

for future modifications of the Tunisian model.

The desirable degree of instrument "resolution" (i.e., the time,

place, form) and control, and the "real" objectives are often even

difficult for policy-decision making authorities to articulate. To

comprehend fully the array of instruments and structural characteristics

at the disposal of the policy makers implies a need to understand the

policy-making process, the capacity and effectiveness of the policy

implementing machinery and to be aware of the human frailities and general

behavior of these institutions. We suggest that this is the importance

of the dialogue between model builder and planner as discussed by Kornai

(9) and the need to consider the institutional constraints as advanced

by Sherbini (7).

It also appears to us that plans designed for making ASA techniques

an integral part of the policy-decision making and program implementing

framework of a ministry delegated with this responsibility, must recognize

and take into consideration that traditional channels for information flow

between policy-decision making authorities and program implementing

agencies have developed over a period of time. Consequently, these


traditional methods and channels have become institutionalized or at

least have developed an inertia in terms of the ways to make decisions

and take action. The more closely the use of ASA techniques can be made

to accommodate and to rely on these traditional structures, the more

quickly it is likely to become part of the planning process. If the

traditional organizational structure is such that ASA techniques cannot

be designed to accommodate and rely on these traditional structures, then

its our notion that they must be associated (in dialogue and office location)

as closely as possible with the decision making authorities themselves.


This paper focused on factors affecting the institutionalization of

agricultural sector analyses (ASA) as a useful policy-decision making

tool in developing countries. We suggested that the difficulties faced

in institutionalizing sector analysis efforts are probably common to

these efforts. These difficulties are associated with the resource,

structure, and behavior of the host institutions) in the developing country

which should be taken into consideration by the ASA analysts if these

methods are to exert an important influence on the policy decision making


We would also like to raise the following question: since sector

analysis experts are willing and seem interested in incorporating instru-

ments common to policy-decision making problems in their analysis, are

there not perhaps even more important though subtler issues that should

be considered in the design and use of ASA frameworks? Should some


consideration be given to formalizing some aspects of the policy formulation

implementation, feedback and control process into ASA frameworks? After

all, at the farm management level, farm plan formulation and implementation

types of issues are commonly considered by agricultural extension

economists. For example, we suggest the notion that it may be desirable,

in so far as possible, to actually include in a model some of the physical

activities of offices or agencies responsible for program implementation.

This may provide insights into administrative contradictions and incon-

sistencies, and in so doing, provide an additional degree of utility to

the policy-decision making authority.

There is an additional notion that we would like to suggest. The

difficulty of developing an analytical economic model which meets the

tests of explaining observed behavior and predicting future values of

endogenous variables is a difficult task. If we wish to include in our

empirical frameworks the instruments and other variables that are inherent

in the existing policy-decision making implementing apparatus (assuming

that we can't change it to fit our analytical methods) this is likely to

make it yet more difficult to construct models to meet traditionally or

classically established explanatory and predictive criteria.

While this criteria is desirable, its application to analytical

efforts of this type often results in a decision not to model some phenomenon

or to model it in a manner such that the variable it seeks to predict and

structure it seeks to capture are at a "resolution" or degree of aggregation

that is of little utility to a policy-decision makers. Its of little


utility because they are constrained to a given set of instrument whose

dimensions are critical to the implementing agencies of the ministry.

Another validation criterion can be suggested which has more intuitive

than analytical appeal. The criterion advanced in (11) is simply the answer

to the question, does the analytical tool help make "better" decisions

than the previous mix of methods used? "Better" decisions in the sense

that because of the use of the tool, the consequences of the policy

formulation-implementation activity produces results that are in closer

agreement with the targets or objectives for which the policy was

designed than would have otherwise been the case.



H. Klein is an Assistant Professor, School of Management, Temple

University, Philadelphia, Pennsylvania and T. Roe is an Associate Professor,

Department of Agricultural and Applied Economics, University of Minnesota,

St. Paul, Minnesota. Professors Klein and Roe were associated with a

USAID-University of Minnesota Project in Tunisia during the period 1972-74,

This research was funded by the Economic and Sector Planning Division of

the Development Support Bureau, USAID.



(1) Atkin, M. H. and G. E. Rossmiller, Sector Analysis and the General
System Simulation Approach to Agricultural Development Planning,
(paper presented at CENTO Workshop for Agricultural Planners,
Islamabad, Pakistan, 27 Nov. 4 Dec. 1972).

(2) Bassoco, L. M. and Norton, R, D., "A Quantitative Approach to
Agricultural Policy Planning," Annals of Economic and Social
Measurement, 4/4, 1975.

(3) Biggs, S. D., "A Review of Agricultural Sector Models," Agricultural
Development Council Interregional Seminar on Agricultural
Sector Analyses, Singapore, November 1976.

(4) Condox, A., Agriculture Sector Analysis in Tunisia (paper presented
at FAO/SIDA seminar on Agricultural Sector Analysis in the
Near East and Naib Africa, Cairo, 20-26 October 1975).

(5) Duloy, J. H. and Norton, R. D., "CHAC, A Programming Model of
Mexican Agriculture," Goreux and Manne eds., and Multi-Level
Planning Case Studies in Mexico, North-Holland, 1973.

(6) Duloy, J. H. and Norton, R. D., "Prices and Incomes in Linear
Programming Models," AJAE, Nov. 1975, p. 590-600.

(7) El-Sherbini, A.A., Agricultural Sector Analysis in Developing Countries:
Some Institutional Constraints (paper presented at the FAO/SIDA
Seminar on Agricultural Sector Analysis in the Near East.and
North Africa, Cairo, 20-26 October, 1975).

(8) Johnson, G. L., General, Systems, Simulation Models for Sector
Analysis (paper presented at a seminar on the Evaluation of the
Korean Agricultural Sector Simulation Model, Arlie House,
Arlie,~Virginia, 27-29, March 1974).

(9) Kornai, J., "Models and Policy: The Dialogue Between Model Builder and
Planner," in Blitzer, Clark and Taylor eds., Economy-Wide Models
and Development Planning, Oxford University Press, 1975.

(10) Rice, E. B. and E. Glaeser, "Agricultural Sector Studies, An Evaluation
of AID's Recent Experience," AID Evaluation Paper 5, USAID,
August 1972.

(11) Roe, T. L. and Draoui, H., The Tunisian Sector Analysis Model, Initial
Version, and Sector Analysis: Objectives and Constraints to
Framework Design, Bureau du Plan et due Developpement Agricole,
Tunis, Tunisia, 1973.


(12) Roe, Terry, Modeling of Nonlinear Functions into a Linear Programming
Format, Staff Paper, Department of Agricultural and Applied
Economics, University of Minnesota, St. Paul, 1975.

(13) Thorbecke, E., Sector Analysis and Models of Agriculture in Developing
Countries, Department of Economics, Cornell University, 1974.

(14) Vercueil, J., Integration of Agriculture Sector Analysis Models in
the Planning Process (paper presented at the FAO/SIDA Seminar
on Agriculture Sector Analysis in the Near East and North Africa,
Cairo, 20-26 October 1975).

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