Jeffrey, Scott R.

Quagrainie, Kwamena K.

Unterschultz, James R.

English

Research Papers in Economics

The Impact of Post-Farmgate Value-Adding on Western Canadian
Agriculture
K. K. Quagrainie
1, J. Unterschultz, and S. Jeffery
Paper presented at the Western Agricultural Economics Association Annual Meetings,
Vancouver, British Columbia, June 29-July 1, 2000.
Copyright 2000 by K. Quagrainie, Jim Unterschultz and Scott Jeffrey.  All rights reserved.
Readers may make verbatim copies of this document for non-commercial purposes by any
means, provided that this copyright notice appears on all such copies.
                                                       
1 Authors are respectively, graduate student and associate professors at the Department of Rural
Economy, University of Alberta, Edmonton, Alberta, Canada T6G 2H1. Email addresses are
respectively, kquagrai@ualberta.ca, jim.unterschultz@ualberta.ca, and scott.jeffrey@ualberta.ca.
The financial assistance of the Alberta Agricultural Research Institute is acknowledged.1
The Impact of Post-Farmgate Value-Adding on Western Canadian Agriculture
Introduction
Most of Canada’s grain/oilseed and livestock is produced in the Prairie provinces with
much of the grain destined for the export market. Domestic demand for agricultural and food
products is relatively stable. Thus, apart from influences from the weather and technological
factors, variations in farm prices and farm incomes are predominantly determined by situations
in the international market. Such situations have caused a renewed interest in the concept of
“post-harvest value adding” by the federal and provincial governments and the agriculture
industry. Consequently, substantial investment has been made in value-added initiatives in the
post-harvest sector.
Agricultural economists have expended much effort toward evaluating the economic
benefits from cost-reducing research in agriculture. Much of the work has been carried out using
a multi-stage production system in a partial-equilibrium framework. Studies have focused on the
distribution of economic benefits from government policy such as investment in research and
development (Dryburgh and Doyle 1995; Holloway 1991; Huang and Sexton 1996; Mullen et. al
1989; Voon and Edwards 1991;). Other studies have examined the benefits from investments in
commodity promotion and advertising (Cranfield et. al 1995; Kinnucan et. al 1996; Wohlgenant
1993). The literature provides important insights into the effects of different types of exogenous
factors on commodity prices and quantities as well as the welfare of particular groups in the food
production system. The effects of promotion and/or advertising are evaluated under the
assumption that promotion and/or advertising shift the retail demand curve and for research, the
effects are evaluated under the assumption that research shifts the farm input supply curves.
While this multi-stage approach is equally applicable to estimating the effects of value adding
investment, no attention has been given to it. This study extends the literature on distribution of
gains in a multi-stage production system to include gains/losses from investment in value adding
in the post-farm-gate sector.
This study is similar to the work of Martin and Alston (1994) who measure the impact of
a technological change that shifts the supply curve of farm commodities. This study is concerned
with the impact of investment in value adding that shifts the derived demand curve for farm
commodities. Five commodities are examined namely wheat, feed barley, canola, slaughter cattle2
and slaughter hogs. Functional equations representing the supply and demand for the
commodities are used to conduct simulation experiments involving increased demand for the
commodities. Results from the experiments provide insights into the effects of investment in
value adding on prices, quantities and farmers’ welfare.
The Model
The modelling procedure employed in the study lends itself directly to applications of full
general equilibrium models but attention focuses on only a few commodity sub-sectors.
Functional relationships are specified for the farm and processing sectors and are put together in
a partial equilibrium framework and used for simulating the effects of changes in domestic
demand for commodities.
The production functions for the farm commodities were derived from a Generalised
Leontief profit function. The supply functions are represented as:
5 ,..., 1 , & ) (
5
2
5 . 0
5 . 0
5 . 0 = „ + + = ￿
=
j i j i
w
w
w
w q
j i
j
ij ii
i
i
i a a
a
(1)
where qi is the quantity of commodity i supplied; and wi is the price. The subscripts i,j are
indexed 1=wheat, 2=canola, 3=slaughter cattle, 4=slaughter hogs and 5= feed barley. In equation
(1), the constant term aii, subsumes the effects of the fixed and quasi-fixed factors. Similarly, the
demand functions for the farm commodities were derived from a Translog profit function. The
demand functions are represented as:
4 ,..., 1 ) ln ln ( * = + + - =
P
= i w b p b b
q w
s i ii k i i
d
i i
i (2)
where si is the cost of the commodity to total profit; P is the processor profit; 
d
i q is the quantity
of the commodity demanded domestically; and pk is the price of the output k produced from
commodity i. It is assumed that feed barley is used mainly as livestock feed. Consequently, the
demand function for barley (i=5) is specified as a linear function of the price of slaughter cattle,
slaughter hogs and barley:
5 ,..., 3 0 5 = + = ￿ j w q j
j
ij
d s s (3)
where 
d q5  is the quantity of barley demanded and the ss are parameters.3
To complete the model some market closing identities (market equilibrium conditions)
and other price linkages need to be established. The commodity market closing identities are
represented as:
5 ,..., 1 = + ” i q q q
x
i
d
i i (4)
where
x
i q  is export of commodity i. For feed barley, 
x
i q is denoted by a parameter that accounts
for stocks. For wheat, canola, slaughter cattle and slaughter hogs, export supply functions are
specified as functions of own price, that is,
4 ,..., 1 1 0 = + = i w q i
x
i f f (5)
where the fs are parameters.
Other price linkage equations involve relationships between processor output price and
farm commodity price. These are specified as:
4 ,..., 1 , 1 0 = + = k i w p i k d d (6)
where the ds are parameters.
Simulation
The complete model consisted of 22 variables and 22 equations and the solution method
followed to solve the model was to treat the model as a collection of linear and non-linear
algebraic equations. The system of equations was then solved using GAMS (General Algebraic
Modelling System) and the CONOPT solver (Brooke et. al 1996). The process involved first,
solving the system of equations to obtain optimal solutions for the variables (base case). Then
shock experiments are conducted by increasing domestic demand of each commodity by 20%.
With each shock, the system is resolved to obtain new solutions for prices and quantities besides
the fixed levels. The changes in quantity, price and farmers’ welfare are calculated for each
solution. Data used are 1996 values obtained from Statistics Canada.
With the model specification as above, the values of the model parameters are determined
using elasticity estimates from Quagrainie (2000). Econometric estimates are used to calibrate
the export and price linkage relationships. One implication of this mode of calibration is that the
model cannot be statistically tested since the parameters are chosen in a deterministic way. In
addition, a fundamental assumption is that the market is in equilibrium in the base period.4
The system of equations derived and used in the present study involves more than one
commodity and for that matter, changes in more than one price. Consequently, producer welfare
is evaluated in this study using changes in producer profit. Producer profit (P
f ) is calculated as:
5 ,..., 1 , 2
5 . 0 5 . 0
5
1
5
1
5
1
5 . 0 = + = P ￿￿ ￿
= = =
j i w w w j i
i j
j i
i
i i
f a a (7)
All variables are defined as previously. The as identified in equation (1) are used to parameterise
equation (7).
Preliminary Results
The analyses of the effects of value-adding investment follow the nature of the set up of
the model. The base solution represents the initial market equilibrium conditions. Exogenous
shocks to the system affect the initial equilibrium causing imbalances in the market. The
variables then adjust to establish a new market equilibrium. From economic theory, it is assumed
that changes in the price variables trigger changes in quantity variables and/or vice versa. Thus
the model solution illustrates price and quantity response and cross-commodity substitutions
(Table 1). The changes that occur in the variables contain both direct and indirect effects of the
introduced shocks but it is difficult to distinguish between the two effects. However, it may be
assumed that the direct effects are relatively larger that the indirect effects. This ensures the
stability of the system.
Effects of a 20% Increase in Domestic Demand for Wheat
With an increase in domestic wheat demand, the price of wheat declined by 9.04% and
barley by 2.81% (Table 1). There is however an increase in canola price. With the decline in
prices, wheat and barley production experienced some decline in production. Canola production
declined as well. The decline in barley price did not result in an increase in domestic demand but
for canola, the increase in the price caused the domestic demand to fall by 4.19%. Canola export
increased by 60%, which probably explains the increase in canola price. Wheat exports also
increased by 10.78%. The changes in wheat and canola exports appear to be more pronounced
than the changes in production of the commodities. The effects on barley were quite minimal. In
terms of welfare, producer profits declined by 5.77%, which may be attributed to the unrealised
increase in farm prices particularly, the grains.5
Table 1 Effects of 20% Increase in Domestic Demand for Commodities
Percentage change (%) from base solution
Variable
Increase in
domestic demand
for wheat
increase in
domestic demand
for canola
increase in
domestic demand
for cattle
increase in
domestic demand
for hogs
Wheat production -4.09 -3.12 0.68 -1.80
Barley production -0.06 -0.02 -0.19 0.01
Canola production -3.59 21.06 -1.89 -1.04
Cattle production 0.00 -0.32 16.90 -0.11
Hog production -0.69 -11.11 4.86 2.78
Wheat price -9.04 -6.21 2.26 1.13
Barley price -2.81 -1.40 0.00 0.28
Canola price 2.73 5.45 1.36 0.91
Cattle price 0.00 -0.19 -1.14 0.09
Hog price 0.09 0.36 -0.18 0.18
Flour price -5.40 -3.71 1.18 0.51
Oil price 2.88 6.12 1.44 0.72
Meat price 0.00 0.00 -0.84 0.00
Wheat demand 19.99 21.69 -6.34 -2.61
Barley demand -0.12 -0.04 -0.40 0.01
Canola demand -4.19 20.11 -2.19 -1.24
Cattle demand 0.00 -0.11 20.00 -0.22
Hogs demand -9.52 -95.24 42.86 19.05
Wheat export 10.78 49.61 49.70 0.01
Cattle export 0.00 -5.88 -64.71 2.94
Hogs export 0.81 3.25 -1.63 0.00
Canola export 60.00 50.00 30.00 20.00
Producer profit -5.77 -1.42 5.09 4.72
Effects of a 20% Increase in Domestic Demand for Canola
From Table 1, a 20% increase in the domestic demand for canola caused an increase in
the price of canola by 5.45% but a decline in the price of wheat and barley. With an increase in
price, canola production increased by 21.06%. The production of wheat and barley declined
which may be attributed to the decline in price and to substitution effects in production with
canola. Exports of canola increased by 50%. The decline in wheat price however, caused an
increase in domestic demand for wheat by 21.69%. An increase in the domestic demand for
canola resulted in an increase in hog price but a decrease in cattle price. Nonetheless, the
production of both cattle and hogs decreased by 0.32 and 11.11 respectively. The domestic6
demand for the two commodities also declined and for exports, hogs exported increased by
3.25% while export of cattle decreased by 5.88%.
Effects of a 20% Increase in Domestic Demand for Cattle
Table 1 also reports the effects of a 20% increase in domestic demand for slaughter cattle
and hogs. With a 20% increase in domestic cattle demand, the price of cattle declines by 1.14%
instead of increasing. The price decline appears contrary to expectation nevertheless, there is an
increase in cattle production by 16.9% suggesting a positive net effect for the cattle industry.
Export of cattle decreased by 64.71%. The price of hogs fell by 0.18% but hog production
increased by 4.86%. However, the decrease in hog price resulted in an increase in the domestic
demand for hogs by 42.86%. Export of hogs decreased by 1.63%. Generally, changes in the
prices and production of the crops were modest but significant in the quantities exported. In
terms of producer welfare, total profits increased by 5.09%.
Effects of a 20% Increase in Domestic Demand for Hogs
Generally, a 20% increase in domestic demand for slaughter hogs resulted in price
increase for all the five commodities ranging from 0.09% to 1.13% (Table 1). The price rise did
not cause much change in commodity supply except in hog production. The production of hogs
increased by 2.78%. There was no change in hog exports. With a price increase, the domestic
demand for wheat, canola and cattle decreased. The quantity of canola and cattle exported
increased by 20 and 2.94% respectively. The effects on barley were minimal. In terms of
producer welfare, total profits increased by 4.72%, which may be attributed to the resulting
increases in commodity prices.
Summary
Research investment in value adding is assumed to enhance demand for primary
commodities through improvement in product quality and production of new and alternative
products causing an outward shift in the demand curve for farm commodities. The resulting
effects would include price and quantity responses as well as cross-commodity substitution in
production. Overall, the various simulation results indicate that increases in commodity prices
cannot be realised in the short term from increased domestic demand for commodities. Currently,7
commodity prices appear to be exogenously determined. Nonetheless, results suggest that, to
smaller extent, increased domestic demand for cattle and hogs may increase farmers’ welfare.
Value-added investment in the livestock and canola processing industries appears to provide
some short-term returns.8
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THE IMPACT OF POST-FARMGATE VALUE-ADDING ON WESTERN CANADIAN AGRICULTURE

THE IMPACT OF POST-FARMGATE VALUE-ADDING ON WESTERN CANADIAN AGRICULTURE

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