Cdn. J. of Agric. Economics I87 (March 1984) An Economic View of the Debate on Farm Size in Saskatchewan Ken Jensen* The continuing trend towards larger farms in Saskatchewan is of concern for several reasons. With a land-based agriculture, larger farms means fewer farms, which in turn means that fewer families are left in rural areas and fewer people are able to pursue a rural lifestyle. Rural depopulation has implications for the size and number of schools, hospitals, stores, implement dealerships and many other businesses and services. The availability and structure of these services are of direct concern to those people remaining in the rural areas and, as some of these services have a component of public funding. the change becomes a concern to society. A decrease in the number of farms also means that control of an important resource falls into fewer hands and the benefits from public programs designed to assist the farming sector go to fewer individuals - ones who often have higher incomes. If directing financial benefits, which accrue from programs such as research and freight rate assistance, to fewer individuals benefits society due to more efficient production, the attitude toward such programs will be different than if no efficiency gain is rea- lized. From 1961 to 1980 the population of Saskatchewan increased by about 5 percent while the farm population in Saskatchewan declined by.about 35 percent. During this same period, the number of farms in Saskatchewan declined from nearly 94,000 to just over 69,000, while the total land in farms increased from 64.4 million acres to 67.2 million acres. The total amount of improved farm land increased from 43.1 million acres in 1961 to 48.3 million acres in 1980. The average number of acres per farm increased from 686 acres in 1961 to 970 acres in 1980. There were 459 cultivated acres per farm in 1961 and 695 cultivated acres per farm in Saskatchewan in 1980, on average. Farms have also been growing in terms of gross revenue per farm. Furtan and Thompson show that in the decade from 1966 to 1976 the number of farms in Saskatchewan with gross sales over $35,000 measured in constant 1976 dollars grew from 10,475 farms in 1966 to 18,075 in 1976, while the number of farms with gross sales of less than $35,000 decreased from 74,955 in 1966 to 52,605 in 1976. In percentage terms only 12 percent of Saskatchewan farms had sales over $35,000 (constant 1976 dollars) in 1966 while 26 percent had sales over $35,000 in 1976. The same data show that the number of farms in all acreage categories of less than 1,120 acres declined from 1966 to 1976, while the number of farms in all acreage categories over 1,120 acres increased during the same ten years. The number of farms with less than 1,120 acres @Copyright 1984, Canadian Agricultural Economics and Farm Management Society 'Department of Agricultural Economics. University of Saskatchewan
Transcript
Cdn. J. of Agric. Economics I87
(March 1984)
An Economic View of the Debate on Farm Size in Saskatchewan
Ken Jensen* The continuing trend towards larger farms in Saskatchewan is of concern for several
reasons. With a land-based agriculture, larger farms means fewer farms, which in turn means that fewer families are left in rural areas and fewer people are able to pursue a rural lifestyle. Rural depopulation has implications for the size and number of schools, hospitals, stores, implement dealerships and many other businesses and services. The availability and structure of these services are of direct concern to those people remaining in the rural areas and, as some of these services have a component of public funding. the change becomes a concern to society.
A decrease in the number of farms also means that control of an important resource falls into fewer hands and the benefits from public programs designed to assist the farming sector go to fewer individuals - ones who often have higher incomes. If directing financial benefits, which accrue from programs such as research and freight rate assistance, to fewer individuals benefits society due to more efficient production, the attitude toward such programs will be different than if no efficiency gain is rea- lized.
From 1961 to 1980 the population of Saskatchewan increased by about 5 percent while the farm population in Saskatchewan declined by.about 35 percent. During this same period, the number of farms in Saskatchewan declined from nearly 94,000 to just over 69,000, while the total land in farms increased from 64.4 million acres to 67.2 million acres. The total amount of improved farm land increased from 43.1 million acres in 1961 to 48.3 million acres in 1980. The average number of acres per farm increased from 686 acres in 1961 to 970 acres in 1980. There were 459 cultivated acres per farm in 1961 and 695 cultivated acres per farm in Saskatchewan in 1980, on average.
Farms have also been growing in terms of gross revenue per farm. Furtan and Thompson show that in the decade from 1966 to 1976 the number of farms in Saskatchewan with gross sales over $35,000 measured in constant 1976 dollars grew from 10,475 farms in 1966 to 18,075 in 1976, while the number of farms with gross sales of less than $35,000 decreased from 74,955 in 1966 to 52,605 in 1976. In percentage terms only 12 percent of Saskatchewan farms had sales over $35,000 (constant 1976 dollars) in 1966 while 26 percent had sales over $35,000 in 1976. The same data show that the number of farms in all acreage categories of less than 1,120 acres declined from 1966 to 1976, while the number of farms in all acreage categories over 1,120 acres increased during the same ten years. The number of farms with less than 1,120 acres
@Copyright 1984, Canadian Agricultural Economics and Farm Management Society 'Department of Agricultural Economics. University of Saskatchewan
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declined from 71.390 in 1966 to 52,815 in 1976, while those with more than 1,120 acres increased from 14,040 in 1966 to 17,865 in 1976.
Economists tend to view firm size in terms of output per firm rather than by some physical size of input measurement. Farms which produce a variety of products can be aggregated for size measurement by expressing output in value terms. This type of measurement changes the relationship between farm size and farm numbers to some extent because output in dollar terms can be increased in ways other than by increasing the land base. However, the data suggest (Furtan and Thompson) that there is a strong correlation between farm size measured by gross revenue and by acreage in Saskatchewan. Thus, the growth in average farm size in Saskatchewan continues to be achieved mainly at the expense of farm numbers.
This paper examines the relationship between farm size and efficiency to determine if it is necessary to have fewer and larger farms in order to gain cost efficiency in primary agricultural production in Saskatchewan. In the light of the evidence presented it then goes on to evaluate some of the current agricultural policies that tend to provide benefits on the basis of size.
Theoretical Considerations As mentioned. the size of a farm firm can be measured by the quantity of some
input which is being employed, or i t may be measured by the quantity of output produced. In the land-based agriculture typical of Saskatchewan, i t is common to view the size of the firm in terms of the number of acres of land employed. This may be total acres controlled, improved, cultivated or seeded. When aggregating farms over a large area, this type of measurement presents a problem in that there is a large difference in productivity per acre of land, and thus an acre is not a homogeneous unit. Size may be viewed in terms of the assessed value of the farm land employed. While this may account for some of the soil productivity. differences, it still leaves problems of inter-regional climatic differences and differences in the levels of capital investment and labor employed.
Total investment in land, buildings and equipment is another possible measure of size on the input side. This method presents the problem of accurately valuing the inputs. Is this best done using market value, replacement value, or depreciated book value? Good estimates of these values are often very difficult to obtain. This method of measurement also has the problem that labor can substitute for capital in many types of farming. If this is not taken into account, then the measurement will not be accu- rate.
On the output side, farm size can be measured in terms of the physical volume of output or on the basis of the total value of output produced or sold. When farms producing different products are aggregated, then the total value of output from the farm can be used as a measure to accomplish the aggregation. This method’s greatest shortcoming is associated with inventory adjustment, but it is used in this study as a size measure because it best fits the data available and the nature of the study.
The average cost and economies associated with the size of the production unit can be thought of in terms of the short run or the long run. In the short run. some input factors remain constant and thus economies associated with the short run relate to fuller utilization of those fixed factors. Diseconomies in the short run come from over-utilization of the fixed factors.
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The long run can be defined as a time period sufficiently long to allow all of the input factors to be vaned. Economies associated with the long run thus relate to efficiencies associated with different plant sizes. When dealing with cross-sectional data, the long-run average cost curve is the locus of the minimum points of all possible short-run cost curves that represent all different possible firm sizes. The minimum point on this curve then represents the most eflicient size of firm in terms of producing at the lowest possible average cost or cost per unit of output. It is possible for a firm to produce at an average cost equal to that shown by the long-run average cost (LAC) curve if that firm is completely efficient. However, if the perfect knowledge assumption is dropped and management errors are made, then the firm will have a n average cost of production which is greater than that shown by the LAC curve. Thus, the actual average cost of production exhibited by firms might range from the minimum possible for a given size and upward from that minimum.
There are several methods which have been employed to measure economies of size and many of these have been employed in studies of agricultural production. Madden points out that n o single analytical procedure is best for all studies - the best method depends upon the situation being studied and the kinds of questions to be answered. Madden and Partenheimer divide the studies used to discover the nature of economies associated with farm size into three broad categories: analyses of synthetic firms; cross-sectional data from actual farms; and census data showing secular trends in size distribution of farms. They then point out that all of these methods have limitations in terms of interpreting the results to show either economies or diseconomies of size.
Synthetic firm analysis generally constructs a long-run average cost curve as a locus of a number of short-run average cost curves representing differently sized units. In doing this, pure competition is assumed and the problems associated with managing large units with heterogeneous and spatially dispersed resources are either ignored or assumed away. Hall and LeVeen state that this technique is not designed to explain actual farm data or to estimate all the possible advantages and disadvantages of size. It illustrates the relationship between production costs and size if all the assumptions are met; however, if the assumptions are not met the resulting curves will not be a realistic representation of the minimum cost curve.
Cross-sectional data from actual farm records tend to exhibit a considerable variation in average cost within size categories as well as over a range of sizes. This suggests that, while some firms may be producing on or near the theoretical minimum LAC curve for the industry, most firms are producing somewhat above the curve. This may happen because: several plant sizes are represented by a given level of production and thus have different degrees of plant utilization; there are variations in yields, resource and product prices which will give rise to different average costs; enterprise selections and mixes vary; and technological change coupled with the fixity of some assets leads to variations in average cost. Some of these cost differences are the result of management differences, though some are not under the control of individual manag- ers.
Seckler and Young indicate that these factors lead to a regression fallacy because small, inefficient farms exist and can continue to operate even at a loss because of off-farm income, past savings, and a base of operator-owned resources and unpaid labor. Large farms are unlikely to operate with the same inefficiencies because of the potential magnitude of the loss. Although attempts have been made to account for
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differences in management, when estimating LAC curves from cross-sectional data these measures are far from perfect and leave much of the variation unexplained. As a result, the large number of inefficient small farms causes the regression line to be unduly influenced upward even though the true frontier curve is much lower.
The third method of measuring economies associated with the size of firm is to examine the distribution of firms over time on the basis of size. This assumes that firm size will tend towards that which is most efficient. Seckler and Young convincingly argue that the fact that farm size has been increasing over time does not indicate the existence of economies associated with Larger firms, but rather it merely suggests that significant diseconomies do not exist. As long as the minimum average cost is such that the low-cost operators realize a pure profit, then there is an incentive to expand to increase total profit. Therefore. it does not necessarily follow that if the trend is to larger farms then there are cost economies associated with larger units. All that is necessary is that significant diseconomies do not exist for the larger units.
Evidence of Constant Costs Related to Size for Saskatchewan Farms
A long-run average cost curve estimated with ordinary least squares is an average of the observed firms rather than a frontier curve. Although attempts can be made to shift the curve to the frontier, i t is rare that more than a small amount of the variation is accounted for using cross-sectional data. It is possible that a frontier curve could yield different conclusions about the cost structure than would the estimated curve using ordinary Least squares.
Recent studies (Fleming and Uhm; Sorboe) use linear regression to show that larger farms in Saskatchewan produce at a lower average cost than smaller farms. However, Sorboe found no significant relationship between the size (as measured by the number of improved acres) of farms with high soil-productivity and the average cost of production. For low soil-productivity farms, a significant relationship existed between the sue measurement and average cost, but the relationship was not consistent from year to year, and overall only a small percentage of the cost variations 'among farms was explained. This would indicate that factors other than farm size are most important in determining average cost.
Fleming and Uhm use Canfarm data to show a significant relationship between farm size, as measured by the weight of grain produced, and the average cost of production. However, upon examining the regression line shown in their study, it appears that most of the economies associated with larger size are realized by the time a very modest size is reached (250 tonnes of output), and the regression line is approaching a horizontal line by the time an average size of Saskatchewan farm is reached. It seems very likely that in this case, as in the cases discussed by Seckler and Young. some small farms have an average cost somewhat below the regressed long-run average cost curve and that the curve is unduly influenced by some inefficient small farms.
In the examination of two separate sets of cross-sectional data for Saskatchewan farms, this regression fallacy can be readily observed. The first data set used in this research came from the Agricultural Enumerative Survey of Saskatchewan in 1978. The data refer to the 1977 calendar year. Statistics Canada developed a probability sample which included some 4,100 Saskatchewan farms. However, due to problems of
19 I
missing data plus observations that had to be deleted because of confidentially or errors in measurement, the sample was reduced to 1,964 farms. These farms were divided into groupings for analysis: those which produce only grain, and those which produce both grain and livestock.
The average cost of production was computed as the ratio of total cost to the total revenue for each firm in the sample. The total cost was the sum of variable cost plus a fixed component for machinery and livestock investment. The variable costs included commercial fertilizer, chemicals, custom work, fuel and oil, repairs and maintenance on machines and buildings, feed supplements, veterinary services, and baler twine. Labor cost was calculated as the number of hours worked on the farm reported by operator, spouse, family and hired labor, evaluated at $4.00 per hour. Machinery investment cost was evaluated at 13 percent of reported capital stock value, while livestock was evaluated at 10 percent of stock value. The costs missing from the data were land taxes and seed purchases. No return to land was included, so land was the residual claim- ant.
T h e total revenue figure was the total value of agricultural products sold from the farm operation together with receipts from custom work and the rental of farm machinery and equipment. To this revenue, the value of livestock (cattle and pigs) slaughtered for home consumption was added.
The questionnaire asked for the number of years of schooling obtained by the operator and his or her spouse. The management variable was taken to be the interactive value of these education levels. Some researchers (Welch) have used weighted years of schooling, while others (Patrick and Kehrberg) have simply used the number of years of schooling. There is no clear consensus on which is the better assumption. The years of schooling was chosen as the management variable.
The second data set came from a household enumerative survey conducted by the Department of Agricultural Economics, University of Saskatchewan, in the summer of 1981. The data collected cover the 1980 calendar year.
T h e study was conducted in Crop Districts Five and Seven of Saskatchewan. Crop District Seven is on the western border of Saskatchewan, in a highly productive grain-producing region, while Crop District Five is on the eastern border, in a highly productive mixed farming region. Crop District Seven is part of the prairie region, with predominantly dark brown soils, while Crop District Five is park land with black soils and higher rainfall.
Within each crop district, three hundred farms were selected at random from a list provided by the Western Grain Stabilization Office in Winnipeg. After adjustments were made for missing and incomplete data, 5 19 farms were left in the set which was analyzed.
The average cost was calculated as a ratio of the total cost to the total revenue; however, with this data set it was possible to include investment in land and buildings as a cost. This was calculated as 3 percent of the market value of all land and buildings in the operation. This data set included the number of years of experience as a farm operator and this was included in the model as a variable; however, the number of years of experience proved to be insignificant in determining efficiency. The amount
I This may. on the surface, appear to imply that there is no "learning by doing" in farming. However, a more in-depth analysis would be required to suppofi such a conclusion.
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of wealth brought into the operation as a gift o r inheritance was also included, but proved to be insignificant in terms of its influence on efficiency.
The last variable used in the second analysis was a dummy variable used to separate the two crop districts. District Seven farms proved to have a significantly lower average cost of production than District Five farms.
Implications of the Cost Curve Estimates The cost curves were estimated from the data1 and the results are reported in Table
I . The specification of the estimated equations is:
( 1 ) Ct = PO + Pi41 + P 2 4 + P3mf I + P5qtmt + Pbat + Ei where C, = average cost per unit of revenue for firm i : q, = total revenue of firm i, in
dollars per year; rn, = the number of years of schooling for the operator times the number of years o f schooling for the operator's spouse, for firm i
The variable (I, is a dummy variable separating the western area from the eastern area for the second data set. If the farm is in the western area, then the dummy variable takes on a value of one, and if the farm is in the eastern district, then the value of u, is zero. This variable does not apply to data set number one.
The hypothesis from economic theory is that there is a negative relationship between size and the average cost of production. By introducing a second-power variable, the hypothesis is that the relationship between average cost and size changes as size increases. If the coefficient on the first-power term (4 , ) is negative (PI < 0). then the average cost declines with increased farm size, but if the coefficient on the second-power term (4:) is positive (J2 > 0), then eventually the relationship levels off and turns up, This functional form describes a parabola which opens upward. The same relationship applies for the management variable (m,). If the coefficient p, < 0 and the coefficient p4 > 0. then the average cost is lower, with higher levels of education for the operator and spouse but with diminishing returns.
The interaction term between size and education hypothesizes that large farms benefit differently from increased management capacity than d o smaller farms. If the coefficient is negative (J3, < 0), the larger farms receive a greater efficiency benefit from more education than d o small farms.
The signs of the estimated parameters support the hypothesis that the average cost curve first declines as farm size increases and then eventually flattens out and turns upward (Le., f l , < 0 and p2 > 0). The estimates for the parameters for management (i.e., ,L?, and p,,) also have the signs hypothesized from the theory. These estimates suggest that, the more education obtained by the operator and spouse, the more efficient the farm operation will be. The insignificance of the /I4 parameter indicates that there are no diminishing returns to education: i.e.. increased education will reduce cost of production without diminishing returns. In this case, the data partly support the hypothesis put forth.
The insignificance of the parameter ps would cause a rejection of the hypothesis that there is a n interactive effect between the size of farms and the level of education.
2 For a discussion of the use of cross-sectional data to estimate long-nrn cost curves see Intriligstor, p. 281. and Kmenta. pp. 451-52.
Tab
le 1
: Est
imat
ed C
ost
Cur
ves
Dat
a S
et 1
D
ata
Set
1
Dat
a S
et 2
Gra
in fm S
td.
Eev
iati
rn
Pro
b >
t G
rain
Liv
esto
ck Farrm
Std
. E
svia
tion
P
rcb
>t
All
Far
m
Std
. &
via
tio
n
Pn
A >t
8, 1.439919
0.094848
0.0001
1.902515
0.072143
. 0001
2.78
.ox
.0001
(15.18)
(26.371)
(7.65)
B1
-0.007995
0.000945
0.0001
-0.01397
(8.45)
(14.85)
B2
0.0000108
0.0000013
0.0001
0.000015
(8.099)
(14.861
B3
-0.00315
0.00138
0.0235
-0.00363
(2.26)
(3.21)
0.00094
.OOO
l -0.0000092
0.00000215
.0001
(4.29)
0.000001
.0001
8.22(10-12)
0.000000
(4.88)
0001
0.00112
.0013
-0.0741
0.0304
.0151
(2.44)
B4
0.00000873
0.00000498
0.0799
0.0000031
0.0000046
.4949
0.001127
.000699
.107
7 (1.75)
(0.68)
(1.61)
B5
0.0000044
0.0000065
0.5015
0.0000339
0.0000065
.0001
1.16(10-’)
.000
0000
8 .1649
(0.672)
(5.18)
(1.39)
-0.242
.054
.OOOl
(4.45)
F 45.23
137.59
17.62
R2
0.25
0.35
0.28
n 70 1
1263
519
Not
e: r
-val
ues a
re s
how
n in
par
enth
eses
.
c
W
W
I94
In other words, large farms would not get a larger reduction in cost per unit from management than would small farms. This may result from small farms requiring superior management in order to obtain the same average cost of production as larger farms.
The results are quite consistent for both grain-only farms and for mixed farms. They are also consistent with the two separate data sets collected for different years and with different surveys. It is also important to note that, although larger farms have a lower average cost of production and although a higher level of education for the operator and spouse leads to a lower average cost of production, these factors only account for a small percentage of the overall variation in average costs.
An examination of the average cost plotted against the size of the firm reveals that with ordinary least squares a regression fallacy may exist (Figures I , 2, and 3). This regression result indicates that as farm size increases, up to some point, the average cost of output decreases. As stated earlier, this appears to be true on average. However, a LAC curve is a frontier curve. Visual observation of the scatter of individual farms’ average costs plotted against size indicates that the true frontier LAC curve is flat. The regression fallacy results because many small farms are inefficient. However, it appears to be technically possible for small farms to produce as efficiently as larger farms. The regression result then. by itself, may lead to erronous conclusions.
There are two important implications that can be drawn from Figures I , 2 and 3. First. there is more efficiency variation between farms in the small farm size categories than between farms in the large size categories. Second, the average cost frontier is such that constant returns to size are the norm in the industry - not decreasing or increasing returns to size, as suggested by the regression results. Both of these observations are discussed below in terms of their implications for the farm size de- bate.
The large variation in cost per unit of small farms is in part due to the entry to the industry of some firms. New firms may be incurring costs but have not as yet realized returns from the expenditures. Some small farms may be inefficient because of off-farm work, Farmers who are employed part-time off the farm may have a higher opportunity cost for their labor than farmers on the same size of operation who are not employed off the farm..For this reason, the input of labor into the farm may be less than optimal from a farming point of view but optimal across the farm/non-farm allo- cation.
The most interesting observation gained from examining the scatter of average cost (Figures I, 2 and 3) measured against size is that constant returns to size appear to exist at the least-cost frontier. It is evident that small farms can be as efficient as large farms, even though a large percentage of small farms are inefficient. This suggests that farms grow in size to gain higher incomes rather than to gain efficiency.
From the data available it was not possible to trace the development of farms over time, but it seems likely that those small farms which are able to expand are the ones which are efficient as small farms. In this way many of those farms would take the low-cost management ability with them to the larger size rather than gaining the low-cost production because of the larger size.
If farmers increase their firm size to achieve higher incomes but with no resulting efficiency gain, then the agricultural policies that governments might consider are quite different. Distribution of incomes within the farming sector, and particularly the
distribution of income transfers from the non-farming to the farming sector that results from government policies, is of great concern if the efficiency gain for consumers is not relevant.
The types of policies which should be examined in light of the absence of any strong evidence for decreasing average costs with larger size are those which allocate benefits on the basis of size of input or output. The “Crow” freight rate subsidy is certainly one which fits into this category. The payment of benefits is based upon the amount of grain shipped under that rate structure. Publicly funded irrigation projects, where the user of the system pays less than the full cost of providing the service, is another example of benefit according to amount used. The grain delivery quota system for the Wheat Board area of western Canada, which allocates access to scarce handling and transportation systems on the basis of the number of acres operated, provides another example which can be examined.
These and other policies are brought into question with constant returns to size. Some policy options which could influence farm size and distribute policy benefits more widely are examined in the next section.
Policy Directions for Influencing Farm Size Governments could consider removing policies which favor larger units; restructur-
ing such policies so they became neutral in terms of their affect on size: or. restructuring these policies to favor growth only to some limited size in order to restrict the amount of income transfer or benefit which can go to any one individual. These approaches are based on the notion that when redistribution of income results from a government policy, then the redistribution should be aimed at individuals rather than at the resource base or business size.
One indirect method which could be used to influence the size of grain enterprises is through the delivery quota system. The Canadian Wheat Board, through the use of grain quotas, limits the access of each producer to grain markets outside of the local area. This system has been generally well accepted amongst Saskatchewan producers. The system could be modified so the first hundred acres per producer under grain production could receive a higher quota than the next hundred, and each additional hundred-acre lot under the control of one producer receives smaller and smaller quota allocations. This method of quota allocation would give small producers a guaranteed market even when delivery quotas are low, and would give the small producer quicker access to the marketing system at all times. This suggestion recognizes that individual families have a requirement for family income which is independent of the size of the land resource controlled. It also moves towards allocating access to a marketing system which has a component of public funding’ on an individual basis, rather than on the basis of the amount of land controlled. Assuming farmers are risk-averse, this would discourage the growth of farm size and not affect overall efficiency.
The “Crow” freight rate subsidy currently applies equally on a per-tonne-shipped basis for those products falling under the rate structure, regardless of the amount any one producer ships. Obviously, the larger the producer, the larger the quantity of the subsidy which is captured by that individual. A freight rate subsidy could be
3 For example. the public funding or railroad cons!ruc!ion, seaway investment and operation. government grain terminals. the Canadian Grain Commission, etc.
I99
constructed so that it would apply only up to a certain volume shipped by any one producer. Beyond that amount the producer would be required to pay a larger share of the freight costs. A sliding scale could be developed so that beyond some size the large producer would pay the full cost of shipping the product. This would limit the absolute amount of subsidy that any one individual could receive, as well as discourage expansion beyond a predetermined size. The same type of subsidy limits could be applied to other existing publicly funded inputs, such as irrigation system^.^
The government could also use indirect market intervention, such as a progressive land tax. In this case, larger operators would pay progressively higher rates of land tax. This scheme would be similar to the manner in which income taxes are currently calculated. This system would work as a disincentive to growth because i t would add to the cost structure of the larger farms.
Much of the growth in farm size has been due to the development of large machinery. T o some extent, small producers are at a disadvantage because appropriately sized technology packages are not being produced. This appears to be an institutional problem more than a technological problem. It is possible that research and development programs could reverse this trend by placing more emphasis on technologies which favor small farms. Such a change in emphasis could slow the trend toward farm expansion.
A number of policy options are possible for governments, should they decide to directly control farm size. The most direst method would be to use legislative power to restrict farm size on the basis of the total amount of some input one producer could employ or the total amount of output which could be produced. The most obvious way to directly restrict farm size in Saskatchewan would be to limit the quantity of land that one operator could control. This type of legislation has been discussed for many years and remains very controversial. Beyond the acceptability of this type of legislation lies the problem of how to decide what the acreage limit should be, as acreage needed to support an acceptable living standard varies between soil types, climatic regions and individuals. Assessed value or market value of the resource employed are size measurement methods which could be used to overcome the resource quality differences. The control of the quantity of output produced is already used by some marketing boards and commissions. This can be done through licensing an individual to produce and market a specified quantity of product. This method appears to have some problems when the basic resource used in production cannot be created, as is the case with land.
Con c 1 us i o n The arguments that farms have grown in size because of increasing returns to size in
agriculture appears to be questionable. While it appears to be true that, on average, larger farms are more efficient, the information in this paper supports the notion that, at the frontier, constant returns to size are the norm in Saskatchewan agriculture. This means that farms increase in size to increase income rather than to increase economic efficiency. In this light, subsidy or income transfer policies that pay a benefit to one
4 Some attempt has been made to encourage small farmers in this way through fuel rebates and tax rebates. but the size of the benefit has not been great enough to have much effect. The current government in Saskatchewan has introduced an interest rate subsidy program to lower the start-up costs in an attempt 10 stabilize farm numbers.
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individual based on the size of business that the individual is operating are brought into question. Perhaps these policies should be designed to encourage growth up to a size that could provide an acceptable level of income but would not continue to encourage growth and pay benefits to the same individual beyond that size.
Governments have many market options opcn if they wish to control the growth in farm size. It appears that some combination of a quota constraint on output, a restructuring of current subsidies, and a progressive land tax would discourage farm growth through expansion of the land base and encourage farms to intensify in order to maintain or increase income levels. Research and development programs could be made to emphasize technologies for small farms and affect the trend in the longer term.
The public debate on farm size may well change the structure of farms in Saskatchewan. As this debate progresses, it is important that the participants in the debate have a basic understanding of the production opportunities and cost structure of primary agriculture. Finally, each policy that has a direct or indirect effect on farm size, whether extant or proposed, should be thoroughly evaluated in terms of its impact on economic efficiency and income distribution.
Funan. W. H.. and Thompson. S. J. “Farm Size and Agricultural Credit Requirements to IYY0.” Paper
Hall. B. F.. and LeVeen. E. P. “Farm Size and Economic EfIiciency: The Case of Calirornia.” American Journal
Intriligator. M. D. Economerric Models. Techniques and Applications. Englewood Cliffs. N.J.: Prenlice Hall,
Kmenta. J. Elemenls of Economefrics. New York. N.Y.: Macmillan. IY71
Madden, J. P. Economics of Sire in Farming. Economic Research Service Agricultural Report no. 107. Washington. D.C.: U.S. Department of Agriculture, 1967.
Madden, J. P.. and Partenheimer, Earl J. “Evidence of Economies and Diseconomies of Farm Site.” In Size. Slrucrure and the Future DjForms. pp. 91-107. Edited by A. Gordon Ball and Earl 0. Heady. Ames. Iowa: Iowa State University Press. 1972.
Patrick, G. F.. and Kehrberg, E. W. “Costs and Returns of Education in Five Agricultural Areas of Eastern Brazil.” American Journal of Agriculfurol Economics 55 (1973): 145-54.
