5.1 PROCESSES: SYSTEMS OF ORDER LEVELS 1 AND 2
5.2 INTERRELATEDNESS OF SYSTEM COMPONENTS: STRUCTURAL COEFFICIENTS
5.3 THE FARM SERVICE MATRIX: A SYSTEM OF ORDER LEVEL 9
5.4 DETERMINATION OF CAPITAL FIXED COSTS
5.5 DEPRECIATION METHODS
5.6 REFERENCES
'So soon as the time for ploughing is arrived, then make haste ... and bestir yourself early in the morning.'Hessiod, c. 8-th Century B.C.
This chapter continues the discussion of the elements of the farm-household system as listed in Sections 1.4 and 5.
5.1.1 Definition and nature of processes
5.1.2 Number of relevant processes
5.1.3 Analytical problems presented by processes
Structurally, the main building blocks of a whole-farm system are its enterprises; these provide its income in cash or kind. Enterprises may stand alone or be supported by resource-providing activities. The building blocks of both enterprises and their enabling activities are agro-technical processes.
A process is the specific way in which a production operation is done, together with the levels or amounts of resources used in doing it. A process specifies or implies the use of some operational technology, the types and levels of resources used in its operation, and the types and levels of its resultant outputs.1 Processes present two general analytical or management problems: (a) to select the 'best' or most appropriate technology, and (b) to operate the selected technology at its optimal level in terms of inputs and outputs.
1 According to the general definition of a system in Chapter 1, a process is itself a system. Its components are its technology, its inputs and its outputs. Interaction exists in the relationships among these inputs and outputs. The (management) objective relative to a process system is to operate it (i) at a level which is optimal for the enterprise to which it contributes and (ii) in such fashion as to achieve maximum efficiency in resource use, i.e., maximum output for a given input, or minimum input for a given output. The boundaries of a process are defined by the specification of the process itself and, at least conceptually, a given process system can usually be disaggregated into successively smaller subsystems.
Before looking further at these problems it will be useful to consider some examples. Table 5.1 presents a typical activity budget for maize production. While Table 5.1 (and similar activity or enterprise tables such as Table 4.1) would be adequate as the basis for financial evaluation of this activity, it is nonetheless a highly generalized statement: it offers little or no structural information about any of the seven operations which comprise the activity, e.g., no information is given regarding how the field was ploughed (mule, bullock or tractor?), the number of times it was ploughed or the degree of tilth aimed at. Or considering operation (2), planting, no information is offered regarding the several variations possible in this operation which could affect crop yield, e.g., depth of seed placement, in-row and between-row plant spacing, seasonality of planting, the moisture level of the field at planting time etc. Nor is any agro-technical information offered regarding any of the other operations beyond the bare fact that they were done and the inputs which were used in doing them.
TABLE 5.1 - Budget of a Maize-growing Activity
|
Inputs per acre |
||||
|
Operation |
Materials |
Labour |
Oxen |
Costs/returns |
|
(days) |
(days) |
(Rs) |
||
|
1. Ploughing |
|
5 |
4 |
200 |
|
2. Planting |
seed: 7 kg |
1 |
|
240 |
|
3. Irrigating |
water: 1 ac ft |
1 |
|
50 |
|
4. Fertilizing |
fert: 40 kg N |
1 |
|
200 |
|
5. Weeding |
|
3 |
|
30 |
|
6. Harvesting |
sacks: 50 |
6 |
|
280 |
|
7. Drying |
wood: 2 m |
3 |
|
400 |
|
Total inputs and costs |
|
20 |
4 |
1 400 |
|
Outputs per acre |
||||
|
Item |
grain: 1 t |
|
|
3 000 |
The seven operations shown in Table 5.1 represent seven operational subsystems, one each relating to ploughing, planting, irrigating etc. However, due to the absence of data, it is not possible to judge whether or not these subsystems consist of the best of all possible technologies to use in each operation, nor whether each one is operated at maximum efficiency. Seven kilograms of seed are specified but would it be better to use six or nine kilograms? Forty kilograms of fertilizer are budgeted but might this better be 60 or 80 kilograms? In short, Table 5.1 tells nothing about the optimality of resource use. Clearly, if interest is in ascertaining whether there are better ways of performing these separate operations and whether the resources to be used in them are being used to their maximum efficiency, these operations have to be examined in greater detail.
The operations of Table 5.1 are listed again in Figure 5.1. This also shows, for each operation, the alternative technologies that might be employed in performing it and a range of input intensity levels at which each technology might be implemented. For example, the 'ploughing' operation could be done by tractor, by oxen or by spade; and whichever ploughing technology is chosen could be applied one, two, three or four times: further, whichever of these possible combinations is used, it could be applied to cultivate to a depth of 7, 14 or 21 centimetres. Alternative possible technologies and alternative possible technology intensities or input levels are also shown for the other of the seven production operations.
Each specific technology (i.e., the way or means by which an operation is performed), operating with the application of one or more different kinds of (variable-level) inputs, is a process. The technology operates either as a single-variable input process or, if it is used with two, three, four ... different kinds of inputs, as a multi-variable input process. In Figure 5.1, three possible technologies are shown for the planting operation: using two-row or four-row machines or doing this operation by hand. Whichever of these planting technologies is chosen by the farmer, it can be used with a variable amount or intensity level of seed (20-, 30- or 40-thousand seeds per acre). Each of the three planting technologies is thus a single-variable input process where the variable input is seed used in conjunction with a fixed input consisting of either a two-row, four-row or hand planter.
FIGURE 5.1 - Example of Alternative Technologies in Maize Production (per Acre Basis)
On the other hand, the operation 'ploughing' is a two-variable input process: each of the three possible ploughing technologies (doing this operation by tractor or by oxen or by hand) can be done or combined with some variable range of the two 'inputs' shown - depth to which the field can be ploughed and number of times it can be ploughed. Thus there are a total of three by three by three, or 27, combinations of ploughing technology by depth by frequency which could be applied to this operation. Each of these 27 combinations could at least potentially result in a different crop yield as illustrated relative to number and depth of ploughings by the graphs in the lower half of Figure 5.2. For analytical purposes, such processes are usually described and quantified in mathematical terms as response functions or production functions which relate the output of a crop, livestock activity etc. to the inputs used in producing it (Dillon and Hardaker 1993, Ch. 7). For a single-variable input process, they are specified by the general functional form Y = f(S) which states that, e.g., crop yield per ha (denoted by Y) is some function of the amount of seed used per ha (denoted by 5); or more realistically as a multi-variable input process, Y = f(S, C) which states that yield is significantly determined by both the amount of seed and the number of times the field is cultivated (denoted by C); or more realistically still, Y = f(S, C, N, P) where the effects of nitrogen fertilizer (N) and phosphate fertilizer (P) are also considered.
Figure 5.2 illustrates the concept of production functions. In the top figure, crop yield per ha (for some particular set of climatic, soil and husbandry conditions) is graphed as a function of the single input-variable seeding rate over the range from 10 000 to 50 000 seeds per ha. This depicts the response or production function Y = f(S). In the lower figure, crop yield per ha (again for some particular set of climatic, soil and husbandry conditions - including seeding rate but excluding ploughing frequency and depth) is shown as a function of the two variable inputs depth (7, 14 or 21 cm) and number of ploughings (1, 2, 3, 4 or 5). This depicts the production function Y = f(D, K) by the set of three single-variable input-output graphs Y = f(K/D) (for D respectively equal to 7, 14 or 21) where D and K respectively denote depth and number of ploughings and the symbolism K/D indicates that K is variable while D is fixed at some specified level (Dillon and Anderson 1990, Ch. 2).
The number of separate operations in an activity can be large (seven in the above example of Figure 5.1). The number of processes in an operation can also be large; e.g., in Figure 5.1 three technologies are shown for the irrigation operation (the alternatives of splash, furrow or sprinkler application), each of these operating over some intensity range (days' interval between water applications). One could, if it were appropriate, list many more factors relating to irrigation which would have an effect on crop yield, i.e., other dimensions in which irrigation could operate such as the amount of water applied at each irrigation, the quality/salinity of water used, the time of day at which irrigating is done etc.
However, such an examination of an operation in greater-and-greater detail by defining more-and-more dimensions in which it exists, if done for all operations in all farming environments, would be not far short of defining the total scope of all agricultural science. (Thus relative to the operations listed in Figure 5.1, 'planting' would encompass the realm of agronomists; 'harvesting' and 'drying' that of engineers; etc.) From the very large number of physical processes which do exist, farm management is concerned with selecting and analysing only that relatively small number which are of practical economic significance; or, in terms of the example of Figure 5.1, only those processes which have or are thought to have a significant (economic) impact on crop yield. Just which of these processes are 'significant' and thus to be subjected to economic analysis via response analysis, as outlined in Chapter 8, will depend on analytical circumstances. As a practical guide, farm management analysis would be confined to processes which have a relatively large effect on output or which are expensive or which require large inputs of scarce resources. In short, in such activities as those shown in Table 5.1 and Figure 5.1, there might be only two or three processes of sufficient importance to warrant full economic analysis. (But whether such analysis is in fact to be done at all will depend on the Field and Mode of the farm management analysis as discussed in Section 2.1.)
FIGURE 5.2 - Graphical Examples of Single-variable Input and Two-variable Input Production Functions
Types of processes
In agricultural production there are three broad types of processes:
(i) Biological processes are those in which the stimulus or input operates directly on the biological system of an animal or plant. Irrigation water applied to a crop root zone, feed digested by a dairy cow are examples. The great majority of economically relevant agricultural processes are of this type.(ii) Bio-mechanical processes are those in which the stimulus or input operates indirectly on a plant or animal, its direct or immediate effect being on the physical micro-environment in which the plant or animal exists. An example is the number of times a field is tilled. This will affect subsequent plant growth/yield, but will operate indirectly through changing the physical/mechanical conditions in which plant growth occurs - e.g., through changes to clod size, particle cohesiveness, water infiltration and soil moisture storage capacity etc. At a practical farming level these bio-mechanical processes are usually not distinguished from direct biological processes.
(iii) Mechanical processes do not exist as part of a plant/animal biological system, but act as physical/mechanical support to such systems. Some of them can be operated at varying intensity levels, such as the delivery of feed to a herd of cows by a conveyor belt driven at varying speed. Here there might be some non-linear relationship between, say, fuel consumption and amount of feed conveyed by the belt, and the relationship would appear as in Figure 5.3 B. In consequence, determination of optimal belt speed would be economically relevant. Many types of mechanically powered equipment - tractors, trucks, stationary motors - have such an optimal operating rate. But with others the relationship between fuel input/speed and work output is linear over some specified range (Part C of Figure 5.3); if the machine is operated beyond this range, it might simply disintegrate.
The discussion of response analysis of processes in Chapter 8 is limited to biological processes.
Shape of input-output process relationships
Figure 5.3 illustrates some differently shaped production functions for the case of a single-variable input production process. Each graph shows the physical input-output relationship or total physical product curve as the level of the single variable input is increased with all other input factors held constant. Note that, in graphs A and B, the law of diminishing returns (sometimes called the law of variable proportions) prevails - beyond some point, as the level of the variable input increases with no change in the level of other input factors, increases in output occur at a diminishing rate (the marginal product is decreasing) and eventually, beyond the point of maximum output, output declines in absolute terms (the marginal product becomes negative).
In graph A of Figure 5.3, which is the classical depiction of a production function, all three theoretical stages of production are to be seen as the level of the variable input increases: first, an initial stage of increasing returns with output increasing at an increasing rate - maximum efficiency would never be achieved by operating the process in this stage since the marginal product is increasing; second, a middle stage of decreasing returns with output increasing at a decreasing rate (i.e., marginal product is positive but declining); and, third, beyond some maximum level of output, a final stage where output declines (i.e., marginal product is negative). Graph B is more realistic in showing only the second and third stages since increasing returns are not found in practice. Graph C depicts a process in which output increases at a constant rate (i.e., linearly) up to some maximum level and then remains constant (at least within the input range covered by the graph - it must be expected eventually to decline). While graphs A and B are non-linear, graph C is of (segmented) linear form. Note also that as depicted in all three graphs, output is zero when none of the variable input is used. This indicates that the variable input under consideration is essential to production (as, e.g., seed in crop production). Often, however, some output may still be obtained when none of the variable input is used. In this case the input is to some extent optional (as, e.g., chemical fertilizer in crop production).
FIGURE 5.3 - Stylized Production Functions or Input-Output Relationships for a Single Variable Input
The reasons why the use of some kinds of inputs beyond a certain level causes a decline in output will be intuitively obvious. As more and more water is added to a crop, keeping all other inputs constant (especially drainage capacity), the field will eventually become waterlogged and yield will decline; or as a crop is weeded with greater and greater frequency (i.e., weeding labour inputs are increased), the point will be reached where workers will cause more damage in trampling the crop than benefit. Or again, as in curve C of Figure 5.3, offering more feed to a cow than she can consume might not cause actual milk output to decline, but beyond a certain level feed will be uneaten and go to waste (and the value of output will decline relative to the increasing cost of inputs).
As noted, processes present two problems in farm systems analysis: (a) selection of the 'best' technology or method of performing an operation, and (b) determination of the optimal level of intensity at which the process should be operated.
· Technology: Usually, selection of the 'best' process is not difficult on small farms; it is often determined by the socioeconomic environment. Selection of a two-row or four-row mechanical grain planter might present a real management problem in South Dakota, but there would be no such alternative possibilities among the hill farmers of Nepal where all field operations are done by hand. Where a farmer does face a management choice in technology selection, decisions can be made by budgeting out the costs and returns of the alternatives (partial budgeting, Section 4.5).· Optimization of input or intensity levels: The second problem of operating the 'best' process at the 'best' level can be a little more complicated. If the choice is between two, three, four ... discrete alternatives, this also can be made on the basis of comparative partial budgets. If the process is of such economic significance as to warrant more precision and if it relates to a continuous type of input, then it might require the more sophisticated methods of response analysis (Chapter 8).
5.2.1 Interrelatedness within an activity: internal structural coefficients
5.2.2 Structural coefficients as critical parameters
5.2.3 Interrelatedness among activities: external structural coefficients
The next element of a system to be examined is its structural coefficients. From the system definition of Section 1.1, a necessary property of any system is the existence of interrelatedness among its components. In farm-household systems this takes the form of structural coefficients of two kinds. Internal structural coefficients exist and operate within individual production activities or other subsystems and define explicitly or implicitly the interrelatedness which exists between/among their several sub-components. External structural coefficients are also often relevant for a given system, such as a production activity/enterprise, but their function here is to quantify relatedness between the given system or subsystem and other related systems or subsystems.
Internal structural coefficients are those which 'tie together' or link the various components of a (crop, livestock or whole-farm) system. They are an especially important characteristic of those farm production activities which generate part of their own resources, e.g., mixed livestock activities (Makeham and Malcolm 1986, Ch. 12). The budget for one such activity, annual maintenance of a sheep flock to produce wool and lambs, is shown in the lower section of Table 5.2.
This flock budget would probably be adequate if the purpose is to evaluate the financial results of sheep production and perhaps compare such results with those of other activities.
TABLE 5.2 - Internal Structural Coefficients and Annual Activity Budget for a Self-sustaining Flock of 100 Ewes
|
Internal Structural Coefficients |
|
|
|
|
Ewe mortality rate |
0.05 |
|
|
Lamb birth rate |
0.90 |
|
|
Lamb mortality |
0.09 |
|
|
Rams: ewes |
0.05 |
|
|
Ewe and ram replacement rate |
0.20 |
|
Activity Budget |
(Rs) |
|
|
Input costs |
||
|
|
Replacement rams |
(bred) |
|
|
Replacement ewes |
(bred) |
|
|
Feed |
8 000 |
|
|
Veterinary |
300 |
|
|
Shearing |
1 900 |
|
|
Labour |
2 000 |
|
|
Marketing |
800 |
|
|
Total direct costs |
13 000 |
|
Output returns |
||
|
|
Culled ewes and rams |
9 000 |
|
|
Male lambs |
10 000 |
|
|
Female lambs |
5 000 |
|
|
Wool |
8 000 |
|
|
Total returns |
32 000 |
|
Gross margin |
19 000 |
|
On the other hand, however, the budget tells practically nothing about the techno-economic structure of the activity, i.e., how the various internal components of ewes, lambs and rams, and the technical performance of each, impact on each other and on the overall budget results.
Such interrelatedness must, of course, exist but in the budget itself it is only implied. To be of use for some analytical purpose - e.g., analysis in problem-diagnostic mode - the implied coefficients have to be stated in explicit form. The relevant internal structural coefficients are shown in the upper section of Table 5.2. They indicate that in this example the normal death rate among ewes is five per cent annually; 90 lambs are born annually per 100 ewes; nine per cent of lambs do not survive; five rams are run per 100 ewes; 20 per cent of the (old) ewes and rams are replaced (by retained lambs) annually.
There are three main reasons for taking explicit note of these internal structural coefficients. First, they show at a glance the techno-economic conditions under which the results of an activity are achieved (in this example the results are a self-sustaining flock of 100 ewes yielding an annual gross margin of Rs 19 000). Second, they are essential information if the budget is intended for activity problem diagnosis. Third and of primary interest here, they provide a basis for closer examination of the interrelatedness of the various components of the activity - in this example between populations of and returns from the lamb and ewe components of the activity.
The objective might be to quantify the separate effects of sheep losses and sales on the annual maintenance of a constant-size flock of 100 ewes. Assuming that this particular aspect of the sheep system is to be examined, a flowchart such as that of Figure 5.4 would be prepared showing the interrelatedness of components, in terms of animal numbers, in more detail. This is an elaboration of the relevant parts of the budget table. As noted, this flowchart refers to sheep populations. If some other aspect of interrelatedness is of interest (e.g., feed supply versus births/deaths etc.), a flowchart based on the relevant parameters would be prepared analogously to Figure 5.4.
From the previous discussion of parametric budgets (Section 4.6), most of the internal structural coefficients of Table 5.2 will be recognized as 'critical parameters'. Such coefficients as lamb birth rates etc. are critical in the sense that any significant change from their present level would obviously flow through to alter the final result (sustainability and gross margin) of the activity. Such changes would be evaluated by making conditional or parametric extensions to the budget of Table 5.2.
However, it might be noted that while internal structural coefficients are similar to critical parameters, they are not exactly equivalent. Some factors, e.g., lamb mortality rates, are both coefficients and critical parameters. But others, such as the amounts of wool cut from ewes and lambs and the prices received for these, are critical parameters although they might not involve interrelatedness among the several elements of the system and are therefore not internal structural coefficients. Similarly, some activity input/cost items such as labour and feed might be economically 'critical' but would have nothing to do with interrelatedness among activity components.
The second type of system interrelatedness, that which is quantified in terms of external structural coefficients between activities or enterprises, is illustrated by the example of Figure 5.5. This presents budgets for four integrated coconut activities: growing coconuts for direct sale, or alternatively using the nuts and by-products as inputs to the three related activities of making copra (from coconut flesh), making charcoal (from shells) and making coir fibre (from husks). From the previous discussion (Section 4.1), it is here useful to distinguish, on the one hand, between this set of four coconut-based operations as an enterprise and, on the other hand, each of the product-specific subsets of operations as activities. Note also that Figure 5.5 encompasses only a small set of the great number of coconut activities that are possible (Grimwood 1975).
Activity budget 1 of Figure 5.5. which relates to producing 4 000 nuts annually from the standard 64 palms per acre, would apply if these nuts are simply to be grown and sold. Budgets 2, 3 and 4 apply if instead the nuts are retained on the farm for further processing. They show operations, inputs, costs, outputs, gross returns and net returns for the respective activities (all of which are possible components of the overall coconut enterprise). For present purposes what are of interest are the external structural coefficients which link these several activities together. These coefficients are briefly explained.
FIGURE 5.5 - Structural Relationships among Four Coconut Activities (per Acre Basis)
In Figure 5.5 the first relationship between Activities 1 and 2 is through the output of nuts in Activity 1 as this determines the raw material available for Activity 2, copra making. This linking coefficient has a value of 1.0 - all nuts are used for copra. But on some other farm the coefficient could be, say, 0.75 if three quarters of the nuts are processed and one quarter sold as nuts. This would occur, e.g., if 25 per cent of nuts are first grade and sold as food, while all second-grade nuts are processed as copra.
In Activity 2, copra making, the first operation is husking 4 000 nuts, which produces 4 000 clean nuts plus 4 000 husks. The clean nuts are then split into halves which contain the (future) copra. These are first sun-dried for half a day then loaded into a fuel-burning drier for five days. After unloading, the cured copra is hand-extracted from the half-shells and is then subjected to the further operations shown under Activity 2. The now-empty shells, on the other hand, are disposed of in two ways: two thirds of them are recycled back as dryer fuel for curing some future batch of copra (i.e., two thirds of the shells from any batch would provide sufficient heat to dry the copra of that batch). This is shown in Figure 5.5 as a coefficient value of 0.67 (of 8 000 half-shells) so that 5 360 half-shells are cycled back as fuel into the copra-drying operation.
The remaining output of one third of the half-shells, i.e., 2 640, now becomes raw material input for the next activity, charcoal making. Thus the output of charcoal in Activity 3 is governed by the (shell) fuel requirements of Activity 2. Note, however, that these coefficients of two thirds and one third are subject to some variation. Firing the half-shells in copra curing requires considerable skill, the degree of which can be directly measured in terms of the copra-shell fuel requirement coefficient: if this rises much above 0.67, say to 0.75 (leaving only 25 per cent of the shells available for processing to charcoal), it would indicate unskilled workmanship or poor management.
To return to the second structural linkage between Activities 1 and 2: the size of this external structural coefficient is determined by the degree of maturity of the nuts at harvest time (coconut is usually harvested at two-month intervals). Maturity level affects the rate of recovery of copra. The recovery or nuts-to-copra conversion rates for three maturity conditions are shown as structural coefficients in Activity 2, but they are determined by the timing of the harvesting operation in Activity 1: the conversion rate, denoted here by C, will be 1 330 nuts required to make one 'candy' of copra (480 pounds, 218 kilograms) if nut harvesting is at the still-green stage. For ripe nuts, C = 1 150, and for brown nuts, C = 1 100. (Of course, other management practices such as palm fertilizer applied, weeding etc. will also affect the absolute level of nuts-to-copra conversion, but the relative recovery rates due to the maturity effect will still hold.)
Finally, Activity 4 consists of making coir fibre from the husks by-product generated in Activity 2. The structural coefficient relating these two activities has a value of unity since each nut for copra production provides one husk for making coir fibre. This is the only structural coefficient shown as providing linkage between Activity 4 and the other activities. However, on most estates another important linkage does in fact operate between Activities 1, 3 and 4: it consists of the common practice of retaining some proportion of the husks generated in Activity 2 and using them (buried in trenches alongside the palms) as a source of potash in the fertilizing operation of Activity 1. The proportion of husks used for this purpose, which will depend on the potash status of soils on any particular estate, will then govern coir production output in Activity 4. (The deciding factor between using husks as fertilizer or as an input to coir production will be the cost saved by using husks instead of artificial potash versus the income foregone by not making coir.)
In summary, the external linkage coefficients shown in Figure 5.5 quantify the interrelatedness which exists between the various activity subsystems of this total coconut enterprise. Any full analysis of any one of these activities would also require consideration of its effects on the others.
Both internal and external structural coefficients become very important in linear programming (Section 9.6).
5.3.1 General charges
5.3.2 Capital fixed costs
5.3.3 Relative importance of total farm fixed costs
The next element of a farm-household system to be considered is its farm service matrix. This is a system of Order Level 9 (Figure 1.2). It consists of some set of material, labour and cash inputs which enables the farm-household to function as a system, but which is not specific to any particular production activity of the system. (If they are activity-specific they will be treated as costs of the appropriate activity.) This section thus continues the discussion of resources, capital and costs begun in Section 3.3.6.
In their financial dimension these system-service inputs are referred to as whole-farm overhead, common or farm fixed costs. Such fixed costs must be included in the economic evaluation of a farming system for the two reasons that they influence both the profitability and the sustainability of the system.
There are two broad categories of overhead costs, general charges and capital fixed costs. General charges represent an actual money expenditure and as such, when included together with the aggregated direct costs of the production activities of the system, will determine its profitability. The second category of fixed costs (capital fixed costs, below), while not directly affecting immediate system profitability, will affect its sustainability.
General charges are those fixed costs incurred in obtaining service inputs of an institutional nature (see Section 3.3.6) which logically cannot be assigned to any specific production activity of the farm and which must be paid for. They represent an actual financial outlay. Some examples are: land tax payments, taxes on general-purpose livestock, water licence fees and vehicle registration fees.
Table 5.3 provides an example of the general charges and capital fixed costs making up the annual fixed costs on a rubber estate. It illustrates the importance and wide range of general charges.
Capital fixed costs are those costs incurred in the use of non activity-specific physical farm capital and pertain to its maintenance, operation (in non activity-specific uses only) and provision for its eventual end-of-life replacement. Their payment is not mandatory - at least in the short run - and 'payment' is often in the nature of an internal bookkeeping transfer which is designed to provide - if indeed at all - only for the long-term sustainability of the system's fixed capital and for the eventual replacement of such capital as it wears out. Typical of these capital fixed costs are 'payments' or provisions for the maintenance, use and replacement of farm buildings, houses, fences, pumps and other machinery, paths, roads, farm bridges, ponds, irrigation and soil conservation systems, and breeding livestock.
TABLE 5.3 - Example Listing of Annual Total Fixed Costs on a Rubber Estate
|
Cost Item |
Amount |
|
|
General charges |
||
|
|
Salaries |
Rs 18 757 |
|
|
Staff allowances |
600 |
|
|
Staff provident fund |
1 012 |
|
|
Workers provident fund |
11 462 |
|
|
Wage adjustment |
673 |
|
|
Labour holidays |
6 454 |
|
|
Food for functions |
708 |
|
|
Medical, sanitation |
3 635 |
|
|
All insurance |
2 852 |
|
|
Office supplies |
1 771 |
|
|
Commissions paid |
1 005 |
|
|
Visiting agent |
750 |
|
|
Rents, taxes |
2 231 |
|
|
Vehicles |
10 000 |
|
|
Watchmen |
1 373 |
|
|
Retirement gifts |
2 478 |
|
Capital fixed costs |
||
|
|
Housing upkeep |
Rs 9 264 |
|
|
Labour-lines upkeep |
1 857 |
|
|
Minor buildings |
390 |
|
|
Roads, water supply |
950 |
|
Total fixed costs |
Rs 78 222 |
|
|
Total production (pounds weight) |
276 600 |
|
|
Fixed cost/pound weight |
Rs 0.28 |
|
The essential difference between general charges and such capital fixed costs is that payment for the former is mandatory, while cash disbursement for the latter is not. (The alternative, if no funds are put aside for capital replacement and no replacement is carried out, is to run down the farm capital structure, in which case it sooner or later ceases to be sustainable.)
On most small farms, expenditure on fixed costs of both categories will be very low. Most fixed-capital costs (i.e., for capital maintenance) will be 'paid' for in the form of family labour used to repair and eventually reconstruct fences, ponds, ox gear etc. Obviously, the importance of farm fixed costs will thus vary according to the farm type under consideration (Chapter 2). The forest-garden farms of Kerala and Sri Lanka can practically ignore capital fixed costs (but not general charges such as land taxes), simply because apart from their trees, a few hand tools and the land itself, they have little capital. On the other hand, on the intensively operated mixed crop-livestock farms of Sind, capital fixed costs (and total farm fixed costs) might be significant - but still much less so than on commercial estates. The typical situation on these latter is summarized in Table 5.4 which shows annual average direct, fixed and total cost of production (COP) per pound of made rubber on a sample of 148 Sri Lankan estates. Total estate fixed costs (general charges plus capital costs, but, as noted, mainly general charges) are very significant and amount to about one third of total costs.
TABLE 5.4 - Average Annual Costs of Production of Made Rubber for a Sample of Sri Lankan Rubber Estates (Rs per Pound Weight)
|
Sample |
Direct costs |
Fixed costs |
Total COP |
||
|
Cultural |
Factory |
Marketing |
|||
|
36 sheet estates |
0.402 |
0.088 |
0.030 |
0.249 |
0.769 |
|
86 crepe estates |
0.430 |
0.147 |
0.045 |
0.293 |
0.915 |
|
26 mixed estates |
0.450 |
0.117 |
0.049 |
0.289 |
0.905 |
|
All 148 estates |
0.430 |
0.138 |
0.044 |
0.289 |
0.901 |
Source: Data from a survey by the senior author and Marshall Perera for the Office of the Rubber Controller, Colombo. 1989.
Obtaining the general charges of a farm or estate will usually present no problems. Table 5.3 is an adequate guide to the types of cost items which may occur. On the other hand, the evaluation of capital fixed costs will require a little arithmetic as exemplified by the illustrative schedule of Table 5.5. This is for a particular farm whose operating budget is presented later in Table 7.1. The schedule consists of a complete inventory listing of all the farm's fixed-capital items (including land) and their capital values as shown respectively in columns (1) and (2). The inventory is then assessed to obtain the annual fixed costs of replacing/repairing/operating these capital items as respectively listed in columns (4), (5) and (6). These costs are aggregated in column (8) to give the annual fixed cost of each capital item. Column (7) is not needed immediately; it will be required later for economic evaluation of a farming system (Section 7.2).
In calculating annual capital fixed costs as per Table 5.5, the values given to capital items in column (2) and hence their depreciation charge in column (4) should not be based on their initial purchase or construction cost. Capital items should be valued at their current expected replacement cost. The tractor, e.g., might actually have cost Rs 8 000 five years ago, but today the cost of replacing this five-year-old machine with a new one might be Rs 10 000. Whatever the initial cost or value might have been is of historical interest only and, except by coincidence, will no longer be of relevance in making provision for eventually replacing the item when that becomes necessary. Column (3) contains estimates of the years of useful service which can be expected of each item from the time of its initial purchase by the farmer. These are inevitably somewhat arbitrary. Land is assumed to be used sustainably and thus to have an indefinite useful life. Columns (4), (5) and (6) of Table 5.5 show the individual components of the fixed-capital cost of each capital item, based on columns (2) and (3).
TABLE 5.5 - Farm Capital Investment Inventory and Schedule for calculating Annual Capital Fixed Costs
|
Capital investment inventory |
|||||||
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
(8) |
|
Capital item |
Item valuea |
Useful life |
Deprec'nb |
Repairs |
Operating costs |
Interest at 10% |
Total (4)+(5)+(6) |
|
(Rs) |
(years) |
(Rs) |
(Rs) |
(Rs) |
(Rs) |
(Rs) |
|
|
Land |
50 000 |
- |
- |
- |
- |
5 000 |
- |
|
House, sheds |
15 000 |
25 |
600 |
200 |
- |
1 500 |
800 |
|
Tractor |
10 000 |
10 |
1 000 |
400 |
- |
1 000 |
1 400 |
|
Hand thresher |
2 000 |
6 |
330 |
50 |
- |
200 |
380 |
|
Cultivators |
3 000 |
5 |
600 |
100 |
- |
300 |
700 |
|
Livestock gear |
600 |
3 |
200 |
50 |
- |
60 |
250 |
|
Barn |
5 000 |
20 |
250 |
200 |
- |
500 |
450 |
|
Fences |
6 000 |
30 |
200 |
400 |
- |
600 |
600 |
|
Dam/pond |
8 000 |
40 |
200 |
- |
- |
800 |
200 |
|
Water pump |
4 000 |
8 |
500 |
200 |
800 |
400 |
1 500 |
|
Oxen |
3 000 |
5 |
600 |
- |
200 |
300 |
800 |
|
Total |
106 600 |
|
4 480 |
1 600 |
1 000 |
10 660 |
7 080 |
a Value based on current expected replacement cost. 'Land' includes all fixed improvements (drains, levelling, earthworks etc.) and permanent tree crops in house yard.b Here the straight-line method of calculating depreciation is used and it is assumed that the capital items have no residual value at the end of their useful life (see Section 5.5).
Depreciation is the decline over time in the capacity of a capital item to provide the service expected of it and for which it is held (Barnard and Nix 1973, pp. 85-88; Doll and Orazem 1984, pp. 263-266). Depreciation is usually measured on an annual basis. Ideally, it would be measured in actual terms but that would involve inordinate record keeping. Instead, simpler rule-of-thumb procedures (as outlined in Sections 5.5 and 10.10) are used. As well as through wear and tear arising from use of the capital item, depreciation also occurs through technical obsolescence as more modem machines or other items providing the same service but at lower unit cost become available. While wear and tear may be relatively predictable and approximately constant over time, technical obsolescence may not be. In consequence, to be as correct as possible, annual depreciation should be calculated afresh each year. Whether or not it is economically worthwhile to do so will depend on the particular situation.
Column (4) of Table 5.5 provides some examples of depreciation. These amounts are measured as a constant pro rata proportion over each item's life of its expected replacement cost (i.e., straight-line depreciation, Section 5.5). In percentage terms this depreciation cost corresponds to 100 divided by the item's useful life. Consider the tractor valued at Rs 10 000 which is estimated to have a total useful life of ten years. On a pro rata basis, the annual cost of obtaining this service is Rs 10 000/10 or Rs 1 000. Or to put it another way, based on the present assessment, if the farm's fixed capital is not to be depleted, a sum of Rs 1 000 per year should be set aside to enable the tractor to be replaced when it finally wears out or, due to technological advance, becomes obsolescent (in five years' time if it is five years old now). (Hence the preference for basing item value in column (2) on current expected replacement cost rather than past/historical actual cost.) There are several methods by which annual depreciation cost can be calculated; they are discussed in Section 5.5 below.
Repairs refers to the sum of money which normally must be spent on maintaining each capital item in good repair. Note, however, that in spite of such repairs, the item (tractor, thresher, fences etc.) will sooner or later wear out or become obsolete, hence the need for its depreciation as well as its routine repair.
Operating costs are the costs of actually operating a capital item: e.g., Rs 800 for water-pump fuel, Rs 200 of feed and veterinary expenses for the oxen. In Table 5.5 the tractor would, of course, also incur fuel and oil operating costs but in a typical farm situation it would be fairly easy to charge these against the separate specific activities (paddy, cotton etc.) which actually consume this fuel or incur such operating costs, rather than against the farm as a whole. Often, however, some capital operating costs will be incurred in nonspecific farm work, in which case they should be included in column (6). This was discussed in Section 3.3.6 in relation to Figure 3.3.
Interest as listed in column (7) of Table 5.5 is a bookkeeping charge levied on total farm capital - i.e., all capital invested in the farm - in order to assess the productivity of the several farm resource categories or factors of production (land, labour and capital) as outlined in Section 7.2.3. It is not a 'cost' in the conventional sense of detracting from the value of farm net output (or family income). For the moment, only the procedure of obtaining this item is of concern. Briefly, some appropriate rate of interest, here ten per cent, is applied to the assessed value of each/all of the capital investment items as listed in column (2) of Table 5.5. The appropriate interest rate is determined by the opportunity cost of similar capital items in their 'most likely most profitable most prudent' other use. Thus if the best alternative investment available were for the family to sell the farm and put the proceeds in a bank earning ten per cent annual interest, this would determine the opportunity cost of farm capital and thus the appropriate interest rate to apply in obtaining column (7).
To conclude, one might state the obvious: these procedures for obtaining the interest costs of column (7) are full of practical pitfalls. Is the replacement value of an item a proper representation of its value in use? If not, a more appropriate value should be used. Or, as is not infrequently done, items might be valued at the mid-point of their useful life with allowance made for any residual value they may possess at the end of their useful life. Thus the oxen of Table 5.5 with a useful life of five years and, say, a residual value of Rs 800 as meat would be valued at Rs (3 000 + 800)/2 = Rs 1 900. Is it sufficient to apply some rate of interest (say ten per cent, as above) uniformly to all capital items, or are the opportunity costs of some capital items greater than of others? (Probably yes, but precision must be weighed against the extra work required in obtaining the necessary information.) What is an appropriate alternative investment? Could money, instead of being put in the bank at ten per cent, be lent to a speculator in the souk at 50 per cent and still be regarded as a prudent alternative investment? (Probably not.).... Anyway, do realistic alternative uses of farm investment capital actually exist? (Certainly yes in South India, possibly not in the hills of Bhutan.)
On the other hand, when concern is with small farms, these practical difficulties are largely removed by the facts that (a) the value of farm capital itself, and thus the level of fixed costs associated with it, will not be very great; and (b) most capital can be maintained and replaced by using (largely 'free') farm-generated resources and family labour. In short, while the effort that goes into the construction of Table 5.5 must inevitably be considerable if later analysis based on it is to be technically satisfactory, the actual data obtained within and subsequently from Table 5.5 might not make much practical difference in the evaluation of small-farm performance (Chapter 7).
To summarize the discussion of Table 5.5: total capital fixed costs on this farm, column (8), are the sum of the previous cost-item columns (4), (5) and (6) - in the example Rs 7 080 annually. Total farm fixed costs are the sum of this item and the farm's general charges.
It was noted previously that payment of general charges is usually mandatory. Taxes and licence fees must be paid. It was also noted that payment of capital fixed costs might be considered optional, at least in the short run. In fact it would be more correct to say that some of the components of capital fixed costs (Table 5.5) are mandatory while others are optional. Again referring to Table 5.5, payments for running repairs and operation (e.g., fuel, feed for the oxen) are in a large sense mandatory, while provision for depreciation is largely optional (in any one operating year). Depreciation (column 4) might be provided for in practice by setting aside Rs 4 480 per year; or such an amount might be re-invested in the business to generate the necessary future replacement funds; or no provision at all might be made. This third case implies that: (a) farm capital stock is being run down or depleted; (b) to the extent that such depletion is occurring, real farm net income is being overestimated; and (c) sooner or later the farm will cease to be a sustainable system (Norman and Douglas 1994. Ch. 2).
Ideally, the annual depreciation of a capital item should be measured in terms of its actual wear and tear due to usage and the change in its degree of obsolescence (Barnard and Nix 1973, pp. 85-88; Doll and Orazem 1984, pp. 260-267). This would imply much inconvenient record keeping not worth its cost. Instead, it is assumed that usage of the item and the accompanying flow of service from it follow some regular pattern and depreciation is estimated accordingly (Thuesen 1959, Ch. 5). Thus there are four main methods of calculating annual depreciation 'cost' or the annual rate at which a capital item provides services and is thereby used up or becomes obsolete. Three of these methods are briefly discussed here. (The fourth, which involves the application of amortization procedures, is outlined in Section 10.10.)
Straight-line depreciation assumes a constant flow of service with consequent wear and tear and/or obsolescence during the item's useful life so that the value of the item will therefore decrease by a constant uniform annual amount over its life (Makeham and Malcolm 1986, Ch. 13). This is the easiest method to apply. The formula for obtaining the annual straight-line depreciation amount, denoted by D, is
D = (PV - SV)/L
where PV is the item's present value (i.e., its expected future replacement cost at the moment of analysis), SV is its expected salvage or residual value at the end of its useful life and L is its expected total years of life. Thus annual depreciation on a cultivator with an expected replacement cost of Rs 1 000 and which has an expected total useful life of ten years and can then be sold for Rs 200 as scrap would be
Rs (1 000 - 200)/10 = Rs 80;
or if it has no salvage value,
Rs 1 000/10 = Rs 100.
This method is probably most appropriate for small Asian farms where most capital items (pumps, cultivators, livestock gear etc.) suffer no loss in value due to obsolescence, are entirely used up in the production process, and do not have a residual value (e.g., as the basis for trade-in on a new model). The results of applying this method are shown in the lefthand-side graph of Figure 5.6.
Declining-balance depreciation assumes that the item is used up and/or becomes obsolescent at a constant percentage rate of its annual starting value. Applied to the previous example with a zero salvage value and assuming an annual depreciation rate of ten per cent, this would result in an annual depreciation amount of Rs 1 000 x 0.10 or Rs 100 in year 1 of the item's life, Rs (1 000 - 100)0.10 or Rs 90 in year 2, Rs (1 000 - 100 - 90)0.10 or Rs 81 in year 3, Rs 73 in year 4, etc. With declining-balance depreciation, the formula for calculating the annual depreciation 'cost' in year t, denoted by Dt is:
Dt = (Vt-1)d
where Vt-1 is the item's depreciated value at the end of year t-1, Vt-1 = (Vt-2 - DT - 1), V0 = (PV0 - SV) where PV0 is the item's expected replacement cost at time zero, i.e., at the start of the depreciation analysis, and d is the constant annual rate of depreciation.
Obviously, as illustrated by the middle graph of Figure 5.6, the procedure results in a lower and declining depreciation loss in later years. This is appropriate where the value loss is due to the 'planned obsolescence' of modem equipment (which is reflected in dealers' secondhand machinery and vehicle-buying price schedules as these are used in the West). Such obsolescence hardly exists on small Asian farms where, as noted, value loss is due to wear and tear from physical use. Note also from Figure 5.6 that, unlike straight-line depreciation, the declining-balance method does not lead to full write-down of an item at the end of its useful life.
Sum-of-integers depreciation is essentially similar to the declining-balance approach in that this method also results in less than full write-down and in a declining annual depreciation 'cost' which eventually becomes zero in the last year of life as shown by the righthand-side graph of Figure 5.6. Compared to the declining-balance and straight-line methods, the sum-of-integers method implies a more rapid initial depreciation but slower later depreciation. The formula for sum-of-integers depreciation is:
Dt = (PVt=0 - SV) [Remaining years of life/Sum of integers of total life]
where Dt is again depreciation for year t and PVt=0 is the expected replacement value of the capital item at time zero, i.e., at the start of the depreciation analysis. Using the previous example of the cultivator with a life of ten years and no salvage value (i.e., SV = 0), the 'sum of the integers' would be (1 + 2 + 3..... + 10) or 55, and the annual depreciation 'cost' would be:
|
Year 1: |
Rs 1 000 x 9/55 = Rs 164 |
|
Year 2: |
Rs 1 000 x 8/55 = Rs 145 |
|
Year 3: |
Rs 1 000 x 7/55 = Rs 127 |
|
... |
... |
|
Year 9: |
Rs 1 000 x 1/55 = Rs 18 |
|
Year 10: |
Rs 1 000 x 0/55 = Rs 0. |
Comparing the three depreciation methods outlined above, the straight-line approach is generally to be preferred on the grounds that it is less complicated and ensures full depreciation or write-down of the item.
Barnard, C.S. and J.S. Nix (1973). Farm Management and Control, Cambridge University Press.
Dillon, J.L. and J.R. Anderson (1990). The Analysis of Response in Crop and Livestock Production, 3rd edn, Pergamon Press, Oxford.
Dillon J.L. and J.B. Hardaker (1993). Farm Management Research for Small Farmer Development, FAO Farm Systems Management Series No. 6, Food and Agriculture Organization of the United Nations, Rome.
Doll, J.P. and F. Orazem (1984). Production Economics: Theory with Applications, 2nd edn, Wiley, New York.
Grimwood, B.E. (1975). Coconut Palm Products: Their Processing in Developing Countries, FAO Agricultural Development Paper No. 99, Food and Agriculture Organization of the United Nations, Rome.
Makeham, J.P. and L.R. Malcolm (1986). The Economics of Tropical Farm Management, Cambridge University Press.
Norman, D. and M. Douglas (1994). Farming Systems Development and Soil Conservation, FAO Farm Systems Management Series No. 7, Food and Agriculture Organization of the United Nations, Rome.
Thuesen, H.G. (1959). Engineering Economy, 2nd edn, Prentice-Hall, Englewood Cliffs.
