Aboki, peter maisaje

2.3 Profitability Measures and Value addition

Profit is defined as total revenue minus total cost (Erikson, et al 2004). They outlined four perspectives of profit; (i) profit is a reward for taking risks in business; (ii) profit results from the control of scarce resources; when a citizen owns a resource that others want, the others will bid up the price which will then generate profit for the owner; (iii) profits exist because some people have access to information others do not have. This special knowledge include secret formulas or processes, exclusive right to inventions, property rights and patents, e.t.c., ensuring profit for the creator; and (iv)profits could exist simply because some businesses are managed better than others; their managers are often creative planners and thinkers with efficient organizational abilities.

The accountant looks at profit as the income that remains after all contractual, measurable costs are subtracted. The economists however determine profits by examining alternative uses of resources within the firm. Hence, economic profit is defined as accounting profit less opportunity cost. It forces an examination of alternative uses of resources and helps in analyzing alternative courses of action by the firm (Kay, 2000).

It is contended that the entrepreneur’s motive for producing any given product is that of the attainment of maximum profit, while consumers or buyers’ motive is that of utility maximization (Olayide & Heady, 1982). The profit motive is the ‘spark plug’ of a market oriented capitalist economy. The prospect of earning and keeping a profit serves as the incentive for creativity and efficiency among people. It stimulates risky ventures and drives people to develop ways of cutting costs and improving techniques, always in an effort to satisfy consumers desires (Erikson et al, 2002).

Kotler & Keller (2006) suggested that firms should be able to measure the profitability of their products, territories, customer groups, segments, trade channels and other sizes; emphasizing that this will help the management to determine whether any products or marketing activity should be expanded, reduced or eliminated. Marketing profitability analysis generally indicates the relative profitability of different channels, products, territories or other marketing entities. More so, companies are showing interest in using market profitability analysis or broad version activity based cost accounting (ABC) to quantify the true profitability of different activities (Cooper & Kaplan, 1991). Profitability can be improved by managers if there is reduction in resources needed to perform various activities or make resources more productive or acquire them at least cost; or alternatively raise prices on products that consume heavy amount of support services (Kotler & Keller, 2006).

Various models of profitability have been used in production and marketing researches. Onuoha, Okereke & Asumugha (2009) applied the gross margin and net income analysis in determining profitability of feed-mills in Umudike, Abia State, Nigeria; in which profitability was reported at 1.06 for every naira spent. In similar study on paddy enterprises, Okoye & Anuebunwa (2009) reported gross margin of 33% and 27% for the two enterprises. Ezedinma (2007) noted that the profitability of a market is a direct indicator of degree of efficiency of the marketing system.

2.3.1Profitability analysis

In economic theory, profit is maximized at output level where marginal cost equals marginal revenue (Koutsiyianis, 1979). Thus, one can determine profit by comparing total revenue with total cost, or by comparing average price and average total cost. Multiplying the difference by the total output gives the total profit or loss (Nellis & Parker, 2000).

Olayide & Heady (1982) derived unconstrained profit maximization given two factors and one product production function as follows;

Q = f (x₁, x₂) ……………………………………. 2.1

C = r₁ x₁ + r₂ x₂ + b……………………………. 2.2

Where,

Q = output, C= cost, x₁, x₂ are inputs;, r= price of input, b= fixed cost.

Understanding that profit (π) is given as revenue (price multiplied by quantity) less cost, and then one has a function of the form:

π = Pf (X_1, X₂) – r₁ X₁ – r₂ X₂ – b) ……………………. 2.3

To maximize profits, we set the partial derivatives of π with respect to Xs and equate to zero and solve. Hence profit is maximized at output level where marginal cost (MC) equals marginal revenue (MR), given p= price of output. This is given as

δπ/δx1= pf₁-r₁ = 0 …………………..2.4

δπ/δx2 = pf₂ – r₂ = 0 …………………… 2.5

Solving 1and 2 then

Pf₁ = r₁; pf₂=r₂ ……………………… 2.6

If the price of a commodity exceeds the average total cost (ATC) of production, supernormal (pure) profits are made as opposed to normal profits; and if the price is below average variable cost (AVC), the firm is at shut down point, in the short run (Nellis & Parker, 2000). Normal profit is the minimum rate of profit which must be earned to ensure that sufficient number of people are prepared to invest, organize production and undertake risk in an industry (Nellis & Parker, 2000; Frank & Bernanke, 2001).

2.3.2 The value adding process in agriculture

The difference in values of raw agricultural product before processing and after processing is the added value. Black (2002) defined value adding as the total value of a firm’s output less the value of inputs purchased from other firms. Value added is thus what is left to be shared between wages of the employees and profits for owners of the business. Gittinger (1972) noted that one could have gross value added, in which case the value of inputs is not subtracted, and the net value added where deductions are made for inputs including depreciation, labor, management, and cost, among others. In this case value added could be positive or negative as the case may be. In agricultural processing, Austin (1992) and Brown et al, (1994) explained that the difference between cost of ingredients (including farm produce), and the ex-factory or post- processing price of the finished products is the value added through processing. Without prejudice to other opinions, this will be the working definition for this study.

Agricultural marketing provides form, place, time and possession utilities to consumers (Kohls & Uhls, 2000). Agricultural processing changes the form of the farm produce to a state required by consumers or next stage in a manufacturing scheme, hence creating form utility. Olukosi & Isitor (1990) described processors and manufacturers’ activities as increasing the quality and value of farm produce.

The value adding process however runs in the entire food marketing channel from production through processors, the traders to the final consumer. The optimization of the food marketing chain is now attracting attention from agencies involved in agricultural research and rural development (Fellows & Hampton, 1997; Bruinsma, 1999). The technical advisory committee to CGIAR also takes the view that research on agricultural productivity needs to be complemented by more research on product utilization and post-production activities, storage, processing and marketing as part of a coherent approach (Bruinsman, 1999). Ezedinma (2007) also advocated commodity chain approach to agricultural development. Ganewatta, Waschik, Jayasuriya & Edward (2005) observed that the East Asian industrialized countries adapted policies to enhance domestic processing of primary commodities as a tool for accelerating employment, growth, export revenues and development.

Agricultural processing industry or Agro-industry has grown in size because of its integration of agricultural and industrial activities (Austin, 1992). It is seen as probably the most important component of agribusiness (Olayide & Heady, 1982). In the United States of America, food processing constitutes the bulk of value adding activities and small businesses (Torok, et al, 1990). Agro- industry has also been defined as any activity that deals with the processing of material of plant or animal origin, which is why agro-processing industries dominate manufacturing activities in less developed countries where agriculture is the main stay of the economies (Brown, Deloitte & Touch, 1994). Brown (1986) & Austin (1992) explained agro-industries to include such activities as oil seed crushing, grain milling, fruit and vegetable canning, meat packaging, the textile industry, and function of marketing.

It is said that one of the first steps on the road to industrialization is the processing industry, so that starting a small rice mill or an oil press marks an early stage in industrialization (Austin, 1992). More so a nation may not fully use its agronomic resources without a viable agricultural processing sector, because most agricultural products including subsistence products are processed to some extent (Brown, 1986). Brown, Deloitte & Touche (1994) pointed out that a post-harvest enterprise can influence the volume and disposition of agricultural production, likewise the degree of food self-sufficiency, it induces changes in infrastructure; enhance employment and contribution to foreign exchange earnings. The establishment of agro allied industry can in addition to immediate and direct benefits to farmers bring about development of other infrastructural amenities such as improved transportation facilities, water and electricity supply, schools and health services (Barau, 1979; Orewa, 1978).

2.4 Input Use and Efficiency Measurement

Agricultural productivity is an index of the ratio of the value of total farm input to the value of output. The attainment of social welfare ‘parieto optimality’ of every society hinges on the maximum use of available resources, which with every re-allocation of resources, everyone is made better and no one is made worst off (Kutsoyianis, 1979; Black, 2000). The input- output relationship in production process becomes important in four areas; (i) distribution of income, (ii) allocation of resources, (iii) the relationship between stock and flow resources, and (iv)the measurement of efficiency or productivity (Olayide & Heady, 1982). Kutsoyianis (1979) also emphasized the principle of efficiency in the overall equilibrium of the consumers, producers and the markets. Maximum resource productivity then means obtaining the maximum possible output from the minimum possible set of inputs. In this perspective, optimal resource productivity implies an efficient utilization of resources in the production process; thereby expressing synonymy of productivity and efficiency (Olayide & Heady, 1982). Lassita & Odening (2003) noted that maximum productivity also called ‘best practice’ is revealed in the production frontier and, hence, efficiency involves the distance to this frontier.

2.4.1 Efficiency measurement

Efficiency is a term that applies in several aspects of economic life, defined by Black (2000) as getting any given results with the smallest possible inputs, or getting the maximum possible output from given resources. This is applied both in agricultural production and marketing. In agricultural marketing, the term market efficiency is used to describe the performance of the marketing system, encompassed in performance of marketing factors in which efficiency is defined as increasing the output – input ratio (Erikson et al, (2002). Olukosi & Isitor (1990) observed that efficiency was an engineering terminology commonly used in machines to measure the ratio of output to input. Hence, marketing efficiency can be defined as the maximization of the ratio of output to input of marketing (Kotler & Keller, 2006). The inputs of marketing include the resources expended in providing marketing services such as capital, labour and management.

Meanwhile, marketing output includes time, form, place and possession utilities which consumers derive from the marketing of products. Therefore, marketing inputs are the cost of providing marketing services whereas marketing outputs are the benefits or satisfaction created, or the value added to the commodity when it passes through the marketing system (Olukosi & Isitor, 1990; Kotler & Keller, 2006). Efficiency ratios can be measured in physical terms or in monetary terms (Bamire et al, 2007). If in monetary terms, the concept becomes a ratio of benefits to cost (Olukosi & Isitor, 1990).The higher the ratio the higher the marketing efficiency, and the better the marketing system.

Estimating the inputs of marketing is much easier than the outputs of marketing. The input cost of marketing is the value of all resources used in the marketing process. The best measure of marketing output (consumers’ satisfaction) is the price consumers are willing to pay for the farm products with different levels of marketing utilities (Shepherd & Futrell, 1970; Downey and Trocke, 1981; Olukosi & Isitor, 1990).

Marketing efficiency, according to Kohls & Uhls (2000), Erikson et al, (2002), and Kotler & Keller (2006) could be attained in any of the following situations:

1. 
   output remains constant while input decreases;
   
2. 
   output increases while input remains constant;
   
3. 
   output increase more than input increase; and
   
4. 
   output decreases more slowly than decreases in input
   

Marketing efficiency can be looked upon in two perspectives, operational efficiency or technical efficiency and pricing efficiency or economic efficiency. Operational or technical efficiency measures the productivity of performing marketing services within a firm, with emphasis on the cost of providing marketing services. This assumes that the essential nature of output of goods and services remain unchanged, hence the focus is on reducing the cost of inputs used in doing the job. For instance, an innovative method of crating eggs or tomatoes may not only increase the quantity handled in a given space, but also reduce damages during transportation. In this, one has improved operation efficiency.

Olukosi & Isitor (1990) posit that pricing efficiency assumes a physical input-output relationship that remains constant; hence, pricing efficiency is concerned with how effectively prices reflect the costs of moving the output through the marketing system. In this case, prices that consumers pay for goods delivered by the marketing system should adequately reflect all marketing and production costs, therefore bringing about improvements in the operations of buying and selling and the pricing aspect reflecting consumers’ wishes. In a perfectly competitive economic environment, prices will adequately serve this purpose by reflecting all costs of marketing. Marketing imperfections such as dominance of few firms or inadequate price information will give rise to pricing inefficiency (Truet & Truet, 1990; Olukosi & Isitor, 1990; Frank & Bernanke, 2002).

In the light of the above, Bressler & King (1970) noted that efficiency models were closely related to and sometimes identical with competitive models. Here, the theoretical construct must come largely from the theory of perfect market in which efficient market will establish prices that are interrelated through space by transportation costs, through form by costs of processing and through time as a consequence of the costs of storage. Therefore, only a normal profit is earned by participants in the marketing system (Kutsoyianis; 1979; Nellis & Parker, 1999).

In production, efficiency is concerned with the relative performance of the process in transforming inputs into output (Arene, 2003). Efficiency of a production system then compares between observed and optimal values of its output and the inputs used in the production process. This is in the form of ratio of observed output to the maximum potential of observed inputs required to produce a given level of output or some combinations of the two scenarios (Olayide & Heady, 1982)

Arising from the initial definitions of efficiency by Farell (1957), Alvarez & Arias (2004) said that a firm is considered to be technically efficient if it obtains the maximum attainable output given a level of inputs and the technology used. Also from Farell’s work, Osborne & Trueblood (2006) made a distinction among technical efficiency (TE), allocation efficiency (AE) and economic efficiency (EE). Furtherance to that, with an input orientation, TE refers to the ability to minimize physical input use for a given level of output; AE refers to the ability to achieve cost minimization for a given output level, while EE refers to the combined effect of achieving both TE and AE. Most empirical studies of efficiency are on technical efficiency rather than economic efficiency because data on price, input and output for economic efficiency analysis are difficult to gather due to price instability, (Osborne & Trueblood, 2006). Efficiency is illustrated in figure 2.1.

Figure 2.1: Illustration of efficiency adopted from Osborne & Trueblood (2006)

In Figure 2.1, given an efficient isoquant Y and the Iso- cost line, point A is technically inefficient since it is located away from the production isoquant for output level Y. Point B is technically efficient because it lies on the isoquant for the output level Y, however this point is not allocatively efficient because it does not lie on the iso-cost line, that is no tangency between the isoquant and the iso-cost line. Point C lies on both the isoquant and the iso- cost line, where it is both technically and allocatively efficient, that is economically efficient (Osborne & Trueblood, 2006). Parametric and non- parametric approaches have been used to measure efficiency (Alvarez and Arias, 2004; Latruffe, Belcombe, Davidora & Zawalinska, 2005; Osborne & Trueblood, 2006; Amaefula, Onyenweaku & Asumugha, 2009).

2.5 Market Integration

Market integration has been studied by several authors, with several approaches to testing spatial market integration using market price to examine the concepts of spatial arbitrage of food marketing systems in developing countries. Jones (1972) and Dadi et al (1992) applied correlation analysis in the study of food market integration in Nigeria and Ethiopia, respectively. Damisa & Rahaman (2004) also used static regression analysis to study market integration of cowpea, ground nut, sorghum and millet in Kano in which prices in some markets affected the others, while some others did not.

Markets are said to be integrated or efficient if the correlation coefficient (R) or regression (β) attain values greater than zero but not greater than one. If R> 0.9, markets are said to be highly integrated; if R<0.8, the markets are said to be moderately integrated. But if R<0.5, then there is no integration and prices move independently of each other (Adeleye, 1988, Damisa & Rahaman 2004).

Okoh (1999) and Akintola (1999) also adopted the Mendoza & Rosegrant (1995) approach to study market co-integration, but avoided the problem of non stationarity by undertaking unit root test and differencing the series; they observed that cassava root and gari markets in the study area were weakly associated, and had some form of price leadership in the system. Kindie et al (2005) applied the auto regressive distributed lagged (ARDL) via OLS in the analysis of markets integration for white teff in Ethiopia. Dittoh (1994) applied the Ravallion model using ARDL to study market efficiency in vegetable markets in Nigeria. Static regression models and some others have been found to be inadequate for analysis of LOP and co-integration due to possible non-stationarity of the series which may lead to spurious regression (Chirwa 2000, Okoh & Egbon 2005, Asche et al, 1999). The Johansen trace test has been found to be more suitable. The price series used in various studies were collected weekly or fortnightly (Damisa & Rahaman, 2004; Ali & Rahaman 2009). Those that used monthly data include Okoh (1999), Okoh & Akintola 1999; Chirwa, 2000; Kindie et al, 2005; Asche et al, 2005).

Several studies on the integration of Nigerian markets and elsewhere point to some major sources of poor integration and inefficiency to include poor price information transmission, too many intermediaries and high cost of transportation as well as the sources and validity of price data (Okoh & Egbon, 2005). Chirwa (2000) also noticed factors influencing market integration to include infrastructure, consisting of transport costs, extent of the transport network, communication facilities and availability and access to credit facilities.

2.5.1 Market integration and the law of one price (LOP)

Two markets are said to be spatially integrated if when trade takes place between them; price in the importing market equals price in the exporting market plus the transportation cost and the other transfer costs involved in moving the commodity (Chirwa, 2000); rural prices and urban prices plus transportation or other transfer costs (Okoh & Egbon, 2005); producer price and wholesale price plus transportation and other cost (Kindie et al, 2005); wild Salmon price and Farmed Salmon prices (Asche et al, 2005).

The perfectly competitive market conditions represent an ideal market structure for market integration, given the attributes that prices adjust instantaneously to any new information. The principle of market integration is itself hinged on the ‘law of one price’ (LOP), which is analysed within the framework of perfect market model. By the Marshallian propositions on economic market, two regions are in the same economic markets for a homogeneous good if the price for that good differs by exactly the inter – regional transportation cost (Okoh & Egbon, 2005). The expression for the LOP can be given as

P_tⁱ + K_t^ij = P_t^j …………… 2.7

Where,

P_tⁱ = Price of product in the exporting market in the period t.

P_t^j = the contemporaneous price of the product in the importing market.

K_t^ij = the transfer cost in the same period

a strict version of the LOP; trade exist between the markets. But if

P_tⁱ + K_t^ij > P_tⁱ ………………… 2.8

then there is no incentives to trade; or if K_t^ij ≠ 0 , then the prices have a proportional relationship, but their levels would differ due to factors such as transportation cost , processing cost, market fees, quality differences e.t.c. This is a weak version of LOP. If no barriers to trade exist between markets, trade will cause prices in the two markets to move on a one-for-one basis and the spatial arbitrage conditions are holding (Asche et al, 1999; Okoh & Egbon, 2005).

2.5.1.1 Stochastic Process and the Unit Root Problem

The unit root analysis and test are the starting point in the analysis of market integration. Consequently stationary stochastic process is of great interest to the price series analyst with respect to market integration. This implies stationarity (weak stationarity) in a random or stochastic process in a collection of random variables ordered in time (Gujarathi, 2007). This is expressed as

Mean: E (Y_t) = μ

Variance: Var (Y_t) = E (Y_t – μ) ² = σ²

Covariance: Y_t = E [(Y_t – μ) (Y_t+k - μ)]

A time series is stationary if its mean, variance and auto covariance remain the same at various lags or points of measurement that is they are time invariant. Hence non-stationary time series will have a time varying mean or time varying variance or both. A stochastic process (time series) is purely random or white noise if it has zero mean, constant variance and is serially uncorrelated, denoted as U_t ̴ iidN (0, σ²) (Gujarathi, 2007).

Although the interest lies in stationarity of series, economic series are seldom stationary (non stationary). A classical example is in the random walk model (RWM). This is distinguished into random work without drift given as:

Y_t = Y_t-t + U_t ……………………………… 2.9

Y_t = Value of y at time t

Y_t-1 = value of Y_t lag 1 period

Equation (1) can be written as (Y_t-Y_t-1) = ∆Y_t = U_t ……………….. 2.10

Random walk with drift given as

Y_t = δ + Y_t-1 + U_t …………….. 2.11

where δ is the drift parameter. Equation (2.11) can also be written as,

Y_t - Y_t-1= ∆Y_t = δ + U_t …………… 2.12

Which shows that Yt drifts upward or downward depending whether δ is positive or negative. Equation (4) is an AR (1) model. The random walk model is an example of a unit root process. If we rewrite equation (1) as

Y_t = ρY_t-1 + U_t -1 ≤ ρ ≤ 1 ………….. 2.13

If ρ =1, equation (5) becomes a RWM without drift and we face a unit root problem, situation of non-stationarity where the variance of Y_t is non-stationary. If however the absolute value /ρ/ ≤ 1 the time series Y_t is stationary.

To achieve stationarity and avoid the phenomenon of spurious and nonsensical regression in the case of the unit root or RWM model i e the series is integrated of the order one I (1), differencing the series of I (0) has to take place. Most economic time series are I (1) and generally become stationary only after taking their first difference. If a series is differenced d times to become stationary, then it is integrated of order d, I (d).