Suppose, in a business you invest 1,000 and get 1,500 as return. You have 500 as net profit. Suppose you expand on the business by additionally investing 1,000. Now you get a net profit of 800 instead of 500.Would you consider the decision of this additional investment as a wise decision? We raised this question in a meeting of a mixed group, consisting mainly of social workers working with farmers, fisherfolk, pastoral, and tribal communities. We were discussing the economics of livelihood for people dependent on nature. Some of them said, Yes. We will invest 1,000 more because by doing so, our net profit goes up. Some of them said, No. This is not wise! Because, even if net profit goes up, it is not in proportion to the additional investment. The ratio actually decreases with the additional investment.

Which of the answers is correct? Is it really wise to make the additional investment or not? Both the groups certainly used logic which was right in their context. Both the groups were doing a careful costbenefit analysis. But, one group was using net profit, defined as returns minus the cost. The other was using a ratio, defined as returns divided by the cost. Interestingly, even within the latter group, individuals working with farmers appeared to think in a different way than individuals working with tribal communities. For this article, we will use the words cost and benefit to describe the actualities of a deal, and the words investment and returns to refer to the perceptions and strategies of an investor.

Although the dilemma of using difference or division, or rather when one should use difference and division, could seemingly be solved by employing common sense, we believe it is a fundamental question that requires serious thought. Many people may not even think that it is an important question, since business wisdom lies in reducing costs and increasing returns. Theoretically, if business wisdom is applied in real-life situations, both difference as well as ratio willincrease. But, this does not always work. The above example, although very simple, demonstrates that optimising difference and optimising ratio can lead us to diametrically opposite decisions. The question is not only important in economics, but also in biology. Evolutionary biologists frequently worry about budgets, where energy, time, health, longevity, or reproductive success is the currency. Only the ones with a profitable budget will survive. As a result, an intuitive sense of optimising has evolved in animals. It is unlikely that humans are an exception to the evolved intuitive optimisation mechanisms. But, humans also have conscious thinking and theorisation, so we should seek a logical explanation for our decisions in our conscious beliefs and theories. So, we wanted a logical answer to the question of when to divide and when to subtract.

We then started scanning economics textbooks and asking economist friends about when to take the ratio and when to take the difference in the costbenefit analysis. The economists we consulted ranged from teachers of first-year economics in colleges to senior economists working as consultants in multilateral organisations. Surprisingly, we did not get any definitive answer. The responses included Use ratio; Use difference; We always use ratios, but I dont know why; Use either, what difference does it make? I dont know; and Frankly speaking, I never thought of this question. The theory of probability in mathematics begins with two simple rules that tell us when to add probabilities and when to multiply. We thought there would be such simple rules that instruct when to use difference and ratio. However, we learnt that such rules do not exist, or even if they do, most economists, at least in our sample, do not seem to know them.

Use of Ratio and Difference

So, how does it matter whether we take difference or ratio? As we discussed further in that group, some inquisitive individuals asked. Are we limited to only one business? What if we start a second unit of the same business and invest another 1,000 in it, instead of going from 1,000 to 2,000 in the same unit? With two independent units of the same business, we will earn 3,000 with an investment of 2,000. This is better than earning 2,800 from 2,000. This turned out to be the key question, and it gives a simple answer to the fundamental question as well. If you have multiple investment opportunities, then go by the ratio, and if you have a single opportunity or your possible investment opportunities are almost saturated, then you should go by the difference. The same can be demonstrated by a more rigorous mathematical proof given in Box 1.

A simple generalisation is that whenever a law of diminishing returns applies and there is an overhead cost in the endeavour, the difference optimum is typically much to the right of the ratio optimum (Box 1 and Figure 1). Thus, to maximise net benefit, it is necessary to invest much more in terms of money or efforts. Whereas, in maximising the benefit to cost ratio, it is a better strategy to have a smaller investment per unit, but to increase the number of units. In simple words, when there is one investment opportunity, it is desirable to extract the maximum output from the unit, even at a higher cost. Whereas, if many replicates of the unit are possible, it is desirable to invest less per unit, but increase the number of units. How much to invest in a unit depends on the overhead costs too. With greater overhead costs of a unit, one needs to invest much more in the unit. The higher the overhead investment, the lower the difference between ratio optimum and difference optimum. The investment still remains lower in ratio optimisation than in difference optimisation. So, the choice of model (whether to use difference model or ratio model) and the optimum investment per unit depends upon how many investment opportunities you have and the overhead cost.

In the case of Indian agriculture, a farmer most commonly has only one investment opportunity: their own land. Therefore, it is natural to use a difference model and extract maximum output, even at a higher cost. On the other hand, in the case of livestock in the Indian context, more investment opportunities (number of animals) are available, so the natural tendency should be to invest little per animal, but let the number of animals increase on their own.

Domesticated herbivores in India typically grazed on common pasture lands (Roy 1997). Therefore, keepers have little overhead as well as running costs. In a ratio model, when the denominator is near zero, the ratio is always high and, therefore, there is no need to worry so much about the productivity of an individual animal. In the context of a typical Western dairy farming model, where there are private ranches, a ranch becomes the unit, and since the owner has a single unit, there would be an attempt to increase the net productivity of the unit even at a higher investment. In this model, on the one hand, investment on owning the huge piece of ranch increases the overheads, making high productivity necessary. On the other hand, long-term assured ownership is a good motivation for worrying about sustainability. Therefore, there is no option but to increase the investment per animal, at the same time, keeping the number of animals limited.

In that context, cattle are more like a crop and land is a limiting factor. This sets the ground for a difference model to work in which the investment as well as productivity goes up. Thus, the economics of modern Western dairy farming and traditional cattle keeping is fundamentally different, and therefore, the breeds and characteristics of animals supporting the two economic models are also fundamentally different. In a ratio model that is typical of traditional Indian animal keeping, people will tend to select animals requiring near zero inputs without worrying much about their productivity. In the modern Western private ranching system, there would be a selection for high-productivity animals even if they require greater inputs. The difference in productivity in different varieties of animals originates in the selection operating on these animals. Animals bred for generations in the difference model become more productive, and those under the ratio model become more hardy and resilient, but less productive.

Innate and Intuitive Economics

Evolutionary ecologists have shown that even the so-called dumb or unintelligent animals with tiny brains make very careful costbenefit judgments. For example, a parasitoid wasp typically lays eggs on the caterpillar of a host insect. The number of eggs to be laid on a given caterpillar is a complex investment decision. The optimum egg investment per caterpillar unit depends upon a number of factors, including the expected remaining lifespan of the female, the residual egg-laying capacity, the probability of finding more host caterpillars, whether a caterpillar found already has eggs laid by a competing female, and so on. Mathematical ecologists have shown that wasp females are able to take a complex economic decision (Heimpel et al 1996: 241020).

Considering the astonishing innate mathematical ability of a wasp, it should not be surprising that even illiterate humans do take wise economic decisions even when they have not studied economics formally. Humans appear to make complex costbenefit analysis while making several decisions where the currency need not always be money. Time, labour, energy, sex, reproductive success, survival, or social status work as currencies in human intuitive economic calculations (McNamara and Houston 1986: 35878), but it is beyond doubt that using costbenefit optimisation is an innate tendency of animals (Parker and Smith 1990: 2733; Smith and Winterhalder 1992: 2560) and that legacy continues in humans. Formal education is not a primary requirement for making such complex calculations. While doing formal economics, some of the currencies can be put in numbers as equivalents of money, whereas for other currencies, it is difficult to set up an equivalence with money. Herein lies the difference between intuitive economics and formal economics. Nevertheless, the fundamental principles of costbenefit analysis, including the above stated rule about ratio versus difference, need not be different.

If asked directly, farmers do not know what a difference model is and what a ratio model is, but they appear to use the right model in the right context. In another study published earlier (Bayani et al 2016), we tested the differential predictions of the difference versus ratio models on a set of farmers (Watve et al 2016: 86167). The results showed very clearly that farmers unanimously used the difference model. Thus, the farmers appeared to have an intuitive knowledge of some principles of economics, which our educated economists have not yet clearly figured out.

Hybrid Crops vs Crossbred Cows

The green revolution entered India in the late 1960s. It was brought in by government efforts, with the help of visionary scientists. The government wholeheartedly promoted the use of hybrid seeds, chemical pesticides, and fertilisers, bringing about changes in traditional farming practices. The new agricultural practices needed more investment not only in purchasing hybrid seeds, but also for chemical fertilisers, pesticides, and irrigation. Hybrid or high-yielding varieties of seeds certainly required more care, since they were more susceptible to climatic variation as well as diseases and pests. Within a decade, almost the entire country changed agricultural practices. Individual farmers invested more in order to get more returns, although the benefit to cost ratio might have actually declined. It should also be noted that although there were many incentives and promotional schemes launched by the government, nothing was made mandatory. The farmers largely accepted the green revolution in a short span of time.

More recent is the specific case of Bt cotton. India is the worlds largest cotton producing country (Statista 2019). Bt cotton was introduced in 2002, and it took a few years to be known. Soon, Bt cotton percentage in terms of production area boomed up from 6% in 200405 to 81% in 200910. In less than eight years, 93% cotton farmers started using Bt cotton (ISAAA 2014). The change was so rapid that non-Bt cotton seeds were practically out of the market, and many indigenous varieties were threatened to extinction (Kumarnath 2016). More generally, hybrid or high-yielding varieties have replaced indigenous varieties, and a special drive is needed to conserve indigenous varieties.

In contrast, if we see the case of livestock, Operation Flood, launched in 1972, was a project of Indias National Dairy Development Board (NDDB), which was the worlds biggest dairy development programme. High milch foreign breeds were introduced in the cattle population. Programmes like artificial insemination (AI) were launched, with substantial thrust from government and non-governmental agencies. Concerned agencies worked with targets and tried to reach out to every doorstep to inseminate local cows with high-quality semen (NDDB 2015). Furthermore, there were moves to improve feed, fodder and veterinary services. But, the efforts precede Operation Flood since even before Operation Flood, there were active efforts to eradicate and replace indigenous cattle. For example, in Kerala, castration of local bulls was made mandatory under the Kerala Livestock Improvement Act of 1961. Under this act, any bull of an indigenous breed reaching sexual maturity had to be castrated and a task force set up to implement the castration operations at a mass scale. Nothing comparable to this was ever done for Bt cotton or any high-yielding crop variety. Even doorstep-level facilitation and persuasion was never needed for the green revolution. In spite of all such efforts, the trend in the growth of exotic/crossbred cattle remained poor, in contrast with the trends in high-yielding crop varieties (Figure 2).

Although there has been a steady decline in indigenous cattle percentage and a steady increase in exotic/hybrid cattle, the percentage share of exotic/crossbreed cattle has increased only by 14% in two decades (from 1992 to 2012). In comparison with the 93% spread of Bt cotton in eight years, this increase is meagre. Particularly notable is the vast majority of the so-called non-descript cattle (DAHD 2012). There have been excellent indigenous cattle breeds, such as gir, that are high-yielding, but even they were never abundant across the country. Majority of the population was happy with the low-yielding one, but self-sustaining hardy cattle that needed little care and survived droughts, diseases, and parasites (Mazoomdaar 2013). These animals performance was poor if seen through the difference model, but excellent by the ratio model because theinvestment needed was negligible.

Thus, there is a stark contrast between peoples response to high-yielding crop varieties and high-yielding animal breeds. They seem to have accepted the former in a short time, but have resisted the latter even after the option has existed for a long time. We feel that the difference lies in the economic model of optimisation used. With the difference model predominating agricultural economics, they are ready to invest more money and efforts and go for higher yields. But, with animals, they are happier with small yields coming out of near zero investment because they are using a ratio model. This choice of the model is completely innate and intuitive. Nobody did any calculations consciously. Such calculations must be as natural and built-in as the wasp optimising her egg investment. Now, it is high time that formal economics recognises the innate economic models of people.

Ratio Model in Agriculture

The ratio model can be appropriate for agriculture under a set of conditions. In slash-and-burn agriculture, where new land can be brought under cultivation, that is, new investment opportunities can be created, a ratio model will work better. Also, in a society that is free to expand the agricultural land, a ratio model is appropriate. We see this difference in the history of modern agriculture too. In the 1960s, the green revolution took quick and firm roots in India, but it did not succeed in much of Africa, although its promotion was attempted (Pingali 2012: 12,305). For the 1960s population-to-land ratio in much of Africa, people could rely on the ratio model and were not interested in difference optimisation. As the population grew, and there was a clear demarcation of agricultural lands and land saturation, the difference model started gradually taking over, and the response to the green revolution improved.

Today, we see substantial and sincere efforts to promote zero-budget agriculture, which is ecologically sound (Palekar 2007). We raise no doubts about the ecological and sustainability-related merits of zero-budget agriculture. But, the response from the farmer community to this model so far is extremely limited. Out of the 140 million hectares (ha) of agricultural land in India (Directorate of Economics and Statistics 2014: 305), farmers have committed to organic farming in only 0.51 million ha (PoliticalTruth 2016). The reason is likely to be that the promoters are trying to promote ratio optimisation (Misra 2007), whereas the farmers community has a difference model in their intuitive calculation. It would be necessary for the promotion of organic farming to rework its economics and see how it performs in a difference model. If Misras (2007) claim is correct, both the ratio and difference models could be more favourable in spiritual agriculture. But, unless it is propagated by projecting its economic superiority by the difference model, farmers are unlikely to adopt it on a large scale.

When Two Optima Contradict

The contrasting example comes from the rapidly rising dairy industry. When a dairy company or cooperative is established, it has invested substantial amounts into overhead costs like land, establishment cost, machinery, storage, and supply chains. Although the dairy industry might still be using the ratio model, a rise in overheads shifts the optimum to the right. The dairy unit has certain other limitations. It can take raw material from several cattle or buffalo owners. But, since milk is highly perishable, there is a limit to the area from which it can transport raw milk. Within this area, they need to maximise the incoming flow. Therefore, the industry is interested in a higher investment and higher returns model. This goes in a subtle conflict with the animal owners. The optimum for the industry is far to the right than the optimum for animal keepers (Figure 3, p 31). As a result, the industry would have to take special efforts to motivate people to increase their investment per animal and improve the returns per animal. For this, they need to give incentives, attractive offers, free veterinary services, animal insurance, assured market or some other means to motivate them. Only with such efforts, the high-yielding varieties can be sustainable by peoples intuitive economics.

As a result, in the milk catchment area of large dairy units, high-yielding breeds are expected to be better accepted by people. In the absence of incentives and active promotion by organised dairy agencies, people are unlikely to accept and maintain these varieties on a mass scale and over a long time. This prediction of the hypothesis matches with the statistical trend. The spread of cross-bred varieties closely follow the rise in the dairy industry (Figure 4).

Dairy Industry and Breed Selection

The organised sector of the Indian dairy industry started growing post-independence, and in the early 1960s, the share of the organised sector in total milk procurement was only 3.7%. By the mid-1990s, it reached 12% (Sharma et al 2002). By 2008, the share of organised milk production was 23.39%, and by 2015, it was 26.26%. The pattern of this rise is closely followed by the pattern of the number of cross-bred cattle reflecting acceptance of cross-breed cattle by people. Although the jersey cow was introduced in India long ago in 1856 (Chako 1994), systematic breeding programmes began only in the 1960s. Thereon, it followed the growth curve of the organised dairy sector very faithfully. Even geographically, the statewise success of artificial insemination programme shows a good positive correlation (r = 0.64, p = 0.018) with the number of organised sector units and the total capacity (Figure 5). The correlation remains significant even after correcting for the area of the state. Thus, much of the spread of high-yielding cattle is catering to the economic interest of the organised dairy industry rather than the economic interest of individual cattle keepers.

Our emphasis on the use of ratio versus difference models of intuitive economics does not mean that other factors, such as government policies, market infrastructure, advertising andsocio-politicalcultural acceptance do not play any role in the growth and acceptance of high-yielding varieties. But, it gives the right platform on which the effects of every factors can be rightly mapped. If planning is based on the appropriate economic model, the implementation is more likely to be effective.

Conclusions

For any microeconomic model, it is necessary to have clarity about whether one should use a ratio model or a difference model. People appear to use the two models discriminately and appropriately. Formal economics needs to realise this, which would help the planning of large-scale operations in the right direction and in the most effective way.

This article is neither to support genetically modified (GM) crops, nor to oppose better animal husbandry practices. It demonstrates how the underlying innateintuitive economic model used by ordinary people dominates the outcome. For promoting any new technology or practice on a nationwide scale, it is necessary to understand peoples economics without which huge efforts can turn unproductive. The whole motive of this analysis is to understand how microeconomics at the farmers level affect trends in a bigger picture. It is surprising that such an analysis has not been the centre of thinking in this field. Huge amounts of efforts have gone into developing better breeds, sperm banks, artificial insemination techniques, and the like. A number of excuses are given to explain the relative failure of cattle-breed improvement. The predominant excuses include the relatively high care required for cross-bred cows, the need for continued cross-breeding programme since the quality is not maintained in subsequent generations and the lack of awareness and education in people (Sainath 2012; Ramdas and Ghotge 2006). Interestingly, all of these factors were applicable to hybrid crops as well, but they did not prevent their acceptance and spread (Koshy 2011).

It is necessary to differentiate between reasons and justification/excuses, which can be revealed only through insightful, evolutionary socio-economic investigation. Advancement in the field of technology needs to be accompanied by an equally intensive, scientific, unbiased and insightful research in peoples behaviour for a socially important policy to be successfully implemented over a large population like ours.

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Difference, Division, Desi Breeds : Intuitive Economics and the Outcome of an Operation - Economic and Political Weekly