"...how is it possible that the most uncertain sector (agriculture) is actually explained by the most certainty-preferring model (the manufacturing sector)?"
Question: Is the discipline of 'Agricultural Economics', as it has developed since its inception and continues to this day, truly suited to the unique characteristics of agricultural businesses and systems?
AI's answer: Not entirely. While the discipline of Agricultural Economics, as it has developed since its inception, is indeed very useful, many of its components are built on a Neoclassical Economics framework that does not always fit the unique characteristics of agriculture. Therefore, to this day, this discipline continues to be "corrected" and expanded.
Agricultural Economics was founded from its inception with a noble ambition: to explain and improve the performance of the agricultural sector through the logic of efficiency and economic rationality. However, its analytical foundations are heavily borrowed from Neoclassical Economics—a framework born of the relatively controlled industrial world, not the fields subject to rain, pests, and biological uncertainty. This is where the first irony arises: the most uncertain sector is actually explained by the most certainty-preferring model. While classical studies, such as that of Theodore W. Schultz, have shown that farmers are “rational” within their limits, this rationality is clearly not as simple as a neat production function on a blackboard.
Furthermore, agricultural economics tends to treat farmers as small firms seeking maximum profits, when in reality they are households balancing production, consumption, risk, and even social values. This assumption has long been criticized by Alexander Chayanov, who emphasized that the economic logic of farm households is not identical to corporate capitalism. However, rather than embracing this as the primary foundation, many analyses persist in imposing a perfect market model on a rural context characterized by limited credit, asymmetric information, and dense social relations. The result? Models that are mathematically elegant, but often clumsy when confronted with rural realities.
As reality becomes more “resilient,” the discipline has begun to adapt by borrowing from other perspectives, such as Institutional Economics (for example, through the work of Douglass C. North), which recognizes that rules of the game, norms, and power shape economic behavior. Behavioral Economics, on the other hand, demonstrates that farmers’ decisions are not always rational in the strict sense, but are instead influenced by biases, experience, and risk perception. In fact, approaches such as the Agricultural Innovation System have emerged that implicitly recognize that agriculture is not simply about production and prices, but about networks of actors, knowledge, and institutions. Ironically, these approaches often appear as "additional" approaches, rather than as mainstream approaches that replace old assumptions.
In the context of developing countries like Indonesia, this tension is even more pronounced. Smallholder farmers operate in an environment far from ideal market assumptions, with a heavy reliance on public policies, government programs, and local social networks. However, agricultural economic analysis often continues to proceed from the logic of individual efficiency and market mechanisms, as if villages were miniature competitive markets. It is not surprising that many policies based on this analysis end up with recommendations that sound rational on paper but are difficult to implement or even counterproductive in practice. At this point, agricultural economics appears to be a discipline continually trying to explain a reality that is reluctant to follow its logic.
Thus, the question is not whether agricultural economics is "wrong," but rather whether it is honest enough to acknowledge its limitations. So far, the answer has tended to be half-hearted: there have been attempts to broaden perspectives, but the basic framework inherited from neoclassical economics remains dominant. Perhaps what is needed is not mere theoretical patching, but the courage to accept that agriculture is a complex socio-ecological system—one that cannot be reduced to supply and demand curves alone. Until that point is reached, agricultural economics will remain in a somewhat awkward position: supremely confident of being a science, but secretly relying on assumptions that are increasingly difficult to maintain.
******