It is that time of the academic year when most instructors prepare to begin teaching a new cohort of perceptive, young minds joining university campuses. As an instructor of economics, it is fascinating to welcome students, introduce them to higher possibilities of learning, and teach foundational concepts using illustrative cases based on real-world scenarios.
Economics in the larger field of social sciences, and over the last century or so, has occupied a vital space in understanding different aspects of human behaviour.There remains little scope for disputing this fact. However, the method of teaching, learning and studying basic economics still provokes debates among members both within and outside the econ-tribe.
These debates have intensified since the time of the great recession (2007-08), particularly with regard to the relevance of mathematical models and the extent to which they can help us provide answers to a complex web of social and economic problems in an age of uncertainty. This critical dialogical process has allowed distinguished economists like Jean Tirole, Paul Krugman, and Dani Rodrik to argue for greater public dissemination of economic ideas and a strengthening of the weakened social contract between the economist and civil society. At the same time, on the methodological relevance of modelling in economics, there remain some important points to be made.
Modelling in basic economics plays an instrumental role in explaining the essential workings of a given society. Economic models, as Dani Rodrik argues, despite their “simplicity, (mathematical) formalism and neglect of many facets of the real world”, remain integral to the discipline. What’s important to emphasize here though is that any given model, whether testing for the effectiveness of a tax policy or the role of tariffs in creating new jobs, may seem to work only in a given context. Different contexts can drastically affect stated outcomes of models. An under-acknowledgment of this contextual condition in modelling often gets most economists (advocating for “a” model as “the” model) into trouble. Analysing the effective role of markets in distributing scarce resources and gains between agents, buyers and sellers in a particular society can involve the use of models to explain the relationship of any one aspect of the agent-market relationship, assuming other conditions to be constant. Thus, any model can (at best) help us focus on particular causes to show their effects through the system in a given period. To achieve this, a modeller needs to operate from an abstract, artificial position to study the extent of a causal degree of relationship between social variables, which, from their respective real-world position, would be difficult (if not impossible) to analyse on their own.
For example, a simple supply-demand model of a given good/service can help us explain the relationship between the price of that good/service and, let’s say, the total quantity demanded/supplied. This is perhaps one of the simplest and most useful models studied in basic microeconomics. The model seems operational only under certain given conditions (assumptions of “perfect competition”, “rational” human behaviour) to satisfy essential mathematical axioms as a conceptual requirement. It remains highly possible that as conditions of such assumptions change, the results of the model change in such a revised context. The effectiveness of economic models remains, thus, closely connected with the nature and quality of assumptions it works under.
One of the ways by which most debates on the validation of economic models, and the test of their real-world applicability, may be better studied is by incorporating greater use of “narratives” in the method of analysis itself. Narratives here may simply refer to humanist, contextual perspectives accumulated from subjects or recipients who are most likely to be affected by any given model’s application, especially when applied in the form of a policy.
For example, when any government increases the tariffs of a particular basket of goods (or services) with the expectation of helping to protect domestic industries, it remains important to see whether a target group actually witnesses an increase in its productivity or not.
Most economic models studying the effectiveness of tariffs in improving the aggregate productivity of any product may reflect on how there is very little empirical support for such a trade policy measure. The role of narratives here would be to draw out perspectives from target groups of domestic manufacturers and facilitate such observed findings as part of a feedback mechanism, testing the effectiveness of the policy. With a complementary use of narratives over and above the mathematical framework of models, it is further possible to determine under what kind of conditions a policy may or may not yield a desired set of outcomes.
Economists and those training to become one can, therefore, be seen merely as social engineers or modelling architects representing different real-world scenarios. Students and teachers of the discipline can hardly see economics as some form of an exact science but one that simply uses mathematics and narratives as mediums of communication. Cultivating an attitude of humility with a quest to constantly experiment with methods within different contexts are critical values in training students of economics to further strengthen the social contract between the economist and civil society.
Deepanshu Mohan is assistant professor of economics, at O.P. Jindal Global University.