My Academic Interests and Achievements

I was trained in economics (theory and thought in particular) but took to econometrics and statistics for my professional survival. At IIT, Kharagpur, I was also trained in regional planning, which may be considered as a practical side of economics in keeping with space (which is conspicuously absent from the traditional economic analysis), geography, sociology and other associated aspects of reality. This blending also reinforced my interest in institutional economics. In due course, I turned to computer programming because econometric and statistical applications need a lot of data analysis that cannot be accomplished manually. Many ideas that I wanted to introduce into econometric/statistical analysis could not be implemented (or experimented with) without being able to solve usually non-traditional optimization problems by non-traditional optimization methods. So, I had to turn to global optimization. I was also influenced by the prediction made by Alfred Marshall that ultimately economics has to learn a lot from biology rather than physics. This prediction I saw come true in the biologically inspired population methods of global optimization. I became interested in Evolutionary Economics as well, introduced it to the MA syllabus at North-Eastern Hill University, Shillong and taught it for several years before my retirement. I realized that institutions and memes really matter to make meso-economics that translates the inspirations and endeavours of socio-economic agents at micro level into the macroeconomic features of the economy and the society. Evolution of institutions is a serious and absorbing field that economists should turn to. I tried to share all these ideas with my colleagues/students and incorporated many of them into optional courses for MA students at NEHU - courses in Evolutionary Economics and Institutional Economics in particular. However, after my retirement the course on Evolutionary Economics in particular was dropped from the syllabus, possibly because none was interested in teaching it or the course was thought to be irrelevant or unmanageable. Yes, one would agree that Evolutionary Economics is far off the dominant paradigm.

Economics is the science and arts of managing the society in matters of material prosperity and well being of the people. There is a view, championed by the scholars of establishment (orthodox) economics, that such management of the society is self-organizing; the market as an institution, under the conditions of private ownership of resources and driven by the selfisness of economically rational agents, it accomplishes the task of managing the society in most fair (just) and efficient manner. There are others (scholars of heterodox economics) who doubt the self-organizing capability of the market, cite examples of mild to severe instances of market failure, and plead for public intervention in varying degrees. Both the schools have argued for their own stand and critically analyzed the arguments of the rival school of thought. Academically, economics is a well-organized set of such arguments.

No particular school of thought has been able to defend its stand indubitably. After the Great Depression of 1930s, econometrics arose as a discipline to address the validity of economic arguments in view of the empirical reality. However, the scholars had two (leading) views with regard to the scope of econometrics. The one held that formulation of economic theories (testable propositions) should be out of the scope of econometrics. Econometrics should concentrate on testing the given hypotheses and developing new methods for such an endeavor (Cowles Foundation scholars). The others were not happy with the economic theories and wanted that econometrics should also be used to formulate economic theories (Institutional economists in general - leading scholar : W.C. Mitchell). The leading endeavor favoured the first stream, although soon it degenerated so as to dissatisfy one of its founding fathers (Ragner Frisch).

Optimization is a mathematical enterprise to determine the magnitude of decision variables that provide the best solution of a problem (mostly mathematically expressed objective function or functions), possibly under some constraints. In a sense, all endeavors to estimation in econometrics/statistics are exercises in optimization. The problem may have multiple optima or many local optima. Global optimization addresses the problems with multi-optima, nonconvex (nonlinear) problems that might not be differentiable. Many scholars have found that biologically inspired population methods of global optimization have a potential to resolve such difficult problems.

There is a school of thought (led by Herbert A. Simon) that doubts the ability of an agent to perceive and mathematically formulate an objective function to be optimized. This is more so when the objectives relate to a group of agents or the society (such as social welfare function). However, there are others who argue that such optima may be characterised by some symptom or indicator functions and a satisficing solutions to those symptom functions may be used as proxy solution to the problem. It boils down to multi-criteria decision-making or multi-objective global optimization. This field is a hotbed of research.

All these currents combine into a larger flow that makes economics a lively research subject. I have worked with all my limitations to understand and participate as a conscious particle in those currents. I have enjoyed it throughout my life. It has been my passion rather than profession.