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Showing posts with the label decision making

Decision Making as Output and Bounded Rationality

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  The classical economics theories proceed on the assumption of rational agents. Rationality implies the economic agents undertake actions or exercise choices based on the cost-benefit analysis they undertake. The assumption further posits that there exists no information asymmetry and thus the agent is aware of all the costs and benefits associated with the choice he or she has exercised. The behavioral school contested the decision stating the decisions in practice are often irrational. Implied there is a continuous departure from rationality. Rationality in the views of the behavioral school is more an exception to the norm rather a rule. The past posts have discussed the limitations of this view by the behavioral school. Economics has often posited rationality in the context in which the choices are exercised rather than theoretical abstract view of rational action. Rational action in theory seems to be grounded in zero restraint situation yet in practice, there are numerous restra
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Robert Aumann's Agreement Theorem: A Note

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  In 1976, publishing in the Annals of Statistics, Robert J Aumann made a contribution that perhaps is not just significant but provokes certain debate. He propounded what has to come be known as the Aumann agreement theorem. It is about agreeing to disagree or rather there would be no agreeing to disagree. To Aumann, two people let’s say 1 and 2 are said to ha have common knowledge of an event E if both know it, 1 knows that 2 knows about it and 2 knows 1 knows about it and 1 knows that 2 knows 1 knows about it and so on. Implied is the knowledge about the event is public with no secrecy. Carrying on, the theorem suggests, if two people have the same priors and their posteriors for an event A are common knowledge, then there posteriors are equal. If one were to decode the meaning, it implies given the absence of information asymmetry about an event, the two people in knowledge of the events would hold the same views even though their source of information would have differed in quanti
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Macroeconomics and Firm Decision Making

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  As observed in many past posts, economics has close linkages with real life. As practising managers or entrepreneurs economics helps in undertaking structured analysis and decision making. There are pointers towards increasing returns of decision making using structured tools like economics. Therefore, economics to a business practitioner would be indispensable. It is not that economics offers something new or novel. Many economic theories have been practiced consciously or sub-consciously over centuries by businessmen and others. What economists have done from Adam Smith onwards is to theorize the empirical observations. The empirical observations when aggregated would point to certain patterns which emerge as theory. For long, there were no distinction between macro or micro economics, something came into existence through the thoughts of John Maynard Keynes and his successors. Macroeconomics evolved in a different fashion in contrast to microeconomics. The former sounded glamorous
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Big Data and Diminishing Returns

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In many industries has become the buzzword. Scarcely a discussion seems to happen without touching upon the perceived advantages of big data. Firms seem to outcompeting with each other in collecting reams of data. The question however is the effectiveness of this data. The firm’s outcomes are determined primarily by the utilization of big data rather than collection of data per se. Ferreting out big data is a challenging task. Although the big data presents a data set that shows 10X or 100X in relation to existing mechanisms, it does not necessarily convey 10X or 100X worth of increase in insight. While the implication of big data is that quantity is paramount, the returns generated do not match the quantity of data generated. Big data too is subject to diminishing returns. Experts point out, it is not per se the data that should be big, but the primary factor that counts is the diversity of data. Even if datasets may be small, the amount of richness they provide when the
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