Causality in the context of analytical models and numerical experiments

Intuition tends to guide model formulation, as it is generally impossible to consider all dimensions of a problem. The ability to surprise, heightening the focus on paradox and the contradiction of reality, is therefore more useful than a literal representation of reality. While numerical experiments are useful in exploring patterns not well suited to analytic approaches, features of the model that underlies the experiment determines the experiments’ ability to provide insight and offer surprise.     

Sequential Solutions to Capacity‐Planning and Pricing Decisions*

Ideally, firms should jointly solve capacity‐planning and product‐pricing problems. In practice, informational limitations and cognitive bounds may force firms to sequentially solve the two problems. For example, a firm may plan capacity using limited demand information, and update prices subsequently once additional demand information becomes available. In a simple setting, we characterize the economic loss due to such sequential planning. We use simulation experiments to assess the extent of this loss in more complex settings. We find a relatively low loss if the firm plans for capacity using limited demand information and subsequently adjusts product prices to reflect realized market conditions. However, even “reasonable” restrictions on the subsequent price adjustment (e.g., constraining adjusted prices to always exceed full cost) lead to significant economic loss.     

The Effects of Biasing Performance Measurement Systems on Incentives and Retention Decisions

We examine a principal–agent setting in which the principal uses a performance measurement system for multiple purposes—to provide incentives and for retention decisions. The principal chooses the nature and extent of bias in the system, which determines whether the performance report is stringent, neutral, or lenient relative to the unobservable actual outcome. We show that when the report is used only for incentive purposes (an incentive role), stringency alleviates moral hazard. On the other hand, when the principal's objective is to minimize the cost from incorrect retention and firing decisions (a fit evaluation role), there is a demand for leniency. Surprisingly, however, we show that adding a fit evaluation role to a system serving an incentive role can accentuate the demand for stringency because stronger incentives can also indirectly improve retention decisions.     

Legal Treatment of Abuse of Dominance in Indian Competition Law: Adopting an Effects-Based Approach

Review of Industrial Organization - Abuse of dominance investigations around the world are often form-based, primarily centred on the pre-requisite of dominance. This may lead to false positives or...