Building economic models and measures of search

Economics provides an intuitive and natural way to formally represent the costs and benefits of interacting with applications, interfaces and devices. By using economic models it is possible to reason about interaction, make predictions about how changes to the system will affect behavior, and measure the performance of people's interactions with the system. In this tutorial, we first provide an overview of relevant economic theories, before showing how they can be applied to formulate different ranking principles to provide the optimal ranking to users. This is followed by a session showing how economics can be used to model how people interact with search systems, and how to use these models to generate hypotheses about user behavior. The third session focuses on how economics has been used to underpin the measurement of information retrieval systems and applications using the C/W/L framework (which reports the expected utility, expected total utility, expected total cost, and so on) - and how different models of user interaction lead to different metrics. We then show how information foraging theory can be used to measure the performance of an information retrieval system - connecting the theory of how people search with how we measure it. The final session of the day will be spent building economic models and measures of search. Here sample problems will be provided to challenge participants, or participants can bring their own

A new approach to causality and economic growth.

This paper examines the issue of causality in cross-sectional empirical models of economic growth. Using an approach to determining causal structures based on tests for conditional independence in sets of variables, we uncover alternative causal structures that are consistent with the correlation pattern of the variables in the data. We use these methods to develop alternative causal empirical models of economic growth. One of our consistent findings is that we can rule out the possibility that equipment investment causes growth. Our search procedure leads naturally to a structural model with latent variables which we then estimate. The results of our estimation are broadly consistent with traditional models of economic growth augmented for human capital.Economic development ; Econometric models

In search of synergies between policy-based systems management and economic models for autonomic computing

Policy-based systems management (PBM) and economics-based systems management (EBM) are two of the many techniques available for implementing autonomic systems, each having specific benefits and limitations, and thus different applicability; choosing the most appropriate technique is the first of many challenges faced by the developer. This talk begins with a critical discussion of the general design goals of autonomic systems and the main issues involved with their development and deployment. The discussion forms a backdrop for a detailed evaluation of the two techniques, in which the concepts underpinning each of PBM and EBM are reviewed and placed into context with each other as well as with the other popular techniques for autonomic computing. After considering the operation and suitability of the techniques in isolation, the focus shifts to look at how PBM and EBM could be combined in complementary ways to achieve more sophisticated and versatile control systems whilst keeping the complexity and human-configuration input low. There is then some deeper explanation of the features of PBM and a specific technology is briefly presented as a case example, focusing on its novel and advanced features. The talk ends by looking to the future of autonomic systems; identifying a possible next set of challenges and considering the roles that PBM and EBM may play in addressing these

Market equilibrium with search and computational costs

Although it is an empirical regularity that in the trade of homogeneous goods there is persistent price dispersion and buyers search for low-priced items, theoretically we find that in market equilibrium, when buyers are optimisers (the neo-classical framework), these regularities do not occur. Summing this undesirable theoretical result to the fact that the computation of optimal strategies is demanding, the relevance of using optimisation models in rationalising human behaviour is put in question. Even so, Lucas (1981) claims that optimisation models should not be abandoned because only these are “able to isolate those aspects of behaviour that remain invariant to policy shifts from those that do not”. In this work, following Lucas’ claim, we introduce economic agents as having computational limitations in the neo-classical optimisation model, which is new in the literature. As a result of this alteration to the model, in market equilibrium, we observe both price dispersion and search when buyers have information and computational limitations.Computational limitations, Optimisation, Search, Market equilibrium