Value Estimation and Comparison in Multi-Attribute Choice

The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?

In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.

Production of the chironomids of the Uchinsk Reservoir. [Translation of: Methods for the estimation of production of aquatic animals. (Handbook and papers) (ed. G. G. Vinberg) p226-239. Minsk, Vysheishaya Shkola, 1968]

The method of E.V. Borutski was used for determining the production of chironomids, that is, the dynamics of the number and biomass of the larvae were analysed, their death, a calculation of emergence and the number of deposited egg layings was carried out. In addition to the method of Borutski, the authors also calculated the seasonal dynamics of the number of larvae of the younger age stages in the microbenthos.