DR. TATIANA MAYSKAYA

I am an Assistant Professor of Economics at the International College of Economics and Finance and at the Faculty of Economic Sciences (Department of Theoretical Economics) in Higher School of Economics in Moscow, Russia

Research Interests: Information Economics, Economic Theory, Behavioral Economics, Experimental Economics, Networks

MY RESEARCH

Aug 03, 2017

Job Market Paper

I characterize the unique optimal learning strategy when there are two information sources, three possible states of the world, and learning is modeled as a search process. The optimal strategy consists of two phases. During the first phase, only beliefs about the state and the objective characteristics of information sources matter for the optimal choice between these sources. During the second phase, this choice also depends on how much the agent values different alternatives he has to choose from. The information sources are substitutes when each individual source is likely to reveal the state eventually and when the cost of information is low, and they are complements otherwise. Optimal delegation of information collection leads to the socially optimal outcome.

Oct 21, 2017

We present a dynamic model that illustrates three forces that shape the effect of overconfidence (overprecision of consumed information) on the amount of collected information. The first force comes from overestimating the precision of the next consumed piece of information. The second force is related to overestimating the precision of already collected information. The third force reflects the discrepancy between how much information the agent expects to collect and how much information he actually collects in expectation. The first force pushes an overconfident agent to collect more information, while the second and the third forces work in the other direction.

May 29, 2014

Many experiments demonstrate that an individual’s choice decisions are inconsistent. Following Luce (1959) and Block, Marschak, et al. (1960), a random choice approach to this problem has become very popular. It posits the existence of a probabilistic choice function that describes the probability of choosing an alternative from a given set of options. This paper contributes to the theoretical literature that narrows the class of random choice functions. Each alternative can be fully characterized by a vector in a n-dimensional space. A decision maker pays attention only to a randomly chosen subset of coordinates (or criteria) each time he faces a set of alternatives to choose from. Given this randomly chosen subset, he is perfectly rational, that is he chooses according to some strict preference ordering. For this procedure to be well-defined, the preference ordering must be separable with respect to criteria. In other words, the preference of the decision maker over any two alternatives should not depend on the characteristics that these alternatives have in common. This paper characterizes all systems of choice probabilities that are induced by this choice procedure.

Sep 26, 2017

Theoretical paper DeMarzo, Vayanos, and Zwiebel (2003) proposes a model of information aggregation in networks when individuals are subject to persuasion bias. The term "persuasion bias" refers to a particular form of boundedly rational behavior when individuals connected into a network do not account for repetition in the information they acquire. We argue that under the assumption that agents form their beliefs as a weighted average of all information available to them, the persuasion bias assumption is equivalent to a generalized version of the famous DeGroot model (DeGroot (1974)). We test the persuasion bias hypothesis against the (generalized) Bayesian updating model and find support for the persuasion bias hypothesis. We also found a positive correlation between how well a subject fits the generalized DeGroot model, compared to the alternative generalized Bayesian updating model, and their performance in the experiment. Data suggest that the generalized DeGroot model better accommodates other subjects' deviations from equilibrium, which explains the positive correlation.

Paper is on hold, major revision of the experimental part is required

Selective Exposure to Information

work in progress

This paper develops a dynamic model of information search in continuous time using Brownian motion to model gradual learning. In symmetric environment, the optimal strategy is to choose the source that most likely "confirms" the current beliefs: the individual will always prefer the information source that differentiates the most likely state from all other states.

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CONTACT INFORMATION

The best way to contact me is by email tmayskaya@gmail.com or simply put your message in the contact form below:

Phone: +7 (910) 402-0257 (Russia), +1 (626) 773-0382 (US)

National Research University Higher School of Economics,

26 Shabolovka street, Moscow 119049, Russia

office 3116-б

Office hours:

Tuesday, Thursday 3pm-4pm

National Research University

Higher School of Economics

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