Zobrazeno 1 - 10
of 65
pro vyhledávání: '"KOVACH, MATTHEW"'
We study how a Bayesian decision maker (DM) learns about the biases of novel information sources to predict a random state. Absent frictions, the DM uses familiar sources as yardsticks to accurately discern the biases of novel sources. We derive the
Externí odkaz:
http://arxiv.org/abs/2309.08740
Autor:
Kovach, Matthew, Tserenjigmid, Gerelt
We propose a generalization of Quantal Response Equilibrium (QRE) built on a simple premise: some actions are more focal than others. In our model, which we call the Focal Quantal Response Equilibrium (Focal QRE), each player plays a stochastic versi
Externí odkaz:
http://arxiv.org/abs/2304.00438
We introduce and characterize inertial updating of beliefs. Under inertial updating, a decision maker (DM) chooses a belief that minimizes the subjective distance between their prior belief and the set of beliefs consistent with the observed event. I
Externí odkaz:
http://arxiv.org/abs/2303.06336
We study conditioning on null events, or surprises, and behaviorally characterize the Ordered Surprises (OS) representation of beliefs. For feasible events, our Decision Maker (DM) is Bayesian. For null events, our DM considers a hierarchy of beliefs
Externí odkaz:
http://arxiv.org/abs/2208.02533
Autor:
Kovach, Matthew, Tserenjigmid, Gerelt
We provide the first behavioral characterization of nested logit, a foundational and widely applied discrete choice model, through the introduction of a non-parametric version of nested logit that we call Nested Stochastic Choice (NSC). NSC is charac
Externí odkaz:
http://arxiv.org/abs/2112.07155
Autor:
Kovach, Matthew1 (AUTHOR) mlkovach@purdue.edu
Publikováno v:
Economic Theory. Aug2024, Vol. 78 Issue 1, p155-180. 26p.
Autor:
Kovach, Matthew, Suleymanov, Elchin
We explore the ways that a reference point may direct attention. Utilizing a stochastic choice framework, we provide behavioral foundations for the Reference-Dependent Random Attention Model (RD-RAM). Our characterization result shows that preference
Externí odkaz:
http://arxiv.org/abs/2106.13350
Autor:
Kovach, Matthew
Models of updating a set of priors either do not allow a decision maker to make inference about her priors (full bayesian updating or FB) or require an extreme degree of selection (maximum likelihood updating or ML). I characterize a general method f
Externí odkaz:
http://arxiv.org/abs/2102.11429
Autor:
Patel, Kaizad F., Rod, Kenton A., Zheng, Jianqiu, Regier, Peter, Machado-Silva, Fausto, Bond-Lamberty, Ben, Chen, Xingyuan, Day, Donnie J., Doro, Kennedy O., Kaufman, Matthew H., Kovach, Matthew, McDowell, Nate, McKever, Sophia A., Megonigal, J. Patrick, Norris, Cooper G., O'Meara, Teri, Peixoto, Roberta B., Rich, Roy, Thornton, Peter, Kemner, Kenneth M., Ward, Nick D., Weintraub, Michael N., Bailey, Vanessa L.
Publikováno v:
In Geoderma April 2024 444
Autor:
Kovach, Matthew
This paper provides a behavioral analysis of conservatism in beliefs. I introduce a new axiom, Dynamic Conservatism, that relaxes Dynamic Consistency when information and prior beliefs "conflict." When the agent is a subjective expected utility maxim
Externí odkaz:
http://arxiv.org/abs/2102.00152