We formulate a family of direct utility functions for the consumption of a differentiated good. This family is based on a generalization of the Shan-non entropy. It includes dual representations of all additive random utility discrete choice models, as well as models in which goods are complements. Demand models for market shares can be estimated by plain regression, enabling the use of instrumental variables. Models for microdata can be estimated by maximum likelihood
This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum ent...
Information measures arise in many disciplines, including forecasting (where scoring rules are used ...
We propose a data-constrained generalized maximum entropy (GME) estimator for discrete sequential mo...
We formulate a family of direct utility functions for the consumption of a differentiated good. The ...
We formulate a family of direct utility functions for the consumption of a differentiated good. This...
In this article, we describe the gmentropylogit command, which implements the generalized maximum en...
Methodologies related to information theory have been increasingly used in studies in economics and ...
J. D. Herniter's entropy model for brand purchase behavior has been generalized for A. Renyi's measu...
This paper contributes to the literature on hedonic models in two ways. First, it makes use of Queyr...
Based on the Jaynes principle of maximum for informational entropy, we find a generalized probabilit...
There are several main contributions of the work presented in this thesis. Specifically, we have: (1...
This paper establishes a general equivalence between discrete choice and rational inattention models...
Abstract. We present an approach to maximum entropy models that highlights the convex geometry and d...
International audienceWe consider the maximum entropy problems associated with Rényi $Q$-entropy, su...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum ent...
Information measures arise in many disciplines, including forecasting (where scoring rules are used ...
We propose a data-constrained generalized maximum entropy (GME) estimator for discrete sequential mo...
We formulate a family of direct utility functions for the consumption of a differentiated good. The ...
We formulate a family of direct utility functions for the consumption of a differentiated good. This...
In this article, we describe the gmentropylogit command, which implements the generalized maximum en...
Methodologies related to information theory have been increasingly used in studies in economics and ...
J. D. Herniter's entropy model for brand purchase behavior has been generalized for A. Renyi's measu...
This paper contributes to the literature on hedonic models in two ways. First, it makes use of Queyr...
Based on the Jaynes principle of maximum for informational entropy, we find a generalized probabilit...
There are several main contributions of the work presented in this thesis. Specifically, we have: (1...
This paper establishes a general equivalence between discrete choice and rational inattention models...
Abstract. We present an approach to maximum entropy models that highlights the convex geometry and d...
International audienceWe consider the maximum entropy problems associated with Rényi $Q$-entropy, su...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum ent...
Information measures arise in many disciplines, including forecasting (where scoring rules are used ...
We propose a data-constrained generalized maximum entropy (GME) estimator for discrete sequential mo...