Entropy maximization as a basis for information recovery in dynamic economic behavioral systems - George Judge (Econometrics, 2015)
As a basis for information recovery in open dynamic microeconomic systems, we emphasize the connection between adaptive intelligent behavior, causal entropy maximization and self-organized equilibrium seeking behavior. This entropy-based causal adaptive behavior framework permits the use of information-theoretic methods as a solution basis for the resulting pure and stochastic inverse economic-econometric problems. We cast the information recovery problem in the form of a binary network and suggest information-theoretic methods to recover estimates of the unknown binary behavioral parameters without explicitly sampling the configuration-arrangement of the sample space.
Keywords: C10; C24; C40; 330; information-theoretic methods; adaptive behavior; causal entropy maximization; pure and stochastic inverse problems; binary network; dynamic economic systems