In many econometric studies of demand relationships the design matrix is frequently subject
to severe collinearity. In this paper the Generalized Maximum Entropy methodology is …

Mathematical measures of entropy as defined by Shannon and cross entropy as defined by
Kullback and Leibler are currently in vogue in the field of econometrics, primarily due to the …

A new information-based approach for estimating systems of many equations with
nonnegativity constraints is presented. This approach, called generalized maximum entropy …

Generalised maximum entropy methods are used to estimate a dual model of production on
panel data of Dutch cash crop farms over the period 1970-1992. The generalised maximum …

Maximum entropy and Bayesian approaches provide superior estimates of a ratio of
parameters, as this paper illustrates using the classic Nerlove model of agricultural supply …

The entropy concept was developed and used by Shannon in 1940 as a measure of
uncertainty in the context of information theory. In 1957 Jaynes made use of Shannon's …

This paper examines Australian retail demand for meat for the post‐war period 1949‐50 to
1978‐79. Several systems of demand equations are estimated, each system (comprising …

This paper proposes the use of the Generalised Maximum Entropy (GME) method to
estimate input‐output coefficients, which reflect the unobserved allocation of farm input …

We show that generalized maximum entropy (GME) is the only estimation method that is
consistent with a set of five axioms. The GME estimator can be nested using a single …

The origin of entropy dates back to 19th century. In 1948, the entropy concept as a measure
of uncertainty was developed by Shannon. A decade after in 1957, Jaynes formulated …