Systems of equations comprising cost functions and first‐order derivative equations are often used to estimate characteristics of production technologies. Unfortunately, many estimated systems violate the regularity conditions implied by economic theory. Sampling theory methods can be used to...

Rainfall during the germination, growing and flowering periods is a major determinant of wheat yield. The degree of uncertainty attached to a wheat-yield prediction depends on whether the prediction is made before or after the rainfall in each period has been realised. Bayesian predictive...

A problem with the use of flexible functional forms is that the estimated functions frequently violate the regularity conditions (eg, monotonicity, concavity) implied by economic theory. Sampling theory methods exist for imposing curvature conditions at all non-negative prices, but such methods...

Forecasts from regression models are frequently made conditional on a set of values for the regressor variables. We describe and illustrate how to obtain forecasts when some of those regressors are stochastic and their values have not yet been realized. The forecasting device is a Bayesian...

Systems of equations comprising cost functions and first-order derivative equations are often used to estimate characteristics of production technologies. Unfortunately, many estimated systems violate the regularity conditions implied by economic theory. Sampling theory methods can be used to...

The effects of including different kinds of prior information in estimation of the probit model is examined within the framework of Bayesian inference. Of interest is the effect on posterior information for coefficients, probabilities and elasticities. In a model designed to explain choice...