Replaced with revised version of paper 05/29/04.

In this poster a Bayesian estimation framework for a non-stationary Markov model is developed for situations where sample data with observed transition between classes (micro data) and aggregate population shares (macro data) are available. Posterior distributions on transition probabilities are...

We formulate and estimate a farm level simulation model of agricultural crop production, and apply it to a scenario with increasing yield variability. The objective function is of the mean-variance utility type with a positive mathematical programming (PMP) cost function, and it is estimated...

We develop a Bayesian framework for estimating non-stationary Markov models in situations where macro population data is available only on the proportion of individuals residing in each state, but micro-level sample data is available on observed transitions between states. Posterior...

Presumed portfolio benefits of commodities and the availability of index fund-type investment products increase attractiveness of commodity markets for financial traders. But resulting “index trading” strategies are suspected to inflate commodity prices above their fundamental value. We use...

This paper reviews and discusses the more recent literature and application of Positive Mathematical Programming in the context of agricultural supply models. Specifically, advances in the empirical foundation of parameter specifications as well as the economic rationalisation of PMP models...

The increased interest in Integrated Assessment (IA) of agricultural systems reflects the growing complexity of policy objectives and corresponding impacts related to this sector. The paper contemplates on the status of quantitative tools for IA in agriculture, drawing on recent European...

The addition of commodities to financial portfolios and resulting weight adjustments may create volatility linkages between commodity and financial markets, especially during financial crises. Also, biofuel mandates are suspected to integrate agricultural and energy markets. We calculate...

We develop a Bayesian estimation framework for non-stationary Markov models for situations where both sample data on observed transitions between states (micro data) and population data, where only the proportion of individuals in each state is observed (macro data), are available. Posterior...

The paper introduces a general methodological approach for the estimation of constrained optimisation models in agricultural supply analysis. It is based on optimality conditions of the desired programming model and shows a conceptual advantage compared to Positive Mathematical Programming in...