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...

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 presents a Bayesian alternative to Generalized Maximum Entropy (GME) and Generalized Cross Entropy (GCE) methods for deriving solutions to econometric models represented by underdetermined systems of equations. For certain types of econometric model specifications, the Bayesian...

In this article, it is shown how the parameters of a transport model can be estimated in a way that, in contrast to previously used methods, utilizes observations of regional prices as well as of trade costs. The proposed method uses bi-level programming to minimize a weighted least squares...

The primary objective of this paper is to estimate behavioural parameters of the quadratic regional supply models in the modelling system CAPRI, using the time series data in the CAPRI database. A secondary objective is to replace the constant yields of the original model by functions that...

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...

This paper introduces a semi-parametric bootstrapping approach to Bayesian analysis of structural parameters in simultaneous equation systems that extends the single and multivariate regression approaches of Heckelei and Mittelhammer (1996, 2002) to models with endogenous regressors. Monte Carlo...

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...