172 research outputs found

    EXCISE TAXES AND COMMODITY PROMOTION: BAYESIAN RETRIEVAL OF THE OPTIMUM

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    This article shows how the solution to the promotion problem--—the problem of locating the optimal level of advertising in a downstream market--—can be derived simply, empirically, and robustly through the application of some simple calculus and Bayesian econometrics. We derive the complete distribution of the level of promotion that maximizes producer surplus and generate recommendations about patterns as well as levels of expenditure that increase net returns. The theory and methods are applied to quarterly series (1978:2S1988:4) on red meats promotion by the Australian Meat and Live-Stock Corporation. A slightly different pattern of expenditure would have profited lamb producers.Bayesian estimation, commodity promotion as an experiment, distribution of the optimum, Taylor-series expansion, Livestock Production/Industries, Marketing,

    Sustainable land use pathway ranking and selection

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    This paper presents methodology for ranking and selecting sustainable ‘land-use pathways,’ arguing that the methodology is central to sustainable-land-use-policy prescriptions, providing essential innovation to assessments hitherto devoid of probabilistic foundation. Demonstrating routine implementation of Markov-Chain, Monte-Carlo procedure, ranking-and-selection enactment is widely disseminable and potentially valuable to land-use policy prescription. Application to a sample of Ethiopian-highlands, land-dependent households highlights empirical gains compared to conventional methodology. Applications and extensions that profit future land-use sustainability are discussed (68 words)

    Bayesian Ranking and Selection of Fishing Boat Efficiencies

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    The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods—Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.Ranking and selection, hierarchical composed-error model, Markov Chain Monte Carlo, Pacific hake fishery, Resource /Energy Economics and Policy, Q2, L5, C1,

    Organic farming policies and the growth of the organic sector in Denmark and the UK: a comparative analysis

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    There has been little systematic analysis of the extent to which organic farming policies have influenced growth in the organic sector. Analyses of organic farming policy instruments, for the most part, provide extensive and detailed reviews of instruments applied either in a single country or across countries. Hence, there is a great need to examine systematically whether there is a relationship between the introduction of organic farming policies and the growth of the organic food sector, and whether particular designs of organic farming policies are more effective than others. In this paper, we take the first step in the endeavour of analysing the effects of organic farming by undertaking an econometric analysis of the relationship between organic farming policies in Denmark and the UK and their effects on the number of farmers and growers converting to organic production

    Bayes Estimates of Time to Organic Certification

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    The adoption of organic production has increased dramatically over recent years, especially in less developed countries. However, little information is available about who adopts, the difficulties they face in converting and how these factors vary over time. Using small-scale avocado producers (<15ha) from Michoacán, Mexico as a case study, this paper explores the factors affecting the time-to-adoption of organic production and certification, drawing from five parametric descriptions of the data. These models are implemented using a Bayesian approach and advances in Markov chain Monte Carlo methods. The results indicate that additional sources of income, together with membership of producers associations, higher levels of education and experience of export markets, other than the US, have a positive effect on the adoption decision. Labour requirements and administrative capacity appear to be unimportant, while information sources and the frequency of contact with these sources have a varied, but largely negative effect on the probability of adoption. These findings raise a number of questions about the future of organic production in Mexico and the avocado zone, not least how to overcome credit and information constraints, but more importantly whether aiming for the organic market is a viable production strategy for small-scale producers.Crop Production/Industries, Farm Management,

    CONDUCT AND VOLATILITY IN FOOD-PRICE DETERMINATION: VAR EVIDENCE FROM TURKISH AGRICULTURE

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    The relationship between price volatility and competition is examined. A theoretic, vector autoregressions on farm prices of wheat and retail prices of derivatives (flour, bread, pasta, bulgur and cookies) are compared to results from a dynamic, simultaneous-equations model with theory-based farm-to-retail linkages. Analytical results yield insights about numbers of firms and their impacts on demand- and supply-side multipliers, but the applications to Turkish time series (1988:1-1996:12) yield mixed results.conduct, volatility, food marketing., Marketing, Risk and Uncertainty,
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