Bayesian ranking and selection of fishing boat efficiencies

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.

A continuum model of a fishing net

A working report for the Department of Agriculture and Fisheries, Scotland, Marine Laboratory Aberdeen

Estimating regional benefits of reducing targeted pollutants: An application to agricultural effects on water quality and the value of recreational fishing

The general focus of this paper is the regional estimation of marginal benefits of targeted water pollution abatement to instream uses. Benefit estimates are derived from actual consumer choices of recreational fishing activities and the implied expenditures for various levels of water quality. The methodology is applied to measuring the benefits accruing to recreational anglers in Indiana from the abatement of pollutants that are by-products of agricultural crop production.

Bayesian ranking and slection of fishing boat efficiencies

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.

Urban warming in villages

Long term meteorological records (> 100 years) from stations associated with villages are generally classified as rural and assumed to have no urban influence. Using networks installed in two European villages, the local and microclimatic variations around two of these rural-village sites are examined. An annual average temperature difference ($\Delta{T}$) of 0.6 and 0.4 K was observed between the built-up village area and the current meteorological station in Geisenheim (Germany) and Haparanda (Sweden), respectively. Considerably larger values were recorded for the minimum temperatures and during summer. The spatial variations in temperature within the villages are of the same order as recorded over the past 100+ years in these villages (0.06 to 0.17 K/10 years). This suggests that the potential biases in the long records of rural-villages also warrant careful consideration like those of the more commonly studied large urban areas effects.