An Examination of Production Effiency in New England's Oyster Aquaculture Industry

Shellfish aquaculture is a widespread practice in New England, but few economic studies have focused on this industry. Several different production methods are currently employed in this region to raise oysters, each of which involves a different level of capital and labor intensity. This analysis seeks to determine whether there are significant differences in productivity resulting from employing these different oyster production methods.

We employed a mixed-mode survey format to collect information from oyster growers. Respondents were given the option to complete our survey either online or by mail, and those who participated were compensated for their time with a $20 cash gift. This survey was sent to 530 oyster farms located throughout Maine, New Hampshire and Massachusetts. We sent three rounds of surveys by mail and email, and have received 155 completed surveys, yielding a response rate of over 29%.

This presentation identifies the factors that significantly contribute to oyster production efficiency. A stochastic frontier production function (SFPF) was estimated to evaluate the productive efficiency of oyster operations. This model allows us to investigate the relative contribution of different productive inputs to the overall productivity of each oyster farm. Additionally, we assess the impact of factors such as location experience, and diversity of species in determining the productive efficiency of each grower.

This study provides a tool that allows oyster growers to evaluate the efficiency of the production methods they are currently employing. This analysis also has important policy implications. Assessing the relative efficiency of Maine’s oyster aquaculture industry will allow policymakers to determine whether more resources need to be dedicated to education and outreach to improve outcomes in this industry. This information could play a critical role in helping Maine's oyster aquaculture business owners to continue to be successful.

Faculty Mentor: Xuan Chen