MEASURING TECHNICAL EFFICIENCY IN A SMALL-SCALE FISHERY: A causality analysis
The analysis of technical efficiency (TE) on the small-scale fishery is relevant for several reasons. While this type of fishery is highly common in developing countries like Mexico, there are a very limited number of analyses assessing their efficiency. Indeed, there is no precise information on the contribution of the small-scale fisheries to livelihoods and economies in developing nations. Exploring this gap in the research would be relevant for the decision making policy. On the one hand, small-scale fisheries can generate significant profits and be more resilient to shocks and crises; two important elements to poverty alleviation and food security. But on the other hand, small-scale fisheries may overexploit stocks, harming the environment and generating low profits. Certainly, it is desirable the preservation of resources of common access like lakes or reservoirs, at the same time it is desirable an efficient use of the fishery. The question is what factors constrain the efficiency? Aiming for a contribution on the knowledge of the small-scale fisher’s performance; this research applies “directed acyclic graphs”, an innovative technique to explore the causal relationship on the variables to explain the TE. To assess the fisher’s TE, this research uses “stochastic frontier analysis”, a method commonly used to estimate the efficiency. This study explores the causal pattern among the production function variables to corroborate, by estimating the TE, the hypothesis that: fisher’s skills favor the fisher performance. Compared to previous research, the results show an improvement on the assessment of the variables that constrain the efficiency. Getting a more precise TE assessment is valuable information. It would help to define the strategies for the assistance of the fishing communities; in a search for a policy to remedy the production inefficiencies and increase the competitiveness in small-scale fisheries.
|Date of creation:||2011|
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