Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/174307
Authors: 
Grilli, Gianluca
Curtis, John A.
Hynes, Stephen
O'Reilly, Paul
Year of Publication: 
2017
Series/Report no.: 
ESRI Working Paper 574
Abstract: 
The relationship between angling effort and catch is well-recognised, in particular that effort influences catch rates. But increased catch, which can be considered an attribute of fishery quality, may influence effort in terms of number of fishing trips. This suggests bi-directional feedback between catch and effort. In many travel cost applications little attention has been given to this endogeneity problem. In this paper we expand the application of structural equation models to address this issue by jointly estimating demand (effort) and catch functions. Using a cross-section dataset of sea bass anglers we propose two separate joint models. First, we include expected catch as an explanatory variable in the demand equation. In the second, we reverse the causality and use the expected number of fishing days as a covariate in the catch function. The two approaches produce similar model estimates, and perform better at predicting anglers' catch and effort than standard models. The findings confirm that "catch & release" does not curtail fishing activity and that sea bass angling is highly valued. Furthermore higher catches result more days fished, on average in a 2:1 ratio. Whereas on average, an additional fishing day results in 3-4 additional bass caught.
Document Type: 
Working Paper

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