Vol. 9 No. 2 (2020): Economics of culture and food in evolving agri-food systems and rural areas
Full Research Articles

Assessing preferences for rural landscapes: An attribute based choice modelling approach

Mary Ryan
Teagasc, the Irish Agriculture and Food Development Authority
Cathal O'Donoghue
National University of Ireland, Galway
Stephen Hynes
National University of Ireland, Galway
Paul Kilgarriff
Luxembourg Institute for Socio Economic Research
Andreas Tsakiridis
Teagasc, the Irish Agriculture and Food Development Authority
Published November 5, 2020
Keywords
  • Rural landscapes,
  • choice modelling,
  • ordered logit,
  • attribute preference heterogeneity
How to Cite
Ryan, M., O’Donoghue, C., Hynes, S., Kilgarriff, P., & Tsakiridis, A. (2020). Assessing preferences for rural landscapes: An attribute based choice modelling approach. Bio-Based and Applied Economics, 9(2), 171-200. https://doi.org/10.13128/bae-8287

Abstract

This study adopts a choice modelling framework to disentangle individual preferences for rural landscape attributes based on the viewing of photographs of the Irish countryside. Using ordered logit and standard panel and pooled regression models, societal preferences are quantified for rural landscape attributes, grouped into natural, agricultural and human-built non-agricultural categories. The preferences of 430 individuals towards 50 rural landscape photographs are analysed. The results show positive preferences for landscapes with natural attributes such as cliffs, mountainous features, water and native trees, as well as preferences for neat/managed agricultural landscapes and traditional human-built features such as stone walls and planted hedgerows. The study shows negative preferences for features such as flooding, unmanaged landscapes, industrial turf cutting and mechanised features such as wind turbines. There is significant preference heterogeneity observed across the sample particularity across the urban-rural residency divide. It is argued that analysing preferences for specific attributes of landscapes rather than preferences for individual landscape photographs allows for further applications particularly in the area of simulation.

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