Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random-Effects Models
By D. Campbell. 2007
234 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/0e22e898cbbc64347f121b1f38f5fa4955c06242
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Riccardo Scarpa
- John M. Rose
- David A. Hensher
- D. Campbell
- S. B. Olsen
- Stephane Hess
- W. Hutchinson
- S. Garcia
In Global and Planetary Change
- Riccardo Scarpa
- John M. Rose
- David A. Hensher
- D. Campbell
- W. Hutchinson
- S. B. Olsen
- S. Garcia
- J. Abildtrup
Citations in the corpus
- Incorporating Discontinuous Preferences into the Analysis of Discrete Choice Experiments (2008, methodology): “We utilise the survey data collected and described by Campbell (2007) and Campbell et al.”
- Non-attendance to attributes in environmental choice analysis: a latent class specification (2011, methodology): “We utilise the survey data collected and described by Campbell (2007), Campbell et al. (2008, 2009) and Scarpa et al. (2007, 2009) on the general public’s attitudes and preferences regarding rural environmental landscape improvements in the Republic of Ireland.”
- Spatial preference heterogeneity in forest recreation (2013, methodology): “Model (3) is more flexible than the model in Campbell (2007) since we have included attribute-fixed effects and attribute-specific parameters, reflecting that characteristics of the individual and local access to forests may not have the same effect on the marginal utility for all attributes.”
- Valuing biodiversity enhancement in New Zealand's planted forests: Socioeconomic and spatial determinants of willingness-to-pay (2014, methodology): “Campbell (2007) also used a panel of individual specific means of the conditional distributions of marginal WTP values as the dependent variable, and socioeconomic characteristics and location as explanatory variables.”