Random Coefficient Models for Stated Preference Surveys

By D. Layton. 2000

190 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Marketing

View Paper: https://www.semanticscholar.org/paper/9200f84278e9ca45c8ec19cea2480d5b32e5c1ad

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Citations in the corpus

External Tests of Scope and Embedding in Stated Preference Choice Experiments: An Application to Endangered Species Valuation (2011, unknown): “In recent years, researchers have increasingly used these models in non-market valuation applications due to the advantages they have over the conditional logit models that are most often turned to for estimating discrete choice data (e.g., Train 1998; Layton 2000; Siikamaki and Layton 2007).”
Valuing externalities from water supply: Status quo, choice complexity and individual random effects in panel kernel logit analysis of choice experiments (2007, methodology): “The first one refers to the description of taste variation in the observable component of utility and it is well known and often employed in the context of data analysis from choice experiments (see Layton, 2000; Garrod et al., 2002; Foster & Mourato, 2003; Scarpa et al., 2003).”
Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models (2008, unknown): “Similar success has been enjoyed by this method in other areas of applied research including transportation (Amador, Gonzales, and Ortuzar 2005), consumer choices (Revelt and Train 1998), health (Personn 2002), and waste management (Layton 2000).”
Valuing water quality changes using a bioeconomic model of a coastal recreational fishery (2006, methodology): “We model survey respondents’ stated choices using a repeated choice mixed logit model [23,33,44].”
Definition, Measurement and Determinants of the Consumer's Willingness to Pay: A Critical Synthesis and Avenues for Further Research (2009, methodology): “…responses of these s gments (Desarbo et al, 1992) - to estimate a random coefficient model, by postulating continuous distributions of parameters (Layton, 2000 ; Baltas and Doyle, 2001) The first method is simple, but can only be used when the heterogeneity of respondents is based on a few…”
Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently? (2009, methodology): “…of Sydney, stephaneh@itls.usyd.edu.au ‡Institute of Transport and Logistics Studies, The University of Sydney, johnr@itls.usyd.edu.au, Tel: +61 2 9351 0168, Fax: + 61 2 9351 0088 valuations particularly using stated choice (SC) data (e.g. Adamowicz et al., 1994; Layton, 2000; Willis et al., 2005).”
Combining Revealed and Stated Preference Data to Estimate the Nonmarket Value of Ecological Services: An Assessment of the State of the Science (2008, unknown): “Cross validation models are estimated n times (Layton, 2000) and n predi s In the contingent valuation literature, a large number of studies compare actual willingness to pay obtained from laboratory experiments and field surveys with hypothetical willing ys. cs on ctions are made.”
State dependence and heterogeneity in fishing location choice (2005, methodology): “Random parameters for taste heterogeneity in a discrete choice model have also been applied to stated preference data [21].”
Estimating Non-Market Environmental Benefits of the Conversion of Cropland to Forest and Grassland Program: a choice modeling approach (2007, unknown): “Brownstone and Train (1999), Train (1998) and Layton (1999) used a lognormal distribution for the coefficient of cost to constrain it to be negative.”
Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment (2005, background): “Discrepancies in population mean WTP estimates between fixed and random parameters logit specifications on the same data are well-documented in stated preference work (see, e.g., Layton 2000).”
Quality Signals? The Role of Patents, Alliances, and Team Experience in Venture Capital Financing (2015, unknown): “This assumption, however, is likely violated with data from choice experiments, as respondents’ preferences will influence the error terms in their various choice decisions in a similar way (Hausman and Wise, 1978; Layton, 2000).”