Details

Title

Accounting for Spatial Heterogeneity of Preferences in Discrete Choice Models

Journal title

Central European Journal of Economic Modelling and Econometrics

Yearbook

2021

Issue

No 1

Affiliation

Budziński, Wiktor : University of Warsaw ; Czajkowski, Mikołaj : University of Warsaw

Authors

Keywords

discrete choice experiment ; discrete choice models ; individual-, region- and population-level parameter estimates ; spatial preference heterogeneity

Divisions of PAS

Nauki Humanistyczne i Społeczne

Coverage

1-24

Publisher

Oddział PAN w Łodzi

Bibliography

[1] Abildtrup J., Garcia S., Olsen S. B., Stenger A., (2013), Spatial preference heterogeneity in forest recreation, Ecological Economics 92(1), 67–77.
[2] Broch S. W., Strange N., Jacobsen J. B., Wilson K. A., (2013a) Farmers’ willingness to provide ecosystem services and effects of their spatial distribution, Ecological Economics 92, 78–86.
[3] Broch S. W., Strange N., Jacobsen J. B., Wilson K. A., (2013b), Farmers’ willingness to provide ecosystem services and effects of their spatial distribution, Ecological Economics 92(0), 78–86.
[4] Budzinski W., Campbell D., Czajkowski M., Demsar U., Hanley N., (2018), Using geographically weighted choice models to account for spatial heterogeneity of preferences, Journal of Agricultural Economics 69(3), 606–626.
[5] Budzinski W., Campbell D., Czajkowski M., Demsar U., Hanley N., Using geographically weighted choice models to account for spatial heterogeneity of preferences, Journal of Agricultural Economics, forthcoming.
[6] Campbell D., Hutchinson W. G., Scarpa R., (2009), Using Choice Experiments to Explore the Spatial Distribution of Willingness to Pay for Rural Landscape Improvements, Environment and Planning A 41(1), 97–111.
[7] Campbell D., Scarpa R., Hutchinson W. G., (2008), Assessing the spatial dependence of welfare estimates obtained from discrete choice experiments, Letters in Spatial and Resource Sciences 1(2-3), 117–126.
[8] Carson R. T., Czajkowski M., (2014), The Discrete Choice Experiment Approach to Environmental Contingent Valuation, [in:] Handbook of choice modelling, Hess S., Daly A., [eds.] Elgar E., Northampton, MA.
[9] Czajkowski M., Budzinski W., (2015), An insight into the numerical simulation bias – a comparison of efficiency and performance of different types of quasi Monte Carlo simulation methods under a wide range of experimental conditions, Environmental Choice Modelling Conference, Copenhagen.
[10] Czajkowski M., Budzinski W., (2019), Simulation error in maximum likelihood estimation of discrete choice models, Journal of Choice Modelling 31, 73–85.
[11] Czajkowski M., Budzinski W., Campbell D., Giergiczny M., Hanley N., (2017), Spatial Heterogeneity of Willingness to Pay for Forest Management, Environmental and Resource Economics 68(3), 705–727.
[12] Dekker T., Koster P., Brouwer R., (2014), Changing with the Tide: Semiparametric Estimation of Preference Dynamics, Land Economics 90(4), 717– 745.
[13] Fotheringham A. S., Brunsdon C., Charlton M., (2003), Geographically weighted regression: the analysis of spatially varying relationships, John Wiley & Sons.
[14] Fotheringham S., Charlton M., Brunsdon C., (1998), Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis, Environment and Planning A 30(11), 1905–1927.
[15] Gelman A., Carlin J. B., Stern H. S., Dunson D. B., Vehtari A., Rubin D. B., (2014), Bayesian data analysis, CRC Press Boca Raton, FL.
[16] Hanley N., Czajkowski M., (2019), The Role of Stated Preference Valuation Methods in Understanding Choices and Informing Policy, Review of Environmental Economics and Policy 13(2), 248–266.
[17] Hess S., Train K., (2017), Correlation and scale in mixed logit models, Journal of Choice Modelling 23, 1–8.
[18] Hynes S., Hanley N., O’Donoghue C., (2010), A Combinatorial Optimization Approach to Nonmarket Environmental Benefit Aggregation via Simulated Populations, Land Economics 86(2), 345–362.
[19] Johnston R. J., Ramachandran M., (2014), Modeling Spatial Patchiness and Hot Spots in Stated Preference Willingness to Pay, Environmental and Resource Economics 59(3), 363–387.
[20] Johnston R. J., Ramachandran M., Schultz E. T., Segerson K., Besedin E. Y., (2011), Characterizing spatial pattern in ecosystem service values when distance decay doesn’t apply: choice experiments and local indicators of spatial association. Paper number 103374 provided by Agricultural and Applied Economics Association in its series 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania.
[21] Koster P. R., Koster H. R. A., (2015), Commuters’ preferences for fast and reliable travel: A semi-parametric estimation approach, Transportation Research Part B: Methodological 81, Part 1, 289–301.
[22] LeSage J. P., (1999), The Theory and Practice of Spatial Econometrics, unpublished manuscript available at: http://www.spatial-econometrics.com.
[23] McFadden D., (1974), Conditional Logit Analysis of Qualititative Choice Behaviour, [in]: Frontiers in Econometrics, [ed.:] Zarembka P., Academic Press, New York, NY, 105–142.
[24] Smith T. E., LeSage J. P., (2004), A bayesian probit model with spatial dependencies, Spatial and Spatiotemporal Econometrics 18(18), 127–160.
[25] Train K., Sonnier G., (2005), Mixed Logit with Bounded Distributions of Correlated Partworths, [in:] Applications of Simulation Methods in Environmental and Resource Economics, [eds.:] Scarpa R., Alberini A., Springer Netherlands, 117–134.
[26] Train K. E., (2009), Discrete Choice Methods with Simulation, 2 Ed., Cambridge University Press, New York.
[27] Yao R. T., Scarpa R., Turner J. A., Barnard T. D., Rose J. M., Palma J. H. N., Harrison D. R., (2014), Valuing biodiversity enhancement in New Zealand’s planted forests: Socioeconomic and spatial determinants of willingness-to-pay, Ecological Economics 98(0), 90–101.


Date

2021.05.13

Type

Article

Identifier

DOI: 10.24425/cejeme.2021.137353

Source

Central European Journal of Economic Modelling and Econometrics; 2021; No 1; 1-24
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