Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/wiw/wiwreg/region_7_1_279.html
   My bibliography  Save this article

Random Parameters and Spatial Heterogeneity using Rchoice in R

Author

Listed:
  • Mauricio Sarrias
Abstract
This study focus on models with spatially varying coefficients using simulations. As shown by Sarrias (2019), this modeling strategy is intended to complement the existing approaches by using variables at micro level and by adding flexibility and realism to the potential domain of the coefficient on the geographical space. Spatial heterogeneity is modelled by allowing the parameters associated with each observed variable to vary “randomly” across space according to some distribution. To show the main advantages of this modeling strategy, the Rchoice package in R is used.

Suggested Citation

  • Mauricio Sarrias, 2020. "Random Parameters and Spatial Heterogeneity using Rchoice in R," REGION, European Regional Science Association, vol. 7, pages 1-19.
    • Handle: RePEc:wiw:wiwreg:region_7_1_279
    as

    Download full text from publisher

    File URL: https://openjournals.wu.ac.at/ojs/index.php/region/article/view/279/version/544
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lee, Lung-fei, 2000. "A numerically stable quadrature procedure for the one-factor random-component discrete choice model," Journal of Econometrics, Elsevier, vol. 95(1), pages 117-129, March.
    2. Yoshihiro Hashiguchi & Kiyoyasu Tanaka, 2015. "Agglomeration and firm-level productivity: A Bayesian spatial approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 95-114, November.
    3. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    4. Guanpeng Dong & Jing Ma & Richard Harris & Gwilym Pryce, 2016. "Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(1), pages 19-35, January.
    5. Borjas, George J. & Sueyoshi, Glenn T., 1994. "A two-stage estimator for probit models with structural group effects," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 165-182.
    6. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    7. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    8. Kamar Ali & Mark D. Partridge & M. Rose Olfert, 2007. "Can Geographically Weighted Regressions Improve Regional Analysis and Policy Making?," International Regional Science Review, , vol. 30(3), pages 300-329, July.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    10. Duranton, Gilles & Puga, Diego, 2004. "Micro-foundations of urban agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 48, pages 2063-2117, Elsevier.
    11. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    12. Gelfand A.E. & Kim H-J. & Sirmans C.F. & Banerjee S., 2003. "Spatial Modeling With Spatially Varying Coefficient Processes," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 387-396, January.
    13. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    14. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    15. David Revelt and Kenneth Train., 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Economics Working Papers E00-274, University of California at Berkeley.
    16. Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, vol. 8(4), pages 518-552, December.
    17. Christian Gouriéroux & Alain Monfort, 1991. "Simulation Based Inference in Models with Heterogeneity," Annals of Economics and Statistics, GENES, issue 20-21, pages 69-107.
    18. Steven Stern, 1997. "Simulation-Based Estimation," Journal of Economic Literature, American Economic Association, vol. 35(4), pages 2006-2039, December.
    19. Mauricio Sarrias, 2019. "Do monetary subjective well-being evaluations vary across space? Comparing continuous and discrete spatial heterogeneity," Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(1), pages 53-87, January.
    20. Sarrias, Mauricio, 2016. "Discrete Choice Models with Random Parameters in R: The Rchoice Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i10).
    21. repec:adr:anecst:y:1991:i:20-21:p:04 is not listed on IDEAS
    22. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, September.
    23. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, June.
    24. Guanpeng Dong & Richard Harris & Kelvyn Jones & Jianhui Yu, 2015. "Multilevel Modelling with Spatial Interaction Effects with Application to an Emerging Land Market in Beijing, China," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-18, June.
    25. Gourieroux, Christian & Monfort, Alain, 1997. "Simulation-based Econometric Methods," OUP Catalogue, Oxford University Press, number 9780198774754.
    26. Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Francisco Rowe & Gunther Maier & Daniel Arribas-Bel & Sergio Rey, 2020. "The Potential of Notebooks for Scientific Publication, Reproducibility and Dissemination," REGION, European Regional Science Association, vol. 7, pages 1-5.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarrias, Mauricio, 2016. "Discrete Choice Models with Random Parameters in R: The Rchoice Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i10).
    2. Falco, Paolo & Maloney, William F. & Rijkers, Bob & Sarrias, Mauricio, 2015. "Heterogeneity in subjective wellbeing: An application to occupational allocation in Africa," Journal of Economic Behavior & Organization, Elsevier, vol. 111(C), pages 137-153.
    3. Ufer, Danielle J. & Ortega, David L. & Wolf, Christopher A. & McKendree, Melissa & Swanson, Janice, 2022. "Getting past the gatekeeper: Key motivations of dairy farmer intent to adopt animal health and welfare-improving biotechnology," Food Policy, Elsevier, vol. 112(C).
    4. Gustavo Ahumada & Victor Iturra & Mauricio Sarrias, 2020. "We Do Not Have the Same Tastes! Evaluating Individual Heterogeneity in the Preferences for Amenities," Journal of Happiness Studies, Springer, vol. 21(1), pages 53-74, January.
    5. Nannan Kang & Erda Wang & Yang Yu, 2019. "Valuing forest park attributes by giving consideration to the tourist satisfaction," Tourism Economics, , vol. 25(5), pages 711-733, August.
    6. Nguyen, Ly & Gao, Zhifeng & Anderson, James L., 2022. "Regulating menu information: What do consumers care and not care about at casual and fine dining restaurants for seafood consumption?," Food Policy, Elsevier, vol. 110(C).
    7. Galassi, Veronica & Madlener, Reinhard, 2017. "The Role of Environmental Concern and Comfort Expectations in Energy Retrofit Decisions," Ecological Economics, Elsevier, vol. 141(C), pages 53-65.
    8. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    9. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    10. Achtnicht, Martin, 2011. "Do environmental benefits matter? Evidence from a choice experiment among house owners in Germany," Ecological Economics, Elsevier, vol. 70(11), pages 2191-2200, September.
    11. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    12. Bijan J. Borah, 2006. "A mixed logit model of health care provider choice: analysis of NSS data for rural India," Health Economics, John Wiley & Sons, Ltd., vol. 15(9), pages 915-932, September.
    13. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    14. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    15. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    16. Faure, Corinne & Guetlein, Marie-Charlotte & Schleich, Joachim & Tu, Gengyang & Whitmarsh, Lorraine & Whittle, Colin, 2022. "Household acceptability of energy efficiency policies in the European Union: Policy characteristics trade-offs and the role of trust in government and environmental identity," Ecological Economics, Elsevier, vol. 192(C).
    17. Faulques, Martin & Bonnet, Jean & Bourdin, Sébastien & Juge, Marine & Pigeon, Jonas & Richard, Charlotte, 2022. "Generational effect and territorial distributive justice, the two main drivers for willingness to pay for renewable energies," Energy Policy, Elsevier, vol. 168(C).
    18. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    19. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    20. Carole Ropars-Collet & Philippe Goffe & Qods Lefnatsa, 2021. "Does catch-and-release increase the recreational value of rivers? The case of salmon fishing," Review of Agricultural, Food and Environmental Studies, Springer, vol. 102(4), pages 393-424, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwreg:region_7_1_279. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.