IDEAS home Printed from https://ideas.repec.org/p/fae/wpaper/2016.12.html
   My bibliography  Save this paper

How useful are (Censored) Quantile Regressions for Contingent Valuation?

Author

Listed:
  • Victor Champonnois

    () (AMSE-GREQAM)

  • Olivier Chanel

    (AMSE-GREQAM)

Abstract

We investigate the interest of quantile regression (QR) and censored quantile regression (CQR) to deal with issues from contingent valuation (CV) data. Indeed, although (C)QR estimators have many properties of interest for CV, the literature is scarce and restricted to six studies only. We proceed in three steps. First, we provide analytical arguments showing how (C)QR can tackle many econometric issues associated with CV data. Second, we show by means of Monte Carlo simulations, how (C)QR performs w.r.t. standard (linear and censored) models. Finally, we apply and compare these four models on a French CV survey dealing with flood risk. Although our findings show the usefulness of QR for analyzing CV data, findings are mixed on the improvements from CQR estimates with respect to QR estimates.

Suggested Citation

  • Victor Champonnois & Olivier Chanel, 2016. "How useful are (Censored) Quantile Regressions for Contingent Valuation?," Working Papers 2016.12, FAERE - French Association of Environmental and Resource Economists.
  • Handle: RePEc:fae:wpaper:2016.12
    as

    Download full text from publisher

    File URL: http://faere.fr/pub/WorkingPapers/Champonnois_Chanel_FAERE_WP2016.12.pdf
    File Function: First version, 2016
    Download Restriction: no

    References listed on IDEAS

    as
    1. Rodolfo M. Nayga, Jr. & Ximing Wu & Robert G. Brummett, 2007. "On the Use of Cheap Talk in New Product Valuation," Economics Bulletin, AccessEcon, vol. 2(1), pages 1-9.
    2. Yang, Shang-Ho & Hu, Wuyang & Mupandawana, Malvern & Liu, Yun, 2012. "Consumer Willingness to Pay for Fair Trade Coffee: A Chinese Case Study," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 44(1), pages 1-14, February.
    3. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    4. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    5. Dekker, Thijs & Hess, Stephane & Brouwer, Roy & Hofkes, Marjan, 2016. "Decision uncertainty in multi-attribute stated preference studies," Resource and Energy Economics, Elsevier, vol. 43(C), pages 57-73.
    6. Paarsch, Harry J., 1984. "A Monte Carlo comparison of estimators for censored regression models," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 197-213.
    7. Craig E. Landry & Paul Hindsley & Okmyung Bin & Jamie B. Kruse & John C. Whitehead & Ken Wilson, 2011. "Weathering the Storm: Measuring Household Willingness-to-Pay for Risk-Reduction in Post-Katrina New Orleans," Southern Economic Journal, Southern Economic Association, vol. 77(4), pages 991-1013, April.
    8. Seth Owusu & Grant Wright & Scott Arthur, 2015. "Public attitudes towards flooding and property-level flood protection measures," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(3), pages 1963-1978, July.
    9. Wiktor Adamowicz & J. Deshazo, 2006. "Frontiers in Stated Preferences Methods: An Introduction," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 1-6, May.
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, January.
    11. repec:ebl:ecbull:v:2:y:2007:i:1:p:1-9 is not listed on IDEAS
    12. Nahuelhual, Laura & Loureiro, Maria L. & Loomis, John B., 2004. "Using Random Parameters to Account for Heterogeneous Preferences in Contingent Valuation of Public Open Space," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-16, December.
    13. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.
    14. Janelle Seymour & Paul McNamee & Anthony Scott & Michela Tinelli, 2010. "Shedding new light onto the ceiling and floor? A quantile regression approach to compare EQ-5D and SF-6D responses," Health Economics, John Wiley & Sons, Ltd., vol. 19(6), pages 683-696.
    15. Mahalia Jackman & Troy Lorde, 2014. "Why buy when we can pirate? The role of intentions and willingness to pay in predicting piracy behavior," International Journal of Social Economics, Emerald Group Publishing, vol. 41(9), pages 801-819, September.
    16. Jayson L. Lusk & W. Bruce Traill & Lisa O. House & Carlotta Valli & Sara R. Jaeger & Melissa Moore & Bert Morrow, 2006. "Comparative Advantage in Demand: Experimental Evidence of Preferences for Genetically Modified Food in the United States and European Union," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(1), pages 1-21, March.
    17. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, October.
    18. Lima, Luiz Renato & Mesquita, Shirley & Wanamaker, Marianne, 2015. "Child labor and the wealth paradox: The role of altruistic parents," Economics Letters, Elsevier, vol. 130(C), pages 80-82.
    19. Botzen, W.J.W. & van den Bergh, J.C.J.M., 2012. "Risk attitudes to low-probability climate change risks: WTP for flood insurance," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 151-166.
    20. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    21. Tadao Hoshino, 2013. "Estimation of the preference heterogeneity within stated choice data using semiparametric varying-coefficient methods," Empirical Economics, Springer, vol. 45(3), pages 1129-1148, December.
    22. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    23. Nick Hanley & Bengt Kriström & Jason F. Shogren, 2009. "Coherent Arbitrariness: On Value Uncertainty for Environmental Goods," Land Economics, University of Wisconsin Press, vol. 85(1), pages 41-50.
    24. W. Viscusi & Joel Huber & Jason Bell, 2012. "Heterogeneity in Values of Morbidity Risks from Drinking Water," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 52(1), pages 23-48, May.
    25. Glenk, Klaus & Fischer, Anke, 2010. "Insurance, prevention or just wait and see? Public preferences for water management strategies in the context of climate change," Ecological Economics, Elsevier, vol. 69(11), pages 2279-2291, September.
    26. Fitzenberger, Bernd, 1994. "A note on estimating censored quantile regressions," Discussion Papers 14, University of Konstanz, Center for International Labor Economics (CILE).
    27. Konishi, Yoshifumi & Adachi, Kenji, 2011. "A framework for estimating willingness-to-pay to avoid endogenous environmental risks," Resource and Energy Economics, Elsevier, vol. 33(1), pages 130-154, January.
    28. Marta Meleddu & Manuela Pulina & Maria Gabriela Ladu, 2013. "Evaluating the demand for cultural goods: just income and tastes do matter?," Economia della Cultura, Società editrice il Mulino, issue 2, pages 203-216.
    29. Cameron, Trudy Ann & Huppert, Daniel D., 1989. "OLS versus ML estimation of non-market resource values with payment card interval data," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 230-246, November.
    30. Anne-Kathrin Last, 2007. "The Monetary Value of Cultural Goods: A Contingent Valuation Study of the Municipal Supply of Cultural Goods in Lueneburg, Germany," Working Paper Series in Economics 63, University of Lüneburg, Institute of Economics.
    31. Smith, Richard D. & Richardson, Jeff, 2005. "Can we estimate the `social' value of a QALY?: Four core issues to resolve," Health Policy, Elsevier, vol. 74(1), pages 77-84, September.
    32. Sonia Akter & Roy Brouwer & Saria Choudhury & Salina Aziz, 2009. "Is there a commercially viable market for crop insurance in rural Bangladesh?," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 14(3), pages 215-229, March.
    33. Dodd, Mark C., 2014. "Intertemporal discounting as a risk factor for high BMI: Evidence from Australia, 2008," Economics & Human Biology, Elsevier, vol. 12(C), pages 83-97.
    34. Yao, Xi-Long & Liu, Yang & Yan, Xiao, 2014. "A quantile approach to assess the effectiveness of the subsidy policy for energy-efficient home appliances: Evidence from Rizhao, China," Energy Policy, Elsevier, vol. 73(C), pages 512-518.
    35. M. Ghanbarpour & Mohsen Saravi & Shokoufe Salimi, 2014. "Floodplain Inundation Analysis Combined with Contingent Valuation: Implications for Sustainable Flood Risk Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2491-2505, July.
    36. Johnston, Robert J. & Swallow, Stephen K. & Weaver, Thomas F., 1999. "Estimating Willingness to Pay and Resource Tradeoffs with Different Payment Mechanisms: An Evaluation of a Funding Guarantee for Watershed Management," Journal of Environmental Economics and Management, Elsevier, vol. 38(1), pages 97-120, July.
    37. Rotimi Joseph & David Proverbs & Jessica Lamond, 2015. "Assessing the value of intangible benefits of property level flood risk adaptation (PLFRA) measures," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(2), pages 1275-1297, November.
    38. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    contingent valuation; quantile regression; censored quantile regression; Monte Carlo simulations; flood;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fae:wpaper:2016.12. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mireille Chiroleu-Assouline). General contact details of provider: http://edirc.repec.org/data/faereea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.