Environmental and Resource Economics

, Volume 37, Issue 1, pp 211–232 | Cite as

Beyond implicit prices: recovering theoretically consistent and transferable values for noise avoidance from a hedonic property price model

  • Brett Day
  • Ian Bateman
  • Iain Lake


Using a two-stage hedonic pricing methodology we estimate a system of structural demand equations for different sources of transport-related noise. In the first stage, we identify market segments using model-based clustering techniques and estimate separate hedonic price functions (HPFs) for each segment. In so doing, we show how a semiparametric spatial smoothing estimator outperforms other standard specifications of the HPF. In the second stage, we control for non-linearity of the budget constraint and identify demand relationships using techniques that account for problems of endogeneity and censoring of the dependent variable. Our estimated demand functions provide welfare estimates for peace and quiet that we believe to be the first derived from property market data in a theoretically consistent manner.


Noise Non-market valuation Hedonic pricing Model-based clustering Partial linear model Spatial smoothing Demand system Simultaneous-equation Tobit 

JEL Classifications

Q51 C14 C21 C24 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Abraham JM, Goetzmann WN and Wachter SM (1994). Homogenous groupings of metropolitan housing markets. J Housing Econ 3(3): 186–206 CrossRefGoogle Scholar
  2. Allen MT, Springer TM and Waller NG (1995). Implicit pricing across residential rental markets. J Real Estate Finance Econ 11: 137–151 CrossRefGoogle Scholar
  3. Amemiya T (1979). The estimation of a simultaneous-equation Tobit model. Int Econ Rev 20(1): 169–181 CrossRefGoogle Scholar
  4. Anglin PM and Gencay R (1996). Semiparametric estimation of a hedonic price function. J Appl Economet 11: 633–648 CrossRefGoogle Scholar
  5. Bajic V (1993). Automobiles and implicit markets: An estimate of a structural demand model for automobile characteristics. Appl Econ 25(4): 541–551 Google Scholar
  6. Barde J-P (2007) Harnessing the political economy of environmental policy: David Pearce’s contribution to OECD, Environ Resour Econ 37(1): 33–42 (this issue)Google Scholar
  7. Bartik TJ (1988). Measuring the benefits of amenity improvements. Land Econ 64(2): 172–183 CrossRefGoogle Scholar
  8. Bateman IJ, Day BH, Lake I and Lovett AA (2001). The effect of road traffic on residential property value: a literature review and hedonic pricing study. Scottish Executive and The Stationary Office, Edinburgh Google Scholar
  9. Bateman IJ, Day BH and Lake I (2004). The valuation of transport-related noise in Birmingham. Technical Report to the Department for Transport. University of East Anglia, Norwich Google Scholar
  10. Bell K and Bockstael NE (2000). Applying the generalised method of moments approach to spatial problems involving micro-level data. Rev Econ Stat 82(1): 72–82 CrossRefGoogle Scholar
  11. Blomquist NS (1989). Comparative statics for utility maximization models with nonlinear budget constraints. Int Econ Rev 30: 275–296 CrossRefGoogle Scholar
  12. Bourassa SC, Hamelink F, Hoesli M and MacGregor BD (1999). Defining housing submarkets. J Housing Econ 8: 160–183 CrossRefGoogle Scholar
  13. Boyle KJ, Poor PJ and Taylor LO (1999). Estimating the demand for protecting freshwater lakes from eutrophication. Am J Agric Econ 81(5): 1118–1122 CrossRefGoogle Scholar
  14. Brown JN and Rosen HS (1982). On the estimation of structural hedonic price models. Econometrica 50(3): 765–768 CrossRefGoogle Scholar
  15. Carson RT, Groves T (2007) Incentive and informational properties of preference questions, Environ Resour EconGoogle Scholar
  16. Cheshire P and Sheppard S (1998). Estimating the demand for housing, land and neighbourhood characteristics. Oxford Bull Econ Stat 60(3): 357–382 CrossRefGoogle Scholar
  17. Cliff A and Ord JK (1972). Testing for spatial autocorrelation among regression residuals. Geogr Anal 4: 267–284 CrossRefGoogle Scholar
  18. Day BH (2005) Hedonic analysis of property markets: theory and applications to UK cities. PhD Thesis, Department of Economics, University College London.Google Scholar
  19. Department for Transport (DfT) (2006) Transport analysis guidance. TAG Unit 3.3.2: Noise, London: DfT; Scholar
  20. Department for Environment, Food & Rural Affairs (DEFRA) (2000) A report on the production of noise maps of the City of Birmingham. DEFRA, LondonGoogle Scholar
  21. Edlefsen LE (1981). The comparative statics of hedonic price functions and other nonlinear constraints. Econometrica 49: 1501–1520 CrossRefGoogle Scholar
  22. Ekeland I, Heckman JJ and Nesheim L (2002). Identifying hedonic models. Am Econ Rev 92(2): 304–309 CrossRefGoogle Scholar
  23. Ekeland I, Heckman JJ and Nesheim L (2004). Identification and estimation of hedonic models. J Polit Econ 112(1): 60–109 Google Scholar
  24. European Commission (EC) (1996) Future noise policy – European Commission Green Paper. Report COM(96) 540 final. European Commission, BrusselsGoogle Scholar
  25. European Commission (EC) (2002) Directive 2002/49/EC for the assessment and management of environmental noise. Official Journal of the European Communities L189/12, European Commission, BrusselsGoogle Scholar
  26. Fraley C and Raftery AE (1998). How many clusters? Which clustering method? Answers via model-based cluster analysis. Computer J 41(8): 578–588 CrossRefGoogle Scholar
  27. Geweke J (1986). Exact inference in the inequality constrained normal linear regression model. J Appl Econ 1: 127–141 CrossRefGoogle Scholar
  28. Gibbons S and Machin S (2003). Valuing English primary schools. J Urban Econ 53(2): 197–219 CrossRefGoogle Scholar
  29. Goetzmann WN and Wachter SM (1995). Clustering methods for real estate portfolios. Real Estate Econ 23(3): 271–310 CrossRefGoogle Scholar
  30. Haab TC and McConnell KE (2003). Valuing environmental and natural resources: the econometrics of nonmarket valuation. Edward Elgar, Northampton, MA Google Scholar
  31. Hanemann WM (1991). Willingness to pay and willingness to accept: how much can they differ?. Am Econ Rev 81(3): 635–647 Google Scholar
  32. Heckman J, Matzkin R, Nesheim L (2003) Simulation and estimation of hedonic models. CENMAP working paper, CWP10/03. Institute of Fiscal Studies, UCL, LondonGoogle Scholar
  33. Kelejian HH and Prucha IR (1999). A generalised moments estimator for the autoregressive parameter in a spatial model. Int Econ Rev 40(2): 509–533 CrossRefGoogle Scholar
  34. Kelejian HH and Robinson DP (1992). Spatial autocorrelation: a new computationally simple test with an application to per capita county police expenditures. Regional Sci Urban Econ 22: 317–331 CrossRefGoogle Scholar
  35. McConnell KE and Phipps TT (1987). Identification of preference parameters in hedonic models: consumer with nonlinear budgets. J Urban Econ 22: 35–52 CrossRefGoogle Scholar
  36. Murray MP (1982). Mythical demands and supplies for proper estimation of Rosen’s hedonic price model. J Urban Econ 14: 327–337 CrossRefGoogle Scholar
  37. Nellthorp J, Bristow AL, Day BH (forthcoming) Introducing willingness-to-pay for noise changes into transport appraisal – an application of benefit transfer. Transport RevGoogle Scholar
  38. Nesheim L (2002) Equilibrium sorting of heterogeneous consumers across locations: theory and empirical implications. CEMMAP working paper, CWP08/02. Institute of Fiscal Studies, Department of Economics, University College LondonGoogle Scholar
  39. Newey WK (1987). Efficient estimation of limited dependent variable models with endogenous explanatory variables. J Econometr 36(3): 231–250 CrossRefGoogle Scholar
  40. Odgaard T, Kelly C, Laird J (2005) Current practice in project appraisal in Europe: analysis of country reports. HEATCO Work Package 3 Deliverable 1. IER, University of StuttgartGoogle Scholar
  41. Palmquist RB (1988). Welfare measurement for environmental improvements using the hedonic model: the case of nonparametric marginal prices. J Environ Econ Manage 15: 297–312 CrossRefGoogle Scholar
  42. Palmquist RB and Isangkura A (1999). Valuing air quality with hedonic and discrete choice models. Am J Agric Econ 81(5): 1128–1133 CrossRefGoogle Scholar
  43. Posse C (2001). Hierarchical model-based clustering for large datasets. J Comput Graphical Stat 10(3): 464–486 CrossRefGoogle Scholar
  44. Randall A and Stoll JR (1980). Consumer’s surplus in commodity space. Am Econ Rev 70(3): 449–457 Google Scholar
  45. Robinson PM (1988). Root-N-consistent semiparametric regression. Econometrica 56: 931–954 CrossRefGoogle Scholar
  46. Rosen S (1974). Hedonic prices and implicit markets: production differentiation in pure competition. J Polit Econ 82: 34–55 CrossRefGoogle Scholar
  47. Smith RJ and Blundell RW (1986). An exogeneity test for a simultaneous equation Tobit model with an application to labor supply. Econometrica 54(3): 679–685 CrossRefGoogle Scholar
  48. Turner K (2007) Limits to CBA in UK and European environmental policy: retrospect & future prospects. Environ Resour Econ 37(1): 253–269 (this issue)Google Scholar
  49. Watkins CA (2001). The definition and identification of housing submarkets. Environ Plan A 33: 2235–2253 CrossRefGoogle Scholar
  50. Weesie J (1999). Seemingly unrelated estimation: an application of the cluster-adjusted sandwich estimator. Stata Technical Bull 52: 34–47 Google Scholar
  51. Willig RD (1976). Consumer’s surplus without apology. Am Econ Rev 66(4): 589–597 Google Scholar
  52. Zabel JE and Kiel KA (2000). Estimating the demand for air quality in four U.S. cities. Land Econ 76(2): 174–194 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  1. 1.Centre for Social and Economic Research on the Global Environment, School of Environmental SciencesUniversity of East AngliaNorwichUK
  2. 2.Centre for Environmental Risk, School of Environmental SciencesUniversity of East AngliaNorwichUK

Personalised recommendations