Building an Environmental Quality Index for a big city: a spatial interpolation approach with DP2
The elaboration of Environmental Quality Indexes (EQI) for big cities is one of the main topics in regional and environmental economics. One of the usual methodological paths consists of generating a single measure as a linear combination of several air contaminants applying Principal Component Analysis (PCA). Then, as a final step, a spatial interpolation is carried out to determine the level of contamination across the city in order to point out the so-called ‘hot points’. In this article, we propose an alternative approach to build an EQI introducing some methodological and practical novelties. From the point of view of the selection of the variables, first we will consider noise -joint to air pollution- as a relevant environmental variable. We also propose to add ‘subjective’ data -available at the census tracts level- to the group of ‘objective’ environmental variables, which are only available at a number of environmental monitoring stations. This combination leads to a mixed environmental index (MEQI), which is more complete and adequate in a socioeconomic context. From the point of view of the computation process, we use kriging to match the monitoring stations registers to the Census data. We follow an inverse process as usual, since it leads to better estimates. In a first step, we krige the environmental variables to the complete surface and finally, we elaborate the environmental index. At last, in order to build the final synthetic index, we do not use Principal Components Analysis -as it is usual in this kind of exercises- but a better one, the Pena Distance method (DP2).
|Date of creation:||24 Sep 2008|
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- De Iaco, S. & Myers, D. E. & Posa, D., 2002. "Space-time variograms and a functional form for total air pollution measurements," Computational Statistics & Data Analysis, Elsevier, vol. 41(2), pages 311-328, December.
- Jon P. Nelson, 2004. "Meta-Analysis of Airport Noise and Hedonic Property Values," Journal of Transport Economics and Policy, University of Bath, vol. 38(1), pages 1-27, January.
- Banzhaf, H. Spencer, 2002.
"Green Price Indices,"
dp-02-09-, Resources For the Future.
- Delucchi, Mark & Murphy, James & McCubbin, Donald, 2002. "The Health and Visibility Cost of Air Pollution: A Comparison of Estimation Methods," Institute of Transportation Studies, Working Paper Series qt03s2x9xb, Institute of Transportation Studies, UC Davis.
- Smith, V Kerry & Huang, Ju-Chin, 1995. "Can Markets Value Air Quality? A Meta-analysis of Hedonic Property Value Models," Journal of Political Economy, University of Chicago Press, vol. 103(1), pages 209-27, February.
- Kenneth Y. Chay & Michael Greenstone, 2005.
"Does Air Quality Matter? Evidence from the Housing Market,"
Journal of Political Economy,
University of Chicago Press, vol. 113(2), pages 376-424, April.
- Kenneth Y. Chay & Michael Greenstone, 1998. "Does Air Quality Matter? Evidence from the Housing Market," NBER Working Papers 6826, National Bureau of Economic Research, Inc.
- Kim, Chong Won & Phipps, Tim T. & Anselin, Luc, 1998.
"Measuring The Benefits Of Air Quality Improvement: A Spatial Hedonic Approach,"
1998 Annual meeting, August 2-5, Salt Lake City, UT
20959, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
- Gotway C.A. & Young L.J., 2002. "Combining Incompatible Spatial Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 632-648, June.
- Helen R. Neill & David M. Hassenzahl & Djeto D. Assane, 2007. "Estimating the Effect of Air Quality: Spatial versus Traditional Hedonic Price Models," Southern Economic Journal, Southern Economic Association, vol. 73(4), pages 1088–1111, April.
- Luc Anselin & Nancy Lozano-Gracia, 2008. "Errors in variables and spatial effects in hedonic house price models of ambient air quality," Empirical Economics, Springer, vol. 34(1), pages 5-34, February.
- Tzeng, ShengLi & Huang, Hsin-Cheng & Cressie, Noel, 2005. "A Fast, Optimal Spatial-Prediction Method for Massive Datasets," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1343-1357, December.
- V. Smith & Ju Huang, 1993. "Hedonic models and air pollution: Twenty-five years and counting," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 3(4), pages 381-394, August.
- Spence, Jeffrey S. & Carmack, Patrick S. & Gunst, Richard F. & Schucany, William R. & Woodward, Wayne A. & Haley, Robert W., 2007. "Accounting for Spatial Dependence in the Analysis of SPECT Brain Imaging Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 464-473, June.
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