Regresión con variables ortogonales y regresión alzada en el modelo STIRPAT

  1. Claudia García García 1
  2. Catalina B. García García 1
  3. Román salmerón Gómez 1
  4. José García Pérez 2
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 Universidad de Almería
    info

    Universidad de Almería

    Almería, España

    ROR https://ror.org/003d3xx08

Journal:
Estudios de economía aplicada

ISSN: 1133-3197,  1697-5731

Year of publication: 2017

Issue Title: Crisis, Economía y Finanzas

Volume: 35

Issue: 3

Pages: 717-734

Type: Article

DOI: 10.25115/EEA.V35I3.2504 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: Estudios de economía aplicada

Abstract

STIRPAT model is one of the most analyzed methodologies in environmental studies. The specification of this econometric model provokes multicollinearity. Although a first option could be to eliminate the variable (or variables) that generates the collinearity, it does not allow to estimate the effects of the main forces driving environmental impacts. It is necessary to develop or to apply new methods that could mitigate the collinearity problem in the STIRPAT model. This work applies two methodologies alternatives to the traditional Ordinary Least Squares (OLS) estimation: the raise regression and the regression with orthogonal variables. Both methodologies manage to mitigate the collinearity between variables that exists in the original model, and furthermore, they have two different perspectives about the variables: while the raised method has an important geometric factor in its application, the purpose of the regression with orthogonal variables is to give new interpretations of the variables

Bibliographic References

  • BELSLEY, D.; KUH, E.; WELSCH, R. (1980). Regression diagnostics: Identifying influential data and sources of collinearity. Nueva York: John Wiley and Sons.
  • BÜCHS, M.; SCHNEPF, S.V. (2013). “Who emits most? Associations between socio-economic facors and UK households’ home energy, transport, indirect and total CO2 emissions”. Ecological Economics, 90, pp. 114-123.
  • COMMONER, B.; CORR, M.; STAMLER, P. (1971). “The causes of pollution”. Environment: Science and Policy for Sustainable Development, 13(3), pp. 2-19.
  • DIETZ, T.; ROSA, E.A. (1994). “Rethinking the environmental impacts of population, affluence and technology”. Human Ecology Review, 1, pp. 277-300.
  • DISLI, M.; NG, A.; ASKARI, H. (2016). “Culture, income, and CO2 emission”. Renewable and Sustainable Energy Reviews, 62, pp. 418-428.
  • DONG, J.; DENG, C.; LI, R.; HUANG, J. (2017). “Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models”. Sustainability, 9, pp. 24.
  • EHRLICH, P.R.; HOLDREN, J.P. (1970). “The people problem”. Saturday Review, 4(42), pp. 42-43.
  • EHRLICH, P.R.; HOLDREN, J.P. (1971). “The Impact of Population Growth”. Science, 171(3977), pp. 1212-1217.
  • EHRLICH, P.R.; HOLDREN, J.P. (1972). “One-dimensional economy”. Bulletin of the Atomic Scientists, 28(5), pp. 16-27.
  • FAN, Y.; LIU, L.C.; WU, G.; WEI, Y.M. (2006). “Analyzing impact factors of CO2 emissions using the STIRPAT model”. Environmental Impact Assessment Review, 26(4), pp. 377-395.
  • GARCÍA, J.; GARCÍA, C.B., LÓPEZ, M.M.; SALMERÓN, R. (2013). “Desarrollo del método de alzado para el tratamiento de la multicolinealidad. Determinacion del factor de alzamiento”. En XXVII International Conference of Applied Economics, 1848-1862.
  • GARCÍA, J.; SALMERÓN, R.; GARCÍA, C.B.; LÓPEZ, M.M. (2017). “The raise estimator estimation, inference, and properties”. Communications in Statistics-Theory and Methods, 46(13), pp. 6446-6462.
  • GASSEBNER, M.; LAMLA, M.J.; STURM, J.E. (2011). “Determinants of pollution: what do we really know?” Oxford Economic Papers, 63, pp. 568-595.
  • HAIR, J.F.J.; ANDERSON, R.E.; TATHAM, R.L.; BLACK, W.C. (1995). Multivariate Data Analysis. New York: MacMillan.
  • HARBAUGH, W.T.; LEVINSON, A.; WILSON, D.M. (2002). “Reexamining the Empirical Evidence for an Environmental Kuznets Curve.” The Review of Economics and Statistics, 84(3), pp. 541-551.
  • JIA, J.; DENG, H.; DUAN, J.; ZHAO, J. (2009). “Analysis of the major drivers of the ecological footprint using the STIRPAT model and the PLS method. A case study in Henan Province, China.” Ecological Economics, 68(11), pp. 2818-2824.
  • KENNEDY, P. (1992). A Guide to Econometrics. Oxford: Blackwell.
  • LIN, S.; ZHAO, D.; MARINOVA, D. (2009). “Analysis of the environmental impact of China based on STIRPAT model”. Environmental Impact Assessment Review, 29(6), pp. 341-347.
  • MARQUARDT, D.W. (1970). “Generalized inverses, ridge regression, biased linear estimation and nonlinear estimation.” Technometrics, 12(3), pp. 591-612.
  • MARTÍNEZ-ZARZOSO, I.; BENGOCHEA-MORANCHO, A.; MORALES-LAGE, R. (2007). “The impact of population on CO2 emissions: evidence from European countries.” Environmental and Resource Economics, 38(4), pp. 497-512.
  • NETER, J.; WASSERMAN, W.; KUTNER, M.H. (1989). Applied Linear Regression Models. Homewood: Irwin.
  • NOVALES, A.; SALMERÓN, R.; GARCÍA, C.B.; GARCÍA, J.; LÓPEZ, M.M. (2015). “Tratamiento de la multicolinealidad aproximada mediante variables ortogonales.” Anales de Economía Aplicada, pp. 1212-1227.
  • RASKIN, P. (1995). “Methods for estimating the population contribution to environmental change”. Ecological Economics, 15(3), pp. 225-233.
  • ROSA, E.; DIETZ, T. (1998). “Climate change and society: speculation, construction and scientific investigation”. International Sociology, 13(4), pp. 421-455.
  • SALMERÓN, R.; GARCÍA, J.; GARCÍA, C.B.; GARCÍA, C. (2016). “Treatment of collinearity through orthogonal regression: an economic application”. Boletín de Estadística e Investigación Operativa, 32(3), pp. 184-202.
  • SCHULZE, P.C. (2002). “I = PBAT”. Ecological Economics, 40(2), pp. 149-150.
  • UDDIN, G.; ALAM, K.; GOW, J. (2016). “Estimating the major contributors to environmental impacts in Australia”. International Journal of Ecological Economics and Statistics, 37(1), pp. 1-14.
  • WAGGONER, P.E.; AUSUBEL, J.H. (2002). “A framework for sustainability science: a renovated IPAT identity”. Proceedings of the National Academy of Sciences, 99(12), pp. 7860-7865.
  • YORK, R.; ROSA, E.A.; DIETZ, T. (2003). “STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts”. Ecological Economics, 46(3), pp. 351-365.
Data source: Dialnet