Advertisement

A generalized method of moments estimator for a spatial model with moving average errors, with application to real estate prices

  • Bernard FingletonEmail author
Part of the Studies in Empirical Economics book series (STUDEMP)

This paper proposes a new GMM estimator for spatial regression models with moving average errors. Monte Carlo results are given which suggest that the GMM estimates are consistent and robust to non-normality, and the Bootstrap method is suggested as a way of testing the significance of the moving average parameter. The estimator is applied in a model of English real estate prices, in which the concepts of displaced demand and displaced supply are introduced to derive the spatial lag of prices, and the moving average error process represents spatially autocorrelated unmodelled variables.

Keywords

Moving averages GMM Real estate Spatial econometrics 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anselin L (1988a) Lagrange multiplier test diagnostics for spatial dependence and spatial heterogeneity.Geogr Anal 20:1–17Google Scholar
  2. Anselin L (1988b) Spatial econometrics: methods and models. Kluwer, DordrechtGoogle Scholar
  3. Anselin L (2003) Spatial externalities, spatial multipliers, and spatial econometrics. Int Reg Sci Rev 26: 153–166CrossRefGoogle Scholar
  4. Anselin L, Kelejian HH (1997) Testing for spatial error autocorrelation in the presence of endogenous regressors. Int Reg Sci Rev 20:153–182CrossRefGoogle Scholar
  5. Anselin L, Florax R (1995) New directions in spatial econometrics. Springer, LondonGoogle Scholar
  6. Anselin L, Bera A (1998) Spatial dependence in linear regression models with an introduction to spatial econometrics. In: Ullah A, Giles DE (eds) Handbook of applied economic statistics. Marcel Dekker, New YorkGoogle Scholar
  7. Brueckner JK (2003) Strategic interaction among governments: an overview of empirical studies. Int Reg Sci Rev 26:175–188CrossRefGoogle Scholar
  8. Cheshire P, Sheppard S (2004) Capitalising the value of free schools: the impact of supply characteristics and uncertainty. Econ J 114:F397–F424CrossRefGoogle Scholar
  9. Cliff AD, Ord JK (1981) Spatial processes : models and applications. Pion, LondonGoogle Scholar
  10. Dubin RA (1988) Estimation of regression coefficients in the presence of spatially autocorrelated error terms. Rev Econ Stat 70:466–474CrossRefGoogle Scholar
  11. Gibbons S, Machin S (2003) Valuing english primary schools. J Urban Econ 53:197–219CrossRefGoogle Scholar
  12. Haining RP (1978) The moving average model for spatial interaction. Trans Inst Br Geogr 3:202–225CrossRefGoogle Scholar
  13. Kapoor M, Kelejian HH, Prucha I (2007) Panel data models with spatially correlated error components. J Econom (forthcoming)Google Scholar
  14. Kelejian HH, Robinson DP (1993) A suggested method of estimation for spatial interdependent models with autocorrelated errors, and an application to a county expenditure model. Papers Reg Sci 72:297–312CrossRefGoogle Scholar
  15. Kelejian HH, Prucha IR (1998) A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. J Real Estate Financ Econ 17:99–121CrossRefGoogle Scholar
  16. Kelejian HH, Prucha IR (1999) A generalized moments estimator for the autoregressive parameter in a spatial model. Int Econ Rev 40:509–533CrossRefGoogle Scholar
  17. Kelejian HH, Prucha IR (2004) Estimation of simultaneous systems of spatially interrelated cross sectional equations. J Econom 118:27–50CrossRefGoogle Scholar
  18. Leech D, Campos E (2003) Is comprehensive education really free? : acase-studyof the effects ofsecondary school admissions policies on house prices in one local area. J Roy Stat Soc A 166:135–154CrossRefGoogle Scholar
  19. Ord JK (1975) Estimation methods for models of spatial interaction. J Am Stat Assoc 70:120–126CrossRefGoogle Scholar
  20. Upton GJG, Fingleton B (1985) Spatial data analysis by example, vol 1. Wiley, ChichesterGoogle Scholar

Copyright information

© Physica-Verlag Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Land EconomyCambridge UniversityCambridgeUK

Personalised recommendations