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Computation of Box-Cox Transform Parameters: A New Method and its Application to Spatial Econometrics

In: New Directions in Spatial Econometrics

Author

Listed:
  • Reinaud A. J. J. Gastel

    (Erasmus University)

  • Jean H. P. Paelinck

    (Erasmus University)

Abstract

The reason for undertaking the present investigation is that, in spatial econometrics, as was argued in Paelinck and Klaassen (1979, pp. 6–9), econometric relations in space result more often than not in highly non-linear specifications. This is very probably even more the case if services or enterprise functions in space are considered [Paelinck (1987)].

Suggested Citation

  • Reinaud A. J. J. Gastel & Jean H. P. Paelinck, 1995. "Computation of Box-Cox Transform Parameters: A New Method and its Application to Spatial Econometrics," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 6, pages 136-155, Springer.
  • Handle: RePEc:spr:adspcp:978-3-642-79877-1_6
    DOI: 10.1007/978-3-642-79877-1_6
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    Cited by:

    1. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    2. Malikov, Emir & Sun, Yiguo, 2017. "Semiparametric estimation and testing of smooth coefficient spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 199(1), pages 12-34.
    3. Su, Liangjun & Jin, Sainan, 2010. "Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 157(1), pages 18-33, July.

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