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A class of partially adaptive one-step m-estimators for the non-linear regression model with dependent observations

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  • Potscher, Benedikt M.
  • Prucha, Ingmar R.

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  • Potscher, Benedikt M. & Prucha, Ingmar R., 1986. "A class of partially adaptive one-step m-estimators for the non-linear regression model with dependent observations," Journal of Econometrics, Elsevier, vol. 32(2), pages 219-251, July.
    • Handle: RePEc:eee:econom:v:32:y:1986:i:2:p:219-251
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    Cited by:

    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Liebscher, Eckhard, 2003. "Strong convergence of estimators in nonlinear autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 84(2), pages 247-261, February.
    3. Joel Corrêa da Rosa & Álvaro Veiga & Marcelo C. Medeiros, 2003. "Three-structured smooth transition regression models based on CART algorithm," Textos para discussão 469, Department of Economics PUC-Rio (Brazil).
    4. Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
    5. Lima Luiz Renato & Xiao Zhijie, 2010. "Testing Unit Root Based on Partially Adaptive Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-34, June.
    6. Robinson, Peter M., 2007. "Efficient estimation of the semiparametric spatial autoregressive model," LSE Research Online Documents on Economics 4535, London School of Economics and Political Science, LSE Library.
    7. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    8. Xiao, Zhijie, 2004. "Estimating average economic growth in time series data with persistency," Journal of Macroeconomics, Elsevier, vol. 26(4), pages 699-724, December.
    9. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    10. Peter M Robinson, 2007. "Efficient Estimation of the SemiparametricSpatial Autoregressive Model," STICERD - Econometrics Paper Series 515, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. José Luis Aznarte & Marcelo Cunha Medeiros & José Manuel Benítez Sánchez, 2010. "Linearity Testing Against a Fuzzy Rule-based Model," Textos para discussão 566, Department of Economics PUC-Rio (Brazil).
    12. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    13. Robinson, P.M., 2010. "Efficient estimation of the semiparametric spatial autoregressive model," Journal of Econometrics, Elsevier, vol. 157(1), pages 6-17, July.
    14. Phillips, Robert F., 1997. "On the robustness of two alternatives to least squares: A Monte Carlo study," Economics Letters, Elsevier, vol. 56(1), pages 21-26, September.
    15. Luiz Lima & Jaime de Jesus Filho, 2008. "Further investigation of the uncertain trend in US GDP," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1207-1216.

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