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Additive Models: Extensions and Related Models

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  • Enno Mammen
  • Byeong U. Park
  • Melanie Schienle

Abstract

We give an overview over smooth back tting type estimators in additive models. Moreover we il- lustrate their wide applicability in models closely related to additive models such as nonparametric regression with dependent error variables where the errors can be transformed to white noise by a linear transformation, nonparametric regression with repeatedly measured data, nonparametric panels with xed e ects, simultaneous nonparametric equation models, and non- and semiparamet- ric autoregression and GARCH-models. We also discuss extensions to varying coecient models, additive models with missing observations, and the case of nonstationary covariates.

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File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2012-045.pdf
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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2012-045.

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Length: 30 pages
Date of creation: Jul 2012
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2012-045

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Keywords: smooth backfitting; additive models;

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References

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  1. Oliver Linton & Søren Feodor Nielsen & Jens Perch Nielsen, 2009. "Nonparametric Regression with a Latent Time Series," STICERD - Econometrics Paper Series /2009/538, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Park, Byeong U. & Mammen, Enno & Härdle, Wolfgang & Borak, Szymon, 2009. "Time Series Modelling With Semiparametric Factor Dynamics," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 284-298.
  3. Whitney Newey & James Powell & Francis Vella, 1998. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Working papers 98-16, Massachusetts Institute of Technology (MIT), Department of Economics.
  4. Göran Kauermann, 2003. "Local Likelihood Estimation in Generalized Additive Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 30(2), pages 317-337.
  5. Oliver B. Linton & Enno Mammen & J. Nielsen & Carsten Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," Econometric Society World Congress 2000 Contributed Papers 0235, Econometric Society.
  6. Raymond J. Carroll & Arnab Maity & Enno Mammen & Kyusang Yu, 2009. "Nonparametric additive regression for repeatedly measured data," Biometrika, Biometrika Trust, vol. 96(2), pages 383-398.
  7. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  8. Chen, Xiaohong & Reiss, Markus, 2011. "On Rate Optimality For Ill-Posed Inverse Problems In Econometrics," Econometric Theory, Cambridge University Press, vol. 27(03), pages 497-521, June.
  9. Darolles, Serge & Fan, Yanqin & Florens, Jean-Pierre & Renault, Eric, 2003. "Non Parametric Instrumental Regression," IDEI Working Papers 228, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2010.
  10. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
  11. Oliver Linton & E. Mammen & J. Nielsen, 1999. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 300, London School of Economics and Political Science, LSE Library.
  12. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  13. Berthold R. Haag, 2008. "Non-parametric Regression Tests Using Dimension Reduction Techniques," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 35(4), pages 719-738.
  14. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  15. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  16. Oliver Linton & Enno Mammen, 2006. "Nonparametric Transformation to White Noise," STICERD - Econometrics Paper Series /2006/503, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  17. Stefan Hoderlein & Enno Mammen & Kyusang Yu, 2011. "Non‐parametric models in binary choice fixed effects panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 351-367, October.
  18. Enno Mammen, 2003. "Generalised structured models," Biometrika, Biometrika Trust, vol. 90(3), pages 551-566, September.
  19. Mammen, Enno & Støve, Bård & Tjøstheim, Dag, 2009. "Nonparametric Additive Models For Panels Of Time Series," Econometric Theory, Cambridge University Press, vol. 25(02), pages 442-481, April.
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