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Functional Coefficient Models for Economic and Financial Data

  • Zongwu Cai

This paper gives a selective overview on the functional coefficient models with their particular applications in economics and finance. Functional coefficient models are very useful analytic tools to explore complex dynamic structures and evolutions for functional data in various areas, particularly in economics and finance. They are natural generalizations of classical parametric models with good interpretability by allowing coefficients to be governed by some variables or to change over time, and also they have abilities to capture nonlinearity and heteroscedasticity. Furthermore, they can be regarded as one of dimensionality reduction methods for functional data exploration and have nice interpretability. Due to their great properties, functional coefficient models have had many methodological and theoretical developments and they have become very popular in various applications.

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Paper provided by Wang Yanan Institute for Studies in Economics (WISE), Xiamen University in its series WISE Working Papers with number 2013-10-14.

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Date of creation: 14 Oct 2013
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Publication status: published
Handle: RePEc:wyi:wpaper:002009
Contact details of provider: Web page: http://www.wise.xmu.edu.cn/english/

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  1. Bruce E. Hansen, 1996. "Sample Splitting and Threshold Estimation," Boston College Working Papers in Economics 319., Boston College Department of Economics, revised 12 May 1998.
  2. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
  3. Li, Qi, et al, 2002. "Semiparametric Smooth Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 412-22, July.
  4. David Card, 2000. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," NBER Working Papers 7769, National Bureau of Economic Research, Inc.
  5. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  6. Cochrane, John H, 1996. "A Cross-Sectional Test of an Investment-Based Asset Pricing Model," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 572-621, June.
  7. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
  8. Wayne E. Ferson & Campbell R. Harvey, 1999. "Conditioning Variables and the Cross-Section of Stock Returns," NBER Working Papers 7009, National Bureau of Economic Research, Inc.
  9. Yongmiao Hong & Tae-Hwy Lee, 2003. "Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1048-1062, November.
  10. Andrew Ang & Jun Liu, 2003. "How to Discount Cashflows with Time-Varying Expected Returns," NBER Working Papers 10042, National Bureau of Economic Research, Inc.
  11. Eric Ghysels, 1998. "On Stable Factor Structures in the Pricing of Risk: Do Time-Varying Betas Help or Hurt?," Journal of Finance, American Finance Association, vol. 53(2), pages 549-573, 04.
  12. Xiaoping Xu & Zongwu Cai, 2013. "Nonparametric Quantile Estimations For Dynamic Smooth Coefficient Models," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  13. Kevin Q. Wang, 2003. "Asset Pricing with Conditioning Information: A New Test," Journal of Finance, American Finance Association, vol. 58(1), pages 161-196, 02.
  14. Davis, Richard A. & Lee, Thomas C.M. & Rodriguez-Yam, Gabriel A., 2006. "Structural Break Estimation for Nonstationary Time Series Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 223-239, March.
  15. Ravi Jagannathan & Zhenyu Wang, 2002. "Empirical Evaluation of Asset-Pricing Models: A Comparison of the SDF and Beta Methods," Journal of Finance, American Finance Association, vol. 57(5), pages 2337-2367, October.
  16. Harvey, Campbell R., 1989. "Time-varying conditional covariances in tests of asset pricing models," Journal of Financial Economics, Elsevier, vol. 24(2), pages 289-317.
  17. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  18. Phillips, Peter C. B., 2001. "Trending time series and macroeconomic activity: Some present and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 21-27, January.
  19. Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
  20. Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
  21. Cai, Zongwu & Das, Mitali & Xiong, Huaiyu & Wu, Xizhi, 2006. "Functional coefficient instrumental variables models," Journal of Econometrics, Elsevier, vol. 133(1), pages 207-241, July.
  22. Jagannathan, Ravi & Wang, Zhenyu, 1996. " The Conditional CAPM and the Cross-Section of Expected Returns," Journal of Finance, American Finance Association, vol. 51(1), pages 3-53, March.
  23. Fan J. & Zhang C., 2003. "A Reexamination of Diffusion Estimators With Applications to Financial Model Validation," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 118-134, January.
  24. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  25. Bansal, Ravi & Viswanathan, S, 1993. " No Arbitrage and Arbitrage Pricing: A New Approach," Journal of Finance, American Finance Association, vol. 48(4), pages 1231-62, September.
  26. Zongwu Cai, 2002. "A two-stage approach to additive time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(4), pages 415-433.
  27. Damla Şentürk & Hans-Georg Müller, 2008. "Generalized varying coefficient models for longitudinal data," Biometrika, Biometrika Trust, vol. 95(3), pages 653-666.
  28. DAMLA ŞENTÜRK & HANS-GEORG MÜLLER, 2005. "Covariate Adjusted Correlation Analysis via Varying Coefficient Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 365-383.
  29. Caner, Mehmet & Hansen, Bruce E., 2004. "Instrumental Variable Estimation Of A Threshold Model," Econometric Theory, Cambridge University Press, vol. 20(05), pages 813-843, October.
  30. Jianhua Z. Huang & Haipeng Shen, 2004. "Functional Coefficient Regression Models for Non-linear Time Series: A Polynomial Spline Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(4), pages 515-534.
  31. Bansal, Ravi & Hsieh, David A & Viswanathan, S, 1993. " A New Approach to International Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 48(5), pages 1719-47, December.
  32. Wang, Kevin Q., 2002. "Nonparametric tests of conditional mean-variance efficiency of a benchmark portfolio," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 133-169, March.
  33. Reyes, Mario G., 1999. "Size, time-varying beta, and conditional heteroscedasticity in UK stock returns," Review of Financial Economics, Elsevier, vol. 8(1), pages 1-10, June.
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