402
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Inference of the Trend in a Partially Linear Model with Locally Stationary Regressors

REFERENCES

  • Ball, L., Mankiw, N. G. (2002). The NAIRU in theory and practice. Journal of Economic Perspectives 16:115–136.
  • Bickel, P. J., Rosenblatt, M. (1973). On some global measures of the deviations of density function estimates. Annals of Statistics 1:1071–1095.
  • Cai, Z. (2007). Trending time-varying coefficient time series models with serially correlated errors. Journal of Econometrics 136:163–188.
  • Carlstein, E. (1986). The use of subseries values for estimating the variance of a general statistic from a stationary sequence. The Annals of Statistics 14:1171–1179.
  • Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterlpots. Journal of the American Statistical Association 74:829–836.
  • Craven, P., Wahba, G. (1979). Smoothing noisy data with spline functions. Numerische Mathematik 31: 377–403.
  • Dahlhaus, R. (1997). Fitting time series models to non-stationary processes. Annals of Statistics 25:1–37.
  • Engle, R. F. (1982). Autoregressive conditional Heteroscedasticity with estimates of the variance of united kingdom inflation. Econometrica 50:987–1007.
  • Eubank, R. L., Speckman, P. L. (1993). Confidence bands in nonparametric regression. Journal of the American Statistical Association 88:1287–1301.
  • Fair, R. C. (2000). Testing the NAIRU model for the United States. The Review of Economics and Statistics 82:64–71.
  • Fan, J., Gijbels, I. (1996). Local Polynomial Modelling and Its Applications. London: Chapman and Hall.
  • Fan, J., Zhang, W. (2000). Simultaneous confidence bands and Hypothesis testing in varying-coefficient models. Scandinavian Journal of Statistics 27:715–731.
  • Gao, J., Hawthorne, K. (2006). Semiparametric estimation and testing of the trend of temperature series. Econometrics Journal 9:332–355.
  • González, A., Hubrich, K., Teräsvirta, T. (2009). Forecasting inflation with gradual regime shifts and exogenous information. Manuscript.
  • González, A., Teräsvirta, T. (2008). Modelling autoregressive processes with a shifting mean. Studies in Nonlinear Dynamics & Econometrics 12:1–28.
  • Gordon, R. J. (1997). The time-varying NAIRU and its implications for Economic policy. Journal of Economic Perspectives 11:11–32.
  • Gordon, R. J. (1998). Foundations of the Goldilocks economy: Supply shocks and the time-varying NAIRU. Brookings Papers on Economic Activity 2:197–333.
  • Hall, P. (1991). On Convergence rates of suprema. Probability Theory and Related Fields 89:447–455.
  • Härdle, W. (1986). A note on jackknifing kernel regression function estimators. IEEE Transactions on Information Theory 32:298–300.
  • Härdle, W. K., Liang, H., Gao, J. (2000). Partially Linear Models. Heidelberg: Physica-Verlag.
  • Härdle, W. K., Song, S. (2010). Confidence bands in quantile regression. Econometric Theory 26:1180–1200.
  • Johnston, G. J. (1982). Probabilities of maximal deviations for nonparametric regression function estimates. Journal of Multivariate Analysis 12:402–414.
  • Kim, K. H. (2014). Counter-cyclical risk aversion. Journal of Empirical Finance 29:384–401.
  • Kim, K. H., Zhou, Z., Wu, W. B. (2010). Non-stationary structural model with time-varying demand elasticities. Journal of Statistical Planning and Inference 140:3809–3819.
  • Komlós, J., Major, P., Tusnády, G. (1975). An approximation of partial sums of independent RV's and the sample DF I. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete. 32:111–131.
  • Koo, B., Linton, O. (2012). Estimation of semiparametric locally stationary diffusion models. Journal of Econometrics 170:210–233.
  • Liu, W., Wu, W. B. (2010). Simultaneous nonparametric inference of time series. The Annals of Statistics 38:2388–2421.
  • Mallat, S., Papanicolaou, G., Zhang, Z. (1998). Adaptive covariance estimation of locally stationary processes. Annals of Statistics 26:1–47.
  • Ombao, H., Von Sachs, R., Guo, W. (2005). SLEX analysis of multivariate nonstationary time series. Journal of American Statistical Association 100:519–531.
  • Priestley, M. B. (1965). Evolutionary spectra and Non-stationary processes. Journal of the Royal Statistical Society, Series B. 27:204–237.
  • Robinson, P. M. (1988). Root-N-Consistent semiparametric regression. Econometrica 56:931–954.
  • Staiger, D., Stock, J. H., Watson, M. W. (1996). How precise are estimates of the natural rate of unemployment? NBER Working Paper No. 5477.
  • Staiger, D., Stock, J. H., Watson, M. W. (1997). The NAIRU, unemployment and monetary policy. Journal of Economic Perspectives 11:33–49.
  • Staiger, D., Stock, J. H., Watson, M. W. (2001). Prices, wages, and the U.S. NAIRU in the late 1990s. The Roaring Nineties: Can Full Employment Be Sustained? Alan B. Krueger and Robert Solow, eds., 3–60, Russell Sage Foundation, New York.
  • Tong, H. (1990). Nonlinear Time Series: A Dynamical System Approach. Oxford, U.K: Oxford University Press.
  • Vogt, M. (2012). Nonparametric Regression for Locally Stationary Time Series. Centre for Microdata Methods and Practice (CEMMAP) Working Paper CWP22/12.
  • Wu, W. B. (2005). Nonlinear system theory: Another look at dependence. Proceedings of the National Academy of Sciences USA 102:14150–14154.
  • Wu, W. B. (2007). Strong invariance principles for dependent random variables. The Annals of Probability 35:2294–2320.
  • Wu, W. B., Zhao, Z. (2007). Inference of Trends in Time Series. Journal of the Royal Statistical Society, Series B. 69:391–410.
  • Yatchew, A. (1997). An elementary estimator of the partial linear model. Economics Letters 57:135–143.
  • Zhang, T., Wu, W. B. (2012). Inference of time-varying regression models. The Annals of Statistics 40:1376–1402.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.