Atak, Alev and Linton, Oliver B. and Xiao, Zhijie (2010): A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom. Forthcoming in: Journal of Econometrics
Download (708kB) | Preview
This paper is concerned with developing a semiparametric panel model to explain the trend in UK temperatures and other weather outcomes over the last century. We work with the monthly averaged maximum and minimum temperatures observed at the twenty six Meteorological Office stations. The data is an unbalanced panel. We allow the trend to evolve in a nonparametric way so that we obtain a fuller picture of the evolution of common temperature in the medium timescale. Profile likelihood estimators (PLE) are proposed and their statistical properties are studied. The proposed PLE has improved asymptotic property comparing the the sequential two-step estimators. Finally, forecasting based on the proposed model is studied.
|Item Type:||MPRA Paper|
|Original Title:||A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom|
|Keywords:||Global warming; Kernel estimation; Semiparametric; Trend analysis|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions
|Depositing User:||Alev Atak|
|Date Deposited:||13. Apr 2010 14:06|
|Last Modified:||02. Jul 2015 06:18|
Ahn, H., and J.L. PowellL (1993): "Estimation of Censored Selection Models with a Nonparametric Selection Mechanism." Journal of Econometrics, 58, 3-30.
Bickel, P. J., C. A. J. Klaassen, Y. Ritov, J. A. Wellner (1993): Efficient and Adaptive Inference in Semiparametric Models, Forthcoming Monograph. Baltimore: Johns Hopkins University Press.
Campbell, S.D., and F.X. Diebold. (2005). Weather Forecasting for Weather Derivatives. Center for Financial Institutions Working Papers, Wharton School Center for Financial Institutions, University of Pennsylvania
Chen, H. (1988): "Convergence Rates for Parametric Components in a Partly Linear Model," Annals of Statistics, 16, 136-146.
Engle, R. F., C. W. J. Granger, J. Rice, and A. Weiss (1986): "Semiparametric Estimates of the Relationship Between Weather and Electricity Sales," Journal of the American Statistical Association, 81, 310-320.
Fan, J. (1992): "Design-Adaptive Nonparametric Regression." Journal of the American Statistical Association, 87, 998-1004.
Fan, J. and I.Gijbels (1992): "Variable Bandwidth and Local Linear Regression Smoothers." Annals of Statistics, Forthcoming .
Gao, J. and K. Hawthorne (2006). Semiparametric estimation and testing of the trend of temperature series. Econometrics Journal 9, 332-355.
Hall, P., and C. Heyde (1980): Martingale Limit Theory and its Application. New York, Academic Press.
Hart, J.D. (1991). Kernel regression estimation with time series errors. Journal of the Royal Statistical Society, Series B. 53, 173-187.
Heckman, N.E., (1986): "Spline Smoothing in a Partly Linear Model." Journal of the Royal Statistical Society, Series B, 48, 244-248.
Hoogstrate, Andre J., Palm, Franz C., Pfann, Gerard A. (2000), "Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates", Journal of Business and Economic Statistics, Vol. 18, 3, pp. 274-83.
Issler, J.V. and L.R. Lima (2009), "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Vol. 152, pp. 153-164.
Marron, J.S. and M.P.Wand (1992): "Exact Mean Integrated Squared Error." Annals of Statistics, 20, 712-736.
Milionis, A.E. and Davies, T.D. (1994). Box-Jenkins univariate Modeling for Climatological Time Series Analysis: An Application to the Monthly Activity of Temperature Inversions. International Journal of Climatology 14 569-579.
Müller, H. G. (1988): Nonparametric Regression Analysis of Longitudinal Data. Lecture Notes in Statistics, Vol. 46. Heidelberg/New York: Springer-Verlag.
Newey, W.K., J.L. Powell, and J.R.Walker, (1990): "Semiparametric Estimation of Selection Models: Some Empirical Results." American Economic Review, 80, 324-328.
Rice, J. (1986): "Convergence Rates for Partially Splined Models." Statistics and Probability Letters, 4, 203-208.
Robinson, P.M. (1983). Nonparametric estimation for time series models. Journal of Time Series Analysis 4, 185-208.
Robinson, P. M. (1988): Root-N-Consistent Semiparametric Regression, Econometrica, 56, 931-954.
Severini, T.A. and W.H. Wong (1992). Profile likelihood and conditionally parametric models. The Annals of Statistics 20, 1768-1802.
Silverman, B. (1986): Density estimation for statistics and data analysis. London, Chapman and Hall.
Speckman, P. (1988): "Kernel Smoothing in Partial Linear Models," Journal of the Royal Statistical Society Series B, 50, 413-436.
Stock, J. H. (1989): "Nonparametric Policy Analysis," Journal of the American Statistical Association, 84, 567-576.
Stock, J. H. (1991): "Nonparametric Policy Analysis: An Application to Estimating Hazardous Waste Cleanup Benefits," in Nonparametric and Semiparametric Methods in Econometrics and Statistics. Eds Barnett, Powell, and Tauchen.
Stoker, T.M, (1989): "Tests of Average Derivative Constraints," Review of Economic Studies, 56, 535-552.
Stoker, T.M, (1993): "Smoothing Bias in Derivative Estimation." Journal of the American Statistical Association, Forthcoming.
Wikipedia. Climate Change. (2009) http://en.wikipedia.org/wiki/Climate_change