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Heteroscedasticity and Autocorrelation Efficient (HAE) Estimation and Pivots for Jointly Evolving Series

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Hrishikesh D. Vinod (Fordham University, Department of Economics)

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Abstract

A new two-way map between time domain and numerical magnitudes or values domain (v-dom) provides a new solution to heteroscedasticity. Since sorted logs of squared fitted residuals are monotonic in the v-dom, we obtain a parsimonious fit there. Two theorems prove consistency, asymptotic normality, efficiency and specification-robustness, supplemented by a simulation. Since Dufour’s (1997) impossibility theorems show how confidence intervals from Wald-type tests can have zero coverage, I suggest Godambe pivot functions (GPF) with good finite sample coverage and distribution-free robustness. I use the Frisch-Waugh theorem and the scalar GPF to construct new confidence intervals for regression parameters and apply Vinod’s (2004, 2006) maximum entropy bootstrap. I use Irving Fisher’s model for interest rates and Keynesian consumption function for illustration.

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Paper provided by Fordham University, Department of Economics in its series Fordham Economics Discussion Paper Series with number dp2008-15.

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Date of creation: 2008
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Handle: RePEc:frd:wpaper:dp2008-15

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  1. Robinson, P M, 1987. "Asymptotically Efficient Estimation in the Presence of Heteroskedasticity of Unknown Form," Econometrica, Econometric Society, vol. 55(4), pages 875-91, July. [Downloadable!] (restricted)
  2. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March. [Downloadable!] (restricted)
  3. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
  4. Vinod, Hrishikesh D., 2006. "Maximum entropy ensembles for time series inference in economics," Journal of Asian Economics, Elsevier, vol. 17(6), pages 955-978, December. [Downloadable!] (restricted)
  5. Antonio E. Noriega & Daniel Ventosa-Santaulària, 2006. "Spurious Regression Under Broken-Trend Stationarity," Journal of Time Series Analysis, Blackwell Publishing, vol. 27(5), pages 671-684, 09. [Downloadable!] (restricted)
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  6. Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March. [Downloadable!] (restricted)
  7. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June. [Downloadable!]
  8. Vinod, H. D., 1985. "Exact maximum likelihood regression estimation with ARMA (n, n - 1) errors," Economics Letters, Elsevier, vol. 17(4), pages 355-358. [Downloadable!] (restricted)
  9. Godfrey, L.G., 2006. "Tests for regression models with heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2715-2733, June. [Downloadable!] (restricted)
  10. Vinod, H. D., 2004. "Ranking mutual funds using unconventional utility theory and stochastic dominance," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 353-377, June. [Downloadable!] (restricted)
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