New Solution to Time Series Inference in Spurious Regression Problems

36 Pages Posted: 7 Mar 2010 Last revised: 28 Jun 2010

Hrishikesh D. Vinod

Fordham University - Department of Economics

Date Written: February 26, 2010

Abstract

Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of related literature on spurious regression is that one cannot trust the usual confidence intervals. Therefore it is recommended that after carrying out unit root tests we work with differenced series instead of original data in levels. We propose a new alternative of using confidence intervals based on Maximum Entropy bootstrap explained in Vinod and Lopez-de-Lacalle (2009, J of Statistical Software). Extensive Monte Carlo simulations show that our proposal can provide more reliable conservative confidence intervals than traditional, differencing and block bootstrap (BB) intervals. We hope to let researchers avoid differencing the variables and work with their original specifications in levels.

Keywords: bootstrap, simulation, confidence intervals

JEL Classification: C12, C15, C22, C51

Suggested Citation

Vinod, Hrishikesh D., New Solution to Time Series Inference in Spurious Regression Problems (February 26, 2010). Available at SSRN: https://ssrn.com/abstract=1560074 or http://dx.doi.org/10.2139/ssrn.1560074

Hrishikesh D. Vinod (Contact Author)

Fordham University - Department of Economics ( email )

Dealy Hall
Bronx, NY 10458
United States
718-817-4065 (Phone)
718-817-3518 (Fax)

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