New Solution to Time Series Inference in Spurious Regression Problems

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.

Number of Pages in PDF File: 36

Keywords: bootstrap, simulation, confidence intervals

JEL Classification: C12, C15, C22, C51

working papers series