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A unit-root AR(1) has no weakly stationary solution with nonzero white noise
Example
Let be centered white noise with variance . The equation has AR polynomial , whose root is . It has no weakly stationary solution. Under Countable Choice, this is a boundary illustration for the unit-circle-root premise of the paired spectral-density theorem; it does not show that premise is essential, since there is no stationary solution to which the density conclusion could apply.
Facts & Assumptions
Given: A centered white-noise sequence with , and the proposed AR(1) equation .
Countable Choice is assumed only for the contextual comparison with the spectral-density theorem; the covariance contradiction does not use it.
Linear processes, white noise, and ARMA models: white noise has zero covariance at nonzero lags, and the AR(1) equation has .
Strict and weak stationarity for integer-indexed time series and Autocovariance and sample autocovariance: under weak stationarity, is independent of .
Moments, variance, and covariance on a probability space defines variance and covariance; Cauchy-Schwarz for random variables gives .
The causal criterion in ARMA causality and invertibility root criteria is stated for a weakly stationary ARMA solution and excludes closed-unit-disk roots; under Countable Choice, Spectral density of a stationary ARMA solution excludes unit-circle roots for its density conclusion. This example compares root locations only and applies neither theorem to a nonexistent stationary solution.
Verification
Suppose a weakly stationary solution exists and write its autocovariance as . For every integer , white-noise covariance gives . Substituting and expanding the four covariances using [F2] yields
The recurrence in step 1.1 says for every . Induction makes these first differences constant, so for , where .
By [F3], for every . The affine sequence in step 2.1 is bounded only if , hence . Then contradicting the given . No weakly stationary solution exists. The polynomial root is by direct substitution, on the unit circle excluded by [F4]'s spectral-density premise under [A1]. Since the contradiction rules out a stationary solution, this only illustrates the boundary of that premise and does not establish its essentiality.
Depends on
- Linear processes, white noise, and ARMA models
- Strict and weak stationarity for integer-indexed time series
- ARMA causality and invertibility root criteria
- Spectral density of a stationary ARMA solution
- Autocovariance and sample autocovariance
- Moments, variance, and covariance on a probability space
- Cauchy-Schwarz for random variables
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
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Sources
- Dewei Wang, STAT 720 Time Series Analysis, Theorems 3.1 and 4.4 (standard reference, not scraped)
- Nicolai Meinshausen, Time Series Analysis: Notes for the course HS 2022, Section 2.3 (standard reference, not scraped)