FRM Part I · FRM Exam Part I · Nonstationary Time Series
A Dickey-Fuller test is applied to a series that follows a stationary AR(1) with coefficient 0.95 in a sample of only 60 observations. Which statement best describes the likely outcome and the reason?
The test has low power in this situation and will often fail to reject the unit root null, even though the series is stationary. A highly persistent AR(1) with a short sample is hard to distinguish from a random walk.
- AThe test will almost surely reject the unit root null, since 0.95 is below 1
- BThe test has low power and will often fail to reject, so a stationary but highly persistent series may be mistaken for a unit rootCorrect
- CThe test is biased toward rejection because small samples inflate the t-statistic
- DThe test is invalid because it requires the AR coefficient to be exactly 1
Explanation
With a root close to one and a short sample, the data look very similar to a random walk, so the Dickey-Fuller test has low power. Failure to reject therefore does not prove a unit root. The test does not require the coefficient to equal 1; that is only the null.
Did you get it right without looking?
One question tells you little. A timed set on Nonstationary Time Series shows your real accuracy, how long you take and where you lose marks.
More Nonstationary Time Series questions
- Which statement best describes the effect of ignoring a structural break in the mean of a stationary series when applying a Dickey-Fuller te…
- An analyst fits the regression Y_t = δ·Y_{t-1} + ε_t to a monthly series of a bond spread and wants to test for a unit root using the Dickey…
- In a Dickey-Fuller regression ΔY_t = γY_{t-1} + ε_t, the estimated γ is −0.060 with a standard error of 0.030. The 5% Dickey-Fuller critical…
- An AR(1) model Y_t = 0.2 + phi Y_{t-1} + e_t is estimated. In the Dickey-Fuller regression of the first difference on the lagged level, the …
- A risk team analyzes monthly log values of a series that has a stochastic seasonal pattern. Seasonal differences, Y_t - Y_{t-12}, look stati…
- An analyst fits an AR(1) model to monthly changes in a bond spread over 2005-2023 and suspects that the intercept and slope changed after a …