The mean-reverting level for an AR(1) model is calculated as:

$\text{Mean-reverting level} = \frac{\text{intercept}}{1 - \text{AR parameter}}$

Given:

• Intercept = 0.24
• AR parameter = 0.65

Calculation: $\text{Mean-reverting level} = \frac{0.24}{1 - 0.65} = \frac{0.24}{0.35} = 0.6857 \approx 0.69$

This means that the time series tends to revert to a long-term mean of approximately 0.69. The AR(1) model specification is: $Y_t = 0.24 + 0.65Y_{t-1} + \epsilon_t$

For a stationary AR(1) process, the unconditional mean (mean-reverting level) is given by the formula above. Option A (0.69) is the correct answer.