Explanation:

In time series analysis:

• AR(p) models (Autoregressive models) are identified by the Partial Autocorrelation Function (PACF) cutting off after lag p
• MA(q) models (Moving Average models) are identified by the Autocorrelation Function (ACF) cutting off after lag q

Since the question mentions a PACF plot and asks for the best regression approach, we're looking at AR models. The options suggest:

• AR(1): PACF would cut off after lag 1
• AR(2): PACF would cut off after lag 2

Without seeing the actual PACF plot, but based on the question structure and typical exam patterns, AR(2) is likely the correct answer as it represents a model where the partial autocorrelation is significant for the first two lags and then cuts off.