有两个地方不太明白

问题如下：

A linear time trend model is estimated on annual real euro-area GDP, measured in billions of 2010 euros, using data from 1995 until 2018. The estimated model is $RGDP_t = -234178.8 + 121.3 * t + \widehat\epsilon_t$. The estimate of the residual standard deviation is $\widehat\sigma = 262.8$.

Construct point forecasts and 95% confidence intervals (assuming Gaussian white noise errors) for the next three years. Note that t is the year, so that in the first observation, t = 1995, and in the last, t = 2018.

解释：

Note that there is no AR or MA component, so the variance remains constant. Therefore, the 95% confidence interval is + / - 1.96*262.8 = + / - 515.1 about the expected value.

As for the expected means:

$E[RGDP_{2019}] = -234178.8 + 121.3 * 2019 = 10,725.9$

$E[RGDP_{2020}] = -234178.8 + 121.3 * 2020 = 10,847.2$

$E[RGDP_{2021}] = -234178.8 + 121.3 * 2021 = 10,968.5$