可以具体解释一下虚拟变量是怎么取值， 来分别预测四个季度的啊？谢谢～

NO.PZ2020011101000026 问题如下 The seasonmmy mol Yt=δ+∑j=13γjljt+ϵtY_t = \lta + \sum_{j=1}^3\gamma_jl_{jt}+\epsilon_tYt​=δ+∑j=13​γj​ljt​+ϵt​ is estimateon the quarterly growth rate of housing starts, anthe estimateparameters are γ^1=6.23,γ^2=56.77,γ^3=10.61\wihat\gamma_1 = 6.23, \wihat\gamma_2 = 56.77, \wihat\gamma_3 = 10.61γ​1​=6.23,γ​2​=56.77,γ​3​=10.61, anδ^=−15.79\wihat\lta = -15.79δ=−15.79 using ta until the enof 2018. Whare the forecast growth rates for the four quarters of 2019? Though there is varianfrom quarter-to-quarter, the expectevalue of YtY_tYt​ is the same for any two observations of the same quarter, regaress of the year. Accorngly:E[YQ1]=δ+∑j=13γjljt=−15.79+6.23∗1+56.77∗0+10.61∗0=−9.56E[Y_{Q1}]=\lta + \sum_{j=1}^3\gamma_jl_{jt}=-15.79 + 6.23 * 1 + 56.77 * 0+ 10.61 * 0 = -9.56E[YQ1​]=δ+∑j=13​γj​ljt​=−15.79+6.23∗1+56.77∗0+10.61∗0=−9.56E[YQ2]=δ+∑j=13γjljt=−15.79+6.23∗0+56.77∗1+10.61∗0=40.98E[Y_{Q2}]=\lta + \sum_{j=1}^3\gamma_jl_{jt}=-15.79 + 6.23 * 0 + 56.77 * 1+ 10.61 * 0 = 40.98E[YQ2​]=δ+∑j=13​γj​ljt​=−15.79+6.23∗0+56.77∗1+10.61∗0=40.98E[YQ3]=δ+∑j=13γjljt=−15.79+6.23∗0+56.77∗0+10.61∗1=−5.18E[Y_{Q3}]=\lta + \sum_{j=1}^3\gamma_jl_{jt}=-15.79 + 6.23 * 0 + 56.77 * 0+ 10.61 * 1 = -5.18E[YQ3​]=δ+∑j=13​γj​ljt​=−15.79+6.23∗0+56.77∗0+10.61∗1=−5.18E[YQ4]=δ+∑j=13γjljt=−15.79+6.23∗0+56.77∗0+10.61∗0=−15.79E[Y_{Q4}]=\lta + \sum_{j=1}^3\gamma_jl_{jt}=-15.79 + 6.23 * 0 + 56.77 * 0+ 10.61 * 0 = -15.79E[YQ4​]=δ+∑j=13​γj​ljt​=−15.79+6.23∗0+56.77∗0+10.61∗0=−15.79 残差项不用考虑么？