如何为此线性模型构建回归？
我有以下线性模型，我想为此建立回归。
I have the following linear model, for which I want to build a regression.
????[i,t] = ????[i]+????[i]????[m,t] +????[i]????[m,t]????[t]+????[i,t]
r[i,t] and r[m,t] are the returns of financial data at time t and an equity index [i] or market[m], d[t] is a dummy variable which takes value 1 after a specific event and value 0 before the event. ???? is an error term.
the null hypothesis is H0: y[i] = 0;
a rejection would mean H1a : y[i] < 0 or H1b: y[i] > 0
I'm not sure how to implement the y in my regression.
I would really appreciate your help.
Thank you!
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这很难在没有看到数据的情况下说，但是看起来可以作为固定效果模型表示，在这种模型中，您在
r_ {m，t}和d_ {t}之间有相互作用。但是，实际上没有足够的信息来确切解释如何在没有有关您的模型和数据的更多信息的情况下实施此信息。您可以找到一个如何实现的示例在此上网站（带有R的计量经济学）一般而言，有几种方法和功能（例如
plmVesuslm，内部与第一差）。This is difficult to say without seeing your data, but looks like this could be expressed as a fixed effects model, where you have an interaction between
R_{m,t}andD_{t}. However, there isn't really enough information to explain exactly how to implement this without more information about your model and data.You can find an example of how this is implemented on this website (Econometrics with R) in general, with several approaches and functions (e.g.
plmvesuslm, within versus first-difference).