Solved – Deriving OLS estimates using method of moments

I've worked the slope all the way down to $sum [x_i(y_i – bar{y})] = hatbeta_1 sum[x_i(x_i – bar{x})]$

But I can not figure out how to show the steps for:

$sum[x_i(y_i – bar{y})] = sum(x_i – bar{x})(y_i – bar{y})$


$hat beta_1 sum[x_i(x_i – bar{x})] = hat beta_1 sum(x_i – bar{x})^2$

Add and subtract and then look whether the unwanted term disappears:

$$sum[x_i(y_i-bar y)]=sum[(x_i-bar x+bar x)(y_i-bar y)]=sum[(x_i-bar x)(y_i-bar y)]+sum [bar x(y_i-bar y)].$$


$$sum [bar x(y_i-bar y)]=bar xsum [y_i-bar y]=bar xleft[sum y_i-nbar yright]=0,$$

where $n$ is the number of the terms in the sum. Apply the same trick for the second equation.

Similar Posts:

Rate this post

Leave a Comment