open data4-1
matrix y = {price}
matrix X = {const, sqft}
matrix XTX = X'X
matrix XTXi = inv(XTX)
# get beta estimates
matrix B = XTXi * X'y
print B
# compute residuals
matrix u = y - X*B
print u
# get ESS, uu' and sigma-hat
scalar ESS = u'u
print ESS
matrix uu = u*u'
print uu
scalar s = sqrt(ESS/($nobs-rows(B)))
print s
# get variance of beta and standard errors
matrix VB = s^2 * XTXi
print VB
matrix se = sqrt(diag(VB))
print se

# compare the canned command
ols 1 0 2 --vcv

# compute robust variance matrix and SEs
matrix Omega = I(14)
Omega[diag] = u.^2
print Omega
matrix ham = X'*Omega*X
matrix VB2 = XTXi*ham*XTXi
print VB2
matrix se2 = sqrt(diag(VB2))
print se2

# again compare the canned command
set hc_version 0
ols 1 0 2 --robust --vcv