* moving-window regression of wpi on quadratic time trend
* cfb 4325

webuse wpi1,clear
g t2=t^2
local wwidth 12
qui su t,meanonly
local nwind = r(N)-`wwidth'
tempname se
mat res = J(`nwind',7,0)
forv i=1/`nwind' {
	local j = `i'+`wwidth'-1
	qui reg wpi t t2 in `i'/`j'
	mat res[`i',1] = e(b)
	mat `se' = vecdiag(e(V))
	mat res[`i',4] = `se'
	mat res[`i',7] = e(rmse)
	}
svmat double res, name(rollreg)
g lb = rollreg1-1.96*rollreg4
g ub = rollreg1+1.96*rollreg4
tsline rollreg1 lb ub, legend(off) ti("Coefficient of linear time trend for wpi") b2("Moving window of `wwidth' quarters")
graph rename fig1,replace
label var rollreg7 "RMS Error"
tsline rollreg7, ti("RMS Error for quadratic trend model of wpi")
graph rename fig2,replace
graph combine fig1 fig2,col(1)