Regression in Hamilton filter add-in

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KrilleJ
Posts: 40
Joined: Fri Feb 20, 2015 6:15 am

Regression in Hamilton filter add-in

Postby KrilleJ » Tue Jan 23, 2018 2:00 am

Looking at the Hamilton filter add-in it seems as if a regression on the four most recent lags is run and direct forecasts are made h periods into the future based in the estimation results in order to get a trend estimate. That is:

y_t=c(1)+c(2)*y_{t-1}+c(3)*y_{t-2}+c(4)*y_{t-3}+c(5)*y_{t-4}

is estimated while the trend estimate is:

\hat{y}_{t+h}=est_c(1)+est_c(2)*y_{t-1}+est_c(3)*y_{t-2}+est_c(4)*y_{t-3}+est_c(5)*y_{t-4}

The code in the add-in is:

Code: Select all

HamiltonEstimation192873.ls {%inputvarname} c {%inputvarname}(-1) {%inputvarname}(-2) {%inputvarname}(-3) {%inputvarname}(-4)
   
'Generate the trend with the fitted values from the equation estimation and lags
{%trendoutputname}(!i + 5 +!h) = c(1) _
+ c(2) * {%inputvarname}(!i+4)  _
+ c(3) * {%inputvarname}(!i+3)  _
+ c(4) * {%inputvarname}(!i+2)  _
+ c(5) * {%inputvarname}(!i+1) 


This is not how I read Hamilton's paper. Instead, I gather that the filter regression to be estimated is:

y_{t+h}=c(1)+c(2)*y_{t}+c(3)*y_{t-1}+c(4)*y_{t-2}+c(5)*y_{t-3}

Have I missed something or is there room for changing the regression in the add-in?

Best,
Krille

EViews Gareth
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Joined: Tue Sep 16, 2008 5:38 pm

Re: Regression in Hamilton filter add-in

Postby EViews Gareth » Tue Jan 23, 2018 8:07 pm

Given how simple his technique is, you’re probably best off doing it manually.
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KrilleJ
Posts: 40
Joined: Fri Feb 20, 2015 6:15 am

Re: Regression in Hamilton filter add-in

Postby KrilleJ » Thu Jan 25, 2018 4:08 am

Great, I will.


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