# How to correct for generated regressor bias?

Dear Stack Exchange heroes,

For my thesis I am writing a paper on the financial crisis. In my model, I use two regressions, which look like this:

$$CONF = α + β_1 DEF_t + β_2 DIV_t + β_3 INF_t + β_4 IP_t + β_5 CONS_t + β_6 TBILL_t + β_7 URATE_t + β_8 NBER_t + β_9 DEF_{t-1} + β_{10} DIV_{t-1} + β_{11} INF_{t-1} + β_{12} IP_{t-1} + β_{13} CONS_{t-1} + β_{14} TBILL_{t-1} + β_{15} URATE_{t-1} + β_{16} NBER_{ t-1} + ε_t$$

Where $CONF$ is confidence index data and the rest are macroeconomic variables.

$$ΔS_t = α_1 + λΔε_{t-1} + η_t$$

Where $S$ is a stock price index and $Δε$ uses the residuals from the previous equation.

I use Eviews to run these equations and it works fine, but apparently I need to correct for the fact that $Δε$ is a generated regressor. The Pagan (1984) paper is often referred to for this, but after attempting to read it I'm still clueless on what to adjust in my covariance matrix to fix for this bias.

Is there any program that can do this for me, or someone who can explain this in easy steps? Any help is appreciated :)