Question

Suppose that we want to evaluate the effect of several variables onannual saving and that we have a panel data set on individuals collected in January1990 and January 1992. If we include a year dummy variable for 1992 and use firstdifferencing, can we also include age in the original model? Explain.

Answer 1

Following are the responses to the given question:

Step-by-step explanation:

Note that others will therefore increase his age by two percent from 2009 to 1992.

`\Delta age_(i)=2 \ \ \ where \ \ i =1,2,....,n`

And if the trend is running:

`\Delta saving_(i)=\beta _(0)+\beta _(1)\Delta age_(i)+...+u_(i)`

We're breaking MLR.3 as
`\Delta agei` it's the same for all -> No different from a permanent designer cannot immediately distinguish the influence of age from the aggregate time effect because age changes per person by the same amount.