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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.

Respuesta :

Answer:

Following are the responses to the given question:

Explanation:

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

[tex]\Delta age_{i}=2 \ \ \ where \ \ i =1,2,....,n[/tex]

And if the trend is running:

 [tex]\Delta saving_{i}=\beta _{0}+\beta _{1}\Delta age_{i}+...+u_{i}[/tex]

We're breaking MLR.3 as [tex]\Delta agei[/tex] 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.

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