SUGGESTED_SOLUTIONS_PRACTICE_PROBLEMS

SUGGESTED_SOLUTIONS_PRACTICE_PROBLEMS - SUGGESTED SOLUTIONS...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
SUGGESTED SOLUTIONS PRACTICE PROBLEMS PAM 305 FALL 2006 13.3 We do not have repeated observations on the same cross-sectional units in each time period, and so it makes no sense to look for pairs to difference. For example, in Example 13.1, it is very unlikely that the same woman appears in more than one year, as new random samples are obtained in each year. In Example 13.3, some houses may appear in the sample for both 1978 and 1981, but the overlap is usually too small to do a true panel data analysis. 13.5 No, we cannot include age as an explanatory variable in the original model. Each person in the panel data set is exactly two years older on January 31, 1992 than on January 31, 1990. This means that age i = 2 for all i . But the equation we would estimate is of the form Δ saving i = δ 0 + β 1 Δ age i + , where 0 is the coefficient the year dummy for 1992 in the original model. As we know, when we have an intercept in the model we cannot include an explanatory variable that is constant across i; this violates Assumption MLR.3. Intuitively, since age changes by the
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 2

SUGGESTED_SOLUTIONS_PRACTICE_PROBLEMS - SUGGESTED SOLUTIONS...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online