8/11/2019 H Brown Lecture 3 Assignment With R Code
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Hayley Brown
Applied Spatial Econometrics Lecture 3 Assignment
Fall 2014 Due: 03 Oct 2014 @ 11:59PM
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A model of the constant elasticity variety is linear in
elasticities. Elasticities are percentage
changes. So a constant elasticity model would be:
log(salary) = !0 + !1log(sales) + !2log(mktval) + u.
In this case, the constant elasticity equation is:!"#!!"#"$%!=
4.62 + 0.162log(sales) + 0.107log(mktval)n = 177
R2= 0.299
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This variable cannot be included in logarithmic form because
nine of the companies in the
sample have negative profit values. It is impossible to take the
log of a negative value, as it is
undefined. The new model is as follows:
!"#!!"#"$%!= 4.69 + 0.161log(sales) + 0.098log(mktval) +
0.000036(profits)
n=177
R2= 0.299
Given the value of R2, I surmise that together these variables
account for nearly 30% of the
sample variation in log(salary). This is certainly not most of
the variation. Moreover,
profits seem to add very little to the model, suggesting that
profits exert negligible influence
over log(salary).
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!"#!!"#"$%!= 4.56 + 0.162log(sales) + 0.102(mktval) +
0.000029(profits) + 0.012(ceoten)
n = 177
R2= 0.318
8/11/2019 H Brown Lecture 3 Assignment With R Code
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The implication is that when CEO tenure increases by one year,
salary increases by 1.2%.
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The sample correlation coefficient is 0.78. This suggests that
log(mktval) and profits are
highly correlated. Give this close correlation, it is difficult
to estimate the independent effectof each on log(salary). This does
not indicate bias in the OLS estimators, though it may cause
their variances to be large. It is worth noting that profit is a
short-term measure, while mktval
is based on past and current profitability; however, mktval also
incorporates future
expectations of profitability, which may or may not come to
fruition and should scrutinized in
their own right.
Code
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8/11/2019 H Brown Lecture 3 Assignment With R Code
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