Find a useful approximation for
when is close to , and give the next correction term.
Turn the quotient into a small perturbation. Write with small compared with . Then
The quantity is the relative change of over . Recasting the problem in terms of is what makes a single series expansion do all the work.
Expand the logarithm about . The Maclaurin series is
The absence of a constant term reflects , and the leading coefficient is at .
Read off the first-order approximation. Keeping only the leading term,
This is the familiar statement that a log-difference approximates a percentage change: a rise gives a log change of about .
Add the quadratic correction. Keeping one more term,
The correction is always negative for , which says the first-order estimate systematically overstates the log of a rise — the logarithm is concave.
Note the alternative base point and quantify the error. Expanding about instead of gives , which understates the value; the two one-sided estimates bracket the truth, and dividing by the midpoint is more accurate than either. Numerically at , : the exact value is , the first-order estimate is (error ), and the second-order estimate is (error ) ✓.
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