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I am having some trouble interpreting my regression output. My model is LN of transaction volume = alpha + $\beta_1$_RER + control variables RER is defined as the change in the average exchange rate from one period (half year) to another. And it is expected to have an impact on the transaction volume. Log-level : %Δy = (100*β1)Δx The coefficient for RER is -12. In my opinion this means that : - An increase of 1 unit in the exchange rate change (100 percentage points) would mean a 1200% drop in transaction volume - An increase of 1p.p. in exchange rate change would mean a 15,98% decrease in transaction volume

With standard deviation :

STD : 0,0535

0,0535 * -12 = 0.642

  • A one standard deviation increase in RER means a 64% drop in transaction volume Is that correct? I have just very confused because I am interpreting a change in a change and am unsure how to deal with the coefficient.
Ferdi
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CharlotteC
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  • Possible duplicate of [Interpretation of log transformed predictor and/or response](https://stats.stackexchange.com/questions/18480/interpretation-of-log-transformed-predictor-and-or-response) – Ertxiem - reinstate Monica Apr 29 '19 at 10:56
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    Percent change is not a good basis for statistical models because it's an asymmetric measure. A 100% increase is balanced by a 50% decrease. There is a section about this in [BBR](http://hbiostat.org/doc/bbr.pdf). – Frank Harrell Apr 29 '19 at 12:13

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