Transcription of Linear Regression Models with Logarithmic Transformations
{{id}} {{{paragraph}}}
Example: quiz answers
Linear Regression Models with Logarithmic Transformations
Linear Regression Models with Logarithmic TransformationsKenneth Benoit Methodology InstituteLondon School of 17, 20111 Logarithmic Transformations of variablesConsidering the simple bivariate Linear modelYi= + Xi+ i,1there are four possible com-binations of Transformations involving logarithms: the Linear case with no Transformations , thelinear-log model , the log- Linear model2, and the log-log Yi= + Xi Yi= + logXilogYlog-linearlog-loglog Yi= + Xilog Yi= + logXiTable 1: Four varieties of Logarithmic transformationsRemember that we are usingnaturallogarithms, where the base ise Logarithms mayhave other bases, for instance the decimal logarithm of base 10. (The base 10 logarithm is used inthe definition of the Richter scale, for instance, measuring the intensity of earthquakes as Richter=log(intensity). This is why an earthquake of magnitude 9 is 100 times more powerful than anearthquake of magnitude 7: because 109/107=102and log10(102)=2.)
linear-log model, the log-linear model2, and the log-log model. X Y X logX Y linear linear-log Y^ i = + Xi Y^i = + logXi logY log-linear log-log logY^ ... to as elastic in econometrics, and the coefficient of logX is referred to as an elasticity. So in terms of …
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: