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From |
Maarten Buis <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Economic significance |

Date |
Tue, 19 Jun 2012 09:28:48 +0200 |

--- On Tue, Jun 19, 2012 at 1:06 AM, FredVer wrote: > I have a question about the economic significance of a variety of variables > on a variety on dependent variables. I thought that the economic > significance is calculated as: > > (standard deviation indepent variable*coefficient indep variable)/standard > deviation dependent variable. The standard deviations can be interpreted > from the summary statistics right? > > The thing i think interpretation differs when the variable of itself is > ratio or logged, right? How to interpret it than? It is really hard to find > on the net (also only one thread on statlist) how economic significance must > be calculated. Some also say that you must not use a one standard deviation > but a one percent?!:S Please read the Statalist FAQ before posting on Statalist. Here is one relevant quote: "It is long-standing practice on Statalist that most members, especially the most active members who supply a large fraction of the answers, post using their real names. This is one of the ways in which we show respect to others. So we discourage you from posting from behind fake names or identifiers. [...] Please note that many members are less inclined to answer anonymous emails, sometimes to the point of ignoring them on principle. These choices are personal, but your chances of eliciting a good reply are greatly diminished if you write and conceal your identity." What you describe is standardization, which may or may not help with determining economic significance. Economic significance just means that you interpreted the coefficient and made the subjective decision that it is so big that it has a meaningful effect. Standardization will in some cases help you with that, but in many cases it will make it harder. The key is that you (and your readers/audience) can substantively understand the size of the coefficient. Standardization can be done in various ways, e.g. by standard deviations, percentages, but also ranks. These are all ways that are sometimes useful to assign a scale to a variable. If a variable already has a natural scale (e.g euros, liters, headloads(*), etc. ) than using these methods will just make it harder to interpret your coefficient. Sometimes a variable has no natural scale, typically this occurs when the variable is a composite index. In those cases any of these methods might make sense. Sometimes standardization is used to compare effects of variables. Now you need to decide if a standard deviation increase in income is really comparable to a standard deviation increase in education. In most cases I would argue that they are just different, and such comparisons make no sense. -- Maarten (*) How much one can carry on his or (more common) her head. In some regions this a useful metric for things like firewood, as this is the relevant metric for the respondent. -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Economic significance***From:*FredVer <[email protected]>

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