Shift-share analysis
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Shift/share analysis is a widely used analytical technique sometimes used for retrospectively decomposing changes, usually in employment, in a set of urban areas or regions. The analysis is meant to identify industries considered to have a comparative advantage in that particular area.[1]
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[edit] Formula
We have a study area in which employment and population are growing (or declining; the technique works the same way in either case and it saves words to make the growth assumption.) Total employment in our area is e, and that in the ith activity is ei . We have a larger frame reference area, usually the nation, where total employment is E, and that in the ith activity is Ei . The shift-share model says that growth in the study area’s ith activity employment is a function of:
- The study area’s share of national (or regional) growth.
- The mix change in activities.
- And the shift change of activities toward the study area.
This says that change in employment in the study area’s ith activity from time t to time t+n can be measured:
or
As this brief discussion suggests, shift-share analysis may be viewed as adding explicit considerations to economic base analysis. Economic base analysis asks how an area shares in national growth. Shift-share goes on to look at the changing mix of activities and at whether activities are shifting toward or away from the study area.
[edit] Assumptions
Shift-share analysis makes several assumptions:
- The larger reference area is a closed economic system
- Each job counted in the employment of every industry is of equal weight
[edit] Application
Shift-share analysis
[edit] Criticisms
- Often reflects initial resources of an area, which is not typically indicative of comparative advantage [2]
- Typically presents agricultural, manufacturing, and service industries as have competitive advantages as localities progress[2]
[edit] Adjustments or Alternatives
Many scholars have begun tweaking shift-share analysis to use probabilistic models and regression analysis, rather than simple analysis of two data points.[1][3]
Other forms of industry analysis, such as location quotient, econometric modeling, and input-output analysis are also used.

![e_i^{t + n} - e_i^t = e_i^t \left[ {{{E_{}^{t + n} } \over {E_{}^t }} - 1} \right] + e_i^t \left[ {{{E_i^{t + n} } \over {E_i^t }} - {{E^{t + n} } \over {E^t }}} \right] + e_i^t \left[ {{{e_i^{t + n} } \over {e_i^t }} - {{E_i^{t + n} } \over {E_i^t }}} \right]](http://upload.wikimedia.org/wikipedia/en/math/a/c/b/acbe266e1fd84d0309c21c79b327ee68.png)