The analysis separates the regional economic changes within each industry into different categories.
Although there are different versions of a shift-share analysis, they all identify national, industry, and regional factors that influence the variable changes.
The traditional form of the shift-share analysis was developed by Daniel Creamer in the early 1940s, and was later formalized by Edgar S. Dunn in 1960.
As an example, a shift-share analysis might be utilized to examine changes in the construction industry of a state's economy over the past decade, using employment as the economic variable studied.
The shift-share analysis implies that state construction would have increased by 5,000 employees, had it followed the same trend as the overall national economy.
The local share effect in this example is equal to the beginning 100,000 employees times the state construction employment growth rate of −2% (it is negative because of the loss of employees), minus the national construction growth rate of 8%.
[7] In 1988, Richard Barff and Prentice Knight, III, published the dynamic model shift-share analysis.
Although it requires much more data to perform the calculations, the dynamic model takes into account continuous changes in the three shift-share effects, so the results are less affected by the choice of starting and ending years.
[8] The growth rates used in the calculations are annual rates, not growth from the beginning year in the study period, so the percent change from year k-1 to k in the economic variable nationwide for all industries combined is Gk, while the national and regional industry-specific percent changes are Gik and gik, respectively.
[9] The model introduced a then-new concept to shift-share analyses, a homothetic level of the economic variable within an industry.
[9] In the Esteban-Marquillas model, the calculations of the national share and industrial mix effects are unchanged.
The allocation effect indicates the extent to which the region is specialized in those industries where it enjoys a competitive advantage.
In 1984, Francisco Arcelus built upon Esteban-Marquillas' use of the homothetic variables and extended the traditional model even further.
[10] He used this method to decompose the national share and industrial mix effects into expected and differential components.
The expected component is based on the homothetic level of the variable, and is the effect not attributed to the regional specializations.