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Shift-share analysis
A shift-share analysis, used in regional science, political economy, and urban studies, determines what portions of regional economic growth or decline can be attributed to national, economic industry, and regional factors. The analysis helps identify industries where a regional economy has competitive advantages over the larger economy. A shift-share analysis takes the change over time of an economic variable, such as employment, within industries of a regional economy, and divides that change into various components. A traditional shift-share analysis splits regional changes into just three components, but other models have evolved that expand the decomposition into additional components.
A shift-share analysis attempts to identify the sources of regional economic changes. The region can be a town, city, country, statistical area, state, or any other region of the country. The analysis examines changes in an economic variable, such as migration, a demographic statistic, firm growth, or firm formations, although employment is most commonly used. The shift-share analysis is performed on a set of economic industries, like those defined by the North American Industry Classification System (NAICS). 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. Also known as the comparative static model, it examines changes in the economic variable between two years. Changes are calculated for each industry in the analysis, both regionally and nationally. Each regional change is decomposed into three components.
The regional change in the variable e within industry i between the two years t and t+n is defined as the sum of the three shift-share effects: national growth effect (NSi), industry mix effect (IMi), and local share effect (RSi).
The beginning and ending values of the economic variable within a particular industry are eit and eit+n, respectively. Each of the three effects is defined as a percentage of the beginning value of the economic variable.
The total percent change in the economic variable nationwide for all industries combined is G, while the national and regional industry-specific percent changes are Gi and gi, respectively.
These three equations substituted into the first equation yield the following expression (from where the decomposition starts), which simply says that the regional economic variable (for industry i) grows at the speed of the regional industry-specific percent change. Note that usually (in case of slow growth) 0 < gi < 1 and that gi refers to the whole period from t to t+n.
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. Total national employment may have increased 5% over the decade, while national construction employment increased 8%. However, state construction employment decreased 2%, from 100,000 to 98,000 employees, for a net loss of 2,000 employees.
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Shift-share analysis
A shift-share analysis, used in regional science, political economy, and urban studies, determines what portions of regional economic growth or decline can be attributed to national, economic industry, and regional factors. The analysis helps identify industries where a regional economy has competitive advantages over the larger economy. A shift-share analysis takes the change over time of an economic variable, such as employment, within industries of a regional economy, and divides that change into various components. A traditional shift-share analysis splits regional changes into just three components, but other models have evolved that expand the decomposition into additional components.
A shift-share analysis attempts to identify the sources of regional economic changes. The region can be a town, city, country, statistical area, state, or any other region of the country. The analysis examines changes in an economic variable, such as migration, a demographic statistic, firm growth, or firm formations, although employment is most commonly used. The shift-share analysis is performed on a set of economic industries, like those defined by the North American Industry Classification System (NAICS). 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. Also known as the comparative static model, it examines changes in the economic variable between two years. Changes are calculated for each industry in the analysis, both regionally and nationally. Each regional change is decomposed into three components.
The regional change in the variable e within industry i between the two years t and t+n is defined as the sum of the three shift-share effects: national growth effect (NSi), industry mix effect (IMi), and local share effect (RSi).
The beginning and ending values of the economic variable within a particular industry are eit and eit+n, respectively. Each of the three effects is defined as a percentage of the beginning value of the economic variable.
The total percent change in the economic variable nationwide for all industries combined is G, while the national and regional industry-specific percent changes are Gi and gi, respectively.
These three equations substituted into the first equation yield the following expression (from where the decomposition starts), which simply says that the regional economic variable (for industry i) grows at the speed of the regional industry-specific percent change. Note that usually (in case of slow growth) 0 < gi < 1 and that gi refers to the whole period from t to t+n.
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. Total national employment may have increased 5% over the decade, while national construction employment increased 8%. However, state construction employment decreased 2%, from 100,000 to 98,000 employees, for a net loss of 2,000 employees.