Shift-share analysis is a widely used economic tool that decomposes changes in regional employment into three distinct components: national growth, industry mix, and regional competitiveness. This analytical framework helps policymakers, planners, and researchers understand the factors contributing to regional economic performance, identify competitive strengths and weaknesses, and design targeted interventions to foster growth.
Key Components of Shift-Share Analysis
Shift-share analysis breaks down employment changes into three effects:
- National Growth Effect (NGE):
- Measures how much of the regional employment change can be attributed to overall national economic growth.
- It assumes that if the regional economy grew at the same rate as the national economy, the employment change would reflect national trends.
- Industry Mix Effect (IME):
- Examines the role of the region’s industrial composition in employment changes.
- Regions with a concentration of industries that are growing faster nationally will experience a positive industry mix effect, while those dominated by slow-growing or declining industries will see a negative effect.
- Regional Competitive Effect (RCE):
- Captures the extent to which the region’s employment growth outperforms or underperforms national and industry-specific trends.
- A positive competitive effect indicates the region is more productive or attractive than its peers in certain industries.
Formula for Shift-Share Analysis
The change in regional employment (ΔE\Delta E) is expressed as the sum of the three effects: ΔE=NGE+IME+RCE\Delta E = NGE + IME + RCE
Where:
- NGE=Ei,t−1×GnNGE = E_{i,t-1} \times G_n
- Ei,t−1E_{i,t-1}: Employment in sector ii at the beginning of the period
- GnG_n: National employment growth rate
- IME=Ei,t−1×(Gi,n−Gn)IME = E_{i,t-1} \times (G_{i,n} – G_n)
- Gi,nG_{i,n}: National growth rate of sector ii
- RCE=Ei,t−1×(Gi,r−Gi,n)RCE = E_{i,t-1} \times (G_{i,r} – G_{i,n})
- Gi,rG_{i,r}: Regional growth rate of sector ii
Applications in Economic Development
- Identify Regional Strengths and Weaknesses:
- Shift-share analysis highlights which industries in a region are performing well or poorly compared to national trends, enabling targeted economic strategies.
- Support Strategic Planning:
- Policymakers can use insights from shift-share analysis to prioritize sectors with high growth potential or address weaknesses in underperforming industries.
- Track Regional Competitiveness:
- The competitive effect provides a measure of how well a region is leveraging its unique assets, such as workforce skills, infrastructure, and business climate.
- Evaluate Economic Policies:
- By comparing the analysis over time, policymakers can assess the impact of economic development initiatives on regional growth.
Examples
- Positive Competitive Effect: If a region’s healthcare sector grows faster than the national average for healthcare, the regional competitive effect for healthcare is positive. This suggests the region has a competitive advantage, such as strong institutions, a skilled workforce, or favorable policies.
- Negative Industry Mix Effect: A region heavily reliant on industries experiencing national declines, such as traditional manufacturing, will have a negative industry mix effect. This may signal the need for diversification into emerging sectors.
Limitations of Shift-Share Analysis
While shift-share analysis is a powerful tool, it has limitations:
- Static Assumptions: The analysis assumes constant growth rates, which may not account for dynamic changes in industries or regions.
- Focus on Employment: It typically measures employment changes and may not capture broader economic indicators like productivity or wages.
- Aggregated Data: The results depend on the level of industry aggregation, which can obscure finer nuances at the sub-sector level.
Conclusion
Shift-share analysis is a valuable framework for understanding regional economic dynamics and guiding strategic development efforts. By isolating the effects of national trends, industry composition, and regional competitiveness, it equips decision-makers with insights to design informed policies, allocate resources efficiently, and foster sustainable economic growth.