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<p>This paper introduces the spatial multifactor partitioning (SMFP), a new method that extends shift-share analysis by incorporating growth rate standardization and a spatial benchmark into a single framework. Traditional shift-share analysis (SSA) faces two main challenges: distinguishing between regional and industry effects and accounting for spatial spillovers. Previous extensions have addressed these issues individually, but SMFP integrates both strategies, allowing for a more precise assessment of whether a region’s employment growth is due to its economic advantages or broader industry patterns, while also capturing the influence of neighboring regions. The method is applied to measure the role of industry and region effects on employment changes in U.S. Manufacturing and Wholesale &amp; Retail Trade, over the period 2005–2019. Results indicate that SMFP isolates regional dynamics from industry trends and reveals spatial employment patterns and clusters. By refining the decomposition of employment change, SMFP offers a clear picture of regional advantages, improving both analysis and potential policy implications.</p>

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Unraveling region effects with a new Spatial Multifactor Partitioning method

  • 期刊论文

  • 发表日期：

    2026年2月10日

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  • Claudia V. Montanía

摘要

This paper introduces the spatial multifactor partitioning (SMFP), a new method that extends shift-share analysis by incorporating growth rate standardization and a spatial benchmark into a single framework. Traditional shift-share analysis (SSA) faces two main challenges: distinguishing between regional and industry effects and accounting for spatial spillovers. Previous extensions have addressed these issues individually, but SMFP integrates both strategies, allowing for a more precise assessment of whether a region’s employment growth is due to its economic advantages or broader industry patterns, while also capturing the influence of neighboring regions. The method is applied to measure the role of industry and region effects on employment changes in U.S. Manufacturing and Wholesale & Retail Trade, over the period 2005–2019. Results indicate that SMFP isolates regional dynamics from industry trends and reveals spatial employment patterns and clusters. By refining the decomposition of employment change, SMFP offers a clear picture of regional advantages, improving both analysis and potential policy implications.