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<p>Changes in population size and density in a jurisdiction affect its economic and social characteristics. Since increases and decreases in subnational population tend to offset each other resulting in a more subdued change at the national level, the challenge of population volatility is therefore largely a subnational problem. This research defines a parametric function called&#xa0;<i>ɛ</i>-volatility&#xa0;to analyze population volatility across the 50 states of the United States and the District of Columbia between 2010 and 2019. Three levels of volatility were considered to cover the full range of population changes: <i>ɛ</i>-normal,&#xa0;mildly&#xa0;<i>ɛ</i>-volatile, and&#xa0;strongly&#xa0;<i>ɛ</i>-volatile. Using data from the U.S. Census Bureau and Bureau of Labor Statistics, a multinomial linear regression model was used to examine the impact of educational attainment, unemployment, housing starts, wage, age and race on subnational volatility. The results suggest that subnational population volatility is most strongly influenced by the older working age group (45–64) that are at least high school graduates. The younger working age-group (18–44) also positively impacted population volatility regardless of educational attainment. The senior population (65 +) with high school or higher education affected population volatility to a lesser extent under certain circumstances. High population volatility can lead to urban squalor, congestion and fewer resources for social and municipal services. The ability to identify strong, mild, and normal population volatility can facilitate the formulation of policy decision-making at all levels.</p>

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Parametric Subnational Population Volatility: The Importance of Abnormal Fluctuations

  • 期刊论文

  • 发表日期：

    2025年4月7日

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  • Fazley K. Siddiq,
  • Gholam R. Amin,
  • Halyna Klymentieva

摘要

Changes in population size and density in a jurisdiction affect its economic and social characteristics. Since increases and decreases in subnational population tend to offset each other resulting in a more subdued change at the national level, the challenge of population volatility is therefore largely a subnational problem. This research defines a parametric function called ɛ-volatility to analyze population volatility across the 50 states of the United States and the District of Columbia between 2010 and 2019. Three levels of volatility were considered to cover the full range of population changes: ɛ-normal, mildly ɛ-volatile, and strongly ɛ-volatile. Using data from the U.S. Census Bureau and Bureau of Labor Statistics, a multinomial linear regression model was used to examine the impact of educational attainment, unemployment, housing starts, wage, age and race on subnational volatility. The results suggest that subnational population volatility is most strongly influenced by the older working age group (45–64) that are at least high school graduates. The younger working age-group (18–44) also positively impacted population volatility regardless of educational attainment. The senior population (65 +) with high school or higher education affected population volatility to a lesser extent under certain circumstances. High population volatility can lead to urban squalor, congestion and fewer resources for social and municipal services. The ability to identify strong, mild, and normal population volatility can facilitate the formulation of policy decision-making at all levels.