What drives labor force participation rate variability? The case of West Virginia

This study examines the dynamics of labor force participation rates across counties in West Virginia to better understand local labor market integration and the factors influencing fluctuations in participation. Drawing on county-level data from January 1990 to July 2020, the research employs a dynamic factor model to decompose labor force participation rates into latent factors at the state, metropolitan/non-metropolitan, and county levels. The findings reveal a general lack of labor market integration across West Virginia, highlighting potential opportunities for growth through enhanced integration. Further analysis using panel data models identifies key determinants of labor force participation, including personal income, education, infrastructure, and the prominence of industries such as agriculture and natural gas. The results underscore the necessity for targeted county-level policies to bolster employment and promote economic expansion within the state.

Authors

Institutions

Publication Details

Journal
Economic Modelling
Published
2024-08-23
DOI
https://doi.org/10.1016/j.econmod.2024.106861
Citations
4
Primary Topic
Gender, Labor, and Family Dynamics
Type
article
Field-Weighted Citation Impact
3.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

What drives labor force participation rate variability? The case of West Virginia

Josh Beverly, Shamar L. Stewart, Clinton L. Neill
4 citations
Economic Modelling
Gender, Labor, and Family Dynamics
3.72
article

What drives labor force participation rate variability? The case of West Virginia

Josh Beverly, Shamar L. Stewart, Clinton L. Neill
article en
4 citations

Abstract

This study examines the dynamics of labor force participation rates across counties in West Virginia to better understand local labor market integration and the factors influencing fluctuations in participation. Drawing on county-level data from January 1990 to July 2020, the research employs a dynamic factor model to decompose labor force participation rates into latent factors at the state, metropolitan/non-metropolitan, and county levels. The findings reveal a general lack of labor market integration across West Virginia, highlighting potential opportunities for growth through enhanced integration. Further analysis using panel data models identifies key determinants of labor force participation, including personal income, education, infrastructure, and the prominence of industries such as agriculture and natural gas. The results underscore the necessity for targeted county-level policies to bolster employment and promote economic expansion within the state.

Economic ModellingVol. 140
Cornell University (US), Virginia Tech (US), Hamline University (US)
Decent work and economic growth
Openalex Percentile: Top 7%
Gender, Labor, and Family Dynamics
3.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

What drives labor force participation rate variability? The case of West Virginia — Josh Beverly, Shamar L. Stewart, et al. · Economic Modelling (2024) | TGRS Research Map | TGRS