IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v140y2024ics0264999324002189.html
   My bibliography  Save this article

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

Author

Listed:
  • Beverly, Josh
  • Stewart, Shamar L.
  • Neill, Clinton L.

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.

Suggested Citation

  • Beverly, Josh & Stewart, Shamar L. & Neill, Clinton L., 2024. "What drives labor force participation rate variability? The case of West Virginia," Economic Modelling, Elsevier, vol. 140(C).
  • Handle: RePEc:eee:ecmode:v:140:y:2024:i:c:s0264999324002189
    DOI: 10.1016/j.econmod.2024.106861
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999324002189
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2024.106861?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Amir Borges Ferreira Neto, 2023. "Do public libraries impact local labour markets? Evidence from Appalachia," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(2), pages 216-238, April.
    3. Lee, Grace H.Y. & Parasnis, Jaai, 2014. "Discouraged workers in developed countries and added workers in developing countries? Unemployment rate and labour force participation," Economic Modelling, Elsevier, vol. 41(C), pages 90-98.
    4. Solmaria Halleck Vega & J. Paul Elhorst, 2014. "Modelling regional labour market dynamics in space and time," Papers in Regional Science, Wiley Blackwell, vol. 93(4), pages 819-841, November.
    5. Alpay Filiztekin, 2009. "Regional unemployment in Turkey," Papers in Regional Science, Wiley Blackwell, vol. 88(4), pages 863-878, November.
    6. Michael W. L. Elsby & Ryan Michaels & David Ratner, 2019. "The aggregate effects of labor market frictions," Quantitative Economics, Econometric Society, vol. 10(3), pages 803-852, July.
    7. Barbara Petrongolo & Christopher A. Pissarides, 2008. "The Ins and Outs of European Unemployment," American Economic Review, American Economic Association, vol. 98(2), pages 256-262, May.
    8. Arusha Cooray & Nabamita Dutta & Sushanta Mallick, 2017. "Trade Openness and Labor Force Participation in Africa: The Role of Political Institutions," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 56(2), pages 319-350, April.
    9. Maté-Sánchez-Val, Mariluz & López-Hernandez, Fernando & Rodriguez Fuentes, Christian Camilo, 2018. "Geographical factors and business failure: An empirical study from the Madrid metropolitan area," Economic Modelling, Elsevier, vol. 74(C), pages 275-283.
    10. Jun Ma & Andrew Vivian & Mark E. Wohar, 2018. "Global factors and equity market valuations: Do country characteristics matter?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 427-441, October.
    11. Betz, Michael R. & Partridge, Mark D. & Farren, Michael & Lobao, Linda, 2015. "Coal mining, economic development, and the natural resources curse," Energy Economics, Elsevier, vol. 50(C), pages 105-116.
    12. Heather M Stephens & John Deskins, 2018. "Economic Distress and Labor Market Participation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(5), pages 1336-1356.
    13. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
    14. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    15. Michael W. L. Elsby & Bart Hobijn & Ayşegül Şahin, 2013. "Unemployment Dynamics in the OECD," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 530-548, May.
    16. Mark D. Partridge & Michael R. Betz & Linda Lobao, 2013. "Natural Resource Curse and Poverty in Appalachian America," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 449-456.
    17. Bian, Zhicun & Ma, Jun & Ni, Jinlan & Stewart, Shamar, 2020. "Synchronization of regional growth dynamics in China," China Economic Review, Elsevier, vol. 61(C).
    18. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
    19. Gary Solon & Ryan Michaels & Michael W. L. Elsby, 2009. "The Ins and Outs of Cyclical Unemployment," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 84-110, January.
    20. Alessandra Fogli & Laura Veldkamp, 2011. "Nature or Nurture? Learning and the Geography of Female Labor Force Participation," Econometrica, Econometric Society, vol. 79(4), pages 1103-1138, July.
    21. Kagraoka, Yusho, 2016. "Common dynamic factors in driving commodity prices: Implications of a generalized dynamic factor model," Economic Modelling, Elsevier, vol. 52(PB), pages 609-617.
    22. Alison E. Weingarden, 2017. "Labor Market Outcomes in Metropolitan and Non-Metropolitan Areas : Signs of Growing Disparities," FEDS Notes 2017-09-25, Board of Governors of the Federal Reserve System (U.S.).
    23. Decressin, Jorg & Fatas, Antonio, 1995. "Regional labor market dynamics in Europe," European Economic Review, Elsevier, vol. 39(9), pages 1627-1655, December.
    24. J. Elhorst, 2008. "A spatiotemporal analysis of aggregate labour force behaviour by sex and age across the European Union," Journal of Geographical Systems, Springer, vol. 10(2), pages 167-190, June.
    25. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    26. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    27. Neely, Christopher J. & Rapach, David E., 2011. "International comovements in inflation rates and country characteristics," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1471-1490.
    28. Bhatt, Vipul & Kishor, N Kundan & Ma, Jun, 2017. "The impact of EMU on bond yield convergence: Evidence from a time-varying dynamic factor model," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 206-222.
    29. Euan Phimister & Esperanza Vera-Toscano & Alfons Weersink, 2002. "Female Participation and Labor Market Attachment in Rural Canada," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 210-221.
    30. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    31. Martín-Román, Ángel L., 2022. "Beyond the added-worker and the discouraged-worker effects: the entitled-worker effect," Economic Modelling, Elsevier, vol. 110(C).
    32. Chinhui Juhn & Simon Potter, 2006. "Changes in Labor Force Participation in the United States," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 27-46, Summer.
    33. Michael W. L. Elsby & Bart Hobijn & Aysegul Sahin & Robert G. Valletta, 2011. "The Labor Market in the Great Recession — An Update to September 2011," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 42(2 (Fall)), pages 353-384.
    34. Etienne Lalé, 2018. "Turbulence and the employment experience of older workers," Quantitative Economics, Econometric Society, vol. 9(2), pages 735-784, July.
    35. Hamrick, Karen S., 1997. "Rural Labor Markets Often Lead Urban Markets in Recessions and Expansions," Rural America/ Rural Development Perspectives, United States Department of Agriculture, Economic Research Service, vol. 12(3), June.
    36. Maureen Kilkenny & Sonya Kostova Huffman, 2003. "Rural/Urban Welfare Program and Labor Force Participation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 914-927.
    37. Jacob Mincer, 1962. "Labor Force Participation of Married Women: A Study of Labor Supply," NBER Chapters, in: Aspects of Labor Economics, pages 63-105, National Bureau of Economic Research, Inc.
    38. Lührmann, Melanie & Weiss, Matthias, 2010. "The effect of working time and labor force participation on unemployment: A new argument in an old debate," Economic Modelling, Elsevier, vol. 27(1), pages 67-82, January.
    39. Stephen T. Marston, 1985. "Two Views of the Geographic Distribution of Unemployment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 100(1), pages 57-79.
    40. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    41. Tomaz Cajner & Tyler Radler & David Ratner & Ivan Vidangos, 2017. "Racial Gaps in Labor Market Outcomes in the Last Four Decades and over the Business Cycle," Finance and Economics Discussion Series 2017-071, Board of Governors of the Federal Reserve System (U.S.).
    42. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    43. J. Paul Elhorst, 2003. "The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 709-748, December.
    44. Fang Cai & Yang Lu, 2013. "Population Change and Resulting Slowdown in Potential GDP Growth in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(2), pages 1-14, March.
    45. Akiko Sakanishi, 2020. "Spatial analysis of female labor force participation rates in Japan," International Journal of Economic Policy Studies, Springer, vol. 14(2), pages 351-361, August.
    46. Rodrigo Ad'o & Costas Arkolakis & Federico Esp'sito, 2019. "Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence," Cowles Foundation Discussion Papers 2163, Cowles Foundation for Research in Economics, Yale University.
    47. Baltagi, Badi H. & Blien, Uwe & Wolf, Katja, 2012. "A dynamic spatial panel data approach to the German wage curve," Economic Modelling, Elsevier, vol. 29(1), pages 12-21.
    48. Eleonora Patacchini & Yves Zenou, 2007. "Spatial dependence in local unemployment rates," Journal of Economic Geography, Oxford University Press, vol. 7(2), pages 169-191, March.
    49. Solmaria Halleck Vega & J. Paul Elhorst, 2017. "Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 138-160, July.
    50. John B. Taylor, 2016. "Can We Restart the Recovery All Over Again?," American Economic Review, American Economic Association, vol. 106(5), pages 48-51, May.
    51. Julie L. Hotchkiss & Fernando Rios-Avila, 2013. "Identifying Factors behind the Decline in the U.S. Labor Force Participation Rate," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 257-275, June.
    52. Michael W. L. Elsby & Bart Hobijn & Aysegul Sahin & Robert G. Valletta, 2011. "The Labor Market in the Great Recession — An Update to September 2011," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(2 (Fall)), pages 353-384.
    53. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Beverly, Joshua P. & Neill, Clinton L. & Stewart, Shamar, 2022. "The Dynamics of Labor Force Participation: All Quiet on the Appalachian Front?," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322258, Agricultural and Applied Economics Association.
    2. Ángel L. Martín‐Román & Jaime Cuéllar‐Martín & Alfonso Moral, 2020. "Labor supply and the business cycle: The “bandwagon worker effect”," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1607-1642, December.
    3. Solmaria Halleck Vega & J. Paul Elhorst, 2017. "Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 138-160, July.
    4. Heather M Stephens & John Deskins, 2018. "Economic Distress and Labor Market Participation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(5), pages 1336-1356.
    5. Halleck Vega, Solmaria & Elhorst, J. Paul, 2016. "A regional unemployment model simultaneously accounting for serial dynamics, spatial dependence and common factors," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 85-95.
    6. Enrique López-Bazo & Elisabet Motellón, 2013. "The regional distribution of unemployment: What do micro-data tell us?," Papers in Regional Science, Wiley Blackwell, vol. 92(2), pages 383-405, June.
    7. Ana María Díaz, 2016. "Spatial Unemployment Differentials in Colombia," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 76, February.
    8. Semerikova, Elena, 2014. "Unemployment in East and West Germany: Spatial panel data analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 107-132.
    9. Cuéllar Martín, Jaime & Martín-Román, Ángel L. & Moral, Alfonso, 2017. "A composed error model decomposition and spatial analysis of local unemployment," MPRA Paper 79783, University Library of Munich, Germany.
    10. Solmaria Halleck Vega & J. Paul Elhorst, 2014. "Modelling regional labour market dynamics in space and time," Papers in Regional Science, Wiley Blackwell, vol. 93(4), pages 819-841, November.
    11. Albertini Julien & Poirier Arthur & Sopraseuth Thepthida, 2020. "Informal work along the business cycle: evidence from Argentina," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 11(1), pages 1-16, January.
    12. Reneé van Eyden & Rangan Gupta & Christophe André & Xin Sheng, 2022. "The effect of macroeconomic uncertainty on housing returns and volatility: evidence from US state-level data," Chapters, in: Charles K.Y. Leung (ed.), Handbook of Real Estate and Macroeconomics, chapter 8, pages 206-238, Edward Elgar Publishing.
    13. Carl Singleton, 2018. "Long‐Term Unemployment and the Great Recession: Evidence from UK Stocks and Flows," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(2), pages 105-126, May.
    14. Christophe Andre & David Gabauer & Rangan Gupta, 2020. "Time-Varying Spillovers between Housing Sentiment and Housing Market in the United States," Working Papers 202091, University of Pretoria, Department of Economics.
    15. Elsby, Michael W.L. & Hobijn, Bart & Şahin, Ayşegül, 2015. "On the importance of the participation margin for labor market fluctuations," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 64-82.
    16. Laura Helena Kivi, 2019. "Spatial Interactions Of Regional Labour Markets In Europe," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 116, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    17. Franziska Lottmann, 2012. "Regional Unemployment in Germany: a spatial panel data analysis," ERSA conference papers ersa12p53, European Regional Science Association.
    18. André, Christophe & Gabauer, David & Gupta, Rangan, 2021. "Time-varying spillovers between housing sentiment and housing market in the United States☆," Finance Research Letters, Elsevier, vol. 42(C).
    19. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    20. Ciccarelli, Carlo & Elhorst, J.Paul, 2018. "A dynamic spatial econometric diffusion model with common factors: The rise and spread of cigarette consumption in Italy," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 131-142.

    More about this item

    Keywords

    Labor force participation; Dynamic factor model; Metro/non-metro; Bayesian analysis; Time series analysis;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • P25 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Urban, Rural, and Regional Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:140:y:2024:i:c:s0264999324002189. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.