Este artículo amplía el modelo seminal de mercado laboral regional de Blanchard y Katz con la inclusión de efectos de interacción por medio de un enfoque de datos de panel espacial dinámico. Son tres las contribuciones clave de este modelo ampliado: (i) la suposición poco realista de que las regiones son independientes entre sí ya no es necesaria; (ii) la magnitud y la importancia de los llamados efectos de spillover se pueden evaluar empíricamente; y (iii) se puede investigar las propagaciones temporal y espacial de perturbaciones en la demanda de mano de obra. Por medio de datos anuales del período 1986–2010 para 112 regiones en ocho países de la UE, se han estimado tanto los modelos no espaciales como los espaciales. Se encontró que la mayoría de los efectos de spillover son altamente significativos. De acuerdo con la teoría económica, el impacto de una perturbación de la demanda específica para una región es más grande en la región en la que se origina la perturbación. La perturbación también se propaga a otras regiones, afectando especialmente a los vecinos de primer y segundo orden."> Este artículo amplía el modelo seminal de mercado laboral regional de Blanchard y Katz con la inclusión de efectos de interacción por medio de un enfoque de datos de panel espacial dinámico. Son tres las contribuciones clave de este modelo ampliado: (i) la suposición poco realista de que las regiones son independientes entre sí ya no es necesaria; (ii) la magnitud y la importancia de los llamados efectos de spillover se pueden evaluar empíricamente; y (iii) se puede investigar las propagaciones temporal y espacial de perturbaciones en la demanda de mano de obra. Por medio de datos anuales del período 1986–2010 para 112 regiones en ocho países de la UE, se han estimado tanto los modelos no espaciales como los espaciales. Se encontró que la mayoría de los efectos de spillover son altamente significativos. De acuerdo con la teoría económica, el impacto de una perturbación de la demanda específica para una región es más grande en la región en la que se origina la perturbación. La perturbación también se propaga a otras regiones, afectando especialmente a los vecinos de primer y segundo orden."> Este artículo amplía el modelo seminal de mercado laboral regional de Blanchard y Katz con la inclusión de efectos de interacción por medio de un enfoqu">
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Modelling regional labour market dynamics in space and time

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  • Solmaria Halleck Vega
  • J. Paul Elhorst
Abstract
type="main" xml:lang="es"> Este artículo amplía el modelo seminal de mercado laboral regional de Blanchard y Katz con la inclusión de efectos de interacción por medio de un enfoque de datos de panel espacial dinámico. Son tres las contribuciones clave de este modelo ampliado: (i) la suposición poco realista de que las regiones son independientes entre sí ya no es necesaria; (ii) la magnitud y la importancia de los llamados efectos de spillover se pueden evaluar empíricamente; y (iii) se puede investigar las propagaciones temporal y espacial de perturbaciones en la demanda de mano de obra. Por medio de datos anuales del período 1986–2010 para 112 regiones en ocho países de la UE, se han estimado tanto los modelos no espaciales como los espaciales. Se encontró que la mayoría de los efectos de spillover son altamente significativos. De acuerdo con la teoría económica, el impacto de una perturbación de la demanda específica para una región es más grande en la región en la que se origina la perturbación. La perturbación también se propaga a otras regiones, afectando especialmente a los vecinos de primer y segundo orden.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:presci:v:93:y:2014:i:4:p:819-841
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    2. Pablo Fernández & Marcos Herrera Gómez, 2023. "Regresiones SUR Espaciales. Análisis Espacio-temporal del Empleo Sectorial en Argentina," Working Papers 279, Red Nacional de Investigadores en Economía (RedNIE).
    3. Iris Wanzenböck & Philipp Piribauer, 2018. "R&D networks and regional knowledge production in Europe: Evidence from a space‐time model," Papers in Regional Science, Wiley Blackwell, vol. 97(S1), pages 1-24, March.
    4. 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.
    5. Emmanuel Duguet & Yannick L'horty & Florent Sari, 2023. "Agglomeration effects and unemployment to work: Evidence from French data," Papers in Regional Science, Wiley Blackwell, vol. 102(1), pages 129-166, February.
    6. Elhorst, J. Paul & Emili, Silvia, 2022. "A spatial econometric multivariate model of Okun's law," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    7. Alejandro Almeida & Aida Galiano & Antonio A. Golpe & Juan M. Martín, 2020. "Regional unemployment and cyclical sensitivity in Spain," Letters in Spatial and Resource Sciences, Springer, vol. 13(2), pages 187-199, August.
    8. Haller, Peter & Heuermann, Daniel F., 2016. "Job search and hiring in local labor markets: Spillovers in regional matching functions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 125-138.
    9. 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.
    10. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
    11. J. Paul Elhorst & Marco Gross & Eugen Tereanu, 2021. "Cross‐Sectional Dependence And Spillovers In Space And Time: Where Spatial Econometrics And Global Var Models Meet," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 192-226, February.
    12. Dapeng Zhang, 2024. "Examining the Effects of Confirmed COVID-19 Cases and State Government Policies on Passenger Air Traffic Recovery by Proposing an OD Spatial Temporal Model," Networks and Spatial Economics, Springer, vol. 24(2), pages 341-359, June.
    13. Evgeny V. Balatsky & Natalia A. Ekimova, 2023. "Antifragility of the national economy: A heuristic assessment," Journal of New Economy, Ural State University of Economics, vol. 24(2), pages 28-49, July.
    14. Florin Oprea & Mihaela Onofrei & Dan Lupu & Georgeta Vintila & Gigel Paraschiv, 2020. "The Determinants of Economic Resilience. The Case of Eastern European Regions," Sustainability, MDPI, vol. 12(10), pages 1-11, May.
    15. 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.

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