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Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models

Author

Listed:
  • Dayton M. Lambert

    (Department of Agricultural and Resource Economics, University of Tennessee, Knoxville, TN, USA)

  • Wan Xu

    (Wan Xu is a graduate student at the University of Florida, Gainesville, USA)

  • Raymond J. G. M. Florax

    (Department of Agricultural Economics, Purdue University, West Lafayette, IN, USA
    Department of Spatial Economics, VU University, Amsterdam, The Netherlands
    Tinbergen Institute, Amsterdam, The Netherlands)

Abstract

In this application, income and job growth in the eastern United States are explained using a partial adjustment model with regime switching potential and spatial spillover, or “Smooth Transition†spatial process models (STAR). This relatively new class of spatial regression models provides a parametric approach to testing hypotheses about the influence external economies have on “core-periphery†structures characterizing the Dixit-Stiglitz-Krugman type models describing regional economies. Growth is endogenized as a locally contagious process and specific to regimes, which are also endogenously determined by access to urban economies. The estimation approach relaxes distributional assumptions, using instruments to estimate the STAR process models with special attention given to instrument selection and definitions of spatial neighbors. In the empirical analysis, the authors focus on the specification of partial adjustment models by employing a common factor test to discern serial correlation from partial adjustment processes. Finally, an ex post qualitative analysis is conducted using phase diagrams to study convergence and stability properties of the regime-specific equilibrium solutions. A sensitivity analysis suggests that steady state employment levels in counties with Appalachian development highway networks is higher than counties without this infrastructure, but income levels are not different.

Suggested Citation

  • Dayton M. Lambert & Wan Xu & Raymond J. G. M. Florax, 2014. "Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models," International Regional Science Review, , vol. 37(3), pages 328-364, July.
  • Handle: RePEc:sae:inrsre:v:37:y:2014:i:3:p:328-364
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    References listed on IDEAS

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    Cited by:

    1. Di Caro, Paolo, 2014. "Testing and explaining economic resilience with an application to Italian regions," MPRA Paper 60298, University Library of Munich, Germany.
    2. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    3. repec:bla:presci:v:96:y:2017:i:1:p:93-113 is not listed on IDEAS
    4. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    5. repec:spr:anresc:v:60:y:2018:i:2:d:10.1007_s00168-017-0816-7 is not listed on IDEAS
    6. Brown, Jason & Lambert, Dayton, 2014. "Location decisions of natural gas extraction establishments: a smooth transition count model approach," Research Working Paper RWP 14-5, Federal Reserve Bank of Kansas City.
    7. Pede, Valerien O. & Florax, Raymond J.G.M. & Lambert, Dayton M., 2014. "Spatial econometric STAR models: Lagrange multiplier tests, Monte Carlo simulations and an empirical application," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 118-128.
    8. Timo Mitze & Torben Schmidt, 2015. "Internal migration, regional labor markets and the role of agglomeration economies," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 55(1), pages 61-101, October.
    9. repec:eee:appene:v:218:y:2018:i:c:p:266-281 is not listed on IDEAS

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