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State-level wage Phillips curves

Author

Listed:
  • George Kapetanios
  • Simon Price
  • Menelaos Tasiou
  • Alexia Ventouri

Abstract

Two reduced-form versions of New Keynesian wage Phillips curves based on either sticky nominal wages or real-wage rigidity using monthly US state-level data for the period 1982-2016 are examined, taking account of the endogeneity of unemployment by instrumentation and the use of common correlated effects (CCE) and mean group (MG) methods. This is the first time that this methodology has been applied in this context. These are important issues, as ignoring them may lead to substantial biases. The results show that while the aggregate data do not provide estimates that are consistent with either of the theoretical models examined, the panel methods do. Moreover, use of an appropriate MG CCE estimator leads to economically significant changes in parameters (primarily a steeper Phillips curve) relative to those from inappropriate but widely used panel methods, and in the real-wage rigidity case is required to deliver results that have a theoretically admissible interpretation.

Suggested Citation

  • George Kapetanios & Simon Price & Menelaos Tasiou & Alexia Ventouri, 2020. "State-level wage Phillips curves," CAMA Working Papers 2020-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2020-08
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    Cited by:

    1. Rotundo, G. & Ausloos, M., 2007. "Microeconomic co-evolution model for financial technical analysis signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 569-585.
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    3. El-Shagi, Makram & Tochkov, Kiril, 2024. "Regional heterogeneity and the provincial Phillips curve in China," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1036-1044.
    4. Nie, Binjian & Zou, Boyang & She, Xiaohui & Zhang, Tongtong & Li, Yongliang & Ding, Yulong, 2020. "Development of a heat transfer coefficient based design method of a thermal energy storage device for transport air-conditioning applications," Energy, Elsevier, vol. 196(C).
    5. Schuffels, Johannes & Kool, Clemens & Lieb, Lenard & van Veen, Tom, 2024. "Is the slope of the euro area Phillips curve steeper than it seems? Heterogeneity and identification," Journal of International Money and Finance, Elsevier, vol. 148(C).
    6. Alderremy, A.A. & Saad, Khaled M. & Agarwal, Praveen & Aly, Shaban & Jain, Shilpi, 2020. "Certain new models of the multi space-fractional Gardner equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
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    8. Coma, Julià & Chàfer, Marta & Pérez, Gabriel & Cabeza, Luisa F., 2020. "How internal heat loads of buildings affect the effectiveness of vertical greenery systems? An experimental study," Renewable Energy, Elsevier, vol. 151(C), pages 919-930.
    9. Shi, Xin & Jiang, Haizhou & Li, Huan & Xu, Dong, 2020. "Maritime cluster research: Evolutionary classification and future development," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 237-254.
    10. Yoo, Yeawon & Escobedo, Adolfo R. & Skolfield, J. Kyle, 2020. "A new correlation coefficient for comparing and aggregating non-strict and incomplete rankings," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1025-1041.

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    Keywords

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    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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