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Oil price fluctuations and employment in Kern County: A Vector Error Correction approach

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  • Michieka, Nyakundi M.
  • Gearhart, Richard

Abstract

Kern County is one of the country's largest oil producing regions, in which the oil industry employs a significant fraction of the labor force in the county. In this study, the short- and long-run effects of oil price fluctuations on employment in Kern County are investigated using a Vector Error Correction model (VECM). Empirical results over the period 1990:01 to 2015:03 suggest long-run causality running from both WTI and Brent oil prices to employment. No causality is detected in the short-run. Kern County should formulate appropriate policies, which take into account the fact that changes in oil prices have long-term effects on employment rather than short term.

Suggested Citation

  • Michieka, Nyakundi M. & Gearhart, Richard, 2015. "Oil price fluctuations and employment in Kern County: A Vector Error Correction approach," Energy Policy, Elsevier, vol. 87(C), pages 584-590.
    • Handle: RePEc:eee:enepol:v:87:y:2015:i:c:p:584-590
    DOI: 10.1016/j.enpol.2015.09.043
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    Cited by:

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    2. Iman Cheratian & Mohammad Reza Farzanegan & Saleh Goltabar, 2019. "Oil Price Shocks and Unemployment Rate: New Evidence from the MENA Region," MAGKS Papers on Economics 201931, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Akinlo A. Enisan, 2020. "Asymmetric impacts of oil price shocks on unemployment: Evidence from Nigeria," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 12(1), pages 63-78, June.
    4. Cai, Zhengyu & Maguire, Karen & Winters, John V., 2018. "Who Benefits from Local Oil and Gas Employment? Labor Market Composition in the Oil and Gas Industry in Texas," GLO Discussion Paper Series 246, Global Labor Organization (GLO).
    5. Carpenter, Angela & Wagner, Marcus, 2019. "Environmental justice in the oil refinery industry: A panel analysis across United States counties," Ecological Economics, Elsevier, vol. 159(C), pages 101-109.
    6. Michieka, Nyakundi M. & Gearhart, Richard S., 2019. "Oil price dynamics and sectoral employment in the U.S," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 140-149.

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    More about this item

    Keywords

    C32; E24; Q43; R11; Keywords:; Kern County; Employment; Brent; West Texas Intermediate;
    All these keywords.

    JEL classification:

    • 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
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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