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Oil price changes and wages: a nonlinear and asymmetric approach

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Abstract

We assess the relationship between oil prices and wages in 15 top oil producing counties in the USA using data between 2001 and 2018. The analysis is conducted at the sectoral level where wages in seven industries are assessed in both the long- and short-run using a panel ARDL model. Asymmetric county level analyses are also conducted using nonlinear ARDL (NARDL) models. Results from the panel indicate that in the long-run, a positive shock to oil prices granger causes wages to increase in all sectors, with the largest (smallest) increase in the manufacturing (service) sector. Short-run coefficients indicate that oil price shocks have the largest effect on resource sector wages. County level results from the NARDL models provide evidence that there is no consistent effect on wages following oil price shocks in the long- and short-run in the overall economy.

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Fig. 1

Source: Adapted from the Bureau of Labor Statistics (2015)

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Notes

  1. Each state represents the county from the sample. For example, the “dark-blue” in California represents the correlation of correlation (r) between oil prices and the wages in Kern County.

  2. Estimated equations that failed all diagnostic tests (not homoskedastic, serially correlated, or not normally distributed) were omitted. For instance, total wages for Kern, Las Animas and Washington Counties were missing from Tables 10, 11 and 16, respectively, because the estimated models failed the diagnostic tests.

  3. In this study, we do not report the cumulative long-run coefficients to save on space.

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Acknowledgement

We acknowledge the useful comments made by the reviewers. We would also like to thank Jasneet Kaur and Jordy De Jesus for their help with data collection.

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  1. Department of Economics, California State University, 9001 Stockdale Highway, Bakersfield, USA

    Nyakundi M. Michieka & Richard S. Gearhart III

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  1. Nyakundi M. Michieka
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  2. Richard S. Gearhart III
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Correspondence to Nyakundi M. Michieka.

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Appendices

Appendix 1: Panel unit root tests

See Table 18 and 19.

Table 18 Panel unit root test results—employment
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Table 19 Panel unit root test results—wages
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Appendix 2: Zivot Andrews unit root tests

See Tables 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35.

Table 20 Union County (Arkansas)
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Table 21 Kern County (California)
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Table 22 Las Animas County (Colorado)
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Table 23 Lawrence County (Illiniois)
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Table 24 Grant County (Kansas)
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Table 25 Pike County (Kentucky)
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Table 26 Plaquemines Parish (Louisiana)
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Table 27 Richland County (Montana)
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Table 28 Bowman County (North Dakota)
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Table 29 Eddy County (New Mexico)
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Table 30 Noble County (Ohio)
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Table 31 Washington County (Oklahoma)
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Table 32 McKean County (Pennsylvania)
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Table 33 Young County (Texas)
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Table 34 Duchesne County (Utah)
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Table 35 Lincoln County (Wyoming)
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Michieka, N.M., Gearhart, R.S. Oil price changes and wages: a nonlinear and asymmetric approach. Econ Change Restruct 55, 1–71 (2022). https://doi.org/10.1007/s10644-020-09314-4

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