Do production subsidies have a wage incidence in wind power?

De Silva, Dakshina G. and McComb, Robert P. and Schiller, Anita R. (2011): Do production subsidies have a wage incidence in wind power?

Abstract

Employment in electricity generation from renewable resources has expanded rapidly in the US and in Texas during the last decade. Availability of the Production Tax Credit has been an important driver of this growth. Using establishment-level employment and payroll data for Texas at the NAICS-6 level, we analyze the differences in average wages between firms generating electricity from fossil fuels and those generating electricity from wind power. We compare relative average wages before and after the rapid expansion of wind power development that followed the ex ante renewal of the Production Tax Credit (PTC) in 2006. Our main finding using both parametric and the nonparametric estimation technique proposed by Racine and Li (2004), is that average payrolls for wind power generators increased relative to fossil fuel-based electricity generators after 2006.

• Item Type: MPRA Paper
• Language: English
• Keywords: Wages, Production Tax Credits, Wind energy, Clean Energy
• Subjects: J - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J31 - Wage Level and Structure ; Wage Differentials; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q2 - Renewable Resources and Conservation > Q28 - Government Policy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q2 - Renewable Resources and Conservation > Q20 - General

References

Addison, John T., McKinley L. Blackburn, and Chad D. Cotti (2009). “Do minimum wages raise employment? Evidence from the U.S. retail-trade sector” Labour Economics, 16(4): 397-408.

Ahmad, I.A. and P.B. Cerrito (1994). “Nonparametric estimation of joint discrete-continuous probability densities with applications.” Journal of Statistical Planning and Inference , 41: 349- 364.

Aitchison, J. and C.G.G. Aitken (1976). “Multivariate binary discrimination by the kernel method.” Biometrika, 63: 413-420.

Arulampalam, W., Devereux, M. P. and Maffini, G.(2010). “The Direct Incidence of Corporate Income Tax on Wages.” IZA Discussion Paper No. 5293.

Bond, Christopher S. (2009). “Yellow Light on Green Jobs,” U.S. Senate Sub-Committee on Green Jobs and the Economy, A Report by the U.S. Senate Subcommittee on Green Jobs and the New Economy.

Bertrand M, E Duflo and S Mullainathan (2004). How much should we trust differences-in differences estimates? The Quarterly Journal of Economics, 119 (1): 249-275.

De Silva, Dakshina G., Robert P. McComb, Young-Kyu Moh, Anita R. Schiller, and Andres J. Vargas (2010). "The Effect of Migration on Wages: Evidence from a Natural Experiment." American Economic Review, 100(2): 321–26.

Dube, A., S Naidu, and Michael Reich (2007). “The economic effects of a citywide minimum wage” Industrial and Labor Relations Review, 60(4): 522-543.

Dube, A., T. William Lester, and Michael Reich (2010). “Minimum Wage Effects Across State Borders: Estimates Using Contiguous Counties” The Review of Economics and Statistics, 92(4): 945–964.

Grund, B. (1993), “Kernel estimators for cell probabilities.” Journal of Multivariate Analysis, 46, 283-308.

Grund, B. and P. Hall (1993). “On the performance of kernel estimators for high-dimensional sparse binary data.” Journal of Multivariate Analysis, 44: 321-344.

Gulen, G., Michelle Foss, Dimitry Volkov, Ruzanna Makaryan (2009). RPS in Texas – Lessons Learned & Way Forward 32nd IAEE International Conference. Online Proceedings.http://www.usaee.org/usaee2009/submissions/OnlineProceedings/Gulen%20et%20al.pdf

Häardle, W. and J.S. Marron (1985). “Optimal bandwidth selection in nonparametric regression function estimation,” The Annals of Statistics, 13: 1465-1481.

Hall, P. (1981). “On nonparametric multivariate binary discrimination," Biometrika, 68: 287-294.

Hall, P. (1987a). “On Kullback-Leibler loss and density estimation,” The Annals of Statistics, 15: 1491-1519.

Hall, P. (1987b). “On the use of compactly supported densities in problems of discrimination," Journal of Multivariate Analysis, 23: 131-158.

Lewis, Joanna I. and Ryan H. Wiser (2007). Fostering a renewable energy technology industry: An international comparison of wind industry policy support mechanisms, Energy Policy, 35(3): 1844-1857.

Lindstrom, E. (2011) “Renewable Energy in the Inland Empire,” Center of Excellence, Desert & San Diego/Imperial Regions, available at http://pdc.sbccd.cc.ca.us/Docs/ES_Reports/Renewable_Energy_in_the_IE_Apr2011.pdf

Moulton, Brent R. (1990). “An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Units,” Review of Economics and Statistics 72(2): 334-38.

Pollin, Robert, James Heintz, and Heidi Garrett-Peltier (2009). “The Economic Benefits of Investing in Clean Energy: How the Economic Stimulus Program and New Legislation Can Boost U.S. Economic Growth and Employment,” Center for American Progress and Political Economy Research Institute, June http://www.peri.umass.edu/fileadmin/pdf/other_publication_types/green_economics/economic_benefits/economic_benefits.PDF

Pollin, R., James Heintz, and Heidi Garrett-Peltier (2010). “Clean Energy Investments for the U. S. Economy: Researching the Effects on Employment Opportunities and Economic Growth.” Department of Economics and Political Economy Research Institute, University of Massachusetts-Amherst. Working Paper.

Racine J. and Q. Li (2004). “Nonparametric estimation of regression functions with both categorical and continuous data.” Journal of Econometrics 119 (1): 99-130.

Summers, Lawrence H. (1981), “Taxation and Capital Accumulation in a Life-Cylce Growth Model,” American Economic Review, 533-544.

Tutz, G. (1991). “Consistency of cross-validatory choice of smoothing parameters for direct kernel estimates,” Computational Statistics Quarterly, 4: 295-314. U.S. Energy Information Administration – EIA – Independent Statistics and Analysis. http://www.eia.doe.gov

Wiser, Ryan (2007). “Wind Power and the Production Tax Credit: An Overview of Research Results.” Testimony Prepared for a Hearing on “Clean Energy: From the Margins to the Mainstream” Senate Finance Committee, Lawrence Berkeley National Laboratory / PUB-971.

Wiser, R., M. Bolinger, G. Barbose (2007). Using the Federal Production Tax Credit to Build a Durable Market for Wind Power in the United States. The Electricity Journal, 20(9): 77-88.