IDEAS home Printed from https://ideas.repec.org/p/spa/wpaper/2019wpecon41.html
   My bibliography  Save this paper

The impact of wind power on the Brazilian labor market

Author

Listed:
  • Solange Goncalves
  • Thiago Rodrigues, Andre Chagas

Abstract

Wind power is an important source of renewable energy. Beyond the environmental dimension, the wind energy may contribute to the local development. Due to its weather conditions, Brazil emerges as one of the leading countries in the generation of wind power. This study estimates the impact of wind farms on the Brazilian labor market, through the exploration of the staggered nature of the sequential process of wind farm implantation between 2004 and 2016. We estimate the treatment effect parameters using a Difference--in--Differences (DiD) approach with: i) multiple time periods, ii) variation in treatment timing, and iii) dynamic treatment effects, through an event study design. We aggregate information from several data sources into a panel and we analyze the impact on employment and wages, by considering economic sectors, educational levels, and firm sizes. Our findings suggest that wind farms increase employment in the industry, agriculture and construction, and increase the wages in all economic sectors. Additionally, we find positive effects on the employment and wages of less--educated workers, and of small and medium--sized firms. The impact of this intervention can last for up to two years. Our results suggest that wind power may generate significant social impacts through the labor market, by contributing to local development and increasing social welfare in developing economies.

Suggested Citation

  • Solange Goncalves & Thiago Rodrigues, Andre Chagas, 2019. "The impact of wind power on the Brazilian labor market," Working Papers, Department of Economics 2019_41, University of São Paulo (FEA-USP).
  • Handle: RePEc:spa:wpaper:2019wpecon41
    as

    Download full text from publisher

    File URL: http://www.repec.eae.fea.usp.br/documentos/Goncalves_Rodrigues_Chagas_41WP.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Irene Botosaru & Federico H. Gutierrez, 2018. "Difference‐in‐differences when the treatment status is observed in only one period," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 73-90, January.
    2. Dettmann, Eva & Giebler, Alexander & Weyh, Antje, 2019. "flexpaneldid: A Stata command for causal analysis with varying treatment time and duration," IWH Discussion Papers 5/2019, Halle Institute for Economic Research (IWH).
    3. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    4. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    5. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
    6. Louis S. Jacobson & Robert J. LaLonde & Daniel G. Sullivan, 1993. "Long-term earnings losses of high-seniority displaced workers," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 17(Nov), pages 2-20.
    7. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    9. Athey, Susan & Imbens, Guido W., 2022. "Design-based analysis in Difference-In-Differences settings with staggered adoption," Journal of Econometrics, Elsevier, vol. 226(1), pages 62-79.
    10. Blanco, Maria Isabel & Rodrigues, Glória, 2009. "Direct employment in the wind energy sector: An EU study," Energy Policy, Elsevier, vol. 37(8), pages 2847-2857, August.
    11. Du, Yimeng & Takeuchi, Kenji, 2019. "Can climate mitigation help the poor? Measuring impacts of the CDM in rural China," Journal of Environmental Economics and Management, Elsevier, vol. 95(C), pages 178-197.
    12. Andrew Goodman-Bacon, 2018. "Difference-in-Differences with Variation in Treatment Timing," NBER Working Papers 25018, National Bureau of Economic Research, Inc.
    13. Mori-Clement, Yadira & Bednar-Friedl, Birgit, 2019. "Do Clean Development Mechanism Projects Generate Local Employment? Testing for Sectoral Effects across Brazilian Municipalities," Ecological Economics, Elsevier, vol. 157(C), pages 47-60.
    14. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    15. Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan & Vance, Colin, 2019. "Local cost for global benefit: The case of wind turbines," Ruhr Economic Papers 791, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, revised 2019.
    16. Antonio Pastorelli Rodrigues, Thiago & Ledi Gonçalves, Solange & Squarize Chagas, André, 2019. "Wind power and the labor market in the Brazilian Northeast: a spatial propensity score matching approach," Revista Brasileira de Estudos Regionais e Urbanos, Associação Brasileira de Estudos Regionais e Urbanos (ABER), vol. 13(3), pages 357-378, March.
    17. Hartley, Peter R. & Medlock, Kenneth B. & Temzelides, Ted & Zhang, Xinya, 2015. "Local employment impact from competing energy sources: Shale gas versus wind generation in Texas," Energy Economics, Elsevier, vol. 49(C), pages 610-619.
    18. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    19. Bergmann, Ariel & Hanley, Nick & Wright, Robert, 2006. "Valuing the attributes of renewable energy investments," Energy Policy, Elsevier, vol. 34(9), pages 1004-1014, June.
    20. Brown, Jason P. & Pender, John & Wiser, Ryan & Lantz, Eric & Hoen, Ben, 2012. "Ex post analysis of economic impacts from wind power development in U.S. counties," Energy Economics, Elsevier, vol. 34(6), pages 1743-1754.
    21. Moreno, Blanca & López, Ana Jesús, 2008. "The effect of renewable energy on employment. The case of Asturias (Spain)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(3), pages 732-751, April.
    22. Simas, Moana & Pacca, Sergio, 2014. "Assessing employment in renewable energy technologies: A case study for wind power in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 83-90.
    23. del Río, Pablo & Burguillo, Mercedes, 2008. "Assessing the impact of renewable energy deployment on local sustainability: Towards a theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(5), pages 1325-1344, June.
    24. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alexandre Costa, Rayssa & Nunes de Almeida, Alexandre & Martins Costa, Edward & Urano de Carvalho Castelar, Pablo & de Souza Nunes, Erivelton, 2022. "The effects of occupational mobility on wages of rehabilitated workers in Brazil," World Development, Elsevier, vol. 154(C).
    2. Peñasco, Cristina & Anadón, Laura Díaz, 2023. "Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales," Energy Economics, Elsevier, vol. 117(C).
    3. Marco Vocciante & Vincenzo G. Dovì & Sergio Ferro, 2021. "Sustainability in ElectroKinetic Remediation Processes: A Critical Analysis," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    4. Anne A. Gharaibeh & Deema A. Al-Shboul & Abdulla M. Al-Rawabdeh & Rasheed A. Jaradat, 2021. "Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization," Land, MDPI, vol. 10(5), pages 1-32, April.
    5. Arvanitopoulos, T. & Agnolucci, P., 2020. "The long-term effect of renewable electricity on employment in the United Kingdom," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    6. Diniz, Tiago B. & Caiado Couto, Lilia, 2024. "Achieving a high share of non-hydro renewable integration in Brazil through wind power: Regional growth and employment effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    7. Nunes, Gustavo & Giglio, Thalita, 2022. "Effects of climate change in the thermal and energy performance of low-income housing in Brazil—assessing design variable sensitivity over the 21st century," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    2. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    3. Arvanitopoulos, T. & Agnolucci, P., 2020. "The long-term effect of renewable electricity on employment in the United Kingdom," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    5. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    6. Rösner, Anja & Haucap, Justus & Heimeshoff, Ulrich, 2020. "The impact of consumer protection in the digital age: Evidence from the European Union," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    7. Jorge Rodríguez & Fernando Saltiel & Sergio Urzúa, 2022. "Dynamic treatment effects of job training," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 242-269, March.
    8. Bruno Ferman, 2023. "Inference in difference‐in‐differences: How much should we trust in independent clusters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 358-369, April.
    9. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
    10. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    11. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    12. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    13. Barreto, Yuri & Silveira Neto, Raul da Mota & Carazza, Luis, 2021. "Uber and traffic safety: Evidence from Brazilian cities," Journal of Urban Economics, Elsevier, vol. 123(C).
    14. Meekes, Jordy & Hassink, Wolter H.J., 2019. "The role of the housing market in workers′ resilience to job displacement after firm bankruptcy," Journal of Urban Economics, Elsevier, vol. 109(C), pages 41-65.
    15. Peter Z. Schochet, 2021. "Statistical Power for Estimating Treatment Effects Using Difference-in-Differences and Comparative Interrupted Time Series Designs with Variation in Treatment Timing," Papers 2102.06770, arXiv.org, revised Oct 2021.
    16. Ulbing, Philipp, 2024. "The Zero Lower Bound on Household Deposit Rates: Not As Binding As We Thought," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302353, Verein für Socialpolitik / German Economic Association.
    17. Yu, Fan & Xiao, De & Chang, Meng-Shiuh, 2021. "The impact of carbon emission trading schemes on urban-rural income inequality in China: A multi-period difference-in-differences method," Energy Policy, Elsevier, vol. 159(C).
    18. Meekes, Jordy & Hassink, Wolter, 2017. "The Role of the Housing Market in Workers' Resilience to Job Displacement after Firm Bankruptcy," IZA Discussion Papers 10894, Institute of Labor Economics (IZA).
    19. J. Meekes & W.H.J. Hassink, 2016. "The role of the housing market in workers’ resilience to job displacement after firm bankruptcy," Working Papers 16-10, Utrecht School of Economics.
    20. Luigi Aldieri & Jonas Grafström & Kristoffer Sundström & Concetto Paolo Vinci, 2019. "Wind Power and Job Creation," Sustainability, MDPI, vol. 12(1), pages 1-23, December.

    More about this item

    Keywords

    Wind power; staggered difference-in-differences; event study; employment; wages; labor market;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spa:wpaper:2019wpecon41. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pedro Garcia Duarte (email available below). General contact details of provider: https://edirc.repec.org/data/deuspbr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.