IDEAS home Printed from https://ideas.repec.org/p/zbw/hwuaef/299236.html
   My bibliography  Save this paper

Investigating the effect of green finance initiatives on renewable energy penetration in Europe

Author

Listed:
  • Szendrei, Tibor
  • Eross, Andrea
  • Mohammed, Mustapha
  • Ersoy, Erkal

Abstract

As climate change becomes an ever-present problem, efforts have been made to make energy generation greener. One key tool to encourage renewable energy generation are feed-in-tariff policies, which have been employed in various countries across Europe. Using quarterly data, this study investigates the impact these policies had on the greening of the economy, on carbon emissions and on macroeconomic factors in European countries for the period 2011-2021. To achieve this, an energy augmented production function is postulated and estimated using a Bayesian Global VAR framework. We find a large degree of heterogeneity in the impact of feed-in-tariffs have on renewable energy penetration across the countries. Furthermore, negative externalities of simultaneous employment of green finance is found, highlighting that some coordination might be necessary to maximise the impact of such policies in achieving the goal of a greener energy profile.

Suggested Citation

  • Szendrei, Tibor & Eross, Andrea & Mohammed, Mustapha & Ersoy, Erkal, 2024. "Investigating the effect of green finance initiatives on renewable energy penetration in Europe," Accountancy, Economics, and Finance Working Papers 2024-07, Heriot-Watt University, Department of Accountancy, Economics, and Finance.
  • Handle: RePEc:zbw:hwuaef:299236
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/299236/1/1892313235.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eickmeier, Sandra & Ng, Tim, 2015. "How do US credit supply shocks propagate internationally? A GVAR approach," European Economic Review, Elsevier, vol. 74(C), pages 128-145.
    2. Bloch, Harry & Rafiq, Shuddhasattwa & Salim, Ruhul, 2015. "Economic growth with coal, oil and renewable energy consumption in China: Prospects for fuel substitution," Economic Modelling, Elsevier, vol. 44(C), pages 104-115.
    3. Akan, Taner, 2023. "Can renewable energy mitigate the impacts of inflation and policy interest on climate change?," Renewable Energy, Elsevier, vol. 214(C), pages 255-289.
    4. repec:hal:spmain:info:hdl:2441/2vteelu0n785l82j764n6ul273 is not listed on IDEAS
    5. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    6. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    7. Christopher A. Sims & Tao Zha, 1999. "Error Bands for Impulse Responses," Econometrica, Econometric Society, vol. 67(5), pages 1113-1156, September.
    8. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    9. Ewa Dziwok & Johannes Jäger, 2021. "A Classification of Different Approaches to Green Finance and Green Monetary Policy," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    10. Marin, Giovanni & Vona, Francesco, 2019. "Climate policies and skill-biased employment dynamics: Evidence from EU countries," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    11. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
    12. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    13. Cem Ertur & Wilfried Koch, 2007. "Growth, technological interdependence and spatial externalities: theory and evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1033-1062.
    14. Bercegol, Hervé & Benisty, Henri, 2022. "An energy-based macroeconomic model validated by global historical series since 1820," Ecological Economics, Elsevier, vol. 192(C).
    15. Kastner, Gregor, 2016. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i05).
    16. Smith, L. Vanessa & Yamagata, Takashi, 2011. "Firm level return–volatility analysis using dynamic panels," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 847-867.
    17. McWilliams, Ben & Sgaravatti, Giovanni & Tagliapietra, Simone & Zachmann, Georg, 2023. "How would the European Union fare without Russian energy?," Energy Policy, Elsevier, vol. 174(C).
    18. Keen, Steve & Ayres, Robert U. & Standish, Russell, 2019. "A Note on the Role of Energy in Production," Ecological Economics, Elsevier, vol. 157(C), pages 40-46.
    19. Burriel, Pablo & Galesi, Alessandro, 2018. "Uncovering the heterogeneous effects of ECB unconventional monetary policies across euro area countries," European Economic Review, Elsevier, vol. 101(C), pages 210-229.
    20. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    21. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2016. "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1371-1391, November.
    22. Severin Borenstein, 2012. "The Private and Public Economics of Renewable Electricity Generation," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 67-92, Winter.
    23. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    24. Florian Egli & Bjarne Steffen & Tobias S. Schmidt, 2018. "A dynamic analysis of financing conditions for renewable energy technologies," Nature Energy, Nature, vol. 3(12), pages 1084-1092, December.
    25. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    26. Böhringer, Christoph & Cuntz, Alexander & Harhoff, Dietmar & Asane-Otoo, Emmanuel, 2017. "The impact of the German feed-in tariff scheme on innovation: Evidence based on patent filings in renewable energy technologies," Energy Economics, Elsevier, vol. 67(C), pages 545-553.
    27. Kamil Makieła & Błażej Mazur & Jakub Głowacki, 2022. "The Impact of Renewable Energy Supply on Economic Growth and Productivity," Energies, MDPI, vol. 15(13), pages 1-13, June.
    28. Hervé Bercegol & H. Benisty, 2022. "An energy-based macroeconomic model validated by global historical series since 1820," Post-Print cea-03451983, HAL.
    29. Anneleen Vandeplas & Istvan Vanyolos & Mauro Vigani & Lukas Vogel, 2022. "The Possible Implications of the Green Transition for the EU Labour Market," European Economy - Discussion Papers 176, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    Full references (including those not matched with items on IDEAS)

    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. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    2. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2020. "International effects of a compression of euro area yield curves," Journal of Banking & Finance, Elsevier, vol. 113(C).
    3. Celani, Alessandro & Cerchiello, Paola & Pagnottoni, Paolo, 2024. "The topological structure of panel variance decomposition networks," Journal of Financial Stability, Elsevier, vol. 71(C).
    4. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    5. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Discussion Paper Series in Economics 31/2018, Norwegian School of Economics, Department of Economics.
    6. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    7. di Mauro, Filippo & Dées, Stéphane & Al-Haschimi, Alexander & Jančoková, Martina, 2014. "Linking distress of financial institutions to macrofinancial shocks," Working Paper Series 1749, European Central Bank.
    8. Sona Benecka & Ludmila Fadejeva & Martin Feldkircher, 2018. "Spillovers from Euro Area Monetary Policy: A Focus on Emerging Europe," Working Papers 2018/04, Latvijas Banka.
    9. Skouralis, Alexandros, 2021. "The role of systemic risk spillovers in the transmission of Euro Area monetary policy," ESRB Working Paper Series 129, European Systemic Risk Board.
    10. Deniz Sevinc & Edgar Mata Flores, 2021. "Macroeconomic and financial implications of multi‐dimensional interdependencies between OECD countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 741-776, January.
    11. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).
    12. Lastauskas, Povilas & Nguyen, Anh Dinh Minh, 2023. "Global impacts of US monetary policy uncertainty shocks," Journal of International Economics, Elsevier, vol. 145(C).
    13. Konstantakis, Konstantinos N. & Soklis, George & Michaelides, Panayotis G., 2017. "Tourism expenditures and crisis transmission: A general equilibrium GVAR analysis with network theory," Annals of Tourism Research, Elsevier, vol. 66(C), pages 74-94.
    14. Miguel A. Márquez & Julián Ramajo & Geoffrey JD. Hewings, 2015. "Regional growth and spatial spillovers: Evidence from an SpVAR for the Spanish regions," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 1-18, November.
    15. Benecká, Soňa & Fadejeva, Ludmila & Feldkircher, Martin, 2020. "The impact of euro Area monetary policy on Central and Eastern Europe," Journal of Policy Modeling, Elsevier, vol. 42(6), pages 1310-1333.
    16. Tomoo Inoue & Tatsuyoshi Okimoto, 2022. "How does unconventional monetary policy affect the global financial markets?," Empirical Economics, Springer, vol. 62(3), pages 1013-1036, March.
    17. Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Tsionas, Efthymios G. & Minou, Chrysanthi, 2015. "System estimation of GVAR with two dominants and network theory: Evidence for BRICs," Economic Modelling, Elsevier, vol. 51(C), pages 604-616.
    18. Florian Huber & Jesus Crespo-Cuaresma & Martin Feldkircher, 2014. "Forecasting with Bayesian Global Vector Autoregressions," ERSA conference papers ersa14p25, European Regional Science Association.
    19. Victor Echevarria Icaza & Simón Sosvilla-Rivero, 2017. "Yields on sovereign debt, fragmentation and monetary policy transmission in the euro area: A GVAR approach," Working Papers 17-01, Asociación Española de Economía y Finanzas Internacionales.
    20. Andrejs Zlobins, 2020. "Country-level effects of the ECB’s expanded asset purchase programme," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 20(2), pages 187-217.

    More about this item

    Keywords

    Bayesian Global VAR; Energy policy; Feed-in-tariff; GIRF; renewable energy; spillover effects;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:zbw:hwuaef:299236. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/dehwuuk.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.