IDEAS home Printed from https://ideas.repec.org/a/kap/ecopln/v57y2024i2d10.1007_s10644-024-09591-3.html
   My bibliography  Save this article

The impact of domestic R&D and North–South R&D spillovers on energy intensity in developing countries

Author

Listed:
  • Dierk Herzer

    (Helmut-Schmidt-University Hamburg)

Abstract

This study utilizes panel data between 1995 and 2015 for a cross section of 33 developing (low- and middle-income) countries to investigate the impact on domestic energy intensity both of domestic R&D and of possible spillovers from foreign R&D conducted in developed (high-income) countries. More specifically, it examines R&D spillovers from developed countries (North) to domestic energy intensity in developing countries (South) through disembodied channels, total goods imports, and imports of machinery and equipment. Our main findings, based on panel cointegration techniques, are as follows: First, domestic R&D in the long run does not contribute to reductions in energy intensity in developing countries; second, there is no evidence to suggest that disembodied North–South R&D spillovers affect the long-run level of domestic energy intensity; third, there are nevertheless significant spillovers from R&D conducted in industrial countries that reduce energy intensity in developing countries; and fourth, while many imported goods are not a channel for North–South R&D spillovers, such spillovers are transmitted through imports of machinery and equipment.

Suggested Citation

  • Dierk Herzer, 2024. "The impact of domestic R&D and North–South R&D spillovers on energy intensity in developing countries," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-31, April.
  • Handle: RePEc:kap:ecopln:v:57:y:2024:i:2:d:10.1007_s10644-024-09591-3
    DOI: 10.1007/s10644-024-09591-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10644-024-09591-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10644-024-09591-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Madsen, Jakob B. & Saxena, Shishir & Ang, James B., 2010. "The Indian growth miracle and endogenous growth," Journal of Development Economics, Elsevier, vol. 93(1), pages 37-48, September.
    2. Juan J. Cortina & Tatiana Didier & Sergio L. Schmukler, 2018. "Corporate debt maturity in developing countries: Sources of long and short‐termism," The World Economy, Wiley Blackwell, vol. 41(12), pages 3288-3316, December.
    3. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    4. Entorf, Horst, 1997. "Random walks with drifts: Nonsense regression and spurious fixed-effect estimation," Journal of Econometrics, Elsevier, vol. 80(2), pages 287-296, October.
    5. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    6. Torfinn Harding & Beata S. Javorcik, 2011. "Roll Out the Red Carpet and They Will Come: Investment Promotion and FDI Inflows," Economic Journal, Royal Economic Society, vol. 121(557), pages 1445-1476, December.
    7. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    8. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    9. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    10. Davidson, James, 1998. "Structural relations, cointegration and identification: some simple results and their application," Journal of Econometrics, Elsevier, vol. 87(1), pages 87-113, August.
    11. Narjess Boubakri & Jean-Claude Cosset, 1998. "The Financial and Operating Performance of Newly Privatized Firms: Evidence from Developing Countries," Journal of Finance, American Finance Association, vol. 53(3), pages 1081-1110, June.
    12. Peter Pedroni, 2007. "Social capital, barriers to production and capital shares: implications for the importance of parameter heterogeneity from a nonstationary panel approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 429-451.
    13. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    14. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    15. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    16. Pedroni, Peter, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 653-670, Special I.
    17. Artūras Juodis & Simon Reese, 2022. "The Incidental Parameters Problem in Testing for Remaining Cross-Section Correlation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1191-1203, June.
    18. Hart, Rob, 2018. "Rebound, directed technological change, and aggregate demand for energy," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 218-234.
    19. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    20. Baccini, Leonardo & Urpelainen, Johannes, 2014. "International institutions and domestic politics: can preferential trading agreements help leaders promote economic reform?," LSE Research Online Documents on Economics 55608, London School of Economics and Political Science, LSE Library.
    21. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    22. Sadorsky, Perry, 2013. "Do urbanization and industrialization affect energy intensity in developing countries?," Energy Economics, Elsevier, vol. 37(C), pages 52-59.
    23. Christian Gengenbach & Jean‐Pierre Urbain & Joakim Westerlund, 2016. "Error Correction Testing in Panels with Common Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 982-1004, September.
    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. Dierk Herzer & Holger Strulik, 2017. "Religiosity and income: a panel cointegration and causality analysis," Applied Economics, Taylor & Francis Journals, vol. 49(30), pages 2922-2938, June.
    2. Herzer, Dierk & Nunnenkamp, Peter, 2015. "Income inequality and health: Evidence from developed and developing countries," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-56.
    3. Krenz, Astrid, 2016. "Do political institutions influence international trade? Measurement of institutions and the Long-Run effects," University of Göttingen Working Papers in Economics 276, University of Goettingen, Department of Economics.
    4. Herzer, Dierk, 2014. "Unions and income inequality: a heterogenous cointegration and causality analysis," Working Paper 146/2014, Helmut Schmidt University, Hamburg.
    5. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2014. "Green Growth in Mexico, Brazil and Chile: Policy strategies and future prospects," Ibero America Institute for Econ. Research (IAI) Discussion Papers 229, Ibero-America Institute for Economic Research.
    6. Dierk Herzer, 2016. "Unions and Income Inequality: A Heterogeneous Panel Co-integration and Causality Analysis," LABOUR, CEIS, vol. 30(3), pages 318-346, September.
    7. Adolfo Maza & Paula Gutiérrez-Portilla, 2022. "Outward FDI and exports relation: A heterogeneous panel approach dealing with cross-sectional dependence," International Economics, CEPII research center, issue 170, pages 174-189.
    8. Herzer, Dierk, 2013. "Cross-Country Heterogeneity and the Trade-Income Relationship," World Development, Elsevier, vol. 44(C), pages 194-211.
    9. Dierk Herzer & Julian Donaubauer, 2018. "The long-run effect of foreign direct investment on total factor productivity in developing countries: a panel cointegration analysis," Empirical Economics, Springer, vol. 54(2), pages 309-342, March.
    10. Dierk Herzer, 2017. "Refugee Immigration and Total Factor Productivity," International Economic Journal, Taylor & Francis Journals, vol. 31(3), pages 390-414, July.
    11. Daniel Sakyi & Jose Villaverde & Adolfo Maza & Krishna Reddy Chittedieonardo, 2012. "Trade Openness, Growth and Development: Evidence from Heterogeneous Panel Cointegration Analysis for Middle-Income Countries," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, August.
    12. Naima Chrid & Sami Saafi & Mohamed Chakroun, 2021. "Export Upgrading and Economic Growth: a Panel Cointegration and Causality Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 811-841, June.
    13. Dierk Herzer & Holger Strulik & Sebastian Vollmer, 2012. "The long-run determinants of fertility: one century of demographic change 1900–1999," Journal of Economic Growth, Springer, vol. 17(4), pages 357-385, December.
    14. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    15. Markus Eberhardt & Francis Teal, 2013. "No Mangoes in the Tundra: Spatial Heterogeneity in Agricultural Productivity Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 914-939, December.
    16. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    17. Markus Eberhardt & Francis Teal, 2010. "Aggregation versus Heterogeneity in Cross-Country Growth Empirics," CSAE Working Paper Series 2010-32, Centre for the Study of African Economies, University of Oxford.
    18. Gazi Hassan & Arusha Cooray & Mark Holmes, 2017. "The effect of female and male health on economic growth: cross-country evidence within a production function framework," Empirical Economics, Springer, vol. 52(2), pages 659-689, March.
    19. Dierk Herzer, 2017. "The Long-run Relationship Between Trade and Population Health: Evidence from Five Decades," The World Economy, Wiley Blackwell, vol. 40(2), pages 462-487, February.
    20. R. Golinelli & I. Mammi & A. Musolesi, 2018. "Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area," Working Papers wp1120, Dipartimento Scienze Economiche, Universita' di Bologna.

    More about this item

    Keywords

    Energy intensity; Domestic R&D; North–South R&D spillovers; Developing countries; Panel cointegration methods;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • F18 - International Economics - - Trade - - - Trade and Environment

    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:kap:ecopln:v:57:y:2024:i:2:d:10.1007_s10644-024-09591-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.