IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v57y2018icp236-245.html
   My bibliography  Save this article

A cointegrating polynomial regression analysis of the material kuznets curve hypothesis

Author

Listed:
  • Grabarczyk, Peter
  • Wagner, Martin
  • Frondel, Manuel
  • Sommer, Stephan

Abstract

This paper investigates the Material Kuznets Curve (MKC) hypothesis, postulating an inverted U-shaped relationship between a country's level of economic development and its intensity of material use, by means of nonlinear cointegration analysis. We use consumption data for aluminum, lead and zinc for eight OECD countries spanning from 1900 to 2006 and employ the tests and estimation techniques for nonlinear cointegration developed by Saikkonen and Choi (2004), Wagner (2013) as well as Wagner and Hong (2016). We find evidence for the prevalence of a cointegrating quadratic MKC for about half of the country-metal pairs.

Suggested Citation

  • Grabarczyk, Peter & Wagner, Martin & Frondel, Manuel & Sommer, Stephan, 2018. "A cointegrating polynomial regression analysis of the material kuznets curve hypothesis," Resources Policy, Elsevier, vol. 57(C), pages 236-245.
  • Handle: RePEc:eee:jrpoli:v:57:y:2018:i:c:p:236-245
    DOI: 10.1016/j.resourpol.2018.03.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420717304841
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2018.03.009?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.

    Citations

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


    Cited by:

    1. Xin, Yongrong & Ajaz, Tahseen & Shahzad, Mohsin & Luo, Jia, 2023. "How productive capacities influence trade-adjusted resources consumption in China: Testing resource-based EKC," Resources Policy, Elsevier, vol. 81(C).
    2. Fabian Knorre & Martin Wagner & Maximilian Grupe, 2021. "Monitoring Cointegrating Polynomial Regressions: Theory and Application to the Environmental Kuznets Curves for Carbon and Sulfur Dioxide Emissions," Econometrics, MDPI, vol. 9(1), pages 1-35, March.
    3. Wagner, Martin, 2023. "Fully modified least squares estimation and inference for systems of cointegrating polynomial regressions," Economics Letters, Elsevier, vol. 228(C).
    4. Olimpia Neagu, 2019. "The Link between Economic Complexity and Carbon Emissions in the European Union Countries: A Model Based on the Environmental Kuznets Curve (EKC) Approach," Sustainability, MDPI, vol. 11(17), pages 1-27, August.
    5. Martin Wagner, 2023. "Residual-based cointegration and non-cointegration tests for cointegrating polynomial regressions," Empirical Economics, Springer, vol. 65(1), pages 1-31, July.
    6. Razzaq, Asif & Ajaz, Tahseen & Li, Jing Claire & Irfan, Muhammad & Suksatan, Wanich, 2021. "Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economi," Resources Policy, Elsevier, vol. 74(C).
    7. Ulucak, Recep & Koçak, Emrah & Erdoğan, Seyfettin & Kassouri, Yacouba, 2020. "Investigating the non-linear effects of globalization on material consumption in the EU countries: Evidence from PSTR estimation," Resources Policy, Elsevier, vol. 67(C).
    8. Kassouri, Yacouba & Alola, Andrew Adewale & Savaş, Savaş, 2021. "The dynamics of material consumption in phases of the economic cycle for selected emerging countries," Resources Policy, Elsevier, vol. 70(C).
    9. Wagner, Martin & Grabarczyk, Peter & Hong, Seung Hyun, 2020. "Fully modified OLS estimation and inference for seemingly unrelated cointegrating polynomial regressions and the environmental Kuznets curve for carbon dioxide emissions," Journal of Econometrics, Elsevier, vol. 214(1), pages 216-255.

    More about this item

    Keywords

    Intensity of use; Material Kuznets curve; Metals; Nonlinear cointegration;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development

    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:eee:jrpoli:v:57:y:2018:i:c:p:236-245. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.