IDEAS home Printed from https://ideas.repec.org/a/spr/minecn/v37y2024i4d10.1007_s13563-024-00475-6.html
   My bibliography  Save this article

How does climate policy uncertainty influence sustainable development? Unraveling role of recycling and natural resources in the United States

Author

Listed:
  • Ilma Sharif

    (University of Karachi)

  • Syed Tehseen Jawaid

    (University of Karachi)

  • Muhammed Nadeem Khan

    (Iqra University)

  • Aamir Hussain Siddiqui

    (University of Karachi)

Abstract

The impending climate policy has now become a threat to the United States (US) to maintain its economic growth. However, prevailing studies have extensively discovered economic uncertainty, with a scant emphasis on climate policy uncertainty (CPU). Therefore, policymakers emphasize the need to analyze the impact of CPU on economic dynamics. In this perspective, recycling (RCY) can mitigate adverse effects, and natural resources (NRR) are economic drivers in the US. Our study investigates the influence of CPU, RCY, and NRR on economic growth using annual data between 1990 and 2021. After confirming unit root and cointegration analysis, the study employs an autoregressive distributed lag (ARDL) model and rolling window approach for empirical evaluation. The long-run findings exhibit that CPU has a significant negative association and dampens economic growth by 0.046%. Contradictly, RCY and NRR promote economic growth by 0.518% and 0.026%, respectively. Likewise, consistent outcomes are estimated in the short run with different magnitudes, and the post-estimation affirms the consistency of the outcomes. Besides, the rolling window calculation indicates positive parameters for RCY and NRR and a negative coefficient for CPU. The study also estimated regression coefficients in the robustness analysis. The Granger causality estimation reveals one-way causality from NRR and RCY to economic growth, while unidirectional causality from economic growth to CPU. Overall, this study suggests that sustainable climate policies require recycling practices and efficient resource allocation to stimulate economic growth in the US.

Suggested Citation

  • Ilma Sharif & Syed Tehseen Jawaid & Muhammed Nadeem Khan & Aamir Hussain Siddiqui, 2024. "How does climate policy uncertainty influence sustainable development? Unraveling role of recycling and natural resources in the United States," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 37(4), pages 943-960, December.
  • Handle: RePEc:spr:minecn:v:37:y:2024:i:4:d:10.1007_s13563-024-00475-6
    DOI: 10.1007/s13563-024-00475-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13563-024-00475-6
    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/s13563-024-00475-6?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.

    More about this item

    Keywords

    Natural resources; Recycling; Climate uncertainty; Economic growth; United States; ARDL;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:spr:minecn:v:37:y:2024:i:4:d:10.1007_s13563-024-00475-6. 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: 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.