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Time, frequency, and quantile-based role of R&D investments in energy on sectoral degradation in the United States

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  • Mustafa Tevfik Kartal

Abstract

An important part of environmental pollution has resulted in energy consumption, the level of environmental pollution varies across sectors, and energy R&D investments have been strategic tools in this respect. Considering this fact, the research studies the role of R&D investments in energy on CO 2 emissions by focusing on the USA case as pioneering R&D investing country in energy technologies. In this context, the study makes a disaggregated level analysis and performs various nonlinear methods to data between 1975/Q1 and 2020/Q4. The nonlinear empirical results demonstrate that (i) R&D investments have a strong dependency on sectoral CO 2 emissions across times and frequencies; (ii) at higher quantiles, R&D investments in nuclear energy have a generally declining impact on power and building sector CO 2 emissions, whereas R&D investments in renewable energy stimulate sectoral CO 2 emissions; (iii) R&D investments are causally effective on sectoral CO 2 emissions across various quantiles; (iv) R&D investments in total curb generally sectoral CO 2 emissions. The research demonstrates that R&D investments in energy on sectoral CO 2 emissions have a varying heterogonous impact based on time, frequency, quantile, and R&D types. Thus, USA policymakers should include time, frequency, quantile, R&D types, and sector-based differentiating impacts to curb sectoral CO 2 emissions in re-formulating energy environmental policy framework as a critical issue for ensuring sustainable development. Accordingly, various policies (e.g. relying on nuclear R&D investments, re-balance distribution of the R&D investments among the alternatives, consideration of sectoral differences) are discussed.

Suggested Citation

  • Mustafa Tevfik Kartal, 2025. "Time, frequency, and quantile-based role of R&D investments in energy on sectoral degradation in the United States," Energy & Environment, , vol. 36(8), pages 3658-3676, December.
  • Handle: RePEc:sae:engenv:v:36:y:2025:i:8:p:3658-3676
    DOI: 10.1177/0958305X241228508
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • N52 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - U.S.; Canada: 1913-
    • N72 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - U.S.; Canada: 1913-
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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