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The Relationship between Renewable Energy Consumption, CO2 Emissions, Economic Growth, and Industrial Production Index: The Case of Kazakhstan

Author

Listed:
  • Gulmira Issayeva

    (M.Auezov South Kazakhstan University, Shymkent, Kazakhstan)

  • Zhanar Dyussembekova

    (Narxoz University, Almaty, Kazakhstan)

  • Aina B. Aidarova

    (M.Auezov South Kazakhstan University, Shymkent, Kazakhstan)

  • Adelina B. Makhatova

    (Peoples’ Friendship University named after Academician A. Kuatbekov, Shymkent, Kazakhstan)

  • Gulnar Lukhmanova

    (Zhetysu University named after I. Zhansugurov, Taldykorgan, Kazakhstan)

  • Dariya Absemetova

    (Kenzhegali Sagadiyev University of International Business, Almaty, Kazakhstan)

  • Artur Bolganbayev

    (Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan)

Abstract

CO2 emission is an important parameter that indicates a country's development level and respect for nature. It's a well-known fact that a country's industrialization level and economic growth have a direct impact on CO2 emissions. We must prioritize the use of energy obtained from renewable sources and be mindful of our impact on the environment. This study analyses the industrial production index, economic growth, and the percentage of energy produced from renewable energy sources in energy consumption and CO2 emissions in Kazakhstan. The data are collected from the National Statistical Bureau of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan, Our World in Data, and the World Bank web pages. Research data were analyzed using the Johansen cointegration test, Vector Autoregressive (VAR) analysis, Granger causality analysis, and VECM model. In the study, we analyzed three key factors that impact CO2 emissions in Kazakhstan. Our findings revealed that these factors account for 16.1% of the variability in CO2 emissions, indicating the statistical accuracy of these variables. When deciding on renewable energy investments, it is very important to determine the causal relationship between renewable energy consumption and CO2 emissions. It seems that industrial development and economic growth can occur without any major concerns about CO2 emissions. This is based on the lack of statistical significance in the relationship between CO2 emissions and both the industrial production index and economic growth.

Suggested Citation

  • Gulmira Issayeva & Zhanar Dyussembekova & Aina B. Aidarova & Adelina B. Makhatova & Gulnar Lukhmanova & Dariya Absemetova & Artur Bolganbayev, 2023. "The Relationship between Renewable Energy Consumption, CO2 Emissions, Economic Growth, and Industrial Production Index: The Case of Kazakhstan," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 1-7, November.
    • Handle: RePEc:eco:journ2:2023-06-1
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    References listed on IDEAS

    as
    1. Saule Bekzhanova & Gulzhanat Tayauova & Serik Akhanov & Gulnar B. Tuleshova & Artur Bolganbayev & Gulnara M. Moldogaziyeva, 2023. "The Relationship between Gold and Oil Prices and the Stock Market Returns of Kazakh Energy Companies: Comparison of the pre-COVID-19 and post-COVID-19 Periods," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 8-14, September.
    2. Bhattacharya, Mita & Paramati, Sudharshan Reddy & Ozturk, Ilhan & Bhattacharya, Sankar, 2016. "The effect of renewable energy consumption on economic growth: Evidence from top 38 countries," Applied Energy, Elsevier, vol. 162(C), pages 733-741.
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    More about this item

    Keywords

    Kazakhstan; Renewable Energy; CO2 Emission; Economic Growth; Industrial Production Index;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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