Causal relationship between renewable energy consumption and manufacturing value added: Evidence from Kazakhstan

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The paper investigates the causal interaction between renewable energy consumption and manufacturing value added in Kazakhstan, a relationship of growing importance in the context of sustainable industrial development. The aim of the study is to assess the direction and nature of causality between these variables over the period from 2000 to 2021. To this end, the Toda-Yamamoto Granger causality test is applied, offering robust results regardless of the order of integration of the time series data. The empirical analysis identifies a statistically significant bidirectional causal relationship. Specifically, renewable energy consumption has a significant impact on manufacturing value added (p = 0.003), while manufacturing value added also significantly influences renewable energy consumption (p = 0.006). These findings reveal a reciprocal mechanism in which the expansion of renewable energy supports industrial growth, and industrial development, in turn, enhances renewable energy usage. The results underscore the strategic importance of integrating renewable energy policies with industrial development plans. From a policy perspective, the study provides practical insights into fostering sustainable economic growth by aligning environmental and industrial objectives in Kazakhstan.

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    • Figure 1. Trends in manufacturing value added and renewable energy consumption (2000–2021)
    • Figure 2. Scatter plot of manufacturing value added and renewable energy consumption
    • Figure 3. Dynamic responses of manufacturing value added and renewable energy consumption: Impulse response functions
    • Table 1. Descriptive statistics of data variables
    • Table 2. Unit root test
    • Table 3. Optimal lag selection
    • Table 4. Roots of the characteristics polynomial
    • Table 5. VAR diagnostic test results
    • Table 6. Toda-Yamamoto Granger causality test results
    • Conceptualization
      Ramil Hasanov, Asli Kazimova, Aytakin Mammadova
    • Data curation
      Ramil Hasanov, Rashad Salahov
    • Investigation
      Ramil Hasanov, Aytakin Mammadova
    • Methodology
      Ramil Hasanov, Laszlo Vasa
    • Resources
      Ramil Hasanov, Asli Kazimova, Aytakin Mammadova, Rashad Salahov
    • Software
      Ramil Hasanov
    • Supervision
      Ramil Hasanov, Laszlo Vasa
    • Visualization
      Ramil Hasanov, Rashad Salahov
    • Writing – original draft
      Ramil Hasanov, Aytakin Mammadova
    • Formal Analysis
      Asli Kazimova, Aytakin Mammadova, Rashad Salahov, Laszlo Vasa
    • Validation
      Asli Kazimova, Aytakin Mammadova, Rashad Salahov, Laszlo Vasa
    • Writing – review & editing
      Asli Kazimova, Rashad Salahov, Laszlo Vasa
    • Project administration
      Laszlo Vasa