This paper investigates the association among energy consumption, carbon-dioxide emission, and India's economic growth along with supplemental variables including foreign direct investment, population density, inflation, and agricultural land. An autoregressive distributive lag model is applied over annual time-series data from 1985 to 2019. Further, the robustness and novelty of the model are confirmed by applying fully modified ordinary-least-square, dynamic ordinary-least-square, canonical co-integrating regression, variance decomposition, and impulse response function. The analysis results indicate that a cointegration association exists among variables. In the short run, the profound determinants of economic development are energy consumption, carbon-dioxide emission, inflation, and agricultural land. In the long run, both inflation and agricultural land significantly negatively influence economic growth while carbon emission drives a positive impact. Interestingly, a one-way Granger causality runs from economic growth towards energy consumption, carbon emission, and agricultural land. The new research presents a comprehensive understanding of economic growth indicators, aiding policymakers, and advancing existing literature. Consequently, as a recommendation, the policymakers should constitute explicit goals for renewable energy consumption to stimulate sustainable economic growth with carbon emission reduction.

中文翻译：

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能源消耗和碳排放会影响经济增长吗？印度使用 ARDL 方法获得的新见解

本文研究了能源消耗、二氧化碳排放和印度经济增长之间的关联，以及包括外国直接投资、人口密度、通货膨胀和农业用地在内的补充变量。对 1985 年至 2019 年的年度时间序列数据应用自回归分布滞后模型。此外，通过应用完全修改的普通最小二乘、动态普通最小二乘、典型协整，证实了模型的稳健性和新颖性回归、方差分解和脉冲响应函数。分析结果表明变量之间存在协整关联。在短期内，经济发展的深刻决定因素是能源消耗、二氧化碳排放、通货膨胀和农业用地。从长远来看，通货膨胀和农业用地都对经济增长产生了显着的负面影响，而碳排放则产生了积极影响。有趣的是，从经济增长到能源消耗、碳排放和农业用地的单向格兰杰因果关系。新研究全面了解经济增长指标，帮助决策者并推进现有文献。因此，作为一项建议，政策制定者应制定可再生能源消费的明确目标，以通过减少碳排放来刺激可持续经济增长。新研究全面了解经济增长指标，帮助决策者并推进现有文献。因此，作为一项建议，政策制定者应制定可再生能源消费的明确目标，以通过减少碳排放来刺激可持续经济增长。新研究全面了解经济增长指标，帮助决策者并推进现有文献。因此，作为一项建议，政策制定者应制定可再生能源消费的明确目标，以通过减少碳排放来刺激可持续经济增长。