**1. Introduction**

Increasing fossil energy consumption aggravates the problems of energy shortage and environmental pollution, resulting in an increase in greenhouse gas emissions [1,2]. While long-term large-scale greenhouse gas emissions are the key reason for extreme weather change [3]. To strengthen the governance of global climate and environment to promote green economic growth, the Paris Climate Agreement clearly puts forward the development of a low-carbon economy [4]. However, the increasing weather events further exacerbate the energy consumption for temperature regulation [5]. Driven by economic growth and increasing income, the energy consumption and greenhouse gas emissions in Organization for Economic Co-operation and Development (OECD) countries tend to be higher than that in non-OECD countries, and then needs to increase innovation input and improve the utilization rate of renewable energy [6]. Therefore, this paper explores the dynamic nexus of innovation input, climate change, and energy-environment-growth in OECD and non-OECD countries, which helps the policymaker to formulate differentiated

**Citation:** Li, Z.; Shen, T.; Yin, Y.; Chen, H.H. Innovation Input, Climate Change, and Energy-Environment-Growth Nexus: Evidence from OECD and Non-OECD Countries. *Energies* **2022**, *15*, 8927. https://doi.org/10.3390/ en15238927

Academic Editor: David Borge-Diez

Received: 31 October 2022 Accepted: 21 November 2022 Published: 25 November 2022

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energy and environmental policies to promote innovation input, increase renewable energy consumption and achieve green economic growth

Most studies have shown that energy consumption in response to temperature change varies greatly among countries in different climate regions [7–9]. Specifically, OECD countries are generally located in high latitudes with huge temperature differences, that is, hot summer and cold winter, while non-OECD countries are on the contrary In addition, according to the Environmental Kuznets Curve (EKC) hypothesis, when the economic income of OECD countries reaches a certain level, they begin to gradually pay attention to the improvement of the ecological environment [10]. With the support of high innovation input, energy efficiency and renewable energy consumption began to improve significantly, and greenhouse gas emissions gradually decreased [11]. In this context, based on the panel data of 35 OECD and 36 non-OECD countries from 2000–2019, this paper further examines the nexus of energy-environment-growth under the differentiated innovation input, which provides theoretical support for the EKC hypothesis.

Compared with the existing literature [12–14], using simultaneous equation and system generalized method of moments (sys-GMM) model is an effective method to explore the dynamic nexus of innovation input, climate change, and energy-environment-growth. As we all know, from the perspective of the production function, the framework of energyenvironment-growth includes three important equations: production equation, energy consumption equation, and pollution equation, and each equation provides a reference for further research in this field [15,16]. Moreover, cross-validation shows that the three equations should not be studied separately, which confirms that the simultaneous equations can effectively estimate the dynamic nexus of renewable energy consumption, greenhouse gas emissions, and green economic growth, and help to generate reliable empirical research conclusions [17,18].

This paper is dedicated to exploring the impact of innovative inputs, climate change on renewable energy, consumption of greenhouse gas emissions, and green economic growth. The contributions of this paper are in the following four aspects: First, this paper creatively introduces innovation inputs and climate change into the energy-environment-growth research framework to study their effects on renewable energy consumption, greenhouse gas emissions, and green economic growth. Second, this paper analyzes the differences in the effects caused by the heterogeneity of the sample intervals, and examines the dynamic relationship between innovation inputs, climate change, and energy-environmental growth comprehensively and systematically in the short (2015–2019), medium (2010–2019), and long term (2000–2019), respectively, further confirming the EKC hypothesis. Third, this paper uses frontier simultaneous equations and sys-GMM models to reveal the dynamic relationship among innovation inputs, climate change, and energy-environmental growth, which can better solve the heteroskedasticity, autocorrelation, and endogeneity problems in the model. Fourth, considering the accuracy and comprehensiveness of variable calculation this paper uses principal component analysis to construct the green economic growth index from four dimensions: economic development, resources and environment, globalization, and urban construction (see Table 1). Finally, according to the research results, this paper provides targeted suggestions for the government to develop differentiated energy and environmental policies to promote carbon emission reduction and green economic growth.


**Table 1.** Indicator system of green economic growth.

#### **2. Literature Review**

Energy-environment-growth nexus studies the causality among energy consumption, environmental pollution, and economic growth. Considerable foregoing discussions about this nexus have employed the method of the Granger causality test [19], while the simultaneous equation model is less familiar. To be specific, the granger causality test can only detect whether there is a causal relationship between the concerned variables, but not the relationship sign and sensitivity. However, the simultaneous equation model does not have this limitation. It can not only detect the sign and sensitivity between variables, but also add other essential control variables to avoid missing variables.

In recent decades, the energy-environment-growth nexus has been the subject of a great deal of academic research. There are three branches of research in the literature that deals with the relationships between target variables. The first branch of research focuses on the relationship between economic growth and environmental pollution. Existing literature relies heavily on the Environmental Kuznets Curve (EKC) hypothesis when studying the relationship between the two variables. Stern [20] asserts that the degree of environmental degradation first increased and then decreased with the increase of the GNP per capita. In addition, the degree of environmental degradation is usually measured by air pollution. Some empirical studies verify the EKC hypothesis, such as Naseem et al. studied the relationship between economic development and pollutant gas emissions in OECD and non-OECD countries [21]. And Nasir and Ur-Rehman [22] and Saboori et al. [23] confirmed the existence of the EKC hypothesis by examining the long-term relationship between greenhouse gas emissions (GHGs) and income in Malaysia and Pakistan, respectively.

The second branch investigates the relationship between energy consumption and economic growth. Since the initial study of Kraft [24], the nexus between energy and economy has been the focus of discussion among scholars [25–27]. However, in the existing literature, scholars have several different views on the existence and direction of the causal relationship between these two variables. Soytas and Sari [28] believed that there is no significant causal relationship between energy consumption and economic growth, and supports the neutral hypothesis. Huang et al. [29] pointed out that in middle-income and high-income countries, the economy can affect energy consumption, and supported the conservation hypothesis. In addition, Saidi and Hammami [30] indicated that energy consumption has a significant stimulative effect on economic growth, which supported the feedback hypothesis that there is a two-way causal relationship between the two variables [31,32]. The third branch is related to energy consumption and GHGs. There is a consensus that energy consumption is the main source of GHGs [33–35].
