Globally, economies are highly concerned about the balance between climatic issues and attaining agricultural sustainability. However, empirical evidence regarding the nexus of agricultural sustainability, emissions, land use, and agricultural trade is scarce and requires appropriate policy-level attention. The current study examines the influence of land-use resources, agricultural exports, and foreign direct investment on agriculture-related greenhouse gas emissions in Brazil. Using various time series diagnostic measures on quarterly data from 1990Q1 to 2020Q4 reveals non-normality and a mixed order of stationarity in variables. The autoregressive distributed lag (ARDL) model and quantile ARDL approach are employed for comprehensive empirical analysis. The results assert that land resources and foreign investments are harmful to environmental sustainability, as they significantly enhance agricultural greenhouse gas emissions. Additionally, agricultural exports and green energy significantly contribute to emissions mitigation by tackling land-use and agricultural emissions in the short and long run. The results are robust across the ARDL and quantile regressions and pairwise granger causality. The study concludes that agricultural exports and land use are key factors inducing agricultural sustainability by inducing emissions. The study recommends increased spending on research and development, solar-based irrigation, and promotion of green energy projects. The study discusses novel findings and implications apropos land resources, foreign investments, agricultural exports, and emissions in the lens of COP 28.

This paper explores the impact of economic complexity and financial development on energy efficiency through two indicators: energy intensity and carbon intensity, within the top 10 complex economies. Other control variables, such as economic growth, urbanization, and human capital, are also included in the models. Random and fixed-effects estimators with heteroskedasticity-consistent standard errors were used. Clustered random and fixed-effects estimators were considered to handle within-group (cluster) dependence. The study utilized the Driscoll-Kraay (DK) method to address non-spherical disturbances and ensure consistent standard errors and robustness against dependence. Feasible Generalized Least Squares (FGLS) considered entity-specific autocorrelation, and System Generalized Method of Moments (Sys-GMM) accommodated unobserved panel-level effects, were also employed. Our findings reveal that economic complexity is crucial in reducing carbon and energy intensity, highlighting the significance of fostering technological sectors to diversify and sophisticate the productive structure. However, the influence of financial development on these intensity measures remains ambiguous and necessitates further exploration. We propose policy implications aimed at boosting technological sectors, facilitating a green transition in the economy, and advancing the adoption of renewable energy technologies.

Economic complexity is considered key a driver of social change, structural change, and economic development. Economic complexity is mostly used to capture issues apropos product diversification of exports, trade, technological innovation, human knowledge, and skills. The current study has conducted a detailed bibliometric review of economic complexity, export quality, and trade diversification. In doing so, the authors used the literature up to 2021 to unveil economic complexity’s contextual information that witnessed structural change, social change, and trade indicators. The current study is the first integrative review to report the theoretical contribution, future research agendas, and thematic analysis of economic complexity, export quality, and export diversification. Our study, on the subject of economic complexity, export diversification, and import diversification in the period from 1966 to 2021, was carried out by systematically scanning 386 documents, and it is one of the pioneering studies in this field. In addition, economic diversity, development, and economic complexity; export diversification, import diversification, trade openness, and economic growth; energy, environmental Kuznets curve, and economic complexity; and sustainability and economic diversification are the four main research topics of the study. The findings are discussed apropos of economic complexity and exports, methodological aspects of economic complexity, and environmental issues nexus with economic complexity. The current study reports novel findings toward a path for achieving SDG-9 (industry and innovation) and SDG-13 (climate action). The biometric review enables researchers and policymakers to understand export quality, economic complexity, and the trade nexus and report future research directions for achieving sustainable growth in industries and innovation.