Trade has a crucial role in a country’s economic development. This study scrutinizes the impact of terms of trade (TOT), labor force, and capital on the United States’ economic growth. This study aims to investigate the short and long-run impacts of Capital, Labor, and Terms of Trade on the economic growth of the United States. To accomplish the study’s goals, this study analyzed a time series of annual data for the United States from 1980 to 2021. The Philipps-Perron test, the model of Augmented Dickey-Fuller (ADF) model, and the Autoregressive Distributed lag (ARDL) of the bound tests were applied to test whether the data is stationary or not. We employed an Autoregressive Distributed lag (ARDL) unit root model to examine the study variables’ short- and long-term associations. The outcomes of the unit root of the (ADF) test explain that both the Trace and Maximum Eigenvalues values showed that the study’s variables were stationary at both level and first difference, but stationarity was not there at the first difference using the PP model. At I(0) and I(1), the log(GDP), labor, capital, and log(TOT) stayed stationary. However, the estimated results of the (ARDL) model revealed that the economic growth of the United States was negatively and significantly affected by the (TOT), but economic growth, capital, and the labor force have favorable long and short-run relationships. The results of ECM(-1) imply that 7% of adjustment from disequilibrium to equilibrium from short-run to long-run. This study’s findings suggest that policymakers and governments ease trade between countries to achieve the highest economic growth.

Technological advancement and favorable geographical factors significantly increase environmental development. This study contributes to the existing body of knowledge by examining the impact of China‐East Asia trade, geography, and digitalization on CO₂ emissions, aiming to assess sustainable environmental development in East Asia from 1990 to 2021. The analysis employs Feasible Generalized Least Squares (FGLS) and the Dumitrescu and Hurlin (DH) causality tests to provide comprehensive insights. The findings reveal that China‐East Asia trade positively contributes to sustainable environmental development in East Asia by promoting economic integration and cleaner technological practices. However, the direct impact of geographical factors worsens sustainable environmental development, likely due to challenges related to distance, terrain, and natural resource distribution. Furthermore, the results highlight that digitalization significantly reduces CO₂ emissions, enhancing sustainable environmental development. Additionally, the threshold effect indicates that digitalization plays a crucial role in either amplifying or mitigating the impact of trade and geography by enhancing technological efficiency and facilitating information exchange, ultimately contributing to sustainable environmental development. The DH causality test results confirm that China‐East Asia trade, geography, and digitalization exhibit predictive power for sustainable environmental development, highlighting their interconnected roles in shaping environmental outcomes. This study concludes with key policy recommendations aimed at promoting sustainable environmental development by strengthening digitalization and refining trade policies to mitigate geographical constraints.

Technological innovation has emerged as a crucial driver of sustainable productivity in high‐income countries over the past five decades. Despite this, limited focus has been placed on achieving deep decarbonization and understanding the specific contributions of digitalization to enhance sustainable development. To fill this gap, our study explores the impact of the digitalization and geography nexus with sectoral factors, including agriculture and industry, in driving sustainable development from 1995 to 2022 in 67 high‐income countries. Utilizing the augmented mean group (AMG) estimator, a two‐step system generalized method of moments (GMM) model, and threshold effects to span both high and low levels of sustainable development. The results indicate that digitalization, geography, industrial, and agricultural expansion are significantly embedded in improving sustainable development. However, the interaction between digitalization and geography shows a diminishing effect, while digitalization's correlation with the agriculture and industrial sectors significantly boosts sustainable development. Furthermore, the outcomes of the threshold effects illustrate how digitalization is required to adapt and evolve across different levels of sustainable development within the geography, industrial, and agricultural sectors. Policymakers should invest in digital infrastructure and literacy, particularly in disadvantaged areas, to address the diminishing effects of digitalization on geography. Integrating advanced technologies into agriculture and industry can boost productivity and sustainability.