AUTHOR=Abate Meseret C. , Cai Baozhong , Albert Tesfay , Woldemariam Asrat Ayele , Zeng Rong , Addis Amsalu K. , Long Wenjin , Mekonen Melkamu K. 

TITLE=Do agricultural input resources contribute to economic growth in China? A dynamic ARDL simulation approach

JOURNAL=Frontiers in Sustainable Food Systems

VOLUME=Volume 9 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2025.1619447

DOI=10.3389/fsufs.2025.1619447

ISSN=2571-581X

ABSTRACT=Sustainable agricultural inputs are essential for enhancing food security, promoting development, and ensuring resilience in rapidly emerging economies; however, studies utilizing the advanced autoregressive distributed lag (ARDL) approach to investigate their impact on agriculture-driven economic growth remain limited. This research aims to fill this gap by employing a dynamic ARDL simulation model to analyze the relationship between sustainable agricultural inputs and economic growth in the agricultural sector, utilizing annual time series data spanning from 1983 to 2023. The analysis includes unit root tests, which affirm the stationarity of all variables, and the ARDL bounds test, which reveals a significant long-run cointegrating relationship among them. Our findings indicate that the expansion of irrigated areas and increased usage of chemical fertilizers contribute significantly to agricultural economic growth in both the short and long run, while agricultural mechanization only positively affects growth in the short run. Notably, the variable representing crop-sown land does not exhibit a statistically significant impact on agricultural economic growth across both time frames. Furthermore, the results from novel DYARDL simulations, which assess the implications of 10% positive and negative shocks, further substantiate both short-run and long-run analysis outcomes. The insights generated from this study highlight the critical role that sustainable agricultural inputs play in agricultural economic dynamics and provide evidence-based recommendations for fostering resilient, low-input systems that support global food security and agro-environmental sustainability.