Temporal Dynamics, Spatial Heterogeneity, and Associated Factors of Certified Organic Plant Production in China

Certified organic plant production has become an important component of China’s agricultural sustainability transition, yet its development remains temporally volatile and regionally uneven. Using a balanced panel of 31 provincial-level regions from 2014 to 2023, constructed from 118,953 product-level certification records, this study examines the temporal dynamics, spatial heterogeneity, and provincial factors associated with certification-recorded production of primary organic plant products. Descriptive statistics and concentration indicators are used to characterize temporal changes and regional disparities, while annual Global Moran’s I statistics assess spatial autocorrelation. A two-way fixed-effects (TWFE) model is then used to estimate conditional within-province associations, and spatial autoregressive (SAR), spatial error (SEM), and Spatial Durbin (SDM) models are employed as diagnostic comparisons for residual spatial dependence. Robustness analyses include winsorization, exclusion of 2023, one-year-lagged explanatory variables, and an alternative production-intensity measure. The results show pronounced temporal volatility and persistent regional concentration. Global Moran’s I indicates significant positive spatial autocorrelation in 2018–2021 and 2023, but not in the remaining years. In the baseline TWFE specification, urbanization rate and e-commerce purchasing volume are positively associated with certified organic plant production, whereas population size shows a significant negative conditional association. The negative association with population size is the most consistent across robustness checks, while the positive associations with urbanization and e-commerce are less stable under lagged or alternative specifications. Spatial-model comparisons provide no evidence of robust residual spatial dependence after observed covariates and province and year fixed effects are controlled for, supporting the more parsimonious TWFE specification. Given the observational design, these estimates should be interpreted as associations rather than causal effects. The findings demonstrate the importance of distinguishing descriptive geographical clustering from residual spatial dependence when assessing the regional development of certified organic agriculture.