Toward synergy in Mozambique’s agricultural production statistics: Complementarity between integrated agricultural survey and statistics from space approach

Agricultural production data plays a critical role in economic development, especially for developing countries like Mozambique, as it informs more effective policymaking on agricultural investments, subsidies, and initiatives at local, national, and regional levels. Currently the Integrated Agricultural Survey (“Inquérito Agrário Integrado” - IAI) serves as the official source of agricultural information in Mozambique. It collects various types of data at farmers level, including estimates of crop cultivated areas, which is based on farmers self-reporting and the measurement of two farmers’ plot sizes in each enumeration area (EA). Although IAI employs rigorous methodologies, the accuracy of cultivated area estimates may be limited due to low literacy levels among farmers and the prevalence of intercropping production systems, which complicate the determination of the area occupied by each crop. In recent years, digital technologies and satellite remote-sensing methodologies have emerged as promising tools for estimating crop areas with greater precision and timeliness. In this paper, we advocate for the application of such methodologies – referred to here as “Statistic from Space (SFS)” – for crop area estimation. We use two data sources: IAI 2023, representing official government data collected by the Ministry of Agriculture in collaboration with the National Institute of Statistic (INE); and SFS data collected in 2025 under the “Statistics from Space” project. We conduct a simulation study using both sources of data and evaluate the performance of each approach using statistical metrics such as the range of confidence interval, margin of error, and the asymptotic relative efficiency of the SFS approach compared to its counterpart, the IAI. The results indicate that the SFS proposed in this paper outperforms the IAI across all performance measures. These findings suggest substantial complementarity and synergy between the SFS approach and IAI methodologies. We conclude that integrating the SFS approach into the planning and implementation of the IAI could significantly enhance the precision of the crop area estimates in Mozambique.