Boris D. Klyukin

This article examines the reliability of official GDP statistics in India and China, two key but statistically opaque economies. While skepticism about the data in both countries is widespread, the author argues that the reasons for this are fundamentally different. In India, mistrust stems from the technical and methodological deterioration of the statistical apparatus—an institutional erosion that compromises data quality, although this deterioration is itself closely linked to political pressure to present favorable growth scenarios. In China, doubts are rooted in systemic political incentives that structurally encourage data manipulation at multiple administrative levels, generating systemic distortions rather than simply technical errors. Both countries have acknowledged these reliability gaps and initiated reforms. Meanwhile, researchers need to adhere to transparent working methods, clearly stating data limitations, using conditional language, and describing data specifications. A comprehensive analysis requires cross-checking official data with alternative metrics such as electricity production, rail freight, purchasing managers’ indices, and corporate financial reports. According to the author, the statistical opacity of India and China opens up new opportunities for research at the intersection of social science, data science, and econometrics. This future endeavour primarily involves compiling lists of the most optimal alternative data and developing methodologies for processing them using tools such as computer vision and natural language processing to peer beyond the veil of politicized data.