Closing the SME Emissions Data Gap

Purpose: This paper develops a scalable method, called tilt, and an associated dataset to estimategreenhouse gas emissions and emission reduction potentials of small and medium-sized enterprises(SMEs). Thereby, we close the SME emission data gap.Design/methodology/approach: We estimate firm-level emissions by matching firms’ productinformation to product-level emission factors and aggregating them using simulated revenue shares.We apply the method to a sample of 7,885 German SMEs.Findings: tilt produces granular estimates that capture within-sector heterogeneity omitted bysectoral averages. Benchmarking against a sector-based model and large firms’ reported emissionsshows strong correlations, with tilt yielding more conservative estimates on average. Differences areinherent to methodological choices. We further identify high-emitting SME sectors and emission-intensive firms with high reduction potential.Research limitations/implications: We achieve representativeness through stratified sampling andpost-stratification weighting. The data enable research on SME decarbonisation pathways, regionalanalyses of sectoral emission hotspots, and linkages to financial datasets. The method is applicablebeyond Germany in other countries. Model uncertainty is documented transparently.Practical implications: The data help banks address asymmetric information in SME climaterisk assessment and enable SMEs to conduct emissions analysis and supply-chain disclosure usinginterpretable, product-based estimates.Social implications: Moving beyond sector averages, the dataset supports more targeted climatepolicy, financial regulation, and empirical evaluation of SME decarbonisation pathways.Originality/value: To the best of our knowledge, this paper introduces the first scalable methodand dataset for estimating product-based emissions and reduction potentials for SMEs.