Digital Resources, Industrial Structure, and Urban Carbon-Emission Intensity in the Chengdu–Chongqing Region: Measurement, Spatial Associations, and Uncertainty

City-level digital indicators measure the availability of resources whose use in production and energy management may be associated with carbon-emission intensity (CEI).We examine measurement, conditional spatial associations, and estimation uncertainty using 208 observations for 16 prefecture-level statistical units in the Chengdu–Chongqing region during 2011–2023. A five-component Digital-Resource Index (DRI) and a two-component Industrial-Base Index (IBI) were entered into two-way fixed-effects and spatial-lag-of-X models. Confidence intervals and power calculations quantify the precision of the design. Regional real-GDP CEI declined by 53.0% as mean DRI increased by 0.245, but the within-city DRI estimate was imprecise (β = 0.104; 95% confidence interval: −0.053 to 0.261; and wild p = 0.2534). The local IBI changed between real- and nominal-GDP CEI specifications and is treated as exploratory. Positive neighbor-IBI estimates describe conditional geographic associations whose precision declines under boundary and no-fill restrictions. An alternative emissions inventory reproduced regional decline while city intensity rankings differed, and annualized CEI decline slowed across three descriptive stages. With only 16 city clusters, smaller but policy-relevant within-city associations cannot be ruled out. The study clarifies what city indices measure and how denominator choice, spatial definition, and statistical precision shape their interpretation.