Does Artificial Intelligence Reduce Urban Carbon Emission Intensity? Evidence from 272 Chinese Cities with Spatial and Threshold Perspectives

This repository provides a comprehensive dataset and supporting materials for analyzing the relationship between artificial intelligence, carbon emissions, and sustainable urban development in China. The collection covers 272 cities from 2006 to 2022 and is organized to ensure transparency, replicability, and flexibility for further research.Contents:Full panel dataset: Balanced panel data covering economic, technological, and environmental dimensions across cities and years.Code package: Stata code files to replicate the empirical analysis, including data cleaning, model estimation, and robustness checks.Data formats: The dataset is available in Stata (.dta) format for direct use, with supporting documentation for ease of application.Spatial weight matrices: Files constructed to support spatial econometric models, enabling the analysis of spatial dependence and spillover effects.Data processing: All sources were harmonized, standardized, and deflated to constant prices for temporal comparability. Outlier treatments and spatial structure construction were applied to improve robustness and enable advanced econometric modeling.Applications: The dataset and code can be used for econometric, mediation, moderation, and spatial analyses, as well as extended to broader studies on urban low-carbon transition, technological innovation, and policy evaluation. It is designed to be both reproducible and adaptable for future research.This integrated dataset provides a valuable resource for scholars and policymakers interested in climate change mitigation, digital transformation, and sustainable development in urban China.