Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Understanding the convergence of energy intensity helps in assessing whether policies targeted at reducing energy intensity are effective and should thus be continued or reinforced. This paper analyzes the convergence of cross-province energy intensity in China based on panel data of 29 provinces for the period 2003–2015 by means of sigma convergence, kernel density analysis, and unconditional and conditional beta convergence. The empirical results show that the omission of spatial spillovers underestimates conditional beta convergence. We thus argue that the implementation of effective policy for reducing energy intensity depends not only on the driving forces in the own province but also on the spatial spillover effects in neighboring provinces, particularly technology transfer, knowledge spillovers, and the input-output relationship. From the analysis, it follows that adopting low-energy capital, attracting more FDI inflows and developing indigenous innovation capabilities are major policy handles.