Research on the relationship between urban public infrastructure, CO2 emission and economic growth in China

The main purpose of this study is to analyze the relationship between urban public infrastructure, CO2 emissions and economic growth in China for the period 1990-2019 using the Dynamic Conditional Correlation Multivariate GARCH model (DCC-MGARCH) and Autoregressive Distributed Lagged Model (ARDL). According to the estimated results of the DCC-MGARCH, there is a positive influential effect among the economic growth, urban public infrastructure and CO2 emissions, while there is a negative influential effect between the urban public infrastructure and CO2 emissions, but the duration of volatility between the urban public infrastructure and CO2 emissions is relatively weak. Among such relationships, the conditional correlation also shows there is an effect in S-shape between the urban public infrastructure and economic growth, but the trend variation between the urban public infrastructure and CO2 emissions shows an inverted U-shape of Environmental Kuznets Curve Theory. The results of the ARDL-Bounds test show that there are long-term co-integration relationships and short-term dynamic correlation among all models. Also, the results of error correction terms show that the speed deviating economic growth and CO2 emissions from the long-term equilibrium and CO2 emissions deviating from the long-term equilibrium is larger than that of the urban public infrastructure, which indicates that the relationship between the economic growth and CO2 emissions is relatively strong.

Automated summary

The study reveals complex interrelationships among urban public infrastructure, CO2 emissions, and economic growth in China, with relatively weak volatility between these factors. Long-term co-integration relationships and short-term dynamic correlations exist, indicating a relatively strong relationship between economic growth and CO2 emissions.