The Impact of Tax Policy on Economic Growth from Aggregate and Structural Tax Perspective in China: A LT-TVP-FAVAR Approach

This study proposes a new latent threshold time-varying parameters factor-augmented vector autoregressive (LT-TVP-FAVAR) model and then explore the dynamic impact of Chinese tax policy on economic growth from the dual perspective of total tax revenue and tax structure. The proposed LT-TVP-FAVAR model can both model parameter changes and avoid overparameterization such that it can capture economic dynamics better. We propose a two-step estimation method (including a Markov chain Monte Carlo algorithm) to estimate the LT-TVP-FAVAR model. Extensive point forecasts present evidence for the LT-TVP-FAVAR model’s strength. The main empirical conclusions are: (1) increasing total tax revenue has a negative impact on economic growth, but this has weakened since China entered the economic new normal period; (2) From the perspective of tax structure, increases in both commodity tax and income tax primarily exert a positive effect on economic growth, while increases in the other tax have a negative effect on economic growth. Additionally, the positive effect of increasing commodity taxes on economic growth has obviously weakened since China entered the economic new normal period, whereas the positive effect of income tax on economic growth sharply increased after the outbreak of the COVID-19 pandemic. The inhibitory effect of increases in the other tax on economic growth during the economic new normal and COVID-19 pandemic periods is stronger than during the financial crisis and economic recovery periods.