In this paper, a vector autoregression (VAR) model has been constructed in order to analyze a two-way mechanism between PM2.5 pollution and industry development in Beijing via the combination of an impulse response function and variance decomposition. According to the results, long-term equilibrium interconnection was found between PM2.5 pollution and the development of primary, secondary, and tertiary industries. One-way Granger causalities were found in the three types of industries shown to contribute to PM2.5 pollution, though the three industries showed different scales of influences on the PM2.5 pollution that varied for about 1⁻2 years. The development of the primary and secondary industries increased the emission of PM2.5, but the tertiary industry had an inhibitory effect. In addition, PM2.5 pollution had a certain inhibitory effect on the development of the primary and secondary industries, but the inhibition of the tertiary industry was not significant. Therefore, the development of the tertiary industry can contribute the most to the reduction of PM2.5 pollution. Based on these findings, policy-making recommendations can be proposed regarding upcoming pollution prevention strategies.
Keywords: haze pollution; impulse response function; industry development; variance decomposition; vector autoregression model.