Side issues of economy development break out in China during recent decades, like environmental pollution or the widely ignored one, shadow economy. Using annual data for the three provinces at northeast China over the period 2000 to 2016, this paper examines the size of the shadow economy by MIMIC model first and then adopts the dynamic panel analysis to study the direct relationship between the shadow economy and pollution level. The major innovation point of this paper is the pioneering study of the impact from the pollution level on the size of shadow economy. We also employ various pollution descriptions from terrestrial, aquatic, and atmospheric ecosystems as the robustness check to make our following conclusions more comprehensive and credible: (1) shadow economy is a direct quality factor to the increase of the pollution level. (2) A positive effect from pollution to shadow economy also exists: the higher the pollution level is, the larger the size of shadow economy will be. In the end, this paper proposes several valuable information and suggestions to the government in economy development and pollution abatement.
Keywords: Dynamic panel analysis; GMM method; MIMIC method; Pollution; Shadow economy.