The heterogeneous treatment effect of low-carbon city pilot policy on stock return: A generalized random forests approach

Abstract

To achieve sustainable development, China has launched the low-carbon city pilot (LCCP) program in 2010. However, the impact of this policy on firm performance has not been well investigated. By the cutting-edge generalized random forests (GRF) method, this paper takes LCCP as a quasi-natural experiment and analyzes its heterogeneous treatment effect on the stock return of Chinese firms. It is found that LCCP has a significantly negative effect on stock return and the market reacts in advance. The effect is heterogeneous and nonlinearly decided by firm features. Specifically, firms with lower financial leverage, greater profitability and longer listing years suffer more decrease in stock return. Best linear predictor test suggests that the GRF method provides satisfying estimate of the true heterogeneous treatment effect.