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This study examines whether and how government fiscal pressure influences corporate charitable giving (CCG).

The authors exploit sub-national tax revenue sharing changes as exogenous variations to government’s fiscal pressure at the city level and then construct a quasi difference-in-differences (DiD) model to conduct the analysis based on a sample that consists of 14,168 firm-year observations in China during the period of 2003 to 2012.

The authors found that firms increase charitable donations when local governments face higher fiscal pressure. Such effects are more pronounced for firms that have stronger demand for political connectedness in the sample period. Furthermore, this study’s findings suggest that the timing strategy of donating helps firms to lower the effective tax rate and to build stronger political connections. In addition, donating firms outperform non-donating firms in terms of bank loan access and market reputation.

The authors contribute to at least three lines of literature: first, extend the understanding of timing strategies of corporate charitable behaviors; second, contribute to the literature studying the “crowd out” effect between government-provided charitable funds and private donations; finally, contribute to the emerging literature exploring the financial interests associated with corporate donation strategy (Claessens et al., 2008; Cull et al., 2015).

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.