Note(s): Table 4 presents the results of the cross-sectional analysis, including cross-sectional analysis for government quality, industry competition, the proportion of state-owned shareholdings, and the age of board chairmen. Columns (1) and (2) show the influence of local governments' quality; Gov_quality = 1 (Gov_quality = 0) means higher (lower) quality. Columns (3) and (4) show the influence of industry competition; Mono = 1 (Mono = 0) means monopolistic (competitive) firms. Columns (5) and (6) show the influence of the proportion of state-owned shareholdings; Mshare = 1 (Mshare = 0) means a higher (lower) proportion of state-owned shareholdings. Columns (7) and (8) show the influence of the age of board chairmen; Hage = 1 (Hage = 0) means older (younger) board chairmen. The dependent variables are innovation measured by the natural logarithm of 1 plus the number of invention patent applications in year t+1 (Innovation_t+1). The key independent variable is the establishment of local SASACs (GZW). We report in parentheses t-statistics based on standard errors that are robust to heteroskedasticity. ***p < 0.01; **p < 0.05; *p < 0.10; two-tailed test. See Appendix A for variable definitions