Table 12 Channel - Jinshi density effects on contemporaneous innovation.

	(1)	(2)	(3)	(4)
Dependent Variable:	ln (RD per capita+1)	ln (patent application per capita+1)	ln (patent authorization per capita+1)	ln (invention authorization per capita+1)
Panel A: OLS
Jinshi density in Ming-Qing(logged)	0.246*** (0.051)	0.231** (0.085)	0.215** (0.084)	0.332*** (0.084)
R2	0.609	0.835	0.840	0.782
Panel B: 2SLS
Jinshi density in Ming-Qing(logged)	0.306* (0.172)	0.346*** (0.149)	0.319*** (0.118)	0.497*** (0.130)
Observations	243	226	224	223
KP-F statistics	79.835	84.334	83.133	84.784
Cluster	Province	Province	Province	Province
Controls	Yes	Yes	Yes	Yes
Provincial fixed effects	Yes	Yes	Yes	Yes
Industrial fixed effects	Yes	Yes	Yes	Yes

Each Column in each Panel represents a separate cross-sectional regression, with endogeneity issues uncontrolled in Panel A and Panel B. In Column (1), results of the Jinshi density effects on RD per capita are displayed, while effects on the patent application are presented in Column (2). Columns (3) and (4) report estimates on invention authorization per capita and invention authorization per capita, respectively. Covariates include rainfall and air pollution, nightlight in 2004, population density in Ming-Qing, the urbanization rate in Ming-Qing, distance to coast, agricultural sustainability, and terrain ruggedness. All 2SLS regressions are clustered at the province level. These estimated Jinshi density effects can be interpreted as the percentage changes in wages per worker with a percent change in Jinshi density. The KP F-statistic provided in Panel B is the Kleibergen-Paap Wald rk F-statistic for weak identification in the first stage (Kleibergen and Paap, 2006). ***denotes significant at 1% level, **denotes significant at 5% level, * enotes significant at 10% level.

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