Table 16 Jinshi density effects on fringe benefits (Public Service and Facilities).

	(1)	(2)	(3)	(4)	(5)	(6)
Dependent Variable:	ln (Hospital+1)	ln (doctor density+1)	ln (cinema density+1)	ln (road density+1)	ln (bus density+1)	ln (book density+1)
Panel A: OLS
Jinshi density in Ming-Qing(logged)	0.110 (0.070)	0.130*** (0.034)	0.006 (0.005)	0.264*** (0.091)	0.330** (0.127)	0.400*** (0.079)
R2	0.406	0.672	0.336	0.746	0.676	0.668
Panel B: 2SLS
Jinshi density in Ming-Qing(logged)	0.290* (0.150)	0.163* (0.085)	0.021* (0.012)	0.303* (0.183)	0.524* (0.282)	0.493*** (0.110)
Observations	243	243	243	243	243	243
KP-F statistics	98.969	98.969	98.969	98.969	102.030	98.969
Cluster	Province	Province	Province	Province	Province	Province
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Provincial fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
Industrial fixed effects	Yes	Yes	Yes	Yes	Yes	Yes

Each column in each Panel represents a separate cross-sectional regression, with the endogeneity issue uncorrected in Panel A and corrected in Panel B. In Columns (1) - (6), we provide estimates of Jinshi’s effects on hospital density, doctor density, cinema density, road density, bus density, and book density, 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 OLS regressions are clustered at the firm 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, *denotes significant at 10% level.

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