had stronger incentives to develop manufacturing and commerce (i.e., the new tax base). This would have raised _de facto_ power to the capitalists there (Acemoglu et al. 2005). Moreover, because the Capital-Close areas had higher urbanization rates after the war (Li and Ma 2016), the capitalists there would have been more closely congregated. They would have been more politically powerful as a group and should have found it easier to overcome the collective action problem and to organize to advocate for favorable policies for themselves. Due to the complementarity between technology (or physical capital) and human capital, the capitalists would then have demanded more public schooling (Galor et al. 2009), and they were likely to have succeeded due to their expected relative ease in overcoming the collective action problem. The rise in initial fiscal capacity thus would have made more post-war school financing feasible. Thus, more schools would have been built in Capital-Close areas, and schooling attainment should have been higher.

_The institution-induced skill-demand hypothesis_ . The increase in initial _Likin_ revenue would raise schooling in Capital-Close regions to a larger extent than elsewhere.

# **III. Data and Measurement**

Our main data consist of 266 of the 317 prefectures in the Qing Dynasty in 1820 in China.<sup>25</sup> Of the sample, 147 prefectures had never been occupied by the Taiping Army, 55 prefectures had been under the Taiping jurisdiction, and 64 prefectures had been occupied by the Taiping Army but were not in the Taiping rulers’ jurisdiction (“Occupied”) (see Appendix B). Inside the Taiping jurisdiction group, 37 prefectures had ambiguous land property rights policies associated with the early Taiping controlled areas (Early Taiping hereafter), and 18 prefectures adopted the stronger land property rights policies in the late TP areas (Late Taiping hereafter).<sup>26</sup> _Economic Development_ **.** Our first measure of development is population density,<sup>27</sup> and we choose it for three reasons. First, the population data are the only well-recorded data for measuring long-term prosperity coving the sample period for China. Other proxies, such as historical urbanization are either unavailable or have significant measurement issues, which render them poor candidates for our analysis.<sup>28</sup> Second, studies of the consequences of

> 25 Since the literature suggests that shared state antiquity strongly affects long-term development (Bockstette et al. 2002), we exclude prefectures with significantly lower shares of state antiquity, which include those in minority areas of China that were underdeveloped and less populated before 1953: Xinjiang, Tibet, Qinghai, and the north of the Great Wall (Inner Mongolia, Outer Mongolia); we similarly exclude three provinces in Northeast China (Fengtian, Jilin, and Heilongjiang).

> 26 Where it is obvious, we sometimes shorten them to be Early and Late.

> 27 In the regression, we use total population in the prefecture, but we control for the prefecture fixed effects. So, in essence, we are using the population density as the dependent variable.

> 28 Urbanization measurements have only been recorded since the late nineteenth century. Skinner (1977) estimates the population in the core area of cities or towns of China in 1893; similar estimates in the 1920s can be found in

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