but one has to keep in mind that population growth is only partly driven by migration.<sup>31</sup> Combined with our earlier “migrants-results” in Table 1a (as well as the extensions in Table A1), and the survey and provincial evidence in earlier studies (Poncet, 2006; Rozelle et al., 1999; and Zhao, 1999a,b), all our evidence supports the idea that real wages are indeed a very important driver of migration decisions in present day China.<sup>32</sup> In the counterfactual scenarios that allow for labor mobility, we always use the results shown in Table 1a, column 3, as shaping people’s migration decisions. We do not only use the estimated parameters of (7), but also the corresponding estimates of the unobserved amenities in each prefecture’s urban and rural parts (the sum of each location’s residual and its urban-rural/province fixed effect).

# **5. The spatial impacts of the construction of the NEN and the Hukou system**

With all the structural model parameters in hand, we are now in a position to assess the impact of the NEN and/or Hukou restrictions on China’s spatial economy. We do this by simulating our full structural NEG model under three different scenarios. We discuss in detail how we generate the counterfactual spatial equilibria that each of these scenarios rely on. In all three scenarios our analysis focuses on the distribution of four main variables across China’s prefectures: real income per worker, the urban-rural real wage gap, urbanization rates, and overall population.<sup>33</sup> For sake of comparison, we also sometimes report the Roberts _et al._ (2012) results that consider the impact of the NEN under an extreme Hukou scenario (i.e. no labor mobility), and/or compare our “no Hukou”-findings to those found by Bosker _et al._ (2012).

# _5.1 Simulating the impact of the NEN and/or Hukou system_

We observe the current 2007 distribution of people, urbanization and real incomes across the urban

> 31 On average, only about 40% of Chinese city growth is driven by migration.  Another 40% is driven by urban expansion into rural areas, leaving 20% as being determined by natural population growth [World Bank and DRC, 2014].

> 32 From the perspective of our later simulation exercises, the coefficient on real wages in these regressions is most important. In our setup, the (construction of the) NEN affects people’s location decision solely through its effect on real wages in the rural and urban part of each prefecture. We are aware that our main results regarding the importance of real wages in people’s migration decision might still be plagued by reverse causality or omitted variable bias. We lack a convincing source of exogenous variation to deal with this issue. But, in light of all findings in our robustness checks as well as in earlier papers that have shown the importance of wage/income considerations when deciding to migrate or not, we find it very unlikely that addressing these endogeneity concerns will entirely undo the positive effect of real wages that we identify in our regressions. It could result in a smaller positive effect however. Our results in section 5 are qualitatively robust to assigning a smaller role for wages in people’s migration decision.

> 33 Our simulations also allow us to look at nominal incomes, price levels, etc. in the urban and rural part of each prefecture. Results are available upon request.

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