**DRAFT – Not for citation**

people in the currently wealthy coastal prefectures in South-East China that arises when abandoning the Hukou system.

We are aware that all effects we find in this Scenario 2 appear very large (especially so when compared to Scenarios 1 and 1b), but one has to remember that they reflect the (very) long run impact of a relaxation of the Hukou restrictions (see also footnote 36). It would probably take years, if not decades, for these effects to play out. It is also quite important to note that our model abstracts from congestion forces other than rising competitive pressure on wages in the most agglomerated prefectures<sup>42</sup> (although one could argue that some of these congestion forces are to some extent captured by each location’s unobserved amenities, see equation (7), or (8), and the discussion in section 3). We do not explicitly consider pressure on the housing market, pollution issues, nor the often stressed problems with the provision of public services that will most likely emerge with population movements of the scale suggested by our simulations.<sup>43</sup>

# **6. Conclusions**

China’s urban population share is expected to rise to about 75 percent by the middle of this century. By then, more than a billion people will live in Chinese cities. Investments in connective infrastructure and migration policies have the potential to significantly shape the speed and pattern of this massive urbanization process. A better understanding of the impacts of these policies will help to achieve the greatest social and economic benefits in each and every part of China.

This paper compares the spatially differentiated impacts of the construction of China’s national expressway network (NEN) with those from relaxing its long-standing Hukou restrictions on migration. To do this we develop a structural new economic geography model that, importantly, can be empirically implemented using readily available data on the urban and rural parts of 331 Chinese prefectures. We fit our model to the data, and simulate counterfactual scenarios that allow us to compare each policy’s respective impact on regional economic development and urbanization patterns across China.

> 42 Our model also does not incorporate remittances. All wages earned in a particular location are spent there (either on local products, or products imported from other parts of China or from elsewhere).

> 43 We could extend our model to incorporate one or more of these issues. But it is important to note that in order to be able to also implement such an extension empirically, requires detailed information on (each of the) congestion forces in each of the locations that we consider; and to have an idea on how they depend on a location’s population size. Bosker _et al._ (2012) for example do this by exogenously fixing each location’s housing stock. This poses a strong additional congestion force, as rental prices go up when more people migrate to a location. This can be viewed as more or less the polar opposite of our model that implicitly assumes that a location’s housing stock perfectly adapts to changes in population (so that these changes leave no effect on the cost of living other than through their effect on the consumer price index). Reality lies in between these two polar cases: cities do respond to population changes by building additional housing units (in fact in some cities in China house prices have fallen despite a growing population as a result of overconstruction).

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