registration.<sup>22</sup> Other costs of migration facing rural households include the risk of losing one’s (administratively allocated) land allocation at the origin and various forms of discrimination against rural migrants in urban areas. A rough estimate of the magnitude of these policy-induced costs of migration is provided by Shi et al., (2004) who report that even after controlling for worker characteristics and cost-of-living differences provide, urban wages are about 50 percent higher. The high costs of migration underlying these gaps have probably been both poverty and inequality increasing. There are also similar restrictions on within-rural and within-urban migration.

Sizeable aggregate output losses from these inequality-increasing restrictions on migration are likely. Not only is labor mis-allocated across sectors, but the restrictions make it harder for China to realize agglomeration economies (Au and Henderson, 2006). Under the (plausible) assumption that these costs of migration lower earnings in the poorer (labor-surplus) sector, they will increase poverty and inequality. Other policy biases against the poor have included public spending and industrial policies that have favored China’s coastal areas over the (poorer) inland regions.

In both countries, an important area of policy neglect has been service delivery. The deficiencies of India’s education system (and not just from the point of view of the poor) are well known (Drèze and Sen, 1995; PROBE, 1999). Issues of service quality loom large in these concerns (World Bank, 2006). While starting from greater equity in service delivery (though even then with large gaps between urban and rural areas) China has also seen growing inequalities in access to health and education (Zhang and Kanbur, 2005). The weaknesses and inter-regional disparities in service delivery in both countries can be traced, at least in part, to the large and rising disparities in public spending per capita between rich and poor areas, with rather weak fiscal redistribution and (hence) heavy dependence of local governments on local resources. We return to this point when we discuss policies.

# **Dynamics: Good inequalities can turn into bad ones**

Without the appropriate institutional checks and balances, rising inequality, even if it is initially of the “good” variety, can engender phenomena such as corruption, crony capitalism, rent-seeking or efforts by those who benefit initially from the new opportunities to restrict access of others to those opportunities or alter the rules of the game so as to preserve their initial advantages.<sup>23</sup> Thus bad inequalities emerge over time.

The growth and subsequent performance of China’s township and village enterprises (TVEs) provides an example of this dynamic at work. The emergence and growth of TVEs in various parts of China starting in the mid-1980s is often cited as a successful example of the country’s strategy of incremental institutional innovation—in this case, economic

> 22 In spite of this, China has still had a more rapid rate of urbanization than has India. China’s urban population share rose from 19 percent in 1980 to 39 percent in 2002. In India (with no such restrictions) the urban share of the population rose from 23 percent to 28 percent over the same period.

> 23 Antecedents to this argument can be found in the writings of North (1990) and Hellman (1998).

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