11 job), which corresponds closely with the rural population reflected in the model, i.e. employed in the informal sector at a lower income (wr).

In 2010, there are 557 town migrants and 315 city migrants, or _Ns/Nc=1.77_ . We subsequently calculate ( �� ~~)~~ and the observed wage gap between working in the formal and informal sector in the �� towns and the city ( ������ ~~)~~ . This provides the necessary information to identify a range of _tc/ts_ ������ combinations that can solve (11). In the towns, 18.9 percent lives in a household that relies on formal wage employment; in the cities, this share rises to 22.2 percent.<sup>20</sup> The _Es/Ec_ ratio thus equals 1.5.<sup>21</sup> Figure 2 overlays the cumulative density functions (cdf) of annual consumption per capita for each of the five incomes of interest (informal rural employment, informal and formal town employment, and informal and formal city employment).<sup>22</sup> For the largest part, the income distributions first order dominate each other in the expected manner, i.e. _wr<wos< woc< ws< wc_ .<sup>23</sup> Note that this is different from the assumptions in the traditional H‐T model, whereby _wo<wr<w_ , underscoring the importance to account for migration costs for the basic H‐T assumption to hold empirically.

Taking median incomes (in ‘000 TSH) of each group yields: _wr_ =372 < _wos_ =613 < _woc_ =871 < _ws_ =1,088 < _wc_ =1,475.<sup>24</sup> The ratio of the town and city income gaps between formal and informal incomes thus equals 0.79,<sup>25</sup> suggesting greater income polarization in cities than in towns, as expected (Ferré, Ferreira, and Lanjouw, 2012).

��������� <u>���������</u> Returning to (11), it can be seen that � needs to equal 1.5, that tc> 499 and ��������� ��������� ts>241 for (11) to hold.<sup>26</sup> Several ( _tc,ts_ ) pairs can be found that meet these conditions. For example, setting tc at 500, or 133 percent of annual rural income per capita, ts must equal, 242, or 66 percent of 20 Contrary to expectations, after about two decades (20 years), the degree of formal employment among city migrants is thus not that much higher than among town migrants. As expected, the share of the formally employed working in the public sector is slightly higher in the towns (21 percent versus 11 percent in the cities), consistent with a relatively greater role of local government and public service provision in formal employment in towns. Nonetheless, in both towns and cities, most of the formally employed work in the private sector (70 and 80 percent respectively).

> 21 _Es,_ the total number of migrants formally employed in towns equals 105 (=0.189*557); _Ec_ , the total number of migrants formally employed in cities equals 70 (=0.222*315), or _Es/Ec=105/70=1.5_ .

22 These are obtained from the KHDS migrants employed in each of these occupations/locations as well as those who stayed in the rural areas. Given the difficulties in obtaining reliable income data in African settings, consumption per capita, spatially deflated and expressed in 2010 Tanzanian shillings (TSH), is taken as a proxy for income. For a detailed description of the data and the consumption variable construction, we refer to De Weerdt et al. (2012).

23 Formal secondary town employment dominates informal city employment over most of the income range, except at the very bottom and top of the income distribution, which may also be linked to measurement errors. 24 A similar gradient is observed when taking average incomes, which are more sensitive to outliers: _wr_ = 495 < _wos_ =765 < _woc_ =1,063 < _ws_ =1,325 < _wc_ =1,605.

> _Ni>0_ ), _wr+tc>woc and wr+ts>wos_ .