_U U_ 2 2 _wi_  _c_  _GDP_ PWi_  _LONGi_  _LATi_  ( _LONGi_ )  ( _LATi_ )  ( _LONGi_  _LATi_ )  _i_ [A1] for the 317 non-missing observations, where _GDP_PWi_ denotes the GDP per worker of prefecture _i_ , _LONGi_ its longitude and _LATi_ its latitude. The longitude and latitude for a prefecture both refer to its geographic center. The estimated regression has _R_<sup>_2_</sup> = 0.70.

**Rural wage rate (** **_w_**<sup>**_R_**</sup> **):** proxied by average net income per capita for rural households.  The net income of a rural household is its total income from all sources minus all corresponding expenses.  Expenses in this context consist of household operation expenses, taxes and fees, an allowance for depreciation of fixed assets used in rural production, and gifts made to nonrural residents.   The income subsidy received for survey participation is also subtracted. **Source:** _Regional Economic Statistical Yearbook 2008_ .

Data is missing for one prefecture on this variable. The value of the missing observation has been filled-in using the predicted value generated from OLS estimation of an equation analogous to equation [A1] for _w_<sup>_R_</sup> for the 330 non-missing observations ( _R_<sup>_2_</sup> = 0.73).

**Income (** **_Y_ ):** in constructing the measures of real market access for the urban and rural sectors ( _RMA_<sup>_U_</sup> and _RMA_<sup>_R_</sup> respectively), a measure of income is required. The measure used is GDP. **Data source:** _Regional Economic Statistical Yearbook 2008_ ,

**Investment per worker** **_(I pw_ ):** measured separately for the urban and rural sectors as fixed investment per worker. **Data source:** _Regional Economic Statistical Yearbook 2008_ .

**Human capital (** **_human_ ):** for both the urban and rural sectors, proxied by the average number of years of education held by a prefecture's population in 2000. **Data source:** _China 2000 Population Census Data Assembly_ .

The spatial lags of ln( _I pw_ ) and ln( _human_ ), i.e. **W** *ln( _I pw_ ) and **W** *ln( _human_ ), which also enter into the estimation of the urban and rural wage equations as control variables, are constructed through pre-multiplying the column vectors of observations on ln( _I pw_ ) and ln( _human_ ) by the spatial weights matrix, **W** . The _i_ - _j_ th element of this matrix, _wij_ , equals 1 if regions _i_ and _j_ share a contiguity relationship; otherwise, _wij_ = 0. Contiguity is inferred from the geographic co-ordinates of the centers of the prefectures using a Delaunay trianglarization scheme. To implement this scheme, we use the xy2cont _MatLab_ function from James LeSage's spatial econometrics toolbox (downloadable from www.spatial-econometrics.com). The **W** matrix is row-standardized so that the elements on the _i_ th row sum to unity.

_Instrumental variables_ In estimating the urban and rural wage equations, equations [10] and [11], using 2SLS and the FGS2SLS estimator, the following instruments are used for, the (natural) logarithms of, domestic urban and rural real market access:

**Urban:** ln[  {1/[ _area j_ 1(  _d ij_ )]}] **, W** * **W** * ln( _I pw_ ) _j_

**Rural: W** * **W** *ln( _I pw_ ), **W** * **W** *ln( _human_ ), ln(1  _d iport_ .045 )

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