**Table 10:** Correlates of city mobility indices, benchmark mobility index

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|log population|-0.18<sup>_a_</sup>|-0.18<sup>_a_</sup>|-0.17<sup>_a_</sup>|-0.17<sup>_a_</sup>|-0.17<sup>_a_</sup>|-0.17<sup>_a_</sup>|-0.17<sup>_a_</sup>|-0.16<sup>_a_</sup>|
||(0.016)|(0.015)|(0.016)|(0.017)|(0.016)|(0.018)|(0.016)|(0.017)|
|log area|0.15<sup>_a_</sup>|0.14<sup>_a_</sup>|0.13<sup>_a_</sup>|0.12<sup>_a_</sup>|0.12<sup>_a_</sup>|0.12<sup>_a_</sup>|0.12<sup>_a_</sup>|0.11<sup>_a_</sup>|
||(0.016)|(0.017)|(0.017)|(0.018)|(0.017)<br>|(0.019)|(0.017)|(0.019)|
|log roads||0.013<sup>_a_</sup>|0.012<sup>_a_</sup>|0.013<sup>_a_</sup>|0.011<sup>_b_</sup>|0.014<sup>_a_</sup>|0.013<sup>_a_</sup>|0.014<sup>_a_</sup>|
|||(0.0043)|(0.0043) <br>|(0.0040) <br>|(0.0044)|(0.0045) <br>|(0.0042) <br>|(0.0042)|
|log income|||0.22<sup>_b_</sup>|0.23<sup>_b_</sup>|0.20<sup>_c_</sup>|0.23<sup>_b_</sup>|0.22<sup>_b_</sup>||
||||(0.10)<br>|(0.10)<br>|(0.11)|(0.11)|(0.10)<br>||
|log<sup>2 </sup>income|||-0.064<sup>_b_</sup>|-0.066<sup>_b_</sup>|-0.055<sup>_c_</sup>|-0.064<sup>_c_</sup>|-0.065<sup>_b_</sup>||
||||(0.031)|(0.031)|(0.033)<br>|(0.034)|(0.032)||
|Network / shape||||0.26<sup>_a_</sup><br>(0.096)|0.11<sup>_b_</sup><br>(0.049)|0.055<sup>_c_</sup><br>(0.029)|||
|Pop. growth 90-10|||||||0.052<sup>_c_</sup><br>(0.030)||
|share w. car||||||||0.21<br>(0.14)<br>|
|share w. motorcycle||||||||0.11<sup>_b_</sup><br>(0.054)|
|Observations|153|153|153|153|153|142|153|152|
|R-squared|0.54|0.56|0.57|0.59|0.58|0.60|0.58|0.59|

_Notes:_ OLS regressions with a constant in all columns. The dependent variable is the city fixed effect estimated in the specification reported in column 5 of table 4. Robust standard errors in parentheses. _a_ , _b_ , _c_ : significant at 1%, 5%, 10%. Log population is constructed from town populations from the 2011 census. Log roads is log kilometers of primary roads within the city-light. Income is measured with male earnings from the 2011 census. The network / shape variable used in column 4 measures the share of edges in the road network that conform to the grid’s main orientation, i.e., whose compass bearing is within 2 degrees of the modulo 90 modal bearing in the network. The network / shape variable in column 5 is a Gini index for the distribution of edge compass bearings in the road network. It also measures how grid-like the city is. The network / shape variable used in column 6 uses Harari’s (2016) measure of the average distance between the centroid of the city and all the points that define its periphery. It measures the compactness of the city. The measure of population growth between 1990 and 2010 was constructed UN data. The share of households with access to a car or to a motorcycle is from the 2011 census.

roads on mobility mostly occurs through uncongested mobility while the effect of primary roads on the congestion factor is a precisely estimated zero. We think these findings reflect two facts. First, primary roads are intrinsically faster than secondary or tertiary roads. Second, the absence of an effect on the congestion factor is consistent with the fundamental law of congestion: more primary roads attract new traffic and eventually leave congestion unchanged (Duranton and Turner, 2011). We return to this issue below.

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