Uber operates and regressed the growth measure on these characteristics. Results are summarized in Table 2. Column 1 provides estimates for the full sample of 97 cities, and columns 2-4 restrict the sample to 80 cities for which we have information on the number of taxi licneses, In all of the estimated models, the number of Uber drivers per month in operation rises with city population, and we cannot reject a unit elasticity. Cities with more taxi licenses per capita have added relatively more Uber drivers, suggesting that there is excess demand for ride-sharing services in cities with relatively more taxis, all else equal. Interestingly, the cost of a five-mile Uber ride has a statistically insignificant and small coefficient. The unemployment rate in a city is also unrelated to the growth in the number of Uber drivers, consistent with the observation made in light of Figure 1 that the exponential growth of Uber drivers held in periods of high- and low-unemployment. Real GDP and population density in a metropolitan area are both found to be unrelated to the number of Uber drivers. Lastly, cities where Uber started earlier have added significantly more drivers per month than cities where Uber started later, suggesting that Uber was strategic in launching earlier in cities with greater latent demand for ride-sharing services. Table 2: Determinants of Growth of Uber Driver-Partners Across Cities Dependent variable: Log of Average Active Monthly Driver-Partners in 2015Q4 Per Number of Months Operating (1) (2) (3) (4) Months Operating 0.045*** 0.041*** 0.041*** 0.042*** (0.008) (0.008) (0.007) (0.007) Log of MSA Pop. (2010) 1.097*** 1.098*** 0.876*** 0.895*** (0.325) (0.327) (0.313) (0.315) Log of MSA Density (2010) 0.122 0.132 0.012 0.022 (0.090) (0.100) (0.100) (0.101) Log of MSA Real GDP -0.267 -0.201 -0.028 -0.048 (2013) (0.293) (0.298) (0.282) (0.285) Log of MSA Median Taxi 0.386 -0.056 -0.039 -0.093 Earnings (2015) (0.606) (0.628) (0.590) (0.598) Annual Unemployment -0.061 -0.059 -0.035 -0.039 (2014) 16