Fig. 5: The results of robustness test.
From: A new model for residential location choice using residential trajectory data
Graphs (a, b) depict the percentage change in coefficient and goodness of fit with the inclusion of amenity variables in Shenzhen and Beijing, respectively. The vertical axis indicates the percentage change of the coefficient of HBNC time/coefficient of commuting time/goodness of fit of the regression model. On the horizontal axis, reg_1 is the baseline regression, and reg_2 to reg_7 represent regressions that gradually add the variables of subway, bus station, hospital, retail market, park and school. Graphs (c−f) show the relative importance of commuting time and HBNC time in determining residential locations on diverse spatial scales (tiles of 250 m × 250 m, 500 m × 500 m, 1000 m × 1000 m, and 2000 m × 2000 m, respectively). To ensure the reliability of the results, we choose the maximum value of the coefficients of commuting and HBNC time at the 5% confidence level.
