Table 5: Estimation of (5) by distance and by incremental change in the cdf.

||**Mo**|**del (7), by dist**|**ance**||**Model (7), by**|**incremental**c|df|
|---|---|---|---|---|---|---|---|
|Variables|cdf 10km|cdf 100km|cdf 500km|_∆γi_(10, 25)|_∆γi_(25, 50)|_∆γi_(50, 100)|_∆γi_(100, 500)|
|Ad valorem trucking costs (residual)|-0.269<sup>_a_</sup><br>(0.080)|-0.250<sup>_a_</sup><br>(0.073)|-0.212<sup>_a_</sup><br>(0.048)|-0.253<sup>_a_</sup><br>(0.079)|-0.238<sup>_a_</sup><br>(0.080)|-0.229<sup>_a_</sup><br>(0.069)|-0.105<br>(0.090)|
|Asian share of imports|-1.359<sup>_a_</sup>|-0.923<sup>_a_</sup>|-0.307<sup>_b_</sup>|-1.029<sup>_b_</sup>|-0.724<sup>_b_</sup>|-0.352|0.583|
||(0.467)|(0.299)|(0.139)|(0.433)|(0.337)|(0.235)|(0.429)|
|Input distance|-0.382<sup>_a_</sup>|-0.340<sup>_a_</sup>|-0.242<sup>_a_</sup>|-0.332<sup>_a_</sup>|-0.322<sup>_a_</sup>|-0.315<sup>_a_</sup>|-0.193<sup>_a_</sup>|
||(0.063)|(0.049)|(0.033)|(0.061)|(0.055)|(0.054)|(0.041)|
|Output distance|-0.307<sup>_a_</sup>|-0.307<sup>_a_</sup>|-0.197<sup>_a_</sup>|-0.341<sup>_a_</sup>|-0.340<sup>_a_</sup>|-0.302<sup>_a_</sup>|-0.122<sup>_a_</sup>|
||(0.046)|(0.040)|(0.027)|(0.045)|(0.045)|(0.045)|(0.039)|
|Average minimum distance|-0.322<sup>_a_</sup>|-0.268<sup>_a_</sup>|-0.137<sup>_a_</sup>|-0.298<sup>_a_</sup>|-0.243<sup>_a_</sup>|-0.204<sup>_a_</sup>|-0.038|
||(0.046)|(0.035)|(0.024)|(0.041)|(0.043)|(0.038)|(0.036)|
|Other trade shares included|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Industry controls included|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Industry dummies|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year dummies|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|_R_<sup>2</sup>|0.473|0.540|0.545|0.481|0.417|0.436|0.168|

_Notes:_ All estimations for 257 industries and 17 years (4,369 observations). The dependent variable is the unweighted (count based) DurantonOverman _K_ -density cdf at the reported distance.<sup>_a_</sup> ,<sup>_b_</sup> and<sup>_c_</sup> denote coefficients significant at the 1%, 5% and 10% levels, respectively. We use simple ols. All specifications include industry and year fixed effects. Standard errors, given in parentheses, are clustered at the industry level. Our measures of input and output distances are computed using _N_ = 5. ‘Ad valorem trucking costs (residual)’ denotes the residual of the regression of ‘Ad valorem trucking costs’ on industry multi-factor productivity. A constant term is included in all regressions but not reported. All industry controls (Total industry employment; Firm Herfindahl index (employment based); Mean plant size; Share of plants affiliated with multiplant firms; Share of plants controlled by foreign firms; Natural resource share of inputs; Energy share of inputs; Share of hours worked by all workers with post-secondary education; In-house R&D share of sales) are included but not reported. All trade share variables are included in the regressions, but we do not report detailed results to save space.

kilometers. Note also that the standard errors start to increase more quickly after about 110 to 120 kilometers, i.e., the estimated coefficients on transport costs become less precise.

# **. Robustness checks 5 3**

We now provide additional evidence on the robustness of our key findings. First, we investigate the robustness of our results to the choice of the dependent variable. Table 13 in the Supplementary Appendix S.4 shows that the effect of transport costs on geographic concentration is weaker – and the of the model lower – when the latter explanatory power slightly is measured using either employment- or sales-weighted cdfs. Although the key qualitative flavor of the results and the sign and significance of our key coefficient remain unchanged, the estimates using employment- or sales-weighted _K_ -densities are slightly less sharp. Furthermore, the effect of import competition tends to be more limited to imports from Asia, and the coefficient tends to be smaller too. This suggests that much of the adaptation to import competition, particularly from low-wage countries which are responsible for the bulk of exit in Canadian manufacturing, occurs for smaller plants and firms (Behrens _et al._ , 2016). The residual transport cost variable remains significantly negative in all specifications that we estimate, irrespective of how we construct the dependent variable. In a nutshell, changes in transport 21