Table 5: Estimates of the effect of distance on trade costs

||KE|MG|NG|RW|TZ|GE|
|---|---|---|---|---|---|---|
|_Panel A: All goods_|||||||
|Geodesic distance to origin (log km)|0_._148<sup>_∗∗∗_</sup>|0_._024|0_._052<sup>_∗∗∗_</sup>|0_._024<sup>_∗_</sup>|0_._016<sup>_∗∗∗_</sup>|0_._000|
||(0_._014)|(0_._028)|(0_._007)|(0_._011)|(0_._004)|(0_._029)|
|Adjusted _R_<sup>2</sup>|0_._980|0_._931|0_._849|0_._971|0_._831|0_._990|
|Driving distance to origin (log km)|0_._127<sup>_∗∗∗_</sup>|0_._028|0_._052<sup>_∗∗∗_</sup>|_−_0_._0010|0_._023<sup>_∗∗∗_</sup>|_−_0_._047|
||(0_._013)|(0_._026)|(0_._007)|(0_._009)|(0_._004)|(0_._035)|
|Adjusted _R_<sup>2</sup>|0_._98|0_._931|0_._849|0_._971|0_._832|0_._99|
|Time along best route (log hrs)|0_._134<sup>_∗∗∗_</sup>|0_._048|0_._060<sup>_∗∗∗_</sup>|0_._004|0_._029<sup>_∗∗∗_</sup>|_−_0_._04|
||(0_._013)|(0_._028)|(0_._007)|(0_._010)|(0_._005)|(0_._039)|
|Adjusted _R_<sup>2</sup>|0_._98|0_._931|0_._851|0_._971|0_._831|0_._99|
|Observations|9_,_280|5_,_997|48_,_378|26_,_215|50_,_583|6_,_173|
|_Panel B: Locally-produced goods only_|||||||
|Geodesic distance to origin (log km)|0_._148<sup>_∗∗∗_</sup>|0_._068<sup>_∗_</sup>|0_._041<sup>_∗∗∗_</sup>|0_._120<sup>_∗∗∗_</sup>|0_._028<sup>_∗∗∗_</sup>|0_._084<sup>_∗∗∗_</sup>|
||(0_._014)|(0_._031)|(0_._010)|(0_._015)|(0_._004)|(0_._021)|
|Adjusted _R_<sup>2</sup>|0_._980|0_._915|0_._846|0_._979|0_._825|0_._978|
|Driving distance to origin (log km)|0_._127<sup>_∗∗∗_</sup>|0_._05|0_._043<sup>_∗∗∗_</sup>|0_._100<sup>_∗∗∗_</sup>|0_._031<sup>_∗∗∗_</sup>|0_._133<sup>_∗∗∗_</sup>|
||(0_._013)|(0_._029)|(0_._009)|(0_._012)|(0_._004)|(0_._028)|
|Adjusted _R_<sup>2</sup>|0_._980|0_._915|0_._846|0_._979|0_._825|0_._978|
|Time along best route (log hrs)|0_._134<sup>_∗∗∗_</sup>|0_._056|0_._050<sup>_∗∗∗_</sup>|0_._074<sup>_∗∗∗_</sup>|0_._037<sup>_∗∗∗_</sup>|0_._185<sup>_∗∗∗_</sup>|
||(0_._013)|(0_._032)|(0_._010)|(0_._012)|(0_._005)|(0_._036)|
|Adjusted _R_<sup>2</sup>|0_._980|0_._915|0_._848|0_._979|0_._825|0_._978|
|Observations|9_,_280|5_,_271|43_,_541|9_,_999|36_,_541|3_,_406|
|Destination fxed efects|Yes|Yes|Yes|Yes|Yes|Yes|
|Product-time fxed efects|Yes|Yes|Yes|Yes|Yes|Yes|

_Notes_ : This table presents the effects of distance on intra-national trade costs. All regressions use the adjusted price gap between trading pairs and include product-time and destination fixed effects ˆ multiplied by (1 _− ρod_<sup>_k_)</sup><sup>_/ρ_ˆ</sup><sup>_k_</sup> _od_<sup>.PanelAincludesallgoods,includingimportedgoods.PanelBconsiders</sup> locally produced goods only. Product-time clustered standard errors in parentheses.<sup>_∗∗∗_</sup> significant at 1%,<sup>_∗∗_</sup> at 5%, and<sup>_∗_</sup> at 10%. Source: Authors’ estimates based on national CPI data and distances calculated using Google.

# **5 Discussion of results and robustness checks**

The baseline estimation presented above uses geodesic distance as the main exogenous variable shifting trade costs. However, this measure may mask cross-country differences in the quantity and quality of road infrastructure. For example, if country A has more roads connecting two locations than country B, then the cost-advantage of having more roads would be reflected in a lower coefficient in country A. Figure 1 suggests road infrastructure certainly varies across the countries in our sample. In the same vein, if there are crosscountry differences in road quality, adjusting for the quality of roads should also reduce cross-country differences in our baseline estimates.

Motivated by this, Panel A of Table 5 also includes coefficients when we replace geodesic 17