**Table S21:** Association of changes in market access on changes in outcome variables using a long difference. _θ_ = 5, using a 50km doughnut IV

||NT|L|Urb|an|Crop|land|NT|L|U|rban|Cro|pland|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|MA|_−_0_._06<sup>_∗∗∗_</sup>|_−_0_._08<sup>_∗∗∗_</sup>|0_._01<sup>_∗∗_</sup>|0_._01<sup>_∗_</sup>|0_._002|0_._001|_−_0_._08|_−_0_._11|0_._03|0_._01|_−_0_._001|_−_0_._004|
||(0_._02)|(0_._02)|(0_._01)|(0_._004)|(0_._01)|(0_._01)|(0_._07)|(0_._07)|(0_._04)|(0_._05)|(0_._02)|(0_._02)|
|MA_×NTL_96 Low||0_._07<sup>_∗∗_</sup>||_−_0_._01<sup>_∗∗_</sup>||0_._003||0_._19<sup>_∗∗∗_</sup>||0_._05<sup>_∗_</sup>||0_._01|
|||(0_._03)||(0_._01)||(0_._01)||(0_._06)||(0_._03)||(0_._01)|
|MA_×NTL_96 Med||0_._13<sup>_∗∗∗_</sup>||_−_0_._004||0_._003||0_._32<sup>_∗∗∗_</sup>||0_._18<sup>_∗∗∗_</sup>||0_._02<sup>_∗_</sup>|
|||(0_._03)||(0_._01)||(0_._01)||(0_._08)||(0_._04)||(0_._01)|
|MA_×NTL_96 High||0_._25<sup>_∗∗∗_</sup>||0_._06||0_._02||0_._50<sup>_∗∗∗_</sup>||0_._58<sup>_∗∗∗_</sup>||0_._08<sup>_∗∗_</sup>|
|||(0_._04)||(0_._04)||(0_._02)||(0_._09)||(0_._16)||(0_._04)|
|MA, 1996|0_._11<sup>_∗∗∗_</sup>|0_._10<sup>_∗∗∗_</sup>|0_._02<sup>_∗∗∗_</sup>|0_._02<sup>_∗∗∗_</sup>|_−_0_._01<sup>_∗_</sup>|_−_0_._01<sup>_∗_</sup>|0_._06<sup>_∗∗∗_</sup>|0_._03|0_._02|_−_0_._01|_−_0_._002|_−_0_._01|
||(0_._01)|(0_._01)|(0_._002)|(0_._002)|(0_._003)|(0_._003)|(0_._01)|(0_._02)|(0_._02)|(0_._01)|(0_._004|)<br>(0_._005)|
|Log mean light, 1996|0_._02|_−_0_._13<sup>_∗∗_</sup>|0_._46<sup>_∗∗∗_</sup>|0_._43<sup>_∗∗∗_</sup>|_−_0_._05<sup>_∗_</sup>|_−_0_._06<sup>_∗∗_</sup>|_−_0_._11|_−_0_._34<sup>_∗∗∗_</sup>|0_._32<sup>_∗_</sup>|0_._06|_−_0_._11|_−_0_._15|
||(0_._05)|(0_._05)|(0_._12)|(0_._13)|(0_._02)|(0_._03)|(0_._07)|(0_._08)|(0_._19)|(0_._19)|(0_._10)|(0_._11)|
|Pre-trend: log mean light|0_._09|0_._16<sup>_∗∗_</sup>|0_._16|0_._19|_−_0_._003|0_._01|0_._11|0_._09|_−_0_._20|_−_0_._18|0_._13|0_._13<sup>_∗_</sup>|
||(0_._08)|(0_._08)|(0_._15)|(0_._16)|(0_._03)|(0_._03)|(0_._13)|(0_._10)|(0_._23)|(0_._21)|(0_._08)|(0_._08)|
|Pre-trend: log N urban pixels|0_._35<sup>_∗∗_</sup>|0_._34<sup>_∗∗∗_</sup>|0_._57<sup>_∗∗∗_</sup>|0_._57<sup>_∗∗∗_</sup>|_−_0_._04|_−_0_._04|_−_0_._25<sup>_∗∗_</sup>|_−_0_._22<sup>_∗∗_</sup>|0_._36<sup>_∗_</sup>|0_._39<sup>_∗_</sup>|_−_0_._05<sup>_∗_</sup>|_−_0_._04<sup>_∗_</sup>|
||(0_._14)|(0_._13)|(0_._21)|(0_._21)|(0_._12)|(0_._12)|(0_._10)|(0_._09)|(0_._21)|(0_._23)|(0_._02)|(0_._02)|
|Unit|_Keb._|_Keb._|_Keb._|_Keb._|_Keb._|_Keb._|_Wor._|_Wor._|_Wor._|_Wor._|_Wor._|_Wor._|
|Observations|15,714|15,714|15,714|15,714|15,714|15,714|780|780|780|780|780|780|
|Adjusted R<sup>2</sup>|0.17|0.18|0.22|0.22|0.14|0.14|0.32|0.35|0.27|0.28|0.37|0.36|

Standard errors are clustered on Woredas when using Kebeles as the unit of analysis and are clustered on Zones when using Woredas as the unit of analysis. All models include Zone fixed effects. MA is the logged difference of MA from 1996 to 2016. MA is instrumented with a 50km MA Doughnut variable; that is, in calculating market access, units within 50km are excluded. _NTL_ 96 Low, Medium, and High are dummy variables for different groups of baseline nighttime lights; groups are formed using 3-quantiles of the maximum value of nighttime lights within Woredas that had some positive nighttime lights. The excluded group is Woredas where the maximum value of nighttime lights at baseline was 0. NTL is the average nighttime lights within Kebeles, Urban is the total urban area within Kebeles, and Cropland is the total cropland area within Kebeles; we use the inverse hyperbolic sine transformation on all outcome variables, which has a similar interpretation as logs.<sup>_∗_</sup> p _<_ 0.1; _∗∗ ∗∗∗_ p _<_ 0.05; p _<_ 0 _._ 01

**Table S22:** Association of changes in market access on changes in outcome variables using a long difference. _θ_ = 8, using a 50km doughnut IV

||NT|L|Urb|an|Crop|land|N|TL|U|rban|Cro|pland|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|MA|_−_0_._06<sup>_∗∗∗_</sup>|_−_0_._08<sup>_∗∗∗_</sup>|0_._01<sup>_∗∗_</sup>|0_._01<sup>_∗_</sup>|0_._002|0_._001|_−_0_._08|_−_0_._11|0_._03|0_._01|_−_0_._001|_−_0_._004|
||(0_._02)|(0_._02)|(0_._01)|(0_._004)|(0_._01)|(0_._01)|(0_._07)|(0_._07)|(0_._04)|(0_._05)|(0_._02)|(0_._02)|
|MA_×NTL_96 Low||0_._07<sup>_∗∗_</sup>||_−_0_._01<sup>_∗∗_</sup>||0_._003||0_._19<sup>_∗∗∗_</sup>||0_._05<sup>_∗_</sup>||0_._01|
|||(0_._03)||(0_._01)||(0_._01)||(0_._06)||(0_._03)||(0_._01)|
|MA_×NTL_96 Med||0_._13<sup>_∗∗∗_</sup>||_−_0_._004||0_._003||0_._32<sup>_∗∗∗_</sup>||0_._18<sup>_∗∗∗_</sup>||0_._02<sup>_∗_</sup>|
|||(0_._03)||(0_._01)||(0_._01)||(0_._08)||(0_._04)||(0_._01)|
|MA_×NTL_96 High||0_._25<sup>_∗∗∗_</sup>||0_._06||0_._02||0_._50<sup>_∗∗∗_</sup>||0_._58<sup>_∗∗∗_</sup>||0_._08<sup>_∗∗_</sup>|
|||(0_._04)||(0_._04)||(0_._02)||(0_._09)||(0_._16)||(0_._04)|
|MA, 1996|0_._11<sup>_∗∗∗_</sup>|0_._10<sup>_∗∗∗_</sup>|0_._02<sup>_∗∗∗_</sup>|0_._02<sup>_∗∗∗_</sup>|_−_0_._01<sup>_∗_</sup>|_−_0_._01<sup>_∗_</sup>|0_._06<sup>_∗∗∗_</sup>|0_._03|0_._02|_−_0_._01|_−_0_._002|_−_0_._01|
||(0_._01)|(0_._01)|(0_._002)|(0_._002)|(0_._003)|(0_._003)|(0_._01)|(0_._02)|(0_._02)|(0_._01)|(0_._004|)<br>(0_._005)|
|Log mean light, 1996|0_._02|_−_0_._13<sup>_∗∗_</sup>|0_._46<sup>_∗∗∗_</sup>|0_._43<sup>_∗∗∗_</sup>|_−_0_._05<sup>_∗_</sup>|_−_0_._06<sup>_∗∗_</sup>|_−_0_._11|_−_0_._34<sup>_∗∗∗_</sup>|0_._32<sup>_∗_</sup>|0_._06|_−_0_._11|_−_0_._15|
||(0_._05)|(0_._05)|(0_._12)|(0_._13)|(0_._02)|(0_._03)|(0_._07)|(0_._08)|(0_._19)|(0_._19)|(0_._10)|(0_._11)|
|Pre-trend: log mean light|0_._09|0_._16<sup>_∗∗_</sup>|0_._16|0_._19|_−_0_._003|0_._01|0_._11|0_._09|_−_0_._20|_−_0_._18|0_._13|0_._13<sup>_∗_</sup>|
||(0_._08)|(0_._08)|(0_._15)|(0_._16)|(0_._03)|(0_._03)|(0_._13)|(0_._10)|(0_._23)|(0_._21)|(0_._08)|(0_._08)|
|Pre-trend: log N urban pixels|0_._35<sup>_∗∗_</sup>|0_._34<sup>_∗∗∗_</sup>|0_._57<sup>_∗∗∗_</sup>|0_._57<sup>_∗∗∗_</sup>|_−_0_._04|_−_0_._04|_−_0_._25<sup>_∗∗_</sup>|_−_0_._22<sup>_∗∗_</sup>|0_._36<sup>_∗_</sup>|0_._39<sup>_∗_</sup>|_−_0_._05<sup>_∗_</sup>|_−_0_._04<sup>_∗_</sup>|
||(0_._14)|(0_._13)|(0_._21)|(0_._21)|(0_._12)|(0_._12)|(0_._10)|(0_._09)|(0_._21)|(0_._23)|(0_._02)|(0_._02)|
|Unit|_Keb._|_Keb._|_Keb._|_Keb._|_Keb._|_Keb._|_Wor._|_Wor._|_Wor._|_Wor._|_Wor._|_Wor._|
|Observations|15,714|15,714|15,714|15,714|15,714|15,714|780|780|780|780|780|780|
|Adjusted R<sup>2</sup>|0.17|0.18|0.22|0.22|0.14|0.14|0.32|0.35|0.27|0.28|0.37|0.36|

Standard errors are clustered on Woredas when using Kebeles as the unit of analysis and are clustered on Zones when using Woredas as the unit of analysis. All models include Zone fixed effects. MA is the logged difference of MA from 1996 to 2016. MA is instrumented with a 50km MA Doughnut variable; that is, in calculating market access, units within 50km are excluded. _NTL_ 96 Low, Medium, and High are dummy variables for different groups of baseline nighttime lights; groups are formed using 3-quantiles of the maximum value of nighttime lights within Woredas that had some positive nighttime lights. The excluded group is Woredas where the maximum value of nighttime lights at baseline was 0. NTL is the average nighttime lights within Kebeles, Urban is the total urban area within Kebeles, and Cropland is the total cropland area within Kebeles; we use the inverse hyperbolic sine transformation on all outcome variables, which has a similar interpretation as logs.<sup>_∗_</sup> p _<_ 0.1; _∗∗ ∗∗∗_ p _<_ 0.05; p _<_ 0 _._ 01 S33