  How good are the public services and the public infrastructure? Does their
quality vary by income? These are vital questions---they shed light on how well
the government is doing its job, the consequences of disparities in local
funding, etc. But there is little good data on many of these questions. We fill
this gap by describing a scalable method of getting data on one crucial piece
of public infrastructure: roads. We assess the quality of roads and sidewalks
by exploiting data from Google Street View. We randomly sample locations on
major roads, query Google Street View images for those locations and code the
images using Amazon's Mechanical Turk. We apply this method to assess the
quality of roads in Bangkok, Jakarta, Lagos, and Wayne County, Michigan.
Jakarta's roads have nearly four times the potholes than roads of any other
city. Surprisingly, the proportion of road segments with potholes in Bangkok,
Lagos, and Wayne is about the same, between .06 and .07. Using the data, we
also estimate the relation between the condition of the roads and local income
in Wayne, MI. We find that roads in more affluent census tracts have somewhat
fewer potholes.
