Abstract
This paper develops an identification strategy to generate unbiased estimates of Internet usage spillovers using a unique data set of US households. I identify multiple potential sources of learning including those from the household’s locality, from educational Internet subsidies, and from universities. I find general support for all sources, but the locality and subsidy results are both more robust and larger. These findings have implications for policies to encourage Internet use as well as for identification strategies for the effects of the Internet on behavior.
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