This paper estimates the relative price sensitivity of individuals' choice of whether to buy computers online versus in retail stores using a new data source on the computer purchase behavior of almost 30,000 people. To estimate the degree of competition between the two channels, the paper uses a two step approach. First, it fits hedonic regressions for the prices paid for a computer in a retail store as a function of characteristics. The coefficients on the city fixed effects in these regressions give a measure of the retail price level The second stage then looks at whether individuals purchase their computers in stores versus online as a function of the retail price and their own personal characteristics. The results indicate that the decision to buy remotely is sensitive to the relative price of computers in retail stores. Conditional on buying a computer, the elasticity of buying remotely with respect to retail store prices is about 1.5.