Nevertheless, to assess the validity of causal inferences about the various impacts of transport costs drawn from such cross-sectional data,we carry out two tests prior to our main estimation. The first test, presented in Section 2, looks for systematic differences in land productivity across space. Such differences might explain why roads are not built into certain areas, and thus why these areas remain remote. At the same time, location-specific productivity may well be
correlated with household level outcomes, such as land values, farm input use and output. The second test is for the presence of systematic differences in farm productivity across households at a given location; in particular, between migrant and native households. Poorer, less able migrants may be attracted to more remote areas by virtue of cheaper land. This selective migration could make the impacts of inaccessibility appear greater than they really are Before turning to these tests, Section 2 describes our data and sampling methodology in detail. This section also presents a set of stylized facts that undergird our agricultural household model. Section 3 lays out the model and derives formulae for the willingness- to-pay for a reduction in transport costs. In Section 4, we implement these formulae using a nonparametric estimation procedure. Section 5 recaps the results.