Standard errors as weights in multilateral price indexes

Various multilateral methods for computing price indexes use bilateral comparisons as their basic building blocks. Some give greater weight to those bilateral comparisons deemed more reliable. However, none of the existing reliability measures adjusts for gaps in the data. We show how the standard errors on bilateral price indexes derived using weighted least squares provide reliability measures that solve this problem. We then apply our methodology to a dataset on agricultural production in 103 countries. Our results demonstrate the appeal of weighted methods and the importance of using weights based on a comprehensive measure of reliability.