Panel data measures of price discovery

This paper considers disaggregated price data that are observed not only for multiple markets over extended periods of time, but also for a large number of assets. The previous literature has argued that in such data rich environments, which arise frequently in applied work, the analysis of price discovery can be made more precise by accounting for the panel structure of the data. Moreover, since the individual assets are not that interesting anyways, little is lost by taking the overall panel perspective. These arguments are, however, mainly based on empirical observations, and there is little in terms of econometric support. The purpose of the present study is to fill this gap in the literature. This is done by offering a full-blown econometric analysis of panel analogs of the information share and permanent–transitory measures of price discovery, which are the workhorses of the time series literature. Both measures are shown to be consistent and they support standard normal inference, which is in contrast to the time series case, where such inference is only possible for the permanent–transitory measure.