End of sample vs. real time data: perspectives for analysis of expectations

Abstract

Data revision is defined as an adjustment published after the initial announcement had been made; it may reflect rectification of errors, availability of new information, etc. When economists use a database, they may not even be aware that some of the values have been revised, perhaps repeatedly, and corrected numbers may significantly differ from original ones. I propose to test whether including information on data revisions helps to model properties of expectations, improve quantification procedures, or adjust tests of rationality to data vintage. This paper presents review of literature and databases available for the purposes of real time analysis, and offers an introduction to empirical analysis of influence of data vintage on tests of expectations