The importance of macroeconomic statistics compiled by the government, such as Gross Domestic Product (GDP) and the Consumer Price Index (CPI), is difficult to overstate. The data used to calculate these statistics are collected through surveys fielded by a host of differing government agencies, including the Bureau of Labor Statistics, the Bureau of Economic Analysis, and the Census Bureau. These surveys have significant and well-known methodological limitations leading to inaccuracies, substantial lag times, sampling distortions, and the need for (often significant) revisions. The worrying methodological basis of many economic statistics stands at odds with the increasingly high-quality data available about the economy. Vast improvements in the ability of retailers, for instance, to electronically track transactions provide a wealth of data for price and quantity measurement that is several orders of magnitude richer than currently captured in government surveys.
This grant funds a pilot project by a team led by John Haltiwanger at the University of Maryland, College Park, to develop new, more accurate, and more timely methods to calculate portions of GDP and CPI using administrative data collected by retail firms. Partnering with several large retailers, the team will compile a large set of administrative data bearing on retail prices and quantities produced and sold, document how these data can be acquired and harvested, use the data to calculate portions of CPI and GDP, and then issue a report comparing and contrasting these calculations along several dimensions with current methodologies. Though it is too much to hope that such a project will, by itself, change the way government economic statistics are calculated, this project is an important proof of concept demonstrating one potential path to what all agree is badly needed reform.