News, Noise, and Estimates of the "True" Unobserved State of the Economy

Which provides a better estimates of the growth rate of “true” U.S. output, gross domestic product (GDP) or gross domestic income (GDI)? Past work has assumed the idiosyncratic variation in each estimate is pure noise, taking greater variability to imply lower reliability. We develop models that relax this assumption, allowing the idiosyncratic variation in the estimates to be partly or pure news; then greater variability may imply higher information content and greater reliability. Based on evidence from revisions, we reject the pure noise assumption for GDI growth, and our results favor placing sizable weight on GDI growth because of its relatively large idiosyncratic variability. This calls into question the suitability of the pure noise assumption in other contexts, including dynamic factor models.

Integrating Expenditure and Income Data: What to Do with the Statistical Discrepancy?

The purpose of this paper is to build consistent, integrated datasets to investigate whether various disaggregated data can shed light on the possible sources of the statistical discrepancy. Our strategy is first to use disaggregated data to estimate consistent sets of input-output models that sum to either GDP or GDI and compare the two in order to see where the discrepancy resides. We find a few “problem” industries that appear to explain most of the statistical discrepancy. Second, we explore what combination of the expenditure data and the income data seem to produce the most sensible data according to a few economic criteria. A mixture of data that do not aggregate either to GDP or to GDI appears optimal

News, Noise, and Estimates of the "True" Unobserved State of the Economy

Which provides a better estimate of the ``true'' state of the U.S. economy, gross domestic product (GDP) or gross domestic income (GDI)? Past work has assumed the difference between each estimate and the ``true'' state of the economy is pure noise, taking greater variability to imply lower reliability. However each difference may be pure news instead; then greater variability implies higher information content and greater reliability. We analyze various vintages of estimates, developing models for combining GDP and GDI under the differing assumptions, and use revisions to the estimates to show the news assumption is probably more accurate.