Aggregation Issues in Integrating and Accelerating BEA's Accounts: Improved Methods for Calculating GDP by Industry

Aggregate measures of real GDP growth obtained from the GDP by Industry Accounts often differ from the featured measure of real GDP growth obtained from the National Income and Product Accounts (NIPAs). We find that differences in source data account for most of the difference in aggregate real output growth rates; very little is due to the treatment of the statistical discrepancy, differences in aggregation methods, or the contributions formula. Moreover, we demonstrate that with consistent data, use of BEA's Fisher-Ideal aggregation procedures to aggregate value added over industries yields the same estimate of real GDP as aggregation over final commodities. Thus, two major approaches to measuring real GDP -- "expenditures" approach used in the NIPAs and the "production" or "industry" approach used in the Industry Accounts -- give the same answer under certain conditions. This result enables us to show that the "exact contributions" formula that the NIPAs use to calculate commodity contributions to change in real GDP can also be used to calculate consistent industry contributions to change in real GDP. We also find that using some newly developed datasets would help to bring the aggregate real output measures into closer alignment.

What Do We Know About Contracting Out in the United States? Evidence from Household and Establishment Surveys

A variety of evidence points to significant growth in domestic contracting out over the last two decades, yet the phenomenon is not well documented. In this paper, we pull together data from various sources to shed light on the extent of and trends in domestic outsourcing, the occupations in which it has grown, and the industries engaging in outsourcing for the employment services sector, which has been a particularly important area of domestic outsourcing. In addition, we examine evidence of contracting out of selected occupations to other sectors. We point to many gaps in our knowledge on trends in domestic outsourcing and its implications for employment patterns and to inconsistencies across data sets in the information that is available. We recommend steps to improve data in this area

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

Priorities for Industry Accounts at BEA

The U.S. economy is undergoing significant structural change that economists and policymakers would like to study from an industry perspective. BEA’s industry accounts--the input-output (I-O) accounts, the gross product originating (GPO) accounts, and the gross state product (GSP) estimates--provide much of the relevant data, but further enhancements are possible. BEA has ideas for improving these accounts, but resource constraints require that priorities be established and choices made. The impending conversion of BEA’s industry estimates to the new North American Industry Classification System (NAICS) offers both opportunities and challenges. This paper discusses the key issues, presents options for improving the industry accounts, and makes recommendations for future action.