Price indexes play a significant role in measuring real output and productivity; thus, potential bias in price indexes, as well as a lack of price indexes, can impact the accuracy of productivity measures

Productivity growth for the U.S. business sector has been slow since 1973, compared with that of earlier periods. From 1959 to 1973, for example, estimates prepared by the Bureau of Labor Statistics showed that labor productivity (output per hour) in the business sector increased by about 3 percent per year. Since 1973, by contrast, the growth rate has been just slightly more than 1 percent per year. Interestingly, however, during this recent period of relatively slow productivity growth, industrial technology advanced considerably, and the financial markets were healthy as well, phenomena often associated with increases in the rate of productivity growth.

As a result of this apparent contradiction, many economists and government officials have begun to question whether the slower growth was real or the result of measurement problems in the official government productivity statistics. In particular, recent discussions have focused on the issue of possible upward bias in the Consumer Price Index (CPI), leading some economists to assert that productivity growth has been understated as a result. This article attempts to add to these discussions by examining the relationship between price indexes and productivity statistics, gauging the relative importance of each of the various indexes used.

The Office of Productivity and Technology publishes productivity statistics for major sectors and subsectors of the U.S. economy, as well as for many domestic industries and foreign countries.(1) In this article, the focus is on labor productivity statistics for the business sector of the U.S. economy. These statistics relate the real output of an aggregate sector of the U.S. economy to the labor resources used to produce that output. Hence, data series on labor productivity, or output per hour, capture changes in output that cannot be attributed to changes in labor inputs. Growth in labor productivity can be a result of many influences, including changes in technology, capital investment, purchased inputs from outside the sector, capacity utilization, returns to scale, and workforce skill and effort.

To calculate labor productivity for the U.S. business sector, BLS combines indexes of real output from the national income and product accounts (national accounts), produced by the Bureau of Economic Analysis (BEA) of the U.S. Department of Commerce, with hours measures constructed primarily using data from the BLS Current Employment Statistics program, Current Population Survey (CPS), and the Hours-at-Work Survey.(2) Thus, the article begins with a discussion of three methods used by BEA to construct time series for real components of gross domestic product (GDP) and for the business sector output used to construct BLS productivity measures: deflation, extrapolation and direct-valuation techniques. (The deflation and extrapolation techniques make use of various price indexes, including the CPI.)

Next, using BEA data from 1997, the relative importance of various price indexes in measuring business sector output is examined. These calculations indicate that components of the CPI are used to construct approximately 57 percent of the business sector output measure used for BLS productivity statistics. Due to its relative importance in measuring real output, the CPI receives more attention here than do the other indexes. In addition, some aspects of the recent controversy surrounding the CPI and its methodology are reviewed, including a discussion of the Advisory Commission to Study the Consumer Price Index (Boskin Commission) December 1996 report to the Senate Finance Committee and the official BLS response to the Boskin Commission's findings.

Finally, the article discusses an area that has not been highlighted in the recent evaluation of productivity measures: the use of input-based methods to construct components of real output. …