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Webb, Roy H.. "National productivity statistics." Economic Quarterly. Federal Reserve Bank of Richmond. 1998. HighBeam Research. 21 Apr. 2018 <https://www.highbeam.com>.
Webb, Roy H.. "National productivity statistics." Economic Quarterly. 1998. HighBeam Research. (April 21, 2018). https://www.highbeam.com/doc/1G1-20738582.html
Webb, Roy H.. "National productivity statistics." Economic Quarterly. Federal Reserve Bank of Richmond. 1998. Retrieved April 21, 2018 from HighBeam Research: https://www.highbeam.com/doc/1G1-20738582.html
Many people now enjoy levels of prosperity that would have been barely imaginable a few hundred years ago. That remarkable achievement can be viewed through the lens of productivity statistics that give quantitative estimates of output per unit of input. By studying productivity, analysts can improve their understanding of the causes of national prosperity and economic growth. Since different definitions of productivity are widely used, this article reviews the most important ones used in the United States. The article also contains a brief sketch of the historical behavior of productivity and then warns readers about potential pitfalls in using productivity statistics. Finally, the background material is used to address questions concerning the recent behavior of productivity statistics.
1. WHAT EXACTLY IS PRODUCTIVITY?
Simply stated, productivity is output per unit of input. Actually calculating a number can be somewhat more complicated. Suppose that we can agree that aggregate national output is adequately modeled by using a Cobb-Douglas production function
[Mathematical Expression Omitted], (1)
where Y is aggregate output, K is the capital stock, L is labor input, t is a time-period index, [Alpha] is a number between zero and one, and A will be discussed later. For national productivity statistics, an obvious starting point is to take an estimate of aggregate output such as real gross domestic product (GDP) from the National Input and Product Accounts (NIPAs). On the input side, the first requirement is to measure labor input, such as the number of workers or the number of hours worked.
The Bureau of Labor Statistics (BLS) currently publishes three categories of productivity estimates, which in terms of equation (1) are simply of the form Y/L. The most widely cited category is published quarterly and takes an output measure from the NIPAs for a large sector of the economy. Business product is the portion of real GDP produced by the business sector, and thus excludes production from the household sector, the foreign sector, and the government sector. Nonfarm business, naturally, is business product minus farm production. Product of nonfinancial corporations further excludes production by financial firms and by proprietorships and partnerships. Also, as part of its quarterly estimates, the BLS publishes productivity statistics for the manufacturing sector. In 1992, business product accounted for 76 percent of GDP, nonfarm business product was 75 percent of GDP, nonfarm nonfinancial corporate business product was 52 percent of GDP, and manufacturing product was 17 percent of GDP. Since the only input considered is hours worked, these estimates are often described as labor productivity. Most of the data on employee-hours comes from the BLS's establishment survey, although for some workers other sources are used.
The BLS publishes a second category of estimates annually, using a more comprehensive definition of inputs into the production process; the result is referred to as multifactor, or total-factor, productivity and is represented by the term A in equation (1). The statistic is estimated by dividing product of a broad sector by an input index that is a weighted average of two indexes, one of labor inputs and the other of capital inputs. The index of labor inputs can be thought of as a quality-adjusted labor index; for broad sectors it is calculated as a weighted average of employee-hours for several groups of workers. The groups are defined by sex, level of education, and amount of experience. The capital input index is a weighted average of capital services from many different categories of structures, equipment, inventories, and land.
In both the quarterly and annual estimates, productivity in the narrow manufacturing sector is calculated using input and output measures that differ from the measures used to estimate productivity in the broader sectors. Manufacturing productivity is therefore not strictly comparable to the broad-sector estimates. For multifactor productivity, manufacturing labor input does not receive the demographic adjustments that the labor input receives for broader sectors. In addition to labor and capital, manufacturing's aggregate input index includes purchases of energy, other raw materials, and business services. Those additional items are crucial, since purchased inputs account for the bulk of manufacturing costs. With regard to output, the manufacturing measure is gross output, excluding shipments within the manufacturing sector. In contrast, for the broader sectors, output represents value added; accordingly, the value of material inputs is subtracted from gross output.
The BLS publishes a third category of estimates for particular industries. In this category, they estimate labor productivity for 150 specific industries, again using a different methodology from the other two categories. Multifactor productivity is also calculated for a smaller number of industries. The BLS first estimated industry productivity in 1898 in response to congressional concerns over the employment effects of labor-saving technology. Today, the choice of which industries to cover depends on data availability and therefore is heavily tilted toward manufacturing. Nonetheless, the BLS estimates productivity for important industries outside manufacturing, including mining, communications, banking, trade, and transportation. In these industry estimates, output indexes measure gross output and are taken from census surveys. The labor input is measured by employee-hours, without demographic adjustments. For multifactor productivity calculations, capital services and intermediate purchases supplement the labor input.
In order to supplement the BLS productivity estimates, many analysts construct their own numbers. Since GDP and population estimates are available for relatively lengthy time spans for many countries, GDP divided by population is often used as a rough estimate of labor productivity. Either the numerator or the denominator of this output-per-person ratio can be refined. Most importantly, instead of population, one could use the labor force, employment, or employee-hours. Many analysts also construct their own estimates of multifactor productivity. The main requirement is to have a method to construct an input index; in equation (1), for example, the input index is [K.sup.[Alpha]][L.sup.1-[Alpha]]. By constructing one's own multifactor productivity index, an analyst can include the most relevant factors of production. Thus one might distinguish between skilled and unskilled labor or between privately owned and government-owned physical capital. Finally, industry productivity estimates have often been constructed directly from the NIPA measures of output by sector, which by definition represent value added rather than gross output.
2. POTENTIAL PITFALLS AND MEASUREMENT ISSUES
Any meaningful interpretation of national productivity statistics must account for the following potential pitfalls.
(1) Current estimates of productivity understate both its level and rate of growth. That bias reflects a basic difficulty in estimating real output. Real GDP, for example, is estimated by taking spending for over 1,000 separate categories, adjusting each spending estimate for price change, and summing the resulting estimates of real expenditure. …
Economic Quarterly - Federal Reserve Bank of Richmond; January 1, 1998
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