Academic journal article Monthly Labor Review

Developing Statistics to Meet Society's Needs

Academic journal article Monthly Labor Review

Developing Statistics to Meet Society's Needs

Article excerpt

Developing statistics to meet society's needs

Three historical illustrations show how Government agencies adapt to changing social and economic needs by developing new concepts and methods

The development of statistics in the United States has been very much stimulated by the country's need for knowledge about its people, its economy, and the conditions of life. Beginning with the counting of the population as required by the Constitution, government data collection has expanded to cover employment, agriculture, industrial production, prices, earnings, consumption, health conditions, and a variety of other important areas. As the statistical system developed, data collection techniques became standardized and scientific sampling and estimation procedures were developed.

Although the history of this methodological progress is well known, it is surprising that so little attention has been paid to the development of the concepts and definitions that frame the issues and give substance to the results of statistical series. This is especially true when social and economic phenomena are measured, because definitions in these areas tend to change with society's view of the issue.

A statistical system, if it is to remain relevant, must build on the past but also must be prepared for change. Of course, there also must be order in the system for useful statistics to be developed; without consensus on what to measure and on the definitions and classifications involved, statistical knowledge cannot be developed.

Imagine the confusion if analysts were to compare statistics on the textile industry and some surveys included knitting mills while others restricted the information to weaving mills; or, if it had not been decided whether trucking firms that deliver textiles were part of the industry or separate from it, or whether the manufacture of machinery for textile production should be included as part of the industry. Ambiguities such as these led to the establishment of the Standard Industrial Classification system.

Even what would appear to be the simple counting of the people in the country has required the development of definitions and categories that are accepted as relevant to the characteristics of the population at the time of data collection. The earliest U.S. censuses enumerated slaves and free men. Slavery was abolished, but concerns about racial characteristics continued, and the categories for which counts would be made reflected those concerns. Later, the large waves of immigration that took place in the 19th and 20th centuries highlighted the need for additional racial and ethnic classifications.

As congressional legislation required the collection of information on conditions of work, and more particularly on the earnings of working men and women in the United States, further refinement of concepts occurred in that area. The point is that the phenomena underlying government statistics keep changing, the country's view of the concepts underlying data also changes, and those responsible for the measurement of these phenomena in official statistical series need to take account of the changes in the definitions used in the conduct of surveys.

As conditions in society have changed, new information needs have emerged, and new classification schemes and innovative approaches to the conceptual framework and the definitions within it have been developed and modified to meet those needs. This article discusses three examples of the conceptual contributions of Federal agencies to statistical development.

Employment by industry

National information on employment by detailed industry dates back to the 1899 Census of Manufactures, although the Bureau of Labor Statistics had conducted a number of special surveys in particular areas and industries in the 1880's. Earlier population censuses, such as the one in 1810, made broad distinctions among agriculture, commerce, and manufacturing. …

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