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Measuring Innovation: Better Data to Help Design Policies to Revive Economic Growth

1 April 2011 2,247 views No Comment
I’m honored to have Dale Jorgenson as this month’s guest columnist. A Fellow of the ASA since 1965 and the recipient of the 2010 Julius Shiskin Memorial Award for Economic Statistics, Jorgenson discusses the components of economic growth in the context of furthering the U.S. economic recovery.
~ Steve Pierson, ASA Director of Science Policy

Contributing Editor
Dale Jorgenson is the Samuel W. Morris University Professor at Harvard University. A Fellow of the ASA since 1965, he is the recipient of the 2010 Julius Shiskin Memorial Award for Economic Statistics for his leadership in the integration of the U.S. National Accounts and contributions to the measurement of productivity, innovation, capital, human capital, and poverty.

The great preponderance of economic growth in the United States involves the replication of existing technologies through investment in equipment and software and expansion of the skilled labor force. Replication generates economic growth with no increase in productivity. Productivity growth is the key economic indicator of innovation and accounts for less than 12% of U.S. economic growth, despite its importance in industries such as computers and software. Although innovation contributes only a modest portion of growth, this is vital to long-term gains in the American standard of living.

The predominant role of replication of existing technologies in U.S. economic growth is critical to the formulation of economic policies. As the U.S. economy recovers from the Great Recession of 2007–2009, economic policy must focus on reviving the growth of employment and stimulating investment. Policies that concentrate on enhancing the rate of innovation will have a modest impact over the intermediate run. However, the long-run growth of the economy depends on the performance of a relatively small number of sectors in which innovation takes place.

The trade industries head the list of innovators.

The U.S. statistical system has begun to incorporate inputs of capital, labor, energy, materials, and services (KLEMS), as well as outputs and productivity for individual industries. The KLEMS framework was endorsed by the Advisory Committee on Measuring Innovation in the 21st Century Economy to Secretary of Commerce Carlos Gutierrez. The Bureau for Economic Analysis and the Bureau of Labor Statistics are now implementing this approach to measuring productivity. The U.S. Census Bureau is providing important new data on inputs and outputs of services.

The U.S. statistical system has shifted gradually to the North American Industry Classification System (NAICS), beginning with the Business Census of 1997. The national accounts converted to NAICS in the 2003 Comprehensive Revision of the National Income and Product Accounts. An important advantage of NAICS is the greater detail available on the service industries that make up a growing proportion of the U.S. economy. NAICS also provides more detail on industries that produce information technology hardware, software, and services.

An examination of economic growth by industrial sector for the period 1960–2007 reveals that more than half was due to trade and services industries that are particularly intensive users of information technology equipment and software. The information-producing industries—computer hardware, software, services, and the related industries—accounted for slightly less than 10%. The rest of economic growth is accounted for by the remaining industries in manufacturing and mining, as well as service industries that do not use information technology equipment and software intensively.

The industries that lead in innovation are, surprisingly, headed by wholesale and retail trade, which comprise a large swath of the U.S. economy and have rapidly adopted information technology equipment and software. The trade industries head the list of innovators because of leading firms such as Walmart and Cisco that have used information technology to integrate supply chains around the world. These supply chains link electronic cash registers at retail outlets and business-to-business ordering systems with order dispatch and transportation scheduling at remote factories.

Semiconductors and computers have sustained high rates of innovation through new products and processes pioneered by firms such as Apple, IBM, and Intel. The rapid pace of innovation in information technology and software has continued through successive generations of technology, beginning with mainframe computers and continuing with minicomputers and then personal computers. Recently, this has shifted to services accessed through the Internet such as cloud computing. Voice, data, and video communications moved onto the Internet as broadband services became available to households, along with mobile and landline communications services.

Successful applications of information technology require new organizational structures to manage the steady procession of new generations of equipment and software. These organizational structures rapidly become antiquated so that executive-level management of information technology–based businesses must direct a continuous process of restructuring. Business systems have become imbedded in software that requires incessant updating as business needs evolve.

For details, download “New Data on U.S. Productivity Growth by Industry,” by Dale W. Jorgenson, Mun Ho, and Jon Samuels.

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