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The Solow Productivity Paradox: What Do Computers Do to Productivity?

Jack E. Triplett

You can see the computer age everywhere but in the productivity statistics.
Robert Solow (1987)

Abstract

Solow’s aphorism, now more than ten years old, is often quoted. Is there a paradox? And if so, what can be said about it? This paper reviews and assesses the most common “explanations” for the paradox. It contains separate sections evaluating each of the following positions.

(1) You don’t see computers “everywhere,” in a meaningful economic sense. Computers and information processing equipment are a relatively small share of GDP and of the capital stock.

(2) You only think you see computers everywhere. Government hedonic price indexes for computers fall “too fast,” according to this position, and therefore measured real computer output growth is also “too fast.”

(3) You may not see computers everywhere, but in the industrial sectors where you most see them, output is poorly measured. Examples are finance and insurance, which are heavy users of information technology and where even the concept of output is poorly specified.

(4) Whether or not you see computers everywhere, some of what they do is not counted in economic statistics. Examples are consumption on the job, convenience, better user-interface, and so forth.

(5) You don’t see computers in the productivity statistics yet, but wait a bit and you will. This is the analogy with the diffusion of electricity, the idea that the productivity implications of a new technology are only visible with a long lag.

Author

(6) You see computers everywhere but in the productivity statistics because computers are not as productive as you think. Here, there are many anecdotes, such as failed computer system design projects, but there are also assertions from computer science that computer and software design has taken a wrong turn.

(7) There is no paradox: Some economists are counting innovations and new products on an arithmetic scale when they should count on a logarithmic scale.

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