Conclusion


Conclusion

Concerns about an IT "productivity paradox" were raised in the late 1980s. Over a decade of research since then has substantially improved our understanding of the relationship between IT and economic performance. The firm-level studies in particular suggest that, rather than being paradoxically unproductive, computers have had an impact on economic growth that is disproportionately large compared to their share of capital stock or investment, and that this impact is likely to grow further in coming years.

In particular, both case studies and econometric work point to organizational complements such as new business processes, new skills, and new organizational and industry structures as a major driver of the contribution of IT. These complementary investments, and the resulting assets, may be as much as an order of magnitude larger than the investments in the computer technology itself. However, they go largely uncounted in our national accounts, suggesting that computers have made a much larger real contribution to the economy than previously believed.

The use of firm-level data has cast a brighter light on the black box of production in the increasingly IT-based economy. The outcome has been a better understanding of the key inputs, including complementary organizational assets, as well as the key outputs including the growing roles of new products, new services, quality, variety, timeliness, and convenience. Measuring the intangible components of complementary systems will never be easy. But if researchers and business managers recognize the importance of the intangible costs and benefits of computers and undertake to evaluate them, a more precise assessment of these assets needn't be beyond computation.



Acknowledgments

This chapter is reprinted with permission from Journal of Economic Perspectives 14, no. 4 (Fall 2000): 23–48. Portions also appear in MIS Review and in an edited volume, The Puzzling Relations Between Computer and the Economy, Nathalie Greenan, Yannick Lhorty, and Jacques Mairesse, eds., MIT Press, 2001.

The authors thank David Autor, Brad DeLong, Robert Gordon, Shane Greenstein, Dale Jorgenson, Alan Krueger, Dan Sichel, Robert Solow, Kevin Stiroh, and Timothy Taylor for valuable comments on (portions of) earlier drafts. This work was funded in part by NSF Grant IIS-9733877.



Notes

  1. For a more general treatment of the literature on IT value see reviews by Attewell and Rule (1984), Brynjolfsson (1993), Wilson (1995), and Brynjolfsson and Yang (1996). For a discussion of the problems in economic measurement of computers contributions at the macroeconomic level see Baily and Gordon (1988), Siegel (1997), and Gullickson and Harper (1999).

  2. These studies assumed a standard form (Cobb-Douglas) for the production function, and measured the variables in logarithms. In general, using different functional forms, such as the transcendental logarithmic (translog) production function, has little effect on the measurement of output elasticities.

  3. Hitt (1996) and Brynjolfsson and Hitt (2000) present a formal analysis of this issue.

  4. Part of the difference in coefficients between short and long difference specifications could also be explained by measurement error (which tends to average out somewhat over longer time periods). Such errors-in-variables can bias down coefficients based on short differences, but the size of the change is too large to be attributed solely to this effect (Brynjolfsson and Hitt 2000).

  5. Kelley (1994) found that the use of programmable manufacturing equipment is correlated with several aspects of human resource practices.

  6. It is worth noting that if the exact quality change of an intermediate good is mismeasured, then the total productivity of the economy is not affected, only the allocation between sectors. However, if computer-using industries take advantage of the radical change in input costs and quality to introduce new quality levels (or entirely new goods) and these changes are not fully reflected in final output deflators, then total productivity will be affected. In periods of rapid technological change, both phenomena are common.