There is a new paper out from the Brookings Institution’s Hutchins Center on Fiscal and Monetary Policy that has important implications for how we address lagging productivity. Part of the Hutchins Center’s Productivity Measurement Initiative, the paper by Prasanna Tambe, Lorin M. Hitt, Daniel Rock and Erik Brynjolfsson is called Digital capital and superstar firms.
Building upon previous work, the paper looks at a different categorization of intangible assets labeled “digital capital” consisting of “employee training that is related to new information technologies, firm-specific human capital related to technology systems, and the development and implementation of business processes and other forms of organizational transformation required to support or use new information technologies.” (p. 5) This definition excludes brands and intellectual property, and general human capital (as opposed to the IT related firm-specific human capital).
They find that investment in digital capital accounts for increases in productivity. “Our findings suggest that the higher values the financial markets have assigned to firms with large digital investments in recent years reflect greater digital capital quantities, rather than simply higher prices for existing assets. In other words, they reflect genuine improvements to firms’ productive capacity. In fact, we find that digital capital, if included as a separate factor in firm-level production functions, predicts differences in output and productivity among firms.” (p. 19)
Importantly, most of the value of digital capital is concentrated in a small number of superstar companies.
The combination of these findings has major implications for how to raise productivity: “One interpretation of our findings is that translating organizational innovations into productive capital requires significant investment in organizational re-engineering and skill development. Therefore, even if firms have the appropriate absorptive capacity, knowledge of how to construct digital assets will not automatically generate productive digital capital any more than access to the blueprints of a competitor’s plant will directly lead to productive capacity.” (p. 19)
In other words, laggard companies face daunting obstacles in trying to catch up. Knowledge is not enough and is not easy to translate into action.
In light of that finding, the public policy question is “what can governments do to help?” Clearly, technical assistance is not enough. It may be a necessary condition, but it is not a sufficient one. Investment in organizational and human capital is also required. Government support for investment both areas is somewhat controversial. While funding for general human capital has long been acceptable, funding for firm-specific human capital is less acceptable. And government funding for organizational capital is viewed as questionable. In both cases, government support is seen as using public funds to benefit private interests.
This is not to say that there isn’t already a good deal of government support for specific industries and firms, often through the tax code. I’m just pointing out that the case needs to be made for investments in digital capital. That case rests on the fact that digital capital is a key driver of productivity, which is crucial for continued economic prosperity. Just like R&D spending, there are great public spillovers of investment in digital capital.
In addition, we need to think more about the most effective mechanisms for fostering digital capital. Funding for firm-specific human capital can be relatively straight forward. One example is funding industry-community college partnerships. Funding organizational capital may be much trickier. Current government policies focused on technical assistance. We need creative ways to go beyond this narrow focus. Otherwise, we risk digital equivalent of, as the authors of this paper put it, assuming “access to blueprints of a competitor’s plant will directly lead to productive capacity.”