The dark energy and matter that drives economic performance: Innovation, like dark matter, can t be measured well, but regional science is getting closer.

• Author: Slaper, Timothy F.

Anyone reading this article or anyone who decided not to read it, quits in the middle of reading it, or doesn't even know the article exists, is a part of the 5%. Only 5% of the universe is observable and directly measurable. The rest of the universe is something of a head scratcher for most of us-dark energy and dark matter.

In a similar way, measuring innovation is a challenge We'll hear more and more about the importance of innovation in the coming years as a driver of economic growth, especially from political and thought leaders But talk as they may, few can figure out how to measure it even remotely close to real time Economists, business analysts and economic developers, to name a few, can observe it after it has happened, but getting a signal as it emerges and produces new products and creates new jobs is tricky.

I We can observe innovation after it has happened, but getting a signal as it emerges and produces new products and creates new jobs is tricky.

A common, generally accepted measure for innovation is the count and rate of patent production. Another measure might be the rate of entrepreneurship, or new business formation, especially in the industry sectors that produce and apply new patent technologies. Others interested in the development, application and commercialization of knowledge might look at university or federal research laboratory collaborations with private industry as an indicator of innovation activities. All of these metrics have merit, if one can get good data for them. But even still, there is still a lot of innovation dark matter beyond our ability to measure and understand.

The IBRC has published an innovation index over the last decade (see StatsAmericaorg). The first index iteration was rather simple, e.g., counting the number of patents or the STEM occupations in a region. In the second iteration, the IBRC expanded the offerings of measures, including proxy measures for knowledge spillovers from universities or investments in new production facilities. While StatsAmerica will soon publish its next iteration of an innovation index-what we are going to call Innovation Intelligence-this isn't an introduction to the new tool and data. That will be announced later in 2021.

This article describes and distills recent research that measures innovation and how we may apply it to Indiana What we call innovation dark matter, professors Goetz and Han (2020) call "latent innovation." (View their article.) We hope that our translation of the article does not do violence to their work or reputation. We hope that the description of the concepts make their work more accessible as we wrap our heads around innovation dark matter

"Innovation theory," if there is such a thing

In simple speak, innovation is making something better or new. Selling innovation on the open market-commercializing innovation-also needs to put more money in your pocket. No one is going to bring innovation to market unless there is an expected profit.

An innovative product or service has knowledge and know-how baked into it. One doesn't need to be "super smart" to be innovative and bring a new or better product/service to market-simply smart within a single domain in which one excels.

The question then becomes, where does this knowledge and know-how come from? In broad strokes, knowledge and know-how can come from study (hence the notion of university spillovers) or come from aptitude and experience (hence the notion of learning by doing and apprenticeships). The latter we'll call experience as a short cut. Clearly, there is great overlap in terms of study and experience driving innovation and the two reinforce and make each other stronger. The new measures presented by Goetz and Han are not the "same old same old" established metrics for innovation--e.g., the number of STEM degree graduates or patents in a region. Instead, they measure the relatively invisible relationships between industries, technologies and people.

Alfred Marshall was the economist who, early on, observed that similar industries located together to their mutual benefit. They shared similar workforce needs and often contributed to each other's supply chain. Whether workers moved from firm to firm, or worker know-how was shared among friends down at the pub, worker know-how diffused throughout a region. Regions specialized.

A more recent contributor to this understanding about how and why many regions prosper is professor Michael Porter. (Porter's cluster mapping project is also available via StatsAmerica.org.) As regions specialize, productivity, employment and profits...