4Q GDP and investment in intangibles

Somewhat disappointing news this morning from BEA’s advanced estimate of U.S. 4th quarter GDP. According to this first estimate, GDP grew by only 2.6% in 4Q 2014. I say only because expectations were for a 3% growth rate. Still, the economy continues to grow at a healthy pace (see chart below).
The growth in business investment in intellectual property products (IPP) remained at a high level at a 7.1% increase with a positive trendline (see chart). The 3Q growth rate was 8.8%. Software investment picked up a little with a 9.4% growth rate in 4Q compared with a 8.9% growth rate in 3Q. R&D slipped somewhat to a still strong level of 6.1% in 4Q compared to a 10.6% increase in 3Q. Growth in investment in entertainment, literary, and artistic originals remained steady at 2.5% in 4Q; it was 2.4% in 3Q. As the chart below shows, investment in IPP has tracked but exceeded overall GDP growth recently. However, over time the two have often diverged quite extensively.
Remember that this is the advanced estimate. It is subject to considerable revision as key pieces of information on the last three months have yet to be compiled (such as December’s trade data).
GDP 4Q14 - 1st.png
IPP percent 4Q14 -1st.png
IPP parts 4Q14 - 1st.png
GDP-IPP 4Q14 - 1st.png

Design and Innovation

OECD has a new paper out on Measuring Design and its Role in Innovation. The paper is part of OECD’s efforts to look more closely at non-technological innovation by the Working Party of National Experts on Science and Technology Indicators. This primarily a report on measurement which looks at the advantages ad limitations of various methods of measuring the economic impact of design. While that is an important contribution to the public policy literature, what I find more interesting is its insights about design and the innovation process.
As the report notes in the beginning, one measurement problem is the interconnection of types of innovation.

Results from innovation surveys have repeatedly shown that the two broad types of innovation (product and process on the one hand and organisational and marketing on the other) are more likely to co-occur than take place in isolation. Furthermore, cognitive interviews with business managers in several countries have revealed difficulties among respondents in separating between some types of innovations, in particular between process and organisational innovations.

Building on this, they look more closely at the interconnections and come up with some interesting findings on the role of design based on some optional questions on design by Statistics Denmark in its 2010 innovation survey:

– Around one enterprise out of four reports using design, either with the sole purpose of providing a last finish on products (5%), as an integrated though not determining element (10%) or as a central and determining element (8%) in their activities. The sectors showing the highest propensity to integrate design are high-tech manufacturing sectors, followed by ICT services, other professional business services and lower and medium tech manufacturers with a focus on consumer products.
– The use of design as an integrated element is highly correlated with innovation outcomes, particularly product and marketing innovations, including new-to-market innovations. Controlling for observed firm characteristics, the probability of introducing a product (marketing) innovation is 24 % (31%) higher for firms where design is integrated.
– Design integration tends to have a positive effect also on the success of innovative products. On average the percentage of innovative turnover of product innovating firms is nine times higher in firms using design as an integrated element.
– The use of design as an integrated element is highly correlated with measures indicating the implementation of methods of user engagement such as consumer panels and other advanced methods, thus lending support to a “user centred” view of design.
– The use of design as an integrated element is found to be significantly related to other innovation activities, both internal and external. Design integration generally reduces reliance on external product development, except for firms where design is a determining element, which rely heavily on external R&D and often co-develop their innovations with other partners.
– Robust correlations are found between design use and firm’s economic outcomes, especially value added and productivity growth. Firms using design as an integrated element are found to have on average a 9.1% higher employment growth rate, a 18.7% higher value added growth rate and a 10.4% higher productivity growth rate than similar-sized firms within their own sectors over the three-year period covered by the survey.

These finding reinforce my own thinking about the role of design thinking and how intangible assets working in a holistic ecosystem. First, as the report notes, “The concept of design as a broad ranging user-centred development activity is insightful in its integration of development and implementation and the integration of users and producers.” Design is an integrating activity, not simply an add-on or stand-only attribute. Second, the integrating nature of design highlights the fact that intangible assets need to work together to be effective.
However, this nature of design makes the measurement problem much more difficult:

it is apparent that identifying potential mechanisms for measuring design and producing indicators will not by itself satisfy the needs and expectations of policy users. Potential questions concern estimating the private and social rate of return to design investment, the extent of spillovers from design activities, the most appropriate protection frameworks for design outputs, the case of or against financial reporting requirements, the relevance of raising awareness on design and developing links with the design community, or the potential promotion of design skills and capabilities in firms, the workforce and youth. Dealing actively with these questions requires an ambitious research agenda. Identifying and addressing data gaps is a necessary step, which must be supported by the legal and physical infrastructure that provide the means for linking data sources and policy experiences in an analytical setting. This agenda requires first and foremost a continued dialogue to identify the most crucial questions of interest for policy makers and how they can be tested empirically.

Our task therefore is not to downplay the importance of design and other non-technological factors – as some might be tempted to do. Rather our task is to come up with new ways to tell the analytical story beyond the simple metrics now available. As the saying goes, “better to have an imprecise answer to the right question than a precise answer to the wrong question.”

What I want to hear in the State of the Union – 2015

According to press accounts (and comments by President Obama himself), tonight’s State of the Union address will focus on the economy and the middle class. Much of what the President is expected to propose has already been announced. But there may still be some initiatives that have not been made public yet. In case there is still an opportunity for additional proposals, here is what I would like to hear in the State of the Union address:

America is coming back from a devastating economic recession. Over the past year, despite ups and down, we have see the recovery of the American economy taking hold. But our job is not done yet. Recovery must be followed by sustained growth and improved economic competitiveness – especially if we expect that rising tide to lift all boats.
Our first task is to make sure the tide continues to rise. Our second is to make sure that the tide does in fact lift all boats. Both of these will require understanding the fundamental changes that are occurring in our economy — and crafting tools that fit this new environment in which we find ourselves.
Let us look more closely one part of that change: the current manufacturing renaissance. More and more, companies are finding it to their benefit to open production facilities in the U.S. as opposed to abroad. But, while manufacturing is coming back to the United States, it is different from the manufacturing that left our shores. It is leaner and smarter — requiring higher levels of workers skills. To keep our competitive edge requires fostering an educational enterprise that can provide the constantly changing skills required in a knowledge- and information-intensive economy.
We now see the fusion of manufacturing and services where companies provide solutions not just products. Customization, speed, and responsiveness to customer needs are the keys to success in this new environment. And as the linkage between goods and services grows, we are seeing international competition in services once thought immune to such challenges.
In confronting these new challenges, we cannot rely on simply repeating the policies of the past. We need a combination both new and old solutions.
For example, basic research helped sustain America’s economy growth in the 20th Century. But basic research is not enough. It is one part of a larger mix that fuels the economy. We moving to a post-scientific economy where, to quote Dr. Christopher Hill, former Vice Provost for Research at George Mason University, “the creation of wealth and jobs based on innovation and new ideas will tend to draw less on the natural sciences and engineering and more on the organizational and social sciences, on the arts, on new business processes, and on meeting consumer needs based on niche production of specialized products and services in which interesting design and appeal to individual tastes matter more than low cost or radical new technologies.”
Education needs to move from the classroom to the living room. Life-long learning should not be a slogan but an ingrained part of everyday activity. And as important as STEM is, our economic future is not solely in the hands of our scientists and engineers. Our future prosperity rest on raising the skills and knowledge level of everyone. Productivity no longer comes just from new machines, but from new ways of organizing work.
So let us be clear. The manufacturing jobs of our father and grandfather are not coming back. But we can create the manufacturing jobs for our children and grandchildren. We cannot — we will not — compete on the basis of a race to the bottom where wages and living standards are lowered to keep jobs from moving elsewhere. We can – and will — compete based on raising the knowledge content of our products — both goods and services. By doing so, we can also raise the living standards for all.
Government can play a major role in raising living standards through increased economic competitiveness via innovation and the development and diffusion of new products. But, innovation policy needs to catch up to the innovation process.
In crafting a new policy, we must recognize three points:
 • the innovation model has changed,
 • it’s all about people and organizations, and
 • technology plays multiple roles.
First, we all need to recognize that the innovation model has changed. It is not the linear process of flowing from basic research to final product that sticks in everyone mind. It is a network process. There are many points on the network where innovation can come from. We have used a number of terms to try to describe parts of the new model: “open innovation,” “user-driven innovation,” and even “design thinking.”
It is also not solely about technology. Technology remains an important component. But, as noted earlier, social innovations, marketing, finance, design and business models are also key sources of innovation as well.
Suffice it to say that innovation policy needs embraced this broader concept.
Second, innovation is about people and organizations. Skills, not just education, are critical. To both improve our competitiveness and provide for a more shared economic prosperity, we need to continually upgrade the skills of our worker and our workforce. Highly skills workers contribution more to, and benefit more from increased productivity and economic growth.
To create more highly skilled workers, we need to fundamentally upgrade our workforce training programs. Too many of these programs are focused on helping worker upgrade their skills only after they lose their jobs. Don’t get me wrong, job re-training for the unemployed is very important. But we need to also focus more on upgrading work skills (and thereby company competitiveness) so they don’t lose their jobs in the first place. Continual training on-the-jobs training need to become the backbone of our worker training programs – not an afterthought.
That said, we need to recognize that there will be times of slower demand where even the most competitive of companies may need to cut back on production. Rather than using these slowdowns as time of cut backs on training, we should embrace them as an opportunity. One way we can do this is by tying the concept of “job sharing” with worker training. Under a job sharing program, workers cut back on their hours (meaning that the company does not have to lay off workers completely) and the government picks up the cost of those lost hours through a program similar to unemployment insurance. This concept has been credited as one of the reasons Germany was able to weather the Great Recession. But we need to take the idea one step further. Rather than simply reduce workers hours, we should use those hours for training. In other words, when companies need to cut back on production, let’s pay workers to spend that slack time in the classroom or on-the-job training.
Besides continually upgrading workers skills, we need to continually upgrade the workforce itself. America has long been the destination of choice for the brightest and most ambitious. We need to make sure that America remains open and welcoming to those who would seek to improve their lives – and thereby enrich and improve ours. Immigrants have fueled the U.S. economy for generations – from the brightest Ph.D.s to the hard working entrepreneur and employee. We need comprehensive immigration reform to make sure that we can continue to rely on this source of economic growth and vitality.
But upgrading skills in not enough. Both tacit and experiential knowledge, not just codified and science-based knowledge, are also important. In order to put those skills and knowledge to proper use, organizational structure comes into play. The old hierarchical systems of the industrial age are no longer adequate or appropriate. New adaptive organizations which encourage innovation are needed. What we use to be called “High Performance Work Organizations” are needed to effectively utilize worker skills and knowledge.
Such organizations also play a large role in ensuring that the benefits of increased competitiveness are widely shared.
Finally, any innovation policy needs to understand that there are multiple roles for technology. Technology can be a driver of innovation, a tool of innovation, and even sometimes not all that that relevant to innovation. As a driver, the creation of new technology is a major source of innovation – the kind we normally think of when we use the word “innovation.”
But technology is also a tool in the innovation process. Technology as innovation tool works in two ways. One is innovation as the absorption and utilization of technology. For example, the iPod contained little new technology. It utilized the technology in a new way. The other is technology as an enabler. This is especially true in the information technology (IT) area, where IT allows for a myriad of new applications and innovations.
Take the analogy of the railroad. The marrying of the steam engine to a carriage on iron rails brought about far reaching changes in many difference areas. The railroads spurred on development of a number of other industries, most notably the steel industry. They changed opened up vast new markets and changed the retail and wholesale industries. They even gave rise to new management practices and the shift from ownership capitalism to managerial capitalism.
And sometimes technology plays a very minor role in innovation, if at all. Which was more important in creating the American suburbs: the automobile, Levittown or the 30 year mortgage? One was technological; one was design; one was financial. All were important. As a nation we need to recognize and promote multiple forms of innovation.
So here are some policies I plan to put forward. The new demand driven model innovation shows that government procurement and regulations can drive innovation. Government as a demanding customer can create the “thin opening wedge” — new products and services that have a specialized use. Once that specialized use is established, the product or service can be refined and adopted to a broader customer base. The demanding customer in fact becomes a co-creator. Smart regulations can serve the same function by creating demanding customers.
Here is another example of how we can expand our thinking on innovation. We have a program to create and fund Engineering Research Centers (ERCs) in a number of areas. We should create one for design thinking. We should expanding the ERC model to funding research on and demonstration of new business methods and organizational mechanisms as part of our “Catalyze Breakthroughs for National Priorities” element of the innovation strategy. And we should fund more organizationally-focused challenges, such as the famous DARPA “Red Balloon” challenge.
These are but few of the types of new policies we will pursue — beyond the status quo and conventional thinking that government should confine itself to basic research, education and infrastructure. That might be uncomfortable for some to hear. But it is where we need to go if we are to restore long term economic prosperity in this highly competitive global economy.

Webinar on IP and Intangible Capital

On Wednesday, January 21 at 11:00 EST I will be presenting a webinar with Mary Adams on “Maximizing IP Value
(through understanding intangible capital)
“. The webinar is being hosted by the IP consulting group Oxfirst and is open to the public. You can register here at https://attendee.gotowebinar.com/register/2293074742946252802.
As readers of this blog know, intellectual property (IP) is a critical strategic asset for corporations. But there are enormous differences in the value of IP stemming from the ecosystem that supports commercialization of the IP. What are the elements of the IP ecosystem? Can they be modeled and measured? The answer is yes. This webinar will introduce basic concepts about how to model, measure and maximize the potential of IP through a sound broader ecosystem of intellectual capital (IC). We will explore how a broader understanding of IC creates a richer and deeper understanding of the value of IP. As part of the presentation, open source tools will be provided to help participants implement these concepts in their own businesses.
I hope you can joins us — and share your stories and case examples of how IP connects to IC.
For more background, see my IAM Magazine article on “From IP to IC: why intangible capital matters.”

December employment

More indications this morning that the economy is getting better. The Bureau of Labor Statistics reports that the economy gained 252,000 jobs in December with the unemployment rate dropping to 5.6%. This was slightly better than economists had forecast. Importantly, both the manufacturing and professional & business services sectors hired more workers. These are key areas for future economic growth.
The number of involuntary underemployed (part time for economic reasons) continued to decline in December. The decline was due completely to a drop in those part time because of slack work. The number of those who could only find part time work remained the same as last month. But as the chart below shows, the level of involuntary underemployment remains well above pre-Great Recession levels.
Involuntary underemployed Dec 2014.png

Changes in House rules a lost opportunity for understanding intangibles

As expected, yesterday that House of Representatives adopted as part of its Rules a provision requiring dynamic budget scoring. This controversial provision changes the way legislation is analyzed for budgeting purposes (see NY Times story “House Republicans Change Rules on Calculating Economic Impact of Bills”). Existing rules require legislation to fit in certain budget caps, otherwise a budgetary offset (i.e. new revenues or cuts elsewhere) are needed. Dynamic scoring allows projected future revenues based on the estimated macroeconomic effects to be counted as part of the overall cost of the legislation (reducing the need for an offset if the estimate is of a positive effect on revenues).
As I noted in an earlier posting, I am not a big fan of dynamic scoring. As a recent report from The Center for Budget and Policy Priorities points out, “the estimates are highly uncertain and subject to manipulation.”
But I believe that using the interest in dynamic scoring could have been an opportunity to increase our understanding of investments in intangibles. Unfortunately, that will not happen.
Under the new House rules, legislation that meets a threshold impact test that is equal to or greater than 0.25 percent of the projected GDP for that year must be scored using “macroeconomic scoring.” In addition, the chair of the House Budget Committee can require such scoring for any direct spending legislation that he designates as “major legislation” — see Rule XIII clause 8(d)(1)(B). However, the explanation on the House Budget Committee website makes clear that the rule will have a limit applicability:

Q. Why doesn’t this rule apply to appropriations bills?
A. This rule builds on section 402 of the Congressional Budget Act, which requires formal cost estimates for legislation. This longstanding provision of the Budget Act has never applied to appropriations bills. In addition, since the rule applies to legislation making large increases or decreases in budgetary effects, it would be unusual for an appropriations bill to meet the threshold because it would have to make such a large change in annual funding levels.
Q. Why does this rule exclude proposals like infrastructure and education funding that could benefit the economy?
A. The legislation applies to mandatory spending and revenue legislation. Pell grants and student loans are mandatory funding and would be covered by the rule if the legislation had a budgetary effect greater than 0.25 percent of the economy. The rule modifies existing requirements for formal cost estimates for reported legislation. The Congressional Budget Act does not require CBO to produce a formal written cost estimate for appropriations bills. As a result, the rule does not apply to appropriations bills. And even if it did, it almost certainly would not be triggered, since appropriations bills provide funding only one year at a time, and the change in spending caused by an appropriations bill is unlikely to reach 0.25 percent of the economy.

This is fatal flaw in the rule. As the Director of the Office of Management and Budget notes:

dynamic scoring can create a bias favoring tax cuts over investments in infrastructure, education, and other priorities. While the House rule would require dynamic scoring for legislation making large changes in revenues and/or mandatory spending, and makes it permissible at the option of leadership for any such legislation (even if modest), it would not apply to discretionary spending, ignoring potential growth effects of investments in research, education, and infrastructure. More insidious, economic models that find large growth effects of tax cuts are often based on the assumption that they would be paid for entirely through reduced spending – without taking into account at all the economic consequences the reduction in government investment.

If dynamic scoring is to be used on the revenue (tax) side, it must also be used on the expenditure side. For example, if it is both proper and possible to assess the macroeconomic impact on federal tax revenues of an R&D tax credit, such analysis should also apply to government spending on R&D.
One other point. Edward Lazear (former Chair of the Council of Economic Advisors in the Bush Administration) defends the use of dynamic scoring in today’s Wall Street Journal (‘Scoring’ Legislation for Growth). But he adds three important caveats:

First, to prevent manipulation, the CBO should be required to use the same macroeconomic model for all pieces of legislation. This will limit the influence of politics on the estimates. The models can be updated periodically, but not on a case-by-case basis.
Second, the CBO should be required to make its models and approaches public so that the economics community can comment on the validity of the estimates and legislators can attach their own weights to the estimates.
Third, the CBO should be required to use the best science available to model the economy. Although what is best will always be subject to debate, this stipulation, coupled with the requirement that the models be made public, will force the CBO to defend its assumptions, just as nongovernment economists do in their published work.

These are very important points that highlight why I have argued that such scoring should be supplemental and not mandatorily used for parliamentary budgeting rules.
We should take a step back and look carefully at our process. Lazear’s three points could help advance our understanding of macroeconomic effects of legislation as a supplemental analysis and if properly applied to investments as well as revenues. That would require the economics profession to take a serious look at the effects of investment — and hopefully improve their analysis.
Sadly, that is not what will happen.