3Q 2011 GDP – not as good as we thought

This morning the BEA released its third (what we used to call the “final”) estimate of 3Q GDP. The bad news is that economic growth is not as strong as earlier thought (and even that was moderate). The first estimate was a growth rate of 2.5% — not earth shattering, but not bad. The second estimate was 2.9% and this third estimate is down to 1.8%. Ominously, the primary reason for the latest downward revision: lower consumer spending.

Mapping economic complexity

Earlier this year, Ricardo Hausmann, César Hidalgo and others at the Center for International Development at the Kennedy School at Harvard released a report Atlas of Economic Complexity. [See also a story in the New York Times Magazine earlier this year on The Art of Economic Complexity and their technical paper – “The Building Blocks of Economic Complexity” from the Proceedings of the National Academy of Sciences, June 30, 2009.]
This study looks at a nation’s economic structure and prosperity from an output base — as opposed to most other studies of competitiveness which look at inputs (i.e. years of education, R&D spending, etc.). Their concept of Economic Complexity is two-fold. First, it measures what they call the product complexity of a particular industry (based on its output). Crude oil production ranks the lowest while specialized machinery ranks the highest. Note: which crude oil is not a very “complex” product, lubricating petrol oils is the 4th highest in complexity. In this way they attempt to measure the knowledge intensiveness of any particular product. They then combines a country’ portfolio of products to get an overall indication of how advanced the economy is. Countries that make complex products, a greater variety of them and products that no one else can make score higher on their Economic Complexity Index (ECI):

According to our measures, Japan and Germany are the two countries with the highest levels of economic complexity. Ask yourself the question: If a good cannot be produced in Japan or Germany, where else can it be made? That list of countries is likely to be a very short one, indicating that Japan and Germany are complex economies. Now take an opposite example: if a product cannot be made in Mauritania or Sudan, where else can it be made? For most products this is likely to be a long list of countries, indicating that Sudan and Mauritania are among the world’s least complex economies.

They argue that “economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy.” It is the social accumulation of productive knowledge.

Most modern products require more knowledge than what a single person can hold. Nobody in this world, not even the saviest geek nor the most knowledgeable entrepreneur knows how to make a computer. He has to rely on others who know about battery technology, liquid crystals, microprocessor design, software development, metallurgy, milling, lean manufacturing and human resource management, among many other skills. That is why the average worker in a rich country works in a firm that is much larger and more connected than firms in poor countries. For a society to operate at a high level of total productive knowledge, individuals must know different things. Diversity of productive knowledge, however, is not enough. In order to put knowledge into productive use, societies need to reassemble these distributed bits through teams, organizations and markets.
Accumulating productive knowledge is difficult. For the most part, it is not available in books or on the Internet. It is embedded in brains and human networks. It is tacit and hard to transmit and acquire. It comes from years of experience more than from years of schooling. Productive knowledge, therefore, cannot be learned easily like a song or a poem. It requires structural changes. Just like learning a language requires changes in the structure of the brain, developing a new industry requires changes in the patterns of interaction inside an organization or society.
Expanding the amount of productive knowledge available in a country involves enlarging the set of activities that the country is able to do. This process, however, is tricky. Industries cannot exist if the requisite productive knowledge is absent, yet accumulating bits of productive knowledge will make little sense in places where the industries that require it are not present. This “chicken and egg” problem slows down the accumulation of productive knowledge. It also creates important path dependencies. It is easier for countries to move into industries that mostly reuse what they already know, since these industries require adding modest amounts of productive knowledge. By gradually adding new knowledge to what they already know, countries economize on the chicken and egg problem. That is why we find empirically that countries move from the products that they already create to others that are “close by” in terms of the productive knowledge that they require.

As they stress, much of this knowledge is tactic and relational:

For example, to make a shirt you need to design it, procure the fabric, cut it, sew it, pack it, brand it, market it and distribute it. In a firm that manufactures shirts, expertise in each of these knowledge chunks will be held by different people. And shirts require all of them. Moreover, you need to finance the operation, hire the relevant people, coordinate all the activities and negotiate everybody’s buy-in, which in itself require different kinds of knowhow. We can say that putting together this operation requires know-who and know-where. Know-who can be thought of as knowledge of who has the requisite chunks of knowledge, and know-where as knowledge of where the people and organizations that have this knowledge are located. To make shirts, you can import the fabric and access the knowledge about looms and threading that is embedded in a piece of cloth. Yet some of the knowledge required cannot be accessed through shipped inputs. The people with the relevant knowledge must be near the place where shirts are made.

Why does this matter? Because countries with more complex economies grow faster and become richer — since, as the previous explanation indicates, they have a competitive advantage. The key here is “become” — since countries with abundant natural resources (e.g. oil) can be rich but not have the capacity for economic growth. As they state, “economic complexity is not just a symptom or an expression of prosperity: it is a driver.”

The ability of the ECI to predict future economic growth suggests that countries tend to move towards an income level that is compatible with their overall level of embedded knowhow. On average, their income tends to reflect their embedded knowledge. But when it does not, it gets corrected through accelerated or diminished growth.
. . .
In short, economic complexity matters because it helps explain differences in the level of income of countries, and more important, because it predicts future economic growth. Economic complexity might not be simple to accomplish, but the countries that do achieve it, tend to reap important rewards.

How do countries develop?

countries expand their productive knowledge by moving into nearby goods. This increases the likelihood that the effort to accumulate any additional capability will be successful, as the complementary capabilities needed to make a new product are more likely to be present in the production of the nearby goods.

The more capabilities a country has over a range of products, the easier it is for that country to move into new products — or, as I would argue, create new products. While the authors don’t explicitly discuss innovation, their findings of the importance of economic complexity for innovation are clear.
I should note that the U.S. is right on the trend line – meaning its income level reflects it knowledge base. The correlation is slightly less when looking at the rate of growth — not just overall income. However, the U.S. has had a slower rate of growth between 1998 and 2008 than its Economic Complexity Index in 1998 would have indicated. Based on this analysis, they expect the U.S. to have an annual growth rate of about 2% in GDP per capita between 2009 and 2020 and an overall GDP growth rate of 2.84% (based on our 2008 level of economic complexity).
Unfortunately, the America’s Economic Complexity Index score has declined since 1964 — and especially in the past decade. It was 1.78 in 1964. Dipped to 1.35 by 1978. Rose again to 1.81 in 1998. Then dropped to 1.45 in 2008. The change between 1964 and 2008 was a decline of .33. Between 1998 and 2008, the drop was .36. This reinforces what others have been saying about the last 10 years being more of a lost decade. As such, the U.S. ranks 13th (as of 2008). By comparison, Japan has a 2008 ECI of 2.3 and Germany’s ECI in 2008 was 1.985.
What is missing from the analysis is the linkage back to policy. The report is silent on what the best policies are to develop the capabilities needed to expand their productive knowledge beyond what they already have or would gain from moving into nearby product. I’m sure as the data is reviewed more widely, policy prescriptions will emerge. Something I hope to look into myself in the new year.

R&D spending – a shift in pharma

According the a story in the Wall Street Journal (based on the latest Battelle Memorial Institute survey), global R&D spending will continue to increase in 2012 — with a noteworthy exception:

One exception is the pharmaceutical industry, which has planned big R&D cuts. The report notes, for example, that Pfizer Corp. has announced plans to reduce its overall R&D budget from $9.4 billion in 2010 to between $8.1 billion and $8.4 billion this year. In 2012, the company plans to spend $6.5 billion on R&D.
“The retrenchment of pharma’s conventional model has created significant R&D opportunities for universities, nonprofits and the government,” the Battelle report said.

I wonder if that is really an opportunity — or if we are seeing the breakdown of the drug research enterprise? In other words — is this a shift in the model or is the R&D effort aimed a new drug components becoming less productive overall? If the latter, will we see a shift in health care research to a new non-pharmaceutically based paradigm?
Just some question – I don’t have an answer.

Tales from globalization — an Apple example

Two connected news stories about Apple this morning.
First comes word from Reuters that Apple is now sourcing its A5 processor for the iPad 2 and the iPhone 4S from Samsung’s new plant in Austin, Texas. The second story is from the Wall Street Journal that Apple the iPhone is selling well in China but is facing stiffer competition — including from fakes. It appears from the story that Apple is getting over 16% of its revenues from China and Taiwan.
So Apple is in the position of buying components from Texas to put into produces sold in China. That is an interesting turn around of the standard globalization story.

SBIR reauthorization

After much debate and doubt, Congress has reauthorized the Small Business Innovation Research (SBIR) program. The reauthorization came as part of the last minute deal on the defense authorization bill. The folks over at SBIR Insider have the some of the details, including the entire 107 page section of the bill. For those of you who don’t know about the program, SBIR is a technology development and commercialization program focused on small businesses. The program requires certain Federal agencies to allocate 2.5% percent of their R&D budget to small business grants.
Bottom line: an important technology program will continue.

New manufacturing reports — and focusing our efforts

A couple of new reports on manufacturing. Make: An American Manufacturing Movement from the Council on Competitiveness and 2011 Next Generation Manufacturing Study from the Manufacturing Performance Institute. The former looks at a number of economic and technology policies — such as taxation, regulation, immigration, training etc. The latter focuses on the business level with a scorecard as to how we are doing on six key Next Generation Manufacturing (NGM) strategies: process improvement, customer-focused innovation, human-capital management, supply chain management, sustainability, and global engagement. Given both the state-of-play in manufacturing (see earlier postings) and the state of policy making in Washington, I think the company level focus is more productive activity.
In that regard, the Next Generation Manufacturing Study holds out some hope and points the way to the challenges. The good news is that companies understand the issues. The bad news is that they are having trouble implementing solutions. For example:

82% of manufactures have business systems and equipment to support “current requirements” for customer-focused innovation (the highest percentage among any of the six strategies) — but only a small percentage of manufacturers describe their tools as “state-of-the-art,” capable of providing long-term support for this or other NGM strategies.

The study shows that companies are attempting to change this and are reaching out to external partners for help — including the Manufacturing Extension Partnership (MEP). [BTW – the only mention of the MEP in the Make report is to say that MEP should help companies use computer simulation and modeling tools.]
So in a time of limited resources, let’s focus on providing that help and creating the tools the companies need to succeed. Here is my basic roadmap: Start with a major expansion of the MEP budget and tool key (to include innovation and management of intangible assets). Move on to more manufacturing oriented train (as advocated in the Make report. And then craft a full blown manufacturing strategy to creates a high-valued added industry that both exports and provides a robust supply chain for domestic production.
Manufacturing is undergoing a transformation. By focusing on how to foster that transformation we can create a more health and balanced economy.

Tech transfer — what is the goal?

Here is why I am beginning to think that our university technology transfer system is offtrack — Top 20 U.S. technology transfer programs by 2010 license income. Based on this metric the goal of university research is to maximize university licensing revenues. Wrong, wrong wrong. Where are the metrics about the number of spin-off companies, the jobs created, the knowledge transferred? Universities are knowledge creation factories. I realize that they need to figure out how to get paid for their products. But the system of maximizing licensing revenues is not the way to create the university of the 21st Century.

Reviving manufacturing – update

On Monday the White House announced that Commerce Secretary John Bryson would join National Economic Council Director Gene Sperling as co-chairs of the White House Office of Manufacturing Policy to push for implementation of the Administration’s manufacturing initiative. Part of that announcement stressed the announcement stressed the SBA’s work to increase access to capital for small and medium size manufacturers. Let me suggestion a few other actions — based on the fact that manufacturing is, like the rest of the economy, becoming a knowledge intensive activity (taken from our Policy Brief–Intellectual Capital and Revitalizing Manufacturing):
Expand the Manufacturing Extension Partnership (MEP) to Boost Intellectual Capital. The Administration’s A Framework for Revitalizing American Manufacturing appropriately calls for doubling the MEP budget, but the scope of this assistance to manufacturers needs to be expanded to include innovation, new product development, and utilization of intellectual capital. Manufacturing companies have a wealth of intellectual capital that they often do not recognize or manage well. MEP services must include intellectual resource management that covers a broad array of assets, beyond help with intellectual property. The program’s budget increase should be used to expand services and staffing in areas such as marketing, finance, and business model development, in addition to new product development and process adoption.
Help Entrepreneurs Manage Intellectual Capital. The Framework specifically cites efforts by the U.S. Small Business Administration (SBA) to provide entrepreneurship training and to foster partnerships with community colleges, universities, and others. It also mentions the U.S. Economic Development Administration (EDA) program of supporting business incubators. But most of these training programs do not explicitly recognize the importance of managing intangible assets and intellectual capital. Programs that support entrepreneurs need to incorporate these topics as part of their activities and impart these essential skills to would-be innovators.
Increase Worker Training. The Framework rightly calls for increasing federal funding for job training. However, the current system is geared toward assisting workers who have lost their jobs. Just as vital is support for on-the-job training so that workers are able to bolster their current skills, which enhances the competitive edge of employers and improves workers’ viability in the marketplace. The important of on-the-job training is heightened in an economic downturn, when companies can easily lose their built-up supply of intellectual capital by laying off workers who may eventually find employment elsewhere.
Funding for on-the-job training could take a number of forms:
•   Direct government funding of training programs, possibly run through the community colleges (as also mentioned in the Framework).
•   A knowledge tax credit to cover employer costs. We already give tax incentives for investments in research and development (R&D) and in machinery. We should also give tax incentives for investments in workers.
•   In a “job-sharing” program. Proposals have been made for a national job-sharing program, where workers would reduce the number of hours worked from full time to part time; for example, from 40 hours to 35 hours a week. The wages saved by the employer would be use to hire additional workers and unemployment insurance funds would be used to pay workers for hours not worked as part of the program. On-the-job training could be included in such programs by requiring workers to spend that time in a training program.
Use IP to Provide Capital. As noted in the Framework, the administration is taking steps to increase the flow of capital to small businesses. Currently, small businesses can raise money based on their physical and financial assets, which can be easily bought and sold, borrowed against, and used to back other financial instruments. But using intangible assets, such as IP, to borrow funds is difficult. Here are some ways the government can free up this type of capital to unleash small business creation, innovation, and growth:
•   Tap SBA loans to fund innovation. SBA underwriting rules should be changed to allow companies to use their IP as collateral on loans. SBA already allows its loan funds to be used to buy intangibles when a new owner wants to acquire a company. Allowing IP to be used as collateral will increase the amount of funds a company, such as one in the high-tech sector, would qualify for.
•   Create an IP-backed loan fund. Other nations have developed special programs to encourage IP-based finance. The U.S. should set up similar programs on a pilot basis, ideally run by the SBA to take advantage of its lending expertise. Technical support could be provided by the SBA’s Office of Technology, which already coordinates the Small Business Innovation Research (SBIR) program. The SBA technology office also works with the U.S. Commerce Department’s National Institute of Standards and Technology (NIST) on its Technology Innovation Program and has a hand in other federal science- and technology-related initiatives. Such a direct lending program would be a step beyond SBA’s current loan guarantee programs–direct lending is needed to jumpstart the process. Once the process of utilizing IP as collateral is fully established, the program could be converted to a loan guarantee structure.
Include Intellectual Capital and Intangible Assets in the Financial Regulatory System. The Framework explicitly points out that financial regulatory reform is necessary to create an environment of stability to promote economic growth and innovation. Yet intellectual capital and intangible assets remain outside of the discussion on financial reform, even though they represent between one-half and two-thirds of aggregate company value. The following methods could be used to bring these assets into the financial regulatory system:
•   Increase disclosure of intangible assets. The U.S. Securities and Exchange Commission (SEC) should be directed to study the barriers to intangible asset disclosure on corporate financial statements; assess past disclosure requirements, such as the 2003 guidance on the Management’s Discussion and Analysis (MD&A) section in financial statements; and analyze the merits of a safe harbor for limited disclosure of financial information on intangibles not currently allowed in financial statements. In addition, the relevant federal agencies–the SEC and the departments of Treasury and Commerce–should establish an advisory committee to recommend ways to provide investors with an improved method of assessing the impact intangibles have on the accuracy of a company’s financial picture and for supporting industry trade associations’ efforts to adopt intellectual asset management and intangible disclosure guidelines for particular industries.
•  Provide information on intellectual capital and bank lending practices. The U.S. Federal Reserve is seeking to strengthen bank supervision practices through the expansion of stress testing to assess the health of individual institutions. As bank regulators undertake these actions, they should be aware of the role and value of intangible assets. The failure to overtly include intangible assets may have the following consequences:
  •  Underestimation in the amount of collateral a lending institution has to call on in case of default (and therefore the undervaluation of the underlying loan).
  •  Miscalculation of a lending institution’s ability to recapture collateral if the lending institution is dealing with an asset it does not understand.
  •  Improperly priced loans due to a failure to assign the correct value to the intangible assets or a tendency to apply exceedingly low loan-to-value ratios that are less a reflection of risk than of the institution’s lack of knowledge about the performance of intangible assets.
  •  Higher capital costs for borrowers, especially those in businesses heavily reliant on knowledge and technology.
Regulatory agencies can take steps to study and collect information on the role of intangibles in the financial system–and to underscore the risks of ignoring them. As they build knowledge in this area, the Federal Reserve and other financial regulatory agencies might consider the following questions:
  •  To what extent are lending institutions employing intangible asset as collateral, either explicitly or implicitly?
  •  What provisions are there in bank reporting requirements for intangibles?
  •  Given that intangible assets can be wrapped up in the catch-all category of a blanket lien on all assets, how can lending institutions determine the value of intangible assets for the purposes of assessing collateral?
  •  If intangibles are used explicitly as collateral, what underwriting standards are used and what are the specific valuation standards and loan-to-value ratios?
Promote Better Understanding of Intellectual Capital and Intangible Assets. The Framework mentions intellectual capital using the example of patents and managerial know-how. Yet, as noted earlier, intellectual capital and intangible assets cover a much broader range of categories, including worker skills and knowledge, business methods, organizational structure, and customer relations. There is a need to broaden the understanding of policymakers, business leaders, and the general public on the full scope of intellectual capital and intangible assets and how they function in the marketplace. There are a few ways to widen the scope of knowledge around this subject:
Commission a National Academies’ study on intangibles. This was proposed at a June 2008 conference sponsored by the Bureau of Economic Analysis and the National Academies. A broad study of intangibles could include the following components:
  •  A survey of efforts in other countries to advance the understanding of intangibles and their role in corporate performance and economic growth, promote financial investments in intangible assets, and foster the utilization of intangibles.
  •  An inventory of federally owned intangible assets and an exploration of how to exploit them for economic growth.
  •  A list of policy recommendations to accelerate private investment in and management of the types of intangible assets most likely to contribute to growth.
Manage the government’s intangible assets more effectively. The federal government is a major investor in intangibles, but we don’t have a clear picture of the size or nature of that investment across the agencies. The U.S. Office of Management and Budget (OMB) should build on the current federal budgeting process to engage in a cross-cutting analysis of federal investments in intangible assets. For some time the federal budget, as prepared by the Office of Management and Budget (OMB), has included a capital budget that includes physical capital, R&D, and education and training. The budget documents also include a separate analysis of statistical agencies’ funding, which is not included in the investment budget. These and other budget studies already undertaken by OMB can serve as the starting point for a wide-ranging budgetary analysis of federal investments in intangible assets.

Spectrum deals analyzed

In a couple of previous postings, I pointed to the possibility that spectrum licenses for wireless applications are the next intangible asset to heat up — following the mini-boom in patent valuations. Over at the blog The Deal Advisor, they provide a detailed analysis of the deals and ask the question: Is a Spectrum License Land Grab in the Offing?

It’s potentially the beginning of a real land grab for spectrum licenses; those who ‘have’ will benefit from the major projected increase in mobile broadband use, and those who ‘have not’ could well be left behind. Those who ‘have and sell’ might earn a nice return today, but that leaves open the question of how to participate in the coming hockey stick growth pattern. The good news is that it seems much of the long dormant AWS spectrum is going to emerge from its cocoon, providing options for ILEC license holders.

I would note that the same dynamic is pushing both patents and spectrum: the fight to control the future of wireless. So while intangible assets in this area are heating up, it is unclear whether other intangibles in other areas will benefit from the attention. Clearly companies are taking another look at their patent portfolios. It is up to those of us who understand the importance of intangibles to use this opportunity to educate others.