Second estimate of 1Q 2015 GDP and worrisome R&D data

As expected, the second estimate of 1st quarter GDP from BEA shows the economy actually declined by 0.7% (rather than rising by 0.2% as earlier estimated – see earlier posting). Part of the revision was a downgrading of investments in intellectual property products (IPP) – which grew by only 3.6% as opposed to 7.8% in the earlier estimate. The biggest revisions was that R&D investment was almost flat in the 1st quarter — up by only 1.1% instead of the 12.3% growth estimated earlier. Given that today’s estimate is based on the latest R&D data, this is a very worrisome trend.
Of course, this figure could get revised again next month. Stay tuned.
IPP parts 1Q15 - 2nd.png

Senator Hirono (D-HI) gets it

Earlier this month, Senator Mazie K. Hirono (D-HI) introduced S.1262: The Small Business Start-up Savings Accounts Act of 2015. The bill would allow entrepreneurs to establish a business savings account similar to an individual retirement account to pay for start-up expenses. Qualified distributions explicitly include “purchase of equipment or facilities, marketing, training, incorporation, and accounting fees.” In other words, the intangible investments needed to start and grow a business.
This is one of the few pieces of legislation that explicitly includes such intangibles. Senator Hirono clearly gets it.
(See also her press release)

Productivity, growth and intangible capital: a short history lesson

Earlier this year, Andrew Haldane, Chief Economist at the Bank of England, gave a fascinating speech on “Growing, fast and slow.” In it he succinctly sums up the history of economic growth. As he notes, “If the history of growth were a 24-hour clock, 99% would have come in the last 20 seconds.” Given that economic growth is a very new phenomenon, he goes on to look at where growth comes from. Specifically, he outlines the difference between the Neo-Classical exogenous growth model (where innovation is an outside random factor – “manna from heaven”) and the “New Growth Theory” endogenous growth model (where innovation is a function of internal factors). [See my paper on Technology and Economic Growth: A Review for Policymakers for a somewhat dated discussion of exogenous versus endogenous growth theories.]
The Neo-Classical model sees the Industrial Revolution as sparked by successive waves of general purpose technologies (GPTs):

During the first industrial revolution, these GPTs included the steam engine, cotton spinning and railways; during the second, electricity, the internal combustion engine and internal water supply and sanitation; and in the third, the personal computer and the internet.

The endogenous capitals model takes a more complex view. As Haldane says, “On this interpretation, sociological transformation supported, perhaps preceded, technological transformation.”
What I found of great interest was how Haldane ties the endogenous theory to the intangible capital model:

The factors driving growth [in the endogenous model] are multiple, not singular. They are as much sociological as technological – skills and education, culture and cooperation, institutions and infrastructure. These factors are mutually-supporting, not exogenous and idiosyncratic. And they build in a cumulative, evolutionary fashion, rather than spontaneously combusting.
One way of accommodating these broader factors is to widen the definition of “capital”: physical capital (such as plant and machinery); human capital (such as skills and expertise); social capital (such as cooperation and trust); intellectual capital (such as ideas and technologies); and infrastructural capital (such as transport networks and legal systems). Growth results from the cumulative accretion of multiple sources of capital.
To take a simple example, the success of the railways relied not just on the invention of the steam engine (intellectual capital), but on the materials (physical capital) and skills (human capital) to build locomotives and track. And to become a GPT, railways needed in addition a network (infrastructure capital) and the cooperation and trust of the general public (social capital).

He uses the “capitals” model to provide what he calls a sociological view of the rapid economic growth in during the Industrial Revolution.
The first driver of faster economic growth was the development of human capital. Sometime in the 16th Century literacy rates began to dramatically rise, providing a human capital foundation for innovation process that fueled the Industrial Revolution. Education levels also rose continuing the accumulation of human capital (both widening and deepening) needed to keep the innovation process moving.
The second driver was an increase in social capital:

Violent crime fell dramatically between the 15th and 18th centuries, by a factor of around five. By the time of the Industrial Revolution, it had levelled-off.

This helped support the trust and co-operation that facilitate commerce and economic growth.
Likewise institutional and infrastructure capital developed earlier provided a foundation for future growth:

England was the birth place of the Industrial Revolution. Its parents, arguably, were English institutions well into adolescence at the dawn of the Industrial Revolution: a parliamentary system from the 11th and 12th centuries; a legal and judicial system from the 12th and 13th centuries; a central bank, the Bank of England, from the end of 17th century.

Finally, the innovation during the Industrial Revolution was built on the existing stock of intellectual capital:

From the windmill in the 12th century, the mechanical clock in the 13th, the cannon in the 14th, the printing press in the 15th, the postal service in the 16th and the telescope and microscope in the 17th, the innovation escalator was in service well before the Industrial Revolution, albeit stepped and sticky.

All of this historical analysis becomes especially important when Haldane turns his attention to the current debate over economic growth. He characterizes this as secular innovation versus secular stagnation. The Neo-Classical model, he argues, leads one to an optimist secular innovation point of view. He sees a new wave of GPTs re-igniting growth:

it is only recently that the digital revolution may have reached critical velocity. Perhaps consistent with that, a number of transformative technologies have arrived on the scene recently, including in the fields of robotics, genetics, 3D printing, Big Data and the “internet of things”. These are not new. What is new is their widening application, as they have moved from inventions to GPTs.

On the other hand, the endogenous capitals model points out the headwinds that leads to a more pessimistic secular stagnation view. Inequality is eroding both social and human capital (see also my earlier postings). As Haldane notes, “Inequality may retard growth because it damps investment in education, in particular by poorer households.” Lower levels of education and social trust and cohesion are a recipe for lower growth. Levels of investment in infrastructure capital are also eroding (which may be, I would argue, another result of the decline in social capital due to inequality leading to a lower willingness to invest in projects for the common good).
Other factor eroding the intangible capitals is increased short-termism and impatience. Haldane argues that social patience has been a key ingredient in economic growth:

In the run-up to the Industrial Revolution, society became more willing to wait than in the past. That, in turn, enabled saving, investment and ultimately growth. Patience was a virtue.

The reasons he gives for this shift are multiple. One is rising incomes:

During the Malthusian era, much of the population operated at close to subsistence income levels. If experimental evidence is any guide, that is likely to have generated an acute sense of societal short-termism. This may have manifested itself in, for example, a failure to invest in physical and human capital, retarding growth. Poverty and impatience would have been self-reinforcing, in a Malthusian poverty trap.
The raising of incomes above subsistence levels which occurred after 1800 will have reversed that cycle. It will have boosted patience and laid the foundations for higher saving and investment and, ultimately, growth. In other words, after the Industrial Revolution patience may have created its own virtuous reward, endogenous growth style.

Another is the technology itself:

Technological innovation has also been found to influence patience. The invention of the printing press by Guttenberg in around 1450 led to an explosion in book production. It is estimated that there were more books produced in the 50 years after Guttenberg than in the preceding 1000 years. What followed was much more than a technological transformation.
Books contributed to a great leap forward in literacy levels, boosting human capital. More speculatively, they may also have re-wired our brains. Nicholas Carr argues that the changes brought about by the printing press, and other information media, may have re-shaped our minds. Books laid the foundations for “deep reading” and, through that, deeper and wider thinking. Technology was, quite literally, mind-bending.
It has been argued that this re-wiring stimulated the slow-thinking, reflective, patient part of the brain identified by psychologists such as Daniel Kahneman. If so, it will have supported the accumulation of intellectual capital – creativity, ideas, innovation. Technology will have first shaped neurology and then neurology technology, in a virtuous loop. Slow thought will have made for fast growth.

He worries that technology might now be undermining patience resulting in slow growth:

We are clearly in the midst of an information revolution, with close to 99% of the entire stock of information ever created having been generated this century. This has had real benefits. But it may also have had cognitive costs. One of those potential costs is shorter attention spans. As information theorist Herbert Simon said, an information-rich society may be attention-poor. The information revolution could lead to patience wearing thin.
Some societal trends are consistent with that. The tenure of jobs and relationships is declining. The average tenure of Premiership football managers has fallen by one month per year since 1994. On those trends, it will fall below one season by 2020. And what is true of football is true of finance. Average holding periods of assets have fallen tenfold since 1950. The rising incidence of attention deficit disorders, and the rising prominence of Twitter, may be further evidence of shortening attention spans.
If so, that would tend to make for shorter-term decision-making. Using Daniel Kahneman’s classification, it may cause the fast-thinking, reflexive, impatient part of the brain to expand its influence. If so, that would tend to raise societal levels of impatience and slow the accumulation of all types of capital. This could harm medium-term growth. Fast thought could make for slow growth.

As much as I like Haldane’s analysis using the endogenous capitals model, I have to argue with his conclusions. Specifically I disagree with the conclusion that the endogenous capitals model leads to a pessimistic secular stagnation view while the Neo-Classical exogenous models supports an optimistic secular innovation view.
First, much of the argument of the techno-pessimists is grounded in the Neo-Classical exogenous growth model. Their entire point is that the manna has stopped falling. The low hanging fruit has been picked, to paraphrase Tyler Cowen. [In fairness to Cowen he does include human capital – in the form of education – as one of the factors powering past growth.]
Second, the capitals model provides as much a direction as it does a forecast. By laying out the factors that foster economic growth, the endogenous capitals model provides a blueprint for what needs to be done (for example see my posting on the State of the Union). Human capital can be strengthened though both formal education and informal training based on the principle of live-long learning. Social capital can be improved through various means. Institutional and infrastructure capital can be re-built. Intellectual capital can be expanded, in part by recognizing that the model of innovation has shifted.
More importantly, the endogenous capitals model indicates that something can be done. As Haldane says of the Industrial Revolution, “Innovation was an earthly creation, not manna from heaven.” Our task is to continues that creation.

The intangible capital case for equality

Last week, the Brooking Institution held a symposium on the 40th anniversary of Arthur Okun’s classic essay Equality and Efficiency: The Big Tradeoff (see also Brad DeLong’s posting on the event). While the event celebrated Okun’s economic insights, the speakers debated the relevance of the essay’s central argument. Many pointed out that the context of 1975 is very different than today. One of the speakers, Heather Boushey, went as far as to state (in her blog) that

Rereading Okun in 2015, however, feels about as relevant to my work as an economist as does reading Hilary Mantel’s “Wolf Hall,” about 16th century Britain. Both are interesting and enjoyable swings through the historical past-and I highly recommend them-but neither should be used as a roadmap for today’s policymakers.

Robert Samuelson echoed this theme in his look at the traditional argument for an equality/efficiency trade off in the Washington Post (Poof goes the big tradeoff). Even the keynote speaker, Larry Summers, while praising the book made this point:

In my forward to the reprinting of Equality and Efficiency I describe the major changes in the economy, and speculate about what Art would be recommending if he were with us today. Rather than reprising that discussion here, let me conclude by noting how in areas relating to equity and efficiency my thinking has changed in response to a changing economy over the last 40 years. This is not I believe because my values have changed but is rather because of changes in the economy and our understanding of it.

One of the ways that the economy (and our understanding of it) has changed is the nature of work. The speakers touched on this
lightly, mostly in the context of new technology and the role of education. I would argue that there is a fundamental difference in how we view the workforce compared with 40 years ago.
In 1975, standard view of labor was a mind-hand split. Most workers were “doers” (physical labor) not “thinkers.” This is the classic Taylorist vision of the economy. It even translates into the “post-industrial” vision of the economy which highlighted the leading role of the knowledge class and the centrality of formalized knowledge. The “thinkers” contribute more to economic growth and need to be groomed (through elite education) and valued (paid more). They need to be rewarded for the risks they take, otherwise they would not take those risks. The result is this group of risk takers are rewarded more — i.e. unequally. The natural result is some level of inequality.
We have since come to understand the importance of the “doer” class. It turns out that the human capital of those other workers is huge. Both tacit and experiential knowledge, not just codified and science-based knowledge, are important. A decade ago, I noted in a posting that the changing nature of the economy made tacit knowledge more important:

The ability to innovate and to “design a compelling experience” are the important intangible assets. Routine activities — no matter how technically sophisticated or important — will gravitate to the cheapest workforce or be automated. Key to non-routine activities is a person’s tacit knowledge as well as problem solving abilities.

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. In other words, we need all forms of intangible capital for economic growth.
As I’ve noted in earlier postings, inequality undermines the development of various forms of intangible capital that are needed to sustain economic growth. Inequality undermines human capital development by limiting education and the ability of all to contribute. Inequality undercuts strategic capital by weakening opportunity for entrepreneurship. It destroys relationship capital by undermining trust. Finally, inequality undercuts social capital through political instability and uncertainly.
Thus, let us acknowledge to contributions of great scholars such as Arthur Okun. But let us also understand how their work fits into the context of today. In this case, we need to understand the new relationship between equality and growth. Otherwise, we are trapped on Keynes’ famous warning about being “slaves of some defunct economist.”

April employment in tangible and intangible industries

April’s employment data from BLS shows steady growth of 223,000 job with the unemployment rate ticking down slightly to 5.4%. This is about what economists had forecast (an increase of 228,000 jobs).
Employment in tangible producing industries grew by 106,000 in March led by growth in Accommodation & Food Service, Tangible Business Services and Tangible Education & Health Services. Intangible producing industries added 116,000 jobs with most of that gain in Professional & Business Services and Educational & Health Services. (See tables below.)
As the charts below shows, U.S. employment in tangible producing industries and intangible producing industries is just about equal. Up until March, employment in tangible producing industries had been growing slightly faster than in intangible producing industries.
For more background on this data, see my earlier posting.
Apr 2015 tangible & intangible employment.png
Apr 2015 parts.png
Apr 2015 pie.png

No, its not a "services" index

Contrary to what you will read in the press this morning, the Institute of Supply Management (ISM) did not release data this morning on a services index. ISM publishes a manufacturing report and indices and a non-manufacturing report and indices. They are very careful to call the non-manufacturing report as “non-manufacturing”, not “services.” That is because the non-manufacturing report contains more than service industries:

• Agriculture, Forestry, Fishing & Hunting
• Mining
• Construction Educational Services
• Wholesale Trade
• Retail Trade
• Transportation & Warehousing
• Utilities
• Arts, Entertainment & Recreation
• Accommodation & Food Services
• Real Estate, Rental & Leasing
• Management of Companies & Support Services
• Finance & Insurance
• Information
• Health Care & Social Assistance
• Public Administration
• Professional Scientific & Technical Services
• Other Services

Thus, while the index contain service industries, it also covers important non-service and non-manufacturing industries such as agriculture and construction. That is a part of the story that the press misses when it call this a “service” index.
So the next time you read a story about the “services” index remember what it really is. You might also ruminate on how we need a better set of descriptors for this new Information-Innovation-Intangibles (I-Cubed) Economy. “Non-manufacturing” just doesn’t do it. Unfortunately, it plays into and reinforces the outdated and simplistic notion that the economy is divided manufacturing and services. (See my earlier postings on tangible versus intangible producing industries and on the fusion of manufacturing and services.)
By the way, the latest index for April shows the composite index for non-manufacturing rose by 1.3 percentage points to 57.8 percent in April. This indicates continued growth. However, growth was not even:

The 14 non-manufacturing industries reporting growth in April — listed in order — are: Arts, Entertainment & Recreation; Real Estate, Rental & Leasing; Management of Companies & Support Services; Transportation & Warehousing; Wholesale Trade; Finance & Insurance; Utilities; Health Care & Social Assistance; Agriculture, Forestry, Fishing & Hunting; Public Administration; Retail Trade; Accommodation & Food Services; Construction; and Educational Services. The four industries reporting contraction in April are: Mining; Other Services; Professional, Scientific & Technical Services; and Information.

March trade in intangibles

The U.S. trade deficit took a big jump in March, according to the latest data from the BEA. The March deficit rose by $15.5 billion to $51.4 billion. February’s revised deficit was $35.9 billion. March imports surged by $17.1 billion while exports were up only $1.6 billion. Economist had expected the deficit to rise by $5.8 billion to $41.7 billion.
Even a drop in the deficit in oil and petroleum products was not enough to counter the surge in the non-petroleum products deficit. As the chart below shows, our deficit in petroleum products continues to improve. But the March deficit in non-petroleum goods fell through the floor.
In large part, the increase in the deficit was due to an import surge as a result of the re-opening of the west coast posts after a dock strike. However, the weakness in exports is also troublesome.
The increased deficit means that the weak GDP numbers for the 1st quarter of 2015 are likely to come in even worse in the next estimate.
One small silver lining is that our surplus in pure intangibles rose sightly as exports grew more than imports. The surpluses in maintenance & repair services and continued to grow with exports up more than imports. The surplus in financial services also grew in March after declining in February with both exports and imports up. The deficit in insurance services improved slightly, as did the very small surplus in telecommunications services. The surplus in business services continued to grow a long string of declines last year. However, net revenues from the use of intellectual property dropped slightly as revenues from foreign sources (exports) were up but charges for the use of intellectual property paid out to foreign sources (imports) increased more.
Unfortunately, our Advanced Technology deficit followed the same course as for goods in general by almost doubling. The deficit grew by $3.2 billion to reach $6.3 billion. The biggest change in the deficit came from a surge of almost $4.5 billion in Information and Communications Technology (ICT). That surge was only partial offset by a $1 billion rise in ICT exports and a $2 billion increase in aerospace exports.
Advanced Technology goods also represent trade in intangibles. These goods are competitive because their value is based on knowledge and other intangibles. While not a perfect measure, Advanced Technology goods serve as an approximation of our trade in embedded intangibles. Adding the pure and embedded intangibles shows an overall surplus of $8.7 billion in compared with $11.8 billion in February. Again, much of this was due to the higher ICT imports.
Intangibles trade-Mar15.png
Intangibles trade parts-Mar15.png
Intangibles and goods-Mar15.png
Oil goods intangibles-Mar15.png

Note: I am now reporting the trade data using the new BEA classifications for services trade, which breaks services into more categories. In the past, the intangible trade data was the sum of Royalties and License Fees and Other Private Services. Under the new classification system, intangibles trade data is the sum of the following items: maintenance and repair services n.i.e. (not included elsewhere); insurance services; financial services; charges for the use of intellectual property n.i.e.; telecommunications, computer, and information services; other business services.

Charges for the use of intellectual property n.i.e. is simply a renaming of Royalties and License Fees. This includes transactions with foreign residents involving intangible assets and proprietary rights, such as the use of patents, techniques, processes, formulas, designs, know-how, trademarks, copyrights, franchises, and manufacturing rights.

Maintenance and repair services n.i.e., financial services, and insurance services, were previously included in Other Private Services. Telecommunications, computer, and information services is a combination of those two items (telecommunications and computer & information services) that were also previously included in Other Private Services. Three categories previously in Other Private Services — education-related and health-related travel and the expenditures on goods and services by border, seasonal, and other short-term workers — were removed and reclassified to travel. The new category of other business services is a continuation of the older category Other Private Services with those components removed.

Thus, other business services includes categories such as advertising services; research, development, and testing services; management, consulting, and public relations services; legal services; construction, engineering, architectural, and mining services; and industrial engineering services. It also includes personal, cultural, and recreational services which includes fees related to the production of motion pictures, radio and television programs, and musical recordings; payments or receipts for renting audiovisual and related products, downloaded recordings and manuscripts; telemedicine; online education; and receipts or payments for cultural, sporting, and performing arts activities.

For more information on the changes, see the March 2014 Survey of Current Business article, “The Comprehensive Restructuring of the International Economic Accounts: Changes in Definitions, Classifications, and Presentations.”

New policies needed on data access and ownership

Last week, David Brailer published an op-ed in the Wall Street Journal warning of the problems with access to health information (see “They’re Your Vital Signs, Not Your Medical Records” – subscription required). He points out that the problem goes beyond third party access; individuals don’t necessarily have access to their own data. As he says, “You can’t force a covered entity to give your data to someone you choose, and you can’t stop them from giving it to someone they choose.”
The problem is called “health information blocking.” Brailer explains that companies “unreasonably withhold health information to gain an edge over competitors and make it difficult for customers and patients to switch to other providers. These companies also want revenue that comes from using health information for drug research, targeted marketing and other efforts.” He points to a recent “Report on Health Information Blocking” from the Office of the National Coordinator for Health Information Technology (ONC) at HHS which highlights the need for Congressional action.
As problematic as this is (and it is very problematic), is just part of a larger issue. As the subtitle of the WSJ piece says, “Americans don’t own their own health information.” Delete the word “health” and the larger issue becomes clear.
Back in 2011 I posted a piece on “Who owns your data”. In the piece I reported on what appeared to be a new consensus emerging that people should be paid for access to their personal information (for example, see the WSJ story published back then on The Market for Online Privacy Heats Up). I also noted the World Economic Forum’s Initiative on Rethinking Personal Data. I was especially excited by their report Personal Data: The Emergence of a New Asset Class). that report argued that:

Increasing the control that individuals have over the manner in which their personal data is collected, managed and shared will spur a host of new services and applications. As some put it, personal data will be the new “oil” – a valuable resource of the 21st century. It will emerge as a new asset class touching all aspects of society.

Unfortunately, enthusiasm for the idea of data as a personal asset seems to have died down in the intervening years. The most recent report from the WEF are about trust and privacy.
But issues of trust/privacy and of access/ownership are the proverbial two sides of the same coin. As I have argued before, in our report Information Age: Reframing the Debate,

we currently treat privacy, computer security, intellectual property rights, freedom of information, “right-to-know” policies and free speech issues as separate policy areas. Yet, they are all part of managing the information commons: what information is and should be private, what information is and should be proprietary and what information is and should be public. A more comprehensive approach is needed.

We see this fragmented approach played out in the ongoing debate over health records (as I’ve noted in 2009 and again in 2011). There continues to be a number of issues all jumbled up in the debate, including whether sold data would be used to discriminate and whether the data can be used to send marketing and our promotional materials. The emphasis in the debate seems to be on the right of the collector to collect and sell that data versus the patient’s privacy rights. The health care industry argues that excessive privacy restrictions would drive up administrative costs and stifle innovation. Privacy advocates argue that the industry simply wants to protect its profit stream. The latest issue of health information blockage adds a new twist to the debate–which may bring us back to the ownership issue.
What Congress and the Administration do (if anything) about health information blockage could provide a spark for a look at a more broader set of laws and regulation governing information. Likewise, crafting health information policy might learn from other areas, such as credit and other financial information, as to how sensitive information is handled.
But crafting a broader information policy also needs to be sensitive to the different uses of the information in different areas. The value of data (public versus private) is tied to its use. The public value of anonymous medical data for research purposes is incalculable. It seems to me that such data should be publicly available – with strong anonymity safeguards and no patient opt-out provision (just like Census data or data provided to financial regulators). Policy issues to be addressed include whether (and how much) such data could be sold and manipulated as a private information service–and what share should go to individual patient. Policies on private value-added to publicly available government collected data are already in place for other types of data.
Data that is used for improved customer services, such as flagging drug interaction problems, is also valuable. Here, a strict usage provision might be in order, i.e. cannot be shared with outside providers without permission. An opt-out provision might be in order for data used strictly for customer service. But if the data is going to a proprietary database (such as for marketing purposes, then an opt-in provision with a standard “royalty” rate applied.
Bottom line: information policy continues to be fragmented into sector silos (e.g. health information, financial information, economic & trade data, personal “sociological” data). Policymakers need to view all these areas as interrelated, with a common core set of principles applied to each specific circumstance. Addressing the health information blocking issue might be a way into a discussion of the larger principles.
Thanks to Jon Low at The LowDown blog for highlighting this.

More on those "trade" agreements

Earlier this week, I posted a piece on ““Why trade agreements are so difficult.” In it I argued that these agreements are so difficult to negotiate because they are no longer about trade but about economic harmonization. As such they require parties to agree on economic policy, not simply on reducing tariffs. That is made even more difficult because there is often internal domestic disagreement over policy within a nation. One side or the other may try to use an international agreement to lock in its view of what domestic policy should be.
An illustration of this dynamic recently popped up over at AEI’s Tech Policy Daily blog. Tom Sydnor wrote a piece on “Why exporting fair use through TPP is a bad idea.” That was followed by Markham Erickson’s (General Counsel to the Internet Association) response “Promoting US copyright law in trade agreements is a good idea.” While Sydnor makes a case on the problem of harmonizing differing legal systems, their disagreement is less about trade agreements and more about where they stand on copyright law. For example, Sydnor worries about how other nations would enforce an internationalized version of our Communications Decency Act (CDA), which he call “a vague, ambiguous statute.” Erickson argues that, “The protections of Section 230 [of the CDA] are important because they encourage online commerce by providing uniformity and certainty for websites, web hosts, and online businesses that they will not be held liable for the unlawful activities of their users.”
It will be interesting to see how this battle plays out. In any event, in the end it will be a decision about the internationalization of U.S. law. That is a very different place than where the trade agreement process started from in the post WWII era.