Category Archives: technology forecasting

climate change, technology forecasting

Links – early August, 2015

Well, I’m back, after deep dives into R programming and statistical modeling. I’d like to offer these links which I’ve bookmarked in recent days. The first four cover a scatter of topics, from impacts of the so-called sharing economy and climate developments to the currency impacts of the more and more certain moves by the US Federal Reserve to increase interest rates in September.

But then I’ve collected a number of useful links on robotics and artificial intelligence.

How the ‘sharing economy’ is upending the travel industry

DS: New York Attorney General Eric Schneiderman last October issued a report finding 72 percent of the reservations on Airbnb going back to 2010 were in violation of city law. What’s the industry doing to address these concerns?

MB: Listen, I think there are a lot of outdated regulations and a lot of outdated laws that were written in a time where you couldn’t possibly imagine the innovation that has come up from the sharing economy, and a lot of those need to be updated to meet the world that we live in today, and I think that’s important.  Sometimes you have regulations that are put in place by incumbent industries that didn’t want competition and you have some regulations that were put in place back in the ’60s and ’70s, where you couldn’t imagine any of these things, and so I think sometimes you need to see updates.

So there you go – laws on the books are outdated.

Brain-controlled prosthesis nearly as good as one-finger typing

The goal of all this research is to get thought-controlled prosthetics to people with ALS. Today these people may use an eye-tracking system to direct cursors or a “head mouse” that tracks the movement of the head. Both are fatiguing to use. Neither provides the natural and intuitive control of readings taken directly from the brain.

The U.S. Food and Drug Administration recently gave Shenoy’s team the green light to conduct a pilot clinical trial of their thought-controlled cursor on people with spinal cord injuries.

Jimmy Carter: The U.S. Is an “Oligarchy With Unlimited Political Bribery”

Unfortunately, very apt characterization from a formal standpoint of political science.

Carter

What to Expect from El Niño: North America

The only El Niño events in NOAA’s 1950-2015 database comparable in strength to the one now developing occurred in 1982-83 and 1997-98… Like other strong El Niño events, this one will almost certainly last just one winter. But at least for the coming wet season, it holds encouraging odds of well-above average precipitation for California. During a strong El Niño, the subtropical jet stream is energized across the southern U.S., while the polar jet stream tends to stay north of its usual winter position or else consolidate with the subtropical jet. This gives warm, wet Pacific systems a better chance to push northeast into California… Milder and drier a good bet for Pacific Northwest, Northern Plains, western Canada.. Rockies snowfall: The south usually wins out…Thanks to the jet-shifting effects noted above, snowfall tends to be below average in the Northern Rockies and above average in the Southern Rockies during strong El Niños. The north-south split extends to Colorado, where northern resorts such as Steamboat Springs typically lose out to areas like the San Juan and Sangre de Cristo ranges across the southern part of the state. Along the populous Front Range from Denver to Fort Collins, El Niño hikes the odds of a big snowstorm, especially in the spring and autumn. About half of Boulder’s 12” – 14” storms occur during El Niño, and the odds of a 20” or greater storm are quadrupled during El Niño as opposed to La Niña.

According to NOAA, the single most reliable El Niño outcome in the United States, occurring in more than 80% of El Niño events over the last century, is the tendency for wet wintertime conditions along and near the Gulf Coast, thanks to the juiced-up subtropical jet stream.

Emerging market currencies crash on Fed fears and China slump

The currencies of Brazil, Mexico, South Africa and Turkey have all crashed to multi-year lows as investors flee emerging markets and commodity prices crumble.

Robotics and Artificial Intelligence

Some of the most valuable research I’ve found so far on the job and societal impacts of robotics comes from a survey of experts conducted by the Pew Research Internet Project AI, Robotics, and the Future of Jobs,

Some 1,896 experts responded to the following question:

The economic impact of robotic advances and AI—Self-driving cars, intelligent digital agents that can act for you, and robots are advancing rapidly. Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?

Half of these experts (48%) envision a future in which robots and digital agents have displaced significant numbers of both blue- and white-collar workers—with many expressing concern that this will lead to vast increases in income inequality, masses of people who are effectively unemployable, and breakdowns in the social order.

The other half of the experts who responded to this survey (52%) expect that technology will not displace more jobs than it creates by 2025. To be sure, this group anticipates that many jobs currently performed by humans will be substantially taken over by robots or digital agents by 2025. But they have faith that human ingenuity will create new jobs, industries, and ways to make a living, just as it has been doing since the dawn of the Industrial Revolution.

Read this – the comments on both sides of this important question are trenchant, important.

The next most useful research comes from a 2011 publication of Brian Arthur in the McKinsey Quarterly The second economy – which is the part of the economy where machines transact just with other machines.

Something deep is going on with information technology, something that goes well beyond the use of computers, social media, and commerce on the Internet. Business processes that once took place among human beings are now being executed electronically. They are taking place in an unseen domain that is strictly digital. On the surface, this shift doesn’t seem particularly consequential—it’s almost something we take for granted. But I believe it is causing a revolution no less important and dramatic than that of the railroads. It is quietly creating a second economy, a digital one.

Twenty years ago, if you went into an airport you would walk up to a counter and present paper tickets to a human being. That person would register you on a computer, notify the flight you’d arrived, and check your luggage in. All this was done by humans. Today, you walk into an airport and look for a machine. You put in a frequent-flier card or credit card, and it takes just three or four seconds to get back a boarding pass, receipt, and luggage tag. What interests me is what happens in those three or four seconds. The moment the card goes in, you are starting a huge conversation conducted entirely among machines. Once your name is recognized, computers are checking your flight status with the airlines, your past travel history, your name with the TSA (and possibly also with the National Security Agency). They are checking your seat choice, your frequent-flier status, and your access to lounges. This unseen, underground conversation is happening among multiple servers talking to other servers, talking to satellites that are talking to computers (possibly in London, where you’re going), and checking with passport control, with foreign immigration, with ongoing connecting flights. And to make sure the aircraft’s weight distribution is fine, the machines are also starting to adjust the passenger count and seating according to whether the fuselage is loaded more heavily at the front or back.

These large and fairly complicated conversations that you’ve triggered occur entirely among things remotely talking to other things: servers, switches, routers, and other Internet and telecommunications devices, updating and shuttling information back and forth. All of this occurs in the few seconds it takes to get your boarding pass back. And even after that happens, if you could see these conversations as flashing lights, they’d still be flashing all over the country for some time, perhaps talking to the flight controllers—starting to say that the flight’s getting ready for departure and to prepare for that…

If I were to look for adjectives to describe this second economy, I’d say it is vast, silent, connected, unseen, and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on, and endlessly configurable. It is concurrent—a great computer expression—which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting, and self-healing…

If I were to look for adjectives to describe this second economy, I’d say it is vast, silent, connected, unseen, and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on, and endlessly configurable. It is concurrent—a great computer expression—which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting, and self-healing

I’m interested in how to measure the value of services produced in this “second economy.”

Finally, China’s adoption of robotics seems to signal something – as in this piece about a totally automatic factor for cell phone parts –

China sets up first unmanned factory; all processes are operated by robots

At the workshop of Changying Precision Technology Company in Dongguan, known as the “world factory”, which manufactures cell phone modules, 60 robot arms at 10 production lines polish the modules day .. The technical staff just sits at the computer and monitors through a central control system… In the plant, all the processes are operated by computer- controlled robots, computer numerical control machining equipment, unmanned transport trucks and automated warehouse equipment.

celebrity forecasters, cell phone data analytics, survey research and polls, technology forecasting

Links May 10, 2015

I start these Links with how the polls in the UK Election fell on their face and why. The cell phone is somewhat implicated, and, almost by association, I move onto the Internet of Everything (IoE), then to thoughts on how the Internet and artificial intelligence (AI) is shaping things.

It’s important to keep things loose and open on occasion, since the world itself doesn’t show tremendous closure, but is open, and evolving.

Election Poll Predictions In La-La Land

Nate Silver, the celebrity forecaster heading up FiveThirtyEight, had a big miss in calling the recent British Election (See What We Got Wrong In Our 2015 U.K. General Election Model and Nate Silver: Polls are failing us).

DavidCameron

A similar misfire happened in the recent Israeli elections, where Netanyuahu won by significant numbers in an election predicted to be neck-and-neck.

The cell phone may be partly to blame, as noted in British polling flop prompts global reassessments

..changes in communications are threatening the viability of public election polling in many developed countries where the landline phone was once a reliable medium for representative surveys.

This is going to be a big forecasting issue in the upcoming General Elections in the US.

The Internet of Everything (IoE)

From time to time, Cisco Systems produces projections and forecasts of Internet traffic volumes (presumably to some extent on its equipment). Now there is the Internet of Everything (IoE), a sort of expansion of the “internet of things.”

InternetOfEverything

Internet of Everything: A $4.6 Trillion Public-Sector Opportunity

Peter Diamandis writes,

..Imagine a world in which everything is connected and packed with sensors. 50+ billion connected devices, loaded with a dozen or more sensors, will create a trillion-sensor ecosystem. These devices will create what I call a state of perfect knowledge, where we’ll be able to know what we want, where we want, when we want. Combined with the power of data mining and machine learning, the value that you can create and the capabilities you will have as an individual and as a business will be extraordinary.

Here are some examples posted by Vincent Granville at Data Science Central.

◾Retail: Beyond knowing what you purchased, stores will monitor your eye gaze, knowing what you glanced at… what you picked up and considered, and put back on the shelf. Dynamic pricing will entice you to pick it up again.

◾City Traffic: Cars looking for parking cause 40% of traffic in city centers. Parking sensors will tell your car where to find an open spot.

◾Lighting: Streetlights and house lights will only turn on when you’re nearby.

…

◾Dynamic pricing: In the future, everything has dynamic pricing where supply and demand drives pricing. Uber already knows when demand is high, or when I’m stuck miles from my house, and can charge more as a result.

◾Transportation: Self-driving cars and IoE will make ALL traffic a thing of the past.

◾Healthcare: You will be the CEO of your own health. Wearables will be tracking your vitals constantly, allowing you and others to make better health decisions.

…

◾Forests: With connected sensors placed on trees, you can make urban forests healthier and better able to withstand — and even take advantage of — the effects of climate change.

◾Office Furniture: Software and sensors embedded in office furniture are being used to improve office productivity, ergonomics and employee health.

◾Invisibles: Forget wearables, the next big thing is sensor-based technology that you can’t see, whether they are in jewelry, attached to the skin like a bandage, or perhaps even embedded under the skin or inside the body. By 2017, 30% of wearables will be “unobtrusive to the naked eye,” according to market researcher Gartner.

Daniel Kraft, a physician, is a name to watch in this @Daniel_Kraft.

Impact of Artificial Intelligence (AI)

Generally, the under-the-radar spread of AI – in cell phone and tablet features such as Siri, or Google’s Now, which, incidentally, may be pulling ahead in terms of sheer accuracy – meets criteria of technology which can fundamentally change things.

It’s so easy to drive along and ask Siri for directions, or where a good restaurant is. And people focus on their cell phones in public places. There’s even the cartoon about a couple out on a date texting each other across the table.

The impact of technology on society has always been one of my favorite topics. For more than a decade, the Internet and emergent IT companies, have triggered huge, on-the-ground changes, possibly not all good. But the absorption of advertising revenues by Google has been dramatic, and a game-changer for newspapers and magazines (print technology). Online book sales put Borders Books out of business, and impacts book stores everywhere. The music business has changed forever, with singers and bands now almost wholly reliant on tours and real audiences for real revenue, with record and song sales contributing only minor funds to most.

I’d be interested in adding to this list, if readers have thoughts on this.

Big Data, disruptive innovation, technology forecasting

Peer-to-Peer Lending – Disruptive Innovation

Today, I chatted with Emmanuel Marot, CEO and Co-founder at LendingRobot.

We were talking about stock market forecasting, for the most part, but Marot’s peer to peer (P2P) lending venture is fascinating.

LRspread

According to Gilad Golan, another co-founder of LendingRobot, interviewed in GeekWire Startup Spotlight May of last year,

With over $4 billion in loans issued already, and about $500 million issued every month, the peer lending market is experiencing phenomenal growth. But that’s nothing compared to where it’s going. The market is doubling every nine months. Yet it is still only 0.2 percent of the overall consumer credit market today.

And, yes, P2P lending is definitely an option for folks with less-than-perfect credit.

In addition to lending to persons with credit scores lower than currently acceptable to banks (700 or so), P2P lending can offer lower interest rates and larger loans, because of lower overhead costs and other efficiencies.

LendIt USA is scheduled for April 13-15, 2015 in New York City, and features luminaries such as Lawrence Summers, former head of the US Treasury, as well as executives in some leading P2P lending companies (only a selection shown).

Speakers

Lending Club and OnDeck went public last year and boast valuations of $9.5 and $1.5 billion, respectively.

Topics at the Lendit USA Conference include:

◾ State of the Industry: Today and Beyond

◾ Lending to Small Business

◾ Buy Now! Pay Later! – Purchase Finance meets P2P

◾ Working Capital for Companies through invoice financing

◾ Real Estate Investing: Equity, Debt and In-Between

◾ Big Money Talks: the institutional investor panel

◾ Around the World in 40 minutes: the Global Lending Landscape

◾ The Giant Overseas: Chinese P2P Lending

◾ The Support Network: Service Providers for a Healthy Ecosystem

Peer-to-peer lending is small in comparison to the conventional banking sector, but has the potential to significantly disrupt conventional banking with its marble pillars, spacious empty floors, and often somewhat decorative bank officers.

By eliminating the need for traditional banks, P2P lending is designed to improve efficiency and unnecessary frictions in the lending and borrowing processes. P2P lending has been recognised as being successful in reducing the time it takes to process these transactions as compared to the traditional banking sector, and also in many cases costs are reduced to borrowers. Furthermore in the current extremely low interest-rate environment that we are facing across the globe, P2P lending provides investors with easy access to alternative venues for their capital so that their returns may be boosted significantly by the much higher rates of return available on the P2P projects on offer. The P2P lending and investing business is therefore disrupting, albeit moderately for the moment, the traditional banking sector at its very core.

Peer-to-Peer Lending—Disruption for the Banking Sector?

Top photo of LendingRobot team from GeekWire.

innovation research, technology forecasting

Some Thoughts for Monday

There’s a kind of principle in invention and innovation which goes like this – often the originator of new ideas and approaches is a kind of outsider, stumbling on a discovery by pursuing avenues others thought, through training, would be fruitless. Or at least this innovator pursues a line of research outside of the mainstream – where accolades are being awarded.

You can make too much of this, but it does have wide applicability.

In science, for example, it’s the guy from the out-of-the-way school, who makes the important discovery, then gets recruited to the big time. I recall reading about the migration of young academics from lesser schools to major institutions – Berkeley and the Ivy League – after an important book or discovery.

And, really, a lot of information technology (IT) was launched by college drop-outs, such as the estimable Mr. Bill Gates, or the late Steve Jobs.

This is a happy observation in a way, because it means the drumbeat of bad news from, say, the Ukrainian or Syrian fronts, or insight such as in Satjajit Das’ The Sum of All Our Fears! The Outlook for 2015, is not the whole story. There are “sideways movements” of change which can occur, precisely because they are not obvious to mainstream observers.

Without innovation, our goose is cooked.

I’m going to write more on innovation this week, detailing some of my more recent financial and stock market research under that heading.

But for now, let me comment on  the “libertarian” edge that accompanies a lot of innovation, these days.

The new new peer-to-peer (P2P) “sharing” or social access services provide great examples.

Uber, Lyft, Airbnb – these companies provide access to rides, vehicles, and accommodations. They rely on bidirectional rating systems, background checks, frictionless payment systems, and platforms that encourage buyers and sellers to get to know each other face-to-face before doing business. With venture funding from Wall Street and Silicon Valley, their valuations rise a dramatic way. Uber’s valuation has risen to an estimated $40 billion, making it one of the 150 biggest companies in the world–larger than Delta, FedEx or Viacom. Airbnb coordinates lodging for an estimated 425,000 persons a night, and has an estimated valuation of $13.5 billion, almost half as much as 96-year-old Hilton Worldwide.

There are increased calls for regulation of these companies, as they bite into markets dominated by the traditional hotel and hospitality sector, or taxi-cab companies. Clearly, raising hundreds of millions in venture capital can impart hubris to top management, as in the mad threats coming from a Uber executive against journalists who report, for example, sexual harassment of female customers by Uber drivers.

Noone should attempt to stop the push-and-pull of regulation and disruptive technology, however. Innovations in P2P platforms, pioneered by eBay, pave the way for cultural and institutional innovation. At the same time, I feel better about accepting a ride within the Uber system, if I know the driver is insured and has a safe vehicle.

predictive analytics, technology forecasting, telecommunications forecasting

Modeling High Tech – the Demand for Communications Services

A colleague was kind enough to provide me with a copy of –

Demand for Communications Services – Insights and Perspectives, Essays in Honor of Lester D. Taylor, Alleman, NíShúilleabháin, and Rappoport, editors, Springer 2014

Some essays in this Festschrift for Lester Taylor are particularly relevant, since they deal directly with forecasting the disarray caused by disruptive technologies in IT markets and companies.

Thus, Mohsen Hamoudia in “Forecasting the Demand for Business Communications Services” observes about the telecom space that

“..convergence of IT and telecommunications market has created more complex behavior of market participants. Customers expect new product offerings to coincide with these emerging needs fostered by their growth and globalization. Enterprises require more integrated solutions for security, mobility, hosting, new added-value services, outsourcing and voice over internet protocol (VoiP). This changing landscape has led to the decline of traditional product markets for telecommunications operators.

In this shifting landscape, it is nothing less than heroic to discriminate “demand variables” and “ independent variables” deploying and produce useful demand forecasts from three stage least squares (3SLS) models, as does Mohsen Hamoudia in his analysis of BCS.

Here is Hamoudia’s schematic of supply and demand in the BCS space, as of a 2012 update.

BCS

Other cutting-edge contributions, dealing with shifting priorities of consumers, faced with new communications technologies and services, include, “Forecasting Video Cord-Cutting: The Bypass of Traditional Pay Television” and “Residential Demand for Wireless Telephony.”

Festschrift and Elasticities

This Springer Festschrift is distinctive inasmuch as Professor Taylor himself contributes papers – one a reminiscence titled “Fifty Years of Studying Economics.”

Taylor, of course, is known for his work in the statistical analysis of empirical demand functions and broke ground with two books, Telecommunications Demand: A Survey and Critique (1980) and Telecommunications Demand in Theory and Practice (1994).

Accordingly, forecasting and analysis of communications and high tech are a major focus of several essays in the book.

Elasticities are an important focus of statistical demand analysis. They flow nicely from double logarithmic or log-log demand specifications – since, then, elasticities are constant. In a simple linear demand specification, of course, the price elasticity varies across the range of prices and demand, which complicates testimony before public commissions, to say the least.

So it is interesting, in this regard, that Professor Taylor is still active in modeling, contributing to his own Festschrift with a note on translating logs of negative numbers to polar coordinates and the complex plane.

“Pricing and Maximizing Profits Within Corporations” captures the flavor of a telecom regulatory era which is fast receding behind us. The authors, Levy and Tardiff, write that,

During the time in which he was finishing the update, Professor Taylor participated in one of the most hotly debated telecommunications demand elasticity issues of the early 1990’s: how price-sensitive were short-distance toll calls (then called intraLATA long-distance calls)? The answer to that question would determine the extent to which the California state regulator reduced long-distance prices (and increased other prices, such as basic local service prices) in a “revenue-neutral” fashion.

Followup Workshop

Research in this volume provides a good lead-up to a forthcoming International Institute of Forecasters (IIF) workshop – the 2nd ICT and Innovation Forecasting Workshop to be held this coming May in Paris.

The dynamic, ever changing nature of the Information & Communications Technology (ICT) Industry is a challenge for business planners and forecasters. The rise of Twitter and the sudden demise of Blackberry are dramatic examples of the uncertainties of the industry; these events clearly demonstrate how radically the environment can change. Similarly, predicting demand, market penetration, new markets, and the impact of new innovations in the ICT sector offer a challenge to businesses and policymakers. This Workshop will focus on forecasting new services and innovation in this sector as well as the theory and practice of forecasting in the sector (Telcos, IT providers, OTTs, manufacturers). For more information on venue, organizers and registration, Download brochure

Chinese economy, energy forecasting, population forecasts, technology forecasting

Links – February 2015

I buy into the “hedgehog/fox” story, when it comes to forecasting. So you have to be dedicated to the numbers, but still cast a wide net. Here are some fun stories, relevant facts, positive developments, and concerns – first Links post for 2015.

Cool Facts and Projections

How the world’s population has changed – we all need to keep track of this, 9.6 billion souls by 2050, Nigeria’s population outstrips US.

worldpop

What does the world eat for breakfast?

Follow a Real New York Taxi’s Daily Slog 30 Days, 30 random cabbie journeys based on actual location data

Information Technology

Could Microsoft’s HoloLens Be The Real Deal?

MSHolo

I’ll Be Back: The Return of Artificial Intelligence

BloomAI

Issues

Why tomorrow’s technology needs a regulatory revolution Fascinating article. References genome sequencing and frontier biotech, such as,

Jennifer Doudna, for instance, is at the forefront of one of the most exciting biomedical advances in living memory: engineering the genomes not of plants, but of people. Her cheap and easy Crispr technology holds out the promise that anybody with a gene defect could get that problem fixed, on an individual, bespoke basis. No more one-size-fits all disease cures: everything can now be personalized. The dystopian potential here, of course, is obvious: while Doudna’s name isn’t Frankenstein, you can be sure that if and when her science gains widespread adoption, the parallels will be hammered home ad nauseam.

Doudna is particularly interesting because she doesn’t dismiss fearmongers as anti-science trolls. While she has a certain amount of control over what her own labs do, her scientific breakthrough is in the public domain, now, and already more than 700 papers have been published in the past two years on various aspects of genome engineering. In one high-profile example, a team of researchers found a way of using Doudna’s breakthrough to efficiently and predictably cause lung cancer in mice.

There is more on Doudna’ Innovative Genomics Initiative here, but the initially linked article on the need for regulatory breakthrough goes on to make some interesting observations about Uber and Airbnb, both of which have thrived by ignoring regulations in various cities, or even flagrantly breaking the law.

China

Is China Preparing for Currency War? Provocative header for Bloomberg piece with some real nuggets, such as,

Any significant drop in the yuan would prompt Japan to unleash another quantitative-easing blitz. The same goes for South Korea, whose exports are already hurting. Singapore might feel compelled to expand upon last week’s move to weaken its dollar. Before long, officials in Bangkok, Hanoi, Jakarta, Manila, Taipei and even Latin America might act to protect their economies’ competitiveness…

There’s obvious danger in so many economies engaging in this race to the bottom. It will create unprecedented levels of volatility in markets and set in motion flows of hot money that overwhelm developing economies, inflating asset bubbles and pushing down bond rates irrationally low. Consider that Germany’s 10-year debt yields briefly fell below Japan’s (they’re both now in the 0.35 percent to 0.36 percent range). In a world in which the Bank of Japan, the European Central Bank and the Federal Reserve are running competing QE programs, the task of pricing risk can get mighty fuzzy.

Early Look: Deflation Clouds Loom Over China’s Economy

The [Chinese] consumer-price index, a main gauge of inflation, likely rose only 0.9% from a year earlier, according to a median forecast of 13 economists surveyed by the Wall Street Journal

China’s Air Pollution: The Tipping Point

Chinapollution

Energy and Renewables

Good News About How America Uses Energy A lot more solar and renewables, increasing energy efficiency – all probably contributors to the Saudi move to push oil prices back to historic lows, wean consumers from green energy and conservation.

Nuclear will die. Solar will live Companion piece to the above. Noah Smith curates Noahpinion, one of the best and quirkiest economics blogs out there. Here’s Smith on the reason nuclear is toast (in his opinion) –

There are three basic reasons conventional nuclear is dead: cost, safety risk, and obsolescence risk. These factors all interact.            

First, cost. Unlike solar, which can be installed in small or large batches, a nuclear plant requires an absolutely huge investment. A single nuclear plant can cost on the order of $10 billion U.S. That is a big chunk of change to plunk down on one plant. Only very large companies, like General Electric or Hitachi, can afford to make that kind of investment, and it often relies on huge loans from governments or from giant megabanks. Where solar is being installed by nimble, gritty entrepreneurs, nuclear is still forced to follow the gigantic corporatist model of the 1950s.

Second, safety risk. In 1945, the U.S. military used nuclear weapons to destroy Hiroshima and Nagasaki, but a decade later, these were thriving, bustling cities again. Contrast that with Fukushima, site of the 2011 Japanese nuclear meltdown, where whole towns are still abandoned. Or look at Chernobyl, almost three decades after its meltdown. It will be many decades before anyone lives in those places again. Nuclear accidents are very rare, but they are also very catastrophic – if one happens, you lose an entire geographical region to human habitation.

Finally, there is the risk of obsolescence. Uranium fission is a mature technology – its costs are not going to change much in the future. Alternatives, like solar, are young technologies – the continued staggering drops in the cost of solar prove it. So if you plunk down $10 billion to build a nuclear plant, thinking that solar is too expensive to compete, the situation can easily reverse in a couple of years, before you’ve recouped your massive fixed costs.

Owners of the wind Greenpeace blog post on Denmark’s extraordinary and successful embrace of wind power.

What’s driving the price of oil down? Econbrowser is always a good read on energy topics, and this post is no exception. Demand factors tend to be downplayed in favor of stories about Saudi production quotas.

Chinese economy, financial forecasting, stock market forecasts, technology forecasting

Links – Beginning of the Holiday Season

Economy and Trade

Asia and Global Production Networks—Implications for Trade, Incomes and Economic Vulnerability Important new book –

The publication has two broad themes. The first is national economies’ heightened exposure to adverse shocks (natural disasters, political disputes, recessions) elsewhere in the world as a result of greater integration and interdependence. The second theme is focused on the evolution of global value chains at the firm level and how this will affect competitiveness in Asia. It also traces the past and future development of production sharing in Asia.

Chapter 1 features the following dynamite graphic – (click to enlarge)

GVC2009

The Return of Currency Wars

Nouriel Roubini –

Central banks in China, South Korea, Taiwan, Singapore, and Thailand, fearful of losing competitiveness relative to Japan, are easing their own monetary policies – or will soon ease more. The European Central Bank and the central banks of Switzerland, Sweden, Norway, and a few Central European countries are likely to embrace quantitative easing or use other unconventional policies to prevent their currencies from appreciating.

All of this will lead to a strengthening of the US dollar, as growth in the United States is picking up and the Federal Reserve has signaled that it will begin raising interest rates next year. But, if global growth remains weak and the dollar becomes too strong, even the Fed may decide to raise interest rates later and more slowly to avoid excessive dollar appreciation.

The cause of the latest currency turmoil is clear: In an environment of private and public deleveraging from high debts, monetary policy has become the only available tool to boost demand and growth. Fiscal austerity has exacerbated the impact of deleveraging by exerting a direct and indirect drag on growth. Lower public spending reduces aggregate demand, while declining transfers and higher taxes reduce disposable income and thus private consumption.

Financial Markets

The 15 Most Valuable Startups in the World

Uber is among the top, raising $2.5 billion in direct investment funds since 2009. Airbnb, Dropbox, and many others.

The Stock Market Bull Who Got 2014 Right Just Published This Fantastic Presentation I especially like the “Mayan Temple” effect, viz

MayanTemple

Why Gold & Oil Are Trading So Differently supply and demand – worth watching to keep primed on the key issues.

Technology

10 Astonishing Technologies On The Horizon – Some of these are pretty far-out, like teleportation which is now just gleam in the eye of quantum physicists, but some in the list are in prototype – like flying cars. Read more at Digital Journal entry on Business Insider.

  1. Flexible and bendable smartphones
  2. Smart jewelry
  3. “Invisible” computers
  4. Virtual shopping
  5. Teleportation
  6. Interplanetary Internet
  7. Flying cars
  8. Grow human organs
  9. Prosthetic eyes
  10. Electronic tattoos

Albert Einstein’s Entire Collection of Papers, Letters is Now Online

Princeton University Press makes this available.

AEinstein

Practice Your French Comprehension

Olivier Grisel, Software Engineer, Inria – broad overview of machine learning technologies. Helps me that the slides are in English.

Big Data, energy forecasting, technology forecasting

Big Data and Fracking

Texas’ Barnett Shale, shown below, is the focus of recent Big Data analytics conducted by the Texas Bureau of Economic Geology.

BarnettShale

The results provide, among other things, forecasts of when natural gas production from this field will peak – suggesting at current prices that peak production may already have been reached.

The Barnett Shale study examines production data from all individual wells drilled 1995-2010 in this shale play in the Fort Worth basin – altogether more than 15,000 wells.

Well-by-well analysis leads to segmentation of natural gas and liquid production potential in 10 productivity tiers, which are then used to forecast future production.

Decline curves, such as the following, are developed for each of these productivity tiers. The per-well production decline curves were found to be inversely proportional to the square root of time for the first 8-10 years of well life, followed by exponential decline as what the geologists call “interfracture interference” began to affect production.

TierDCurves

A write-up of the Barnett Shale study by its lead researchers is available to the public in two parts at the following URL’s:

http://www.beg.utexas.edu/info/docs/OGJ_SFSGAS_pt1.pdf

http://www.beg.utexas.edu/info/docs/OGJ_SFSGAS_pt2.pdf

Econometric analysis of well production, based on porosity and a range of other geologic and well parameters is contained in a followup report Panel Analysis of Well Production History in the Barnett Shale conducted under the auspices of Rice University.

Natural Gas Production Forecasts

Among the most amazing conclusions for me are the predictions regarding total natural gas production at various prices, shown below.

Barnetshalecurvelater

This results from a forecast of field development (drilling) which involved a period of backcasting 2011-2012 to calibrate the BEG economic and production forecast models.

Essentially, it this low price regime continues through 2015, there is a high likelihood we will see declining production in the Barnett field as a whole.

Of course, there are other major fields – the Bakken, the Marcellus, the Eagle-Ford, and a host of smaller, newer fields.

But the Barnett Shale study provides good parameters for estimating EUR (estimate ultimate recovery) in these other fields, as well as time profiles of production at various prices.

energy forecasting, technology forecasting

Forecasting Shale Oil/Gas Decline Rates

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Forecasting and data analytics increasingly are recognized as valued partners in nonconventional oil and gas production.

Fracking and US Oil/Gas Production

“Video Friday” here presented a YouTube with Brian Ellis – a Michigan University engineer – discussing hydraulic fracturing and horizontal drilling (“fracking”).

USannualoilprod

Fracking produced the hockey stick at the end of this series.

These new technologies also are responsible for a bonanza of natural gas, so much that it often has nowhere to go – given the limited pipeline infrastructure and LNG processing facilities.

shalegasprod

Rapid Decline Curves for Fracking Oil and Gas

In contrast to conventional wells, hydraulic fracturing and horizontal drilling (“fracking”) produces oil and gas wells with rapid decline curves.

Here’s an illustration from the Penn State Department of Energy and Mineral Engineering site,

Pennstatedeclinecurve

The two legends at the bottom refer to EUR’s– estimated ultimate recovery times (click to enlarge).

Conventional oil fields typically have decline rates on the order of 5 percent per year.

Shale oil and gas wells, on the other hand, may produce 50 percent or more of their total EUR in their first year of operation.

There are physical science fundamentals behind this, explained, for example, in

Decline and depletion rates of oil production: a comprehensive investigation

You can talk, for example, of shale production being characterized by a Transient Flow Period followed by Boundary Dominated Flow (BDF).

And these rapid decline rates have received a lot of recent attention in the media:

Could The ‘Shale Oil Miracle’ Be Just A Pipe Dream?

Wells That Fizzle Are a ‘Potential Show Stopper’ for the Shale Boom

Is the U.S. Shale Boom Going Bust?

Forecasting and Data Analytics

One forecasting problem in this context, therefore, is simply to take histories from wells and forecast their EUR’s.

Increasingly, software solutions are applying automatic fitting methods to well data to derive decline curves and other shale oil and gas field parameters.

Here is an interesting product called Value Navigator.

This whole subject is developing rapidly, and huge changes in the US industry are expected, if oil and gas prices continue below $60 a barrel and $4 MMBtu.

The forecasting problem may shift from well and oil field optimization to evaluation of the wider consequences of recent funding of the shale oil and gas boom. But, again, the analytics are available to do this, to a large extent, and I want to post up some of what I have discovered in this regard.