Category Archives: Innovation

… Writing & Technology

In a past life, I had a job as a Credit Analytics consultant with Ernst & Young. I whipped up more than my fair share of spreadsheets and coded up a few SAS analyses here and there for the banks I worked with. However, the most important part of my work was the documents I wrote. Distilled into one sentence, my job as a consultant was to synthesize analytical work into model validation reports and model methodology documentation. At one bank I wrote over 500 pages of text, and over my more than two years with EY I produced more than 1,000 pages of analytical documentation.

However, my true love for writing and a passion for technology both blossomed while I was a Volunteer in the Peace Corps.

Writing seems like something that naturally goes with Peace Corps service. Volunteers have tons of meaningful experiences and tons of time for reflection. That lends itself to writing. I did plenty of writing, mostly on my two blogs, both of which I continue writing on to this day. However, technology is more of a non-sequitur with Peace Corps service. I did not have much access to technology, so how did I become so interested in it?


Me being Nicaraguan

Along with time to write, Peace Corps service gave me a lot of time to read. I had to tell my mom to stop sending me links to articles. I had inevitably already read them. I read most of the NY Times on a daily basis, and my parents got me a digital subscription to The Economist. I also devoured much of Wired, and whatever else popped up around the internet and on my Facebook feed.

Digesting all of this information led me to realize that technology could go a long way to solve many of the problems that Nicaragua and other lesser-developed countries around the world face. Even more so than ‘technology,’ which is a word typically associated with something tangible or engineered, there is a thirst for innovation in lesser-developed countries. New ideas, new ways of doing things, and connecting disparate ideas to come up with novel solutions to problems can all be used to solve the problems of international development. Even a staid and old idea in one culture might be embraced as new and promising in another.

When I completed my Peace Corps service I entered business school intent on learning about global business, operations management, entrepreneurship, and technology and innovation.

Midway through business school, during the height of my summer internship with UPS, I felt confident that I had the skills to try to tackle some of the problems I encountered in Nicaragua. I founded a startup in July 2017 called ChickenBus. It is a socially minded tech startup dedicated to improving access to public transportation in lesser developed countries. The MVP is under development, and I hope to ship in Q1 2018.

Read the continuation here on my other blog, Incidents of Travel


… One-to-Many

Think back forty years to how businesses used to operate and grow. Someone would cook up a good idea for a product. A company would be formed around that idea to manufacturer it, warehouse it, and then distribute it. Supporting these functions were a sales, marketing, and finance workforce. If you invented something, you then had to get machinery to manufacture it and hire a sales force to get it into the hands of customers. There were few other options.

Since then, businesses have evolved considerably. If someone has a good idea for a product they design it and market it. That’s it. Manufacturing is outsourced, often offshore. Sales are facilitated through e-commerce marketplaces. Fewer and fewer companies are bothering to have their very own websites, let alone a brick-and-mortar store. Logistics are handled by third-party logistics providers. Going asset-lite is the way to go. That lets you rapidly scale scale scale if you want to.

The other side of the coin is the companies that are providing all of these support functions. Since they have to own the assets – whether they be warehouses, vehicles, servers, machines, or financial capital, they have an incentive to be very large companies. Scale is their friend. In fact, it is imperative for success.

What has emerged is a dumbbell economy: On one side, you have many small weights that all add up to a hefty load of economic activity. There is a bar connecting these weights to the other side, which is comprised of a few heavy weights. Summed together, the few heavy weights equal the weight of the smaller weights on the other side, but there are far fewer heavy weights than there are small ones.

The dumbbell economy can be best illustrated through these two graphs. While companies with 1,000 or more employees make up just 0.21% of all companies in the United States, nearly 40% of all privately employed workers in the United States work for one of these companies.


I’m not the only person to have made this observation about the shape of the economy. The Economist reported on it in 2016. Deutsche Bank also wrote a report on the matter.

In this dumbbell economy, the few heavy weights represent large service corporations that provide services and other knowledge-economy goods to other companies. These include Microsoft, Dell, IBM, Amazon, the Big 4 accounting firms, UPS and FedEx, Google, Maersk, Delta, Caterpillar, John Deere, and The many smaller weights represent small and medium businesses. These include mom and pops and specialty stores, but they are not only brick and mortar. Growing online brands, artists, and many other private companies are on the lightweight side of the economic dumbbell. To complete the metaphor, the bar connecting the two sides of weights represents infrastructure. Roads, airports, cables, and public utilities, which are essential for commerce to be able to function. Government is the arm that curls the dumbbell and makes it move. If the government is not exercising then iron won’t get pumped – the economy will not function properly and grow.

The heavyweight companies invest in assets and then sell them as a service to the lightweights. Without the heavyweights, the lightweights would not be able to grow as fast and expand their reach as wide. The most successful heavyweights are those that are most valuable to the lightweights. Those that can help the smaller, growing companies the most while pinching the lightweights’ bank accounts the least will find themselves with the most demand, as well as investors willing to provide cash to allow them to invest and grow.

While the dumbbell is a useful analogy to understand this phenomenon, I think that it is most appropriate to call this one-to-many. One company can support activity for many others.

It may be best to provide a hypothetical example. For the sake of illustrating my point, I will bold all of the heavyweight companies that I mention in my narrative:

Imagine that I am an engineer, and with the assistance of Autodesk design software I invent a great new device that I want to start selling. I’ve drummed up a lot of support for my nascent product by creating an Instagram account for the device, but I do not have any capital to start production, so I start a crowdfunding campaign on Indiegogo. I raise enough money to begin production, and I hire a contract manufacturer in Asia to begin batch producing the device. I pay FedEx as my freight forwarder to get the batches from Asia to the United States, where I will offer the device for sale. My primary sales channel is, although I store the units in my home and ship them upon receiving an order using UPS and the US Postal Service.

I do have a website which is hosted by It’s basically just a landing page for people who find the device through Indiegogo. It forwards them to the Amazon product page so they can make purchases. However, as sales continue to grow, I continue to design, and support grows for my ideas, I raise some additional money from a venture capital firm. With this money, I hire some employees, and we move into an old industrial area in my city that has been repurposed as a business campus. It’s perfect for my small business that needs a lot of space for industrial design work.

As we launch new products and have a steadier flow of inventory crossing the ocean from Asia, we make a concerted effort to strengthen our brand and diversify our sales channels away from We build out our website and hire a third-party logistics provider to warehouse our inventory. We want to be able to take orders online and receive payments so we pay for some third-party software plugins and also work with Paypal. We also use some third-party digital marketing software services and pay for adds on websites like Google and Facebook.

The beauty of the one-to-many economy is that it allows new ideas for products and services to be born, grow, and be distributed to consumers who find them appealing and valuable. The problem, some may say, is that we continue to feed the “heavyweights” and cede more and more economic power to them as a result.

One-to-many supports a vast number of growing small and medium businesses, but it also necessitates the existence of a few large third-party providers – the heavyweights. Many people dislike the control of these large companies. In the wake of Amazon’s acquisition of Whole Foods some people said that there were anti-trust concerns. Goldman Sachs has been described as rather tentacular. The EU just slammed Google with a multi-billion Euro fine.

“[Goldman Sachs is a] great vampire squid wrapped around the face of humanity, relentlessly jamming its blood funnel into anything that smells like money.”Matt Taibbi, “The Great American Bubble Machine,” Rolling Stone, July 9-23, 2009

To ease some of the discomfort that we have with the heavyweights having more and more control over the economy, we have to think about ways that we can leverage the one-to-many economy to nurture the economic activity that we most value. Use the heavyweights to make the lightweights as attractive as possible.

What exactly are the elements of capitalism that we value, particularly in the United States?

  • Creativity and art
  • Entrepreneurship (and equality of opportunity)
  • Diversity and inclusion
  • Equality
  • Innovation
  • Distribution of income and wealth
  • Family business
  • Sustainability
  • Poverty alleviation

The heavyweights need to proactively ensure that they are not hindering the attainment of any of these values. They may also go a long way in earning widespread public support if they are proactively supporting these values. Aligning themselves with these values may also strengthen their businesses. However, just creating a foundation and donating to community causes is not enough when it comes to the heavyweights. Their core business functions need to keep these values in mind.

My hypothesis here is far from original. Michael Porter, Harvard professor of Porter’s five forces fame, called this concept, “creating shared value,” in his 2011 HBR article with Mark Kramer. I’ve simply contextualized it here using some new data and appended my proposals to the “shared value” idea.

Here are some examples of companies that I think are going a good job:


Autodesk, which creates and sells software for design (AutoCAD is one of their hallmark products, but they have countless other programs which are used in 3D design and printing, animation, architecture, and more fields), has heavily invested in education (primary through university), entrepreneurship, sustainability, and medical innovation. Students, entrepreneurs, and teachers actually receive free access to Autodesk software. They figure that by advancing these fields they will build goodwill, train practitioners that will in the future become loyal customers, and the company may even position itself to capture a lot of business in emerging fields, such as Internet of Things and augmented reality/virtual reality.

UPS has gone one step further and has come up with a way to help the customers of their customers. Rio Grande (whose parent company is Berkshire Hathaway) is a manufacturer of speciality jewelry equipment. They ship with UPS. This year, Rio Grande created a membership program for their customers called Rio Pro. UPS became a partner with Rio Pro and offers discounted shipping services to Rio Pro members. In this relationship structure, everyone wins. Rio Grande’s customers are pleased because they get access to discounted shipping. Rio Grande wins because their customers are more satisfied and more successful. UPS wins by bolstering its relationship with Rio Grande as well as building a trusted relationship with a number of growing small businesses.


DHL, one of UPS’s main competitors, particularly outside of the United States, is creating an online marketplace for brick and mortar retailers in its headquarters city of Bonn, Germany. The marketplace is called Allyouneedcity, and I highly doubt that DHL is doing this just altruistically. They certainly hope that it will help support the retailers, but it also opens up opportunities for them. For example, they could use this marketplace to launch a pilot of same-day delivery, or they could expand the marketplace to compete with increasingly powerful e-retailers and expand DHL’s own revenue channels.

Amazon launched an interesting program this year, in which families on government assistance (SNAP and TANF) can receive a discounted membership to Amazon Prime. Prime is a large sales channel for retailers selling on Amazon’s marketplace (third-party e-commerce sales are actually growing faster than traditional e-commerce), so this will give those retailers more access to lower-income earners. On the face of things it might just seem like Amazon is shooting across the bow of Walmart, or even that they are trying to exploit lower-income individuals. With Amazon forging more and more into e-groceries, different kinds of merchandise, and value-added services, this discounted Prime service may actually improve access of lower-income individuals to products that they need for their health, nutrition, well-being, and income generating activities. Access, particularly in areas known as “food deserts” where there are no nearby grocery stores, is a serious problem for lower-income individuals. Amazon’s new service may be beneficial to its bottom line and help its customers as well.

In my opinion, Facebook may be the heavyweight that is most struggling with its vaunted position. It grew to prominence by facilitating a kind of social interaction that had never been conducted before. However, these sharings are increasingly being pushed to other platforms in the Facebook ecosystem, such as Messenger, Instagram, and WhatsApp. That’s left Facebook with a free speech billboard. At its most benign, people would say that Facebook is just a dumping ground for useless videos, blurry photos, and pitiful updates on people’s lives. At its worst, it’s a hate-littered echo chamber that is being used to manipulate people into believing things that are patently false.

Facebook is far from doomed. It remains a very successful company, and I believe that it offers a lot of value to society, despites the criticisms. However, to remain relevant, it needs to start focusing more on economic values. For instance, I could imagine Facebook launching an AI assistant (a la Siri or Alexa – it’s so in vogue these days) that focuses on social connections (I’m partial to the name Joffrey, but that’s up to Mark).

“Joffrey … when was the last time I talked to George?’

“It’s been six years since you last heard from George. Would you like to contact him now?”

“No, that’s alright, he’s probably busy.”

Meanwhile, in George’s house:

“George, I see it’s been awhile since you spoke with your friend. Would you like to contact her?”

“Yes, I would.”

“How would you like to contact her?”

“By e-mail.”

“Would you like a summary of your friend’s activity since the last time you spoke to her before we write an e-mail?”

“Yes I would Joffrey.”

There are various permutations of how Joffrey could facilitate meaningful interpersonal interactions around the world, and help with networking, friendships, tourism, mental health, and education. Facebook would benefit as well, because the more activity that takes place within their network, the more opportunities it has to monetize the activity.

There are countless more examples of how heavyweights can focus on economic values. Imagine if AT&T offered a comprehensive telecommunication plan for refugees arriving to the United States. Even more so, they could offer a special plan to refugees starting new businesses. AT&T would make great strides in facilitating communal integration for some of the neediest people in the world and helping them become successful members of society. If AT&T could expand this plan to include additional social support services, educational and NGO partners, as well as language assistance (Rosetta Stone or DuoLingo) then even more value could be created, and at little additional cost to AT&T (I only choose AT&T because it is one of the largest telecommunication companies in the country).

In coming years, one-to-one many businesses will continue to not only shape, but shake markets. Much has been said about the impending doom of brick-and-mortar retail. However, emergent one-to-many type companies are already nipping at the heels of e-retail juggernauts like Amazon. Instagram, owned by Facebook, has a retail team. Their goal is to let users make purchases without ever leaving the app. Amazon has already taken steps to respond to this emerging threat by introducing Spark, its own social media platform for product discovery.
Even being an established one-to-many titan for many years no longer guarantees the continuation of a business model.

For instance, banks

, credit card companies, and other financial one-to-many companies need to make plans to integrate with these the new heavyweights of commerce or they may find themselves cut off from what were once reliable and steady revenue streams. Other one-to-many companies can partner up behind your back and uproot your market position. UPS and FedEx should heed this warning and consider new one-to-many retail patterns. Transportation and logistics upstarts, such as Uber RUSH and Deliv (which, granted, UPS has invested in) are already directly integrating with large retailers as well as payment processing companies such as Clover.

As one-to-many companies begin to support more and more smaller businesses, and the connections among firms become more and more complex, I begin to see the economy less traditionally, with individual companies making one-off transactions of goods or services. Instead, I see an economic mesh. Every transaction is distributed among many different firms in the economy, and these transaction could not be successfully completed without all of the firms working together. The heavyweights may continue to grow, and some people may get very rich as a result, but so long as they are supporting opportunity for millions of other people and in-line with our economic values then it is a win-win outcome.

Joffrey: “Catelyn, I noticed that your sister Lisa just posted a photo on Instagram from near you. Would you like to send her a message?”

Catelyn: “No Joffrey, that’s ok, thank you.”

… Shipping Packages

… Artificial Intelligence

Over the last year artificial intelligence (AI) has become nearly ubiquitous in the news. Just recently, Elon Musk called it a threat to human civilization. His warnings have been the direst, but many other people think that AI has the potential to replace billions of human jobs, and we need to adapt now to prevent mass-unemployment.

This represents a naïve view of capitalism, but one that is increasingly popular with politicians, pundits, and people who listen to them. Jobs may certainly be cut, but it is more likely that new jobs, in the traditional sense, simply will not be created. Companies will reduce labor costs across the board, leaving more profits for business owners and their remaining knowledge workers. Prices for goods and services that involve automated labor will also come down, relative to all other prices. The result will be more discretionary income, and where we choose to spend it will determine in what sectors new jobs will be created. Certainly, there will be people left behind, at least temporarily. Society may need to step in and assist those people. However, in the long-term, so long as workers have the necessary knowledge skills to manage AI, automation, and other technologies, the economy will benefit, and not be harmed, by the AI-age.

As more and more work becomes automated, there will certainly be less work to be done, in the aggregate, by humans. There is always the opportunity for new work to emerge – work that does not exist today and work that we have not conceived of yet as being possible, necessary, or important. However, this work may also be able to be automated. Some may say that there will always be work for humans to manage the automation – repairs on robots and writing code for the automation software, to begin with. I see no reason to think that this cannot be automated either.

As a result of this ubiquitous automation, there may be no jobs left for humans at all, sometime in the future. People fear that we would be left with artificial/robotic economic overlords. I also think that this is a naïve understanding of the economy. In fact, I think that the AI-age could also be a post-capitalism age. People would work less and the work left to us would be judgement based. How do we apportion the food that the robots are cultivating? Who should have the rights to exploit minerals that we can mine from the Earth (and asteroids!), since nearly everyone would have limitless abilities to produce with those metals and minerals? I doubt that we would want to automate the answers to these types of important questions. Even if we did want to, it would not be wise, because the ability to think critically would then be diminished worldwide and not be passed down to future generations. In some respects, everyone in the post-capitalism age would be one of Plato’s philosopher kings. We could also dedicate more work-time to art and creation, as well as its consumption.

AI isn’t just ubiquitous in the news anymore. It is become increasingly common in our homes and in our pockets. Chat bots and digital personal assistants and home devices like Amazon Echo’s Alexa, Siri, and Google Now are all examples of artificial intelligence. My phone is always trying to guess where I am and when I should leave for events. That’s AI in my pocket (I’ve actually been meaning to turn that off, since I don’t have a car).

As AI proliferates, so too does how we are talking about it. Along with AI, people mention machine learning, deep learning, and cognitive computing. In general, it seems to me that AI is an umbrella term that encompasses all of these techniques. In popular terms, AI refers to consumer applications where a computer is emulating activities that we would typically conduct with another person. Think of talking with Alexa as a prime example. Getting down-to-the-minute weather predictions from an app, rather than a meteorologist, is another good example. In more technical terms, AI refers to all applications in which a computer is doing what used to be restricted to the domain of a biological brain: sensing and cataloguing information, processing and analyzing it, and using that synthesized information to recognize patterns, to make predictions, and to take decisions.

Ex Machina

Machine Learning

Consider a smart watch or wrist band that records the time its user wakes up every morning for an entire month. After collecting that data for a month, it calculates an average weekday wake up time and sets an alarm automatically. For three out of five proceeding weekday mornings the user snoozed the alarm ten minutes, and on two of the mornings the user got up as soon as the alarm went off. Using this new information, the wearable revises the wakeup time to be slightly later, and thereafter continues to monitor and revise the wakeup time according to the user’s actual behavior.

This is an example of machine learning. Without any user input the machine makes inferences, assesses their veracity, and iterates accordingly. However, it’s quite rudimentary. The techniques used are fairly basic, and the result was not something that the human mind could not have arrived to on its own.

A more complex application would involve inferring where the user works based on normal daily travel patterns (unless you have turned it off, your smartphone is probably already transmitting this information), and then analyzing traffic on the roadways and the activities of other users to automatically set the user’s alarm so that they arrive at work (or school, or the gym, etc.) at their preferred time. By relying on more information for decision making the analysis techniques become more complex and begin to resemble artificial intelligence.

More important to understand than the capabilities of machine learning, is that its approach to information analysis vastly different from traditional analytical decision making. For instance, a financial institution can feed a computer vast quantities of information on borrowers and their loan performance history. A machine learning program could then process all of this information and determine what variables are best correlated with loan performance. Traditionally, a bank would apply financial and economic theory to create credit models and then test the model, altering it to find the best fit. The machine learning approach relies on a completely different paradigm. Rather than approaching the problem with a basis of assumptions, using machine learning implies ignorance, or at the very least an openness to unanticipated patterns and relationships. Machine learning tests all possible relationships and patterns and makes the best predictions, even if they go against our intuitions. Industries and practitioners that are not accustomed to this approach or unwilling to appreciate its merits may soon find themselves outpaced and outperformed by more machine-savvy competitors.

Deep Learning

Deep learning is an even more sophisticated form of machine learning. Deep learning employs a non-parametric data analysis technique called neural networks (or neural nets) to identify relationships between data. The technique is referred to as a neural net because it resembles the structure of neurons in the brain.

Here is a YouTube video that does a fairly good job of explaining the technique in a short amount of time:


Deep learning is powerful enough to accomplish advanced pattern recognition – pattern recognition which can be deployed in situations as diverse as understanding what is happening on city streets and high-speed highways (self-driving vehicles) to learning what different types of animals look like and then making drawings of them. I can imagine a deep learning application that is fed many thousands of oncological images and trains itself to identify cancer. As doctors confirm or reject the conclusion of the program it would store this information and refine its own predictions. Eventually, the program would become more accurate than doctors and radiologists.

This extreme accuracy is what has people such as Elon Musk concerned about artificial intelligence. Will we need doctors if algorithms are better at their work than the doctors themselves?

Cognitive Computing

Cognitive computing is a term I have been hearing less and less. Artificial intelligence seems to have become the preferred buzzword. However, I think that cognitive computing retains a unique definition and is useful to understand many technologies. Generally, cognitive computing are computing processes that are designed to emulate how humans process information and think. Watson is the most famous cognitive computer, and its name and its promoted abilities all seem to allude to a human mind.

One of Watson’s abilities is natural language processing. Rather than having to be fed data in a neat spreadsheet or form, Watson can consume unstructured data, make heads or tails with them, and then process the data. In business school a common assignment is creating a pro forma financial statement from a professor’s explanation of the financial conditions of a company. It’s fairly rote and mechanical. Students have to translate the explanation of the finances into a familiar form which then does the mathematical processing. Cognitive computing skips that translation step. It can understand the natural language explanation of the company’s finances and directly make the necessary computations for the pro forma.

In fact, it seems that Goldman Sachs and other investment banks are doing just that. They’ve been announcing more and more investments in AI along with reductions in the sizes of their M&A teams over the last few years. Goldman Sachs may have gone the furthest. Their CEO has declared that Goldman is really just a “tech” company, and the former Chief Information Officer is now the CFO of the company.

Machine-powered gaming is also a direct application of cognitive computing, because it pits computer cognition directly against human cognition. AI watchers were stunned early this year when a Google designed machine was able to defeat a Go master. Go is an ancient Chinese game that is strategically very complex. For those of us of the Indo-European persuasion, Go is more difficult and complex than chess.

Quantum Computing

One of the challenges with artificial intelligence is that conventional super-computers do not possess enough processing power to crunch through all the nodes in deep neural networks fast enough. Physicists and computer engineers are working on a solution known as quantum computing. Traditional computers store information in bits, which can either represent a 1 or a 0. However, using the quantum physics concept of superposition, a quantum bit, or qubit, can exist in both states at once. If engineers can create stable computers that harness qubits, computing power will exponentially increase.

Here is a good explanation of the concept and recent developments in the field.

Quantum computing would rapidly improve our abilities to create deep neural networks and accelerate the development of artificial intelligence. However, quantum computers will be so powerful, they may be able to easily crack the codes of even the most powerful computer encryption and security systems. Parallel to the development of quantum computing, society needs to invest in new cyber-security techniques that are complementary to quantum computing, not made obsolete by it.


I encourage everyone, no matter what job they have, what they enjoy doing, or how they interact with other people in the world, to consider, ‘how can some of the tasks that I do be automated?’ Try to imagine what it would take to automate the task and what the analytical system would be structured like. Then think about what value you can add as an individual, so that you remain necessary, despite the elimination of a human performing the task. Also consider how society needs to prepare and train its members so that the most people benefit from the advantages of AI, and the fewest people are left behind. That is likely the true message the Elon Musk is urging our policy makers to hear, and I hope that they hear it.

… Bitcoin Mining

This is part three of a four-part series of posts on the Economics of Oil. Previous posts:

Oil PumpThe Economics of Gas Prices

The Economics of International Oil Price Conspiracies

The Economics of Airfare


BitcoinFirst off, at this point you are probably wondering what similarities Bitcoins have to oil. I suppose that the main hypothesis of this post is that Bitcoins are nothing more than a plain old commodity, just like oil, and they are subject to the same market forces. In fact, at this moment “Bitcoin miners” are struggling with the same issues that shale oil producers in North Dakota and oil sands extractors in Alberta, Canada are struggling with.

Bitcoins are a digital currency. They do not exist in any physical form, and there is no central monetary authority, like the United States Federal Reserve or the European Central Bank, that can issue new Bitcoins. The currency was established in 2009 on a system of computers. The computers maintain a running log of every Bitcoin transaction (basically a big long list of debits and credits) known as the “Blockchain.” The computers interact with each other to clear transactions and verify that their registries on the Blockchain are legitimate. Every time a user successfully verifies a block of transactions (which is a complicated computing algorithm that needs to be “solved”) the transactions are processed and that user receives a pre-determined number of newly minted Bitcoins for her efforts.

The designers of Bitcoin programmed the software so that the algorithms that need to be solved to verify the Blockchain and win yourself new Bitcoins get solved about every ten minutes. As more computers are added to the system, the algorithms are programmed to get more difficult. And with more and more user-systems vying for the new Bitcoins, more and more powerful computer systems are needed to be the first system to successfully verify the Blockchain and win the digi-cash. Basically, mining Bitcoins is deliberately designed to get progressively more difficult over time. Cloud computing companies are literally selling use of their systems to Bitcoin miners. Massive amounts of capital are being put into configuring powerful computer systems. And this comes with its own costs and externalities. A lot of electricity is needed to cool super-computing systems, and if the electricity is generated through non-renewable means then there is the additional cost of the pollution that is generated.

A Bitcoin mining operation

A Bitcoin mining operation

The similarity between Bitcoins and oil, I contend, is not because Bitcoins are “mined” in this digital sense. Rather, it is because we allocate capital to Bitcoin mining in much the same way we allocate capital to oil extraction. Bitcoins have absolutely no intrinsic value. They only have value as expressed in terms of other currencies (such as US Dollars or Euros). So, ostensibly, Bitcoins have exchange rates and have an ever changing value to them. Yes, certain companies do accept Bitcoins in lieu of traditions currencies, but prices are still expressed in the traditional currency and then converted into Bitcoins based on the prevailing exchange rate. This is what drives Bitcoin miners to devote their computing power to Bitcoin mining. They can then sell their Bitcoins for other currencies and use that money in the traditional sense.

Bitcoin Price Chart

The value of a Bitcoin, expressed in US Dollars


So when the exchange rate, or rather the value of Bitcoins goes down, there is less incentive for Bitcoin miners to devote their computing power to Bitcoin mining because they could be using their super computers for more lucrative endeavors. And mining Bitcoins is an expense endeavor. It requires ever more sophisticated computer equipment as well as vast amounts of electricity to cool the computers. And this is just like oil. It costs money to get oil out of the ground and into barrels, just like it costs money to mine Bitcoins. And if the price of oil falls below what it costs a company to extract oil, that company will shutter rigs until the price of oil climbs back up. All the same, if the value of Bitcoins drops below what it costs to mine them, the digital mining company will flip the switch to ‘off.’

Another interesting attribute about Bitcoins is that every four years, since the currency’s establishment in 2009, the number of Bitcoins that can be mined by a new block verification halves. So from 2009 through the end of 2012 the number was 50, now it is 25, and in 2017 it will be 12.5. By 2030 the number of Bitcoins will be limited to around 21 million. To me, this raises an interesting question. If Bitcoin only works because the people mining the coins for a profit are also verifying the Blockchain, once there are no more Bitcoin to mine, won’t everyone spending massive amounts of money on super-computing capabilities just stop bothering, making it impossible to verify transactions and trade Bitcoins, essentially destroying the currency? There needs to be an expectation that the value of a Bitcoin will be perpetually increasing, otherwise the entire system will cease to function.

And that is precisely what is happening right now in the United States oil extraction business (well, not a total destruction of value, but the drop in the price of oil is certainly concussing the current system). The number of oil rigs in the United States, as reported by Baker Hughes, peaked in October at 1,609 rigs. It has since fallen to 1,421 rigs. This basically indicates that exploration for new oil, which accounts for an enormous initial investment, is dropping off; however, United States domestic production is still surging. US crude production added 60,000 barrels a day last week, according to the Energy Information Administration (EIA). That puts the United States at 9.19 million barrels a day. However, as the price continues to fall and companies alter their exploration and investment plans, we very well may see domestic production peak.

An abundance of oil was discovered in North Dakota that was relatively cheap to extract, given the price of oil. So producers flocked to western North Dakota (a place where even geese wouldn’t flock to) and started to drill baby, drill. Over the same time period, emerging economies, such as China, and developed economies, such as those of Europe and Japan, slowed down. The demand for oil decreased, but the supply was steadily increasing. This has precipitated a large drop in the price of oil. Normally, we would expect Saudi Arabia to cuts its own production of the black gold to stabilize the price, but as I previous wrote, I believe they are not doing that this time around for political reasons. But it doesn’t hurt that this “price war” could help drive the Bakken Shalers out of business. Whereas Saudi Arabia only spends between $5 and $6 to get a barrel out of the ground, in North Dakota it costs maybe $42 on average to extract it out of the ground and get a 10% return on capital. The lower oil goes, the more it hurts American and Canadian producers, whereas Saudi Arabia has $900 billion of cash reserves on hand to ride out any prolonged dip in the price of oil.

Crude Prices

As a result of the flooded market and Saudi Arabia’s decision, the price of oil has dropped below the point at which it is profitable to continue to pump it out of the ground in the Bakken Shale fields of North Dakota. North Dakota, which has undoubtedly had the best performing economy in the country, even throughout the Recession (home prices in North Dakota actually went up through the Recession, whereas in most of the rest of the country they were plummeting), may finally see its wings melt. Texas, Oklahoma, Colorado, Louisiana, Alaska, and parts of Canada, may also see employment losses. The Federal Reserve Bank of Texas has estimated that there may be 140,000 job losses in Texas alone in 2015 as a result of the drop in the price of oil. Policy makers and regulators are also bracing for some troubles ahead for certain banks, housing markets, and even state budgets that rely on oil revenues.

Fill Up at the PumpHowever, over all, the drop in the price of oil will be good for the American economy. By saving at the pump Americans will be able to pad their savings accounts as well as go out and buy other things that will spur the economy. The Keystone Pipeline, which has been in the headlines for years now, might wind up being a moot point after all. The Pipeline was intended to bring crude oil from the oil sands of northern Alberta, Canada, to the US Gulf Coast. But oil sands extraction is costly and may drop in the future now that the price of oil is so much lower. If the pipeline ever gets built nothing may ever run through it.

As for Bitcoins, the only possible positive outcome of the boom (or is it a bubble?) that I see is that computing power might become exchange traded. First, companies became exchange traded on stock markets. And since then commodities and even more obscure assets like shipping contracts (Baltic Dry index) have become traded on exchanges. I don’t see any reason why computing power couldn’t become exchange traded in the future. Cloud computing companies are already offering their services over the internet to global markets; if there is enough volume in the market all that is needed is for the contracts to be standardized so that they could be traded freely between suppliers, consumers, and even speculators.

In the case of Bitcoin, I fear that by creating this digital currency and beginning to accept payments denominated by it, we are simply letting people with immense computing power at their disposal generate wealth for themselves. In addition, they are diverting their computing power from other uses that might be better for society, such as genomic coding, and in the process driving up the price for computer processing for the rest of us.


… the Inter-Oceanic Canal

Ometepe Island, in Lake Nicaragua

Ometepe Island, in Lake Nicaragua

Today marks the day that Nicaragua and her Chinese backers are breaking ground on the grand inter-oceanic canal that in five years will bisect the Central American isthmus and allow super-tankers too large for the Panama Canal to make the Pacific-Atlantic journey with ease.

Except it is never going to happen.

The history of Nicaragua is basically the history of failed canal attempts, and the foreign manipulation and betrayal, as well as the domestic anguish and languish that this brings. This is no less than the 72nd official proposal for a Nicaraguan canal. This won’t even be the first time that construction has begun. The first plans for a canal across Nicaragua were hatched by the conquistadors way back in the 1500’s, and Cornelius Vanderbilt nearly secured the financing he needed to construct the canal before the Civil War scuttled his attempts. But he did manage to incite a war and build a railroad through Nicaragua in the meantime.

Anyone who looks at a map of Central America may be puzzled by the proposal for a canal through Nicaragua. Costa Rica and Panama are far less wide. Nicaragua is the largest country, by area, in Central America. However, Nicaragua also has the largest lake in the region, Lake Nicaragua. At its closest, it is only 17 km from the Pacific Ocean. And Lake Nicaragua drains all the way to to the Caribbean Sea by way of the Rio San Juan (San Juan, or Saint John River). The vast majority of Nicaragua is an Atlantic, not a Pacific watershed. The Rio San Juan is rocky, shallow, and fraught with rapids at spots, but that has not stopped pirates from sneaking all the way up the river, as well as steam ships from being towed up the river. It is the most logical path for a successful canal through Central America.

As treacherous as the terrain of the river, the geopolitics of the river are far more rocky. The Rio San Juan is the border between Nicaragua and Costa Rica. However, it is the only riparian border in the world that is wholly owned by one country – in this case Nicaragua. And that has created endless problems and disputes with Costa Rica. So many, in fact, that the proposed route of the canal is completely bypassing the river and being cut straight through the interior of Nicaragua (and even so Costa Rica still has watershed issues that they claim Nicaragua is not responding to, in regards to the canal).

I don’t see why this time around should be any different from the 71 other attempts.

The main, insurmountable obstacle this time is the estimated price of the canal. Panama started with a good ‘ole American-made canal. Let’s say a Ford. And they have made a series of upgrades through the years. Let’s say right now they have a nice BMW model. To compete with Panama, Nicaragua is trying to acquire a Buggati. A $50 billion Bugatti, super-wide, super-deep, complete with access roads and highways, two deep-water ports, an airport, electric generation, pipelines, free-trade zones, a railroad, and a number of other necessary supply and infrastructure projects! They estimate it will take 50,000 workers and only take five years to complete.

So how is Nicaragua going to secure investors willing to provide nearly 4.5x its annual GDP ($11.26 billion, 2013 estimate, according to the World Bank)? I’ve put together a small list of possible backers and will go through my thoughts on each:

  • China
  • Nordic Sovereign Wealth Funds
  • Middle Eastern Sovereign Wealth Funds
  • Malaysian Sovereign Wealth Fund
  • Big Banks, the Backers of the Many Engineering Marvels of the Past
  • Venezuela and ALBA


If you ask a Nicaraguan where the money is going to come from they always say “China.” I don’t think so. Sure, the main investor at this point is a Chinese telecom mogul. And he is a multi-billionaire. But no one in the world has $50 billion to throw around, and our man in China is quick to point out that he has absolutely no backing from the Chinese government with regards to the canal. No one believes him, but it makes it very unlikely that he can muster $50 billion from his own domestic sources. Besides, between 2010 and 2012 China invested $101 billion, in total, in the entire continent of Africa (source: Business Insider). To think that they would even put half of that into one small country is irrational.

Nordic Sovereign Wealth Funds

I’ll make this one easy. Nordic countries, primarily Norway, have a lot of oil money that they are saving. But they are not going to invest it in Nicaragua. These countries have already pulled back on diplomatic channels and foreign aid to Nicaragua because of transparency concerns. They’re not going to pull a 180 and start pumping billions into a project fraught with questions and uncertainty.

Malaysian Sovereign Wealth Fund

Same story as Norway. They’re saving their oil money, and they’re not going to give it to Nicaragua. Unfortunately, this year, Malaysian Airlines, owned partially by the fund, had a rough one, losing two 777’s in their tragic entirety. The fund had to bail out the airline.  The price of oil is tumbling, which is probably helping to prop up Malaysian Airlines, on the one hand, but it is stunting the funds cash flow, on the other hand. I doubt they will be announcing a non-stop to Managua from KL anytime soon.

Middle East Sovereign Wealth Funds

And that leaves the Arabs. This is where I see the miracle coming from, if it comes from anywhere. Everyone knows that the Arabs have lots of oil wealth. And they’re known for the audacious. For one, Dubai. For seconds, it was the Arabs who bailed out some of the banks and hedge funds in the early days of the Sub-Prime Mortgage Crisis, long before Lehman Brothers became all too well known. So maybe, just maybe, a jet-setting Chinese man and Ortega’s outdated mustache can convince the right mix of petrocrats to throw in a good chunk of the $50 billion and really get the show on the road.

The Big Banks

No way Josue. Big banks in America, Europe, and elsewhere, are under immense pressure to demonstrate the viability of their investments. American regulators would pounce on any bankers working on this less-than transparent project, and European banks are already very bearish on shipping, since Northern European banks with shipping exposure were under extra scrutiny during the recently completed European banking stress tests, since global shipping has been very weak since the global recession.

Venezuela and ALBA

For years Hugo Chávez’s Venezuela was the standard-bearer for Latin-American Leftist opposition to America. When Chavez died last year his followers all started pounding their chest to become his heir. This included Correa in Ecuador, Ortega here in Nicaragua, Evo Morales in Bolivia, and of course Maduro in Venezuela. For years Venezuela, and its leftist sphere of influence, the Bolivarian Alliance of the Americas (ALBA in Spanish), have been financing cheap oil for member states as well as other social development projects. However, this all comes from Venezuelan stability and a steady stream of oil dollars into her state coffers. But with oil prices tumbling and Venezuela simmering in social unrest, it’s another no way Josue.

It is serenely ironic that the same trends, the rise of US oil and gas production, are giving rise to the need for an American super-canal, while at the same time driving the nail into the coffin of possible financing options, by driving down the price of oil.

The Sovereign Wealth Fund Institute has a nice map showing the size of sovereign wealth funds around the world. Click on the map for the link:

Red circles represent oil wealth, and blue circles represent other wealth (often mineral)

Red circles represent oil wealth, and blue circles represent other wealth (often mineral)

So it is never going to happen. But that does not mean I do not want it to happen. No one doubts that Nicaragua is starved for development. It is tied for being the second-poorest country in the Americas. Haiti takes the unfortunate crown, with Bolivia tied for second with Nicaragua.

The largest concern, after the obvious financing issues, is environmental. First and foremost, there is a 20-foot tide differential between the east and west coasts. And plans for the canal have not addressed this engineering obstacle yet. But furthermore, the canal will drive through protected wetlands, productive agricultural communities, and protected indigenous communities on the Caribbean coast. This is all not to mention that the route will go straight through and require the dredging of Lake Nicaragua, which is the largest source of freshwater in Central America. It is already an extremely fragile freshwater ecosystem due to agricultural and other pollutants streaming into the lake. Everyone from locals to parties interested in the fledgling tourism industry are in extreme opposition to the canal.

But lastly, I doubt that Nicaraguans will reap the benefits of the canal, which is how Ortega is selling the whole scheme to his people. The Chinese development corporation has a 50-year concession on profits, with another 50-year option to extend. Ortega is promising 250,000 jobs that will be born as a result of the canal, plus the need for 50,000 laborers on the construction. But of course I have my doubts. The canal will drive through some of the most sparsely populated and least developed departments of the country. Hundreds of thousands of people will have to relocate in order to realize those 250,000 jobs, which will lead to a lot of social strains on the country. Plus, given the under-education of the Nicaraguan people, the best-paying of the 50,000 construction jobs will mostly go to foreigners, not Nicaraguans. And I think it also bears mentioning that the highest HIV rates in Nicaragua are often in mobile populations, much like the worker camps will be. Has anyone put any thought into the epidemiological and public health effects of this project?

Nicaragua and the Chinese development company hired McKinsey to conduct a feasibility study. Officials refuse to release the results, but they are quick to point out the stellar economic projections. In 2013 GDP growth paced along at 4.6%. Official projections for the canal show that in the first year of construction GDP growth will skyrocket to above 14% and stay there for the foreseeable future. I just finished reading Confessions of an Economic Hitman. I hated the book. It was poorly written and not believable. But I can’t fail to mention that the author emphasized that the main tool of an economic hitman is inflated growth projections. It is guaranteed that the construction of a canal would attract a ton of foreign direct investment in Nicaragua, but sustained rates above 10% are preposterous and only part of the Chinese boondoggle to attract investment in the first place.

If the project ever truly gets off the drawing board (the groundbreaking today is ceremonial, nothing more) I will be in opposition. I fear that Nicaragua will bear many negative externalities while reaping few benefits.

… Manhattan

I recently noticed on Facebook that a New York Times article in a column called “The Hunt” has gained some traction, mainly in a negative light. The article is titled, “How to Get to Manhanttan? Save, Save, Save,” and it tells the story of a very young woman who was able to afford a nice apartment on the Upper East Side. The problem with the story is that the math just doesn’t add up.


Annie, a financial services adviser and the subject of the piece, put down 35% on a $426,000 apartment. That’s $149,100. Plus, she spent $30,000 on renovations and remodeling. In total, she used $179,100 of her savings. From the article, it sounds like she worked for about two years and a quarter before making the bid on the apartment. That means she was putting away $6,633.33 a month, at bare minimum. Assuming she was putting away 100% of her take-home pay into savings, her average annual salary was a whopping $79,600. I personally worked in banking consulting until the beginning of this year, starting right out of college just like Annie, and I never made that much even before taxes.

But further questions remain. She certainly couldn’t have saved 100% of her salary. Even though she lived at home she must have used some of her income on transportation (particularly to get to work, even if it is deductible), food, entertainment, clothing, other personal items, and leisure and entertainment. Did she pay for any benefits through her employer, such as health insurance, life insurance, long-term disability insurance, eye care, or dental care? Most likely. What about her 401(k)? Certainly someone as financial savvy as Annie  would be putting away money for retirement at her young age and taking advantage of what we can assume was a match from her employer. And then of course there are taxes. Working in New York and living in New Jersey, Annie must have been hemorrhaging paychecks to the Man on those long nights stuck in the Lincoln tunnel. All in all, this article would lead you to believe that Annie was making six digits out of college.

The last question that needs to be raised really doesn’t need to be asked at all. By now, it should be apparent that Annie received considerable financial help, most likely from her parents, in the purchase of this apartment. So one could assume that she doesn’t have any student debt because her wealthy benefactors most likely supported her through Binghamton University as well. And herein lays my major complaint with this story. The article lauds the virtues of saving and what it can get you in the (relatively) long run. However, the subject of the article is a daughter of wealthy circumstance. I concede that she likely saved a large ton of money, especially for someone of her age. But the fact remains that for the 99% a free education is not possible, and even someone with the discipline of Mother Theresa could never afford that apartment after working for less than three years without someone pitching in with a fat check.

My true complaint is not with Annie though. She legally bought this apartment and she has every legal right to live in it and pursue satisfaction and happiness in her life however she pleases. The problem in this case is the NY Times. By failing to run the numbers and fact check this article they failed their readership. But through this failure they have reinforced the false ideal that hard work and discipline alone can help you achieve your materialistic goals. Rather, the NY Times should be espousing alternatives means by which young people and the middle-class can find safe, comfortable housing in New York City and other places around the world. What we need is innovation. Innovation in how we finance shelter. And innovation in how we actually shelter ourselves and how we conceive of adequate and satisfying shelter. This article reinforces materialistic societal norms and makes people believe that they are doing something wrong if they are not walking a taught tight rope towards their “American dream.” Didn’t we learn with the Triple-F Fiasco (Fannie-Freddie-Foreclosure!) that the American dream can easily turn into a nationwide nightmare? Renters can be happy people too. The NY Times doesn’t seem to realize this. With income inequality large and growing the NY Times and its readership need to realize that wealth and assets are not the only way to lead the good life. People can choose their own path.

I suppose since this blog is called “The Economics Of …” and I titled this post The Economics of Manhattan I should talk about economics a bit. I hope that my readers do not think that economics is about making everyone rich or maximizing wealth for everyone. I am an economist because I want to maximize opportunity for everyone – their opportunity to be happy, whether it is through wealth and asset accumulation, or whether it being through less materialistic means. My hope is that societies will put policies in place so that the opportunity is available to everyone, not that society will define what happiness is and have everyone marching towards that goal through the engines of the economy.

… Uber

Uber_logoTo me, Uber is the pinnacle of economic innovation. It harnessed technology, the app revolution, and used it to improve efficiency and provide a new service. The service is designed to deliberately overcome a classic economic problem, asymmetric information. And the pricing model is based on sound economic principles. It is at the forefront of a technology driven revolution that economists are calling “the sharing economy.” Similar services include Lyft, AirBnB, and Craigslist.

Uber, at its core, is simply an app. You download it to your smartphone from an app store, and then you give it some basic information, including a credit card number. Then, whenever you need a ride you use a map to tell the app where you want to be picked up and you specify the level of service you want – a private car, a taxi, a black car, or an SUV. The app takes care of the rest. It dispatches a driver and gives you his or her name, user rating, contact information, and estimated time of arrival.

When the driver arrives the app alerts you and you can head outside and hop in. All you need to do is tell the driver where you are headed and he or she will take you. Then when you arrive at your destination you just get out. No fumbling for change in your pocket or listening to the taxi driver grumble about you wanting to use a credit card. The app, which already has your credit card information, automatically bills you based on level of service, distance traveled, and time elapsed. All of this information, including a map, is e-mailed to you. I’ve used these e-mails in the past to compile invoices for my business trip expenses at my old job. Gratuity and any taxes are automatically subsumed into the rate. The app simply asks you to rate the driver, out of five stars, and provide any comments or feedback.

Black car

Asymmetric information is a classic economic challenge. It is when the two sides of a transaction – the buyers and sellers, demanders and suppliers, consumers and providers, whatever you want to call them – do not have the same information about the product or service. For example, the used car market suffers considerably from asymmetric information. The dealers know a car’s history and if it’s a lemon, but the buyers don’t have this information, which saps demand and can lead to less than optimal prices on vehicle sales.

Uber has solved this problem for the chauffeured rides-on-demand market. Not only does the rider have to rate the driver, but the driver has to rate the rider. Riders and drivers both have average ratings out of five stars, which are revealed to both parties when the service is called for. Riders can decline a driver with a poor rating, and drivers can decline service to rude riders with a poor rating. This symmetrical access to information improves the efficiency of the market and helps secure the fairest price for service possible. It also ensures quality. I’ve taken many uber-clean Ubers in which I’ve been offered a small bottle of water or a nice sucking candy, at no additional cost.

Pricing is another strong feature of Uber. Accurate prices take into account both real-time supply and demand for a service. But sometimes prices are fixed and only take into account one side of the curve. For example, one problem with certain popular “hot lanes” on interstates is that they only take into account demand. The price goes up when the normal lanes are congested, but it doesn’t take into account how congested the express lanes are. When the express lanes are also jammed this has the effect of unnecessarily attracting more vehicles, worsening the congestion. And when the fast lanes are empty the prices are not optimized to attract more vehicles, improving traffic flow for the normal lanes.

Uber, on the other hand, has base rates for distance and time traveled. However, when demand is high or there are not a lot of cars available, they implement a surge pricing scheme which multiplies the price of the ride based on the real-time state of the market. At first this pricing scheme got Uber some bad press due to lack of transparency, but now that they have improved the app to make the user aware of the price it is a great system. The people who are most willing to pay for the service, as expressed by price, are most efficiently matched with the drivers most willing to provide the ride.

I've never seen surge pricing this high, but it only reflects real-time market conditions. It could have been during a bad storm when no one wanted to be out driving, or during a high-demand period, like New Year's Eve

I’ve never seen surge pricing this high, but it only reflects real-time market conditions. It could have been during a bad storm when no one wanted to be out driving, or during a high-demand period, like New Year’s Eve

The app is sleek. The pricing system is fair, and the its rating system overcomes classic economic challenges to ensure as free of a market as possible. So what’s the problem? What’s all the fuss with Uber about? The problem with Uber and the sharing economy is that everyone who has their hands in the traditional economic structure is throwing a fit. Uber’s success is partially at the expense of traditional taxi drivers. And taxi services are heavily regulated in most cities around the world. This is leading to taxi commissions throwing up roadblocks (some literal, most legal) all across the world. However, regulated taxi markets are a relic of an over-regulated past. Like most markets, regulation and government intervention benefits few and passes on unnecessary costs and under-service to most. I can certainly understand why taxi commissions are protesting. The livelihood of their beneficiaries is being completely upended. However, innovation, invention, and new technology, are the engine of economic growth. When government policies suppress the urge for unnecessary regulation and allow innovation to flourish economic prosperity reaches the most people – even the disrupted taxi drivers, once they adjust their service or find another job.


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