Why we need a national response

It seems quite clear now that we do not do a very good job of projecting COVID-19 progression. There are many reasons. One is that it is hard to predict how people and governments will behave. A fraction of the population will practice social distancing and withdraw from usual activity in the absence of any governmental mandates, another fraction will not do anything different no matter any official policy and the rest are in between. I for one get more scared of this thing the more I learn about it. Who knows what the long term consequences will be particularly for autoimmune diseases. The virus is triggering a massive immune response everywhere in the body and it could easily develop a memory response to your own cells in addition to the virus.

The virus also spreads in local clusters that may reach local saturation before infecting new clusters but the cross-cluster transmission events are low probability and hard to detect. The virus reached American shores in early January and maybe even earlier but most of those early events died out. This is because the transmission rate is highly varied. A mean reproduction number of 3 could mean everyone has R=3 or that most people transmit with R less than 1 while a small number (or events) transmit with very high R. (Nassim Nicholas Taleb has written copiously on the hazards of highly variable (fat tailed) distributions. For those with mathematical backgrounds, I highly recommend reading his technical volumes: The Technical Incerto. Even if you don’t believe most of what he says, you can still learn a lot.) Thus it is hard to predict when an event will start a local epidemic, although large gatherings of people (i.e. weddings, conventions, etc.) are a good place to start. Once the epidemic starts, it grows exponentially and then starts to saturate either by running out of people in the locality to infect or people changing their behavior or more likely both. Parts of New York may be above the herd immunity threshold now.

Thus at this point, I think we need to take a page out of Taleb’s book (like literally as my daughter would say), and don’t worry too much about forecasting. We can use it as a guide but we have enough information to know that most people are susceptible, about a third will be asymptomatic if infected (which doesn’t mean they won’t have long term consequences), about a fifth to a tenth will be counted as a case, and a few percent of those will die, which strongly depends on age and pre-existing conditions. We can wait around for a vaccine or herd immunity and in the process let many more people die, ( I don’t know how many but I do know that total number of deaths is a nondecreasing quantity), or we can act now everywhere to shut this down and impose a strict quarantine on anyone entering the country until they have been tested negative 3 times with a high specificity PCR test (and maybe 8 out of 17 times with a low specificity and sensitivity antigen test).

Acting now everywhere means, either 1) shutting everything down for at least two weeks. No Amazon or Grubhub or Doordash deliveries, no going to Costco and Walmart, not even going to the super market. It means paying everyone in the country without an income some substantial fraction of their salary. It means distributing two weeks supply of food to everyone. It means truly essential workers, like people keeping electricity going and hospital workers, live in a quarantine bubble hotel, like the NBA and NHL or 2) Testing everyone everyday who wants to leave their house and paying them to quarantine at home or in a hotel if they test positive. Both plans require national coordination and a lot of effort. The CARES act package has run out and we are heading for economic disaster while the pandemic rages on. As a recent president once said, “What have you got to lose?”

The depressing lack of American imagination

Democratic presidential candidate Andrew Yang made universal basic income a respectable topic for debate. I think this is a good thing because I’m a major proponent of UBI but my reasons are different. Yang is a technology dystopian who sees a future where robots take all of our jobs and the UBI as a way to alleviate the resulting pain and suffering. I think a UBI (and universal health care) would lead to less resentment of the welfare system and let people take more entrepreneurial risks. I believe human level AI is possible but I do not accept that this necessarily implies an economic apocalypse. To believe such a thing is to believe that the only way society can be structured is that a small number of tech companies owns all the robots and everyone else is at their mercy. That to me is a depressing lack of imagination. The society we live in is a human construct. There is no law of nature that says we must live by any specific set of rules or economic system. There is no law that says tech companies must have monopolies. There is no reason we could not live in a society where each person has her own robot who works for her. There is no law that says we could not live in a society where robots do all the mundane work while we garden and bake bread.

I think we lack imagination in every sector of our life. We do not need to settle for the narrow set of choices we are presented. I for one do not accept that elite colleges must wield so much influence in determining the path of one’s life. There is no reason that the US meritocracy needs to be a zero sum game, where one student being accepted to Harvard means another is not or that going to Harvard should even make so much difference in one’s life. There is no reason that higher education needs to cost so much. There is no reason students need to take loans out to pay exorbitant tuition. That fact that this occurs is because we as a society have chosen such.

I do not accept that irresponsible banks and financial institutions need to be bailed out whenever they fail, which seems to be quite often. We could just let them fail and restart. There is no reason that the access to capital needs to be controlled by a small number of financial firms. It used to be that banks would take in deposits and lend out to homeowners and businesses directly. They would evaluate the risk of each loan. Now they purchase complex financial products that evaluate the risk according to some mathematical model. There is no reason we need to subsidize such activity.

I do not accept that professional sports teams cannot be community owned. There is no law that says sports leagues need to be organized as monopolies with majority owners. There is no reason that communities cannot simply start their own teams and play each other. There is no law that says we need to build stadiums for privately owned teams. We only choose to do so.

The society we live in is the way it is because we have chosen to live this way. Even an autocrat needs a large fraction of the population to enforce his rule. The number of different ways we could organize (or not organize) is infinite. We do not have to be limited to the narrow set of choices we are presented. What we need is more imagination.

The failure of supply-side social policy

The US is in the midst of two social crises. The first is an opioid epidemic that is decimating parts of rural and now urban America and the second is a surge in the number of migrants crossing the southern US border primarily from Central America. In any system that involves flow, either physical (e.g. electricity) or social (e.g. money), the amount of flow (i.e. flux) is dependent on the amount of supply (e.g. power station/federal reserve) and the amount of demand (e.g. air conditioner/disposable income). So if you want to reduce opioid consumption or illegal immigration you can either shut down the supply or reduce the demand.

During the twentieth century there was a debate over the causes of booms and busts in the economy. I am greatly simplifying the debate but on one side were the demand-side Keynesians who believed that the business cycle is mostly a result of fluctuating demand. If people suddenly decide to stop spending then businesses would lose customers, which would lead them to lay off workers, who would then have less money to spend in other businesses and thus reduce demand further and so forth, leading to a recession. On the other side there were the supply-siders who believed that the problem of economic downturns was inadequate supply, which would be solved by cutting taxes and reducing business regulations. The Great Recession of 2008 provided a partial test of both theories as the US applied a demand-side fix in the form of a stimulus while Europe went for “expansionary austerity” and cut government spending, which slashes demand. The US has now experienced over a decade of steady growth while Europe went into a double dip recession before climbing out after the policy changed. That is not to say that demand-side policies always work. The 1970’s were plagued by stagflation with high unemployment and high inflation for which the Keynesians had no fix. Former Fed Chairman Paul Volcker famously raised interest rates in 1979 to reduce the money supply. It triggered a short recession, which was followed by nearly three decades of low inflation economic growth.

In terms of social policy, the US has really only tried supply-side solutions. The drug war put a lot of petty dealers and drug users in jail but did little to halt the use of drugs. It seems to me that if we really want to solve or at least alleviate the opioid and drug crisis, we need to slash demand. Opioids are pain killers and are physically addictive. Addicted users who try to stop will experience withdrawal, which is extremely painful. If you do succeed you will no longer be physically addicted. However, you can always relapse if you use again. The current US opioid epidemic started with a change in the philosophy of pain management by the medical establishment with a concurrent development of new supposedly less addictive opioid pills. So doctors, encouraged by the pharmaceutical industry, began prescribing opioids for all manners of ailments. Most doctors were well intentioned but a handful participated in outright criminal activity and became de facto drug dealers. In any case, this led to the initial phase of the opioid epidemic. When awareness of over prescription started to enter public consciousness there was pressure to reduce the supply. Addicts then turned to illicit opioids like heroin, which started phase 2 of the epidemic. However, as this supply was targeted by drug enforcement, a new highly potent and cheaper synthetic opioid, fentanyl, emerged. This was something that was easy to produce in makeshift labs anywhere and also provided a safer business model for drug dealers. However, fentanyl is so potent that this is has led to a surge in overdose deaths. Instead of targeting supply we need to reduce demand. First we need to understand why people take them in the first place. While some drugs are taken for the experience or entertainment, opioids are mostly being used to alleviate pain and suffering. It is probably no coincidence that the places most ravaged by opioids are also those that are struggling most economically. If we want to get a handle on the opioid crisis we need to improve these areas economically. People probably also take drugs for some form of escape. This is where I think video games and virtual reality may be helpful. We can debate the merits of playing Fortnite 16 hours a day but it is surely better than taking cocaine. I think we should take using video games as a treatment for drug addiction seriously. We could and should also develop games for this purpose.

Extra border security has not stemmed illegal immigration. What does slow immigration is a downturn in the US economy, which quenches demand for low-skilled labour, or an improvement in the conditions of the originating countries, which reduces the desire to leave in the first place. The current US migrant crisis is mostly due to the abhorrent and dangerous conditions in Guatemala and Honduras. For Europe, it is problems in Africa and the Middle East. In both cases, putting up more barriers or treating the migrants inhospitably is not really doing much. It just makes the journey more perilous, which is bad for the migrant and a moral and public relations nightmare for host countries. Perhaps, we could try to stem demand by at least making it safer in the originating countries. The US could provide more aid to Latin America including stationing American troops if necessary to curb gang activity and restore civil order. This would at least help diminish those seeking asylum. Reducing economic migration is much harder since we really don’t know how to do economic development very well but more investment in source countries could help. While globalization and free trade may have hurt the US worker and contributed to the opioid epidemic by decimating manufacturing in the US, it has also brought a lot of people out of abject poverty. The growth miracles in China and the rest of Asia would not be possible without international trade and investment. Thus the two crises are not independent. More free trade could help to reduce illegal immigration but it could also lead to worsening economic conditions for some regions spurring more opioid use. There are no magic bullets but we at least need to change the strategy.

Optimizing luck

Each week on the NPR podcast How I Built This, host Guy Raz interviews a founder of a successful enterprise like James Dyson or Ben and Jerry. At the end of most segments, he’ll ask the founder how much of their success do they attribute to luck and how much to talent. In most cases, the founder will modestly say that luck played a major role but some will add that they did take advantage of the luck when it came. One common thread for these successful people is that they are extremely resilient and aren’t afraid to try something new when things don’t work at first.

There are two ways to look at this. On the one hand there is certainly some selection bias. For each one of these success stories there are probably hundreds of others who were equally persistent and worked equally hard but did not achieve the same success. It is like the infamous con where you send 1024 people a two outcome prediction about a stock.  The prediction will be correct in 512 of them so the next week you send those people another prediction and so on. After 10 weeks, one person will have received the correct prediction 10 times in a row and will think you are infallible. You then charge them a King’s ransom for the next one.

Yet, it may be possible to optimize luck and you can see this with Jensen’s inequality. Suppose x represents some combination of your strategy and effort level and \phi(x) is your outcome function.  Jensen’s inequality states that the average or expectation value of a convex function (e.g. a function that bends upwards) is greater than (or equal to) the function of the expectation value. Thus, E(\phi(x)) \ge \phi(E(x)). In other words, if your outcome function is convex then your average outcome will be larger just by acting in a random fashion. During “convex” times, the people who just keep trying different things will invariably be more successful than those who do nothing. They were lucky (or they recognized) that their outcome was convex but their persistence and willingness to try anything was instrumental in their success. The flip side is that if they were in a nonconvex era, their random actions would have led to a much worse outcome. So, do you feel lucky?

AI and authoritarianism

Much of the discourse on the future of AI , such as this one, has focused on people being displaced by machines. While this is certainly a worthy concern, these analyses sometimes fall into the trap of linear thinking because the displaced workers are also customers. The revenues of companies like Google and Facebook depend almost entirely on selling advertisements to a consumer base that has disposable income to spend. What happens when this base dwindles to a tiny fraction of the world’s population? The progression forward will also most likely not be monotonic because as people initially start to be replaced by machines, those left with jobs may actually get increased compensation and thus drive more consumerism. The only thing that is certain is that the end point of a world where no one has work is one where capitalism as we know it will no longer exist.

Historian and author Yuval Harari argues that in the pre-industrial world, to have power is to have land (I would add slaves and I strongly recommend visiting the National Museum of African American History and Culture for a sobering look at how America became so powerful). In the industrial world, the power shifted to those who own the machines (although land won’t hurt) while in the post-industrial world, power falls to those with the data. Harari was extrapolating our current world where large corporations can track us continually and use machine learning to monopolize our attention and get us to do what they desire. However, data on people is only useful as long as they have resources you want. If people truly become irrelevant then their data is also irrelevant.

It’s anyone’s guess as to what will happen in the future. I proposed an optimistic scenario here but here is a darker one. Henry Ford supposedly wanted to pay his employees a decent wage because he realized that they were also the customers for his product. In the early twentieth century, the factory workers formed the core of the burgeoning middle class that would drive demand for consumer products made in the very factories where they toiled. It was in the interest of industrialists that the general populace be well educated and healthy because they were the source of their wealth. This link began to fray at the end of the twentieth century with the rise of the service economy, globalisation, and automation. After the second World War, post-secondary education became available to a much larger fraction of the population. These college educated people did not go to work on the factory floor but fed the expanding ranks of middle management and professionals. They became managers and accountants and dentists and lawyers and writers and consultants and doctors and educators and scientists and engineers and administrators. They started new businesses and new industries and helped drive the economy to greater prosperity. They formed an upper middle class that slowly separated from the working class and the rest of the middle class. They also started to become a self-sustaining entity that did not rely so much on the rest of the population. Globalisation and automation made labor plentiful and cheap so there was less of an incentive to have a healthy educated populace. The wealth of the elite no longer depended on the working class and thus their desire to invest in them declined. I agree with the thesis that the abandonment of the working class in Western liberal democracies is the main driver of the recent rise of authoritarianism and isolationism around the world.

However, authoritarian populist regimes, such as those in Venezuela and Hungary, stay in power because the disgruntled class that supports them is a larger fraction of the population than the opposing educated upper middle class that are the winners in a contemporary liberal democracy. In the US, the disgruntled class is still a minority so thus far it seems like authoritarianism will be held at bay by the majority coalition of immigrants, minorities, and costal liberals. However, this coalition could be short lived. Up to now, AI and machine learning has not been taking jobs away from the managerial and professional classes. But as I wrote about before, the people most at risk for losing jobs to machines may not be those doing jobs that are simple for humans to master but those that are difficult. It may take awhile before professionals start to be replaced but once it starts it could go swiftly. Once a machine learning algorithm is trained, it can be deployed everywhere instantly. As the ranks of the upper middle class dwindle, support for a liberal democracy could weaken and a new authoritarian regime could rise.

Ironically, a transition to a consumer authoritarianism would be smoothed and possibly quickened by a stronger welfare state. A possible jobless economy would be one where the state provides a universal basic income that is funded by taxation on existing corporations, which would then compete for those very same dollars. Basically, the future incarnations of Apple, Netflix, Facebook, Amazon, and Google would give money to an idle population and then try to win it back. Although, this is not a world I would choose to live in, it would be preferable to a socialistic model where the state would decide on what goods and services to provide. It would actually be in the interest of the corporations and their elite owners to lobby for high taxes and to not form monopolies and allow for competition to provide better goods and services. The tax rate would not matter much because in a steady state loop, any wealth inequality is stable regardless of the flux. It is definitely in their interest to keep the idle population happy.

The wealth threshold

The explanation for growing wealth inequality proposed by Thomas Piketty in his iconic book Capital in the Twenty-First Century, is that the rate of growth from capital exceeds that of the entire economy in general. Thus, the wealth of owners of capital (i.e. investors) will increase faster than everyone else. However, even if the rate of growth were equal, any difference in initial conditions or savings rate, would also amplify exponentially. This can be seen in this simple model. Suppose w is the total amount of money you have, I is your annual income, E is your annual expense rate, and r is the annual rate of growth of investments or interest rate. The rate of change in your wealth is given by the simple formula

\frac{dw}{dt} = I(t) - E(t)+ r w,

where we have assumed that the interest rate is constant but it can be easily modified to be time dependent. This is a first order linear differential equation, which  can be solved to yield

w = w_0 e^{r t} + \int_{0}^t (I-E) e^{r(t-s)} ds,

where w_0 is your initial wealth at time 0. If we further assume that income and expenses are constant then we have w = w_0 e^{r t} +  (I-E)( e^{rt} -1)/r. Over time, any difference in initial wealth will diverge exponentially and there is a sharp threshold for wealth accumulation. Thus the difference between building versus not building wealth could amount to a few hundred dollars in positive cash flow per month. This threshold is a nonlinear effect that shows how small changes in income or expenses that would be unnoticeable to a wealthy person could make an immense difference for someone near the bottom. Just saving a thousand dollars per year, less than a hundred per month, would give one almost a hundred and fifty thousand dollars after forty years.

Equifax vs Cassini

The tired trope from free market exponents is that private enterprise is agile, efficient, and competent, while government is prodding, incompetent, and wasteful. The argument is that because companies must survive in a competitive environment they are always striving to improve and gain an edge against their competitors. Yet history and recent events seem to indicate otherwise. The best strategy in capitalism seems to be to gain monopoly power and extract rent. While Equifax was busy covering up their malfeasance instead of trying to fix things for everyone they harmed, Cassini ended a brilliantly successful mission to explore Saturn. The contrast couldn’t have been greater if it was staged. The so-called incompetent government has given us moon landings, the internet, and built two Voyager spacecraft that have lasted 40 years and have now exited the Solar system into interstellar space. There is no better run organization than JPL. Each day at NIH, a government facility, I get to interact with effective and competent people who are trying to do good in the world. I think it’s time to update the government is the problem meme.

The robot human equilibrium

There has been some push back in the media against the notion that we will “soon” be replaced by robots, e.g. see here. But absence of evidence is not evidence of absence. Just because there seem to be very few machine induced job losses today doesn’t mean it won’t happen tomorrow or in ten years. In fact, when it does happen it probably will happen suddenly as have many recent technological changes. The obvious examples are the internet and smartphones but there are many others. We forget that the transition from vinyl records to CDs was extremely fast; then iPods and YouTube killed CDs. Video rentals became ubiquitous from nothing in just a few years and died just as fast when Netflix came along, which was then completely replaced a few years later by streaming video. It took Amazon a little longer to become dominant but the retail model that had existed for centuries has been completely upended in a decade. The same could happen with AI and robots. Unless you believe that human thought is not computable, then in principle there is nothing a human can do that a machine can’t. It could take time to set up the necessary social institutions and infrastructure for an AI takeover but once it is established the transition could be abrupt.

Even so that doesn’t mean all or even most humans will be replaced. The irony of AI, known as Moravec’s Paradox (e.g. here), is that things that are hard for humans to do, like play chess or read X-rays, are easy for machines to do and vice versa. Although drivers and warehouse workers are destined to be the first to be replaced, the next set of jobs will likely be highly paid professionals like stock brokers, accountants, doctors, and lawyers. But as the ranks of the employed start to shrink, the economy will also shrink and wages will go down (even if the displaced do eventually move on to other jobs it will take time). At some point, particularly for jobs that are easy for humans but harder for machines, humans could be cheaper than machines.  So while we can train a machine to be a house cleaner, it may be more cost effective to simply hire a person to change sheets and dust shelves. The premium on a university education will drop. The ability to sit still for long periods of time and acquire arcane specialized knowledge will simply not be that useful anymore. Centers for higher learning will become retreats for the small set of scholarly minded people who simply enjoy it.

As the economy shrinks, land prices in some areas should drop too and thus people could still eke out a living. Some or perhaps many people will opt or be pushed out of the mainstream economy altogether and retire to quasi-pre-industrial lives. I wrote about this in quasi-utopian terms in my AlphaGo post but a dystopian version is equally probable. In the dystopia, the gap between the rich and poor could make today look like an egalitarian paradise. However, unlike the usual dystopian nightmare like the Hunger Games where the rich exploit the poor, the rich will simply ignore the poor. But it is not clear what the elite will do with all that wealth. Will they wall themselves off from the rest of society and then what, engage in endless genetic enhancements or immerse themselves in a virtual reality world? I think I’d rather raise pigs and make candles out of lard.

 

 

 

 

Trade and income inequality

The conventional wisdom in economics is that trade is mutually beneficial to all parties and the freer the trade the better. However, as David Autor and collaborators have empirically shown, the benefits of trade can be unevenly distributed. A simple way to think about this is to consider a simple model of a nation’s income (I) as a function of socio-economic status (S), I = \alpha +\beta S. Here, S can be distributed in anyway but has zero mean. The mean income of the nation is \alpha while \beta is a measure of inequality (i.e. proportional to standard deviation). Generally, it was presumed that trade increases \alpha. However, as Autor finds, trade can also increase \beta and then it becomes a quantitative game as to whether you personally will do better or worse with trade. Your change in income will be \Delta I = \Delta \alpha +\Delta\beta S. Thus, if you are above the mean S then trade is always beneficial and increasing \beta helps you even more.  However, where the mean is with respect to the median is strongly dependent on the tails of the distribution of S. So if people with high S are very far away from the median, then the mean could also be high with respect to the median. If you are below the mean then gains from \Delta \alpha are offset by decreases in \Delta \beta S and if you’re S is more negative than -\Delta \alpha/\Delta\beta then you will do worse in absolute terms. This could explain what has been happening in the US. The nation benefits from trade by having cheaper goods but some sectors like manufacturing and textiles are greatly hurt and the cheaper goods cannot make up for the decrease in income. Those above the mean are benefitting from a mean shift in income due to trade as well as any increases in inequality. Those below the mean are getting smaller gains and in some cases doing worse as a result of trade. Thus, it may not be surprising that there are divergent views on the benefits of trade.

The demise of Barnes and Noble

Near the end of the twentieth century, there was a battle between small bookstores and the big chains like Barnes and Noble and Borders, typified in the film You’ve Got Mail.  The chains won because they had lower prices, larger stocks, and served as mini-community centers where people liked to hang out. It was sad to see the independent bookstores die but the replacement was actually a nice addition to the neighborhood. The Barnes and Noble business model was to create attractive places to spend time, with play areas for children, a cafe with ample seating, and racks and racks of magazines. The idea was that the more time you spent there the more money you would spend and it worked for at least ten years. Yet, at the height of their dominance, the seeds of their destruction could be plainly seen. Amazon was growing even faster and a new shopping model was invented. People would spend time and browse in B and N and then go home to order the books on Amazon. The advent of the smartphone only quickened the demise because people could order directly from the store. The large and welcoming B and N store was a free sample service for Amazon. Borders is already gone and Barnes and Noble is on its last legs. The one I frequent will be closing this summer.

The loss of B and N will be a blow to many communities. It’s a particular favorite locale for retirees to congregate. I think this is a perfect example of a market failure. There is a clear demand for the product but no viable way to monetize it. However, there already is a model for providing the same service as B and N that has worked for a century and that is called a library. Libraries are still extremely popular and provide essential services to people, and particularly low income people. The Enoch Pratt Free Library in Baltimore has a line every morning before it opens for people scrambling to use the computers and access the internet. While libraries have been rapidly modernizing, with a relaxation of behavior rules and adding cafes, they still have short hours and do not provide the comforting atmosphere of B and N.

I see multiple paths forward. The first is that B and N goes under and maybe someone invents a new private model to replace it. Amazon may create book stores in its place that act more like showrooms for their products rather than profit making entities. The second is that a philanthropist will buy it and endow it as a nonprofit entity for the community much like Carnegie and other robber barons of the nineteenth century did with libraries. The third is that communities will start to take over the spaces and create a new type of library that is subsidized by tax payers and has the same hours and ambience of B and N.

Productivity, marginal cost, and monopoly

240px-supply-and-demand-svg

In any introductory economics class, one is introduced to the concept of supply and demand. The price of a product is expressed as a function of the number of products that suppliers would produce and buyers would purchase at that price, respectively. Supply curves have positive slope, meaning that the higher the price the more suppliers will produce and vice versa for demand curves. If a market is perfectly competitive, then the supply curve is determined by the marginal cost of production, which is the incremental cost of production for making one additional unit. Firms will keep producing more goods until the price falls below the marginal cost.

Increases in productivity lead to decreases in marginal cost, and since the advent of the industrial revolution, technology has been increasing productivity. In some cases, like software or recorded music, the marginal cost is already zero. The cost for Microsoft to make one more copy of Office is miniscule. However, if the marginal cost is zero then according to classical microeconomic theory firms would produce goods and give it away for free. Public intellectual Jeremy Rifkin has been writing about a zero marginal cost society for several years now, (e.g. see here and here), and has proposed that ubiquitous zero marginal cost will lead to a communitarian revolution where capitalism is overturned and people will collaborate and share goods along the lines of the open software model, which has produced the likes of Wikipedia, Linux, Python, and Julia.

I’m not so sanguine. There are two rational strategies for firms to pursue to increase profit. The first is to lower costs and the second is to create monopolies. In completely unregulated markets, like drug trafficking, it seems like suppliers spend much of their time and efforts pursuing monopolies by literally killing their competition. In the absence of the violence option, firms can gain monopolies by buying or merging with competitors and through regulatory capture to create barriers to entry. There are also industries where size and success create virtual monopolies. This is what happens for tech companies where a single behemoth like Microsoft, Google, Facebook, or Amazon, completely dominates a domain. Being large has a huge advantage in finance and banking. Entertainment seems to breed random monopoly status where a single artist will garner most of the attention even though objectively there may not be much difference between the top and the 100th best selling artist. As costs continue to decrease, there will be even more incentive to create monopolies. Instead of a sharing collaborative egalitarian world, a more likely scenario is a world with a small number of entrenched monopolists controlling most of the wealth.

 

Insider trading

I think one of the main things that has fueled a backlash against the global elites is the (correct) perception that they play by different rules. When they make financial mistakes, they get bailed out with taxpayer dollars with no consequences. Gains are privatized and losses are socialized. Another example is insider trading where people profit from securities transactions using nonpublic information. While there have been several high profile cases in recent years (e.g. here is a Baltimore example), my guess is that insider trading is rampant since it is so easy to do and so hard to detect. The conventional wisdom for combating insider trading is stronger enforcement and penalties. However, my take is that this will just lead to a situation where small time insider traders get squeezed out while the sophisticated ones who have more resources will continue. This is an example where a regulation creates a monopoly or economic rent opportunity.

Aside from the collapse of morality that may come with extreme wealth and power (e.g. listen here), I also think that insider traders rationalize their activities because they don’t think that it hurts anyone even though there is an obvious victim. For example, if someone gets inside information that a highly touted drug has failed to win approval from the FDA then they can short the stock (or buy put options), which is an agreement or opportunity to sell the stock at the current price in the future. When the stock decreases in value after the announcement, they just buy the stock at the lower price, resell at the higher price, and reap the profits. The victim is the counter party to the trade who could be a rich trader but could also be someone’s pension fund or employees of the company.

Now the losing party or a regulatory agency could suspect a case of insider trading but to prove it would require someone confessing or finding an email or phone recording of the information passed. They could also try to set up a sting operation to try to catch serial violators. All of these things are difficult and costly. The alternative may seem ridiculous but I think the best solution may be to make insider trading legal. If it were legal then several things would happen. More people would do it which would drive down the prices for the trades, the information would more likely be leaked to the public since people would not be afraid of sharing it, and people would be more careful in making trades prior to big decisions because the other party may have more information than they do. Companies would be responsible for policing people in their firms that leak information. By making insider information legal, the rent created by regulations would be reduced.

The US election and the future

Political scientists will be dissecting the results of the 2016 US presidential election for the next decade but certainly one fact that is likely to be germane to any analysis is that real wages have been stagnant or declining for the past 45 years. I predict that this trend will only worsen no matter who is in power. The stark reality is that most jobs are replaceable by machines. This is not because AI has progressed to the point that machines can act human but because most jobs, especially higher paying jobs, do not depend heavily on being human. While I have seen some consternation about the prospect of 1.5 million truck drivers being replaced by self-driving vehicles in the near future, I have seen much less discourse on the fact that this is also likely to be true for accountants, lawyers, middle managers, medical professionals, and other well compensated professionals. What people seem to miss is that the reason these jobs are well paid is that there are relatively few people who are capable of doing them and that is because they are difficult for humans to master. In other words, they are well paid because they require not acting particulary human. IBM’s Watson, which won the game show Jeopardy and AlphaGo, which beat the world’s best Go player, shows that machines can quite easily better humans at specific tasks. The more specialized the task, the easier it will be for a machine to do it. The cold hard truth is that AI does not have to improve for you to be replaced by a machine. It does not matter whether strong AI, (an artificial intelligence that truly thinks like a human), is ever possible. It only matters that machine learning algorithms can mimic what you do now. The only thing necessary for this to happen was for computers to be fast enough and now they are.

What this implies is that the jobs of the future will be limited to those that require being human or where interacting with a human is preferred. This will include 1) jobs that most people can do and thus will not be well paid like store sales people, restaurant servers, bar tenders, cafe baristas, and low skill health workers, 2) jobs that require social skills that might be better paid such as social workers, personal assistants, and mental health professionals, 3) jobs that require special talents like artisans, artists, and some STEM professionals, and 4) capitalists that own firms that employ mostly robots. I strongly believe that only a small fraction of the population will make it to categories 3) and 4). Most people will be in 1) or not have a job at all. I have argued before that one way out is for society to choose to make low productivity work viable. In any case, the anger we saw this year is only going to grow because existing political institutions are in denial about the future. The 20th century is over. We are not getting it back. The future is either the 17th or 18th century with running water, air conditioning and health care or the 13th century with none of these.

Forming a consistent political view

In view of the current US presidential election, I think it would be a useful exercise to see if I could form a rational political view that is consistent with what I actually know and believe from my training as a scientist. From my knowledge of dynamical systems and physics, I believe in the inherent unpredictability of complex nonlinear systems. Uncertainty is a fundamental property of the universe at all scales. From neuroscience, I know that people are susceptible to errors, do not always make optimal choices, and are inconsistent. People are motivated by whatever triggers dopamine to be released. From genetics, I know that many traits are highly heritable and that includes height, BMI, IQ and the Big Five personality traits. There is lots of human variance. People are motivated by different things, have various aptitudes, and have various levels of honesty and trustworthiness. However, from evolution theory, I know that genetic variance is also essential for any species to survive. Variety is not just the spice of life, it is also the meat. From ecology, I know that the world is a linked ecosystem. Everything is connected. From computer science, I know that there are classes of problems that are easy to solve, classes that are hard to solve, and classes that are impossible to solve and no amount of computing power can change that. From physics and geology, I fully accept that greenhouse gases will affect the energy balance on earth and that the climate is changing. However, given the uncertainty of dynamical systems, while I do believe that current climate models are pretty good, there does exist the possibility that they are missing something. I believe that the physical laws that govern our lives are computable and this includes consciousness. I believe everything is fallible and that includes people, markets and government.

So how would that translate into a political view? Well, it would be a mishmash of what might be considered socialist, liberal, conservative, and libertarian ideas. Since I think randomness and luck is a large part of life, including who your parents are, I do not subscribe to the theory of just desserts. I don’t think those with more “talents” deserve all the wealth they can acquire. However, I also do realize that we are motivated by dopamine and part of what triggers dopamine is reaping the rewards of our efforts so we must leave incentives in place. We should not try to make society completely equal but redistributive taxation is necessary and justified.

Since I think people are basically incompetent and don’t always make good choices, people sometimes need to be protected from themselves. We need some nanny state regulations such as building codes, water and air quality standards, transportation safety, and toy safety. I don’t believe that all drugs should be legalized because some drugs can permanently damage brains, especially those of children. Amphetamines and opioids should definitely be illegal. Marijuana is probably okay but not for children. Pension plans should be defined benefit (rather than defined contribution) schemes. Privatizing social security would be a disaster. However, we should not over regulate.  I would deregulate a lot of land use especially density requirements. We should eliminate all regulations that enforce monopolies including some professional requirements that deliberately restrict supply. We should not try to pick winners in any industry.

I believe that people will try to game the system so we should design welfare and tax systems that minimize the possibility of cheating. The current disability benefits program needs to be fixed. I do not believe in means testing for social programs as it gives room to cheat. Cheating not only depletes the system but also engenders resentment in others who do not cheat. Part of the anger of the working class is that they see people around them gaming the system. The way out is to replace the entire welfare system with a single universal basic income. People have argued that it makes no sense for Bill Gates and Warren Buffet to get a basic income. In actuality, they would end up paying most of it back in taxes. In biology, this is called a futile cycle but it has utility since it is easier to just give everyone the same benefits and tax according to one rule then having exceptions for everything as we have now. We may not be able to afford a basic income now but we eventually will.

Given our lack of certainty and incompetence, I would be extremely hesitant about any military interventions on foreign soil. We are as likely to make things worse as we are to make the better. I think free trade is in net a good thing because it does lead to higher efficiency and helps people in lower income countries. However, it will absolutely hurt some segment of the population in the higher income country. Since income is correlated with demand for your skills, in a globalized world those with skills below the global median will be losers. If a lot of people will do your job for less then you will lose your job or get paid less. For the time being, there should be some wage support for low wage people but eventually this should transition to the basic income.

Since I believe the brain is computable, this means that any job a human can do, a robot will eventually do as well or better. No job is safe. I do not know when the mass displacement of work will take place but I am sure it will come. As I wrote in my AlphaGo piece, not everyone can be a “knowledge” worker, media star, or CEO. People will find things to do but they won’t all be able to earn a living off of it in our current economic model. Hence, in the robot world, everyone would get a basic income and guaranteed health care and then be free to do whatever they want to supplement that income including doing nothing. I romantically picture a simulated 18th century world with people indulging in low productivity work but it could be anything. This will be financed by taxing the people who are still making money.

As for taxes, I think we need to go a system that de-emphasizes income taxes, which can be gamed and disincentivizes work, to one that taxes the use of shared resources (i.e. economic rents). This includes land rights, mineral rights, water rights, air rights, solar rights, wind rights, monopoly rights, eco system rights, banking rights, genetic rights, etc. These are resources that belong to everyone. We could use a land value tax model. When people want to use a resource, like land to build a house, they would pay the intrinsic value of that resource. They would keep any value they added. This would incentivize efficient utility of the resource while not telling anyone how to use it.

We could use an auction system to value these resources and rights. Hence, we need not regulate wall street firms per se but we would tax them according to the land they use and what sort of monopoly influence they exploit. We wouldn’t need to force them to obey capital requirements, we would tax them for the right to leverage debt. We wouldn’t need Glass-Steagall or Too Big to Fail laws for banks. We’ll just tax them for the right to do these things. We would also not need a separate carbon tax. We’ll tax the right to extract fossil fuels at a level equal to the resource value and the full future cost to the environment. The climate change debate would then shift to be about the discount rate. Deniers would argue for a large rate and alarmists for a small one. Sports leagues and teams would be taxed for their monopolies. The current practice of preventing cities from owning teams would be taxed.

The patent system needs serious reform. Software patents should be completely eliminated. Instead of giving someone arbitrary monopoly rights for a patent, patent holders should be taxed at some level that increases with time. This would force holders to commercialize, sell or relinquish the patent when they could no longer bear the tax burden and this would eliminate patent trolling.

We must accept that there is no free will per se so that crime and punishment must be reinterpreted. We should only evaluate whether offenders are dangerous to society and the seriousness of the crime. Motive should no longer be important. Only dangerous offenders would be institutionalized or incarcerated. Non-dangerous ones should repay the cost of the crime plus a penalty. We should also do a Manhattan project for nonlethal weapons so the police can carry them.

Finally, under the belief that nothing is certain, laws and regulations should be regularly reviewed including the US Constitution and the Bill of Rights. In fact, I propose that the 28th Amendment be that all laws and regulations must be reaffirmed or they will expire in some set amount of time.

 

 

 

AlphaGo and the Future of Work

In March of this year, Google DeepMind’s computer program AlphaGo defeated world Go champion Lee Sedol. This was hailed as a great triumph of artificial intelligence and signaled to many the beginning of the new age when machines take over. I believe this is true but the real lesson of AlphaGo’s win is not how great machine learning algorithms are but how suboptimal human Go players are. Experts believed that machines would not be able to defeat humans at Go for a long time because the number of possible games is astronomically large, \sim 250^{150} moves, in contrast to chess with a paltry \sim 35^{80} moves. Additionally, unlike chess, it is not clear what is a good position and who is winning during intermediate stages of a game. Thus, any direct enumeration and evaluation of possible next moves as chess computers do, like IBM’s Deep Blue that defeated Gary Kasparov, seemed to be impossible. It was thought that humans had some sort of inimitable intuition to play Go that machines were decades away from emulating. It turns out that this was wrong. It took remarkably little training for AlphaGo to defeat a human. All the algorithms used were fairly standard – supervised and reinforcement backpropagation learning in multi-layer neural networks1. DeepMind just put them together in a clever way and had the (in retrospect appropriate) audacity to try.

The take home message of AlphaGo’s success is that humans are very, very far away from being optimal at playing Go. Uncharitably, we simply stink at Go. However, this probably also means that we stink at almost everything we do. Machines are going to take over our jobs not because they are sublimely awesome but because we are stupendously inept. It is like the old joke about two hikers encountering a bear and one starts to put on running shoes. The other hiker says: “Why are you doing that? You can’t outrun a bear.” to which she replies, “I only need to outrun you!” In fact, the more difficult a job seems to be for humans to perform, the easier it will be for a machine to do better. This was noticed a long time ago in AI research and called Moravec’s Paradox. Tasks that require a lot of high level abstract thinking like chess or predicting what movie you will like are easy for computers to do while seemingly trivial tasks that a child can do like folding laundry or getting a cookie out of a jar on an unreachable shelf is really hard. Thus high paying professions in medicine, accounting, finance, and law could be replaced by machines sooner than lower paying ones in lawn care and house cleaning.

There are those who are not worried about a future of mass unemployment because they believe people will just shift to other professions. They point out that a century ago a majority of Americans worked in agriculture and now the sector comprises of less than 2 percent of the population. The jobs that were lost to technology were replaced by ones that didn’t exist before. I think this might be true but in the future not everyone will be a software engineer or a media star or a CEO of her own company of robot employees. The increase in productivity provided by machines ensures this. When the marginal cost of production goes to zero (i.e. cost to make one more item), as it is for software or recorded media now, the whole supply-demand curve is upended. There is infinite supply for any amount of demand so the only way to make money is to increase demand.

The rate-limiting step for demand is the attention span of humans. In a single day, a person can at most attend to a few hundred independent tasks such as thinking, reading, writing, walking, cooking, eating, driving, exercising, or consuming entertainment. I can stream any movie I want now and I only watch at most twenty a year, and almost all of them on long haul flights. My 3 year old can watch the same Wild Kratts episode (great children’s show about animals) ten times in a row without getting bored. Even though everyone could be a video or music star on YouTube, superstars such as Beyoncé and Adele are viewed much more than anyone else. Even with infinite choice, we tend to do what our peers do. Thus, for a population of ten billion people, I doubt there can be more than a few million that can make a decent living as a media star with our current economic model. The same goes for writers. This will also generalize to manufactured goods. Toasters and coffee makers essentially cost nothing compared to three decades ago, and I will only buy one every few years if that. Robots will only make things cheaper and I doubt there will be a billion brands of TV’s or toasters. Most likely, a few companies will dominate the market as they do now. Even, if we could optimistically assume that a tenth of the population could be engaged in producing goods and services necessary for keeping the world functioning that still leaves the rest with little to do.

Even much of what scientists do could eventually be replaced by machines. Biology labs could consist of a principle investigator and robot technicians. Although it seems like science is endless, the amount of new science required for sustaining the modern world could diminish. We could eventually have an understanding of biology sufficient to treat most diseases and injuries and develop truly sustainable energy technologies. In this case, machines could be tasked to keep the modern world up and running with little need of input from us. Science would mostly be devoted to abstract and esoteric concerns.

Thus, I believe the future for humankind is in low productivity occupations – basically a return to pre-industrial endeavors like small plot farming, blacksmithing, carpentry, painting, dancing, and pottery making, with an economic system in place to adequately live off of this labor. Machines can provide us with the necessities of life while we engage in a simulated 18th century world but without the poverty, diseases, and mass famines that made life so harsh back then. We can make candles or bread and sell them to our neighbors for a living wage. We can walk or get in self-driving cars to see live performances of music, drama and dance by local artists. There will be philosophers and poets with their small followings as they have now. However, even when machines can do everything humans can do, there will still be a capacity to sustain as many mathematicians as there are people because mathematics is infinite. As long as P is not NP, theorem proving can never be automated and there will always be unsolved math problems.  That is not to say that machines won’t be able to do mathematics. They will. It’s just that they won’t ever be able to do all of it. Thus, the future of work could also be mathematics.

  1. Silver, D. et al. Mastering the game of Go with deep neural networks and tree search. Nature 529, 484–489 (2016).

What Uber doesn’t get

You may have heard that ride hailing services Uber and Lyft have pulled out of Austin, TX because they refuse to be regulated. You can read about the details here. The city wanted to fingerprint drivers, as they do for taxis, but Uber and Lyft forced a referendum on the city to make them exempt or else they would leave. The city voted against them. I personally use Uber and really like it but what I like about Uber has nothing to do with Uber per se or regulation. What I like is 1) no money needs to be exchanged especially the tip and 2) the price is essentially fixed so it is in the driver’s interest to get me to my destination as fast as possible. I have been taken on joy rides far too many times by taxi drivers trying to maximize the fare and I never know how much to tip. However, these are things that regulated taxis could implement and should implement. I do think it is extremely unfair that Uber can waltz into a city like New York and compete against highly regulated taxis, who have paid as much as a million dollars for the right to operate. Uber and Lyft should collaborate with existing taxi companies rather than trying to put them out of business. There was a reason to regulate taxis (e.g. safety, traffic control, fraud protection), and that should apply whether I hail a cab on the street or I use a smartphone app.

Inequality, spending, and GDP

In this article in the New Republic, economists Alan Auerbach and Lawrence Kotlikoff give empirical evidence that the rich spend less in proportion to their wealth than the less well off.

3114c4f1245834a98303e801cbf1c9b8d304b13dAlthough, their article is about how inequality is not as bad as we think if we compare how much people spend rather than their wealth, their conclusion implies that if we made wealth more equal overall spending would go up since the rich are not spending to their full potential. In fact, only in the highest quintile does wealth exceed spending. Thus, the spending of the lower four quintiles is wealth limited and thus would increase if they had more wealth. Now, Rick Gerkin would argue that GDP growth would not increase or may even slow if wealth were redistributed because savings and investment would decrease but that is a separate issue. The bottom line is that there would be an immediate GDP boost if wealth were made equal.

How income inequality can affect GDP

Since income inequality is a big issue in the United States and the upcoming election, I thought it would be instructive to look at how income inequality may affect the total US income (GDP) in a very simple model. This will only be a linear model in the sense that I will model domestic spending given some income without demanding self-consistency so spending equals income. However, I think the same qualitative results will hold. Let us suppose that the a person’s spending as a function of income I is given by s(I). Now let \rho(I) be the distribution of income (i.e probability density function).  The national income is then I_{total} = N \int s(I) \rho(I) dI, where N is the US population. We can write this as I_{total} = N\bar{s}(I), where the bar denotes expectation value or average.  So income inequality is measured by how wide \rho(I) is. A perfectly equal society would have \rho(I) =\delta(I-\bar{I}). Now let’s first suppose that s(I) is linear so your spending is exactly proportional to your income. In this case, I_{total}=Ns(\bar{I}), for any distribution and thus income inequality does not affect GDP. You will always get a GDP equal to spending at the US average. Now suppose that spending is super-linear or convex so you spend more as you earn faster than you earn it. This assumes that you save less the richer you are. In this case, by Jensen’s inequality I_{total}>Ns(\bar{I}), and the total GDP is bigger than if everyone spent at the average.  In this case, income inequality would actually increase the pie. Now, finally in the case where the spending function is concave, you spend less as you earn more, or save more as you earn more then I_{total}<Ns(\bar{I}), and thus the total spending is less than spending at the average. In this case, income inequality would reduce the GDP. So depending on how spending changes with income, income inequality could decrease or increase the size of the pie. My guess is that spending functions are concave so a little more equality could improve the economy.

The hazards of rounding

I parked at a meter today where the rate was 8 minutes per 25 cents. I threw in a nickel and the meter added 1 minute. I inserted in a dime and got and an additional 3 minutes. The meter was rounding down and not even correctly. My 5 cent piece should have netted me 96 seconds and my 10 cent piece 192 seconds. Instead, one quarter, four dimes and three nickels only got me 23 minutes, where I should have received 25 and a half minutes. I believe not accepting all forms of money at face value is a Federal offense. I certainly was offended.

The liquidity trap

The monetary base (i.e. amount of cash and demand deposits) has risen dramatically since the financial crisis and ensuing recession.

fredgraph

Immediately following the plunge in the economy in 2008, credit markets seized and no one could secure loans. The immediate response of the US Federal Reserve was to lower the interest rate it gives to large banks. Between January and December of 2008, the Fed discount rate dropped from around 4% to zero but the economy kept on tanking. The next move was to use unconventional monetary policy. The Fed implemented several programs of quantitative easing where they bought bonds of all sorts. When they do so, they create money out of thin air and trade it for bonds. This increases the money supply and is how the Fed “prints money.”

In the quantity theory of money, increasing the money supply should do nothing more than increase prices and people have been screaming about looming inflation for the past five years. However, inflation has remained remarkably low. The famous bond trader Bill Gross of Pimco essentially lost his job by betting on inflation and losing a lot of money. Keynesian theory predicts that increasing the money supply can cause a short-term surge in production because it takes time for prices to adjust (sticky prices) but not when interest rates are zero (at the zero lower bound). This is called a liquidity trap and there will be neither economic stimulus nor inflation. The reason is spelled out in the IS-LM model, invented by John Hicks to quantify Keynes’s theory. The Kahn Academy actually has a nice set of tutorials too. The idea is quite simple once you penetrate the economics jargon.

The IS-LM model looks at the relationship between interest rate r and the general price level/economic productivity (Y). It’s a very high level macroeconomic model of the entire economy. Even Hicks himself considered it to be just a toy model but it can give some very useful insights. Much of the second half of the twentieth century has been devoted to providing a microeconomic basis of macroeconomics in terms of interacting agents (microfoundations) to either support Keynesian models like IS-LM (New Keynesian models) or refute it (Real Business Cycle models). In may ways this tension between effective high level models and more detailed microscopic models mirrors that in biology (although it is much less contentious in biology). My take is that what model is useful depends on what question you are asking. When it comes to macroeconomics, simple effective models make sense to me.

The IS-LM model is analogous to the supply-demand model of microeconomics where the price and supply level of a product is set by the competing interests of consumers and producers. Supply increases with increasing price while demand decreases and the equilibrium is given by the intersection of these two curves. Instead of supply and demand curves, in the IS-LM model we have an Investment-Savings curve and a Liquidity-Preference-Money-supply curve. The IS curve specifies Y as an increasing function of interest rate. The rationale  that when interest rates are low, there will be more borrowing, spending, and investment and hence more goods and services will be made and sold, which increases Y.  In the LM curve, the interest rate is an increasing function of Y because as economic activity increases there will be a greater demand for money and this will allow banks to charge more for money (i.e. raise interest rates). The model shows how government or central bank intervention can increase Y. Increased government spending will shift the IS curve to the right and thus increase Y and the interest rate. It is also argued that as Y increases, employment will also increase. Here is the figure from Wikipedia:

540px-Islm.svg

Likewise, increasing the money supply amounts to shifting the LM curve to the right and this also increases Y and lowers interest rates. Increasing the money supply thus increases price levels as expected.

A liquidity trap occurs if instead of the above picture, the GDP is so low that we have a situation that looks like this (from Wikipedia):

440px-Liquidity_trap_IS-LM.svg

Interest rates cannot go lower than zero because otherwise people will simply just hold money instead of putting it in banks. In this case, government spending can increase GDP but increasing the money supply will do nothing. The LM curve is horizontal at the intersection with the IS curve, so sliding it rightward will do nothing to Y. This explains why the monetary base can increase fivefold and not lead to inflation or economic improvement. However, there is a way to achieve negative interest rates and that is to spur inflation. Thus, in the Keynesian framework, the only way to get out of a liquidity trap is to increase government spending or induce inflation.

The IS-LM model is criticized for many things, one being that it doesn’t take into account of dynamics. In economics, dynamics are termed inter-temporal effects, which is what New Keynesian models incorporate (e.g. this paper by Paul Krugman on the liquidity trap). I think that economics would be much easier to understand if it were framed in terms of ODEs and dynamical systems language. The IS-LM model could then be written as

\frac{dr}{dt} = [Y - F]_+ - r

\frac{dY}{dt} = c - r - d Y

From here, we see that the IS-LM curves are just nullclines and obviously monetary expansion will do nothing when Y-F <0, which is the condition for the liquidity trap. The course of economics may have been very different if only Poincaré had dabble in it a century ago.

2104-12-29: Fixed some typos