Monthly Archives: June 2015

Book Review: The Second Machine Age

Throughout history, people have predicted the end of work, but so far it has never materialized. Is this time different? In their book The Second Machine Age Erik Brynjolfsson and Andrew McAfee argue it is. Machines already beat people regularly in chess and in the near future they will drive our cars, educate our students or do Amazon’s logistics. The authors call this the 2nd machine age. The first machine age, the industrial revolution, fundamentally transformed the world of the 19th century. In a similar way, the infinite re-combinations of computers and robots will transform our society.

Lao Tzu allegedly said “Those who have knowledge, don’t predict. Those who predict, don’t have knowledge.” Indeed, the authors show that some predictions about the new age have proved remarkably wrong. Until recently, for instance, most experts believed that computers are bad at pattern recognition and good at routine tasks. Today it seems hard problems (computing a strategy for chess) are easy for computers, but easy tasks (found in the care or service sectors) are surprisingly difficult. In general however, the frontier of things machines can do is shifting rapidly. Automatically generated contents in newspapers or machines grading students’ essays are just two examples of what intelligent machines can do. The world seems at an inflection point. The authors invoke the famous Moore’s law that computer power doubles every year and find exponential growth confirmed in many dimensions of technological progress.

Skeptics wonder why this has not transformed into higher growth rates in the last years. Indeed, freely available content and cheap replication make it hard for many economists to see the profitability of it all. And yet, there is massive positive change even if its traces are more difficult to measure. First, the internet, Brynjolfsson and McAfee argue, has risen well-being by much more than growth in GDP; so much, in fact, that the 2nd machine age needs a different metric to think about social progress.  The authors estimate that intangible assets would add another 2 trillion to existing capital assets in the U.S. alone. Second, it will need time to make people realize the full potential, just like in the 1st machine age: it took several decades from the invention of the steam engine to using it in transportation and construction. Third, modern information technology lets people increasingly access to the world’s stock of knowledge. Options multiply. This is good news.

The bad news is, the benefits are not evenly spread. Sure, consumers benefit enormously, but the majority of employees will lose. Skill-based technological change puts a huge premium on college degrees, and creates job loss especially in routine blue- and white-collar occupations. Technical change can be relentless. Photo company Kodak, which in its heyday employed nearly 150,000 people, filed for bankruptcy in the same year Instagram, merely employing 15, was sold to Facebook for $1 billion.  Upswings in the economy create less and less new jobs, the share of labor in GDP is on decline in recent years, and even within this share, the spoils are distributed more and more unevenly. We experience the rise of what they (and others) call the superstar economy.

The dynamics of the superstar economy can be described in many ways: the Matthew effect (“For unto every one that hath shall be given, […] but from him that hath not shall be taken even that which he hath.”), a winner-takes-it-all society, or, more prosaically, the dominance of power laws. One J.K. Rowling sells a multiple of books of her closest competitors, those competitors sell a multiple of their closest rivals etc. These effects are hard to deny. Even if the authors refute simplistic fallacies, they are remarkably ambivalent about the possibility of what Keynes famously called technological unemployment. Granted, voluntary unemployment might be a society’s ultimate goal, freeing human potential from menial occupations, but this would require a very different social contract from the one we are seeing nowadays.

It is hard to predict in which domains the comparative advantage of humans will survive. Skills complementary to machines, e.g. engineering or data analysis, will probably be in higher demand. ‘Nerd is the new sexy’, as they say (though I suspect that it is, by and large, nerds who say that). To rather race with than against the machines the authors suggest a (laundry) list of short-term policy recommendations: teach children well, use technology, improve matching on the labor market, more infrastructure etc. In the long run, the authors recommend more controversial tools such as basic income schemes, or labeling products with high percentage of human content.

All in all, this is a very easy, sometimes gripping, even alarming read. The authors’ liquid writing style, in combination with a nice batch of anecdotal and systematic evidence attracts huge readership in and beyond academia. In some ways, the book is remarkable, especially given its provenance: M.I.T. It seems that the recent crisis has truly shaken mainstream economics and opened the cracks for heterodox thinking. Talking about technological unemployment seemed to be close to blasphemia only years ago. In this sense, the book is a welcome game changer that allows the public discourse to talk about really important issues of our time. The problem is, many economists tend to be ill equipped for these purposes.

In the same way economists for long have defined away the problem of inequality as none of their business, job scarcity has, by and large, been a temporary or government-related issue. In some sense, this has changed. The new rise of automatization has created a lot of scholarly interest, much of which is referenced in the book: David Autor, Daron Acemoglu, Joseph Stiglitz, Lawrence Summers to name but a few. The diagnosis coming from this research seems sound – as far as I can judge – even if somewhat partial. Most examples come from technology enclaves around M.I.T. and Stanford. It is a bit alarming that many of the aforementioned authors even use the same case studies, which questions the generalizability of these findings. A bit of long-term perspective would also sometimes be consoling: perhaps the largest transformation of labor markets so far was not the industrial, but the agricultural revolution, which essentially made everyone work for endless hours on the fields, only to barely survive on a highly unbalanced diet of mono-crops.

Whereas the diagnostic part of the book is fascinating, the sections about policy recommendations are disappointing. They basically don’t go beyond the litany of ideas found in any econ 101 textbook. Looking at some policy recommendations in more detail fully reveals a kind of helplessness usually only seen in a rabbit shortly before being gobbled up by a snake. When it comes to schooling the authors first criticize the tendency of educational institutions of being too lax and not making students work enough before they praise Montessori schools for letting pupils decide themselves what they are best at.

In more general, the book shows the kind of lop-sided thinking which cares much more about allocation than distribution. However, the main issue has and always will be a problem of distribution. Taking away unemployment benefit systems and job agencies, takes away (legally defined) unemployment, but it does not take away underemployment, inequality and poverty. In this sense, the recommendations found in the book are fairly limited. If social scientists like Karl Polanyi are right, the first industrial revolution generated a new kind of welfare model. Back then higher growth did also not turn automatically into benefits for everyone, and perhaps would have never, if not for better organization and more solidarity among workers. If contemporaries of the industrial revolution had recommended something akin to things Brynjolfsson and McAfee suggest, we would still have Speenhamland (British 18th century poor laws) instead of the modern welfare state. In this sense, the new revolution, assuming that there is one, will only benefit everyone, if accompanied by fundamental changes in the social contract.

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Hay Fever, Sugar Intake and my Personal Frustration with Modern Medicine

Let me begin with a disclaimer: I am personally affected by hay fever, it is (late) spring, and no wonder I digress on a topic, I know very little about. I do know (even if surprisingly badly), however, my own body, so once I exhausted all tools of modern medicine to combat the mother load of unnecessary illnesses I started experimenting with myself. I read a lot about hay fever from non-scientific sources and tried to put some of the recommendations into practice. In one year, I did a relatively drastic diet doing away with ‘white calories’, refined white sugar, white flower etc. My hay fever did not go away, but turned out to be less of a nuisance than usual.

I told this to my physician who won’t have any of it. He had never heard or read about a connection between sugar consumption and hay fever. As a scientifically trained doctor, he did not know the causal mechanism linking sugar to hay fever and thought of my idea as a fluke. Of course, it is well known that sugar creates a lot of problems for immune system and is the culprit of many civilization diseases like diabetes. But hay fever?

I began screening the scientific literature – some 100 studies and counting. Perhaps screening is still somewhat exaggerated, since I have a very basic understanding of modern medicine, and obviously struggle with technical terms. However, I am semi-literate when it comes to empirical methods and statistics and thought I give it a shot.

A few general observations along the way: Causality issues, the traditional bone of contention in many fields of social sciences, are no strangers in the hard sciences either. Most studies I read are based on some sort of correlational analysis, with observational data. There are a few clinical trials (some on animals), but all in all it is hard to uncover the roots of a phenomenon as complex as hay fever.

What seems to be clear is that hay fever (allergic rhinoconjunctivitis ) is a sort of civilizational disease: specific (Western) civilizations seem to be particularly vulnerable. Hay fever barely exists in some very poor countries, and was already very important in Europe and North America the 19th century, where it has increased tremendously in the last decades. Just check this google ngram using the German word for hay fever. We see that hay fever as a problem mentioned in the literature has increased over time, first until the second world war, and then from the 1970s onwards to an all-time high current times (I have no story for the jumps in the 1940s and 1950s, but the graph would look similar if smoother using the English term). Quite interestingly Eastern Germans only started having hay fever after reunification (Mutius et al. 1998).


Hence, although it is clear that genes do play a role, there has to be a huge environmental or behavioural driving force explaining the trend towards more hay fever. Three dominant hunches are contamination, hygiene, and nutrition. Some scholars argue that air pollution makes the effect of pollen on the immunologic system more aggressive. Others argue that modern hygiene has counter-productive effects, making the human body reacting strongly to hitherto innocuous substances like pollen. There is some evidence from studies comparing people being exposed to livestock (especially on farms, but also pets (e.g. Waser et al. 2004, Smit et al. 2007). There are quite a few studies relating the incidence of hay fever to family size: in larger families small kids in early childhood mutually infect each other on a regular basis, thereby training the immune system against real as opposed to ‘fake’ threats (e.g. Strachan 1989, Ponsonby et al. 1999, Forastiere et al. 1997, Raesaenen et al. 1997). Given that all these observations are based on observational data, and family size might be a proxy for many things, it is still unclear whether these findings are truly valid, and how exactly the causal mechanisms for the hygiene hypothesis works.

The most bewildering literature deals with the effects of nutrition. There are a few (often industry-financed) studies on breast-feeding and different types of formula milk for infants (e.g. Berg et al. 2008). There are several studies relating fatty acids to hay fever (Murray et al. 2005, Laitinen et al. 2005). There are studies arguing that vitamins and a (Mediterranean) diet based on fruits and vegetables reduces hay fever (Ruehl et al. 2007, Zaknun et al. 2012). Yet, there are often complex causal relationships linking nutrition to allergies (e.g. Rosenlund et al. 2012), and quite a few studies are unable to demonstrate said relationship. For instance, Miyake et al. (2006) argue that the reason why Japanese are relatively unbothered by hay fever is less related to vitamins and more to other peculiarities of Japanese diet like the intake of seaweed.

To the best of my knowledge, no study has directly probed the relationship between sugar consumption and hay fever. There may be studies which did not find anything and did abstain reporting a null finding, but all in all, sugar does not figure prominently in the current medical debate. I think that is a pity. My own experience biases me toward a belief that there is some truth to the sugar hypothesis. But sugar is also a well known trouble maker for other civilizational diseases such as diabetes. It is also well known to create problems for the immune system (by blocking vitamins and causing digestive difficulties). It is therefore tempting to test the relationship between sugar consumption and the occurrence of hay fever more systematically.
Since I do not dispose of an adequate micro dataset I return to one of my work-horse tools: country comparisons. A consortium of many research institutes (the ISAAC or International Study of Asthma and Allergies in Childhood link) has collected data for the late 1990s from more than 50 countries around the world (The lancet article 1998). I use this data (average information in cases where several observations are available within a country).
For sugar consumption I use data compiled by a Swedish website, which measures annual intake of per capita. The following graph shows a scatter plot for the two types of information.


Nigeria and Paraguay pop into the eye immediately. These countries have more than 30 percent of the children showing symptoms of hay fever, and relatively low levels of sugar consumption. In contrast, other countries with low sugar levels like Ethiopia or Albania also have very low levels of hay fever. The trend line for all countries shows a moderately increasing relationship between sugar intake and hay fever, but is clearly affected by extreme countries like Nigeria, Paraguay, or Singapore.
Looking at the graph the litmus test has resulted grayish. So let’s add a little more information to the dataset and see whether we can isolate the relationship between sugar consumption and hay fever from confounding factors. To this end, I collected several types of information:
o I added information about the share of young population (up to 15 years old) of the total population. This should proxy household size in these countries and therefore control for the hygiene hypothesis.
o I include World Bank estimates on GDP per capita in purchasing power parities as a proxy for many things: standard of living, life style, access to modern medicine.
o Finally, I include latitude to control for differences in vegetation. One would assume that well known forms of aggressive pollen are more likely in specific climate zones. I use absolute numbers for the latitude to account for the fact that there are two hemispheres, and use a squared term, because it is middle latitudes where (e.g. ragweed) pollen activity is highest (at least within that short period of time that is spring).
o In further tests I use other specifications which also include, continental dummies, dummies for countries producing a lot of ethanol (i.e. sugar extraction for non-food purposes) etc.

I excluded extreme outliers (Nicaragua and Paraguay). I have no story why allergy is so strong in these two countries. The results for the remaining countries are only as good as your willingness to accept this exclusion. Other outliers (such as Malta or Singapore) don’t prove to invalidate the results. Given that the data in the scatter plot is more cone-shaped than equally distributed (pointing to what econometricians call heteroscedasticity), I use regression models with robust standard errors.

The results of these regressions are quite remarkable, considering the paucity of the underlying data. Sugar consumption is the most robust factor, and substantively quite strong. Let me talk you through the other factors first: As expected, incidence of hay fever rises with income levels. The effect is not as strong as I thought. Increasing per capita income by another 1000$ (e.g. from Belgium to Austria) only increases the incidence by a fifth of a percentage point. I.e. you would have to jump 5000$ (e.g. from Belgium to US income levels) to reach another percentage point of affected population. The share of young population does not matter unlike in many micro studies. Maybe because it is a poor proxy, or because other factors of life style matter more than having large families. The model does predict that with latitudes farer away from the equator first the incidence rises, and then (very far away) drops again. Up to latitude 21, the incidence rises, thereafter it falls. At the extremes, e.g. going from the equator to another 1 degree north or south, the (marginal) effect is .3. That is going 3 degrees north or south the incidence of hay fever increases by a percentage point.
Now to my main concern: sugar consumption. To repeat, the metric is kilos per person per year. The mean of the sample is 33.4 kilos, but with tremendous diversity (as seen in the plot above). Adding another kilo of sugar to the average diet in a country increases incidence of hay fever by 0.15 percentage points. I.e. increasing sugar consumptions of Japan (a relatively modest 22 kilo) to Australia (with a whopping 50 kilo) would add another 5 percent(age points) of people suffering from hay fever to the population. That is no trivial quantity. The effect is statistically significant, and as robust as the limited data allow. The following graph gives a visualization of this (partial) effect.


I imagine that medical scientists would ridicule this kind of ‘empirical evidence’. Clearly, my analysis is limited in many ways: it uses macro data, which is only cross sectional (both sugar and allergy data hard to get and compare across time), observational, and I had to omit many other confounding factors. Nonetheless, I would contend, this is a promising start. With good micro data, and perhaps some experimental trials, it would be interesting to see whether changes in diet really alleviate the symptoms of hay fever, or even reduce its incidence. I very much hope that a group of medical scientists one day tries this out. I am willing to help out, as much as I can.


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It’s Still Time to Save Yangon from Itself

Late development can have advantages: you don’t need to make the same old mistakes. Except that most often you do. Hyper-urbanization is such a mistake: (capital) cities in poor and emerging markets have grown like wildfire in last decades. Just look at the spread of Indian cities in the last twenty years. The figures show satellite data on night-time luminosity for 1992 and 2012.


One could only hope that in the remaining cases in which the brunt of urbanization is yet to come we can avoid some of the massive congestion effects. Myanmar’s major cities are such a case. 70 percent of the population still live in the country side. What should we expect of Burmese cities in the future? In the last 20 years China’s urban population has increased by some 20% points. If we use this yardstick to project the size of Burmese urbanization, Yangon could easily grow up to 10 million from currently 6 million inhabitants in two decades. Similar things would apply to the other main cities (mainly Mandalay and Naypyidaw). And that’s not even counting the possibility that the country could massively liberalize foreign trade.

The problems, already staggering in one of the world’s poorest countries would be enormous: traffic, pollution, public health. It doesn’t particularly help that the country has been heavily centralized, politically and administratively ever since colonialism to the current regime. However, and rather ironically, economic growth and sectoral change, very often heralded as the quintessential tools to lift countries out of poverty would only exacerbate the situation leading people to flock into the major cities.

What a shame. Some hundred years ago, cities like Rangoon were the jewels of the British empire and the cause of many a British officers and literates’ hazy dreams. With good reasons if you look at some of the historical paintings and photos.


Some of this beauty has survived urbanization. See here or here. But the question is for how long. Urbanization, growth and excessive modernization destroys a lot of opportunities and environmental, cultural and social assets. It’s important to highlight that it’s not (only) about fancy colonial architecture, which usually is where most political energy flows into. It is much more about urban planning and keeping the broad streets, the big trees that maintain a micro-climate and allow for a healthy environment.

Just look at two different Asian cities and the importance of green landscapes and forest for recreation and micro-climate the two cities have given: Bangkok vs. Singapore. Bangkok is a good example of an urban Moloch eating into green countryside, and doing away with a lot of its historical charm and, quite literally, breathing space. Singapore, being a very wealthy political island in the Malaysian archipelago, jealously watched over its green assets (among other things, presumably to have a large enough reservoir of drinking water).


Yangon has the choice of becoming like Bangkok, lot’s of green further and further outside the city, and an urban jungle inside, with low quality of life, huge commuting times (especially for the poor) etc.; or a place like Singapore, where traffic and pollution is manageable (for a city that size), and people have breathing space. So much that even foreigners will pay a visit. Political activism is crucial. Tourism will be an important ally, and tourist come if there is decent infrastructure plus impressive sights. Let’s just hope that the infrastructure (and urban planning) arrive before the sights disappear.

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