Excited about the super Tuesday? I am! So I have decided to focus on an issue that might not make a big difference in terms of who wins and who loses, and yet, it does affect policy making. This is a long story concerning science, politics and their very difficult relation. I had to split it into three blocks. Stay tuned for the next ones!
Part 1: on Sanders unconventional economics
In a very detailed analysis by the title: “What would Sanders do? Estimating the economic impact of Sanders programs” (download), the economist G. Friedman has recently argued that Sanders proposed policies would boost the GDP in the US, favouring a more equal distribution of wealth and having a positive impact in the long run at many levels. Here is a few key sentences from the one page abstract (see link above):
The economic proposals of Senator Sanders can be grouped under three headings. First, he proposes spending programs for infrastructure, education, retirement security, health care, and to address the threat of climate change. Second, there are progressive tax increases to pay for these programs, and lastly there are regulatory changes to raise wages and to reduce discrimination against women. […] The growth rate of the real gross domestic product will rise from 2.1% per annum to 5.3% so that real GDP per capita will be over $20,000 higher in 2026 than is projected under the current policy. Faster economic growth and redistributive taxation will raise the growth rate of median income from 0.8% per annum to 3.5%, adding nearly $22,000 to median household income in 2026. Higher GDP comes with increased employment, specifically nearly 26 million additional jobs in 2026. […] Medicare-for-all will lower the cost of health care and contain health care inflation even while saving thousands of lives […] After increasing in the first years of the Sanders Administration, the Federal budget’s cash deficit will drop sharply and there will be a significant and growing surplus in a Sanders second term. Instead of a deficit of $1.3 trillion in 2026, there will be a large budget surplus.
This is a strategically important issue: Bernie Sanders is attacked by his opponents in the US by claiming that his ideas are far from being realistic, they will lead to excessive spending at the federal level and ultimately will fail. Even among the liberals in the country, many consider Bernie’s plan like a nice dream, an impossible to achieve utopia which is only possible in small countries like Sweden, Denmark and a few more (by the way, Denmark is considered a model of liberal socialism here in the US, please somebody tell the Danish they should stop breaking character!). The key point is that a technical analysis, grounded on formal mathematical models, rather than wishful thinking, seems to predict that such proposed measures are not only feasible, but they have a lasting positive effect that can be quantified using standard economic measures.
Here comes the New York Times, which has openly taken position in support of Hillary Clinton, citing as a reason exactly the matter of who among the candidates is more likely “to get the job done”. I am sure this is ringing a lot of bells in several other countries: really nothing new in itself. It is rather interesting the way the NYT has decided to carry out its attack against the described analysis. The title of the article by J. Wolfers is very explicit in this sense: “Uncovering the Bad Math (or Logic) of an Economic Analysis Embraced by Bernie Sanders”
It is quite annoying that the author has decided the math underlying a certain model is not sound, but then he backed up claiming that the fault should be actually found in the logic of the model itself. The two things can be both faulty of course, but are not interchangeable. Anyway, this is the important bit:
Most economists believe that temporary increases in government spending will yield temporary increases in output. To see why the effect of stimulus is temporary, realize that if raising government spending raises output, then because the end of a stimulus program means cutting government spending, the same forces are later set in motion, but in reverse. And so in the standard story, a temporary stimulus improves the economy, but only temporarily. Here’s the problem: Mr. Friedman’s calculations assume that removing a stimulus has no effect. The result is that temporary stimulus has a permanent effect. […] There are two interpretations of Mr. Friedman’s findings. The first is that he has simply gotten his math wrong. The second is that he has a different view about how the economy operates. Either way, his numbers don’t represent conventional economic thinking.
It is an overused rhetoric tool: validate a model or a theory, by appealing to its popularity (or lack of thereof). This is a common misconception: it is indeed helpful sometimes to simplify by saying e.g. the vast majority of the scientists believes the models showing Climate change is caused by humans are correct. But this is indeed a simplification. Truth is that the majority of the scientists might be (and have been in the past) wrong. They usually know they are wrong when something new comes out that forces them to change their mind (magic words: paradigm shift). A more correct way to say it might be: there is overwhelming evidence supporting the models etc… The number of scientists acknowledging the evidence is usually correlated, but it comes as a consequence, and it is not really a cause. Let’s leave this thought aside for a moment (I’ll deal with this in the next two parts) and let’s move to the fun part: falsification and character assassination.
My reaction in reading those lines is: THANKS GOD! I thought after the last 8 years of unpredicted multiple economic crises (plural!) any journalist had gotten that “conventional economic thinking” (i.e. neoclassical or mainstream economics) is a load of the conventional crap. Let’s linger a bit in the comparison UE-USA: the former is still enduring massively enforced cut-spending strategies (which conventional economics predicts should trigger economic improvements), and the latter has steadily adopted strategies centred on government spending. Which of the two systems has been most successful in coping with the crisis? Here is a detailed analysis of how well it went in the EU, by P.Krugman (non conventional economics, either), which can be summarised in one simple chart:
I am sure this was really not surprising.
So how does it work? We have one unconventional model claiming State investments have long term beneficial effects and another conventional model claiming the effects reverse into negative as soon as the investment ends. The second one seems reasonable: the free market might become “addicted”, requiring more and more state support and investments to be sustained, incapable to walk by itself. There are people actually claiming this with a straight face, so we are lucky this is not a popularity contest (oh, wait… it is!).
It is easy to kill this reasoning appealing to a simple case study. The case of the General Motors is perfect for the gargantuan scale it involved, and a page on wikipedia about the bankruptcy of the General Motors is sufficient for this purpose.
On July 10, 2009, General Motors emerged from government backed Chapter 11 reorganization after an initial filing on June 8, 2009. Through the Troubled Asset Relief Program the US Treasury invested $49.5 billion in General Motors and recovered $39 billion when it sold its shares on December 9, 2013 resulting in a loss of $10.3 billion. The Treasury invested an additional $17.2 billion into GM’s former financing company, GMAC (now Ally). The shares in Ally were sold on December 18, 2014 for $19.6 billion netting $2.4 billion. A study by the Center for Automotive Research found that the GM bailout saved 1.2 million jobs and preserved $34.9 billion in tax revenue. In the reorganization, Hummer, Pontiac and Saturn were closed. After initially moving to shut down the Swedish brand Saab, GM eventually sold it to Dutch automaker Spyker.
So an initial temporary investment of almost 50 billions in 2009 ended up five years later with net profit for the investor (the Government) and saved more than a million jobs, preventing the system from spiraling down (jobless people would have spent less, which would have caused further crisis etc.).
It seems investing money did trigger long lasting positive effect which were not stopped by the end of the government investments. Who would have known, right?
Predicting is complicated and projections are not a piece of cake to interpret, but there are ways to use what we have with good results. I’ll try to explain the main problems with creating reliable models in the next bit.
Oh, by the way, I am writing in English, so read it with an italian accent! The reasons are: 1) apparently I have potential readers who do not speak Italian (hard to believe, but let’s be honest, the world is packed with weird people). 2) I can avoid using accented vowels with an English keyboard (long uninteresting story).