Thread on Programming Ability

Ethan Mollick brought this Nature article to my attention. One of the authors Chantel Prat, is also on the thread.

The sample size for this study is only 36, so we should think of it as preliminary work toward understanding how people learn to program.

Their abstract, with emphasis added by me:

This experiment employed an individual differences approach to test the hypothesis that learning modern programming languages resembles second “natural” language learning in adulthood. Behavioral and neural (resting-state EEG) indices of language aptitude were used along with numeracy and fluid cognitive measures (e.g., fluid reasoning, working memory, inhibitory control) as predictors. Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the variance, followed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numeracy (2%). These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments.

Learning Python, at least at first, is more like learning a foreign natural language than it is like doing arithmetic problems.

There are still many open questions in this area, so I see this paper as an important small step in the right direction. I have also done a study on this topic.

Endless Frontiers: Old-School Pork or New Cold War Tech Race?

The Endless Frontiers Act passed the Senate Tuesday in a bipartisan 68-32 vote. What was originally a $100 Billion bill to reform and enhance US research in ways lauded by innovation policy experts went through 616 amendments. The bill that emerged has fewer ambitious reforms, more local pork-barrel spending, and some totally unrelated additions like “shark fin sales elimination”. But it does still represent a major increase in US government spending on research and technology- and other than pork, the main theme of this spending is to protect US technological dominance from a rising China. One section of the bill is actually called “Limitation on cooperation with the People’s Republic of China“, and one successful amendment was “To prohibit any Federal funding for the Wuhan Institute of Virology

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What Is Income?

The United States, like nearly all countries, has an income tax. What is an income tax? It’s a tax on income. What is income? That’s actually a very hard question.

The question comes up in a recent report by ProPublica on the taxes that very wealthy Americans pay (I’m not going to link to it, because the data was likely illegally obtained, and almost certainly immorally obtained, but you can easily find it). What’s really interesting is that never define income, but they do have an implicit definition which includes changes in net wealth. More on this later, but it does raise an important question under an income tax: what exactly should count as income?

For most wage and salary workers, income is fairly straightforward. It’s the compensation that your employer pays you in exchange for your labor services. Easy enough. There are some wrinkles. For example, most non-cash compensation is not considering income for tax purposes. And even some cash compensation, such as contributions to retirement plans, are not considered income. Still, pretty straightforward.

But what if you own a business? It gets a little more complicated. We could define your income as all of the money you receive when you sell goods and services to your customers. But that has a few problems. Let’s say you run a restaurant. You sell burgers for $5. Should you pay income tax on every $5 burger you sell? Keep in mind that you probably had $4.50 in expenses to sell that burger. You bought the beef, buns, and condiments. You paid your workers. You paid to “keep the lights on” (that’s how small business owners refer to utilities and other overheard). So our income tax system will only tax you on the $0.50 difference, which we usually call profit (in some years, of course, businesses have costs that exceed their sales revenue, in which case they owe no income tax).

Now for the really hard question: what if most of your income is derived from assets that you own? That’s where things get even more complicated, and both legal and philosophical questions come up.

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Should student debt be dischargeable in bankruptcy?

I’m not an economist who studies education or bankruptcy, and I’m not 100% confident I spelled dischargeable correctly. I am, however, above average at highlighting the difficulty of a question when dissuading a grad student from attempting an impossible thesis question, so let’s dig into this one, which sounds pretty hard to me.

First of all, it is very difficult to discharge student debt during Chapter 7 or 13 bankruptcy, but I think you still can do it if you convince a judge that continued attempts at repayment would create undue hardship i.e. put you in a state of poverty in the wake of previous good faith efforts.

That said, maybe you shouldn’t have to face literal starvation to discharge student loans. That’s a reasonable idea, but what would the broader consequences be? This is tricky question to untangle because there are both welfare consequences and knock-on effects where we are put down different forking paths of politics and policy.

If debt is dischargable, then lenders will expect lower rates of repayment. This increase in lender risk and decrease in return on capital would likely have immediate consequences in the form of:

  1. Higher interest rates
  2. Lower rates of loan approval
  3. Greater dependence on loan collateral
  4. Greater lender interest in what the loaned funds will be applied towards.

Before we tackle those, we also have to consider the different policy environment paths lenders may have to anticipate:

  1. The government stops subsidizing loans. This would lower tuition, but also lower access for low income students.
  2. A loan forgiveness program. Great for people with outstanding debt, but changes how expectations are formed forever going forward.
  3. The government launches a massive “free college” program that covers tuition at state colleges and universities. This would have all kinds of consequences potentially.

But where this really leaves us is with a billion dollar question: will dischargeable students loans lead to lower costs of higher education? I am confident that the answer is a definitive, unassailable maybe.

Higher interest rates is a pretty straightforward prediction, but the consequences are less clear. Higher interest rates could lead to less college matriculation, greater barriers for lower income individuals, and higher expected rates of bankruptcy, in part because decisions are being made by young people who don’t know the future, their future, or, really, anything. Related to this, lenders will become more discerning regarding who they lend to, giving more money on more favorable terms to matriculants from wealthier backgrounds, in no small part because wealthy parents are filled to the brim with collateral, making for excellent co-signers and providers of high school graduation gifts nicer than any car I ever hope to drive.

That is all boring and moderately obvious. It’s 4) that I’m most curious about. If you get into medical school, there is no shortage of institutions eager to dump several hundred thousand dollars in the foyer of your home. Part of the reason for this is the expected future income of physicians and their high graduation rates from medical school thanks to rigorous admission screening. But what is underappreciated is the 100% rate at which medical school students study medicine.

Not so with undergraduate education. You might study electrical engineering with a minor in computer science. You also might study something a senior tells you is the easiest major at your school. You might major in something that sounds fun or interesting. You might study Miscelleneous Studies, where Miscelleneous is a subject that is likely interesting and possibly extremely important, but within which you can choose classes that facilitate your avoiding learning anything useful or applicable in the labor market.

Herein lies the problem. Lenders treat loans for consumption very differently than loans for investment. Nursing and statistics degrees are investments. Art History classes (for most people) are consumption. What’s going to happen to higher education when the lender tells you you can have $200K at 3% to study any STEM field or $75K at 6% to study anything in the humanities? Will the demand for humanities degrees drop? Will the supply of humanities education recede? Are humanities and STEM education complements or substitutes?1

Let me phrase it a different way? Are wealthy fine arts majors cross-subsidizing STEM majors pursuing the first college degrees in their family? Or are they driving up the price of tuition because heavily subsidized credit is facilitating pre-career retirement lifestyles for 4 years?

All of this leaves me with the suspicion that dischargeable student loans will lower tuition for some while raising it for others. This heterogeneity would likely shift the electoral popularity of free tuition programs while also shifting the nature of those program. Maybe “free college” turns into a means-tested program. Maybe “free college” becomes “free STEM college”. Maybe both.

We could speculate what this means for loan forgiveness or subsidies, but this post is too long already and, as should be already clear, we’re not going to solve anything today. My elegant and succinct point is this:

When you massively subsidize a [knowledge, signal] bundled good for so long that it transforms into a [knowledge, signal, 4-year luxury cruise with your peers] bundle, and to accommodate that subsidy you protect your poorly constructed macro-investment in human capital by exempting it from bankruptcy proceedings, and as a result of this weird landscape a bizarre higher education industry emerges that is both one of the greatest achievements in US history but also a trap that 19-year-olds fall into because, really, is there any trap we don’t fall into when we’re 19, and from which thousands of people never financially recover, but if you just fix one part of it no one knows what will happen, and if you try to fix all of it at once in the back of your mind you’re afraid it could turn into the US healthcare industry part deux, well then what you have is a real and important problem that I don’t know how we will solve but I remain confident that other people will be very confident that they know how to solve it and they will get extremely cross with me for not sharing their confidence.2

So maybe don’t try to solve that in your dissertation.3 Might be safer to just definitively estimate the natural rate of interest that underlines all monetary transactions. That’ll be easier.

1The answer is “Yes”.

2 This is, to be extremely clear, not me picking on Ms. Reisenwitz’s tweet which was good and interesting and left me thinking about student loans for two days when I should have been working on the research topics I have actual expertise in.

3 Of course, if you do find a natural experiment where huge chunks of student debt were accidentally made dischargeable in a state for 2 years because of a legislative SNAFU, you should write that dissertation and put me in the acknowledgements.

History according to Polybius

It’s unusual for me to sit down on a weekend morning and read *literally checks notes* Polybius. This was assigned to me for a seminar. Here’s his proposal for the inevitable endless cycle of human leadership structures:

  1. Some humans are still alive. They band together because they are too weak to survive alone.
  2. A strong man who bravely defends the group in his youth becomes a monarch. “Kingship” is the next progression. Polybius assumes that people could consent to be under the leadership of a powerful and noble man.
  3. The king has children. The people venerate the descendants of the good king, but these princes and princesses will be spoiled and selfish. The princes “gave way to their appetites owing to this superabundance…” Thus, kingship becomes tyranny.
  4. Nobles overthrow the tyrants, and so become aristocrats. “But here again when children inherited this position of authority from their fathers, having no experience of misfortune and none at all of civil equality and liberty of speech… they abandon themselves to greed… and… rape…” The aristocracy becomes a corrupt oligarchy.
  5. Democracy emerges when people have “killed or banished the oligarchs” and the people remember being mistreated by kings. How does Polybius think democracy ends? Once again, it’s the new generation and the corruption they indulge in. Where do they end up? “… democracy in its turn is abolished and changes into a rule of force and violence.”
  6. There are two ways to get back to stage 1 monarchy. Life in the decline of a democracy is chaotic enough that people willingly back a strong man to protect them. Alternatively, he presents a “floods, famines, failure of crops… all arts and crafts perish…” scenario. A natural disaster, regardless of what stage in the political cycle humans were at before, will position the survivors to start again at monarchy.
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Overfitting Celebrity Pitches

The Washington Post created a fun infographic of celebrity baseball pitches.

I use this graphic in my Data Analytics class. Students are tempted to draw inferences about individuals from this data set. John Wall and Michael Jordan are great athletes, but in this case they are underperforming Avril Lavigne and George W. Bush. Do we conclude that Sonia Sotomayor missed her calling as an MLB player?

The first lesson here is that we should not assume we can predict where Harrison Ford’s next pitch will go based on observing just one pitch. A single pitch should be considered a random draw from a distribution centered around Ford’s average ability. Any single pitch could be an outlier.

Snoop Dog features twice on this graph. In 2012 he got the ball in the strike zone. Had we only seen that, we would want to conclude that he is a great pitcher. However, in 2016 he was way off to the right. In either case, overconfidence that he is predictably near a single pitch would have been a mistake.

Lastly, I use this graph to illustrate the concept of overfitting (investopedia definition). I suggest a model that is obviously inappropriate. What if we conclude from these data that anyone with the last name of Bieber will not be able to throw the ball in the strike zone? That model surely will not generalize. The problem is that if we test that prediction on the same data we used to train the model, the misclassification rate will be zero. If possible, start with a large data set and set aside some portion of the data for validation, before training a model. Having validation data for assessment is a good way to check that you haven’t modeled the noise in your training set.

The Research Process: Identifying the Ideas that Motivate You

Hello to all the EWED readers! I’m Dr. Darwyyn Deyo, an Assistant Professor of Economics at San José State University and a Visiting Scholar at the Knee Center for the Study of Occupational Regulation. I research law and economics, occupational licensing, and the economics of crime. I would also like to thank Joy for inviting me to write some blog posts this summer! I’ll be writing a series of posts about the curriculum of the research process, from the initial idea to the development of a complete draft. This week, I’m focusing on the mechanics behind choosing that initial idea.

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Does Cohabitation Predict Divorce?

My article, coauthored with Sarah Kerrigan and published last week, tries to answer the question. In short, the answer seems to be yes- cohabitation before marriage is associated with a 4.6 percentage point increase in the rate of marital dissolution. This is in line with much of the previous literature, which notes one big exception- choosing right (or getting lucky) the first time: “cohabitation had a significant negative association with marital stability, except when the cohabitation was with the eventual marriage partner”.

But we found some even more interesting facts while digging through the National Survey of Family Growth.

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Publications as Positional Goods, and the Division of Labor in Academia

My co-blogger Mike Makowsky has a thoughtful post this week about the academic publishing process. I wanted to offer a slightly different perspective on the same topic. But my perspective comes from someone who is not at a research university, and someone who has recently survived the tenure process.

A little background for those not completely familiar with the academic world: schools are usually considered either teaching or research schools. At first this seems confusing: both Clemson (where Makowksy is) and the University of Central Arkansas (where I am) require that faculty engage in both research and teaching. The difference is subtle, but the big hint is that Clemson is considered an “R1” school (the highest research designation) and has a PhD program with many graduate students. At a school like Clemson, research is valued more than teaching. At UCA, teaching is valued more than research. (Much more could be said about the differences, perhaps in a future post.)

We both engage in both teaching and research (as well as service!), but the emphasis is different. For me at UCA, the expectations of which journals I will publish in and how frequently I will publish are lower than at a school like Clemson. At Clemson, some of your publications should be in the Top 5 (or at least Top 10) journals from time-to-time. At UCA, if you published in one of the top journals, the assumption would be that you are probably leaving soon to go to an R1 school

I’m glad both types of schools exist, and my point here is not to disparage either type of school. But the difference is important for thinking about the academic publishing process.

For someone at an R1 school, publications in top journals are positional goods. Makowsky doesn’t say this exactly, but that’s my takeaway from his post. There are only so many spots available in these journals, and they have value because there is only a fixed number available. And since there has been, over the years, a lot more economists doing a lot more research not all of the great papers will end up being published in one of the top journals.

Upshot: there are a lot of great papers being published in Top 50 or even Top 100 journals! Let me pick on myself. As I said, I recently successfully survived the tenure process. My publication record was good enough. You can inspect my publications over at Google Scholar. I’m proud of these publications. I think some of them are really great. But I’m fairly confident that I would never earn tenure at Clemson with these publications. Instead, you need a publication record like Makowsky.

What’s interesting here is that Mike and I occasionally publish in some of the same journals. Public Choice and Constitutional Political Economy jump out to me. These are, in my view, very fine journals. Lots of interesting research is published in these journals. I’m especially proud of this paper in Public Choice. But if someone published only in these two journals and journals like them, they wouldn’t get tenure at an R1 university.

So what do we do with this information?

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The Rise and Fall (?) of Bitcoin Price

Well, it has been a fun party. Here is a chart of Bitcoin prices over the last year or so. Folks that bought in before December were up X4 or more by April. Woo-hoo! But prices have dropped by half in the past two months. Many articles were published over the winter justifying ever greater heights for Bitcoin. It was to be the digital equivalent of gold as a store of value. Also, it is touted as being decentralized and free of government manipulation – – a global, privatized people’s currency. What happened?

Source: Seeking Alpha
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