Data Landfill

This semester, the textbook I am using to teach data analytics is Business Intelligence by Sharda, Delen, and Turban. In Chapter 3, the authors describe how a data warehouse fits into a business enterprise. A data warehouse (DW) is more than a spreadsheet. It is more than a two-dimensional transactional database. A DW takes expertise to build and maintain. If done correctly, users within the company will be able to quickly access important data that they need to make decisions. Having a good DW is essential for any large enterprise today.

Near the end of the chapter, the authors list problems that are encountered when technologists go in to build a DW for an enterprise.

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In Defense of Austenland (2013)

Imagine you finish watching The Greatest Showman and immediately watch it all again. The sets are beautiful and the movie inspires you to believe in the American Dream again. Looking for someone who shares your joy, you google movie reviews. Up comes the NYT website and some reviewer has written, “I expected a movie about the circus to have clowns, but director Michael Gracey disappoints.” You would be upset and feel the need to set the internet record straight.

Today I write to defend female filmmaker Jerusha Hess and her delightful directorial debut Austenland (2013). I will not link to or quote the nasty NYT review.

Jerusha Hess is the brilliant writer of Napoleon Dynamite (2004). I loved Napoleon Dynamite so much that I used my screen printing assignment in high school art class to create custom shirts with references to the movie. If you don’t get Napoleon Dynamite, you really don’t get it. It is funny, and every visual feature is intentional.

Austenland is also funny. There are slapstick moments that made me laugh. I also enjoyed little details such as the recurring motif of characters holding fake animals. Ironically, one of the only real animals is a newborn horse foal, who ultimately turns out to be part of a lie. The fake things are real and the real things turn out to be fake. This film is meta. It has layers, like Shrek. It is only inside of the theatrical play within the theme park that the leading man expresses his true feelings.

On the surface, this film is a guilty pleasure romantic comedy. It does deliver on fantasy wish fulfillment, which I think it should. Impressively, it delivers on wish fulfillment while simultaneously delivering interesting commentary on fantasy versus reality.

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Date-onomics

This short spark plug of a book written in 2015 by author Jon Birger was hard to put down. The book is informative on the idea of “marriage markets” and makes the case that, “college and post-college hookup culture, the decline in marriage rates among college-educated women, and the dearth of marriage-material men willing to commit are all by-products of lopsided gender ratios and a massive undersupply of college educated men.” (p. 5)

Recall from an earlier blog post, when there are more women relative to men, women compete with each other and effectively lower their “asking price” (their share of the marital benefits). This also applies to dating markets too. If you’re having trouble seeing how sex ratios matter, consider this example from the book,

“Among undergrads at UNC there are 50 percent more women than men …” That is for every 40 men there are 60 women which means 3 women for every 2 men, “If you want to visualize what 3:2 looks like, imagine you’re back in college. Imagine it’s late at night, and you’re hanging out with friends in someone’s dorm room. Imagine everyone has had a few beers, the mood is flirty, and people are thinking about pairing off. Now imagine there are three women and two men.” 

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An Economist Learns Piano: Part 1

My life didn’t change all that much due to Covid-19 pandemic. I live in a small university town. I mostly continued to go to work and my kids mostly continued to play with their neighbor friends. After a brief hiatus, I ended up growing much closer to my neighbors. One nearby couple are even the godparents my most recently born child.

The university at which I teach is a liberal arts school…. And I teach economics. I knew that these music-type of students and professors were out there, but I didn’t have much exposure. I recently obtained a zero-priced piano and had a good 2-hour conversation with a music major. This post illustrates part of I’ve learned so far. First, a graph.

Whether we want to or not, many of us know the musical scale thanks to The Sound of Music. What I didn’t know was that there is not a uniform distance between all of those notes. Along the x-axis is the note labels (do re mi fa so la ti do). The pitch is characterized by an increment called a step. Given some arbitrary pitch for the first note, do, each subsequent note is a specific number of steps away. The pattern is that each increment between notes is 1 step, except the step from mi to fa and from ti to do. Those are half steps. The result is a segmented function.

Now, this pattern can be applied to a piano.

There are a total of 88 keys on a piano. Some are black, others are white. But all of them are a half-step increment from the prior and subsequent key. IDK why there are small black keys and big white ones. But pianos would be a lot bigger without the narrower black keys. Every single white key on a piano is labeled with a letter. The letter *does not move*. A ‘C’ is always a ‘C’.

What can move is the scale label, do, which can be any key. The pattern identified in the graph above must be maintained. To play ‘in the key of C’ means that ‘C’ is identified as do. The remaining keys can be labeled.

The key of ‘C’ is easy because the entire scale can be played on all white keys.

Those two half steps that we mentioned earlier? Those might have been on a black key – except that there is no black key between ‘B’ and ‘C’ or between ‘E’ and ‘F’. The B-C keys are adjacent. That means that their pitch is a half-step apart – exactly what is necessary for the pitch difference between mi and fa. The same is true for the E-F step and the pitch difference between ti and do.

What about the black keys? We can see their roll by placing do on a different lettered key. We can start on ‘D.  

do to re is a full step, from ‘D’ to ‘E’ – skipping the black half-step that’s between them. For re to mi we need to skip a key, all keys are a half step apart. So? To the black key! We skip ‘F’ and land on the subsequent black key. Then, fa falls on ‘G’, a half step and a single key higher in pitch. ‘A is a full step away from ‘G’, so that’s so. la is another full step away on ‘B‘. Recall that all of the keys are separated by a half-step – the key colors are 100% unimportant. ti is a full step higher – but there is no key separating ‘B’ and ‘C’. So, we skip up to the black key again just as we did with mi. Finally, do is a single key and a half step more.

There you have it! One of the things that a pianists can do is play the entire scale, from do to do, starting from any lettered key on the piano. I can’t do that yet, but golly I certainly feel like I have a better handle of what I’m even looking at.

PS – My conversation took a long time and I had to nail down the difference between 1) The note label, 2) the pitch step increments, & 3) the piano key letter labels. Key letter labels and the note labels are ordinal variables while the steps are cardinal. So, the graph at the top of this post isn’t the only important relationship. The graph below includes the relationship between the step and key letter labels. A graph of the note label and the key letter labels requires a rudimentary knowledge of flats and sharps (with two different do’s).

Economic Research on COVID-19

The past 12 months has been dominated by COVID-19, the related recession, the government response, and other matters. But it has not just dominated our lives, it has also dominated new research, including research by economists!

Working papers from the National Bureau of Economic Research are one place to track on-going research by economists. While not all economic research is released as an NBER working paper (there are other series, and some economists just post them on their own website or department page), the volume of NBER papers should tell us something about the trends.

Here’s a chart showing the weekly NBER working papers that are in some way related to COVID-19. The first batch of three papers was released in late February, one long year ago. The second batch of nine papers came one month later. Since then, there have been papers released every single week, with the exception of the week of Christmas.

In total, there have 373 papers released that relate to COVID-19. The peak comes in late May and early June, with 61 papers released in a 4-week period and 21 of those papers coming out on May 25 alone. Since the May-June peak, we’ve seen a slow decline in papers on COVID-19, and we are now at our lowest level, with just 14 papers released in the past 4 weeks.

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Cryptocurrencies, 1: What Exactly Is Bitcoin?

Everybody knows that Bitcoin is a “digital currency”. But what does that really mean, and what is Bitcoin really good for? Who developed it? Turns out, oddly, that we don’t actually know. Can you buy a pizza with it? Turns out that perhaps the most famous pizza purchase of all time was made with Bitcoin.

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Academia as tax shelter

A very brief story:

My advisor was Laurence Iannaccone, student of Gary Becker, seminal and in many ways founding contributor to the economic study of religion, now of Chapman University. His observation is a common one in academia, a point of pride for some even, though that varies greatly by discipline, as does their market options outside of the academy. And, yes, flexible work schedules, post-tenure job security, and sometimes picturesque campuses all should be counted towards the total compensation of those fortunate enough to secure a faculty appointment. But the power of the observation goes far beyond proper labor market accounting.

As I find so often to be the case, there is good sociology to be done, but the best first step in doing so is a little bit of economics. To wit:

The academy is, on average, considerably to the left of the population at large. Now this difference, mind you, is grossly exaggerated by your typical right-wing windbag who seems to think that universities begin and end in the English department, but the difference remains. So why would your typical economics, chemistry, or architecture professor tend to be left of the popular center? Well, if the median self-identified lefty got to choose the federal and state tax rates, what would they be? Ok, and how much of that will I have to pay out of my non-pecuniary income? Until they figure out how to tax the thrill of pursuing my own self-determined research agenda, not very much. Taxes are cheap when half of your compensation is non-pecuniary.

The academy is a club.

Scratch that.

The academy is a hierarchy of nested clubs. Which means that we often suffer from exclusionary FOMO akin to fourth tier English gentry trying to marry off five daughter in the early 19th century. Membership in those clubs– those famed research groups, donor-named centers, or even (god forbid) schools of thought — they become more than just sources of funding, workshop critique, and coauthor match-making sock hops. These clubs become the well springs from which ever increasing portions of our non-pecuniary income come from. They become our social networks, our friends, and even ,with a handful of co-authors you’ve gone into scientific battle alongside, a second family. The next time you see someone dig in their heels, seemingly denying the mounting evidence that they were on the wrong side of a scientific argument, don’t just blindly assume they are too stubborn and arrogant to acknowledge they might have been wrong. Consider how unfunded or, more importantly, how lonely they stand to be if they’re the first to give up the fight.

It’s why we covet tenure so much. Don’t get me wrong, everyone wants job security. But for most of us, the prospect of being laid off doesn’t necessarily include the possibility of being jettisoned from what you’ve slowly constructed as a separate parallel universe within which you have carefully curated the technical, educational, and social capital necessary to produce your career and life. If you get laid off from programming for Netflix, the next few weeks or months will be unpleasant, scary even. You may begin to doubt your ability or life choices. But that next job will come, and you will as often as not find yourself with a nearly identical life on the other side.

There are those in the academy though for whom this is all they’ve ever known. Bachelors, doctorate, tenure-track academic placement. Throw in a post-doc and that’s 20 years, and you’re entire adult life, in and around universities. Even if they’re from a field fortunate enough to have robust private sector options, how much will doubling your salary really soften the blow for such a person?

I say all of this now not as a critique of academia, or even to lead to prescriptions or advice. You want my advice? Fine, here: don’t go straight to grad school. Dip your toe in the real world, see how you like it. Come back in a few years with a little experience and distaste for office life. It’ll serve you well when your dissertation hits one of its many inevitable nadirs.

Rather, I invite you to consider this: what does the world start to look like when our utility comes less from the goods that we buy and the experiences we have, and more from the clubs we are members of? What does it look like when those clubs find newer and better ways to monitor our behavior and our expressed beliefs? What does it look like when the purging of membership rolls becomes a part of the culture of those clubs?

Emily Oster on Vaccines in February 2021

My third post on Covid data heroes features Dr. Emily Oster. Emily is a mom. Lot’s of economists are moms, but few have incorporated it quite as much into their careers. Emily has written a book on pregnancy and a new one on what to do with the kids after they are born. She does a great job explaining scientific research in a way that is easy to understand.

Emily made a big push to collect data on schools and covid back when there was crippling uncertainty about how dangerous it is to let children go to school in person.

She has a great email newsletter and substack. Her latest post is called “Vaccines & Transmission Redux Redux”. In this post, she distills the latest research to give practical advice on when kids can see grandparents once the vaccines are out.

For a long time now, some families have been avoiding close contact with elderly relatives. When can we go back to normal?

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Gen Z on Deep Work

I asked students to read an excerpt of the first chapter of Cal Newport’s book Deep Work and comment in a discussion board. The prompt asked whether deep work goes on in college and what are the barriers to deep work. I think it’s important for society that some people engage in deep work on our problems. I’m interested in how 20-year-olds perceive Newport’s ideas on focus and what barriers they identify to deep work.

Replies ranged from “I do believe that deep work is happening at college, but I think that it is hard to find students using this strategy regularly.” to “I know multiple people who do not practice deep work….” They each have a different subjective view of “deep work” and their replies are anecdotal. It’s possible that some students are too hard on themselves, considering that I biased them to be negative with the discussion prompt. Some of them might have thought that “deep work” requires many consecutive hours of focus, which is not actually what I expect of undergraduates. Still, the discussion could be helpful to others who aspire to deep work.

The following barriers to deep work were identified:

“The barriers that we experience include social media, roommates, friends, significant others, going to classes, having to work, and any number of other things that cause our day to become disjointed …  We are the first generation that has spent the majority of our life utilizing social media… and in general, are used to taking in information from a large number of sources over a short period of time.

“Most students cannot spend a large amount of hours just focused on the one task at hand and that is required for deep work. For most college students it will be nearly impossible to practice deep work because of a job, outside social life, or a heavy class workload …

“I believe that deep work happens in college a lot.  Students often times must prepare/study for tests for a long time and that is when it happens the most.  When someone has to study for hours they are intensely focused if they put themselves in a good studying environment…

“This can be achieved when you are able to clear your mind of external things and place yourself in a non-distracting environment. As a college student, this can be difficult especially because we are constantly thinking about our to-do list, when will we hang out with friends, or what’s for dinner.

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Education and Marriage

In class today we discuss education and marriage. While we see a general trend toward fewer and later marriages there are substantial differences across education. More educated men and women are marrying more than less educated men and women. They are also divorcing less. So highly educated people who are well-paid are combining their incomes and securing the benefits that come from marriage. Meanwhile less educated individuals are either not forming relationships (single parents) or forming relationships and living arrangements that are less durable (e.g. cohabitation). So on average there is either a low single income or two low but combined incomes. This is a topic that has been discussed substantially in news outlets. For example, here are articles from The Atlantic, Forbes, and Freakonomics.

You can imagine this has lead to substantial income inequality. For example, this study from a few years ago in the NBER reports that, “Data from the United States Census Bureau suggests there has been a rise in assortative mating….[I]f matching in 2005 between husbands and wives had been random, instead of the pattern observed in the data, then the Gini coefficient would have fallen from the observed 0.43 to 0.34, so that income inequality would be smaller.”

That assortative mating refers to people sorting into relationships with people like them. In this case, people with high education marrying people with high education. But, even for its coverage in the media, we probably do not discuss enough how rising income inequality is driven by patterns in marriage and divorce among those with high and low education.