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Here, fixed that for you…
I’ve written about this supposed dystopian nightmare before- the real problem isn’t that we can create a lot of stuff without taking up a lot of people’s time (that in itself sounds lovely, right?), the problem is that we as a society don’t know how to efficiently allocate resources without the price system, and, more importantly, we can’t seem to conceive of a mechanism for getting the inputs to that price system (i.e. dollars) to people that doesn’t involve trading said dollars for worker effort (i.e. labor). I’m not entirely convinced that we’re getting to the dire point of labor obsolescence any time soon (see here for some evidence of what ATMs have done to bank tellers, for instance), but I do think that we need to start getting potential solutions out into the public consciousness well ahead of time, since social norms and attitudes don’t change overnight (looking at you, gay marriage).
It’s worth noting that my statements aren’t a criticism of Reich himself except in that he appears to have taken up the journalistic hobby of burying the lede by putting this part at the end:
Our underlying problem won’t be the number of jobs. It will be – it already is — the allocation of income and wealth.
What to do?
“Redistribution” has become a bad word.
But the economy toward which we’re hurtling — in which more and more is generated by fewer and fewer people who reap almost all the rewards, leaving the rest of us without enough purchasing power – can’t function.
It may be that a redistribution of income and wealth from the rich owners of breakthrough technologies to the rest of us becomes the only means of making the future economy work.
I get the sense that people like Reich believe that the public will pay more attention if they are presented with the dystopian nightmare view of the situation- they may be right, but I’m curious as to how a “the world will be so awesome except for this distribution problem that we need to figure out” marketing angle would play instead. In any case, we do need to start thinking about a mindset change, since otherwise we run the risk of being that society that has people do busy work so that we have an excuse to give them money. We all know how much we “love” that at our jobs nowadays, so how about we start considering some alternatives, hm?
P.S. I definitely feel that some Player Piano fan fiction is in order here. Let’s get on that, shall we?
I can’t decide whether this is more or less ridiculous than negative interest rates for dealing with a liquidity trap…
(One nitpick: Technically, savings is what funds investment, so it doesn’t generally make sense to think that they move in opposite directions as suggested above. That said, if you define “saving” as putting money in banks or government securities and “investment” as private-sector investment, then the statement is pretty reasonable.) On a practical level, however, this can only work if people don’t recognize Janet Yellen, since they need to get scared and run away rather than be all “OMG it’s Janet Yellen, you’re so cool, can I take a selfie with you?” Fortunately (in this context and probably no other), Yellen’s celebrity doesn’t appear to be a limiting factor:
The survey showed 70% of those polled don’t know or aren’t sure who Ms. Yellen is. In contrast, just 1% had never heard of former president George W. Bush.
When it comes to the Federal Reserve as an institution, 42% said they had a neutral view, while 30% had a somewhat or very positive view and 20% had a somewhat or very negative view. Just 8% didn’t know the name or weren’t sure what it was.
Yellen shouldn’t take it entirely personally, though, since, as of last year, one in six Americans thinks that Alan Greenspan is still in charge of the Fed. Yellen and Bernanke need to go commiserate over some cocktails- and Yellen should pick up the tab since Yellen’s a millionaire and Bernanke couldn’t refinance his mortgage. =P
I didn’t entirely believe that Justin was serious the first time I read this:
— Justin Wolfers (@JustinWolfers) March 6, 2015
Because really, what? You’re probably not shocked that I went down the rabbit hole of looking for the original article…and yup, there it is, plain as day:
It is useful for policy-making purposes to adjust monthly data to an expected annual rate. But the current method needs to be updated and based on something other than the weather.
Somewhere in this process I managed to get into a Twitter spat with Phil Izzo, who defended his employer (the WSJ) by pointing out that the article was written by a Harvard Business School professor and not one of the journal’s journalists. (For the record, I generally think that Phil is a good dude.) What started this was a comment that I made about how journalists should have subject matter expertise, so I responded by pointing out that editors are journalists too. I don’t care if something is in the “opinion” section or not, it’s gotta be vetted for the crazy sauce. In this case, even the author’s job title wasn’t vetted, since he’s been retired for a while as far as I can tell. (Emeritus, people, come on.) Otherwise, people get mislead by the parts of the “opinion” pieces that aren’t actually opinions, and five thirty eight has to spend its time trying to combat the absurdity:
This is so wrong that it’s hard to know where to begin. First, seasonal adjustment isn’t entirely, or even primarily, about the weather. It’s about accounting for recurring patterns, whatever they may be. Tax preparation firms hire lots of people every spring and then lay them off after April 15. Landscaping firms employ far more people in the summer than in the winter. Automakers shut down their factories each summer to change over to the new model year.
But Mills doesn’t make that argument. Instead, he writes: “The [Bureau of Labor Statistics] should report both seasonally adjusted and actual figures each month.” But of course, the BLS already does this — which Mills knows, because that’s where he gets his “2.7 million jobs” figure from the first paragraph of his story.
I figured I should do my part too, so I answered in the form of a video about the jobs report and a very simple seasonal adjustment example, and some fun new visual tricks:
I think I kind of like looking like I’m trapped in numbers jail.
Update: I’m not the only one on the case…
— Matt O'Brien (@ObsoleteDogma) March 13, 2015
Pop quiz: What do Larry Summers and John Oliver have in common? Are they both British? No…Are they both funny? Not intentionally…Do they both make awkward statements about women? Actually, I’m not sure, but I hope not…Are they both actively advocating for infrastructure spending? Ding ding ding!
Larry Summers recently said something startling: “At this moment . . . the share of public investment in GDP, adjusting for depreciation, so that’s net share, is zero. Zero. We’re not net investing at all, nor is Western Europe,” he told a Princeton University audience.
In other words, total federal, state, and local government investment is enough to cover only the amount of wear and tear on bridges, roads, airports, rails, and pipes. “Can that possibly make sense?” asked the former Treasury secretary, who has been campaigning for more government spending on infrastructure.
Well, technically it could make sense- if spending were such that everything was being maintained properly but new infrastructure wasn’t being built, then at least it would be true that things aren’t getting worse. What we see instead, however, is that there are structures that are actively in disrepair and without the funding to return them to their former (lack of) glory. Summers’ argument is that increased debt burdens are bad for future generations, but so is crappy infrastructure, and he asserts that low-interest-rate environments (like we currently have) are a relatively good time to borrow to undertake such projects.
Overall, I agree- as long as we’re not talking about “that weird old bridge that no one uses anyway” or something like that, then infrastructure at the very least needs to be maintained properly. In terms of leaving burdens for future generations, maintaining now is particularly important in cases where letting structures depreciate makes them disproportionately more expensive to fix later. (You know, in the same way that paying for healthy food now is cheaper than paying for diabetes later.) That said, I’m a little frustrated that people just now seem to be getting on the infrastructure bandwagon, since you know when’s an even better time to undertake infrastructure projects? When you have a bunch of unemployed people sitting on the couch- it’s more efficient to pull people off the couch to repair bridges than it is to pull them from other productive work. (This isn’t even a Keynesian stimulus argument, just an opportunity cost one.)
I get it, infrastructure is easy to take for granted- it’s just always there and passive, like that old boyfr…er, pair of slippers. We don’t pay for it directly or use it exclusively, so thinking about its upkeep is far more abstract than contemplating condo renovations or whatnot. It’s important to keep in mind, however, that we have the luxury of taking infrastructure for granted only because past generations made it a priority to put it there, so it’snot really feasible to take it for granted forever. And believe me, you notice when it’s not there, whether it be potholes in roads, construction projects that get in the way and take way too much time, poorly functioning public transport (can you tell I live in Boston?)…or, you know, this:
If that didn’t get your attention, I don’t know what will…except perhaps this, featuring Ed Norton:
I would like to think that we’re not children and therefore don’t need things to be sexy in order to pay attention, but one glance at my site’s name would suggest that I’m more cynical than that.
In related news, I got a care package from John Oliver’s show that included a magic 8-ball that knows more about me than I think I am comfortable with:
There was also a USB drive include in the package, and of course the drive had a video on it…in the video, Oliver puts Meryl Streep and Thomas Piketty in the outer “neither” space of the “has an active social media presence” and “watches Last Week Tonight”- while the empirical evidence regarding Piketty is in Oliver’s favor on the social media front, I really want to think that Piketty sits on the couch with his…well, French Cheetos (Les Cheez Doodles?) and Ben & Jerry’s (Francois & Pierre’s?) and watches all of the parody news shows to see how often they mention him. (for the record, that is not a judgment on you, Tommy boy, but I will judge your book’s social media team for giving up after four tweets…FOUR. I think my cat has tweeted more than that by walking on the keyboard.)
In the event that you can handle the truth (hee), here’s some Goodmen talking about cutting edge research on papers involving surname-sharing authors:
I think that was pretty good, but I am also aware that the bar for economic humor is not always particularly high…for example, it turns out that jokes (and I use this term loosely) are tagged with [laughter] tags in transcripts published by the Federal Reserve, so a simple search function highlights all of the moments of supposed nerd hilarity. Some excerpts:
CHAIRMAN BERNANKE. …Let me turn now to the economic situation. Boy, I think it has been a while since we were three and a half hours into the meeting before we got to the staff forecast.
MR. STOCKTON. The GDP is a little smaller than it was at the start of the meeting.
Or perhaps you prefer this one…
MS. YELLEN. …The residential housing sector has now shrunk so much that the only real assurance that it will ever stabilize seems to be the fact that construction spending cannot go negative. This is just about the only zero lower bound that is working on our side. [Laughter]
I don’t care what anyone says, Yellen is totally going on the list for next year’s humor session. =P
Let’s begin by working through a situation that has been quite popular recently…suppose that you show the following photo to 10 of your friends:
Now, let’s say that 8 of your friends saw the dress as blue and black and 2 saw it as white and gold. You’d probably feel pretty comfortable asserting that, if you were to poll more people, more would see the dress as blue and black than white and gold. What about if your sample had 6 reporting blue and black and 4 reporting white and gold? You’d probably think something along the lines of “yeah, I know the result isn’t split 50/50, but it’s not that weird to get a little away from 50/50 in a sample even when the population is divided 50/50.” Neither of these statements is particularly unreasonable…but where do you draw the line? What if your sample reports 7 for blue and black and 3 for white and gold?
This is what tests of statistical significance are supposed to help out with.* Wouldn’t it be nice to know how likely it would be that your sample would give a 7-3 vote if the population really were split 50/50? This is what a statistical “p-value” tells us. If that value is sufficiently small, we say to ourselves “self, you know what? It’s pretty darn unlikely that I would see what I’m seeing from my sample if the population were really split 50/50 on this issue- maybe it’s time to entertain the notion that more people think the dress is blue and black then think it is white and gold.” (In reality, I think the white/gold camp wins out, but this is my story, so just go with it.) This is what statistical hypothesis testing does.
Sounds pretty compelling, right? If so, then I hope for your sake that you aren’t a social psych researcher, since the Journal of Basic and Applied Social Psychology decided to ban statistical significance testing in all of th articles that it publishes. (For you Bayesians out there, they aren’t too happy with you either but are willing to consider your analyses on a case by case basis.) Okay, I get that the generally accepted practice of considering a finding with a p-value of 0.05 or less as significant and everything else garbage isn’t without it’s problems, most obviously that researchers have incentives to finagle their analyses to sneak in under this threshold, but what on earth are researchers supposed to do instead? (i.e. what is the counterfactual to statistical hypothesis testing? So meta.)
I have some suggestions:
The downside I suppose is that none of these approaches really have the gravitas normally associated with scientific rigor, so I’m at a bit of a loss. Seriously though, I don’t understand what researchers are supposed to do instead- the article mentions something about descriptive statistics, but the point of the statistical analysis that I referred to above is to give some context as to whether differences in descriptive statistics are large enough to be worth paying attention to.
As I said, statistical analysis is not without its flaws, but there are a number of far less controversial and likely more productive steps that the journal could have taken:
I guess this makes me thankful that I’m an economist, since if I ever write a paper that reads “well, my cat and I think this result looks pretty good, how about you?” it will be because I wanted to and not because I had to.
* Yes, I know that this doesn’t have to do with causality specifically, but this same method is used for analyses that attempt to tease out cause and effect.
In a recent article, labor economist David Autor was quoted as saying that “If we automate all the jobs, we’ll be rich—which means we’ll have a distribution problem, not an income problem.” David, have you been reading drafts of my dystopian future economic science-fiction novel again?
The synopsis of my (mostly, but not entirely) hypothetical Hunger Games fan fiction goes something like the following: Imagine a world where technology has progressed to the point where one person can create all of the output that we have today (or maybe even then some) by pushing a really fancy version of the Staples easy button- you know, like this:
Would society in the aggregate be better off economically as a result? The answer is most surely yes- if we believe that most people would rather sit on a beach and have their work done for them than actually do the work, then the button basically has to be a boon to society overall. In this situation, people would have two options: one, they could be content with the current standard of living and continue sitting on the beach, or they could use their newly-acquired free time to produce new (hopefully) cool stuff for society. (You know you were just looking for the right moment to get into the artisan cupcake pick business.) Let’s, for the sake of argument, assume that people take option number one- this is what Autor meant when he said that technology would make us richer, since we would now have all of the stuff and all of the free time rather than just all of the stuff.
You’ve probably caught on by now, however, that the GDP button presents some interesting challenges for society. We are currently pretty much accustomed to distributing money in exchange for labor and capital- that’s how markets for the factors of production work. Under this regime, the guy/girl who owns the GDP button (Katniss Everdeen in my fan fiction, obviously, to make up for being from a poor family) would get all of the factor payments. (Hence the distributional problem that Autor referred to.) But this is where it gets sticky- payments from whom? If Katniss keeps pressing the button and people keep buying her output, eventually everyone but KAtniss is going to run out of money and not be able to buy the output anymore. Granted, this might not bother Katniss, since she has the button that makes stuff and therefore doesn’t really need your money. Everyone else, on the other hand, runs into a bit of a problem.
This problem is not technically insurmountable, so it’s not a given that everyone but Katniss is going to die of starvation. (I suppose this is where the narrative diverges from the parent books a bit.) That said, the problem isn’t the easiest to solve either. One option would be for Katniss to give away the stuff that she doesn’t use. This would prevent at least some of the starvation problem, but it would introduce new logistical problems- giving stuff away doesn’t exactly get said stuff to those who value it the most. For example, if I saw that, say, a motorcycle was being given away, I might go get it because hey, free motorcycle, but I don’t actually like motorcycles that much. Now, you might think that this would take a motorcycle away from a motorcycle enthusiast, but think this through a little more. Since I’m not the only person wandering around perusing free stuff, society would likely end up in a situation where the more popular free items have longer lines. (Just ask the people who tried to get free Krispy Kreme the other day.) This would solve the resource allocation problem to some degree, since I would be more likely than the motorcycle enthusiast to balk at the line for motorcycles, and it approximates a world where time is the currency used for resource allocation. On the up side, this seems pretty fair, since everyone has the same endowment of time. On the down side, we’ve now gone from a wondrous society on the beach to a society where we’re all waiting in line for our “free” stuff.
What if, instead, Katniss kept giving out the money that people pay her for stuff each period so that people can keep paying for stuff? Prices would adjust so that resources are allocated efficiently, so this approach seems promising (especially if Katniss realizes that this approach doesn’t make her worse off)- just don’t think too much about how the money gets allocated. Does each adult get the same amount? Do parents with more children get more? Do people with health issues get more than healthy people? These sorts of questions really highlight the fact that issues of fairness don’t have a “right” answer.
The world described above is obviously a very extreme version of what we actually see in society today and what Autor is referring to, but it presents a nice allegory for some of the issues that society is currently facing or worried about facing in the future. Specifically, how can companies continue to thrive by selling stuff to middle-class and working-class households if these households don’t continue to get the money to spend? Conversely, how can middle-class and working-class households thrive if they aren’t endowed with or have the means to develop the factors of productions that are valued in the economy? If capital (the analogue to the magic button) becomes the most crucial factor in production, how does society ensure that citizens have an endowment of capital equivalent to their current endowment of labor? (You have to admit that nature does a nice job of leveling the playing field by endowing most people with the ability to work.) At the risk of channeling Piketty, I will fully acknowledge that it seems like a shift towards capital being the main factor of production would have to, as per the allegory, be accompanied by some serious thought as to the heritability of wealth and even possibly a wealth endowment. (For comparison, consider that the median household is endowed with somewhere in the neighborhood of $1 million of labor “wealth,” assuming a 5% return and $50,000 median household income.)
Fun fact: Fifty Shades of Grey started out as Twilight fan fiction, so feel free to suggest some BDSM aspects of the narrative so that I can make a boatload of money, thanks.
I couldn’t resist…from The Onion:
Half Of Hollywood Test Group Screened Placebo Film
LOS ANGELES—Saying the methodology helps them ensure unbiased results in their marketing research, studio executives at Paramount Pictures confirmed that during a Hollywood test screening this week they showed half of all theatergoers a placebo film. “Instead of watching our authentic big-budget studio film, this randomly selected control group saw a movie that lacked any recognizable star, overt ‘high-concept’ premise, rapidly unfolding narrative, or extensive computer-generated effects, so that we could compare their reactions with those of the real movie’s viewers,” said Paramount production head Marc Evans, acknowledging that many members of the control group exhibited the same level of emotional gratification and entertainment as those who viewed the actual upcoming action-adventure blockbuster. “Such a double-blind screening method allows us to determine whether the thrills, laughs, and heartbreak experienced by audience members actually stem from Arnold Schwarzenegger’s performance in the Terminator sequel we have coming out this July, or whether they are simply the result of a placebo effect.” Despite poor findings that showed no significant improvement upon the placebo film, executives said they had already spent $170 million developing the franchise feature and would just give it a wide international release anyway.
Hmmm…would it be completely unreasonable to create treatment and control films in order to determine how much of a wage premium big stars should really get? Come on, an NSF grant would totally cover the cost of that…in related news, just a reminder that sophisticated data analysis is helpful because experiments aren’t always feasible or practical!
With Fifty Shades of Grey coming out this weekend, I figured it was a good time for a reminder to be careful out there when doing it with models:
Sex toy injuries surged after ‘Fifty Shades of Grey’ was published
The number of Americans requiring emergency room care for injuries involving sex toys has approximately doubled since 2007, according to data from the Consumer Product Safety Commission. Much of that increase happened in 2012 and 2013, following the release of the wildly popular erotic novels in the Fifty Shades of Grey series. And the overwhelming majority of these injuries — 83 percent — require “foreign body removals.”
So do we need to be thinking about the negative public-health externalities of this particular phenomenon? I get the feeling that the headline writer chose her words carefully, but the article itself (and others like it) seem to reallllly want me to think, despite an offhand sentence to the contrary, that the increase in injuries is actually because of the book (or at least that the increase in injuries is a result of the increase in sex toy use that resulted from the publication of the book). But we nerds know better…
This suggestion is a particular form of the correlation versus causation issue known as the “post hoc ergo propter hoc” fallacy (not to be confused with the second episode of The West Wing)- namely, that just because one thing happens after another doesn’t imply that the latter happened because of the former. In this instance, we see a claim that sex toy injuries increased after the book was published, but we can’t conclude that the increase happened because of the book itself.
The fallacy is highlighted further when a more complete dataset is observed:
Now it is more clear that the increase was largely following what appears to be a longer term trend- in fact, the data suggest that perhaps the relationship goes in the other direction and the increased proliferation of sex toys and sexual experimentation lead to the book being published and getting so popular.
It’s worth keeping in mind, however, when causality matters and when it doesn’t- for example, my warning to be careful is relevant regardless of what is causing the increase in injuries. Also, having this data makes this scenario a tad less surprising:
Given the 87 percent figure mentioned in the article, I’m actually kind of surprised that this didn’t show up on the board.
Dear Jacksonville, FL,
I will be in you tomorrow to talk about the economics of The Simpsons. All I ask is that you have better weather than exists here in Boston, which is not a tall order. (Technically, I also request good coffee, so feel free to leave suggestions in the comments.) The details are as follows:
Presented by Florida State College Jacksonville
Thursday, February , 2015
3939 Roosevelt Blvd.
Free (or, as Dan Ariely would say, FREE!)
For tickets and more info, email Susan Reilly – sreilly at fscj dot edu
I hope to see some of you tomorrow!
P.S. The official flyer:
A couple of years ago, I was told a story about how Milton Friedman would teach his Principles of Economics courses by walking into the classroom each day, opening the newspaper, and discussing the economics behind the stories that he saw. Now, I don’t know whether this tale is an urban legend or not, but the idea is quite solid, since it’s of crucial importance to tie back what is taught in the classroom to what students see out in the world. The downside of this approach, of course, is that the outside world isn’t organized for the purposes of providing examples in a logical order that students can easily follow and instructors can piece together into a syllabus in real time.
That’s where this document comes in- as an instructor and consumer of information myself, I spend a number of hours each day looking for interesting things that happen in the world that illustrate (or, in some cases, are at odds with) economic theory. Such an activity, with its high fixed cost and low marginal cost (when quantity is measured as number of instructors served), has the structure of a potential natural monopoly. In this case, however, the document has the features of a public good, since I’m making it open to everyone. Whoever said that public goods wouldn’t be provided by the free market? Oh right, (non behavioral) economists.
I hope that this database of Econ 101 examples (or, technically, spreadsheet, as some persnickety individuals have pointed out) is helpful to you! I will continue adding to it, hopefully almost daily, as I come across new things to talk about. There are a few features that I’ve put in to make the document easy to navigate and use:
– Sheets: The examples, not shockingly, are on the sheet labeled “Examples.” (This is the “Overview” sheet- see the tabs at the bottom left of the sheets to toggle between them.)
– Description/Comments: I’ve tried to provide enough information so that you don’t have to click through to the sources to understand what they are and whether you want to use them. In addition, I often give suggestions on how you can use the source in your classroom.
– Date: Where possible, I’ve added a date so that you can avoid sources that you feel are outdated. You can (reverse) sort by date and stop looking when you feel that the sources get too old. Note, however, that not every item has a date- such sources are obviously timeless!
– Date Added: You can (reverse) sort by date added in order to look at only those items that you haven’t already examined.
– Course: You can filter by course to only see items that are relevan to what you are teaching. Note, however, that some items are assigned to both Micro 101 and Macro 101, and this designation gets its own filter category.
– Tags: Created to help you find relevant items more easily, and I would search this column rather than trying to sort of filter, since a lot of items have multiple tags. When possible, I recommend scanning the items rather than relying solely on the tags so that you don’t miss anything relevant- for example, an item I’ve tagged as “price ceiling” when you’re looking for “price controls” or something like that.
– EDIWM Post: Where applicable, I’ve added links to posts on my web site that give more extensive discussion on the sources presented.
– Submitted By: For the most part, I am compiling this document myself with some help from a few econ friends. That said, I want to give proper credit where credit is due! In related news, email econgirl at economistsdoitwithmodels.com if you have something relevant/fun to share, and be sure to let me know how you would like to be credited.
I hope this is helpful to you and makes economics more interesting to your students! You can also follow my Twitter- @jodiecongirl- in order to see most if not all of the items as I find them (as well as other econ stuff). If you want even more Econ 101 materials, be sure to check out the “Econ Classroom” section of my web site (listed below).
Lecturer, Northeastern University Department of Economics
My current plan is to update the database as I find new examples and then post a summary of new items once a week as a reminder. I also added a link to the document at the top of the Economics Classroom page for easy reference.
In a lot of ways, non-economists are in the best position to create economic humor, since their outsider status basically makes it so they are looking in on the world of economics and being like wtf? On the other hand, Zach Weinersmith might argue that the nature of economics makes relevant humor relatively challenging:
Nonetheless, I convinced Zach to give it a go at the AEA Annual Meeting Humor Session:
If that (or economics in general I suppose) hasn’t given you your fill of bad ad-hoc hypotheses, you can see much more at BAHfest.com.
You all seemed to like the conversation about the gender wage gap after Obama’s State of the Union address, so I put together something a bit more formal for the Boston Globe. (sidenote: I am strangely fascinated by the graphic used for that article- it’s very Beatles-esque trippy, as in “picture yourself in a bot on a money river” or something…I don’t know about you, but I’ve always wanted to fish for money with a red suction cup.) Here’s a more, let’s say, unfiltered version for those already somewhat familiar with the matter:
In terms of “equal pay for equal work,” literally speaking, men and women are in fact on pretty equal footing- about 96 cents on the dollar for non-married women versus men if I recall correctly, so better enforcement of narrowly-defined discrimination laws won’t do a whole lot to narrow the observed wage gap that has been defined as problematic. In other words, let’s cut it out with the 77-cents crap. From a fairness perspective, the matter is somewhat complicated, since women with families (and, by extension, women on average) do in fact work fewer hours than men and ask for more flexibility in terms of working hours and location. So what would be fair? Let’s say that a woman works 20 percent less than an equivalent male- one starting point for fairness might be that she earn 20 percent less than the man. But what if working 20 percent less means that she’s not as “on call” or “present” as the man? This could make her productivity, on an hours-adjusted basis, less than the man’s, in which case it could be considered fair to pay her more than 20 percent less.
The situation described above illustrates how an inflexible workplace that likely seems generally fair leaves women with family responsibilities behind in two ways. First, women who care for children can’t work as many hours as men who don’t have such responsibilities if it is mandated that those hours have to be between 8 a.m. and 6 p.m., for example, but they likely could if they could get proper credit for hours they spend working in the early mornings and evenings, perhaps from home. Second, inflexibility in terms of worker substitution makes it nearly impossible for a more “part time” employee to have the same productivity (even on an hours-adjusted basis) as one who gives over his entire existence to his employer. If workplaces enabled more flexible organizational practices, women would both be able to work more hours and be more productive in those hours, thereby alleviating much of the wage gap without what potential critics would refer to as special treatment. Also, men would get more flexibility too. (This is where you say “yay!”)
Claudia Goldin gives a very good example of how rigidity in the workplace that is not actually necessary has been done away with, to the benefit of women and their earnings:
Several changes in the pharmacy profession have been responsible for the increase of female to male earnings. The first is the decrease in self-ownership and the rise of large corporation and hospital employment. As corporate ownership and hospital employment increased, the portion of earnings that came from self-employment decreased. The ratio of the (time-adjusted) earnings of female to male pharmacists, in consequence, increased as the rents from ownership decreased and because men were disproportionately the owners.
The second change involves decreased costs to flexible employment in pharmacy. Pharmacists have become better substitutes for each other with the increased standardization of procedures and drugs. The extensive use of computer systems that track clients across pharmacies, insurance companies, and physicians mean that any licensed pharmacist knows a client’s needs as well as any other. If a pharmacist is assisting a customer and takes a break, another can seamlessly step in. In consequence, there is little change in productivity for short-hour workers and for those with labor force breaks. Other factors mentioned in the O*Net section are also of importance. For example, there is less need for interdependent teams in pharmacy and for extensive contact with other employees.
Female pharmacists have fairly high labor force participation rates and only a small fraction have substantial interruptions from employment. Rather than taking off time, female pharmacists with children go on part-time schedules. In fact, more than 40 percent of female pharmacists with children work part-time from the time they are in their early thirties to about 50 years old. Male pharmacists work around 45 hours a week, about nine hours more than the average female pharmacist.
Goldin also notes that similar changes have occurred in the field of obstetrics (i.e. delivering babies and such) once patients started accepting that anyone from a team of qualified doctors could deliver a baby under most circumstances, so having their particular obstetrician on call and available at all times was not absolutely crucial.
So why doesn’t this happen everywhere without the dreaded government intervention? In some industries, it might not logistically be possible. In those cases, I’m not sure what can be done other than making sure that people (not just women) know what they’re getting into when they make educational investments and career commitments. In other industries, well…how do I put this delicately…not everyone wants to compete with women with families for their jobs. These people aren’t necessarily being jerks, they’re just being rational- less competition for jobs means higher wages, although kind of in an inefficient rent-seeking fashion if changes that could make more people more productive are needlessly curtailed for the benefit of the incumbent workers. (before you judge too harshly, think about how you would respond if you were told that your employer wanted to enact policies that would make workers more interchangeable.)
I suppose that the second scenario could be legislated to some degree in the same sense that antitrust is legislated- on a complicated, case by case basis- but that sounds like a disaster waiting to happen. By process of elimination, I guess I would want to know what caused the industries that Goldin described above to change and have some smart people think about how similar mindsets and incentives could be brought to other industries. In any case, doesn’t it seem better to narrow the pay gap by enabling women to work as much and be as productive as men rather than by trying to just will it out of existence?
And here you thought it was my logo that was setting feminism back 50 years. =P
My sarcastic intro comments aside (obviously part of the problem for the specific event is that CSI is not supposed to be funny), I still think that this should exist on a larger scale…
You probably guessed that I am more of a Law and Order gal, since I’m obviously guilty of mixing my metaphors. I did try though- in the name of research, I bought the first season of the original CSI on Amazon, and, well…I just couldn’t get into it, and, other than what I included, there wasn’t anything obvious enough to pull from. Maybe because it wasn’t about statistics, maybe because it didn’t have Olivia Benson, who knows. Anyway…you can see by the list of sources at the end of the video, you just learned the basics of three academic papers and a reply in under ten minutes and you didn’t even feel the pain! In case you weren’t paying attention, here’s the overall trajectory of (some of) the research on the causal impact of police presence on crime:
I think that this sort of approach- i.e. showing rather than telling- is so powerful, and there definitely should be more teaching that is done in this way. (I might be a bit biased since Mathnet was an important part of my childhood. In related news, you’re welcome.) Granted, it’s harder- I’m pretty sure it took more effort to write the script (reproduced below in case you want it) than it did to write the list of bullet points above. But I’m convinced that it’s worth it, especially with some production value thrown into the mix. Okay, here’s the script, and I’m (not even kidding) going to go back to watching Law and Order now.
CSI: Regression Analysis
*intro screen – The following story is sort of fictional but sort of depicts actual people and events.*
Cop: You guys from Internal Affairs?
Econ 1: Nope, we’re from…the Program Evaluation squad. *David Caruso sunglasses moment, with music/regression graphic*
Cop: *completely breaking the dramatic moment* The what?
Econ 1: The Program Evaluation squad- you know, you catch criminals who cause crimes, we identify the culprits that cause…well, a bunch of stuff.
Cop: So…nerd detectives, got it. What brings you here?
Econ 1: Well, we’ve been enlisted to study the effect of police presence on crime rates, so your department seemed like a natural place to start.
Cop: And what happens to my job if I’m found to be useless?
Econ 2: We’re economists, so such policy questions are outside of our jurisdiction. So…we’re going to need your data on number of police officers and number of crimes committed over time.
Cop: I’m not exactly inclined to share data that could cost me my job.
Story of my life. Do I need to get the Captain involved?
Cop: No, let me find what you’re looking for.
Econ 1: *looks at data on paper and writes some numbers on white board, then inputs into computer* Hmmm…from what I see here, it actually appears that more police officers leads to MORE crime. Weird, right?
Cop: Wait, what? That can’t be right…you have to keep looking- after all, the first suspect is never the true culprit, right?
Econ 2: We’re looking into the matter, sir.
Econ 2: He’s right, you know.
Econ 1: About what?
Econ 2: There’s a problem with our case. Look- I found these forms that request additional officers into the department. what do you notice?
Econ 1: *looks at forms* That the reason listed for the request is…oh. Increased crime prevalence. So that means…
Econ 2: …that we can’t tell whether the police officers cause crime increases or if the crime increases cause more police officers to be hired.
Econ 1: So are we back to square one?
Econ 2: *looks at data* Mayyyyyyybe not…
Look at this- crime increases aren’t the only reason that officers are requested.
Econ 1: There’s no reason given at all, actually. What’s up with that?
Econ 2: *at white board* I have a theory….*does some math* Yep, what I suspected- the requests match up with election cycles.
Econ 1: Why would that be?
Cop: Welllllll…I probably should be saying this, but the mayor likes us to beef up our presence before elections because it makes him look good.
Econ 2: Even though crime doesn’t follow election cycles?
Cop: *sadly* Yeah…I know it’s wrong, but…
Econ 1: *cuts off cop* Perfect.
Econ 1: If we look at the part of the increase in police presence that has to do with election cycles and not crime sprees, we can use that data to estimate the causal effect of police on crime.
*Instrumental Variables start playing*
Cop: What the…?
Band: Sorry, thought you called for us.
Econ 2: *doing math* Ok, this seems to make more sense. Now I see a negative elasticity of crime with respect to police, especially for violent crimes.
Cop: *breathes sigh of relief*
Econ 1: *looks at math on board* Actuallyyyyyyy…you made a math error.
Econ 2: Where?
Econ 1: *points* There.
Econ 2: Ughhhhhhhhh…. *fixes mistake* Well, there goes my result.
Cop: Can’t you try something else?
Econ 2: Let me see… *searches around* How about firefighters? The number of firefighters is correlated with the number of police officers, but we certainly don’t get more firefighters when we have more crime…
*Instrumental Variables start playing*
Band: Again, I thought…
Econ 1: Okay, that seems to work, but we need a corroborating witness if we’re going to be convincing. What else affects the amount of police presence?
Cop: Well, we have to send out more cops when Homeland Security sets a high terrorism alert.
Econ 2: Am I the only one who finds it funny that when the government is helpful for research it’s rarely on purpose? Ok, do we have historical data on terrorism levels?
Cop; *runs in* Way ahead of you- after all, my ass is on the line here.
Econ 1: Unbiased and unmotivated research at its best, right here. *rolls eyes* *puts data in computer and on board* Bingo- another negative elasticity estimate.
Econ 2: Meaning that the data shows that, when police presence increases for reasons other than increases in crime, the increased presence leads to decreases in crime.
Cop: It’s good to feel useful.
Econ 1 and Econ 2: You can say that again.
*Dick Wolf-type credit thing – Executive Producer Charles Wheelan*
I suppose that should technically read “Correcting The State Of The Union Address,” since I make no claims as to my ability to fix all of the nonsense that is currently going in the U.S. Anyway, I of course had a number of (usually nitpicky) objections regarding President Obama’s State of the Union address last night, but I know by this point that people have to choose their battles. So here’s mine…from the speech:
Today, women make up about half our workforce. But they still make 77 cents for every dollar a man earns. That is wrong, and in 2014, it’s an embarrassment. A woman deserves equal pay for equal work. She deserves to have a baby without sacrificing her job. A mother deserves a day off to care for a sick child or sick parent without running into hardship – and you know what, a father does, too. It’s time to do away with workplace policies that belong in a “Mad Men” episode. This year, let’s all come together – Congress, the White House, and businesses from Wall Street to Main Street – to give every woman the opportunity she deserves. Because I firmly believe when women succeed, America succeeds.
I am soooooo sick of this statistic, since it basically suggests that a woman shows up at a workplace and her boss is like hey, you look like you might have ovaries, here’s $0.77 rather than $1. And that’s not what is actually happening. Yes, it is true that, on average (actually, comparing medians if you want to be technical), a woman in the U.S. earns 77 percent of what a man in the U.S. earns, but that figure doesn’t control for any relevant determinants of income- schooling, industry, tenure, etc. Therefore, I cringe whenever the “equal pay for equal work” line is trotted out, since “equal work” would imply that whoever is handing out this 77 percent figure did in fact run some sort of regression that would control for enough to get to a point where the comparison was at least close to equal. In the spirit of actually wanting to understand the gender pay disparity issue and not just quote a meaningless number, let’s look at some actual research from Claudia Goldin. Some helpful excerpts:
Men and women begin their employment with earnings that are fairly similar, both for full-time year-round workers and for all workers with controls for hours and weeks. In the case of the latter group, relative earnings are in the 90 percent range for the most recent cohorts even without any other controls. But these ratios soon decline and in some cases plummet to below the 70 percent level.
Translation: We’re basically at a place now where young men and women don’t differ substantially in their levels of education (in fact, I think women are actually outperforming in terms of educational attainment according to a number of metrics), so when comparing the initial situations of these young people, the divide is 90-some-odd cents on the dollar, not 77. And this is without taking into account the fact men pay be sorting into higher-paying jobs. That said, there seems to be a shift in gender disparity as people move on their lives that should be examined.
The main takeaway is that what is going on within occupations—even when there are 469 of them as in the case of the Census and ACS—is far more important to the gender gap in earnings than is the distribution of men and women by occupations. That is an extremely useful clue to what must be in the last chapter. If earnings gaps within occupations are more important than the distribution of individuals by occupations then looking at specific occupations should provide further evidence on how to equalize earnings by gender. Furthermore, it means that changing the gender mix of occupations will not do the trick.
Translation: Convincing men and women to enter the same occupations wouldn’t make the gender disparity go away, so let’s perhaps stop focusing on that so much as a potential solution.
The clear finding is that the occupations grouped as Business have the largest negative coefficients and that occupations grouped as Technology and Science have the smallest ones. That is, given age and time worked residual differences for Business occupations are large and residual differences in Technology and Science are small. In fact, for the “young” group (less than 45 years old) some Technology and Science occupations have positive coefficients.
Translation: The female “penalty” differs a lot by occupation, and in some cases there is no penalty and even a benefit to being female.
As I will later demonstrate using data on occupations in business and law, the impact of hours on the gender gap is large and goes far to explain much of the gender earnings gap. Individuals who work long hours in these occupations receive a disproportionate increase in earnings. That is, the elasticity of earnings with respect to hours worked is greater than one.
Translation: Within an occupation (in some cases), being a high earner (even on a per-hour basis) requires long hours and, as is shown in another part of the paper, working a particular schedule. This feature explains a lot of the gender discrepancy and is a result of women and men selecting into these situations at different rates, especially as women start caring for families.
The gender gap in annual earnings for the JDs and MBAs, although large by year 15, is almost entirely explained by various factors, such as hours worked, time out of the labor force, and years spent in part-time employment.
Translation: This is not an ovaries penalty story, at least not directly.
What, then, is the cause of the remaining pay gap? Quite simply the gap exists because hours of work in many occupations are worth more when given at particular moments and when the hours are more continuous. That is, in many occupations earnings have a nonlinear relationship with respect to hours. A flexible schedule often comes at a high price, particularly in the corporate, financial, and legal worlds.
Hopefully there is no translation needed here. The overall point of presenting this is that, in order to craft an actual solution to a problem, it’s crucially important to identify what is causing the problem. As a society, we seem to have decided that a gender pay differential is a problem. However, the lack of understanding of the nature and cause of the problem is going to prevent the problem from being solved. The information provided above suggests that any legislation of the “equal pay for equal work” form, for example, will be mostly ineffective, since observed differences in pay are in fact largely explained by inequalities in either job tenure or work quantity. In order to solve the problem, then, policymakers must look one step behind the curtain and think about how to mitigate the effects of differences in worker hours or tenure rather than just keep trotting out a well-worn sound bite to overshadow the real issue.
Econgirl out. *mic drop*
So, for those of you who weren’t able to attend the humor session at the AEA annual meeting in Boston this year, here’s some more from the event. First, the opening remarks, which explain who Caroline Postelle Clotfelter, the sessions’s namesake, is, and some commentary on the house band’s name. (The band footage wasn’t included due to a bad guitar feed, but they performed covers of economics songs that were submitted as part of Kim Holder’s Rock-o-nomix project.)
Next, James Tierney from Penn State gives the American Economic (Year In) Review:
I will be putting up more videos from the event, and you can see the full playlist here to make sure that you haven’t missed anything.
I seriously need to order this for my office:
If you don’t get it, I humbly suggest a reminder on the mechanics of money supply and interest rates.
One of my undergraduate professors has a new book. It looks like this:
And he looks like this:
I point this out mainly because yes, he also sounds just like Ben Stein. Anyway, the book is about the creative tactics that social scientists use to identify cause and effect. From the Technology Review:
If you want to produce good quantitative social-science research, remember two words: ceteris paribus.
That’s Latin for “all other things being equal.” And it’s a key research principle: if you take two groups of people that are different in one key feature but equal in other ways, you may be able to identify the effects of that difference.
“People are constantly looking at the world around them and trying to learn from it, and that’s natural,” says economics professor Joshua Angrist. “But it turns out to be very difficult, because the world’s a complicated place, and many things are going on.”
Fun fact: I’m still not sure what the proper way to pronounce ceteris paribus is, so that day of econ 101 is always pretty awkward. If this sort of things is up your alley, you should also check out Angrist and Pischke’s earlier, more technical book on a similar topic.
Yes, I realize that the title could refer to what transpired on any of the nights of the conference, but I’m talking about something a bit more structured:
Overall, I wish the video had come out a bit better, but I suppose it’s difficult to prepare a shot for a person sprawled on the stage floor in a bean bag chair. If you’ve been following along, you know that my choice of High West whiskey is not random, and, actually, neither are the Hard Rock Cafe shot glasses- I am not too proud to admit that I have a fairly expensive collection of HRC glassware (must have at one point contained a tequila shot), and I’ve actually met a few of my best econ friends because they were the ones who didn’t mind being dragged along for my cheesy alcohol-infused ritual. (Looking at you, James Tierney.) At least now you know what to look out for during the next economics conference.
In case you’re curious, most of the material was pulled from the following sources:
Hopefully the video makes this make a bit more sense:
I think the first YouTuber to comment gave a review that is on par with Siskel and Ebert’s best work: “It seems like the drunk chick at a party has managed to lure people into a lecture hall and everyone is a little confused about what’s happening.” And now I have a new life goal.
Thanks to everyone who came to the humor session on Sunday night- it was a blast, and I hope to have video up soon to commemorate the event. Additional thanks to everyone who stopped by my exhibit booth to say hi- I particularly liked our discussions on how to be innovative (read, fun) in the world of online content.
Now, for some more FAQs:
Q: What was in the whiskey bottle?
A: A combination of whiskey and iced tea, the composition of which varied over the course of the evening.
Q: I saw a camera- will there be video of said event?
A: Yup, I will post it here once I’m done editing out awkward A/V moments.
Q: I tried to come say by at your booth Monday morning, but you weren’t there. What gives?
A: I think economists need to develop a theory of rational hangovers. (Or, in video form, here.) I would also like to give a particular thank you to Peter Griffin (awesome name) for leaving goldfish crackers and a nice note.
In related news, I came upon this when confirming that the series was in fact available on Netflix:
I guess when the Netflix recommendation engine fails, it fails big.