Since it’s now spring semester (my spring semester starts very early, so I am jealous of all of you who are still on break), I figured it would make sense to shift over to macroeconomics a bit rather than exclusively focusing on microeconomics. (It also doesn’t hurt that I’m teaching graduate macro this semester and want to give my students some review materials.) MY students are currently getting into economic growth models, so I figured it would make sense to write up a refresher on some growth math:
Gotta love that mathematical precision gives way to the fact that students giggle too much at a “rule of 69.” (And no, I can’t decide if I want to be the pot or the kettle.) See here for an overview of classroom-type materials available on the site.
Tags: Econ 101 of the Day
Happy New Year! I am celebrating by trying to stuff an entire exhibit booth of stuff into a convertible. As many of you know, this weekend is the annual meeting of the American Economic Association (which is, as the post’s title implies, part of the Allied Social Science Association). This year’s meeting is in Philadelphia, and it’s a great time to get your nerd on with about 10,000 or so economists.
If you’re reading this, you likely don’t need me to tell you what this site is all about, but if you want to stop by the exhibit hall I would be happy to remind you. Oh, and I have stickers and candy, but, sadly, no windowless van. BUT…more importantly, I have projects for you- one if you’re feeling ambitious, and one if you’re feeling bored. If you’re feeling ambitious, I want you to think of a fun example of an economic principle that you can describe in about 2 minutes or so. When you stop by the booth, my RA will use whatever videography skills she may possess to tape your segment, which we’ll then put together into a fun little series.
If you’re feeling bored, I’m working on an economics bingo card for you to take with you to talks to give you things to listen for. This is what I’ve got so far:
Suggestions welcome- I see lots of potential for turning econ bingo into a drinking game. Also, you should go to the humor session on Saturday.
First off, happy holidays!
I am currently visiting my parents in Florida…
…and apparently the holidays are a time for tweeting:
I’m keeping up with my RSS reader over the holidays, and I came upon this gem:
I usually look at this sort of thing and roll my eyes, except that I came upon this after I had already bookmarked the following links:
Sigh. If you want more, here are some xmas links from The Economist.
Lastly, in a stunning display of behavioral economics taking over the world, economists seem to be coming around on the idea of gift giving:
Historically, these opinions have generally been viewed as atypical- for example, economist Joel Waldfogel wrote a paper called “The Deadweight Loss of Christmas” and a book called Scroogenomics that explain why giving gifts rather than cash leads to economic inefficiency (because you’re likely paying money for something that the receiver wouldn’t buy at that price). That said, once you consider that people care about warm fuzzies and aren’t perfect utility maximizing economic robots, a much stronger argument for gift giving emerges.
You can see what the economists specifically think regarding gift giving in the poll comments, and some of the musings are, well, exactly what you would expect from economists…so much so, in fact, that the quotes make hilarious holiday cards. For example:
Now I’m curious as to whether economists have also come around regarding New Year’s celebrations or whether they still think that calendars just lead to inefficient choice bracketing.
Update: This is also pretty hilarious.
Tags: Behavioral Econ · Just For Fun
I’ve written about weird economic indicators before, and there are even pretty comprehensive lists of such things available on the interwebs. What is less available is clarification regarding the different types of economic indicators.
Luckily, the taxonomy of indicators uses fairly intuitive names- “leading” indicators are quantities that tend to track future economic movements, “coincident” or “concurrent” indicators are quantities that tend to track current economic movements, and “lagging” indicators are quantities that tend to track past economic movements. (Technically, indicators can be related to things other than economic movements, but we’re talking about economics here, so none of that funny business.)
I can easily see how leading indicators are useful, since they essentially predict future recessions, expansions, etc. If I think about it for a second, I can also see how coincident indicators are useful, especially in cases where they are available sooner than official economic statistics. (In other words, even though coincident indicators basically say things like “hey, we’re in a recession right now,” which seems sort of silly, it may be the case that we can see the indicator data before we can see the GDP data, in which case the indicator could help us learn sooner that we are actually in a recession.) In contrast, lagging indicators basically tell us “hey, did you know that we’ve been in a recession for 4 months now?” so it’s significantly more difficult for me to see how they could be leveraged effectively…but hey, let me know if you have suggestions or inside information. (Investopedia, for example, cites confirming trends as a use of lagging indicators, but even they don’t seem particularly, well, bullish on the concept.)
Luckily, I have a leading rather than lagging indicator for you- cat aspect ratio as a leading indicator of economic performance. Yes, this indicator probably doesn’t stand up to empirical scrutiny, but what it lacks in accuracy it more than makes up for in cuteness. Oh, and something about engineers describing cat features.
Tags: Fun With Data · Macroeconomics
Lots of people like saying that playing the lottery is a bad bet- and it is, mathematically speaking. If you ever need to convince someone of this, allow me to suggest the following argument:
Let’s say you had the option to put a dollar into a collection along with 9 other people. One of the 10 people is chosen at random to get the $10 collected. Would you go for this? On average, you’d win $10 one out of every ten times, so the expected value of the system is $1, exactly what you are being asked to pay. If a person is neutral to risk, he would probably be indifferent to participating and not participating. In reality, however, most people are risk averse in most situations, which means that they prefer guaranteed outcomes to gambles with the same expected value. For example, a risk-averse person would prefer a guaranteed $50 to a gamble with a 50% chance of getting $100 and a 50% chance of getting nothing, even though both options have the same payout on average (or, in mathematical terms, the same expected value). Therefore, since most people are risk averse in most situations, I wouldn’t expect many people to take up the offer above.
But wait- this isn’t even how most lotteries work. Instead, the analogue of the lotto situation would go something like this: Let’s say you had the option to put a dollar into a collection along with 9 other people. Half of the money collected gets taken by the person collecting it, and the 10 people are asked to pick numbers from 0-9. The person running the lottery also picks a number from 0-9, and the $5 still available for payout gets split among all of the people who matched the lotto czar’s number. If nobody matched the lotto czar’s number, you have to pay again next week to try to match the number in order to get this week’s payout, but at least there’s the upside that you’ll have new people buying in to add to the existing payout.
This proposition sounds terrible to most people, yet there are plenty of people who play the lotto. It’s probably not surprising that economists really like to ponder why this happens- do people just happen to be risk loving in certain contexts? (If this were the case, they would be willing to pay $1 to take a gamble with an expected value of less than $1, which is what the lotto is.) Are they behaving irrationally in some way? (Behavioral economists hypothesize that lotto participation arises due to narrow choice bracketing in which paying $1 for a lotto ticket seems like “peanuts” when one choice to play the lotto is considered in isolation, and the lotto-playing individual doesn’t stop to consider that while $1 might not buy anything meaningful, the same cannot be said for the $52 spent on the weekly lotto tickets over the course of a year, for instance.) Personally, I have a sneaking suspicion that people aren’t even considering the odds when deciding whether to purchase their tickets. Is there a way to test this?
Thanks to the lovely people at Mega Millions, that answer might just be yes:
Your odds of winning the jackpot used to be 1 in 176 million. As of Oct. 22, those odds changed to 1 in 259 million.
That’s because you used to have to pick six numbers from 1 to 56. Now you have to pick them from 1 through 75.
The Mega numbers have decreased to 15 from 46, but your overall chances of winning still are substantially reduced.
John Garnett, a UCLA math professor, explained to me that the changes mean that “for every three winners under the old system, now there will be two.”
Now, this analysis is a bit oversimplified and pessimistic because it doesn’t take into account the fact that, if there are fewer winners, then the jackpots will get larger, and, if there are more numbers to choose from, the chances that a winner would have to split the prize decreases. But here’s something important to consider: while it may be true that, say, cutting one’s probability of winning in half does in fact cut the attractiveness of a gamble by half, the same cannot be said when scaling the size of the prize up and down. Why is this? The simple fact of the matter is that people are generally susceptible to what is known as “diminishing marginal utility of wealth”- basically a fancy way of saying that $300 million is not twice as useful to you as $150 million, since, as you get richer, what on earth are you really going to do with those last dollars on top of the giant pile anyway? Overall, therefore, the increase in expected jackpot size isn’t likely to make up for the decrease in odds.
So why did the Mega Millions people do this? They keep roughly half of the ticket revenue coming in, so they obviously have an incentive to maximize the number of tickets sold. Since the size of the jackpot is far more salient than the odds, the lottery managers are basically betting that people will be distracted by the huge shiny jackpot numbers and not really notice that their lottery deal got crappier overall. On the up side, this change to the lottery system results in a sort of natural experiment (especially since Powerball didn’t change its system, so it can serve as a control group) where we’ll be able to see the change in people’s ticket-purchasing behavior and make inferences about what factors people consider when purchasing lottery tickets.
Or, in shorter form, sucks for people, great for research.
P.S. If you are going to ignore most mathematical reasoning and play the lotto, I humbly request that you at least don’t play the same numbers that my parents insist on playing every week (and apparently convince me to play when they can’t):
I guess the apple sometimes does fall far from the tree in certain ways. =P
Tags: Behavioral Econ · Decision Making · Fun With Math
I feel like I’m going crazy- this is backwards, right?
I’m pretty sure I was taught that one of the side effects of strong unions is that they discourage hiring, both because unions tend to lobby for above-market wages and because companies are hesitant to hire employees when they know that said employees will be difficult to get rid of. If you don’t believe me, ask France.
Update: In related news, this exists. Also, if you want to noodle on the pros and cons of “right to work” laws, I suggest you look into how to become a member of the Screen Actors’ Guild.