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.
First off, HAPPY THANKSGIVING! I am very thankful that you all read my online ramblings
Once you get drowsy from eating too much Thanksgiving dinner (and no, it’s not the turkey, that’s mostly an urban legend, unless of course you ate the entire turkey), you should feast on what Dan Ariely has to say about giving:
Also, it’s a bit late for dietary advice, but in case you are curious how behavioral economists think about planning a Thanksgiving meal, this is totally for you. Actually, it should probably be for everyone, given that the average Thanksgiving dinner contains about 4,500 calories, or, for context, the recommended caloric intake for at least two days. If you feel like this excessive smorgasbord of calories has been getting more extreme as of late, it’s likely at least in part because the stuff that goes into making Thanksgiving dinner has gotten much cheaper in real terms over time.
Soooo…you may have noticed that I am writing rather than eating turkey and making awkward small talk with family members on this fine Thanksgiving day…that is largely by design, and the photos of the airports and train stations that have been floating around on the Internet suggest that my strategy is in fact optimal on a number of levels. (I suppose it also helps that I am not alone in choosing this strategy and that restaurants in Boston are more than happy to exchange money for turkey and stuffing…and cocktails.) Even so, I am quite pleased that Massachusetts is one of (I think) three states that has blue laws that prevent most retail establishments from opening on Thanksgiving. (Since Massachusetts is a small state, it’s probably helpful to know that the other two states with such laws are Rhode Island and Maine.)
But wait- shouldn’t I be against seemingly arbitrary regulation? Yes, and I am more than happy to explain myself…but let me give you some more Massachusetts fun facts first:
Until a few years ago, blue laws in Massachusetts stipulated that liquor stores in Massachusetts couldn’t be open on Sunday unless one of two conditions was met- either the store was located within 3 miles of the New Hampshire border (since liquor stores in New Hampshire were open on Sundays and it was easy for customers near the border to take their dollars out of state) or it was between Thanksgiving and New Year’s Day (I have no idea what the reason was for that one). Once discussions about repealing said laws began, many were surprised to find out that many liquor store owners were vehemently opposed to repealing the law. Their (likely correct) reasoning was that people knew that the liquor stores weren’t open on Sunday and, in most cases, planned accordingly, so opening on Sunday wouldn’t add a while lot to overall demand. It would, however, add to the store’s cost, so it would lower the store’s profits. (In other words, the store owners didn’t think that the incremental demand would cover the variable costs associated with being open on Sunday.) Furthermore, it wouldn’t make sense for a single store to refuse to open on Sunday, since customers could easily find one that is open and therefore don’t have an incentive to plan ahead. Overall, repealing the law was probably good for consumers but probably not good for producers.
Most of the same logic holds for stores being open on Thanksgiving, since both scenarios have the characteristics of a prisoners’ dilemma, or, more specifically, an arms race. Each store believes that it has to do what all the other stores are doing (or even more) or their customers will go elsewhere, so we end up in situations where stores are opening on Thanksgiving and trying to get people to shop rather than enjoy their Thanksgiving dinner. Consumers, for their part, see many deals that are either for a limited time or that will run out of stock quickly, so they (perhaps rationally) are compelled to forgo the turkey for the shopping sprees even though most of them would prefer to have a nice meal with family and do the shopping later.
The thing about both the prisoners’ dilemma and the arms race is that all parties are better off if their actions are constrained. In the same vein, Massachusetts is (probably unwittingly) being mostly helpful by constraining the actions of retailers- people can have their Thanksgiving dinner and still make it to the stores when they open, no one is cajoled into working on Thanksgiving (I get that this reduces labor hours, but the general consensus appears to be that retail workers don’t want to work on turkey day), and the stores aren’t likely to see their sales suffer, since it’s unlikely that the Thanksgiving shopping is actually incremental spending. (There’s not even really an incentive to go shop out of state, since customers will have the same deals available in Massachusetts on Friday morning.)
Or, in short, both Massholes and the businesses that they frequent should give thanks to their state government for helping to nip a coordination failure in the bud. Regulation that turns out to be useful- looks like a Christmas miracle came early this year. =P
Tags: Behavioral Econ · Buyer Beware · Game Theory · Policy
This video reviews how to calculate costs and maximize profit in competitive markets and then discusses how to determine market supply and profit in the short run and how to analyze the transition to the long run. The problem is taken from Principles of Microeconomics, 6th Edition, by N. Gregory Mankiw, and is Ch. 14 problem #12.
You can find more practice problems via the Practice Problem of the Day category archive or by visiting the Econ Classroom page. You can also be notified of new practice problems by subscribing to the YouTube channel.
Tags: Practice Problem of the Day