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I contributed to a thing. It’s pretty interesting!
|Bad With Money With Gaby Dunn – Get Rich or Die Vlogging
by Gaby Dunn/Panoply
You know those money podcasts where financial experts teach you practical steps for maximizing your income? “Bad With Money” is the opposite of that. Gaby Dunn is anything but a financial expert. A self-described “bridge-burning livewire,” she’s always viewed money as an endless existential crisis – and she has a sneaking suspicion you do, too. So much of our identity and self-worth is caught up in how much money we have (or don’t have), how hard it is to get it, and even harder to keep it. Money makes us freak out, cry, and do wildly inappropriate things. So how come nobody ever talks about it? Join Gaby for conversations with comedians, artists, musicians, actors, her parents, a financial psychologist, her boyfriend, and many others about the ways that money makes us feel confused, hopeless, and terrified. This is a safe space to admit that you have no idea what you’re doing either.
Apologies for the break in posting videos- I got distracted and kind of forgot I hadn’t finished with them! Anyway, this one looks at some more detail in the disposition effect data and discusses whether investors in the sample seem to be learning to be rational as time goes on.
As usual, you can see the whole behavioral economics playlist here in case you want to catch up or need a review.
Trying out a new platform here…so far so good I think? At least it’s more productive than screaming into my poop emoji pillow, which is the other thing I’ve been doing lately.
|Maybe Working-Class Trump Voters Aren’t Racist, But They Are Comcast
by Jodi Beggs
It’s only been a week since the country was rocked by a seemingly improbable election result, and we are seeing an unprecedented level of protest and anger at both Donald Trump and those who voted for Trump. Much of the protesting appears focused on social and civil rights issues, which have been discussed fairly extensively in the media. (Personally, I think this guy has got my feelings covered.) In addition, there are many think pieces expressing frustration over how Trump voters either aren’t going to get what they voted for or won’t actually be helped by it. I certainly concur with these sentiments, but I also have my own economist-y reasons for being irritated with at least a particular subset of Trump voters. Allow me to explain via an analogy…
Hope you enjoy my rage. =P
I can’t resist appropriating a good meme…
It occurred to me earlier that some people didn’t get the joke, so allow me to ruin it by explaining. Donald Trump, staying in theme with the fake news that made him look good during his campaign (and after I guess), has on numerous occasions claimed that the “real” unemployment rate is around 40 percent rather than the 5 or so percent that the government reports. His general idea appears to be that the 5 percent doesn’t include nearly enough people who should be working but aren’t, but to get to Trump’s number you’d basically have to count every student, grandma, stay-at-home-mom-married-to-i-banker, etc. as unemployed. While it is true that convincing them to work would increase output (i.e. GDP), I tend to recall that history suggests that people don’t like being forced to work, so the 40 percent calculation isn’t really helpful from a policy perspective as an indicator of economic health. Besides, the government already publishes a number of “alternative measures of labor force underutilization,” which try to capture discouraged and underemployed workers that the main unemployment number doesn’t account for. (The government is clearly better at numbers than coming up with sexy names for said numbers.) To be fair, however, labor force participation has been declining since about 2007, which does give a bit economists a bit of pause, though it’s important to understand a bit more about the drivers of this decline (hi, retiring baby boomers!) before deciding what, if anything, to do about it.
I’m sure Ivanka’s going to explain this to him any day now.
I am not a macro person (by nature at least- I don’t deal well with severe empirical limitations and unanswered questions I guess). That said, I enjoy this profusely:
What I think I don’t like about basic macroeconomics is that I feel like we (I mean instructors) don’t always do a great job explaining why things work the way that they do. For example, we introduce the concept of gross domestic product, or GDP (but even then are kind of murky on how goods with imported components get counted), and we give the “real” version of GDP a variable, namely Y. We then say that Y can represent aggregate production, expenditure, or income. Ok great- I guess it has to be true that the amount people spend on our stuff has to equal our income, but it would be nice to point that out explicitly. What is less obvious is why it must be true that the amount of stuff we produce has to equal the amount that people spend on the stuff we make- sure, that should be true in equilibrium, but what is stopping an economy from producing a whole bunch of stuff that goes into inventory? As it turns out, the extra output is counted as purchased by the company that made it, so we’re sort of forcing that part of the equality by redefining expenditure a bit. Sure, why not.
Then we get to the “expenditure categories of GDP”– you know, the thing in the bed:
Y = C + I + G + NX = C + I + G + (X – IM)
You see this all the time in macro, and what it means is that the spending on an economy’s output can be broken down into
If you’re anything like me, this all makes perfect sense until you get to the net exports part, and then you’re like wait, what? Allow me to summarize a discussion that I think should happen in the classroom much more…
If we think about the different ways that stuff can be produced and consumed, we get something like this:
Since GDP, by definition, represents domestic production (regardless of where stuff is consumed), the area that should count in GDP looks like this:
But let’s think about the other GDP categories for a second- consumption, for example. Consumption represents the purchases by domestic households (other than newly constructed houses, technically speaking), and, if you’re anything like me, some of what you consume is produced in the U.S. and some of it is imported. As a result, the consumption area looks like this:
Therefore, the GDP identity needs to have a correction factor to turn the domestic consumption area (and, by similar logic to some degree, investment and government spending) into the domestic production area. Looking at the picture, it becomes pretty clear that we can do so by adding in exports and subtracting out imports. Funny thing- this is exactly what the net exports category of expenditure does!
Hopefully that helps the expenditure identity actually make sense as opposed to something you just memorize and try not to think too hard about. But it also highlights an important point- taking away imports, in and of itself, doesn’t increase GDP. Now, I get why people might think that, since looking at the basic Y = C + I + G + (X – IM), it certainly seems like Y goes up if you take away the thing that is subtracted out. The problem with this logic, as the pictures above illustrate, is that the IM part is just a correction factor, and you can’t take away a correction factor without also taking away the thing that you’re correcting! In other words, if you’re going to take away IM, you have to reduce, well, mainly C, and maybe some I and G, by a corresponding amount, at least in an accounting sense.
As a result, whenever anyone tells you that limiting or eliminating imports will increase GDP, they are making hidden assumptions about consumption (mainly along the lines that people will just buy domestic stuff instead and nothing else will change) that generally fall under the heading of assuming the conclusion. They are also potentially ignoring the fact that such an increase may not actually increase households’ standard of living if it makes their consumption decrease. (Taking away $100 of my imported stuff isn’t going to magically generate $100 of just as cool stuff for me to purchase from domestic producers- if this were true, I probably wouldn’t have been buying imported stuff in the first place.)
With me so far? Great, you’re farther along than Trump’s economic advisers in an important way. In reality, there are interconnections between the expenditure components that are not shown in the basic Y = C + I + G + NX identity, and these interconnections make it so that you can’t just look at this simple equation to analyze cause and effect.
Here, Greg Mankiw explains it a bit better, after mentioning that he agrees with Paul Krugman on the matter:
But of course you can’t model an economy just using the national income accounts identity. Even a freshman at the end of ec 10 knows that trade deficits go hand in hand with capital inflows. So an end to the trade deficit means an end to the capital inflow, which would affect interest rates, which in turn influence consumption and investment.
I suppose that their calculations might make sense in the simplest Keynesian Cross model, in which investment is exogenously fixed and consumption only depends on income. But that is surely not the right model for analyzing the impact of trade policy over the course of a decade.
(Mankiw provides more detail, but you have to acknowledge that Krugman wins the headline game.) I find it funny that people make it such a big deal when Mankiw and Krugman agree on anything…I mean, they agree on lots of stuff, namely basically everything in their respective textbooks. (Related: I know people who won’t use one of said textbooks bc of bias or whatever, and I find it hilarious since they are functionally identical for the most part.)
I’m guessing many of you are familiar with the trolley problem:
The problem is interesting because there is an objectively “right” answer- absent specific circumstances, one dead person is better than five dead people- but psychology, philosophy, ethics, etc. bring in a whole host of other considerations having to do with intention, fate, and so on. Such considerations result in a problem without a correct answer, and these considerations can’t (and probably shouldn’t) be ignored in a society of human beings and not robots.
Because of this unexpected complexity, the trolley problem has spawned a number of extensions, ranging from the even more nerdy…
…to the snarky and political:
There’s even what I will call the economist version, which incorporates opportunity cost/cost of effort as well as a few other factors…
In any case, we seem to be pretty familiar with the “clear efficient answer under some basic assumptions, but fairness and ethical considerations make things complicated” concept. So allow me to present a more accurate economic version of the trolley problem:
You are currently looking at a crisis area. The status quo is that there is a large shortage of Uber drivers to get people out of the area. Do you 1. Do nothing, or 2. Implement surge pricing?
I think this is a situation that we’ve seen before a number of times. Allow me to explain the similarities to the trolley problem:
“Clear Efficient Answer Under Some Basic Assumptions”
Surge pricing is the obvious answer here, under two assumptions: first, that surge pricing gets more drivers to the area, and second, that how much a person is willing to pay for an Uber is an accurate proxy for how important it is to them. Under these assumptions, shortages are smaller (or nonexistent) under surge pricing than they would be otherwise, and cars go to those who need/want them the most. (In case you’re curious, the first assumption seems to have empirical support even though surge pricing doesn’t appear to always get more drivers on the road overall.)
“But Fairness and Ethical Considerations Make Things Complicated”
I can’t really tell you what’s fair- that’s kind of the deal with value judgments- so I will instead report some common themes that I’ve come across. One is that people should have at least a chance to get an item at the “regular” price, and some people view random rationing as more ethical than price-based rationing when extenuating circumstances are present. (I wonder how this would change if pricing were framed as regular prices and discounts rather than surge pricing.) Another is that willingness to pay is a better proxy for wealth than need/want, in which case surge pricing unfairly rations items to rich people. (This may be true in cases of extreme income inequality, but shouldn’t be the case in a market with more uniformly distributed resources, so this view is somewhat of a fact/opinion hybrid.) Yet another that hadn’t even occurred to me (thanks Internet!) is that it’s unethical to use the promise of money to get largely low-income individuals (the Uber drivers) to take on risk of bodily harm, especially when said risk is incurred during the service of higher-income individuals. (See last point, and note that this is the same logic used to justify outlawing kidney donations and such.) Yet another is what Russ Roberts says. You’ll notice that all of the fairness arguments presented except the last one are against surge pricing.
My point in bringing this up isn’t to have a discussion on fairness or convince you of anything in this regard- like I said, you’re more than welcome to subscribe to one of these viewpoints or come up with your own. My point, instead, is to highlight the role that economics can play in conversations about what is best for society. To that end, here are a few points to keep in mind:
I guess I could do something similar for economists:
Okay? Great- now let’s go have some thoughtful policy discussions.
Technically, “constant returns to scale” describes a production process where you get exactly twice as much stuff out if you put twice as much stuff in. Economists often argue that at least constant returns to scale should be achievable since, worst case scenario, you could just build a second identical factory next to the first one. As such, I want economic instructors to start using this as their example of constant returns to scale.
Alternatively, you could examine the economics of chocolate more directly. Mmmmmmmmm…
Technically, I’m cheating with the “causal Friday” title, since, while regressions do identify associations that exist when controlling for other variables, these associations aren’t always of the causal variety. (This is particularly true when not all relevant factors can be controlled for.) But I choose to not be too persnickety because I think the comic is funny and wanted to share it.
Okay, you should have known better than to believe that I was going to avoid “too persnickety.” Personally, I won’t decide whether I am suspicious of the linear regression until someone tells me whether the slope is statistically significant. Also, if there are multiple explanatory variables that affect an outcome, a scatter plot that only looks at one of them at a time will generally looks like a mess even when all of the variables are individually important. In related news, this is a good opportunity to talk about the distinction between estimated effects (i.e. regression coefficients) and R-squared. (Don’t stop reading if you aren’t super into econometrics, I promise to make this make sense.)
Let’s say an economist is trying to model how much coffee I drink. (In reality, this is not necessary- the regression would just have a really big constant term, but go with me here.) Unfortunately, the only data available to use as an explanatory variable is income. Obviously, there are a lot more factors that affect my coffee consumption than just my income, so it shouldn’t surprise you that if I were to plot coffee consumption as a function of income (where each data point is a month of time, let’s say) I would get something that looks like the scatter plot above.
Let’s say that I’m measuring my income in hundreds of dollars and the estimated slope of the regression line is 0.01. This means that, on average, each hundred dollar increase in income is associated with 0.01 more coffees per month. If the numbers show that this estimate is statistically significant, then it’s pretty unlikely that this association exists in the data by random chance. Let’s also say that the R-squared of the regression is 0.06, like in the picture. This means that changes in my income only explain 6 percent of the variation in my coffee consumption.
My point is that these two conclusions aren’t in conflict with one another- it’s entirely possible for a relationship to both be statistically significant and for it to explain only a small fraction of what is going on. (This happens a lot in finance, actually, and an R-squared of 0.06 wouldn’t generally be seen as a red flag just because there is so much unexplainable noise in the data.) Sure, the result would be more impressive with a higher R-squared, but it’s largely a matter of personal judgment whether explaining, say, 6 percent of a phenomenon is worth talking about. (Not gonna lie- some economics journals vote no on this question.)
That said, I do recommend watching out for a red flag of a slightly different sort- one of the conditions in order for a regression to be valid is that your explanatory variables are uncorrelated with all the relevant stuff that you aren’t controlling for (your error term, in technical terms). In the case of my coffee regression, my result is valid only if my income isn’t correlated with whatever else could be causing variation in my coffee consumption (hours worked, for example). I can tell you personally that that is a lot of stuff.
I’m now tempted to perform a neural net analysis of my coffee consumption in order to see if I could get Rexthor out of it.
— Justin Sandefur (@JustinSandefur) August 25, 2016
Well played, sir. =P
Tired of the disposition effect yet? This one’s short, I promise- just shows how the incentives for tax-motivated selling of losing stocks change over the year and cloud the disposition effect test statistics.
As usual, you can see the whole behavioral economics playlist here in case you want to catch up or need a review.
So here’s a decent and concise overview of the latest issue to be taking over the internet:
|Have a peanut allergy? Chance are you’re about to spend a lot more on EpiPens
by Emma Hinchliffe
Over the past few weeks, EpiPens have slowly overtaken the news. So what is going on with them exactly?
I feel like we’ve talked about this before as it relates to this guy, who apparently has some feelings about economists:
@jodiecongirl lol economics professors lmao
— Martin Shkreli (@MartinShkreli) July 22, 2016
I don’t think he understands that economists are one of the groups likely most sympathetic to his ideals of profit maximization. Anyway, the general narrative is “company buys product, decides to make money from product, raises price of product,” and I would like to proceed by addressing one of Senator Sanders’ specific points:
There's no reason an EpiPen, which costs Mylan just a few dollars to make, should cost families more than $600. https://t.co/rVWUlMxD0Q
— Bernie Sanders (@SenSanders) August 18, 2016
This is where I point out that just because someone doesn’t like the reason doesn’t mean that the reason doesn’t exist. (As you’ll see in a bit, however, I pretty much agree with the spirit of what Sanders is saying.) In this case, the reason is some combination of inelastic demand and monopoly power– if consumers aren’t price sensitive (in this case because the product is a necessity) and they don’t perceive substitutes as being available (in this case one technically exists but often isn’t viewed as an acceptable substitute, so forgive me for not opining on the evils of patent protection at the moment), a producer can increase profit by increasing price. Sure, it will usually lose some customers, but the additional profit from customers that remain will more than make up for it. (In fact, the Lerner Index shows that markup over cost is inversely related to price elasticity of demand.)
Now, Bernie’s a smart guy, so I’m pretty sure that he knows this. He probably also knows that, even when producers are always maximizing profit, not all price increases are a result of cost increases. They could be the result of cost increases, but they also could be the result of an increase in demand for the product, at least in the short run. (That said, individuals do tend to view the former as fair and the latter as unfair.) In this case, there does seem to be an increase in demand for EpiPens over time, but what has more likely transpired is that the producer has shifted its values over time to focus more on pure profit maximization and less on keeping prices “fair.”
The somewhat uncomfortable reality is that, unless I’m interpreting price-gouging laws wayyyyyy too narrowly, the producer is within its rights to increase the price of its output, regardless of whether or not its costs have changed. (I feel like this point gets lost since companies often pay lip service to government to try to justify price changes in order to try to avoid future increases in regulation.) In fact, there’s even somewhat of an expectation coming from investors and capital markets that companies act so as to maximize profit. (While investors do seem to be increasing their emphasis on fairness and good corporate citizenship, the notion of a fiduciary responsibility to shareholders does still exist.)
I’m not saying that this outcome is right, either from an ethical or an efficiency standpoint, just that it shouldn’t be surprising. Again, the uncomfortable reality is that we rely on companies being “nice” as far as necessities are concerned in many cases, and recently we’ve gotten smacked with examples that show how fragile that trust can be. I’m also not saying that regulation is easy- how do you decide whether a product is truly a necessity? How do you decide whether a market is sufficiently competitive so as to solve its own problems? How do you regulate price or remove barriers to entry without destroying the incentives to innovate or keep costs down? (Economists have some models for regulating natural monopolies such as this, but they’re not perfect solutions.) I do think, however, that it’s a little unfair for policymakers to resort to shaming companies that are operating within the legal framework that they created because they kicked the regulatory can down the road (but, ironically yet likely justifiably, regulated enough to create the problem in the first place) rather than addressing what is an easily foreseeable issue from an economic standpoint.
Last time, we discussed the main result that shows evidence for the disposition effect- i.e. the bias toward selling winning stocks and against selling losing stocks. What I didn’t tell you at the time was that the calculation suffers from somewhat of an econometric problem, so I make up for my oversimplification and discuss that here.
As usual, you can see the whole behavioral economics playlist here in case you want to catch up or need a review.
So the internet seems pretty much obsessed with this story right about now…
|Ramen is displacing tobacco as most popular US prison currency, study finds
by Mazin Sidahmed
Cost-cutting measures by private facilities have led to subpar food quality and fewer meals, making noodles a commodity that trades well above its value
|Source: The Guardian|
The headline, taken at face value, isn’t particularly surprising to economists- we are quick to point out that a pretty wide variety of items can count as “money”, provided that they perform a few functions:
By this characterization, sure, ramen could serve as money- I guess ramen packs aren’t so large as to be too cumbersome to be traded, you could quote “prices” of other items in terms of packs of ramen (and measure your wealth in packs of ramen, I suppose, though that sounds a little sad), and ramen isn’t particularly perishable so it could make a decent store of value. If you think about it, basically any non-perishable commodity could be used as money in this way, it’s just a matter of changing your “base currency” to the good in question. For example, let’s say that the “price” of a pack of cigarettes is 3 packs of ramen- this means that 3 packs of ramen can be traded for one pack of cigarettes. (Note that prices are really just terms of trade.) I could have just as easily quoted the price of a pack of ramen as 1/3 of a pack of cigarettes- nothing has changed except I’m in an universe where the cigarettes are the base currency, i.e. money. (This framing shift happens all the time in foreign exchange, since a nominal exchange rate is just the price of one currency in terms of another currency.) I used this example because, historically speaking, cigarettes are commonly used as currency in prison situations, as the article points out.
When economists talk about money, we are careful to distinguish between commodity money- i.e. money with intrinsic value- and fiat money, which isn’t useful in and of itself. Clearly, ramen falls under the heading of commodity money, since, if you are anything like me, you get utility from eating ramen. (Technically I am referring to the restaurant version, but just go with me here.) Interestingly, it’s precisely this feature that causes me to question a. whether ramen is actually being used as money is typically used, and b. whether, if true, such use would even be a good idea.
The article above states that “the decline in quality and quantity of food available in prisons due to cost-cutting has made ramen noodles a valuable commodity.” I completely buy this statement, but “valuable commodity” and “money” are not synonymous. The article does go on to mention that ramen does often get traded for other goods and services, and the “prices” imply that there is some sort of arbitrage opportunity for those who can acquire ramen at the commissary price of 59 cents and then trade for other goods rather than acquire the other goods directly. The “money” argument kind of breaks down, however, when the article clarifies that people do in fact want to eat the ramen- I suppose you can technically eat a dollar bill if you wanted to, and you see situations where people use pennies decoratively rather than as a medium of exchange, but it seems like the opportunity cost of forgone consumption is pretty low when it comes to traditional currency, and you don’t see a lot of traditional currency being diverted for consumption purposes. Ramen, on the other hand, has a high opportunity cost of forgone consumption, literally speaking…and a prisoner decreases the the money supply every time he or she gets hungry! I’m not convinced that that is how money is supposed to work- just imagine the hunger-related swings in interest rates that could result. (At least when money is used to buy food, the food gets consumed whereas the money just gets transferred.) Even if the prison economy isn’t sophisticated enough to support a market for loans, eating the ramen currency is going to result in deflation, since there’s going to be less ramen currency to go around to conduct other economic transactions. (In other words, ramen purchasing power will increase because there is less of it available for purposes of exchange.) This isn’t great, since stable prices are thought to be a desirable feature in an economy.
I do think that there’s an important metaphor here- the above discussion suggests that sure, ramen can technically function as money, but the fact that it’s useful in itself causes it to function suboptimally as money in a number of ways. More generally, using an item as money either takes that item out of consideration as a useful resource or causes undesirable money supply/price stability effects (or some combination of the two). In this way, fiat money is pretty efficient in that it minimizes the productive stuff diverted to count as money (mainly some fancy paper, zinc, etc. Hey, it’s not a perfect system.). By similar logic, it’s not surprising that gold was a popular form of commodity money, since the uses for gold (electronics, jewelry, tooth caps. etc.) are actually pretty limited compared to the amount of gold available in the world. (If this were not the case, we wouldn’t see so much of it in bar form.)
I guess what I’m saying is that I hope this ramen as currency thing doesn’t catch on as a larger trend, since I don’t want to have to feel as bad about eating ramen as I do about leaving dollar bills in jeans pockets when I do my laundry. (I was going to say that I didn’t want to have to decide between eating the ramen and buying stuff with it, but I suppose the tradeoff between consuming one good and consuming another exists even when money itself is not consumable.) Also, it’s thought that contractionary monetary policy can cause recessions, and I certainly don’t want my ramen consumption habits to be responsible for that.
Update: The internet is a fantastic place, so now we’re discussing how the commissary could act as a ramen central bank and I am pondering the amount of seigniorage potential present in ramen minting. For now, I’m going to go in the kitchen and whip up some counterfeit ramen.
So a little while ago I wrote about the efficiency of free trade where I went through a situation in which a country would want to start importing a good from abroad. At the end, I noted that an export situation is basically the same but with a role reversal for producers and consumers. Nonetheless, there is an objection of “yeah, but you didn’t consider exports” in the comments section…I was mainly trying to not be repetitive, but in retrospect I think I inadvertently did what so many economists (especially economics instructors, sorry about that) do- we focus on the effects of imports and then gloss over the effects of exports. This isn’t great for students etc., and it’s particularly problematic because people more generally focus on the impact of foreign competition for production much more than the impact of foreign competition for consumption. So I apologize, and I’m here to make up for my earlier oversight.
I think this bias occurs at least partly because it’s easier to find motivating examples/case studies/etc. that have to do with imported goods. (This doesn’t mean that imports are a bigger deal, just that, like I said, we tend to focus on them more, so…chicken and egg, you know?) But here’s one on a topic near and dear to my heart…and stomach, and brain probably:
|Meet the Man Bringing Coffee Back to Colombia
by Ethan Fixell
Despite the country’s reputation for fantastic coffee, it’s nearly impossible to get a good cup of joe in Colombia. The second largest coffee exporter on earth sent $2.6 billion worth of beans to other countries around the world last year, forcing locals in most Colombian cities to brew imported beans from far-off places like Vietnam.
Like before, I’m going to try to explain what’s going on here without using any graphs (even though I like them so much!). Say you’re a coffee grower in Colombia, and you live in a world where there is no trade among countries. Your only option, therefore, is to sell your coffee to people in Colombia, who might not have a lot of disposable income or might not like coffee that much or whatever. In this world, you sell your coffee (unroasted wholesale, to make the numbers make a little more realistic) for 25 cents per pound. (No, I don’t know why our Colombian transactions are denominated in USD, but let’s try to focus here.) The point is that Colombian roasters can buy your coffee pretty cheap, which is good since they can’t set too high a price for the finished product, what with Colombians not having a lot of cash and not liking coffee and whatnot.
Now let’s open up Colombia to some trade- you know, that thing that people have taken a sharp turn against for some reason:
— Carroll Doherty (@CarrollDoherty) August 18, 2016
If we’re honest with ourselves for a second, I think we can all agree that Americans have a (relatively) decent amount of disposable income and are pretty much welded (I was going to say wedded but I think the typo works better) to our coffee intake. This combination of factors leads to a higher willingness to pay for coffee, especially Colombian coffee, since we all bought into the coffee marketing of the 1980’s:
(No really, that ad is from 1983, and I have no idea why this marketing was so salient to my young self.)
As a result, let’s say that roasters in the US will pay $1 per pound for Colombian coffee. Also, let’s note that we drink a lot of coffee, so the US roasters are willing to buy as much as Colombia will sell us at that price. What are Colombian coffee growers going to do?
I feel like the article preview pretty much ruined the suspense here- if coffee growers can sell all they want to the US for $1, they aren’t going to sell to Colombia for less than $1, so the price to Colombian roasters goes from 25 cents to $1. Colombian roasters don’t buy as much Colombian coffee (demand curves do slope downward after all), and Colombian coffee drinkers get coffee imported from Vietnam rather than the stuff that it right around them. Weird, right? But is perfectly understandable from an economic standpoint.
In this scenario, Colombian coffee producers are better off because of trade and Colombian consumers are worse off. (Told you it was the reverse of the import situation.) Like with imports, trade is efficient since the producers win from trade more than consumers lose from trade. Why is this? Well, let’s think about this in a few consumer-group parts:
This combination of no change, increase, increase has to result in an overall increase in value for Colombian society. (Like the basic import analysis, however, this doesn’t address distributional concerns regarding winners and losers.)
Not gonna lie- it’s pretty perplexing to me that this dynamic doesn’t seem to call for export restrictions nearly as much as the reverse situation results in calls for import restrictions. If I had to guess, I would hypothesize that people are more inclined to think about their welfare in terms of money coming in (i.e. the producer side) rather than in money going out (i.e. the consumer side). On the other hand, people complain way too much about inflation for this explanation to be entirely satisfying, so who knows. Maybe it has to do with the fact that producers tend to be more concentrated than consumers, and more protest happens when losers are more concentrated? In any case, it *is* sort of unfair to talk about the effects of imports without considering the effects of exports, or vice versa, if for no other reason it’s difficult to include a “we want to sell you stuff without restriction but we’re going to tax the stuff you try to send to us” clause in trade agreements nowadays.
In a previous video, my class went over the empirical setup in one of the main papers about the disposition effect in stock-market behavior. Now they got to talk about the results of that analysis:
If you need a refresher, you can see the whole behavioral economics playlist here.
You know you’re an econ/math nerd if you read this and think “haha, it’s like the matching pennies game”:
But hear me out…here’s the matching pennies game, and, like the joke, the crux of the game is that there is no Nash equilibrium without randomization. To further the analogy: The matching pennies game works as it does because player 1, let’s say, “gets off” when the pennies match whereas player 2 gets off when the pennies don’t match. (This wording hopefully shows the intuition of why there is no pure-strategy Nash equilibrium, since the goals of the players are clearly mutually exclusive.) The…uh, matching fetishes game works in a similar fashion, since the guy gets off when he and his partner are in agreement, but the woman gets off when there is discord.
With some minor labeling changes, you could even make a payoff matrix for the matching fetishes game, the conclusion of which is…hm, can one randomize being turned on or not?
In my class, I try to introduce a topic and then give my students a discussion question to work through so I can make sure that everyone is catching on. This discussion question relates back to the disposition effect, or the bias towards selling winning stocks and away from losing stocks.
If you need a refresher, you can see the entire behavioral economics playlist here.
Steve Levitt, in addition to gaining fame (at least at an economist level, not a Justin Bieber level) for writing Freakonomics, has made a career teasing cause and effect out of (largely) observational data. (By “observational data,” I mean that he doesn’t explicitly run controlled experiments in a lot of cases and just looks at the world as it transpired naturally instead.) Observational data presents an interesting challenge because people usually make choices in life rather than being guided by randomness. As a result, we often end up with selection bias that makes causal interpretations difficult- for example, we can look at people with and without pets and observe that the people who have pets are happier. (This is hypothetical, but it is in keeping with everything I would like to believe about the world.) This doesn’t mean that pets make people happier, since it could just be the case that people who are already happier also tend to adopt pets. It would be better from a data analysis standpoint if people were just randomly endowed with pets (like when a cat showed up on my doorstep when I was little I suppose), but unfortunately for science purposes we live in a society where people choose whether or not to have pets, and this choice aspect kind of messes things up.
To try to overcome this issue, economists tend to look really hard for sources of randomization- technically known as instrumental variables. In the pet example, whether a stray animal showed up on the doorstep might make a good instrumental variable, at least if the showing up was fairly random and people tended to keep the animals once they showed up. Using some statistical fanciness, we could compare the group of people who had animals show up versus those that didn’t and get a reasonable estimate of the causal effect of pets on happiness.
I know what you’re thinking- this is all nice in theory, but it’s not like we keep good records on stray animal on doorstep prevalence. This is true, and wouldn’t it be nice if we could actively create an instrumental variable- perhaps let a bunch of stray cats loose in a neighborhood and record what happens? (I was going to add a disclaimer to not try this, but it could actually be pretty interesting for research purposes.) How about if we could introduce a source of randomness in the easiest way possible, by flipping a coin?
Turns out that Levitt actually implemented the coin flip as instrumental variable to assess the causal effect of change on happiness:
Little is known about whether people make good choices when facing important decisions. This paper reports on a large-scale randomized field experiment in which research subjects having difficulty making a decision flipped a coin to help determine their choice. For important decisions (e.g. quitting a job or ending a relationship), those who make a change (regardless of the outcome of the coin toss) report being substantially happier two months and six months later. This correlation, however, need not reflect a causal impact. To assess causality, I use the outcome of a coin toss. Individuals who are told by the coin toss to make a change are much more likely to make a change and are happier six months later than those who were told by the coin to maintain the status quo. The results of this paper suggest that people may be excessively cautious when facing life-changing choices.
(Note that you should be able to access the article with most university email addresses, and even some alumni email addresses. Worth trying, at least.)
So let’s think this through…the outcome of a coin flip is random, so people were essentially randomized into “change” and “don’t change” groups. This randomization implies that the two groups are (at least approximately) comparable along other dimensions, leaving the change directive as the only systematic difference between the groups (and therefore the only plausible cause of any observed differences in outcomes). If everyone who was told by the coin to make a change actually did so (and vice versa), Levitt wouldn’t have even had to do anything statistically fancy and could have just compared the average levels of happiness of the two groups. Because not everyone listened to the coin (which I guess is sort of a good thing for the world more generally), he had to do the more fancy version of the math but is still able to find a statistically significant causal effect of change on happiness. Cool, huh? Now go make a change- apparently it’s good for you.
In case you’ve forgotten, the disposition effect is the bias toward selling winning stocks (or other investments I guess) and away from selling losing stocks. In the video below, I start covering one of the seminal empirical papers on the disposition effect and can’t resist fangirling out for a second in the process.
You can see the full behavioral economics playlist here.