Last week I did a comparison of “time prices” for several goods and services in 1971 compared with 2024. For almost all goods and services, it took fewer hours of work in 2023 to purchase them. In some cases, huge increases in affordability; air travel is 79% cheaper and milk is 59% cheaper, in terms of how much time an average worker needs to labor to pay for them.
There was one major exception though: housing. Especially the cost of buying a new home. Just using the median sale price of a home, the cost (in terms of hours of work) roughly doubled between 1971 and 2024. That’s not good!
Many who commented on the post mentioned that houses are much bigger today, and I noted that in the post but still claimed this is a worrying trend: “since 1971 you can’t really argue the quality improvements make up for the increase. Yes, houses are much bigger (about double in size), but that’s not clearly driven by consumer demand (more so by zoning and other laws). The 1971 house also had indoor plumbing (but maybe not air conditioning).”
Are houses bigger today? Yes, but not nearly enough to account for the decreasing affordability I showed in the previous post. In 1971, the median new home had 1,400 square feet of floor space. In 2023, it was 2,286. That’s a big increase (over 60%), but let’s now do the time-price affordability calculation, which I show in the table below.
For decades, our family favorite holiday cookie recipe has been a hearty ginger cookie containing, among other things, wheat germ. The original recipe author claimed that these cookies “got my family through Alaskan winters”. That’s hard core.
With my family’s help, I made big batches for decades to hand out among colleagues at work. This always included my boss and boss’s boss, and their admins. (Cynics may think what they wish of my motives there.) Also, we like to hand out small, decorated bags of cookies to all our neighbors for several houses in all directions. We like to try to build community as we can, and this is often the only time we get to exchange words with some neighbors.
However, there are two downsides to that ginger cookie. First, it is very labor-intensive. The final mixing with a stiff dough takes a lot of muscle, and forming the cookies takes an assembly line with multiple steps: with the help of a spoon, form the sticky dough into a ball, then roll the ball in sugar, then place on baking tray, then press a blanched almond (can only find these in specialty vendors these days) into the top of the ball. Second, this ginger cookie is a bit on the dry side – – I would usually recommend consuming them with coffee or milk as I handed them out.
Two years ago, however, an esteemed family member pointed me to a radically different recipe, for an oatmeal chocolate chip cookie. That seemed kind of decadent compared to my old favorite, but worth a try. It solved the two drawbacks for the ginger cookies. Making it is easy, just scoop into the dough and plop onto the cookie sheet. (I did buy a cookie scoop for this). And there was no need to apologize for dryness. These babies are just plain delicious. So now I make large batches of these cookies to hand out to neighbors at Christmas.
Without further ado, here is a link to the recipe for Chewy Oatmeal Chocolate Chip Cookies, by Sally McKenney of Sally’s Baking Addition. You do have to follow the directions, including the step of creaming the butter (see links in recipe for what “room temperature” means) and sugar, and using old-fashioned (not instant) oatmeal.
Here are some of my tweaks to this recipe:
Make two double batches, in two separate large bowls. Chill in fridge several hours. Set aside several hours to bake them all.
Don’t bother creaming butter alone. Just add sugars to butter and stir in with wood spoon, then beaters. Add flour, using spoon and then beaters. For adding oats, chips, etc., just use spoon.
I backed out some of the chocolate chips, and added chopped walnuts: so, in each double batch I have total 3 c choc chips (e.g. 2.25 c regular chips, ¾ c mini chips), plus 1 c chopped walnuts. It’s worth getting good chocolate chips. Ghirardelli seems to be the best chocolate chip. Guittard also gets raves.
The recipe calls for big cookies (a full, large scoop, about 3 Tbsp), but those may spread too much, and I want more cookies, so I use about ¾ full large scoop.
Bake at 355 F instead of 350 F, to speed it up a bit. (My oven is wimpy, electric). Parchment paper works well to keep cookies from sticking.
Newly published research from Finlay et al takes the deepest dive yet on how the costs of the criminal justice system impact people’s lives going forward. Leveraging the new (and phenonomenal) integrated data from CJARS, the authors look at 9 (!) separate discontinuous increases in the fines and fees associated with misdemeanor and felony convictions. The paper is exceptionally well executed, connecting criminal and earnings records to estimate a pooled seemingly unrelated regression of those 9 separate treatments. They observe null effects on future convictions, earnings, and living conditions. So does this mean we can soak those convicted for every penny in their pockets without consequence? No, I don’t think so (and I strongly doubt the authors do either). Does it mean that people, such as myself, need to soften their calls to stem the growing tide of law enforcement as local regressive taxation scheme? Maybe in some cases, but I do think additional context matters here. A couple quick comments, in no particular order:
Of the 9 increased fine and fee treatments, 4 are small (≤$65), 5 are large (≥$200). Four of the large increases are explicitly raising the fines and fees of traffic offenses (DUIs). It’s not unfair to summarize the legislated treatments here as mild for those more likely to be in a state of poverty since you have to have access to a car to receive the larger treatments.
There’s always a little bit of a Rorschach test with RD designs, even when the differences are or are not statistically significant. In this case we observe null effects, but it sure seems like something happens with convictions in the first 100 days after reform and then it returns to trend (see below in Panel A). That feels like a system updated the de facto rules to accomodate the new de jure. As for earnings, it’s always tough when slopes change sign (Panels B and C), but the differences aren’t significant.
In the subgroup analysis there are two significant increases in recidivism, most notably a 4.7% increase in recidivism for those in the lowest predicted income quartile. This isn’t an enormous effect, but when it comes to what I consider to be a regressive tax, then focusing on the lowest income quartile isn’t an exercise in p-hacking, it’s to some degree the point of the endeavor. Combine that with the fact that the overweighting of the high magnitude treatments on driving offense can be expected to attenuate the potential effect on treated individuals with low incomes, a 4.7% increase in recidivism doesn’t seem that small anymore.
This is good research, but like most contributions it isn’t the last word. The growing use of fines and fees as revenue sources is a complex and, in many ways, adaptive system that exists to generate revenue for local governments whose revenue apparatuses hamstrung in countless ways, frequently struggling to keep the lights on (whether those lights should necessarily be on is a whole separate question). When they’re looking for that revenue, many (but not all) will arrive at the conclusion that they can only get so much much from poor people. Sometimes, such as with traffic offenses, the poorest individuals that do get caught in this system aren’t necessarily the intended targets, but rather the collateral damage. When we’re looking for that collateral damage, it’s important to know both where that damage is occuring and where it is being mitigated by local adaptation, particularly that which exists outside of the laws as written.
If you spend any time on Twitter/X, you must know the suit guy, Derek. Given my interest in the economics of fast fashion, I read his new thread about expensive craft sweaters.
He explains that some clothes on this earth are still made by hand. Artisan sweaters cost a lot because of the labor. Supporting that art or tradition is fine, if you have $500 on hand.
The comments on the thread are interesting as well. (Caveat, a good number of anonymous accounts are trolls bent on your destruction – read accordingly always.)
One comment, presumably by an amateur knitter in a rich country: “As a knitter, I know how much work would go into hand making sweaters like these. That’s not even taking into account the cost of a good wool yarn. If anything, they are underpriced.”
Not a lot of people want to spend $500 on a sweater. I really loved this reply about thrift stores. We don’t all have to buy the sweater new.
My related posts on fast fashion (a.k.a. factory-made sweaters cost $5):
Cato Globalization book out in paperback – my most optimistic take on this is that AI will facilitate the sharing part of the sharing economy, which will help justify the cost of high-quality new garments.
I wrote about the protein content of different foods previously. I summarized how much beef versus pea and wheat flour one would need to eat in order to consume the recommended daily intake (RDI) of ‘complete proteins’ – foods that contain all of the essential amino acids that compose protein. These amino acids are called ‘essential’ because, unlike the conditionally essential or non-essential amino acids, your body can’t produce them from other inputs. Here, I want to expand more on complete proteins when eating on a budget.
Step 1: What We Need
To start, there are nine essential amino acids with hard to remember names for non-specialists, so I’ll just use the abbreviations (H, I, L, K, M, F, T, W, V). The presence of all nine essential amino acids is what makes a protein complete. But, having some of each protein is not the same as having enough of each protein. Here, I’ll use the World Health Organization’s (WHO) guidelines for essential amino acid RDI for a 70kg person. See the table below.
Step 2: What We Need to Eat
What foods are considered ‘complete proteins’? There are many, but I will focus on a few animal sources: Eggs, Pork Chops, Ground Beef, Chicken, & Tuna. Non-animal proteins will have to wait for another time. Below are the essential amino acid content per 100 grams expressed as a percent of the RDI for each amino acid. What does that mean? That means, for example, that eating 100 grams of egg provides 85% of the RDI for M, but only 37% of the RDI for H.
That’s the title of a recent book by Liran Einav and Amy Finkelstein, subtitled “Rebooting American Health Care”. I reviewed the book for Independent Review; the short version of my review is that while I don’t agree with all of their policy proposals, the book makes for an engaging, accurate, and easily readable introduction to the current US health care system. Here’s the start of the review:
Liran Einav and Amy Finkelstein are easily two of the best health economists of their generation. They have each spent twenty years churning out insightful papers published in the top economics journals. As a young health economist, I would read their papers and admire how well they addressed the technical issues at hand, but I was always left wondering what they thought about the big picture of health care in the United States….
The book’s prologue describes how Finkelstein’s father-in-law finally bullied her into writing on the topic, using almost the exact words I always wanted to: “I know these are hard issues. But come on … You’ve been studying them for twenty years. You must be one of the best placed people to help us understand the options. Do you really have nothing to say on this topic?”
The conclusion:
I learned a lot reading the book, despite having already studied U.S. health financing for over a decade—for instance, that the first compulsory health insurance program in the U.S. was a 1798 law pushed by Alexander Hamilton to cover foreign sailors. While the authors are more used to writing math-heavy academic papers, We’ve Got You Covered reads like the popular press book it is. Perhaps the highest endorsement comes from a non-academic family member of mine who picked up the book and noted, “These are not dry writers … this doesn’t sound like a book written by economists, no offense.”
The full review is free here, the book is for sale here.
I’ve written before on this blog about “time prices”: the amount of time it takes at a particular wage to buy a specific product. Time prices are especially useful for making historical comparisons of the real price of a good or service. Rather than adjusting historical prices for inflation (which only tells you whether they have increased faster or slower than average prices), time prices give you a real comparison of whether a good has become more or less affordable.
You will notice a few things here. For the median worker, most things are much more affordable in 2024. Some things are dramatically so! For many items, the median worker in 2024 is similar to someone in the top 1% in 2024. Huge improvements in the standard living.
It will probably not surprise you that one major exception is housing. For renters, things are not obviously worse, but they are not better, depending on what size of city you are in (renters also have lower incomes, but that would be true in both time periods). However compared to the average home price, things look much worse in 2024. You can reasonably reply that the home is much larger and better quality in 2024 (as late as 1940, barely half of homes had complete indoor plumbing!), and this is all true. Still, an average house today is much better, but also much less affordable.
Despite the high cost of housing, the average worker today is much better off than 1924. It’s hard to deny it.
But what about more recent times? As a recurring meme likes to date it, what about since 1971?
This is a guest post by Mary Buchanan, a Board Certified Behavior Analyst. Here she explores the intersection of behavioral economics with her own health and fitness behavior change.
My childhood dentist often said, “Take care of your teeth, or they’ll go away.” As I approach my 40th birthday, I’m learning the same is true of my muscle mass. I can use it or lose it. And I can lose it faster or slower based on my lifestyle choices.
As a behavior analyst, I have spent many years practicing the science of behavior, specifically teaching others how to master new, meaningful skills. I see myself as my own client now as I work to replace my old aimless approach to fitness with evidence-based eating and exercise interventions.
I wish I could say I embraced strength training as soon as I heard about its benefits. Instead, as I noticed more and more recommendations for women to “lift heavy”, I kept filing that information away for someday in the future. When I joined a gym last January, I returned to what I used to do in years past: Pilates classes or cardio machines. After 9 months of that approach with no benefits to show for my efforts, it was time to change my behavior.
Behavioral economics has a term for what causes people to resist changing their behaviors without a significant incentive for doing so: status quo bias.
Another behavioral economics term, loss aversion, helps to explain what moved me into action. Loss aversion refers to how people are often more motivated not to lose something they have than they are motivated to gain something similar. All humans start to lose muscle mass around age 30, but that fact was not on my radar until recently. I wasn’t interested in building muscles when I thought mine were adequate to my daily tasks. Now that I realize my muscle loss has been underway for years and the liabilities of that loss are clear to me, I’m motivated to rebuild and mitigate future muscle loss. How? By doing heavy lifting 2-3x per week and eating enough protein for my body to keep the muscle it makes.
There are many great resources that provide advice in this area, but I’ve decided to begin with learning from Dr. Stacy Sims since she specializes in what works for women. Based on what I’ve learned, here are my target behaviors for increase:
Practice strength training for at least 30 minutes, 2x per week. Dr. Sims says 3x per week is better, but 2x is an acceptable minimum that I can commit to either through classes at a gym or YouTube videos. As a behavior analyst, I know that I’m more likely to maintain a new behavior pattern when it is easy to feel successful early and often.
Continue to challenge myself throughout strength training by adding weight as I get stronger. To stimulate muscle growth you must challenge your muscles so they break down and repair stronger. How heavy is enough? If you lift a weight 10x and it’s difficult to lift on the last two reps, but still possible for you to maintain good form, that is an appropriate weight for you to train with. When that weight gets easy to lift, it’s no longer heavy enough for your training purposes.
Increase my healthy protein intake. In Roar, Dr. Sims suggests that women aim for .75-0.8 grams of protein per lb. on a light or non-training day, and increase to 1-1.2 grams of protein per lb. on strength training days.
Working on these goals together creates synergy. I am more motivated to make healthier eating choices because my eating is connected to my strength training goal. Strength training has also become more exciting for me the more I’ve learned about its benefits, including:
Increased metabolic rate
Improved posture and stability
Stronger bones
Better blood pressure control
Improved immunity
Maintenance of healthy body composition (lifting heavy helps maintain lean muscle and reduce fat gain)
As if that weren’t enough, I have another reason to keep going. As soon as I started resistance training, my sleep improved! I’ve had difficulty sleeping for many years already, both with falling asleep and staying asleep, and honestly, if sleeping through the night was the only benefit available to me from resistance-based workouts, I would still be all in.
While none of this constitutes professional medical advice, it is worth looking into, especially if you, like me, never saw role models strength training as a young person. Once you understand how it works in your favor now and as you age, the benefits are too good to pass up.
RESOURCES
Stacy Sims, MSC, PHD is an exercise physiologist and nutrition scientist. She specializes in teaching women what works for their bodies based on their body type, stage of life, and fitness goals.
There’s probably nothing more dangerous to an already successful business than giving customers what they say they want. This is not to say you can give customers something they don’t want, quite the opposite in fact. Rather, it’s to never deny the preeminence of revealed preferences.
People want things. They don’t always, however, enjoy how those preferences might be perceived by others (or by themselves). Customizing your consumption to fit the preferences that you would prefer to signal is not a luxury that we can often indulge, however. Basic instrumental needs have to come first. Once a good is already in a household’s portfolio of consumption, however, it is relatively low cost to signal alternative preferencs to peers, surveyers, or focus group organizers. If a producer were to take these signals as earnest, however, they could end up undermining the good already previously purchased and consumed, leading to a business catastrophe. “Trust people’s actions over words” is at least a cliche, if not an outright proverb. I’ll leave it to you to find its most archaic analogue.
I’ve been thinking about this a lot, and no, not in the context of political polling and the recent election, though I will grant the relevance. I’ve been thinking about it more when watching sports and consuming the news.
Soccer in the top leagues, particularly the English Premiere League (currently the best in the world) is in year 5 of a growing injury crisis. Most seasons the winner can be predicted based on total salary outlays. Not because of superior top line talent, however, but because they can afford 11 second string players of top quality to play when the starters are inevitably injured. This is largely because of a tragedy of the commons in international soccer, but it’s been massively exacerbated because the EPL responded to the perceived request from consumers that the sport become “more physical”. This amorphous physicality has been granted in the form of more lenient refereeing. The result of this has not been to increase the “fight in the game”, but to grant less talented players greater license in kicking and sliding through the legs of more talented players. I don’t know the full economics of modern sports, but I’m pretty sure fans don’t pay large ticket prices to see the best players in the world on the sidelines in high-end athleisure wear draped discreetly over a walking boot.
As for the news, I see a related, but not identical phenomena. Being a GenX-er, I spent a lot of time in heavy conversation during college bemoaning the impact of advertisers on media content. The “news as propaganda” bit is not a new concept, I assure you. What very, very few us would have guessed, however, is that Craigslist destroying the ad revenue of newspapers and the internet walking off with the customer base most interested in news as information source would lead television program producers untethered to the desires of their advertising sponsors, leaving them to create bespoke content for their new overlords: the consumer. As it turns out, what the remaining subset of customers most wants isn’t information or insight, it’s reaffirmation. We wanted advertisers out of content, but it turns out you got better news when the true customers were corporate overlords hawking sugar water and baggy clothes. People signaled that they wanted deep reporting, uncompromised integrity, and uncomfortable truths. And hey, more people than ever subscribe to The Economist. But it turns out most people just wanted confirmation bias.
Sure, by clicking on the link to this post you’ve signaled to me that you want a depth of insight you just can’t get anywhere on the internet. But I, enwisened scribe, know that what you really want is cliched aphorisms.
Rosenberg: What impact do you foresee in your field due to the increasing sophistication of AI, and what kind of skills do you think your students will need to be successful?
Buchanan: AI will reshape economic analysis and modeling, making complex data processing and predictive analytics more accessible. This will lead to more sophisticated economic forecasting and policy design. Economists will become more productive, and expectations will rise accordingly. While some fields might resist change, economics will be at the forefront of AI integration.
For students aiming to succeed, it’s crucial to embrace AI tools without relying on them excessively during college. Strong fundamentals in economic theory and critical thinking remain essential, coupled with data science and programming skills.
Interdisciplinary knowledge, especially in tech and social sciences, will be valuable. Adaptability and lifelong learning are key in this evolving field. Human skills like creativity, communication, and ethical reasoning will remain crucial.
While AI will alter economics, it will also present opportunities for those who can adapt and effectively combine economic thinking with technological proficiency.
Economist Writing Every Day 