I will be doing a Conversation with him, here is the opening part of his Wikipedia page:
Pierpaolo Barbieri (Buenos Aires, May 17, 1987) is an economic historian, researcher, Executive Director at Greenmantle[and founder of Ualá, an Argentina-based personal financial management mobile app. He is the author of the book Hitler’s Shadow Empire: The Nazis and the Spanish Civil War. He has been featured in publications like Financial Times, New York Times, Foreign Affairs, El País, and The Wall Street Journal.
So what should I ask him?
That is the topic of my latest Bloomberg column, drawing upon an earlier discussion by Robin Hanson. The problem is this: if families find that having three or four kids just isn’t that fun, and women wish to focus more on their careers, which forces might be capable of reversing that trend?:
One possibility is that a shrinking population itself will bring self-reversing mechanisms. For instance, a Japanese population half its current size would make Japan an emptier place, presumably lowering land prices. Some families would find it easier to afford a larger apartment in central Tokyo and perhaps decide to have more children.
But that mechanism seems more likely to reduce population decline than to reverse it. Living space is only one of many factors behind decisions about family size. And as population declines, the stock of houses and apartments will decline too, so in the longer run the amount of space per family may not increase by very much…
Another factor in declining fertility, especially in the U.S., is single parenthood. If a potential mother is facing a fertility decision without another full-time parent on the scene, she is more likely to choose to have fewer children. As population falls, will single-parent families become less common? It is hard to see why. Whether the issue is a lack of marriageable men, unstable family norms or women who simply prefer to go it alone, there is no particular reason to think those factors will disappear in an era of population decline.
What might be some other intervening factors to restore fertility? Perhaps tender and loving robots will make it much easier to raise young children. Or maybe, as populations fall to much lower levels, a sense of moral panic will set in. Families might decide to have more children, feeling that the very survival of their country is at stake. A more elaborate and dystopian scenario would be that corporations take over empty parts of the globe and pay for the raising of children there, in return for a share of their future income.
Here is Ross Douthat’s Sunday column on broadly similar issues, each column was written independently of the other. As I interpret his discussion, he is more (potentially?) optimistic about ideological and religious forces reversing the decline than I am, in any case an interesting contrast of approach. By the way, here is Robin Hanson’s proposal for how to escape the problem, more economistic than either Ross or myself.
A question for econtwitter from my bartender. If the US government via deficit spending engages in economic development in other countries, does that increase inflation here?
I would approach this question as follows. Assume the government is running a foreign aid program that mostly makes purchases and investments abroad with non-U.S. suppliers, furthermore assume floating exchange rates.
The foreign aid, a kind of capital outflow, will induce the dollar to depreciate somewhat, a’ la “the transfer problem” of the 1920s. That will lead to a modest inflationary impact on imported goods, possibly of a one-off nature if the foreign aid is itself a one-off policy. American exporters will gain, noting that under some unusual assumptions about the terms of trade the U.S. domestic economy can end up better off. (Induced profits on the depreciation can in principle outweigh the initial loss from the transfer, though please “do not try this at home.”)
If the deficit is monetized, the exchange rate may depreciate all the more, as individuals shift their future expectations toward a more expansionary monetary policy. Furthermore, the higher global money supply of dollars would give foreigners a higher option value on making purchases in the United States, another form of (likely modest) inflationary pressure.
If the deficit is financed by borrowing, someday that debt must be repaid. If it is repaid by higher taxes, that has a deflationary effect on aggregate demand, though the incentive effects of the taxes will lower supply in the future, again creating a (probably modest) upward push on the price level as a further effect.
If you wish, you can toss in added second- and third-order effects on those taxes on exchange rates, terms of trade, and so on.
As an exercise to be performed at home, what if the U.S. sends aid to a dollarized economy, such as Ecuador or El Salvador?
Another one from the Department of Uh-Oh:
Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many‐analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect’s sign varied as well. The standard deviation of estimates across replications was 3–4 times the mean reported standard error.
Khanna says these intricacies mean that brash political talk about reshoring operations is naive. “Even the supply chain has a supply chain,” he says.
A dose of the BioNTech/Pfizer vaccine, for example, requires 280 components from multiple countries, according to the company. The idea of moving from what Okonjo-Iweala calls “just in time to just in case to just at home” is harder than it looks.
The biggest question in the U.S. right now is how rapidly vaccinations will proceed. Yet only 8.5% of the new appropriations — under the most generous calculations — are directed toward vaccine supply and anti-Covid-19 efforts.
The biggest question for the world is whether the wealthier nations will put up the estimated $25 billion needed to jump-start a global vaccination campaign in a (relatively) timely manner. So far it appears that they will not — again, a supply-side issue. There did not seem to be much interest in putting such an expenditure into the American Rescue Plan, even though the resulting resumption of trade and migration would undoubtedly have benefited the U.S. by far more than $25 billion.
Major stories about supply-side problems receive only fleeting notice in the U.S. media. Poor infrastructure and distribution are making it difficult for the 270 million inhabitants of Indonesia to get vaccinated, yet very few Americans are paying attention. Indonesia is not usually the focus of attention — and people are not sufficiently obsessed with the supply side.
In the corporate world, there was the big announcement that Intel plans to move full speed ahead to produce more high-quality semiconductor chips and to put more chip factories in the U.S. That switch has come after years of disappointing results from Intel. Can it set things straight? Right now there is a chip shortage in automobile manufacturing, and given the potential fragility of Taiwanese chip supply, U.S. national security hangs in the balance…
Supply-side economics got a bad name because it was associated with too many economists who insisted that tax cuts would be self-financing, or who insisted on tax cuts above all other possible supply-side improvements. Yet all economists ought to proudly announce that they are supply-side economists, first and foremost. That is pretty far from the world we live in, especially as social media have made U.S. monetary and fiscal policies a touchstone for the entire world to debate, often in highly emotional terms.
Here is the rest of my Bloomberg column.
The Mayor of Charlottesville recently tweeted.
Please explain how building more market rate housing will free up the housing market for low-income citizens. Which low-income citizens will be able to afford to buy or rent a home that’s going to sell to $450,000? New construction will not lower the selling price of older homes….
Fortunately, Bryan Caplan has an excellent explanation, the game of reverse musical chairs.
New housing is usually nice housing, because over time technology improves and capital depreciates. Since richer people are more willing to pay the upcharge for nicer housing, the future residents of new construction are usually well-to-do.
So what do casual observers miss? They miss the big picture: People who move into new construction are moving away from older construction. When they move, those older units become available for others. While those others probably won’t be drastically poorer than those they replace, they tend to be slightly poorer. Think: “one rung down.” When these slightly poorer people move, their prior dwellings will tend to be taken over by those who are a further rung down. And so on, in a great chain reaction. Allowing new construction really does help the whole income distribution.
Since this is hard to visualize, picture a game of musical chairs. With one key difference. A normal game of musical chairs starts out with one chair per person, then subtracts a chair every turn. The result: Faster, aggressive kids push out everyone else, until the fastest, most aggressive kid wins. In my variant game, we start out with fewer chairs than people, then add a chair every turn. The result: Slower and more pacific kids start getting places to sit, until there are enough chairs for everyone.
Both games feature a competitive scramble. In conventional musical chairs, however, the competition gets more and more cutthroat and in the end almost everyone loses. In my reverse musical chairs, in contrast, competition gets milder and milder and in the end everyone wins.
For those with pandemic pangs for the sweet crunch of Grape Nuts, take heart. The Great Grape-Nuts Shortage of 2021 is officially over.
After months of being out of stock, the cereal is shipping at full capacity to stores nationwide, parent company Post Consumer Brands told USA TODAY exclusively.
And if you paid wildly inflated prices on the black market to get your hands on a box, you may be eligible for reimbursement.
“It became abundantly clear during the shortage that Grape-Nuts fans are ‘Nuts for Grape-Nuts,’” Kristin DeRock, Grape-Nuts brand manager at Post Consumer Brands, said in a statement. “So much so that some of our loyal super fans were willing to pay extreme prices just to ensure they wouldn’t be without their favorite crunchy cereal.”
Here is the full story, via John B. Chilton. One way to read this is Grape Nuts subsidizing habit formation. Alternatively, you might read it as Grape Nuts subsidizing very loyal customers, and hoping to get publicity in the process. Or is Grape Nuts subsidizing future middlemen in any future black market transactions by assuring them of ongoing demand? How are you supposed to prove you bought a black market box? And was it illegal to resell and buy Grape Nuts in the first place? I don’t entirely understand all of the microeconomic mechanisms at work here.
I keep on hearing that “running the economy hot” is going to be very good for workers. So shall we look at the decades of evidence?
On average, the prevailing view has been that real wages are roughly acyclical across the business cycle, though with variation across and across researchers.
Here is one take from the AER:
The cyclical behavior of real wages has evolved from mildly countercyclical during the interwar period to modestly procyclical in the postwar era.
In recent times a mild acyclicality for real wages has become a more popular view, but in the 1980s it was more likely that the RBC theorists would try to show cyclicality and the aggregate demand theorists would pooh-pooh such demonstrations and insist on much weaker and theoretically ambiguous correlations. Here is an older view, incomplete in my opinion but far from absurd:
It is shown that real wages are procyclical in response to technology and oil price shocks but are countercyclical in response to aggregate demand shocks.The evidence is consistent with models where nominal wages are stickier than nominal prices
Here is a biased but interesting post Keynesian survey of the questions, with the author more or less implying we don’t know what we are talking about. Here is one of the stronger results on pro-cyclical real wages, for the EU, but it requires you to believe there is no nominal downward wage stickiness during the Great Recession (ready to bite that bullet?).
Here is a 1995 JEL survey by very good economists (Katherine Abraham and John Haltiwanger). Part of the very first sentence is:
…the debate over the cyclicality of real wages has a very long history and is filled with conflicting hypotheses and inconclusive evidence.
Here is another 1995 survey. Notice that what is probably the best and best-known attempt to explain why the cyclicality of real wages might be changing over time is built on a general equilibrium business cycle model, which has become a horror of horrors on Twitter and also in blog space.
Overall, if you study the evidence on the cyclicality of real wages you will find it is a confusing and difficult problem, and furthermore that past results may not hold in the future or for that matter in the present. Yet one rarely sees this literature, or its implications, discussed on Twitter, or for that matter on econ blogs. Here is a simple rule: if you see a discussion of current labor markets and wages, ask if the author is coming to terms with these results or not.
And I don’t know of a single research result considering macro real wages, or other labor market factors, coming out of a pandemic with suddenly available highly effective vaccines.
It is once again time to take scientific agnosticism seriously. Most of what you all are saying I just don’t think is founded upon very much, maybe in some cases there is n = 1 support but typically not more.
And dare I suggest that if we do not very well understand the course of wage/price over the business cycle, there is a lot more about cyclical labor markets we also don’t understand?
Here is the audio, video, and transcript. Here is part of the summary:
She joined Tyler to discuss what caused the Bronze Age Collapse, how well we understand the level of ancient technologies, what archaeologists may learn from the discovery of more than a hundred coffins at the site of Saqqara, how far the Vikings really traveled, why conservation should be as much of a priority as excavation, the economics of looting networks, the inherently political nature of archaeology, Indiana Jones versus The Dig, her favorite contemporary bluegrass artists, the best archeological sites to visit around the world, the merits of tools like Google Earth and Lidar, the long list of skills needed to be a modern archeologist, which countries produce the best amateur space archeologists, and more.
Lots of talk about data issues and rights as well. Here is one excerpt:
COWEN: Here’s something that struck me studying your work. Give me your reaction. It seems to me your job is almost becoming impossible. You have to know stats. You have to know trigonometry. You have to know geometry. In your case, you need to know Egyptian Arabic, possibly some dialect, possibly some classical Arabic, maybe some other languages.
You have to know archaeology, right? You have to know history. You must have to know all kinds of physical techniques for unearthing materials without damaging them too much. You need to know about data storage, and I could go on, and on, and on.
Hasn’t your job evolved to the point where you’re almost . . . You need to know about technologies, right? For finding data from space — we talked about this before. That’s also not easy. Isn’t your job evolving to the point where, literally, no human can do it, and you’re the last in the line?
PARCAK: I am, I guess, jack of all trades, master of a few. But that’s not true either because I have to know the remote sensing programs. I have to know geographic information systems. I have to be up to date on international cultural heritage laws.
I think I’m not special by a long shot. Every archaeologist is a specialist. This archaeologist is a specialist in the pottery of this period of time, or does DNA, or excavates human remains — they’re bioarchaeologists — or they do computation. We all are specialists in a particular thing, but that’s really broad. My unsexy, more academic term is landscape archaeologist, so I’m interested in ancient human-environment interaction, which encompasses a lot of different fields and subfields. I’ve taken many courses in geology.
All of us who study Egyptology — we do a lot of training in art history because, of course, the iconography and the art and the objects that we’re finding. It takes a lot, but I would say most of the knowledge I’ve gotten is experiential. It’s from being in the field, I’ve visited hundreds of museums. I’ve spent countless hours in museum collections learning, touching objects.
Yeah, it’s a lot, but it’s also the field of archaeology. That’s why so many people really love it — because you get to touch on so many different areas. I would never, for example, consider myself a specialist in bioarchaeology. I know a tibia. When I find pitting on a skull, I know what that could potentially mean.
But also, I’m in a position now where I’m a dig director, so that means I’m in charge of a large group of humans, most of whom are far smarter, more capable than I am in whatever they’re doing. They’re specialists in pottery and bone, in rocks — project geologist — and conservation in art. We have project artists. We have specialists in excavation, and of course, there’s my very talented Egyptian team. They’re excavating. I’m probably a lot more of a manager now than I ever expected to be —
COWEN: And fundraiser perhaps, right?
One of my favorite CWTs in some time. And here is Sarah’s book Archaeology from Space: How the Future Shapes Our Past.
The most interesting thing about the new Macro Wars is that academic research is almost a total non-factor. In 2011 we were arguing about the Zero Lower Bound, DSGE models versus reduced-form models, etc. Now, though academics are involved in the debates, you rarely see an actual paper invoked. And when it is, it’s nearly always an empirical paper rather than a theory paper.
Why? If academics themselves weren’t involved in the debates, you could say that OK, maybe these people are just ignorant of the literature. But academics are involved, and they do know the literature; they’re just not invoking it much. Also, it’s not that Twitter econ debates are lightweight or short on references — the minimum wage debate, for example, cites papers constantly.
You can come up with various hypotheses for this, but it seems fairly clear to me that the reason is that everyone quietly stopped believing in the usefulness of academic macro theory. Macro profs are still out there doing their jobs, writing theory papers, and getting paid handsomely for it — in fact, I’d argue that with folks like Emi Nakamura, Jon Steinsson, Yuriy Gorodnichenko, and Ivan Werning on the job, the field of macro theory is chock full of top talent. And those are good people who take their jobs seriously and aren’t out to push political narratives.
But the problem is that macro theory is just really, really hard.
His whole Substack post is very good, though I give the entire matter a different interpretation. I do not view contemporary macroeconomics as wonderfully predictive, but it does put constraints on what you can advocate or for that matter on what you can predict. I saw the Republicans go down this path some time ago, and now the Democrats are following them — it ain’t pretty. I think what we are seeing now is that (some, not all) Democratic economists want Democrats to be popular, and to win, and so they will rearrange macroeconomic thinking accordingly. David Henderson, in a recent post, put the point well:
Notice what even Krugman admits. First, that the aid to state and local governments is too much, even by his standards. Second, the checks to people who hadn’t suffered much, which are a huge part of the package, are the “least-justifiable piece in terms of standard economics.” And what’s Krugman’s justification for those payments? That they are “by far the most popular” and, for that reason, we can’t “entirely disregard that.”
On the actual analytics of this debate, Summers has been a clear winner, and that simply hasn’t mattered much at all. See also this excellent comment by Karl Smith:
Bidenism is hitting at exactly the right time politically. It’s not pushing the American people but meeting them where they are. It is quite frankly the coherent manifestation of MAGAism in the same way that Reaganism was a coherent manifestation of Carter-era deregulation
I have worried about related issues for some while, and now that someone has done the hard work I find the results disturbing and possibly significant:
Econometric models of temperature impacts on GDP are increasingly used to inform global warming damage assessments. But theory does not prescribe estimable forms of this relationship. By estimating 800 plausible specifications of the temperature-GDP relationship, we demonstrate that a wide variety of models are statistically indistinguishable in their out-of-sample performance, including models that exclude any temperature effect. This full set of models, however, implies a wide range of climate change impacts by 2100, yielding considerable model uncertainty. The uncertainty is greatest for models that specify effects of temperature on GDP growth that accumulate over time; the 95% confidence interval that accounts for both sampling and model uncertainty across the best-performing models ranges from 84% GDP losses to 359% gains. Models of GDP levels effects yield a much narrower distribution of GDP impacts centered around 1–3% losses, consistent with damage functions of major integrated assessment models. Further, models that incorporate lagged temperature effects are indicative of impacts on GDP levels rather than GDP growth. We identify statistically significant marginal effects of temperature on poor country GDP and agricultural production, but not rich country GDP, non-agricultural production, or GDP growth.
That is from Richard G Newell, Brian C. Prest, and Steven E. Sexton. Via the excellent Kevin Lewis.
The subtitle of the paper is “New Estimates of Productivity Growth in England from 1250 to 1870” and it is by Paul Bouscasse, Emi Nakamura, and Jon Steinsson:
We provide new estimates of the evolution of productivity in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. We develop and implement a new methodology for estimating productivity that accounts for these Malthusian dynamics. In the early part of our sample, we find that productivity growth was zero. Productivity growth began in 1600—almost a century before the Glorious Revolution. Post-1600 productivity growth had two phases: an initial phase of modest growth of 4% per decade between 1600 and 1810, followed by a rapid acceleration at the time of the Industrial Revolution to 18% per decade. Our evidence helps distinguish between theories of why growth began. In particular, our findings support the idea that broad-based economic change preceded the bourgeois institutional reforms of 17th century England and may have contributed to causing them. We also estimate the strength of Malthusian population forces on real wages. We find that these forces were sufficiently weak to be easily overwhelmed by post-1800 productivity growth.
That is a new research paper by Tom Coupé, here is one excerpt:
I find that search intensity rankings based on Google Trends data are only modestly correlated with more traditional measures of scholarly impact…
The definition of who counts as an economist is somewhat loose, so:
Plato, Aristotle and Karl Marx constitute the top three. They are followed by B. R. Ambedkar, John Locke and Thomas Aquinas, with Adam Smith taking the seventh place. Smith is followed by Max Weber, John Maynard Keynes and the top-ranking Nobel Prize winner, John Forbes Nash Jr.
…John Forbes Nash Jr., Arthur Lewis, Milton Friedman, Paul Krugman and Friedrich Hayek are the most searched for Nobel Prize winners for economics, while Tjalling Koopmans, Reinhard Selten, Lawrence Klein, James Meade and Dale T. Mortensen have the lowest search intensity.
Here are the Nobelist rankings. Here are the complete rankings, if you are wondering I come in at #104, just ahead of William Stanley Jevons, one of the other Marginal Revolution guys, and considerably ahead of Walras and Menger, early co-bloggers (now retired) on this site. Gary Becker is what…#172? Ken Arrow is #184. The internet is a funny place.
I guess I found this on Twitter, but I have forgotten whom to thank – sorry!
I’ll compare Twitter macro to blog macro throughout, and here is how I see the strengths and weaknesses of Twitter macro:
1. Super-fast speed of response, and less repetitive than the old blog world. It is easy to comment right away on the most current happening. Unlike with (some) blogs, no wind-ups are required. On Twitter both good and bad ideas go viral far more rapidly.
2. It is more fun than blog macro, and attracts fewer hobby horse drones.
3. It is too easy to tell people that they “completely misunderstand” something, because links, while they exist on Twitter, are not the prime currency. This leads to many bad tweets, typically tweets that…completely misunderstand something or someone, yet with less verification possible.
4. It attracts a younger set of writers than blog macro did. That makes it both more left-wing and also less informed about economic history, recent decades in particular. Very recent evidence and experience is considerably overstressed in its relevance, and this is reinforced by the fad-like nature of Twitter opinion.
5. Twitter macro is poor at spelling out the entirety of an empirical literature on an empirical question. I am not sure whether this is intrinsic to the medium, but I observe this regularly. Blogs in contrast are/were most likely to take a more exhaustive approach to literature survey, sometimes too exhaustive rather than focusing on the single best argument.
6. Twitter macro is poor for spelling out mechanisms. Most coherent macro mechanisms do in fact take more than 280 characters to spell out. Tweet storms are useful, but more for a series of sequential observations on some new data, rather than for mechanisms per se. Overall Twitter is poor for “grasping the whole elephant” approaches to economics, and for that matter to other topics as well.
7. It is easier to learn from other people on econ Twitter, due to the “rapid scan” and retweet and “comment on tweet” properties of the system. At the same time, econ Twitter is more prone to fads and bubbles of opinion, for broadly the same reasons.
8. Econ Twitter involves more “don’t really know anything at all” kinds of people, and sarcastic people, in the discussions. Overall this has a negative external impact on the tone and thoughtfulness of those who do know something. In the blog world, we all made each other a bit more “cross-checking, linking, and drone-like.”
9. I genuinely do not understand why more tweeters do not set up free blog or Substack accounts, and, if only five times or so a year, write a longer post or column explaining and defending their views and tying them into the broader literatures. This seems to me to betray a certain kind of intellectual laziness, which the Twitter medium itself encourages and amplifies.
10. Entry barriers are lower with Twitter, so there is a much broader diversity of opinion. This can be very good, but see #8.
11. It is easier to express meaningful agnosticism in a successful blog post than in a successful tweet. This is one of the biggest problems with Twitter macro, and indeed with Twitter more broadly. It is also hard to express trade-offs in a successful tweet, another major problem. “We must do this” kinds of thinking are instead encouraged.
12. Both blog posts and tweets very often mix in normative judgments with the positive analysis. But it is much harder to be sophisticated on the normative side on Twitter. The morality is often third-rate or worse.
13. The one-sentence (supposed) refutation is very much overrated on Twitter, even serious Twitter. Such dismissals are usually wrong, or at least seriously incomplete, and their possibility and popularity discourage people from developing deeper understandings.
14. Is Twitter so great for methodological self-awareness? Yes, you could do a tweet storm but this kind of analysis, as embodied in this post itself, seems harder to do on Twitter, and harder to receive non-sarastic feedback on.