Economics

Book review: The British Industrial Revolution in Global Perspective, by Robert C. Allen.

Here we have yet another explanation of the most important event in history, this time from an economic historian.

Allen mostly focuses on one key piece of the causal chain: British wages were high compared to the cost of energy.

Nearly everything he says seems correct, but I have some medium-sized complaints about what he neglects.

High Wages

British wages were higher than those of just about any other country, at least after 1575. That was an important component in Britain’s lead at producing technological innovation. The initial steps in many key technological advances were crude enough that they wouldn’t have made sense if they were competing with cheap labor.

It seems important to focus on what caused the high wages. Allen is a bit weak here.

He mentions British diets, mostly as evidence of high British wages. But he also hints that the high calorie, high protein diet enabled higher productivity, which may have perpetuated the high wages.

A low ratio of workers to land seems to be part of the story. Malthusian forces usually pushed societies away from this. The Black Death provided some respite from high population density. Allen mumbles something about the Black Death’s effects maybe still being important a couple of centuries later. But why was this more true of Britain than of neighboring countries?

Some urbanization was also important, as inventors needed other skilled craftsmen nearby as sources of ideas, tools, and parts. So maybe it took a good deal of luck for Britain to get just the right population density?

Cheap Energy

Before the 1700s, most countries used wood instead of coal, even when they had an ample supply of coal. Switching to coal required significant redesigns to most systems that burned wood.

Countries such as Britain didn’t recklessly exhaust their supply of wood. Demand for wood in Britain grew due to population growth, and the resulting rise in wood prices would have constrained London’s population growth if it weren’t for increased use of coal. But that was due at least as much to the high cost of transporting fuel over long distances as it was to the limited supply of wood.

Something was fairly unusual about Britain’s best coal mines. They produced unusually cheap coal. That helped Britain switch from wood to coal for heating and machinery, well before other countries did.

That didn’t mean that coal was much cheaper in London than in other major cities. High transportation costs made coal a mediocre option almost anywhere other than right at a mine.

China is a key country to look at when wondering where the industrial revolution could have started. How did China’s cheapest coal mines compare to Britain’s? Allen presents no data. Pomeranz seems to care about the quantity of coal reserves, not the cost of the lowest hanging fruit. Coal use in 1700 seems to have been too small relative to reserves for the quantity of reserves to matter much.

It’s unclear whether anyone knows whether China had locations where coal was as cheap as Britain’s cheapest coal mines.

If China didn’t have cheap coal, how much of that was due to natural conditions, and how much of it was due to less interest in developing cheap coal mines? I’m frustrated at how little I’ve found on this subject. The closest that I’ve found to an answer is this claim from Vries:

My thesis would be that China, in a way, also had its ‘coal’ and its colonies, but that government was a serious hindrance in making the most of them. When it comes to coal mining, the Qing often prohibited opening mines in the first place or wanted those already opened closed down. Initiatives by government itself to open mines or to ‘modernize’ them are absent.

Allen implies that cheap coal is obviously good. I see some tension between that and evidence from the past century concerning the effects of natural resources on economic development. There are enough examples of failing resource-rich countries that economists often refer to a curse of natural resources. The curse appears to mostly depend on large international commodity markets, which didn’t exist for coal until sometime after 1800. So it’s not a strong argument against Allen’s theory. It’s merely a warning that it’s easy to overestimate the benefits of natural resources.

Coal seems like a plausible guess as to why Britain developed key technologies before highly similar societies such as Denmark and the Netherlands. But there were numerous differences between Britain and China. I don’t see a clear argument that coal prices deserve to be treated as one of the top two relevant differences. I’ll guess that, in spite of the “Global” in the book’s title, Allen hasn’t studied China enough to have much insight about why it lagged behind Europe.

Steam Engines

Allen gives a detailed description of the development of steam power, as a clear example of where innovation depended on wages being high relative to energy costs. The first steam engines were inefficient enough that they were only worthwhile at coal mines, where they were used to pump water out of the mines. The inefficient use of fuel made it very sensitive to fuel costs.

It took decade of R&D for Newcomen to perfect this underwhelming machine. That much effort could only be repaid where there were many mines that were willing to buy such machines. Britain had far more coal mines than other European countries, partly because the low price of coal led Britain to heat more homes with coal. So Britain was able to afford more R&D.

It took nearly a century of refining steam engines before it made commercial sense for other countries to adopt steam engines.

Why was Britain’s early adoption of the steam engine important? It took a century or so to produce large benefits, at which time other countries copied it.

Was it because the technical knowledge enabled British innovators to be the first to develop better steam engines, and use them in a variety of applications such as railroads, ships, better factories, etc.? Or was the steam engine mainly a symptom of British innovation abilities?

Allen suggests that Britain’s cheap coal and first-mover advantages were more important than cultural or institutional features, at least up to WWI.

The steam engine and cheap iron were dependent on cheap coal, and had important influences on automating factories and transportation. That included a bit of recursive self-improvement: factory automation was used to mass-produce machines used to automate factories.

Why 1575?

To the limited extent that Allen identifies a start to the industrial revolution, it was around 1575, when British wages began to diverge from the Malthusian patterns seen in most of Europe and Asia (it took at least another century before British wages exceeded Amsterdam wages).

Allen says cheap coal was around well before then, and doesn’t suggest any other resource-based explanation of what changed in the 1500s to break northwestern Europe out of the Malthusian pattern.

Was it due to lingering effects of the Black Death? Wages certainly increased in the 1300s relative to natural resources, particularly land. That’s a potentially important contributor to high wages two or three centuries later.

But why was that effect stronger and more lasting in Britain than in other parts of Europe? Allen’s coal-related explanation is somewhat plausible from the early 1700s to about 1900. But why did wages stay somewhat above Malthusian levels in the 1600s in northwestern Europe? I’m unclear as to whether Allen thinks he has an answer. I think he attributes it to increased agricultural productivity, driven by growing cities. But I don’t see how those cities provided more of a force in Britain than in the rest of Europe and Asia.

It is now time to compare Allen’s ideas with those of my current favorite book on this topic: Henrich’s The WEIRDest People.

Culture

Henrich promotes a clear answer of why the 1500s were special: the rise of Protestant culture.

Allen downplays cultural explanations, enough that I got 90% of the way through the book before realizing that he admits culture played a nontrivial role in the industrial revolution.

Early in the book, he points to versions of cultural arguments that I agree are weak enough to be dismissed. Those versions were probably somewhat popular when the book was written (2009), but have been fading since then. Toward the end of the book, Allen more respectfully mentions several better ideas about cultural influences, mostly from Mokyr.

Here are some relevant cultural influences for which Allen provides some evidence, and which Henrich convinced me are more important than Allen admits:

Industrial Enlightenment

Allen describes Industrial Enlightenment as a process by which the Scientific Revolution influenced industry.

Allen shows that scientific knowledge contributed to some key inventions, such as the steam engine, via better knowledge of the principles by which those inventions worked. But he also argues that other important industries such as cotton advanced without much contribution from scientific knowledge.

The harder-to-evaluate impact of science involves indirect cultural effects. The social networks associated with science may have indirectly influenced innovation, e.g. by encouraging more experimentation in industry.

I’m reminded of this quote from Shut Out:

The evolution of capitalism has led to almost universal acceptance of middle-class values. Whereas the elite of most societies have sought control and leisure, these few modern open access societies have a citizenry that seeks to be productive, to cooperate, and to innovate. It is common to hear complaints that wealthy children today have an unfair advantage because they can access the best schools, get the best education, and therefore perpetuate inequality by working in the most lucrative careers. But everyone should appreciate how revolutionary this is. Elites of the past would scoff at the notion that this even describes elites. Elites don’t need to be productive. Elites have access and control.

Did this change in elite culture begin around 1500? It was certainly far from common for elites to involve themselves in business, but Allen says some important inventors came from elite backgrounds. How much did this differ from other parts of the world?

There are a variety of ways that elite interest in industry might have improved innovation: more spare time and resources to devote to investments that don’t provide quick payoffs, or maybe better cognitive abilities due to better nutrition and/or better genes.

Literacy, Numeracy

These certainly correlated with the changes that seeded the industrial revolution. Allen expresses doubts about the direction of causality.

Marital Rules / Habits

Protestant culture has some features which slow population growth. Europe, and especially northwestern Europe, had several cultural norms which prevented early marriage, and left a relatively large number of people unmarried.

Without something like that, it seems hard to explain why low population density persisted long enough after the Black Death for technology to sustain high wages.

Trade Secrets

Allen reports that innovators depended on learning from mentors. Many cultures have a distrust of strangers that limits such learning to a small circle of people who trust each other because they’ve lived together most of their life.

Protestant culture promoted trust among all Protestants, paving a path to the accumulation of a richer body of trade knowledge. I’m unsure whether Chinese culture had work-arounds which provided adequate substitutes for this source of trust.

Noncomformity

Allen notes that Luddites threatened innovation, particularly in the key cotton industry. Most cultures value conformity more than Protestant culture does. I can imagine that no other culture would have produced entrepreneurs who persevered in the face of that kind of opposition.

Historians versus Scientists

Henrich, and to a lesser extent Allen, have helped to illustrate the differences between historians and scientists.

Historians focus on building stories about particular, unique, events. Whereas scientists seek general theories whenever possible.

Was the industrial revolution a unique event, or was it a long pattern of related events that might be better explained by a broad theory? Historians seem biased toward the former, scientists toward the latter. Allen seems to be mostly a historian, but has enough economic training to be more neutral on this issue than most authors. Whereas Henrich is mostly trying to be a scientist, and not a historian.

To the extent to which it was a long pattern of events, I value the opinions of scientists who focus on theories about which features of 16th through 18th century Britain caused it to stand out. That would help me predict what countries will become more powerful. So I want to avoid erring in the direction that historians err, more than I want to avoid the opposite mistake.

Here are several considerations that lead me to give more weight to Henrich’s cultural model:

There are many markets today which English-speaking countries dominate in ways that are somewhat hard to explain by coal or high wages: the internet, universities, medicine, movies, etc. That seems to create some presumption in favor of explanations that focus on general-purpose abilities such as culture and institutions.

Allen’s perspective encourages us to imagine that a good deal of British success comes from a first-mover advantage that has been self-sustaining for a couple of centuries. That seems to be somewhat large compared to other historical examples of first-mover advantages or resource-based advantages.

What are the best such examples? Cities built around ports have smaller but longer-lasting advantages, due to natural resources (harbors). I guess that’s a good enough comparison that I can’t say that Allen’s perspective is too far-fetched.

Cultural models provide a clear explanation of the timing of the industrial revolution. I don’t see how resource-based models explain the timing.

Allen says that other countries adopted British technology when it became profitable to do so. Yet that only seems true for countries with cultures similar to Britain’s. Asian countries seem to have adopted it mainly after they imported parts of Western culture.

Conclusion

Allen’s account is the strongest analysis I’ve yet seen of the resource-related forces that contributed to the industrial revolution.

I see almost no conflict between Henrich’s account and Allen’s account about what happened after 1500, only some big disagreements about what was important. They disagree a good deal about what pre-1500 causes were relevant, and they both seem relatively weak there.

Allen emphasizes Britain’s geographic luck, and encourages us to imagine that key inventions were just barely useful enough to create a sustainable take-off. Whereas Henrich attributes northwestern Europe’s luck to cultural choices that were in place by 1520 at the latest, and wants us to believe that take-off was close to inevitable by then. The evidence is weak enough that we may never know which is closer to the truth.

Reading both Allen and Henrich will produce a better understanding than either one of them alone will produce. But if you only read one book, read Henrich’s.

Book review: The Money Illusion: Market Monetarism, the Great Recession, and the Future of Monetary Policy, by Scott Sumner.

This is the best book on macroeconomics that I’m aware of, with a focus on the causes of the 2008 recession.

Most of the book’s important points are based on ideas that economists respect in many contexts outside of macroeconomics, but which seem controversial in the context of macroeconomics.

It’s ironic that Sumner finished writing this book during one of the few recessions that could not have been prevented by better monetary policy.

Note that this review is primarily for people who already know something about monetary policy. It’s hard enough to do that well that I don’t want to attempt anything more ambitious.

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Interest rates have declined from over 5% in the late 1960s to under 0.5% in 2020 (I’m using long-term treasury bond rates as an estimate of pure risk-free rates).

There’s clearly something unusual about savings rates, and it’s causing a semi-stable decline in interest rates.

In my review of Shut Out, I guessed that demographic effects of the boomer generation explain 25% the housing boom, via high savings rates and the resulting low interest rates. I’m now revising that estimate down to 10%.

I now see a similar but bigger effect from a different set of demographic changes. I changed my mind due to the paper by Mian, Straub, and Sufi titled What Explains the Decline in r*? Rising Income Inequality Versus Demographic Shifts (think or r* as an idealized version of interest rates).

Wealth affects savings rates more than age does.

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“Transitory Inflation”

Many pundits are arguing that this year’s inflation is due to temporary pandemic-related problems.

I expect that they’re half-right – we’ve got a one-time pandemic-related burst of inflation, but it’s likely to be bigger than pundits imagine, and the price changes are unlikely to be reversed much when the effects of the pandemic fade.

Also, the presence of one-time effects shouldn’t reassure us about the absence of longer-term pressures.

When evaluating inflation, I focus mainly on the supply of and demand for money. Supply chain problems may be important for many purposes, but they don’t explain a general pattern of dollars becoming less valuable.

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Mancur Olson’s The Rise and Decline of Nations tells us that in stable times special interest groups tend to slowly create increasingly rigid agreements to cement their income streams. Major wars, and other cataclysms of that size, occasionally sweep away those rigidities, creating conditions under which faster economic growth is possible.

COVID has been much less cataclysmic than what Olson talks about. Yet I see hints that the recent pandemic has had effects that weakly resemble war. I see stronger evidence that the pandemic was a useful trigger for overcoming the effects status quo bias. I’m writing this post to help clarify my thoughts about how significant these effects will be, and how they’ll affect stock markets.

Is the stock market’s impressive performance partly due to expectations that the pandemic caused a lasting increase in profits?

I’ll guess that it explains one quarter of the stock market’s rise. A fair amount of that guess reflects my intuitions about how much can’t be explained by other factors. That approach is at least as error-prone as estimating individual pandemic effects. So please interpret this post as mostly groping around in the dark.

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Book review: Shut Out: How a Housing Shortage Caused the Great Recession and Crippled Our Economy, by Kevin Erdmann.

Why did the US have an unusually bad recession in 2008, followed by years of disappointing growth?

Many influential people attribute it to the 2004-2006 housing bubble, and the ensuing subprime mortgage crisis, with an implication that people bought too many houses. Erdmann says: no, the main problems were due to obstacles which prevented the building and buying of houses.

He mainly argues against two competing narratives that are popular among economists:

  • increased availability of credit fueled a buying binge among people who had trouble affording homes.
  • there was a general and unusual increase in the demand for homes.

Reframing the Housing Bubble

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It’s been a decade since I blogged about the benefits of avoiding news.

In that time I mostly followed the advice I gave. I kicked my addiction to The Daily Show in late 2016 after it switched from ridiculing Trump to portraying him as scary (probably part of a general trend for the show to be less funny). I got more free time, and only missed the news a little bit.

Then the pandemic hit.

I suddenly needed lots of new information. Corporate earnings releases were too slow.

Wikipedia, Our World in Data, Metaculus, and some newly created COVID-specific web sites partly filled that gap. But I still needed more, and I mostly didn’t manage to find anything that was faster or more informative than the news media storyteller industry.

That at least correlated with higher than normal stress. I suspect that paying attention to the storytellers partly caused the stress.

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I tried to finish this in time for April 1, 2019, but masterpieces take time, and I didn’t find the time to turn this into a masterpiece. Then I kept adding sections that didn’t fit with the April Fools spirit, for a result that, like South Park, is not suitable for any audience. Finally, an economic crisis prompted me to publish whatever incomplete version of it I could manage to write, before people notice that we’ve avoided a depression. I’m definitely not satisfied with the quality of this post, but can’t afford to put more time into it.

In this post, I’ll try to summarize my guesses as to what are the most controversial parts of Scott Sumner’s monetary policy ideas.

In the process, I’ll try to dress them up to look more like the kind of wisdom that requires years of study to master. After all, I wouldn’t want anyone to get the impression that the Fed’s highly educated experts could be replaced by, say, ordinary bloggers.

In particular, I will attempt to correct the serious shortage of equations and graphs that plagues market monetarist writings.

I’ve attempted to make this fancy enough to belong in a prestigious publication, but I’m little more than an ordinary blogger, and I doubt that I’ve been thorough enough, or have enough experience at creating a prestigious style. Please feel free to write a more sophisticated-looking version of this post, and borrow as much as you like, without any need to credit me.

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Lots of people have been asking recently why the stock market appears unconnected with the economy.

There are several factors that contribute to that impression.

First, stock market indexes are imperfect measures of the whole stock market. Well-known indexes such as the S&P500 are higher than pre-pandemic, but the average stock is down something like 10% over the same time period. The difference is due to some well-known stocks such as Apple and Amazon, which have unusually large weights in the S&P500.

See this Colby Davis post for some relevant charts, and for some good arguments against buying large growth stocks today.

Stock markets react to the foreseeable future, whereas the daily news, and most politicians, prefer to focus attention on the recent past. People who focus on the recent past see a US that’s barely able to decide whether to fight COVID-19, whereas the market sees vaccines and/or good treatments enabling business to return to normal within a year.

Stock markets don’t try to reflect the costs associated with death, chronic fatigue, domestic violence, etc. Too many people want the market to be either a perfect indicator of how well we’re doing, or to dismiss it as worthless. Sorry, but imperfect indicators are all we have.

Plenty of influential people have been exaggerating the harm caused by the pandemic, in order to manipulate the average person into taking the pandemic seriously. As far as I can tell, this backfired, and contributed to the anti-mask backlash. It also contributed to stocks being underpriced in the spring, so parts of the stock market rebound have simply been reactions to the growing evidence that most large companies are recovering.

The vaccine news has been persistently good, except for the opposition from big pharma and their friends at the FDA to making vaccines available as soon as possible.

Another modest factor is that many companies dramatically reduced their capital expenditure plans starting around March and April. That will reduce production capacities for the next year or two, thus making shortages of goods a bit more common than usual. This should prop up profit margins. But I haven’t noticed much connection between the most relevant industries and rising stock prices.

Why is there such a large divergence between the S&P500 and the average stock?

Investors have developed a somewhat unusual degree of preference for well-known companies whose long-term growth prospects seem safe.

I guessed last year that this would be a rerun of the Nifty Fifty. I still see important similarities in investor attitudes, but I see enough divergences in patterns of stock prices that I’m guessing we’ll get something in between the broad, gradual peak of the Nifty Fifty and a standard bubble (i.e. with a well-defined peak followed by a clear reversal within months).

Remember that high volatility is somewhat correlated with being in a bubble. We’ve recently seen Zoom Video Communications rise 40% in one day, and Salesforce rise 26%, in response to good earnings reports. That’s a $50 billion one-day gain for Salesforce. It reminds me of the volatility in PetroChina in 2007 (PetroChina has declined 87% since then). There was also that $173 billion rise in Apple after it’s latest earnings report, but that was a mere 10.5% rise.

Some of the divergence is due to small retailers losing business to Amazon, and to small restaurant chains losing business to fast food chains.

The bubble is a bit broader than just tech stocks – Home Depot and Chipotle are well above their pre-pandemic levels, by much larger amounts than can be explained by any near-term changes in their profits.

Incumbent politicians have been trying to buy votes by shoveling money to influential companies and people. There’s been some speculation that that’s biased toward large companies. It seems likely that large companies are better able to take advantage of those deals, because they’re more likely to employ someone with expertise at dealing with the government than is, say, a barbershop.

But I don’t see how that explains more than 1% of the stock market divergence. Stocks like Apple and Tesla have risen much more than can be explained by any change in this year’s profits. Any sane explanation of those soaring stocks has to involve increased optimism about profits that they’ll be making 5 to 10 years from now.

Large companies have better access to banks. Large companies typically have someone who is an expert at dealing with banks, and they have the accounting competence to make it easy for banks to figure out how much they can safely lend to the company. In contrast, a family-owned business will be slower to figure out how to borrow money, and therefore is more likely to go out of business due to unusual problems such as a pandemic. That might explain a fair amount of the divergence between the S&P500 and what you hear by word of mouth, but it explains little of the divergence between the S&P500 and the publicly traded companies that are too small for the S&P500.

I’ve only done a little selling recently, and I’ve been mostly avoiding large companies for many years. I’m guessing that Thursday’s tech stock crash wasn’t the end of the bubble. Bubbles tend to continue expanding until the average investor gets tired of hearing pundits say that we’re in a bubble. That suggests the peak is at least a month away, and I could imagine it being more than a year away.

Stock markets have a long history of being abnormally risky in September and October. Out of 10 months in which the S&P500 ended at least 15% lower than when it started, 3 were in October. Out of 31 months in which it ended at least 10% lower, 12 were in September or October.

I used to guess that this was due to the onset of seasonal affective disorder. That explanation was a bit unsatisfying, because SAD seems likely to be predictable enough that the effects could be mostly smoothed out by smart investors.

After looking at the 1957 pandemic and its possible effect on the stock market, I wondered whether infectious diseases was a better explanation.

I did a crude analysis of the correlations between flu deaths and stock market changes. I didn’t manage to get as good a dataset as I’d hoped for, and ended up settling for the monthly US data for selected seasons (12 in the period 1941-1976) in table 1 of Trends in Recorded Influenza Mortality: United States, 1900–2004.

I looked at correlations between monthly increases in flu deaths per 100,000 people and the monthly change in the S&P500. I was able to find a large effect, but it disappeared when I left out the 1943-1944 season (which was by far the worst season in that time period, yet wasn’t labeled as a pandemic).

Either there’s no effect in that time period, I don’t have detailed enough data, or the effects precede deaths by enough that the death data aren’t helpful.

I was mostly thinking that diseases might have affected the market via effects on investors moods or liquidity preferences, so I wasn’t assuming there would be much discussion of the topic. The paper The Unprecedented Stock Market Reaction to COVID-19 investigated whether newspapers mentioned the topic, and concluded:

In the period before 24 February 2020 – spanning 120 years and more than 1,100 jumps – contemporary journalistic accounts attributed not a single daily stock market jump to infectious disease outbreaks or policy responses to such outbreaks. Perhaps surprisingly, even the Spanish Flu fails to register in next-day journalistic explanations for large daily stock market moves.

So, after a fair amount of research, I still don’t have good evidence about what’s causing the September / October volatility.

P.S. For some strange reason, January is an unusually safe month, with no declines of more than 9% in the S&P 500.

P.P.S. VIX futures are saying that the S&P500’s volatility around late October will be 3.6 points higher the average of August and December volatilities. That compares to an average of 0.86 points higher (and a maximum of 2.1) over the prior 11 years in which VIX futures have been available (all of these numbers come from prices near July 20 of the relevant year).

So the markets expect something unusual this October. Something more surprising than they expected during the prior two presidential election years. Does anyone know whether this risk is due to weather-related pandemic risk or due to political risk?