The economics of castles

When I'm in Britain or Ireland, one of my favourite sightseeing trips is to visit medieval castles. Even the ruined ones are fun to visit. Actually, maybe the ruined ones are more fun to visit, because you get to imagine what they would have looked like in their heyday. Britain and Ireland are full of castles, many of which were built by and housed local nobles. In fact, in relative terms there were very few royal castles, which the literature in history and economic history has interpreted as a sign that centralised states were weak.

However, this recent article by Desiree Desierto and Mark Koyama (both George Mason University), published in the journal European Economic Review (ungated earlier version here) challenges that view. They instead show that there was an economic logic to the proliferation of private castles.

Desierto and Koyama develop a game theoretic model of medieval states, which first recognises that the monarch cannot rule alone but must rely on a coalition of local lords or barons. Each lord agrees to join the coalition, and pledges resources to the monarch in exchange for a (however small) share of control of the kingdom. The monarch can renege on the agreement, taking the resources without offering a share to the lord. However, the lord would then rebel, leaving the coalition. What allows the lord to leave the coalition, and gives them bargaining power, is the presence of their own castles, since they can retreat to their castle when they rebel against the monarch. Without a private castle, the lord would have little bargaining power, and would anticipate the monarch reneging on any agreement, and so they would not join the coalition in the first place. In economic terms, the castle gives the lord an outside option. 

So, the monarch tolerates private castles held by the lords, because the presence of those castles gives the lords the feeling of security they need to join the kingdom. And, in turn, the presence of those castles disciplines the monarch. Rebellions are more costly to suppress when the lords can retreat to a well-defended private castle. The lords' outside option increases the feasibility of rebellion and ensures that the monarch mostly keeps to their agreement with the lords.

In short, the private castles induce an equilibrium where the kingdom is larger and more stable than it would be without them. Notice that this is the opposite of the conventional view that private castles represent a sign that a state was weak.

Desierto and Koyama support their argument with descriptive evidence, noting that:

In Norman England after the Conquest, castles were built across the country: by 1154 there were 225 baronial castles (compared to 49 royal castles) in England... Baronial castles allowed the Dukes of Normandy to extend their authority over the far larger territory of Anglo-Saxon England. Similarly, in the twelfth century Angevin rule expanded over much of France as semi-independent lords in Gascony accepted the lordship of Henry II.

Desierto and Koyama also note that powerful medieval monarchs did not act to systematically eliminate private castles, and in fact the monarchs often gave away their own castles to local lords. And the power of the lords did keep the monarchs in check - a lord's probability of rebelling against the monarch was positively correlated with the number of private castles in the lord's family network. That last point might sound contradictory, but since castles make rebellion by lords a more credible threat, this can deter monarchs from reneging and reduce the number of rebellions overall. However, when rebellion does occur, lords connected to more castles were more likely to participate in the rebellion.

So, if private castles were so important for the stability of medieval states, why did private castles eventually disappear? Desierto and Koyama note that:

The answer is military technology, not the rising power of the state. Technological changes and the associated ‘‘military revolution’’ that took place beginning in the late Middle Ages reduced the value of medieval fortifications. The main technological innovation was the introduction and improvement of gunpowder weapons, which began in the fourteenth century but only really began to have a serious impact in the fifteenth century with the introduction of iron cannonballs.

This is not a new insight, but it does align well with their model. However, it somewhat reverses the logic of the conventional view, which is that greater state power, along with military technology, reduced the prevalence of private castles. Instead, in Desierto and Koyama's model, the rise of gunpowder reduces the ability of lords to retreat to a well-defended castle in the event of a rebellion (because the castle could not be as well-defended against cannons). This reduced the lords' bargaining power, giving the monarch and the centralised state greater power. As a result, the state should become less stable. In support of this, Desierto and Koyama use the Wars of the Roses in England as an example:

England experienced a large number of rebellions and civil wars between 1450 and 1500. These conflicts are conventionally grouped under the label of the Wars of the Roses (1455–1485), but the period of weak state capacity and frequent rebellion extended from Jack Cade’s uprising in 1450 through Perkin Warbeck’s invasion and the Second Cornish Uprising in 1497. The causes of these rebellions were complex, multifaceted, and varied across cases. Nonetheless, the frequency of civil war during this period is consistent with our model’s prediction that a decline in the military value of castles would destabilize feudal realms.

And so, as gunpowder reduced the military value of castles, private castles became much less useful as a source of bargaining power for lords. That helps explain why the medieval pattern of widespread private castles gave way to state-controlled castles from the mid-15th Century onwards. Now, I'll be thinking more carefully about the vintage of the castles I visit on my next trip to Europe next month!

What Thomas Malthus's death can teach us about how economic ideas shape government policy

Do economic ideas shape government policy? The answer seems obvious. After all, many people complain that economists have a strong influence on governments (for example, see here). But if there is a shift in prevailing economic ideas, does that flow through to government policy? It is an interesting question that is difficult to answer, so I was intrigued to read this job market paper by Eric Robertson (University of Virginia).

Robertson looks at the effect of the death of Thomas Malthus in 1834 on the decisions of British bureaucrats in colonial India. Specifically, he exploits:

...a unique historical experiment in a nineteenth-century British bureaucracy, focusing on an argument that Malthusian population theory and its associated ideas discouraged policymakers from intervening in response to agricultural distress and famine... Central to my approach is a bureaucrat training college, Haileybury, where civil servants studied prior to their careers in British India... Thomas Malthus taught economics at Haileybury for nearly three decades, from 1805 until his abrupt death in 1834, after which he was replaced by a contemporary critic, Richard Jones. I examine how the relative differences in exposure of bureaucrats to economic ideas under each instructor at Haileybury influenced their subsequent policy decisions, as well as their alignment with government directives...

Malthus and Jones had quite different views on the causes of poverty and famine, and their ideas suggested quite different policy responses. Malthus believed that it was diminishing productivity of agriculture as a result of overpopulation that caused poverty and famine, while Jones believed that capital investment and technological growth could offset diminishing agricultural productivity. So, in response to famine, bureaucrats trained by Jones would be more likely to respond with measures to supplement incomes than those trained by Malthus, with the latter believing that assistance was unnecessary in response to a natural mechanism that would ultimately lead to better living standards (because there would be fewer people after the famine).

Robertson constructs a dataset of bureaucrats ('district collectors') in colonial India and their policy decisions in response to droughts ('rainfall shortages'). Bureaucrats who wanted to actively respond to a drought had many means to do so, including:

...writing off taxes on agricultural land, opening public works to provide employment opportunities and raise wage income, distributing cash or food aid, importing food for subsidized sale, and providing loans or advances to the agricultural class...

Robertson looks separately at each of those policy responses. This 'natural experiment' is a useful way of establishing the causal impact of economics ideas on policy decisions, because the exact timing of Malthus's death was unrelated to the traits of the bureaucrats being trained. That means the bureaucrats trained just before Malthus's death, and those trained just after Malthus's death, are unlikely to be systematically different in ways related to policy decisions (other than through the way they were trained).

Robertson finds that:

...compared to their Jones-trained (Jonesian) counterparts, Malthus-trained (Malthusian) bureaucrats were less likely to provide relief across all of these common government interventions. I show that tax write-offs during drought were roughly thirty percent lower under Malthusian collectors than under Jonesians and I find evidence that expenditures on public works may have been up to twenty percent lower...

...a back-of-the-envelope calculation suggests that, if Malthusian collectors had implemented policies comparable to Jonesians, the increased aid would have translated into enough calories to support two million more person-days of subsistence during each episode of drought.

Robertson concludes that:

This research offers evidence that the exposure of bureaucrats to different types of economic ideas alters the types of policies they choose to implement.

So, the good news is that economic ideas do shape government policy (or, at the least, they did in the 19th Century). The bad news is also that economic ideas do shape government policy. Because not all economists agree. In this example, Malthus and Jones disagreed on the appropriate policy response to droughts. The Indian people were far better off (in terms of poverty relief, and probably welfare) during a drought when the bureaucrats were trained by Jones than when they were trained by Malthus. Millions of Indians died in famines in the 19th Century (see here). [*] Getting policy right has high stakes.

This research shows that what economics students are taught at university really does matter. That is both gratifying (to know that students will take on board what they learn and use it later) and a little scary (because what if they take on board the 'wrong' lessons, from the 'wrong' economics?). We could easily take a negative impression away from this, but there is a more hopeful lesson here. Economics classes, books, and arguments can make the world better, and sometimes dramatically so. That’s a pretty good reason to keep doing more of what we are doing, but also ensuring that students are equipped to take a critical view of what economics can really deliver through policy changes.

[HT: Marginal Revolution, both last year and this year]

*****

[*] Robertson reports no statistically significant impact of Malthusian training on famine or mortality, but those analyses lack the same extensive data available for the other analyses. It seems credible that the absence of assistance under Malthusian bureaucrats would have led to at least some negative impacts in the form of greater famine and/or mortality.

European monarchs' cognitive ability and state performance

How important is the quality of a CEO to a company's performance over time? How important is the quality of a leader to a country's performance over time? These questions seem quite straightforward to answer, but in reality they are quite tricky. First, it is difficult to measure the 'quality' of a CEO or a leader. Second, the appointment of a CEO or a leader is not a random event - typically it is the result of a deliberative process, and may depend on the company's or country's past or expected future performance.

What is needed is some CEOs or leaders who differ in 'quality' and who are randomly appointed to the role. This sort of experiment is, of course, not available in the real world. However, a 2025 article by Sebastian Ottinger (SERGE-EI) and Nico Voigtländer (UCLA), published in the journal Econometrica (open access), examines a setting that mimics the ideal experiment in many respects. Ottinger and Voigtländer look at 399 European monarchs from 13 states over the period 1000-1800 CE. To address the two concerns above (measurement of quality and non-random appointment), they:

...exploit two salient features of ruling dynasties: first, hereditary succession—the predetermined appointment of offspring of the prior ruler, independent of their ability; second, variation in ruler ability due to the widespread inbreeding of dynasties.

Ottinger and Voigtländer measure the 'quality' of a ruling monarch using the work of Frederick Adams Woods, who:

...coded rulers’ cognitive capability based on reference works and state-specific historical accounts.

Ottinger and Voigtländer measure the outcome variable, state performance, as a subjective measure from the work of Woods, as well as the change in land area during each monarch's reign, and the change in urban population during each monarch's reign. They then use a measure of the 'coefficient of inbreeding' for each ruler as an instrument for cognitive ability. This is important, because the instrumental variables (IV) approach they employ reduces the impact of any measurement error in cognitive ability, as well as dealing with the endogenous selection of rulers. However, as always with the IV approach, the key identifying assumption is that inbreeding affects the outcome (state performance) only through its effect on ruler cognitive ability (not, say, through the instability of succession). Ottinger and Voigtländer provide a detailed discussion in favour of the validity of the instrument, and support this by showing that the results hold when they instead use 'hidden inbreeding' (inbreeding that is less direct than, say, parents being first cousins or an uncle and niece) as an instrument.

Now, in their main instrumental variables analysis, they find:

...a sizeable effect of (instrumented) ruler ability on all three dimensions of state performance. A one-std increase in ruler ability leads to a 0.8 std higher broad State Performance, to an expansion in territory by 16%, and to an increase in urban population by 14%.

Ottinger and Voigtländer also explore the mechanisms explaining this effect, finding that:

...less inbred, capable rulers tended to improve their states’ finances, commerce, law and order, and general living conditions. They also reduced involvement in international wars, but when they did, won a larger proportion of battles, leading to an expansion of their territory into urbanized areas. This suggests that capable rulers chose conflicts “wisely,” resulting in expansions into valuable, densely populated territories.

Finally, Ottinger and Voigtländer looked at whether a country's institutions mattered for the effect of the ruler's cognitive ability on state performance. They measure how constrained a ruler was, such as by the power of parliament, and using this measure in their analysis they find that:

...inbreeding and ability of unconstrained leaders had a strong effect on state borders and urban population in their reign, while the of constrained rulers (those who faced “substantial limitations on their authority”) made almost no difference.

That result is further support that the cognitive ability of rulers mattered precisely in those situations where a ruler might be expected to have an effect - that is, when they are unconstrained by political institutions. When the ruler is constrained by parliament or other political institutions, their cognitive ability will likely have much less effect on state performance, and that is what Ottinger and Voigtländer found.

One surprising finding from the paper appears in the supplementary materials, where Ottinger and Voigtländer report that the marginal effect of cognitive ability on state performance doesn't vary by gender. That surprises me a little given that earlier research by Dube and Harish (which Ottinger and Voigtländer cite in a footnote) found that queens were more likely to engage in wars than kings (see here). Now, this paper shows that more able rulers fight fewer wars. So, I would have expected that queens, having fought more wars, would show a different relationship between cognitive ability and state performance, but that didn't prove to be the case. Perhaps that tells us that, while queens may have fought more wars, they made better choices about which wars to fight? Or perhaps, they fought more wars but that only affected the level of wars, and not the interaction between cognitive ability and wars (or cognitive ability and state performance)?

Regardless, overall these results tell us that the 'quality' of a leader really does matter. A higher quality ruler, in terms of cognitive ability, improves state performance. Extending from those results, we might expect that a higher quality CEO also improves company performance. Of course, CEO selection isn’t hereditary and differs in important ways, but the broader lesson that leader quality can matter a lot when leaders have discretion likely holds in that setting as well.

[HT: Marginal Revolution, early last year]

Read more:

• The warmongering queens of Europe

Roman rule, and personality traits and subjective wellbeing in modern Germany

History has a long tail. Events in the distant past can have surprising effects today. For instance, past research I have blogged on has shown that autocratic rule in Qing dynasty China affects social capital today (see here), the Spanish Inquisition affects GDP in Spanish municipalities (see here), and Roman roads affect the modern location and density of roads in Europe (see here). In that vein, this recent article by Martin Obschonka (University of Amsterdam) and co-authors, published in the journal Current Research in Ecological and Social Psychology (open access), looks at the effect of Roman rule on modern incidence of personality traits and subjective wellbeing in Germany. To do this, Obschonka et al. compare people on either side of the Limes Wall, noting that:

To protect their territory with its cultural and economic advancements, the Romans built the Limes wall around 150 AD and it served as a border of the empire for more than a century. The Limes consists of three major rivers, namely the Rhine, the Danube, and the Main ("Main Limes"), as well as a physical wall ... It is well-documented that the Limes constituted a physical, economic, and cultural border between the Roman and Germanic cultures...

By comparing people on either side of the Limes Wall, Obschonka et al. try to reveal the enduring impact of Roman rule. They expect this effect on personality traits and subjective wellbeing because:

...the Roman society was much wealthier and considerably more structured and organized than the “barbaric” Germanic tribes, with an effective public administration and a relatively well-elaborated legal system... When the Romans occupied parts of the territories inhabited by Germanic tribes, they imported superior scientific knowledge and a civic structure.

To measure personality traits, Obschonka et al. turn to the German dataset from the Gosling-Potter Internet Personality Project, the largest dataset on the 'Big Five' personality traits. The German sample they use includes over 73,000 observations between 2003 and 2015, which they aggregate to regional-level averages. For subjective wellbeing (life satisfaction), they use data from the German Socioeconomic Panel between 1984 and 2016, again aggregated to regional-level averages. They also look at life expectancy. Using a simple OLS regression model, with a 'treatment variable' indicating that a region was in the Roman occupied area, Obschonka et al. find that:

...the populations in those regions that were occupied by the Romans nearly 2000 years ago show significantly higher levels of extraversion, agreeableness, and openness, and significantly lower levels of neuroticism (which points to more adaptive personality patterns in the former Roman regions of present-day Germany) than do the populations living in the non-occupied regions... Moreover, populations living in the formerly Roman areas today report greater satisfaction with life and health, and also have longer life expectancies...

After including a range of control variables into their models, the effects on agreeableness and openness became statistically insignificant. However, that leaves significant effects of Roman rule on extraversion and neuroticism, as well as life satisfaction and life expectancy. The results are similar when they use a spatial regression discontinuity design (RDD) instead of OLS. The spatial RDD takes account of how far away an observation is from the Limes Wall, which separates the 'treated' and 'control' regions (and regions closer to the line provide more information about the distinctive effect of the treatment, in this case Roman rule). The method assumes that places on either side of the border are similar except for the Roman occupation. This seems plausible, so the spatial RDD results in particular make the results more believable.

Obschonka et al. then turn to looking at the mechanisms that might explain the enduring effect of Roman rule. They show that:

Density of road infrastructure built by the Romans shows a statistically significant, positive effect on life and health satisfaction, as well as on life expectancy. There is a negative, statistically significant relationship with neuroticism, a positive one with extraversion, and a non-significant one with agreeableness, conscientiousness, and openness...

Running the models with the number of Roman markets and mines as the independent variable reveals a negative effect on neuroticism and a positive effect on extraversion. In addition, there is also a positive effect on conscientiousness (and openness). None of the effects on psychological well-being or health were statistically significant. Including Roman road density and the number of Roman markets and mines in the same model... clearly indicates that markets and mines are more strongly related to the personality traits, whereas Roman road density is more closely related to the health and well-being outcomes.

These results should be seen as more exploratory, but Obschonka et al. interpret them as showing:

...support for the notion that the tangible and lasting economic infrastructure built and established by the Romans left a long-term macro-psychological legacy...

Perhaps. I find it less plausible that Roman physical infrastructure had a lasting effect on modern personality traits and subjective wellbeing, and more likely that Roman worldviews and 'social infrastructure' (things like institutions or social norms, for example) was passed down from one generation to the next, showing up as a lasting effect on personality and wellbeing. Unfortunately, Obschonka et al. aren't able to tease out those sorts of mechanisms. Either way, it’s another reminder that borders drawn 2000 years ago can still show up in the data, even in places we might not think to look.

[HT: Marginal Revolution, early last year]

The Census Tree project

An exciting (and new-ish) dataset offers us an unprecedented opportunity to explore research questions using historical US Census data. When I posted about what's new in regional and urban economics last year, one of the things that was raised was the linking of historical Census records over time. That was based on the work of Abramitzky et al., known as the Census Linking Project (CLP). However, in a recent article published in the journal Explorations in Economic History (open access), Kasey Buckles (University of Notre Dame) and co-authors report on an alternative Census linking dataset that has far larger coverage than the CLP. As they explain:

In the Census Tree project, we use information provided by members of the largest genealogy research community in the world to create hundreds of millions of new links among the historical U.S. Censuses (1850–1940). The users of the platform link data sources—including decennial census records—to the profiles of deceased people as part of their own family history research. In doing so, they rely on private information like maiden names, family members’ names, and geographic moves to make links that a researcher would never be able to make using the observable information...

The result is the publicly-available Census Tree dataset, which contains over 700 million links among the 1850–1940 censuses...

The article describes the creation of the Census Tree dataset, which can be accessed for free online. Buckles et al. also demonstrate the use of the dataset, in a particular application in comparison with the CLP data of Abramitzky et al.:

...who show that the children of immigrants were more upwardly mobile on average than the children of the U.S.-born in the late 19th and early 20th centuries. We replicate this result using the Census Tree, and are able to increase the precision of estimates for each sending country. Furthermore, the Census Tree includes sufficient numbers of links to produce estimates for an additional ten countries, including countries from Central America and the Caribbean. We find that the sons of low-income immigrants from Mexico had significantly worse outcomes on average than sons of fathers from other countries, including U.S.-born Whites. We further extend [Abramitzky et al.] by analyzing the mobility of women in a historical sample, and compare these results to historical estimates for men and modern estimates for women. While the patterns for daughters and sons are broadly similar, differences in marriage patterns contribute to gender gaps in mobility in some countries.

As I noted in this post last year, the ability to link people over long periods of time (including between generations) has opened up a wealth of new research questions. Buckles et al. offers a peek at the range of research that has already been done using the Census Tree dataset (see Appendix B in the paper for a bibliography).

Now, the coverage isn't perfect, and there is still some ways to go. You can evaluate the quality of the dataset based on what Buckles et al. report in their article, but it is clearly better than previous efforts. And importantly:

...we plan to update the Census Tree every two-to-three years to incorporate new information added by FamilySearch users, to include new links... and to implement methodological advances in linking methods that we and others develop.

This seems like a really important resources for researchers in economics, sociology, regional science, and other fields, and not just for those interested in economic history. 

Book review: The Rise of the Western World

It is somewhat fitting that, in a week where Joel Mokyr won the Nobel Prize in economics, I was just finishing up reading a book on economic history. It wasn't one of Mokyr's books though (although they are on my to-be-read list now). It was The Rise of the Western World, by Mokyr's fellow Nobel laureate Douglass North, co-authored with Robert Thomas.

A lot of economic history focuses on the Industrial Revolution. North and Thomas focus their attention earlier, on the period between the High Middle Ages and the Enlightenment, between 900 CE and 1700 CE. This period is of interest because it was when western Europe emerged from a feudal society into more modern political states, and during which property rights over land increasingly developed. These changes formed the antecedents to the Industrial Revolution that was to come. North and Thomas summarise this in the introduction to the book:

Economic growth occurs if output grows faster than population. Given the described assumptions about the way people behave, economic growth will occur if property rights make it worthwhile to undertake socially productive activity. The creating, specifying and enacting of such property rights are costly, in a degree affected by the state of technology and organization. As the potential grows for private gains to exceed transaction costs, efforts will be made to establish such property rights. Governments take over the protection and enforcement of property rights because they can do so at a lower cost than private volunteer groups. However, the fiscal needs of government may induce the protection of certain property rights which hinder rather than promote growth; therefore we have no guarantee that productive institutional arrangements will emerge.

My ECONS102 students will probably recognise important elements in there from their lectures, including property rights, institutions, and transaction costs. Indeed, I learned a lot from reading this book that will help to better articulate and link those points, as well as bringing in not only this work, but the work on common governance by Elinor Ostrom.

The majority of the book works through the period chronologically, developing the ideas and presenting supporting data where needed. It finishes by considering differences in institutions and economic growth performance in the 'early modern period' between England, France, Spain, and the Netherlands. The writing can be a little dry, but it is neither heavily data-driven nor overly theoretical. However, economic theory definitely underpins the key ideas in the text. Consider this bit on growth in the Middle Ages:

...we suggest that a growing population was the exogenous variable that basically accounts for the growth and development of Western Europe during the high Middle Ages. An expanding population in a local area would eventually encounter diminishing returns to further increases in the size of the labor force. Part of the increased labor force would as a consequence migrate to take up virgin land in the wilderness, thus extending the frontiers of settlement. However, the density of habitation would still be greater in the older areas than on the frontier, and this differential, resulting in a variation of land-to-labor ratios between areas, when coupled with regional differences in natural resource endowments, would lead to different types of production. Such variances would allow profitable exchanges of products between regions. We submit, therefore, that the development and expansion of a market economy during the Middle Ages was a direct response to the opportunity to gain from the specialization and trade made feasible by population growth.

North and Thomas don't pause to explain the economic terms in their exposition. So, while this book is readable to a non-economist, it seems to me that only those with a bit of economic training will truly appreciate the ideas presented in the book. Indeed, that is almost certainly the audience that North and Thomas had in mind. For those with a little bit of economic knowledge, and an interest in economic history, there is a lot to be gained from reading this book. I recommend it, especially to anyone looking to see the story up to the point where the economic historians specialising in the Industrial Revolution take over.

When John Maynard Keynes was the examiner for New Zealand economics students

One of my former colleagues (now retired), Brian Silverstone, used to share stories of the old days, when examination papers were shipped off from New Zealand to England for marking at the end of the year. The examiner would be some moderately known academic in England, who few in New Zealand would know, and who would likely never have set foot in New Zealand before.

Thankfully, such colonial practices have long since ceased. However, they have lasting effects. For example, this historical examination process explains why most New Zealand universities have graduation ceremonies in April, for students who completed their studies at the end of the previous year. That was necessary in times when the examination scripts would face an eight-week journey by boat in each direction, but it makes little sense these days, when final grades are known within days or weeks of the end of the trimester.

Anyway, not all of the examiners were relatively unknown. As Conrad Blyth (University of Auckland) noted in this 2007 article, published in the journal History of Economics Review (sorry, I don't see an ungated version online), John Maynard Keynes was the economics examiner for the University of New Zealand (as it was in those days) in 1919. Interestingly, his father John Neville Keynes had been the examiner for 1899-1903.

Blyth's article includes full copies of the six Honours and MA examination papers that the younger Keynes set for students. They make for an interesting read. It is surprising how many of the questions bear close resemblance to questions I might ask my students now, such as:

Why are lawyers better paid than coal-miners? Should they be? The answer should contain a careful analysis of all the important underlying causes...

What sort of undertakings can be suitably run by municipalities? Should they aim at making a profit? Would they ever be justified in making a loss?...

Discuss the justification and the utility of Governmental intervention to fix prices. What are the chief dangers of such action?...

What is the incidence of taxes on (a) rent, (b) profits, (c) bread, (d) alcoholic drinks (e) domestic servants?

Of course, Keynes would have been looking for a much greater depth of insight and analysis from these Honours and MA students than what I expect in my ECONS102 class. Nevertheless, the persistence of the sorts of questions that economics academics ask of students is striking, even a century later. In another sign that the more things change, the more they stay the same, this essay topic appears in Paper (f):

The Policy of New Zealand towards Immigration now and in the future. 

I don't ask students to write essays, having dispensed with them after my first year of teaching. However, if I were setting an essay question today, that seems to me to be a topic that would be attractive right now.

My students generally do a good job of answering these questions (to the standard I am expecting). However, Keynes was not impressed by the quality of the students that he examined. He made the following comments in his examiner's report:

The candidates as a whole showed that they had been reasonably industrious and conscientious in their work. If, however, I may make a criticism, it would be that they are unduly tied down to their textbooks, often imperfectly understood, and show an insufficient independence of mind. There was hardly any single instance in any of the papers of an individual or characteristic remark showing the personality of the writer. There was hardly even a lively or impudent passage amongst the lot. The general impression produced on the examiner’s mind is therefore very dull...

I'm extra glad that I don't have dull students!

[HT: Thomas Scrimgeour, via Frank Scrimgeour]

Lifespans of the rich and famous, from 800-1800 C.E.

Life expectancy is one of the key statistics in human wellbeing. However, we know surprisingly little about life expectancy prior to the systematic recording of births, deaths, and marriages, which began in England in 1538 with the establishment of parish registers. Many other countries started recording this data, but later in the 16th Century (or even later).

So, I was really interested to read this 2017 article by Neil Cummins (London School of Economics and Political Science), published in the Journal of Economic History (ungated earlier version here). They use family tree data on the European elite across multiple countries collected by the LDS church. As Cummins explains:

The church has been at the frontier of the application of information technology to genealogy and has digitized a multitude of historical records. Today they make their research available online at familysearch.org. The records number in the billions. The source of the family trees used here are the online databases at histfam.familysearch.org, a collaboration between the LDS church (familysearch) and individual genealogical experts.

The sample size is large:

The family tree records used here contain 402,204 unique date descriptions... Of the 1,329,466 individual records, 167,266 have a birth year between 800 and 1800 with an associated age at death. Of those, 115,650 have an age at death over 20 and 76,403 have a specific date of death.

Cummins uses the data to estimate the length of life of the European elite, after dealing with some tricky data issues (such as 'heaping' of dates in years that end in '0'). The resulting dataset does a good job of picking up changes in lifespan resulting from plague years and from violent battle deaths. On those points:

First, plague, which afflicted Europe 1348-1700, killed nobles at a much lower rate than it did the general population. Second there were significant declines in the proportion of male deaths from battle violence, mostly before 1550... Before 1550, 30 percent of noble men died in battle. After 1550, it was less than 5 percent.

However, more interesting is the trends in lifespan over time, where Cummins finds that:

...there was a common upwards trend in the adult lifespan of nobles even before 1800. But this improvement was concentrated in two periods. Around 1400, and then again around 1650, there were relatively sudden upwards movements in longevity.

Those changes are captured in panel (a) of Figure 8 from the article:

The figure plots average life expectancy in 50-year bins. Life expectancy hovered around 50 years (or slightly higher) from 800 to 1350 C.E., then jumped up to about 52 years in 1400 C.E., then to over 55 years in 1700 C.E. Cummins isn't able to offer a reason as to why those increases happened at those times, and notes that:

No conclusions can be drawn as to why adult noble lifespan increased so much after 1400. No known medical innovations in Europe before 1500 could be responsible... Nutrition, in terms of calories consumed, also cannot explain this rise. These elites could be expected to have always filled their bellies.

Finally, Cummins shows a clear geographical gradient in lifespan:

I find that there were regional differences in elite adult lifespan favoring Northwest Europe, that emerged around 1000 AD. While average lifespan in England in 1400 was 54, in Southern Europe, as well as in Central and Eastern Europe, it was only 50. The cause of this geographic “effect” is unknown.

So, while interesting, this paper leaves a lot to explore in terms of the reasons for changes in the lifespan of the European elite over this time period. There are also open questions about the lifespan differences between the elite and the rest of the population, as Cummins' results imply that the Black Death had a much lower impact on the elite than the rest of the population, which differs from the conclusions of much past research. As I've noted before, we need to understand more about lifespan inequality. Clearly, there is more work necessary in this area.

Christian missions and HIV in Africa

Spreading Christianity was seen by the colonial powers as a way of civilising the native populations in Africa. Indeed, in 1857 David Livingstone wrote that "neither civilization nor Christianity can be promoted alone. In fact, they are inseparable" (see here). Among the many effects of colonisation, the spread of Christianity is seen as one of the few positive aspects (or, at least, one of the least negative aspects). Christian missions were associated with increased availability of education and (Western) health care. However, this may not have meant that health improved along all dimensions. This 2020 article by Julia Cagé (Sciences Po) and Valeria Rueda (University of Nottingham), published in the Journal of Demographic Economics (ungated earlier version here) presents evidence that historical Christian missions were associated with higher prevalence of HIV.

Cagé and Rueda use data on the locations and characteristics of Protestant missions from 1903 (from the Geography and Atlas of Christian Missions) and data on the locations and characteristics of Catholic missions from 1929 (from the Atlas Hierarchicus), in each case distinguishing between missions with and missions without health facilities. That allows them to compare outcomes for people living closer or further away from historical Christian mission locations with and without health facilities. The key outcome variable is HIV infection status, as recorded in the Demographic and Health Surveys from 2003 to 2013 (which includes over 344,000 individuals across 17 African countries).

In their main analysis, they find that:

...a 10% increase in distance to any mission is associated with a 0.003 unit lower probability of an HIV-positive result... Ceteris paribus, at the median distance to a mission, a 15 km increase in distance decreases the average probability of HIV positivity by approximately 5%.

So, people living closer to historical Christian missions are more likely to be infected with HIV. However, the story doesn't end there, as:

...a 10% increase in the distance to a mission with a health investment is associated with a 0.0005-unit increase in the probability of HIV positivity... This result suggests that, ceteris paribus, at the median distance to a mission that invested in health, a 15 km increase in distance to the health investment increases the average probability of HIV by approximately 0.7% to 1.2%.

So, Christian missions are associated with higher HIV prevalence, but this is offset if the mission had a health facility. The results appear to be somewhat greater for Protestant missions than for Catholic missions. Cagé and Rueda show that their results are robust to various alternatives, including limiting the sample to people living in more urban areas, and the results are similar when using a matching approach (although the sample size is much smaller when relying on the matched sample).

Here's where things get interesting though. The results are not generalisable across all health conditions, as when Cagé and Rueda look at anaemia or stunting, they find that:

...unlike for HIV, proximity to a mission does not statistically significantly correlate with these health outcomes. If anything, we observe improved outcomes (less positive results of anemia or stunted growth), but the relationship is not significant.

So, what is it about HIV that sets the results apart? Cagé and Rueda argue that there are:

...two possible countervailing effects of missions on HIV prevalence. On the one hand, their early investments in health facilities have a positive long-term impact on HIV prevalence, through the persistence of infrastructure and safer sexual behaviors. On the other hand, missionaries left a profound cultural imprint: conversion to Christianity increased the risk of contagion by changing family structures and increased exposure to religious institutions that have struggled to effectively address the epidemic.

Then, they find that sexual behaviours differ markedly for Christians and non-Christians in the DHS sample:

We observe that despite being more educated on average than non-Christians, Christians have riskier sexual behaviors. They have more sexual partners over their lifetime and are more likely to use the services of sex workers. Furthermore, they are also less likely to be abstinent before marriage. Despite being more likely to know that condoms lower the chances of transmitting HIV, they are less likely to know where to find them.

And then, comparing Catholics and Protestants (while noting that the categories are not perfectly separable in the survey), they find that:

Catholics exhibit certain riskier behaviors, like a larger age gap inside the household, or a larger number of sex partners. Protestants are nonetheless more likely to use the services of sex workers over their lifetime, which is a very strong determinant of HIV transmission, and less likely to know that condoms lower the chances of HIV contamination. Although it is statistically significant, the difference is quantitatively very small.

This, combined with the greater success of Protestant conversion in African than Catholic conversion, may explain the larger impact of Protestant missions than Catholic missions in their initial results.

So, it appears that Christian missions have had a long-term impact on health in Africa, and not entirely in a positive way. What can we learn from this? Cagé and Rueda point out that:

...our results may help us reflect on contemporary HIV prevention policies. In the United States, religious conservatives strongly support abstinence-until-marriage (AUM) as the central element of HIV prevention efforts, and this policy periodically receives a large share of the Federal funding... Our long-term perspective suggests that a focus only on “Christianizing” marriage patterns and sexual behaviors is unlikely to be successful.

Indeed. Add this to the evidence base against an abstinence-only approach to the HIV pandemic.

The dissolution of English monasteries, the rise of the gentry, and the Industrial Revolution

There are many theories that purport to explain why England experienced the Industrial Revolution first (rather than France, say, or China). For example, the CORE Economics textbook, which I use in my ECONS101 class, focuses on changes in the relative price of coal and labour (alongside the availability of cheap resources arising from colonial conquest and slavery). It's an interesting theory, and has support from data, but probably isn't the whole story.

Another theory posits that the Dissolution of the English Monasteries in the 1530s freed up land from feudal tenure and created a rising class of gentry, who had stronger incentives for investment, innovation, and commercialisation. This theory is attributed to the historian Richard Tawney, and is the theory that is tested in this 2021 article by Leander Heldring (Northwestern University),  James Robinson (University of Chicago), and Sebastian Vollmer (University of Göttingen), published in the Quarterly Journal of Economics (ungated earlier version here).

Specifically, Heldring et al. use a variety of data at the Parish level before and after the Dissolution, and compare parishes that had monastery-owned land ('monastic parishes') with those that didn't ('non-monastic parishes'). They find a number of important results that are consistent with Tawney's theory, including:

...we first use data on the presence of markets in 1600 and the survival of perpetual copyhold into the nineteenth century. We find that former monastic parishes are more likely to have a recurring market, and are less likely to be unencumbered by feudal copyhold tenure, consistent with our interpretation of the shock...

We use a unique census from 1700 that records the number of gentry in each town and village in England and Wales to measure the presence of the gentry... We find, consistent with Tawney, that gentry are more likely to be present on formerly monastic lands. We also find that monastic lands experienced more rapid conversion and thus subsequently had fewer Catholics...

Using census data, we show that monastic parishes employ a smaller share of the working-age male population in agriculture in 1831 and a commensurately larger share in commercialized sectors, like trade and handicraft. Moreover, using data on all textile mills in England in 1838, we find that monastic parishes are more industrialized than non-monastic parishes...

We find that the presence of formerly monastic properties in a parish is positively and significantly correlated with patenting, enclosure, investment, and agricultural yield.

To summarise, monastic parishes were more likely to have markets, were less likely to have feudal tenure of land, had more gentry (and fewer Catholics), were more commercialised, had more textile mills, and had more patenting and agricultural investment, than non-monastic parishes. Heldring et al. note that:

Our results suggest that the end of monastic restrictions on the marketability of one-third of the land in England and relative incidence of customary tenure, itself directly linked to feudalism, were important for fundamental economic change. The lagged abolition of feudal land tenure in France and Germany may be behind why England pulled ahead on the world stage in the eighteenth century.

This is a really interesting and thorough paper, using a variety of the best available data. It doesn't provide the whole story for why England experienced the Industrial Revolution before other countries, but it does provide good evidence of some of the precursors that likely contributed to it.

[HT: The Dangerous Economist, last year] 

Rainfall, military food shortages and the assassination of Roman emperors

Dictators maintain control of their country by maintaining control of the military. If they lose control of the military, they often lose control of their country, or worse. This 2018 article by Cornelius Christian (Brock University) and Liam Elbourne (St. Francis Xavier University), published in the journal Economics Letters (sorry, I don't see an ungated version online), looks at cases where Roman emperors lost control, and their lives (through assassination).

Christian and Elbourne first note some key facts drawn from past research:

(1) The Roman economy was largely agricultural, depending on rainfed agriculture (Harper, 2017).

(2) The bulk of the Roman army was stationed along the Western frontier, and relied heavily on local food sources (Roth, 1998; Elton, 1996)...

(3) Food transport, in Ancient Rome, was very slow (Terpstra, 2013).

Christian and Elbourne then infer that shocks to military food supply, arising from low rainfall in the frontier areas like Germania, would reduce support for the emperor, increasing the chances that the emperor is assassinated. They use data covering the period from 27 BCE to 476 CE, which covers the period from the beginning of the reign of Augustus to the fall of the Western Roman Empire. Over that period, the relationship between rainfall and the number of assassinations is captured in Figure 1 from the article:

If you squint really hard, you can probably see that there are more assassinations in times when rainfall is lower. This is most apparent in the middle of the study period, between 200 and 300 CE, when there was a century of relatively low rainfall and many assassinations. Turning to their quantitative results, Christian and Elbourne find that:

...a standard deviation decline in rainfall causes an 11.6% standard deviation increase in assassination probability... [and] a standard deviation drop in rainfall causes a 13.4% standard deviation increase in total assassinations.

Now, of course this paper doesn't definitively establish a causal relationship between rainfall and assassinations. However, it is interesting that when, instead of using rainfall from the year before, Christian and Elbourne use rainfall from the following year, the correlation with assassinations becomes statistically insignificant. They also find that rainfall is a statistically significant predictor of frontier mutinies, which is consistent with rainfall increasing disquiet in the military.

However, the parts of the story included in this article don't quite feel like they add up to a coherent whole to me. The correlations are strong, but not necessarily entirely convincing. If the mechanism through which negative rainfall shocks increase emperor assassinations is through declining military support, why don't Christian and Elbourne use an instrumental variables approach, with rainfall as an instrument for frontier mutinies, and frontier mutinies as an endogenous variable explaining assassinations? Surely they tried this approach, so there being no mention of it in the paper is perhaps a signal to us that the approach doesn't work. In that case, we should be a little sceptical of the results.

Nevertheless, it is an interesting paper, and I'm sure there will be more work in this area. As attributed to both Napoleon Bonaparte and Frederick the Great, "an army marches on its stomach". When the stomach is not full, I guess the army stops marching, and eventually turns on its leaders.

Tea drinking vs. beer drinking, and mortality in pre-industrial England

When I introduce the difference between causation and correlation in my ECONS101 class, I talk about how, even when there is a good story to tell about why a change in one variable causes a change in the other, that doesn't necessarily mean that an observed relationship is causal. It appears that I am just a susceptible to a good story as anyone else. When a research paper has a good story, and the data and methods seem credible, I'm willing to update my priors by a lot (unless the results also contradict a lot of the prior research). I guess that's a form of confirmation bias.

So, I was willing to accept at face value the results of the article on tea drinking and mortality in England that I blogged about earlier this week. To recap, that research found that the increase in tea drinking in 18th Century England, by promoting the boiling of water, reduced mortality. However, now I'm not so sure. What has caused me to re-evaluate my position is this other paper by Francisca Antman and James Flynn (both University of Colorado, Boulder), on the effect of beer drinking on mortality in pre-industrial England.

Antman is the author of the tea-drinking article, so it should be no surprise to expect that the methods and data sources are similar, given the similarity of the two papers in terms of research question and setting. However, there are some key differences between the two papers (which I will come to in a minute). First, why study beer? Antman and Flynn explain that:

Although beer in the present day is regarded primarily as a beverage that would be worse for health than water, several features of both beer and water available during this historical period suggest the opposite was likely to be true. First, brewing beer would have required boiling the water, which would kill many of the dangerous pathogens that could be found in contaminated drinking water. As Bamforth (2004) puts it, ‘the boiling and the hopping were inadvertently water purification techniques’ which made beer safer than water in 17th century Great Britain. Second, the fermentation process which resulted in alcohol may have added antiseptic qualities to the beverage as well...

Notice that the first mechanism here is basically the same as for tea. Boiling water makes water safer to drink, even when it is being used in brewing. Also:

...beer in this period, which sometimes referred to as ”small beer,” was generally much weaker than it is today, and thus would have been closer to purified water. Accum (1820) found that small beer in late 18th and early 19th century England averaged just 0.75% alcohol by volume, a tiny fraction of the content of even the ‘light’ beers of today.

The data sources are very similar to those used for the tea drinking paper, and the methods are substantially similar as well. Antman and Flynn compare parish-level summer deaths (which are more likely to be associated with water-borne disease than summer deaths) between areas with high water quality and low water quality, before and after a substantial increase in the malt tax in 1780. Using this difference-in-differences approach, they find that:

...the summer death rate in low water quality parishes increases by 22.2% relative to high water quality parishes, with a p-value on the equality of the two coefficients of .001.

Antman and Flynn then use a second identification strategy, which is to compare summer deaths between parishes that have gley soil (suitable for growing barley, which is then malted and used to make beer) and parishes without gley soil, before and after the change in the malt tax. In this analysis, they find that:

...parishes with gley soil had summer death rates which increased by approximately 18% after the malt tax was implemented relative to parishes without gley soil.

Not satisfied with only two identification strategies, Antman and Flynn then use a third, which is rainfall. Their data is limited to the counties around London (because that is where they have the rainfall data from). In this analysis, they find that:

...the effect of rainier barley growing seasons on parishes with few nearby water sources is positive and significant, indicating that summer deaths rise following particularly rainy barley growing seasons... [and] ...rainy barley-growing seasons lead to more summer deaths in areas where beer is most abundant, even controlling for the number of deaths occurring in the winter months.

So, the evidence seems consistent with beer drinking being associated with lower mortality, because in areas where beer drinking decreased (because of the increase in the malt tax) by a greater amount, mortality increased by more.

But not so fast. There are two problems here, when you compare across the tea drinking and beer drinking research. First, the data that they use is not consistent. The tea drinking paper uses all deaths in each parish. The beer drinking paper uses only summer deaths, arguing that summer deaths are more likely to be from water-borne causes. If that is the case, why use all deaths in the tea drinking paper? What happens to the results from each paper when you use the same mortality data specification?

Second, the increase in the Malt Tax was in 1780. The decrease in the tea tax (which the tea drinking paper relies on) was in 1784. The two tax changes are awfully close together timewise, and disentangling their effects would be difficult. However, neither paper seems to account for the other properly. The beer drinking paper includes tea imports as a control variable, but in the tea drinking paper it wasn't tea imports, but tea imports interacted with water quality that was the key explanatory variable (and the timing of the tea tax change interacted with the water quality variable). The tea drinking paper doesn't really control for changes in beer drinking at all.

That second problem is the bigger issue, and creates a potentially problematic omitted variable problem in both papers. If you don't include changes in tea drinking in the beer drinking paper, and the two tax changes happened around the same time, how can you be sure that the change in mortality was due to tea drinking, and not beer drinking? And vice versa for failing to include changes in beer drinking in the tea drinking paper.

However, maybe things are not all bad here. Remember that the two effects are going in opposite directions. It is possible that the decrease in the tea tax increased tea drinking, and mortality reduced, while the increase in the malt tax decreased beer drinking, and mortality increased. However, then we come back to the first problem. Why use a measure of overall mortality in the tea drinking paper, and a measure of only summer mortality in the beer drinking paper, when both papers are supposed to be looking at changes in mortality stemming from water-borne diseases?

Hopefully now you can see why I have my doubts about the tea drinking paper, as well as the beer drinking paper. Both are telling an interesting story, but the inconsistencies in data and approach across the two papers should make use extra cautious about the results, and leave us pondering the question of whether the results are causal or simply correlation.

[HT for the beer paper: The Dangerous Economist]

Read more:

• Tea drinking and mortality in pre-industrial England

Tea drinking and mortality in pre-industrial England

[Update: I now have some doubts about this paper - see this follow-up post]

The importance of clean water for public health is thoroughly uncontroversial in modern times. In the temporary absence of a safe water source, one recommendation is to boil water for drinking, which will kill off most bacteria and other pathogens. However, prior to the acceptance of the germ theory of disease, the importance of clean water was relatively unknown. Water-borne diseases such as dysentery and cholera were relatively common (at least, compared with modern times).

In the late 17th Century, the English began drinking tea in large numbers (more on that in a moment). One of the important aspects of tea drinking is that it requires boiling of water. Did that lead to a reduction in mortality, especially from water-borne disease? That is the research question addressed in this forthcoming article by Francisca Antman (University of Colorado, Boulder), to be published in the journal Review of Economics and Statistics (ungated earlier version here, and relatively non-technical summary by the author here). Why investigate this? Antman notes that:

...several historians have suggested that the custom of tea drinking was instrumental in curbing deaths from water-borne diseases and thus sowing the seeds for economic growth.

Antman's research is the first to quantitatively attempt to assess these claims. She uses data on mortality rates at the parish level for 404 parishes from the mid-16th Century to the mid-19th Century, and a couple of different proxies for water quality:

The primary water quality measure used in the analysis is the number of water sources within 3 km of the parish, as calculated using data from the United Kingdom Environment Agency Statutory Main River Map of England overlaid on a map of historical parish boundaries... It is expected that parishes with a higher number of rivers proximate to the parish would have benefited from greater availability of running water, and thus would have benefited from relatively cleaner water compared with those parishes which were limited to only a few sources and thus suffered from a greater likelihood of contamination...

An alternative water quality proxy, the average elevation within a parish, is also offered to show that the relationship between tea and mortality is robust to alternative measures of water quality... Elevation is believed to be positively correlated with water quality because parishes at higher elevation would have been less likely to be subjected to water contamination from surrounding areas.

Antman applies two different strategies to identify the effect of tea drinking on mortality. In the first, she compares the decline in mortality between high (above the median) water quality parishes and low (below the median) water quality parishes over time. She particularly compares the difference between before and after the widespread adoption of tea drinking, which she dates as:

...the Tea and Windows Act of 1784 which reduced the tea tax from 119 to 12.5 percent at one stroke...

The second strategy uses lagged national-level tea imports as an indicator of when tea drinking increased in prevalence, but is otherwise similar. The results from the first strategy are nicely summarised in panel A1 of Figure 1 from the paper:

Notice that mortality declines in both high-water-quality parishes (dashed line with diamonds) and low-water-quality parishes (solid line with circles) after 1784, but that the decline was larger in low-water-quality parishes. And even though there is an up-tick in mortality towards the end of the time period (probably due to urbanisation, as urban areas had higher mortality than rural areas), the difference between high-water-quality and low-water-quality parishes continued to increase. Antman notes that:

With regard to the magnitudes of the impact of tea drinking on mortality, the estimates suggest that areas with worse water quality saw yearly mortality rates drops by about 18% by the end of the period, relative to parishes with better water quality...

The results are similar using the second strategy, although the size of the effect was smaller. Antman also shows that her results are robust to controlling for smallpox mortality, and to controlling for wages, as well as robust to including different proxies for parish-level population. So, it does seems that tea drinking, by promoting the boiling of water, did reduce mortality in pre-industrial England.

[HT: The Dangerous Economist, last year]

An unlikely argument that UV radiation and cataract prevalence explain differences in institutional quality

Economists define institutions as the basic rules, customs and practices of society, that determine and constrain the way that people interact. Institutions are the foundations of the economic and political systems of each country, and have been implicated in the explaining the differences in economic development between countries (see this article by Dietrich Vollrath, and my post on that topic as well). Indeed, a range of excellent work by Daron Acemoglu and James Robinson and their collaborators focuses on the role of institutions in explaining development, as detailed in their book Why Nations Fail (which I will review sometime this year - it is near the top of my large pile of books-to-be-read).

But what causes countries to have different political and economic institutions? Acemoglu and Robinson have focused attention on colonial relationships, as well as the roles of health and disease. So, I was interested to read this 2018 article by James Ang (Nanyang Technological University), Per Fredriksson (University of Louisville), Aqil bin Nurhakim, and Emerlyn Tay (both Nanyang Technological University), published in the journal Kyklos (ungated version here). Ang et al. focus on what, to me, seems a surprising angle - the role of sunlight (specifically, UV radiation) on institutional quality across countries. Their argument is that:

...populations facing a permanent threat of developing eye disease have historically had a lower incentive to invest in cooperation via institution building. Moreover, specialized activities such as institution building necessitate a food surplus, which requires prior investments in skills and technologies. Such activities and investments are hindered by a higher likelihood of blindness and hence fewer individuals specialize in law creation activities.

If that argument holds, then countries that (in the past) experienced high levels of UV radiation, where eye disease (specifically, cataracts) were more common, would have lower quality institutions in modern times. They use data on UV radiation that is derived from NASA, along with the World Bank Worldwide Governane Indicators (WGI) as their measure of institutional quality. The data do seem to support a relationship, as shown in Figure 1 from the paper:

And their regression analysis supports this. After controlling for a range of geographical variables (mean elevation, distance to nearest coast, terrain ruggedness, precipitation, whether the country is landlocked, a small island, and which continent the country is in):

...a one standard deviation (SD) increase in the intensity of UV-R (1 SD=0.778) leads to a 0.628 SD decrease in institutional quality (1 SD=0.262), all else equal.

The effect seems quite large:

For example, Papua New Guinea has a high UV-R intensity equal to 2.653 (max=3.285), and a poor institutional quality score of 0.272 (max=0.98). Based on the estimates... if Papua New Guinea instead experienced UV-R intensity similar to Estonia (0.514), the estimated institutional quality score would equal 0.725, a substantial rise. This is only slightly lower than Estonia’s current score (0.817), and is similar to those of neighboring Lithuania (0.736) and Latvia (0.710), with UV-R intensities similar to Estonia.

Indeed, possibly implausibly large. Could UV radiation really explain 83 percent of the difference in institutional quality between Papua New Guinea and Estonia? [*] It seems unlikely to me. However, in their robustness checks, Ang et al. go on to rule out a range of other things, including distance from the equator (absolute latitude), land area, agricultural suitability, the proportion of the population living in the tropics, and the number of frost days. They then show that cataract prevalence, unlike other disease prevalence, is negatively correlated with institutional quality, even when UV radiation is also in the econometric model. They conclude that:

...UV-R and institutional quality should be negatively related. Our results provide considerable support for this notion.

However, there are two problems remaining with this study. First, I don't really like their approach to the measurement of institutional quality:

Percentile rank data ranging from 0 to 100 for each country are used, where the country with the lowest ranked institutions is assigned a value of 0. The ranking scores for six abovementioned indicators are first averaged over the period 2006 to 2015 and are then combined into a composite index by taking their average. The data of this variable are then divided by 100 in order to give a measure that varies between 0 and 1, where a larger value signifies greater institutional quality.

I'm not sure what the average percentile ranking actually tells us. Country X can improve its ranking by improving its own institutional quality, or because the institutional quality of other countries improves, but slower than that of Country X. Although Ang et al. show that their results are robust to using other measures of institutional quality, they never show that the results are robust to using the underlying WGI scores rather than the ranking. That in itself should make us a little skeptical.

Second, Ang et al. never show that their results are robust to the inclusion of controls for colonial ties. Institutional quality has been shown to be associated with which colonial power (if any) historically controlled a country, along with the type of control (extractive or inclusive) that the colonial power exercised. This is the big omission, and is the basis of some of Acemoglu and Robinson's prior work. I suspect that the reason that UV radiation looks like it explains such a large proportion of differences in institutional quality is that UV radiation is correlated with colonial ties variables, which themselves are highly explanatory of the differences (economists refer to this as omitted variable bias). Ang et al. try to argue that omitted variable bias is not an issue, but it very much obviously is, when the existing literature suggests that there are important variables that have not been included.

So, I think we can file this study under interesting, but not convincing.

*****

[*] The difference in institutional quality between Estonia (0.817) and Papua New Guinea (0.272) is 0.545. If Papua New Guinea's institutional quality were raised to 0.725, the difference with Estonia would only be 0.092, an 83 percent decrease.

Genetic diversity and its enduring effect on economic development in the US

How important (or otherwise) is ethnic diversity for economic development? This is a genuinely difficult question to answer. However, this 2017 article by Philipp Ager (University of Southern Denmark) and Markus Brueckner (Australian National University), published in the journal Economic Inquiry (ungated earlier version here), makes a good attempt in one context. Ager and Brueckner use US county-level data over the period from 1870 to 2020, looking at how genetic diversity in 1870 (measured using the number of European-born people from different countries) was related to the change in output per capita (which is the sum of agricultural output and manufacturing output, and is a proxy for GDP). In their simplest regression models, they find that:

The point estimates on genetic diversity are positive and significantly different from zero at the 1% level in all regressions; quantitatively, they range between 0.09 and 0.12... the coefficient of 0.09... suggests that, on average, a one unit increase in genetic diversity increased U.S. counties’ output by around 10%. An alternative interpretation is that a one standard deviation increase in immigrants’ genetic diversity increased output per capita growth during the 1870–1920 period by around 20% (equivalent to around 0.25 standard deviations; or alternatively, 0.4% per annum).per capita during the 1870–1920 period.

That is quite a sizeable positive effect. Ager and Brueckner then go on to show that there are enduring effects, even more than a century later. The impact on 2010 income per capita is:

...around 0.04 and significantly different from zero at the 1% level.

There is also a statistically significant and positive (and somewhat larger) relationship with income per capita in 2000, 1990, 1980, and 1970. Ager and Brueckner then go even further, looking at the relationship between genetic diversity in 1790 and income per capita in 2000, finding that:

The estimated coefficient on 1790 genetic diversity is around 3.1... and statistically significant at the 1% level. Quantitatively, the estimated coefficient on immigrants’ 1790 genetic diversity suggests that a one standard deviation higher genetic diversity in 1790 was associated with a higher value of income per capita in the year 2000 of around 0.3 standard deviations.

Their results are also robust to a variety of alternative measures of development, non-linearity, controlling for pre-trends, and excluding outlier observations. However, they fall a bit short of demonstrating a causal impact, even when accounting for pre-trends, since counties that are initially more diverse may differ in meaningful ways from counties that are less diverse, not least in the types and variety of immigrants they attract. Nevertheless, the results are interesting, and especially when Ager and Brueckner consider a potential mechanism, finding that, at the state level:

...the genetic diversity variable has a significant positive effect on patents. On the other hand, there is no significant effect of genetic diversity on conflict for the sample at hand...

They don't dwell on these results too much, but I think they demonstrate that diversity is not associated with greater conflict (which would reduce productivity), but is associated with more innovation (which would increase productivity). Greater diversity leading to more innovation and therefore greater development does seem like a plausible (and good news) story. However, it would be interesting to see some more research corroborating these results in other (and perhaps more contemporary) contexts.

Radio broadcasts and the 1960s race riots in the U.S. South

The role of social media in recent periods of unrest comes as no surprise to us. From the Arab Spring uprisings in 2011, to the U.S. Capitol riot in January this year, to anti-lockdown protests in Melbourne, social media have helped turn a small spark of resistance into a large-scale anti-establishment event. It is tempting to think that the role of media (as exemplified by social media in modern times) in these sorts of incidents is a recent phenomenon. However, that seems unlikely, and this 2020 working paper by Andrea Bernini (University of Oxford) provides one example. Bernini studies the effect of black-appeal radio programming on the 1960s race riots in the U.S. South. For those of you who aren't intimately familiar with those riots (which included me):

In the eight-year period between 1964 and 1971, 752 riots occurred. These totaled to 1,802 days of civil unrest, leading to 228 deaths, 12,741 injuries, 69,099 arrests, as well as 15,835 episodes of arson and other destructive events.

Bernini collected data at the county level on the occurrence and severity of riots (where severity was and index calculated as the average of the number of days of rioting, number of deaths, injuries, arrests, and episodes of arson occurring in each county, as a proportion of the total across all counties and all years). He also collected data on the coverage of black-appeal radio stations (defined as those "airing at least 12 hours of black-appeal programming a week"). The radio coverage was calculated based on a model of electromagnetic signal propagation that incorporates the terrain, using satellite data from NASA - each county was then classified based on the share of the county that was coverage by black-appeal radio broadcasts, or a dummy variable that classified each county into whether or not more than 50 percent of the county was covered.

Looking at the relationship between radio coverage and riots, Bernini found that:

In the preferred specification, a marginal increase in the share of the county receiving the signal from a black-appeal radio station is estimated to lead to a 7% and 15% rise in the mean levels of the likelihood and intensity of riots, respectively.

Here's where the paper goes a little off the rails though, as the interpretations are not quite intuitive. That result isn't the effect of all black-appeal radio stations, but is the effect of black-appeal radio stations that have 100 percent black-appeal programming. The effect for radio stations with less black-appeal programming is smaller (which is, in itself, an important finding). Also, I believe that in saying "a marginal increase", Bernini is actually referring to a one-unit increase in the radio coverage variable. Since that variable ranges from zero (no coverage) to one (complete coverage), then the correct interpretation of these results is that the difference between a county with no black-appear radio coverage and one with complete coverage, holding other variables constant, is a 7 percent increase in the likelihood of a riot, and a 15 percent increase in riot intensity. Those effects are large, but not necessarily as large as the phrase "a marginal increase" in coverage would imply.

Taking things a bit further, and comparing counties covered by radio stations in the top tertile (the top one-third) of the distribution in terms of the proportion of programming devoted to "news, interviews, religion, and public service" with counties in the middle and bottom tertiles, Bernini finds that:

...the content of the programming does have an important effect on the likelihood of a city experiencing a riot. In fact, it is only in the subset of counties receiving the signal from a 100% black-appeal radio station with a high level of political content programming, that a riot does emerge. The coefficient on the other 100% black-appeal radio stations, albeit positive, does not reach statistical significance at conventional levels. On the other hand... there is not a meaningful difference on the severity of riots between the two categories [low and high political content] of radio stations.

It is interesting that 'more political' radio stations increased the likelihood of a riot occurring, but not the severity of the riot. The radio stations provided the spark that ignited the riot, but after that, it was up to the rioters (and the authorities) what happened.

Bernini then went on to look at variations over time. All of the above analyses were based on the distribution of radio stations in 1964 (and not a year-by-year change). He also has data on the 1968 distribution of radio stations. However, from the paper it is difficult to understand exactly how he treated the panel data, since he had only two annual observations of radio coverage, but eight years of data.

Bernini presents an array of different econometric specifications in the paper. The instrumental variables (IV) analysis relies on a number of instruments. However, one of the instruments is the enrolment in Historically Black Colleges and Universities (HBCUs), measured in 1976. This is likely a good example of what econometricians refer to as a 'bad control', because HBCUs enrolment in the 1970s might have been affected the extent of riots in the 1960s. So, I don't find the IV analyses to be particularly convincing (although perhaps dropping the HBCU variable as an instrument would have little effect - maybe journal reviewers will test this point as this paper moves towards peer-reviewed publication).

Despite those gripes, this is a really interesting paper. It surprised me that the research literature hadn't previously established the importance of this relationship quantitatively. Bernini concludes that:

Black-appeal radio stations significantly changed the fabric of southern counties, through their sizable and robust impact on the likelihood and on the severity of the 1960s race riots.

The role of media (and now, social media) in influencing social movements is important, then as now.

[HT: Marginal Revolution, last year]

The contact hypothesis, and African American GIs in Britain

The contact hypothesis posits that contact between members of majority and minority groups (under certain conditions) can reduce prejudice towards the minority group. In a new test of this hypothesis, this article by David Schindler (Tilburg University) and Mark Westcott (Munich Graduate School of Economics), published in the journal Review of Economic Studies (ungated earlier version here), uses data on African American GIs in Britain. They introduce their paper as:

In this paper, we show that the temporary presence of African American G.I.s... in the UK during World War II persistently reduced anti-minority prejudice amongst the British population. As the base of the US military’s European operation, the UK played host to over one and a half million US troops during World War II. Around 150,000 of these troops were black, serving in segregated units with non-combat support duties such as transport and supply... Many Britons thereby saw and interacted with non-whites for the very first time. Despite pervasive racist attitudes before the war, we show evidence from surveys that these interactions were positive experiences for both the local population and for black G.I.s.

More specifically, they derive a measure of which local areas in England and Wales had military bases where African American support units were stationed. They focus on support units because:

As in previous wars, black soldiers served in racially segregated units, normally under command of white officers. With few exceptions, black troops were limited to non-combat “labour” or “service” roles, most often supply and quartermaster services, transport, food preparation, and sanitation...

Schindler and Westcott then compare areas in England and Wales that were more, or less, exposed to African American troops (controlling for the presence of other support troops) during World War II. They make this comparison in terms of a number of measures that are plausibly associated with racial bias in more recent times, including: (1) membership of the far-right BNP political party (using a membership list published online in 2008); (2) local election results (in terms of the share of votes for the BNP in elections from 2006-2012; or the share of votes for the Conservative Party from 1973-2012); (3) online data from Implicit Attitudes Tests taken by UK residents between 2004 and 2013; and (4) online survey data (from the same source as the IAT data) on 'warmth of feelings' towards African Americans. They find that:

...individuals in areas of the UK where more black troops were posted are more tolerant towards minorities 60 years after the last troops left. First, we show that such areas contain fewer members of the British National Party (BNP), a far-right political party with racist policy positions. Next, we demonstrate that voters in affected areas were less likely to vote Conservative in local elections during times when far-right parties were not widely fielding candidates (until the early 2000s). This effect disappears as the BNP emerged as the strongest far-right party and BNP candidates subsequently received fewer votes in locations where black G.I.s were posted. Finally, we show that there is less implicit anti-black bias in these areas, as measured by Implicit Association Test (IAT) scores, and that those living in locations where black G.I.s were posted report warmer feelings towards black people.

The size of the effects are small. Schindler and Westcott provide some additional analyses where they mathematically manipulate their results to account for the number of generations that have passed between World War II and the present day, and the proportion of the population that might have been exposed to African American GIs. Those adjustments rely on some heroic assumptions, and I don't find them compelling. However, in terms of the contact hypothesis, their analysis separated into rural and urban areas is potentially more important, where they find that:

...the effect of black troops on BNP membership is about twice as large in rural areas as in urban areas. In fact, the effect in urban areas is not statistically significant at any conventional level, despite a larger sample size.

That's consistent with the contact hypothesis because urban areas in England and Wales already had minority populations prior to World War II, so exposure to African American GIs is likely to have a much smaller (in this case, effectively zero) impact. Schindler and Westcott only provide this disaggregated analysis for the BNP membership data - in the other analyses, they simply limit their results to the rural population. Perhaps we are to take from that that the results only hold for rural populations overall.

At the start of this post, I noted that the contact hypothesis requires certain conditions. Schindler and Westcott come back to those conditions in their conclusion:

Taken as a whole, our results provide support for the “contact hypothesis” (Allport, 1954), which postulates that contact between groups can reduce animosity towards the minority group, and show that such effects can persist in geographies across time.

It is interesting to note that the contact which we describe meets many of the conditions that Allport postulated were necessary for intergroup contact to lead to improved relations: equal status, common goals, intergroup cooperation, and personal interaction. Black G.I.s were in the UK for a relatively short period of time, to support the war effort, and did not compete for jobs or public goods with the local population.

Of course, those conditions are not always met. For instance, in many Western countries in recent times, some migrant groups or refugee groups would struggle to meet any of the four conditions. That suggests a role for government or non-government organisations to improve the conditions of contact between these groups and the majority population.

[HT: Marginal Revolution, last year]