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. 

The long persistence of retracted 'zombie' papers

When a paper is retracted by a journal, that understandably tends to negatively impact perceptions of the researcher and the quality of their research (see here). However, these 'zombie' papers can maintain an undead existence for some time, continuing to be cited and used, sometimes uncritically, because retractions take time and because publishers are not good at highlighting when an article has been retracted. They may even continue to accrue further citations even after being retracted. In terms of understanding the effect of retractions on the research system, a key question is: how long does it take for a paper to be retracted?

That is essentially the question that this new article by Marc Joëts (University of Lille) and Valérie Mignon (University of Paris Nanterre), published in the journal Research Policy (open access), addresses. Joëts and Mignon draw on a sample of 25,480 retracted research articles over the period from 1923-2023 (taken from the Retraction Watch database), and look at the factors associated with the time to retraction (that is, the time between first publication and when the article is retracted). First, they find that:

...the average time to retraction is approximately 1045 days (nearly 3 years), but there is significant variability, with a standard deviation of 1225 days... However, some extreme cases take much longer, with the longest retraction occurring 81 years after publication.

Joëts and Mignon use several different forms of survival model to evaluate the relationship between the characteristics of an article and the time to retraction. In this analysis, they find that:

Papers in biomedical and life sciences are generally retracted faster than those in social sciences and humanities, and articles published by predatory publishers are withdrawn more promptly than those from reputable journals. Collaboration intensity and type of misconduct also emerge as significant predictors of retraction delays.

The result for predatory journals seems somewhat surprising. However, Joëts and Mignon suggest that:

...predatory journals often publish papers with evident deficiencies that are more easily detectable by external parties, such as watchdog organizations or institutions, leading to quicker retractions when misconduct is identified. Additionally, the lack of formal editorial procedures in predatory journals may result in a less structured and faster retraction process...

Of course, a faster time to retraction doesn't make predatory journals good. It simply makes them less bad, since they almost certainly are a large source of low-quality research that deserves retraction (Joëts and Mignon don't report the proportion of retractions that come from predatory journals).

In terms of collaboration intensity, articles with more co-authors take longer to retract, presumably because more people are involved in the retraction process, or because disputes over who is to blame may take some time to resolve. For types of misconduct, retractions due to 'data issues' take the longest to occur, while those for 'peer review errors' and 'referencing problems' take the least. That likely reflects that it takes some time for data analyses to be replicated and for problems to surface, whereas problems with referencing are more likely to be readily apparent from a simple reading of the article.

Joëts and Mignon also do a lot of modelling of different editorial policy changes and their effects on the distribution of times to retraction, but I don't think we can read too much into that part of the article, as the results are mostly driven by the assumptions on how the policies affect retractions. Nevertheless, this paper provides some insight into why zombie papers can keep shambling through the literature: retractions are slow and the time to retraction depends on discipline, publisher type, collaboration, and the kind of misconduct involved.

Read more:

• Retractions hurt academic careers, and may be worst for senior researchers

This week in research #110

Here's what caught my eye in research over the past week (a quiet one, after a bumper week last week):

• Khan, Önder, and Ozcan (open access) use the UK’s transition from the Research Assessment Exercise to the Research Excellence Framework in 2009 as a natural experiment, and find that performance-based funding increased female participation in collaborative research by 10.3 percentage points, and that increased female participation coincided with higher research impact, with treated papers receiving 4.79 more citations on average