Is War in Our Nature? What Is Right and What Is Wrong about the Seville Statement on Violence

Is War in Our Nature? What Is Right and What Is Wrong about the Seville Statement on Violence. Azar Gat. Human Nature, June 2019, Volume 30, Issue 2, pp 149–154. https://link.springer.com/article/10.1007/s12110-019-09342-8

Abstract: The Seville Statement on Violence rejected the view that violence and war were in any way rooted in human nature and proclaimed that they were merely a cultural artifact. This paper points out both the valid and invalid parts of the statement. It concludes that the potential for both war and peace is embedded in us. The human behavioral toolkit comprises a number of major tools, respectively geared for violent conflict, peaceful competition, or cooperation, depending on people’s assessment of what will serve them best in any given circumstance. Conflict is only one tool—the hammer—in our diverse behavioral toolkit. However, all three behavioral strategies are not purely learned cultural forms. This naive nature/nurture dichotomy overlooks the heavy and complex biological machinery that is necessary for the working of each of them and the interplay between them. They are all very close under our skin and readily activated because they have all been very handy during our long evolutionary past. At the same time, they are variably calibrated to particular conditions through social learning, which means that their relative use may fluctuate widely. Thus, state authority has tilted the menu of human choices in the direction of the peaceful options in the domestic arena, and changing economic, social, and political conditions may be generating a similar effect in the international arena.

Check also The phylogenetic roots of human lethal violence. José María Gómez et al. Nature volume 538, pages 233–237 (October 13 2016). https://www.bipartisanalliance.com/2018/02/the-phylogenetic-roots-of-human-lethal.html

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Seville Statement on Violence https://en.wikipedia.org/wiki/Seville_Statement_on_Violence
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[The Seville statement] was published during the heyday of Rousseauism, the view that the aboriginal human past, before the advent of agriculture and the state, was nonviolent and peaceful. This view dominated anthropology and culture in general during that time and was itself a reaction against earlier scholarly theories and popular books, such as those by Ardrey (1966), Lorenz (1966), and Morris (1967), which presented war as unique to humans, a primary drive rooted in human nature and erupting irresistibly. Thus, the statement rejected the view that violence and war were in any way rooted in human nature and proclaimed that they were merely a cultural artifact.

In the context of the reaction against Rousseauism, the Seville Statement has been criticized as an example of false-consciousness and the subordination of scholarly integrity to an ideological cause, noble as it may be (e.g., Beroldi 1994; Manson and Wrangham 1987; Pinker 1997). While this criticism is fully justified, I take this opportunity to point out both the valid and invalid parts of the statement. In doing so, I hope to clarify why people actually fight; whether fighting is in human nature, and in what sense; and, consequently, whether violence and war can be eliminated or, more realistically, drastically reduced. Because the biological underpinning of war and peace has been the subject of much confusion and a heated controversy—among neurobiologists, ethologists, anthropologists, psychologists, political scientists and others—it is in great need of clarification. And the root of the confusion is this: People habitually assume that if widespread deadly violence has always been with us, it must be a primary, “irresistible” biological drive that is nearly impossible to suppress. Many find in this conclusion sufficient reason to object to the idea that human fighting is as old as our species, whereas others regard it as compelling evidence that war is inevitable.2 However, both sides are wrong. Contrary to fashionable 1960s notions, traced back to Freud’s latter-day theorizing about a death drive or instinct, thanatos (Freud 1920, 1923, 1930, 1933a, b), violence is not a primary drive that requires release, like hunger or sex. The Swiss or Swedes, for example, who have not fought another country for two centuries, show no special signs of deprivation on this account. But try to deny them food for more than a few hours, or sex, say, for more than a few days, and see what will happen. [...]

On the other hand, the fact that violence is not a primary drive does not mean that we are not hardwired for it. Studies on “warless” pre-state societies usually intend to prove that warfare, being neither primordial nor natural to humankind, was probably a late, and in any case wholly contingent, cultural phenomenon. Margaret Mead’s framing of the problem: “Warfare Is Only an Invention – Not a Biological Necessity” (1940), is the mother of all mistakes. It expresses the widespread assumption that violence must be either a primary drive or entirely learned, whereas in reality, its potential is deeply ingrained in us as a means or tool, ever ready to be employed. People can cooperate, compete peacefully, or use violence to achieve their objectives, depending on what they believe will serve them best in any given circumstance. In cooperation, the parties combine efforts, in principle because the synergic outcome of their efforts divided among them promises greater benefit to each of them than their independent efforts might. In competition, each party strives to outdo the other in order to achieve a desired good by employing whatever means they have at their disposal except direct action against the other. Competition runs parallel. By contrast, in a conflict, direct action against the competitor is taken in order to eliminate it or lessen its ability to engage in the competition (Simmel 1955).

Cooperation, competition, and conflict are the three fundamental forms of social interaction (in addition to avoidance, or zero interaction). People have always had all three options to choose from, and they have always assessed the situation to decide which option, or combination of them, seemed the most promising. Indeed, hunter-gatherer societies have elaborate procedures of conflict resolution, especially within their groups, precisely because conflict, often violent, is an ever-present and often occurring threat. People are well equipped biologically for pursuing any of the above behavioral strategies, with conflict being only one tool, albeit a major one—the hammer—in our diverse behavioral toolkit. Furthermore, Homo sapiens is a social species, whose local and regional groups—universally and uniquely bound together by ties of both kinship and shared cultural codes, including language and customs— cooperate within themselves in a variety of group activities, including fighting. Group fighting is often pursued for the attainment of collective goods, above all hunting territory and other scarce sources of food, as well as reproduction opportunities.

Thus, neither a late invention nor a compulsive inevitability independent of conditions, group fighting is part of our evolution-shaped behavioral menu. It is in this sense that both war and peace are “in our genes,” which accounts for their widely fluctuating prevalence in different sociohistorical contexts. The Seville Statement rightly puts it, in rejection of the view that human biology makes violence and war inescapable: “There is nothing in our neurophysiology that compels us to react violently. . . . We conclude that biology does not condemn humanity to war.” However, the statement fell into the opposite fallacy, proclaiming that warfare “is a product of culture” and solemnly prescribing that “IT IS SCIENTIFICALLY INCORRECT [emphasis in the original] to say that war or any other violent behavior is genetically programmed into our human nature.” The statement carelessly concluded: “Violence is neither in our evolutionary legacy nor in our genes.” In reality, the potential for both war and peace is imbedded in us. Although activated interchangeably and conjointly in response to the overall environmental and sociocultural conditions, all three behavioral strategies—violent conflict, peaceful competition, and cooperation—are not purely learned cultural forms. This naive nature/nurture dichotomy overlooks the heavy and complex biological machinery that is necessary for the working of each of these behavioral strategies and the interplay between them. Certainly, these deep, evolution-shaped patterns are variably calibrated to particular conditions through social learning. However, the reason why they are all there, very close under our skin and readily activated, is that they were all very handy during our long evolutionary history. They all proved highly useful and advantageous, thereby becoming part and parcel of our biological equipment. A number of scholars who have dealt with the question in fact express the view that human societies have always been Janus-faced, interchangeably resorting to both peace and violent conflict. According to Walker (2001:590): “Everywhere we probe into the history of our species we find evidence of a similar pattern of behavior: People have always been capable of both kindness and extreme cruelty.” Burch (2005), documenting the Alaskan Eskimos’ highly belligerent record, also devotes one part of his book to their peaceful interactions. Robert Kelly (2013:158, 165) writes: “To summarize so far, it is not useful to ask whether hunter-gatherers (inclusive of egalitarian and nonegalitarian types) are peaceful or warlike: we find evidence for both among them.” He adds: “Aggression appears in many species, suggesting that it has a long evolutionary history. . . . It is part of our behavioral repertoire, and at times served us well.”

Boehm (2013:333) similarly rejects the view “that there should be an either-or choice between setting up friendly, cooperative relations with neighbors, as opposed to fighting with them.” Both took place, interchangeably, with the same and with different neighbors. Based on his survey of 49 simple hunter-gatherer societies, Boehm (2013:334, also 327, 333) writes: “The finding here is that intergroup conflict and external peacekeeping would both seem to have been prominent in human political life, back to at least 45,000 BP and probably earlier.” Boehm (2013:327) puts both sides of simple hunter-gatherer societies’ behavioral repertoire in a proper perspective: “59 percent of the . . . forager sample has enough lethal intergroup conflict for this to be reported in an ethnography.” He adds (2013:330): “With human foragers, negotiations of some type (including truces and peacemaking) are found in more than half of the . . . societies surveyed (59 percent). However . . . formal and effective peacemaking is reported only for a few of the 29 societies.” 3 Hunter-gatherers suffered far greater violent mortality rates than state societies not because they lacked well-established and partly successful patterns of conflict resolution. It is just that hunter-gatherers’ anarchic condition, the absence of effective coercive authority, limited the effectiveness of these patterns as compared to state societies. Wars have been fought for the attainment of the same objects of human desire that underlie the human motivational system in general—only by violent means, through the use of force. Here I take issue with Pinker’s excellent The Better Angels of Our Nature (2011), with whom I am otherwise in much agreement. “Angels” versus “Demons” in the human behavioral system is an allusion to Lincoln’s first inaugural address and is largely invoked metaphorically. And yet not entirely, because Pinker points to particular human quests such as dominance or ideology as “demons” with which the blame for war rests. Yet, dominance or ideology, no less than the desire for sex, can just as well be counted on the side of the “angels”—when pursued by peaceful means and for peaceful ends. For example, there have always been peaceful ideologies—such as Buddhism, and, in principle, though all too often not in practice, Christianity—which have exercised a considerable pacifying effect.

Furthermore, the distinctions that Pinker draws between different categories of violence respectively related to the above “demons” are also questionable. He cites studies showing that separate parts of the brain may trigger violent behavior, which is true of nearly all behaviors. But this does not mean that all violent behaviors are not subject to, and regulated by, a unified evolutionary calculus originally designed to advance survival and reproduction, the very definition of the evolutionary rationale which Pinker as an evolutionist would surely be the first to accept. The “problem” of war is not these or other human desires. Rather, violence and war occur when the conflictual behavioral strategy is judged to be more promising than peaceful competition and cooperation for achieving scarce objects of human desire. Both our basic desires and the conditions that channel the efforts to fulfil them to the conflictual path are necessary for understanding why war occurs. Thus, the advent of coercive state authority and state policing has tilted the menu of the human behavioral strategies in the direction of the peaceful options in the domestic arena, affecting a great reduction in the rate of killings—in the form of homicide and blood revenge—within societies. Moreover, changing economic, social, and political conditions have been generating a similar effect in the international arena, most notably where a modern liberal economic and political order prevails and peaceful behavioral options become that much more rewarding than the violent option in achieving unprecedented levels of affluence and comfort (Gat 2006, 2017; Goldstein 2011; Morris 2014; Pinker 2011). It is not that modern war has become more costly compared with earlier times, as many believe—it has not; it is peace that has become more rewarding (Gat 2006, 2017). Thus, countries with (non-oil) GDP per capita higher than $20,000 no longer fight each other, nor experience civil war. The most developed parts of the world, such as Western Europe and North America, have become a zone of peace. Within them war is not even contemplated, or feared—the famous “Security Dilemma” has disappeared—a situation which is unparalleled in history. [...]

From 2018... The Sordid Truth behind Degas’s Ballet Dancers

From 2018... The Sordid Truth behind Degas’s Ballet Dancers. Julia Fiore. Artsy, Oct 1 2018. https://www.artsy.net/article/artsy-editorial-sordid-truth-degass-ballet-dancers

Excerpts:

The coteries of young women in flowering tutus who populate the approximately 1,500 paintings, monotypes, and drawings Degas dedicated to the ballet are among the French artist’s most universally beloved artworks. At first glance, Degas has rendered the sort of pretty, innocent world one might associate with a 6-year-old’s first recital. These works actually speak to an insidious culture that would be shocking to contemporary audiences.

Although it enjoyed unprecedented popularity in Degas’s era, the ballet—and the figure of the ballerina—had suffered a demoralizing fate by the late 1800s. Performances had been reduced to tawdry interludes in operas, the spectacle serving as an enticing respite for concertgoers, who could ogle the dancers’ uncovered legs.

These relationships always involved an unbalanced power dynamic. Young female members of the corps de ballet entered the academy as children. Many of these ballerinas-in-training, derisively called “petits rats,” came from working-class or impoverished backgrounds. They often joined the ballet to support their families, working grueling, six-day weeks.

And so dancers’ earnings and careers were beholden to the abonnés prowling backstage. They were expected to submit to the affections of these subscribers, and were frequently encouraged by their own mothers to fan the flames of male desire. Such relationships could offer lifelines for the impoverished dancers; not only did these aristocrats and financiers hold powerful positions in society, their patronage underwrote the opera’s operations.

Men like these had authority over who obtained plum roles and who was cast off. As a girl’s “patron,” he could provide her with an opulent lifestyle, paying for a comfortable apartment or private lessons to elevate her standing in the ballet corps. The brothel culture of the ballet was so pervasive, as historian Lorraine Coons remarks in her essay “Artiste or coquette? Les petits rats of the Paris Opera ballet,” that even successful dancers who did not resort to prostitution would likely have been suspected to have done so anyway.

“People call me the painter of dancing girls,” Degas once explained to Parisian art dealer Ambroise Vollard. “It has never occurred to them that my chief interest in dancers lies in rendering movement and painting pretty clothes.” But Degas didn’t care tremendously about the ballet as an art form, let alone frilly pastel tutus. He endeavored to capture the reality of the ballet that lurked behind the artifice of the cool, carefully constructed choreography.

Life was cruel to French ballet dancers, and they didn’t have it much easier at the hands of Degas himself. Although the artist was known to reject the advances of his models, his callousness manifested in other ways. To capture the physicality and discipline of the dancers, Degas demanded his models pose for hours at a time, enduring excruciating discomfort as they held their contorted positions. He wanted to capture his “little monkey girls,” as he called them, “cracking their joints” at the barre. “I have perhaps too often considered woman as an animal,” he once told the painter Pierre Georges Jeanniot in a moment of revealing honesty.

Degas was undoubtedly a merciless, cantankerous man. He was a misogynist—peers seemed almost afraid of his antagonism towards women—an especially troubling reputation considering the already sexist norms of his society.

We investigate the impact of papal visits to Italian provinces on abortions from 1979 to 2012: Find a 10–20% decrease in abortions that commences in the 3rd month and persists until the 14th month

Papal visits and abortions: evidence from Italy. Egidio Farina, Vikram Pathania. Journal of Population Economics, December 31 2019. https://link.springer.com/article/10.1007/s00148-019-00759-0

Abstract: We investigate the impact of papal visits to Italian provinces on abortions from 1979 to 2012. Using administrative data, we find a 10–20% decrease in the number of abortions that commences in the 3rd month and persists until the 14th month after the visits. However, we find no significant change in the number of live births. A decline in unintended pregnancies best explains our results. Papal visits generate intense local media coverage, and likely make salient the Catholic Church’s stance against abortions. We show that papal visits lead to increased church attendance, and that the decline in abortions is greater when the Pope mentions abortion in his speeches.

Keywords: Abortion Religion Pope Culture Fertility

7 Discussion

To recap, we find a large and statistically significant decrease in abortions, ranging from − 10 to − 20%, that commences about 3 months after the papal visit and persists until the 14th month. We do not find any subsequent uptick in live births. The findings taken together suggest a strong indirect effect—papal visits induce a reduction in unintended pregnancies that starts around the time of the visits and persists for almost 1 year. In contrast, any direct effects of restriction in demand and/or supply of abortion appear to play limited role.

We have been agnostic whether the decrease in unintended pregnancies is being driven by increased abstinence or increased usage of contraceptives; we have bundled both behaviours as contraception. Despite extensive search, we were unable to locate extant Italian household survey data that would allow us to measure how papal visits affect the frequency of sexual intercourse or usage of contraceptives. But even if surveys were available, one would have to be careful in interpreting behavioural changes that would be the net effects of an increased desire for intended pregnancy among some women and also an increased aversion to unintended pregnancy among other women.21

In discussing the indirect effect, two other features of Church doctrine are relevant. First, the Church regards sexual intercourse as a sin if conducted outside sacramental marriage, or, even within wedlock, if deprived of its procreative function. Therefore, during and after papal visits, women might practise more abstinence unless they are planning on getting pregnant. Note that this is separate type of stigma that would independently drive down unintended pregnancies. Second, the Church explicitly discourages contraceptive usage because it breaks the connection between sex and reproduction within marriage and encourages recreational sex out of wedlock.22 For women seeking to minimise the risk of an unintended pregnancy, this poses a dilemma. One way out is to more abstinence. But some may opt for more usage of contraceptives as the “lesser of two evils”. Therefore, a mix of both behaviours—more abstinence and more contraceptive usage—may be driving the reduction in unintended pregnancies.

Thus far, we have assumed that all women have the chance to modify their behaviour in response to papal visits. But there is also a group of women who would have gotten pregnant before the papal visit became salient, and detected the (unintentional) pregnancy shortly before or after the visit. Faced with an increased cost of abortion, some women who would have chosen to abort might opt not to do so. We would then expect to see a contemporaneous drop in abortion, albeit smaller than the subsequent decline, and a spike in births 9 months later. But we find no such effects. It appears that, if already pregnant, papal visits do not change women’s abortion decisions. In other words, even the heightened cost of abortion is less than the cost of an unwanted birth. Looking back at the model in Section 4 (and Table 4), we can infer that among women who choose to abort, most are type II (always-aborters) and only a few are type III (switchers). Earlier, we had drawn the same inference from the lack of increase in births reported in Section 5.2. It is worth noting that the proportion of switchers is endogenous to the change in the cost of abortion; the greater the increase, the higher that proportion. The fact that switchers form only a small proportion suggests that the heightened stigma of abortion from papal visits is not sufficiently large to induce women to switch away from abortions, conditional on being pregnant.

Could our findings be driven by under-reporting?23 Stigma could drive women to switch to “back-street” abortion providers to keep the procedure secret. We cannot rule out under-reporting as a factor but it is unlikely to be the main explanation for our findings. With under-reporting, one would expect to see a drop in abortions contemporaneous with the papal visit.

How do our findings compare to those reported in the recent paper by Bassi and Rasul (2017) on the effect of the papal visit to Brazil in 1991? Their methodology is different from ours. For identification, they exploit the fortuitous timing of the 1991 DHS survey in Brazil which was fielded in the weeks before, during

and after the papal visit. They study how short-run beliefs and long-run behaviour of individuals respond to the papal persuasion. They report a substantial increase in the frequency of sexual intercourse, and a large reduction in the use of contraceptives among women interviewed post-visit. The net effect is a 26% increase in the frequency of unprotected sex that drives a positive fertility response with a spike in births 9 months post-visit. In contrast, in the Italian setting, we find no net effect on births. One plausible explanation for the difference is that a papal visit to Brazil is a much bigger event because it is so rare. This could have much larger effects on the perceived costs of abortion as well as on fertility preferences of Brazilian women.

As already noted, abortion ratios are highest among teenagers (see Table 2). We test how teen abortions respond to papal visits. The findings are reported in the Appendix A-Table 15. The effect on abortions is smaller for teenagers; there is a statistically significant decline of about 10% in the third quarter following the visit but no significant declines in other periods. We also test for the impact separately by age group, education level and marital status. The results are summarised in Appendix A, Figs. 9, 10 and 11. In general, the effects appear similar across groups except for a few differences. The decline appears to be larger for married women than for unmarried ones, and to a lesser degree, for less educated women versus higher educated ones. The finding of smaller effects for unmarried women is not surprising given what we find for teens, who likely make up a big part of the unmarried group. However, when we use pooled regressions to explicitly test whether the difference between married versus unmarried is statistically significant, we cannot reject the null of similar sized effects. The same is true for the difference by education level.

7.1 Is there a pattern to papal visits?

We ask whether papal visits are planned in response to underlying trends in abortions or religiosity. The concern is that if the Pope is more likely to visit provinces that are exhibiting a trend of relatively increasing religiosity (and concurrently a decreasing relative abortion rate), our estimate of the impact is not ‘causal’ but merely reflects this underlying trend.

First, we note that our identification strategy relies on the precise timing of the event, and in the preferred specifications, we control for province-specific quadratic time trends. Reassuringly, we find no discernible effect in the quarters (or months) preceding the event. Hence, we would argue that our estimates can be credibly inferred as causal.

Nevertheless, the time and place of a papal visit are unlikely to be random.24 The decision made by the Pope to visit a place could be driven by specific factors, e.g. motivated by the desire to reverse a general decline in religiosity among the local population that leads to an increasing abortion rate. If so, a papal visit may coincide with other (unobserved) ongoing activities by the Church in that province and during that time that could be driving our results.

We test whether the Pope is more likely to visit a province or region that exhibits an increase in the number of abortions or a decrease in the number of births or in the level of religiosity in the 1, 2 or 5 years preceding the papal event, using the following specification:

Pr(Pope Eventp,y=1)=α+β<percent>ΔiZp,y−1+γp×t+δp×t2+θp+θa+up,y$$Pr({\text{Pope Event}}_{p,y}=1)=\alpha +\beta <percent>{\Delta }_i{Z}_{p,y-1}+{\gamma }_p\times t+{\delta }_p\times t^2+{\theta }_p+{\theta }_a+u_{p,y}$$

(3)

where Pope Eventp,y is a binary indicator taking the value 1 if province p was visited by the Pope in year y; %ΔiZp,y− 1 represents the percentage change in the number of abortions, births or in the average religiosity indicator, as defined in Section 6.3, over the 1, 2 or 5 years preceding the visit of the Pope in province p, γp × t and δp × t2 are provincial yearly trends; 𝜃p and 𝜃y are province and year fixed effects.25

Table 10 displays the results from estimating Eq. 3. Starting from panel A, the papal visits do not respond to any pre-trend in the number of abortions registered in the 1, 2 or 5 years preceding the visit to a specific province. We repeat the same exercise to test whether the papal visits are influenced by changes in births (panel B) or religiosity (panel C). Also, in these cases, no statistically significant effect is detected. Overall, the results bolster confidence that our main findings are causal effects of papal visits and not merely picking up underlying trends in local religiosity and Church activities.

Behavioral correlates in twin studies: There was a moderate genetic influence on subjective sleep quality and sleep duration

Twin studies of subjective sleep quality and sleep duration, and their behavioral correlates: Systematic review and meta-analysis of heritability estimates. Juan J Madrid-Valero et al. Neuroscience & Biobehavioral Reviews, December 30 2019. https://doi.org/10.1016/j.neubiorev.2019.12.028

Highlights
• There was a moderate genetic influence on subjective sleep quality and sleep duration.
• There was substantial heterogeneity across studies.
• Heritability did not differ by geographical zone.
• Age and sex were not significant moderators of the heritability of subjective sleep quality or sleep duration.
• Genetic factors played a role in the associations between sleep variables and other factors.

Abstract: Twin studies have shown that a substantial proportion of the variance for sleep variables is due to genetic factors. However, there is still considerable heterogeneity among research reports. Our main objectives were to: 1) Review the twin literature regarding sleep quality and duration, as well as their behavioural correlates; 2) Estimate the mean heritability of subjective sleep quality and sleep duration; 3) Assess heterogeneity among studies on these topics; and 4) Search for moderator variables. Two parallel meta-analyses were carried out for sleep quality and sleep duration. Seventeen articles were included in the meta-analysis. Mean MZ correlations were consistently higher than DZ correlations. A mean heritability of 0.31 (95% CI: 0.20, 0.41) was found for subjective sleep quality (range: 0-0.43) and 0.38 (95% CI: 0.16, 0.56) for sleep duration (range: 0-1). Heterogeneity indexes were significant for both sleep quality (I2 = 98.77, p < .001) and sleep duration (I2 = 99.73, p < .001). The high heterogeneity warrants further research considering possible moderators that may affect heritability.

Keywords: HeritabilityMeta-AnalysisTwinSleep qualitySleep duration

Impacts of market integration on the development of American manufacturing, as railroads expanded through the latter half of the XIX century: Much larger aggregate economic gains than previous estimates

Railroads, Reallocation, and the Rise of American Manufacturing. Richard Hornbeck, Martin Rotemberg. NBER Working Paper No. 26594, December 2019. https://www.nber.org/papers/w26594

Program: We examine impacts of market integration on the development of American manufacturing, as railroads expanded through the latter half of the 19th century. Using new county-by-industry data from the Census of Manufactures, we estimate substantial impacts on manufacturing productivity from relative increases in county market access as railroads expanded. In particular, the railroads increased economic activity in marginally productive counties. Allowing for the presence of factor misallocation generates much larger aggregate economic gains from the railroads than previous estimates. Our estimates highlight how broadly-used infrastructure or technologies can have much larger economic impacts when there are inefficiencies in the economy.

VI Interpretation

We estimate that the railroads substantially increased the scale of the United States’ economy: increasing the production and use of materials, spurring increased capital investment,
and encouraging population growth. The economic consequences of this expansion are substantially greater than previously considered because, in most counties, the value marginal
products of materials, capital, and labor were greater than their marginal costs. We do not
estimate that railroads reduced these market distortions, whether due to firm markups or
input frictions, but the railroads generated substantial economic gains by encouraging the
expansion of an economy with market distortions.
We calculate that aggregate productivity would have been 25% lower in 1890 in the
absence of the railroads, through declines in reallocative efficiency alone. We assume that
technical efficiency would have been unchanged in the counterfactuals, but this decline in
reallocative efficiency is equivalent to a 25% decline in technical efficiency (or total factor
productivity, TFP). It is challenging to estimate aggregate TFP growth, with the proper
price deflators, but estimates suggest that annual TFP growth was approximately 0.37%
from 1855 to 1890 and 1.24% from 1890 to 1927 (Abramovitz and David, 1973). That is,
the railroads effectively contributed 31 years worth of technological innovation, by driving
increases in reallocative efficiency.79
The railroads’ 25% impact on productivity was worth 25% of GDP in 1890, or $3 billion
in 1890 dollars. As a comparison, the estimated cost of the railroad network in 1890 was $8
billion (Adams, 1895). We estimate that the railroads generated an annual private return
of 3.5% in 1890,80 which increases to an annual social return of 7.5% – 8.3% once including
estimates from Fogel (1964) or Donaldson and Hornbeck (2016) and increases to 43% when
also including our estimated impact on productivity.81 These estimates imply that the
railroad sector was capturing roughly 8% of its social return in 1890.
Our estimated increases in productivity do not include the direct benefits of the railroads
from decreasing resources spent on transportation. To see this, consider that we would mechanically estimate no impact on productivity from the railroads if there were no differences
between value marginal product and marginal cost, whereas the economy would still benefit
through decreases in transportation costs. In our model, those decreases in transportation
costs are capitalized into higher land values.
Donaldson and Hornbeck (2016) estimate that agricultural land values would have fallen
by 60% without the railroad network, which, multiplying by an interest rate, generates
annual economic losses equal to 3.2% of GDP. The total loss of all agricultural land would
only generate annual economic losses equal to 5.35% of GDP, so an analysis of agricultural
land values could never find larger economic impacts.82
The crucial difference in our approaches is that Donaldson and Hornbeck (2016) assume
an efficient economy, in which value marginal product is equal to marginal cost, such that all
output value is paid to factors. By contrast, our estimated increases in reallocative efficiency
reflect the creation of output value that is not paid to factors. In both of our analyses, the
railroads increase the scale of the US economy, but because we allow for the marginal value
of product to exceed marginal costs, this increase in economic activity generates surplus
or “profit” that is reflected in aggregate productivity growth rather than increases in land
values. Further, our estimated impacts on productivity do not include any economic gains
reflected in increased factor payments, and so our estimated impact on productivity is in
addition to impacts on land value.
A general implication for measuring economic incidence is that factor payments do not
include all economic gains when there are market distortions. More inelastically supplied
factors will bear more economic incidence, but there are additional economic gains that are
not captured by factor payments. We show that these additional economic gains can be
substantively large, particularly when new infrastructure investment or new technologies are
broadly used and encourage broad expansion of economic activity.
The additional economic gains, from decreasing resources spent on transportation, could
instead be measured directly by calculating the decreases in transportation costs using the
railroads instead of the waterways. This is precisely the social savings calculation in Fogel
(1964), which implies that our estimated impact on productivity is in addition to Fogel’s
estimate of 2.7% of GDP.
In considering why Fogel’s estimates do not include our estimated economic gains, we
highlight the importance of resource misallocation in welfare analysis more generally. Fogel
(1964) proposes a social savings calculation to bound the economic gains from the railroads.
Fogel focuses on the transportation sector, and looks to calculate the additional cost from
using waterways to transport goods instead of the railroads. This calculation is closely
related to aggregate productivity in the transportation sector, measured as revenue minus
costs: for transporting the same quantity of goods (fixing revenue), calculating the increase
in costs without the railroads.83
David (1969) critiques Fogel’s calculations on several grounds, but much of this critique
is essentially calling attention to Fogel’s implicit assumption that value marginal product is
equal to marginal cost.84 This assumption is required for the increase in transportation costs
without the railroads to equal the value lost from decreased production in non-transportation
sectors. David (1969) proposes that this assumption would be violated by increasing returns
to scale, and Fogel (1979) responds by disputing the empirical magnitude of increasing
returns to scale.85 Fogel (1979) also makes this assumption more explicit: that in nontransportation sectors, firms’ value marginal product is equal to their marginal cost.
Our analysis relaxes this assumption, and estimates the economic consequences from
a broader range of market distortions, which restates the above critique by David (1969).
Rather than appealing to increasing returns to scale, we allow for a wide variety of distortions that can drive a wedge between the social benefit and private cost of firms expanding
production (e.g., firm markups, credit constraints, taxes and regulation, imperfect property
rights).86 The railroads decrease transportation costs, effectively subsidizing the expansion
of economic activities throughout the economy that have a positive social return (i.e., whose
value marginal product exceeds their marginal cost).
Fogel (1964, 1979) emphasizes that assuming an inelastic demand for transportation
provides an upper bound estimate on the railroads’ impacts, for the social savings calculation,
but the opposite is true in the presence of market distortions. A greater elasticity of demand
for transportation magnifies the economic impacts of the railroads by yielding greater changes
in activities whose value marginal product exceeds marginal cost across other sectors in the
economy. Fogel does not consider the indirect losses in other sectors due to reductions in
transported goods, because he aims to calculate the costs of maintaining the same levels of
transportation, but it is precisely because transportation would fall that there are such large
indirect losses in other sectors.87
More generally, there is an analogous need to consider resource misallocation in partial
equilibrium welfare analysis. Harberger (1964) lays the foundation for much welfare analysis
in economics, using the example of calculating the economic cost of a tax, making a powerful
assumption that there are no other distortions in the economy. This assumption means that
it is not necessary to consider how a marginal tax affects other activities, which reflect
only small welfare “triangles,” and the welfare effects of the tax are largely captured by the
demand curve for the taxed activity.88 Harberger (1964) makes this assumption clear, and
notes that it probably has the effect of understating the true cost of a tax, but this assumption
is often overlooked in applications due to its substantial analytical convenience.89 In Fogel’s
application, when analyzing the impacts of a higher transportation cost (similar to a higher
tax), the demand curve for transported goods is used to capture the welfare effects, and the
mistake is to not consider impacts from resulting changes in other activities.
Our estimated impacts of the railroads are a reminder that indirect effects on other
economic activities can generate substantial economic benefits, which are missed in partial
equilibrium welfare analysis. When there is resource misallocation, such as due to firm
markups or capital constraints, and other activities are under-provided then there are firstorder welfare gains from their encouragement. Only in a special case, when there are no
market distortions and other economic activities are efficient, can we invoke the envelope
theorem and consider only the direct economic effects

British adolescent twins study: Contact with the justice system—through spending a night in jail/prison, being issued an anti‐social behaviour order (ASBO), or having an official record—promotes delinquency

Does contact with the justice system deter or promote future delinquency? Results from a longitudinal study of British adolescent twins. Ryan T. Motz et al. Criminology, December 29 2019. https://doi.org/10.1111/1745-9125.12236

Abstract: What impact does formal punishment have on antisocial conduct—does it deter or promote it? The findings from a long line of research on the labeling tradition indicate formal punishments have the opposite‐of‐intended consequence of promoting future misbehavior. In another body of work, the results show support for deterrence‐based hypotheses that punishment deters future misbehavior. So, which is it? We draw on a nationally representative sample of British adolescent twins from the Environmental Risk (E‐Risk) Longitudinal Twin Study to perform a robust test of the deterrence versus labeling question. We leverage a powerful research design in which twins can serve as the counterfactual for their co‐twin, thereby ruling out many sources of confounding that have likely impacted prior studies. The pattern of findings provides support for labeling theory, showing that contact with the justice system—through spending a night in jail/prison, being issued an anti‐social behaviour order (ASBO), or having an official record—promotes delinquency. We conclude by discussing the impact these findings may have on criminologists’ and practitioners’ perspective on the role of the juvenile justice system in society.

Keywords: delinquency     family fixed effects     labeling     specific deterrence     twins

4 DISCUSSION AND CONCLUSION

We sought to conduct a rigorous test between deterrence and labeling hypotheses. Drawing on data from a nationally representative and longitudinal birth cohort of British adolescent twins, we found that contact with the justice system—through spending a night in jail/prison, being issued an ASBO, or having an official crime record—promotes misbehavior, which supports the labeling hypothesis. With this in mind, we highlight four contributions from this study that warrant consideration. We then discuss some of the broader implications our findings might have for the justice system.

4.1 Contributions

First, we followed the call of previous research (see, e.g., Farrington, 2003; Murray et al., 2009; Piquero et al., 2011; Pogarsky, 2002) and employed one of the most rigorous nonexperimental methodological designs capable of accounting for a wide range of selection effects and confounding influences. Using the family fixed‐effects model (Kohler et al., 2011), we leveraged nationally representative twin data to take advantage of the natural experiment that twins provide by the fact that they share their family environment and their genetic endowments. Such family effects work to make twins similar to one another. By focusing on within‐twin pair differences, then, we were able to rule out the effects of these family environments and genetic influences, providing us the opportunity to glean some of the most precise estimates for the impact of justice system contact on future behavior. In doing so, we have demonstrated that twin samples and methods have utility for criminological theory testing that reaches beyond the typical strategy of estimating heritability (see Moffitt & Beckley, 2015).
A second feature of this study is that we drew on three separate measures—two that were self‐reported and one obtained from official Ministry of Justice records—of justice system contact. The pattern of findings was substantively consistent across these specifications, providing robust support for the labeling hypothesis. The findings across such forms of contact demonstrate that even sanctions that do not penetrate far into the justice system are potentially criminogenic, an outcome that has important implications for policy. Of interest to labeling theorists, the effect of ASBO was found to be a substantively strong predictor of later misbehavior. This is important because, in our opinion, the ASBO represented an archetypal label—recall that it was not intended to be punitive; rather, it was intended to be preventative by identifying those who were at risk of bad behavior. It was also intended to be a public label, and that is exactly the effect it seemed to have had. We believe the findings from the ASBO analysis are particularly revealing given this context even though ASBOs are no longer in use.
Third, we analyzed as an outcome broad‐spectrum delinquency rather than an official outcome (e.g., rearrest or reconviction) that is more commonly assessed in the deterrence and labeling literatures. The results for justice system outcomes like rearrest may be biased because individuals who experience such contact are often at an increased risk for future contact with the justice system simply because they are known by its actors, such as arresting police officers. An outcome variable such as delinquency, therefore, allowed for us to observe change in behavior that is not biased by the actions of justice system actors. Furthermore, by relying on self‐reported delinquency, we can capture delinquent and illegal acts done by the participants that may not be known to the justice system, which would not be captured if we were to rely on official records. For these reasons, we believe the focus on self‐reported delinquency represents an important contribution to the labeling literature.
Fourth, we relied on a sample of individuals who are within the primary age range for engaging in antisocial behavior (i.e., 18‐year‐olds). This is important as it captures the impact of justice system contact for those who are peaking in their criminal careers. The impact of such contact for this population is notable as the increase in problem behavior may lead to a downward spiral of cumulative continuity for certain youth (e.g., Caspi, Bem, & Elder, 1989; Moffitt, 1993; Nagin & Paternoster, 1991; Sampson & Laub, 1992). Yet it should be noted that, at this time, we cannot observe how the increases in scores for delinquency will go on to affect participants’ criminal trajectories. Follow‐up analyses of this cohort with future phases of data collection will be better suited to answer that question.

4.3 Broader considerations

With the contributions of this study in mind, we now consider the broader substantive, theoretical, and ethical concerns that may stem from them. Particularly, we focus on the concerns revolving around the role of the justice system and its impact on juveniles. With evidence that the impact of contact with the justice system is a substantively negative one, an interesting question can be raised: Why would we have expected contact with the justice system to have a deterrent effect? Perhaps if justice system contact caused people to “fear their future self,” we would see deterrent effects (Paternoster & Bushway, 2009). But what we found is that justice system contact may have the opposite effect—rather than causing people to fear their future self, it may cause them to lose confidence in their future self. Therefore, the current system may work in a way that does not motivate individuals to conform to the norms of society. Instead, it leads young people to doubt their ability to get themselves out of the hole they have dug.
This makes sense when we consider the real‐life consequences of spending time in jail—the event itself is often embarrassing and shameful. Typically, it consists of (at least) an overnight stay followed by a visit with a judge the next morning. The family often has to get involved for the young person to be released back into the community, which then causes anger, hostility, and embarrassment among family members. Given that family is an important part of the desistance process, weakening those social bonds is unlikely to have a crime‐reducing effect. Furthermore, these reactions are often extended out to other interpersonal relationships in different settings, and as these relationships are ruined, prosocial connections are further attenuated, pushing the labeled adolescent further away from conventional society.
What does this mean for the justice system as it is currently constructed? We do not believe our findings show support for a shift to nonintervention. Rather, we believe it is important for the justice system and its actors to recognize the potentially negative impact it has. The public should be aware that the system is for the purpose of justice and retribution and that a utilitarian outcome such as specific deterrence is unlikely. With this in mind, our findings can be used to extend two policy recommendations.
First, although not a test of these hypotheses, we believe our findings fall in line with the arguments of the principles of effective intervention (see Andrews, 1995; Bonta & Andrews, 2016; Gendreau, 1996), which propose low‐risk offenders should not be funneled through official justice system channels. There should be diversionary programs set up for these types of offenders so that they may be able to avoid the labeling process. A metaphor might help explain: Medical doctors do not send a patient suffering from a cold to the emergency room. Even though the patient can certainly get treatment there, the visit would likely be counterproductive as the patient would be exposed to far more harmful viruses and diseases that may ultimately result in worse health. Study findings have repeatedly shown that when low‐risk offenders are brought into the justice system, the outcome is almost exclusively iatrogenic (e.g., Gatti, Tremblay, & Vitaro, 2009; Lowenkamp, Latessa, & Holsinger, 2006; Nagin, Cullen, & Jonson, 2009; Sperber, Latessa, & Makarios, 2013).
Second, our findings do not show support for fewer (or more) juvenile arrests. But they do indicate that if arrest rates are going to be maintained at their current level (or if they are to be heightened), then there should be a concerted effort toward offsetting the negative pathways that they create. If policy makers gain an understanding of these processes and pathways, they can develop and implement strategies to prevent labeling effects. Only then will the system have a chance of deterring criminal activity by way of contact with the offender.