nhaliday + regression   69

Is the bounty system effective? - Meta Stack Exchange
https://math.meta.stackexchange.com/questions/20155/how-effective-are-bounties
could do some kinda econometric analysis using the data explorer to determine this once and for all: https://pinboard.in/u:nhaliday/b:c0cd449b9e69
maybe some kinda RDD in time, or difference-in-differences?
I don't think answer quality/quantity by time meets the common trend assumption for DD, tho... Questions that eventually receive bounty are prob higher quality in the first place, and higher quality answers accumulate more and better answers regardless. Hmm.
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22 days ago by nhaliday
Who We Are | West Hunter
I’m going to review David Reich’s new book, Who We Are and How We Got Here. Extensively: in a sense I’ve already been doing this for a long time. Probably there will be a podcast. The GoFundMe link is here. You can also send money via Paypal (Use the donate button), or bitcoins to 1Jv4cu1wETM5Xs9unjKbDbCrRF2mrjWXr5. In-kind donations, such as orichalcum or mithril, are always appreciated.

This is the book about the application of ancient DNA to prehistory and history.

height difference between northern and southern europeans: https://westhunt.wordpress.com/2018/03/29/who-we-are-1/
mixing, genocide of males, etc.: https://westhunt.wordpress.com/2018/03/29/who-we-are-2-purity-of-essence/
rapid change in polygenic traits (appearance by Kevin Mitchell and funny jab at Brad Delong ("regmonkey")): https://westhunt.wordpress.com/2018/03/30/rapid-change-in-polygenic-traits/
schiz, bipolar, and IQ: https://westhunt.wordpress.com/2018/03/30/rapid-change-in-polygenic-traits/#comment-105605
Dan Graur being dumb: https://westhunt.wordpress.com/2018/04/02/the-usual-suspects/
prediction of neanderthal mixture and why: https://westhunt.wordpress.com/2018/04/03/who-we-are-3-neanderthals/
New Guineans tried to use Denisovan admixture to avoid UN sanctions (by "not being human"): https://westhunt.wordpress.com/2018/04/04/who-we-are-4-denisovans/
also some commentary on decline of Out-of-Africa, including:
"Homo Naledi, a small-brained homonin identified from recently discovered fossils in South Africa, appears to have hung around way later that you’d expect (up to 200,000 years ago, maybe later) than would be the case if modern humans had occupied that area back then. To be blunt, we would have eaten them."

Live Not By Lies: https://westhunt.wordpress.com/2018/04/08/live-not-by-lies/
Next he slams people that suspect that upcoming genetic genetic analysis will, in most cases, confirm traditional stereotypes about race – the way the world actually looks.

The people Reich dumps on are saying perfectly reasonable things. He criticizes Henry Harpending for saying that he’d never seen an African with a hobby. Of course, Henry had actually spent time in Africa, and that’s what he’d seen. The implication is that people in Malthusian farming societies – which Africa was not – were selected to want to work, even where there was no immediate necessity to do so. Thus hobbies, something like a gerbil running in an exercise wheel.

He criticized Nicholas Wade, for saying that different races have different dispositions. Wade’s book wasn’t very good, but of course personality varies by race: Darwin certainly thought so. You can see differences at birth. Cover a baby’s nose with a cloth: Chinese and Navajo babies quietly breathe through their mouth, European and African babies fuss and fight.

Then he attacks Watson, for asking when Reich was going to look at Jewish genetics – the kind that has led to greater-than-average intelligence. Watson was undoubtedly trying to get a rise out of Reich, but it’s a perfectly reasonable question. Ashkenazi Jews are smarter than the average bear and everybody knows it. Selection is the only possible explanation, and the conditions in the Middle ages – white-collar job specialization and a high degree of endogamy, were just what the doctor ordered.

Watson’s a prick, but he’s a great prick, and what he said was correct. Henry was a prince among men, and Nick Wade is a decent guy as well. Reich is totally out of line here: he’s being a dick.

Now Reich may be trying to burnish his anti-racist credentials, which surely need some renewal after having pointing out that race as colloquially used is pretty reasonable, there’s no reason pops can’t be different, people that said otherwise ( like Lewontin, Gould, Montagu, etc. ) were lying, Aryans conquered Europe and India, while we’re tied to the train tracks with scary genetic results coming straight at us. I don’t care: he’s being a weasel, slandering the dead and abusing the obnoxious old genius who laid the foundations of his field. Reich will also get old someday: perhaps he too will someday lose track of all the nonsense he’s supposed to say, or just stop caring. Maybe he already has… I’m pretty sure that Reich does not like lying – which is why he wrote this section of the book (not at all logically necessary for his exposition of the ancient DNA work) but the required complex juggling of lies and truth required to get past the demented gatekeepers of our society may not be his forte. It has been said that if it was discovered that someone in the business was secretly an android, David Reich would be the prime suspect. No Talleyrand he.

https://westhunt.wordpress.com/2018/04/12/who-we-are-6-the-americas/
The population that accounts for the vast majority of Native American ancestry, which we will call Amerinds, came into existence somewhere in northern Asia. It was formed from a mix of Ancient North Eurasians and a population related to the Han Chinese – about 40% ANE and 60% proto-Chinese. Is looks as if most of the paternal ancestry was from the ANE, while almost all of the maternal ancestry was from the proto-Han. [Aryan-Transpacific ?!?] This formation story – ANE boys, East-end girls – is similar to the formation story for the Indo-Europeans.

https://westhunt.wordpress.com/2018/04/18/who-we-are-7-africa/
In some ways, on some questions, learning more from genetics has left us less certain. At this point we really don’t know where anatomically humans originated. Greater genetic variety in sub-Saharan African has been traditionally considered a sign that AMH originated there, but it possible that we originated elsewhere, perhaps in North Africa or the Middle East, and gained extra genetic variation when we moved into sub-Saharan Africa and mixed with various archaic groups that already existed. One consideration is that finding recent archaic admixture in a population may well be a sign that modern humans didn’t arise in that region ( like language substrates) – which makes South Africa and West Africa look less likely. The long-continued existence of homo naledi in South Africa suggests that modern humans may not have been there for all that long – if we had co-existed with homo naledi, they probably wouldn’t lasted long. The oldest known skull that is (probably) AMh was recently found in Morocco, while modern humans remains, already known from about 100,000 years ago in Israel, have recently been found in northern Saudi Arabia.

While work by Nick Patterson suggests that modern humans were formed by a fusion between two long-isolated populations, a bit less than half a million years ago.

So: genomics had made recent history Africa pretty clear. Bantu agriculuralists expanded and replaced hunter-gatherers, farmers and herders from the Middle East settled North Africa, Egypt and northeaat Africa, while Nilotic herdsmen expanded south from the Sudan. There are traces of earlier patterns and peoples, but today, only traces. As for questions back further in time, such as the origins of modern humans – we thought we knew, and now we know we don’t. But that’s progress.

https://westhunt.wordpress.com/2018/04/18/reichs-journey/
David Reich’s professional path must have shaped his perspective on the social sciences. Look at the record. He starts his professional career examining the role of genetics in the elevated prostate cancer risk seen in African-American men. Various social-science fruitcakes oppose him even looking at the question of ancestry ( African vs European). But they were wrong: certain African-origin alleles explain the increased risk. Anthropologists (and human geneticists) were sure (based on nothing) that modern humans hadn’t interbred with Neanderthals – but of course that happened. Anthropologists and archaeologists knew that Gustaf Kossina couldn’t have been right when he said that widespread material culture corresponded to widespread ethnic groups, and that migration was the primary explanation for changes in the archaeological record – but he was right. They knew that the Indo-European languages just couldn’t have been imposed by fire and sword – but Reich’s work proved them wrong. Lots of people – the usual suspects plus Hindu nationalists – were sure that the AIT ( Aryan Invasion Theory) was wrong, but it looks pretty good today.

Some sociologists believed that caste in India was somehow imposed or significantly intensified by the British – but it turns out that most jatis have been almost perfectly endogamous for two thousand years or more…

It may be that Reich doesn’t take these guys too seriously anymore. Why should he?

varnas, jatis, aryan invastion theory: https://westhunt.wordpress.com/2018/04/22/who-we-are-8-india/

europe and EEF+WHG+ANE: https://westhunt.wordpress.com/2018/05/01/who-we-are-9-europe/

https://www.nationalreview.com/2018/03/book-review-david-reich-human-genes-reveal-history/
The massive mixture events that occurred in the recent past to give rise to Europeans and South Asians, to name just two groups, were likely “male mediated.” That’s another way of saying that men on the move took local women as brides or concubines. In the New World there are many examples of this, whether it be among African Americans, where most European ancestry seems to come through men, or in Latin America, where conquistadores famously took local women as paramours. Both of these examples are disquieting, and hint at the deep structural roots of patriarchal inequality and social subjugation that form the backdrop for the emergence of many modern peoples.
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march 2018 by nhaliday
Effects of Education on Political Opinions: An International Study | International Journal of Public Opinion Research | Oxford Academic
Education and Political Party: The Effects of College or Social Class?: https://www.jstor.org/stable/2778029
The impact of education on political ideology: Evidence from European compulsory education reforms: https://www.sciencedirect.com/science/article/pii/S0272775716301704
correlation is with leftism, causal effect is shift to right

Greg thinks there are some effects: https://pinboard.in/u:nhaliday/b:5adca8f16265

https://twitter.com/GarettJones/status/964209775419457536
https://archive.is/oFELz
https://archive.is/f1DBF
https://archive.is/5iiqn

http://econlog.econlib.org/archives/2008/12/education_ideol.html

https://twitter.com/pseudoerasmus/status/963451867912130561
https://archive.is/sHI7g
https://archive.is/B5Gdv
https://archive.is/hFERC
https://archive.is/8IUDm
Bryan Caplan has written a very persuasive book suggesting that retention/transfer of learning is very low. how do we know it’s not the same with the “PoMo ethos”
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february 2018 by nhaliday
Estimation of effect size distribution from genome-wide association studies and implications for future discoveries
We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn’s disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15–20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries.

later paper:
Distribution of allele frequencies and effect sizes and their interrelationships for common genetic susceptibility variants: http://www.pnas.org/content/108/44/18026.full

Recent discoveries of hundreds of common susceptibility SNPs from genome-wide association studies provide a unique opportunity to examine population genetic models for complex traits. In this report, we investigate distributions of various population genetic parameters and their interrelationships using estimates of allele frequencies and effect-size parameters for about 400 susceptibility SNPs across a spectrum of qualitative and quantitative traits. We calibrate our analysis by statistical power for detection of SNPs to account for overrepresentation of variants with larger effect sizes in currently known SNPs that are expected due to statistical power for discovery. Across all qualitative disease traits, minor alleles conferred “risk” more often than “protection.” Across all traits, an inverse relationship existed between “regression effects” and allele frequencies. Both of these trends were remarkably strong for type I diabetes, a trait that is most likely to be influenced by selection, but were modest for other traits such as human height or late-onset diseases such as type II diabetes and cancers. Across all traits, the estimated effect-size distribution suggested the existence of increasingly large numbers of susceptibility SNPs with decreasingly small effects. For most traits, the set of SNPs with intermediate minor allele frequencies (5–20%) contained an unusually small number of susceptibility loci and explained a relatively small fraction of heritability compared with what would be expected from the distribution of SNPs in the general population. These trends could have several implications for future studies of common and uncommon variants.

...

Relationship Between Allele Frequency and Effect Size. We explored the relationship between allele frequency and effect size in different scales. An inverse relationship between the squared regression coefficient and f(1 − f) was observed consistently across different traits (Fig. 3). For a number of these traits, however, the strengths of these relationships become less pronounced after adjustment for ascertainment due to study power. The strength of the trend, as captured by the slope of the fitted line (Table 2), markedly varies between traits, with an almost 10-fold change between the two extremes of distinct types of traits. After adjustment, the most pronounced trend was seen for type I diabetes and Crohn’s disease among qualitative traits and LDL level among quantitative traits. In exploring the relationship between the frequency of the risk allele and the magnitude of the associated risk coefficient (Fig. S4), we observed a quadratic pattern that indicates increasing risk coefficients as the risk-allele frequency diverges away from 0.50 either toward 0 or toward 1. Thus, it appears that regression coefficients for common susceptibility SNPs increase in magnitude monotonically with decreasing minor-allele frequency, irrespective of whether the minor allele confers risk or protection. However, for some traits, such as type I diabetes, risk alleles were predominantly minor alleles, that is, they had frequencies of less than 0.50.
pdf  nibble  study  article  org:nat  🌞  biodet  genetics  population-genetics  GWAS  QTL  distribution  disease  cancer  stat-power  bioinformatics  magnitude  embodied  prediction  scale  scaling-up  variance-components  multi  missing-heritability  effect-size  regression  correlation  data 
november 2017 by nhaliday
Global Evidence on Economic Preferences
- Benjamin Enke et al

This paper studies the global variation in economic preferences. For this purpose, we present the Global Preference Survey (GPS), an experimentally validated survey dataset of time preference, risk preference, positive and negative reciprocity, altruism, and trust from 80,000 individuals in 76 countries. The data reveal substantial heterogeneity in preferences across countries, but even larger within-country heterogeneity. Across individuals, preferences vary with age, gender, and cognitive ability, yet these relationships appear partly country specific. At the country level, the data reveal correlations between preferences and bio-geographic and cultural variables such as agricultural suitability, language structure, and religion. Variation in preferences is also correlated with economic outcomes and behaviors. Within countries and subnational regions, preferences are linked to individual savings decisions, labor market choices, and prosocial behaviors. Across countries, preferences vary with aggregate outcomes ranging from per capita income, to entrepreneurial activities, to the frequency of armed conflicts.

...

This paper explores these questions by making use of the core features of the GPS: (i) coverage of 76 countries that represent approximately 90 percent of the world population; (ii) representative population samples within each country for a total of 80,000 respondents, (iii) measures designed to capture time preference, risk preference, altruism, positive reciprocity, negative reciprocity, and trust, based on an ex ante experimental validation procedure (Falk et al., 2016) as well as pre-tests in culturally heterogeneous countries, (iv) standardized elicitation and translation techniques through the pre-existing infrastructure of a global polling institute, Gallup. Upon publication, the data will be made publicly available online. The data on individual preferences are complemented by a comprehensive set of covariates provided by the Gallup World Poll 2012.

...

The GPS preference measures are based on twelve survey items, which were selected in an initial survey validation study (see Falk et al., 2016, for details). The validation procedure involved conducting multiple incentivized choice experiments for each preference, and testing the relative abilities of a wide range of different question wordings and formats to predict behavior in these choice experiments. The particular items used to construct the GPS preference measures were selected based on optimal performance out of menus of alternative items (for details see Falk et al., 2016). Experiments provide a valuable benchmark for selecting survey items, because they can approximate the ideal choice situations, specified in economic theory, in which individuals make choices in controlled decision contexts. Experimental measures are very costly, however, to implement in a globally representative sample, whereas survey measures are much less costly.⁴ Selecting survey measures that can stand in for incentivized revealed preference measures leverages the strengths of both approaches.

The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences: http://ftp.iza.org/dp9674.pdf

Table 1: Survey items of the GPS

Figure 1: World maps of patience, risk taking, and positive reciprocity.
Figure 2: World maps of negative reciprocity, altruism, and trust.

Figure 3: Gender coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting gender coefficients as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 4: Cognitive ability coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting coefficients on subjective math skills as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 5: Age profiles by OECD membership.

Table 6: Pairwise correlations between preferences and geographic and cultural variables

Figure 10: Distribution of preferences at individual level.
Figure 11: Distribution of preferences at country level.

interesting digression:
D Discussion of Measurement Error and Within- versus Between-Country Variation
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october 2017 by nhaliday
The Importance of Educational Credentials: Schooling Decisions and Returns in Modern China
A key contribution of our paper is to estimate the returns to an additional year of schooling while holding highest credential constant. We find the year generates a two percent gain in monthly income, with somewhat higher returns for China’s disadvantaged. This is much smaller than most estimates which do not separate the returns to additional schooling from those to earning a credential. We show that the policy, while redistributive, has generated a likely net loss of tens of billions of dollars. We interpret these results through a model of signaling and human capital accumulation and conclude that a high signaling value of earning a credential, also known as “credentialism,” plays a crucial role in household schooling decisions and in the returns to schooling in modern China.

Access to Elite Education, Wage Premium, and Social Mobility: Evidence from China’s College Entrance Exam: http://www.fas.nus.edu.sg/ecs/events/seminar/seminar-papers/17-08-31.pdf
woah:
Exploiting a discontinuity in elite university eligibility around the cut off scores, we find elite education increases the monthly wage by around 40%. While elite education eligibility does significantly affect mobility, it does not alter the influence of parental background. We also provide suggestive evidence that the wage premium is more likely to be explained by university-related networks and signaling than that of human capital.
pdf  study  economics  micro  econometrics  microfoundations  china  asia  sinosphere  education  supply-demand  labor  compensation  intervention  correlation  higher-ed  signaling  mobility  institutions  policy  wonkish  human-capital  multi  elite  class  🎩  broad-econ  social-capital  judgement  shift  regression  cost-benefit  network-structure  cracker-econ  natural-experiment  endogenous-exogenous 
october 2017 by nhaliday
Social Animal House: The Economic and Academic Consequences of Fraternity Membership by Jack Mara, Lewis Davis, Stephen Schmidt :: SSRN
We exploit changes in the residential and social environment on campus to identify the economic and academic consequences of fraternity membership at a small Northeastern college. Our estimates suggest that these consequences are large, with fraternity membership lowering student GPA by approximately 0.25 points on the traditional four-point scale, but raising future income by approximately 36%, for those students whose decision about membership is affected by changes in the environment. These results suggest that fraternity membership causally produces large gains in social capital, which more than outweigh its negative effects on human capital for potential members. Alcohol-related behavior does not explain much of the effects of fraternity membership on either the human capital or social capital effects. These findings suggest that college administrators face significant trade-offs when crafting policies related to Greek life on campus.

- III. Methodology has details
- it's an instrumental variable method paper

Table 5: Fraternity Membership and Grades

Do High School Sports Build or Reveal Character?: http://ftp.iza.org/dp11110.pdf
We examine the extent to which participation in high school athletics has beneficial effects on future education, labor market, and health outcomes. Due to the absence of plausible instruments in observational data, we use recently developed methods that relate selection on observables with selection on unobservables to estimate bounds on the causal effect of athletics participation. We analyze these effects in the US separately for men and women using three different nationally representative longitudinal data sets that each link high school athletics participation with later-life outcomes. We do not find consistent evidence of individual benefits reported in many previous studies – once we have accounted for selection, high school athletes are no more likely to attend college, earn higher wages, or participate in the labor force. However, we do find that men (but not women) who participated in high school athletics are more likely to exercise regularly as adults. Nevertheless, athletes are no less likely to be obese.

Online Social Network Effects in Labor Markets: Evidence From Facebook's Entry into College Campuses: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3381938
My estimates imply that access to Facebook for 4 years of college causes a 2.7 percentile increase in a cohort's average earnings, relative to the earnings of other individuals born in the same year.

https://marginalrevolution.com/marginalrevolution/2019/05/might-facebook-boost-wages.html
What Clockwork_Prior said. I was a college freshman when facebook first made its appearance and so I know that facebook's entry/exit cannot be treated as a quasi-random with respect to earnings. Facebook began at harvard, then expanded to other ivy league schools + places like stanford/MIT/CMU, before expanding into a larger set of universities.

Presuming the author is using a differences-in-differences research design, the estimates would be biased as they would essentially be calculating averaging earnings difference between Elite schools and non elite schools. If the sample is just restricted to the period where schools were simply elite, the problem still exist because facebook originated at Harvard and this becomes a comparison of Harvard earnings v.s. other schools.
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september 2017 by nhaliday
Culture, Ethnicity, and Diversity - American Economic Association
We investigate the empirical relationship between ethnicity and culture, defined as a vector of traits reflecting norms, values, and attitudes. Using survey data for 76 countries, we find that ethnic identity is a significant predictor of cultural values, yet that within-group variation in culture trumps between-group variation. Thus, in contrast to a commonly held view, ethnic and cultural diversity are unrelated. Although only a small portion of a country’s overall cultural heterogeneity occurs between groups, we find that various political economy outcomes (such as civil conflict and public goods provision) worsen when there is greater overlap between ethnicity and culture. (JEL D74, H41, J15, O15, O17, Z13)

definition of chi-squared index, etc., under:
II. Measuring Heterogeneity

Table 5—Incidence of Civil Conflict and Diversity
Table 6—Public Goods Provision and Diversity

https://twitter.com/GarettJones/status/924002043576115202
https://archive.is/oqMnC
https://archive.is/sBqqo
https://archive.is/1AcXn
χ2 diversity: raising the risk of civil war. Desmet, Ortuño-Ortín, Wacziarg, in the American Economic Review (1/N)

What predicts higher χ2 diversity? The authors tell us that, too. Here are all of the variables that have a correlation > 0.4: (7/N)

one of them is UK legal origin...

online appendix (with maps, Figures B1-3): http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/downloads/2017_culture_appendix.pdf
study  economics  growth-econ  broad-econ  world  developing-world  race  diversity  putnam-like  culture  cultural-dynamics  entropy-like  metrics  within-group  anthropology  microfoundations  political-econ  🎩  🌞  pdf  piracy  public-goodish  general-survey  cohesion  ethnocentrism  tribalism  behavioral-econ  sociology  cooperate-defect  homo-hetero  revolution  war  stylized-facts  econometrics  group-level  variance-components  multi  twitter  social  commentary  spearhead  econotariat  garett-jones  backup  summary  maps  data  visualization  correlation  values  poll  composition-decomposition  concept  conceptual-vocab  definition  intricacy  nonlinearity  anglosphere  regression  law  roots  within-without 
september 2017 by nhaliday
Accurate Genomic Prediction Of Human Height | bioRxiv
Stephen Hsu's compressed sensing application paper

We construct genomic predictors for heritable and extremely complex human quantitative traits (height, heel bone density, and educational attainment) using modern methods in high dimensional statistics (i.e., machine learning). Replication tests show that these predictors capture, respectively, ~40, 20, and 9 percent of total variance for the three traits. For example, predicted heights correlate ~0.65 with actual height; actual heights of most individuals in validation samples are within a few cm of the prediction.

https://infoproc.blogspot.com/2017/09/accurate-genomic-prediction-of-human.html

http://infoproc.blogspot.com/2017/11/23andme.html
I'm in Mountain View to give a talk at 23andMe. Their latest funding round was $250M on a (reported) valuation of $1.5B. If I just add up the Crunchbase numbers it looks like almost half a billion invested at this point...

Slides: Genomic Prediction of Complex Traits

Here's how people + robots handle your spit sample to produce a SNP genotype:

https://drive.google.com/file/d/1e_zuIPJr1hgQupYAxkcbgEVxmrDHAYRj/view
study  bio  preprint  GWAS  state-of-art  embodied  genetics  genomics  compressed-sensing  high-dimension  machine-learning  missing-heritability  hsu  scitariat  education  🌞  frontier  britain  regression  data  visualization  correlation  phase-transition  multi  commentary  summary  pdf  slides  brands  skunkworks  hard-tech  presentation  talks  methodology  intricacy  bioinformatics  scaling-up  stat-power  sparsity  norms  nibble  speedometer  stats  linear-models  2017  biodet 
september 2017 by nhaliday
Immigrants and Everest, Bryan Caplan | EconLog | Library of Economics and Liberty
Immigrants use less welfare than natives, holding income constant. Immigrants are far less likely to be in jail than natives, holding high school graduation constant.* On the surface, these seem like striking results. But I've heard a couple of smart people [Garett Jones] demur with an old statistics joke: "Controlling for barometric pressure, Mount Everest has the same altitude as the Dead Sea." Sometimes controls conceal the truth rather than laying it bare.
https://twitter.com/GarettJones/status/897153018503852033
https://archive.is/9k2Ww
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august 2017 by nhaliday
trees are harlequins, words are harlequins — bayes: a kinda-sorta masterpost
lol, gwern: https://www.reddit.com/r/slatestarcodex/comments/6ghsxf/biweekly_rational_feed/diqr0rq/
> What sort of person thinks “oh yeah, my beliefs about these coefficients correspond to a Gaussian with variance 2.5″? And what if I do cross-validation, like I always do, and find that variance 200 works better for the problem? Was the other person wrong? But how could they have known?
> ...Even ignoring the mode vs. mean issue, I have never met anyone who could tell whether their beliefs were normally distributed vs. Laplace distributed. Have you?
I must have spent too much time in Bayesland because both those strike me as very easy and I often think them! My beliefs usually are Laplace distributed when it comes to things like genetics (it makes me very sad to see GWASes with flat priors), and my Gaussian coefficients are actually a variance of 0.70 (assuming standardized variables w.l.o.g.) as is consistent with field-wide meta-analyses indicating that d>1 is pretty rare.
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august 2017 by nhaliday
Inherited Trust and Growth - American Economic Association
This paper develops a new method to uncover the causal effect of trust on economic growth by focusing on the inherited component of trust and its time variation. We show that inherited trust of descendants of US immigrants is significantly influenced by the country of origin and the timing of arrival of their forebears. We thus use the inherited trust of descendants of US immigrants as a time-varying measure of inherited trust in their country of origin. This strategy allows to identify the sizeable causal impact of inherited trust on worldwide growth during the twentieth century by controlling for country fixed effects. (JEL N11, N12, N31, N32, O47, Z13)

key data:
Table 1, Figure 1, Figure 3, Figure 4

Trust Assimilation in the United States, Bryan Caplan: http://econlog.econlib.org/archives/2017/05/trust_assimilat.html

How Durable are Social Norms? Immigrant Trust and Generosity in 132 Countries: http://www.nber.org/papers/w19855
We find that migrants tend to make social trust assessments that mainly reflect conditions in the country where they now live, but they also reveal a significant influence from their countries of origin. The latter effect is one-third as important as the effect of local conditions. We also find that the altruistic behavior of migrants, as measured by the frequency of their donations in their new countries, is strongly determined by social norms in their new countries, while also retaining some effect of the levels of generosity found in their birth countries. To show that the durability of social norms is not simply due to a failure to recognize new circumstances, we demonstrate that there are no footprint effects for immigrants’ confidence in political institutions. Taken together, these findings support the notion that social norms are deeply rooted in long-standing cultures, yet are nonetheless subject to adaptation when there are major changes in the surrounding circumstances and environment.

The autocratic roots of social distrust: http://sci-hub.tw/https://www.sciencedirect.com/science/article/pii/S0147596717300951
This paper identifies a new source of social distrust: an individual’s autocratic
origin.
 Individuals whose ancestors migrated from countries with higher autocracy
levels are less likely to trust others and to vote in presidential elections in the
U.S.
 The impact of autocratic culture on trust lasts for at least three generations
whereas the impact on voting disappears after one generation.
 The results are not driven by selection into migration or other factors such as the
GDP, education, or the strength of family ties in home countries in the U.S.
 Autocratic culture also has similar impacts on trust and voting across Europe.
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july 2017 by nhaliday
Econometric Modeling as Junk Science
The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics: https://www.aeaweb.org/articles?id=10.1257/jep.24.2.3

On data, experiments, incentives and highly unconvincing research – papers and hot beverages: https://papersandhotbeverages.wordpress.com/2015/10/31/on-data-experiments-incentives-and-highly-unconvincing-research/
In my view, it has just to do with the fact that academia is a peer monitored organization. In the case of (bad) data collection papers, issues related to measurement are typically boring. They are relegated to appendices, no one really has an incentive to monitor it seriously. The problem is similar in formal theory: no one really goes through the algebra in detail, but it is in principle feasible to do it, and, actually, sometimes these errors are detected. If discussing the algebra of a proof is almost unthinkable in a seminar, going into the details of data collection, measurement and aggregation is not only hard to imagine, but probably intrinsically infeasible.

Something different happens for the experimentalist people. As I was saying, I feel we have come to a point in which many papers are evaluated based on the cleverness and originality of the research design (“Using the World Cup qualifiers as an instrument for patriotism!? Woaw! how cool/crazy is that! I wish I had had that idea”). The sexiness of the identification strategy has too often become a goal in itself. When your peers monitor you paying more attention to the originality of the identification strategy than to the research question, you probably have an incentive to mine reality for ever crazier discontinuities. It is true methodologists have been criticized in the past for analogous reasons, such as being guided by the desire to increase mathematical complexity without a clear benefit. But, if you work with pure formal theory or statistical theory, your work is not meant to immediately answer question about the real world, but instead to serve other researchers in their quest. This is something that can, in general, not be said of applied CI work.

https://twitter.com/pseudoerasmus/status/662007951415238656
This post should have been entitled “Zombies who only think of their next cool IV fix”
https://twitter.com/pseudoerasmus/status/662692917069422592
massive lust for quasi-natural experiments, regression discontinuities
barely matters if the effects are not all that big
I suppose even the best of things must reach their decadent phase; methodological innov. to manias……

https://twitter.com/cblatts/status/920988530788130816
Following this "collapse of small-N social psych results" business, where do I predict econ will collapse? I see two main contenders.
One is lab studies. I dallied with these a few years ago in a Kenya lab. We ran several pilots of N=200 to figure out the best way to treat
and to measure the outcome. Every pilot gave us a different stat sig result. I could have written six papers concluding different things.
I gave up more skeptical of these lab studies than ever before. The second contender is the long run impacts literature in economic history
We should be very suspicious since we never see a paper showing that a historical event had no effect on modern day institutions or dvpt.
On the one hand I find these studies fun, fascinating, and probably true in a broad sense. They usually reinforce a widely believed history
argument with interesting data and a cute empirical strategy. But I don't think anyone believes the standard errors. There's probably a HUGE
problem of nonsignificant results staying in the file drawer. Also, there are probably data problems that don't get revealed, as we see with
the recent Piketty paper (http://marginalrevolution.com/marginalrevolution/2017/10/pikettys-data-reliable.html). So I take that literature with a vat of salt, even if I enjoy and admire the works
I used to think field experiments would show little consistency in results across place. That external validity concerns would be fatal.
In fact the results across different samples and places have proven surprisingly similar across places, and added a lot to general theory
Last, I've come to believe there is no such thing as a useful instrumental variable. The ones that actually meet the exclusion restriction
are so weird & particular that the local treatment effect is likely far different from the average treatment effect in non-transparent ways.
Most of the other IVs don't plausibly meet the e clue ion restriction. I mean, we should be concerned when the IV estimate is always 10x
larger than the OLS coefficient. This I find myself much more persuaded by simple natural experiments that use OLS, diff in diff, or
discontinuities, alongside randomized trials.

What do others think are the cliffs in economics?
PS All of these apply to political science too. Though I have a special extra target in poli sci: survey experiments! A few are good. I like
Dan Corstange's work. But it feels like 60% of dissertations these days are experiments buried in a survey instrument that measure small
changes in response. These at least have large N. But these are just uncontrolled labs, with negligible external validity in my mind.
The good ones are good. This method has its uses. But it's being way over-applied. More people have to make big and risky investments in big
natural and field experiments. Time to raise expectations and ambitions. This expectation bar, not technical ability, is the big advantage
economists have over political scientists when they compete in the same space.
(Ok. So are there any friends and colleagues I haven't insulted this morning? Let me know and I'll try my best to fix it with a screed)

HOW MUCH SHOULD WE TRUST DIFFERENCES-IN-DIFFERENCES ESTIMATES?∗: https://economics.mit.edu/files/750
Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data on female wages from the Current Population Survey. For each law, we use OLS to compute the DD estimate of its “effect” as well as the standard error of this estimate. These conventional DD standard errors severely understate the standard deviation of the estimators: we find an “effect” significant at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the time-series process do not perform well. Bootstrap (taking into account the auto-correlation of the data) works well when the number of states is large enough. Two corrections based on asymptotic approximation of the variance-covariance matrix work well for moderate numbers of states and one correction that collapses the time series information into a “pre” and “post” period and explicitly takes into account the effective sample size works well even for small numbers of states.

‘METRICS MONDAY: 2SLS–CHRONICLE OF A DEATH FORETOLD: http://marcfbellemare.com/wordpress/12733
As it turns out, Young finds that
1. Conventional tests tend to overreject the null hypothesis that the 2SLS coefficient is equal to zero.
2. 2SLS estimates are falsely declared significant one third to one half of the time, depending on the method used for bootstrapping.
3. The 99-percent confidence intervals (CIs) of those 2SLS estimates include the OLS point estimate over 90 of the time. They include the full OLS 99-percent CI over 75 percent of the time.
4. 2SLS estimates are extremely sensitive to outliers. Removing simply one outlying cluster or observation, almost half of 2SLS results become insignificant. Things get worse when removing two outlying clusters or observations, as over 60 percent of 2SLS results then become insignificant.
5. Using a Durbin-Wu-Hausman test, less than 15 percent of regressions can reject the null that OLS estimates are unbiased at the 1-percent level.
6. 2SLS has considerably higher mean squared error than OLS.
7. In one third to one half of published results, the null that the IVs are totally irrelevant cannot be rejected, and so the correlation between the endogenous variable(s) and the IVs is due to finite sample correlation between them.
8. Finally, fewer than 10 percent of 2SLS estimates reject instrument irrelevance and the absence of OLS bias at the 1-percent level using a Durbin-Wu-Hausman test. It gets much worse–fewer than 5 percent–if you add in the requirement that the 2SLS CI that excludes the OLS estimate.

Methods Matter: P-Hacking and Causal Inference in Economics*: http://ftp.iza.org/dp11796.pdf
Applying multiple methods to 13,440 hypothesis tests reported in 25 top economics journals in 2015, we show that selective publication and p-hacking is a substantial problem in research employing DID and (in particular) IV. RCT and RDD are much less problematic. Almost 25% of claims of marginally significant results in IV papers are misleading.

https://twitter.com/NoamJStein/status/1040887307568664577
Ever since I learned social science is completely fake, I've had a lot more time to do stuff that matters, like deadlifting and reading about Mediterranean haplogroups
--
Wait, so, from fakest to realest IV>DD>RCT>RDD? That totally matches my impression.

https://twitter.com/wwwojtekk/status/1190731344336293889
https://archive.is/EZu0h
Great (not completely new but still good to have it in one place) discussion of RCTs and inference in economics by Deaton, my favorite sentences (more general than just about RCT) below
Randomization in the tropics revisited: a theme and eleven variations: https://scholar.princeton.edu/sites/default/files/deaton/files/deaton_randomization_revisited_v3_2019.pdf
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june 2017 by nhaliday
What are the big deals when linking demographics and politics? | We the Pleeple
You can see in the chart that religion/church (the black bars) and race/immigrant (the green bars) are just way bigger deals than education, age, gender, income, and region/density. Further, there are some kinds of items where race/immigrant variables are particularly big deals (party identification along with views on rich-poor issues, immigration, gun regulation, racial issues, and white nationalism, which combines views on immigration, race, etc.), while there are other kinds of items where religion/church variables are clearly the dominant demographic predictors (self-labelled liberal/conservative ideology along with views on homosexuality, abortion, marijuana legalization, environmental regulation, and Middle Eastern conflicts).
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may 2017 by nhaliday
Pearson correlation coefficient - Wikipedia
https://en.wikipedia.org/wiki/Coefficient_of_determination
what does this mean?: https://twitter.com/GarettJones/status/863546692724858880
deleted but it was about the Pearson correlation distance: 1-r
I guess it's a metric

https://en.wikipedia.org/wiki/Explained_variation

http://infoproc.blogspot.com/2014/02/correlation-and-variance.html
A less misleading way to think about the correlation R is as follows: given X,Y from a standardized bivariate distribution with correlation R, an increase in X leads to an expected increase in Y: dY = R dX. In other words, students with +1 SD SAT score have, on average, roughly +0.4 SD college GPAs. Similarly, students with +1 SD college GPAs have on average +0.4 SAT.

this reminds me of the breeder's equation (but it uses r instead of h^2, so it can't actually be the same)

https://www.reddit.com/r/slatestarcodex/comments/631haf/on_the_commentariat_here_and_why_i_dont_think_i/dfx4e2s/
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may 2017 by nhaliday
Deming regression - Wikipedia
Deming regression. The red lines show the error in both x and y. This is different from the traditional least squares method which measures error parallel to the y axis. The case shown, with deviations measured perpendicularly, arises when errors in x and y have equal variances.

https://en.wikipedia.org/wiki/Errors-in-variables_models
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may 2017 by nhaliday
Growing Collectivism: Irrigation, Group Conformity and Technological Divergence
This paper examines the origins of collectivist cultures that emphasize group conformity over individual autonomy. In line with the hypothesis that collaboration within groups in pre-industrial agriculture favored the emergence of collectivism, I find that societies whose ancestors jointly practiced irrigation agriculture have stronger collectivist norms today. The positive effect of irrigation on contemporary collectivism holds across countries, subnational districts within countries, and migrants. For causal identification, I instrument the historical adoption of irrigation by its geographic suitability. Furthermore, this paper establishes that, by favoring conformity, irrigation agriculture has contributed to the global divergence of technology. I document (i) a negative effect of traditional irrigation agriculture on contemporary innovativeness of countries, cities, and migrants; (ii) a positive effect on selection into routine-intensive occupations; and (iii) that the initial technological advantage of irrigation societies was reversed after 1500.

http://marginalrevolution.com/marginalrevolution/2016/09/varying-rainfall-make-people-collectivists.html
This kind of investigation is always going to be fraught with uncertainty and also controversy, given imperfections of data and methods. Nonetheless I find this one of the more plausible macro-historical hypotheses, perhaps because of my own experience in central Mexico, where varying rainfall still is the most important economic event of the year, though it is rapidly being supplanted by the variability of tourist demand for arts and crafts. And yes, they are largely collectivist, at least at the clan level, with extensive systems of informal social insurance and very high implicit social marginal tax rates on accumulated wealth.

Have you noticed it rains a lot in England?

(lol)

http://marginalrevolution.com/marginalrevolution/2014/05/chinese-wheat-eaters-vs-rice-eaters-speculative.html
http://www.scmp.com/news/china/article/1508726/why-chinas-wheat-growing-north-produces-individualists-and-its-rice
in-depth reflection on agricultural ecologies, Europe vs China, and internal Chinese differences/ethnic identity/relations with barbarians/nomads, etc.: https://www.gnxp.com/blog/2008/08/wealth-of-communities.php

Irrigation and Autocracy: http://www.econ.ku.dk/bentzen/Irrigation_and_Autocracy.pdf
http://marginalrevolution.com/marginalrevolution/2012/08/in-defense-of-the-wittvogel-thesis.html

Emerging evidence of cultural differences linked to rice versus wheat agriculture: https://sci-hub.tw/https://www.sciencedirect.com/science/article/pii/S2352250X1930082X
- Historical rice farming linked to interdependent culture.
- Differences tested in China and Japan, as well as in worldwide comparison.
- There is evidence for differences among urbanites with no direct experience farming.
- Rice farming is also linked to holistic thought, fewer patents for inventions.
- Rice cultures are not ‘pro-social’ but rather tight ties, strong division of close versus distant ties.

The agricultural roots of Chinese innovation performance: https://sci-hub.tw/https://www.sciencedirect.com/science/article/pii/S0014292119300893
We provide robust evidence that counties with a legacy of rice cultivation generate fewer patent applications than other counties, and a legacy of wheat production tends to be associated with more patent applications. The results for rice are robust to, e.g., controlling for temperature, precipitation, irrigation, disease burden, religiosity, and corruption, as well as accounting for migration patterns.

Steve Hsu on this stuff:
Genetic variation in Han Chinese population: http://infoproc.blogspot.com/2017/07/genetic-variation-in-han-chinese.html
Largest component of genetic variation is a N-S cline (phenotypic N-S gradient discussed here). Variance accounted for by second (E-W) PC vector is much smaller and the Han population is fairly homogeneous in genetic terms: ...while we revealed East-to-West structure among the Han Chinese, the signal is relatively weak and very little structure is discernible beyond the second PC (p.24).

Neandertal ancestry does not vary significantly across provinces, consistent with admixture prior to the dispersal of modern Han Chinese.

http://infoproc.blogspot.com/2014/01/china-1793.html
My fellow officers informed me, that while the negotiation was going on, the ships were constantly crowded with all kinds of refreshments, and that when they were first boarded by the Chinese they received every attention from them that could be shown; and that the presents received by the different officers belonging to the embassy, were of immense value. That the natives of this part of China were of different complexions and manners from those in and near Canton; their colour being nearly white; and in their manners were much more free and candid; and that they were of a larger stature, and more athletic than the southern Chinese—they were much more sociable, and not so particular respecting their women being seen by the men. And were even fond of receiving the officers into their houses, when on shore, provided it could be done without the knowledge of the mandarins.

http://infoproc.blogspot.com/2014/06/large-scale-psychological-differences.html
The study below discusses a psychological/cognitive/personality gradient between N and S China, possibly driven by a history of wheat vs rice cultivation.

https://en.wikipedia.org/wiki/Northern_and_southern_China
http://shanghaiist.com/2015/07/01/average-heights-men-women.php
https://www.quora.com/Why-are-Northern-Chinese-people-generally-taller-than-Southern-Chinese

https://gnxp.nofe.me/2017/08/01/the-great-genetic-map-of-china/
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may 2017 by nhaliday
Identifying the Determinants of Attitudes towards Immigrants: A Structural Cross-Country Analysis
not much of a difference by gender (seems female->more supportive in northern countries, less supportive in southern countries), biggest thing is urbanity+educational attainment

https://twitter.com/whyvert/status/899850410935975940
https://archive.is/nUJp2
Vote share for WEuro populist parties higher in regions: rural, ⇈foreigners, ⇈unemployment, AND ⇈education except in cities (surprising)
the urban educated hate the nationalist parties but the nonurban educated are prone to support them. Not all educated are alike

The success of radical right-wing parties in Western European regions – new challenging findings: http://www.tandfonline.com/doi/abs/10.1080/14782804.2016.1198691

Can Television Reduce Xenophobia? The Case of East Germany: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2932276
To examine this question, we exploit the fact that individuals in some areas of East Germany – due to their geographic location – could not receive West German television until 1989. We conjecture that individuals who received West German television were exposed more frequently to foreigners and thus have developed less xenophobia than people who were not exposed to those programs. Our results show that regions that could receive West German television were less likely to vote for right-wing parties during the national elections from 1998 to 2013. Only recently, the same regions were also more likely to vote for left-wing parties. Moreover, while counties that hosted more foreigners in 1989 were also more likely to vote for right-wing parties in most elections, we find counties that recently hosted more foreign visitors showed less xenophobia, which is in line with intergroup contact theory.

With an Open Mind: Openness to Experience Moderates the Effect of Interethnic Encounters on Support for Immigration: https://academic.oup.com/esr/article-abstract/33/5/721/4102111/With-an-Open-Mind-Openness-to-Experience-Moderates

Refugees Unwelcome? Changes in the Public Acceptance of Immigrants and Refugees in Germany in the Course of Europe’s ‘Immigration Crisis’: https://academic.oup.com/esr/article-abstract/doi/10.1093/esr/jcx071/4557564/Refugees-Unwelcome-Changes-in-the-Public
Derived from discussions making up the German immigration discourse during this time, we expect reduced acceptance especially of those immigrants who were explicitly connected to the salient events, like Muslims and the offenders of NYE. Most strikingly, we find that refugees were generally highly accepted and even more so in the second wave, whereas the acceptance of immigrants from Arab or African countries further decreased. Moreover, _female respondents’ initial preference for male immigrants_ disappeared. Contrary to our expectations, we find no changes in the acceptance of Muslims.
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may 2017 by nhaliday
Less intelligent people want to exclude racists from the public square – Gene Expression
Millennials with college degrees don’t favor censorship: http://gnxp.nofe.me/2017/05/03/millennials-with-college-degrees-dont-favor-censorship/
Free Expression on Campus: A Survey of U.S. College Students and U.S. Adults: https://www.knightfoundation.org/media/uploads/publication_pdfs/FreeSpeech_campus.pdf
some scary attitudes toward "hate speech" and anonymous speech
http://www.unz.com/akarlin/future-for-aclu-children/
Ironic joking and SJW meltdowns over photos of White children aside, the politically correct peeps at ACLU (who apologized for their social justice faux pas soon afterwards) were actually far more to the point than they could have possibly imagined.

Opinion polls have shown that in the US, Whites tend to have the greatest respect for freedom of speech.

asians quite low across the board

YouGov | Half of Democrats support a ban on hate speech: https://today.yougov.com/news/2015/05/20/hate-speech/
Americans narrowly support (41%) rather than oppose (37%) criminalizing hate speech

http://www.integrationsfonds.at/publikationen/forschungsberichte/forschungsbericht-muslimische-gruppen-in-oesterreich/
A majority of Austrian Muslims believe making fun of Islam shouldn't be allowed. Somalis, Chechens, Afghans & Syrians feel most strongly (9)

Most Liberals And Smart People Want Racists To Be Allowed To Speak: https://gnxp.nofe.me/2017/08/25/189066/
But whenever I look at the General Social Survey I see no great change in support for free speech in terms of the patterns. Perhaps something has changed in the year 2017, but I think what we are seeing are vocal and motivated minorities who are drowning out liberal (in the classical sense) majorities.
https://gnxp.nofe.me/2017/08/25/the-less-intelligent-and-uneducated-really-dont-tolerate-unpopular-views/

Freedom Of Thought As A Perpetual Revolution: https://gnxp.nofe.me/2017/09/13/freedom-of-thought-as-a-perpetual-revolution/
I mentioned offhand on Twitter today that I am skeptical of the tendency to brand the classically liberal emphasis on freedom of thought and speech as “centrist.” The implicit idea is that those on the Right and Left for whom liberalism is conditional, and a means at best, are radical and outside the mainstream.

This misleads us in relation to the fact that classical liberalism is the aberration both historically and culturally. Liberty of thought and speech have existed for time immemorial, but they were the luxury goods of the elite salons. Frederick the Great of Prussia had no use for religion personally, and famously patronized heretical philosophers, but he did not disturb the conservative social order of the polity which he inherited. For the masses, the discourse was delimited and regulated to maintain order and reinforce social norms.

The attempt to position the liberal stance as a centrist one is clearly historically and culturally contingent. It reflects the ascendancy of a particular strand of Anglo-American elite culture worldwide. But it is not universal. In the Islamic world and South Asia free expression of skepticism of religious ideas in public are subject to limits explicitly to maintain public order. The Islamic punishments for apostasy have less to do with the sin of individual disbelief and more to do with disruption to public norms and sedition against the state. Similarly, both China and Russia tap deeply into cultural preferences for state and elite paternalism in regards to public freedom of thought.

A chilling study shows how hostile college students are toward free speech: https://www.washingtonpost.com/opinions/a-chilling-study-shows-how-hostile-college-students-are-toward-free-speech/2017/09/18/cbb1a234-9ca8-11e7-9083-fbfddf6804c2_story.html
https://www.theguardian.com/us-news/2017/sep/22/college-free-speech-violence-survey-junk-science

http://anepigone.blogspot.com/2017/09/its-so-pc-its-killing-me.html
Americans chafe under PC oppressiveness. True across all demographics. Alt right can't emphasize free speech enough

A Run on Liberalism?: https://www.the-american-interest.com/2017/09/20/a-run-on-liberalism/
- Jason Willick

It’s also about taking a long view of our own self-interests—that is, recognizing that if we agree not to suppress the other tribe, then the other tribe just might agree, as a general rule, to not suppress us. If adhered to, it can be positive sum transaction—the free exchange of ideas ultimately makes life richer and more prosperous for everyone. Liberalism is a bargain between elites to set up institutions that allow this positive-sum process to take place despite all the forces working against it.

https://today.yougov.com/news/2017/10/02/americans-support-free-speech-college-campusmost-t/
In fact, Americans prioritize exposing students to all types of speech on campuses, even if that speech is biased or offensive, to providing a positive learning environment for all students at the risk of barring some types of speech. Sometimes this type of question generates a politicized response, depending on the speech that respondents think may be restricted. The most recent and most publicized college incidents involve conservative speakers who have been shouted down or have had speeches on campuses canceled. On this question Democrats and Republicans may be on different sides, but liberals and conservatives agree.

http://reason.com/blog/2017/10/04/black-lives-matter-students-shut-down-th

http://www.mercurynews.com/2017/09/12/poll-most-california-democrats-want-to-restrict-free-speech-from-white-nationalists/
Poll: Most California Democrats want to restrict free speech from white nationalists

40% non-Hispanic White, 51% Latino, 58% Af-American, 59% Asian-American

America's Many Divides Over Free Speech: https://www.theatlantic.com/politics/archive/2017/10/a-sneak-peek-at-new-survey-data-on-free-speech/542028/
A new survey explores Americans’ views on hate speech, political correctness, Nazi-punching, job terminations for offensive speech, and much more.
- CONOR FRIEDERSDORF

https://twitter.com/tcjfs/status/925458956239110145
https://archive.is/ZeY18
Well this explains a lot

https://twitter.com/tcjfs/status/925504773222293505
https://archive.is/oSjru
Democrats..... lmao 😁

https://twitter.com/tcjfs/status/925507818802810880
https://archive.is/vSdrZ
> CATO releases its own report showing that blacks & Latinos have the least attachment to libertarian ideas
> they will change nothing

The State of Free Speech and Tolerance in America: https://www.cato.org/survey-reports/state-free-speech-tolerance-america

Free speech and the Coalition of the Fringes: http://anepigone.blogspot.com/2017/11/free-speech-and-coalition-of-fringes.html

Epigonian aesthetics: http://anepigone.blogspot.com/2017/11/epigonian-aesthetics.html

https://www.nytimes.com/2018/03/12/us/college-students-free-speech.html

https://twitter.com/tcjfs/status/973340678104199168
https://archive.is/PMp5S
European-style hate speech laws, and a SCOTUS favorable to them, will increasingly be a key goal of the left
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april 2017 by nhaliday
[1502.05274] How predictable is technological progress?
Recently it has become clear that many technologies follow a generalized version of Moore's law, i.e. costs tend to drop exponentially, at different rates that depend on the technology. Here we formulate Moore's law as a correlated geometric random walk with drift, and apply it to historical data on 53 technologies. We derive a closed form expression approximating the distribution of forecast errors as a function of time. Based on hind-casting experiments we show that this works well, making it possible to collapse the forecast errors for many different technologies at different time horizons onto the same universal distribution. This is valuable because it allows us to make forecasts for any given technology with a clear understanding of the quality of the forecasts. As a practical demonstration we make distributional forecasts at different time horizons for solar photovoltaic modules, and show how our method can be used to estimate the probability that a given technology will outperform another technology at a given point in the future.

model:
- p_t = unit price of tech
- log(p_t) = y_0 - μt + ∑_{i <= t} n_i
- n_t iid noise process
preprint  study  economics  growth-econ  innovation  discovery  technology  frontier  tetlock  meta:prediction  models  time  definite-planning  stylized-facts  regression  econometrics  magnitude  energy-resources  phys-energy  money  cost-benefit  stats  data-science  🔬  ideas  speedometer  multiplicative  methodology  stochastic-processes  time-series  stock-flow  iteration-recursion  org:mat  street-fighting  the-bones 
april 2017 by nhaliday
I Just Ran Four Million Regressions
great title

In this paper I try to move away from the Extreme Bounds method of identifying" Instead of analyzing the" extreme bounds of the estimates of the coefficient of a particular variable distribution. My claim in this paper is that, if we do this, the picture emerging from the" empirical growth literature is not the pessimistic Robust" that we get with the" extreme bound analysis. Instead, we find that a substantial number of variables can be found" to be strongly related to growth.

http://www.j-bradford-delong.net/Comments/decadenewgrowth.html
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march 2017 by nhaliday
Why does 'everything look correlated on a log-log scale'? - Quora
A correlation on a log log scale is meant to suggest the data follows a power law relationship of the form yy∝x−n.∝x−n.

A low R2R2 is suppose to suggest that the data either actually follows some other distribution like yy∝e−x∝e−xor is simply random noise. The problem is that log log correlation is a necessary but not sufficient condition to prove a power law relationship. While ruling out random noise is fairly easy, ruling out an alternate functional form is much harder- you can reject a power law hypothesis by a log log plot but you cannot prove it by one. As Aaron Brown answer points out, a lot of stuff that looks like it has a power law relationship does not actually follow it in reality. In particular, an exponential or log normal relationship might give similar results over most of the range but will diverge strongly at the tail end .[1] This difference can be difficult to detect if limited data is collected at the tail ends and deviations look like noise.

An example of a log normal distribution plotted on a normal and log-log scale. [2] Note the appearance of a straight line on the right tail that diverges strongly on the left tail. Using a power law relationship in this region will cause serious errors.
q-n-a  qra  data-science  correlation  regression  magnitude  dataviz  street-fighting  gotchas  nibble  plots  multiplicative  additive  power-law 
february 2017 by nhaliday
A Rejection of 'Broken Windows Policing' Over Race Actually Hurts Minority Neighborhoods | Manhattan Institute
https://twitter.com/BookOfTamara/status/778838226983268352
https://archive.is/ETLXf
Late-night slightly controversial criminal justice thread:

Proactive policing and crime control: https://www.nature.com/articles/s41562-017-0227-x
Evidence that curtailing proactive policing can reduce major crime: https://www.nature.com/articles/s41562-017-0211-5

Proactive Policing: Effects on Crime and Communities: http://sites.nationalacademies.org/dbasse/claj/proactive-policing/index.htm
This report from the Committee on Law and Justice finds evidence that a number of proactive policing practices are successful in reducing crime and disorder, at least in the short term, and that most of these strategies do not harm communities’ attitudes towards police.

Is Racial Profiling a Legitimate Strategy in the Fight against Violent Crime?: https://link.springer.com/epdf/10.1007/s11406-018-9945-1?author_access_token=nDM1xCesybebx7yUX2BxZ_e4RwlQNchNByi7wbcMAY6py69jTlOiEGDIgqW0Vv2HrAor6wlMLH695I2ykTiKUxf1RBnu1u_6gjXU-6vgh2gIy6CX2npHD9GR350T20x_TbCcq4MmJUPrxAqsJSe1QA%3D%3D
- Neven Sesardić

Are U.S. Cities Underpoliced?: http://marginalrevolution.com/marginalrevolution/2017/08/u-s-cities-underpoliced.html
Chalfin and McCrary acknowledge the endogeneity problem but they suggest that a more important reason why ordinary regression gives you poor results is that the number of police is poorly measured. Suppose the number of police jumps up and down in the data even when the true number stays constant. Fake variation obviously can’t influence real crime so when your regression “sees” a lot of (fake) variation in police which is not associated with variation in crime it’s naturally going to conclude that the effect of police on crime is small, i.e. attenuation bias.

By comparing two different measures of the number of police, Chalfin and McCrary show that a surprising amount of the ups and downs in the number of police is measurement error. Using their two measures, however, Chalfin and McCrary produce a third measure which is better than either alone. Using this cleaned-up estimate, they find that ordinary regression (with controls) gives you estimates of the effect of police on crime which are plausible and similar to those found using other techniques like natural experiments. Chalfin and McCrary’s estimates, however, are more precise since they use much more of the variation in the data.

Using these new estimates of the effect of police and crime along with estimates of the social cost of crime they conclude (as I have argued before) that U.S. cities are substantially under-policed.

Crime Imprisons and Kills: http://marginalrevolution.com/marginalrevolution/2018/01/crime-imprisons-kills.html
…The everyday lived experience of urban poverty has also been transformed. Analyzing rates of violent victimization over time, I found that the poorest Americans today are victimized at about the same rate as the richest Americans were at the start of the 1990s. That means that a poor, unemployed city resident walking the streets of an average city today has about the same chance of being robbed, beaten up, stabbed or shot as a well-off urbanite in 1993. Living in poverty used to mean living with the constant threat of violence. In most of the country, that is no longer true.

http://marginalrevolution.com/marginalrevolution/2015/09/what-was-gary-beckers-biggest-mistake.html
http://www.sentencingproject.org/wp-content/uploads/2016/01/Deterrence-in-Criminal-Justice.pdf
Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?: http://link.springer.com.sci-hub.tw/article/10.1007/s00181-017-1332-4

Death penalty: https://offsettingbehaviour.blogspot.com/2011/09/death-penalty.html
And so I revise: the death penalty is wrong, and it also likely has little measurable deterrent effect. There may still be a deterrent effect; we just can't show one given available data.

The effects of DNA databases on the deterrence and detection of offenders: http://jenniferdoleac.com/wp-content/uploads/2015/03/DNA_Denmark.pdf
We exploit a large expansion of Denmark’s DNA database in 2005 to measure the effect of DNA registration on criminal behavior. Using a regression discontinuity strategy, we find that DNA registration reduces recidivism by 43%. Using rich data on the timing of subsequent charges to separate the deterrence and detection effects of DNA databases, we also find that DNA registration increases the probability that repeat offenders get caught, by 4%. We estimate an elasticity of criminal behavior with respect to the probability of detection to be -1.7. We also find suggestive evidence that DNA profiling changes non-criminal behavior: offenders added to the DNA database are more likely to get married, remain in a stable relationship, and live with their children.

Short- and long-term effects of imprisonment on future felony convictions and prison admissions: http://www.pnas.org/content/early/2017/09/26/1701544114.short
https://twitter.com/bswud/status/917354893907779585
Prison isn't criminogenic—offenders have higher rates of re-incarceration because of technical parole violations
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january 2017 by nhaliday
Mental rotation and real-world wayfinding. - PubMed - NCBI
r ≈ .3

The results indicate that mental rotation skills are significantly correlated with wayfinding performance on an orienteering task. The findings also replicate sex differences in spatial ability as found in laboratory-scale studies. However, the findings complicate the discussion of mental rotation skills and sex because women often performed as well as men despite having lower mean test scores. This suggests that mental rotation ability may not be as necessary for some women's wayfinding as it is for men's navigation.

Sex Differences in Furniture Assembly Performance: An Experimental Study: http://onlinelibrary.wiley.com/doi/10.1002/acp.3182/abstract
fucking lol

Sex hormones predict the sensory strength and vividness of mental imagery: https://www.ncbi.nlm.nih.gov/pubmed/25703930
- not in the direction I would expect (women have more vivid mental imagery)
- visual working memory is different

Sex hormones and mental rotation: An intensive longitudinal investigation: http://www.sciencedirect.com.sci-hub.tw/science/article/pii/S0018506X12003066
For males and females, estradiol and testosterone were significantly linearly and quadratically related to interindividual variation in performance at the beginning of the study (progesterone was linearly related to performance for females). The association between testosterone and performance differed across sexes: for males, it had an inverse U-shape, for females it was U-shaped. Towards the end of the study, none of the hormones were significantly related to performance anymore. Thus, the relationship between hormones and mental rotation performance disappeared with repeated testing.

very confusing study. seems sketchy.

Is There a Relationship Between the Performance in a Chronometric Mental-Rotations Test and Salivary Testosterone and Estradiol Levels in Children Aged 9–14 Years?: http://sci-hub.tw/10.1002/dev.21333
Results showed a significant gender difference in reaction time and rotational speed in favor of boys, and a significant age, but no gender difference in testosterone and estradiol levels. We found no significant relationships between hormonal levels and any measure of mental-rotation performance.

Having a Male Co-Twin Masculinizes Mental Rotation Performance in Females: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4438761/
There were 351 females from same-sex pairs, 223 males from same-sex pairs, 120 females from opposite-sex pairs, and 110 males from opposite-sex pairs.

hmm:
Sex Differences in Mental Rotation Ability Are a Consequence of Procedure and Artificiality of Stimuli: https://link.springer.com/article/10.1007/s40806-017-0120-x
Our results suggest that the sex difference found on this test is not due to a male advantage in spatial ability, but is an artifact of the stimuli.
study  psychology  cog-psych  psychometrics  spatial  iq  gender  correlation  comparison  psych-architecture  gender-diff  multi  embodied  lmao  attaq  pdf  piracy  🌞  hmm  visuo  dennett  endocrine  neuro-nitgrit  longitudinal  curvature  regression  oscillation  twin-study  developmental  chart  navigation  convexity-curvature 
december 2016 by nhaliday
IQ and National Productivity
National IQ and National Productivity:
The Hive Mind Across Asia: http://mason.gmu.edu/~gjonesb/JonesADR.pdf
Human Capital and National Institutional Quality: Are TIMSS, PISA, and National Average IQ Robust Predictors?: https://www.econstor.eu/bitstream/10419/102105/1/cesifo_wp4790.pdf
This will allow us to give preliminary tests of three different hypotheses about the link between cognitive skill and institutional outcomes: The weakest link theory, the median voter theory, and the smart fraction theory.

mean:
Table 3: Regression results with standardized beta coefficients. Dependent variable: Overall IPR Index. OLS with classical standard errors. IQ scores.

upper tail:
Table 4: Regression results with standardized beta coefficients. Dependent variable: Overall IPR Index. OLS with classical standard errors. CA scores.
pdf  study  economics  hive-mind  group-level  iq  econ-productivity  growth-econ  spearhead  cracker-econ  time-preference  macro  garett-jones  biodet  sociology  stylized-facts  broad-econ  behavioral-gen  rindermann-thompson  chart  biophysical-econ  wealth-of-nations  microfoundations  multi  🎩  🌞  institutions  human-capital  psychology  cog-psych  psychometrics  government  econometrics  patience  elite  general-survey  political-econ  white-paper  pop-diff  models  comparison  tails  regression  property-rights  hari-seldon 
december 2016 by nhaliday
Making the One Percent: The Role of Elite Universities and Elite Peers
I combine administrative data on income and leadership teams at publicly traded firms with a regression discontinuity design based on admissions rules at elite business-focused degree programs in Chile. The 1.8% of college students admitted to these programs account for 41% of leadership positions and 39% of top 0.1% incomes. Admission raises the number of leadership positions students hold by 44% and their probability of attaining a top 0.1% income by 51%. However, these gains are driven by male applicants from high-tuition private high schools, with zero effects for female students or students from other school types with similar admissions test scores. Admissions effects are equal to 38% of the gap in rates of top attainment by gender and 54% of the gap by high school background for male students. A difference-in-differences analysis of the rates at which pairs of students lead the same firms suggests that peer ties formed between college classmates from similar backgrounds may play an important role in driving the observed effects.
study  economics  labor  transitions  higher-ed  class  natural-experiment  institutions  education  optimate  mobility  compensation  legacy  intervention  effect-size  elite  s-factor  progression  vampire-squid  endogenous-exogenous  latin-america  nonlinearity  business  medicine  econometrics  shift  regression  cost-benefit  realness  network-structure  winner-take-all 
december 2016 by nhaliday
In China, prisoners of conscience are literally being butchered - The Boston Globe
In 1999, Chinese hospitals began performing more than 10,000 organ transplants annually, generating a vast and lucrative traffic in “transplant tourists,” who flocked to China on the assurance that they could obtain lifesaving organs without having to languish on a waiting list. China had no voluntary organ-donation system to speak of, yet suddenly it was providing tens of thousands of freshly harvested organs to patients with ready cash or high-placed connections. How was that possible?

https://en.wikipedia.org/wiki/Organ_transplantation_in_China
https://en.wikipedia.org/wiki/Organ_harvesting_from_Falun_Gong_practitioners_in_China

https://twitter.com/mprobertson/status/1195151387585216512
https://archive.is/DksWj
After nearly two years, our paper on the apparent falsification of China's official organ donor registry data has been published! We used statistics to unravel state data manipulation. I believe the findings are both fascinating and important. (Thread...) https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-019-0406-6
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december 2016 by nhaliday
predictive models - Is this the state of art regression methodology? - Cross Validated
I've been following Kaggle competitions for a long time and I come to realize that many winning strategies involve using at least one of the "big threes": bagging, boosting and stacking.

For regressions, rather than focusing on building one best possible regression model, building multiple regression models such as (Generalized) linear regression, random forest, KNN, NN, and SVM regression models and blending the results into one in a reasonable way seems to out-perform each individual method a lot of times.
q-n-a  state-of-art  machine-learning  acm  data-science  atoms  overflow  soft-question  regression  ensembles  nibble  oly 
november 2016 by nhaliday
Information Processing: Search results for compressed sensing
https://www.unz.com/jthompson/the-hsu-boundary/
http://infoproc.blogspot.com/2017/09/phase-transitions-and-genomic.html
Added: Here are comments from "Donoho-Student":
Donoho-Student says:
September 14, 2017 at 8:27 pm GMT • 100 Words

The Donoho-Tanner transition describes the noise-free (h2=1) case, which has a direct analog in the geometry of polytopes.

The n = 30s result from Hsu et al. (specifically the value of the coefficient, 30, when p is the appropriate number of SNPs on an array and h2 = 0.5) is obtained via simulation using actual genome matrices, and is original to them. (There is no simple formula that gives this number.) The D-T transition had only been established in the past for certain classes of matrices, like random matrices with specific distributions. Those results cannot be immediately applied to genomes.

The estimate that s is (order of magnitude) 10k is also a key input.

I think Hsu refers to n = 1 million instead of 30 * 10k = 300k because the effective SNP heritability of IQ might be less than h2 = 0.5 — there is noise in the phenotype measurement, etc.

Donoho-Student says:
September 15, 2017 at 11:27 am GMT • 200 Words

Lasso is a common statistical method but most people who use it are not familiar with the mathematical theorems from compressed sensing. These results give performance guarantees and describe phase transition behavior, but because they are rigorous theorems they only apply to specific classes of sensor matrices, such as simple random matrices. Genomes have correlation structure, so the theorems do not directly apply to the real world case of interest, as is often true.

What the Hsu paper shows is that the exact D-T phase transition appears in the noiseless (h2 = 1) problem using genome matrices, and a smoothed version appears in the problem with realistic h2. These are new results, as is the prediction for how much data is required to cross the boundary. I don’t think most gwas people are familiar with these results. If they did understand the results they would fund/design adequately powered studies capable of solving lots of complex phenotypes, medical conditions as well as IQ, that have significant h2.

Most people who use lasso, as opposed to people who prove theorems, are not even aware of the D-T transition. Even most people who prove theorems have followed the Candes-Tao line of attack (restricted isometry property) and don’t think much about D-T. Although D eventually proved some things about the phase transition using high dimensional geometry, it was initially discovered via simulation using simple random matrices.
hsu  list  stream  genomics  genetics  concept  stats  methodology  scaling-up  scitariat  sparsity  regression  biodet  bioinformatics  norms  nibble  compressed-sensing  applications  search  ideas  multi  albion  behavioral-gen  iq  state-of-art  commentary  explanation  phase-transition  measurement  volo-avolo  regularization  levers  novelty  the-trenches  liner-notes  clarity  random-matrices  innovation  high-dimension  linear-models  grokkability-clarity 
november 2016 by nhaliday
Xavier Amatriain's answer to What is the difference between L1 and L2 regularization? - Quora
So, as opposed to what Andrew Ng explains in his "Feature selection, l1 vs l2 regularization, and rotational invariance" (Page on stanford.edu), I would say that as a rule-of-thumb, you should always go for L2 in practice.
best-practices  q-n-a  machine-learning  acm  optimization  tidbits  advice  qra  regularization  model-class  regression  sparsity  features  comparison  model-selection  norms  nibble 
november 2016 by nhaliday
Crypt on Twitter: ">the murder rate is down >yes but violent assault is up, medical advancements keep more people alive post-violence https://t.co/nJwgKOPxpw https://t.co/yfy1LB7diW"
https://twitter.com/nmgrm/status/788606525677920257
https://twitter.com/RAVerBruggen/status/754446756805509120
https://archive.is/MkXK4
https://thecrimereport.org/2016/07/16/homicide-totals-would-be-higher-without-trauma-care-advances/
https://twitter.com/RAVerBruggen/status/756512858331082752
https://archive.is/8Qi8l
http://www.theamericanconservative.com/articles/ripe-time-for-a-law-and-order-candidate/
Medical advances mask epidemic of violence by cutting murder rate: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1124155/
https://twitter.com/tcjfs/status/834437053823713281
https://archive.is/w8fsE
The far east finds the western tolerance of crime and public disorder bewildering.
Firearms and the Decline of Violence in Europe: 1200-2010: http://economics.wm.edu/wp/cwm_wp158.pdf
relatedly:
MAKE BRITAIN SAFER: BRING BACK PISTOLS: https://www.adamsmith.org/blog/liberty-justice/make-britain-safer-bring-back-handguns
https://twitter.com/bswud/status/565824180990783488
https://archive.is/ORuEr
Look at these breakpoints in violence trend when innovations made guns much cheaper
https://twitter.com/s8mb/status/817668109297389568
https://archive.is/rCdkP
^ Sarah Perry: as crime increases it gets more male
http://www.parliament.uk/business/publications/research/olympic-britain/crime-and-defence/crimes-of-the-century/
http://www.acrosswalls.org/section/gender-imprisonment/punishment-sex-ratio/punishment-trends/page/2/

The History of Homicide in the U.S.: http://sites.nationalacademies.org/cs/groups/dbassesite/documents/webpage/dbasse_083892.pdf

60s-70s:
http://justthesocialfacts.blogspot.com/2017/05/that-was-some-uptick.html
Pinker: https://quod.lib.umich.edu/h/humfig/11217607.0002.206/--decivilization-in-the-1960s?rgn=main;view=fulltext

From Swords to Words: Does Macro-Level Change in Self-Control Predict Long-Term Variation in Levels of Homicide?: https://www.researchgate.net/publication/264402032_From_Swords_to_Words_Does_Macro-Level_Change_in_Self-Control_Predict_Long-Term_Variation_in_Levels_of_Homicide
Over the past decade the idea that Europe experienced a centuries-long decline in homicide, interrupted by recurrent surges and at different speeds in different parts of the continent, became widely acknowledged. So far explanations have relied mostly on anecdotal evidence, usually broadly relying on Norbert Elias's theory of the "civilizing process." One major general theory of large-scale fluctuations in homicide rates, self-control theory, offers a wide range of hypotheses that can be tested with rigorous quantitative analyses. A number of macro-level indicators for so-cietal efforts to promote civility, self-discipline, and long-sightedness have been examined and appear to be strongly associated with fluctuations in homicide rates over the past six centuries.

https://twitter.com/Alrenous/status/1008949447223439365
https://archive.fo/hWjFP
By the way, for those of you who haven't seen the statistics first hand:
(Warning, spreadsheet)
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/116649/rec-crime-1898-2002.xls
Population has doubled.
"more serious wounding" has gone up 60 times. (So, 30 times per cap.)
Murder has only doubled. 300ish to 700ish. So, roughly in line with population. However, WWI and WWII dramatically improved trauma medicine. That's why 'wounding' can go up 30 times and murder stays constant.
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october 2016 by nhaliday

bundles : abstractacm

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