My parents chose it before I was born, then got the ultrasound and picked something else. But my mom told me as a teen what it would have been and I never forgot. When the time came, it was the obvious choice.
My parents chose it before I was born, then got the ultrasound and picked something else. But my mom told me as a teen what it would have been and I never forgot. When the time came, it was the obvious choice.
I suspect variation within regions of the US is pretty limited and highly correlated with population density, which is already a strong predictor of many social, economic, and health outcomes, but it's worth a shot. International differences probably give more variation, but the data is worse.
Figure IV, Prices and Mobile Phone Service in Kerala, from R. Jensen The digital provide: information (technology), market performance, and welfare in the south Indian fisheries sector Q. J. Econ., 122 (3) (2007), pp. 879-924 https://doi.org/10.1162/qjec.122.3.879 The figure shows price time series for 3 regions in Kerala in 2001 Rs./kg average 7:30-8:30am beach price for average sardines over 250 survey weeks. Each region is marked with a vertical line showing the date at which phones are added to the market, with introduction around week 20 for Region I, week 100 for Region II, and week 200 for Region III. In all regions, the volatility decreases markedly, rapidly, and persistently after the date of introduction, with price ranges previously varying at high frequency in the 0-14 Rs/kg range subsequently varying by only a few Rupees from week to week.
Obviously most of the time series arguments about cell phones have hopeless age-period-cohort problems. How many have been cross-checked with staggered geographical introduction? Do we have any credibly identified effects of cell phones on anything other than sardine price volatility in Kerala?
Cover of "The Means of Prediction: How AI Really Works (and Who Benefits)" by Maximilian Kasy
I read and mostly liked @maxkasy.bsky.social's book on the economics of AI, "The Means of Prediction".
I did think it could use a bit more Herbert Simon.
Long review: π
www.goodreads.com/review/show/...
Belatedly following up on the discourse on transfem depictions in art, the Rijksmuseum's new Ovid exhibition showcases Bernini's 'Sleeping Hermaphroditus' (1620) which has the integrity to show us as we truly are: sooooo sleepy. π₯±π€
God I love naps, and that mattress looks so comfy...
Hey! My guess (minor methodological dispute that mostly serves to reify a division in networks existing largely for historical and interpersonal reasons) was right!
Fortunately something like that could never happen in a real scientific discipline like Economics. π
My trick was spending my year abroad studying econometrics and math econ somewhere serious rather than using it as a vacation. There's nothing to see in England anyway!
Hoya Saxa! The cherry blossoms were nice, and I cobbled together a solid econ degree out of it. I suppose I enjoyed all those classes on Southeast Asia that had no use in my current profession. But seeing the alternative turned me into a numbers girlie.
I did SFS and the message was that IR academics are fine but have their head in the clouds and practitioners have more sense. Seeing actual practice in the Bush admin disabused me of the latter. Hence the escape into econ and econometrics. I haven't had a foreign policy opinion since!
Article is paywalled so IDK, but fear of twink death has been tied up with casual transphobia at least since "Giovanni's Room."
That and entitlement: the same thing that makes for "don't call him an egg!" under photos of a 6-months-on-HRT doll tagged #femboy just for SEO. See also "butch flight."
Really not the point, but does the author realize we're currently living in a femboy renaissance? Even subtracting the half of them who will be women in 5 years, there's now an abundance of twinks in thigh-highs not seen since the classical era thanks precisely to loosening of restrictive norms.
I really don't know, but my understanding is that the way that country works is that media is exclusively a chummy club for Oxbridge grads the same way many elite professions in the US are entirely composed of networks of Ivy League douchebags.
Not always! Sometimes they're upper-middle-class elite institution graduates from the UK.
(I've been reading some books lately with the premise that Cambridge grads who go on to be bankers and lawyers actually have rich interior emotional lives. They're surprisingly not bad despite that?)
Congratulations to Charles Manski on winning the BBVA Frontiers Award for his foundational contributions to partial identification, semiparametric methods, subjective expectations, social interactions and policy decision-making under uncertainty
www.premiosfronterasdelconocimiento.es/noticias/xvi...
"worst system of decision-making except for all the others" etc etc
This contained a nice reminder that Ben has a book coming out about computational frameworks for decision making and how he doesn't like any of them. Preordered!
Adjusting for problem difficulty is precisely the point of a regret criterion (cf my notes donskerclass.github.io/Forecasting/... donskerclass.github.io/Forecasting/... or Orabona on the sleeping case parameterfree.com/2024/05/27/b...) but Bayes can do it too with a heteroskedatic likelihood.
The SPF website has a partial bibliography including a lot about evaluation.
Individual evaluation can be challenging because individual forecasters enter and exit the survey irregularly. It does seems like a good case for a panel state space model or a sleeping experts method.
Absolutely no known relation to me (I'm not even part Irish), but the chapters on Ireland highlighted some of the pro-independence writing of the guy this is named after.
It always comes as a pleasant surprise to read about a historical figure with my surname and not have it be 100% awful.
The classic textbook is Spirtes, Glymour, and Scheines "Causation, Prediction, and Search," but I haven't used it as it's a bit dated.
Introductory overviews I found helpful were the Simons Bootcamp lectures simons.berkeley.edu/workshops/ca... and this survey:
A new blog post motivated from this amazing discussion with @akhilrao.bsky.social and @donskerclass.bsky.social
#EconSky #RStats #Stan
jamesblandecon.github.io/posts/2026-0...
Soon enough, people didn't even mention that they had used it, let alone give a proper citation. Frequently the reader was left to guess based on the plots what kind of settings they had used.
This reminds me, for the case of beta-bernoulli where the choice is A vs B vs continue rather than bet vs continue, QuantEcon has a nice series of lectures with code. Even with conjugacy you need approximate dynamic programming since the mean parameters is a continuous scalar state.
Right, the main motivation for approximate approaches here is that the dynamic program requires taking a posterior as state which is high or infinite dimensional even for a scalar continuous parameters if non-conjugate. This is why the bandit literature is so enormous!
For an econ style interpretation of what's going on here, e-values generalize a Kelly multiplicative growth criterion, while dynamic programming optimizes an additively separable expected utility. This was the dispute that provoked Samuelson's famous one-syllable words only paper
A frequentist approach to optional stopping-robust ("anytime-valid") inference is provided by a class of methods typically based on e-values, often with a betting or (super)martingale interpretation.
This Statistical Science intro paper isn't bad; Ramdas also has a book and many papers.
THANKS.
Heterogeneous agents are generally a neutral to good thing to try to understand, and there's plenty of very good research in the area. But reading published work conditions on a collider, inducing a maybe negative correlation with other good things like coherence or empirical plausibility...
I agree that signal noise level may influence how nepotistic this sorting process is and do think that a return to the pre-Samuelson aristocratic or ideological selection mechanism, with some new technical trappings, is a plausible outcome if no new clear technical niche can be found.
I kinda think elitism is basically a conserved quantity in econ, since the real raison d'etre of the field is advising real policy and the content is a sorting mechanism for who gets to be in those few positions. E.g. causal revolution replacing traditional econ logic but leaving networks in place.
Definitely a large part of the effect was a reduction in macro overall, and what remained still had plenty of flaws, with lots of bad work in technical areas not covered by Dynare that could still get by in journals due to difficulty (*cough, het agents*). But I think the field did improve on net.