iiinova — where your digital self keeps evolving

Konstantinos Ioannidis @doctoriw.eurosky.social · 01/09/2026

⚡Session 7.3 (Discrimination) @Room 40.S16: The Impact of Qualitative Reviews in Online Markets: Empirical and Experimental Evidence on Statistical Discrimination (My scheduled paper Noriko Amano-Patiño & James Morris testing how reviews shape market outcomes and demographic penalties.)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 01/09/2026

🏃‍♂️‍➡️ Present, Q&A, sprint down the stairs two floors!

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Konstantinos Ioannidis @doctoriw.eurosky.social · 01/09/2026

⚡Session 7.10 (Social Signaling) @Room 40.147: Is Sharing Caring? Disentangling Prosociality from Virtue Signalling (Covering for my co-author @hmb2829.bsky.social testing whether symbolic actions substitute for meaningful donations)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 01/09/2026

If you catch me sprinting across @upf.edu this Friday, it's because I am presenting in two parallel sessions at the exact same time slot! 🔀

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Konstantinos Ioannidis @doctoriw.eurosky.social · 13/08/2026

Looking forward to present at the joint @eeanews.bsky.social / @econometric.bsky.social conference next week! If anyone is curious about a new General Equilibrium concept that takes into account the complexity of computing the optimal demand (and fits data much better than Walrasian Equilibrium)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/07/2026

@bkleinteeselink.bsky.social found also some evidence that higher income does not automatically translate to higher happiness, but more specifically to lower misery and more broadly lower happiness dispersion.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 09/06/2026

Fascinating talks by: Arnaud Dellis (@arnauddellis.bsky.social), Jacopo Magnani (@jmagnani.bsky.social), Adam Sanjurjo, Ferdinand Vieider, Keyu Wu, Ryan Oprea, Felix Fattinger, Miguel Ballester, Laurence Jin, Stephan Bucher, Hassan Andrabi, Roman Berlanger, Andreas Kapounek, and Peter Bossaerts.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 05/06/2026

I think 10 years ago Mourinho, Guardiola and Konte were all new managers compared to 2015, but that is 3/6 only. I can't think of any other in the PL era. Before I have no clue.

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Reposted by Konstantinos Ioannidis

The Janeway Institute, Cambridge @janewayinstitute.bsky.social · 06/05/2026

Sign up by 15th May for the 3rd Workshop on Computational Complexity & Economic Decision Making in Cambridge on 28-29 May 2026. ➡️Find out more and register yr interest here: www.janeway.econ.cam.ac.uk/event/3rd-wo...

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

We ended with an engaging debate on the two pillars of science (exploratory research and confirmatory research), and philosophised on how the term scientific method sometimes indirectly (and wrongly) implies exploratory research is less important, though hypothesis generation is equally important.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

We discussed how preregistrations and registered reports can (at least partially) address those problems. A great example within economics is the study by Katherine Casey, Rachel Glennerster @rglenner.bsky.social , and Edward Miguel academic.oup.com/qje/article-...

academic.oup.com

Reshaping Institutions: Evidence on Aid Impacts Using a Preanalysis Plan*

Abstract. Despite their importance, there is limited evidence on how institutions can be strengthened. Evaluating the effects of specific reforms is compli

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

An even more entertaining way of illustrating strategic use of language to go around explicitly using the term "insignificant results"

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

A nice comic way of illustrating HARKing

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

A nice comic way of illustrating p-hacking

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

Given the systemic incentives for academic careers, questionable (to put it mildly) practices such as p-hacking and HARKing may become tempting.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

The "dictatorship" of the 0.05 dominated (and still does to some extent) academic journals, resulting in well known problems with publication bias, false positives, and replicability challenges in various fields.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

Fisher later noted that if a researcher found p=0.10 or p=0.02, they should report it and let evidence speak for itself, but unfortunately it became the default threshold, and it still taught using words like "significant" for anything below 0.05, and "insignificant" above 0.05.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

We went on a history tour a century ago, and discovered the origins of the 0.05 threshold of significance. Fisher, 1925 wrote:"It is a common practice to judge a result significant it if is of such a magnitude that it would have been produced by chance not more than once in twenty trials."

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Konstantinos Ioannidis @doctoriw.eurosky.social · 25/03/2026

Last week I had the pleasure and honour to give a talk on the value of preregistrations and registered reports to improve the confidence we have for science to the fascinating @againstpseudocu.bsky.social .

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Konstantinos Ioannidis @doctoriw.eurosky.social · 13/03/2026

Following others around me, I migrated successfully to eurosky. A very slow process to maintain an online presence with cerefully selected providers, but a good first step!

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Konstantinos Ioannidis @doctoriw.eurosky.social · 05/03/2026

Great suggestion, I pulled it off as well, now on eurosky!

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Reposted by Konstantinos Ioannidis

Raphael Wimmer @raphaelwimmer.bsky.social · 27/01/2026

OpenAI just released Prism, a LaTeX editor with embedded ChatGPT for free. Writing a paper has never been easier. Clogging the scientific publishing pipeline has never been easier. It took me 54 seconds to write up an experiment I did not actually conduct. prism.openai.com

Screenshot of Prism - I asked it to create a methods, participants, results, and discussion seconds. It did so within 54 seconds...

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

Ultimately, we find that computational complexity is necessary for equilibration. Cognitive effort to solve complex problem is rewarded. Cognitive constraints often viewed as biases may actually be integral to how decentralised markets allocate resources! (12/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

Result 2: Equilibrium bundles exhibit substantial dispersion in utility. - Strong evidence against WE (marked with X). (11/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

Result 1: Prices reliably converge to computationally hard regions. - Compute confidence ellipsoids from data - Plot against complexity regions - Large overlap both when WE does not exist (left figure) and when it does (right figure). (10/n)

Data against phase transition in treatments where WE does not exist.

Data against phase transition in treatments where WE does exist.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

Controlled lab experiment - 20 participants per session - 15 buyers, 5 sellers per trading period - 3 indivisible goods, induced payoffs Evidence from a dataset of - 180 participants - 2,285 participant-trading periods - 17,628 trade prices - 4,121 realised trades (9/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

In CCE, agents spending higher cognitive effort find better bundles and are rewarded with higher utility. This is in sharp contrast with WE which requires utility indifference between equilibrium bundles. (8/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

In this complex region, agents with identical preferences but varying willingness to expend cognitive effort will solve the problem differently. This induced demand heterogeneity allows supply to equal demand, effectively creating the stratification needed for market clearing. (7/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

Using the prices and payoffs of goods, we can map the computational difficulty of the budget problem in a 2-dimensional space. In the yellow region, the budget problem is most difficulty to solve, both for humans and for computers. (6/n)

Phase transition of solvability of budget problem

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

The key idea is that CCE prices drive the budget problem into a “phase transition”. In this region, determining if a better bundle exists is computationally hardest. (5/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

When goods are indivisible, finding the best bundle you can afford is a computationally difficult (NP-hard) problem. Instead of assuming it away, we develop the Complexity Compensating Equilibrium (CCE) which takes into account the complexity of the budget problem. (4/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

In the simplest case, consider two agents, one indivisible good, and identical budgets b below the valuation v. If p < b, both demand it; if p > b, neither does. Market clearing fails. (3/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

A long-standing puzzle in general equilibrium theory is how markets equilibrate when goods are indivisible. A Walrasian equilibrium (WE) does not generically exist, especially with binding budgets and homogeneous preferences. (2/n)

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Konstantinos Ioannidis @doctoriw.eurosky.social · 12/01/2026

#EconSky New working paper 📝 - Revisit classic economic theory problem of general equilibrium existence - Fresh approach combining computer science and complexity - Theory + Lab experiment 🧵 + link👇

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Reposted by Konstantinos Ioannidis

Jacob Edenhofer @jacobedenhofer.bsky.social · 02/01/2026

By way of preparing for teaching and making sense of current events, I spent today trying to synthesise the demand-side literature on democratic backsliding (see figure below). The starting point of most of this literature is simple: Do voters punish politicians who violate democratic norms, or do

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Konstantinos Ioannidis @doctoriw.eurosky.social · 30/12/2025

I hope your interesting analysis of the themes of the show did not have too many spoilers because I got intrigued to watch it after I finish Stranger Things 😄

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Konstantinos Ioannidis @doctoriw.eurosky.social · 28/12/2025

Indeed, the transition to RRs has a learning curve. Cases like the ones you mention are more design issues rather than format issue. I think having such failures documented transparently is still more beneficial for the long-term scientific progress than allowing them to vanish into a file drawer.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 23/12/2025

Registered Reports are essentially a formalized, enforced version of the scientific method. They are great for reducing p-hacking and ensure informative null results get published. For any experimental economists out there, here are a few lists of journals who accept this submission format.

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Reposted by Konstantinos Ioannidis

Brendan Cantwell @cantb.bsky.social · 15/12/2025

1/ Microsoft Copilot (mostly) fabricated a quantitative study for me based on a one-sentence prompt. The prompt? "Generate an academic article which shows that right handed university presidents are more effective fundraisers."

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Reposted by Konstantinos Ioannidis

Paolo Crosetto @paolocrosetto.bsky.social · 30/11/2025

Since AI slop is again all over Scientific Reports, a thread on the economics of grey-zone publishing. Why does slop keep getting published? What does it mean for science? How can we stop this? Background readings: Understand the strain: tinyurl.com/2b6wxx5r Stop the drain: tinyurl.com/3jfscscy

An obviously AI-generated figure with AI slop and fake text all over it, recently published in Scientific Reports.

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Reposted by Konstantinos Ioannidis

Colin Camerer @cfcamerer.bsky.social · 04/12/2025

1/3 NEW our highly interdisciplinary review on habits is out. (psych, econ, animal learning, neuro) This link authors.elsevier.com/c/1mDCZc9~mJ... allows download until Jan 23 of next yr. It's partly aimed at a marketing academic audience, but covers a lot of ground of general interest.

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Reposted by Konstantinos Ioannidis

Mark A. Hanson @hansonmark.bsky.social · 11/11/2025

We wrote the Strain on scientific publishing to highlight the problems of time & trust. With a fantastic group of co-authors, we present The Drain of Scientific Publishing: a 🧵 1/n Drain: arxiv.org/abs/2511.04820 Strain: direct.mit.edu/qss/article/... Oligopoly: direct.mit.edu/qss/article/...

A table showing profit margins of major publishers. A snippet of text related to this table is below.

1. The four-fold drain
1.1 Money
Currently, academic publishing is dominated by profit-oriented, multinational companies for
whom scientific knowledge is a commodity to be sold back to the academic community who
created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis,
which collectively generated over US$7.1 billion in revenue from journal publishing in 2024
alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit
margins have always been over 30% in the last five years, and for the largest publisher
(Elsevier) always over 37%.
Against many comparators, across many sectors, scientific publishing is one of the most
consistently profitable industries (Table S1). These financial arrangements make a substantial
difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor &
Francis revenues were generated in North America, meaning that North American
researchers were charged over US$2.27 billion by just two for-profit publishers. The
Canadian research councils and the US National Science Foundation were allocated US$9.3
billion in that year.

A figure detailing the drain on researcher time.

1. The four-fold drain

1.2 Time
The number of papers published each year is growing faster than the scientific workforce,
with the number of papers per researcher almost doubling between 1996 and 2022 (Figure
1A). This reflects the fact that publishers’ commercial desire to publish (sell) more material
has aligned well with the competitive prestige culture in which publications help secure jobs,
grants, promotions, and awards. To the extent that this growth is driven by a pressure for
profit, rather than scholarly imperatives, it distorts the way researchers spend their time.
The publishing system depends on unpaid reviewer labour, estimated to be over 130 million
unpaid hours annually in 2020 alone (9). Researchers have complained about the demands of
peer-review for decades, but the scale of the problem is now worse, with editors reporting
widespread difficulties recruiting reviewers. The growth in publications involves not only the
authors’ time, but that of academic editors and reviewers who are dealing with so many
review demands.
Even more seriously, the imperative to produce ever more articles reshapes the nature of
scientific inquiry. Evidence across multiple fields shows that more papers result in
‘ossification’, not new ideas (10). It may seem paradoxical that more papers can slow
progress until one considers how it affects researchers’ time. While rewards remain tied to
volume, prestige, and impact of publications, researchers will be nudged away from riskier,
local, interdisciplinary, and long-term work. The result is a treadmill of constant activity with
limited progress whereas core scholarly practices – such as reading, reflecting and engaging
with others’ contributions – is de-prioritized. What looks like productivity often masks
intellectual exhaustion built on a demoralizing, narrowing scientific vision.

A table of profit margins across industries. The section of text related to this table is below:

1. The four-fold drain
1.1 Money
Currently, academic publishing is dominated by profit-oriented, multinational companies for
whom scientific knowledge is a commodity to be sold back to the academic community who
created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis,
which collectively generated over US$7.1 billion in revenue from journal publishing in 2024
alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit
margins have always been over 30% in the last five years, and for the largest publisher
(Elsevier) always over 37%.
Against many comparators, across many sectors, scientific publishing is one of the most
consistently profitable industries (Table S1). These financial arrangements make a substantial
difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor &
Francis revenues were generated in North America, meaning that North American
researchers were charged over US$2.27 billion by just two for-profit publishers. The
Canadian research councils and the US National Science Foundation were allocated US$9.3
billion in that year.

The costs of inaction are plain: wasted public funds, lost researcher time, compromised
scientific integrity and eroded public trust. Today, the system rewards commercial publishers
first, and science second. Without bold action from the funders we risk continuing to pour
resources into a system that prioritizes profit over the advancement of scientific knowledge.

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Konstantinos Ioannidis @doctoriw.eurosky.social · 24/10/2025

🎉Awarded Cambridge Humanities Research Grants funding🙏 Together with Noriko Amano-Patiño and James Morris, we study statistical discrimination in rental economy (e.g. AirBnb), and how qualitative information in the reviews mitigates it. Glimpse here: konstantinosioannidis.github.io/research/fak...

konstantinosioannidis.github.io

The impact of qualitative reviews in online markets: Empirical and experimental evidence on racial statistical discrimination

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