Jake Jares

Thrilled my paper with @namalhotra is out at @apsrjournal! Have you always been captivated by the impacts of trade policy on political behavior, applications of causal machine learning, and shocks to soybean prices? Ok well regardless this is still the paper for you! A thread 🧵

It’s impressive how far down in the comments you have to go to find someone who realizes that the sum of two dice is not normally distributed.

bröther may I direct you to the Book of Psalms

New short paper w @j_kalla! Candidates gain from moderation, but less than many theories expect. Many conclude voters must not care about issues. This is wrong. Small *average* effects mask large effects on specific issues & are consistent with widespread issue-based voting 🧵

P.S. Bonus fun fact — while it’s very early and our data isn’t ideal for assessing 2028 electability, @mcuban 's performance in the trial heats we did is literally off the charts.

omg this title, this paper

The complexity of deciding who to vote for is directly connected to turning out. In a paper that I'm currently wrapping up (any day now!) I use individual-level ballot length data from CA and find that an additional 5-6 ballot items decreases turnout by 1%

This is really a good paper and it helps put the election admin literature in good perspective. Early papers had no causal inference, showed huge effects, placed well. New paper are often empirically awesome, show small well-identified effects, and can't get placed in top-3.

@PhD_Genie Wait this works on so many levels, never seen a more accurate depiction of my dissertation

How I found the gap in the literature

Like 70% of vicious arguments on here could be resolved immediately if both parties dedicated themselves to a thorough and good faith reading of this Wikipedia article

My governor told me the hillside keeps eating his highway so I asked how many rebuilds he’s done and he said he just goes to caltrans and gets a new highway afterwards so I said it sounds like he’s just feeding the highway to the hillside and then the taxpayers started crying

BUILDING THE TRUTH MACHINE. We built a new dataset focused on political prediction markets, liquidity, and resolution rules. We find: the vast majority of political contracts on prediction markets are ghost towns — only 1.3% have enough liquidity to be worth reporting on. Kalshi and Polymarket rarely list the same contracts with the same rules, further fragmenting liquidity. This matters because AI forecasting is getting very good, and prediction markets are the natural layer for coordinating that intelligence toward the questions society needs answered. We’re not there yet. But we have a blueprint for how to build on PM’s tremendous momentum to help us get there: (1) Stock the shelves — list contracts on the questions that matter most, working with independent groups to define the markets society cares most about pricing (2) Fund the floor — pay market makers to seed liquidity in these new political markets (3) Bring in the AIs — encourage AI agents to trade where humans won't to help generate the prices society wants to know (4) Standardize the pipes — create shared definitions and resolution rules across platforms If we do this, we can get thick markets on political questions we care about. It will also attract traders who want to hedge political risk, getting the flywheel spinning, and bringing us closer to the truth machine we want. Check out the full post linked below.

it's all happening on bluesky

@andre_quentin I hear that the Bernstein–von Mises Theorem is one of their corporate values at Anthropic, you gotta let them have this one

Confidence intervals are so confusing that even Anthropic's skills documents get them wrong

@wifieatscheese Funny enough, apparently there isn't a single Canadian settlement north of the Arctic circle that has 6,000 people in it

some canadians when a big artist doesnt go to a city in the arctic circle with 6000 people in it

@_AashishReddy He was so real for that

See also Carney on his DPhil thesis:

Funny how they avoid discussing the incontrovertible evidence of data fabrication. Thread.

@OVTweetmarck How does this bit work so well every time, SMH

Six figs mostly doesn't mean anything anymore and it's definitely not enough to live on, it adds up to at most 300 calories assuming each one's large

@akoustov Fascinating piece. However, given the extreme variance in the full distribution of AME estimates, I think I was somewhat positively surprised by the size of the diff by ex-ante immigration policy stance? Certainly better overlap that I'd have guessed from the full distribution.

Another great piece on how ideological skew can shape migration research. Don't get me wrong: even biased evidence is better than policymaking by vibes or group animus. Still, this is a reminder we need more careful migration research from moderates and conservatives as well.