Building affordable housing ➡️ support for funding housing.
Nearby homeowners ⬆️ support; renters ⬇️ support. Both are “the policy adjacent”—secondhand recipients & drivers of policy feedback.
Forthcoming @ajpseditor.bsky.social ( doi.org/10.1111/ajps...) w/ A. Magazinnik & @msands.bsky.social 1/9
Yesterday I recorded an ep with @danieltavana.bsky.social, one of the few political scientists with an active research agenda on Iran. We spoke at length about the regime, divisions in Iranian society, the prospects for democracy in Iran. One of my best episodes to date. Link in replies.
nice point. I also think people just got used to the very low (sometimes near 0) inflation we had for a decade post-recession, making the 2022 inflation seem even more anomalous. Groceries (like gas prices) are a salient heuristic
Yep! Different estimation framework entirely but similar in spirit to this approach. I haven't read the paper you linked but looks like it builds on this one which influenced my thinking on this problem academic.oup.com/restud/artic...
In principle yes. Data requirements are: individual level Y1, Y2, X (survey); ground-truth joint distribution of X (census); known marginals of Y2 (auxiliary data). Also need svy to include relevant geographic vars to link to ground-truth Y2 (though this can be relaxed, see sec 5 of the paper)
This post has some more discussion of other methods for incorporating known ground-truth margins in an MRP framework, based on some validation exercises in osf.io/preprints/so...
This package is a companion to my paper with Josh Clinton on MRP calibration (osf.io/preprints/so...)
Please let me know if you try it out the package and email me or file a github issue if you find bugs. Thanks!
This function also works to implement the "logit shift" calibration with a single outcome — e.g. to ensure your subgroup estimates of vote choice are consistent with known election outcomes.
Picture of R package documentation for argument called "method": Calibration method, either "plugin" or "bayes". Plug-in estimates use posterior means of predictions and correlations across outcomes to compute logit shifts for calibration. Bayesian estimates compute the logit shifts separately for each posterior draw, which are then summarized. Defaults to "plugin".
The package supports both full Bayesian calibration (i.e. calibrating each draw from the posterior) as well as a plug-in estimator which works with posterior summaries.
Example code that implements a brms multilevel model with multivariate outcomes.
example of syntax for calibrate_mrp() function
calibratedMRP provides a high-level interface for doing this type of calibration. First, specify a `brms` multilevel regression model. Second, call the `calibrate_mrp()` function to calibrate cell-level estimates to known geographic margins. Third, poststratify to the target groups.
calibratedMRP implements a calibration procedure that accounts for known margins of Y2 to improve estimates of Y1.
Intuition: if your MRP model overestimates Biden vote share, it probably overestimates liberal policy attitudes too. The method implemented here accounts for this discrepancy.
Suppose you have a survey that measures policy attitudes (Y1) alongside demographics (X) and related behavior (Y2). You have population data on the joint distribution of X from the census, but only coarse geographic aggregates (e.g. election results) of Y2.
Folks doing public opinion research: I wrote an R package called `calibratedMRP` that implements methods to calibrate MRP estimates to known geographic-level ground truth (e.g. election results)
github.com/wpmarble/cal...
BJPolS abstract from a scholarly article about the perceived foreign policy failures of the US in Afghanistan and its impact on global perceptions of US leadership. The text mentions a survey across 24 countries and findings on changes in favorability after the fall of Kabul on 15 August 2021.
NEW -
Foreign Policy Failures and Global Attitudes Towards Great Powers: Evidence from the US Withdrawal from Afghanistan - https://cup.org/3YSsX4N
- @rachelmyrick.bsky.social & @wpmarble.bsky.social
#OpenAccess
blog post: 3rd helpings of the logit shift
You have multiple outcomes, but only some have aggregate truth to shift to.
How can we calibrate our estimates of p(y_1, y_2 | X) to aggregate data about E[y_1] ?
@wpmarble.bsky.social and Josh Clinton have ideas !
New paper in @ajpseditor.bsky.social. Is descriptive representation good for substantive representation? Why do voters stay loyal to corrupt and poorly governing ethnic parties? I argue that we ought to focus less on patronage and more on dignity concerns. Defiant pride can come at a price. 1/🧵
I have never seen Casablanca [embarrassing admission] but am resolved to watching it this week
My new op-ed with @lkfazio.bsky.social:
Trump sent a 'compact' to our universities. They should reject this devil's bargain.
Any institution that yields to these broad and intrusive demands would forever be subservient to the whims of the government.
www.msnbc.com/opinion/msnb...
Absolutely momentous day for California. We're turning the corner on housing at the very moment America needs us to.
Job/life update: Today was my last day at Penn, where I've been lucky to teach amazing students and work with great colleagues for the past 3 years. This fall, I'll join @hooverinstitution.bsky.social as a Hoover Fellow—I'm excited to join a vibrant, interdisciplinary community of scholars there.
I made an event timeline to try to make sense of all the federal overreach at @georgemasonu.bsky.social and whoo boy. When you lay it out like this, the executive over reach comes into focus. open.substack.com/pub/misofact...
Wow. A group of top scholars at Harvard just sent a letter to its president, Alan Garber, warning against surrendering to Trump.
Signatories include Steven Levitsky, Dani Rodrik, Ryan Enos, Theda Skocpol, and Steven Walt.
Someone forwarded it to me. Read it here:
Screenshot of title page. "The Long-Run Effects of Colleges on Civic and Political Life" by Michael J. Andrews, William Marble, and Lauren Russell. Abstract: Social theorists and education advocates have long argued for the civic benefits of education. As large, durable institutions, universities are especially likely to affect the civic life of their communities. We investigate how the establishment of a university alters the civic and political trajectory of the surrounding area. For identification, we leverage historical site selection processes in which multiple locations were considered for new colleges. We bring together data on social capital, political preferences, and elections to assess the long-run impacts of college establishment. Communities with colleges exhibit higher levels of civic engagement and greater social trust today, relative to “runner-up” locations without colleges. These counties are also more politically liberal — a gap that has grown substantially since 2000. Our findings suggest understanding universities as place-based policies that shape the long-run civic and political development of their communities. They also shed light on current political battles over higher education policy.
Universities often serve as "anchor institutions" that deeply affect the character of their communities. In a new paper, we estimate how (and when) the establishment of a college influences local political and civic life. 🧵
osf.io/preprints/so...
Nothing more American than getting a head start on work by taking a meeting in your car while you commute to work by yourself
Very cool paper about how important social networks are in driving movement
conference.nber.org/conf_papers...
I just posted a new paper on @ssrn.bsky.social, titled "The Chadha Presidency". Here's the link, and I'll post the abstract in the next post. papers.ssrn.com/sol3/papers....
Been a busy year in the data mines.📊 Just published my mid-year roundup: 29 data visualizations on the state of US democracy, tracking everything from judicial resistance to billionaire influence to why Dems have a mobilization crisis, not a moderation problem.
All charts free to use:
The current administration's attacks on universities risk undermining engines of civic life, just as they harm innovation and prosperity. Places with colleges are more liberal, yes, but colleges also promote the types of social capital that we need.
These results contribute to a literature that understands universities as place-based institutions. We know that they profoundly affect the local economy, as economists (including my co-authors) have shown. This paper documents how universities contribute to the civic life of a community as well.
