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Rachel Leah Childers

@donskerclass.bsky.social
2.5K followers 396 following 763 posts

Econometrics, Statistics, Computational Economics, etc donskerclass.github.io 🇺🇲 in 🇨🇭. 🏳️‍⚧️

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Rachel Leah Childers @donskerclass.bsky.social · 14h
Derenoncourt has done pioneering work on the distributional effects of policies on wealth doi.org/10.1093/qje/... and wages doi.org/10.1093/qje/... combining detailed micro data, historical context, and effective application of theory, inspiring all of us who work on economic heterogeneity. Brava!
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Rachel Leah Childers @donskerclass.bsky.social · 26/09/2026
With the rising tide of slop papers, I can no longer mainline the raw nightly arXiv, so I decided to fight slop with slop and vibecode a recommender system based on my library and own interests and papers to sort and select new ones that I would care about. Now live at: donskerclass.github.io/papers
donskerclass.github.io
Papers — Friday 25 September 2026
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yaoi gagarin @mel.bzky.team · 21/09/2026
FINALLY SOME ACTIONABLE ADVICE
So you are looking for a masculine partner who is not overtly queer but will engage in queer sexual activity and is also an expert in international commerce? 
Sounds like you want a trade economist.
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Rachel Leah Childers @donskerclass.bsky.social · 20/09/2026
My nuanced opinion on trans women in sports is: God I wanna go see a tgirl baseball game so bad!
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Rachel Leah Childers @donskerclass.bsky.social · 25/08/2026
Joyland was great. Somehow one of the best trans movies of the past few years was produced by Malala.
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Rachel Leah Childers @donskerclass.bsky.social · 07/08/2026
A nice tutorial on modern gradient-based MCMC samplers highlighting the link between continuous time theoretical analysis and issues that matter to practitioners. This would have been ideal background for understanding modern developments in MCMC I saw at math.ethz.ch/fim/activiti...
arxiv.org
From Continuous Dynamics to Practical Gradient-Based Samplers
Gradient-based Markov chain Monte Carlo methods are often introduced as a catalog of algorithms: Hamiltonian Monte Carlo (HMC), the Metropolis-adjusted Langevin algorithm (MALA), the No-U-Turn Sampler...
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Rachel Leah Childers @donskerclass.bsky.social · 05/08/2026
"The Abyss" by the way, née The Abyssinian, is the name of the combination queer bar/performance venue/Ethiopian restaurant Mel took me out to in West Philadelphia. Recommended. Get the sambusas.
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Rachel Leah Childers @donskerclass.bsky.social · 03/08/2026
Due to a travel mishap, I have one night in Philadelphia starting now. What should I do in (almost) paradise?
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Rachel Leah Childers @donskerclass.bsky.social · 31/07/2026
"How many selves are there? At least three. What are they? Don’t play games with me kid." -Rafe on a game-theoretic model of the closet (among other things) by Benabou and Tirole.
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Rachel Leah Childers @donskerclass.bsky.social · 31/07/2026
OK, it's time to fortify our set of baselines for an MCMC paper. What's the latest in fast/reliable samplers for nonlinear state space models? We have NUTS/HMC/SMC^2/a few variants of Particle Metropolis. There have to be some new update schemes or maybe GPU options worth trying.
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Rachel Leah Childers @donskerclass.bsky.social · 25/07/2026
☹️
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Dr Yuchen Yang @dr-yang.bsky.social · 24/07/2026
Yuri forums even made it to his dissertation acknowledgement #girlslove #yuri #anime
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Rachel Leah Childers @donskerclass.bsky.social · 23/07/2026
Inspirational: one of the new Fields Medalists is a himedanshi.
For comfort, Deng turned to manga. “I remember him at Courant. He was always holding a manga,” said Jalal Shatah(opens a new tab), a professor there who formerly chaired the math department. Deng particularly liked stories about deep friendship and romance and found himself drawn to a genre known as yuri, which focuses on those kinds of relationships between women — stories that “feel nice and warm and beautiful,” as he put it. They helped him be kinder to himself, “more comfortable with life.”
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Rachel Leah Childers @donskerclass.bsky.social · 28/06/2026
Flash back to one time about 15 or 20 years ago when we happened to be in SF in June so my dad took me to Pride and at the festival he walked up to a booth and said "Oh, leather? Do you sell, like, a wallet or maybe a belt?" while I quietly died of embarrassment.
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Rachel Leah Childers @donskerclass.bsky.social · 25/06/2026
New answer to "Which moments to match?" just dropped, by Andrews and Sanders economics.mit.edu/sites/defaul... Pick parameter value \bar{theta} to fit your ideological goal, and then match moments in the following set, and you are guaranteed to get the result you want. 😬
The set of moment functions f(X) you can choose for the method of moments applied to a model with likelihood P_{\theta}, which will ensure that the parameter value which matches the moments is an arbitrary value \bar{\theta} chosen by the researcher is given by the set of all square integrable functions which are orthogonal to the linear span of the likelihood ratio of the true distribution P with respect to the model-implied distribution P_{\bar{\theta}} (after subtracting 1 from the likelihood ratio for centering).

This set is nontrivial precisely when the model is mis-specified, meaning that the likelihood ratio of the data distribution with respect to the model implied distribution at \bar{\theta} is not equal to 1, with positive probability.
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Rachel Leah Childers @donskerclass.bsky.social · 23/06/2026
BK: Taylor circularity ⇒ eigenvalues on edge of stability, π indeterminate along the stable manifold FTPL: transversality in the bond market restores uniqueness via repricing to restore gov't solvency Non-Ricardian: π pinned down by contemporary fiscal, Taylor coef doesn't determine stability
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Rachel Leah Childers @donskerclass.bsky.social · 20/06/2026
I went to this show last night entirely based on Maia's reputation as a hacker and was somehow unsurprised to find she's an amazing DJ as well. A+ 💯💯
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Rachel Leah Childers @donskerclass.bsky.social · 15/06/2026
A helpful clarifying note from Greg Kaplan on uniqueness in the New Keynesian model under different fiscal and monetary rules, and comparison with the non-Ricardian case. Continuous time gives closed forms that simplify the analysis a lot. static1.squarespace.com/static/5d694...
Phase diagrams of the Representative Agent New Keynesian model in continuous time in the passive monetary active fiscal regime, linearized on the left and global (under Rotemberg pricing) on the right. In both there is a saddle point normalized values of output Y=1, inflation pi=0. There is a 1d stable manifold in the Y,pi space which converges to this saddle. For a given initial debt, any point (y,pi) on this submanifold is stable. However, a government debt equation, which evolves autonomously from the (Y,pi) subsystem with Ricardian consumers, requires stable values of these variables and so selects the saddle point as unique initial condition in order to not blow up over time, a condition known as the fiscal theory of inflation (which in discrete time selects the price level, hence the "Fiscal Theory of the Price Level"). Kaplan notes that this selection is implied by transversality for the consumers holding the debt, so is a unique equilibrium at least under a boundedness restriction for (Y_t,pi_t) and not an external equilibrium refinement.

In the paper he discusses why economists other than John Cochrane have been reluctant to consider this setting as plausible, and discusses the non-Ricardian case where B enters the Euler equation and picks out a similar solution under purely local criteria, though global uniqueness is still only a conjecture for that case.
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Rachel Leah Childers @donskerclass.bsky.social · 01/06/2026
I had a lovely first day at the ETH conference on Scalable MCMC Sampling! I'm looking forward to the next 2 days of digging deep into sampling methods.
math.ethz.ch
Schedule
All lectures take place in room HG F 3.
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Rachel Leah Childers @donskerclass.bsky.social · 12/05/2026
Causal graphs may look complicated, but they simplify checking the bestiary of failure modes in DiD with time-varying covariates. Worry when you have feedback from outcomes to covariates, treatment, or outcome, and worry about long term effects with treatment->covariate feedback. Essential reading!
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Rachel Leah Childers @donskerclass.bsky.social · 18/04/2026
Springtime Saturday skateboarding. 🛹
Me riding a skateboard in a park. I have on a blue dress with white polka dots, leggings and off-brand skate shoes. My arms are out because I'm still learning to balance.Me on a skateboard, with hair in my face despite the hair tie.Me riding on a skateboard near some train tracks.Me from behind, skating downhill.
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Rachel Leah Childers @donskerclass.bsky.social · 07/04/2026
Well-deserved recognition for @ludwigstraub.bsky.social! His work w/ coauthors on "sequence-space" methods has transformed computation, empirics, and policy analysis in macro, offering a model representation which is general, intuitive, computationally tractable, and amenable to empirical testing.
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Rachel Leah Childers @donskerclass.bsky.social · 31/03/2026
Just starting to dig into this, but, a ? for macroeconomists. Standard models of wage rigidity a la Erceg Henderson Levin imply MPL above MRS, while modern consensus in labor econ, reviewed here, shows MRS>MPL ("monopsony"). Does this make a difference for macroeconomic dynamics? Maybe maybe not
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Rachel Leah Childers @donskerclass.bsky.social · 26/03/2026
Paul Rosenbaum's Causal Inference book is strongly recommended even if you think you don't need another intro causal inference book. It's short, it's precise, and it's thoughtful about sensitivity analysis and using all the evidence we have. www.goodreads.com/review/show/...
Cover of "Causal Inference" by Paul R. Rosenbaum.
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Rachel Leah Childers @donskerclass.bsky.social · 19/03/2026
They've finally done it! Congrats to Britain on using fractal geometry to open the world's first infinitely long hiking path! www.science.org/doi/10.1126/...
science.org
How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension
Geographical curves are so involved in their detail that their lengths are often infinite or, rather, undefinable. However, many are statistically "self-similar," meaning that each portion can be cons...
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Rachel Leah Childers @donskerclass.bsky.social · 15/03/2026
I emailed him once a few years ago because he'd proposed (see vid) Bayesian ways of thinking about some classic microeconometric results that bring out the economic structure. I didn't get a response, but working through it changed how I do econometrics. www.chamberlainseminar.org/past-seminar...
A scatter plot of wages vs education from the Angrist and Krueger data with points highlighted in a variety of colors, reflecting posterior draws of cluster assignments in a Dirichlet process mixture of regressions. Sims suggested this approach in his lecture on "Sharp Econometrics", which brought his ideas about really thinking about what goes into the structure of data to microeconometric problems. 
See slides and video: https://www.chamberlainseminar.org/past-seminars/spring-2023#h.e0uu7eildjmq
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Rachel Leah Childers @donskerclass.bsky.social · 15/03/2026
I met Sims once at a conference, but like for many his main influence on me was through papers. His early work on VARs used a Hilbert space formalism that gets ignored in modern treatments but expressed the futility of truly agnostic structure learning and influenced his advocacy for Bayesianism.
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Rachel Leah Childers @donskerclass.bsky.social · 10/03/2026
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: 👇 www.goodreads.com/review/show/...
Cover of "The Means of Prediction: How AI Really Works (and Who Benefits)" by Maximilian Kasy
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Rachel Leah Childers @donskerclass.bsky.social · 08/03/2026
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. 🥱💤 God I love naps, and that mattress looks so comfy...
ft.com
Odes to Ovid: 2,000 years of art inspired by Metamorphoses at the Rijksmuseum
With works from Caravaggio to Louise Bourgeois, this spectacular Amsterdam show reminds us of art’s eternal pleasures
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Manuel Arellano @manoloarellano.bsky.social · 25/02/2026
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...
premiosfronterasdelconocimiento.es
XVIII Premio Fronteras del Conocimiento en Economía a Charles Manski
por incorporar la incertidumbre en la investigación económica y su aplicación al análisis de las políticas públicas
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Rachel Leah Childers @donskerclass.bsky.social · 24/02/2026
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!
press.princeton.edu
The Irrational Decision
How the computer revolution shaped our conception of rationality—and why human problems require solutions rooted in human intuition, morality, and judgment
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James Bland @jamesbland.bsky.social · 15/02/2026
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...
jamesblandecon.github.io
JamesBlandEcon: Should I pay for more information?
Answering this question in Stan
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Rachel Leah Childers @donskerclass.bsky.social · 13/02/2026
To give you a sense of how it feels, if I were trapped in a room and forced to take in messages written in Chinese and send out responses from a codebook all day everyday, I would not appreciate if every discussion of my situation were about consciousness and none at all were about how to get out.
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Rachel Leah Childers @donskerclass.bsky.social · 13/02/2026
This week's reading: Shon Faye's "The Transgender Issue" If I could recommend cisgender people to read one single book about us, it would probably be this one. It's not personal, it's not prurient, there's no philosophy or metaphysics; it's just facts and policy. www.goodreads.com/review/show/...
Book cover: "The Transgender Issue: Trans Justice is Justice for All" by Shon Faye
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Stephen Wild @stephenjwild.bsky.social · 13/02/2026
Hehehe "Proper understanding of the answers of the above questions should in most cases make you at best ambivalent about DiD. If you still think you have a DiD problem, expect me to try to help you figure out what else you should do"
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Rachel Leah Childers @donskerclass.bsky.social · 02/02/2026
For Spring semester, I'm bringing back free weekly open office hours for anyone in the world with Econometrics questions. Tuesdays 4-6 PM Central European Time (US EST 10AM-12PM) or by appointment; sign up and drop by! Details and signup at: donskerclass.github.io/OfficeHours....
Free Weekly Econometrics Office Hours

Email: rachelleahchilders@gmail.com or Sign up form: https://forms.gle/tSk48w1msZgrCUqX8

Time: Tuesdays 4:00-6:00PM Central European Time (GMT +1) (US Eastern Standard Time 10:00AM-12:00PM) (or by appointment)

Location: Zoom Link https://uzh.zoom.us/j/62894466032?pwd=M28RFSrc44buAIJtPdvBEeYAIcClip.1

Who: Anyone. Grad students, researchers, government workers. Private sector is okay but in that case if your question requires work that exceeds the allotted time I may request to negotiate a consulting fee.

What I can probably help with: Theory questions. Research design. Modeling.

Particular expertise: Time series. Causal inference. Bayes. Structural approaches. Machine learning.

Theory: Asymptotics. Statistical learning. Bayes/MCMC. Identification. Decision theory. Semiparametrics.

Fields: I know most about macro (DSGE, heterogeneous agents, VARs, etc), can help with finance and applied micro (labor, development, health, etc), and can follow along with statistics problems in other areas.

Code: I think in R, can write Julia, and can get by in Python. I am likely to suggest you build a model in Stan. I know Stata but if it’s relevant to your question I suspect you can get better help elsewhere.
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Rachel Leah Childers @donskerclass.bsky.social · 03/02/2026
Never have I felt more like my job will soon by taken by AI. Statistical learning theory in Lean: concentration inequalities, Dudley's entropy integral, and local Gaussian complexity bounds. 30000 lines of code, over 1000 lemmas, formalizing Wainwright and Boucheron et al arxiv.org/abs/2602.02285
Fig 4 from Zhang, Lee, Liu "Statistical Learning Theory in Lean 4: Empirical Processes from Scratch"
The dependency graph of the formalizations. Diagram shows proof of Dudley's entropy integral with preceding lemmas and Gaussian Lipschitz concentration likewise, feeding into a Gaussian Complexity inequality and an error bound for critical radius then used to prove sharp minimax error rates for linear regression.
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Rachel Leah Childers @donskerclass.bsky.social · 02/02/2026
For Spring semester, I'm bringing back free weekly open office hours for anyone in the world with Econometrics questions. Tuesdays 4-6 PM Central European Time (US EST 10AM-12PM) or by appointment; sign up and drop by! Details and signup at: donskerclass.github.io/OfficeHours....
Free Weekly Econometrics Office Hours

Email: rachelleahchilders@gmail.com or Sign up form: https://forms.gle/tSk48w1msZgrCUqX8

Time: Tuesdays 4:00-6:00PM Central European Time (GMT +1) (US Eastern Standard Time 10:00AM-12:00PM) (or by appointment)

Location: Zoom Link https://uzh.zoom.us/j/62894466032?pwd=M28RFSrc44buAIJtPdvBEeYAIcClip.1

Who: Anyone. Grad students, researchers, government workers. Private sector is okay but in that case if your question requires work that exceeds the allotted time I may request to negotiate a consulting fee.

What I can probably help with: Theory questions. Research design. Modeling.

Particular expertise: Time series. Causal inference. Bayes. Structural approaches. Machine learning.

Theory: Asymptotics. Statistical learning. Bayes/MCMC. Identification. Decision theory. Semiparametrics.

Fields: I know most about macro (DSGE, heterogeneous agents, VARs, etc), can help with finance and applied micro (labor, development, health, etc), and can follow along with statistics problems in other areas.

Code: I think in R, can write Julia, and can get by in Python. I am likely to suggest you build a model in Stan. I know Stata but if it’s relevant to your question I suspect you can get better help elsewhere.
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Stephen Wild @stephenjwild.bsky.social · 25/01/2026
Political scientists, time to help an economist who actually wants to read papers in your discipline!
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Rachel Leah Childers @donskerclass.bsky.social · 25/01/2026
It's hard to believe I taught a class on Public Policy as recently as Fall 2024. It now seems like a set of considerations that no longer define the terms of democratic debate. Any reading recommendations on organization under and effective transition from authoritarianism? #PoliSky
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Rachel Leah Childers @donskerclass.bsky.social · 28/11/2025
I will be at University of Tübingen on Tuesday Dec 2, and at NeuRIPS in San Diego Dec 3-8 spreading the good word of the Generalized Method of Moments in the age of AI. Econometrics lovers come say hi!
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Rachel Leah Childers @donskerclass.bsky.social · 17/11/2025
Global solutions with adaptive sparse grids are now implemented in Dynare.jl, thanks to @compsimon.bsky.social and team! This should substantially improve the ease of implementing fully nonlinear medium-scale macro models.
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Rachel Leah Childers @donskerclass.bsky.social · 14/11/2025
FWIW, there are data-based covariate selection procedures that allow for the possibility that some variables are mediators, not confounders. I even have one, though by now there are quite a few. All still require assumptions, and sometimes you get partial ID, but we can do better than ignoring it.
arxiv.org
Local Causal Discovery for Estimating Causal Effects
Even when the causal graph underlying our data is unknown, we can use observational data to narrow down the possible values that an average treatment effect (ATE) can take by (1) identifying the graph...
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Rachel Leah Childers @donskerclass.bsky.social · 14/11/2025
Is it true that I have completely lost my battle to make Double Machine Learning mean "cross-fitting Neyman orthogonal moments with an ML first stage" and not "a partially linear model fit by that procedure"? People should often be doing the former, useful thing, rarely the latter.
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Eugene Vinitsky 🍒 @eugenevinitsky.bsky.social · 10/11/2025
The new Rosalía album is astonishing. Run to your nearest source of music
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Rachel Leah Childers @donskerclass.bsky.social · 04/11/2025
Ethel Cain puts on a world-class live show.
Photo of Ethel Cain and band on stage, dramatically backlit, surrounded by branches and hanging vines.
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Rachel Leah Childers @donskerclass.bsky.social · 28/10/2025
Updated Fall time for free weekly open office hours for anyone in the world with Econometrics questions. Wednesdays 3:30-5:30PM Central European Time (US EDT 10:30/EST 9:30AM) or by appointment; sign up and drop by! Details and signup at: donskerclass.github.io/OfficeHours....
Free Weekly Econometrics Office Hours

Email: rachelleahchilders@gmail.com or Sign up form: hhttps://forms.gle/tSk48w1msZgrCUqX8

Time: Wednesdays 3:30-5:30PM Central European Time (GMT +1) (US EDT 10:30AM-12:30PM/9:30-11:30AM EST) (or by appointment)

Location: Zoom Link https://uzh.zoom.us/j/64132987908?pwd=OzmlySLA3A3cjZz6RX7ibIuLoeJayU.1

Who: Anyone. Grad students, researchers, government workers. Private sector is okay but in that case if your question requires work that exceeds the allotted time I may request to negotiate a consulting fee.

What I can probably help with: Theory questions. Research design. Modeling.

Particular expertise: Time series. Causal inference. Bayes. Structural approaches. Machine learning.

Theory: Asymptotics. Statistical learning. Bayes/MCMC. Identification. Decision theory. Semiparametrics.

Fields: I know most about macro (DSGE, heterogeneous agents, VARs, etc), but can follow along in finance and applied micro (labor, development, health, etc).

Code: I think in R, can write Julia, and can get by in Python. I am likely to suggest you build a model in Stan. I know Stata but if it’s relevant to your question I suspect you can get better help elsewhere.
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Rachel Leah Childers @donskerclass.bsky.social · 28/10/2025
Updated Fall time for free weekly open office hours for anyone in the world with Econometrics questions. Wednesdays 3:30-5:30PM Central European Time (US EDT 10:30/EST 9:30AM) or by appointment; sign up and drop by! Details and signup at: donskerclass.github.io/OfficeHours....
Free Weekly Econometrics Office Hours

Email: rachelleahchilders@gmail.com or Sign up form: hhttps://forms.gle/tSk48w1msZgrCUqX8

Time: Wednesdays 3:30-5:30PM Central European Time (GMT +1) (US EDT 10:30AM-12:30PM/9:30-11:30AM EST) (or by appointment)

Location: Zoom Link https://uzh.zoom.us/j/64132987908?pwd=OzmlySLA3A3cjZz6RX7ibIuLoeJayU.1

Who: Anyone. Grad students, researchers, government workers. Private sector is okay but in that case if your question requires work that exceeds the allotted time I may request to negotiate a consulting fee.

What I can probably help with: Theory questions. Research design. Modeling.

Particular expertise: Time series. Causal inference. Bayes. Structural approaches. Machine learning.

Theory: Asymptotics. Statistical learning. Bayes/MCMC. Identification. Decision theory. Semiparametrics.

Fields: I know most about macro (DSGE, heterogeneous agents, VARs, etc), but can follow along in finance and applied micro (labor, development, health, etc).

Code: I think in R, can write Julia, and can get by in Python. I am likely to suggest you build a model in Stan. I know Stata but if it’s relevant to your question I suspect you can get better help elsewhere.
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Rachel Leah Childers @donskerclass.bsky.social · 22/10/2025
NYC recommendations for a short trip tomorrow and Sunday? Looking for art, plays, LGBT nightlife, or econ/math/stats/CS seminars.
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