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#econometrics

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MinmiTheDino

What are people’s fave methods for this situation:

At t0, all units are untreated.

As time goes on, individual units are one by one selected for treatment, on an expert’s assessment of their potential improvement under treatment.

How to measure the treatment effect, either over all units or ideally the treatment effect on each unit?

Oh, for extra fun, they’re probably not independent

#Statistics#CausalInference#Econometrics
*
Stefano Zacchiroli

New #paper out: « The impact of the #COVID19 pandemic on women’s contribution to public code » (Empir. Softw. Eng. 30(1): 25 (2025)) where we establish, using #econometrics techniques and relying on the @swheritage archive, that the pandemic disproportionately impacted women's ability to contribute to the development of public code, relatively to men. #Openaccess preprint at: hal.science/hal-04716803/

With A. Casanueva, D.Rossi, and @Zimm_i48

hal.scienceThe Impact of the COVID-19 Pandemic on Women's Contribution to Public CodeDespite its promise of openness and inclusiveness, the development of free and open source software (FOSS) remains significantly unbalanced in terms of gender representation among contributors. To assist open source project maintainers and communities in addressing this imbalance, it is crucial to understand the causes of this inequality. In this study, we aim to establish how the COVID-19 pandemic has influenced the ability of women to contribute to public code. To do so, we use the Software Heritage archive, which holds the largest dataset of commits to public code, and the difference in differences (DID) methodology from econometrics that enables the derivation of causality from historical data. Our findings show that the COVID-19 pandemic has disproportionately impacted women's ability to contribute to the development of public code, relatively to men. Further, our observations of specific contributor subgroups indicate that COVID-19 particularly affected women hobbyists, identified using contribution patterns and email address domains.
#SoftwareEngineering#opensource
R Consortium

The US Federal Reserve's FRB/US model is now available in R! 📊 Guest post by Andrea Luciani (Bank of Italy, Directorate General for Economics, Statistics and Research), maintainer of the #bimets package. Learn how to perform econometric exercises using #R.

🔗 r-consortium.org/posts/us-fede

r-consortium.orgThe U.S. Federal Reserve quarterly model in R – R Consortium
#Econometrics#FedEconomy#RStats
Akshay

New article in Nature estimates huge potential climate damages based on econometric estimates of past climate damages.

What do statisticians think about whether the methodology used makes sense? Can any such statistical approach have enough power to estimate past damages from a zillion confounding variables?

Link to study in below popular article

#Econometrics #Statistics #Climate #ClimateChange #ClimateCrisis

arstechnica.com/science/2024/0

Ars Technica · Climate damages by 2050 will be 6 times the cost of limiting warming to 2°Study tracks the past costs of climate events and projects them into the future.
Eduardo Vera-Valdes

Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊

I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.

LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊

The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.

I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!

#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @julialanguage@bird.makeup @julialanguage@mastodon.social

Maximilian Kasy

#introduction I am a Prof at Oxford.

My research lies at the intersection of several fields, including #econometrics, #machinelearning, #labor, #inequality, #AI.

Current interests include the combination of ML theory and welfare economics, adaptive experimental design, pre-analysis plans, #jobguarantee programs, and #basicincome.

I teach foundations of ML to economists.I post links to papers, talks, long-form articles etc.

Website: maxkasy.github.io/home/

Maximilian KasyMaximilian KasyResearch on machine learning, experimental design, economic inequality, and optimal policy
Martin Modrák

Is there some word for doing inferences with data you know are a sum of multiple values (e.g. just seeing row/column sums of a table, ...)? One example I have is "deconvolution" in bioinformatics, but I'd like to see more. I'd expect this would be a common problem in econometrics or similar, but I struggle to find relevant papers... Any ideas?
#econometrics #econ #stats

atecon

Trying myself on unknown terrain: Just published a working paper about the use of Large Language Models for low-resource programming languages! 🖥️👋

The study shows that #LLM-s can be a useful for writing, understanding, improving and documenting code.

I choose #gretl + its domain-specific scripting language for #statistics + #econometrics for illustration.

Comments welcome!
arxiv.org/abs/2307.13018

#softwaredevelopment #computerscience #GPT3.5 #econtwitter

@gretl

arXiv.orgThe potential of LLMs for coding with low-resource and domain-specific programming languagesThis paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.
Léo Varnet

sciencedirect.com/science/arti
"Capitalism and extreme poverty: A global analysis of real wages, human height, and mortality since the long 16th century"
Une critique détaillée de la position de #Pinker selon qui le capitalisme industriel a permis à l'humanité de sortir de la pauvreté. Je parlais de cet argumentaire et de ses détracteurs dans cette note de blog :
dbao.leo-varnet.fr/2019/08/26/
#econometrics #StevenPinker

Gretl

RT @giuseppe on twitter

"Hi #EconTwitter!📚

Planning to study or teach #econometrics at the undergrad level, with a user-friendly software?🖥️

Explore this brilliant book by Lee Adkins (
@okstate
). It's filled with 749 pages of examples and applications using
@gretl_stats
!🎓

Extremely valuable stuff!

𝐋𝐢𝐧𝐤𝐬
book (PDF), 5th edition: learneconometrics.com/gretl/po

more on Lee's page: learneconometrics.com/gretl/in
"

twitter.com/CavaliereGiu/statu

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