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#econometrics — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #econometrics, aggregated by home.social.

  1. ⭐ It's official now! ✨ Our latest paper is out in the Journal of Econometrics 💫 doi.org/10.1016/j.jeconom.2025

    ⭐ Partial identification of structural vector autoregressions with non-centred stochastic volatility 💛

  2. ⭐ It's official now! ✨ Our latest paper is out in the Journal of Econometrics 💫 doi.org/10.1016/j.jeconom.2025

    ⭐ Partial identification of structural vector autoregressions with non-centred stochastic volatility 💛

    #econometrics #bsvars #identification #verification #fiscal

  3. 📊 Turning data into business insights with analytics & AI.

    🎓 Master Business Analytics & Econometrics (M.Sc.)

    ✨ Analytics, AI & machine learning
    ✨ Hands-on skills in R, Python & econometrics
    ✨ International career opportunities in data & consulting

    🔗uni.koeln/R86FF

    #BusinessAnalytics #Econometrics #UniversityOfCologne

  4. 📊 Turning data into business insights with analytics & AI.

    🎓 Master Business Analytics & Econometrics (M.Sc.)

    ✨ Analytics, AI & machine learning
    ✨ Hands-on skills in R, Python & econometrics
    ✨ International career opportunities in data & consulting

    🔗uni.koeln/R86FF

    #BusinessAnalytics #Econometrics #UniversityOfCologne

  5. I've been reading about missForest today

    MissForest—non-parametric missing value imputation for mixed-type data

    academic.oup.com/bioinformatic

    github.com/stekhoven/missForest

    Runs much faster than `{mice}` in my experience, and I like the fewer parametric assumptions.

    The above article on missForest is David Stekhoven and Peter Bühlmann's most cited article.

    #DataScience #statistics #academia #econometrics #Epidemiology

  6. I've been reading about missForest today

    MissForest—non-parametric missing value imputation for mixed-type data

    academic.oup.com/bioinformatic

    github.com/stekhoven/missForest

    Runs much faster than `{mice}` in my experience, and I like the fewer parametric assumptions.

    The above article on missForest is David Stekhoven and Peter Bühlmann's most cited article.

    #DataScience #statistics #academia #econometrics #Epidemiology

  7. Fun fact: the Europe, Australasia, and Far East index of stock markets includes precisely four Asian countries: Israel, Singapore, Hong Kong, and Japan. Those are the only countries with sufficiently large and stable stock markets that the economists at MSCI put them in the same category as Germany or New Zealand. #investing #econometrics

  8. Alright! Today we premiered the logo of my subject Quantitative Methods 1. Ofc, it presents linear regression output. My question to you is: what's the applied problem we're talking about here? Can you guess?

    Reproduction scripts: github.com/donotdespair/naklej

  9. Alright! Today we premiered the logo of my subject Quantitative Methods 1. Ofc, it presents linear regression output. My question to you is: what's the applied problem we're talking about here? Can you guess?

    Reproduction scripts: github.com/donotdespair/naklej

    #qm1 #unimelb #econometrics #rstats

  10. Maximising the value of a portfolio. Using #Variance, CoVariance and Portfolio Variance. Briefly Variance is the deviation of a stock’s return with its own average returns, Co variance on the other hand is the variance of a stock’s return with respect to another stocks’ return. financemetrics.scienceontheweb Using #Matrix Algebra in a 5 Company Model. #economics #econometrics

  11. Maximising the value of a portfolio. Using #Variance, CoVariance and Portfolio Variance. Briefly Variance is the deviation of a stock’s return with its own average returns, Co variance on the other hand is the variance of a stock’s return with respect to another stocks’ return. financemetrics.scienceontheweb Using #Matrix Algebra in a 5 Company Model. #economics #econometrics

  12. I’ve been trying to read more carefully about instrumental variables and make up my mind about when IV arguments are scientifically convincing.

    Here's a tension I keep running into:

    Should the scientific question alone determine the causal parameter of interest?

    Or is it legitimate for the target parameter to reflect an interplay between scientific interest and the identifying assumptions we actually find tenable?

    IVs can be difficult to interpret when instruments are weak, who “compliers” are is opaque, exclusion restrictions are debatable, or linear models are used in settings where the true data-generating process may be nonlinear.

    On the other hand, when an entire body of (aspirationally causal) literature rests on methods that try to close backdoor paths, IVs offer a genuinely different identification strategy. That seems valuable for evidence triangulation, even if IV analyses have their criticisms.

    What do you think? Are you a big IV proponent? Are you an IV critic?

    When do you find IV evidence persuasive?

    Some literature I've been reading & re-reading:

    pubmed.ncbi.nlm.nih.gov/167552

    academic.oup.com/ije/article/4

    pmc.ncbi.nlm.nih.gov/articles/

    arxiv.org/abs/2402.09332

    arxiv.org/abs/2402.05639

    #CausalInference #InstrumentalVariables #Econometrics #Statistics #DataScience #HealthPolicy

  13. I’ve been trying to read more carefully about instrumental variables and make up my mind about when IV arguments are scientifically convincing.

    Here's a tension I keep running into:

    Should the scientific question alone determine the causal parameter of interest?

    Or is it legitimate for the target parameter to reflect an interplay between scientific interest and the identifying assumptions we actually find tenable?

    IVs can be difficult to interpret when instruments are weak, who “compliers” are is opaque, exclusion restrictions are debatable, or linear models are used in settings where the true data-generating process may be nonlinear.

    On the other hand, when an entire body of (aspirationally causal) literature rests on methods that try to close backdoor paths, IVs offer a genuinely different identification strategy. That seems valuable for evidence triangulation, even if IV analyses have their criticisms.

    What do you think? Are you a big IV proponent? Are you an IV critic?

    When do you find IV evidence persuasive?

    Some literature I've been reading & re-reading:

    pubmed.ncbi.nlm.nih.gov/167552

    academic.oup.com/ije/article/4

    pmc.ncbi.nlm.nih.gov/articles/

    arxiv.org/abs/2402.09332

    arxiv.org/abs/2402.05639

    #CausalInference #InstrumentalVariables #Econometrics #Statistics #DataScience #HealthPolicy

  14. Hi @geneshackman ,

    #Gretl has a GUI (incl. an editor + terminal). You can steer gretl it via the GUI or via pure scripting.

    Website: gretl.sourceforge.net/

    Additional resources & links : github.com/gretl-project/mater

    Link to manual and references:
    gretl.sourceforge.net/#man

    Let us know if you need more information.

    #econometrics #statistics #datascience

  15. Identification and Semiparametric Estimation of Conditional Means from Aggregate Data
    arxiv.org/pdf/2509.20194
    Ecological inference is the challenge of estimating subgroup behavior using only aggregate data like geographic averages. This paper introduces a new semiparametric method using debiased #machineLearning to improve estimate accuracy. The approach formalizes identifying assumptions and uses many covariates to minimize statistical bias. Tools for sensitivity analysis and unit-level estimation ensure results remain #robust under varying conditions. Tests on voting and pollution data show this method outperforms traditional models in precision and speed.
    #Rstats package: corymccartan.com/seine/
    #ecologicalinference #machinelearning #statistics #econometrics

  16. Identification and Semiparametric Estimation of Conditional Means from Aggregate Data
    arxiv.org/pdf/2509.20194
    Ecological inference is the challenge of estimating subgroup behavior using only aggregate data like geographic averages. This paper introduces a new semiparametric method using debiased #machineLearning to improve estimate accuracy. The approach formalizes identifying assumptions and uses many covariates to minimize statistical bias. Tools for sensitivity analysis and unit-level estimation ensure results remain #robust under varying conditions. Tests on voting and pollution data show this method outperforms traditional models in precision and speed.
    #Rstats package: corymccartan.com/seine/
    #ecologicalinference #machinelearning #statistics #econometrics

  17. Analysis of Financial Time Series 3rd Edition by Ruey S. Tsay (PDF)
    Author: Ruey S. Tsay
    File Type: PDF
    Download at sci-books.com/analysis-of-fina
    #Econometrics, #RueyS.Tsay

  18. Analysis of Financial Time Series 3rd Edition by Ruey S. Tsay (PDF)
    Author: Ruey S. Tsay
    File Type: PDF
    Download at sci-books.com/analysis-of-fina
    #Econometrics, #RueyS.Tsay

  19. Don't miss today's #DiSCourseSeminar with Vaarun Vijairaghavan from the University of Calgary, Canada, at 12:00 (CET). You can join onsite at the DiSC, Innrain 15, 6020 Innsbruck or remotely via Big Blue Button: webconference.uibk.ac.at/b/car

    Topic: Fair Play for Fair Pay: Fighting Digital Piracy through Revenue Sharing

    #InformationSystems
    #ResearchTalk
    #DigitalPiracy
    #CopyrightInfringement
    #Modeling
    #Econometrics

  20. Don't miss today's #DiSCourseSeminar with Vaarun Vijairaghavan from the University of Calgary, Canada, at 12:00 (CET). You can join onsite at the DiSC, Innrain 15, 6020 Innsbruck or remotely via Big Blue Button: webconference.uibk.ac.at/b/car

    Topic: Fair Play for Fair Pay: Fighting Digital Piracy through Revenue Sharing

    #InformationSystems
    #ResearchTalk
    #DigitalPiracy
    #CopyrightInfringement
    #Modeling
    #Econometrics

  21. Gretl version 2026a is now available. Key updates include:

    - RNG: Mersenne Twister replaced by xoshiro256+.
    - Estimation: QR decomposition for binary logit/probit Hessian stability.
    - Commands: New --head/--tail for 'print'.
    - Accessors: Improved $coeff and $stderr for multiple-tau quantreg.
    - Bug fixes: Resolved crashes in mat2list() and kdsmooth(); fixed MPI issues in regls().

    Changelog: gretl.sourceforge.net/ChangeLo

    #Gretl #Econometrics #Statistics #DataScience #OpenSource

  22. Gretl version 2026a is now available. Key updates include:

    - RNG: Mersenne Twister replaced by xoshiro256+.
    - Estimation: QR decomposition for binary logit/probit Hessian stability.
    - Commands: New --head/--tail for 'print'.
    - Accessors: Improved $coeff and $stderr for multiple-tau quantreg.
    - Bug fixes: Resolved crashes in mat2list() and kdsmooth(); fixed MPI issues in regls().

    Changelog: gretl.sourceforge.net/ChangeLo

    #Gretl #Econometrics #Statistics #DataScience #OpenSource

  23. Asymptotic Chaos Expansions in Finance: Theory and Practice (Springer Finance) 2014th Edition by David Nicolay (PDF)
    Author: David Nicolay
    File Type: PDF
    Download at sci-books.com/asymptotic-chaos
    #Econometrics, #DavidNicolay

  24. Asymptotic Chaos Expansions in Finance: Theory and Practice (Springer Finance) 2014th Edition by David Nicolay (PDF)
    Author: David Nicolay
    File Type: PDF
    Download at sci-books.com/asymptotic-chaos
    #Econometrics, #DavidNicolay

  25. 🎉 Gretl 2025c is here!
    Exciting updates to your favorite econometrics toolkit! Version 2025c brings powerful new features and improvements:

    ✨ New Features:
    Gibbs sampler command for Bayesian analysis is available now!

    🚀 Performance & Quality:
    Faster forward stepwise regression

    🎨 GUI Enhancements:
    Better dbnomics search integration
    Improved dark theme support

    Full changelog:

    gretl.sourceforge.net/ChangeLo

    #gretl #econometrics #opensource #statistics #datascience #economics #timeseries

  26. AI’s $1 trillion bet - is it an #AI bubble or dot-com bust? Global data‑center capital expenditure to power AI is projected to rise from roughly $430 billion this year to over $1.1 trillion by 2029 (which is equal to the GDP of the Netherlands). Why it matters:
    We’re witnessing an infrastructure boom that echoes a familiar pattern in tech history but the question is whether it’s building toward lasting transformation or racing toward collapse.

    Capital is pouring into data centers, cooling systems, power infrastructure, and networks at a staggering pace. Yet most AI applications haven’t proven they can generate sustainable revenue at scale.

    BTW, this article is a good one, even though it bears the hallmarks of some AI input. I’m tired of hearing about #AISlop from folks who don’t even read materials to determine if they deliver meaningful content. I use AI as my research & brainstorming asst. It works.

    jeffbullas.com/ai-bubble-or-do #ArtificialIntelligence #economy #econometrics #markets #finance #technology

  27. AI’s $1 trillion bet - is it an #AI bubble or dot-com bust? Global data‑center capital expenditure to power AI is projected to rise from roughly $430 billion this year to over $1.1 trillion by 2029 (which is equal to the GDP of the Netherlands). Why it matters:
    We’re witnessing an infrastructure boom that echoes a familiar pattern in tech history but the question is whether it’s building toward lasting transformation or racing toward collapse.

    Capital is pouring into data centers, cooling systems, power infrastructure, and networks at a staggering pace. Yet most AI applications haven’t proven they can generate sustainable revenue at scale.

    BTW, this article is a good one, even though it bears the hallmarks of some AI input. I’m tired of hearing about #AISlop from folks who don’t even read materials to determine if they deliver meaningful content. I use AI as my research & brainstorming asst. It works.

    jeffbullas.com/ai-bubble-or-do #ArtificialIntelligence #economy #econometrics #markets #finance #technology

  28. 👽 There it is! 👾 Our new and shiny paper for the Journal of Econometrics! 🤖
    doi.org/10.1016/j.jeconom.2025 🚀

    In this paper:
    ✅ we provide general conditions for partial identification of Structural VARs through heteroskedasticity
    ✅ we show that it's great for analysing fiscal policy effects on the economy
    ✅ it's the methodological paper for my bsvars package

    👇

  29. 👽 There it is! 👾 Our new and shiny paper for the Journal of Econometrics! 🤖
    doi.org/10.1016/j.jeconom.2025 🚀

    In this paper:
    ✅ we provide general conditions for partial identification of Structural VARs through heteroskedasticity
    ✅ we show that it's great for analysing fiscal policy effects on the economy
    ✅ it's the methodological paper for my bsvars package

    👇

    #econometrics #1000hofComputations #itwaswothit

  30. CPC-CG members Professor Jackie Wahba OBE and Professor Athina Vlachantoni have been announced as #REF 2029 Sub-panel members for #Economics and #Econometrics, and #SocialWork and #SocialPolicy, respectively.

    They join CPC-CG Director Professor Jane Falkingham CBE who is Chair of Main Panel C– #SocialSciences. Full story: cpc.ac.uk/news/latest_news/?ac

    #researchexcellenceframework #demography #research #socialscience #ageing #migration #economist

  31. 從檢定發現美國失業率是廣義極值分配特性。同時,Gumbel,type I有機率密度函數,真實告訴你美國失業率的機率模型,而不是出一張圖代表存在機率模型。

    以上這些方法都是超越傳統AI的數據分析方法,真正從數據本質出發打造精確統計模型,解決通用模型無法捕捉真實數據規律的難題,通過自動化建模過程揭示隱藏的數學規律。

    你學的是落在哪種層次呢?

    直線建模能做到,當然非線性的人工智慧自動化建模同樣能做到。數據規律的數學化、自動化(更新+建模+模擬)、強大而直觀的統計分析工具集成,統計學習達成。

    其中一種非線性建模:x.com/meiyulee357/status/19632

    @academicchatter @econometrics @ida

    #AI #數據分析 #失業 #美國 #經濟 #計量經濟 #modelling #econometrics #unemployment #Statistics #USA #dataanalysis

  32. 從檢定發現美國失業率是廣義極值分配特性。同時,Gumbel,type I有機率密度函數,真實告訴你美國失業率的機率模型,而不是出一張圖代表存在機率模型。

    以上這些方法都是超越傳統AI的數據分析方法,真正從數據本質出發打造精確統計模型,解決通用模型無法捕捉真實數據規律的難題,通過自動化建模過程揭示隱藏的數學規律。

    你學的是落在哪種層次呢?

    直線建模能做到,當然非線性的人工智慧自動化建模同樣能做到。數據規律的數學化、自動化(更新+建模+模擬)、強大而直觀的統計分析工具集成,統計學習達成。

    其中一種非線性建模:x.com/meiyulee357/status/19632

    @academicchatter @econometrics @ida

    #AI #數據分析 #失業 #美國 #經濟 #計量經濟 #modelling #econometrics #unemployment #Statistics #USA #dataanalysis

  33. 如何建構美國失業率的機率模型?機率模型最後要有數學式顯示,不能只是圖形。

    1) 直方圖?別想了,沒有數學式。只是圖像視覺化,不是數據分析,也不是人工智慧該有的數據模型。【不合格】
    2) 用直方圖的組中點和對應機率值?11組可以使用AI-based piecewise linear regression method的結果是兩段直線。整體的R2達73%。【合格】
    3) 建立更多分組的直方圖產生組中點與機率值。運用AI-based piecewise linear regressin method,產生9段直線。整體的R2達93%。【合格】
    4) 運用適合度檢定,檢定45種機率分配?發現美國失業率的機率模型服從Gumbel,type I(a=0.68,b=27.82)。根據a值升序模擬產生條件機率分配。【合格】

    @academicchatter @econometrics @ida

    #AI #數據分析 #失業 #美國 #經濟 #計量經濟 #modelling #econometrics #Statistics #artificialintelligence

  34. 如何建構美國失業率的機率模型?機率模型最後要有數學式顯示,不能只是圖形。

    1) 直方圖?別想了,沒有數學式。只是圖像視覺化,不是數據分析,也不是人工智慧該有的數據模型。【不合格】
    2) 用直方圖的組中點和對應機率值?11組可以使用AI-based piecewise linear regression method的結果是兩段直線。整體的R2達73%。【合格】
    3) 建立更多分組的直方圖產生組中點與機率值。運用AI-based piecewise linear regressin method,產生9段直線。整體的R2達93%。【合格】
    4) 運用適合度檢定,檢定45種機率分配?發現美國失業率的機率模型服從Gumbel,type I(a=0.68,b=27.82)。根據a值升序模擬產生條件機率分配。【合格】

    @academicchatter @econometrics @ida

    #AI #數據分析 #失業 #美國 #經濟 #計量經濟 #modelling #econometrics #Statistics #artificialintelligence

  35. 美國貨幣供給量的增加,維持近20個月的穩定增長。從2023年12月到2025年7月,平均每月增加673.29699億美元。2025年3月接近2022年3月的金額,4月突破2022年3月的金額,6與7月的貨幣供給量再次超過2022年3月的金額。

    #美國 #經濟 #財經 #貨幣 #M2 #AI #MathAI #AI數據分析 #economy #economics #econometrics #econdon #usa

  36. 美國貨幣供給量的增加,維持近20個月的穩定增長。從2023年12月到2025年7月,平均每月增加673.29699億美元。2025年3月接近2022年3月的金額,4月突破2022年3月的金額,6與7月的貨幣供給量再次超過2022年3月的金額。

    #美國 #經濟 #財經 #貨幣 #M2 #AI #MathAI #AI數據分析 #economy #economics #econometrics #econdon #usa

  37. Yet another disturbing trend to be concerned about…Margin debt just hit a high.
    “Margin debt is often seen as a measure of investor sentiment and risk appetite. High levels of margin debt can signal confidence, but extreme spikes may also indicate excessive speculation, increasing the risk of market instability.
    “Margin debt reached a new all-time high of $1.02 trillion in July, according to the latest data from FINRA. This represents a 1.5% rise from June and marks the third straight monthly increase. The debt level is up 26.1% compared to one year ago.” #economy #finance #markets #StockMarket #investments #economics #econometrics

    advisorperspectives.com/dshort

  38. Yet another disturbing trend to be concerned about…Margin debt just hit a high.
    “Margin debt is often seen as a measure of investor sentiment and risk appetite. High levels of margin debt can signal confidence, but extreme spikes may also indicate excessive speculation, increasing the risk of market instability.
    “Margin debt reached a new all-time high of $1.02 trillion in July, according to the latest data from FINRA. This represents a 1.5% rise from June and marks the third straight monthly increase. The debt level is up 26.1% compared to one year ago.” #economy #finance #markets #StockMarket #investments #economics #econometrics

    advisorperspectives.com/dshort

  39. Hey! Save the date as my new presentation for fantastic 🇺🇦Workshops for Ukraine 🇺🇦 by Dariia Mykhailyshyna is coming up on Sep 25! And it's about:

    💙 Intro to C++ programming for R applications for Econometricians 💛

    Register following the instructions at: sites.google.com/view/dariia-m

    Nice! ❤️🇺🇦

  40. Hey! Save the date as my new presentation for fantastic 🇺🇦Workshops for Ukraine 🇺🇦 by Dariia Mykhailyshyna is coming up on Sep 25! And it's about:

    💙 Intro to C++ programming for R applications for Econometricians 💛

    Register following the instructions at: sites.google.com/view/dariia-m

    Nice! ❤️🇺🇦

    #IsupportUkraine #UKR #cpp4Rapp #rstats #econometrics #Rcpp #RcppArmadillo

  41. "One danger on display here is that the #data is so interesting, and modern #econometrics and computers so powerful, that we can generate huge quantities of statistics without gaining much insight." #AI 😏 ft.com/content/dcb69ebe-23f1-4

  42. "One danger on display here is that the #data is so interesting, and modern #econometrics and computers so powerful, that we can generate huge quantities of statistics without gaining much insight." #AI 😏 ft.com/content/dcb69ebe-23f1-4

  43. Great new resource from Roger Bivand (NHH, June 2024): slides on spatial econometrics and ML for economic & social research.

    URL: rsbivand.github.io/nem24_talk/

  44. Great new resource from Roger Bivand (NHH, June 2024): slides on spatial econometrics and ML for economic & social research.

    URL: rsbivand.github.io/nem24_talk/

    #Geospatial #Econometrics #ML #GISchat

  45. Dealing with Censored Earnings in Register Data d.repec.org/n?u=RePEc:hal:jour
    "… In many register #data worldwide a relevant part of earnings and wealth is top-coded (right-censored), , can severely undermine its usefulness. For instance, how can #inequality and top earnings be credibly studied if the right tail of the earnings distribution is missing? Taking a distributional approach that is based on the semi-parametric modelling of the right tail being Pareto-like, we show how the missing tail can be successfully estimated using the administrative censored data.
    … The presented distributional approach should not be confused with individuallevel imputations of #censoredData. The latter requires, in addition to the Pareto parameter, the assignment of a rank of to each censored observation. Due to the censoring, these ranks are unobserved… "
    #Econometrics #PublicStatistics #economics

  46. Dealing with Censored Earnings in Register Data d.repec.org/n?u=RePEc:hal:jour
    "… In many register #data worldwide a relevant part of earnings and wealth is top-coded (right-censored), , can severely undermine its usefulness. For instance, how can #inequality and top earnings be credibly studied if the right tail of the earnings distribution is missing? Taking a distributional approach that is based on the semi-parametric modelling of the right tail being Pareto-like, we show how the missing tail can be successfully estimated using the administrative censored data.
    … The presented distributional approach should not be confused with individuallevel imputations of #censoredData. The latter requires, in addition to the Pareto parameter, the assignment of a rank of to each censored observation. Due to the censoring, these ranks are unobserved… "
    #Econometrics #PublicStatistics #economics

  47. It was super cool to visit Macau for the first time and present at the SETA conference! 😎 So many interesting researchers to meet and presentations to watch! ...and to share our essential evidence for Time Varying Identification of Structural VARs! 📊