CrunchEconometrix

20/09/2026

🔥 ATTENTION ACADEMIC TRACKERS: Protect Your Thesis Chapters! Our Staggered Adoption DiD RStudio Diagnostics Lab Is LIVE! 🥂🎉
If you are currently writing your university dissertation or an empirical paper on staggered policy rollouts, your supervisors and examiners will test you heavily on your identification strategy. Today, we are putting our software panels to work to show how a rigorous diagnostic phase can save your research design from catastrophic errors.
We are pulling back the curtain on why advanced conditional estimators struggle under small cross-sections, and how to spot "common support failures" visually before you hit the model editor!
What you will master inside this active laboratory session:
✅ How to interpret and navigate a non-invertible covariance matrix on micro-panels tracking single-country waves.
✅ How to defend a non-significant placebo parameter at horizon T-1 (p = 0.655) as an absolute mathematical victory against anticipation leaks.
✅ Why a severe common support failure on your propensity histogram map warns you that your software is guessing across space.
✅ How to enforce strict trimming rules (dropping observations where p-hat < 0.05 or p-hat > 0.95) to stabilise your weights.
Don't let hidden panel noise distort your coefficients or threaten your graduation pipeline. Grab your coffee, open your script windows, and let's lock in our empirical armour together!
👇 Click here to watch the full masterclass video on YouTube: https://youtu.be/Np3ayjsaQGA?si=QXQDplDmJueVVX95

👇 Grab the master datasets and complete R code scripts on: https://github.com/CrunchEconometrix/Staggered-Adoption-Difference-in-Differences🥰

🤝 Link to JOIN our Premium CrunchEconometrix P.E.R.S. Tier is pinned on our Channel dashboard!
Until next time... keep crunching! 📊💻🚀👑

Find out: Are Your Staggered Adoption DiD Estimates Valid? Essentia...

14/09/2026

🔥 ATTENTION PHD & POSTGRADUATE RESEARCHERS: Stop Pooling Staggered Timelines Blindly! Our Part 3 RStudio Estimation Lab Is LIVE!

If you are currently writing your university thesis or preparing a journal manuscript chapter on staggered policy updates, your examiners will look strictly at how you handle treatment heterogeneity.

In this 3rd video of our brand-new Staggered Adoption Difference-in-Differences (DiD) Masterclass Series, we open our RStudio markdown windows and execute our master estimation scripts side-by-side with traditional models!

We walk step-by-step through our RStudio console panel:
✅ The TWFE Overestimation Mirage: Revealing how traditional OLS returns an inflated, heavily biased policy coefficient of 7.492** because it relies on contaminated comparisons.
✅ The Callaway-Sant'Anna Correction: Utilizing the group-time estimation engine to clear out negative weights, causing the global aggregate parameter to drop safely to an unbiased, non-significant 2.163.
✅ Exposing Cohort Asymmetry: Disaggregating the simple average to prove that while our early 2007 wave (Spain) flatlined, our late 2013 (Italy) and 2014 (Mexico) waves experienced explosive, highly significant surges.
✅ Dynamic Event Study Trajectories: Extracting horizon-by-horizon leads and lags to evaluate parallel trends, passing the short-run placebo check at horizon T-1 with a clean p-value of 0.655.

True to the CrunchEconometrix mission, all raw master datasets, parallel R exploratory blocks, and twin Stata .do files are open-source and free to download from our master GitHub repository: https://github.com/CrunchEconometrix/Staggered-Adoption-Difference-in-Differences

Bring absolute methodological integrity to your empirical work and kick off the new series with us today. Watch Part 1 Live Now: https://youtu.be/PxsmlZBRl68

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Staggered Adoption DiD (Part 3): Mastering Event Studies in RStudio...

07/09/2026

🔥ATTENTION PHD & MASTER'S RESEARCHERS: Stop Blindly Running Regressions! Our Staggered Adoption DiD RStudio EDA Lab Is LIVE! 🥂🎉

If you are currently writing your university thesis or an empirical paper on staggered policy rollouts, your supervisors and examiners will look strictly at your data diagnostics. Today, we are putting our software panels to work to prove how a rigorous exploratory phase saves your research design from catastrophic errors.

We are pulling back the curtain on why advanced conditional estimators struggle under small cross-sections, and how to spot "covariate drift" visually before it ruins your standard errors!

What you will master inside this active laboratory session:
✅ How to use modern R pipes to group your sample into explicit policy treatment cohorts (2003, 2007, 2013, 2014).
✅ How to build a high-impact ggplot2 Rollout Density Heatmap to check your available counterfactual control pools.
✅ How to use Tukey’s exploratory philosophy to identify non-parallel background trends in your continuous controls.
✅ How to screen your panel for severe multicollinearity using linear correlation grids before hitting the model editor.

True to the CrunchEconometrix mission, all raw master datasets, parallel R exploratory markdown notebooks, and twin Stata .do files are open-source, free, and journal-ready to download from our master GitHub repository: https://github.com/CrunchEconometrix/Staggered-Adoption-Difference-in-Differences 🥰

Bring absolute methodological integrity to your empirical chapters and conquer your data lifecycle today. Watch the RStudio EDA Masterclass Live Now: https://youtu.be/SubhMnNFdAs

🤝 Link to JOIN our Premium CrunchEconometrix P.E.R.S. Tier is on the video’s page!
Let's keep crunching! 📊💻🚀👑

Before You Estimate: EDA for Staggered DiD in RStudio is a hands-on...

03/09/2026

Crunchers!🔥 The Grand Premiere: Purging Staggered Bias & The TWFE Trap (Part 1 is LIVE!) 🥂🎉

Are you still blindly trusting standard linear panel regressions when evaluating policies passed at different points in time? If you use a standard Two-Way Fixed Effects (TWFE) approach on a staggered rollout, your entire research narrative could be a heavily biased statistical mirage.

In this 1st video of our brand-new Staggered Adoption Difference-in-Differences (DiD) Masterclass Series on CrunchEconometrix, we lift the hood on heterogeneous treatment timing and mathematically uncover why classical panel models fail!

We walk step-by-step through:
✅ Uncovering the Goodman-Bacon negative weighting trap where traditional regressions accidentally use already-treated units as controls.
✅ Demystifying how dynamic, time-varying treatment effects contaminate your counterfactual baseline and artificially flip positive policy signs into negative ones.
✅ Introducing the Callaway-Sant'Anna (2021) "divide-and-conquer" framework to calculate clean Group-Time Average Treatment Effects (ATT(g,t)).
✅ Organizing our micro-panel master dataset across three unique country entry waves (2007, 2013, and 2014) to prepare for upcoming RStudio and Stata code labs.

True to the CrunchEconometrix mission, all raw master datasets, parallel R exploratory blocks, and twin Stata .do files are open-source and free to download from our master GitHub repository: https://github.com/CrunchEconometrix/Staggered-Adoption-Difference-in-Differences 🥰

Bring absolute methodological integrity to your empirical work and kick off the new series with us today. Watch Part 1 Live Now: https://youtu.be/A-ttFZatEMU

👉 (Want to unlock our private library of 85+ premium advanced metrics courses? Click the JOIN button on our channel page.

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📊 CALLAWAY-SANT'ANNA VS TWFE (PART 1): WHICH DiD METHOD WINS? 📊Dis...

01/09/2026

IMPORTANT ANNOUNCEMENT: P.E.R.B.A on the Teachable platform is closing on 30 September 2026 >> Moving to YouTube

Dear Community,

As notified in February, P.E.R.B.A (Practical Econometrics for Researchers and Beginners-Advanced) on Teachable will officially close on 30 September 2026.

What happens now?

We have fully moved to P.E.R.S (Practical Econometrics for Researchers and Students) on YouTube.

👉 Join P.E.R.S Membership: https://www.youtube.com/channel/UCK9hD254JKbCZ4Bf8Iz1s7g/join
👉 YouTube Channel: https://www.youtube.com/
👉 Website: https://cruncheconometrix.com

Please note:
For existing Enrolees (those who bought a course) and Users (those who signed up for free videos) on Teachable, access remains until 30 Sept 2026.

Your old Teachable username/password will NOT work on YouTube. Access on YouTube is via your personal YouTube/Google account membership.

Thank you for learning with us since 2018. The mission continues — Econometrics Made Easy — now on YouTube.

Warm regards,

Dr. Ngozi ADELEYE
Founder, CrunchEconometrix

31/08/2026

✋🏼The Final Chapter: Is Your Policy Effect a Statistical Mirage? Part 4 is LIVE!

Are you certain your regression results aren't being completely distorted by a handful of extreme outlier observations? In the grand finale of our Canonical Difference-in-Differences series, we show you exactly how a rigorous data-cleaning protocol can completely flip your policy conclusions!

Watch side-by-side inside RStudio and Stata as we enforce the 1.5x IQR outlier rule to purge 30 highly volatile stores, causing our sample to drop from 351 to 321 observations. See how our treatment effect cuts in half and loses all statistical significance, proving why robust data hygiene determines whether your thesis parameters represent economic reality or a statistical illusion. Plus, we master reading the bottom diagnostic rows of your output matrix!

🔥 No gatekeeping code here! Every data sheet, mirrored R script, and Stata do-file is 100% FREE to download on our public GitHub repository https://github.com/.../Canonical-Difference-in-Differences
👉 Watch the grand finale video now: https://youtu.be/mBiYqyJaUuI

💎 READY TO ELIMINATE REJECTION LETTERS? Tap the "JOIN" button on our channel homepage to access over 85 private, premium econometric courses under our new YouTube Members-Only (P.E.R.S.) research portal!

.5x

📊 WELCOME TO CRUNCHECONOMETRIX! 📊Making applied econometrics and c...

28/08/2026

👉 OLS vs. DiD: The Ultimate Regression Showdown is officially LIVE! 📊

Are you building your master's thesis or PhD dissertation around basic linear regressions? Watch out! Pooled OLS is completely blind to historical baseline trends, meaning your causal conclusions could be built on total selection bias.

In Part 3 of our masterclass series, we program a progressive 4-specification regression pipeline live on screen across RStudio and Stata side-by-side.

Learn how to compile your coefficients into beautiful tables, master complex model diagnostics (R-squared, Log-Likelihood, F-stats), and run critical Breusch-Pagan loops to catch severe heteroskedasticity!

🔥 No gatekeeping code here! Every data file, mirrored R script, and Stata do-file is 100% FREE to download on our public GitHub repository https://github.com/CrunchEconometrix/Canonical-Difference-in-Differences

👉 Watch the video now: https://youtu.be/68IfXtwOyck

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💎 READY TO SURVIVE PEER REVIEW? Tap the "JOIN" button on our channel homepage to access over 85 private, premium econometric courses under our new YouTube Members-Only (P.E.R.S.) research portal!

📊 WELCOME TO CRUNCHECONOMETRIX! 📊Empowering global researchers wit...

26/08/2026

📊 Part 2 of our Canonical Difference-in-Differences Masterclass is LIVE!

If you are throwing regressions at raw data without checking your distribution shapes first, your OLS standard errors might be built on total noise. Today, we are learning how to execute a professional Exploratory Data Analysis (EDA) pipeline simultaneously in RStudio and Stata!

🔥 No gatekeeping code here! Download every single script, data sheet, and .do file for FREE on GitHub to replicate our steps line-by-line https://github.com/CrunchEconometrix/Canonical-Difference-in-Differences

Watch live as we screen our workspace, build beautiful group frequency cross-tabs, generate side-by-side boxplots, and program a mathematical 1.5x IQR rule to flag and catch the 30 volatile outlier stores hiding inside the historic Card-Krueger dataset.

👉 Watch the video now: https://youtu.be/wLrfkr8NYds

💎 READY TO ELIMINATE REJECTION LETTERS? Tap the "JOIN" button on our channel homepage to access over 85 private, premium econometric courses under our new YouTube Members-Only (P.E.R.S.) research portal!

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📊 WELCOME TO CRUNCHECONOMETRIX! 📊Making applied econometrics and c...

24/08/2026

🚀 Esteemed Colleagues!...Milestone Reached: Turning Causal Inference Theory into Code!

For years, researchers have relied on traditional regression models to evaluate policy impacts, often falling straight into severe selection bias traps.

To help postgraduate researchers, PhD candidates, and data analysts achieve absolute empirical precision, I am thrilled to launch the first module of our brand new, fully comprehensive Difference-in-Differences (DiD) Masterclass Series on CrunchEconometrix!

In Part 1, we throw open the curtains on the Canonical 2x2 DiD Estimator.

We move past basic textbook definitions to unpack:
✅ The structural mathematical and algebraic frameworks of quasi-experimental design.
✅ The iconic empirical background of Card & Krueger's 1992 minimum wage expansion study.
✅ The absolute scientific necessity of the Parallel Trends Assumption.

Best of all? This is a dual-software masterclass. Every single replication dataset, clean Excel spreadsheet, standalone R script, and companion Stata .do file executed in this series is fully open-source, secure, and free to download from our master CrunchEconometrix GitHub repository https://github.com/CrunchEconometrix/Canonical-Difference-in-Differences 🥰

Elevate your dissertation analysis, protect your empirical frameworks from tough thesis defense panels, and master policy evaluation today.
📺 Watch Part 1 Live Now: https://youtu.be/LaR87iThfTE

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📊 WELCOME TO CRUNCHECONOMETRIX! 📊The ultimate destination for maki...

04/08/2026

Esteemed Colleagues,
📢 CALL FOR CHAPTER ABSTRACTS
Target Series: Advances in Spatial Science (Springer Nature, Scopus-Indexed)

I am pleased to announce an open Call for Abstracts for an upcoming edited volume entitled:
📖 "Advanced Spatial Econometrics in Public Health and Environmental Justice: Global Perspectives on Regional Heterogeneity"

👉 This volume bridges a critical methodological gap by shifting the paradigm from traditional cross-sectional modeling to rigorous, non-linear spatial panel frameworks --> primarily utilizing Stata software.

🌟 Key Details & Tracks:
👉 Track 1: Methodological Innovations (W matrix design, GWR diagnostics, non-linear spillovers, ML integration).
👉 Track 2: Global Empirical Applications (EJ case studies across North America, Europe, and the Global South using SAR, SEM, and SDM panel models).

⏳ Key Production Deadlines:
👉 Abstract Submission Deadline: December 15, 2026
👉 Abstract Selection & Notification: February 01, 2027
👉 Full Chapter Manuscript Submission: November 01, 2027
👉 Peer Review & Editorial Feedback: February 01, 2028
👉 Full Manuscript Delivery to Publisher: May 31, 2028

📥 Submission Guidelines:
👉 Please submit a 500-word Abstract detailing your core research question, econometric models, and data framework, alongside a brief academic biography (maximum 200 words), directly to: [email protected]
👉 Note: The Volume Editor is currently discussing publication with Springer Nature for inclusion within this flagship series.