Assistant Professor of Economics | Forecasting • Structural Modelling • Macroeconomics
Macroeconometrics is in crisis. Forecasts of period averages failed to test against the true random walk null (end-of-period no-change), testing instead against the period-average no-change. This has resulted in spurious predictability, calling into question every macroeconomic forecasting result from the last 50 years. Working (1960) was wrong: a random walk (RW) does not aggregate to a moving average (MA) process. Consequently, every macro model estimated on monthly or quarterly averages has mistimed shocks and introduced spurious endogeneity. The fix is simple: any macro modeller could halve their forecast error right now just by replacing period averages with alternative data sampling. This page distributes the data, code, and techniques to elevate empirical macro.
High-frequency and real-time datasets for Econometrics and Machine Learning.
Key Advantage: Using high-frequency and end-of-month (EOM) data enables testing against the random walk hypothesis, reduces shock mistiming, avoids spurious endogeneity, and can improve forecasting accuracy by up to 40% compared to using monthly averages. Moreover, to ensure your empirical results are actually relevant, you must backtest using real-time data, relying strictly on pre-revision data that accounts for publication lags.
| Dataset | Scope | Tech Highlights |
|---|---|---|
| Real-Time Daily & EOM EERs | 160 Countries | World's first real-time daily/EOM effective exchange rate dataset. |
| 17 Primary Commodities | Global Markets | Mixed-frequency spot data & futures-based forecasts. |
| Real-Time Oil Vintages | Monthly Vintages | Real-time global crude oil production, activity, and inventories. |
| EOM Backcasted Oil Prices | Since 1973 | WTI/Brent EOM spot prices. Optimized for Random Walk testing. |
Level up your data analysis and coding from "Zero to Hero."
- 📺 The Stata Economics Masterclass (Complete: 5 Videos + Code)
- 💻 The R Economics Masterclass (In Development: Starter code available now, videos coming soon!)
- Automated Import & Cleaning: Stop wasting time on manual data formatting.
- Debug Like a Pro: Identifying AI "slop" and structural errors.
- Core Skills: Graphing, priors, and predictive modeling.
- Monte Carlo: Using simulations to verify your results.
- The "Copy-Paste" Intervention: Full automation of result reporting.
- 📺 Filters & The Business Cycle: A deep dive into business cycle filtration.
- 📺 Canadian Economic Data Guide: A streamlined gateway to Canadian Data.
