About

Methodology

Our forecasting methodology combines dynamic stochastic general equilibrium (DSGE) models, time-series models, and expert-based forecasts. Each model contributes to the aggregate forecast based on its past performance and relevance to current macroeconomic conditions.

Model Description

The project includes a diverse set of macroeconomic models, including DSGE models used in central banks and academic institutions, as well as simpler autoregressive models for benchmarking.

You can find a collection of the models used here

Data Description

Forecasts are based on historical macroeconomic indicators including GDP, inflation, and interest rates. Data vintages are carefully managed to replicate the real-time information sets available at each forecast date.

A detailed overview of the data can be found here

References

The development and design of this forecasting platform builds upon the contributions and foundational research of numerous scholars. Notable references include:

• Wieland, V., Wolters, M., 2011. The diversity of forecasts from macroeconomic models of the US economy. Economic Theory, 47(2-3): 247-292.
• Del Negro, M., Schorfheide, F., 2013. DSGE model-based forecasting. Handbook of Economic Forecasting, 2A: 57-140.
• Wieland, V., Wolters, M., 2013. Forecasting and policy making. Handbook of Economic Forecasting, 2A: 239-325.
• Wolters M, 2015. Evaluating point and density forecasts of DSGE models. Journal of Applied Econometrics, 30(1): 74-96.