External data plays an integral role in building accurate predictive forecasting models, especially as businesses navigate the volatile pandemic-impacted economy.

Data science and dataops have a critical role to play in developing revenue forecasts business leaders can count on.

When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series.

The authors put forward a means address data scarcity in operational risk modelling by supplementing internal loss data with external loss data.

Nilanjan Chatterjee, Yi-Hau Chen, Paige Maas, Raymond J. Carroll, Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-Level Information From External Big Data Sources, ...

Using a Global Vector Autoregressive model with quarterly data from 1987 to 2022, we find that external factors such as the imported inflation from main trading partners, mainly driven by China, and ...