Possibility and Econometric Tutor-Advanced Econometric AI

Example

Calculating the likelihood of overlapping events in a dataset.

Scenario

A user might ask how to calculate the probability that a stock’s return exceeds a certain threshold on days when the market index also rises. The tool would guide the user through the process of defining and calculating conditional probabilities, possibly suggesting the use of Bayesian methods or probability trees to structure the analysis.

Example

Interpreting and diagnosing a regression model used to predict housing prices.

Scenario

The tool could assist a real estate analyst in understanding the significance of slope coefficients in a housing price prediction model, explain the meaning of R-squared and adjusted R-squared, and discuss potential issues like multicollinearity or heteroscedasticity. It might also provide guidance on model improvement techniques such as transformation of variables or inclusion of interaction terms.

Example

Determining the causal effect of a new policy on sales.

Scenario

If a business analyst is trying to infer the causal impact of a new marketing strategy on sales volume, the tool would help in setting up a difference-in-differences analysis or a regression discontinuity design, explaining the assumptions behind these methods and how they help to isolate the causal effect from other confounding factors.