Run Preliminary Econometrics Models
Econometrics helps users run preliminary models directly in Ecodata. The goal is quick screening before exporting data for deeper analysis.
Implemented Models
| Group | Models |
|---|---|
| Regression | OLS, GLS, WLS |
| Panel | Fixed Effects, Random Effects |
| Time series | VAR, ARIMA |
| Discrete choice | Logit, Probit |
Workflow
- Open Econometrics.
- Choose a model category.
- Select the model.
- Select the dependent indicator.
- Select independent indicators from
/api/indicators. - Choose year range.
- Add custom variables if needed.
- Run the analysis.
- Review coefficients, standard errors, t-statistics, p-values, model fit, and interpretation.
Choosing Model Indicators
| Component | Examples |
|---|---|
| Dependent variable | GDP growth, poverty rate, export value, stock return. |
| Main explanatory variable | FDI, PCI, tariff, education, investment. |
| Controls | Population, labor force, CPI, sector structure, year. |
| Time range | Choose a period with enough observations for the model. |
Citation Style
The module supports citation styles such as APA 7, Chicago 17, Harvard 2008, IEEE 2008, and MLA 7. Keep indicator citations together with exported data and metadata.
Limits
Econometrics is suitable for quick checks. For academic or official reports, export the data and re-test it in R, Python, Stata, or another specialized environment. For panel models, verify entity keys, time indexes, missing values, and aggregation before interpreting results.
Combining With AI Chat
AI Chat can help choose a model, explain coefficients, remind users to check multicollinearity, missing data, stationarity, lag structure, or suggest alternate indicators when coverage is insufficient.