| Estimator: | PPML with {{ fe_type }} Fixed Effects |
| Number of observations: | {{ n_obs }} |
| Number of entities: | {{ n_entities }} |
| Number of time periods: | {{ n_time }} |
| Deviance: | {{ deviance|number_format }} |
| Pseudo R²: | {{ pseudo_r2|number_format }} |
| Iterations to convergence: | {{ iterations }} |
| Variable | Coefficient | Std. Error | z-stat | p-value | Elasticity |
|---|---|---|---|---|---|
| {{ param.name }} | {{ param.estimate|number_format }} | {{ param.std_error|number_format }} | {{ param.z_stat|number_format }} | {{ param.p_value|pvalue_format }}{{ param.p_value|significance_stars }} | {% if param.is_log %} {{ param.estimate|number_format }} {% else %} {{ (param.estimate * param.mean_value)|number_format }} {% endif %} |
For log-transformed variables: The coefficient β represents the elasticity directly. A 1% increase in X leads to a β% change in E[y].
For level variables: The coefficient β represents the semi-elasticity. A one-unit increase in X leads to a (exp(β)-1)×100% change in E[y].
For dummy variables: The coefficient β indicates that E[y] is exp(β) times larger when the dummy equals 1 compared to 0.
| Number of zeros: | {{ zeros_info.n_zeros }} |
| Percentage of zeros: | {{ zeros_info.pct_zeros|percentage }} |
| Advantage over OLS-log: | PPML includes {{ zeros_info.n_zeros }} observations that would be dropped in log-linear OLS |
| Test | Statistic | p-value | Result |
|---|---|---|---|
| {{ test.name }} | {{ test.statistic|number_format }} | {{ test.p_value|pvalue_format }} | {{ test.interpretation }} |
| Entity fixed effects: | {{ n_entities }} effects absorbed |
| Time fixed effects: | {{ n_time }} effects absorbed |