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| Ecological Inference× | Modello Dinamico a Dati Panel× | |
|---|---|---|
| Campo≠ | Political Science | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1997 | 1988–1991 |
| Ideatore≠ | Leo Goodman (ecological regression); Gary King (statistical EI solution) | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Tipo≠ | Aggregate-data model inferring individual-level rates from grouped totals | Dynamic regression / GMM estimation |
| Fonte seminale≠ | King, G. (1997). A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton: Princeton University Press. ISBN: 9780691012414 | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗ |
| Alias | EI, Ecological regression, King's ecological inference, Aggregate-to-individual inference | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| Correlati | 5 | 5 |
| Sintesi≠ | Ecological inference is the problem of learning about individual behavior — such as how Black and white voters cast their ballots — when only aggregate data are available, like precinct-level turnout and racial composition. Because individual-level data are missing, the within-group rates are not directly observed; ecological inference recovers them by combining the deterministic accounting constraints that each precinct must satisfy with a statistical model of how the unobserved rates vary across precincts. Gary King's 1997 solution unified the deterministic method of bounds with Leo Goodman's classic ecological regression, sharply reducing the long-standing risk of the ecological fallacy. | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. |
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