eiIT: Ecological Inference via Information Theory
Estimates RxC transfer matrices from aggregated marginal data using
a two-stage (GME+IPF) information-theoretic approach within a two-step
(global+local) estimation procedure. The resulting matrices are consistent
with observed row and column marginals across collections of subtables
(e.g. precincts, polling stations, or districts).
References:
Golan, A., Judge, G., & Miller, D. (1996). Maximum Entropy Econometrics: Robust Estimation with Limited Data. Wiley.
Judge, G., Miller, D.J., & Cho, W.K.T. (2004). An information theoretic approach to ecological estimation and inference. In G. King, O. Rosen, & M. A. Tanner (Eds.), Ecological Inference: New Methodological Strategies (pp. 162–187). Cambridge University Press.
Mittelhammer, R., Judge, G., & Miller, D. (2000). Econometric Foundations. Cambridge University Press.
Pavia, J.M. (2023) <doi:10.1007/s43545-023-00658-y>
Acknowledgements: The author wish to thank Conselleria de Economia, Hacienda y Administracion Publica (grant CIACIO/2023/031) for supporting this research.
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