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Fei Jin
;
Lung-fei Lee
;
Kai Yang

best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in us counties (replication data)

This archive contains the data and code files for "Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties" by Fei Jin, Lung-fei Lee, and Kai Yang, in Journal of Applied Econometrics. Data and code for Monte Carlo experiments and the empirical application are provided: see the readme.jly.txt file for details and the zip folder for the code and data.

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Jin, Fei; Lee, Lung-fei; Yang, Kai (2024): Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2024045.0850271337

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