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policies can switch on and off over time. With large G and small T, one can estimate an unstricted variance matrix g and proceed with GLS – this is the approach suggested by Kiefer (1980) and studied more recently by Hausman and Kuersteiner (2003). Works pretty well with G 50 and T 10, but get substantial size distortions for G 50 and T 20. If the Mgt are not large, might worry about

̂ ignoring the estimation error in the gt. Can instead

aggregate the equations over individuals, giving

ȳgt t g xgtz̄gtvgt ūgt, t 1, . . , T, g 1, . . . , G.

Can estimate this by FE and use fully robust inference because the composite error,

  • rgt vgt ūgt, is weakly dependent.

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