Again, by Theorem 1.3.3 in Molchanov (2017), the conclusion follows

Then, for any x ∈ Y , the distance function ρ(x, Y (ω)) = inf{∥x − y∥, y ∈ Y (ω)} = inf{∥x − υn(ω)∥, n ≥ 1} (C · 2017

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econ.EM · 2024-03-01 · unverdicted · novelty 7.0

Generalizes control function identification to set-valued functions, yielding sharp bounds on causal parameters under relaxed selection assumptions.

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Set-Valued Control Functions econ.EM · 2024-03-01 · unverdicted · none · ref 19
Generalizes control function identification to set-valued functions, yielding sharp bounds on causal parameters under relaxed selection assumptions.