Estimation of Nonlinear Models with Measurement Error Using Marginal Information1

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The Econometrics of Data Combination (2007, background): “Hu and Ridder (2003) show that the identification involves two sequential deconvolution problems .”
Local indirect least squares and average marginal effects in nonseparable structural systems (2012, methodology): “Z; and E [V jZ;U2] = E [V jZ] : Assumption 4.3 Z1 = Z + U1 and Z2 = Z + U2: We now show that gV; can be de ned solely in terms of the joint distribution of V;Z1; and Z2: This generalizes Schennach (2004b), which focused on the = 0 case.”
SOME EXTENSIONS OF A LEMMA OF KOTLARSKI (2012, methodology): “Thus, the original result of Kotlarski (1967) as well as the lemmas of Li and Vuong (1998), Schennach (2004), and Evdokimov (2008) do not apply, yet our Lemma 1 does guarantee identification.”
Testing Q theory with financing frictions (2007, methodology): “For example, the remedy in Hausman, Ichimura, Newey, and Powell (1991) assumes a specific polynomial functional form, and the method in Schennach (2004) requires extra information not available in Compustat.”
On deconvolution with repeated measurements (2008, unknown): “Recent, related research in the regression setting, and in the econometrics literature, includes that of Li (2002), Li and Hsiao (2004) and Schennach (2004a, 2004b), who demonstrated that replications can be used to good effect in regression problems with measurement error.”