Abstract
This paper is concerned with asymptotic efficiency bounds for the estimation of the finite dimension parameter of semiparametric models that have singular score function for θ at the true value
The resulting singularity of the matrix of Fisher information means that the standard bound for
is not defined. We study the case of single rank deficiency of the score and focus on the case where the derivative of the root density in the direction of the last parameter component, θ2, is nil while the derivatives in the p – 1 other directions, θ1, are linearly independent. We then distinguish two cases: (i) The second derivative of the root density in the direction of θ2 and the first derivative in the direction of θ1 are linearly independent and (ii) The second derivative of the root density in the direction of θ2 is also nil but the third derivative in θ2 is linearly independent of the first derivative in the direction of θ1. We show that in both cases, efficiency bounds can be obtained for the estimation of
with j = 2 and 3, respectively and argue that an estimator
is efficient if
reaches its bound. We provide the bounds in form of convolution and asymptotic minimax theorems. For case (i), we propose a transformation of the Gaussian variable that appears in our convolution theorem to account for the restricted set of values of
This transformation effectively gives the efficiency bound for the estimation of
in the model configuration (i). We apply these results to locally under-identified moment condition models and show that the generalized method of moments (GMM) estimator using
as weighting matrix, where
is the variance of the estimating function, is optimal even in these non standard settings. Examples of models are provided that fit the two configurations explored.
Notes
1 We refer to Powell (Citation1994) for a more precise characterization of semiparametric models.
2 The score function in the direction of θ is given by which amounts to
3 The sets and H1 are defined as in Section 2 but with the spaces introduced in the current section.
4 We refer the reader to, e.g., Dovonon and Renault (Citation2019) for a more general specification of the second-order local identification condition and its characterizations.