To solve the problems of large mechanical powertrain such as complex structure, serious
accident, strong nonlinear characteristics of running state, bad operating environment, non …

Existing proofs of the asymptotic validity of conventional methods of impulse response
inference based on higher-order autoregressions are pointwise only. In this paper, we …

This paper presents a limiting distribution theory for GMM and Indirect Inference estimators
when local identification conditions fail at first-order but hold at second-order. These limit …

This paper develops an approach to detect identification failure in moment condition models.
This is achieved by introducing a quasi-Jacobian matrix computed as the slope of a linear …

This paper presents a unified framework for inference on parameters of the form ϕ (θ 0),
where θ 0 is unknown but can be estimated by θ ˆ n, and ϕ is known with null first order …

The main contribution of this paper is to study the applicability of the bootstrap to estimating
the distribution of the standard test of overidentifying restrictions of Hansen (1982) when the …

This paper studies the inference problem of an infinite‐dimensional parameter with a shape
restriction. This parameter is identified by arbitrarily many unconditional moment equalities …

We show that, in the random coefficients logit model, standard inference procedures can
suffer from asymptotic size distortions. The problem arises due to boundary issues and is …

Dovonon and Hall (Journal of Econometrics, 2018) proposed a limiting distribution theory for
GMM estimators for ap-dimensional globally identified parameter vector {\phi} when local …

I adapt the Generalised Method of Moments to deal with nonlinear models in which a finite
number of isolated parameter values satisfy the moment conditions. To do so, I initially study …