The Annals of Statistics

A maximum likelihood method for the incidental parameter problem

Marcelo J. Moreira

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Abstract

This paper uses the invariance principle to solve the incidental parameter problem of [Econometrica 16 (1948) 1–32]. We seek group actions that preserve the structural parameter and yield a maximal invariant in the parameter space with fixed dimension. M-estimation from the likelihood of the maximal invariant statistic yields the maximum invariant likelihood estimator (MILE). Consistency of MILE for cases in which the likelihood of the maximal invariant is the product of marginal likelihoods is straightforward. We illustrate this result with a stationary autoregressive model with fixed effects and an agent-specific monotonic transformation model.

Asymptotic properties of MILE, when the likelihood of the maximal invariant does not factorize, remain an open question. We are able to provide consistent, asymptotically normal and efficient results of MILE when invariance yields Wishart distributions. Two examples are an instrumental variable (IV) model and a dynamic panel data model with fixed effects.

Article information

Source
Ann. Statist., Volume 37, Number 6A (2009), 3660-3696.

Dates
First available in Project Euclid: 17 August 2009

Permanent link to this document
https://projecteuclid.org/euclid.aos/1250515401

Digital Object Identifier
doi:10.1214/09-AOS688

Mathematical Reviews number (MathSciNet)
MR2549574

Zentralblatt MATH identifier
1183.62040

Subjects
Primary: C13 C23 60K35: Interacting random processes; statistical mechanics type models; percolation theory [See also 82B43, 82C43]
Secondary: C30

Keywords
Incidental parameters invariance maximum likelihood estimator limits of experiments

Citation

Moreira, Marcelo J. A maximum likelihood method for the incidental parameter problem. Ann. Statist. 37 (2009), no. 6A, 3660--3696. doi:10.1214/09-AOS688. https://projecteuclid.org/euclid.aos/1250515401


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