Instrumental variable estimation based on grouped data

PA Bekker*, Jan van der Ploeg

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    25 Citations (Scopus)

    Abstract

    The paper considers the estimation of the coefficients of a single equation in the presence of dummy intruments. We derive pseudo ML and GMM estimators based on moment restrictions induced either by the structural form or by the reduced form of the model. The performance of the estimators is evaluated for the non-Gaussian case. We allow for heteroscedasticity. The asymptotic distributions are based on parameter sequences where the number of instruments increases at the same rate as the sample size. Relaxing the usual Gaussian assumption is shown to affect the normal asymptotic distributions. As a result also recently suggested new specification tests for the validity of instruments depend on Gaussianity. Monte Carlo simulations confirm the accuracy of the asymptotic approach.

    Original languageEnglish
    Pages (from-to)239-267
    Number of pages29
    JournalStatistica Neerlandica
    Volume59
    Issue number3
    Publication statusPublished - Aug-2005

    Keywords

    • instrumental variable estimation
    • limited information maximum likelihood
    • generalized method of moments
    • linear functional relationship
    • group asymptotics
    • many-instruments asymptotics
    • natural experiments
    • LINEAR FUNCTIONAL-RELATIONSHIP
    • SMALL-SAMPLE DISTRIBUTION
    • SIMULTANEOUS-EQUATIONS
    • WEAK INSTRUMENTS
    • APPROXIMATE DISTRIBUTIONS
    • CROSS-SECTIONS
    • ECONOMETRICS
    • REGRESSION
    • INFERENCE
    • RELEVANCE

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