The Estimation of Relationships with Autocorrelated Residuals by the Use of Instrumental Variables

By J. Sargan. 1959

Subfields: Statistics and Probability, Economics & Operations Research

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Citations in the corpus

Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference (2002, background): “In a parallel development, Sargan (1958, 1959) considered both linear and nonlinear instrumental variable (IV) estimators for models with a residual that is linear in the variables.”
Sargan's Intrumental Variables Estimation and the Generalized Method of Moments (2002, methodology): “Sargan (1958) stressed the distinction between the purely theoretical asymptotic results and the accuracy of the asymptotic approximations for nite T .”
Generalized Method of Moments and Macroeconomics (2002, methodology): “The formulation of two-stage least squares as an optimal instrumental variable (IV) estimator under conditional homoscedasticity and a test for overidentifying restrictions was proposed by Sargan (1958, 1959).”
The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis (2002, methodology): “This general theory was applied to time series data with autocorrelated residuals in Sargan (1959).”
Nobel Lecture: Uncertainty Outside and Inside Economic Models (2014, background): “…ð1982bÞ I also studied statistical efficiency for a class of GMM estimators given a particular choice of Z in a manner that extends an approach due to Sargan ð1958, 1959Þ.12 When ð3Þ has more equations than unknown parameters, multiple GMM estimators are the outcome of using ðat least implicitlyÞ…”
Large sample estimation and hypothesis testing (1986, methodology): “Nonlinear instrumental variable estimators were developed and analyzed by Sargan (1959) and Amemiya (1974).”
Information and Entropy Econometrics - A Review and Synthesis (2008, background): “At the same period, Sargan (1958, 1959) developed his work on instrumental variables within a linear framework.”