Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations

By Theodore W. Anderson, H. Rubin. 1949

Subfields: Economics & Operations Research

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Citations in the corpus

Concrete Problems in AI Safety (2016, methodology): “ 69]. The econometrics literature has in fact developed a large family of tools for handling partial specication, which also includes limitedinformation maximum likelihood and instrumental variables [10, 11, 133, 132]. Returning to machine learning, the method of moments has recently seen a great de”
THE COLONIAL ORIGINS OF COMPARATIVE DEVELOPMENT: AN EMPIRICAL INVESTIGATION (2001, unknown): “28 We do this mostly because Albouy has emphasized the importance of using Anderson and Rubin (1949) confidence sets and reports only these in his comment.”
Specification tests in econometrics (1978, methodology): “21 Within the single equation context this test has been proposed by Anderson and Rubin [1], Basmann [2], and Koopmans and Hood [11].”
A MONTE CARLO COMPARISON OF VARIOUS ASYMPTOTIC APPROXIMATIONS TO THE DISTRIBUTION OF INSTRUMENTAL VARIABLES ESTIMATORS (2002, methodology): “We found that confidence intervals based on the Andersen and Rubin [12] statistic and on the K statistic of Kleibergen [13] have virtually exact Monte Carlo coverage probabilities: Their coverage probabilities were always within 1% point of the nominal coverage probability.”
Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data (2014, unknown): “Because of possible problems with instrument relevance for some samples and some horizons, we will also conduct some key hypothesis tests using Anderson and Rubin (1949) statistics, which are robust to weak instruments.”
A New Specification Test For The Validity Of Instrumental Variables (2000, unknown): “Another approach has been to consider the statistic originally put forward by Anderson and Rubin (1949).”
Weak Identification in Fuzzy Regression Discontinuity Designs (2016, methodology): “In exactly identified models, the approach suggested by Anderson and Rubin (1949) results in efficient inference if instruments turn out to be strong and remains valid if instruments are weak.”
An Applied Econometricians' View of Empirical Corporate Governance Studies (2002, methodology): “For earlier tests, see Anderson and Rubin (1949) and Koopmans and Hood (1953).”
Generic results for establishing the asymptotic size of confidence sets and tests (2020, background): “(3.6) 17 For notational convenience, subscripts n are omitted.8 18 We define the Anderson and Rubin (1949) statistic and the Lagrange Multiplier statistic of Kleibergen (2002) and 19 Moreira (2009), generalized to allow for heteroskedasticity, as follows: 20 AR ≡ n̂g ′Ω̂−1̂g and LM ≡ n̂g…”
Government Spending Multipliers under the Zero Lower Bound: Evidence from Japan (2018, unknown): “The Anderson and Rubin (1949) p-values are slightly higher than the standard p-values but they are all below 0.1, suggesting that the difference is statistically significant in both short and longer horizons.”
A Conditional Likelihood Ratio Test for Structural Models (2003, methodology): “Monte Carlo simulations suggest that this conditional likelihood ratio test not only has power close to the power envelope of similar tests when identification is good but it also dominates the test proposed by Anderson and Rubin (1949) and the score tests proposed by Kleibergen (2000) and Moreira (”
Does Institutional Quality Foster Economic Complexity? (2019, unknown): “Third, I perform the test of robust inference with weak instruments of Anderson and Rubin (1949). The low p-value indicates that we can reject the null hypothesis that the coefficient of the endogenous variable is zero at the 1% level.”
Women and corruption: What positions must they hold to make a difference? (2014, unknown): “Freedom House awards a score of 1 through 7 for political rights – a score of 1 indicates that the citizens enjoy a wide range of political rights while a rating of 7 implies few or no political rights.(7) (4)For details of data sources, questions and methodology used in computing the CCI, see Kaufm”
Confidence Sets for Partially Identified Parameters that Satisfy a Finite Number of Moment Inequalities (2006, methodology): “This paper proposes a computationally attractive way to perform inference via pointwise testing in the spirit of Anderson and Rubin (1949, 1950) in a large class of models whose application often results in partial identication: moment inequality models. These are models in which the parameter of i”