TESTS OF RANK

By J. Robin, Richard J. Smith. Econometric Theory, 2000

198 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bc5fd978aa5575a743dac097b3f17850471e9ad5

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Citations in the corpus

Growth, distance to frontier and composition of human capital (2004, methodology): “To see whether jointly the rank test would reject a rank less than three we implemented the Robin and Smith (2000) rank test which gave a P-value of 7% (see Table 3, column [4]) for reduced forms based on the BL data.”
Semi‐Nonparametric IV Estimation of Shape‐Invariant Engel Curves (2003, methodology): “First, we test the hypothesis H0 : rank(A) = r∗ by applying the result in Robin and Smith (2000).”
Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve (2009, result): “This conclusion is consistent with the findings of Rudd and Whelan (2006), and it is robust to using additional instruments, as in Galí and Gertler (1999) and Rudd and Whelan (2006).”
Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics (2007, methodology): “Instead of the Cragg and Donald (1997) rank statistic, other rank statistics that are based on DðbÞ, like, for example, those proposed by Robin and Smith (2000) and Kleibergen and Paap (2006) can be used in the GMM–MLR statistic as well.”
Non-Unitary Models of Household Behavior: A Survey of the Literature (2009, methodology): “The procedure is then to estimate a system of demands, to calculate the matrix (S S0), and to test the rank of this matrix by appealing to existing techniques; see Robin and Smith (2000) for example.”
Statistical Tests and Estimators of the Rank of a Matrix and Their Applications in Econometric Modelling (2009, unknown): “Choices for and are not discussed in much detail by Robin and Smith (2000).”
Heterogeneity in Reported Well-Being: Evidence from Twelve European Countries (2005, unknown): “8 The critical values for the statistics proposed by Robin and Smith (2000) were obtained after simulation of their distribution functions.”
Model Comparison with Sharpe Ratios (2019, methodology): “14This condition can be evaluated using rank-restriction tests, such as the ones proposed by Cragg and Donald (1997), Robin and Smith (2000), and Kleibergen and Paap (2006).”
Non‐parametric identification and estimation of the number of components in multivariate mixtures (2014, unknown): “As shown by Robin and Smith (2000), theorem 5.2, r̂ converges to r0 in probability as N →∞ if we choose αN such that αN =o.1/ and −N−1 log.αN/=o.1/.”