ALTERNATIVE APPROXIMATIONS TO THE DISTRIBUTIONS OF INSTRUMENTAL VARIABLE ESTIMATORS

By P. Bekker. 1994

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Citations in the corpus

Instrumental variable estimation based on grouped data (2005, methodology): “For the other estimators the deviations between the simulated distribution and their approximations can be explained in part by the skewness of VVS, 2005 the distributions (cf. BEKKER, 1994).”
A regularization approach to the many instruments problem (2012, methodology): “The poor performance of IV estimator is due to the fact that its bias increases with the number of moment conditions (Bekker, 1994, Newey and Smith, 2004).”
Instrumental variable estimation in the presence of many moment conditions (2011, methodology): “We also compute the coverage probabilities based on Bekker’s (1994) asymptotic variance estimator for the LIML-type estimators (see also Hansen, Hausman and Newey (2008)). It is denoted “B. Cov. Rate” in the tables. Bekker’s asymptotic variance estimator is consistent for the asymptotic variance eve”
Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity (2009, methodology): “As a result, we turn to many-instrument asymptotics (also called group asymptotics) previously used by Bekker (1994), Angrist and Krueger (1995), AIK, Chao and Swanson (2005), and Newey (2004).9 The basic idea of many-instrument asymptotics is to allow the number of instruments K1 to go to infinity…”
Decision Theory Applied to an Instrumental Variables Model (2007, background): “2 See, for example, Bekker (1994) and Staiger and Stock (1997).”
Robust Inference for Consumption‐Based Asset Pricing (2019, unknown): “This “limited T versus large N” problem is not accounted for in standard asymptotic approximations of t and Wald statistics (Bekker (1994), Newey and Windmeijer (2009)) and thus provides a second argument for why researchers cannot rely on standard t/Wald-tests to conduct dependable statistical…”
The reduced form: A simple approach to inference with weak instruments (2008, background): “9Hansen, Hausman, and Newey (2005) suggest that a cutoff value in the mid-thirties provides a useful rule of thumb for the use of the asymptotic approximation of Bekker (1994).”
Pivotal statistics for testing structural parameters in instrumental variables regression (2002, methodology): “Bekkers LIML Statistic. Bekker (1994) constructs an estimate of the asymptotic variance of the LIML estimator, ̂LIML, that is consistent under the many instrument asymptotics.”
Robust priors in nonlinear panel data models (2007, background): “Equation (8) thus forms a non trivial set of restrictions.”
Frugal IV alternatives to identify the parameter for an endogenous regressor (2009, methodology): “simulations, suggest that the small sample size impairs identifiability of the IH estimator. Hogan and Rigobon (2003) and Rigobon (2003) applied the IH method to estimate the returns to education and to estimate the relation across emerging-markets' sovereign bonds yields using fairly large samples,”
Testing with many weak instruments (2007, methodology): “Many IV asymptotics (with strong IVs) have been employed in Anderson (1976), Kunitomo (1980), Morimune (1983), Bekker (1994), Donald and Newey (2001), Hahn (2002), Hahn et al. (2004), and Hansen et al. (2005) among others.”
Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain (2012, background): “It is well-known that this will result in poor-finite sample properties unless there are many more observations than instruments; see, for example, Bekker (1994).”
The optimal choice of moments in dynamic panel data models (2009, methodology): “Therefore, if the time dimension of the data is moderately large, we would have a large number of moment conditions.”
An empirical analysis of milk addiction. (2004, unknown): “The exact small-sample properties of the estimates are very difficult to obtain even in considerably simpler models (in related contexts, seePhillips, 1977; Bekker, 1994), so we simulate their properties.”