Consistent Estimation with a Large Number of Weak Instruments

By John C. Chao, Norman R. Swanson. 2005

350 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5fa7acbebcdcb6af827738d5b781a9161b809462

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In Economics and Econometrics

Citations in the corpus

Instrumental variable estimation in the presence of many moment conditions (2011, background): “Chao and Swanson (2005) and Stock and Yogo (2005) discuss the consequences of a large number of weak instruments, and Anderson, Kunitomo and Matsushita (2008) provide extensive simulation results. mean square error as a criterion for choosing the number of instruments.”
INSTRUMENTAL VARIABLE ESTIMATION IN A DATA RICH ENVIRONMENT (2010, methodology): “Our framework of many instruments is different from that of the existing literature, such as Bekker (1994), Donald and Newey (2001), and Chao and Swanson (2005), among many others.”
Instrumental Variable Estimation with Heteroskedasticity and Many Instruments (2012, positive): “The solution is a Fuller (1977) like estimator and standard errors that are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic efficiency in a range of cases. The standard errors are easy to compute, being like White’s (1982), with ad”
Evidence of jointness in the terms of relationship lending (2007, background): “This leads us to introduce a large number of candidate instruments ( see Chao and Swanson , 2003 ) .”
Asymptotic Distributions of Instrumental Variables Statistics with Many Instruments (2004, background): “Some of these results might be of more general interest, however; for example, Chao and Swanson (2002) show that LIML is consistent under these conditions, and in this paper we provide its √ K2-limiting distribution.”
GMM with many weak moment conditions (2005, methodology): “The alternative asymptotics is based on many weak moment sequences like those of Chao and Swanson (2004, 2005), Stock and Yogo (2004), and Han and Phillips (2005).”
Controlling for endogeneity with instrumental variables in strategic management research (2008, background): “Finally, several authors (Ackerberg and Devereux, 2003; Chao and Swanson, 2004; Hausman et al., 2007) find that LIML estimation is sensitive to the presence of heteroscedasticity but, as Ackerberg and Devereux (2006) later noted, it is possible to derive a LIML estimator allowing for…”
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 ”
Long-Run Substitutability Between More and Less Educated Workers: Evidence from U.S. States, 19501990 (2004, neutral): “…substitution are as robust as possible to weak instrument concerns we implement the limited information maximum likelihood estimator recommended by Chao and Swanson (2002) as well as the Fuller-modified limited information maximum likelihood estimator recommended by Stock, Wright, and Yogo (2002)…”
Director Ownership, Governance, and Performance (2013, background): “From an econometric perspective, validity of instruments is a matter of degree, not kind; see Berkowitz, Caner, and Fang (2008) and Chao and Swanson (2005). Ashbaugh-Skaife, Collins, and LaFond (2006) make a similar point in their study of the effects of corporate governance on firms’ credit ratings”
Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain (2012, background): “See, for example, Bekker (1994), Chao and Swanson (2005), Hansen, Hausman, and Newey (2008), and Hausman, Newey, Woutersen, Chao, and Swanson (2009) which propose solutions for this problem based on “manyinstrument” asymptotics.1 In this paper, we contribute to the literature on IV estimation with…”
GMM estimation of social interaction models with centrality (2010, background): “…Donald and Newey (2001), we focus on the case where the number of instruments grows with, but at a slower rate than, the sample size.5 Another important direction of research in the IV estimation literature is on weak instruments or weak identi cation (see, e.g., Chao and Swanson, 2005 and 2007).”
Optimal Estimation of Cointegrated Systems with Irrelevant Instruments (2014, neutral): “In this context, the approach delivers a general purpose long 1 However, recent results of Chao and Swanson (2005) and Han and Phillips (2006) show that it is possible to compensate for the effects of weak (and even irrelevant instruments in some cases) through the use of large numbers of…”