Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed Effects

By Jinyong Hahn, Jerry A. Hausman, G. Kuersteiner. 2001

60 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/dba376443a03edbf7bfe34648f213907b82884ed

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In Economics and Econometrics

Citations in the corpus

Estimating Panel Models With Internal and External Habit Formation (2010, background): “For example, see Hahn, Hausman, and Kuersteiner (2002).”
A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments (2002, methodology): “A second omitted topic is estimation of linear panel data models with a lagged dependent variable, in which instruments (lags) are weak if the lag coef cient is almost 1; recent work in this area includes that of Kiviet (1995), Alonso-Borrego and Arellano (1996), and Hahn et al. (2001b).”
Bias in Dynamic Panel Estimation with Fixed Effects, Incidental Trends and Cross Section Dependence (2003, background): “Hahn et al. (2001) have suggested a long difference estimator to alleviate some of these difficulties, but that estimator is not investigated here.”
GMM Estimation of Autoregressive Roots Near Unity with Panel Data (2004, unknown): “…(i) g 1t = t and (ii) g 2t = ¡ t;t 2 ¢ 0 : The set up is formalized as follows: Assumption 1 (Trend Formulation) The polynomial trend in model (1) is either (i) g 1t = t or (ii) g 2 t = ¡ t; t 2 ¢ 0 : Assumption 2 (Error Condition) " it are linear processes satisfying the following condi- tions.”
Dynamic Panel Estimation and Homogeneity Testing Under Cross Section Dependence (2002, unknown): “HK is the bias corrected GMM estimator suggested in Hahn and Kuersteiner (2002) and Hahn et al. (2001) and this estimator apparently has performance closest to that of the PMU estimator.”
Democracy Does Cause Growth (2019, background): “10 Hahn et al. (2001) note that Arellano and Bond’s GMM estimator is a minimumdistance combination of estimates of the model”
The optimal choice of moments in dynamic panel data models (2009, methodology): “Hahn, Hausman, and Kuersteiner (2001) propose several moment-based estimators with bias-reducing properties.”
Political budget cycles: Do they differ across countries and why? (2006, background): “See Hahn et al. (2001), and references therein, on the pros and cons of GMM. 7 Gonzalez (2002a), building on Rogoff (1990), also points to the variation in institutional environment.”
Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators (2003, methodology): “These include the bootstrap, as in Horowitz (1998) for GMM, the jackknife, as in Kezdi, Hahn, and Solon (2001) for minimum distance, and analytical methods, as in Hahn, Hausman, and Kuersteiner (2001) for dynamic panel data.”
Econometric Analysis of Panel Data (2020, methodology): “This method of simulating probabilities is referred to as the Geweke, Hajivassiliou and Keane (GHK) simulator because it was independently developed by these authors. Keane (1994) performs Monte Carlo experiments and finds that even for large T and small simulation sizes, the bias in the MSM estimat”