Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods

By Cheng Hsiao, M. Pesaran, A. K. Tahmiscioglu. 2002

496 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/32ceb128ec46d56cd006472908b580f8716ba8b1

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In Economics and Econometrics

Citations in the corpus

Measuring resilience to economic shocks: an application to Spain (2018, methodology): “Finally, Hsiao et al. (2002) propose the use of Maximum Likelihood (ML) estimation based on the unconditional likelihood function of the model, concluding that ML estimator is asymptotically more efficient than the GMM.”
The Productivity Effects of Internal and External R&D: Evidence From a Dynamic Panel Data Model (2008, unknown): “Hence, alternatively, we use recently proposed fixed-effects and random-effects maximum likelihood estimators (MLE) for dynamic panel data models (Hsiao et al., 2002) based on the transformed likelihood function.”
Panel data analysis—advantages and challenges (2007, unknown): “Furthermore, the prediction of aggregate outcomes using aggregate data can be less accurate than the prediction based on micro-equations (e.g., Hsiao et al. 2005).”
Unit roots: identification and testing in micro panels (2005, methodology): “When ω is restricted in this way, the ML estimator also estimates α = 1 consistently, and a simple t-test is valid, even though the parameter is on the boundary of the parameter space (see Hsiao et al. (2002) and Kruiniger 2002a).”
X-DIFFERENCING AND DYNAMIC PANEL MODEL ESTIMATION (2013, unknown): “Econometric Theory, 30, 2014, 201–251. doi:10.1017/S0266466613000170”
Estimation of linear dynamic panel data models with time‐invariant regressors (2019, methodology): “To ensure an adequate degree of fit, we obtain the population value of the coefficient of determination for the first-differenced model, R2∆y, in a similar fashion as Hsiao et al. (2002).”
QML estimation of dynamic panel data models with spatial errors (2015, methodology): “…regular dynamic models, Balestra and Nerlove (1966), Nerlove (1971), Maddala (1971), Anderson and Hsiao (1981, 1982), Bhargava and Sargan (1983); Hsiao et al. 2002, Hsiao (2003), and Binder et al. (2005); and for spatial models, Su and Yang (2007), Elhorst (2010), and Parent and LeSage…”
Bias-Corrected Estimation in Dynamic Panel Data Models (2005, background): “Hsiao, Pesaran, and Tahmiscioglu (2002) introduced a maximum likelihood estimator based on first differencing the dynamic panel data model to get rid of the unobserved individual effects.”
Dynamic panel data modelling using maximum likelihood: an alternative to Arellano-Bond (2018, unknown): “…as they require some programming capabilities (e.g. Alonso-Borrego and Arellano 1999; Ahn and Schmidt 1995; Hansen, Heaton, and Yaron 1996; Hsiao, Pesaran, and Tahmiscioglu 2002; Moral-Benito 2013).14 Moreover, concern has intensified in recent years that many instrumental variables of…”
Maximum likelihood estimation and inference methods for the covariance stationary panel AR(1)/unit root model (2008, background): “More recently, Hsiao et al. (2002) and Kruiniger (2001) have independently shown that the panel AR(1) model with fixed effects and arbitrary initial conditions can be consistently estimated by the ML method, viz. the Restricted FEML (RFEML) estimator, if the differences between the initial…”
Dynamic spatial panels: models, methods, and inferences (2012, methodology): “More recently, Hsiao et al. (2002) have suggested an alternative procedure for the fixed effects dynamic panel data model.”
Technological complexity and economic growth of regions (2020, methodology): “This approach has been shown to outperform the more common GMM estimators (Hsiao et al., 2002).”
Dynamic panels with threshold effect and endogeneity (2016, unknown): “Ramirez-Rondan (2013) has extended the Hansen’s (1999) work to allow the threshold mechanism in dynamic panels, and proposed the maximum likelihood estimation techniques, following the approach by Hsiao et al. (2002).”