Confronta i metodi

	Regressione quantilica	Modello Autoregressivo a Transizione Liscia (STAR)	GMM Sistematico (Arellano-Bover / Blundell-Bond)
Campo	Econometria	Econometria	Econometria
Famiglia	Regression model	Regression model	Regression model
Anno di origine	1978	1994	1998
Ideatore	Koenker & Bassett	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)	Arellano & Bover (1995); Blundell & Bond (1998)
Tipo	Conditional quantile regression	Nonlinear time-series regime-switching model	Dynamic panel data estimator
Fonte seminale	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.	Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297.
Alias	conditional quantile regression, regression quantiles, Kantil Regresyon	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR	Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond)
Correlati	5	4	4
Sintesi	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.	The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.	System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small.