Confronta i metodi

	Regressione spaziale (modelli a lag spaziale ed errore spaziale)	Regressione quantilica
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1988	1978
Ideatore	Luc Anselin	Koenker & Bassett
Tipo	Spatial regression (cross-sectional)	Conditional quantile regression
Fonte seminale	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	spatial econometrics, spatial lag model, spatial error model, SAR / SEM	conditional quantile regression, regression quantiles, Kantil Regresyon
Correlati	5	5
Sintesi	Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term.	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.