33 citations · 47 across the 10 of their papers we have counts for
11 papers
Estimating causal quantile exposure response functions via matching
Luca Merlo, Francesca Dominici, Lea Petrella +2
We develop new matching estimators for estimating causal quantile exposure-response functions and quantile exposure effects with continuous treatments. We provide identification re…
Unified unconditional regression for multivariate quantiles, M-quantiles and expectiles
Luca Merlo, Lea Petrella, Nicola Salvati +1
In this paper, we develop a unified regression approach to model unconditional quantiles, M-quantiles and expectiles of multivariate dependent variables exploiting the multidimensi…
lqmix: an R package for longitudinal data analysis via linear quantile mixtures
Marco Alfó, Maria Francesca Marino, Maria Giovanna Ranalli +1
The analysis of longitudinal data gives the chance to observe how unit behaviors change over time, but it also poses a series of issues. These have been the focus of an extensive l…
A Nested Error Regression Model with High Dimensional Parameter for Small Area Estimation
Partha Lahiri, Nicola Salvati
In this paper we propose a flexible nested error regression small area model with high dimensional parameter that incorporates heterogeneity in regression coefficients and variance…
Scale estimation and data-driven tuning constant selection for M-quantile regression
James Dawber, Nicola Salvati, Timo Schmid +1
M-quantile regression is a general form of quantile-like regression which usually utilises the Huber influence function and corresponding tuning constant. Estimation requires a nui…
Causal Inferences in Small Area Estimation
Setareh Ranjbar, Nicola Salvati, Barbara Pacini
When doing impact evaluation and making causal inferences, it is important to acknowledge the heterogeneity of the treatment effects for different domains (geographic, socio-demogr…