7 citations · 13 across the 8 of their papers we have counts for
5 papers · 1 filter
Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
Matias D. Cattaneo, Max H. Farrell, Michael Jansson +1
The density weighted average derivative (DWAD) of a regression function is a canonical parameter of interest in economics. Classical first-order large sample distribution theory fo…
Distributional Counterfactual Analysis in High-Dimensional Setup
Ricardo Masini
In the context of treatment effect estimation, this paper proposes a new methodology to recover the counterfactual distribution when there is a single (or a few) treated unit and p…
Bridging factor and sparse models
Jianqing Fan, Ricardo Masini, Marcelo C. Medeiros
Factor and sparse models are two widely used methods to impose a low-dimensional structure in high-dimensions. However, they are seemingly mutually exclusive. We propose a lifting…
Machine Learning Advances for Time Series Forecasting
Ricardo P. Masini, Marcelo C. Medeiros, Eduardo F. Mendes
In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting. We consider both linear and nonlinear alter…
Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction
Jianqing Fan, Ricardo P. Masini, Marcelo C. Medeiros
Optimal pricing, i.e., determining the price level that maximizes profit or revenue of a given product, is a vital task for the retail industry. To select such a quantity, one need…