17 citations · 18 across the 6 of their papers we have counts for
6 papers · 1 filter
Limited-Information Estimation of Heterogeneous Agent Models
Laura Liu, Mikkel Plagborg-Møller, Nelson Matthew P. Tan
We develop a method for estimating and testing a single block of a macroeconomic model with heterogeneous agents, without placing assumptions on the structure of the rest of the ec…
A Simple and Powerful Diagnostic Test for Binary Choice Models
Ting Ji, Laura Liu, Yulong Wang +1
Conventional binary choice models, such as probit and logit, impose thin-tailed errors, and that tail determines whether the parameters of a binary choice model can be estimated at…
Inference in partially identified moment models via regularized optimal transport
Grigory Franguridi, Laura Liu
Many statistical and econometric problems involve parameters defined by moments of a joint distribution when only marginal distributions are observed, leading naturally to partial…
Bayesian Double Machine Learning for Causal Inference
Francis J. DiTraglia, Laura Liu
This paper proposes a simple, novel, and fully-Bayesian approach for causal inference in partially linear models with high-dimensional control variables. Off-the-shelf machine lear…
Binary Outcome Models with Extreme Covariates: Estimation and Prediction
Laura Liu, Yulong Wang
This paper presents a novel semiparametric method to study the effects of extreme events on binary outcomes and subsequently forecast future outcomes. Our approach, based on Bayes'…
Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data
Laura Liu, Mikkel Plagborg-Møller
We develop a generally applicable full-information inference method for heterogeneous agent models, combining aggregate time series data and repeated cross sections of micro data.…