109 citations · 450 across the 21 of their papers we have counts for
15 papers · 1 filter
Localized Neural Network Modelling of Time Series: A Case Study on US Monetary Policy
Jiti Gao, Fei Liu, Bin Peng +1
In this paper, we investigate a semiparametric regression model under the context of treatment effects via a localized neural network (LNN) approach. Due to a vast number of parame…
Time-Varying Vector Error-Correction Models: Estimation and Inference
Jiti Gao, Bin Peng, Yayi Yan
This paper considers a time-varying vector error-correction model that allows for different time series behaviours (e.g., unit-root and locally stationary processes) to interact wi…
Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models
Chaohua Dong, Jiti Gao, Yundong Tu +1
Robust M-estimation uses loss functions, such as least absolute deviation (LAD), quantile loss and Huber's loss, to construct its objective function, in order to for example eschew…
Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation
Ruofan Xu, Jiti Gao, Tatsushi Oka +1
We propose a quantile random-coefficient regression with interactive fixed effects to study the effects of group-level policies that are heterogeneous across individuals. Our appro…
Semiparametric Single-Index Estimation for Average Treatment Effects
Difang Huang, Jiti Gao, Tatsushi Oka
We propose a semiparametric method to estimate the average treatment effect under the assumption of unconfoundedness given observational data. Our estimation method alleviates miss…
Time-Varying Multivariate Causal Processes
Jiti Gao, Bin Peng, Wei Biao Wu +1
In this paper, we consider a wide class of time-varying multivariate causal processes which nests many classic and new examples as special cases. We first prove the existence of a…