Search Results for author: Jiti Gao

Found 11 papers, 0 papers with code

A Localized Neural Network with Dependent Data: Estimation and Inference

no code implementations8 Jun 2023 Jiti Gao, Bin Peng, Yanrong Yang

In this paper, we propose a localized neural network (LNN) model and then develop the LNN based estimation and inferential procedures for dependent data in both cases with quantitative/qualitative outcomes.

Time-Varying Vector Error-Correction Models: Estimation and Inference

no code implementations28 May 2023 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 with each other to co-exist.

Time Series

Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models

no code implementations16 Jan 2023 Chaohua Dong, Jiti Gao, Yundong Tu, Bin Peng

Generalized functions incorporate local integrable functions, the so-called regular generalized functions, while the so-called singular generalized functions (e. g. Dirac delta function) can be obtained as the limits of a sequence of sufficient smooth functions, so-called regular sequence in generalized function context.

Time Series Time Series Analysis

Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects

no code implementations7 Aug 2022 Ruofan Xu, Jiti Gao, Tatsushi Oka, Yoon-Jae Whang

We study the estimation of heterogeneous effects of group-level policies, using quantile regression with interactive fixed effects.


Semiparametric Single-Index Estimation for Average Treatment Effects

no code implementations17 Jun 2022 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.

Time-Varying Multivariate Causal Processes

no code implementations1 Jun 2022 Jiti Gao, Bin Peng, Wei Biao Wu, Yayi Yan

In this paper, we consider a wide class of time-varying multivariate causal processes which nests many classic and new examples as special cases.

Higher-order Expansions and Inference for Panel Data Models

no code implementations1 May 2022 Jiti Gao, Bin Peng, Yayi Yan

In this paper, we propose a simple inferential method for a wide class of panel data models with a focus on such cases that have both serial correlation and cross-sectional dependence.

Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice

no code implementations3 Nov 2021 Chaohua Dong, Jiti Gao, Bin Peng, Yundong Tu

This paper proposes a class of parametric multiple-index time series models that involve linear combinations of time trends, stationary variables and unit root processes as regressors.

Time Series Time Series Analysis

On Time-Varying VAR Models: Estimation, Testing and Impulse Response Analysis

no code implementations31 Oct 2021 Yayi Yan, Jiti Gao, Bin Peng

Vector autoregressive (VAR) models are widely used in practical studies, e. g., forecasting, modelling policy transmission mechanism, and measuring connection of economic agents.

Productivity Convergence in Manufacturing: A Hierarchical Panel Data Approach

no code implementations31 Oct 2021 Guohua Feng, Jiti Gao, Bin Peng

Despite its paramount importance in the empirical growth literature, productivity convergence analysis has three problems that have yet to be resolved: (1) little attempt has been made to explore the hierarchical structure of industry-level datasets; (2) industry-level technology heterogeneity has largely been ignored; and (3) cross-sectional dependence has rarely been allowed for.

Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects

no code implementations6 Dec 2020 Jiti Gao, Fei Liu, Bin Peng, Yayi Yan

In this paper, we investigate binary response models for heterogeneous panel data with interactive fixed effects by allowing both the cross-sectional dimension and the temporal dimension to diverge.

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