no code implementations • 16 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.
no code implementations • 27 Sep 2022 • Baoyu Jing, Si Zhang, Yada Zhu, Bin Peng, Kaiyu Guan, Andrew Margenot, Hanghang Tong
In this paper, we show both theoretically and empirically that the uncertainty could be effectively reduced by retrieving relevant time series as references.
no code implementations • 1 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.
no code implementations • 1 May 2022 • Jiti Gao, Bin Peng, Yayi Yan
In this paper, we propose a simple dependent wild bootstrap procedure for us to establish valid inferences for a wide class of panel data models including those with interactive fixed effects.
no code implementations • 22 Nov 2021 • Bin Peng, Liangjun Su, Joakim Westerlund, Yanrong Yang
This paper considers a model with general regressors and unobservable factors.
no code implementations • 3 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.
no code implementations • 31 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.
no code implementations • 31 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.
no code implementations • 17 Jan 2021 • Yufeng Mao, Bin Peng, Mervyn Silvapulle, Param Silvapulle, Yanrong Yang
This study decomposes the bilateral trade flows using a three-dimensional panel data model.
no code implementations • 6 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.