Forecasting using heterogeneous panels with cross-sectional dependence
نویسندگان
چکیده
منابع مشابه
Asymptotic Theory for Dynamic Heterogeneous Panels with Cross-Sectional Dependence and Its Applications
This paper considers dynamic heterogeneous panels with cross-sectional dependence (DHP+CSD), where the dependence is modeled using a factor structure. Dynamics, heterogeneity and cross-sectional dependence are pervasive characteristics of most data sets and it is therefore essential for empirically realistic models to allow for the three features. It is also well-known that the persistence of a...
متن کاملNonparametric Estimation in Large Panels with Cross Sectional Dependence
In this paper we consider nonparametric estimation in panel data under cross sectional dependence. Both the number of cross sectional units (N) and the time dimension of the panel (T ) are assumed to be large, and the cross sectional dependence has a multifactor structure. Local linear regression is used to lter the unobserved cross sectional factors and to estimate the nonparametric condition...
متن کاملBootstrap Unit Root Tests in Panels with Cross-Sectional Dependency
We apply bootstrap methodology to unit root tests for dependent panels with N cross-sectional units and T time series observations. More speci cally, we let each panel be driven by a general linear process which may be di erent across crosssectional units, and approximate it by a nite order autoregressive integrated process of order increasing with T . As we allow the dependency among the innov...
متن کاملBootstrapping factor models with cross sectional dependence
We consider bootstrap methods for factor-augmented regressions with cross sectional dependence among idiosyncratic errors. This is important to capture the bias of the OLS estimator derived recently by Gonçalves and Perron (2014). We first show that a common approach of resampling cross sectional vectors over time is invalid in this context because it induces a zero bias. We then propose the cr...
متن کاملNonparametric Trending Regression with Cross-Sectional Dependence
Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have a common time trend. The time trend is of unknown form, the model includes additive, unknown, individual-speci c components, and we allow for spatial or other cross-sectional dependence and/or heteroscedasticity. A simple smoothed nonparametric trend estimate is shown to be dominated by an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2020
ISSN: 0169-2070
DOI: 10.1016/j.ijforecast.2019.11.007