The paper studies large-dimention factor models with nonstationary factors and allows for deterministic trends and factors integrated of order higher then one.We follow the model speci.cation of Bai (2004) and derive the convergence rates and the limiting distributions of estimated factors, factors loadings and common components. We discuss in detail a model with a linear time trend. We ilustrate the theory with an empirical exmple that studies the fluctuations of the real activity of U.S.economy. We show that these .uctuationas can be explained by two nonstationary factors and a small number of stationary factors. We test the economic interpretation of nonstationary factors.Common-stochastic trends; Dynamic factors; Generalized dynamic fac...
Forecasting using "diffusion indices" has received a good deal of attention in recent years. The ide...
This paper studies a general class of nonlinear varying coefficient time series models with possible ...
This paper focuses on the effects of disaggregation on forecast accuracy for nonstationary time seri...
The paper studies large-dimension factor models with nonstationary factors and allows for determinis...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
Abstract. Factor modelling of a large time series panel has widely proven useful to reduce its cross...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
This thesis deals with the development and application of new estimation approaches based on factor ...
In this paper, we analyze and compare the finite sample properties of alternative factor extraction ...
In this paper we present a generalized dynamic factor model for a vector of time series which seems ...
We propose a testing-based procedure to determine the number of common trends in a large nonstationa...
In this paper, we analyze and compare the finite sample properties of alternative factor extraction ...
This dissertation focuses on studying two topics of large non-stationary Dynamic Factor Models (DFM...
This PhD thesis applies the time-series concepts of unit-roots and cointegration to nonstationary pa...
Forecasting using "diffusion indices" has received a good deal of attention in recent years. The ide...
This paper studies a general class of nonlinear varying coefficient time series models with possible ...
This paper focuses on the effects of disaggregation on forecast accuracy for nonstationary time seri...
The paper studies large-dimension factor models with nonstationary factors and allows for determinis...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
Abstract. Factor modelling of a large time series panel has widely proven useful to reduce its cross...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional...
This thesis deals with the development and application of new estimation approaches based on factor ...
In this paper, we analyze and compare the finite sample properties of alternative factor extraction ...
In this paper we present a generalized dynamic factor model for a vector of time series which seems ...
We propose a testing-based procedure to determine the number of common trends in a large nonstationa...
In this paper, we analyze and compare the finite sample properties of alternative factor extraction ...
This dissertation focuses on studying two topics of large non-stationary Dynamic Factor Models (DFM...
This PhD thesis applies the time-series concepts of unit-roots and cointegration to nonstationary pa...
Forecasting using "diffusion indices" has received a good deal of attention in recent years. The ide...
This paper studies a general class of nonlinear varying coefficient time series models with possible ...
This paper focuses on the effects of disaggregation on forecast accuracy for nonstationary time seri...