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The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors Ft are I(1) and singular, i.e. Ft has dimension r and is driven by a q-dimensional white noise, the common shocks, with q r, and (2) the idiosyncratic components are I(1). We show that Ft is driven by r-c...
Persistent link: https://www.econbiz.de/10011499818
The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors F_t are I(1) and singular, i.e. F_t has dimension r and is driven by a q-dimensional white noise, the common shocks, with q r, and (2) the idiosyncratic components are I(1). We show that F_t is driven by r − c...
Persistent link: https://www.econbiz.de/10013006677
Persistent link: https://www.econbiz.de/10012619245
The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors Ft are I(1) and singular, i.e. Ft has dimension r and is driven by a q-dimensional white noise, the common shocks, with q r, and (2) the idiosyncratic components are I(1). We show that Ft is driven by r-c...
Persistent link: https://www.econbiz.de/10013210379
Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q r. The present paper studies...
Persistent link: https://www.econbiz.de/10012161569
We introduce an approximate dynamic factor model for modeling and forecasting large panels of realized volatilities. Since the model is estimated by means of principal components and low dimensional maximum likelihood, it does not suffer from the curse of dimensionality. We apply the model to a...
Persistent link: https://www.econbiz.de/10013092430
Persistent link: https://www.econbiz.de/10010374236
Persistent link: https://www.econbiz.de/10010497747
This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...
Persistent link: https://www.econbiz.de/10003746039
We model a large panel of time series as a VAR where the autoregressive matrices and the inverse covariance matrix of the system innovations are assumed to be sparse. The system has a network representation in terms of a directed graph representing predictive Granger relations and an undirected...
Persistent link: https://www.econbiz.de/10014158917