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on Econometric Time Series |
| By: | Juan Carlos Aquino; Gabriel Rodríguez (Departamento de Economía - Pontificia Universidad Católica del Perú) |
| Abstract: | This paper analyzes and employs two versions of the Functional Central Limit Theorem within the framework of a unit root with a structural break. Initial attention is focused on the probabilistic structure of the time series to be considered. Later, attention is placed on the asymptotic theory for nonstationary time series proposed by Phillips (1987a), which is applied by Perron (1989) to study the effects of an (assumed) exogenous structural break on the power of the augmented Dickey-Fuller test and by Zivot and Andrews (1992) to criticize the exogeneity assumption and propose a method for estimating an endogenous breakpoint. A systematic method for dealing with e¢ ciency issues is introduced by Perron and RodrÌguez (2003), which extends the Generalized Least Squares detrending approach due to Elliott, Rothenberg, and Stock (1996) |
| Keywords: | Hypothesis Testing, Unit Root, Structural Break, Functional Central Limit Theorem, Weak Convergence, Wiener Process, Ornstein-Uhlenbeck Process |
| JEL: | C12 C22 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pcp:pucwps:wp00319&r=ets |
| By: | Mario Forni; Marc Hallin; Marco Lippi; Paolo Zaffaroni |
| Abstract: | Factor model methods recently have become extremely popular in the theory and practice of large panels of time series data. Those methods rely on various factor models which all are particular cases of the Generalized Dynamic Factor Model (GDFM) introduced in Forni, Hallin, Lippi and Reichlin (2000). In that paper, however, estimation relies on Brillinger’s concept of dynamic principal components, which produces filters that are in general two-sided and therefore yield poor performances at the end of the observation period and hardly can be used for forecasting purposes. In the present paper, we remedy this problem, and show how, based on recent results on singular stationary processes with rational spectra, one-sided estimators are possible for the parameters and the common shocks in the GDFM. Consistency is obtained, along with rates. An empirical section, based on US macroeconomic time series, compares estimates based on our model with those based on the usual staticrepresentation restriction, and provide convincing evidence that the assumptions underlying the latter are not supported by the data. |
| Keywords: | generalized dynamic factor models; vector processes with singular spectral density; one-sided representations for dynamic factor models; consistency and rates for estimators of dynamic factor models |
| JEL: | C00 C01 E00 |
| Date: | 2011–08 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/94959&r=ets |
| By: | Kilian, Lutz |
| Abstract: | Structural vector autoregressive (VAR) models were introduced in 1980 as an alternative to traditional large-scale macroeconometric models when the theoretical and empirical support for these models became increasingly doubtful. Initial applications of the structural VAR methodology often were atheoretical in that users paid insufficient attention to the conditions required for identifying causal effects in the data. In response to ongoing questions about the validity of widely used identifying assumptions the structural VAR literature has continuously evolved since the 1980s. This survey traces the evolution of this literature. It focuses on alternative approaches to the identification of structural shocks within the framework of a reduced-form VAR model, highlighting the conditions under which each approach is valid and discussing potential limitations of commonly employed methods. |
| Keywords: | Identification; Structural model; VAR |
| JEL: | C32 C51 |
| Date: | 2011–08 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:8515&r=ets |