Cointegration analysis with mixed-frequency data

Arbeitspapier

We develop a method for directly modeling cointegrated multivariate time series that are observed in mixed frequencies. We regard lower-frequency data as regularly (or irregularly) missing and treat them with higher-frequency data by adopting a state-space model. This utilizes the structure of multivariate data as well as the available sample information more fully than the methods of transformation to a single frequency, and enables us to estimate parameters including cointegrating vectors and the missing observations of low-frequency data and to construct forecasts for future values. For the maximum likelihood estimation of the parameters in the model, we use an expectation maximization algorithm based on the state-space representation of the error correction model. The statistical efficiency of the developed method is investigated through a Monte Carlo study. We apply the method to a mixed-frequency data set that consists of the quarterly real gross domestic product and the monthly consumer price index.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: CESifo Working Paper ; No. 1939

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
• Thema: missing data ; Kalman filter ; expectation maximization algorithm ; forecasting ; error correction model ; smoothing ; maximum likelihood estimation ; Kointegration ; Zeitreihenanalyse ; Zustandsraummodell ; Prognoseverfahren ; Fehlerkorrekturmodell ; Theorie ; Schätzung ; Sozialprodukt ; Lebenshaltungsindex ; USA

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Seong, Byeongchan ; Ahn, Sung K. ; Zadrozny, Peter A.
• Ereignis: Veröffentlichung
• (wer): Center for Economic Studies and ifo Institute (CESifo)
• (wo): Munich
• (wann): 2007

Weitere Informationen

• Handle: http://hdl.handle.net/10419/25984
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ