Vector Error Correction Models
Helmut Lütkepohl
Chapter 6 in New Introduction to Multiple Time Series Analysis, 2005, pp 237-267 from Springer
Abstract:
Abstract As defined in Chapter 2, a process is stationary if it has time invariant first and second moments. In particular, it does not have trends or changing variances. A VAR process has this property if the determinantal polynomial of its VAR operator has all its roots outside the complex unit circle. Clearly, stationary processes cannot capture some main features of many economic time series. For example, trends (trending means) are quite common in practice. For instance, the original investment, income, and consumption data used in many previous examples have trends (see Figure 3.1). Thus, if interest centers on analyzing the original variables (or their logarithms) rather than the rates of change, it is necessary to have models that accommodate the nonstationary features of the data. It turns out that a VAR process can generate stochastic and deterministic trends if the determinantal polynomial of the VAR operator has roots on the unit circle. In fact, it is even sufficient to allow for unit roots (roots for z = 1) to obtain a trending behavior of the variables. We will consider this case in some detail in this chapter. In the next section, the effect of unit roots in the AR operator of a univariate process will be analyzed. Variables generated by such processes are called integrated variables and the underlying generating processes are integrated processes. Vector processes with unit roots are considered in Section 6.2. In these processes, some of the variables can have common trends so that they move together to some extent.
Keywords: Unit Root; Forecast Error; Vector Error Correction Model; Deterministic Term; Cointegration Relation (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (1)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Journal Article: Problems related to over-identifying restrictions for structural vector error correction models (2008) 
Journal Article: Residual autocorrelation testing for vector error correction models (2006) 
Chapter: Estimation of Vector Error Correction Models (2005)
Working Paper: Problems Related to Over-identifying Restrictions for Structural Vector Error Correction Models (2005) 
Working Paper: Residual Autocorrelation Testing for Vector Error Correction Models (2004) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-27752-1_6
Ordering information: This item can be ordered from
http://www.springer.com/9783540277521
DOI: 10.1007/978-3-540-27752-1_6
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().