Robustness of Multivariate Time Series Forecasting Based on Systems of Simultaneous Equations

Yuriy Kharin
Additional contact information
Yuriy Kharin: Belarusian State University, Department of Mathematical Modeling and Data Analysis

Chapter Chapter 9 in Robustness in Statistical Forecasting, 2013, pp 273-303 from Springer

Abstract: Abstract Systems of simultaneous equations (SSE) are a well-studied class of multivariate time series models with applications to macroeconometrics. In this chapter, we analyze robustness of forecasting statistics based on the least squares method and its modifications under model specification errors and $$\varepsilon$$ -drift of model coefficients.

Keywords: Change Point; Exogenous Variable; Endogenous Variable; Specification Error; Multivariate Time Series (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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:978-3-319-00840-0_9

Ordering information: This item can be ordered from
http://www.springer.com/9783319008400

DOI: 10.1007/978-3-319-00840-0_9

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 ().