Granger Causality Testing and LEI Forecasting of Quarterly Mergers and the Unemployment Rate

John B. Guerard ()
Additional contact information
John B. Guerard: McKinley Capital Management, LLC

Chapter Chapter 8 in The Leading Economic Indicators and Business Cycles in the United States, 2022, pp 291-329 from Springer

Abstract: Abstract Ιn this chapter we examine, in the context of a data-specific case study, the automatic time series approach to modeling and forecasting time series. The time series modeling approach has evolved from the Box and Jenkins (1970) approach for the identification, estimation, and forecasting of stationary (or series transformed to stationarity) series, through the analysis of the series autocorrelation and partial autocorrelation functions, to the world of Clive Granger (2001) and causality testing, to current applications of automatic time series modeling and forecasting of Tsay (1988, 1989), implemented in the Scientific Computing Associates (DCA) program, and Vinod (2014), in his R-program.

Date: 2022
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:978-3-030-99418-1_8

Ordering information: This item can be ordered from
http://www.springer.com/9783030994181

DOI: 10.1007/978-3-030-99418-1_8

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 ().