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

In: The Leading Economic Indicators and Business Cycles in the United States

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  • John B. Guerard

    (McKinley Capital Management, LLC)

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.

Suggested Citation

  • John B. Guerard, 2022. "Granger Causality Testing and LEI Forecasting of Quarterly Mergers and the Unemployment Rate," Springer Books, in: The Leading Economic Indicators and Business Cycles in the United States, chapter 0, pages 291-329, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-99418-1_8
    DOI: 10.1007/978-3-030-99418-1_8
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