Activity Number:
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463
- SPEED: Methodological Advances in Time Series: BandE Speed Session, Part 1
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Type:
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Contributed
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Date/Time:
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Wednesday, July 31, 2019 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #306684
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Presentation
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Title:
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The Development of a Calculation of Composite Coincident Indicator (CCI) for the United States
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Author(s):
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Brian Sloboda* and Chandra Putcha
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Companies:
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University of Phoenix and California State University at Fullerton
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Keywords:
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Peak-Valley Algorithm;
coincident indicators ;
business cycles;
local maximum and minimum;
global maximum and minimum
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Abstract:
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The purpose of this paper is to continue work on a composite coincident indicator (CCI) for the United States and by each state as covered in Putcha and Sloboda (2017, 2018). This research looks at the economic time series for the United States by examining behavior of the key time series and applying the peak-valley algorithm as proposed by Schneider (2011) before creating the CCI. The detection of peaks and valleys in time series has been a longstanding problem in economic time series. To identify the trends in the economic time series, we provide two approaches to determine the trend in the time series: the geometric approach and the statistical definition of peaks and valleys. These two approaches can detect the significant trends within economic time series. This preliminary research examines the proposed variables that could be included into an eventual CCI for the United States.
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Authors who are presenting talks have a * after their name.