Coherence Coefficient for Official Statistics

被引:3
作者
Krapavickaite, Danut [1 ]
机构
[1] Vilnius Gediminas Tech Univ, Dept Math Stat, Sauletekio Al 11, LT-10223 Vilnius, Lithuania
关键词
weakly stationary time series; Fourier transform; periodogram; Granger causality; multidimensional scaling; TIME-SERIES; CAUSALITY;
D O I
10.3390/math10071159
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
One of the quality requirements in official statistics is coherence of statistical information across domains, in time, in national accounts, and internally. However, no measure of its strength is used. The concept of coherence is also met in signal processing, wave physics, and time series. In the current article, the definition of the coherence coefficient for a weakly stationary time series is recalled and discussed. The coherence coefficient is a correlation coefficient between two indicators in time indexed by the same frequency components of their Fourier transforms and shows a degree of synchronicity between the time series for each frequency. The usage of this coefficient is illustrated through the coherence and Granger causality analysis of a collection of numerical economic and social statistical indicators. The coherence coefficient matrix-based non-metric multidimensional scaling for visualization of the time series in the frequency domain is a newly suggested method. The aim of this article is to propose the use of this coherence coefficient and its applications in official statistics.
引用
收藏
页数:20
相关论文
共 46 条
  • [1] African Development Bank, 2012, LAB FORC DAT AN GUID, P92
  • [2] [Anonymous], 2009, GLOSS STAT TERMS
  • [3] [Anonymous], The Comprehensive R Archive Network
  • [4] Bendat JS, 2011, Random data - analysis and measurement procedures
  • [5] Bernataviciene J, 2015, INT J COMPUT COMMUN, V10, P8
  • [6] Borg I., 2005, MODERN MULTIDIMENSIO
  • [7] Assessing the Utility of Sentinel-1 Coherence Time Series for Temperate and Tropical Forest Mapping
    Borlaf-Mena, Ignacio
    Badea, Ovidiu
    Tanase, Mihai Andrei
    [J]. REMOTE SENSING, 2021, 13 (23)
  • [8] Testing for short- and long-run causality: A frequency-domain approach
    Breitung, Jorg
    Candelon, Bertrand
    [J]. JOURNAL OF ECONOMETRICS, 2006, 132 (02) : 363 - 378
  • [9] The Effect of Common Signals on Power, Coherence and Granger Causality: Theoretical Review, Simulations, and Empirical Analysis of Fruit Fly LFPs Data
    Cohen, Dror
    Tsuchiya, Naotsugu
    [J]. FRONTIERS IN SYSTEMS NEUROSCIENCE, 2018, 12
  • [10] Assessing Granger-Causality in the Southern Humboldt Current Ecosystem Using Cross-Spectral Methods
    Contreras-Reyes, Javier E.
    Hernandez-Santoro, Carola
    [J]. ENTROPY, 2020, 22 (10)