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Extracting information from mega‐panels and high‐frequency data

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  • C. W. J. Granger

Abstract

With the advent of very large data sets in economics, econometricians, with the help of statisticians, have to re‐evaluate current techniques and develop new procedures and their interpretation. Most tests of significance become irrelevant, for example, and conditional distributions become important, but difficult to report. Time series with high frequency data also present new and interesting questions.

Suggested Citation

  • C. W. J. Granger, 1998. "Extracting information from mega‐panels and high‐frequency data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(3), pages 258-272, November.
    • Handle: RePEc:bla:stanee:v:52:y:1998:i:3:p:258-272
    DOI: 10.1111/1467-9574.00084
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    9. Jacob A. Bikker & Laura Spierdijk & Paul Finnie, 2006. "The Impact of Bank Size on Market Power," DNB Working Papers 120, Netherlands Central Bank, Research Department.
    10. Hiroyuki Moriya, 2017. "Quantized price volatility model for transaction data," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 397-408, December.
    11. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    12. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    13. Namwon Hyung & Clive W.J. Granger, 2008. "Linking series generated at different frequencies This work is part of a PhD dissertation presented at the University of California, San Diego (1999)," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 95-108.
    14. Kézdi, Gábor & Mátyás, László & Balázsi, László & Divényi, János Károly, 2014. "A közgazdasági adatforradalom és a panelökonometria [The revolution in economic data and panel econometrics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1319-1340.
    15. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2019. "Forecast density combinations with dynamic learning for large data sets in economics and finance," Working Paper 2019/7, Norges Bank.
    16. Peter, Eckley, 2015. "Measuring economic uncertainty using news-media textual data," MPRA Paper 64874, University Library of Munich, Germany, revised 01 May 2015.
    17. Galati, Luca, 2024. "Exchange market share, market makers, and murky behavior: The impact of no-fee trading on cryptocurrency market quality," Journal of Banking & Finance, Elsevier, vol. 165(C).
    18. Roy Cerqueti & Claudio Lupi, 2021. "Some New Tests of Conformity with Benford’s Law," Stats, MDPI, vol. 4(3), pages 1-17, September.
    19. I. Koetsier & J.A. Bikker, 2017. "Herding behaviour of Dutch pension funds in sovereign bond investments," Working Papers 17-15, Utrecht School of Economics.
    20. Jacob Bikker & Laura Spierdijk & Paul Finnie, 2006. "Misspecifiation of the Panzar-Rosse Model: Assessing Competition in the Banking Industry," DNB Working Papers 114, Netherlands Central Bank, Research Department.
    21. Jaeheon Choi & Kyuil Lee & Hyunmyung Kim & Sunghi An & Daisik Nam, 2020. "Classification of Inter-Urban Highway Drivers’ Resting Behavior for Advanced Driver-Assistance System Technologies using Vehicle Trajectory Data from Car Navigation Systems," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    22. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

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