IDEAS home Printed from
   My bibliography  Save this paper

Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA


  • Klaus Ackermann

    (SoDa Laboratories, Monash University)

  • Simon D Angus

    (SoDa Laboratories, Monash University)

  • Paul A Raschky

    (SoDa Laboratories, Monash University)


Alternative data is increasingly adapted to predict human and economic behaviour. This paper introduces a new type of alternative data by re-conceptualising the internet as a data-driven insights platform at global scale. Using data from a unique internet activity and location dataset drawn from over 1.5 trillion observations of end-user internet connections, we construct a functional dataset covering over 1,600 cities during a 7 year period with temporal resolution of just 15min. To predict ac- curate temporal patterns of sleep and work activity from this data-set, we develop a new technique, Segmented Functional Classification Analysis (SFCA), and compare its performance to a wide array of linear, functional, and classification methods. To confirm the wider applicability of SFCA, in a second application we predict sleep and work activity using SFCA from US city-wide electricity demand functional data. Across both problems, SFCA is shown to out-perform current methods.

Suggested Citation

  • Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
  • Handle: RePEc:ajr:sodwps:2020-04

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Müller, Hans-Georg & Yao, Fang, 2008. "Functional Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1534-1544.
    2. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
    3. Vera Straat & Piet Bracke, 2015. "How well does Europe sleep? A cross-national study of sleep problems in European older adults," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 60(6), pages 643-650, September.
    4. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    5. Garcia, Damien, 2010. "Robust smoothing of gridded data in one and higher dimensions with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1167-1178, April.
    6. Till Roenneberg, 2013. "The human sleep project," Nature, Nature, vol. 498(7455), pages 427-428, June.
    7. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
    8. Reiss, Philip T. & Ogden, R. Todd, 2007. "Functional Principal Component Regression and Functional Partial Least Squares," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 984-996, September.
    9. An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
    10. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    11. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    12. Roland Hodler & Paul A. Raschky, 2014. "Regional Favoritism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(2), pages 995-1033.
    13. Matthew Gibson & Jeffrey Shrader, 2018. "Time Use and Labor Productivity: The Returns to Sleep," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 783-798, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102,
    2. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2017. "The Internet as Quantitative Social Science Platform: Insights from a Trillion Observations," Papers 1701.05632,
    3. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Boslett, Andrew & Hill, Elaine & Ma, Lala & Zhang, Lujia, 2021. "Rural light pollution from shale gas development and associated sleep and subjective well-being," Resource and Energy Economics, Elsevier, vol. 64(C).
    5. Ufuk Beyaztas & Han Lin Shang, 2021. "A partial least squares approach for function-on-function interaction regression," Computational Statistics, Springer, vol. 36(2), pages 911-939, June.
    6. Han, Yi & Wu, Mingqin, 2024. "Inter-regional barriers and economic growth: Evidence from China," Journal of Development Economics, Elsevier, vol. 167(C).
    7. Prakash, Nishith & Rockmore, Marc & Uppal, Yogesh, 2019. "Do criminally accused politicians affect economic outcomes? Evidence from India," Journal of Development Economics, Elsevier, vol. 141(C).
    8. De Luca, Giacomo & Hodler, Roland & Raschky, Paul A. & Valsecchi, Michele, 2018. "Ethnic favoritism: An axiom of politics?," Journal of Development Economics, Elsevier, vol. 132(C), pages 115-129.
    9. Dickinson, Jeffrey, 2020. "Planes, Trains, and Automobiles: What Drives Human-Made Light?," MPRA Paper 103504, University Library of Munich, Germany.
    10. Thomas McGregor & Samuel Wills, 2016. "Surfing A Wave Of Economic Growth," OxCarre Working Papers 170, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    11. Michał Myck & Mateusz Najsztub, 2020. "Implications of the Polish 1999 administrative reform for regional socio‐economic development," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 28(4), pages 559-579, October.
    12. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2018. "Shedding Light on the Spatial Diffusion of Disasters," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181556, Verein für Socialpolitik / German Economic Association.
    13. Lessmann, Christian & Seidel, André, 2017. "Regional inequality, convergence, and its determinants – A view from outer space," European Economic Review, Elsevier, vol. 92(C), pages 110-132.
    14. Lee, Yong Suk, 2018. "International isolation and regional inequality: Evidence from sanctions on North Korea," Journal of Urban Economics, Elsevier, vol. 103(C), pages 34-51.
    15. Hodler, Roland & Raschky, Paul A., 2017. "Ethnic politics and the diffusion of mobile technology in Africa," Economics Letters, Elsevier, vol. 159(C), pages 78-81.
    16. Ishak, Phoebe W., 2022. "Murder nature: Weather and violent crime in rural Brazil," World Development, Elsevier, vol. 157(C).
    17. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    18. Anna Bruederle & Roland Hodler, 2018. "Nighttime lights as a proxy for human development at the local level," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-22, September.
    19. Appau, Samuelson & Awaworyi Churchill, Sefa & Smyth, Russell & Trinh, Trong-Anh, 2021. "The long-term impact of the Vietnam War on agricultural productivity," World Development, Elsevier, vol. 146(C).
    20. Peydró, José-Luis & Abuka, Charles & Alinda, Ronnie & , & Minoiu, Camelia, 2017. "Financial Development and Monetary Policy: Loan Applications, Rates, and Real Effects," CEPR Discussion Papers 12171, C.E.P.R. Discussion Papers.

    More about this item


    functional data analysis; time use; electricity demand; big data; alternative data;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ajr:sodwps:2020-04. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ashani Amarasinghe (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.