IDEAS home Printed from https://ideas.repec.org/p/hhs/nhhfms/2022_013.html
   My bibliography  Save this paper

Adjusting for Cell Suppression in Commuting Trip Data

Author

Listed:
  • Braathen, Christian

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Thorsen, Inge

    (Dept. of Business Administration, Western Norway University of Applied Sciences)

  • Ubøe, Jan

    (Dept. of Business and Management Science, Norwegian School of Economics)

Abstract

Maximum entropy methods are used to infer the true trip-distribution matrix in cases where parts of the data are suppressed due to privacy concerns. Large proportions of the suppressed data are found to be inferred correctly when the marginal totals in the trip distribution are known. Entropy-based approaches are further found to outperform a strategy of ignoring suppressed information in cases with suppressed marginal totals and/or a higher cut-off value of suppressing cell information. Our methods are demonstrated to reduce the systematic bias in estimates of the distance deterrence parameter to such small numbers that it is effectively zero, preventing potentially serious bias in estimates and predictions resulting from standard spatial interaction models. Another useful contribution is to identify what scenarios an entropy-maximization approach benefits from incorporating information on times series and/or information on distances in the transportation network.

Suggested Citation

  • Braathen, Christian & Thorsen, Inge & Ubøe, Jan, 2022. "Adjusting for Cell Suppression in Commuting Trip Data," Discussion Papers 2022/13, Norwegian School of Economics, Department of Business and Management Science.
  • Handle: RePEc:hhs:nhhfms:2022_013
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/11250/3037535
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Philip Mcarthur & Inge Thorsen & Jan Ubøe, 2010. "A Micro‐Simulation Approach to Modelling Spatial Unemployment Disparities," Growth and Change, Wiley Blackwell, vol. 41(3), pages 374-402, September.
    2. Raj Chetty & John N. Friedman, 2019. "A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 414-420, May.
    3. Arnstein Gjestland & Inge Thorsen & Jan Ubøe, 2006. "Some aspects of the intraregional spatial distribution of local sector activities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 40(3), pages 559-582, August.
    4. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    5. Mattsson, Lars-Goran & Weibull, Jorgen W., 2002. "Probabilistic choice and procedurally bounded rationality," Games and Economic Behavior, Elsevier, vol. 41(1), pages 61-78, October.
    6. Sven B. Erlander, 2010. "Cost-Minimizing Choice Behavior in Transportation Planning," Advances in Spatial Science, Springer, number 978-3-642-11911-8, Fall.
    7. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    8. Damiaan Persyn & Wouter Torfs, 2016. "A gravity equation for commuting with an application to estimating regional border effects in Belgium," Journal of Economic Geography, Oxford University Press, vol. 16(1), pages 155-175.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    10. Craig Wesley Carpenter & Anders Van Sandt & Scott Loveridge, 2022. "Measurement error in US regional economic data," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 57-80, January.
    11. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    12. John M. Abowd & Ian M. Schmutte, 2019. "An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices," American Economic Review, American Economic Association, vol. 109(1), pages 171-202, January.
    13. Page, Scott E., 1999. "On the Emergence of Cities," Journal of Urban Economics, Elsevier, vol. 45(1), pages 184-208, January.
    14. John M. Abowd & Ian M. Schmutte, 2015. "Economic Analysis and Statistical Disclosure Limitation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 50(1 (Spring), pages 221-293.
    15. Elena G. Irwin, 2010. "New Directions For Urban Economic Models Of Land Use Change: Incorporating Spatial Dynamics And Heterogeneity," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 65-91, February.
    16. Paass, Gerhard, 1988. "Disclosure Risk and Disclosure Avoidance for Microdata," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(4), pages 487-500, October.
    17. Binswanger, Johannes & Oechslin, Manuel, 2020. "Better statistics, better economic policies?," European Economic Review, Elsevier, vol. 130(C).
    18. John M. Abowd & Ian M. Schmutte, 2015. "Economic Analysis and Statistical Disclosure Limitation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(1 (Spring), pages 221-293.
    19. Anas, Alex, 1983. "Discrete choice theory, information theory and the multinomial logit and gravity models," Transportation Research Part B: Methodological, Elsevier, vol. 17(1), pages 13-23, February.
    20. Jens P Gitlesen & Inge Thorsen, 2000. "A Competing Destinations Approach to Modeling Commuting Flows: A Theoretical Interpretation and An Empirical Application of the Model," Environment and Planning A, , vol. 32(11), pages 2057-2074, November.
    21. Duncan, George & Lambert, Diane, 1989. "The Risk of Disclosure for Microdata," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(2), pages 207-217, April.
    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. Michler, Jeffrey D. & Josephson, Anna & Kilic, Talip & Murray, Siobhan, 2022. "Privacy protection, measurement error, and the integration of remote sensing and socioeconomic survey data," Journal of Development Economics, Elsevier, vol. 158(C).
    2. Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Ubøe, Jan, 2019. "Analyzing learning effects in the newsvendor model by probabilistic methods," Discussion Papers 2019/13, Norwegian School of Economics, Department of Business and Management Science.
    3. Vilhuber, Lars, 2023. "Reproducibility and transparency versus privacy and confidentiality: Reflections from a data editor," Journal of Econometrics, Elsevier, vol. 235(2), pages 2285-2294.
    4. Craig Wesley Carpenter & Anders Van Sandt & Scott Loveridge, 2022. "Measurement error in US regional economic data," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 57-80, January.
    5. Ubøe, Jan & Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Sandal, Leif K., 2014. "Probabilistic cost efficiency and bounded rationality in the newsvendor model," Discussion Papers 2014/41, Norwegian School of Economics, Department of Business and Management Science.
    6. Ubøe, Jan & Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Sandal, Leif, 2017. "Statistical testing of bounded rationality with applications to the newsvendor model," European Journal of Operational Research, Elsevier, vol. 259(1), pages 251-261.
    7. Raj Chetty & John N. Friedman, 2019. "A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 414-420, May.
    8. John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Simson Garfinkel & Micah Heineck & Christine Heiss & Robert Johns & Daniel Kifer & Philip Leclerc & Ashwin Machanavajjhala & Brett Moran & William, 2022. "The 2020 Census Disclosure Avoidance System TopDown Algorithm," Papers 2204.08986, arXiv.org.
    9. Mogens Fosgerau & Julien Monardo & André de Palma, 2019. "The Inverse Product Differentiation Logit Model," Working Papers hal-02183411, HAL.
    10. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    11. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    12. Pennesi, Daniele, 2021. "Intertemporal discrete choice," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 690-706.
    13. Thorsen, Helge Sandvig & Thorsen, Inge, 2017. "Effects of transportation barriers on geographic asymmetries in labour markets," Research in Transportation Economics, Elsevier, vol. 63(C), pages 27-37.
    14. Fedor Sandomirskiy & Omer Tamuz, 2023. "Decomposable Stochastic Choice," Papers 2312.04827, arXiv.org.
    15. Melvin Wong & Bilal Farooq, 2019. "Information processing constraints in travel behaviour modelling: A generative learning approach," Papers 1907.07036, arXiv.org, revised Jul 2019.
    16. Tsionas, Mike G., 2020. "Bounded rationality and thick frontiers in stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 762-768.
    17. Stefano Mainardi, 2021. "Preference heterogeneity, neighbourhood effects and basic services: logit kernel models for farmers’ climate adaptation in Ethiopia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 6869-6912, May.
    18. Persyn, Damiaan, 2021. "Migrants looking for opportunities - On destination size and spatial aggregation in the gravity equation for migration," MPRA Paper 111064, University Library of Munich, Germany.
    19. Ian M. Schmutte & Nathan Yoder, 2022. "Information Design for Differential Privacy," Papers 2202.05452, arXiv.org, revised Dec 2022.
    20. Breitmoser, Yves, 2017. "Discrete Choice with Presentation Effects," Rationality and Competition Discussion Paper Series 35, CRC TRR 190 Rationality and Competition.

    More about this item

    Keywords

    Maximum entropy methods; trip-distribution matrix; spatial interaction;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:hhs:nhhfms:2022_013. 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: Stein Fossen (email available below). General contact details of provider: https://edirc.repec.org/data/dfnhhno.html .

    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.