IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i11p6214-d566615.html
   My bibliography  Save this article

Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

Author

Listed:
  • Bumjoon Bae

    (Center for Privately-Financed Highway Studies, The Korea Transport Institute, Sejong 30147, Korea)

  • Changju Lee

    (Environment, Planning and Economic Division, Virginia Transportation Research Council, Charlottesville, VA 22904, USA
    Current Affiliation: Transport Division, United Nations Economic and Social Commission for Asia and the Pacific, Bangkok 10200, Thailand.)

  • Tae-Young Pak

    (Department of Consumer Science, Sungkyunkwan University, Seoul 03063, Korea)

  • Sunghoon Lee

    (Business Data Analytics Team, Samsung Card Co., Ltd., Seoul 04514, Korea)

Abstract

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.

Suggested Citation

  • Bumjoon Bae & Changju Lee & Tae-Young Pak & Sunghoon Lee, 2021. "Identifying Temporal Aggregation Effect on Crash-Frequency Modeling," Sustainability, MDPI, vol. 13(11), pages 1-10, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6214-:d:566615
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/11/6214/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/11/6214/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    2. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bae, Bumjoon & Seo, Changbeom, 2022. "Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models," Transport Policy, Elsevier, vol. 126(C), pages 336-342.

    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. Sai Chand & Emily Moylan & S. Travis Waller & Vinayak Dixit, 2020. "Analysis of Vehicle Breakdown Frequency: A Case Study of New South Wales, Australia," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    2. María Flor & Armando Ortuño & Begoña Guirao, 2022. "Does the Implementation of Ride-Hailing Services Affect Urban Road Safety? The Experience of Madrid," IJERPH, MDPI, vol. 19(5), pages 1-18, March.
    3. Bae, Bumjoon & Seo, Changbeom, 2022. "Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models," Transport Policy, Elsevier, vol. 126(C), pages 336-342.
    4. María Flor & Armando Ortuño & Begoña Guirao & Jairo Casares, 2021. "Analysis of the Impact of Ride-Hailing Services on Motor Vehicles Crashes in Madrid," Sustainability, MDPI, vol. 13(11), pages 1-16, May.
    5. Gillen, David & Hasheminia, Hamed, 2013. "Estimating the demand responses for different sizes of air passenger groups," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 24-38.
    6. Daniel Albalate, 2013. "The Road against Fatalities: Infrastructure Spending vs. Regulation?," ERSA conference papers ersa13p221, European Regional Science Association.
    7. Najaf, Pooya & Thill, Jean-Claude & Zhang, Wenjia & Fields, Milton Greg, 2018. "City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 257-270.
    8. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    9. Bijwaard, G.E. & Franses, Ph.H.B.F., 2006. "Does rounding matter for payment efficiency?," Econometric Institute Research Papers EI 2006-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Lederman, Daniel & Saenz, Laura, 2005. "Innovation and development around the world, 1960-2000," Policy Research Working Paper Series 3774, The World Bank.
    11. Symeonidis, George, 2001. "Price Competition, Innovation and Profitability: Theory and UK Evidence," CEPR Discussion Papers 2816, C.E.P.R. Discussion Papers.
    12. Verdier Valentin, 2018. "Local Semi-Parametric Efficiency of the Poisson Fixed Effects Estimator," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-10, January.
    13. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    14. de Rassenfosse, Gaétan, 2013. "Do firms face a trade-off between the quantity and the quality of their inventions?," Research Policy, Elsevier, vol. 42(5), pages 1072-1079.
    15. Zhang, Feng & Jiang, Guohua & Cantwell, John A., 2015. "Subsidiary exploration and the innovative performance of large multinational corporations," International Business Review, Elsevier, vol. 24(2), pages 224-234.
    16. Daron Acemoglu & Amy Finkelstein, 2008. "Input and Technology Choices in Regulated Industries: Evidence from the Health Care Sector," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 837-880, October.
    17. Sagnik Bagchi & Surajit Bhattacharyya & K. Narayanan, 2015. "Anti-dumping Initiations in Indian Manufacturing Industries," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 16(2), pages 278-294, September.
    18. Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2006. "Vehicle and Fleet Random Effects in a Model of Insurance Rating for Fleets of Vehicles," ASTIN Bulletin, Cambridge University Press, vol. 36(1), pages 25-77, May.
    19. Bergman, Mats A. & Johansson, Per & Bergman, M.A., 2002. "Large investments in the pulp and paper industry: a count data regression analysis," Journal of Forest Economics, Elsevier, vol. 8(1), pages 29-52.
    20. repec:lan:wpaper:2935 is not listed on IDEAS
    21. William Greene, 2001. "Estimating Econometric Models With Fixed Effects," Working Papers 01-10, New York University, Leonard N. Stern School of Business, Department of Economics.

    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:gam:jsusta:v:13:y:2021:i:11:p:6214-:d:566615. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.