IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i20p9071-d1502423.html
   My bibliography  Save this article

Macroscopic State-Level Analysis of Pavement Roughness Using Time–Space Econometric Modeling Methods

Author

Listed:
  • Mehmet Fettahoglu

    (Department of Civil, Structural and Environmental Engineering, University at Buffalo—The State University of New York, Buffalo, NY 14260, USA)

  • Sheikh Shahriar Ahmed

    (Steer Group, Brooklyn, NY 11201, USA)

  • Irina Benedyk

    (Department of Civil, Structural and Environmental Engineering, University at Buffalo—The State University of New York, Buffalo, NY 14260, USA)

  • Panagiotis Ch. Anastasopoulos

    (Department of Civil, Structural and Environmental Engineering, University at Buffalo—The State University of New York, Buffalo, NY 14260, USA
    Stephen Still Institute for Sustainable Transportation and Logistics, University at Buffalo—The State University of New York, Buffalo, NY 14260, USA)

Abstract

This paper used pavement condition data collected by the Federal Highway Administration (FHWA) between 2001 and 2006 aggregated by U.S. states to identify macroscopic factors affecting pavement roughness in time and space. To account for prior pavement conditions and preservation expenditure over time, time autocorrelation parameters were introduced in a spatial modeling scheme that accounted for spatial autocorrelation and heterogeneity. The proposed framework accommodates data aggregation in network-level pavement deterioration models. Because pavement roughness across different roadway classes is anticipated to be affected by different explanatory parameters, separate time–space models are estimated for nine roadway classes (rural interstate roads, rural collectors, urban minor arterials, urban principal arterials, and other freeways). The best model specifications revealed that different time–space models were appropriate for pavement performance modeling across the different roadway classes. Factors that were found to affect state-level pavement roughness in time and space included preservation expenditure, predominant soil type, and predominant climatic conditions. The results have the potential to assist governmental agencies in planning effectively for pavement preservation programs at a macroscopic level.

Suggested Citation

  • Mehmet Fettahoglu & Sheikh Shahriar Ahmed & Irina Benedyk & Panagiotis Ch. Anastasopoulos, 2024. "Macroscopic State-Level Analysis of Pavement Roughness Using Time–Space Econometric Modeling Methods," Sustainability, MDPI, vol. 16(20), pages 1-21, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9071-:d:1502423
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/20/9071/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/20/9071/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    2. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    3. Prozzi, J A & Madanat, S M, 2004. "Development of Pavement Performance Models by Combining Experimental and Field Data," University of California Transportation Center, Working Papers qt6cf8v5cw, University of California Transportation Center.
    4. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    5. Jason Abrevaya & Jerry A. Hausman & Shakeeb Khan, 2010. "Testing for Causal Effects in a Generalized Regression Model With Endogenous Regressors," Econometrica, Econometric Society, vol. 78(6), pages 2043-2061, November.
    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. Catherine Baumont & Cem Ertur & Julie Le Gallo, 2001. "A spatial econometric analysis of geographic spillovers and growth for European regions, 1980-1995," Working Papers hal-01526858, HAL.
    2. Jørgen Lauridsen & Reinhold Kosfeld, 2007. "Spatial cointegration and heteroscedasticity," Journal of Geographical Systems, Springer, vol. 9(3), pages 253-265, September.
    3. Tsimpanos, Apostolos & Tsimbos, Cleon & Kalogirou, Stamatis, 2018. "Assessing spatial variation and heterogeneity of fertility in Greece at local authority level," MPRA Paper 100406, University Library of Munich, Germany.
    4. Machado, Jose A. F. & Silva, J. M. C. Santos, 2000. "Glejser's test revisited," Journal of Econometrics, Elsevier, vol. 97(1), pages 189-202, July.
    5. repec:zbw:rwirep:0227 is not listed on IDEAS
    6. Frondel, Manuel & Ritter, Nolan & Vance, Colin, 2012. "Heterogeneity in the rebound effect: Further evidence for Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 34(2), pages 461-467.
    7. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    8. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
    9. LE GALLO, Julie, 2000. "Econométrie spatiale 2 -Hétérogénéité spatiale," LATEC - Document de travail - Economie (1991-2003) 2001-01, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    10. Cho, Seong-Hoon & Kim, Taeyoung & Kim, Hyun Jae & Park, Kihyun & Roberts, Roland K., 2015. "Regionally-varying and regionally-uniform electricity pricing policies compared across four usage categories," Energy Economics, Elsevier, vol. 49(C), pages 182-191.
    11. Julie Le Gallo, 2004. "Hétérogénéité spatiale : principes et méthodes," Économie et Prévision, Programme National Persée, vol. 162(1), pages 151-172.
    12. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    13. Cem Ertur & Julie Le Gallo & Catherine Baumont, 2006. "The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?," International Regional Science Review, , vol. 29(1), pages 3-34, January.
    14. Vanessa Berenguer Rico & Ines Wilms, 2018. "White heteroscedasticty testing after outlier removal," Economics Series Working Papers 853, University of Oxford, Department of Economics.
    15. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    16. Johan Lundberg, 2006. "Using spatial econometrics to analyse local growth in Sweden," Regional Studies, Taylor & Francis Journals, vol. 40(3), pages 303-316.
    17. Monique DANTAS & Frédéric GASCHET & Guillaume POUYANNE, 2010. "Regulatory zoning and coastal housing prices: a bayesian hedonic approach (In French)," Cahiers du GREThA (2007-2019) 2010-12, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    18. Olaru, Doina & Mulley, Corinne & Smith, Brett & Ma, Liang, 2017. "Policy-led selection of the most appropriate empirical model to estimate hedonic prices in the residential market," Journal of Transport Geography, Elsevier, vol. 62(C), pages 213-228.
    19. Cox, Michael & Ross, Justin M., 2011. "Robustness and vulnerability of community irrigation systems: The case of the Taos valley acequias," Journal of Environmental Economics and Management, Elsevier, vol. 61(3), pages 254-266, May.
    20. Tom Broekel & Thomas Brenner, 2011. "Regional factors and innovativeness: an empirical analysis of four German industries," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(1), pages 169-194, August.
    21. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5.

    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:16:y:2024:i:20:p:9071-:d:1502423. 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.