IDEAS home Printed from https://ideas.repec.org/p/ags/ndtr05/208165.html
   My bibliography  Save this paper

An Analysis of Gender Differences in Vehicles Miles Traveled (VMT) Using Nonparametric Methods

Author

Listed:
  • Sloboba, Brian W.
  • Yao, Vincent W.

Abstract

In the United States as in many nations, there are often differences between the travel patterns of men and women with regards to the differences in travel. Traditionally, women make shorter work trips, make greater use of public transit, make more trips for the purpose of serving another person's travel needs, and drive far fewer miles per year than men. These differences in travel are delineated by the separate social responsibilities of men and women. However, in the past few decades, women have been participating more in the labor force. In addition, women still retain their family obligations as nurturers, shoppers, and homemakers. Given the changes in the transit patterns of women in recent decades, women’s travel patterns still differed substantially from those of men. In fact, these emerging trends from transit patterns of women, their actual vehicle miles traveled (VMT) are starting to increase and may surpass the VMT of men. Additionally, it is speculated by transportation planners and policy-makers that the VMT of women will surpass the VMT of men in the future. In the past, transportation studies have not been particularly oriented to women’s’ travel issues despite the presence of the data and statistical methodologies. On the other hand, surveys such as the National Household Transportation Survey (NHTS) can be used to understand trends in women's travel patterns, which are often attributed to changes in labor force participation, household structure, and attitudes. This paper will analyze the differences in the vehicle miles traveled (VMT) between men and women using nonparametric methods using the data from the NHTS data as prepared by the Bureau of Transportation Statistics (BTS) in the U.S. Department of Transportation. Moreover, the examination of the relationship of VMT and other household variables would be estimated in a flexible way which cannot be assessed using parametric modeling methods.

Suggested Citation

  • Sloboba, Brian W. & Yao, Vincent W., 2005. "An Analysis of Gender Differences in Vehicles Miles Traveled (VMT) Using Nonparametric Methods," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208165, Transportation Research Forum.
    • Handle: RePEc:ags:ndtr05:208165
    DOI: 10.22004/ag.econ.208165
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/208165/files/2005_GenderDifferences_paper.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.208165?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Racine, Jeff, 1997. "Consistent Significance Testing for Nonparametric Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 369-378, July.
    2. Li, Qi & Maasoumi, Esfandiar & Racine, Jeffrey S., 2009. "A nonparametric test for equality of distributions with mixed categorical and continuous data," Journal of Econometrics, Elsevier, vol. 148(2), pages 186-200, February.
    3. Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
    4. Kitamura, Ryuichi, 1984. "A model of daily time allocation to discretionary out-of-home activities and trips," Transportation Research Part B: Methodological, Elsevier, vol. 18(3), pages 255-266, June.
    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. De la Cruz, Marco & Mergoni, Anna, 2024. "Assessing the performance of Peruvian education system from a governance perspective," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    2. López-Herrera, Carmen & Cordero, José M. & Pedraja-Chaparro, Francisco & Polo, Cristina, 2023. "Fiscal rules and their influence on public sector efficiency," MPRA Paper 119018, University Library of Munich, Germany.
    3. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "Public sector transparency and countries’ environmental performance: A nonparametric analysis," Resource and Energy Economics, Elsevier, vol. 38(C), pages 19-37.
    4. repec:clg:wpaper:2008-28 is not listed on IDEAS
    5. Dependra Bhatta & Krishna P. Paudel & Kai Liu, 2023. "Factors influencing water conservation practices adoptions by Nepali farmers," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10879-10901, October.
    6. Baležentis, Tomas & De Witte, Kristof, 2015. "One- and multi-directional conditional efficiency measurement – Efficiency in Lithuanian family farms," European Journal of Operational Research, Elsevier, vol. 245(2), pages 612-622.
    7. Kourtesi, Sofia & De Witte, Kristof & Polymeros, Apostolos, 2016. "Technical Efficiency in the Agricultural Sector - Evidence from a Conditional Quantile-Based Approach," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    8. Julius Owusu, 2024. "A Nonparametric Test of Heterogeneous Treatment Effects under Interference," Papers 2410.00733, arXiv.org.
    9. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    10. Corak, Miles & Lauzon, Darren, 2009. "Differences in the distribution of high school achievement: The role of class-size and time-in-term," Economics of Education Review, Elsevier, vol. 28(2), pages 189-198, April.
    11. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    12. Degl’Innocenti, Marta & Matousek, Roman & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank efficiency and financial centres: Does geographical location matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 188-198.
    13. Silvia Saravia-Matus & T. S. Amjath-Babu & Sreejith Aravindakshan & Stefan Sieber & Jimmy A. Saravia & Sergio Gomez y Paloma, 2021. "Can Enhancing Efficiency Promote the Economic Viability of Smallholder Farmers? A Case of Sierra Leone," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    14. Fall, François Seck & Tchakoute Tchuigoua, Hubert & Vanhems, Anne & Simar, Léopold, 2022. "Investigating the unobserved heterogeneity effect on microfinance social efficiency," LIDAM Discussion Papers ISBA 2022010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
    16. George E. Halkos & Nickolaos G. Tzeremes, 2015. "Measuring Seaports' Productivity: A Malmquist Productivity Index Decomposition Approach," Journal of Transport Economics and Policy, University of Bath, vol. 49(2), pages 355-376, April.
    17. Garling, Tommy & Kwan, Mei-Po & Golledge, Reginald G., 1991. "Computational-Process Modelling of Travel Decisions: Review and Conceptual Analysis," University of California Transportation Center, Working Papers qt6mk0h2s2, University of California Transportation Center.
    18. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    19. Temel, Tugrul T., 2001. "A Nonparametric Hypothesis Test Via The Bootstrap Resampling," 2001 Annual meeting, August 5-8, Chicago, IL 20600, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.

    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:ags:ndtr05:208165. 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: AgEcon Search (email available below). General contact details of provider: https://trforum.org/annual-forum/ .

    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.