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Relationships Between US Consumer Expenditures on Communications and Transportation Using Almost Ideal Demand System Modeling: 1984--2002

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  • Sangho Choo
  • Taihyeong Lee
  • Patricia L. Mokhtarian

Abstract

This study analyzes aggregate consumer expenditure data from the US between 1984 and 2002, to determine relationships between expenditures on transportation and communications. We first identified 15 categories of goods -- nine for transportation, five for communications, and one for all others -- and obtained prices for each category across time. Then, we applied the linear approximate almost ideal demand system (AIDS) method for estimating consumer demand functions, aggregating the categories to six (non-personal vehicle (PV), PV capital, PV operation, electronic communications media, print communications media, and all others) due to the small sample size. The results indicate that transportation and communications categories have both substitution and complementarity relationships. The existence of effects in both directions (substitution and complementarity) is testimony to the complexity of the relationships involved, with both generation and replacement possible and happening simultaneously. In addition, expenditures in the transportation categories are generally more income-elastic and price-elastic than those in communications, indicating that communications expenditures are more essential than those for travel. The transportation categories have both substitution and complementarity relationships with each other, while the two communications categories have a substitution relationship.

Suggested Citation

  • Sangho Choo & Taihyeong Lee & Patricia L. Mokhtarian, 2007. "Relationships Between US Consumer Expenditures on Communications and Transportation Using Almost Ideal Demand System Modeling: 1984--2002," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(5), pages 431-453, July.
  • Handle: RePEc:taf:transp:v:30:y:2007:i:5:p:431-453
    DOI: 10.1080/03081060701599920
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    References listed on IDEAS

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    1. Blanciforti, Laura Ann & Green, Richard D. & King, Gordon A., 1986. "U.S. Consumer Behavior over the Postwar Period: An Almost Ideal Demand System Analysis," Monographs, University of California, Davis, Giannini Foundation, number 11939, December.
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    2. Stavroula Malla & K. K. Klein & Taryn Presseau, 2020. "Have health claims affected demand for fats and meats in Canada?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(3), pages 271-287, September.
    3. Oliver, Atara Stephanie, 2013. "Information Technology and Transportation: Substitutes or Complements?," MPRA Paper 46548, University Library of Munich, Germany.
    4. Siwarat Kuson & Songsak Sriboonchitta & Peter Calkins, 2012. "Household determinants of poverty in Savannakhet, Laos: Binary choice model approach," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(3), pages 33-52, September.
    5. Burguillo, Mercedes & Romero-Jordán, Desiderio & Sanz-Sanz, José Félix, 2017. "The new public transport pricing in Madrid Metropolitan Area: A welfare analysis," Research in Transportation Economics, Elsevier, vol. 62(C), pages 25-36.
    6. Bris, Myriam & Pawlak, Jacek & Polak, John W., 2017. "How is ICT use linked to household transport expenditure? A cross-national macro analysis of the influence of home broadband access," Journal of Transport Geography, Elsevier, vol. 60(C), pages 231-242.
    7. Sungtaek Choi & Sangho Choo & Sujae Kim, 2020. "Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts," Sustainability, MDPI, vol. 12(8), pages 1-21, April.
    8. Bhat, Chandra R. & Castro, Marisol & Pinjari, Abdul Rawoof, 2015. "Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 59-77.

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