Skip to main content
Log in

Estimating the effects of income inequality, information communication technology, and transport infrastructure on transport-oriented household expenditures

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

This study investigates the influence of transport infrastructure, income inequality, information and communication technology on transport-oriented household expenditures. For this purpose, we chose the data set period from 1997 to 2021 for the 24 OECD countries and employed the cross-sectional auto-regressive distributed lagged (CS-ARDL) approach. Therefore, the outcomes reveal that income inequality drastically upsurges transport-oriented household expenditures, especially the pre-tax income share of the 100th percentile concentration of the super-rich. Besides, there is a convex relationship between income inequality and household expenditures. The magnitudes of information and communication technology (ICT) are negative and significant, implying that ICT reduces transport-related household expenditures by allowing them to access real-time information and choose their destination as well as travel modes from the comfort of their own homes. Also, the combined effect of income inequality and ICT reduces transport-related household expenditures in the sample countries. Thus, the findings recommend some policy implications and direct future research directions based on empirical evidence.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data availability

The data set can be requested corresponding author.

References

  • Agrawal, A.W., Blumenberg, E.A., Abel, S., Pierce, G., Darrah, C.N.: Getting around when you're just getting by: the travel behavior and transportation expenditures of low-income adults. (No. MTI Report 10–2. San Jose, CA) (2011)

  • Aljoufie, M., Tiwari, A.: Exploring housing and transportation affordability in Jeddah. Hous. Policy Debate 33(3), 506–532 (2023)

    Article  Google Scholar 

  • Bailey, N., Kapetanios, G., Pesaran, M.H.: Exponent of cross-sectional dependence: estimation and inference. J. Appl. Economet. 31(6), 929–960 (2016)

    Article  Google Scholar 

  • Bai, J., Ng, S.: A panic attack on unit roots and cointegration. Econometrica 72, 1127–1177 (2004). https://doi.org/10.1111/j.1468-0262.2004.00528.x

    Article  Google Scholar 

  • Bardazzi, R., Pazienza, M.G.: Ageing and private transport fuel expenditure: do generations matter? Energy Policy 117, 396–405 (2018)

    Article  Google Scholar 

  • Beaman, L., Dillon, A.: Do household definitions matter in survey design? Results from a randomized survey experiment in Mali. J. Dev. Econ. 98, 124–135 (2012). https://doi.org/10.1016/j.jdeveco.2011.06.005.

  • Blomquist, J., & Westerlund, J.: Testing slope homogeneity in large panels with serial correlation. Econ. Lett. 121(3), 374-378 (2013)

  • Bradley, M., Vovsha, P.: A model for joint choice of daily activity pattern types of household members. Transportation (Amst) 32, 545–571 (2005). https://doi.org/10.1007/s11116-005-5761-0

  • Bris, M., Pawlak, J., Polak, J.W.: How is ICT use linked to household transport expenditure? A cross-national macro analysis of the influence of home broadband access. J. Transp. Geogr. 60, 231–242 (2017). https://doi.org/10.1016/j.jtrangeo.2017.03.012

    Article  Google Scholar 

  • Cascajo, R., Olvera, L.D., Monzon, A., Plat, D., Ray, J.B.: Impacts of the economic crisis on household transport expenditure and public transport policy: evidence from the Spanish case. Transp. Policy 65, 40–50 (2018)

    Article  Google Scholar 

  • Channels to Make Hotel Choice Decisions: A comparative study of russian federation and american tourists' online consumer behavior. (No. WP BRP 44) Higher School of Economics Research Paper, Moscow (n.d.)

  • Choo, S., Lee, T., Mokhtarian, P.L.: Do transportation and communications tend to be substitutes, complements, or neither? Transp. Res. Rec. J. Transp. Res. Board 2010, 121–132 (2005). https://doi.org/10.3141/2010-14

    Article  Google Scholar 

  • Choo, S., Lee, T., Mokhtarian, P.L.: Relationships between US consumer expenditures on communications and transportation using almost ideal demand system modeling: 1984–2002. Transp. Plan. Technol. 30(5), 431–453 (2007). https://doi.org/10.1080/03081060701599920

  • Chudik, A., Pesaran, M.H.: Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. J. Econ. 188(2), 393–420 (2015)

    Article  Google Scholar 

  • Cobham, A., Schlögl, L., Sumner, A.: Inequality and the tails: the Palma proposition and ratio. Glob. Pol. 7(1), 25–36 (2016). https://doi.org/10.1111/1758-5899.12320

    Article  Google Scholar 

  • Combes, P. P., & Lafourcade, M.: Transport costs decline and regional inequalities: evidence from France. Available at SSRN 285267 (2001)

  • Roorda, M.J., Miller, E.J. (eds.).: Cross-national analysis. In: Travel behaviour research: current foundations, future prospects. IATBR, Toronto (n.d.)

  • Deaton, A.S., Ruiz-Castillo, J., Thomas, D.: The influence of household composition on household expenditure patterns: theory and Spanish evidence. J. Polit. Econ. 97, 179–200 (1989)

    Article  Google Scholar 

  • Diaz-Olvera, L., Plat, D., Pochet, P.: Household transport expenditure in Sub- Saharan African cities: measurements and analysis. J. Transp. Geogr. 16, 1–13 (2008)

    Article  Google Scholar 

  • Dong, H.: Evaluating the impacts of transit-oriented developments (TODs) on household transportation expenditures in California. J. Transp. Geogr. 90, 102946 (2021)

    Article  Google Scholar 

  • Dumitrescu, E. I., & Hurlin, C.: Testing for Granger non-causality in heterogeneous panels. Econ. Model. 29(4), 1450–1460 (2012)

  • Eberhardt, M., & Bond, S. (2009). Cross-section dependence in nonstationary panel models: a novel estimator.

  • Gandelman, N., Serebrisky, T., Suárez-Alemán, A.: Household spending on transport in Latin America and the Caribbean: a dimension of transport affordability in the region. J. Transp. Geogr. 79, 102482 (2019)

    Article  Google Scholar 

  • Gaspar, J., Glaeser, E.: Information technology and the future of cities. J. Urban Econ. 43, 136–156 (1998). https://doi.org/10.1006/juec.1996.2031

    Article  Google Scholar 

  • Gulyi, I.M., Badetsky, A.P., Kovalev, K.E.: Methodological aspects of assessment of digital transformation of transport and logistics systems. Russ. J. Logist. Transp. Manag. 4(2), 48–56 (2019). https://doi.org/10.1016/j.jtrangeo.2022.103292

    Article  Google Scholar 

  • Hartwig, T., Nguyen, T.T.: Local infrastructure, rural households’ resilience capacity and poverty: evidence from panel data for Southeast Asia. J. Econ. Dev. 25(1), 2–21 (2023)

    Article  Google Scholar 

  • Holden, G.R.: Mr. Keynes’ consumption function and the time-preference postulate. Q. J. Econ. 52(2), 281–296 (1938). https://doi.org/10.2307/1881735

  • Hussain, Z., Khan, M.K., Shaheen, W.A.: Effect of economic development, income inequality, trasnportation, and environmental factor on TCO2 emissions. Environ. Sci. Pollut. Res. (2022a). https://doi.org/10.1007/s1356-022-19580-6

  • Hussain, Z., Khan, M.K, Zhiqing, X.: Investigating the role of green transport, environmental taxes and expenditures in mitigating the TCO2 emissions. Transp. Lett. (2022b). https://doi.org/10.1080/19427867.2022.2065592

  • Hussain, Z., Maio, C. Zhang, W., Khan, M.K.., Xia, Z.: Assessing the role of environmental expenditures and green transport on emissions released by transport: an application of ARDL approach frontiers in environmental science-environmental economics and management. 9, 769608 (2021)

  • Hussain, Z., Yousaf, M., Cui, M.: Investigating the simultaneous impacts on transport infrastructure: evidence from one-belt one-road countries. Int. J. Transp. Econ. 47(4), 401–417 (2020)

    Google Scholar 

  • Hussain, Z., Zhiqing, X., Ping, Li.: Sustainable transport efficiency and socioeconomic factors: application of non-parametric approach. Transp. Lett. (2021b). https://doi.org/10.1080/19427867.2022.2082004

    Article  Google Scholar 

  • ITU: ICT facts and figures. The world in 2015. ICT Facts and Figures. Geneva (2015)

  • Kazakov, S.P., Predvoditeleva, M.D.: How travelers use online and social media. J. Soc. Sci. 1, 220–225 (2015)

    Google Scholar 

  • Kim, S.N.: Two traditional questions on the relationships between telecommuting, job and residential location, and household travel: revisited using a path analysis. Ann. Reg. Sci. 56(2), 537–563 (2016)

    Article  Google Scholar 

  • Kowald, M., Ven Den Berg, P., Frei, A., Carrasco, J.A., Arentze, T.A., Axhausen, K.W., Mok, D., Timmermans, H.J.P., Wellman, B.: In: The spatiality of personal networks in four countries: a comparative study. 13th international conference on travel behaviour research. IATBR, Toronto (2012)

  • Leone, T., Coast, E., Randall, S.: In: Did you sleep here last night? The impact of the household definition in sample surveys: a Tanzanian case study. European population conference. Vienna, Austria (2010)

  • Liu, D., Kwan, M.P., Huang, J., Kan, Z., Song, Y., Li, X.: Analyzing income-based inequality in transit nodal accessibility. Travel Behav. Soc. 27, 57–64 (2022)

    Article  Google Scholar 

  • Martiskainen, M., Sovacool, B. K., Lacey-Barnacle, M., Hopkins, D., Jenkins, K. E., Simcock, N., ... & Bouzarovski, S.: New dimensions of vulnerability to energy and transport poverty. Joule 5(1), 3–7 (2021)

  • Mattioli, G., Nicolas, J.P., Gertz, C.: Household transport costs, economic stress and energy vulnerability. Transp. Policy (2018). https://doi.org/10.1016/j.tranpol.2017.11.002

    Article  Google Scholar 

  • Moon, H.R., Perron, B.: Testing for a unit root in panels with dynamic factors. J. Econ. 122(1), 81–126 (2004)

    Article  Google Scholar 

  • OECD: Crude oil import prices (indicator). https://doi.org/10.1787/9ee0e3ab-en (Accessed on 17 July 2022) (2022)

  • OECD: OECD meetings of national accounts experts [WWW Document]. OECD Natl. Accounts. (URL http://www.oecd.org/std/na/2682315.pdf accessed 6.17.15) (1998)

  • Ozbilen, B., Wang, K., Akar, G.: Revisiting the impacts of virtual mobility on travel behavior: an exploration of daily travel time expenditures. Transp. Res. A Policy Pract. 145, 49–62 (2021)

    Article  Google Scholar 

  • Samuelson, P.A., Nordhaus, W.D.: — 19th ed. p. cm.—(The McGraw-Hill series economics (n.d.)

  • Pawlak, J., Le Vine, S., Polak, J.W., Sivakumar, A., Kopp, J.: ICT and physical mobility: state of knowledge and future outlook. (Munich). (2015)

  • Pawlak, J., Sivakumar, A., Polak, J.: Digital behaviour and physical mobility: a (2014)

  • Pesaran, M.H.: A simple panel unit root test in the presence of cross-section dependence. J. Appl. Economet. 22(2), 265–312 (2007)

    Article  Google Scholar 

  • Pesaran, M. H., & Yamagata, T.: Testing slope homogeneity in large panels. J. Econom. 142(1), 50–93 (2008)

  • premature: Pap. Reg. Sci. 83, 229–248 (n.d.). https://doi.org/10.1007/s10110-003-0184-9

  • Preston, J., Rajé, F.: Accessibility, mobility and transport-related social exclusion. J. (2007)

  • Rao, P.K., Biswas, A., Singh, G., Abdullah, T.A., Kulshrestha, V.: Role of transportation cost in housing affordability for the urban poor in the metropolitan cities in India-a case of Lucknow. Int. J. Innov. Res. Sci. Stud. 6(3), 484–494 (2023)

    Google Scholar 

  • Rietveld, P., Vickerman, R.: Transport in regional science: the “death of distance” is (2003)

  • Schmidt, T. P.: Consumption theory. In Elgar encyclopedia of post-Keynesian economics (pp. 69–70). Edward Elgar Publishing Limited (2023)

  • Selvanathan, E.A., Selvanathan, S.: The demand for transport and communication in the United Kingdom and Australia. Transp. Res. Part B Methodol. 28, 1–9 (1994). https://doi.org/10.1016/0191-2615(94)90027-2

    Article  Google Scholar 

  • Smoreda, Z., Thomas, F.: In: Social networks and residential ICT adoption and (2001)

  • Thomopoulos, N., Givoni, M., Rietveld, P. (eds.): ICT for transport: opportunities and threats (NECTAR series on transportation and communications networks research). Edward Elgar Publishing, Cheltenham (2015)

    Google Scholar 

  • Tjostheim, I., Tussyadiah, I.P., Hoem, S.O.: Combination of information sources in travel planning a cross-national study. In: Sigala, M., Mich, L., Murphy, J. (eds.) Information and communication technologies in tourism 2007. Springer, Vienna, pp. 153–162 (2007). https://doi.org/10.1007/978-3-211-69566-1_15

  • Transp. Geogr. 15, 151–160 (n.d.) https://doi.org/10.1016/j.jtrangeo.2006.05.002

  • Ünalan, T.: Definition of household membership in international migration surveys. (2005)

  • UNHRC: The promotion, protection and enjoyment of human rights on the internet. (Hum. Rights Counc. Thirty-second Sess. Agenda item 3. Promot. Prot. all Hum. rights, civil, Polit. Econ. Soc. Cult. rights, Incl. right to Dev.) (2016)

  • United Nations: Report of the special rapporteur on the promotion and protection of the right to freedom of opinion and expression. Frank La Rue, Human Rights Council Report, New York (doi:A/HRC/17/27) (2011)

  • Use: Eurescom Summit 2001. EURESCOM, Heidelberg (n.d.)

  • Uzar, U., Eyuboglu, K.: The nexus between income inequality and CO2 emissions in Turkey. J. Clean. Prod. 227, 149–157 (2019). https://doi.org/10.1016/j.jclepro.2019.04.169

    Article  Google Scholar 

  • Valenzuela-Levi, N.: Why do more unequal countries spend more on private vehicles? Evidence and implications for the future of cities. Sustain. Cities Soc. 43, 384–394 (2018). https://doi.org/10.1016/j.scs.2018.09.003

    Article  Google Scholar 

  • Valenzuela-Levi, N.: The rich and mobility: a new look into the impacts of income inequality on household transport expenditures. Transp. Policy 100, 161–171 (2021). https://doi.org/10.1016/j.tranpol.2020.10.002

    Article  Google Scholar 

  • Volscho, T.W., Kelly, N.J.: The rise of the super-rich: Power resources, taxes, financial markets, and the dynamics of the top 1 percent, 1949 to 2008. Am. Sociol. Rev. 77(5), 679–699 (2012). https://doi.org/10.1177/0003122412458508

    Article  Google Scholar 

  • Vovsha, P., Petersen, E., Donnelly, R.: Explicit modeling of joint travel by household members: statistical evidence and applied approach. Transp. Res. Rec. J. Transp. Res. Board 1831, 1–10 (2003). https://doi.org/10.3141/1831-01

    Article  Google Scholar 

  • Wang, D., Law, F.Y.T.: Impacts of information and communication technologies (ICT) on time use and travel behavior: a structural equations analysis. Transportation (amst). 34, 513–527 (2007). https://doi.org/10.1007/s11116-007-9113-0

    Article  Google Scholar 

  • WBCSD: Mobility 2030: Meeting the Challenges to Sustainability. Geneva. (2004)

Download references

Author information

Authors and Affiliations

Authors

Contributions

Zahid Hussain developed conceptual model and critically analyzed based on empirical findings. Chunhui Huto, Jabbar Ul-haq, Huber visas and Muhammad Umair conduct the econometric techniques and analysis the findings. Also, they prepared the whole draft including suggestions.

Corresponding author

Correspondence to Zahid Hussain.

Ethics declarations

Ethical approval

Not applicable.

Consent to publish

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hussain, Z., Huo, C., Ul-Haq, J. et al. Estimating the effects of income inequality, information communication technology, and transport infrastructure on transport-oriented household expenditures. Transportation (2024). https://doi.org/10.1007/s11116-024-10486-5

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11116-024-10486-5

Keywords

JEL Classification

Navigation