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Impact of high-speed rail on income inequalities in Italy

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  • Di Matteo, Dante
  • Cardinale, Bernardo

Abstract

This paper investigates the effects of high-speed rail (HSR) on household income inequalities in Italy at the province level. Gini index, both including and excluding rent expenses, is used as dependent variable to evaluate the effects of the policy in the timeframe 2003–2019. Two-way fixed-effects model is employed to measure the relationship, while augmented synthetic control with staggered treatment adoption, and staggered difference-in-differences explore the sensitivity of results. Main findings suggest a general reduction of inequalities among the provinces receiving HSR treatment, but the effect is not long-lasting many years over the policy outset. Heterogeneities arise depending on whether the station is basic-type or multimodal, and whether the treated province is core or intermediate. Small-sized provinces particularly benefited from the HSR introduction, showing a clear potential to pursue economic convergence objectives. Mechanisms analysis shows that HSR induced the reduction of household income inequalities by positively influencing per capita GDP and employment levels.

Suggested Citation

  • Di Matteo, Dante & Cardinale, Bernardo, 2023. "Impact of high-speed rail on income inequalities in Italy," Journal of Transport Geography, Elsevier, vol. 111(C).
    • Handle: RePEc:eee:jotrge:v:111:y:2023:i:c:s0966692323001242
    DOI: 10.1016/j.jtrangeo.2023.103652
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    as
    1. Christian Dustmann & Bernd Fitzenberger & Markus Zimmermann, 2022. "Housing Expenditure and Income Inequality," The Economic Journal, Royal Economic Society, vol. 132(645), pages 1709-1736.
    2. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
    3. Cascetta, Ennio & Cartenì, Armando & Henke, Ilaria & Pagliara, Francesca, 2020. "Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 412-428.
    4. Cavallaro, Federico & Bruzzone, Francesco & Nocera, Silvio, 2020. "Spatial and social equity implications for High-Speed Railway lines in Northern Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 327-340.
    5. Andreas Diemer & Simona Iammarino & Andrés Rodríguez-Pose & Michael Storper, 2022. "The Regional Development Trap in Europe," Economic Geography, Taylor & Francis Journals, vol. 98(5), pages 487-509, October.
    6. Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro, 2019. "Pre-event Trends in the Panel Event-Study Design," American Economic Review, American Economic Association, vol. 109(9), pages 3307-3338, September.
    7. Zhang, Fangni & Yang, Zhiwei & Jiao, Jingjuan & Liu, Wei & Wu, Wenjie, 2020. "The effects of high-speed rail development on regional equity in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 180-202.
    8. Vickerman, Roger, 2015. "High-speed rail and regional development: the case of intermediate stations," Journal of Transport Geography, Elsevier, vol. 42(C), pages 157-165.
    9. Di Matteo, Dante & Mariotti, Ilaria & Rossi, Federica, 2023. "Transport infrastructure and economic performance: An evaluation of the Milan-Bologna high-speed rail corridor," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    10. Cl'ement de Chaisemartin & Xavier D'Haultfoeuille, 2020. "Difference-in-Differences Estimators of Intertemporal Treatment Effects," Papers 2007.04267, arXiv.org, revised Nov 2023.
    11. Liu, Liwen & Zhang, Ming, 2018. "High-speed rail impacts on travel times, accessibility, and economic productivity: A benchmarking analysis in city-cluster regions of China," Journal of Transport Geography, Elsevier, vol. 73(C), pages 25-40.
    12. Begoña Guirao & Natalia Casado-Sanz & Juan Luis Campa, 2020. "Labour opportunities provided by Spanish high-speed rail (HSR) commuting services in a period of financial crisis: an approach based on regional wage disparities and housing rental prices," Regional Studies, Taylor & Francis Journals, vol. 54(4), pages 539-549, April.
    13. Yatang Lin & Yu Qin & Jing Wu & Mandi Xu, 2021. "Impact of high-speed rail on road traffic and greenhouse gas emissions," Nature Climate Change, Nature, vol. 11(11), pages 952-957, November.
    14. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    15. Chen, Zhenhua & Haynes, Kingsley E., 2015. "Impact of high speed rail on housing values: an observation from the Beijing–Shanghai line," Journal of Transport Geography, Elsevier, vol. 43(C), pages 91-100.
    16. Xiong, Jiacai & Ouyang, Caiyue & Tong, Jamie Yixing & Zhang, Feida Frank, 2021. "Fraud commitment in a smaller world: Evidence from a natural experiment," Journal of Corporate Finance, Elsevier, vol. 70(C).
    17. Shi, Wenming & Lin, Kun-Chin & McLaughlin, Heather & Qi, Guanqiu & Jin, Mengjie, 2020. "Spatial distribution of job opportunities in China: Evidence from the opening of the high-speed rail," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 138-147.
    18. Joachim R. Frick & Markus M. Grabka, 2003. "Imputed Rent and Income Inequality: A Decomposition Analysis for Great Britain, West Germany and the U.S," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 513-537, December.
    19. Gabriel M Ahlfeldt & Arne Feddersen, 2018. "From periphery to core: measuring agglomeration effects using high-speed rail," Journal of Economic Geography, Oxford University Press, vol. 18(2), pages 355-390.
    20. Liu, Xueli & Jiang, Chunxia & Wang, Feng & Yao, Shujie, 2021. "The impact of high-speed railway on urban housing prices in China: A network accessibility perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 84-99.
    21. Borsati, Mattia & Albalate, Daniel, 2020. "On the modal shift from motorway to high-speed rail: evidence from Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 145-164.
    22. Shujie Yao & Fan Zhang & Feng Wang & Jinghua Ou, 2019. "Regional economic growth and the role of high-speed rail in China," Applied Economics, Taylor & Francis Journals, vol. 51(32), pages 3465-3479, July.
    23. Chen, Zhenhua & Haynes, Kingsley E., 2017. "Impact of high-speed rail on regional economic disparity in China," Journal of Transport Geography, Elsevier, vol. 65(C), pages 80-91.
    24. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2020. "Does China’s high-speed rail development lead to regional disparities? A network perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 299-321.
    25. Li, Xiaolong & Wu, Zongfa & Zhao, Xingchen, 2020. "Economic effect and its disparity of high speed rail in China: A study of mechanism based on synthesis control method," Transport Policy, Elsevier, vol. 99(C), pages 262-274.
    26. Biancardo, Salvatore Antonio & Gesualdi, Michele & Savastano, Davide & Intignano, Mattia & Henke, Ilaria & Pagliara, Francesca, 2023. "An innovative framework for integrating Cost-Benefit Analysis (CBA) within Building Information Modeling (BIM)," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    27. Chia-Lin Chen & Roger Vickerman, 2017. "Can transport infrastructure change regions’ economic fortunes? Some evidence from Europe and China," Regional Studies, Taylor & Francis Journals, vol. 51(1), pages 144-160, January.
    28. Min Jiang & Euijune Kim, 2016. "Impact of high-speed railroad on regional income inequalities in China and Korea," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(3), pages 393-406, September.
    29. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    30. Pagliara, Francesca & Mauriello, Filomena & Garofalo, Antonio, 2017. "Exploring the interdependences between High Speed Rail systems and tourism: Some evidence from Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 300-308.
    31. Francesca Pagliara & Irina Di Ruocco, 2018. "How public participation could improve public decisions on rail investments?," Regional Science Policy & Practice, Wiley Blackwell, vol. 10(4), pages 383-403, November.
    32. Liang, Yutian & Zhou, Keyang & Li, Xun & Zhou, Zhengke & Sun, Wei & Zeng, Jiaqi, 2020. "Effectiveness of high-speed railway on regional economic growth for less developed areas," Journal of Transport Geography, Elsevier, vol. 82(C).
    33. Jiao, Jingjuan & Wang, Jiaoe & Zhang, Fangni & Jin, Fengjun & Liu, Wei, 2020. "Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China," Transport Policy, Elsevier, vol. 91(C), pages 1-15.
    34. Niu, Fangqu & Xin, Zhongling & Sun, Dongqi, 2021. "Urban land use effects of high-speed railway network in China: A spatial spillover perspective," Land Use Policy, Elsevier, vol. 105(C).
    35. Chen, Fanglin & Hao, Xinyue & Chen, Zhongfei, 2021. "Can high-speed rail improve health and alleviate health inequality? Evidence from China," Transport Policy, Elsevier, vol. 114(C), pages 266-279.
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