Investments in transport infrastructure have been identified as one of the main factors to promote growth both in urban and ex-urban economies. For instance, the increase of accessibility in the Greater London (+1,5 million of people within 45 minutes from the City and the other central business districts) due to the cross-link project has generated an increase in productivity and growth on labour participation with about 55.000 jobs supported. It has been also estimated that, between 2008 and 2018, Gross Domestic Product in Italy grew of about 7%-10% more in the provinces served by High-speed Rail (HSR) than in those not served (Cascetta, 2020). Appraisal methods in in the current practice (see for instance, EC DG-REGIO, 2014) allow for the estimation of the overall economic impacts in a given region but fail in assessing the distributional effects of transport policies, i.e. who within the region would get greater benefits than others and, eventually, who might get worst. In this paper a modelling framework is proposed to assess the distributional impacts of transport infrastructure investments. The proposed methodology assumes Gross Domestic Product per Capita (GDPC) variation as proxy of the economic growth, and combine spatial econometric techniques with traditional (4-stages) transport models. An application is presented for the case study of the Adriatic and Ionian region (including some EU Countries such as Italy, Slovenia, Croatia and Greece, and also non-EU Countries such as Bosnia-Herzegovina, Montenegro, Albania, North Macedonia, and Kosovo). The models allow to identify the key variables in predicting GDPC variation due to the changes in accessibility that would be generated by on-going infrastructure investment plans for the reconstruction of both road and railway networks in the region, outlining where the current accessibility gaps are bridged up (i.e., mainly along the foreseen extensions of the TEN-T corridors and in the major metropolitan areas), and where not. References Cascetta E. (2020) “Ten years of high-speed railways in Italy: results and perspectives”. AET Seminar on “High-speed Rail in Europe: case studies and perspectives”, Milan (Italy), January 2020. European Commission (2014) “Guide to Cost-Benefit Analysis of Investment Projects”. Directorate General for Regional and Urban policy, December 2014 https://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/cba_guide.pdf

Spatial regression analysis to assess economic impacts of transport infrastructure

Francesco De Fabiis;Alessandro Carmelo Mancuso
2022-01-01

Abstract

Investments in transport infrastructure have been identified as one of the main factors to promote growth both in urban and ex-urban economies. For instance, the increase of accessibility in the Greater London (+1,5 million of people within 45 minutes from the City and the other central business districts) due to the cross-link project has generated an increase in productivity and growth on labour participation with about 55.000 jobs supported. It has been also estimated that, between 2008 and 2018, Gross Domestic Product in Italy grew of about 7%-10% more in the provinces served by High-speed Rail (HSR) than in those not served (Cascetta, 2020). Appraisal methods in in the current practice (see for instance, EC DG-REGIO, 2014) allow for the estimation of the overall economic impacts in a given region but fail in assessing the distributional effects of transport policies, i.e. who within the region would get greater benefits than others and, eventually, who might get worst. In this paper a modelling framework is proposed to assess the distributional impacts of transport infrastructure investments. The proposed methodology assumes Gross Domestic Product per Capita (GDPC) variation as proxy of the economic growth, and combine spatial econometric techniques with traditional (4-stages) transport models. An application is presented for the case study of the Adriatic and Ionian region (including some EU Countries such as Italy, Slovenia, Croatia and Greece, and also non-EU Countries such as Bosnia-Herzegovina, Montenegro, Albania, North Macedonia, and Kosovo). The models allow to identify the key variables in predicting GDPC variation due to the changes in accessibility that would be generated by on-going infrastructure investment plans for the reconstruction of both road and railway networks in the region, outlining where the current accessibility gaps are bridged up (i.e., mainly along the foreseen extensions of the TEN-T corridors and in the major metropolitan areas), and where not. References Cascetta E. (2020) “Ten years of high-speed railways in Italy: results and perspectives”. AET Seminar on “High-speed Rail in Europe: case studies and perspectives”, Milan (Italy), January 2020. European Commission (2014) “Guide to Cost-Benefit Analysis of Investment Projects”. Directorate General for Regional and Urban policy, December 2014 https://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/cba_guide.pdf
2022
accessibility analysis, spatial regressions, Gross Domestic Product
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1230826
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