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Measuring and Exploring Regional Trade Resilience in Italy During Different Crises

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Abstract

Trade growth and resilience show variations within the regions of a country during different recessionary periods. Similarly, the main determinants of trade capacity also register spatial differences. We use novel panel-time series data covering almost three decades and combine resilience indexes and heterogeneous coefficient models to study trade performance and resilience across the Italian regions. We find heterogeneous impact of different crises on trade and crisis-specific effects, together with sector-specific differences. We provide explanations for such differences based on the role of the EU cohesion policy, trade linkages and specialization. Policy implications are finally discussed.

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Notes

  1. Since the Great Recession, the effects of shocks on regional economies have been studied by refreshing the decades-old resilience framework (Martin 2012). For a recent survey on this literature, see Pontarollo and Serpieri (2021); for an overview on the determinants of regional resilience, see Di Caro and Fratesi (2018).

  2. In line with previous regional resilience literature (Martin 2012), we use the growth of the focus variable (i.e. regional export) to conduct the empirical analysis and resilience indexes to describe the relative impact of a given shock during recessionary events. For a more detailed discussion on the usage of resilience variables, see Cellini et al. (2017).

  3. We have controlled our results for the usage of alternative measures of trade resilience, available upon request, including trade openness indicators and variables in real values, with no significant differences.

  4. To check the sensitivity of our shock identification procedure, we have also used year effects covering each crisis one at time; results available upon request.

  5. We have also calculated the sensitivity indexes with respect to the European benchmark, as in Di Caro and Fratesi (2022a); results are reported in the Appendix to save space.

  6. We calculate sectoral specialisation of regional activities as follows: \({SI}_{ijt }= \frac{{x}_{ijt}}{{x}_{iJt}}\), where \({x}_{ijt}\) is the share of export related to sector i (NACE Rev. 2), in the region j at time t; and, \({x}_{iJt}\) is the proportion of export related to sector i (NACE Rev. 2), in the reference area J and for year t.

  7. High-tech economic activities are classified according the Eurostat definition based on NACE Rev.2 classification as follows: manufacture of basic pharmaceutical products and pharmaceutical preparations (21); manufacture of computer, electronic and optical products (26); manufacture of air and spacecraft and related machinery (30.3).

  8. We thank the authors for giving us the possibility of using their data.

  9. In the main estimates, we do not include time fixed effects since we detect a limited number of significant group-specific trends at 5% level. Results with time trends are available upon request.

  10. The preference for the MG model against alternative models is supported by Hausman-type tests (Ditzen 2018).

  11. We excluded from the analysis data on (i) Campania export of manufacture of air and spacecraft and related machinery and (ii) Lazio export of Manufacture of basic pharmaceutical products and pharmaceutical preparations, since they were outlier.

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Arbolino, R., Boffardi, R. & Di Caro, P. Measuring and Exploring Regional Trade Resilience in Italy During Different Crises. Ital Econ J 9, 1027–1047 (2023). https://doi.org/10.1007/s40797-023-00250-6

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