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Socio-economic effects of an earthquake:does sub-regional counterfactual sampling matter in estimates? An empirical test on the 2012 Emilia-Romagna earthquake

Author

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  • Margherita Russo
  • Francesco Pagliacci

Abstract

Estimates of macroeconomic effects of natural disaster have a long tradition in economic literature (Albala-Bertrand, 1993a; 1993b; Tol and Leek, 1999; Chang and Okuyama, 2004; Benson and Clay, 2004; Strömberg, 2007; UNISDR, 2009; Cuaresma, 2009; Cavallo and Noy, 2009; Cavallo et al., 2010; The United Nations and The World Bank, 2010). After the seminal contribution of Abadie et al. (2010) in identifying synthetic control groups, with DuPont and Noy (2015) a new strand has been opened in estimating long term effects of natural disaster at a sub-regional scale, at which the Japan case provides plenty of significant economic variables. Although the same methodology has been applied in estimating the impact of earthquakes in Italy (Barone et al. 2013; Barone and Mocetti, 2014), the analysis has been limited to the regional scale. In our paper, due to a lack in long-term time series data at municipality level, this paper cannot adopt the methodology suggested by Abadie et al. (2010). Nevertheless, it provides a test bed for assessing the relevance of a sub-regional counterfactual evaluation of a natural disaster's impact. By taking the 2012 Emilia-Romagna earthquake as a case study, we propose a comprehensive framework to answer some critical questions arising in such analysis. Firstly, we address the problem of identifying the proper boundaries of the area affected by an earthquake. Secondly, through a cluster analysis we show the importance of intra area differences in terms of their socio-economic features. Thirdly, counterfactual analysis is assessed by adopting a pre- and post-earthquake difference-in-difference comparison of average data in clusters within and outside the affected area. Moreover, three frames to apply propensity score matching at municipality level are also adopted, by taking the control group of municipalities (outside the affected area): (a) within the same cluster, (b) within the same region, (c) in the whole country. The four variables considered in the counterfactual analysis are: total population; foreigner population; total employment in manufacturing local units; employment in small and medium-sized manufacturing local units (0 to 49 employees). All the counterfactual tests largely show a similar result: socio-economic effects are heterogeneous across the affected area, where some clusters of municipalities perform better, in terms of increase of population and employment after the earthquake, against some others. This result sharply contrasts with the average results we observe by comparing the whole affected area with the non-affected one or with the entire region.

Suggested Citation

  • Margherita Russo & Francesco Pagliacci, 2016. "Socio-economic effects of an earthquake:does sub-regional counterfactual sampling matter in estimates? An empirical test on the 2012 Emilia-Romagna earthquake," Center for the Analysis of Public Policies (CAPP) 0139, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Handle: RePEc:mod:cappmo:0139
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    References listed on IDEAS

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    1. Marco Ranuzzini & Francesco Pagliacci & Margherita Russo, 2015. "L'informatizzazione delle procedure per la ricostruzione: prime evidenze dai contributi concessi per le abitazioni," Center for the Analysis of Public Policies (CAPP) 0127, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. David Strömberg, 2007. "Natural Disasters, Economic Development, and Humanitarian Aid," Journal of Economic Perspectives, American Economic Association, vol. 21(3), pages 199-222, Summer.
    3. Vittorio Piazzi & Francesco Pagliacci & Margherita Russo, 2015. "Analisi cluster delle caratteristiche socio-economiche dei comuni dell'Emilia-Romagna: un confronto tra comuni dentro e fuori dal cratere del sisma," Center for the Analysis of Public Policies (CAPP) 0120, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    4. Barone, Guglielmo & Mocetti, Sauro, 2014. "Natural disasters, growth and institutions: A tale of two earthquakes," Journal of Urban Economics, Elsevier, vol. 84(C), pages 52-66.
    5. Eduardo Cavallo & Ilan Noy, 2009. "The Economics of Natural Disasters: A Survey," Research Department Publications 4649, Inter-American Development Bank, Research Department.
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    Cited by:

    1. Cerqua, A. & Ferrante, C. & Letta, M., 2021. "Electoral Earthquake: Natural Disasters and the Geography of Discontent," GLO Discussion Paper Series 790, Global Labor Organization (GLO).

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    More about this item

    Keywords

    cluster analysis; counterfactual analysis; Emilia-Romagna; earthquake;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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