Abstract
The paper presents the experimental attempt to apply the shift-share decomposition technique, mainly used in the economic field to analyse regional differentials, to the growth dynamics of infections during the first wave of the COVID-19 pandemic. Through a partial readjustment of the initial formulations of this technique, the regional patterns of the spread of the infections in Italy are analysed, taking into account the influence exercised by the demographic characteristics (age composition) of the region. In this reformulation, the shift-share analysis (SSA) allows to break down the daily variation of COVID-19 cases according to four effects resulting from: the distribution of the population by age groups (measured through the demographic and allocative effects), the tendency of the regional dynamics to follow the trend of the nation (measured by the national effect) and the rising of specific local dynamics (measured by the local effect). The application of our proposed reformulation studies the diffusion of infections in the Italian regions between March 9 and May 20, 2020, highlighting strengths and weaknesses of the methodology, offering ideas for further development and refinements to use SSA for applications in extra-economic realms (demographic, epidemiologic etc.), fruitfully. For example, the choice of the Italian case study was detrimental to the quality of the results obtained, since in Italy the population’s age distribution tends to be similar. For this reason, at the end of our study, it is suggested the opportunity to test the robustness of the proposed method using as case study other European nations (for example, France, Spain or Germany) characterised by more significant heterogeneity of the regional population than Italy.
Highlights
into account the influence exercised by the demographic characteristics
down the daily variation of COVID-19 cases according to four effects resulting from
the tendency of the regional dynamics to follow the trend of the nation
Summary
L’eccezionalità della malattia e della sua diffusione, insieme con la gravità delle ripercussioni ad essa connesse, hanno fatto del COVID-19 un prioritario ambito di ricerca per gli studiosi di tutte le discipline. Gli svantaggi risiedono invece nella natura deterministica dell’equazione shift-share (Patterson 1991) che si sviluppa a partire da una identità matematica con tre sole variabili (in questo caso: il numero delle infezioni accertate, la regione di riferimento e la classe di età della popolazione). L’effetto nazionale misura la variazione del numero dei non infetti che si avrebbe nel caso in cui la struttura demografica regionale e le caratteristiche regionali che favoriscono o inibiscono la diffusione del virus fossero uguali a quelle medie nazionali. L’effetto demografico indica l’influenza della struttura demografica regionale sulla diffusione del virus, ovvero quantifica la differenza nell’evoluzione del numero dei non infetti causata dalle diverse distribuzioni della popolazione in classi di età tra regioni e nazione. I dati pubblicati sono stati riportati a una serie temporale giornaliera attraverso una procedura di interpolazione matematica di tipo lineare
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