Economic resilience and regionally differentiated cycles: Evidence from a turning point approach in Italy

The literature on regional resilience often neglects the timing of recessions and simply uses national cycles. Region-specific cycles and turning points might bias the results, however, and affect the choice of regions to target with policies. This paper investigates the geography and determinants of regional resilience with a regional turning point approach, using data for Italy, a country with a well-known and sizeable regional divide. The results show that the timing of regional cycles varies substantially and that the detected resilience determinants are different across the two approaches, implying that the policy levers may be wrongly estimated with national turning points. La bibliografía sobre la resiliencia regional suele pasar por alto el momento de las recesiones y se limita a utilizar los ciclos nacionales. Sin embargo, los ciclos y los puntos de inflexión específicos de las regiones podrían sesgar los resultados y afectar a la elección de las regiones a las que dirigir las políticas. Este artículo investiga la geografía y los determinantes de la resiliencia regional con un enfoque de punto de inflexión regional, para lo cuál emplea datos de Italia, un país con una división regional bien conocida y considerable. Los resultados muestran que el momento de los ciclos regionales varía sustancialmente y que los determinantes de la resiliencia detectados se pueden distinguir en los dos enfoques, lo que implica que las palancas políticas pueden estimarse erróneamente si se emplean puntos de inflexión nacionales. 地域のレジリエンスに関する研究は、経済不況のタイミングを無視し、単純に国の景気サイクルを使用していることが多い。ただし、地域特有のサイクルや転換点が偏った結果を生み、対象とする地域の選択に影響を与える可能性があります。この論文では、大きな地域格差があることでよく知られているイタリアのデータを使用し、地域の転換点に対するアプローチを用いて地域の回復力の地理と決定要因を調査した。この結果は、地域のサイクルのタイミングが大幅に異なり、検出された回復力の決定要因が2つのアプローチで区別されることを示しており、国の転換点により政策レバーが誤って推定される可能性があることを示唆している。 Resilience is one of the most desirable phenomena in engineering, environmental studies, and social sciences, including economics and regional science. From an engineering standpoint, resilience refers to the resistance of an economic unit to unanticipated negative movements and the ability to achieve the pre-shock situation. The ecological perspective defines resilience rather as the long-term ability to stand robustly against the shocks and to absorb them adequately while not moving to a new equilibrium. Alternatively, an evolutionary or adaptive approach conceives of resilience as the capacity of the systems to reorient, reconfigure, and transform their structure to reach a superior and sustainable long-run equilibrium path (Boschma, 2015; Di Caro, 2017; Di Caro & Fratesi, 2018; Faggian et al., 2018; Fingleton et al., 2012; Folke et al., 2004; Giannakis & Bruggeman, 2015, 2017; Han & Goetz, 2015; Martin, 2012; Martin & Gardiner, 2019; Martin & Sunley, 2015; Modica & Reggiani, 2015; Pike et al., 2010; Simmie & Martin, 2010). These definitions introduce three components of resilience: first, resistance of economies to shocks; second, speed of recovery from recessions; and, third, adaptability of economies by reorienting their economic and industrial structure to maintain a new long-run growth path (Bristow & Healy, 2018; Di Caro, 2017; Faggian et al., 2018; Fingleton et al., 2012; Folke, 2006; Folke et al., 2004; Foster, 2007; Fratesi & Perucca, 2018; Giannakis & Bruggeman, 2015, 2017; Han & Goetz, 2015; Hill et al., 2008, 2011; Martin, 2012; Pike et al., 2010). The analyses of regional resilience may be biased, however, because almost all the literature so far analyses the different behaviours of regions by assuming that the regions are affected by the same shocks and follow the same national economic cycles, which implies that resilience is measured using the statistical national peaks (Faggian et al., 2018; Giannakis & Bruggeman, 2015, 2017; Martin, 2012; Sedita et al., 2017). The purpose of this study is to address an important shortcoming of the literature. Regions may have different cycles, and the fact that they belong to the same country and share the same currency and macroeconomic policy is not a sufficient condition for full cycle synchronization, as the literature on the syncing of national cycles following the start of the Euro shows (Camacho et al., 2006). In the academic literature, the timing of the crisis for regions is, however, mostly defined on the basis of the national business cycle. The possibility of significant region-specific cycles and differential turning points is largely ignored, because these are difficult to detect with annual data, which is what is normally available at the regional level. However, failing to relax the assumption of synced regional cycles might seriously bias the results, as many regions might exhibit quite different timings from the national cycle. Indeed, a stream of scholars has explored large asymmetries across business cycles. Focusing mostly on the Eurozone, they have detected relatively heterogeneous business cycles (Montoya & De Haan, 2008). This paper is intended to show the importance of pursuing resilience analyses on the basis of turning points specific to regions, but not to the national turning points, which may often be biased. The paper seeks to show explicitly the extent of the bias that occurs under national turning points and to show that this bias has important policy implications: (i) using national turning points might lead to the selection of some regions as being most affected by a crisis while others might be in a more severe recession; and (ii) using national instead of regional turning points can lead to wrongly estimating the determinants of regional resilience, resulting in the choice of less effective regional policy levers. To the best of our knowledge, the implications of this shortcoming have never been addressed in the literature, and only a few papers have provided evidence of it. Indeed, only a small number of papers have focused on regional turning points, most of which focus on concordance, diffusion, and synchronization of the regional cycles with each other and with the national business cycle. Owyang et al. (2005), Hall and McDermott (2004), Duran (2014), and Magrini et al. (2013) represent some examples of this stream of scholars who analyse states in the US (except Hall & McDermott, 2004, who focus on regions in New Zealand). Only Sensier et al. (2016) have conducted an analysis for Europe, finding that regional cycles in Europe are inhomogeneous, although their analysis is constrained by annual data and does not look to region-specific determinants, nor specific policy implications. Some of this stream also study the underlying economic or spatial determinants of the bilateral synchronization of fluctuations (Magrini et al., 2013). With to the structure of the an of the In the and region-specific turning points are estimated using an of and The in regional and national turning points are in In the extent of the asymmetries and across regional business cycles are with the of bilateral cycle diffusion, and In regional resilience are using national and regional turning points. The results are with To these some statistical evidence of is investigates the economic and determinants of regional resilience using and they are to under different turning points. the study by the of the for the choice of the regions to be and the levers that be for policies. 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