growth regions’, with a GDP per capita under 90% of the EU average in 2013, and which have not converged towards the EU average between 2000 and 2013.<sup>19</sup>

**We transpose these two types of lagging regions to the NUTS-3 level, to identify ‘low income’ regions and ‘low growth’ regions.** Combining the standard taxonomy from Cohesion Policy with the 2015 ‘catching up’ taxonomy, we classify ‘lagging’ NUTS-3 regions among our sample of 1,321 regions.2003-2017 (������G 2003−2017<sup>20</sup> Income level is defined by average yearly GDP per capita over the period ). Growth rate is defined by the long-run GDP per capita growth rate between the years 2003 and 2017 (������ ∆G 2003−2017).21 Regions are classified by income as: (a) ‘high-������ income’, if G GG2003−2017rr ≥90% of the sample average; (b) ‘transition’, if ������ 75% ≤G 2003−2017 < 90% of the sample average; (c) ‘less developed’, if ������GGrr 50% ≤G 2003−2017 < 75% of the sample average; and (d) ‘low-income’, if GGrr G 2003−2017 < 50% of the sample average. Regions are GGrr classified by growth performance as: (a) ‘high-growth’, if ∆G GGrr2003−2017 ≥50% of the sample average; and (b) ‘low-growth’, if ∆G 2003−2017GGrr < 50% of the sample average. rr GG **According to this classification, 16.1% of NUTS-3 regions are ‘low income’ lagging** rr GG

**According to this classification, 16.1% of NUTS-3 regions are ‘low income’ lagging regions, and 12.9% of NUTS-3 regions are ‘low growth’ lagging regions.** Table 2 reports the distribution of NUTS-3 regions according to the two-sided classification adopted. ‘Low-income’ regions represent the 16.1% of the sample, while ‘low-growth’ regions represent the 33.4% of the sample regions (including also ‘high income’ regions). Among low-growth regions, 61.2% are ‘highincome’, 18.4% are ‘transition’ regions, 17.7% are ‘less developed’, and only 2.7% are ‘low-income’. ‘Low growth’ _lagging_ regions are those in the transition, less developed, and low-income groups. Of the sample NUTS-3 regions, 12.9% are described by this category.

_Table 2: Regions’ distribution by income level and long-run growth rate._

||||Lon-Run G<br>|rowth Rate<br>|||
|---|---|---|---|---|---|---|
|Income Level|H|igh|L|ow|T|otal|
||No.|%|No.|%|No.|%|
|High-Income|480|36.34|270|20.44|750|56.78|
|Transition|113|8.55|81|6.13|194|14.69|
|Less Developed|87|6.59|78|5.90|165|12.49|
|Low-Income|200|15.14|12|0.91|212|16.05|
|Total|880|66.62|441|33.38|1,321|100.00|

Notes: Authors’ elaboration on Eurostat data. Percentages are defined on the total number of regions in the sample. High-income regions are those with an average yearly GDP per capita over the period 2003-2017 equal to or greater than the 90% of the sample average. Transition regions are those with an average yearly GDP per capita over the period 2003-2017 equal to or greater than the 75% of the sample average, but lower than the 90% of the sample average. Less developed regions are those with an average yearly GDP per capita over the period 2003-2017 equal to or greater than the 50% of the sample average, but lower than the 75% of the sample average. Low-income regions are those with an average yearly GDP per capita over the period 2003-2017 lower than the 50% of the sample average. High- (low-)growth regions are those recording a long-run growth rate of GDP per capita between the years 2003 and 2017 equal to or greater than (lower than) the 50% of the sample average.

> 19 Definition taken from “https://ec.europa.eu/regional_policy/en/policy/how/improving-investment/lagging_regions/”.

> 20 It is worth noting that Rodriguez-Pose and Ketterer (2020) have employed the official ‘catching up’ taxonomy proposed by the European Commission to analyse the relationship between institutional quality and economic growth at the NUTS-2 level.

> 21 With respect to the income level dimension, the choice of considering the average yearly GDP per capita evaluated over the period 2003-2017 rather than the 2013 figure, or that referring to the last available year of observation, is aimed at relaxing, first, potential biases due to extreme or outlying values ascribable to abnormal economic performances recorded by a region in a particular year – in the case, for example, of a natural disaster, or the closure of a large plant –, and, second, issues related to linearly interpolation of missing data. With respect to the growth dimension, the choice of considering the long-run growth rate between the years 2003 and 2017 rather than the relative convergence criterion proposed by the European Commission is aimed at capturing the absolute growth capacity of a region rather than its relative performance.

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