Davide Fiaschi (p), Angela Parenti, Cristiano Ricci

Barbara Martini

In this paper we investigate the evolution over time and space of economic activity by the use of nightlights, taking as empirical reference the dynamics of the income of Italian municipalities over the period 2008-2019.
We first show that in each year nightlights are strongly related to income and population at municipal level, which justifies the use of nightlights as an index of income/economic activity. However, we discuss the limits of this approach showing how the rate of transformation of nightlights in municipal income is decreasing in the level of income.
We then discuss that the level of aggregation used in the analysis is crucial for detecting the potential nonlinearity in the growth path of regional income. In particular, the growth path estimated using a very detailed grid (cells of 500m x 500m) appears strongly nonlinear and points to a twin-peaked distribution of nightlights, while the use of a more aggregate grid (cells of 6km x 6km) points to absolute convergence.
Finally, we propose a theoretical spatial model reflecting the evolution over time and space of income sufficiently flexible to incorporate competitive and/or complementary theories based on increasing returns, local amenities, and local diffusion of factors as key determinants of the level of economic activity. The estimate of the model on the base of observed Italian nightlights reveals that all three types of determinants contribute to spatial distribution dynamics of Italian income.

Uwe Radtke (p)

Davide Fiaschi

K-Means is a well known approach for clustering data. The data was provided by the district heating company of Kaposvar. The used data consists of 365 devices, measured hourly for 365 days. With a set of 3.3 million measures the analysis can't be performed on a simple PC any more. But the research did prove - similar results can be achieved using randomized samples of 10.000 sets of data. As only two dimensions were available for public use - the result still will reveal 4 clusters in a 2 dimensional space. Large demand with least operating hours is something probably no district heating company wants. Of course - the method used to analyse the data contained standards like removing unmeasured sets, check if the data is skewed and transforming data.

Fabio Tejedor (p), Eveli van Leeuwen

Uwe Radtke

Multiple alternatives to GDP has been proposed to measure social welfare, yet surprisingly little is known about how these approaches can be used on the urban scale. Thus broader welfare hints at the concept of quality of life and well-being while going beyond the merely economic production and living standards. This work uses the term welfare in relation to the ability to meet present societal needs without compromising future generations to meet their own needs. This paper aims to create a synthetic theoretical overview of the relevance of these alternatives in an urban context. For this purpose, a literature review about conceptual and non-conceptual approaches to measure well-being has been carried out. The methodology includes analyzing peer-reviewed, special reports published by working groups at the UN, OECD, EUROSTAT and other official reports aligned to producing welfare and well-being indicators to have a representative sample. Overall, this work aims to contribute towards the comprehensive understanding of broader welfare in cities while summarizing the main strategies to measure it.

Barbara Martini (p)

Fabio Tejedor

Evolutionary Economic Geography (EEG). EEG aimed to understand why industries concentrate in the space, how networks evolve, and why some regions grow more than others using three key concepts: proximities, capabilities and routines, and industries relatedness. This literature does not consider gender even though gender can play an important role. Gender differences in social behaviour can impact knowledge's proximities and diffusion, especially when females and males are not equally distributed between industries and firms. Industries relatedness and knowledge spills-over are captured through the Related and Unrelated Variety. The Variety index will be decomposed into Related and Unrelated Variety using a three-stage decomposition to consider gender. The properties of these measures will be investigated using a theoretical approach. The results highlight that RV and UV measures have different behaviour when females' (males) employment increases.Furthermore, RV and UV will depend on the females' (males) share in the industry, and they exhibit increasing returns to scale when females' share in an industry is lower than the males' share. This finding has significant consequences in terms of policies. Increasing females' participation in the labour market is essential, but it is also crucial in which industries females will be employed. Increasing females in industries in which the females' share is already high are less effective for labour growth than increasing females' share in industries in which the females' share is low.