Anna Temel (p)

Vicente Royuela

Being a popular city for both enterprises and individuals, certain areas in Berlin are subject to severe revaluation and displacement pressure. To prevent these structural changes and to maintain the social composition of the residents in these areas, as one of the first big cities in Germany, Berlin started to designate social conservation areas in 1991. Consequently, the district council must approve certain changes to buildings or ownership structures in these zones. The number of designated areas has been gradually increasing and currently amounts to 72 zones in 2022. Although this instrument has been effective for more than three decades, there is only some evidence from small-scale studies on behalf of district councils that suggest a stabilizing effect of social conservation areas on the social composition and the rent level within these zones.
This paper analyzes the effects of the designation of social conversation areas on the population and the housing market within and outside of these zones. For this, georeferenced data on real estate offers for rental and sales objects from the internet platform Immobilienscout24 as well as demographic characteristics on the km²-grid level, such as the unemployment rate, age structure and mean purchasing power per grid are used. Utilizing the exact locations of the areal borders, a regression discontinuity design is applied to estimate the local average treatment effect of newly designated social conservation areas on households and the real estate market within and outside of these zones. The effect is estimated in terms of the mean real estate rental and sales prices, mean purchasing power and other demographic characteristics of the neighbourhood, as well as their changes over time. Additionally, potential spillover effects on neighbourhoods close to designated social conservation areas are explored. Estimated effects could be expected to confirm the stabilizing effect of the instrument. However, there might arise unforeseen sorting and spillover effects on neighboring areas or diverging dynamics induced by the designations, such as an increase in purchasing power in the broader area but a stable or decreasing development within the social conservation area. This paper may yield important insights into the effects of the employable and non-employable population.

Dora Szendi (p)

Anna Temel

In the global economy, rapidly changing conditions (globalization, industry 4.0, artificial intelligence or the current pandemic situation) are setting new challenges for cities. The cities are the most important hubs of economic activity around the world (concentration of population, enterprises, trade, stock exchanges). These challenges require new and innovative solutions from cities, to which smart cities can give adequate answers. The cities are not only concentrating the economic activity but are responsible for a huge part of environmental issues (energy consumption, greenhouse gas emissions). That is why besides the economic growth approach also sustainability is more and more current in the smart city definitions. The research aims to examine the connection of smart cities’ economic and environmental pillars in the example of the European capitals. The results show, that also among the capitals there are some differences in this case as different solutions have emerged in the main geographical areas of Europe, both in terms economic component and in terms of taking into account sustainability aspects. Cities in Northern and Western Europe are the best performing in both cases, although, it is worth noting that among medium-sized cities the connection of the overall position and the role of economic component is not strong as e.g. by the environmental or people pillars.

Dimitrios Kallioras (p), Spyros Niavis, George Petrakos, Maria Adamakou

Dora Szendi

The paper discusses whether – and to what extent – sub-national population change responds positively or negatively to agglomeration dynamics (i.e. population density), in ways that reinforce or, instead, equalize population concentrations across space. Examining processes of concentration and de-concentration of population goes beyond the demographic interest per se, as it may, also, shed light on questions concerning economic convergence and divergence in the more general sense of understanding wider economic processes. To this end, the paper presents evidence from China. Under the conditions of the rapid market liberalization process that China has been experiencing, questions of spatial cohesion – and thus of convergence and divergence – even though are still, rather, neglected, become increasingly salient. This is so as the elimination of spatial imbalances is both a pre-condition and a core objective of the reforms aiming at market liberalization. Scholars both in the urban economics and the growth economics tradition have well-recognized that studying population growth offers a window through which to study the process of economic growth as the latter is systematically related to population growth through the trade-off between agglomeration economies and urban (i.e. commuting, housing, land use, environmental, inter alia) costs. This is especially so in China given that productivity levels, capital deepening and levels of technology are still low, and thus economic growth is still very much of the extensive (i.e. increase in inputs, including labor) than the intensive form (i.e. increase in the productivity of each input and in total factor productivity). Moreover, given that China is still at low levels of economic development, spatial productivity differentials are predominantly along the lines of urban-rural (i.e. core–periphery) dichotomy, and thus very much related to patterns of population agglomeration (i.e. urbanization). In these conditions, measures of spatial disparity in population concentration act as a lower bound indicator of spatial disparities in terms of economic development, and this may be of acute analytical and policy interest. If patterns of population growth are found to be cumulative across space, this could be taken as a signal of a wider spatial disequilibrium, representing spatial inequalities in economic opportunities more generally. This may, ultimately, raise concerns as regards the success of the market liberalization process in itself (given the corresponding EU benchmark).

Castells-Quintana, Carlos Gardín, Vicente Royuela (p)

Dimitrios Kallioras

In the last years, there has been an increased interest in the role of inequality in develop-ment, especially as inequality has been on the rise within many countries worldwide. In this paper, we reassess the inequality-development relationship paying special attention at i) different measures of development, ii) different dimensions of income inequality, iii) exploring the mediator factor of urbanisation, and iv) exploring the potential mechanism for inequality to have an impact on devel-opment. To do so, we i) rely on a large global panel of countries over the last decades including in-formation on economic, social, human and sustainable development, as well as information on the distribution of income within countries, benefiting from recent and detailed data produced by WIID (UNU-WIDER), and ii) complementing our analysis looking at different measures of urbanisation.
We relate to previous studies analysing the complexity of the relationship between inequali-ty and development. First, we relate to papers studying the impact of inequality on economic devel-opment (Alesina and Rodrik, 1994; Persson and Tabellini, 1994; Partridge, 1997; Barro, 2000; Forbes (2000); Chen, 2003; Easterly, 2007; Herzer and Vollmer, 2012; Oechslin and Zweimüller, 2014; Os-try et al., 2014; among others). Second, we relate to recent studies pointing to the need to consider the impact of inequality on different dimensions of development beyond income (including Easterly, 2007; Pickett and Wilkinson, 2015; Chetty et al., 2016; Castells-Quintana et al. 2019). Finally, we also relate to papers exploring the different transmission channels for inequality to have an impact on development, and how this impact may therefore depend on the type of inequality (see for in-stance, World Bank, 2005; Easterly, 2007; Marrero and Rodriguez, 2013; and Castells-Quintana and Royuela, 2017). An overall reading from all this literature is that the inequality-development is complex, and that the impact of inequality is likely to be different depending on different aspects of the distribution of income. Our paper aims to connect these different strands in the literature and contribute to it by exploring in depth i) different dimensions of development, ii) the impact of com-plementary measures of inequality, capturing diverse aspects of the distribution of income, iii) the role of agglomeration economies, and iii) different mechanisms in the inequality-development rela-tionship.