Volume 242, Issue 1

This paper investigates the effect of human capital on economic growth in OECD countries by focusing on two different channels: (1) absorption of superior technologies, and (2) augmentation of factors of production. One recent empirical study found that in isolation each channel appears insignificant, which implies that estimates that emanate by restrictive specifications that account for only a subset of these channels are likely to suffer from an omitted variable bias. Using an augmented specification (with interaction terms between the initial level of real GDP per capita and the average years of schooling), we find that OECD countries that start with a higher stock of human capital grow faster, which implies that human capital influences economic growth through the first channel only. Our results differ from previous studies (that investigated both channels), which either confirmed the simultaneous (positive or neutral) effect from both channels, or found that only the second channel had an isolated positive effect. We use a broad array of measures as proxies for human capital (six measures for educational attainment, and two measures for health status). We also account for the quality of human capital.

Based on panel error correction models for a sample of up to 21 countries, this paper analyses the macroeconomic determinants of house prices and rents. In accordance with the existing literature, I find significantly positive effects of per capita income and bank lending on house prices, whereas the housing stock per capita and interest rates have negative effects. For rents, the results are somewhat more remarkable, indicating that both the housing stock and interest rates have a negative effect. While contradicting conventional economic theory, the latter finding might be explained by real estate investors exploiting their pricing power with varying degree depending on the level of real interest rates. Moreover, the estimated impact of interest rates on both house prices and rents varies with structural housing market characteristics. For instance, while interest rates have a more pronounced effect on house prices in countries with more developed mortgage markets, the same does not hold for the effect of interest rates on rents.

An original approach to spatial economic analysis is here proposed with reference to Italy. A granularity approach is applied on microdata related to a panel of firms that have been active during 2007–2017. At each firm is therefore associated a coefficient of exposure to the economic cycle of four major foreign economies: Germany, UK, USA, and China. This information is then linked to territorial level and analyzed at two geographical scales: regional and sub-regional. The autocorrelation spatial analysis carried out lead us to appreciate geography of exposure to positive or negative shocks coming from each of the four foreign economies. This geography is very different from the administrative one and can represent a tool for planning future strategies of economic investments and territorial planning.

This paper provides first econometric evidence on the determinants of the Internet of Things among firms and on potential performance impacts. The analysis is based on representative firm-level data from 874 German firms. A probit model and an instrumental variable regression serve as econometric approach. The results reveal that especially collaboration platforms and B2B e-commerce increase the propensity to use the Internet of Things. The results further indicate that product innovation is highest for firms jointly using the Internet of Things and collaboration platforms while a reduction of the workforce is also highest in this case. In contrast, there is no evidence for a potential impact on sales development.

We study the driving forces behind COVID-19 vaccination in German counties using a cross-sectional and a panel approach. We identify several factors that have a significant impact on vaccination rates. Our results are robust to different model specifications.

This paper gives a comprehensive introduction to the IOER Monitor – an open research data infrastructure (RDI) in Germany providing domain-specific multi-temporal geospatial datasets, services and visualizations for land use and land cover (LULC)-related development of settlements and open space and closely related topics. Its easy-to-use information system provides multi-scale data offers to form a discussion platform that supports spatial development assessment and evidence-based decision making. It contributes to public land-use change discourses by enhancing information offers that can be adopted by other multi-disciplinary data users - even from non-spatial domains. All data and services are freely available. IOER Monitor is committed to offering continuous services implementing FAIR principles (findable, accessible, interoperable and re-usable) and policy-relevant inputs for transformative spatial development.