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Global warming is mainly caused by greenhouse gas emissions. The building sector is responsible for a significant share of energy use and greenhouse gas emissions. Most of the existing buildings in Europe were built before 2001 and the vast majority will remain in place after 2050 when EU aims to achieve climate neutrality. Thus, renovation of the European building stock is needed to reduce operat
Within the literature on innovation systems, there are a growing number of scholars emphasizing the importance of differentiated knowledge bases underlying innovation activities. The existing work on knowledge bases is largely grounded on in-depth case studies; while surprisingly little effort has been done so far to operationalize the concept in a more systematic manner. In this article, an attem
Globalization is a widespread phenomenon that is having a strong influence on the modern society, creating both threats and opportunities. One of the most affected areas by the global pressures is the labor market, which requires specific policies and tools to respond to the increasing challenges. It is thus the task of the modern welfare states, to intervene in the attempt of transforming the glo
Soil and water acidification was internationally recognised as a severe environmental problem in the late 1960s. The interest in establishing “critical loads” led to a peak in weathering research in the 1980s and 1990s, since base cation weathering is the long-term counterbalance to acidification pressure. Assessments of weathering rates and associated uncertainties have recently become an area of
Reshoring, which refers to the relocation of previously offshored activities back to the home country, is a topic of growing interest in the literature. Two primary motivations for reshoring have been identified: the adoption of automation technology by firms and rising wages in offshoring destinations. In this study, wepropose a novel method for identifying and quantifying reshoring using micro-d
The purpose of this thesis is to investigate whether factor augmented vectorautoregression (FAVAR) models estimated using principal component analysis are able to improve monthly inflation rate forecasts for Sweden. We produce 42 forecasts for the period January 2012 to June 2015 and evaluate the forecasts by their root mean square errors as well as their ability to correctly predict the sign of t
