Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This series presents research findings based either directly on data from the German SocioEconomic Panel study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and behavioral sciences: economics, sociology, psychology, survey methodology, econometrics and applied statistics, educational science, political science, public health, behavioral genetics, demography, geography, and sport science.
Terms of use:
Documents inThe decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly.Any opinions expressed in this series are those of the author(s) and not those of DIW Berlin.Research disseminated by DIW Berlin may include views on public policy issues, but the institute itself takes no institutional policy positions.
AbstractWe investigate the effect of the physical presence of wind turbines on residential wellbeing in Germany, using panel data from the German Socio-Economic Panel (SOEP) and a unique novel panel data set on more than 20,000 wind turbines for the time period between 2000 and 2012. Using a Geographical Information System (GIS), we calculate the proximity between households and the nearest wind turbine as the most important determinant of their disamenities, e.g. visual interference into landscape aesthetics.Our unique novel panel data set on wind turbines, which was collected at the regional level, includes their exact geographical coordinates and construction dates. This allows estimating the causal effect of the physical presence of wind turbines on residential wellbeing, using a difference-in-differences design. To ensure comparability of the treatment and control group, we apply propensity-score and novel spatial matching techniques based on exogenous weather data and geographical locations of residence, respectively.We show that the construction of a wind turbine within a treatment radius of 4,000 m...