Photovoltaikanlagepreise und staatliche Förderungen

Ziel dieser Arbeit ist, den Zusammenhang zwischen Photovoltaikanlagepreisen (PV-Preise) und staatlicher Förderung abzufragen und diese empirisch, mittels der Paneldatenanalyse, zusammenzufassen und zu bewerten. Aufgrund der Verfügbarkeit der Daten, konzentriert sie sich ganz konkret auf den Zusammenhang zwischen Photovoltaikanlagepreisen die kleiner gleich 10 Kilowatt (kW) sind und am Strommarkt, die in sieben europäischen Staaten eingesetzt werden: Österreich, Deutschland, Italien, Frankreich, Niederlande, Dänemark und Schweden. Die Hypothese: „Anlagepreise und staatliche Förderungen stehen im positiven Zusammenhang“ wird, unter bestimmten Voraussetzungen, bestätigt.This master’s thesis provides Panel Data analysis of Photovoltaic (PV) system prices in dependence of GDP, module prices and subsides in in seven European countries (Austria, Denmark, France, Germany, Italy, Netherlands and Sweden) between 2009 and 2013. The main hypothesis of this master’s thesis assumes a positive relationship between photovoltaic system prices for system capacities less or equal to 10 kilo Watt (kW). After analyzing module and system prices of residential PV systems and the political and economic reasons behind renewable and photovoltaic electricity support, this thesis highlights the support measures most applied in Europe. Between the period 2009 to 2013, Feed in Tariff (FIT), Feed in Premium (FIP) and Tradable Green Certificates (TGC) represented the main support measures in Europe. After quantifying the main support measures in the above mentioned seven European countries through calculation of Full Load Hours (FLH) and average support data provided by Central European Energy Regulators (CEER)- the most appropriate way to conduct statistical analysis is to differentiate between two linear models. While the first model uses actual FLH data that varies over the time period, the second one uses an average estimation of FLH that doesn’t vary across the time, which means that subsidies for one country in the first case vary across time, whilst, in the second, they do not. Hausman Test results showed that both models should take time as a random effect variable, which means that individual specific differences between states do not exist. In other words, system prices do not vary a lot across countries but do across time. Statistical evaluation showed that module prices always have positive significant impact on system prices, while subsides have positive significant impact in the second model