Many indicators/indices related to real estate markets are either based on list prices or selling prices whereas the latter is usually related to private data. Therefore, the relationship between these two data sets could hardly be investigated. The research in this Ph.D. work aims to enlarge the existing body of knowledge in this area.The data set in an initial part of the study comprises 1,274 transactions of owner-occupied residential properties in rural areas of Rhineland-Palatinate (Germany). The list prices are obtained from ImmoScout24, the largest German real estate brokerage website. The selling prices are acquired from official (yet private) appraisal sources that collect every real estate contract of sale in Germany. It is found that, on average, selling prices are -15.2% (-20,605 Ä) lower than the stated list prices. Moreover, 10% of the sellers had been forced to reduce the list price by more than -33.3% (-47,750 Ä) until a transaction was realized. This indicates that many sellers overestimate the value of their own property, especially in an illiquid real estate market. Several other studies from the USA or Canada came to similar conclusions. In contrast to these studies, this work found that the difference between list price and selling price is not related to common demographic, economic or location characteristics. The owner accuracy regression only indicates a strong influence of the absolute amount of the list price and the age of the dwelling structure. Besides, it is shown that list prices as such are not a perfectly reliable data source. Firstly, it is difficult to match list price and selling price of one single property because often several list prices exist for one single property. Secondly, the time-on-market and changes of the list prices are unknown, yet important to determine the selling price. The same issues applied to many house characteristics like age of the dwelling structure or quality and quantity of building appliances. In a next step, the outlined data problems will be handled with support by the data provider. Furthermore, the regression analyses (with a new sample) will be augmented by other statistical methods. Further, the set of involved variables will be extended, e.g. by owner characteristics that shall be found in surveys of ImmoScout users. The study, as the research progresses, will analyze transactions of owner-occupied residential properties in rural, urbanized and metropolitan areas. Additionally, the study contributes to the price and worth theory and to the valuation practice of residential properties. Furthermore, new scientific insights into the research field ìlist pricesî are expected.