Thesis from the year 2023 in the subject Economy – Real estate industry, grade: 1.0, , language: English, abstract: House prices are some of the few financial goods that are modelled only to a limited extent in microeconomic systems, despite the heterogeneity of real estate. Usually, no distinction is made between the type of property. This paper addresses this gap by examining property prices of privately-owned apartments in the 17th district of Vienna. First, price indices are created from land register sales data using various models to determine the current price level. Factors influencing real estate prices are identified and Machine Learning models are used to forecast the price development in the area of interest. Finally, the broader implications at the micro- and macroeconomic scale are discussed.
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