An examination of the real estate price development in the 17th district of Vienna

Modelling and forecasting property prices


Thesis, 2023

57 Pages, Grade: 1.0


Abstract or Introduction

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.

Details

Title
An examination of the real estate price development in the 17th district of Vienna
Subtitle
Modelling and forecasting property prices
Grade
1.0
Author
Year
2023
Pages
57
Catalog Number
V1460000
ISBN (eBook)
9783389003824
ISBN (Book)
9783389003831
Language
English
Notes
Die Arbeit wurde mit dem 'WU OeNB Research Talent Award 2023' ausgezeichnet.
Keywords
Immobilienpreisprognose, Maschinelles Lernen, Zeitreihenanalyse, Hedonische Modelle
Quote paper
Yan S. Matschi (Author), 2023, An examination of the real estate price development in the 17th district of Vienna, Munich, GRIN Verlag, https://www.grin.com/document/1460000

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