Erinevate objektide asukoha mõju Tallinna korterite hinnale 2019. ja 2020. aastal
Laen...
Kuupäev
2021
Kättesaadav alates
09.09.2021
Autorid
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Eesti Maaülikool
Abstrakt
Asukoha mõju kinnisvara väärtusele on üks küsimustest, mis huvitab pea iga kinnisvaras tegutsevat isikut. Kinnisvara väärtuse mõjutajaks võivad olla erinevad tegurid näiteks asukoht, hoone vanus, pindala, naabruskond, asustustihedus ja turvalisus, kaugus keskustest ja infrastruktuurist või müra. Antud uurimustöös on keskendutud just asukohale ning selle mõjule kinnisvara väärtuse kujunemisel.
Magistritöö eesmärgiks oli välja selgitada, kuidas mõjutavad Tallinnas asuvate korterite väärtust kaugused erinevatest objektidest ja töötada välja tehinguhindadel põhinev mudel korteriomandite turuväärtuse hindamiseks. Töös vaadeldi Tallinna linnas korteriomanditega 2019. ja 2020. aastal tehtud tehinguid (kokku 17 657). Uuringu koostamisel on peamiste programmidena kasutatud ArcMap’i, Statistica’t ja Excel’it. Analüüsiks vajalike objektide ja korterite kauguste andmete saamiseks on kasutatud ArcMap funktsiooni Near. Saadud andmete põhjal on koostatud korrelatsioon- ja regressioonanalüüs.
Korrelatsioonanalüüsi tulemusena leiti, et kõige tugevamad korrelatiivsed seosed on teguritel kaugusega Tallinna Kesklinnast ja lasteaiast. Eristades uusmüügi ja järelturu kortereid leiti, et uusmüügil on valitud teguritega tugevamad seosed kui järelturu korteritel. Regressioonanalüüsi tulemusel selgus, et Tallinna linna mudelit mõjutab peamiselt kaugus Viru väljakust ja lasteaiast. Täpsema analüüsi tulemusena selgus aga, et linnaosade lõikes ei ole kõige paremaks mudeliks Tallinna linna mudel üldiselt, kuna igal linnaosal on omad tegurid, mis mõjutavad nende ruutmeetri hindasid enim.
The effect of location on the value of real estate is one of the issues that interests almost every person operating in real estate. The value of a property can be influenced by various factors such as location, age of the building, size of the apartment, neighborhood, population density and security, distance from city centers and infrastructure, or noise. This research focuses on location and its impact on real estate value. The aim of the master's was to find out how the value of apartments in Tallinn is affected by distances from different objects and to develop a model based on transaction prices for estimating the market value of apartments. The work examined the transactions made with apartment ownership in Tallinn between 2019 and 2020 (in total 17 657 transactions). ArcMap, Statistica and Excel have been used as the main tools in compiling the study. ArcMap's near function has been used to obtain data of the distances between objects and apartments. Correlation and regression analysis has been performed on the basis of the obtained distance data. As a result of the correlation analysis, it was found that the strongest correlative relationships are factors between property and distance to city center (Viru Square in case of Tallinn) and the kindergarten. When comparing new construction and secondary market apartments, it was found that new construction apartments have stronger correlations with the selected factors than secondary market apartments. As a result of the regression analysis, it became clear that the model of the city of Tallinn is mainly influenced by the distance from Viru Square and the kindergarten. However, as a result of a more detailed analysis, it became clear that the model of the city of Tallinn in general is not the best model when looking into districts. Each district has its own factors that influence the prices per square meter the most.
The effect of location on the value of real estate is one of the issues that interests almost every person operating in real estate. The value of a property can be influenced by various factors such as location, age of the building, size of the apartment, neighborhood, population density and security, distance from city centers and infrastructure, or noise. This research focuses on location and its impact on real estate value. The aim of the master's was to find out how the value of apartments in Tallinn is affected by distances from different objects and to develop a model based on transaction prices for estimating the market value of apartments. The work examined the transactions made with apartment ownership in Tallinn between 2019 and 2020 (in total 17 657 transactions). ArcMap, Statistica and Excel have been used as the main tools in compiling the study. ArcMap's near function has been used to obtain data of the distances between objects and apartments. Correlation and regression analysis has been performed on the basis of the obtained distance data. As a result of the correlation analysis, it was found that the strongest correlative relationships are factors between property and distance to city center (Viru Square in case of Tallinn) and the kindergarten. When comparing new construction and secondary market apartments, it was found that new construction apartments have stronger correlations with the selected factors than secondary market apartments. As a result of the regression analysis, it became clear that the model of the city of Tallinn is mainly influenced by the distance from Viru Square and the kindergarten. However, as a result of a more detailed analysis, it became clear that the model of the city of Tallinn in general is not the best model when looking into districts. Each district has its own factors that influence the prices per square meter the most.
Kirjeldus
Magistritöö
Geodeesia, kinnisvara- ja maakorralduse õppekaval
Märksõnad
magistritööd, asukoha mõju, ruumilised tegurid, regressioonanalüüs, korrelatsioonanalüüs