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Standardization of Regression Equation Parameters in the Case of Multiple Linear Regression for an Econometric Model Development to Determine the Price of Apartments

Author

Listed:
  • Szentesi Silviu Gabriel

    (Aurel Vlaicu University of Arad, Arad, România)

  • Pantea Mioara Florina

    (Aurel Vlaicu University of Arad, Arad, România)

  • Trifan Vanina Adoriana

    (Aurel Vlaicu University of Arad, Arad, România)

  • Mazuru Luminița Ioana

    (Aurel Vlaicu University of Arad, Arad, România)

  • Szentesi Noemi Florina Gabriela

    (Aurel Vlaicu University of Arad, Arad, România)

Abstract

This study examines the relationship between apartment prices in Romania and various influencing factors, for which we have constructed a model using multiple linear regression. This type of regression equation's parameters hold practical significance as they aid in establishing the regression equation. The form of the connection, specifically the parameters that define it, greatly influences our understanding of the connection between various quantified variables in the proposed model. By determining the regression function in this manner, we created a model that allows us to make predictions or draw conclusions based on the variables within the model. Microeconomic variables are crucial in influencing real estate price variations at the individual property level. These variables are more specific and relate to factors within the local market of Arad or the property itself. Some key microeconomic variables can influence real estate prices, which are important to ascertain using statistical tools.

Suggested Citation

  • Szentesi Silviu Gabriel & Pantea Mioara Florina & Trifan Vanina Adoriana & Mazuru Luminița Ioana & Szentesi Noemi Florina Gabriela, 2024. "Standardization of Regression Equation Parameters in the Case of Multiple Linear Regression for an Econometric Model Development to Determine the Price of Apartments," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 2344-2352.
    • Handle: RePEc:vrs:poicbe:v:18:y:2024:i:1:p:2344-2352:n:1039
    DOI: 10.2478/picbe-2024-0198
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    References listed on IDEAS

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    1. Steven C. Bourassa & Eva Cantoni & Martin Hoesli, 2010. "Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods," Journal of Real Estate Research, American Real Estate Society, vol. 32(2), pages 139-160.
    2. Deepak Murlidhar Sundrani, 2018. "Factors influencing home-purchase decision of buyers of different types of apartments in India," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 11(4), pages 609-631, May.
    3. Jeonghyeon Kim & Youngho Lee & Myeong-Hun Lee & Seong-Yun Hong, 2022. "A Comparative Study of Machine Learning and Spatial Interpolation Methods for Predicting House Prices," Sustainability, MDPI, vol. 14(15), pages 1-14, July.
    4. Lavinia Denisia Cuc & Dana Rad & Daniel Manațe & Silviu Gabriel Szentesi & Anca Dicu & Mioara Florina Pantea & Vanina Adoriana Trifan & Cosmin Silviu Raul Joldeș & Graziella Corina Bâtcă-Dumitru, 2023. "Representations of the Smart Green Concept and the Intention to Implement IoT in Romanian Real Estate Development," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    5. Khatai Aliyev & Mehin Amiraslanova & Nigar Bakirova & Narmin Eynizada, 2019. "Determinants of housing prices in Baku: empirical analyses," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 12(2), pages 281-297, February.
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    7. repec:eme:ijhma0:ijhma-08-2018-0062 is not listed on IDEAS
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