Standard

Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods. / Komotskiy, E.; Fadichev, B.; Detkov, A.
In: AIP Conference Proceedings, Vol. 2849, No. 1, 090017, 2023.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Komotskiy, E, Fadichev, B & Detkov, A 2023, 'Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods', AIP Conference Proceedings, vol. 2849, no. 1, 090017. https://doi.org/10.1063/5.0164546

APA

Komotskiy, E., Fadichev, B., & Detkov, A. (2023). Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods. AIP Conference Proceedings, 2849(1), [090017]. https://doi.org/10.1063/5.0164546

Vancouver

Komotskiy E, Fadichev B, Detkov A. Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods. AIP Conference Proceedings. 2023;2849(1):090017. doi: 10.1063/5.0164546

Author

Komotskiy, E. ; Fadichev, B. ; Detkov, A. / Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods. In: AIP Conference Proceedings. 2023 ; Vol. 2849, No. 1.

BibTeX

@article{033d64cb33e343cf9fc13b0f3d5259f1,
title = "Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods",
abstract = "The article analyzes data on new construction projects throughout Russia for the period 2017-2019 in order to answer the question of what effect the introduction of escrow accounts had on the building industry in terms of changes in the construction time of comparable facilities. This change from an economic point of view is due to the fact that construction companies have to actively use credit money, and thus there is a motivation to complete the project as soon as possible in order to avoid additional costs for loans. To answer this question, methods of evidence-based policy are used, in particular, matching based on machine learning algorithms and methods of collecting and analyzing data from websites. The data set obtained in the course of work is unique in terms of analysis of the construction industry in Russia. {\textcopyright} 2023 American Institute of Physics Inc.. All rights reserved.",
author = "E. Komotskiy and B. Fadichev and A. Detkov",
note = "We would like to thank the following participants of the Ural Project Change 2020 and the Sirius competition for their invaluable treasure in collecting data for this study: Leonid Zemtsov, Danil Tolstov, Yaroslav Ilyin, Nikita Nekrasov.",
year = "2023",
doi = "10.1063/5.0164546",
language = "English",
volume = "2849",
journal = "AIP Conference Proceedings",
issn = "0094-243X",
publisher = "American Institute of Physics Publising LLC",
number = "1",

}

RIS

TY - JOUR

T1 - Analysis of the effects of escrow accounts in Russia using evidence-based policy and machine learning methods

AU - Komotskiy, E.

AU - Fadichev, B.

AU - Detkov, A.

N1 - We would like to thank the following participants of the Ural Project Change 2020 and the Sirius competition for their invaluable treasure in collecting data for this study: Leonid Zemtsov, Danil Tolstov, Yaroslav Ilyin, Nikita Nekrasov.

PY - 2023

Y1 - 2023

N2 - The article analyzes data on new construction projects throughout Russia for the period 2017-2019 in order to answer the question of what effect the introduction of escrow accounts had on the building industry in terms of changes in the construction time of comparable facilities. This change from an economic point of view is due to the fact that construction companies have to actively use credit money, and thus there is a motivation to complete the project as soon as possible in order to avoid additional costs for loans. To answer this question, methods of evidence-based policy are used, in particular, matching based on machine learning algorithms and methods of collecting and analyzing data from websites. The data set obtained in the course of work is unique in terms of analysis of the construction industry in Russia. © 2023 American Institute of Physics Inc.. All rights reserved.

AB - The article analyzes data on new construction projects throughout Russia for the period 2017-2019 in order to answer the question of what effect the introduction of escrow accounts had on the building industry in terms of changes in the construction time of comparable facilities. This change from an economic point of view is due to the fact that construction companies have to actively use credit money, and thus there is a motivation to complete the project as soon as possible in order to avoid additional costs for loans. To answer this question, methods of evidence-based policy are used, in particular, matching based on machine learning algorithms and methods of collecting and analyzing data from websites. The data set obtained in the course of work is unique in terms of analysis of the construction industry in Russia. © 2023 American Institute of Physics Inc.. All rights reserved.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85176769945

U2 - 10.1063/5.0164546

DO - 10.1063/5.0164546

M3 - Conference article

VL - 2849

JO - AIP Conference Proceedings

JF - AIP Conference Proceedings

SN - 0094-243X

IS - 1

M1 - 090017

ER -

ID: 48546273