title: ÐÐ¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ Ð¿Ð¾ÐºÐ°Ð·Ð°ÑÐµÐ»ÐµÐ¹ ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ð³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ Ð½Ð° Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð² Ð Ð¤
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Modeling the influence of sustainable development indicators on the investment attractiveness of the regions of the Russian Federation
Creators: name: ÐÑÐ·Ð¾Ð²Ð»ÐµÐ²Ð°, ÐÐ»ÑÐ³Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½Ð°Ñ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ
Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¸ Ð² ÑÐµÐ³Ð¸Ð¾Ð½Ñ
ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ðµ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ðµ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐºÐ¾Ð½Ð¾Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
investment attractiveness
investments in regions
sustainable development
machine learning
econometric modeling

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ, Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð², Ð²Ð»Ð¸ÑÑÑÐ¸Ñ Ð½Ð° Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð² Ð Ð¤ Ð² ÐºÐ¾Ð½ÑÐµÐºÑÑÐµ ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ð³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ. Ð ÑÐ¾Ð´Ðµ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÑÐ°Ð»Ð¸ÑÑ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸: 1. Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¼Ð°ÑÐµÑÐ¸Ð°Ð»Ð¾Ð², ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÑÑÐ¸Ñ ÑÐµÐ½Ð´ÐµÐ½ÑÐ¸Ð¸ Ð½Ð° ÑÑÐ½ÐºÐµ Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð²; 2. Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ°ÐºÑÐ¾ÑÐ¾Ð², Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑÐ¸Ñ Ð²Ð»Ð¸ÑÐ½Ð¸Ðµ Ð½Ð° Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð² Ð² ÑÑÐ»Ð¾Ð²Ð¸ÑÑ ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ð³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ; 3. Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ Ð»Ð¸Ð½ÐµÐ¹Ð½Ð¾Ð¹ ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ Ð¿Ð¾ÐºÐ°Ð·Ð°ÑÐµÐ»ÐµÐ¹ ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ð³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ Ð½Ð° Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð² Ð Ð¤; 4. Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ 5 Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¸ Ð»ÑÑÑÐ°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¿ÑÐ¾Ð¸Ð½ÑÐµÑÐ¿ÑÐµÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ SHAP. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ°ÐºÑÐ¾ÑÐ¾Ð², Ð²Ð»Ð¸ÑÑÑÐ¸Ñ Ð½Ð° Ð¸Ð½Ð²ÐµÑÑÐ¸ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¿ÑÐ¸Ð²Ð»ÐµÐºÐ°ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ³Ð¸Ð¾Ð½Ð¾Ð², Ñ ÑÑÐµÑÐ¾Ð¼ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ð¾Ð² ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾Ð³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ. Ð¡Ð±Ð¾Ñ Ð¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ° Ð´Ð°Ð½Ð½ÑÑ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸Ð»Ð°ÑÑ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ MS Office (Excel). ÐÐ½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸Ð»ÑÑ Ð² Google Colab Ð½Ð° ÑÐ·ÑÐºÐµ Ð¿ÑÐ¸Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Python c Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÐ°ÐºÐ¸Ñ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº ÐºÐ°Ðº pandas, matplotlib, seaborn. ÐÐ¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ Ð»Ð¸Ð½ÐµÐ¹Ð½Ð¾Ð¹ ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ Ð¸ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸Ð»Ð¾ÑÑ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐ°ÐºÐ¸Ñ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº ÐºÐ°Ðº sklearn, hyperopt, SHAP.
description: This work is devoted to identifying, analyzing and modeling factors influencing the investment attractiveness of Russian regions in the context of sustainable development. During the work, the following tasks were solved: 1. an analysis of existing materials examining trends in the market for investment attractiveness of regions was carried out; 2. an analysis of factors influencing the investment attractiveness of regions in conditions of sustainable development was carried out; 3. a linear regression of the influence of sustainable development indicators on the investment attractiveness of Russian regions was constructed; 4. 5 machine learning models were built, and the best model was interpreted using the SHAP library. The result of the work is a comprehensive analysis of factors influencing the investment attractiveness of regions, taking into account the principles of sustainable development. Data collection and processing were carried out using MS Office (Excel). Data analysis was carried out in Google Colab in the Python programming language using libraries such as pandas, matplotlib, seaborn. Linear regression and machine learning models were built using libraries such as sklearn, hyperopt, SHAP.