HOUSING DEMAND MODEL ANALYSIS

ABSTRACT

The article is devoted to data analysis of the created and developed model of demand for housing. A web application has been created that allows users to view rental and sale ads. Using the data obtained, an analysis of the demand for housing, as well as optimal prices for the period.

Keywords: analysis, prices, demand, square meters, web application, process automation.

1. Introduction

Dependence is a property of a variable whose changes are determined by changes in other, independent, variables [1].

At the moment, many are wondering when the benefits of buying or renting a home. But it’s difficult for an ordinary person to analyze and process a large amount of data. To determine what factors influence the price increase, you must have a database or web application that was previously created.

Demand for housing is the dependence of the desired volumes of its acquisition, measured in units of living space (in square meters or in the number of apartments or houses) on the price per unit of living space [2].

The work is devoted to the analysis of demand for housing using the created web application for rental and sale of housing.

2. Housing Demand Analysis

The problem of housing provision is highly relevant, as evidenced by the presence of a priority national project to improve housing conditions and a large number of programs aimed at solving the "housing problem" at the state regional and local levels of government. The complexity of solving the "housing problem" in the modern Kazakhstani economy is compounded by the fact that with high demand for housing, its purchase is still poorly accessible for most segments of the population. The work “Creating and Developing a Housing Demand Model” is relevant as there is currently a shortage of affordable housing with adequate prices in Kazakhstan. The housing shortage in Kazakhstan, with which the country has been desperately struggling for about 20 years, has again become the focus of attention.

Development of methodology, methodological and practical recommendations for the development of a regulation system for the residential real estate market of a large city in accordance with modern requirements, patterns and conditions for the organization of market relations. Automation of the processes of buying, selling housing, rental housing.

Additionally, using the received data on the number of ads, as well as the prices indicated for a particular advertisement, analysis will be displayed. Looking at the forecasts and analysis results, the buyer will know in what period the price of real estate rises and when the price drops. For example, according to user requests, it was revealed that affordable housing prices in winter are much more expensive than in summer. This confirms that the higher the quantity of demand and, accordingly, the prices increase. In summer, rental housing prices increase than in winter. This result shows that the majority of users in summer sought rental housing.

In order to derive the analysis data, it was necessary to implement a model of demand for housing, where data on prices, apartment sales, rental apartments will be indicated. The user selects what he needs, and the system remembers all the data received from all announcements and user operations to display statistical analyzes.

Prices are also affected by demand and this can be seen on the attendance chart. (Picture 1). According to the schedule, it can be said that rental housing prices were higher in July 2019, namely in the summer period.

Figure 1. Graph of attendance

According to the chart below, you can consider that in the search for housing in Nur Sultan the leader, i.e. there is a shortage of square meters (Figure 1). According to an article in Forbs magazine, 54 developers are building a residential real estate market in Nur Sultan at the end of the year. They are building 112 residential complexes with a total area of ​​3.1 million square meters in the amount of 39 696 apartments. The undisputed leader is BI Group with a market share of 26%, which is currently building 22 residential complexes for 30 houses with 10,353 apartments. Next comes Nova City Development (a subsidiary of BI Group) with a market share of 13%. Between the four developers of the city 50% of the capital market will be distributed: 39% - BIGroup + NovaCity, 7% - HighVill and 5% - SAT-NS. SAT-NS is a newcomer to this list: previously, the developer sold only one LCD - Arnau Premium with an area of ​​51,000 sq.m. But at the end of 2019, the newcomer announced a new major project - Apple City LCD for 2,000 apartments [3], but this is not enough to fully provide the population of the city.

Figure 2. Demand for housing by city

At the same time, the demand for housing by age category can be divided. Basically, the need for housing in the young part of the population is between the ages of 25-34. This category is able-bodied and has the ability to rent or buy housing.

Figure 1. Demand by age

3. Conclusion

The creation and development of a model of demand for housing - a web application. The web application allows users to view advertisements for rental and sale of housing, with the analysis of optimal prices for the current period. Using the data obtained on the number of ads, as well as the prices indicated for a particular advertisement, analysis was derived and presented in graphs.

References:

1. Dependence.https://ru.wikipedia.org/wiki/%D0%97%D0%B0%D0%B2%D0%B8%D1%81%D0%B8%D0%BC%D0%BE%D1%81%D1%82%D1%8C
2. M.Yu. Malkin. Features of the formation of demand, supply and equilibrium in the residential real estate market of Russia. Article.https://cyberleninka.ru/article/n/osobennosti-formirovaniya-sprosa-predlozheniya-i-ravnovesiya-na-rynke-zhiloy-nedvizhimosti-rossii/viewer
3. Housing prices in 2020-2023: rise or fall? https://forbes.kz//process/property/tsenyi_na_jile_v_2020-2023_rost_ili_padenie/?