Optimizing econometric model of determination of cost of housing on the basis of state policy of Republic of Kazakhstan
AbstractArticle purpose – developing a model of an assessment of real cost of construction projectson the basis of the analysis of state regulation’s mechanisms of housing construction sector.The methods of statistical groups, correlation and regression, economic-mathematical modelingwere used for receiving results. The practical value of research is caused by that its methodicaldevelopment and concrete recommendations can be used by the construction enterprises.The optimizing – econometric model of an assessment of real cost of the construction projectwithin a state program is developed. The optimizing econometric model will give opportunityto consider a real price, so that the construction companies could exactly forecast expenditurefor building. The financial expenses necessary for each of types of objects of affordable housingare considering as random variables. The state tariffs have the fixed character and established bystudying of the average data and endogenous factors characterizing separate construction projects.Nevertheless, the real prices by each type of housing have floating character and changedepending on change of inflation, demand for certain types of housing, etc. In this regard thequestion of an assessment of a deviation of the real prices from the tariff prices is actual. Such problem definition allows to determine the real maximum quantity of affordable housing by eachof types and to distribute resources in the best way.Key words: the housing market, construction sector, a state policy, the econometric model, the fixed tariff.
How to Cite
ОСПAНОВ, С.С.; КОНДЫБAЕВA, С.К.. Optimizing econometric model of determination of cost of housing on the basis of state policy of Republic of Kazakhstan. The Journal of Economic Research & Business Administration, [S.l.], v. 120, n. 2, p. 57-63, jan. 2018. ISSN 1563-0358. Available at: <http://be.kaznu.kz/index.php/math/article/view/1827>. Date accessed: 20 feb. 2018.