ESTIMATION OF ECONOMIC EFFICIENCY OF APPLICATION OF MODELS FOR FORECASTING THE LAND DEMAND FOR CONSTRUCTION BY MUNICIPALITIES OF PRC

Subject: economic and mathematical methods for forecast of the development of a city conducted for the purpose of more accurate determination of the need for land resources. Development of a city is related to development of construction branch which, in turn, reflects the state of economy. If construction process is conducted, the new enterprises emerge and taxes come to all types of budget from new urban areas, etc. Therefore, forecasting the need for land resources for construction of residential and nonresidential real estate needs to be carried out more qualitatively and carefully, applying various scientific methods. Research objectives: the study of the theoretical and methodological foundations of forecasting the use of land for city’s development and application of the model for forecasting the growth of the city’s territory to increase the economic efficiency of the municipal budget under conditions of the PRC legislation. Materials and methods: correlation-regression analysis, Markov chains, “gray” Markov chains. Results: on the basis of analysis of various economic-mathematical models, whose application is possible when forecasting the needs of cities in construction of buildings, plants and factories, comparison of several common prediction methods is carried out: correlation-regression analysis and “gray” model (GM (1,1)). Upgrade of the Markov chain model is proposed with allowance for uncertainty factors. On the basis of the dynamics of the Zhangqiu land growth, using the proposed “gray” Markov chains, a forecast was made and its statistical, mathematical and economic significance was confirmed, which makes it possible to propose the application of the proposed model to predict the growth of any cities, including the ones in the Russian Federation. Conclusions: practical application of the proposed mathematical method under conditions of uncertainty of long-term forecasts on the example of forecast of city’s needs in land resources will increase the accuracy and economic efficiency of creation of master plans.