Skribans, Valerijs (2010): Construction industry forecasting system dynamic model. Published in: Proceedings of the 28th International Conference of the System Dynamics Society (2010): pp. 1-12.
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In a paper construction branch forecasting model which allows to estimate the industry development problems is shown. Difference from anthers models, in given paper the main attention is turned to the building of the living area. Model stands from sub model (blocks): amount of apartments, real estate prices, necessity of apartments and living area forecasting models. Their essence and necessity are shown in separate sections. In the paper final, produced model is applied practical, are given model forecasts. The apartments amount forecasting model show supposition, in which, if there is deficit of dwellings in the economic system, then, first of all, are finance and construct apartments with little areas, i.e., multistory buildings with one-room apartments. Apartment’s amount increase depends from the building financing, as also from middle apartment area and building costs of square meter. The real estate prices forecasting model show supposition, that the once certain price is actual while it is not changed with prices influential parameters. The prices influential parameters are: extend (or diminish) of the live fund, the total market influence on separate market segments (and vice versa). The apartment’s necessities forecasting model show supposition, that in beginning a certain volume of necessities remains not changed, while on their has not changed with influential factors. Between the influential factors there are: apartments amount increase – it diminish apartments amount necessities; apartments wear (amount diminish) - it increase apartments amount necessities; improve of live circumstances - it diminish apartments amount necessities. The live area forecasting model is an additional model, which provides functioning of another’s models. Shown supposition was related with a population tries to purchase apartments with such properties which is similar to present at the market apartments. Till with it the middle area in each analyse group is not changes. In not changes middle area circumstances, knowing apartments amount, it is possible to calculate the total live area. Accumulating statistical data it is to adjoin with a problem, that not all data was certain, for a few data only possible borders of oscillations are certain. Till with that, in the paper are examined a few possible situation development variants. Buildings and real estate market development simulated on separate its segments and in an aggregate. Analysing the forecast data for aggregate apartments building in Latvia, in basic scenario it is certain, that the counterbalanced apartments building volume is about 1800 apartments in the year, but noticing oscillations of overproduces and necessities, this size can brief hesitate from 1434 to 2019. A sensitiveness analysis confirms basic scenario, complements it and extends with credible horizon borders.
|Item Type:||MPRA Paper|
|Original Title:||Construction industry forecasting system dynamic model|
|Keywords:||construction demand, housing fund, system dynamic, market modeling, simulation, economic forecasting|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods
L - Industrial Organization > L8 - Industry Studies: Services > L85 - Real Estate Services
L - Industrial Organization > L7 - Industry Studies: Primary Products and Construction > L74 - Construction
C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C49 - Other
C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics
|Depositing User:||Valerijs Skribans|
|Date Deposited:||10. Dec 2010 16:34|
|Last Modified:||12. Feb 2013 22:46|
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