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Escavy Fernández, José Ignacio and Herrero Fernández, María Josefa and Trigos Luque, Larua and Sanz Pérez, Eugenio (2020) Demographic vs economic variables in the modelling and forecasting of the demand of aggregates: The case of the Spanish market (1995–2016). Resources Policy, 65 (101537). ISSN 0301-4207
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Official URL: https://www.sciencedirect.com/science/article/pii/S0301420719304465
Abstract
Aggregates, including sand, gravel and crushed stones, are the first mined resource by volume of production and the second most employed natural material, only after water. The demand of aggregates depends on the level of activity of the building and construction industry, which supplies housing and infrastructures to society. Knowing the variables controlling the demand of aggregates permits an estimation of future demand. This figure is of great interest for both the private sector to take strategic decisions and for the public sector to optimize permits and to promote or limit extraction in certain areas.
This work studies the relationship between the demand of aggregates and various demographic, economic and construction variables during a complete economic cycle (1995–2016) in Spain. The analysis includes variables such as population, GDP, unemployment rate, etc., as well as variables never used before, that have resulted to be relevant: the number of people reaching the emancipation age, number of divorces, etc. Results indicate that the higher correlations appear between the demand of aggregates and house permitting, net in-migration, population increase, value added by construction, and number of people reaching emancipation age. There is as well a strong inverse correlation between the unemployment rate and the demand of aggregates. With these results, various models to forecast the demand of aggregates are proposed and an estimation of the total demand in Spain until 2050 is given.
Item Type: | Article |
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Uncontrolled Keywords: | Aggregates, Building and construction materials, Economic geology, Demand modelling, Regression analysis |
Subjects: | Sciences > Geology > Petrology |
ID Code: | 59421 |
Deposited On: | 05 Mar 2020 19:03 |
Last Modified: | 05 Mar 2020 19:03 |
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