Forecasting Construction Material Prices Using Vector Error Correction Model

Sayed Amir Mohsen Faghih · Hamed Kashani

74 citations0/0 files storedJournal of Construction Engineering and Management

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Forecasting Techniques and Applications Construction Project Management and Performance Market Dynamics and Volatility

Abstract

This paper presents a vector error correction (VEC) model for use in forecasting the short- and long-term prices of construction materials. This model characterizes the relationship between construction material prices and a set of relevant explanatory variables. The use of VEC models to forecast construction material prices addresses a gap in the existing literature that stems from overlooking the importance of forecasting both the short- and long-term movements of individual construction materials. The proposed model is applied to produce forecast models for asphalt, steel, and cement prices in the United States based on the identified variables that govern the prices of each material. Practitioners can use the proposed model to forecast construction material prices. The derived insights can be used to enhance the chances of project success.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 74 citations exist upstream.

References

1987Co-Integration and Error Correction: Representation, Estimation, and Testing 1979Distribution of the Estimators for Autoregressive Time Series with a Unit Root 1969Investigating Causal Relations by Econometric Models and Cross-spectral Methods 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1977Time Series Analysis: Forecasting and Control 1988Statistical analysis of cointegration vectors 1990MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY n.d.Forecasting principles and practice

Cited by

2020Neural Networks Model for Prediction of Construction Material Prices in Egypt Using Macroeconomic Indicators 2023Scrap steel price forecasting with neural networks for east, north, south, central, northeast, and southwest China and at the national level 2020Impact of Dynamic Workforce and Workplace Variables on the Productivity of the Construction Industry: New Gross Construction Productivity Indicator 2020Predicting City-Level Construction Cost Index Using Linear Forecasting Models

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.