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contributor authorOdey Alshboul
contributor authorAli Shehadeh
contributor authorOla Hamedat
date accessioned2022-05-07T19:55:54Z
date available2022-05-07T19:55:54Z
date issued2021-12-28
identifier other(ASCE)ME.1943-5479.0001003.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4281821
description abstractConsidering the liquidity trap is critical as a primary step for a complete understanding of public investment’s impacts on the financial supply and demand within the construction industry during deflationary periods. However, minimal research has been conducted to formulate efficient models that can quantify optimal governmental investments. To bridge the gap, an integrated model of the investment savings-liquidity preference money supply (IS-LM) curve and the dynamic stochastic general equilibrium (DSGE) analysis was developed to investigate the balance of supply and demand during deflation status in addition to the associated spending adjustment mechanisms. The most recent data were analyzed, and the deep parameters were obtained using Bayesian estimation via the Markov chain Monte Carlo (MCMC) technique. The analysis result showed that public investment within economies in a deflationary state, which is in a liquidity trap, are expected to crowd out private investment. Also, due to the issuance of government bonds during deflation, the effect of public investment in this situation is more significant than that during inflation. Therefore, decision makers can use the proposed model to manage and quantify the highway construction and maintenance sector’s governmental annual optimal investment.
publisherASCE
titleGovernmental Investment Impacts on the Construction Sector Considering the Liquidity Trap
typeJournal Paper
journal volume38
journal issue2
journal titleJournal of Management in Engineering
identifier doi10.1061/(ASCE)ME.1943-5479.0001003
journal fristpage04021099
journal lastpage04021099-16
page16
treeJournal of Management in Engineering:;2021:;Volume ( 038 ):;issue: 002
contenttypeFulltext


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