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Evaluating the Economic Impact of Freight Investment in Chicago Using Computable General Equilibrium

Ming Yan Fu (7958291)

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Abstract

Computable general equilibrium (CGE) is used to analyze the impacts of a transportation investment in Chicago that will induce a 20% reduction in truck congestion. Two simulations are explored: a 20% increase in total factor productivity (TFP) or Hicks neutral technical change and a 20% decrease in capital and labor inputs. These changes were made only to the trucking sectors of the economy. The first simulation employs a popular method used by many researchers in the past to show efficiency gains and infrastructure investments. The result of this simulation is a 1.09% change in gross regional product (GRP). The second simulation replicates efficiency gains as a means to reduce capital and labor cost. The result of this simulation is a -0.32% change in GRP. The results for savings and investments are sensitive to productivity changes, particularly state and local government spending. \nThe first simulation suggests that the trucking sectors pass the cost-savings they achieve through increased productivity to other industries and users of their services. The second simulation suggests that the trucking sectors’ costs rise due to decrease in capital and labor factor demand. The trucking sector then shifts the cost burden to consumers by charging higher prices. The second simulation should be interpreted with caution as a more realistic scenario would hold the trucking sectors’ industry output constant because of research suggesting that congestion has negligible impact on trucking demand.

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What this paper is about

Computable general equilibrium (CGE) is used to analyze the impacts of a transportation investment in Chicago that will induce a 20% reduction in truck congestion. Two simulations are explored: a 20% increase in total factor productivity (TFP) or Hicks neutral technical change and a 20% decrease in capital and labor inputs. These changes were made only to the trucking sectors of the economy. The first simulation employs a popular method used by many researchers in the past to show efficiency gains and infrastructure investments. The result of this simulation is a 1.09% change in gross regional product (GRP). The second simulation replicates efficiency gains as a means to reduce capital and labor cost. The result of this simulation is a -0.32% change in GRP. The results for savings and investments are sensitive to productivity changes, particularly state and local government spending. \nThe first simulation suggests that the trucking sectors pass the cost-savings they achieve through increased productivity to other industries and users of their services. The second simulation suggests that the trucking sectors’ costs rise due to decrease in capital and labor factor demand. The trucking sector then shifts the cost burden to consumers by charging higher prices. The second simulation should be interpreted with caution as a more realistic scenario would hold the trucking sectors’ industry output constant because of research suggesting that congestion has negligible impact on trucking demand.

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Available abstract

Computable general equilibrium (CGE) is used to analyze the impacts of a transportation investment in Chicago that will induce a 20% reduction in truck congestion. Two simulations are explored: a 20% increase in total factor productivity (TFP) or Hicks neutral technical change and a 20% decrease in capital and labor inputs. These changes were made only to the trucking sectors of the economy. The first simulation employs a popular method used by many researchers in the past to show efficiency gains and infrastructure investments. The result of this simulation is a 1.09% change in gross regional product (GRP). The second simulation replicates efficiency gains as a means to reduce capital and labor cost. The result of this simulation is a -0.32% change in GRP. The results for savings and investments are sensitive to productivity changes, particularly state and local government spending. \nThe first simulation suggests that the trucking sectors pass the cost-savings they achieve through increased productivity to other industries and users of their services. The second simulation suggests that the trucking sectors’ costs rise due to decrease in capital and labor factor demand. The trucking sector then shifts the cost burden to consumers by charging higher prices. The second simulation should be interpreted with caution as a more realistic scenario would hold the trucking sectors’ industry output constant because of research suggesting that congestion has negligible impact on trucking demand.

Key concepts: Computable general equilibrium, Investment (military), Economics, Economic impact analysis, Operations research, Microeconomics, Engineering, Political science

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