Geoscience Reference
In-Depth Information
TRANSPORTATION COST IMPACTS MODEL
DATA INVENTORY
FHWA FREIGHT
ANALYSIS
FRAMEWORK
IMPLAN
∆
price of products
consumed at each
origin - destination
state pair by 47
USC sectors
A price-type, state-
level input-output
model (US price IO
model)
Share of total cost
paid for truck
services by State,
509 sectors
State-level input-
output models,
509 sectors
Baseline NIEMO
trade flows for 29 of
47 USC Sectors
FAF 2 mode split
proportions
U.S. Census
Freight shipping
expenditures by
origin State,
509 sectors
Freight shipping
expenditures by
origin State,
29 USC sectors
Separation:
Changed shipping
costs by origin
states by 29 USC
Sectors
Labor
proportion in
truck mode
Freight origin-
destination flows for
the truck mode
aggregate price
effects by
destination states
and 47 USC Sectors
US census:
employment
FAF 2 network
NETWORK DEFINITION
Select
Interstate and State
highways
Centroid points
from MSAs and
remainder areas
NETWORK DISRUPTION SCENARIO
Select
intersection nodes
from the selected
highways
Scenario 1
Scenario i
Scenario N
Buffer miles
boundary
surrounding
network node
points
NETWORK MODELING
Estimate
shortest paths
between network
nodes and aggregate
by states
Calculate proportion
of shortest path time
change by state O-D
pairs
Calculate
changed shipping
costs by states and
by 29 sectors
Network nodes:
10% sample of intersection nodes
within buffer miles
Apply shortest path algorithm
by a selected scenario and
aggregate by states
∆
Final demands by
47 USC Sectors and
by region
DEMAND-DRIVEN NIEMO
IMPACT
Annual rates at which costs accrue by sector
:
Intra- and interstate direct and indirect economic
impacts, 51 regions by 47 USC Sectors
Demand-driven
National Interstate Economic Model (NIEMO):
An open multiregional input-output model
Fig. 4.4
Framework of national-level TransNIEMO.
Source
: Cho et al. (
2014
) TransNIEMO:
economic impact analysis using a model of consistent interregional economic and highway
network equilibria, CESIfo, WP 4601
)
1
, where
LINV
NiEMO
¼
nm
matrix that combines technical
coefficients with coefficients describing interregional trade flows. Note that the
matrix
(
I W
W
is an
nm
W
is defined as
W
¼
T
NIEMO
A
NIEMO
ð
4
:
3
Þ
where
A
NIEMO
is a block diagonal matrix of technical coefficients linking input
commodities to output industries within each region
n
(¼1,
...
, 52), and
T
NIEMO
is
an
nm
nm
collection of diagonal matrices describing interregional trade flows.
The matrix
T
NIEMO
is defined as
T
NIEMO
¼
T T
R
1
ð
4
:
4
Þ
where
T
is an
nm
nm
matrix of trade flows, and
T
R
is an
nm
nm
matrix formed by diagonalizing the 1
nm
row vector
T
R
,
.
Note that we identify losses of foreign exports and final demand losses or gains
as different types of direct impacts, and that these vary across scenarios. Foreign
exports losses and government expenditures define a region-specific vector of direct
impacts. Final demand losses or gains define vectors of regionally distributed direct
consisting of the column sums of
T
