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where
SLINV
NIEMO
¼
(I-SNIEMO)
1
SNIEMO
¼
the technical and trade coefficients in the supply-driven NIEMO; and
ST
NIEMO
¼
the trade coefficients in the supply-driven NIEMO.
In the final step, we estimate
net
induced impacts which equal total induced
impacts from the application of IMPLAN but via subtracting the induced trade
impacts. This is also a part of Type II's induced effects to be added to the original
NIEMO results. The net induced impacts resulting from the IMPLAN sector system
are again aggregated to the USC sector system.
Conclusions
This chapter presents a methodological review of NIEMO (the National Inter-
state Economic Model) that is used for nationwide economic studies, as opposed
to SCPM (the Southern California Planning Model) that is used for applications
in Southern California. NIEMO is the most detailed and most comprehensive
attempt to implement Isard and Leontief's dream of an operational MRIO
(multiregional input-output model), although there have been other
contributions along the way by Chenery, Moses, Polenske, Jackson (Jackson
et al.
2006
) and others. As widely noted, the most serious limitation of IO
modeling is to obtain the fixed coefficients; the standard IO models ignore
substitution opportunities prompted by market signals and uncertainties about
the impact of economic sector losses. The FlexNIEMO model described above
shows initial attempts to overcome this obstacle. Moreover, there are quanti-
tative approaches in information theory that may improve NIEMOs'
coefficients. Furthermore, flexible approaches can be applied to estimating
economic input-output coefficients for areas smaller than the state level. This
is useful in capturing the non-linearity of input-output coefficients because it can
use local employment compensation information for the value added and final
demand consumption sectors, This type of analysis can be used to account for
local economies of scale, impossible with standard IO models. The required
economic data sources in the U.S. are available from the Bureau of Economic
Analysis, Consumer Expenditure Survey, Economic Census, U.S. Census of
Population,; and more. This more disaggregated approach (both spatial and
sectoral) is currently under development and could reinvigorate IO analysis.
However, we have also attempted to go beyond the standard concept of the
MRIO by extending it in three important directions. First, by developing
TransNIEMO we added a highway network that enabled us to explore the
transportation as well as the spatially disaggregated economic impacts of any
exogenous shock, such as a terrorist attack or a natural disaster. Second, as
already suggested, we have attempted to deal with one of the major criticisms of
MRIO, the fixed production coefficients assumption, by developing FlexNIEMO
with a capacity for changing interindustry coefficients by introducing a supply-
side component. Third, we devised a method of tackling a familiar critique of
MRIOs, their inability to measure induced as well as indirect impacts with
respect to interregional trade. Although there is still a need for further progress
