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but reporting was discontinued for some years. For the years since 1993, this data
deficit can be met to some extent with the recent (CFS) data from the Bureau of
Transportation Statistics (BTS), but these data are incomplete with respect to
interstate flows. Based on the currently available CFS data, Jackson et al. (
2006
)
used IMPLAN data (from the Minnesota Implan Group) to adjust the incomplete
CFS reports by adopting gravity models constrained via distance and by making
other adjustments. Along similar lines and using the same basic data sources, we
elaborate Park et al. (
2009
), who suggested a different estimation approach that
relied on an AFM (adjusted flow model) and a DFM (doubly-constrained Fratar
model). To proceed in this way, it was first necessary to create conversion tables to
reconcile the CFS and IMPLAN sectors. The detailed procedure bridging the CFS
and IMPLAN sectors are explained in the study of Park et al. (
2009
).
This chapter focuses on four versions of a National Interstate Economic Model
(NIEMO): NIEMO itself, which is a standard but operational multiregional input-
output model (MRIO); TransNIEMO which adds on a national highway network to
handle interregional freight flows; FlexNIEMO which constructs a supply-side
MRIO that permits relaxation of the fixed production coefficients assumption;
and finally a version that analyzes both intrastate and interstate induced impacts.
The NIEMO model revives an approach adopted in the late 1970s and the early
1980s (Polenske
1980
; Jack Faucett Associates
1983
), the development of a MRIO
(multiregional input-output) model. We combine State level data from the
IMPLAN input-output models with the estimated interregional trade flows based
on the Commodity Flow Survey (CFS) using an approach developed in Park
et al. (
2009
). NIEMO is aggregated to 47 economic sectors over 52 regions
(50 States, Washington, D.C., and the Rest of the World). This results in an
MRIO matrix with almost six million cells. Construction of the model involves
substantial data assembly and considerable data manipulation.
NIEMO is a multiregional input-output model that is fully operational. The idea
for such a model has a long history stretching back to Isard's suggestion of the
“ideal interregional model” (Isard
1951
,
1960
) and Leontief's valiant but failed
attempt to operationalize a variant of the model in the 1960s. The importance of
sub-national models has long been recognized. Aggregation accounts for the loss of
information, especially when positive effects in one area cancel negative impacts in
another. It is also clear that most politicians have a keen interest in local
constituencies. To say that NIEMO has succeeded where Leontief failed is not an
immodest statement, but rather a reflection of the improvements in databases and
computing capacity over the past 30 years. However, building bridges among the
various data sources has been a substantial task.
NIEMO is not an exact replica of the original design as conceived by Isard and
Leontief. Rather, NIEMO rests on the successful integration of state-level input-
output information with data from the Commodity Flow Survey (CFS). The
NIEMO approach is valuable because it uses only secondary data sources yet
represents an innovative regional science procedure. Since 1993, the CFS has
provided the most comprehensive single data source for U.S. freight movement
flows. The data were collected every 5-year by the Bureau of Transportation
