312
Multipliers for goods and services not delineated
as sectors in the transactions table (e.g., tourism
and recreation) cannot be derived directly. However, it is possible to derive multipliers indirectly
by including expected changes in final demand for
the various sectors involved, forecasting the total
output, and then dividing total output by the direct
effect (e.g., see Pedersen et aI., 1989). For example, sectors that would be included for tourism are
hotels, motels, and resorts; eating and drinking
places; and automobile service stations.
It should be recognized that multipliers change
as the spatial aggregation changes. The larger the
geographic area is, the larger the multiplier effect,
because additional interaction effects are quantified
in the multiplier. This emphasizes the importance
of correctly specifying regional boundaries.
21.2.3 Limitations of Multipliers
Although multipliers are very useful in evaluating
economic alternatives, they have some definite limitations.
The Type I and Type III multipliers are useful as measures of the additional activity which can be expected to
occur throughout the economy from changes in a particular economic sector if additional inputs are available.
Because they are ratios of total impacts to the direct impact, use of the Type I and III multipliers can be misleading if used by themselves .... the size of impacts
differs depending on the economic measure considered
and whether the induced component is included. (Pedersen et aI., 1989, p. 15)
Although multipliers are multiplied by direct impacts to estimate the ripple effect from initial
changes in economic activity, magnitudes of multipliers by themselves say little directly regarding
total economic impact. For example, if a sector has
a very high employment multiplier, but the number of direct jobs per one dollar of production is
very low, then total employment impact will be
low.
21.2.4 Distribution of Output, Income,
and Employment
Input-output models contain a tremendous amount
of information that most people never use. Unfortunately, multiplier analysis has tended to dominate
any impact analysis. Often distributional impacts
are not explored at all. This is unfortunate, because
an input-output model can provide estimates of
sectoral distributions of output, income, and employment. The direct coefficients table shows the
Methods of Economic Impact Analysis
distribution of direct effects of outputs and input.
The inverted Leontief matrix shows the distribution of direct and indirect effects in output terms,
which can be transformed to income and employment terms if desired. It is likely that distributional
impacts are more important in the public policy
arena than total regional impacts. Discussion of income distribution impacts is found in Rose et aI.
(1988).
21.3 Selected Available
Input-Output Modeling
Systems: Ready-made Models
Because of the extreme costs and time required to
conduct a survey-based input-output analysis,
much less an economic impact assessment, usually
the most practicable way to proceed is to use one
of the available secondary data models. Many such
models have been reported in the literature. Comparisons of many of the input-output modeling systems are found in Brucker et aI. (1987, 1990). For
practitioners, it is important to select one that is
kept up to date (i.e., the information system used
by the model is continually updated). The most
commonly available supported secondary-databased modeling systems are (1) IMPLAN (developed by Forest Service, USDA, currently sold and
maintained by MIG, Inc.); (2) REMI (Regional
Economic Models, Inc.); and (3) RIMS (Bureau of
Economic Analysis, U.S. Commerce Department).
A brief comparison of the popular ready-made regional economic impact models is shown in Table
21.5.
21.3.1 IMPLAN
A brief description of IMPLAN follows (Shields et
aI., 1996, p. 19):
IMPLAN, an acronym for Impact Analysis for Planning,
is the 1-0 model developed by the USDA Forest Service. It is a non survey-based modeling tool that provides
front- and back-end user interface software plus a
matrix-inverter that creates the Leontief inverse matrix.
Data sets can be manipulated using the software, and scenarios can be developed using the modified information.
A standard run of IMPLAN generates the Leontief inverse, various multipliers, and a wide variety of reports.
IMPLAN is a demand-driven 1-0 model, useful for
examining backward linkages. . . . IMPLAN data sets
represent a single year and utilize make and use matrices, so analyses can be conducted from an industry or a
commodity perspective ....
Multipliers for goods and services not delineated
as sectors in the transactions table (e.g., tourism
and recreation) cannot be derived directly. However, it is possible to derive multipliers indirectly
by including expected changes in final demand for
the various sectors involved, forecasting the total
output, and then dividing total output by the direct
effect (e.g., see Pedersen et aI., 1989). For example, sectors that would be included for tourism are
hotels, motels, and resorts; eating and drinking
places; and automobile service stations.
It should be recognized that multipliers change
as the spatial aggregation changes. The larger the
geographic area is, the larger the multiplier effect,
because additional interaction effects are quantified
in the multiplier. This emphasizes the importance
of correctly specifying regional boundaries.
21.2.3 Limitations of Multipliers
Although multipliers are very useful in evaluating
economic alternatives, they have some definite limitations.
The Type I and Type III multipliers are useful as measures of the additional activity which can be expected to
occur throughout the economy from changes in a particular economic sector if additional inputs are available.
Because they are ratios of total impacts to the direct impact, use of the Type I and III multipliers can be misleading if used by themselves .... the size of impacts
differs depending on the economic measure considered
and whether the induced component is included. (Pedersen et aI., 1989, p. 15)
Although multipliers are multiplied by direct impacts to estimate the ripple effect from initial
changes in economic activity, magnitudes of multipliers by themselves say little directly regarding
total economic impact. For example, if a sector has
a very high employment multiplier, but the number of direct jobs per one dollar of production is
very low, then total employment impact will be
low.
21.2.4 Distribution of Output, Income,
and Employment
Input-output models contain a tremendous amount
of information that most people never use. Unfortunately, multiplier analysis has tended to dominate
any impact analysis. Often distributional impacts
are not explored at all. This is unfortunate, because
an input-output model can provide estimates of
sectoral distributions of output, income, and employment. The direct coefficients table shows the
Methods of Economic Impact Analysis
distribution of direct effects of outputs and input.
The inverted Leontief matrix shows the distribution of direct and indirect effects in output terms,
which can be transformed to income and employment terms if desired. It is likely that distributional
impacts are more important in the public policy
arena than total regional impacts. Discussion of income distribution impacts is found in Rose et aI.
(1988).
21.3 Selected Available
Input-Output Modeling
Systems: Ready-made Models
Because of the extreme costs and time required to
conduct a survey-based input-output analysis,
much less an economic impact assessment, usually
the most practicable way to proceed is to use one
of the available secondary data models. Many such
models have been reported in the literature. Comparisons of many of the input-output modeling systems are found in Brucker et aI. (1987, 1990). For
practitioners, it is important to select one that is
kept up to date (i.e., the information system used
by the model is continually updated). The most
commonly available supported secondary-databased modeling systems are (1) IMPLAN (developed by Forest Service, USDA, currently sold and
maintained by MIG, Inc.); (2) REMI (Regional
Economic Models, Inc.); and (3) RIMS (Bureau of
Economic Analysis, U.S. Commerce Department).
A brief comparison of the popular ready-made regional economic impact models is shown in Table
21.5.
21.3.1 IMPLAN
A brief description of IMPLAN follows (Shields et
aI., 1996, p. 19):
IMPLAN, an acronym for Impact Analysis for Planning,
is the 1-0 model developed by the USDA Forest Service. It is a non survey-based modeling tool that provides
front- and back-end user interface software plus a
matrix-inverter that creates the Leontief inverse matrix.
Data sets can be manipulated using the software, and scenarios can be developed using the modified information.
A standard run of IMPLAN generates the Leontief inverse, various multipliers, and a wide variety of reports.
IMPLAN is a demand-driven 1-0 model, useful for
examining backward linkages. . . . IMPLAN data sets
represent a single year and utilize make and use matrices, so analyses can be conducted from an industry or a
commodity perspective ....