RIMS II Assumptions

RIMS II multipliers are based on the average relationships between the inputs and outputs produced in a local economy. The multipliers are a useful tool for studying the potential impacts of changes in economic activity. However, the relative simplicity of input-output multipliers comes at the cost of several limiting assumptions that produce what are likely to be upper bound estimates. Analysts are encouraged to carefully evaluate how closely these assumptions apply to their projects and to consider collecting additional information specific to their project to adjust their results.1

Assumptions of the model to keep in mind:

• Firms have no supply constraints—Input-output based multipliers assume that industries can increase their demand for inputs and labor as needed to meet additional demand. If local firms are already operating at full capacity, then additional inputs may need to come from outside the region, thereby reducing the local impact.
• Firms have fixed patterns of purchases—Input-output based multipliers assume that an industry must double its inputs to double its output. If a firm can increase its output without hiring additional employees and without purchasing additional inputs, then the impact of the change on the local economy will be smaller than the impact that is estimated using a full multiplier.
• Firms use local inputs when they are available—The method used by RIMS II to develop regional multipliers assumes that firms will purchase inputs from firms in the region before using imports. If a clothing manufacturer located in an area that produces textiles, purchases its textiles from outside the region, then the impact of a change in clothing production on the local economy will be smaller than implied by the full multiplier.

It is also worth keeping in mind that employment changes include both full and part-time jobs—this characteristic applies for all projects, but is especially important for service industries that have large shares of part-time employment.

The example below shows how the employment multiplier for a region can vary when local information is used to improve the accuracy of the multipliers because the model's assumptions do not hold. The example is a construction project for a health care facility.

• Scenario One: Suppose that all the assumptions of the multiplier model hold. For example, there is excess capacity in the local economy so that firms can produce an increase of inputs and that additional construction workers can be hired in the same proportion as the regional average for the industry. In this scenario, the final-demand employment multiplier for the construction industry in the hypothetical study region is 18.0, including the impact of new spending by households whose employment is a result of this new activity. This means that for each million dollars of spending to construct the new health care facility, 18.0 new jobs are expected to be created locally.
• Scenario Two: Suppose that the analyst has carefully studied the details of the construction project, including local work force dynamics, and has determined that 25% of the construction workers come from outside the region. In this case the implied multiplier using local purchases and labor supply estimates is 14.4 new local jobs per \$1 million of new construction.
• Scenario Three: Suppose that the construction activity requires specialized inputs and workers not found in the local area. As a result, local firms cannot supply additional inputs and 75% of the construction workers come from outside the region. In this case the implied multiplier using local purchases and labor supply estimates is 9.8 new local jobs per \$1 million of new construction.
Final-Demand Employment Multiplier for a Hypothetical
Region for Three Alternative Scenarios2
One Two Three
18.0 14.4 9.8

To learn more about how to use local information to refine your analysis, view an example of the Bill of Goods approach in greater detail here.

• 1BEA recommends a Bill of Goods approach for best results.
• 2These are Type II Multipliers.