INTRODUCTION
It is always smart to consider ALL potential audiences for your study. Ultimately, doing so may help you recognize the level of detail in which your final report should describe your study.
Think about your audience. What are you trying to communicate? What drives your stakeholders?
DETAILS
It’s very important to define the who, what, where, and when of your analysis with intention. You must also interpret the results of your analysis and communicate them to your stakeholders and audiences.
From the beginning, you should know why you are performing this analysis. Are you just interested in comparing two Industries in your county? Are you evaluating the impacts of potential projects for government funding? Are you trying to communicate the contribution of an institution to your area?
Knowing why the analysis is being performed will guide not only the design of your study, but also what results will be most meaningful to your stakeholders. If you are communicating your results to both county and regional governments, consider using Multi-Regional Input-Output (MRIO) and showing each regional constituency the impact on their Region.
If you are working for a Workforce Investment Board, consider focusing more on Employment and Employee Compensation. Economic Development professionals might care more about Value Added (GDP).
USING WHY TO DRIVE WHERE
You can also use the answers to why you are performing the analysis to help define the analysis Region. Let’s consider the following example. The Charlotte area, as well as the whole state of North Carolina, is experiencing population growth. We’d like to measure the effect of the new income brought in by new residents.
If the why of the analysis is to communicate to Mecklenburg County (the county that contains Charlotte) officials about the value of investing in attracting new residents to Mecklenburg County, our what ought to be the annual value of income earned by new Mecklenburg residents. Because Mecklenburg County is where the impact is taking place and where we want to measure the impact, Mecklenburg County is the appropriate Region for this analysis.
If instead the why of the analysis is to communicate to North Carolina officials about the value of attracting new residents to North Carolina, our what should pivot to the annual value of income earned by new North Carolina residents as a whole. In this case where the impact is taking place (NC) and where we want to measure the impact (NC) are again the same. But this time we would run the impact on the state of North Carolina.
Now let’s consider the scenario in which where the impact is taking place and where we want to measure the impact are different. In many cases, where the impact is taking place is a subregion of where we want to measure the impact. We would define our study differently if the why of the analysis is to communicate to North Carolina officials about the value of investing in attracting new residents to Mecklenburg County.
One option is to only restrict the what of the analysis to the annual value of income earned by new Mecklenburg County residents and keep our Region defined as the entire state of North Carolina. The benefit of this approach is that we are now capturing the effects of what is happening in Mecklenburg County throughout the state of North Carolina. Measuring effects happening in the rest of North Carolina as a result of population growth in Mecklenburg demonstrates how spending in this one area is connected to the rest of the state and benefits the broader regional economy. If we restricted our Region to Mecklenburg these effects would be leakages and would not be included in our results. The downfall of this approach is aggregation bias.
A solution to avoiding aggregation bias while still achieving the goal of measuring effects to the broader economy is linking Regions using Multi-Regional Input-Output Analysis (MRIO). Using MRIO let’s you model multiple regions and their interactions. We could have the new resident income Event in Mecklenburg County and link that to a combined Region of the remaining 99 counties in the state of NC using MRIO.
RELATED TOPICS
Introduction to Multi-Regional Input-Output Analysis
Written December 10, 2019