We recently re-estimated our model of Michigan state with 2017 data and saw a drastic drop in output, but little change in jobs. This led me to be curious about how much the study area data can change from year to year. For example, sector 45 - Electric power generation - Wind has an output multiplier of 1.454 in the 2016 U.S. National data vs. 1.938 in the 2017 U.S. National data. This is a huge change for a single industry in a single year. Whereas, sector 44 - Electric power generation - Solar shows a much more modest change from 2.076 in 2016 to 2.065 in 2017. It's hard to believe that the economy for these two renewable energy industries experienced such drastically different shifts from 2016 to 2017. Can you tell me more about how the annual study area data is updated each year? Do you have any recommendations for selecting the most appropriate data year for our model?
Output Multipliers Across the Years
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Official comment
Hi Sarah,
Thank you for posting your question to IMPLAN Community. We do make changes year over year to incorporate better data sources and methodologies. We will escalate your question to our data team for any specific details or clarifications they can provide.
In the meantime, to broadly answer your question on how much study area could change, you can take a look at our 2017 Data Release Notes - https://implanhelp.zendesk.com/hc/en-us/articles/360011728033-2017-Data-Release-Notes.
To understand more about IMPLAN's Data Methodologies, you can refer to the Section under Study Area Data - https://implanhelp.zendesk.com/hc/en-us/articles/115002803833-Study-Area-Data.
We will be in touch shortly and appreciate your patience.
Thanks,
IMPLAN Support
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Hi Sarah,
Please see the attached link https://docs.google.com/spreadsheets/d/1JdIibN9ErHMItJnlx6sJQLgjfPdqg_UWAWmpIxxIoh4/edit?usp=sharing.
A few things that should be considered whenever you are comparing multipliers over time:- Multipliers change every year due to changes in economic conditions as well as changes in the underlying data. For instance, decreased U.S. manufacturing and growth in foreign imports will affect the multipliers. In general, productivity goes up, so the direct employment (and payroll) per dollar of output goes down. Lower payroll means lower induced effects. The US economy also gets more global as we progress forward in time - the more imports, the smaller the multipliers.
- The most significant components to impacts are output per worker and earnings per worker (proprietor income can go up or down dramatically from one year to the next). If the output per worker between the 2 years has gone up significantly, then indirect output can go up (more inputs per worker) and the direct employment can go down per million dollars of output.
- A decrease in multiplier can also be caused by a large increase in corporate profits (other property income) per dollar of output. Other Property Income (OPI) is treated as a leakage (it is hard to generalize where stockholders reside and how much and where of the retained earnings are invested). The larger the percentage going to OPI the smaller remaining to help drive the indirect and induced effects.
After reviewing the data, the data team provided the following additional information:
Even though output for sector 45 increased a bit between the two years, labor income (LI) and intermediate expenditures (IE) both increased at a higher rate than did output, such that the LI per Output and IE per Output for the sector have both increased between the two years, the former of which will increase induced impacts and the latter of which will increase both indirect and induced impacts.....thereby increasing the output multiplier! A look at the raw CEW data show a marked increase in Wage & Salary employment and income for this sector between the two years, which explains much of this change. Higher CEW employment and wages, all else equal, will give this sector a greater proportion of the BEA REA's more-aggregate "Utilities" sector's proprietor employment and proprietor income as well, further boosting LI. Other Property Income (OPI) comes from the BEA in the form of Gross Operating Surplus (GOS), which is Proprietor Income (PI) + OPI. The raw data show that GOS fell slightly for the "Utilities" sector between the two years, and with PI being higher, then OPI will be lower, which is what we see reflected in the IMPLAN model, which then gives us higher IE in addition to the higher LI. (Tax on Production and Imports remained roughly the same).
The attached spreadsheet shows the IMPLAN data ratios and growth rates, as well as the raw CEW data.
Thank you,
IMPLAN Staff0
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