Changes of Induced Multiplier Effects
Hello
I built a 9-county model in the San Francisco area using the 2010 model and an identical model using the 2014 model. The induced multipliers are substantially lower in 2014 than they were in 2010. Is there an explanation for this?
I've attached the induced output multipliers for the two models. The region is for Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano and Sonoma.
Thanks
[attachment=673]h3cdd2c3.xlsx[/attachment]
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Hi Steven. Multipliers change for a variety of reasons. Between 2010 and 2014, there are numerous reasons, economic- and data-related, that could explain this. Some important considerations: 1) Economic reasons: a. Induced output multipliers relate business sales to labor income spending. If, over time, in a sector the labor income share of output has decreased, this would decrease output induced effects, all else equal. i. In farming sectors, for example, an increase in the relative number or size of corporate, versus proprietor farms, could reduce induced effects since corporate income is treated by IMPLAN as a leakage. ii. Within corporate farms, if more income flows to holders of capital than to employees, induced effects would decrease, again since corporate income is a leakage. b. Commuting patterns could change. If a region experiences increased in-commuting over time, induced multipliers will decrease. c. Payroll tax rates can change (though they were the same at the federal level in 2010 as in 2014, but there was a payroll tax holiday from 2011 to 2012). d. Agricultural output and compensation levels, in particular, can be highly variable year-to-year. e. Household spending patterns can differ, as can RPCs (which indicate the proportion of local demand for a given commodity is purchased locally), either of which would change induced multipliers. 2) Data reasons: a. Between 2010 IMPLAN data and 2014 IMPLAN data, we re-estimated output-compensation relationships for the farming sectors you identified, based on the new benchmark input-output tables from the Bureau of Economic Analysis. b. We have made numerous other methodological improvements over time, which could change the relationship of output to compensation. c. Our raw data sources for agriculture over time have changes their structure and have published revised historical estimates. Accordingly, we do not recommend treating IMPLAN data sets as a consistent time series. We are currently developing a time-series set of IMPLAN data that will address the majority of data-related reasons for such changes, thereby better isolating the economic reasons. In general, the possible reasons to account for this over such a span of time, especially a span that includes an update to the 5-year benchmark, are manifold. Forum links: http://implan.com/index.php?option=com_kunena&view=topic&catid=80&id=18852&Itemid=1840#19203 http://implan.com/index.php?option=com_kunena&view=topic&catid=84&id=17210&Itemid=1798#17222 http://implan.com/index.php?option=com_kunena&view=topic&catid=84&id=17621&Itemid=1798#17623 http://implan.com/index.php?option=com_kunena&view=topic&catid=80&id=17403&Itemid=1798#17437
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