ST. LAWRENCE COUNTY ECONOMIC DEVELOPMENT STUDY • DECEMBER 2015 • 23
2. Potential implementation risks: Certain factors could
impede implementation of the initiatives over the
five-year time span. Examples could include unforeseen
budget/funding shortfalls, inability to attract as many
manufacturing firms or greenhouses as predicted, or
lower small business creation.
3. A maximum jobs cap based on achievable unemployment
and labor participation rates: A discount on added jobs is
necessary to ensure the predicted unemployment rate is
not unrealistic.
a. According to the Federal Reserve, the long-term
natural rate of unemployment is 5 percent to 5.2
percent.
1
While unemployment rates can dip below
that for a short period of time, it will rise again even
in a stable or growing economy due to workers
leaving jobs or entering the labor market. We there-
fore used the natural rate of unemployment as the
most ambitious unemployment rate this Study could
help St. Lawrence County achieve.
b. The unemployment rate is contingent on both the
number of people employed and labor-force size.
Over the past decade, St. Lawrence County’s overall
labor force has declined by 0.4 percent per year.
So, if St. Lawrence County’s labor force shrinks or
remains steady, but this eort helps the County
create jobs, there must be a theoretical maximum on
the number of jobs that can be filled. This theoret-
ical maximum, over five years, is around 1,700. To
ensure employment predications do not dramatical-
ly exceed this maximum, we applied a 40 percent
discount to the projections, resulting in total jobs
added to a maximum of 1,900. This would allow for a
slight rise in the labor force due to implementation of
these strategies (e.g., inward migration, improvement
of the labor force participation rate).
4. GDP and job growth correlation: GDP is a product of the
number of employees and average productivity. If the
number of people employed grows, GDP must grow
as well. Due to this correlation, we applied the same
40 percent discount to GDP impact as we did to
expected jobs.
1 http://www.federalreserve.gov/faqs/economy_14424.htm
(discussed below) and industry benchmarks. In this case,
applying the value-added multiplier was unnecessary.
However, sources of data for both dairy productivity and
annual tourism spend were in sales. So, once we deter-
mined potential added agriculture sales due to increased
dairy productivity and added tourism sales due to imple-
mentation of the Revitalization Fund, we applied the
corresponding industry-specific RIMS II value-added
multipliers to determine GDP.
Employment and GDP
In calculating direct jobs and GDP added by these initia-
tives, we first determined which metrics, informed as much
as possible by direct, objective data for St. Lawrence
County, regional and national peer counties, and industry
benchmarks where available, were the most indicative for
current and future direct employment and GDP figures in a
given industry. We then compared St. Lawrence County’s
current status, either on an absolute or per capita basis as
well as using historical and projected compound annual
growth rates (CAGR) where available, to regional and/
or national peer county best in class and industry bench-
marks. Doing so informed the level of success possible for a
given initiative. Where appropriate and necessary, we used
assumptions (e.g., the number of commercial-scale green-
houses St. Lawrence County might attract over a five-year
period or each class size of entrepreneurs included in the
Entrepreneur Accelerator) that were rigorously tested with
internal, external, and St. Lawrence County subject matter
experts. For each initiative, we then set conservative and
aspirational employment and GDP creation goals based on
realistic levels of success.
Finally, bottom-up estimates of jobs and GDP impact
numbers were discounted by 40 percent at the strategy
level (which aggregated up to an equivalent reduction
overall) due to the following factors:
1. Potential overlap among initiatives: in a number of instanc-
es, added jobs or GDP could be claimed by two initiatives.
For example, jobs created under Manufacturing Workforce
Development training could also be claimed in a growing
business whose owner received training under the Small
Business Entrepreneur Accelerator. Another example
could be businesses created through funding provided by
the Revitalization Fund, but which also received help from
the Main Street Small Business Concierge service.