Today the
Ontario Federation of Labour and
CUPE Ontario
published calculations I prepared of how Ontario Conservative leader
Tim Hudak’s promise to eliminate 100,000 public sector jobs will be felt
at the local level, on cities and communities across the province.
The original
OFL release
provides info on the magnitude of these impacts for the 15 largest
census metropolitan areas across Ontario, for which labour force
survey figures are available, a
second release has the impacts for smaller communities, while CUPE Ontario has put a
map on-line
that shows the impact for all the metro areas and a number of smaller
cities and towns (or “census agglomerations”). Below I include some
details on how the numbers were calculated and provide the impacts for
the full list of communities.
These job cuts–
more extreme than under Mike Harris–would be devastating for many communities. As I outlined in a
previous post,
if the elimination of 100,000 public sector jobs plus the spin-off jobs
led to an equivalent increase in unemployment, Ontario’s unemployment
rate would
reach 9.7% (based on an increase from current rates)– the highest in 20 years.
But the impacts would be even greater for particular communities.
What this analysis shows is if public sector jobs are eliminated
proportionally, the impacts would be especially severe for mid- and
smaller-sized cities and towns in the province–and could lead to
double-digit unemployment rates in many.
For example, if the cuts were implemented proportionately, Kingston
could see an increase in its unemployment rate by 3.8 percentage points
up to 10.2%; Peterborough up by 3.2% to 14.8%; Oshawa up by 2.9% to
9.9%; Guelph up by 3.2% to 10.4% and Greater Sudbury up 3.2% to 9.4%.
This is because, perhaps contrary to the perception of many, public
sector employment actually tends to be proportionally higher in mid- and
smaller cities than in larger cities. These public sector jobs are
also an important source of economic stability in these communities
because the jobs are more stable and are decently, or at least
more equitably,
compensated. The cruel irony is that the smaller cities and towns
that are often a base of Conservative strength would be most damaged by
the deep cuts Hudak is planning.
The impacts of public sector job cuts of this magnitude would be at
odds with the way Hudak and his Conservatives are trying to sell them:
as cutting “
100,000 jobs in the bureaucracy” that would have little impact on front-line services or local communities.
The reality is the large majority of public sector workers are front-line workers. According to
Statscan data
over 400,000 Ontarians work in education (locals schools, universities,
colleges and trades schools); about 236,000 work in health care and
social services (hospitals, community clinics, residential care); about
275,000 for local governments; and about 40,000 for provincial crown
corporations such as Hydro, the LCBO etc.
In fact, there were only ~90,000 employed in the core provincial
public service. This includes the classic government worker or
“bureaucrat” that Hudak loves to disparage, but it also includes many
others, including provincial police, judicial employees, and those
working for agencies, boards and commissions.
So there’s no question: the cuts Hudak would implement would result
in significant cuts to front-line public services and would have a major
impact on communities across the province. Even prominent conservative
columnist Tasha Kheiriddin (formerly director with the Fraser Institute
and Canadian Taxpayers Federation)
recently wrote she won’t vote for Hudak because she realizes he will cut public services her autistic daughter needs.
(While Hudak claims only private sector jobs create wealth, private
sector industries and companies can often be more bureaucratic with
higher administration costs than the public sector. For example
administrative costs in the US private health care system are
about three times the administration costs in Canada’s largely public system).
How these job impact figures were calculated
These figures are based on the most detailed employment by industry
and occupation figures that are readily (and freely) available for
communities in Canada: data from the National Household Survey (NHS).
From this I calculated employment in public sector industry groups at
the four-digit (most detailed) level for the 48 “Census Divisions”
(CDs) in Ontario (from NHS Table 99-012-X2011052) and separately for
the 42 different Census Metropolitan Areas (CMAs) and smaller Census
Agglomerations (CAs) (from NHS table 99-012-X2011034).
16 different industry groups at the 4-digit level were included, with
most of the employment from these in education, health care and social
services and public administration, but excluding employment in federal
and aboriginal public administration. However, I included in
this local, regional and municipal public administration because Hudak
was reported as saying he would also force municipalities to cut jobs.
From these totals of provincial and municipal broader public sector
employment by community, I subtracted the NHS figures for employment of
nurses, doctors and police officers (commissioned and non-commissioned)
(From NHS tables 99-012-X2011051 and 99-012-X2011033) for each of these
communities as Hudak said these jobs wouldn’t be cut. This provided
net totals for the public sector workforce by community that would be
affected by these cuts.
This analysis assumed then that the cuts would be made proportionate
to these levels of public sector employment across the province. Hudak
hasn’t provided any other details on how specifically the cuts would be
implemented except to admit that they would definitely affect front-line
services and mean fewer teachers.
And because the loss of these direct jobs have multiplier effects
through the loss of their spending in the local community and beyond,
the total impacts also include an estimate of the spin-off effects on
private sector employment, using a multiplier of 0.67, as explained in
my
previous post.
The increase in the unemployment rates was calculated for the 15
Ontario CMAs for which Statistics Canada publishes Labour force Survey
figures using the April 2014 seasonally adjusted figures from Cansim
Table 282-0116.
These are of course estimates. No one knows what the
impacts ultimately will be, but they are the most accurate estimates I
could calculate based on the most detailed data readily available and
making reasonable assumptions. Hudak has of course built his campaign
around a claim that he’s going to create a million jobs through things
such as corporate tax cuts, etc. The credibility of those claims will
be the topic for a subsequent blog post.
The following two tables provide these results: the first for the 15
largest cities (Census Metropolitan Areas) for which labour force survey
data are available; and the second the public and private sector job
losses for all the larger cities (CMAs) as well as the smaller cities
and towns (CAs).
Estimated job losses and increase in jobless rate
from Hudak’s public sector job cuts for the 15 largest cities (CMAs) in
Ontario
|
City (CMA) |
Job losses
|
Increase in unemployment rate
|
Resulting jobless rate (based on April 2014 rate)
|
Ontario |
167,000
|
2.3%
|
9.7%
|
Ottawa |
11,159
|
1.9%
|
8.8%
|
Kingston |
3,333
|
3.8%
|
10.2%
|
Peterborough |
2,057
|
3.2%
|
14.8%
|
Oshawa |
6,134
|
2.9%
|
9.9%
|
Toronto |
62,892
|
1.8%
|
9.6%
|
Hamilton |
10,555
|
2.6%
|
9.0%
|
St. Catharines – Niagara |
5,301
|
2.5%
|
10.7%
|
Kitchener – Cambridge – Waterloo |
6,142
|
2.0%
|
8.8%
|
Brantford |
1,782
|
2.4%
|
9.4%
|
Guelph |
2,480
|
3.2%
|
10.4%
|
London |
7,116
|
2.7%
|
10.7%
|
Windsor |
3,964
|
2.4%
|
10.8%
|
Barrie |
2,547
|
2.2%
|
9.4%
|
Greater Sudbury |
2,785
|
3.2%
|
9.4%
|
Thunder Bay |
2,460
|
3.8%
|
9.6%
|
Estimated impact of Hudak public sector job cuts on Ontario cities and towns
|
City or town (CMA or CA) |
Public sector job cuts
|
Spin-off private sector job losses
|
Total job loss
|
% of provincial total job losses
|
|
|
|
|
|
Cornwall |
471 |
316 |
787 |
0.5%
|
Hawkesbury |
82 |
55 |
137 |
0.1%
|
Ottawa |
6,682 |
4,477 |
11,159 |
6.7%
|
Brockville |
322 |
215 |
537 |
0.3%
|
Pembroke |
231 |
155 |
386 |
0.2%
|
Petawawa |
60 |
40 |
100 |
0.1%
|
Kingston |
1,996 |
1,337 |
3,333 |
2.0%
|
Belleville |
686 |
460 |
1,146 |
0.7%
|
Cobourg |
150 |
101 |
251 |
0.2%
|
Port Hope |
155 |
104 |
258 |
0.2%
|
Peterborough |
1,232 |
825 |
2,057 |
1.2%
|
Kawartha Lakes |
716 |
480 |
1,196 |
0.7%
|
Wellington |
250 |
168 |
418 |
0.3%
|
Oshawa |
3,673 |
2,461 |
6,134 |
3.7%
|
Ingersoll |
99 |
67 |
166 |
0.1%
|
Toronto |
37,660 |
25,232 |
62,892 |
37.7%
|
Hamilton |
6,320 |
4,234 |
10,555 |
6.3%
|
St. Catharines – Niagara |
3,174 |
2,127 |
5,301 |
3.2%
|
Kitchener – Cambridge – Waterloo |
3,678 |
2,464 |
6,142 |
3.7%
|
Brantford |
1,067 |
715 |
1,782 |
1.1%
|
Woodstock |
263 |
176 |
439 |
0.3%
|
Tillsonburg |
86 |
58 |
144 |
0.1%
|
Norfolk |
452 |
303 |
755 |
0.5%
|
Guelph |
1,485 |
995 |
2,480 |
1.5%
|
Stratford |
256 |
171 |
427 |
0.3%
|
London |
4,261 |
2,855 |
7,116 |
4.3%
|
Chatham-Kent |
764 |
512 |
1,277 |
0.8%
|
Leamington |
271 |
181 |
452 |
0.3%
|
Windsor |
2,374 |
1,590 |
3,964 |
2.4%
|
Sarnia |
618 |
414 |
1,032 |
0.6%
|
Owen Sound |
330 |
221 |
551 |
0.3%
|
Collingwood |
133 |
89 |
222 |
0.1%
|
Barrie |
1,525 |
1,022 |
2,547 |
1.5%
|
Orillia |
293 |
196 |
489 |
0.3%
|
Midland |
310 |
207 |
517 |
0.3%
|
North Bay |
751 |
503 |
1,254 |
0.8%
|
Greater Sudbury |
1,668 |
1,117 |
2,785 |
1.7%
|
Elliot Lake |
78 |
53 |
131 |
0.1%
|
Temiskaming Shores |
134 |
90 |
223 |
0.1%
|
Timmins |
448 |
300 |
748 |
0.4%
|
Sault Ste. Marie |
808 |
541 |
1,349 |
0.8%
|
Thunder Bay |
1,473 |
987 |
2,460 |
1.5%
|
Kenora |
203 |
136 |
339 |
0.2%
|