Analysis of Regional Orientation and Unemployment Concerns in Canada

This report investigates the relationship between regional orientation and unemployment concerns in Canada, using statistical analysis to analyze the data and draw conclusions. The study utilizes data from Statistics Canada to compare the unemployment concern views of individuals from different Canadian regions, including Atlantic, Quebec, Ontario, Prairies, and British Columbia. The research employs both univariate and bivariate analysis, with the independent variable being region and the dependent variable being unemployment concern. The findings reveal that the level of unemployment concern is not significantly influenced by the region one comes from. The report concludes that while a majority of individuals express concern about unemployment, there is no statistically significant disparity in these concerns across different regions of Canada. The study also recommends further research to identify factors that influence the level of concern on unemployment, and also highlights the need for the government to create more employment opportunities in order to reduce unemployment rates.

A REPORT ON THE RELATIONSHIP
BETWEEN REGIONAL
ORIENTATION AND
UNEMPLOYMENT CONCERN

Introduction
• Unemployment refers to the scenario where when one who is actively looking for employment fails to find a
job (Krasnoperova V. V., 2013). Unemployment rate is an often used measure of unemployment (Campolieti,
The Canada-US Unemployment Rate Gap, 2012). It is found by dividing the number of the unemployed
people by the total number of people in the labor force.
• The aim of this report is to compare the unemployment concern views of individuals from different Canadian
regions and to highlight possible similarities or differences on these concerns.
• According to statistics Canada, the unemployment rate in Canada for October 2018 is at 5.9%. However,
though the employment rate is quite small, there exist employment disparities among the regions or provinces
of the country (Morley Gunderson, 2000). These disparities could be attributed to such factors as education
(Larsen, 2003). Regions with high number of educated people will have a large number of people in the labor
force whereas regions with low number of uneducated people will consequently have a low number of people
in the labor force. The magnitude of these disparities tends to differ from region to region (N.
GROENEWOLD, 2008).
• Previous research has suggested that unemployment rate in Canada has gradually been falling (Campolieti,
The ins and outs of unemployment in Canada, 1976–2008, 2011). Employment has mainly increased in
Ontario and Colombia, but in Quebec and other provinces it has remained almost unchanged, suggesting that
indeed employment disparity exists (Paul Beaudry, 2000). These disparities are clearly depicted in table.
• Employment disparities could be attributed to factors such as regional economic recessions in the country
which could occur due to provincial exposure to different industries that are affected by different variables
(Suedekum, 2005).
• These economic declines are normally accompanied by negative effects such as higher unemployment
(Santalahti, 2012).

• Theoretically, in a country characterized by absence of adjustment costs and rigidities, inequalities in
unemployment rates across provinces would not be expected to persist as it is thought that excess labor in one
location would move to other locations with higher unemployment rates (Buettner, 2007). However, this is
not true. Regions with high unemployment tend to suffer high unemployment rates in times to come, while
regions with low unemployment rates tend to experience low rates in subsequent times.
• In this study we purpose to understand the responses of the individuals that were studies on their concerns
with respect to unemployment.
• We also try to establish whether the distribution of responses was influenced by regional distribution of the
sampled population.

Research question
The following research question guided the study;
What is the relationship between region one comes from and unemployment concern? Are people from certain regions
more concerned about unemployment than those from other regions? Our study tried to answer this research question.
Hypothesis
The null and alternative hypotheses based on the research question are:
H0: Level of concern on employment is the same for all the regions.
H1: Level of concern on employment is not the same for all regions.
Statistical methods
The analysis contained in this report relies on the political landscape data. Analysis was done using SPSS.
Since we sought to determine whether there exists a relationship between regions and concern on unemployment, the
variables of interest from the dataset were;
QB2.10 (unemployment concern), and;
QA2A (region)
The independent variable is QA2A(region) whereas the QB2.10(unemployment concern) is the dependent variable.
Univariate and bivariate analysis shall be conducted on the regions and unemployment concern variable. Univariate
analysis shall be used to describe the two variables independently using descriptive statistics.
Bivariate analysis shall be used to examine empirical relationships between the two variables, regions and unemployment
concern.

QB2.10 CONCERN: Jobs/unemployment
Frequency Percent Valid Percent
Cumulative
Percent
Valid 0 - Not at all concerned 56 1.9 1.9 1.9
1 23 .8 .8 2.6
2 41 1.4 1.4 4.0
3 71 2.4 2.4 6.4
4 101 3.4 3.4 9.7
5 320 10.7 10.7 20.4
6 318 10.6 10.6 31.0
7 490 16.3 16.3 47.3
8 571 19.0 19.0 66.4
9 376 12.5 12.5 78.9
10 - Extremely concerned
595 19.8 19.8 98.7
Don't Know 38 1.3 1.3 100.0
Total 3000 100.0 100.0
Results
Univariate analysis
Univariate analysis was conducted for the two variables independently for descriptive statistics.
Jobs/unemployment concern
Frequency Table

The level of employment concern was represented on a scale from 0 to 10 with 0 being not at all concerned and 10 being extremely concerned.
The lower the scores the lower the level of concern on unemployment, the higher the score the higher the level of concern on unemployment.
Score 0 had the least number of respondents representing 1.9% while score 10 had the highest number of respondents representing 19.8%. This
implies that the least number of respondents were not at all concerned about unemployment while the highest number of respondents were
extremely concerned about unemployment.
QA2A REGION (FROM PROVINCE)
Frequency Percent Valid Percent Cumulative Percent
Valid Atlantic
231 7.7 7.7 7.7
Quebec
727 24.2 24.2 31.9
Ontario
1140 38.0 38.0 69.9
Prairies
504 16.8 16.8 86.7
BC
398 13.3 13.3 100.0
Total
3000 100.0 100.0
Region

Bivariate analysis
Relationship between region and unemployment concern
Descriptive Statistics
QA2A REGION (FROM PROVINCE) N
Minimu
m
Maximu
m Mean
Std.
Deviation
Atlantic QB2.10 CONCERN:
Jobs/unemployment 231 .00 11.00 7.5974 2.11368
Valid N (listwise) 231
Quebec QB2.10 CONCERN:
Jobs/unemployment 727 .00 11.00 6.9381 2.51174
Valid N (listwise) 727
Ontario QB2.10 CONCERN:
Jobs/unemployment 1140 .00 11.00 7.4965 2.14795
Valid N (listwise) 1140
Prairies QB2.10 CONCERN:
Jobs/unemployment 504 .00 11.00 7.6448 2.30714
Valid N (listwise) 504
BC QB2.10 CONCERN:
Jobs/unemployment 398 .00 11.00 6.9899 2.33361
Valid N (listwise) 398
On splitting the regions and performing descriptive analysis, we obtain the above table.
Atlantic region’s concern of unemployment is about 7.60, Quebec is about 6.94, Ontario about 7.50, Prairies about 7.64 and BC about 6.99. The standard
deviations are about 2.11, 2.51, 2.15, 2.31 and 2.33 respectively for Atlantic, Quebec, Ontario, Prairies and BC respectively. This implies that the concerns
on unemployment are spread within about 1 standard deviation on either side of the means.
The means and standard deviations of concern on unemployment do not explain much about the relationship between region and unemployment concern
since the means and standard deviations do not have much variation.
We conduct a correlation analysis to have a clear insight on the relationship between the two variables and the following results obtained;
Scatter plot

Correlations
QA2A REGION (FROM
PROVINCE)
QB2.10 CONCERN:
Jobs/unemployment
QA2A REGION (FROM PROVINCE) Pearson Correlation 1 .006
Sig. (2-tailed) .725
N 3000 3000
QB2.10 CONCERN: Jobs/unemployment Pearson Correlation .006 1
Sig. (2-tailed) .725
N 3000 3000
The Pearson correlation coefficient between region and concern on employment is 0.006 and the p-value is 0.725.
The Pearson correlation coefficient implies that there is a weak positive relationship between the region from where
one comes and unemployment concern.
The p-value is greater than 0.05 indicating a weak evidence against the null hypothesis, so we fail to reject the null
hypothesis. Therefore, we cannot conclude that region is a factor influencing concern on unemployment. Thus, the
regions of Atlantic Quebec, Ontario, Prairies, BC have indifferent concern on unemployment.

Conclusion
• Univariate analysis conducted indicated that people who were not at all concerned about unemployment had
the least number of responses while those who were extremely concerned had the highest number of
responses. We can therefore conclude that majority of people in the society are concerned about
unemployment.
• The bivariate analysis conducted have shown that a person’s concern on unemployment is not influenced by
the region the person comes from. Thus, there is no variation in people’s concerns on unemployment based on
the regions they come from.
• The study fails to reject the null hypothesis and disqualifies our alternative hypothesis that there exists a
relationship between regional orientation and concern on unemployment.
Recommendations
• Since it has been found out that majority of people in society are concerned about unemployment, there is
need for governments and states to create more employment opportunities in order to reduce unemployment
rates.
• Based on the study results and conclusions, there is need for further research to identify factors that influence
level of concern on unemployment.

References
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• Campolieti, M. (2011). The ins and outs of unemployment in Canada, 1976–2008. 19.
• Campolieti, M. (2012). The Canada-US Unemployment Rate Gap. A New Look with a New Decomposition for
Cross-Country Differences in Unemployment Rates, 25.
• Krasnoperova V. V., M. Y. (2013). Unemployment among young people. 2.
• Larsen, C. A. (2003). An analysis of recruitment and selection mechanisms based on panel data among Danish
long-term unemployed. 12.
• Morley Gunderson, A. S. (2000). Structural Aspects of Unemployment in Canada || Youth Unemployment in
Canada, 1976-1998. 17.
• N. GROENEWOLD, A. H. (2008). REGIONAL UNEMPLOYMENT DISPARITIES. AN EVALUATION OF
POLICY MEASURES, 21.
• Paul Beaudry, T. L. (2000). Structural Aspects of Unemployment in Canada. What Is Happening in the Youth
Labour Market in Canada?, 26.
• Santalahti, P. N. (2012). Children of the recession study I. Are there long-term effects of economic recession?, 1.
• Suedekum, J. (2005). Increasing returns and spatial unemployment disparities. 23.