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1.Choose one of the three EDA approaches reviewed in class.

2.What is the concept you are trying to measure?

3.List the variables you believe are potentially measuring this concept.

4.Conduct your EDA analysis – include printout

5. What can you conclude about your variables and how your concept can be best measured?

Unemployment Definition and Measurement

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).

Geographical region

Unemployment rate

St. John's, Newfoundland and Labrador

9.4

Newfoundland and Labrador

18.5

Charlottetown, Prince Edward Island

6.8

Prince Edward Island 

11.7

Eastern Nova Scotia

15.8

Western Nova Scotia

7.4

Halifax, Nova Scotia

6.7

Fredericton-Moncton-Saint John, New Brunswick

6.6

Madawaska-Charlotte, New Brunswick

7.7

Restigouche-Albert, New Brunswick

12.0

Gaspésie-Îles-de-la-Madeleine, Quebec

15.8

Quebec, Quebec

3.9

Trois-Rivières, Quebec

4.6

South Central Quebec

3.1

Sherbrooke, Quebec

3.9

Montérégie, Quebec

4.6

Montreal, Quebec

6.3

Central Quebec

6.2

North Western Quebec

6.5

Lower Saint Lawrence and North Shore, Quebec

7.3

Hull, Quebec

4.5

Chicoutimi-Jonquière, Quebec

6.5

Ottawa, Ontario

4.6

Eastern Ontario

5.4

Kingston, Ontario

5.5

Central Ontario

6.2

Oshawa, Ontario

5.5

Toronto, Ontario

6.1

Hamilton, Ontario

5.2

St. Catharines, Ontario

7.5

London, Ontario

5.3

Niagara, Ontario

8.1

Windsor, Ontario

7.6

Kitchener, Ontario

4.7

Huron, Ontario

5.4

South Central Ontario

4.1

Sudbury, Ontario

6.4

Thunder Bay, Ontario

4.9

Northern Ontario

10.6

Winnipeg, Manitoba

6.2

Southern Manitoba

6.6

Northern Manitoba

31.6

Regina, Saskatchewan

6.1

Saskatoon, Saskatchewan

7.3

Southern Saskatchewan

7.5

Northern Saskatchewan

19.7

Calgary, Alberta

8.3

Edmonton, Alberta

6.4

Northern Alberta

10.6

Southern Alberta

6.8

Southern Interior British Columbia

7.7

Abbotsford, British Columbia

5.0

Vancouver, British Columbia

4.6

Victoria, British Columbia

4.7

Southern Coastal British Columbia

6.2

Northern British Columbia

9.4

Whitehorse, Yukon

3.0

Yukon 

6.2

Yellowknife, Northwest Territories

3.2

Northwest Territories 

11.8

Iqaluit, Nunavut

6.4

Nunavut 

18.1

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.

Employment Disparities Among Canadian Regions

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.

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.

Univariate analysis was conducted for the two variables independently for descriptive statistics.

Jobs/unemployment concern

Frequency Table

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

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.cc

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

There was a total of 3000 respondents from the five regions of Canada. The Atlantic region with 231 respondents representing 7.7% had the least number of respondents while the Ontario region with1140 respondents representing 38% had the highest number of respondents. The standard deviation of the regional responses is 1.117 implying low variability of the data.

Relationship between region and unemployment concern 

Descriptive Statistics

QA2A REGION (FROM PROVINCE)

N

Minimum

Maximum

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.

Research Question and Hypotheses

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;

A scatter plot for region against concern on unemployment is non-linear therefore we proceed to perform a correlation analysis to check for relationship between region and unemployment concern.

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.

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

Buettner, T. (2007). Unemployment disparities and regional wage flexibility. comparing EU members and EU-accession countries, 11.

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.

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.

Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2019). Unemployment Concern Across Canadian Regions: A Comparative Study. Retrieved from https://myassignmenthelp.com/free-samples/coms-3001-regional-orientation-and-unemployment-concern.

"Unemployment Concern Across Canadian Regions: A Comparative Study." My Assignment Help, 2019, https://myassignmenthelp.com/free-samples/coms-3001-regional-orientation-and-unemployment-concern.

My Assignment Help (2019) Unemployment Concern Across Canadian Regions: A Comparative Study [Online]. Available from: https://myassignmenthelp.com/free-samples/coms-3001-regional-orientation-and-unemployment-concern
[Accessed 29 February 2024].

My Assignment Help. 'Unemployment Concern Across Canadian Regions: A Comparative Study' (My Assignment Help, 2019) <https://myassignmenthelp.com/free-samples/coms-3001-regional-orientation-and-unemployment-concern> accessed 29 February 2024.

My Assignment Help. Unemployment Concern Across Canadian Regions: A Comparative Study [Internet]. My Assignment Help. 2019 [cited 29 February 2024]. Available from: https://myassignmenthelp.com/free-samples/coms-3001-regional-orientation-and-unemployment-concern.

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