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Wage Disparity in Canada

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Gary Champman

on 13 January 2014

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Transcript of Wage Disparity in Canada

Inspiration & Significance
Average earnings notwithstanding, the gap between Ontario and Quebec incomes, both concerning median earnings and individuals earning the average income in Canada, is separated by mere thousands, concluding that there is NOT a significant relationship between province and income.
This idea struck me when comparing my internship income to a family member's income. During the time I'm still in my bachelor program, I will have a chance to earn an approximately equal amount as my family member. They have a master's degree and 30 years of field experience. The inequality intrigued me and I began my research.
Based on my observations, income increases do NOT directly translate in the reduction of differences between wages.

Examining ages, ages 45-54 dominate the higher wage rate, with 50% of individuals earning $100 000+ from 2001-2011. All age groups with employees earning under $5000 decrease at a negative and moderate to strong rate. However, with each age group decreasing at approximately the same rate, the gap has not been reduced. For earners of $35 000 and over, the data is extremely spread out, though it is evident more individuals from ages 35-54 earn the median wage in Canada compared to individuals in the 25-34 age group. Therefore, as age increases, so does an individual’s income. In terms of income gap between age groups, it is inert as higher salaries are earned by experienced individuals, not those fresh in the job industry.

Examining gender, men’s average total income skews positively towards an income above their average income of $53 327.27, women’s total income skews negatively down their $25 936.36 income. Both sex’s median income have no particular frequency shift over 10 years, leaving women financially inconsequential in the face of male incomes, a difference of approximately $20 000. Males and females earning over $60 000 each have a strong, positive, linear correlation. This highlights my thesis that even though wage is increasing, the gap remains the same, as the incomes are expected to be equal in 2071, an unmerited amount of time.

Examining provinces, average earnings in Ontario are weakly declining while they are moderately increasing in Quebec. This is the only indication of wage gaps among provinces. The average median earnings in both provinces are approximately the same, as well as the percentage of individuals earning $30000-$34999.

In conclusion, while incomes grow, the space between age and gender equality is neutral. In addition, inflation has no effect on the relation, as throughout the process measures of central tendency augmented and lowered among the decrease in Canadian inflation.
Topic Conclusion
Wage Disparity in Canada
By: Gabriel Chapman

As income increases in Canada, the difference between wages remains the same.
I believe the main cause of income increase is inflation, therefore though earnings may rise, so will the price of daily life, counteracting the effect.

Wage (in)equality in Canada.
The relationship between income gaps and income increases.

What is the relationship between age and income?
What is the relationship between gender and income?
What is the relationship between province and income?

Bring attention to the social injustice in Canada
Inspire policy review in the government
Data obtained for the purposes of this research project is secondary, meaning it was gathered by a source outside the myself, the researcher. Data was collected from Statistics Canada from sections of “The Census of Population.” The data compilation process, according to Statistics Canada (2012), involved gathering “demographic and linguistic information on every man, woman and child living in Canada.” Conducted in May, “the census is the main source of data available in a standardized format for small areas. It provides nationally comparable data [as] the main body of comprehensive statistical data at the sub-provincial level on Canada's population.”
Employed individuals in Canada from 2001 to 2011, ages 25-54

Independent Variable:
Year/Time (Quantitive, continuous)

Dependent Variable:
Number of Workers (Quantitive, discrete)
Distributed by
By mail
Personal interviews

Specialized to the accessibility of the individual.

Bias Possibilities
Distant, rural areas
Disadvantaged Canadians (Homeless)
Language and literacy barriers for Canadians of different cultural or educational backgrounds.
Avoiding Bias
Ages 25-34:
Mean = 87 744 people
Median = 83 460

Ages 35-44:
Mean = 275 208
Median = 274 790

Ages 45-54:
Mean = 363 220
Median = 364 270

For individuals earning $100,000 or more:
• Ages 25-34 had a stagnant percentage
• Ages 35-44 had a slight decrease in percentage
• Ages 45-54 increased in the number of individuals earning a high salary
• The large gap between the average number of individuals in each age group can be attributed to the field experience and reputation that each group provides
• Younger individuals with less experience earn less, and older individuals with expanded experience earn more.
Each line has a strong, negative correlation.
In all ages, Canadians earning $5000 or less are lowering in numbers
The reaction of this effect is the individuals rise into different income brackets, making the shift better in terms of salary, but not in terms of lowering the gaps between each income bracket.
Ages 25-34:
s= 261 179.22
Q1 = 1 333 750
Q3 = 1 824 790
IQR = 491 040
Min = 1 252 950
Max = 1 982 300
Ages 35-44
s= 130 380.32
Q1 = 2 170 460
Q3 = 2 240 500
IQR = 70 040
Min = 2 117 830
Max = 2 484 560
Ages 45-54:

s= 339 665.69
Q1 = 2 113 030
Q3 = 2 764 150
IQR = 651 120
Min = 1 934 640
Max = 2 867 060
Ages 25-34:
Positively skewed, and has a smaller number of individuals earning more than the median Canadian worker, according to Grant and Curry (2013).
Ages 34-44:
Positively skewed, and has a smaller IQR than the other age groups. Contrarily, many more individuals in this age range earn $35 000 or more.
Ages 44-54:
Negatively skewed. Data demonstrates it is more common in higher age to earn a stable income, which affects the position of the median (closer to the 75th quartile of the box-and-whisker plot).
• With interquartile range not even exceeding a million, workers in different age groups have a low range but a high spread of people earning $35000 or more.
and over
and over
and over
Palpably, as age increases towards retirement, so does one’s income. This trend was to be expected as with age comes skill, status and job steadiness. The promotions within workplaces still do not contribute to more equal incomes between the three age groups.
Employed individuals in Canada from 2001 to 2011

Independent Variable:
Year/Time (Quantitive, continuous)

Dependent Variable:
Income (Quantitive, continuous)
Number of Workers (Quantitive, discrete)

• The
distribution is positively skewed, as the mean is on the right of the peak. Men make generally more than $53 000, the median.

• The
distribution is negatively skewed, as the mean is on the left of the peak. Women generally make less than $35 700, in close proximity of the median Canadian income, per Grant and Curry (2013).

• Men’s measures of central tendency dwarf those of women, and are showing a trend to continue that growth while women are fixed in their unnecessary income inferiority.

Each graph has a uniform distribution, because each outcome has a similar frequency.

Since the median total incomes show no particular frequency shift, women remain in a lower salary bracket than men.
Each line has a strong, positive correlation

Women's salaries seem to be on a sharper incline

The Point Of Intersection determines that the lines will meet midway in 2071, almost 60 years in the future.

Equality in a developed nation should not be that unhurried.
From the data provided, I can conclude that even with both gender’s measures of central tendency and revenue rising, men maintain an unflinching salary superiority.
Employed individuals in Ontario and Quebec from 2001 to 2011

Independent Variable:
Year/Time (Quantitive, continuous)

Dependent Variable:
Income/Earnings (Quantitive, continuous); Number of Workers(Quantitive, discrete)
• Ontario has an extremely low r-value, it is not necessarily representative. Nonetheless, there is a weak, negative trend, though providing the mean of $42 400 would be more accurate of Ontario’s residents average earnings.

• Quebec has a moderate, positive correlation. At its current rate, it is expected to match Ontario's income in 2041.

• Although the average earnings are trending in opposite directions, with one chart containing a very weak correlation, the data is inconclusive.
Yet, the Point Of Intersection for equal average earnings is still much too far away.
- Quebec has a uniform distribution, as each outcome has a similar frequency, with a mean of $27 700.
- Ontario has a U-shaped bimodal distribution, with peaks at both ends of the range. There could be an argument that it is uniform as well. Ontario's mean is $31 645.46.
- Median earnings distribution in both provinces produces no indication of change, keeping the gap between them small but still existent.
Quebec -
Negatively skewed, extreme values closer to negative end, mean on the left of the peak.

Ontario -

Median located to left, however data is positively skewed (where extreme values are closer), with the mean on the right of the peak

The middle of each population has 40% of its employees earning $30 000-$34 999, approximately the average wage in Canada. Quebec has a higher percentage of workers earning the average wage in Canada, however since it is negatively skewed and Ontario is the opposite, the distance between average wages is not conclusive enough for a relationship.
Issues With The Data
- Breathe a sigh of relief, you have reached the end of this magical journey we have shared together. Thank you for listening.

Mrs. MacDonnell
- Please continue with the presentation to view my bibliography. Appendixes have been sent as a separate document, as well as my summary.
Response/Non-response bias:
Distant and rural areas, disadvantaged citizens or those suffering from language and/or literacy barriers might not return their questionnaire or lack understanding of the questions.
Sampling Bias:
The large standard deviations in the Age Groups for Income of $35 000 could possibly fail to accurately represent the population.
General bias:
My manipulation of the data and the charts involved my unintended influence on the data-gathering methodology.
For follow-up/modifications, I suggest the following:

a larger time frame in order to make a stronger forecast on wage disparity

more income groups and examine more provinces to broaden the concept of wage disparity

the scales in order to put multiple sets on data on the same plane in order to make easier comparisons

studies would include income disparity between provinces and territories, as well as exploring the role of social class on income

Deleting all footnotes from Statistics Canada
Altering scales of the charts to better demonstrate income gaps
Putting Fathom charts on Prezi. I had to save each graph as a picture, then insert on to my presentation

Statistics Canada. (2012). Overview of the Census of Population. Retrieved January 5, 2014, from http://www12.statcan.gc.ca/census-recensement/2011/ref/overview-apercu/pop1-eng.cfm#int2

Statistics Canada. (2013) Table111-0008 - Neighbourhood income and demographics, taxfilers and dependents with income by total income, sex and age group, annual. Retrieved on December 14, 2013, from CANSIM (database).

Statistics Canada. (2013). Table202-0101 - Distribution of earnings, by sex, 2011 constant dollars, annual. Retrieved on December 14, 2013, from CANSIM (database).

The Globe and Mail. (2013). The wealth of the nation: A snapshot of what Canadians earn. Retrieved January 4, 2014, from http://www.theglobeandmail.com/news/politics/who-are-the-1-per-cent-a-snapshot-of-what-canadians-earn/article14269972/?page=all

Trading Economics. (2013). Canada Inflation Rate. Retrieved January 11, 2014, from http://www.tradingeconomics.com/canada/inflation-cpi

0.271x – 515.4 = 0.510x – 1010.5
-0.239x = -495.1
x = 2071.55

-60.9x + 164 600 = 134.55x – 234 300
195.45x = 398 900
x = 2040.93

Mode : 38 500 females, 52 000 males
Mean : 25 936.36 females, 53 327.27 males
Median : 35 700 females, 53 000 males
s= 0.3330
Q1= 5.2
Q3= 5.6
IQR= 0.4
Min= 4.9
Max= 6
s= 0.2611
Q1= 6.4
Q3= 6.8
IQR= 0.4
Min= 6.1
Max= 6.9
Full transcript