six facts about how canadians spend their money

Spend Their $$$$$

Factsabout howFacts

D. RodicJ. Syed

6 Facts About How Canadians Spend their Money

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PRE FACE oney is no longer just paper and metal, but while it has transcended it’s physical boundaries

through credit cards, debit cards, and other forms of electronic valuation, it is still treated the same to

this day. Every two weeks when the pay cheque comes in the mail (or is deposited into a bank

account), a decision is made whether to spend the money, save the money, or generally, perform a

blend of the two extremes. As raises are given, promotions are earned, and jobs are changed, there

comes a change in the wages one earns from their job. With this study, we attempted to discover

how does a change in wages affect our spending habits? However, before delving into an answer, the

word “our” must be defined. What is true for the parts is not always true for the whole. Individuals

have their own unique spending habits paralleled with their personalities; however, a change in

wages has a distinct effect on the spending habits of society. It is this distinct effect that this study is

attempted to determine. The common thought is that as more money is accumulated, the more we

will spend. Although it may be true for the overall economy, the demand for each good or service

responds differently to the same change in wages. This study examines all sectors of the Canadian

economy and further subdivides them to see how different goods respond to a change in wages.

This type of study can only be done in capitalist or mixed-market economies as they are very

responsive to the demands of the consumer. Canada possesses a mixed-market economy, allowing

for capitalistic free market operations, while still retaining a level of government regulation derived

from a socialist economic system. Most developed countries operate under a mixed-market

economy, though countries like the United States cater to the capitalist end of the spectrum while

certain European countries tend towards the socialist side.

Within Canada, per capita wages vary by province, adding yet another facet to the spending

habits of the population. However, spending was not examined on a by-province basis as it would

have further complicated the study which already looks at over 10 – 15 different goods on a national

scale.

The data collected1 in this study spans 8 years, from April 1997 to April 2005 in monthly

increments. For each year, the months of April and October were used as benchmarks as they are

unaffected by holidays as well as being a transition months between seasons. This eliminated

considerable extraneous variables, opposed to choosing other months of the year. Since this data is

census data, there are no sampling techniques involved beyond simple data collection. Bias is also

eliminated as all the data used in the study are factual numbers. 1 The data was collected from Statistics Canada: http://www.statcan.ca/start.html ; the following tables were used: 382-0006, 281-0028, 080-0900, 326-0020, 079-0001, 079-0002, 051-0001, 379-0019, 326-0001, 111-0001, 080-0018, 380-0001, 303-0018, 027-0007

M


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GL OSS ARY The following terms are used frequently throughout the study and are required to fully

understand the explanations, and examples contained within this book.

CENSUS

The process of obtaining information about every member of a population

CONSUMER PRICE INDEX ( CPI )

A measure of prices produced by Statistics Canada on a monthly basis. The CPI measures the retail prices of a shopping basket of about 300 goods and services including food, housing, transportation, clothing and recreation. The index is weighted to reflect typical spending patterns. The change in a price index like the CPI is a measure of inflation. Increases in the CPI are also referred to as increases in the cost of living.

CORRELATION ( Correlation Coefficient )

Indicates the strength and direction of a linear relationship between two random variables. The strength is measured by a correlation coefficient known as the “r-value”. It is calculated as follows:

DEMAND

In economics, demand exists when a consumer has both the desire and ability to purchase a good or service. Demand is affected by the price of the good, level of income, personal tastes, the population, and government policies. The law of demand states that as the price of a good increases, the quantity demanded decreases. When studying sectors of the economy or countries, demand is referred to as aggregate demand, or the total demand of a population.

ECONOMIC INDICATOR

Economic indicators include various indices, earnings reports, and economic summaries, such as unemployment, housing starts, Consumer Price Index, Gross Domestic Product, retail sales, stock market prices, and money supply changes. They are used as a yardstick in measuring whether an economy is in a recession, or in a stage of prosperity. They are also used to predict future market conditions.

GOODS

Physically tangible objects that can be used to satisfy economic wants, including but not limited to food, shoes, cars, houses, books and furniture. Inferior goods are goods whose demand drops as the consumers’ income increases. An example would be microwavable meals. As people have more money, they can afford fresh food, and buy less frozen meals.


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GROSS DOMESTIC PRODUCT ( GDP )

GDP is the value of total production of goods and services in a country over a specified period, typically a year. How much GDP grows from one period to the next is an indication of a country's economic health. It is calculated as follows: GDP = Consumer Spending + Government Spending + Business Spending + (Exports – Imports)

OR GDP = C + G + I + (X-M)

INFLATION ADJUSTED

Using the CPI, prices can be inflation adjusted to account for a change in the overall price level which may increase or decrease the actual price of a good or service. Inflation is calculated as follows using the CPI:

100×−

=CPIYearBase

CPIYearBaseCPIYearCurrentInflation

This equation provides the inflation rate between a certain period of time. For example, to find the inflation rate between 1997 and 2005, the “Base Year CPI” is the CPI in 1997, while the “Current Year CPI” is the CPI in 2005. To adjust for inflation between this period, you would raise or lower the price of a good by the percentage yielded by the equation.

MIXED-MARKET ECONOMY

An economic system that incorporates aspects of more than one economic system. This usually means an economy that contains both private-owned and state-owned enterprises or that combines elements of capitalism and socialism. There is no one definition for a mixed-market economy since each country can have varying degrees of either privatized or centralized control depending on their values or political platforms.

PER CAPITA

Latin for Per Person; calculated by dividing a total by the population.

TRANSFER PAYMENTS

The transfer of revenues from rich or “have” provinces, to poorer or “have not” provinces, in an effort to stabilize their economies. Territories are not included; they have a separate fund.

SEASONALLY ADJUSTED

Data is adjusted to eliminate the impact of regularly occurring events due to the climate. There is no set calculation, however, a similar approach to inflation adjusting can be taken through the use of percentages.

WAGES

A compensation which workers receive in exchange for their labor.


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TABLE OF CONTENTS

F a c t 1

S p e n d , S p e n d , S p e n d … B u t o n W h a t ?

F a c t 2

T e r r i t o r i a l W a g e D o m i n a t i o n

F a c t 3

R i c h e r C o n s u m e r s D o e s N o t A l w a y s M e a n R i c h e r C o m p a n i e s

F a c t 4

E x p a n d i n g W a l l e t s & E x p a n d i n g S t o m a c h s ; a n I n t e r e s t i n g C o r r e l a t i o n

F a c t 5

M o n e y C a n ’ t B u y H a p p i n e s s , B u t G i v i n g i t A w a y M u s t H a v e i t ’ s B e n e f i t s

F a c t 6

B o o m o r B u s t ? W h e r e i s o u r E c o n o m y H e a d i n g i n t h e F u t u r e ?


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S p e n d , S p e n d , S p e n d … Bu t o n W h a t ?

Monthly Per Capita Spending Breakdown

74%

5%

1%

0%

1%

1%

4%

1%

0%

0%

11%

1%

1%

0%

27%

Other Food & Beverages Healthcare Jewellery Womens ClothingMens Clothing Furniture Sporting & Leisure Donations Automotive FuelCar Sales + Maintenance Housewares Tobacco Restaurants Spending of Project Study

Percentage Uses of Average Monthly Per Capita Wages ($1324.60)

Fig. 1

Figure 1 shows a breakdown of how, on average, monthly per capita wages are being spent by

Canadians. The green area represents all types of spending examined in this study. The chart shows

that “Car Sales + Maintenance” and “Furniture” expenses rank in the top 3 uses of wages in the

study along side “Food & Beverages”. Despite appearing as possible anomalies, it is in no way

surprising. Furniture and car purchases are large value purchases. While they are usually paid off in

lump sums, for the purposes of this study, these lump sums were extrapolated over a monthly period

which justifies their high percentages. Furthermore, cars require frequent maintenance. Depending

on the make and year of the vehicle, as well as the extent of the repairs, costs can reach the

thousands of dollars if not covered by warranty. Jewelry, despite being another large value purchase,

is not bought frequently enough by the average consumer, and so its cost is spread over a larger time

period. This data does not factor in the cost of shelter, or the amount invested by consumers as it was

unavailable. It is important to note that the wages used to calculate the per capita average were “pre-

tax” wages. Therefore, deductions according to the varying tax brackets were not considered in

Figure 1, or anywhere else throughout the study.

Fig. 1


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The chart in figure 1 shows that spending for

both men’s’ and women’s’ clothing are very

small. On average, men spend between $8 - $12

dollars on clothes a month while women double

that range, going from $18 - $25 per month.

While the difference between the two is

miniscule relative to total wages, its effect on

spending is profound. Since men spend a

smaller percentage of their budget on clothes,

their demand for clothes is less price

responsive, or inelastic. As their wages

increase, clothing becomes “cheaper” relative

to their income, but their demand for clothing

does not change significantly as evidenced by

the moderate positive correlation in figure 2. As

for women, they spend a larger portion of their

budget on clothing, and so their demand is

more price responsive than that of the men.

This is confirmed by the strong positive

correlation in figure 3. Figure 4 further proves

this theory as “Per Capita Furniture” sales has a

very strong positive correlation with per capita

wages while placing top 3 in expenses

examined in this study. Figure 5 shows

Sporting & Leisure expenses (includes sports

gear, entertainment electronics, Steven Segal

DVDs…etc.), having only a moderate positive

correlation with per capita wages as they only

account for 1% of expenses in the study.


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T e r r i t o r i a l Wage Dom ina t i on

Alberta_Monthly_Wages_Per_Capita

BC_Monthly_Wages_Per_Capita

Manitoba_Monthly_Wages_Per_Capita

New_Brunsw ick_Monthly_Wages_Per_...

Newfoundland_Monthly_Wages_Per_Ca...

Nova_Scotia_Monthly_Wages_Per_Capita

NWT_Nunavut_Monthly_Wages_Per_Ca...

Ontario_Monthly_Wages_Per_Capita

PEI_Monthly_Wages_Per_Capita

Quebec_Monthly_Wages_Per_Capita

Saskatchewan_Monthly_Wages_Per_Ca...

Yukon_Monthly_Wages_Per_Capita

0 500 1000 1500 2000 2500 3000

Collection 7 Box Plot

Despite the prosperous oil industry in

Alberta, the province does not take top

spot in monthly per capita wages. In fact,

it is a territory, the Northwest Territories,

which boasts the highest per capita

monthly wages. The Northwest Territories

houses some of Canada’s most valuable

commodities including ethical diamonds,

natural gas, and gold which have all

become backbones to our export industry.

Due to its low population, the NWT

possesses a per capita GDP of $97,9232

which would rank #1 in the world if it

were considered a country. Examining the box plot, it can be seen that the entire IQR of the NWT,

and 2/3 of the IQR of the Yukon is higher than that of Ontario. Whereas figure 3 shows Ontario as

one of the few provinces above the national per capita average wage, Ontario’s IQR is very

compressed compared to both Alberta and the NWT. This can be attributed to the nature of jobs in

the province. Although Ontario has its own forestry and mining industries, they are outweighed by

the booming service sectors in cities like Toronto, Niagara Falls, and Ottawa. Wages in that

industry are very similar across the board, which lends to the concentration around the median.

Provinces which rank above the

national average include B.C.,

Québec, Ontario, Alberta, as well as

the Yukon and Northwest Territories.

In terms of transfer payments, those

provinces are considered the “have”

provinces while the remaining 6 are

considered “have-not” provinces.

Québec barely surpassed the average.

Average Per Capita Monthly Wages By Province Between April 1997 - April 2005

1041.32

1202.31 1189.58

1353.59

1662.9

1284.34

1164.24

1782.53

1430.79

1864.25

2188.93

1094.44

0

250

500

750

1000

1250

1500

1750

2000

2250

2500

1Provinces

Ave

rage

Per

Cap

ita M

onth

ly W

ages

in D

olla

rs

NewfoundlandP.E.I.Nova ScotiaNew BrunswickQuébecOntarioManitobaSaskatchewanAlbertaB.C.YukonNWT & Nunavut

1324.60

Avg. Mth. Wages Per Capita: Canada

Fig. 3

2 http://www40.statcan.ca/l01/cst01/econ15.htm

Fig. 6

Fig. 7


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R i c he r Con sume r s Doe s No t A l wa ys Mean R i c he r Compan i e s

As our income increases, we are provided the

opportunity to buy a larger quantity or higher quality

goods and services. It is when we start purchasing the

latter that inferior goods come into play. Take this

hypothetical example. Imagine a living as a homeless

man. Every day you dig up old cigarettes from ash trays,

eat food in a soup kitchen, panhandle on the cold asphalt

and sleep in a tattered sleeping bag. But how would your

life change if you all of a sudden won the lottery? You

would buy cigars instead of used cigarettes, you would

eat at the finest steakhouses, and you could sleep in a 5-

star hotel. Due to an increase in income, the demand for

goods like cigarettes, and bowls of soup has decreased.

These are known as inferior goods. Even without an

example as extreme as that, our own economy possesses

its own inferior goods. Looking at figure 7 vs. figure 8,

the slope of the line of best fit in figure 7 is positive

opposed the negative slope in figure 8. This is because

figure 7 shows the correlation between wages and

spending on meat and poultry while figure 8 shows the

same correlation, but instead with frozen foods. With an

increased income, people are able to purchase fresh food

while leaving the frozen items behind. Looking at more

expensive goods, North American made trucks and

passenger cars (correlated with wages in figures 9 and

10 respectively), are also inferior goods as their demand

drops as wages increase. However, figure 11 shows a

strong positive correlation between cars produced in

Europe and wages, since they are luxury cars, and only

with a higher income can a consumer purchase such

expensive vehicles. The response of decreasing truck

Fig. 8

Fig. 9

Fig. 7

Fig. 10

Fig. 11


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sales to wages can be explained better than their 4-doored counter parts. As people earn more

money, they are most likely progressing out of jobs which require physical labour and transportation,

instead moving into a job which requires more mental activity. Trucks are used mainly in those types

of heavy labour jobs, and thus as wages increase, their demand will dwindle. Passenger cars are a

different story. The drop in demand for North American cars has nothing to do with unneeded

functionality, but everything to do with perceived quality. The same goes for North American car

companies versus those in Europe. This poses an intriguing problem; how do they market their

inferior goods so to capitalize on an increase in the level of income? As evidenced by figure 12,

having a large market share does not contribute to an increase in sales as North America controls an

overwhelming majority of the passenger car market.

Market Share of Car Companies in CanadaBy Average Monthly Sales From 1997 - 2005

73%

14%

13%

Units Sold: North American Passenger CarsUnits Sold: Japanese Passenger CarsUnits Sold: European Passenger Cars

The only solution is to start producing the good to which your consumers have fled to, and thus you

can capitalize on sales at all income levels. Although this solution would not work for North

American Car Companies since their loss in demand is based on quality, for food producers it is only

a matter of expansion. In figures 7 & 8, the Meat and Poultry producers are getting an increase in

sales due to higher wages, while the frozen food producers are experiencing heavy losses. If the

frozen food producers were able to expand, supplying fresh meat and poultry (e.g. President’s

Choice), they would be able to capitalize on sales from both markets.

Fig. 12


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Expanding Wallets & Expanding Stomachs; an Interesting Correlation

The aggregate demand for food has a strong

positive linear correlation with per capita wages.

Food on the whole is a necessity for survival,

however when breaking down the food and

beverage industry, there still exists a strong

positive correlation within both staple goods like

fruits and vegetables, and more ostentatious

goods like seafood, and bakery products. The only product which has a negative correlation is frozen foods, figure 8, which was examined in

Section 3. Figures 14 – 20 studies the demand for the aforementioned goods. It includes Meat and

Poultry, Seafood, Candy and Snack Foods, Meals in Restaurants, Bakery goods, Dairy Products and

Eggs, and both Alcoholic and Non-Alcoholic Beverages.

Fig. 13

Fig. 14 Fig. 15 Fig. 16

Fig. 17 Fig. 18 Fig. 19

Fig. 20 Fig. 21


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While all the graphs show strong positive correlations, there still exists a difference between the

correlations from graph to graph. Examining alcoholic (F.20) versus non-alcoholic beverages

(F. 21), the former possess a stronger correlation with wages. This is surprising as it is considered a

sin good. Traditionally, sin goods are less price responsive and thus are inelastic. Therefore the

correlation between wages and alcohol purchases should not be as high. However, since it factors in

all types of alcohol (liquors, wines, spirits and beers), certain types of alcohol (e.g. wines and

liquors). can be considered luxury goods. That means that as the price of the good rises, the demand

rises as well. While contradicting the law of demand, consumers sometimes perceive the quality of a

good to be higher than it really is based only on a higher price. It is this paradox which may

contribute to the positive correlation. Going by that trend, seafood (F.15), bakery goods (F.18), and

meals in restaurants (F. 17) are considered luxury goods as well as they have a high correlation

relative to the other graphs.


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More Money Can’t Buy Happiness; but Giving it Away Must Have its Benefits

1

2

3

4

5

6

7

Donors5200000 5400000 5600000 5800000 600000

Collection 6 Histogram

Charitable donations are not reserved for famous celebrities, and wealthy philanthropists. Giving

donations provides a double benefit, both psychologically, and financially. Psychologically, it

provides reassurance in ones life that they are stable enough to part with their money in an effort to

help the less fortunate, or further a cause one believes in. Financially, donors benefit from the ability

to write off charitable contributions on their tax return, thus lowering their overall taxable income.

Shown in red, the majority of donors in Canada are donating in between a per capita monthly wage

of $1325 to $1410.

01234567

AvgDonations_65

1234567

AvgDonations_25_34

0 400 800 1200 1600 2000

Collection 6 Histogram

As Canadians age, the amount they donate also increases. All donations given by those 65 and over

surpass the $1000 mark while those between the ages of 25 – 34, are capped at approximately $900.

This is can be attributed to a multitude of factors. Primarily, retirees usually have a large sum of

money saved up in RRSPs which can be now spent at their leisure. While many of these donations

are done out of good nature, it also provides the opportunity for the elderly to leave a legacy. With

sizeable donations, their name can ring synonymous with a colossal building, or an architectural

marvel. This is not a cardinal concern of those aged 25 – 34 years old.

Fig. 22

Fig. 24

Fig. 23


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Boom o r Bu s t ? Whe r e i s ou r E conomy Head i ng i n t h e F u t u r e ?

The data collected in this survey goes beyond reporting the spending habits of Canadians. It can also

be used to examine the current state of the economy, and can be extrapolated to predict future

economic outcomes. This is where the extended analysis of the study can be directed. Since this

report focused on spending, economic indicators like housing starts did not fit. However, there are

spending habits which mimic these indices. Below, in figure 25, there is a plot of housing starts

versus furniture sales spanning the time period of the data in this report; April 1997 – April 2005.

The furniture sales line is much smoother than that of housing starts; however, it does a very good

job of mirroring this benchmark economic indicator. It is one of the best economic indicators found

in this study. As more houses are built and purchased, furniture is required to fill these houses to

make them livable. Therefore an increase in the sales of furniture is a hint that the housing market is

also growing.

Housing Starts vs. Furniture SalesApril 1997 - April 2005

500000

600000

700000

800000

900000

1000000

1100000

1200000

1300000

Apr-97

Jul-9

7

Oct-97

Jan-9

8

Apr-98

Jul-9

8

Oct-98

Jan-9

9

Apr-99

Jul-9

9

Oct-99

Jan-0

0

Apr-00

Jul-0

0

Oct-00

Jan-0

1

Apr-01

Jul-0

1

Oct-01

Jan-0

2

Apr-02

Jul-0

2

Oct-02

Jan-0

3

Apr-03

Jul-0

3

Oct-03

Jan-0

4

Apr-04

Jul-0

4

Oct-04

Jan-0

5

Apr-05

Dol

lars

in T

hous

ands

100

120

140

160

180

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240

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280

Uni

ts in

Tho

usan

ds

Furniture Sales (Thousands $) Housing Starts (Thousands Units) Indicators like retail sales could be benchmarked against clothing, and sports and leisure sales, while

the GDP could be reflected by the use of Per Capita Wages using simple line graphs, similar to those

in figure 25. As mentioned above, these indicators can be used to predict the state of our future

economy. Using the house starts indicator, one can determine if an economy is heading towards

Fig. 25


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prosperity or a recession as the construction industry is one of the most sensitive industries to

economy fluctuations3. For example, an increase in housing starts means that there is an increase in

the population, as well as an increase in income to pay for the houses. Knowing this, one can safely

say that with all things remaining equal, the country’s GDP is on the rise. A higher population

provides more workers, and subsequently leads to an increase in production. These goods can then

be exported to other countries thus increasing our GDP as per the equation. Furthermore, if the

population has enough income to purchase a house, economic forecasters can predict with greater

certainty that spending overall will increase across the board. While this can cause inflation, if the

government reacts in time, through the control of taxes and interest rates they can curb the inflation

before it strikes. Using economic indicators such as housing starts allows the government to

anticipate problems before they arise, and continually stabilize the economy.

If our sources could have provided us with after-tax wages, monthly savings figures, and

monthly shelter costs, we could have given a more accurate representation of how the spending is

broken down. Savings would have been the most valuable statistic as we could have gone on to

calculates the marginal propensity to save versus the marginal propensity to spend. These valuable

economic tools would allow us to see what percentage on average our country saves as a society,

which could lead into studies on investments, or a further exploration of financially based economic

indicators.

ENDING NOTES…

From such a specifically targeted study, a lot of conclusions can be drawn about Canada’s

economy, and how we as Canadians spend our hard earned money. Despite the high cost of food and

automotive expenses, they only amount to 10% of our total expenses per month. While not examined

in the study, the bulk of our wages go to housing costs which includes rent/mortgages, hydro and

electricity. Further, there is a certain amount we save month to month to build a solid financial

foundation.

Surprisingly, the Northwest Territories placed above both the oil-rich province of Alberta,

and the commerce-driven province of Ontario in both provincial per capita GDP and provincial per

capita wages. The average monthly per capita wage in the Northwest Territories of $2188.93 is

almost double that of the Canadian national average of only $1324.60. The Northwest Territory’s

prosperity is derived from its seemingly limitless holdings of valuable commodities such as

diamonds, natural gas and oil.

3 Fisher, I (1932). Booms and Depressions. New York, New York: Greenberg.


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Looking at different sectors, this study revealed the existence of inferior goods in the

economy. The demand for these types of goods drop as consumer incomes increase. At the brunt of

this decrease in demand were North American Auto Producers (Chrysler, GM, and Ford) despite

having a near ¾ share of the passenger car market in Canada. Other companies that produce cheap

food alternatives, such as frozen food, canned meats or other processed meals also suffer from an

increase in wages as consumers can go on to purchase more fresh foods with their money lined

wallets. Companies like President’s Choice have been able to stave off losses from inferior goods as

they supply both fresh foods like meat and poultry, while still maintaining a distinguished presence

in the prepared foods market.

Probing deeper into the study of food consumption in the Canadian economy, it was

discovered that not only is their a strong positive correlation with “Food & Beverage” sales and per

capita wages on the whole, each segment of “Food & Beverages” has a similarly strong positive

correlation (except for frozen foods). The most intriguing item was alcoholic beverage sales. Despite

being considered a sin good, a good whose demand is very unresponsive to changes in price (and

thus should have a low correlation with wages), it actually presented the strongest correlation out of

all the “Food & Beverage” segments. We attributed this to the composition of alcohol sales, which

included luxury goods like wines and spirits whose demand increases as price increases.

With all the spending that was occurring throughout the report, we felt it was necessary to

look at another use of monthly wages in the form of donations since savings data was unavailable. It

was interesting to note that Canadians with an average per capita monthly wage ranging from $1325

- $1410 were most likely to make a donation. From the perspective of age, donors aged 65 and older

donated almost double that of 25 – 34 year olds over the same 8 year span.

The most intriguing aspect of writing “6 Facts About How Canadians Spend Their Money”

was seeing how this data can be used not only to look at present spending habits, but instead to

predict the future state of our economy. Extending the analysis of the data in this direction would

transform this study into a economic indicator which mimics generally accepted economic

benchmarks such as housing starts, and gross domestic product.

Economics is the perfect subject on which to base a statistical study, as the science of

economics is based solely on the complex net of cause and effect relationships that span the globe.


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Additional Notes…

six facts about how canadians spend their money

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