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THIS IS A STRIPPED DOWN SHOW COVERING MATERIAL
WE DID NOT HAVE TIME TO DO IN LECTURE.
THE MATERIAL HERE IS IMPORTANT TO
UNDERSTANDING ECONOMIC GEOGRAPHY SO YOU
SHOULD LOOK THROUGH IT ALL.
HOWEVER:
THERE ARE VISIBLE AND HIDDEN SLIDES.
YOU WILL BE TESTED ON THE VISIBLE SLIDES SO
REVIEW THEM.
Classification systems (E.G. NAICS, StatsCan)
•
•
•
•
Attempt to group similar activities.
Attempt to separate dissimilar activities.
Be as comprehensive as possible.
Be as consistent as possible (sectorally, spatially, temporally).
Because classifications are by definition static and activities are
not, they always become out-dated and must be changed.
Different systems exist for:
• Economic activities.
• Occupations.
• Products.
• Commodities.
The NAICS and the SIC:
• SIC developed starting after WW2 with the GATT.
• NAICS evolved from this with the NAFTA.
• Both are structured hierarchical typologies that group
economic activities:
• into Divisions,
• divisions into Major Group,
• major groups into Industry Group,
• industry groups into Industry Classes.
• All groupings are based on similarity between hierarchical
levels; that is, like activities are grouped together into
increasingly larger classes.
• But as they get larger, they get more dissimilar!
SIC: Standard Industrial Classification System:
• Now obsolete but old datasets still have SIC “codes” and not
NAICS codes.
• Structure is similar to NAICS however, as we will see shortly.
• Uses divisions, major groups, industry groups, industry classes.
• Divisions have a letter code, and each of the others its own
digit or digits in a four digit number code.
NAICS: the North American Industrial Classification System:
• “New” system started in 1997 and updated 3 times since, with
2012 the latest.
• Developed to ensure consistent classes of activities between
NAFTA nations – but U.S. and Mexico’s are slightly different!
• Uses sectors, sub-sectors, industry group, industry, national
industry, each having its own digit in up to a six digit code.
Sectors
Primary
Primary
Tertiary
Tertiary
Secondary
Tertiary
Tertiary
Tertiary
Quaternary
Quaternary
NAICS 2012 CLASSIFICATION STRUCTURE – SECTORS
http://www.statcan.gc.ca/cgi-bin/imdb/p3VD.pl?Function=getVDPage1&db=imdb&dis=2&adm=8&TVD=118464
11
Agriculture, forestry, fishing and hunting
21
Mining, quarrying, and oil and gas extraction
22
Utilities
23
Construction
31- 33 Manufacturing
41
Wholesale trade
44-45 Retail trade
48-49 Transportation and warehousing
51
Information and cultural industries
52
Finance and insurance
53
Real estate and rental and leasing
54
Professional, scientific and technical services
55
Management of companies and enterprises
56
Administrative and support, waste management and remediation services
61
Educational services
62
Health care and social assistance
71
Arts, entertainment and recreation
72
Accommodation and food services
81
Other services (except public administration)
91
Public administration
Industry Group
31-33 Manufacturing
NAICS:
312 Beverage and Tobacco Product Manufacturing
The Manufacturing Sector‘s 21 Classes
31-33 Manufacturing
311 Food Manufacturing
313 Textile Mills
314 Textile Product Mills
311 Food Manufacturing
315 Clothing Manufacturing
312 Beverage and Tobacco Product Manufacturing
316 Leather and Allied Product Manufacturing
321 Wood Product Manufacturing
322 Paper Manufacturing
313 Textile Mills
323 Printing and Related Support Activities
314 Textile Product Mills
324 Petroleum and Coal Products Manufacturing
325 Chemical Manufacturing
315 Clothing Manufacturing
326 Plastics and Rubber Products Manufacturing
327 Non-Metallic Mineral Product Manufacturing
331 Primary Metal Manufacturing
316 Leather and Allied Product Manufacturing
332 Fabricated Metal Product Manufacturing
333 Machinery Manufacturing
334 Computer and Electronic Product Manufacturing
335 Electrical Equipment, Appliance and Component Manufacturing
336 Transportation Equipment Manufacturing
337 Furniture and Related Product Manufacturing
339 Miscellaneous Manufacturing
31-33 Manufacturing
311 Food Manufacturing
31-33 ManufacturingNAICS
312 Beverage and Tobacco Product Manufacturing
Code Hierarchy for
311 Food Manufacturing Textile Mills
313 Textile Mills
Six Digits
and TobaccotoProduct
Manufacturing
3131 Fibre, Yarn312
andBeverage
Thread Mills
313 Textile Mills
314 Textile Product Mills
315 Clothing Manufacturing
316 Leather and Allied Product Manufacturing
321 Wood Product Manufacturing
31311 Fibre, Yarn and Thread Mills
313 Textile Mills
323 Printing and Related313110
Support ActivitiesFibre, Yarn and Thread Mills
324 Petroleum and Coal Products Manufacturing
314 Textile Product Mills
3132 Fabric Mills
325 Chemical Manufacturing
31321 Broad-Woven Fabric Mills
326 Plastics and Rubber Products Manufacturing
315 Clothing Manufacturing
Broad-Woven Fabric Mills
327 Non-Metallic Mineral313210
Product Manufacturing
331 Primary Metal Manufacturing
31322 Narrow
Fabric Mills
and Schiffli
Machine
Embroidery
316 Leather
and Allied
Product
Manufacturing
332 Fabricated Metal Product Manufacturing
313220 Narrow Fabric Mills and Schiffli Machine Embroidery
333 Machinery Manufacturing
31323
Nonwoven Fabric Mills
334 Computer and Electronic
Product Manufacturing
335 Electrical Equipment,313230
Appliance and Component
Manufacturing Fabric Mills
Nonwoven
336 Transportation Equipment Manufacturing
31324 Knit Fabric Mills
337 Furniture and Related Product Manufacturing
313240 Knit Fabric Mills
339 Miscellaneous Manufacturing
3133 Textile and Fabric Finishing and Fabric Coating
322 Paper Manufacturing
Growth or Not And By How Much?
The answer is not 12%.
First there is the effect of inflation/deflation.
Second, there is the effect of population change.
Third, there are also issues about comparability of:
the variables/units:
apples or oranges?
litres or kilos?
dollars or yen?
differences or magnitudes?
time scales?
Fourth, there are components to a growth value.
An Illustration –The Canadian Economy
Look at the numbers - Two Questions:
Is consumer spending growing faster than GDP?
Are consumer spending and GDP really growing at all?
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP
Consumer Spending
$1,152,905,000,000 $655,722,000,000
$1,213,175,000,000 $686,552,000,000
$1,290,906,000,000 $719,917,000,000
$1,373,845,000,000 $758,966,000,000
$1,450,405,000,000 $801,742,000,000
$1,529,589,000,000 $851,603,000,000
$1,603,418,000,000 $890,601,000,000
$1,528,985,000,000 $898,215,000,000
$1,624,608,000,000 $940,620,000,000
The Answer?
Maybe, because
the values all are
increasing.
But looks can be
deceiving for two
reasons…
Current and Constant Dollar Effects
Removing the effect of inflation/deflation.
Inflation and deflation is caused when the
costs and subsequent prices of products
increase or decrease, so “growth/decline” is
not caused by more/less consumption but by
increased/decreased price caused by
increased/decreased costs.
You fix it by converting current dollars to
constant dollars using the consumer price
index and purchasing power parity.
Current and Constant Dollars Effects
A Note on Terms Used
Economists use the term “nominal” for values
that have not been corrected for inflation and
“real” for those that have.
However, most of the documents you see use
the terms “current” for non-corrected values and
“constant” for corrected values. This is what we
will use.
But much of the time no term is used so you
have no idea whether you are dealing with
corrected or uncorrected data.
Population Change Effects
Compensating for the effect of population
change
More people equals an increase in
consumption and production and not an
increase in individual spending.
You fix it by using per capita rates.
Measurement Effects
Are the variables and/or units of
measurement comparable?
This asks whether you are talking about:
Different variables such as guns, butter,
people.
Different magnitudes such as GDP$ and
spending $.
Different measurement units such as annual or
quarterly, litres or kilos.
You fix it by indexing your data.
So, back to our example…
Look at the numbers - Two Questions:
Is consumer spending growing faster than GDP?
Are consumer spending and GDP really growing at all?
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP
Consumer Spending
$1,152,905,000,000 $655,722,000,000
$1,213,175,000,000 $686,552,000,000
$1,290,906,000,000 $719,917,000,000
$1,373,845,000,000 $758,966,000,000
$1,450,405,000,000 $801,742,000,000
$1,529,589,000,000 $851,603,000,000
$1,603,418,000,000 $890,601,000,000
$1,528,985,000,000 $898,215,000,000
$1,624,608,000,000 $940,620,000,000
The Answer?
Maybe, because
the values are
increasing – GDP
grew by 40% and
CS by 43%.
But looks can be
deceiving for two
reasons…
Are the values comparable?
(No. The magnitudes of values are much different)
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
Current
Current
Dollar
Dollar Consumer
GDP
Spending
Index # Index #
2002=100 2002=100
100.00
100.00
105.23
104.70
111.97
109.79
119.16
115.75
125.80
122.27
132.67
129.87
139.08
135.82
132.62
136.98
140.91
143.45
Create a base 100 index number:
1.Make an arbitrary year’s real
data value equal to 100.
2. Calculate every other year’s
index number in relation to this
base year value (% change).
Now both sets of data values are
directly comparable because
they are relative.
Removing the effects of inflation and population change.
Collecting the base conversion values.
2002
2003
2004
2005
2006
2007
2008
2009
2010
Consumer
Price Index
2002 = 100
100.0
102.8
104.7
107.0
109.1
111.5
114.1
114.4
116.5
Canada
Population
31,373,000
31,676,000
32,048,000
32,359,000
32,723,000
33,115,000
33,506,000
33,894,000
34,349,200
1. Collect the consumer
price index (CPI) values.
2. Collect population data.
3. Use CPI to convert
current to constant dollars
for both variables.
4. Use population values
to calculate per capita
spending and GDP thus…
Removing the effect of inflation from GDP
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP Current Dollars
$1,152,905,000,000.00
$1,213,175,000,000.00
$1,290,906,000,000.00
$1,373,845,000,000.00
$1,450,405,000,000.00
$1,529,589,000,000.00
$1,603,418,000,000.00
$1,528,985,000,000.00
$1,624,608,000,000.00
GDP Constant 2002
Base Year
Dollars
values are
$1,152,905,000,000.00 always the
$1,180,131,322,957.20
same for
$1,232,957,020,057.31 current and
$1,283,967,289,719.63
constant
$1,329,427,131,072.41
dollars.
$1,371,828,699,551.57 That’s how
$1,405,274,320,771.25 you can tell
$1,336,525,349,650.35
the base
$1,394,513,304,721.03
year.
Note that when removing inflation the constant dollar
values are always lower than the current dollar values.
Removing the effect of inflation from consumer
spending
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
Consumer Spending
Current Dollars
$655,722,000,000.00
$686,552,000,000.00
$719,917,000,000.00
$758,966,000,000.00
$801,742,000,000.00
$851,603,000,000.00
$890,601,000,000.00
$898,215,000,000.00
$940,620,000,000.00
Consumer Spending
Constant 2002 Dollars
$655,722,000,000.00
$667,852,140,077.82
$687,599,808,978.03
$709,314,018,691.59
$734,868,927,589.37
$763,769,506,726.46
$780,544,259,421.56
$785,152,972,027.97
$807,399,141,630.90
Base Year
Values are
always the
same for
current and
constant
dollars.
That’s how
you can tell
the base
year.
Note that when removing inflation the constant dollar
values are always lower than the current dollar values.
Compensating for the effect of population change
CURRENT DOLLARS
2002
2003
2004
2005
2006
2007
2008
2009
2010
Per Capita GDP
Current Dollars
$36,748.32
$38,299.50
$40,280.39
$42,456.35
$44,323.72
$46,190.22
$47,854.65
$45,110.79
$47,296.82
CONSTANT DOLLARS
Per Capita
Consumer
Per Capita GDP
Spending
Constant 2002
Current Dollars
Dollars
$36,748.32
$20,900.84
$37,256.32
$21,674.20
$38,472.20
$22,463.71
$39,678.83
$23,454.56
$40,626.69
$24,500.87
$41,426.20
$25,716.53
$41,940.98
$26,580.34
$39,432.51
$26,500.71
$27,384.04
$40,598.13
Per Capita
Consumer
Spending
Constant 2002
Dollars
$20,900.84
$21,083.85
Base
$21,455.31
$21,920.15Year
$22,457.26Same
$23,064.16
$23,295.66
$23,164.95
$23,505.62
Divide dollar values by population – for examples:
Constant $ GDP 2002 = $1,152,905,000,000/31,373,000=$36,748.32
Constant $ CS 2002 = $687,599,808,978/ 32,048,000=$21,455.31
Correcting The Canadian Economy in Summary
What You See
(data uncorrected for…)
Inflation…
Use price indexes to correct
Population growth…
Use per capita to correct
What Do You Get?
Data corrected for both…
Per capita values in constant dollars
So did the Canadian Economy ‘grow’ and if so
by how much?
Correction
No correction
(current dollars)
Corrected for
inflation only
(constant dollars)
Corrected for
population change only
(per capita rates)
Corrected for both
(Constant per capita)
Difference
GDP Growth
Rate
Consumer
Spending
Growth Rate
40.9%
43.5%
21.0%
23.1%
28.7%
31.0%
10.5%
12.5%
-30.4%
-31.0%
An Illustration –The Canadian Economy
Two Questions
1. Is consumer spending growing faster than GDP?
2. Are consumer spending and GDP really growing at all?
Date
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP Current Dollars
$1,152,905,000,000.00
Raw Percent Change
$1,213,175,000,000.00
2002-10
$1,290,906,000,000.00
40.9%
$1,373,845,000,000.00
$1,450,405,000,000.00
Real Percent Change
$1,529,589,000,000.00
2002-10
$1,603,418,000,000.00
10.5%
$1,528,985,000,000.00
$1,624,608,000,000.00
Consumer Spending
Current Dollars
$655,722,000,000.00
Raw Percent Change
$686,552,000,000.00
2002-10
$719,917,000,000.00
43.5%
$758,966,000,000.00
$801,742,000,000.00
Real
Percent Change
$851,603,000,000.00
2002-10
$890,601,000,000.00
12.5%
$898,215,000,000.00
$940,620,000,000.00
Two Answers
1. Can’t tell
from these
raw data.
2. Maybe,
because the
numbers are
increasing.
But looks can
be deceiving.
Index numbers
Simple Index Numbers
Very simple to calculate by taking the base year
value, chosen arbitrarily, dividing it into each
subsequent year’s value, then multiplying by 100.
Date
2002
2003
2004
2005
GDP
$1,152,905,000,000
$1,213,175,000,000
$1,290,906,000,000
$1,373,845,000,000
Index
100.00
105.23
111.97
119.16
$1,213,175,000,000.00/$1,152,905,000,000 = 105.23
$1,290,906,000,000.00/$1,152,905,000,000 = 111.97
NOTE THAT THIS IS JUST A PERCENTAGE CHANGE VALUE
ADDED TO 100
The Consumer Price Index
• What is the CPI?
• Basket of goods and services are “bought” and their
cost is set to equal an index number of 100.
• The year the basket is “bought” is called the base
year, and it remains until a new base year is chosen.
• The same basket is “bought” the next year and its
value is given an index # equal to 100 plus the
percentage change from the previous year’s basket.
• This process is repeated each year (or other time
period) until a new base year is chosen.
• The CPI is listed in a table and the base year is noted
somewhere as, for example, 2002=100.
Therefore you do not calculate the CPI – you must
look it up from Stats Canada
Examples of Price Indices
• Data tables for Prices and price indexes – some SC examples:
•
•
•
•
•
•
•
•
•
•
•
•
Table 25.a Consumer Price Index
Table 25.b Average retail food prices
Table 25.1 Consumer Price Index, 1991 to 2010
Table 25.2 Consumer Price Index, All-items, by province and territory, 2005
to 2010
Table 25.3 Consumer Price Index, food, 2004 to 2010
Table 25.4 New Housing Price Index, by province, 2004 to 2010
Table 25.5 Raw Materials Price Index, 2004 to 2010
Table 25.6 Farm Product Price Index, 2004 to 2010
Table 25.7 Industrial Product Price Index, 1991 to 2010
Table 25.8 Machinery and Equipment Price Index, domestic and imported,
by industry, 2005 to 2010
Table 25.9 Composite Leading Index, March 2005 to March 2011
Table 25.10 Inter-city indexes of retail price differentials, by selected goods
and services, 2005 and 2009
The CPI – Example Tables
Table 25.a Consumer Price Index
All-items
Food
Shelter
2000
2010
2002=100
95.4
116.5
93.3
123.1
95.6
123.3
Household operations, furnishings and equipment
96.7
108.8
Clothing and footwear
Transportation
Health and personal care
100.3
97.2
97.0
91.6
118.0
115.1
Recreation, education and reading
97.0
104.0
Alcoholic beverages and tobacco products
79.0
133.1
Core Consumer Price Index1
95.7
115.6
Note: Annual average indexes are obtained by averaging the indexes for the 12 months of the calendar year.
1. Bank of Canada definition.
Source: Statistics Canada, CANSIM table 326-0021.
Farm Product Price Indices – Example Tables
Canada
Total crops
Grains
Oilseeds
Specialty crops
Fruit
Table 25.6 Farm Product Price Index, 2004 to 2010
2004
2005
2006
2007
1997=100
99.4
96.8
97.4
108.6
100.6 88.3
92.7
117.5
94.1
76.5
84.3
133.3
95.2
74.5
72.2
97.5
102.5 85.2
80.2
120.6
108.7 117.4
124.6
124.4
2008
2009
2010
122.0
144.9
168.3
133.5
185.9
126.3
113.5
126.3
128.5
116.5
158.6
112.5
111.0
114.8
102.5
113.1
137.9
118.3
Vegetables (excluding potatoes)
116.8
113.1
118.2
114.3
119.3
125.3
124.1
Potatoes
119.4
125.9
148.6
135.0
150.7
183.2
175.9
Total livestock and animal products
98.3
103.9
101.3
101.5
103.5
103.6
109.2
Cattle and calves
87.6
103.2
102.7
99.4
99.0
97.7
103.0
Hogs
Poultry
Eggs
Dairy
89.7
97.9
105.6
119.9
83.0
96.4
97.3
128.0
72.3
93.2
98.7
130.3
68.3
102.2
100.8
137.2
67.3
115.0
107.9
139.9
67.5
116.6
103.4
142.4
80.4
111.8
109.0
143.3
The CPI and Purchasing Power Parity (PPP)
CPI only one part of cost of living – some places are just
more expensive to live in because of isolation or large size
that leads to more demand chasing fewer goods.
When values are corrected for the cost of living in
different places the resulting data is labeled as PPP.
This means Purchasing Power Parity – that is, dollar
values are corrected for the differences in the cost of
things like food, housing, taxes, gasoline, etc, for a given
place.
In this case the same basket of goods is valued in each
place, compared, then indexed, and the resulting indexed
values are used to inflate or deflate prices, incomes, GDP,
etc.
Inter City CPI PPP – Example Tables
Vancouver
Edmonton
Winnipeg
Toronto
Montréal
St. John's
Charlottetown &
Summerside
Table 25.10 Inter-city indexes of retail price differentials, by selected goods and services, 2005 and 2009
2005 2009 2005 2009 2005 2009 2005 2009 2005 2009 2005 2009 2005 2009
combined city average=100
All-items
94
97
93
95
110 107 92
Food
103 105 100
103
97
102
101
99
98 101 101 100 106 105
Food purchased from
stores
105 104 103
103
99
101
99
99
99 103 101 102 106 106
Meat, poultry and fish
101 103 108
102
103
99
97
99
93
96
99 103 106 108
101
94
101
91
100
96
106 107 101 106
Dairy products and eggs
95
96
105 102
99
93
94
97 102 102 101
Current
And
Constant
Dollar$
Current to Constant Dollar Conversion
Current dollars are not corrected for inflation so part of
the change over time in values does not come from
growth.
To remove effect of inflation:
Current 2003 GDP = $1,213,175,000,000
CPI (2002=100) = 102.8
Formula:
Constant 2002$ = Current $/(CPI/100)
Calculated:
Current 2003 GDP $ = $1,213,175,000,000/(102.8/100) =
Constant 2003 GDP $ = $1,180,131,322,957.20
Complex Ratios
Ratio of Ratios Approach
Components Approach
Ratio of Ratios Example
Location Quotients
(LQ)
Location Quotients
A method of estimating whether a region has a surplus,
deficit or the average employment in an industry. Given by:
LQ =
Employment in industry i in region j
Total employment in region j
Employment in industry I in the nation J
Total employment in the nation J
Sometimes given as:
LQ = (Eij/Ej)/(EIJ/EJ)
Where i and j represent “industry” and “area” respectively,
with lower case referring to the region in question and
upper case referring to, usually, the nation.
Location Quotients
You should be able to see that this is a ratio of
ratios thus:
Employment in industry i in region
Total employment in region j
Employment in industry I in the nation
Total employment in the nation J
Ratio of regional
employment in i to total
regional employment j
Ratio of national
employment in I to total
national employment J
The resulting ratio is interpreted as follows:
> 1.0:
surplus
national
average
production
In other
words,
is thetoactivity
basic,
non-basic,
or neither?
= 1.0:
national average
production
Thus
we equal
have atotechnique
that could
be used for
< 1.0: deficit
to national
average
production
measuring
economic
base.
Summing up.
The next time you see a growth rate,
think about it:
Current of constant dollars?
Units?
Scale?
Good growth or bad growth?
Components of growth?
Coefficients Approach – An Example
The Gini Coefficient
The Gini Coefficient
The Gini coefficient is a widely used measure of the degree of
inequality in a distribution.
Gives a number between 0 and 1 where 0 is complete equality and 1 is
complete inequality.
Sometimes numbers are multiplied by 100 to give coefficients between
0 and 100.
It is used most generally in describing income inequality in a
population.
Interpreting the Gini Coefficient
A nation with a coefficient of 0 would mean everyone had exactly the
same income.
A nation with a Gini coefficient of 1 (or 100) would mean that one person
had all the income.
Sweden = 23, Namibia = 70.7, USA = 45, Canada = 31.
Global Gini is 40.
Global Gini Coefficient 2010
Measuring Performance in an
Economy
Productivity Indices
Measures the efficiency with which economy’s labour and
capital are being used to produce output using three basic
measures:
Output Per Person Hour
Output/number of hours worked to produce it
Compensation Per Person Hour
Output/wages paid to produce it
Unit Labour Cost
Wages/Output
OR
Compensation Per Person Hour/Output Per Person Hour)
Calculating Productivity Indices
VARIABLES USED TO CALCULATE
INDICES
Output in Value Added
Person Hours Worked
VALUES 2012
$1,558,077,367
30,541,021
Wages Paid
PRODUCTIVITY INDICES
Output Per Person Hour
$972,179,228
Compensation Per Person Hour
Unit Labour Cost
$31.83
$0.62
$51.00
Interpretation: In 2012 Canadian workers:
Produced $51.00 for every hour they worked,
Got paid about $ 31.83 for every hour they worked, and so…
Their labour accounted for .62 cents of each dollar of production.
Source: Statistics Canada. CANSIM Table383-0029
Capacity Utilisation Rates
Compares what you do produce against what you could
have produced.
High CUR indicates that an industry is approaching
capacity and is an indicator of inflation.
Low CUR indicates that unit costs of production are
higher than they should be.
Simple to understand but difficult to measure.
Two basic methods - both try to set an ideal upper limit
and then compare actual production against it.
The two methods are:
The Wharton Trend Through Peaks
StatsCan Capital Output Ratio