Transcript Central Place Theory

Central Place Theory
“5% of U.S. land is in urban
areas, but 90% of real estate
value is in urban areas”
Why???
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Location Patterns for City Size
 Zipf’s Law (a.k.a. the Rank/Size Rule)
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Zipf’s Law in Practice
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Why Might Zipf’s Law Work?
 Mathematically…
 Suppose all cities grow at random rates over time.
 Suppose all cities tend to grow at the same average
rate.
 Suppose all cities have the same “volatility” in their
growth rates.
Zipf’s Law will hold!
 Are these assumptions Reasonable???
Any Limitations???
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Patterns of City Location
“Large cities tend
to be spread out
rather than
concentrated.”
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Patterns of City Location
“City Rank Changes
tend to be
relatively rare,
and systematic
rather than
random.”
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Factors Driving Location Patterns
 Centralizing/Centripetal Forces
 Economies of Scale
 Economies of Agglomeration
 Positive Locational Externalities
 “Cumulative Causation”
 Decentralizing/Centrifugal Forces
 Congestion
 Pollution
 Crime
 Intra-urban transportation costs
 Rent/land prices
 Utility??? Correlation with City Size???
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Factors Driving Location Patterns
 Central Place Theory

“In order to reduce ‘spatial friction,’ places of similar size, rank,
or function will tend to be evenly spaced across geographical
space and/or popluation.”

Ex. #1: Minimize the average distance from HQ to city along a linear path.
A
David M. Harrison, Ph.D.
Texas Tech University
B
C
D
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E
Central Place Theory
 If CPT holds, why aren’t all companies
headquartered in Wichita, KS???
 Limitations
1)
2)
David M. Harrison, Ph.D.
Texas Tech University
Multi-dimensional spacing
Population/economic weightings
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2 Dimensional CPT
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Population/Economic Weights
 Ex. #2: Now suppose that due to locational amenities
(upwind, later sunrise, etc.) more people want to (and do)
live farther west. Specifically, the population/market
served in each town is as follows: A=50, B=40, C=30,
D=20, and E=10. Where should the company locate now?
A
David M. Harrison, Ph.D.
Texas Tech University
B
C
D
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E
What Makes Cities Grow?
 Economic Base
 Export
(Basic) Sector –
 Service
(Nonbasic) Sector –
Economic Growth depends…
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Forecasting Growth in Cities
 Estimate Growth by Industry
 Compare Industry Growth to City Location Quotients:

David M. Harrison, Ph.D.
Texas Tech University
Where:
Nmi = employment in city m, industry I
Nm = total employment (all industries) city m
Ni = national employment, industry I
N = total national employment (all industries)
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Location Quotients
 Ex. Estimate Lubbock’s widget making location
quotient given the following data:




Total U.S. Employment = 150,000,000
U.S. Widget Makers = 300,000
Total Lubbock Employment = 100,000
Lubbock Widget Makers = 700
Interpretation of Result:
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments
Multiplier Effects
 Growth in the export sector…
Employment Multiplier
Population Multiplier
• Rules of Thumb
David M. Harrison, Ph.D.
Texas Tech University
Real Estate Investments