Yale School of Management

Retail, Location and Cities

Lecture for Real Estate Class

William N. Goetzmann

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Overview

Location analysis Retail application

What are cities? Models on cities Economics of place

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Location Analysis

Where to place a marketHow to estimate salesHow to factor in competition

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Retail Real Estate

Variety Specialty Limited Line Department Mass Merchandise Discount Warehouse

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Types of Shopping Centers

Name Radius Building Area GLA

Convenience/ Neighborhood

6 min. 30-100 KSF same

Community 15 min. 100-500 KSF same to 400 KSF

Regional 30+ min 500-1,000 KSF

300-800 KSF

Super-Regional 45 min. world

>1,000,000 SF

no limit

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Mall Shape

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Rationale

Anchors for Draw Shops for Impulse Finance:

Anchors own or lease cheaply Specialty shops pay percentage rents

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Gravity Models

William Reilly (1929) "Retail Score Inversely Proportional to Distance"

Geographical Settlement Patterns Applications:

How many customers will come to the store? Where should we locate our store? What kind of store will work?

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Example

Mall location analysis in ConnecticutTravel TimesPopulation CentersMall Size

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Travel Distance in Miles (or Minutes)

Mall A Mall B Mall C Demand by City

City 1 4 3 5 50,000

City 2 3 7 2 70,000

City 3 8 6 1 150,000

Square footage

10,000 2,500 20,000

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A Gravity Score

Mall A Mall B Mall CScore: square

footage of space/distance 2,500.00 833.33 4,000.00

3,333.33 357.14 10,000.00

1,250.00 416.67 20,000.00

Sum of score by mall 7,083.33 1,607.14 34,000.00

e.g. 2,500=10,000/4

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Market Share by Mall

Mall A Mall B Mall CMall market share of each city sales City 1 0.34 0.11 0.55Mall score/ sum of scores per city City 2 0.24 0.03 0.73

City 3 0.06 0.02 0.92

E.G. .34= 2,500/(2,500+833.33+4,000

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Estimated Sales of Each Mall

Mall A Mall B Mall C Total

City 1 17,045.45 5,681.82 27,272.73 50,000

City 2 17,043.48 1,826.09 51,130.43 70,000

City 38,653.85 2,884.62 138,461.54 150,000

Market share times city demand

e.g. 17,045.45=.34x50,000

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Issues

Linear modelMix of retailConsumer types Inter-position on locationsSayes’ law

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Location

Cities from first principlesMonocentric city model

William Alonso (1964) Location and Land Use Richard Muth (1969) Cities and Housing

Transportation costsEmployment and shopping take place at one pointDemand for housing/budget constraintUtility for leisure time

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Results

Housing prices (and rents) are a decreasing function of distance from CBD.

Shifts in transportation costs and travel times can be analyzed.

Calculus for understanding new structure of cities.

E.g. Rae (2004)

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Another Approach

What are cities? Employment Shopping Social centers Private property Public amenities

What makes them grow?

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From: Diego Puga http://dpuga.economics.utoronto.ca/

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Human Capital

Acquisition of labor is easier.Knowledge spillover leads to positive

externalities. Diversification (Jacobs/Glaeser)

Reduces labor riskCompetition

Leads to innovationSpecialization (Marshall/Arrow/Romer)

Develops particular technology

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Goetzmann, Massa, Simonov

Specialization: the main industry in local employment / share of this same industry in national employment.

Competition: number of firms per employee in a district relative to the number of firms per employee in Sweden.

Diversity is the share of the next top (after the main one) five industries in municipal employment

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Savings, Investment & Finance

Urban housing less risky Diversified industry base => smooth demand

Personal Portfolios Knowledge spillover & speculation Time and attention

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Swedish Household Data

Variable Mean Median

Number of households 292,901 291,913

# of members in household 2.67 2.00

# of adults in household 1.77 2.00

Age of oldest household member 49.28 47

% with secondary education 43.5% 43.5%

% with higher education 31.4% 31.2%

% of immigrants 16.4% 16.3%

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Wealth Variables

VariableRepresentation in

the sample Mean Median

Wealth-Tax Payers 7.9% 359,592 102,700

Real Estate Holders 54.6% 449,400 387,000

Labor Income Earners 100.0% 321,489 287,722

Entrepr. Income Earners 9.8% 88,114 43,268

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Degree of Isolation and Equity Portfolio diversification

Population Density -50.00 (-3.04)

Index of Rural Areas 6.58 (19.03)

Distance from Airport 1.34 (4.09)

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Local Professional Specialization and Equity Portfolio Diversification

Variable Coeff. t-stat

Competition -12.80 (-14.07)

Specialization -0.74 (-7.55)

Concentration -1088.10 (-22.70)

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Under-Diversification

Linked to knowledge creation and spill-over in the urban environment.

Spillover that characterizes city agglomeration on the one hand reduces the availability of time to collect and analyze financial information

Increases the relative information that an investor has with respect to stocks professionally or geographically closer to him.

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Cities

Provide investment opportunitiesRequire less risk hedgingResult in capital growth and more spillover

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Creating Cities

Costa Mesa, CAWorld Financial CenterCanary Wharf, LondonDubai, UAE