Retail, Location and Cities

1. Retail, Location and Cities Lecture for Real Estate Class William N. Goetzmann

2. Overview • Location analysis • Retail application • What are cities? • Models on cities • Economics of place

3. Location Analysis • Where to place a market • How to estimate sales • How to factor in competition

4. Retail Real Estate • Variety • Specialty • Limited Line • Department • Mass Merchandise • Discount • Warehouse

5. Types of Shopping Centers

6. Mall Shape

7. Rationale • Anchors for Draw • Shops for Impulse • Finance: • Anchors own or lease cheaply • Specialty shops pay percentage rents

8. 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?

9. Example • Mall location analysis in Connecticut • Travel Times • Population Centers • Mall Size

10. Travel Distance in Miles (or Minutes)

11. A Gravity Score e.g. 2,500=10,000/4

12. Market Share by Mall E.G. .34= 2,500/(2,500+833.33+4,000

13. Estimated Sales of Each Mall Market share times city demand e.g. 17,045.45=.34x50,000

14. Issues • Linear model • Mix of retail • Consumer types • Inter-position on locations • Sayes’ law

15. Location • Cities from first principles • Monocentric city model • William Alonso (1964) Location and Land Use • Richard Muth (1969) Cities and Housing • Transportation costs • Employment and shopping take place at one point • Demand for housing/budget constraint • Utility for leisure time

16. 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)

17. Another Approach • What are cities? • Employment • Shopping • Social centers • Private property • Public amenities • What makes them grow?

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

19. Human Capital • Acquisition of labor is easier. • Knowledge spillover leads to positive externalities. • Diversification (Jacobs/Glaeser) • Reduces labor risk • Competition • Leads to innovation • Specialization (Marshall/Arrow/Romer) • Develops particular technology

20. 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

21. Savings, Investment & Finance • Urban housing less risky • Diversified industry base => smooth demand • Personal Portfolios • Knowledge spillover & speculation • Time and attention

22. Swedish Household Data

23. Wealth Variables

24. Degree of Isolation and Equity Portfolio diversification

25. Local Professional Specialization and Equity Portfolio Diversification

26. 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.

27. Cities • Provide investment opportunities • Require less risk hedging • Result in capital growth and more spillover

28. Creating Cities • Costa Mesa, CA • World Financial Center • Canary Wharf, London • Dubai, UAE