Chapter 10 Cities and Urban Economies

1. Chapter 10 Cities and Urban Economies • Relation between urban growth and capitalist development • Central place theory (NOT IN TEXT) • Economic base model • Housing markets in urban areas • Gentrification processes, poverty • The development of global cities

2. Cities in Historical Perspective • Early cities: trading points for agriculture, as well as bureaucrats, priests, etc. • City-states – Greek, Roman • Revival in the renaissance • Boom along with the industrial revolution: manufacturing as a “city-forming” sector • The rise of colonial cities • The rise of corporate headquarter concentrations

3. Vance’s Exogenic And Endogenic Model of City System Development

4. Central Place Theory Wasp Nest Nearly Perfect Hexagonal Nests Walter Christaller Barnacle shells on a beach rock Average 5.3 sides per barnacle

5. Simplifying Assumptions: The Isotropic Plain The concept: equal properties in all directions: Flat, no movement barriers Transport costs proportional to distance Equal Quality Environment Population evenly spaced Identical Income Levels, Tastes, Demands Perfect Knowledge: consumers & producers Producers seek to maximize profit Scale economies exist in production

6. Demand and Supply Principles $ D S P S D Q(t) Q A model of expectations!

7. A Simple Market Model of Demand for Sausages Price: $2/ pound Transport cost: 10 cents/mile each way ($.20 round trip) Budget: $8 each week for Sausage Therefore, at the market where TC = 0, 4# each week can be purchased given this budget for sausages. At 10 miles: $2 Transport cost (.1 /mile x 10 miles each way) this leaves $6 for Sausages, or 3# per week. If travel rises to 40 miles, then travel costs are $8, then there is no income to use to purchase sausages. This is the RANGE of the good for this market price and demand quantity.

9. Basic Model, Continued Now, let us assume that the costs of production are $140, and for the moment NOT variable with scale (size of production (Q). This means that the threshold for the example here is 20 miles of market extent: Distance: # customers Q*P Rev Total Up to 1 1 4 x 2 8 8 up to 10 6 3 x 2 36 44 up to 20 24 2 x 2 96 140 up to 30 26 1 x 2 52 192

10. Demand Cone Principles Quantity Demanded Range Zero Distance Distance

11. Threshold and Range Relationship Range Threshold Range Situation: Demand > Costs Situation: Demand < Costs Threshold

12. Competition for Customers Possibly maximum profit Market area Unserved customers The figure suggests that sellers press towards each other, creating hexagonal market areas and possibly eliminating excess profits ? How would producers like to set their price? At the level that maximizes profit, which is at a scale of output where marginal revenues and marginal costs are equal.

13. Lösch’s Market Area Development Sequence

14. Alternative Spatial Market Areas

15. Spatial Competition If producers behave as spatial monopolists, then circular market areas arise, with the range equal to the market area maximizing profit. If producers behave competitively, they will pack together shrinking market area size until excess profit disappears.

16. Christaller’s Central Place Models • Marketing Principle • Transportation Principle • Administration Principle • Implications of each for transportation routes

17. Marketing Principle

18. Marketing Principle Transport routes are not straight between high level centers as they must also serve second level centers (black lines)

19. Marketing Principle - Order of Goods

20. Transportation Principle Transport routes are straight, passing through second order centers

21. Administrative Principle

22. Lösch’s Ten Smallest Market Areas

23. Lösch’s Model

24. Lösch’s System Of Transport Lines and Centers With Activity-rich And Activity-poor sectors

25. Fox & Kumar’s Square Market Areas

26. Central Place Systems: Evidence Hierarchies? Are they out there? Groups of functions vs. continuous spread by size? Rank Size models as surrogates Rank Stability over time Do Consumers Travel as Expected? Desire Line Analyses Are Centers Spaced as we Expect? Nearest-Neighbor Statistical Tests Impact of Density of Settlements

29. Ideal Patterns of Functions Discrete breaks • • • • # of functions • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Largest Rank Size of Place Smallest

30. Ideal Patterns of Functionsversus continuous pattern of functions Discrete breaks • • • • Actual data show a pattern in between these alternatives # of functions • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Largest Rank Size of Place Smallest

31. Lösch’s Test of Spacing of Central Places in Iowa Region Theoretical # Actual#Theoretical Actual Size of of Spacing Spacing (Order) Settlements Settlements 1 615 5.6 2 154 153 11.2 10.3 3 39 39 22.4 23.6 4 10 9 44.8 49.6 5 2 or 3 3 89.6 94.0 6 0 or 1 0 179.2 ?

32. Two Examples of Central Place Hierarchies S.W. Ontario # Centers # Functions Population 10 1-12 25-1702 2 19-22 408-486 2 28-32 673-676 1 78 3507 1 99 22,224 1 150 77,190 Southwest Iowa # Centers # Functions Population 29 less than 10 less than 150 32 10-25 150-400 15 28-50 500-1500 9 over 55 2000-7000

33. Isard’s Model With Varying Density

34. Seyfried’s Urban Hierarchy

35. Impact of Density on Trade Area Size

36. Rank-Size Relationships In many urban systems where population and rank exhibit a relatively continuous distribution, the rank-size model predicts well: Pr = P1 / rq where q tends towards 1. Example: If P1 = 100,000, q = 1, and rank = 25, Then P25 = 100,000/25 = 4,000 U.S. 1790-1950 U.S. Cities - 1960 - 1998 Exception: Primate City conditions

37. Rank Relations Over Time

38. Rank Position Top 20 U.S. Metro Areas

39. Movement of Consumers to Central Places Desire lines: Beyers hardware lawnmower data Overlapping trade areas – Pacific Northwest data for high order services - Eastern Montana - Southern Idaho - Southwest Oregon

40. Source: Preston, The Structure of Central Place Systems

44. Beyers HardwareLawnmowerSalesPatterns

45. Beyers HardwareLawnmowerSalesPatterns

47. Spacing of Urban Centers Tests using “nearest neighbor” statistic: Index = observed average distance expected average distance Expected distance is for a random distribution Index = 1 for a random distribution Index = 0 if all places are clustered Index = 2.15 for a perfect hexagonal pattern Table 1.6: Mixed results! Figure 1.23: Impact of settlement density

48. Uniform Hexagonal R = 2.15 Uniform Square R = 2.0 Random R=1.0 Clustered R=0.0

49. Spatial Pattern of Settlements