McGraw-Hill/Irwin ©2009 The McGraw-Hill Companies, All Rights Reserved Chapter 2 Why Do Cities Exist?

©2009 The McGraw-Hill Companies, All Rights Reserved 2-2 What set of assumptions will rule out cities? Why do trading cities develop? Why do factory cities develop? Who benefits from innovations that generate cities? Introduction--Questions to Address

©2009 The McGraw-Hill Companies, All Rights Reserved 2-3 No differences in productivity for labor or land Constant returns to scale in exchange Constant returns to scale in production Backyard Production Model: Assumptions

©2009 The McGraw-Hill Companies, All Rights Reserved 2-4 No Trade No productivity benefit from specialization and exchange Exchange is costly (time) without any benefit No Cities Dense living is costly (bid up price of land) without any benefit Result: Uniform price of land and population density Backyard Production Model: Implications

©2009 The McGraw-Hill Companies, All Rights Reserved 2-5 Trading Cities Drop assumption of equal productivity Differences in productivity generate comparative advantage

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©2009 The McGraw-Hill Companies, All Rights Reserved 2-7 Gross gain from trade = 2 shirts for each region Net gain = gross gain - transaction time (t) North: If t 0 South: If t 0 Computing the Net Gain From Trade

©2009 The McGraw-Hill Companies, All Rights Reserved 2-8 In absence of scale economies, households will trade directly Scale economies in exchange: lower cost for a trading firm Trade workers live close to firms and bid up land price Higher price of land increases density, generating a trading city Scale Economies in Exchange

©2009 The McGraw-Hill Companies, All Rights Reserved 2-9 Ancient cities: Phoenicians, Athens, Rome. Middle ages. Trading cities in Europe: London, Bruges, Amsterdam, Barcelona, Milan, Venice.  Example: development of Amsterdam. Trading Cities in Urban History

©2009 The McGraw-Hill Companies, All Rights Reserved 2-10 Cotton gin and cotton-trade cities Transport technology: turnpikes, canals, steamship (1807), railroad (2 nd half of XIX). New York, New Orleans. Trading Cities in American History

©2009 The McGraw-Hill Companies, All Rights Reserved 2-11 We’ll assume constant returns to scale in bread production but apply economies of scale to shirt production. Productivity Numbers Home = 1 shirt per hour Factory = 6 shirts per hour Home or factory: 1 loaf of bread per hour Factory Town

©2009 The McGraw-Hill Companies, All Rights Reserved 2-12 The price of shirts at the factory is the unit cost of 1/3 loaf = 4/12 loaf

©2009 The McGraw-Hill Companies, All Rights Reserved 2-13 The net price of a factory shirt is the factory price (4/12 loaf) plus transport cost (1/12 loaf pr mile)

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©2009 The McGraw-Hill Companies, All Rights Reserved 2-15 Workers live close to factory to economize on commuting time Axiom 1: Prices adjust to ensure locational equilibrium Competition for land bids up its price Higher price of land increases density, generating a city Factory workers paid 1/2 loaf per hour to cover higher cost of living Factory Town Develops Around the Factory

©2009 The McGraw-Hill Companies, All Rights Reserved 2-16 The Industrial Revolution shifted production to large factories. Innovations in manufacturing Standard system of mass production: Eli Whitney. Use precise machine tools to generate identical parts. Interchangeable parts, specialized labor and steam powered machines. Sewing machine (1846), shoes. The Industrial Revolution and factory cities

©2009 The McGraw-Hill Companies, All Rights Reserved 2-17 Innovations in transportation Turnpikes, canals, steamship, railroad. Innovations in Agriculture Cast-iron plow (1930s), Steel plow (J.Deere 1940). Innovations in planting, growing harvesting and processing. Share of agriculture employment has dropped from 90% to 3%. Increased productivity in agricultural freed people to work in urban factories and commercial firms. The Industrial Revolution (cont.)

©2009 The McGraw-Hill Companies, All Rights Reserved 2-18 Energy technology and location decisions First factories used waterwheels turned by waterfalls. Refinement of steam engine in 2nd half of 19th C. made energy a transportable input. Factories located near coal mines or navigable waterways, and later next to railroads. Electricity generators were refined in the 1860´s and electric motor in Electricity transmission decreased the importance of energy in location decisions –› accessibility to other inputs and consumers. The Industrial Revolution (cont.)

©2009 The McGraw-Hill Companies, All Rights Reserved 2-19 Axiom 5: Competition generates zero economic profit Firms enter the shirt market until each makes zero economic profit Factories span the region Every location lies within market area of a factory Complete labor specialization, with rural bread and urban shirts Zero economic profit for firms & locational indifference for workers A SYSTEM OF FACTORY TOWNS

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©2009 The McGraw-Hill Companies, All Rights Reserved 2-21 Prices adjust to ensure locational equilibrium Locational indifference in rural areas Lower travel cost at locations close to factory city and rural households bid up the price of land near cities Locational indifference between rural and urban areas Factory wage compensates for higher land prices in cities Land Rent in the Region: Axiom 1

©2009 The McGraw-Hill Companies, All Rights Reserved 2-22 Market-oriented firm: More costly to transport output than inputs Shirt example: assume input transport cost = 0 Firms oriented toward markets to economize on output transport cost Weight gaining activity: beverages produced from local water & syrup Fragility gaining: Fresh food Bulk gaining: Assembly plants Hazard gaining: Explosives Location Orientation: Market Orientation

©2009 The McGraw-Hill Companies, All Rights Reserved 2-23 More costly to transport inputs than output Firms oriented toward markets to economize on output transport cost Weight losing activity: produce sugar from beets, lumber from logs Fragility losing: Canned or frozen food Hazard losing: deodorizing skunks Location Orientation: Resources Orientation

©2009 The McGraw-Hill Companies, All Rights Reserved 2-24 Scale economies in processing, so number of plants is relatively small Farmers sell beets to processing plant offering highest net price Entry and competition generates zero profit System of Towns for Sugar-Beet Processing

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©2009 The McGraw-Hill Companies, All Rights Reserved 2-26 Steel towns: near coal, then ore Leather towns near forest for tannin Lumber towns near forests Other Examples of Materials-Oriented Industries