Historical Development and Changing Technology
Firm Site Selection and
Industrial land Use.
MIT Center for Real Estate
Week 4: Firm Site Selection and
Industrial land Use.
• Households as a factor of production versus
as a client.
• Historic cities – commerce and industry at
the Center.
• Changes in Technology and Transportation.
• Modern Industrial location.
MIT Center for Real Estate
Firm – Household Linkages
• Firms sell products to workers - the friction
is “shopping” or client visit transportation
costs: Retail stores, “retail” services
[insurance dealers, barber shops, retail
brokerage offices…]
• Firms sell products nationally and employ
workers as a factor of production – the
friction is the commuting of workers
MIT Center for Real Estate
Sources of Spatial data on Firms
and employment
• Firms (IRS, SEC) versus Establishments (BLS,
Census). SIC codes
• Federal Establishment files (8 million)
• State surveys (monthly, quarterly, annual)
• Recent release of detailed data by Zip code – “a
revolution”
[http://www.census.gov/epcd/www/zipstats.html.]
MIT Center for Real Estate
Employment dispersal in Dallas CMSA
( see: Shukla and Waddell, RSUE, 1991)
MIT Center for Real Estate
Employment decentralization in
Boston
Boston, City Boston, Suburbs
Employment Category 1970 1980 1990 2000 1970 1980 1990 2000
Private Non-Agricultural 496,548 492,095 539,720 613,385 1,046,936 1,334,948 1,648,863 1,888,350
Mining 180 129 267 (D) 682 1,187 1,513 (D)
Construction 23,159 12,589 14,967 20,803 64,156 59,336 87,537 112,173
Manufacturing 68,078 55,830 34,603 30,071 316,318 367,345 303,883 247,888
Transportation and public utilities 45,458 39,890 38,187 40,911 45,581 55,618 64,333 75,222
Wholesale trade 45,170 31,622 21,706 19,106 56,164 83,974 111,097 116,793
Retail trade 87,315 65,420 67,507 72,227 214,694 263,779 312,328 331,863
Finance, insurance, and real estate 76,743 76,991 94,534 108,413 60,812 97,491 130,903 157,846
Services 150,445 209,624 267,949 321,854 288,529 406,218 637,269 845,450
MIT Center for Real Estate
Monocentric City: Central Business District
Land Rent
rf (d)
r (d)
Firms
(CBD)
Residents
ra
m b Distance (d)
MIT Center for Real Estate
1). Profit/unit output (π)
π = [S – AC – sd] - rf(d)/Q
S = sale price/unit
AC = average cost (inc. capital)
s = shipping cost to port
d = distance to port
rf(d)= firm rent per acre
Q = units of output per acre
In equilibrium profits must be fixed across
locations.
MIT Center for Real Estate
2). Equal profit rent function.
rf(d) = [S – AC – sd - π] *Q
3). Slope of firm rent function:
∂rf/ ∂d = -s*Q
4). Historic changes in s, Q.
- From carts to water to rail to truck
- from 6 story lofts to single story Sheds
5). A “Flat” Industrial Rent Gradient?
[Lockwood and Rutherford]
MIT Center for Real Estate
With a “flat” rent gradient:
Industries move to the edge
Land Rent
Services
Residents
Industries
CBD
ra
m1 m2 b distance (d)
MIT Center for Real Estate
Modern Industrial Location
Why do industries locate:
- Next to Highways
- Next to Airports or seaports
- On land that is recycled, wet, or marginal
But also:
- In areas already developed.
- Near to population ?
[Shukla-Waddell, Struyk-James]
MIT Center for Real Estate
If residential rents look like this – then where do
industrial properties locate?
Land Rent
Negativ
e
Value of
Proximity
Positive Value of Access
Distance from Highway
