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# Chicago Employment

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• pg 1
```									Suburban Sub-centers and
employment density in
metropolitan Chicago

Daniel P. McMillen (Tulane U)
John F. McDonald (U of Illinois)
Journal of Urban Eco, 1998
Introduction (1)
• A location well served by highways, rail lines and
other transportation network may attract many
firms even when the firms have no interest in locating near
one another ---- suburban sub-center may form near
transportation centers. Accessibility to these sub-centers
lead to employment concentration. This implies that scale
economies -- agglomeration        (transportation
saving cost) can generate concentration of employment
at certain locations within an urban area.
Scale Economies - transportation
network
• Transportation
network
Theoretic Framework
• Bid-rent function is used to see effects of suburban sub-
center on employment density. A bid-rent function
represents the maximum amount a firm or an individual
will pay for a unit of land. In standard mono-centric model,
the bid-rent function is a simple function of distance
from the city center -- because all economic
activities is assumed to take place there. Here, sub-urban
interchanges and other features of the
transportation network. (cont…)
Theoretic Framework (2)
• Such accessibility measures are represented by the vector
A, sub-center access measures by vector S and
idiosyncratic characteristics (clear, level land, swampy) by
C, this affects construction cost.
• Hypothesis
• Employment probability in the sub-centers
• Their impact on employment density
Methodology
• Non-residential: lnR1 = 1X + 1         X = (A,S,C)
• Household:          lnR2 = 2X + 2
• Net employment density: ln(E/Le) = ln R1 + 1 = 1X
+1+ 1
• Gross employment:lnD = Z +  ------ (1)
• Employment density is a function of the same variables
that determine land rents.
• Employment density increases when non-residential land
rent increases
Methodology (2)
• Employment density increases when non-residential
land rent increases
• Employment density decreases when residential land
rent increases
•     Prob (I=1) = Prob ( Z +  > 0 )      ------- (2)
• This equation determines whether there is some
employment in a zone or not.
• Correlation between  and  implies employment density
functions are subject to selection bias.
Estimation Procedure
• Two-stage method: a) probit/logit b) OLS
• Maximum-likelihood estimation:
• E (lnD/I=1) =  Z +u  ( Z) /  ( Z)
• Northeastern Illinois Planning Commission data
• Sub-center identification: A set of nearby tracts that
each have at least 10 employee/acre in either 1980 or
1990 and together have an average over the 2 sample years
of at least 10,000 employees ---20 sub-centers
Estimation Results
• Expect: Increasing distance from a suburban
employment sub-center lowers non-residential bid
rents if scale economies exist --- lower employment
density -- negative coefficient on distance ---- lower
employment
Estimation Results (2)
T able 4 – M arginal effects for expected log-e m ploym ent density

V ariables                w ithin 15 m iles      m ore than 15 m iles
O f o,hare             from o’hare
------------------     ------------------------
1980          1990     1980          1990
------        ------   -------       -------

D istance to O ’hare      -0.079       -0.072    -0.005       -0.017
A irport                  (3.705)      (4.750)   (1.123)      (4.550)

D istance to C B D        -0.055       -0.026    -0.007       -0.008
(2.604)      (1.372)   (2.270)      (2.481)

D istance to com m uter -0.239         -0.110    -0.250       -0.200
T rain station          (1.506)        (0.727)   (5.771 )     (5.324)

D istance to high w a y   -0.134       -0.131    -0.083       -0.138
Interchange               (2.032)      (2.068)   (2.734)      (5.045)
(absolute asym ptotic t-values are in parentheses)
Estimation Results (3)
T able 4 – M arginal effects for expected log-e m ploym ent density

V ariables             w ithin 15 m iles      m ore than 15 m iles
O f o,hare             from o’hare
------------------     ------------------------
1980          1990     1980          1990
------        ------   -------       -------

P roportion w ater     0.202        -0.870    -1.225       -1.184
(0.114)      (0.345)   (3.095)      (3.406)

P roportion rail       1.968        1.552     4.272        3.180
(2.898)      (2.033)   (7.288)      (5.450)

P roportion parks      -1.110       -1.113    -0.608       -0.482
A nd open space        (2.382)      (1.103)   (3.490)      (3.057)

D istance to nearest   -0.339       -0.351    -0.126       -0.117
S ubcenter             (6.219)      (4.415)   (7.902)      (7.783)
(absolute asym ptotic t-values are in parentheses)
Conclusion
• Correlation between errors of employment density and
employment probability exists ---OLS estimates are
subject to selection bias -- either two-stage method or
maximum likelihood is appropriate.
• Transportation facilities are subject to economies of scale.
Firms will cluster near transportation facilities even if there
are no direct benefits of locating near one another. The