Download Slides Class 5 - Rosella Nicolini

GEOGRAPHICAL ECONOMICS
(SECOND PART)
URBAN AND REGIONAL ECONOMICS
José-Luis Roig
WHAT IS URBAN AND REGIONAL ECONOMICS
Urban and regional economics adds geographical space to the economic analysis
of utility-maximizing households and profit-maximizing firms. It lies at the
intersection of economics and geography.
Urban and regional economics recognizes that goods are produced at
certain locations, traded at some locations and bought by individuals who
live at one location and work at another location. Distance between
different economic activities implies costs for transporting goods and
moving people. Distance also defines communication and social
interactions among consumers and workers.
Increasing Urbanization Rates
More than half of the World’s population now lives in cities
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
WORLD
AFRICA
ASIA
EUROPE
LATIN AMERICA AND THE CARIBBEAN
NORTHERN AMERICA
Source: UN World Urbanization Prospects, 2014 Revision, esa.un.org/unpd/wup
2049
2046
2043
2040
2037
2034
2031
2028
2025
2022
2019
2016
2013
2010
2007
2004
2001
1998
1995
1992
1989
1986
1983
1980
1977
1974
1971
1968
1965
1962
1959
1956
1953
1950
0
Urban Concentration in Europe
Population density in 2005 by OECD TL3 region
Economic Concentration in Europe
GDP per km2 in 2005 by OECD TL3 region
Employment in the wine industry (SIC 2084)
Sectoral concentration explained by natural advantages
Employment in the computer software industry
(SIC 7371, 7372, 7373, 7375)
No natural advantages
Employment in the Computer Software Industry (SIC 7371, 7372, 7373,
7375) San Francisco
Employment in the Carpet Industry (SIC 2273)
Productivity increases with employment density
Elasticity around 5%(U.S.),4.5%(Europe)
Doubling density increases productivity by 5%(4.5%)
Agglomeration economies
Firms can benefit from the concentration of other firms (A. Marshall):
- Large labour market
- Large market of intermediate input suppliers
- Knowledge spillovers
Strong regional disparities of GDP per capita in EU
- Blue Banana
- Nordic Countries
- Periphery
- Large difference within
some countries
- Spatial contagion (spatial
diffusion of development)
Accessibility and Transport Cost: The Market
Potential
GDP level provides a crude measure of economic size of a region.
Some insight into the potential of attraction of new activity
Besides its size, one expects the accessibility of a region from others to be another
critical determinant of firms’ and workers’ locational decisions
The market potential aims to capture the idea that being close to prosperous
regions makes a region more attractive because it offers good access to
several large markets
4
Mj
j 1
j i
d ij
MPi  
M: Population, GDP,…
Strong core-periphery
pattern
•More spatial dispersion.
Prosperous states scattered all
over the country
•Regional disparities are much
wider within the European
Union than in the United
States.
Less strong core-periphery pattern
How to model the spatial economy
We must start from at least one of three assumptions:
i.
Space is heterogeneous as in the neoclassical theory of international
trade
ii.
There are externalities in production and/or consumption
iii.
Markets are imperfectly competitive
Theory of Industrial Location
 What leads firms to locate where they do?
 Can space confer monopoly power?
 How do compete firms in space?
Theory of Industrial Location
A. Location of the firm and transport costs
B. Location and market areas: spatial monopoly
C. Location and market areas: spatial competition
A. Location of the firm and transport costs
• The Weber location-production model (fixed coefficients
technology)
• The Moses location-production model (factor
substitutability)
The Weber Location-Production Model
• Transfer-oriented firm: transport cost is the dominant
factor in the location decision
 The firm chooses the location that minimizes total
transport costs
Two types of cost:
- Procurement cost is the cost of transporting raw
materials from the input source to the production facility
- Distribution cost is the cost of transporting the firm’s
output from the production facility to the market
• Four assumptions:
1. Single transferable output. The firm produces a fixed quantity of a
single product, which is transported from the production facility to a
market M
2. Single transferable input. The firm may use several inputs, but
only one input is transported from an input source, F, to the
production facility. All other inputs are ubiquitous.
3. Fixed-factor proportions. The firm produces its fixed quantity with
fixed amounts of each input. No factor substitution
4. Fixed prices. The firm is so small that it does not affect the prices of
its input or its output


The only cost that varies across space is transport cost
The firm will choose that location that minimizes transport costs
Resource-oriented firm. Firm that has relatively high costs for transporting its input.
Example: A firm produces baseball bats
Monetary weight input  mi  ti  10  $1  $10
Monetary weight output  mo to  3  $2  $6
PC  mi  ti  x  10  1  x
DC  mo  to  ( xM  x )  3  2  ( xM  x )
7 tons of beets needed for 1 ton of sugar
Market-oriented firm. Firm that has relatively high costs for transporting its output
to the market
Example: Bottling firm of beverages
Monetary weight input  mi  ti  1  $1  $1
Monetary weight output  mo  to  4  $1  $4
PC  mi  ti  x  1  1  x
DC  mo  to  ( xM  x )  4  1  ( xM  x )
10 tns. of wheat needed for 100 tns. of beer
• Transshipment points and port cities
• Labor markets and location choices
Two inputs and one market: the Weber location triangle
Example: car manufacturer uses steel and plastic
 Single establishment –
profit maximizer – price taker –
perfect competition –
2 inputs single output
 Critical factors m1 m2 m3;
p1 p2 p3;
M1 M2 M3; t1 t2 t3; K
 Maximise profit
by minimising total costs
Profit of the firm:
  p3m3  ( p1  t1d1 )m1  ( p2  t2d2 )m2  t3d3m3
Given the assumptions of fixed coefficients of inputs and fixed prices:
3
Min Transport cost =  mi ti d i
i 1
The Moses location-production model
- Now the firm can substitute in favour of the cheaper inputs
- The distance from the factory to the market, d3, is fixed
- The firm chooses a location along the arc IJ
Budget constraints at the end points I and J
The envelope budget constraint
Location-production optimum
Effect of a road-building program that takes place in the area around M1
B. Location and market areas:
Spatial monopoly
Spatial market areas: linear market with equal transport rates
Space can confer monopoly power on firms
The lower transport and production costs are, the larger the monopoly area
Spatial market areas: linear markets with different transport rates and
production costs
C. Location and market areas: spatial competition
The Hotelling location game
Assumptions
1. Costless firm
movement
2. Homogenous product
3. Consumers equally
spaced along main
street (i.e., sales are a
+ function of the
market area)
4. Perfectly inelastic
demand
5. Identical costs and
transport rates
Welfare implications of the Hotelling result
Loss
Loss
Gain
Effect of price competition on the Hotelling result
•
•
•
•
•
A firm lowers its price assuming that its rival’s prices will not change.
Rival firm lowers its price assuming that the original firm will not change its
price again.
Etc.
Every firm is surprised when the other firm retaliates.
Result: Price shading continues until the firms price at or (temporarily)
below MC
Figueiredo et al (2002) (Case of Portugal)
• Preference for the “home base” (“home bias”)
• Reasons:
- Personal factors
- Tangible, non-transferable assets
- Social capital (networks of institutions and relationships cannot be
replicated outside de home base)
•Data on firms can identify entrepreneurs’ “prior locality of economic
activity”
Spatial distribution of new manufacturing plants
Spatial distribution of new manufacturing
Plants created in the investor’s “prior locality created outside the investor’s “prior locality of
economic activity”
of economic activity”
Investor I weighs in all the regional characteristics of the available spatial
choice set and selects the one that will potentially give him the highest profit:
k
 ij    r X rj
r 1
Linear combination of characteristics of the area
An additional variable is included that allows the investor to value differently
the potential profit associated with each choice
k
 ij    r X rj  Dij
r 1
Dij  1
 0
Region coinciding with the investor’s prior locality of economic activity
If there are lower costs (and higher profits) associated with the prior
Locality of economic activity of the investor
Alternatively:
k
k
r 1
r 1
 ij    r X rj    r X rj Dij  Dij
The investor values differently the impact of relevant factors in accordance with
the local/non-local nature of the choice
Those factors that affect potential profit by reducing information costs are not as
significant when the choice under consideration is the investor’s home base
For other locations, the investor will have higher information costs and thus may
value agglomeration economies and proximity to core regions where more and
better quality information is available
Effect of the localization in the prior locality of economic activity on each
characteristic:
Decisions made by 1246 start-ups between 1995 y 1997
Information on the owner situation between 1992 y 1996
Where the current owner (entrepreneur) when worked before the creation of the
new firm
Spatial unit: “concelhos” (275 with an average area of 322.5 km2 )
A STRUCTURAL MODEL: DIXIT-STIGLITZ-KRUGMAN
Accessibility to markets and firm’s profit: a framework for the
empirical analysis


q
rs
   ( p  mr ) rs q  mr
 1
rs
rs
pr
r
rs
mill price  rs iceberg transport cost
marginal cost
mr
 elasticity of substitution/price elasticity qrs quantity sold by the firm in s
prs  pr rs
pr  mr

 1
prs   rs mr

 1
In the short-term with a given number of firms:
qrs   p 


r rs


sYs Ps
 ( 1)
Ps   r nr ( p r rs )

 ( 1)

1
( 1)
r    rs  Fr  cmr ( 1) RMPr  Fr
Total profits of r over all markets
s
c    (  1)  ( 1)
where
RMPr   s rs  sYs Ps 1
rs   rs1
is the Real Market Potential
freeness of trade
RMPr   s rs  sYs Ps 1
recall
MPr  
s
Ys
d rs
Market potential and factors attraction
(Head y Mayer, 2004)
Location decision of firms between two locations i and j
depends on i   j →
Carlton (1983) logit model
Hypothesis: firms locate where markets accessibility is highest
Sample de 452 Japanese branch plants localized in 57 regions from 9 EU countries
in the period 1984-1995
Ur 
ln   ln( r  F )
  ln mr  (  1)1 ln RMPr
 1
ln mr   ln wr  (1   ) ln  r  ln Ar
Variable costs: wages w¨r price of other inputs (land, intermediates)  r
Ar
Total factor productivity
U r   ln wr  (1   )ln r  ln Ar  (  1) 1 ln RMPr
U~r   ln wr  (1   ) ln r  ln Ar  (  1) 1 ln RMPr   i
Pr 
expU r
 s expU s
Construction of the market potential:
RMPr   s rs  sYs Ps 1
Problem: we do not have data of rs and
Ps
We need to proxy these two variables: we will do it with trade flows
Trade flows estimated with a gravity equation:
qrs  prs Ps( 1) sYs
X RS  nR qRS pRS  nR p1R RS   S YS PS 1
Market potential
ln X RS  FX R  ln RS  FM S
Supply capacity of export country
Market capacity of the import country
FX R  ln(nR p1R )
FM S  ln(PS 1  S YS )
ln RS   ln d RS   S FRRS  LRS FRRS
Distance, border effect , same language
ln X RS  FX R  FM S   ln d RS   S FRRS  LRS FRRS
X RR
National production minus exports
ˆrs  exp(  ˆS  ˆ LRS )d rs
Regions from different countries
ˆrs  d rs
Regions from the same country
ˆ
ˆ
 2 Superf r 
ˆ
ˆrr  d rr  
 
3
 sYˆs Pˆs
Ys / YS
 1
ˆ
Intra-regional trade
 (Ys / YS ) exp(FMˆ S )
Share of GDP of s on national GDP of country S
Potential built for 18 sectors (2 digits) each year
Production costs:
1. Labor costs
observable (payroll sector /number of employees in the region)
additionally: non labor costs (only vary across countries)
Unemployment rate
2. Other costs
non observable
a. Capital cost affected by subsidies/taxes:
- Corporate tax rate (only vary across countries)
- Elegibility to benefit from Structural Funds (Objective 1)
b. Control for land supply and price:
- Area of the region
Evidence on clusters. 3 types:
- Number of establishments in the two-digit industry region
- Number of Japanese affiliates in the three-digit industry region
- Number of affiliates owned by the same Japanese parent or members of
same vertical keiretsu
Possible efects of these clusters:
- Lowering intermediates prices     regional production networks
- Share knowledge (non observable)   A
- Clusters will form around the same exogenous sources of low
input costs or high productivity
Hypothesis: clusters form in areas with high market potential in the relevant
industry
The hypothesis would receive support if after controlling for market potential,
the presence of same industry firms lowers the attractiveness of
a region
Main results:
Ambiguous with respect to RMP:
- 10% of RMP increases the probability of locating in the region in 3%-11%
- “theory doesn’t pay”
- Agglomeration variables the most important but, omitted variables?