Regional impacts of regional integration. Tony Venables_ DFID _ Oxford

Document Sample
Regional impacts of regional integration. Tony Venables_ DFID _ Oxford Powered By Docstoc
					 Regional impacts of regional

     Tony Venables, DFID & Oxford
• Integration between similar economies
• Integration and economic differences
  – Underlying comparative advantage
     • Comparative advantage and trade diversion
     • Regional vs international trade

  – Acquired comparative advantage
     • Wage gradients and market access
     • European urban structures
 Comparative advantage and trade diversion
                 Trade diversion a problem for the
Capital          ‘extreme’ country: imports from
abundance        partner are in line with regional but
                 not global comparative advantage

                        Regional integration brings
     Portugal           convergence

     World ave

                         Regional integration brings
      Uganda             divergence
        Regional vs international trade

 Country 2                      Copper

Maize      Copper          Equipment

                                          R of W

  Country 1
        Regional vs international trade

What is effect of integrating economies 1 and 2?

Symmetric equilibrium with free international trade in both
maize and copper, real income both countries = 1.

Only regional trade in maize
Capital stocks fixed:      Country 1     Country 2
       Initial             0.89          1.08
       Regional integr.    0.92          1.09
Capital stocks endog:      Country 1     Country 2
       Initial             0.59          1.04
       Regional integr.    0.71          0.95
Increasing returns and acquired comparative
    Regional integration and regional inequalities

• Regions with good market access, good access to suppliers, and
the other advantages of being in a cluster pay relatively high wages.

•   Centre – periphery wage gradient in the EU.

•   Effects of economic integration: Ambiguous:
        • improves the market access of remote regions
        • facilitates the development of clusters/ economic centres.

        • Brief look at the data and speculation about future
The time path of spatial income inequality (Theil index EU NUTS2)


          Between country

               Within country
Geography and per capita income, NUTS2.

• Regression of per capita income on population
density and distance from centre: (1980- 83 and 1997-
    – Centre-periphery income gradient: present with
    and w/o country fixed effects.
    – Regions with high population density growing
    faster (w and w/o country fixed effects)
    – With country fixed effects, regions with high
    population density have higher income, and effect

High density regions (cities) are doing well:
• In line with economic geography theories of the gains from
• In line with econometric studies of productivity in cities.

What might be the implications of further integration –
particularly increased labour mobility -- for the relative
performance of EU cities?
•Zipf’s law (the rank size rule) : Rank cities by size from the
largest to the smallest, then the nth city has population 1/n that
of the largest.

• New York,highest ranked city, population of 19,876,488.
  Santa Barbara, 100th ranked city, population of 198,760.

• Empirics:    Zipf’s law holds for US, not for the EU.
              US                             EU25

11                               11
10                               10
9                                9
8                                8
7                                7
6                                6
5                                5

4                                4
    0   1     2     3    4   5       0   1   2      3     4   5
            ln city rank                     ln city rank
Largest cities                          Smallest cities
Name                Rank   Population   Name         Rank   Population
                           (thousand)                       (thousand)
Paris               1      11330.7      Grenoble     87     521.7
Rhein-Ruhr          2      11285.9      Szczecin     88     505.0
London              3      11219.0      Murcia       89     486.0
Ranstad (Neths)     4      6534.0       Belfast      90     484.8
Madrid              5      5130.0       Bari         91     480.7
Milano              6      4046.7       Montpellie   92     466.3
Berlin              7      3933.3       Bratislava   93     428.8
Barcelona           8      3899.2       Dublin       94     418.8
Napoli              9      3612.3       Messina      95     415.3
Manchester-L’pool   10     3612.2       Coventry     96     409.1
 What if…..? Change city size distribution
 holding constant the total population in the top
 96 EU cities

Zipf’s law:                     US city size distribution.
1st city nearly triples to      1st city nearly increases to
32.4m.                          18.4 m.
2nd city increases to 16.2 m    2nd city increases to 14.4 m
3rd city shrinks to 10.8 mill   3rd city shrinks to 8 m
4th – 8th ranked cities         4th – 10th ranked cities
increase.                       increase
All remaining cities shrink     All remaining cities shrink
Concluding comments

 • Analysis of regional integration remains
 fascinating because:
    • Varying degree of mobility of knowledge/
       services/ tasks/ goods/ factors
    • Some sources of increasing returns, some
       of decreasing
 • Need to understand effects on particular
 countries/ regions/ cities, as well as on
 • Needs both innovative theory and good applied