Modelling infrastructure and migration in a NEG model Luigi Marattin University of Bologna TERA FINAL CONFERENCE Ghent - 26 th August 2008. 1. THE NEG APPROACH 2. THE MODEL 3. RESULTS AND POLICY IMPLICATIONS. PRESENTATIONS PLAN. N ew E conomic G eography (Krugman 1991)
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University of Bologna
TERA FINAL CONFERENCE
Ghent - 26th August 2008
2. THE MODEL
3. RESULTS AND POLICY IMPLICATIONSPRESENTATIONS PLAN
New Economic Geography (Krugman 1991)
It attempts to provide answers to one question:
What leads the process of concentration / dispersion of economic activities in a given geographical territory?1. THE NEG APPROACH
not so much why a particular industry ends up in a particular place, but rather why manufacturing activities in general end up in a “core” region(s), leaving the other (s) relatively underdeveloped (“periphery”).
INDUSTRIAL vs AGRICULTURAL regions
Heart of EU structural policy problem
SHARE OF MANUFACTURING IN REGIONAL INCOME (determining the relative weight and importance of the crucial sector)
DEGREES OF ECONOMIES OF SCALE (the higher it is, the higher the need for concentration so to exploit cost advantages)
TRANSPORT COSTS (the higher they are, the less incentive to concentration, since it is convenient to locate close to their final market)THREE FACTORS
TWO SECTORS relative weight and importance of the crucial sector)
Agricultural: perfect competition, constant returns to scale, homogenous good traded costlessly.
Manufacturing: monopolistic competition, increasing returns to scale, transport costs.
Labour force fixed in the short run, but responding to real wage movements in the long-run.
MICROFOUNDED OPTIMIZING BEHAVIOUR.THE FORMAL FRAMEWORK
The arising of core-periphery pattern depends on three relative weight and importance of the crucial sector)exogenous parameters:
1) the share of demand going to manufacturing
2) the elasticity of substitution / degree of economies to scale
3) transport costs
THEY ARE ALL EXOGENOUS.
Sooner or later we always bump into something exogenous, especially in economic modelling.
But number 3 is particularly unsatisfying, especially if coupled with the absence of public sector.
INSERT PUBLIC SECTOR INTO THE STANDARD FRAMEWORK: relative weight and importance of the crucial sector)
- distortionary taxation on firms
- public investment in infrastructure
TRADE OFF: Costs / benefits of public expenditure
WHAT ARE THE EFFECTS OF THESE INNOVATIONS ON THE MODEL’S PREDICTION ABOUT AGGLOMERATION PATTERNS?2. MARATTIN (2006) MODEL
The methodology and the solution methods relies heavily on Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.
That is virtually the only empirical application of a (standard) theoretical NEG model.
Our attempt applies a more sophisticated model to six (regional or sub-regional) study areas.
Policy results should be handled rather carefully.THE NOVELTY AND A WARNING
Policy experiments on taxation Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.:
Tax rate in the urban region: +2%
“ “ “ “ “ : +4%
Tax rate in the rural region : +2%
“ “ “ “ “ : +4%Simulations
Policy experiments on labour supply Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.:
Labour supply in the urban region: +5%
“ “ “ “ “ : +5% (intra)
“ “ “ “ “ : +15%
“ “ “ “ “ : +15% (intra)
Labour supply in the rural region: + 5%
“ “ “ “ “ : +15%
Model is calibrated on real data collected by partners. Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.
Structural parameters are calibrated as in Fingleton (2005) or as standard in related literature.
Results show the quantitative effects on:
1) Income differentials
2) Price differentials
3) Nominal wage differentials
4) Real wage differentials
We show only 1) and 4).
1)Home market effect Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.: nominal wage is higher in the bigger region
2) Competition effect: nominal wage is lower in the bigger region
3) Price index effect: prices are lower in the bigger region
(1) and (3) pushes towards divergence
(2) pushes towards convergece
OUR MODIFICATION (distorsionary taxation to finance infrastracture) MESSES EVERYTHING UP, TWICE.FORCES AT WORK
1) BEING DISTORTIONARY, ALTERS NOMINAL AND REAL VARIABLES Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.
2) ITS REVENUE IS USED TO REDUCE TRANSPORT COSTS, WHICH IN TURN IS ANOTHER FORCE PUSHING TOWARDS CONVERGENCE/DIVERGENCE.
SO TRADITIONAL NEG RESULTS CAN BE SIGNIFICANTLY MODIFIED.WHY TWICE?
3 a : RESULTS FOR TAXATION Fingleton (2005), which simulated the standards Krugman 1991 model on Uk.
3 b : RESULTS FOR MIGRATION3.RESULTS AND POLICY
Financing infrastracture via taxation in U affects negatively the income of U and does not significantly affect income in R.
Income differentials reduce.
Net effects (NEG three traditional ones + distorsionary taxation) pushes towards divergence.POLICY IMPLICATIONS
Financing infrastracture via taxation in the R affects the income of R and does not affect income in U (exception:Greece)
Income differentials increase.
Net effects pushes towards convergence, but with a less extent.
HOW TO FINANCE INFRASTRACTURE BETWEEN URBAN AND RURAL REGION?
Tax the urban: income differential reduce, but push for divergence.
Tax the rural: income differential increase, but it is a help for convergence.
Increase in the size of U increases the income differentials, much more if it occurs at the expense of R (internal migration)
It promotes the cumulative effect for divergence.
Specularly, increasing the size of R reduces the income differentials and pushes for convergence.POLICY IMPLICATIONS
1) Allowing for endogenous provisions of infrastructure (via distiortionary taxation) can significantly affect traditional NEG conclusions
2) In the six study areas, we achieve qualitatively identical and quantitatively not-too-dissimilar results.
3) The choice of who bears the burden of infrastructure building is relevant for income differentials and convergence/divergence.
4) Effects on real wage differentialts must, in real life, be mitigated because simulations were run under the assumption that ALL tax revenue goes into infrastructure building.CONCLUSIONS