The Impact of Optimal Tariffs and Taxes on Agglomeration



7 Stability and agglomeration

While the last section has analyzed the welfare effects of taxes and tariffs
the aim of this section is an analysis of the consequences of these policies for
the stability of core-periphery equilibria. Since the real wage relation had
been determined to be the crucial variable characterizing stability of any
equilibrium, the remainder of this section will concentrate on the effects of
the derived optimal policies on this variable.

If policy is inactive, as demonstrated in section 3, the model generates
an intermediate range of transport costs, for which core-periphery equilibria
become stable. This result has been explained by the relative large weight of
corresponding forward and backward linkages outweighing dispersion forces.
Now, optimal policies concerning tariffs and taxes, affect the forward linkage
by their impact on prices and the backward linkage by reallocating demand.
The interplay of these effects determine in which direction policies shifts the
real wage relation

Consider first the non-cooperation case where both regions goal is the
maximization of regional welfare by choosing policies according to (12). In
general, as mentioned above, the corresponding tax-tariff equilibrium can be
determined only numerically, but for the extreme core-periphery distribution
of
L = 0 or L = 1 also analytical results can be derived. Fortunately, the core-
periphery distribution is also of special interest since the question whether
agglomeration is sustainable can be answered by analyzing the sustainpoint.

Concentrating on the arbitrary case of L = 0, where all industry is con-
centrated in the foreign region, welfare optimizing policies can be derived
from (12) and are given by:

TI,Opt


= TA,Opt


__ '/'*       __ 1

T A,opt   σ


*

TI,Opt


σ-γ

σ2 — γ


(19)


Substituting (19) in (10) yields the real wage relation:

Wr = τ2-2σ(σ + γ) (σ — 1)σ+γ (σ2 — γ) + (σ — 1)γ-σ+1

(20)


WR               τ 1+γ (2σ - 1 + γ) σγ σ

16



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