Policy, Flanning, and Research
WORKING PAPERS
Trade Policy
Country Economics Department
The World Bank
January 1 990
WPS 326
Do Exporters Gain
from Voluntary
Export Restraints?
Jaime de Melo
and
L. Alan Winters
The results of the model developed here are a strong indictment
of VERs. For most plausible parameter values, VERs redirect
exports, reduce the size of industries for which countries have
comparative advantage, and cause overall economic losses -
especially if the affected industry is large in the market for its
factors of production.
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Polay nning, and Research
Trade Policy
Most economic literature concentrates on the productive. They develop a general theoretical
rent transfer accruing to exporting countries model that establishes qualitative conditions
when a voluntary export restraint (VER) is under which a VER will result in industry
binding. It suggests that VERs are not very contraction, spillovers of exports to unrestricted
harmful for the exporting country. De Melo and markets, and losses in national welfare.
Winters argue that this view is misconceived.
They estimate key parameters of supply and
Most work has focused on the welfare loss demand for leather footwear exports from
to the imrporting country arising from a loss of Taiwan subject to the U.S. Orderly Marketing
income transfer combined with a distortionary Agreement, and explore the implications in '
loss in efficiency. Implicit is the message that calibrated simulation exercise.
the often large rent transfer to the exporting
country is likely to compensate for any induced The results are a strong indictment of VERs.
inefficiency losses.
For most plausible parameter values, VERs
De Melo and Winters study the effects on redirect exports, reduce the size of the industry,
distribution and efficiency when VERs force and cause overall economic losses, especially if
factors out of industries in which they are most the affected industry is large.
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Produced at the PPR Dissemination Center
Do Exporters Gain from VERs?
bv
Jaime de Melo
and
L. Alan Winters
Table of Contents
I. Introduction 1
II. A Simple Model 3
Industry Profits 4
Firms' Behavior 5
Imposing the VER 8
National Welfare 13
III. Estimation 18
IV. Welfare and Distributional Effects of VERs: Some 25
Illustrative Simulations
Conclusions 31
Notes 33
References 34
Appendix 35
We are grateful to Bela Balassa. Paul Brenton, Shanti Chakravarty, Nicola Rossi,
Wendy Takacs, and to participants of the STEP-CEPR Conference "Adjustment in
Developing Countries' (May 1989), the Europe Research Workshop on International
Trade (June 1989), and the George Washington University Economics Seminar for
comments on an earlier draft. We thank Maria D. Ameal, Alexander Pfaff, and Julie
Stanton for logistic support. This research has been financed by World Bank Research
Project 672-40.
I. INTRODUCTION
The distinguishing feature of Voluntary Export Restraints (VERs)
is that they are administered by exporting countries. So long as the VER
is binding, exports of the product under the VER, earn a scarcity premium
and much work has been dons to estimate the cost to importing countries --
and hence the gain to exporting countries -- from this transfer.l/ There
are, however, other effects in exporting countries arising from a binding
VER. These effects stem from the contractionary pressure on the industry
subjected to the VER and hence against factors employed in it. By forcing
factors out of industries in which they are most productive, VERs can
impose significant efficiency losses on exporters. Curiously, these
losses, which must be balanced against the rent transfer from abroad. have
been neglected in the literature. The purpose of this paper is to explore
these effects systematically.
We study the negative effects of VERs on exporters from three
perspectives. First, we develop a fairly general theoretical model of an
industry sub3ect to the VER (section 2). The industry sells its output to
two markets, one restricted and one unrestricted. We examine the effects
of a VER in the restricted market on sales in the unrestricted market
(spillover effect), on industry size and profits, on national uelfare, and
on the returns to factors in that industry. The analysis suggests that the
effects of a VER depend crucially on a few product supply and factor demand
elasticities. This leads us, in section 3, to carry out an illustrative
exercise to estimate these key elasticities for the case of leather
footwear exports from Taiwan which were subject to the USA Orderly
Harketing Agreement tOHA) during 1977-81. Although not as precise as
2
desirable because of data limitations, these econometric estimates suggest
that the demand and supply of footwear are quite elastic; they lend strong
support to the qualitative prediction that the OMA induced some splllover
to unrestricted markets and some contraction of the industry with attendant
efficiency losses. Finally, in section 4, we combine the results of the
previous two sections into a simple simulatlon model which analyzes the
lLkely effects of a VER on national welfare and lncome dlstribution, taking
into account efficiency losses. For plausible elasticity values we
establish that a typical VER will lead to a worsening income distribution,
as profits in the affected industry rise and the returns to other factors
-- notably labour -- fall. Although not formally part of our model, it is
clear that factor returns will tend to fall most for immobile factors and
especially for labour whose skills are speclflc to the restrLcted lndustry.
We also establish that exporting countries are likely to incur an overall
welfare loss in spite of the rent transfer gain even when the industry
under the VER is of non-negllglble size.
The results of this paper are a strong indLctment of VERs. To be
sure, VERs are less harmful to exporting countrles than are equivalent-
sized import quotas administered by the importing country, but nonetheless,
they can impose notable welfare losses wherever they restrict industries
accounting for significant shares of the exporters' economic activity or
when they make use of particular and relatively immobile skills or physlcal
capital. This suggests that the complacency with whlch the economics
profession has treated the exporters' consequences of VERs has been
misplaced.
3
II. A SIMPLE MODEL
We consider the simplest possible model of a VER. For convenience
we term the restricted industry footwear, but the results generalize to
virtual any competitive industry. We assume that firms in an exporting
country produce footwear for two markets, A and B, using a single composite
variable factor of production, Z. For generality we assume that the two
types of footwear may differ and allow for the possibility that the
marginal costs of one may depend on the output of the other. One possible
justification for this is the existence of a second implicit factor of
production which is fixed in supply - e.g. entrepreneurship or
infrastructure. We write the variable factor requirements for producing
the outputs destined for the two markets, XA and XB, as
(1) Z - G(XA,XB)
where Z is the quantity of the composite factor used,
GA, GB > 0, where Gi - Sz and
Oxi
G is homothetic but homogeneous of degree r < 1.
We consider the consequences of imposing a VER or exports to
market A; those to market B are assumed to be always unrestricted. Firms
are assumed to be simple profit-maximizers and the entire output is
exported. 2/
4
Industry Profits
Total profits from footwear in this simple model are
(2) f - PAXA + PBXB - WZ
where Pi are the prices received from market i, i - A,B
Xi the quantities supplied, and
V the Ivage' of the composite factor.
Taking the total differential of (2), substituting for dXg from the
differential of (1)
(3) dZ GAdXA + GBdXB-
If we use ni for the inverse of the mark-up of price over marginal revenue
in market I, i.e.
(4) vi'1 + ei - A,B,Z
where ei is the elasticity of demand, ei < 0, i - A, B and eZ is the
elasticity of supply of the composite factor, ez > 0, we simply obtain
'IAPA 9B3B 1 BPA
(5) dw - AG _A B v dZ
A' ds D XA + GB
(5') dw = dXA.- NdZ
5
Equation (5) shows that tne effect on pLofits of a shock to the footwear
industry may be decomposed into a par relating to changes in the
allocation of sales between markets (MeXA) ard a part relating to changes
in the overall size of the industry (NdZ). Moreover, the parts bear a
perfectly simple interpretation. 7APA is the marginal revenue from market
A and GA the marginal input requirement for producing for market A: thus
the bracketed component of M reflects the marginal return to factors
* s to XA less that of those devoted to XB. GAdXA is the factor
requirement for a marginal change in XA. If market A generates greater
marginal returns to the factor than does market B, an increase in XA is
desirable. The term N compares the marginal returns to employing extra
factors producing XB with their marginal cost. The latter is the wage
marked up by a term reflecting any tendency for the wage to have to rise as
employment increases. If marginal revenue exceeds marginal costs,
additional factor use, i.e. additional output, would be desirable.
Firms' Behavior
We assume that the footwear industry comprises many identical
representative firms, each of which maximizes profits subject to the
production relation (1). Using to denote firms' outputs and inputs, the
firms' maximization problem is
(6) max L - PAXA + PBXB - WZ + X [Z - G(XA,XB)J
Homotheticity implies that we may use the same derivatives of G( ) for both
firm and industry since both face the same prices.
6
The first order conditions for (6) depend on whether the firm is a
price-taker or not. If it takes both prices and wages as given it solves
(7a) PA - XGA m °
(7b) PB - XGB 3 °
(7c) W - X -
(7d) Z - G( ) - O
whkreas if it recognizes its power in both markets, the first order
conditions become
(8a) VANA - r'GA - 0
(8b) JBPB - )'G1 - 0
(Sc) yZU - o
(8d) Z -G ) -o
If it has market power only in certain markets it mixes (7) and (8)
appropriately.
It is simple to show that if the firn has and exploits the same
market power as exists for the footwear industry as a whole, then M-N-O.
For example, a monopolist with power to discriminate between markets and
with monopsony power in factor markets maximizes industry profits as well
as his own. Conditions (8a) and (8b) equate the ViPi/Gi and thus make M-0.
while conditions (8b) and (8c) give VBPB/0GB zW and thus make N-O.
Similarly if the industry and all the firms are genuine price- and wage-
takers, so that leil - " all i, vi - 1 and (7) ensures that M-N-O. In both
cases small changes in XA and Z have no effect on profits because they have
7
already been maximized with respect to these variables. Non-marginal
changes will reduce the monopolist'ulmonopsonist's profits, but will have
no effect on profits in the competitive case, This is because wi-th fixed
prices and wages, output for each market is expanded until price just
equals marginal cost which, because of competition, equals average cost.
It is only the implicit fixed factor, which gives G( ) decreasing returns
to scale, that makes the equilibrium determinate in this case.
If, on the other hand, individual firms do not (cannot) exploit
the industry's monopoly or monopsony power, profits are not maximized at
the market equilibrium, and the posibility arises that policy-induced
changes in XA and Z may be beneficial. This is essentially a situation in
which the optimum tariff or export tax is non-zero. Substituting (7) into
(5) yields
M T 1 [ ]w and N - [ .l]W
I'eA EB CB CZe
The term N is negative, so a contraction in the industry, dZ 0, only a strongly negative relation-
ship between costs for XA and for XB could make (10) positive. That is,
assuming that marginal costs for each product are rising and that increases
in the output o-f one product raise, or at least do not much reduce, the
marginal costs of the other, a forced reduction in XA will lead to an
increase in XB. Competitive firms will respond to a VER in market A by
increasing sales in market B - the cause of Hamilton's (1989) domino
effect, or in the terminology below, the "domino diversion' of exports.
Further substitution yields
(11) G [- G 2- H
A A iX:B GEB+~ j-
z
10
The expression H is not immediately interpretable intuitively, but
it may readily be shown that almost certainly H > 0, i.e. that a VER will
lead the industry to contract. The first two terms of the numerator and
denominator are identical and negative. The final term of the numerator
will be small (and possibly positive), thus either hardly affecting (or
possibly reducing) thc absolute value of the expression, while the effect
of the final term of the denominator is negative, so increasing its
absolute value. 3/ Only very strong interactions between products A and B
in production could catuse H to become negative. If we rule these out, it
is plain that an enforced fall in XA will also reduce the scale of the
industry's operations. A VER leads the industry to contract.
Substituting (11) into (5) and recalling the definitions of H and
N for price- and wage-taking firms
(12) | [ [ + | d Gm [1M + N.H]G
The term N.H is almost certainly negative, so we conclude that unless the
difference in the elasticities of demand between the restricted and
unrestricted markets is large and favorable, a *small" VEk on a price- and
wage-taking industry boosts profits.
Equation (12) also illustrates some special cases.
* If the industry is genuinely price- and wage-taking, ei -
profits are unaffected by the VER. In fact, they are fixed
at zero if we assume identical firms.
12
* If the industry is a genuine wage-taker, e2 Z U, there is a
presumption that the VER is profit-enhanclng, because (12)
reduces to [(el-(l-H)e§l], and H is unlikely to be far
dlfferent from unity.
* If the elasticLtLes of demand are equal across markets, the
VER is certainly proflt-enhancing because H - 0 whlle N < 0.
* If demand in the unrestricted market is perfectly elastic,
CB- , the VER cannot harm profLts.
Figure 1 presents a simplified account of the model of this
section. It is drawn in factor-factor price space. The lines HRi report
the aggregates of firms' marginal revenues gained from an extra unit of 2
being devoted to producing for market i, PL/Gj or liPl/Gi, i-A,B according
to industry structure. MRz is their sum under free trade. 4/ Coupled with
a rising supply curve for Z, Z - Z(W), the total marglnal revenue function
(MR0) determines the vage rate (W0) and the size of the industry (ZO). It
is clear that at thls wage rate all the first order conditlons are met.
A
When the VER is imposed in A, it implies factor usage 21. The VER
causes the marginal revenue curve to fall to zero at any higher level of
input. MRB is unaffected. The aggregate marginal revenue function, MR4.
is now kinked, and the new industry equilibrium is defined by W1 and 21. It
is plain that the industry has contracted, but that at the lower wage more
resources are devoted to supplying market B. It is also plaln that the
sizes of the varlous changes are affected by the size of the shock,
A A i
(21 -ZO), and the slopes of the various schedules. The slopes of the MR2
curves depend on EL, Gj and Gii, while the slope of the factor supply func-
tion depends on CZ
12
Fiture 1
Z1 ~ ~~ ~ ~~~~~ ~ ~ ~~~~~~ ZO (w)t1
w
MR z ~~MR z MRa
zA zA zB B z z
1 ~~0 1 0
13
National Welfare
So far we have equated national welfare with industry profits.
This is plainly too restrictive. Assuming that all industries in the
economy are competitive, so that wages represent marginal products, we
approximate national welfare by the sum of profits (non-zero only in
footwear) and factor incomes.
(13) U - I + WL
where L is the size of the factor market from which footwear draws its
factors. If there are factors of types which are not used in the footwear
industry they are excluded from L and an additional term should be added to
(13) to cover their income. However, since this is assumed constant, we
can ignore it.
The change in national welfare differs from the change in industry
profits by
(14) LdW -LW dZ
zez
This effect may be added to N in equation (5), so that in the case
of price- and wage-taking firms, the new value of N becomes
(15) N - 11 1 L - Z
(15) N--
CB CZ]
14
It is plain that A could now be positive and that it is more likely to be
so the lower the elasticity of supply of factors to footwear and the larger
the stock of factors outside footwear whose wage is affected by
developments in the footwear sector. Since the extension of the welfare
criterion affects no part of the previous calculations other than N, we may
straight-forwardly generalize (12) to write
[[ 11 1 L-Z ~G
(16) - +6 B +6 GA J
aA eA |C ( B C B eZ Z |
This is more likely to be positive than (12) because 6z now enters
with a positive sign and is multiplied by a factor that may exceed unity.
All the special cases discussed above follow through to (16). An
additional case of interest is where only those factors initially in the
footwear industry enter the welfare criterion. This implies that one is
considering the effect of the VER on the industry (workers and entrepre-
neurs) as a whole. In this case (16) collapses to e6' - (1-H) lB, -which
is likely to be negative unless demand in the restricted market (A) is sig-
nificantly more elastic than demand in the unrestricted market (B). 5/
Further manipulation allows us to rewrite A as
L B 7N
15
wheret eN is the elasticity of demand for factors with respect to the wage
in the non-footwear sectors using L, EN c 0. This expression would be
relevant to an assessment of a footwear VER because if the total stock of
factors were fixed, then the change in the supply of factors to the
footwear industry would merely be the opposlte of the change in the demand
for them elsewhere. With this definition of B, our final welfare criterion
becomes:
(17) dAK1-I+[u HIGA
ditA C A CB IE E 8 N |
Intuitively, (17) suggests that the effects of a VER depends on an
allocation component and a size component. The allocation component asks
whether switching output between markets is beneficial and the size
component whether switching factors between sectors is beneficial. 61
To recapitulate, equations (16) and (17) suggest that an empirical
estimate of the welfare effects of a VER must consider:
* the elasticities of demand in restricted and unrestricted
markets;
* the elasticity of factor supply to the affected industry or
the elasticity of factor demand elsewhere in the economy; and
* the parameters of the production function or factor input
process.
16
So far, we have analyzed the effects of a VER entirely in primal
terms, dealing directly with the parameters of the demand and production
functions. That approach is useful both in its intuitive transparency and
in its ability to deal with non-price-taking behaviour. Once we come to
estimation however, it is less powerful than working with dual functions.
Since in section 3 we exploit duality and flexible functional forms to
specify our output/allocation equations, we briefly restate our main
results in those terms here. It turns out that the crucial derivatives Gij
may be signed in terms of estimable parameters based on dual profit
functions.
The empirical application of duality requires price-taking
behaviour. Thus we are considering a new approach only to the evaluation
of dXg and dZ and the variables dependent upon them. The evaluation of the
factors H and N is unchanged by the switch to duality. For a price-taking
firm the profit function governing the production and allocation of exports
may be written as f - 1(PA, PB, W), and using Sheppard's lemma, the profit
function yields consistent output supply and input demand functions. For
the sake of concreteness, we represent the profit function by Diewert's
(1974) Generalized Leontief form used in the remainder of the paper.
(18) _ E 7ij (-Pi/2 p3/2)
where i - A, B, Z and Pz is just the wage (W). Concavity of the profit
function requires 7ij - 7ji and 7ij > 0 i t j if outputs (XA, XB) are
measured with positive signs and inputs (Z) with negative signs.
17
Differentiating (18) yields the general netput equation ('netputs' are
both inputs and outputs)
(19) Xi' 7ii E 7i (p /pi)
where XZ - -Z in our earlier notation.
Neary and Roberts (1980) show that a constrained equilibrium can
be expressed in terms of the parameters of the unconstrained compensated
demand or supply functions by means of virtual prices. Virtual prices are
the prices at which the actual quantities traded would have been traded
voluntarily according to the compensated functions. For unconstrained
netputs, virtual prices equal actual prices, and for constrained netputs
they may be derived by inverting the compensated netput functions. Solving
(19) for ;A, the virtual price of sales to market A given a value of XA,
and substituting into the two unconstrained netput functions yields:
(20) Xk 7kk 7kA I 7kl 7kA7A1 ] p k,l-B.Z
(XA + 7AA) (XA + 7AMA) k
Now at the initial, unconstrained, equilibrium (X, X, Z*), (20)
will hold as well as (19), so that to calculate the effects of a wsmall'
VER, we need only differentiate (20) w.r.t. XA. This simply indicates that
provided 7ij > 0
dXk
dX< 0
dX
18
which, given the sign convention, shows tAat a VER in market A will boost
supplies to market B and reduce factor inputs, 2. That is, the assumptions
necessary to ensure the concavity of the generalized Leontief profit-
function are sufficient to sign expressions (10) and (11) above if the
duality requirement that IeBI - 1ezl - S is satisfied. But once they are
signed under these conditions, (10) and (11) may be signed (in the same
direction) for all valuis of the elasticities, so concavity is sufficient
to establish a general result of 'domino diversion" and *industry
contraction' in response to a VER.
Using this approach, the quantification of the effects of the VER
depends on both the parameters of the profit function and the various
industry elasticities, and apparently cannot be further simplified as we
did with the primal analysis above. As a practical application, we now
estimate as many of the parameters as possible and use a simulation model
to combine the estimates. Using a simulation model has the additional
virtue of allowing us to consider non-marginal VERs as well.
III. ESTIMATION
In this section we describe two attempts to estimate the principal
parameters of the model above for Taiwanese exports of leather footwear
(CCCN 6402). Most Taiwanese footwear exports are sold in the USA, which
between July 1977 and June 1981 imposed on them a voluntary export
restraint (the so-called Orderly, Marketing Agreement). The OMA has been
investigated several times from the USA's point of view -- e.g. Pearson
(1983) and Aw and Roberts (1986) -- but not, to our knowledge, from
Taiwan's. We estimate the model for leather footwear sales because they
were all affected by the OMA, whereas the other major aggregate available
19
to us (CCCN 6401), although accounting for a larger share of Taivanese
footwear exports, comprises rubber and plastic footwear, the former of
which was not limited by the OHA. We distinguish two markets for footwear,
the USA and the rest of the world and use quarterly data 1974-1986. 7/
We estimate the various parameters of the model presented in
section II in a simultaneous system of non-linear equations using three
stage iterative instrumental variable methods from SAS's SYSNLIN
proce'ures. 8/ The purpose of this estimation is to establish the
plausibility of uur approach and to obtain "ball-park' estimates of the
critical parameters for later policy simulations. Thus we have not
experimented with large numbers of specifications nor have we concerned
ourselves much about insignificant but implausible estimates of non-
critical parameters.
Our first attempt at estimation was a limited one. Recognizing
the paucity of data on the production side of the model, we estimated a
system comprising only demand curves and an export allocation model to
divide a given volume of exports between markets. We had originally
intended to use a constant elasticity of transformation (CET) allocation
model -- see de Melo and Winters (1989) -- but it has the unfortunate
property of obliging GAB from equation (10) above to be negative. This
immediately implies that a VER in A will contract sales to market B in the
fully price-taking case. Therefore, in order to avoid imposing such an
implication, and to allow the data scope to determine the nature of the
spillover, we derived an alternative allocation model from the restricted
profit function of the Generalized Leontief form given by equation (18)
above.
McFadden and Fuss (1978) show that profit functions can be
rewritten to describe the maximum profit available given exogenous values
20
for certain netputs. They show that such restricted profit functions must
be linear homogeneous in the exogenous quantities and should be concave in
the prices of the remaining unconstrained netputs. Hence, we fix total
inputs (Z) exogenously and proxy Z, by total exports of footwear CX), as an
allocation model suggests is appropriate. This allows us to write XA -
f(PA,PB)*X, which, using a Generalized Leontief form, specializes to
(21) XAIX - - A 7AB (PB/P)
The corresponding equation for XB is implicit in (21) given adding up.
Equation (21) was estimated along with demand functions for
leather footwear for the USA and for the rest of the world. These were
normalized to express the price of Taiwanese footwear relative to a linear
combination of the prices of locally produced footwear (Pi) and Korean
exports to the market concerned (PI) as the dependent variable.
Normalizing the demand curve on price is necessary if the data are to have
the opportunity to record infinitely elastic demands. The additional
explanatory variables were a cyclical variable (the index of industrial
production, Qi) and the quantity of exports. Thus the two demand curves
were of the form:
(22) Pi ' (Pi + Pi Qi + piX ) t(l _ p3i L P3 PKi] i - A,B
p (A+±f+A i 2L P i
All three equations were given seasonal dummies and, ln view of
the evident serial correlation when estimated straightforwardly, were also
adjusted for first order serial correlation.
21
During the OMA the demand equations still applied, relating actual
prices and quantities, but the allocation function was over-ridden by the
VER and its implication, given Z, for sales Xg. Thus the quarters 1977:3
to 1981:2 had to be removed from the estimation of equation (21).9/ The
set of instrumental variables included the exogenous variables used in (21)
and (22). The initial estimates of (22) were highly unstable: the serial
correlation coefficients fluctuated around unity and consequently the
resolution on the constant terms P was very weak. The only solution
appeared to be to estimate the demand equations in first difference form,
dropping the constants. Table 1 reports these results as model 1.
The most striking feature of model I is its strong positive
estimate of 'yAB: given total exports the share allocated to market A rises
strongly as their relative price rises. This result is sufficient to
indicate negative spillovers between markets -- i.e. that GAB > 0 -- and
consequently that both "domino diversion' and 'industry contraction' occur,
albeit the latter via an indirect route. The elasticity of the USA share
of exports with respect to its price implied by the estt.mate is about 3.5
in 197617; that is, holding total exports constant, a it increase in the
price available in the USA would have increased exports to the USA by 3.52.
On the demand side, the results indicate that the USA's demand for
Taiwanese footwear is insensitive to the state of the business cycle and
appears to be related only to local footwear prices rather than to those of
competing suppliers from Korea. The price is, however, negatively related
to the quantity of exports with an elasticity of about -14 evaluated at the
mean levels of exports and prices in the year prior to the OMA (1976:3 -
1977:2). 10/ The demand in the rest of the world seems to be fairly
strongly influenced by the state of demand (prices rise with the cycle),
22
Table ls ESTIMATES OF SUPPLY AND DEMAND FUNCTIONS
FOR TAIWANESE FOOTWEAR
Model I a/ Model II b/
7A M-4.67 (1.81) -
7AB 4.31 (2.14) 1.32 (0.90)
7AZ - 0.49 (0.19)
7YBB -
73Bz -0.05 0.09
p 0.87 (0.12) 1.00 (-)
0.0003 (0.0094) 0.0010 (n.0080)
-0.0016 (0.0018) 0.0009 (0.0012)
-0.308 (0.366) -0.087 (0.242)
1 0.0389 (0.0564) -0.0031 (0.0519)
0.0108 (0.0130) 0.0073 (0.0103)
0.5941 (0.171) 0.625 (0.147)
R2/DW
XA 0.903 1.93 0.964 1.89
XB - - 0.958 2.06
PA 0.985 1.86 0.988 2.08
PB 0.955 2.46 0.965 2.52
Notes:
a/ See text and equation (22).
bi See text and equations (19) and (20).
23
and to be related to the prices of both local footwear and competitive
footwear from Korea. The positive term on exports is very fragile,
depending on the dynamics of the equation system, it is best interpreted as
indicating a horizontal demand curve rather than a perverse one. Thus
comparing the USA market in which Taiwan is an important supplier with the
world market in which it is less so we find a lower elasticity of demand
(-14 vs. -U) and less direct competition for Korea. This seems intuitively
plausible. Omitting the two implausible coefficients ( 4 and Pi) has little
effect on the other parameter3 except for increasing absolutely 7AA and 7AB
by about 0.25. Finally, the RZ and Durbin-Watson statistics are
acceptable.
The second estimatior. exercise attempts to incorporate the size of
the industry into the system of estimating equations. As argued above,
this is most 0ap'ly accomplished by means of the profit function. Thus in
addition to the two demand curves (22), we attempted to estimate three
supply functions: equations (19) for i = A,B and (20) for i-B. Equations
(19) rule during periods of free trade and equations (20) during the OMA.
The factor demand equation, (19) with i-Z, is not estimable because no data
exist on factor inputs, but with the exception of lzz, its parameters are
recoverable from the other equations by symmetry. If the stochastic
behaviour of the supply model is unaffected by the OMA, the error structure
of (20) is derivable from that of (19). 11/ However, it would be
exceedingly complex to do this, as Winters and Brenton (1988) have shown
using other functional forms, so it seemed most rational to treat (20) as a
separate equation with its own stochastic errors.
We approached the incorporation of supply iesponses with great
trepidation. The factor price data necessary for equations (19) are
available only on ISIC rather than on SITC commodity classificarions and
24
refer only to wages. Data were also available to us only annually for the
earlier part of our sample, and thus had to be interpolated into quarterly
series. Moreover, it is possible that wages are endogenous. Hence, wages
have to be instrumented in our estimation procedure. For instruments, we
used employment and wages in the whole of Taiwanese manufacturing. Thus,
one should not place great reliance on the results of the expanded
estimation.
The results of the full estimation are reported as model II of
table 1. As previously, severe serial correlation suggested that working
in first differences was a necessary simplification, but this time it
affected all equations. This made it impossible to estimate the constants
of the supply functions which, in turn, meant that (20) was inestimable.
Thus our final system comprised four rather than five equations. The
estimates of the demand functions are even less well defined in model II
than in model I; the only notable change is that the coefficient relating
prices to the quantities of exports in the USA is insignificantly positive.
As before, we interpret this as indicating a horizontal not an upward-
sloping demand curve.
Turning to the supply responses, we find them reduced by the
inclusion of factor prices. For sales to the USA -- the major market --
both terms are positive: exports to the USA depend positively on their
price relative to the prices of both sales elsewhere and factor inputs.
The implied arc elasticity of supply is around 3.1 in 1977. The
coefficients on relative prices for exports to the rest of the world are
positive relative to the price of USA sales but just negative relative to
factor inputs. The latter sign implies implausible behavious at some sets
of prices, but does not disturb the signs of the elasticities at the prices
25
experienced over our sample period. The own price elasticity of supply for
exports to the rest of the world is about 1.0 in 1977, but grows to 1.5 by
1986.
The results for model II are disappointing in their lack of
precision. However, they do suggest that important supply responses exist
and that a more detailed study with better data would be rewarding. They
also suggest that responses are around the levels suggesting that it is
fruitful to study the effects of VERs on resource allocation and welfare.
Thus, until firmer empirical work is undertaken, we take the estimates here
as bases from which to explore the effects of different elasticity
assumptions on the costs of VERs to developing country exporters.
IV. WELFARE AND DISTRIBUTIONAL EFFECTS OF VERS: SOME ILLUSTRATIVE
SIMULATIONS.
The econometric estimates in section 3 for Taiwanese leather
footwear exports suggest that factor demand and output supply
responsiveness are sufficient to produce "domino diversion" towards
unrestricted markets and industry contraction. However, both because we
were unable to estimate precisely all the demand and supply parameters, and
because our estimates are not representative of those in other sectors
subject to VERs, we complete the analysis with some counterfactual
simulations inspired by our earlier results. We loosely ba6e these
simulations on Taiwanese leather footwear exports to the USA and to the ROW
using volume and price data at the eve of the OMA agreement. The
simulations are drawn by applying elasticities to the partial equilibrium
model developed in section 2. The notation is the same, and the set of
equations describing output demand and factor supply responses (constant
26
elasticity demand curves and constant elasticity supply for the factor of
production) are detailed in the appendix along *;ith the calibration
procedure. The output supply and factor demand functions are modelled with
the generalized Leontief form, but they are expressed below in terms of
elasticities for the sake of intuitive transparency.
The results of simulations under different assumptions about
demand and supply elasticities are reported in table _.. All simulations
refer to a negotiated 10 percent cut in exports of Taiwanese leather
footwear to the USA. The objective of the simulations is to establish how
sensitive the results are to systematic variations in demand and supply
elasticities. At this stage, we assume that the footwear industry is small
in the market for its factor Z, so that Pz, the price of the factor is
fixed.
In all the simulations, we rely on pairwise variations in the
parameters of the Generalized Leontief production function. For all
pairwise variations, the conditions for local concavity of the profit
function (i.e. 7ij > 0) are met, as suggested by our econometric estimates.
At this stage, all simulations assume identical pairwise supply and demand
elasticities, since we have no a priori ground for presuming that supply
elasticities tv restricted and unrestricted markets should be different or
for presuming that export demand elasticities should be different (unless
market shares in the restricted and unrestricted markets are radically
different).
As was established in section 2, the simulations in columns 1 to 3
show that the spillover is an increasing function of export demand
elasticities. The results of varying export demand elasticities also show
that, other things equal, the rent transfer gain decreases as the size of
Table 2: SENSITIVITY RESULTS TO ELASTICITY SPECIFICATION (SMALL INDUSTRY CASE)
(1OX REDUCTION IN EXPORTS TO RESTRICTED MARKET) /
ElnsticitilesColumn (1) (2) (J) (4) (5) (6) (7) (8) (9)
Factor dmand elasticity
d
(Ex) y -1 -1 -1 -1/4 -1/4 -1/4 -2 -2 -2
Output *upply elasticities
5 5
(CA UO)SI 2 2 2 1/2 1/2 1/2 4 4 4
Export damand elasticitios
d d
(C EAEE) 1/2 2 4 1/2 2 4 1/2 2 4
Exports to unrestricted market
( change) 0.016 0.03o 0.046 0.034 0.049 0.068 0.009 0.026 0.086
Factor uso (X change) -0.068 -0.045 -0.041 -0.041 -0808U -0.034 -0.056 -0.06 -0.045
Change In profits I/ 7.964 1.452 0.692 6.702 0.989 0.259 8.875 1.649 0.708
Change In Ovirtusl' profits I/ -J.287 -2.709 -2.420 -9.699 -7.997 -7.641 -1.778 -1.640 -1.881
!/ Initial values PA z 1.54; XA a 27.5; P8 e 1.26; Xg = 22.0. Small Industry cse, i.e. Pz fixed.
k Holding output prices constant.
s/ Holding Pz constant.
i/ Initial profits equal to zero. Change in sales revenue minus change In value of factor input.
/ Initial profit. equal to zsro. Restricted profits evaluated at virtual prics.
28
the spillover increases. This is because with more spillover there is less
contraction which in turn reduces industry profits.
More interesting are the results of varying factor demand and
output supply elasticities. Raising output supply response alone increases
the spillover and hence reduces profit to the industry as there is less
contraction. This negative effect on industry profits is offset if the
elasticity of demand for the factor of production is raised. Doubling the
olasticity of factor demand approximately halves the size of the spillover
effect. Holding export demand elasticities constant, doubling all
production function elasticities (col. 3 to col. 9) reduces the spillover
effect by about 50 percent and increases marginally the amount of
contraction and hence profits.
As we saw in section 2 and in figure i, as a result of the VER MRt
. 0 while HRI is unaffected. Breaking the equality of marginal revenues of
the industry factor between sales to the restricted and unrestricted
markets creates an inefficiency. A measure of that inefficiency is
provided by industry profits evaluated at 'virtual" profits. Virtual
prices are the set of prices which would cause actual quantities to be
supplied voluntarily - i.e., the set of prices which, with maximizing
behaviour, would support the observed quantity outcome. Given such prices,
"virtual' profits are the maximum that exporters could earn and thus
represent the efficiency losses that the VER imposes. In the absence of
the VER, actual profits equal virtual profits, *both being equal to zero.
As can be seen from the last row of table 2, virtual profits are more
negative - i.e. efficiency losses are greater - the lower demand and supply
elasticities.
29
In practice, however, industries that enter into VERs are not
small in their domestic economy. Indeed, it is precisely because these
industries have been rapidly gaining market shares in developed-country
markets, that VER arrangements are negotiated in the first place. In table
3, therefore, we report on allocation and welfare effects of the same VER
reduction as for three sets of elasticities selected from table 2, but now
recognizing that the industry faces an upward sloping supply curve for its
factor, Z, so that contraction is accompanied by a fall in the wage of the
industry factor, Pz Because the share of the ine-kstry in the market for Z
is likely to vary from case to case, we report welfare effects for
different assumptions about the size of the industry in the factor market.
Welfare calculations are reported in the bottom of table 3 as a percentage
of the income of factors in the industry prior to the VER and for factor
market sizes ranging from 1 to 20 times the initial allocation of factors
in the industry. Of course, the elasticity of factor supply to the
industry is not independent of its siza in the market for factors so that
the welfare estimate grid should be interpreted accordingly with high
values of the elasticity of factor supply corresponding to cases where the
industry is small in the market for its factors. For example, elasticities
of factor supply in the range between 1 and 5 and factor market sizes in
the range between 1 and 5 times the initial factor allocation, could be
taken as representative for analyzing a VER in textiles. On the other
hand, for a smaller industry like footwear, a more likely factor supply
elasticity range would be between 5 and 10 with a correspondingly higher
range for the size of the factor market in relation to the footwear
industry.
Table: DISTIONAL AND WELFAtE EFFECS OF A VEt
Factor Eua.lh Elasticity a I Fsctor Susely Elasticity * S Factor Sumal. Elalliciti * 10 Factor Sumalw Elsticity *
El_eiciti.. Los 5/ l4eidus 1/ High I/ Law &/ l ium High &/ Low j/ NWI u- si High j/ Low M/ Medium hi HisI S/
bmp.rl to w,re.tri cld
_.rk.t (I chn") 0.042 0.005 0.064 0.0e0 0.04S 0.061 O.08 0.040 0.044 0.049 0.036 0.088
Feetor mm (5 change) -0.0W -0.068 -0.02? -0.041 -0.042 -0.0 0 -0.041 -0.048 -043 4.08 0.045 -0.045
Factor price (U champ) -0.069 -0.08 4.0= -0.006 -.009 -.00 -0.004 -0.004 -0.004 0.0 0.0 0.0
Change in profits 6.849 8.302 2.196 7.1I 1.924 1.186 6.936 1.696 0.947 0.987 1.452 0.708
cane in Vrtual
prof to i-.451 -1.775 -o.647 -9.429 -2.472 -1.162 -9.568 -2. S6 -1.265 -7. nr -2.709 -1.3J1
Change in welfare 1/()0.009 0.014 0.006 0.094 0.019 0.006 0.098 0.020 0.009 0.0 0.0 0.0
0° 2068 0.120 4 .108 0 o.6 -40i 015 0.24 °.078 ° 0 00 0.0
(10)4257 40.267 4.:287 0.020 4.:066 4.0:0 0.0607 4.00020 4.0800 0.:0 0.0 0.00
(2 04. 641 40.621 4O.60 40.063 4.14.1413 001 4060.078 0.0 0.0 0.0
J/ S6.. elaticitige a. tole B. colum S.
hi See eluatlcitiges table S, colum 2.
S/ Sa_ *lastI citie. - tahle 8. coluu 9.
O j/ Itiera is parenthoee. refer to factor *rket size ;i relation to initial factor allocation In the industry. Change in
welfare calculated fm equation (M4 and eapr.aaed so a percentage of initial factor incme in the industry before the Vgt.
31
With wage flexibility the distributional effects of a VER are more
pronounced than earlier. Industry profits rise relatively more as they
shed factors and use remaining factors at a lower wage. Taking the medium
elasticity scenario as a reference, with an industry factor supply
elasticity of 5, profits rise by 30 percent more than in the case of
infinite supply elasticity, and industry wages fall by one percent. In
addition to producing re-deployment, a VER raises profits and lowers wages.
Thus it has a strong adverse effect on the distribution of income.
The harmful effects of a VER, however, are not confined to the
adverse distributional shifts arising frr l higher profits, lo0%r wages and
lower factor use. In addition, as can be seen from the grid of welfare
changes displayed in the bottom of table 3, for most factor market sizes
and for factor supply elasticities of below 10, the VER results in a net
welfare loss. For example, with medium elasticities as a reference, a VER
reducing exports to the restricted market by 10 percent would lead to a
welfare loss of 12 percent of factor income (prior to the VER) for a factor
supply elasticity of 1 and a factor market 5 times the size of the initial
factor allocation in the industry. Of course, higher factor supply
elasticities mitigate the welfare loss and so would differential export
demand elasticities (with relatively lower demand elasticities in the
restricted market). However, the results in the bottom of table 3 suggest
that for most plausible elasticity configurations, a VER is more likely
than not to reduce national welfare in the exporting country.
6. Conclusions
The bulk of the economic literature gives the impression that VERs
are not very harmful for the exporting country. Most work on the subject
has focused on establishing the welfare lose to th 4mporti-g country
32
arising from the conjunction of an income transfer loss and a distortionary
efficiency loss. Implicit in that work is that the exporting country is
likely to receive adequate compensation for any induced inefficiency losses
through the often large rent transfer.
This paper has argued that this view is misconceived. A fairly
general theoretical model of the industry subject to the VER shows that a
VER is likely to lead to both industry contraction and spillover to
unrestricted export markets. We call spillover "domino diversion' since it
lends support to the preoccupation of countries that have not negotiated
VERs with seeing their markets flooded by sales diverted from the
restricted markets. Our econometric estimates for Taiwanese leather
footwear exports to the USA lend support to the fairly general conditions
under which spillover and industry contraction will occur, namely that with
rising marginal costs in the production of sales to both restricted and
unrestricted markets, any increase in the output of one product does not
reduce much (or increases) the marginal cost of the other product.
We also establish that unless there are very strong interactions
in production between the products sold to the restricted and unrestricted
markets, a VER will lead to industry contraction, rising private profits
(because of the rent transfer from abroad), and a lower wage for the
factors employed in the industry, especially those with skills with few
alternative uses in other industries. Thus VERs have strongly negative
distributional implicatwons for exporting countries as profits rise and
wages and employment fall. Finally, illustrative simulations show that for
a plausible range of elasticities and relative sizes of the restricted
industry, national welfare may well fall in spite of the rent transfer from
abroad.
33
Notes
1/ See e.g. Greenaway and Hindley (1985), Tarr and Morkre (1984), and
Feenstra (1984).
2/ The assumption that all output is exported simplifies the welfare
analysis since only producer surplus need be considered. In the
following, we assumD that society's objective function is merely to
maximize industry profits. This assumption is relaxed below.
3/ The second order conditions for profit maximization require that
either or both (GBB/GB - GBA/GA) or (GAAIGA - GAB/Gg) be positive.
Thus the numerator of (11) is unlikely to become positive.
4/ A restriction of the diagram is that marginal costs for the two
products are unrelated - i.e. GAB - 0. If that were not true, the
location of MR* would depend on ZB, etc.
5/ This case is not the same as assuming that the industry size is fixed,
i.e. that dZ-0. The case considered here is less likely to show the
VER as harmful because it allows for the factors initially employed in
footwear to find useful employment elsewhere in the economy albeit at
a lower wage.
6/ The alloLation component essentially compares the marginal revenues
(1+6il) available to factors in different markets. If it is higher in
other industries than in footwear, diversion to the former is
beneficial.
7/ We assume that all output is exported and that the exports to the rest
of the world are not constrained.
8/ The exogenous data plus time and seasonal dummies were used as
instruments. Data sources and data manipulation to obtain a quarterly
wage series are described in the appendix.
9/ When the serial correlation adjustment was made, 1981:3 also had to be
dropped because no unrestricted lagged value of XA was available from
1981:2. For the omitted quarter, actual values of XA and Xg were used
in equation (22) because they were the exogenous.
10/ Our estimate of the US price elasticity of demand for Taiwanese
footwear may appear on the high side. For example, Aw (1989) reports
an average price elasticity of demand of about 3.0, a result higher
than previous global estimates (Szenberg et al. 1977).
11/ The term (XA + 7A ) in (20) will become (XA + 7A - uA) where uA is an
error term distributed identically throughout our sample period.
12/ For evidence that wages and output fall (relative to industry trends)
in the case of VERs on Korean footwear exports, see de Melo and
Winters (1989).
34
References
Aw, B.Y. 1989. 'An Empirical Model of Mark-Ups in a Quality
DlfferentJated Export Market,, mimeo.
Aw, B.Y. and M. Roberts. 1986. *Measuring Quality Change in Quota-
Constrained Import Markets," Journal of International Economics,
vol. 21, pp. 45-60.
Diewert, E. 1974. 'An Application of the Sheppard Duality Theorem: A
Generalized Leontief Production,' Journal of Political Economy,
79, 481-507.
Feenstra, R. 1984. "Voluntary Export Restraints in US Autos: 1980-1:
Quality, Employment and Welfare Effects," in R. Baldwin and A.
Krueger, eds., The Structure and Evolution of Recent US Trade
Policy. NBER. Chicago: University of Chicago Press.
Fuss, H. and D. McFadden. 1978. Production Economics: A Dual Approach to
Theory and Applications. North-Holland, Amsterdam.
Greenaway, D. and B. Hindley. 1985. 'What Britain Pays for Voluntary
Export Restraints,' Thames Essay No. 43, Trade Policy Reseach
Centre, London.
Melo, J. de and L.A. Winters. 1989. 'Voluntary Export Restraints and
Resource Allocation in Developing Countries," mimeo, World Bank.
Neary, P. and K.W.S. Roberts. 1980. "The Theory of Household Behavior
Under Rationing," European Economic Review, Vol. 13, pp. 25-42.
Pearson, C. 1983. Emergency Protection in the Footwear Industry. Thames
Essay No. 36, Trade Policy Research Centre, London.
Szenberg, M.. J. Lombardi, and E. Lee. 1977. Welfare Effects of Trade
Restrictions: A Case Study of the U.S. Footwear Industry. New
York: Academic Press.
Tarr, D. and H. Morkre. 1984. Aggregate Costs to the United States of
Tariffs and Quotas on Imports: General Tariff Cuts and Removal of
Quotas on Automobiles, Steel, Sugar, and Textiles. Federal Trade
Commission.
Winters, L.A. 1988. 'A Multi-Input Multi-Output Model of the UK Footwear
Sector,' mimeo, University College of North Wales.
Winters, L.A. and P.A. Brenton. 1988. 'Voluntary Export Restraints: UK
Restrictions on Imports of Leather Footwear from Eastern Europe,'
Discussion Paper No. 283, CEPR, London.
35
Appendix:
Al. Data Sources for Econometric Estimates
Exports and export unit values: Foreign Trade of China, Taiwan Province
CCN 6402; pairs and USS per pair
Korean export unit values: Korean Customs data - see de Helo and
Winters (1989) for details
Domestic prices/unit values: US: Bureau of Census Current Industrial
Report non-rubber footwear
RoW: British Footwear Manufacturers
Federation, UK domestic production unit
value and I.F.S. average exchange rate
(rf)
Indices of industrial production: F
I.F.S.
Wholesale prices: j RoW - OECD less USA weighted by GDP
-weights
Exchange rate:
Wages and unemployment: Yearbook of Labor Statistics, Republic
of China wages and employment in
leather footwear and average exchange
rate
All data were quarterly except for Taiwanese wages and employment
for which only annual data were available consistent form. These were
interpolated into quarterly series as follows.
We assume each series grows by a constant amount throughout each
I'
year. Thus in any year:
qtj = xt + (j - 2.5) yt j=1...4; t=l...n
where qtj is the observation for quarter j year t
xt is the annual observation
Yt is the quarterly growth in year t
Observation xt is centered between quarters 2 and 3 and qtj at the
centers of their respective quarters.
36
In addition, there is a requirement that the continuous function
represented by x connect at the end of each year and at the beginning of
the next. Thus
xt + 2yt - xt+l - 2Yt+l
from which
2yt + 2yt+l - xt+l - xt m Axt+l
Writing this in matrix form yieldst
2 0 ...... 0
2 2 0 ....0 d
0 2 2 0 .. 0
(Al) .. y - Ax
o .... 0 2 2
where d is an arbitrary starting condition.
(A.1) is solvable once d is known and we choose d to minimize the variance
in growth rates - i.e. we choose to make the quarterly series qtj as smooth
a%i possible.
Minimizing y'y w.r.t. d yields:
d = - [tJ2 Axt (mtl + mit)] / 2mll
where mij is an element of M, and MuN'N, wshere N is the matrix in (A.1).
A2. Simulation Model A
The results in section 4 are based on simulations calibrated to
volumes and unit values of Taiwanese leather footwear exports at the eve of
the OMA. The simulations are based on solutions derived from the equations
system below. Subacripts k, k e A, B refers to the demands in the
restricted and unrestricted markets respectively. Subscripts i and J, i, j
a A, B, Z refer to the two outputs and the single composite input Z, in the
Generalized Leontief production function which describes technology. Bars
37
over a variable indicate an exogenous parameter, stars denote the initial
unconstrained equilibrium, and a tilde over a variable, ", refers to the
prices at which unconstrained producers would replicate the input and
output allocation decisions imposed on them by binding constraints in the
relevant market.
(A2) Xk _ 3 pek k > ; k e A,B
k e
(A3) X z2A z pz ;Pz -P ; e, 0
S z z z 312
(A6) Xi -7ii -33 7ij (P /; ; i, j e A, B, Z
(A5) P. < PA where XA < XA
Equations (A2) and (A3) describe the output demand and factor
supply curves facing the all,around price-taking firms in the industry
subject to the VER. Equation (M) is obtained from applying Sheppard's
lemma to the generalized Leontief restricted profit function
(A5) ir (P; a) - K [ 3~ M '±o((P )l12)
(A5) f(p; a). R |Ei E I7ij ((-Pi Pj)
where K is a fixed factor (not modelled) which ensures a determinate firm
size. Equation (A6) states that when export volumes in the restricted
market are below their free trade values, the price PA at which uncon-
strained suppliers would have voluntarily applied the restricted quantity
XA is less than the premium-ridden price at which sales are actually made,
38
i.e. PA > P > P;A w;ere PA is the free trade price in the restricted
market.
Industry profits, i, is the difference between sales revenues and
costs, both evaluated at the VER-ridden prices, whereas *virtual, profits
given by (A6) are evaluated at virtual prices P. The welfare measure is:
(A7) AVW = W-W*- (Ar + AP L) I P*Z
where L is a scalar indicating the size ot the industry in the market for
Z.
The elasticities in tables 2 and 3 are used to calibrate the
parameters 7ij appearing in the factor demand equations (A3). Calibration
is completed by treating parametrically initial price and quantity data and
by choosing an initial parametric value for Z so that profits are initially
equal to zero.
PPR Working Paper Series
Contact
ia Athor
WPS307 On the Accuracy of Economic Alexander J. Yeats November 1989 J. Epps
Observations: Do Sub-Saharan 33710
Trade Statistics Mean Anything
WPS308 Harmonizing Tax Policies in Central Yalcin M. Baran November 1989 T. Watana
America 31882
WPS309 How to Improve Public Sector Yalcin M. Baran November 1989 T. Watana
Finances in Honduras 31882
WPS31 0 A Framework for Macroeconomic Al Khadr December 1989 S. Jonnakuty
Consistency for Zimbabwe Klaus Schmidt-Hebbel 61769
WPS311 Macroeconomic Performance Leonardo Leiderman November 1989 R. Luz
Before and After Disinflation in Nissan Liviatan 61588
Israel
WPS312 Improving Public Enterprise Mary M. Shirley October 1989 R. Malcolm
Performance: Lessons from 61708
South Korea
WPS313 The Evolution of Paradigms of Michael E. Colby November 1989 C. Evangelista
Environmental Management in 32645
Development
WPS314 Primary Commodity Prices and Theodosios Palaskas November 1989 D. Gustafson
Macroeconomic Variables: A Long- Panos Varangis 33714
run Relationship
WPS315 Notes on Patents. Distortions, Julio Nogues January 1990 M. T. Sanchez
and Development 33833
WPS316 The Macroeconomics of Populism Rudiger Dornbusch December 1989 R. Luz
In Latin America Sebastian Edwards 61588
WPS317 Price and Quality Competitiveness Zdenek Drabek December 1989 Z. Drabek
of Socialist Countries' Exports Andrzej Olechowski 72162
WPS318 Sovereign Debt Buybacks as a Sankarshan Acharya December 1989 S. King-Watson
Signal of Creditworthiness Ishac Diwan 33730
WPS319 Trends in South-South Trade and Refik Erzan December 1989 G. Ilogon
the Potential in Non-Discriminatory 33732
Liberalization of Barriers
WPS320 Protection Facing Exports from Refik Erzan November 1989 G. Ilogon
Sub-Saharan Africa in the EEC, Peter Svedberg 33732
Japan, and the United States
WPS321 Economic and Policy Determinants Jorge Marshall December 1989 S. Jonnakuty
of Public Sector Deficits Klaus Schmidt-Hebbel 61769
PPR Working Paper Series
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WPS322 Earmarking Government Witliam McCleary December 1989 A. Bhalla
Revenues: Does It Work? 60359
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Stabilization Programs: Lessons Nissan Liviatan 61588
from the 1960s and the 1980s
WPS 324 Ethical Approaches to Family F. T. Sai December 1989 S. Ainsworth
Planning in Africa K Newman 31091
WPS325 Manufacturers' Responses to Infra- Kyu Sik Lee December 1989 L. Victorio
structure Deficiencies in Nigeria Alex Anas 31015
WPS326 Do Exporters Gain from Voluntary Jaime de Melo January 1990 M. Ameal
Export Restraints? L Alan Winters 61466
WPS327 Making Noisy Data Sing: A Micro James R. Tybout January 1990 M. Ameal
Approach to Measuring Industrial 61465
Efficiency
WPS328 Europe, Middle East, and North Rodolfo A. Bulatao November 1989 S. Ainsworth
Africa (EMN) Region Population Eduard Bos 31091
Projections, 1989-90 Edition Patience W. Stephens
My T. Vu
WPS329 Latin America and the Caribbean Rodolfo A. Bulatao November 1989 S. Ainsworth
(LAC) Region Population Eduard Bos 31091
Projections, 1989-90 Edition Patience W. Stephens
My T. Vu
WPS330 Africa Region Population Rodolfo A. Bulatao November 1989 S. Ainsworth
Projections, 1989-90 Edition Eduard Bos 31091
Patience W. Stephens
My T. Vu
WPS331 Asia Region Population Projections, Rodolfo A. Bulatao November 1989 S. Ainsworth
1989-90 Edition Eduard Bos 31091
Patience W. Stephens
My T. Vu
WP3332 Effective Incentives in India's Ashok Gulati January 1990 G. Bayard
Agriculture: Cotton, Groundnuts, with James Hanson 38004
Wheat, and Rice and Garry Pursell
WPS333 An Option-Pricing Approach to Stijn Claessens January 1990 S. King-Watson
Secondary Market Debt (Applied Sweder van Wijnbergen 33730
to Mexico)