Income Redistribution, Trade Prices, and International Capital
in
Simulated Trade Models
Abstract
The present paper compares the
quantitative impacts of changing prices and capital endowments on income distribution
across simulated factor proportions and specific factors models. These models
include different production functions, aggregates of skilled labor, and countries. A free trade “program” of 1% changes
in prices and capital stocks are the standard of comparison. These simulations
illustrate two general quantitative properties. When prices change due to trade,
factor intensity has a much stronger influence than factor substitution on income
redistribution. Second, foreign capital has a much weaker influence on income
redistribution short of improvement in technology.
International trade and capital both increase and redistribute income
across domestic factors of production. This income redistribution may explain
in part the lack of universal support for free international commerce. In comparative
static models of small open economies, price changes due to trade cause factor
price adjustments. The Stolper-Samuelson qualitative
price link is based on factor intensity but little intuition has developed
beyond the two factor, two good model. Similarly,
income redistribution due to foreign capital has been difficult to generalize beyond
simple models. Further, there is little insight into the magnitudes of these
general equilibrium effects. The quantitative implications of introducing
specific factors of production have not been explored. Finally, there has been
no investigation of the quantitative distortions of aggregation. Simulations
provide insight into these issues.
The present paper synthesizes a series of simulations of the general
equilibrium model of production and trade developed by Jones (1965), Chipman (1966), Jones and Scheinkman
(1977), Chang (1979), Ethier (1974), and Takayama (1982), based directly on the classic work of Edgeworth, Heckscher, Ohlin, Vanek, and Samuelson. Underlying
assumptions are homothetic neoclassical production functions with constant
returns, competitive pricing of homogeneous products in small open economies,
and full employment of homogeneous factors of production. The present
simulations are more theoretical exercises than the policy oriented computable
models such as those of Fullerton et al. (1985) or Hertel
and Tsigas (1988).
Factors of production in the present simulations include the various
skill groups of labor from the eight skill categories
reported by the US Census. Capital input is derived as the residual of industrial
value added from the Census of Manufacturing. Clark et al. (1988) show that
none of these labor groups can be aggregated and the
present aggregations provide insight into the resulting distortions. Simulations
include models with specific factors of production allowing comparisons with impacts
on shared factors.
For notation, let w represent endogenous factor prices, p
prices of finished products exogenous to the small open economy, and K the
exogenous capital endowment. Analysis begins with estimates of dwi/dpj and dwi/dK elasticities, the effects of changing prices and foreign
capital on factor prices. A free trade “program” of 1% price changes is
multiplied by the matrix of dwi/dpj comparative static elasticities
to derive potential percentage changes in factor prices. Similarly, 1% changes
in the capital stocks are multiplied by the matrix of dwi/dK elasticities to
project potential effects of foreign capital.
Theoretical anticipations
Changing prices of traded products with constant endowments affect factor
prices as reflected in the general equilibrium dwi/dpj elasticities, denoted by wij.
In the model with two factors and two products, the Stolper-Samuelson
(1941) theorem establishes a qualitative link between prices of products and
factors based on factor intensity. The magnification effect of Jones (1965) shows
that any ranking of percentage changes in prices of products is flanked by
percentage changes in factor prices. Regarding the wij
matrix of comparative static elasticities,
for every price pm there must be a factor h such that wmh > 1 and a factor k such
that wmk < 0. For any ceteris
paribus price change, some factor owner must win in terms of real income while
another must lose. The wij elasticities in the present simulations are elastic,
illustrating the magnification effect.
A changing capital endowment with prices of traded products held constant
affects factor prices as reflected by dwi/dK or wiK
elasticities. Foreign capital in the present
models is assumed to directly add to an exogenous capital endowment with no
change in the underlying production function. While national income rises, the
entire gain goes to the capital owner due to thecompetitive
envelope property. As a general property, the derived wiK
elasticities are nearly zero in all of the present
simulations.
Simulations of factor proportions models of production and trade
The foundation of factor substitution is a specified cost or production
function. Cobb-Douglas (CD) production functions have unitary elasticities of substitution. Balistreri
et al. (2001) point out that CD technology cannot be rejected as a null
hypothesis for 20 of 28 US manufacturing industries, and all but one of the
others have Leontief technology, suggesting
Cobb-Douglas is a reasonable starting place for simulations. Flexible translog functions developed by Christensen et al. (1973)
allow variation in the elasticity of substitution along isoquants
and are typically estimated with systems of partial derivative factor share
equations. Uzawa (1962) develops properties of
constant elasticity of substitution (CES) production.
In a model with translog production estimated
across US states, Thompson (1997b) estimates own factor price elasticities of -1.4 for skilled labor,
-1.2 for unskilled labor, and -0.9 for capital. The
strongest cross price elasticities are between
skilled and unskilled labor, both only about unit
value, with capital a weak substitute for both types of labor.
Weak substitution between capital and labor is consistent
with the literature, including Arrow, Chenery et al. (1961).
Free trade might be expected to lower the US price of aggregated
manufactures while raising the relative price of exported business services. Changing
prices have elastic effects on factor prices in the comparative statics. Table 1 reports factor price adjustments for a
free trade “program” with the price of aggregate manufactures falling 1% and
the price of services rising 1%. The extremely elastic wage effects for suggest
there is a great deal at stake in the move toward free trade. In stark contrast,
a change in the stock of capital has negligible wage effects in Table 1. Further,
free trade generally causes prices to change much more than 1% while a 1% increase
in the capital stock would represent huge investment. These results are robust
across a number of simulations of Cobb-Douglas, CES, and translog
production.
Table 1. US
factor price adjustments to “trade program” and capital stock change
|
|
1% price changes [%] |
1% increase in K [%] |
|
3 factor modela |
|
|
|
Skilled wage |
17 |
0.3 |
|
Unskilled wage |
-15 |
-0.0 |
|
Capital |
2 |
-0.3 |
|
Disaggregated labor
adjustment, translog productionb |
|
|
|
Professional wage |
2 |
0.1 |
|
Technical wage |
2 |
0.1 |
|
Service wage |
2 |
0.1 |
|
Resource wage |
-5 |
1.3 |
|
Craft wage |
-1 |
0.1 |
|
Operator wage |
-6 |
0.0 |
|
Handler wage |
0 |
0.1 |
|
Capital |
2 |
-0.3 |
a Thompson (1997b); robust for Cobb-Douglas,
CES, and compliments, Thompson (1995a).
b Thompson (1990); robust for CES
production, Thompson (1997a).
Elasticities of factor prices with respect to factor endowments
are close to zero in all the present simulations, a result I have called near
factor price equalization (NFPE). With an equal number of factors and
products, FPE holds and dw/dK = 0. When endowments change, outputs serve
as “shock absorbers” leaving little impact on factor demands.
In a 3x2 model of the US economy, Thompson (1995a) compares the
influence of factor intensity and substitution on comparative static elasticities with Cobb-Douglas, CES, translog,
and production with very strong complements. The wij
elasticities are consistent across all
simulations and the wiK elasticities are all nearly identical and close to zero.
Disaggregating the eight labor skill groups,
Thompson (1990) reports somewhat larger own translog
factor cross price elasticities, between -1 and -3. Factors
remain weak substitutes because of the strong influence of factor shares in
deriving cross price elasticities. Aggregation lowers
the degree of substitution as anticipated in the literature. These disaggregated
factor price adjustments in Table 1 are much smaller than in the aggregated model
but remain elastic according to the magnification effect. Aggregation
exaggerates the wij elasticities, cofactors of factor shares that increase when
aggregated. NFPE holds for the disaggregated labor
groups in Table 1 except for the wage of resource workers due to a very high
capital share in agriculture.
Thompson (1997a) examines a similar model with CES production and a wide
range of substitution for sensitivity. The free trade program has slightly
smaller effects than with translog production and the
wage of handlers rises slightly. Foreign capital has a weak positive impact on
all wages. Regarding robustness, wide variations in the CES have very little
impact on the comparative static results.
With CES production in a group of less developed and newly
industrialized countries, Thompson (1995b) finds unskilled labor
would gain substantially with free trade characterized by higher prices for
exported manufactures and lower prices for imported business services. In the
1% free trade program of Table 2, unskilled wages rise up to 18% in Mexico. There
should be opponents to free trade, however, with losses of skilled labor ranging up to 13% in Bolivia and capital losses as
high as 5% in Argentina and Mexico. While labor disaggregation would lower estimated elasticities,
free trade involves sizeable price changes. There is apparently quite a bit at
stake inside the NICs and LDCs
as they move toward free trade.
Table 2. NIC
and LDC adjustment to 1% trade programa
|
|
Unskilled wage [%] |
Skilled wage [%] |
Capital return [%] |
|
Mexico |
18 |
-2 |
-5 |
|
Argentina |
13 |
-2 |
-5 |
|
Ecuador |
9 |
-6 |
-1 |
|
Taiwan |
7 |
-3 |
-4 |
|
Bolivia |
6 |
-13 |
-5 |
|
Korea |
6 |
-4 |
-1 |
|
Venezuela |
6 |
-9 |
-0 |
|
Turkey |
4 |
-10 |
-0 |
a CES production, Thompson (1995b).
Relative influence of factor shares and substitution
The underlying reason for the dominance of factor shares in the wij elasticities
is straightforward. Elasticities of substitution εik defined as δln(aij/akj)/δln(wk/wi)
are constant
along isoquants with CES production and with CD production
they equal 1. Cross price elasticities σik defined as (δlnaij/δlnwk) depend almost entirely on factor shares θkj, written
as wkakj/pj. Sato and Koizumi (1973) show that σik = θkjεik. With CD technology, it follows that σik = θkj. In the present estimates of translog production, the εik are close to unit value.
Relative sizes of the wij
and wiK elasticities are due to properties of cost functions. Cost
minimizing factor inputs are positive first derivatives of cost functions by Shephard’s lemma, dc/dw = a, and factor shares θkj are built from these first derivatives. Factor
substitution elasticities are based on second
derivatives of cost functions, da/dw = d2c/dw2. Own effects are negative and the interactive
cross terms dai/dwk = d2c/dwidwk are generally small, ensured by addivity and concavity constraints. In the simulations, a
derived matrix of cross price elasticities σik is combined with a matrix of factor
shares θkj and a matrix of industry shares into a
comparative static system. The derived wij
elasticities are cofactors of relatively large
factor shares while wiK elasticities are cofactors of smaller substitution terms. Generally,
wij elasticities appear to depend little on substitution and wiK elasticities
are nearly zero. In the special case of even models, wij
elasticities are completely independent of
substitution and wiK elasticities are all zero.
Simulations of specific factors models
In a specific factors model of the Japanese economy, Thompson (1994)
examines the potential effects of protection across industrial wages given
Cobb-Douglas production. Protection of an industry has a positive elastic effect
on that wage, weak negative effects on other industrial wages, and a weak
positive effect on the capital return. The example of a 1% change in the price
of iron & steel is reported in Table 3.
Table 3. Japanese industry specific labora
|
|
D1% iron & steel price [%] |
|
Iron & steel wage |
4 |
|
Other industrial wages |
-0.5 to -0.01 |
|
Shared capital |
0.1 |
|
|
D1% in capital stock |
|
Capital return |
-0.3 |
|
Non-metallic minerals wages |
2 |
|
Agricultural wages |
2 |
|
Finance wages |
1 |
|
Iron & steel wages |
1 |
|
Other wages |
0 |
a Cobb-Douglas production, Thompson (1994).
Specific factors absorb price shocks. If a specific factor were to
become mobile across industries, there would be a dampened price effect. An
increase in foreign capital has a slight negative effect on the return to
capital, very inelastic effects on most industrial wages, and elastic effects
on a few industrial wages.
The NAFTA literature anticipates US industries intensive in production labor will face increased import competition. In a study of
the effects of projected NAFTA price changes on 17 Alabama manufacturing
industries, Thompson (1996) uses Cobb-Douglas production with industry specific
capital, production labor, and nonproduction
labor. Testing various vectors of price changes for
sensitivity, output effects are found to be inelastic
with own output elasticities less than 0.1 as summarized
in Table 4. Sector specific capital returns are very sensitive with returns
adjusting as much as 20% to the vector of 1% price changes. In the long run,
such capital return shocks would significantly affect investment and subsequently
outputs. The model then projects long run output adjustments in the range of
20%. Across simulations, production wages fall from 1% to 7% while nonproduction wages increase up to 3%.
Table 4. NAFTA
and Alabama manufacturing with industry specific capitala
|
Short run output effects < 0.1% |
|
D specific capital returns, up to 20% -
similar long run output effects |
|
(-) labor
intensive industries ¯ textiles, apparel, furniture |
|
(+) capital intensive industries chemicals, equipment, machinery,
instruments |
|
-1% < %D production wages < -7% |
|
0% < %D nonproduction
wages < 3% |
a Cobb-Douglas production, Thompson (1995),
various vectors of price changes.
In a study of Bolivia’s entry into Mercosur,
Thompson and Toledo (2001) combine CES production with the government
projection of Mercosur price changes in a specific factors
model with shared skilled and unskilled labor. Results
are summarized in Table 5. Skilled and unskilled labor are projected to
suffer moderate wage declines, while sector specific capital returns vary
widely. These factor price adjustments are robust over a range of sensitivity
analysis. A novel theoretical property is uncovered by these simulations,
namely that the wij elasticities are invariant with respect to the elasticity
of substitution given CES production.
Table 5. Mercosur and Bolivia with industry specific capitala
|
Sector-specific capital, shared skilled
and unskilled labor |
||
|
|
Projected price changes [%] |
%D capital returns [%] |
|
Business services |
-20 |
-25 |
|
Agriculture |
-12 |
-25 |
|
Mining |
4 |
14 |
|
Natural gas |
8 |
23 |
|
Manufacturing |
30 |
47 |
|
|
|
%D shared labor
[%] |
|
Skilled wage |
|
-6 |
|
Unskilled wage |
|
-1 |
a CES production, Toledo and Thompson
(2001).
Conclusion
Support for free trade is less than universal and the present
simulations suggest the high degree of potential income redistribution may be a
primary reason. Price changes due to free trade can be expected to
substantially alter income distribution following patterns suggested by factor
intensity or relative factor shares. While defining factor intensity remains a
theoretical challenge with many factors and many products, relative factor
shares anticipate the general equilibrium price links.
The theoretical literature has concentrated on isolating conditions
under which there would be unambiguous qualitative factor intensity price links
but very little intuition has evolved. It is reassuring that quantitative price
effects tend to follow patterns suggested by factor shares. Elastic effects of
changing prices on factor prices imply substantial income redistribution with a
move to free trade, and specific factors are especially sensitive.
Simulations can gauge the quantitative implications of variable returns,
nonhomothetic production, various production and cost
functions, different utility functions, international monopoly and monopsony power, heterogeneous products and factors,
unemployment, elastic factor supply, joint production, and so on. The effects
of aggregation can be examined in simulations. Specific policy issues for
various countries or regions and can be examined. Detailed production data can
focus on disaggregated industries.
The present simulations suggest factor price equalization would at least
nearly hold across competitive economies and foreign capital has a negligible
impact on factor prices. It bears repeating that the move to free trade promises
to substantially redistribute income among factors of production. To reach the
goal of raising unskilled wages in poor countries, trade holds more potential
than foreign capital.
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