Transcript L13-14-Vietnam - Agricultural & Applied Economics

Globalization, Growth, and Trade
Lectures 13-14:
Specific Factors Model (SFM)
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Overview - Today
 Motivation: Bringing ‘structure’ of economy into trade
discussion, a quick look at global export shares and
comparative advantage
 Overview of the Specific Factors Model (SFM)
 Analytical pieces of the SFM
 Production function
 Production possibility frontier
 Production function and implied factor returns
 4 quadrant model (labor, 2 production functions, possibility
frontier)
 Trade, production and factor payments in the SFM
 Analysis: winners and losers from global market shocks
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Regional export shares by sector
2
Primary product export shares
 Latin Am: 50% avg., but 85% for Andean countries
 60% of Mercosur inc. Bolivia and Chile;
 Over 65%: Argentina, Belize, Bolivia, Chile, Colombia, Nicaragua,
Panama, Paraguay, Peru, Uruguay, Venezuela
 Under 40% - Costa Rica and Mexico
 Comparative advantage of most of LA is clear
 S.S. Africa: most countries are mainly primary exporters
 4 countries with <70% (Togo, Senegal, South Africa, Mauritius)
 6 with 70-80% share (Guinea, Kenya, Madagascar, Niger, Zambia,
Zimbabwe)
 The other 25 have > 80% primary export share
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Comparative Advantage Comparisons
 If export shares => comp advantage, then most of L Am
& Africa have comparative advantage in primary
products.
 What implications might this have for development?
 Why does it matter to poverty?
 Recall that Yh = wLh + rKh: how would expanding primary
products shape household incomes? What does your answer
depend on?
 Why might you be concerned about the poverty implications of
comparative advantage in primary products versus
manufacturing?
 We can get more on this once we dig further into our next trade
model
4
Political economy implications
 HO-SS predicts aggregate gains from trade, but also
losses for some groups
--> Functional (self-interest) basis for some positions
on trade:
 Owners of abundant factors in favor
 Owners of scarce factors opposed
 Examples?
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Overview of Specific Factors Model (SFM)
 2 good model (like H-O)
 But capital (or natural resource) is specific to sectors
(cannot be moved to other sector)
 Does this make sense?
 Can a coffee farm become a clothing factory in short term?
 In long term?
 In SFM, only labor is mobile between sectors
 Use SFM to study how changes in trade patterns, FDI, and
technology affect economic structure and incomes when
factor-specificity limits adjustment
 Helps us to see winners and losers from trade in a slightly
different way.
Production function – 1 sector
 Factors of production
 Production function
 Diminishing returns
 VMP and factor payments
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Production Function
Rice (tons)
ƒx(L, K)
28
27
25
20
0
10
20
30
40
Labor days
• Constant returns to scale in (L,K), so dim. returns to
L when quantity of K is fixed
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Production Function (more K -> more rice)
ƒx(L, K+)
Rice (tons)
ƒx(L, K)
28
27
25
20
0
10
20
30
40
Labor days
• Constant returns to scale in (L,K), so dim. returns to
L when quantity of K is fixed (irrigated paddy)
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Calculating Factor Returns
X
slope = w/px
X = (w/px)Lx + πx
ƒx(K,L)
X0
Revenue = costs
πx
X*px = w*Lx + rx*Kx
or: X = (w/px)Lx + πx
where: πx = (rx/px)*Kx
0
Lx 0
Lx
• Assume: wage = value of labor’s marginal product
• Return on labor (= wage) = slope of tangent to function
• Return on stock of sector-specific capital is height 0πx = (rx/px)Kx
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(Derivation of factor returns)
 Total revenue of the firm:
pxX = wL + rxKx
 By assumption, the value of output is fully divided
between workers and capital owners
 Dividing both sides by px:
X = (w/px)L + (r/px)Kx
= (w/px)L + πx
 Note: w/px is known as the product wage in sector X
 Distribution between L and K: X – (w/px)L = πx
 Higher wage (steeper slope on w/px) implies lower profit
share. Flatter slope implies higher profit share
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The specific factors model
 Assume 2 goods, X and M
 Each sector uses specific capital, Kx, Km
--> prod’n fns yj = ƒj(L, Kj), j = X, M
 Labor is ‘mobile’ (can be reallocated) between X
and M production
 Total labor force is fixed and fully employed:
L = Lx + Lm
 In equilibrium, same wage offered in both sectors
 For given Kx and Km, when labor is fully employed, can
only increase output (create jobs) in one industry by
reducing output (destroying jobs) in the other
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General Equilibrium – Supply Side
Production function M
M
Prod’n Poss. Frontier,
Maps total production possible
given PFs and labor
ƒm(Lm,Km)
L
0
50
X
Production function x
ƒx(Lx,Kx)
Labor constraint
45o
50
L
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Autarky (no trade)
M
•
uA
MA
•L
0
m
L
pA
•XA
X
Lx •
LA
45o
L
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From Autarky to Trade
p* > pA
•
M
uT
•
MA
uA
pA
•
MT
p*
•L
•
m
L
0
•XA • XT
MT < M A
LMT < LMA
…
uT = uA
LT = LA
X
Lx •
LA
•
LT
L
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Trade, income, distribution in SFM
 Integration with world economy raises aggregate real
income & cons. welfare
 Structure of production and labor allocation change in
predictable ways
 What happens to returns to specific factors? (hint:
Stolper-Samuelson - see notes from Week 1)
 What happens to the real wage?
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Aggregate Income
M
uT
uA
pA
pT
0
L
YA YT X
LA
Compare old and new
incomes at constant prices!
LT
45o
L
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(Aggregate income change)
 YT = aggregate income from production of the combination
(XT, MT) valued at world prices pT, measured in terms of
good X (the value of X that could be bought with that
much income)
 Compare: YA = aggregate income from production of the
combination (XA, MA), valued at world prices pT, measured
in terms of good X
 YT > YA says the economy is better off in aggregate
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Changes in factor payments
(w/pM)T
slope =
M
pA
 MA
(w/pM)A
T
M

L
LA

LT
0

 XA
 TX
pT
X

45o
L
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(Changes in factor payments)
 Moving from autarky to trade raises X output and
employment, lowers M output and employment
 Demand for KX rises; πXT > πXA
 Demand for KM falls; πMT > πMA
 Demand for L in M falls; with KM fixed , law of
diminishing returns says that productivity of
remaining workers rises, so (w/pM)A < (w/pM)T
 Demand for L in X rises; with KX fixed,
(w/pX)A > (w/pX)T
 Are workers better off or worse off?
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Comparative Advantage in Agriculture
Capitalists
(Km)
Landowners
(Kx)
Workers
(L)
Effect of rise in
px on nominal
inc.
Effect of rise in
px on real inc.
(a) When
consume
mostly X
(b) When
consume
mostly M
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Comparative Advantage in Agriculture
Capitalists
(Km)
Landowners
(Kx)
Workers
(L)
lose
gain
gain
(a) When
consume
mostly X
lose
gain
lose?
(b) When
consume
mostly M
lose
gain
gain?
Effect of rise in
px on nominal
inc.
Effect of rise in
px on real inc.
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Comparative Advantage in Manufacturing
Capitalists
(Kx)
Landowners
(Km)
Workers
(L)
Effect of rise in
px on nom.
income
Effect of rise in
px on real inc.
(a) When
consume
mostly X
(b) When
consume
mostly M
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Comparative Advantage in Manufacturing
Capitalists
(Kx)
Landowners
(Km)
Workers
(L)
gain
lose
gain
(a) When
consume
mostly X
gain
lose
lose?
(b) When
consume
mostly M
gain
lose
gain?
Effect of rise in
px on nom.
income
Effect of rise in
px on real inc.
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Distributional & poverty effects
 Real specific factor returns follow own prices: for a
rise in px/pm, πx will rise, πm will fall
 Real wage change is indeterminate:
 Wage rises rel. to pm, but falls rel. to px
 H’hold welfare: aggregate has risen, but
 Gains for owners of capital in X
 Losses for owners of capital in M
 Workers’ welfare change is ambiguous
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Discussion
 If we have data on asset ownership & cons. patterns, can
compute changes in Rh and poverty for groups
 Poverty effects depend on distribution of assets as well as
on changes in payments such as wages and rents
 Notice that we have assumed labor is mobile between
sectors. Realistic? What if it is not?
 SFM vs H-O: which is more realistic? When?
 What about more complex models, for example with
some endogenous product prices (nontradables?)
 See next class…
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