1
Trade liberalization, Openness and Growth
Table of Contents
1. The gains from trade ........................................................................................................................ 3
1.1 Comparative advantage in Ricardo’s model .............................................................................. 3
1.2 Comparative advantage with two factors: Heckscher-Ohlin ..................................................... 6
1.2.1 Concepts .............................................................................................................................. 6
1.2.2 Measurement ....................................................................................................................... 8
1.2.3 Do countries specialize or diversify ? ............................................................................... 10
1.3. Monopolistic competition and product variety ....................................................................... 13
1.3.1 Homogenous firms ............................................................................................................ 13
1.3.2 Heterogeneous firms ......................................................................................................... 15
2. The openess-growth debate between 1995 and now...................................................................... 16
2.1 Trade liberalization in a Solow model ..................................................................................... 16
2.2 The « East Asian Miracle » ...................................................................................................... 17
2.3 The cross-sectional evidence ................................................................................................... 19
2.3.1 Trade openess index of Sachs-Warner .............................................................................. 19
2.3.2 The critique of Rodriguez et Rodrik ................................................................................. 23
2.4 The evidence in panel .............................................................................................................. 25
3. Structural adjustment and resource allocation ............................................................................... 34
References .......................................................................................................................................... 36
List of tables
Table 1: Productivity and endowment data in a Ricardian example ................................................... 3 Table 2: candidate equilibrium for the integrated world economy ...................................................... 5
Table 3: Estimated TFPG in the East Asian Miracle ......................................................................... 18 Table 4: Estimation results of Young (1993) ..................................................................................... 19 Table 5: Growth and openness: Cross-section regression results 1980-90 ........................................ 21 Table 6: TFP growth regressions with various openness indices ...................................................... 22
Table 7: Regression results of Rodrik Rodriguez with the decomposed SW index .......................... 23 Table 8: Trade liberalization dates in Wacziarg and Welsh .............................................................. 25 Table 9: Details of trade reforms by country ..................................................................................... 26 Table 10: SW results reproduced ....................................................................................................... 27 Table 11: SW results on a different time period ................................................................................ 28
2
Table 12: Growth and openness in panel ........................................................................................... 29
Table 13: Growth regressed in the liberalization indicator ................................................................ 32 Table 14: Growth regressed on tariff changes ................................................................................... 33 Table 15: Approach 1 with instrumental variable.............................................................................. 34
List of figures
Figure 1: Production Possibility Frontier and autarky equilibrium : Portugal ..................................... 4 Figure 2: Production Possibility Frontier and autarky equilibrium : Great Britain ............................. 4 Figure 3: The gains from trade............................................................................................................. 5
Figure 4: The gains from specialisation ............................................................................................... 6 Figure 5_ Factor Endowment and PPF: The Rybczynski Theorem .................................................... 7 Figure 6: Factor Endowment and Comparative Advantage: The Heckscher-Ohlin Theorem ............. 7
Figure 7: Factor endowments and revealed factor intensities .............................................................. 9 Figure 8: Comparative advantage and the survival of exports .......................................................... 10 Figure 9: Fuel exports and GDP volatility ......................................................................................... 10
Figure 10: Export concentration and the level of income .................................................................. 11 Figure 11: Concentration: Individual country trajectories ................................................................. 11
Figure 12: The export re-concentration at high levels of income ...................................................... 12 Figure 13: What are the closing export lines? ................................................................................... 12 Figure 14: Effect of an increase in the custom duty rate on capital equipment in the Solow model . 17
Figure 15: Average growthe for closed and open economies ............................................................ 20 Figure 16: convergence among closed economies............................................................................. 20
Figure 17: Convergence among open economies .............................................................................. 21 Figure 18: Growth and import tariffs ................................................................................................. 24
Figure 19: Growth and NTB coverage ratios ..................................................................................... 24 Figure 20: Time profile of growth around liberalization year ........................................................... 30
Figure 21: Time profile of investment around the liberalization year ............................................... 30 Figure 22: Decomposition of productivity growth : within-sector vs. Structural adjustment ........... 35 Figure 23: Correlation between productivity and variation in employment per sector ..................... 35
3
1. The gains from trade
Traditional trade theory suggests that:
o Trade among countries generates efficiency gains for all countries, irrespective of their level of
productivity; in other words, all countries, in general gain from trade. Absolute productivity
determines income levels, not trade patterns.
o Countries specialize according to their comparative advantage, generating efficiency.
1.1 Comparative advantage in Ricardo’s model
In the simplest version of the Ricardian model (not to be confused with the Ricardo-Viner model as
we will see later, and which has nothing to do!), the assumptions are
• Two countries (Portugal et GB)
• Two sectors (wine and drape)
• Only one factor of production (labor), perfectly mobile between the two sectors
• Constant returns to scale
• No transport costs
• No government intervention
• Perfect competition (price = cost)
• At the same price, consumers share their budget equally between wine and drape
Comparative advantage is determined by the relative productivity of labor (the only production
factor) in the two sectors, as illustrated in Table 1.
Table 1: Productivity and endowment data in a Ricardian example
Productivity Endowments
(labor)
Wine Drape
Portugal 8 4 5
UK 1 2 20
Note that the example’s assumptions imply that Portugal is everywhere more productive than the
UK; however, it is relatively more productive in wine. The maximum combination of goods that
Portugal can produce in autarky (i.e. without international trade) is shown by its production
possibility frontier, illustrated in Figure 1. The same thing for the UK is shown in Figure 2.
4
Figure 1: Production Possibility Frontier and autarky equilibrium: Portugal
Figure 2: Production Possibility Frontier and autarky equilibrium: Great Britain
In order to illustrate the gains from trade, we « guess » an integrated world equilibrium with free
trade and show that (i) it is a viable equilibrium in the sense that both countries have balanced trade
and supply equals demand in each industry at the global level, and (ii) every country is better off
than under autarky. The equilibrium is characterized in Table 2.
In that equilibrium, Portugal specializes completely in wine, the UK in drape, the relative price of
the two products is just one (meaning that one liter of wine trades for one meter of drape) and each
country splits its consumption half-half between wine and drape. Thus Portugal imports 20 units of
drape and export 20 units of wine, while the UK does the reverse.
Wine
Drape
40
20
PPF (Production Possibility Frontier)
Point of Consumption in Autarky
Indifference Curve
Wine
Drape
20
40
PPF
Point of Consumption in Autarky
Indifference Curve
5
Table 2: candidate equilibrium for the integrated world economy
The fact that Portugal can consume 20 units of drape plus some wine shows that it gains from trade,
since under autarky if it wanted to consume 20 units of drape it would have had to put all its
manpower in that sector, leaving no wine to be produced. Conversely for the UK. So everyone is
better off as a result of specialization.
More generally, gains from trade arise whenever international relative prices, shown by the
(absolute value of the) slope of the blue line in Figure 3, differ from domestic relative prices, shown
by the absolute value of the slope of the PPF.
Figure 3: The gains from trade
While Figure 3 shows the gains from pure trade, additional gains can be generated by specializing
the production structure in order to take advantage of comparative advantage, as shown in Figure 4.
The process of moving from the autarky equilibrium to the specialized equilibrium where the
utilization of resources generates the maximum efficiency gains at world price is called “structural
adjustment” (SA). It is the essence of the policies pushed by the IMF and the World Bank in Latin
American and African countries in the 1980s and 1990s. What the SA reforms entailed is the
closure of industries geared towards import substitution in order to free up resources to be invested
in export-oriented industries. While the principle was sound, as we will discuss later on in this
Wine Drape Wine Drape
Portugal 40 0 20 20
UK 0 40 20 20
Total 40 40 40 40
Production Consumption
World Price Line
Wine
PPF
Drape
Indifference Curves
export
import
6
chapter numerous difficulties stood in the way of demonstrating that this would generate a growth
dividend, and even today there is controversy about whether SA really pushed resources (in
particular employment) toward more “efficient” sectors.
Figure 4: The gains from specialization
1.2 Comparative advantage with two factors: Heckscher-Ohlin
While the Ricardian model is a classical model where labor is the only productive factor, the same
story can be told in a so-called “neoclassical” model where technology combines labor and capital
(or unskilled and skilled labor, or any combination of factors for that matter) to produce output.
1.2.1 Concepts
The first step of the analysis here consists of relating factor endowments with the PPF (the PPF
being drawn in product space, not in factor-endowment space); this is done by the Rybczynski
theorem, which says that if there is an inflow of a given factor of production, the PPF “inflates”
asymmetrically in the direction of the sector that uses that factor most intensively. Quite a
mouthful. What it means is that if there is an inflow of capital and steelmaking is capital-intensive,
the PPF will inflate more in the direction of steelmaking than in the direction of, say, textiles, which
are not capital intensive. This is shown in Figure 5.
Indifference Curves
Wine
PPF
Drape
Lines of World prices
Point of Production
7
Figure 5_ Factor Endowment and PPF: The Rybczynski Theorem
From then on the story is pretty much the same. If a country has lots of capital (because previous
generations saved a lot), it will have a PPF looking like the blue one in Figure 5 and will have a
comparative advantage in capital-intensive industries. Moving from autarky to free-trade as shown
by the flue arrow in Figure 6, it will specialize in those industries and, in so doing, reap efficiency
gains.
Figure 6: Factor Endowment and Comparative Advantage: The Heckscher-Ohlin Theorem
Note that this is frankly a bit of a fairy tale. We are assuming here that for every job destroyed in a
comparative-disadvantage sector by SA, a new job will appear all of a sudden by some miracle in a
comparative-advantage sector. This is because the HO model is, by construction, a full-employment
model. Outside of this fairy tale, in the real world, there are numerous barriers to the movement of
factors and things just don’t that way. People who lose their jobs are typically located in declining
PPF initial
Steel
The impact of foreign investments
The impact of immigration
Textile
“trade triangle”
Steel
Textile
Indifference curves
Relative Price on world market (textile less expensive)
Point of consumption after structural adjustment
Autarky relative price
Point of production after structural adjustment
PPF
8
regions where “sunrise” industries don’t locate. Many of them have firm-specific or no skills,
making them poor hires for the sunrise industries. And so on.
1.2.2 Measurement
When there are more goods than factors of production, in general the direction of trade (who
exports what) is not determined.1 However, overall, countries tend to export goods whose factor
intensity corresponds more or less to their factor endowments.
The traditional measure of comparative advantage is the Balassa index of revealed comparative
advantage, calculated as follows: let inx be country i’s exports of product n, ix the total exports of
country i, nx world exports of product n, and x world exports. The Balassa index is then:
/
/
in iin
n
x x
x x
The problem with this index is that it assumes that if country i exports product n, it has a
comparative advantage in this product; but the index does not use the factor endowment of country
i.
Here is another approach. Using data on factor endowments from UNCTAD, we can determine the
« revealed » factor intensity of each product by taking the average endowments of the countries that
are exporting it. If i is the endowment of capital of country i, the capital intensity of the good n is
approximated by a weighted average of the capital endowments of the countries exporting it:
n in ii
where in , the weights, are modified versions of the Balassa index made to add up to one, i.e.
1ini .2 The advantage of this normalization is that it allows us to represent national factor
endowments and the products’ revealed intensities in the same space, i.e. to superimpose them on
one picture. If countries export products whose intensities correspond more or less to their factor
endowment, the cloud of points representing their export portfolio should be relatively concentrated
around their endowments. That’s just what we observe in Figure 7, where the horizontal axis
measures capital intensity/endowments (in dollars of capital per worker), the vertical axis measures
human-capital intensity/endowments (in years of education per worker), and each circle
corresponds to a product, with circle size proportional to the product’s dollar export value for the
country in question. The black cross is the country’s endowment. In the case of Costa Rica in 1993,
the capital and HK’s intensity of its biggest export product (bananas) corresponded to a factor
endowment slightly lower in terms of capital and human capital than its own; in other words, it was
slightly under-selling itself. The reverse was clearly true for Pakistan in 2003-5.
1 Can be found in trade flows with a continuum of goods as in Dornbusch Fisher Samuelson model. 2 Caution: If some countries subsidize the exports of products that do not correspond to their comparative advantage,
the computation is distorted (e.g. agricultural products to Europe). We must therefore correct for this bias in the
computations.
9
Figure 7: Factor endowments and revealed factor intensities
Costa Rica 1993 Pakistan 2003-5
Figure 7 (ctd)
Tunisie 2003-5 Tunisie : new export products
Interestingly, exported products that are distant from a country’s factor endowment (hence do not
correspond to a clear comparative advantage) seem to survive less on export markets, as shown by
the slightly negative correlation visible in Figure 8.
02
46
810
12
Re
vea
led
Hu
man
Cap
ital I
nte
nsity
Inde
x
0 50000 100000 150000 200000Revealed Physical Capital Intensity Index
Endowment point
02
46
810
12
Re
vea
led H
um
an
Capita
l In
tensi
ty In
de
x
0 50000 100000 150000 200000Revealed Physical Capital Intensity Index
02
46
810
12
Rev
eale
d H
uman
Cap
ital I
nten
sity
Inde
x
0 50000 100000 150000 200000Revealed Physical Capital Intensity Index
02
46
810
12
Re
vea
led
Hu
man
Cap
ital I
nte
nsity
Inde
x
0 50000 100000 150000 200000Revealed Physical Capital Intensity Index
10
Figure 8: Comparative advantage and the survival of exports
1.2.3 Do countries specialize or diversify?
The Ricardian model suggests that countries should specialize in their comparative advantage rather
than diversify. But specialization in raw materials, for example, can be synonymous of "imported
volatility", because the prices of raw materials fluctuate widely. This is shown in Figure 9 where the
horizontal axis measures the share of hydrocarbons in country exports and the vertical axis
measures the coefficient of variation (standard error/mean) of GDP over a seven-year period. The
positive correlation between the two is pretty obvious.
Figure 9: Fuel exports and GDP volatility
23
45
67
2 2.2 2.4 2.6 2.8 3(mean) std_dist_1
(mean) length Fitted values
Length of trade relationship and distance to CA
GABGABGABGABGABGABGABGAB
0.2
.4.6
.81
Coef
fici
ent
of
var
iati
on o
f G
DP
, 2000-2
007
0 20 40 60 80 100Fuel share in exports
11
Recent studies also suggest that the decline in the volatility of GDP observed in recent decades in
the United States is largely linked to the diversification of the economy (in services).
Interestingly, generally the concentration of exports follows a non-monotone path as countries
develop: first diversification, then reconcentration. We measure the concentration of exports in
similar way as we measure the concentration in income, by three indices: (i) Gini, (ii) Herfindahl,
and (iii) Theil. Here we considered the index of Theil, whose formula is:
1
lni i
i
x xT
n x x
(1)
Figure 10: Export concentration and the level of income
And the reconcentration occurred in the individual trajectories of countries:
Figure 11: Concentration: Individual country trajectories
24
68
0 20000 40000 60000 80000GDP per cap, 2005 PPP dollars
Theil index Theil index, Uganda
Fitted values
More concentrated than
predicted
Less
concentrated
than predicted
Uganda
2000 Predicted
Uganda
2010
IRL
ESP
GRC
GBR23
45
15000 20000 25000 30000 35000 40000GDP per capita, PPP (constant 2005 international $)
12
Which countries are those that re-concentrate?
Figure 12: The export re-concentration at high levels of income
How can we explain the reconcentration? Essentially the inertia of trade flows, export lines that are
closed have factor intensities corresponding to weaker endowments than those of countries that
close. For example, the average of trade lines closed by the EU corresponds to the combined
endowment of human and physical capital of Indonesia. These lines should be long gone, but they
remain open by inertia.
Figure 13: What are the closing export lines?
In short, the theory seems to stick quite well with empirical observation, although the "content
factors" does appear to explain only a small part of international trade. We therefore need other
models to have a more complete view of its determinants.
34
56
7
The
il in
de
x
0
100
02
00
03
00
04
00
05
00
0
num
ber
of e
xport
ed p
rod
ucts
0 20000 40000 60000GDP per capita PPP (constant 2005 international $)
Active lines - quadratic Active lines - non parametric
Theil index - non parametric Theil index - quadratic
# active export lines
Theil index
24
68
10
12
0 50000 100000 150000 200000
Product intensities Country endowments
Capital
Human capital
13
On the other hand, so far everything discussed was essentially static: allocative efficiency
considerations tell us nothing about the growth. In the models of endogenous growth, growth is
mainly due to innovation; international trade plays only an indirect role (i.e. through innovation).
So we will discuss the relationship between trade and growth from an essentially empirical point of
view, except a small detour to the Solow model in Section 3
1.3. Monopolistic competition and product variety
1.3.1 Homogenous firms
The monopolistic competition model The Heckscher-Ohlin model explains trade by differences in factor endowments. It cannot explain
the trade between countries with similar endowments, and even less intra-industrial trade. We will
now focus on an alternative model proposed by Krugman (1980), called « monopolistic
competition».
The ingredients for a model of monopolistic competition are:
o Product differentiation that generates a finite elasticity for each firm
o Economies of scale
The gains of trade in the MC model come from competition, which compresses margins and prices.
Consider the following example from Krugman, Obstfeld and Mélitz (2012), pp 168-177
Let S be the volume of national trade, which we take as exogenously given (independent of the
prices of the firms active in this market) which is of course unrealistic but simplifies the analysis
greatly. Let n be the number of firms active in the market, b a parameter of demand (linear), Qi the
quantity sold per company i, pi its price and p the average price in the market.
Total cost is the sum of a fixed cost F and a marginal cost c:
i iC F cQ
which gives average cost of :
i
i
FAC c
Q (2)
Demand function facing firm i:
1
i iQ S b p pn
(3)
In a «symmetric equilibrium» where all firms set the same price ip p , it can be seen from (3)
that /iQ S n ; market shares are equal.
Optimal pricing by profit-maximizing firms equalizes marginal cost and marginal revenue. To
derive marginal revenue, invert (3) to get the demand price:
1 i
i
Qp p
bn bS (4)
14
Revenue is price multiplied by quantity
2
i ii i i
Q Qp Q pQ
bn bS (5)
and marginal revenue is the derivative of revenue w.r.t. quantity:
1 2
1
i
ii
i i
p
ii
QRM p
bn bS
Q Qp
bn bS bS
Qp
bS
(6)
Marginal cost is simply c. Optimal pricing is therefore
ii
Qp c
bS (7)
Or
"mark-up"
ii
Qp c
bS (8)
In the symmetric equilibrium where all firms adopt the same price, Q = S/n, optimal pricing
simplifies to
1
ip p c ibn
(9)
In this equilibrium, average cost is found by substituting Q = S/n in (2), which yields
Fn
AC cS
(10)
With free entry, profits must be zero, which means that price has to equal average cost:
1 Fn
c cbn S
(11)
or
2 Sn
bF (12)
which determines the number of firms compatible with zero profits in the market (no incentive for
additional entry). In this model, gains from trade arise because of
o Economic integration that creates a bigger market
o Increasing competition, reducing margins
15
This can be seen by « merging » two countries with equal size S as part of a big-bang trade-
liberalization experiment.
Effects of trade liberalization
We do the comparison that is commonly done in international trade between an equilibrium in
autarky and an equilibrium with free trade where all barriers are eliminated. The effect is illustrated
in a numerical example in the excel file ‘Exemple concurrence monopolistique.xlsx.’ Suppose that
the two countries are of equal size and that there is no transportation cost. Then their combined size
is ' 2S S , so the total number of firms is
' 2
' 2 1.414S S S
n nbF bF bF
and the equilibrium price and quantity are
1
''
p c pbn
' 2
' 2 2' 2
S S SQ Q Q
n nn
So :
o The total number of varieties available to any consumer in the two-country area increases (there
are fewer in each country but consumers have access to both)
o The equilibrium price is lower, and so are profit margins (not shown but easy to calculate)
o Output per firm increases.
Damn it, everything is fine in this world?
1.3.2 Heterogeneous firms
Note that the trade liberalization induces firm exit, since ' 2 2n n n . In a symmetric
equilibrium, which firms will exit is indeterminate. But suppose now that potential entrants differ in
their marginal cost ci, in accordance with new “heterogeneous-firm” models. Those with marginal
cost higher than the « choke price » don’t enter.
Intercept of demand facing each firm: Using (3), Qi = 0 implies
choke 1p p
bn
And the slope of the demand curve is:
1i
i
dp
dQ bS
16
Trade liberalization means that chokep goes down as n goes up, while the slope becomes “less
negative” as S goes up. Thus, under the effect of an increase in S and the induced increase of n, the
demand curve rotates anticlockwise.
o The demand increases for big firms with low marginal cost
o But it decreases for firms with higher marginal cost, which leads to the exit of some firms.
2. The openness-growth debate between 1995 and now
2.1 Trade liberalization in a Solow model
Everything that we saw at the beginning of this chapter was static. Is there any reason to think that
trade liberalization could accelerate the growth? Yes if trade liberalization affects the price of
capital goods, for example. To see this, we take the Solow model and assume that the domestic
price of capital goods (the capital) is:
* 1K K Kp p t
where *
kp is the world price of one unit of capital (one « machine ») and kt is the customs duty on
imported capital. Assume, to simplify, that * 1kp , that is if we measure the capital in dollars, then
one unit is worth a dollar. Rewrite the law of motion of capital as :
1K K
I IK K K
p t
Then we have :
1 ˆ
1 ˆ1
1.
1
K
K
K
IK
tdkk kL
dt L
I KkL
t L L
sk n kt
A high customs duty therefore lowers the curve in Figure 14; the steady state (the intersection of the
curves, that are respectively representing the first term on the right of the equation above, and the
second term) moves to the left (at a lower level of capital per worker) and the rate of growth during
the transition to steady state, slows.
17
Figure 14: Effect of an increase in the custom duty rate on capital equipment in the Solow model
In the particular case of capital goods, the link between trade liberalization is therefore direct (and
obvious). This explains the 'climbing' structures of tariffs, prevailing in most developing countries:
low or zero tariff on capital goods, moderate tariff rates on intermediate products used as inputs in
the industry, and the highest rates on consumer goods.
2.2 The « East Asian Miracle »
Empirically, what can we say about the relationship between trade and growth? The « East Asian
miracle » is the title of a World Bank report published in 1994 and dedicated to the spectacular
growth of the Asian tigers (compared to other continents, in particular Africa and Latin America).
This report had considerable visibility although it was highly controversial.
The approach was a “growth accounting” one based on a Cobb-Douglass production function:
ln
it it it it
it it
Y K L H
y Y
(0.13)
Log-linearizing gives an estimable growth equation
it it it it ity k h u (14)
18
where ui is the error term. Let ei be the residual of the estimation in (14), i.e.
ˆˆ ˆit it it it ite y k h (0.15)
We will give a name to this residual: TFP (Total Factor Productivity). Taking first differences (i.e.
growth rates, since everything is in logs) we define Total Factor Productivity Growth (TFPG) as
1it it it ite e e TFPG (0.16)
This gives us a decomposition of sources of growth in two components:
o Accumulation, i.e. what is predicted by (14),
o TFPG or improved Efficiency (the residual)
This decomposition is very important. If accumulation (especially capital) is the dominant
contribution to growth, the recipe for economic policy is the "mobilization of savings" for
investment. This can be done - and has been historically - abruptly by taxing agriculture to generate
the resources needed for investment. Extreme cases: the Soviet Union under Stalin. It is also what
inspired many economic policies in Africa.
On the other hand, if the TFPG is dominant, then is something else. The problem is that as the
TFPG is a residual, by definition it is not known what it is, and we could put what we want as
interpretation.
Table 3: Estimated TFPG in the East Asian Miracle
There is clearly a difference in the nature of growth between the SE Asia and the remainder (AL
and ASS). The TFPG is dominant in Asia, not elsewhere. Explanation: trade openness that forces
local businesses to restructure and improve the efficiency.
Unfortunately, the same year when the preliminary draft of the « East Asian Miracle » circulated,
Alwyn Young published a paper that showed the labor factor was improperly measured
(underestimated) for SEA (South East Asia) countries in the report of the Bank, the residual
measured correctly was a bit smaller for these countries. Even more of a miracle!
Average TFP 1970-90 (% per year)
Taiwan 3.76 Hong-Kong 3.64 Korea 3.10 Japan 3.48 Thailand 2.49 Singapore 1.19 Malaysia 1.07
Latin Am. 0.13 Afr. sub-sah. -0.99
19
Table 4: Estimation results of Young (1993)
Source : Young, 1993
2.3 The cross-sectional evidence
2.3.1 Trade openness index of Sachs-Warner
Idea: correlate the growth in the period 1980-90 with a measure of trade openness. Binary measure:
either open or closed country. « Closed » if one or more of the following criteria are satisfied:
1. Average tarif greater than 40%
2. Rate of coverage of non-tariff barriers (quotas etc.) greater than 40% of imports
3. Black market currency premium greater than 20% during the decade
4. Export State Monopoly
5. Socialist Economy
SW found a strong correlation between growth and their measurement of the opening. Already in
descriptive statistics, the difference is clear:
20
Figure 15: Average growthe for closed and open economies
Source: Sachs and Warner (1995)
In addition there is convergence among the open countries but not closed countries:
Figure 16: convergence among closed economies
Source: Sachs and Warner (1995)
21
Figure 17: Convergence among open economies
Source: Sachs and Warner (1995)
The cross-section regression results confirm the descriptive statistics (table 5).
Table 5: Growth and openness: Cross-section regression results 1980-90
Source: Sachs and Warner (1995)
22
Edwards (1998) attempted to show that the results of Sachs and Warner were robust and not the
effect of a particular approach. It includes all of the openness measures (Sachs and Warner and
other) and systematically explores the correlation between these measures and the TFPG.
OPEN Sachs-Warner
WDR Openness Index of the World Bank (composite)
LEAMER Residual of an equation of openness
BLACK Black market premium on currencies
TARIFF Average import tarif
QR Rate of coverage of quantitative trade barriers
HERITAGE Trade-distortion perception index
CTR Revenue on import taxes in proportion of the value of imports
WOLFF Another residual of a regression of openness
SW results are robust; several other similar exercises give the same results
Table 6: TFP growth regressions with various openness indices
Source: Edwards 1998.
23
Basically, the message is that regardless of the measure of openness that we take, the correlation
with the TFPG seems well-established. The message of the East Asian Miracle was fundamentally
correct even if the measures are different good this is.
2.3.2 The critique of Rodriguez and Rodrik
Rodriguez and Rodrick (2001) show the opposite. They do an exercise of brutal deconstruction of
all this econometrics, in particular of the econometrics of Sachs Warner.
1 si tariffs < 40% & NTB < 40% et pas SOC
0 sinonSQT
1 si BMP < 20% & pas de MON
0 sinonBM
Table 7: Regression results of Rodrik Rodriguez with the decomposed SW index
24
Figure 18: Growth and import tariffs
Source: Rodriguez and Rodrik (2001)
Figure 19: Growth and NTB coverage ratios
Source: Rodriguez and Rodrik (2001)
So what explains the differences of TFPG, is not so much trade policy stricto sensu, but rather
macroeconomic policy (the overvaluation of the exchange rate measured by the premium on
currencies) and export monopolies. But, what country had exchange rates overvalued in the 1980s?
Latin America. Which country had export monopolies? Africa.
25
2.4 The evidence in panel
All first generation studies were cross-sectional. Wacziarg and Welsh (2008) remake the estimates
in panel data by carefully identifying the date of trade liberalization (while SW did not date, since
they were using a cross-sectional over a decade). Employing a panel allows to use the fixed-effects
estimator (dummy variables that capture country-invariant characteristics over time). The effect is
much better identified, as it is "within-country" that is to say, it filters the heterogeneity between
countries due to unrelated trade openness factors.
Table 8: Trade liberalization dates in Wacziarg and Welsh
26
Table 9: Details of trade reforms by country
27
Results: Reproducing exactly the exercise of SW, they find the same findings:
Table 10: SW results reproduced
28
On the other hand, when running the same regressions on another time period (the 90s), nothing
stays significant:
Table 11: SW results on a different time period
What to make of it? The answer comes with panel regressions where the fundamental explanatory
variable is the date of trade liberalization; the date of the liberalization contains additional
information that is not distorted by other unexplained differences between countries (since we use
the difference in time for each country).
29
Table 12: Growth and openness in panel
Once doing this, the results become correct for all periods – far more convincing. Figure 20
displays the results in a more intuitive way. Time is normalized to be zero in the year of trade
liberalization for each country (so if Colombia liberalizes in 1995, 1994 = -1, 1995 = 0, 1996 =
1 for Columbia; if Chile liberalizes in 1970, 1969 = -1 etc.). Each point on the curve is the average
of the sample growth at t = -10, t = -9, etc. We observe an acceleration of growth of about 1.5
percentage points around the year zero.
30
Figure 20: Time profile of growth around liberalization year
Figure 21 shows the same finding for investment. We observe a spectacular rise in the rate of
investment after the liberalization.
Figure 21: Time profile of investment around the liberalization year
On the other hand, the identification problem remains still unsolved in Wacziarg and Welsh due to
the fact that the trade reforms were often implemented at the same time as reform packages that
affected several other sectors of the economy (macroeconomic stabilizations, privatizations,
31
governance reforms, etc.) and oftentimes also coincide with changes in government. So: is it really
the trade liberalization causing the effects or other simultaneous developments?
Estevadeordal and Taylor (2009) revisited the question in the different ways where the second one
is interesting in itself to understand for the used methodology.
Approach 1 (« simple differences »)
They regress the change in growth on the change in tariffs in a panel of countries—a standard
technique. With i representing a country, t the time, itg the growth of country i at time t,
,it it ith zx a country-specific vector (human capital and characteristics of governance), and it the
average of tariffs of country i in time t.
, 1it it i tg g g (17)
And the same for other variables put in differences. The equation becomes
0 1 , 1 2 3 ln 1it i t it it itg g u x α (18)
Approach 2 (« differences in differences »)
E&T use as natural experiment the liberalization implemented by a number of countries during
trade negotiations in Uruguay (the « Uruguay Round » that took place between 1986 and 1994).
Certain countries liberalized their tariffs; they form the « treatment group », other countries that
didn’t liberalize are put in the « control group ». Again, the sample structure is a panel, but now the
estimation technique is called « differences in differences ». This term expresses that we compare
the performance before and after a certain date where the treatment starts (the first difference), but
for two groups, the treatment and the control group (second difference). This estimation technique
is commonly used in medical sciences.
With iD being a dummy variable marking belonging to the treatment group and tT the treatment
period (after the Uruguay round); so
1 if 1994
0 if < 1994t
tT
t
The basic equation becomes
0 1 2 3 0 4
_
it i t i t i it
Treatment effect
g D T D T u x α (19)
And the coefficient 3 gives the treatment effect. We can also re-write (19) in a simpler way with
fixed effects for countries and years:
Treatment effect
it i t i t itg D T u (20)
32
Finally a third way of writing and estimating this equation consists of defining two long periods (
0 1975 1989t and 1 1990 2004t ), which gives us a two-period panel, and taking the change
between those two periods :
1 0, ,i i t i tg g g (21)
Which yields
00 1 , 2 3i i t i i ig g D u x α (22)
The basic results of the Diff-in-Diff approach (DD) are displayed in Table 13. The first column uses
the average of tariffs for all goods as regressor of interest (« liberalizer indicator »); the second
column uses the average of tariffs only on consumption goods, the third uses the average on tariffs
on equipment goods and the fourth uses the average tariff on intermediate goods. We find that the
coefficients are significant and estimated more precisely for the equipment goods than for
consumption goods. However, the effects are rather weak.
Table 13: Growth regressed in the liberalization indicator
33
The results of the first approach are very similar, but with the opposite sign since lower tariffs
accelerate growth:
Table 14: Growth regressed on tariff changes
Again, the coefficients are very small (signaling a very weak effect) and only significant at the 10%
level (signaling that the effect is not well measured). On the other hand, the coefficient on the tariffs
for equipment good is two times higher than the coefficient for consumption goods, which is in line
with the basic growth model of section 2.1.
Endogeneity
The two approaches face similar problems, firstly endogeneity and secondly selection. They only
handle the first problem, where the problem is that the variation in tariffs and the variation in
growth could be explained by the same omitted variable, for example a change in government.3
The instrumental variable is the interaction between two things:
1. The intensity of the Great Depression in the observed countries
2. The level of tariffs in the countries before the Uruguay round.
The idea of the first element is that countries that suffered more in the Depression have more than
others lost the faith in liberalism and adopted more protectionist policies afterwards, which could
3 In the second approach, we face a selection problem. The approach relies on the hypothesis that the decision to take
the treatment is uncorrelated with the potential effect of the treatment. In fact, if the countries that liberalized were
systematically more likely to benefit from the treatment, we cannot use the equation (19) to deduct that the same effect
would have worked in the countries that were not treated. Therefore we have to control for this selection effect that is
always present when the treatment is not given at random, but this control is not done here.
34
have survived until today and resulted in less willingness for a liberalization. The idea of the second
element is that for liberalizing, countries must have entered the Uruguay round with high tariffs
(otherwise no need for liberalization). So, low intensity of the Great Depression × high level of
tariffs predict a strong liberalization in the Uruguay round.
Table 15: Approach 1 with instrumental variable
We note that the effect is now stronger and more significant (it’s the « second stage » that we care
about; we have -0.05 now vs. -0.03 before, and the effect is significant at 5%).
3. Structural adjustment and resource allocation
Is this the end of the debate? Not yet. In a recent paper, McMillan and Rodrik (2010) have
decomposed the growth of productivity and shown a result opposing the message of the beginning
of the course:
o The productivity growth in a sector is comparable across countries ; particularly there is no
substantial difference between Africa and America as before
o In contrast, in favor of a structural adjustment: in these two regions resources have moved from
sectors with high productivity growth towards sectors with low productivity growth.
Supposing that the productivity of the manufacturing sector was a weighted average of the
productivity of several sectors.
t j jj
q q
with 1jj . We can express its variation, 1t t tq q q as
Croissance "within" Structural adjustment small--we ignore it!
j j j j j jj j jq q q q
35
Representing the first term in grey and the second in black in averages per region, McMillan and
Rodrik (2011) obtain in Figure 22:
Figure 22: Decomposition of productivity growth: within-sector vs. Structural adjustment
Source : McMillan and Rodrik (2011).
The grey component doesn’t really vary from one region to the other. However, the black part
really makes a difference. The structural adjustment has moved resources to the wrong place! The
case of Argentina is particularly interesting (Figure 23).
Figure 23: Correlation between productivity and variation in employment per sector
Source: McMillan and Rodrik (2011).
36
References
Edwards, Sebastian (1998); “Openness, Productivity and Growth: What Do We Really Know?”;
Economic Journal 108, 383-98.
Estevadeordal, Antoni, and Alan Taylor (2009), “Is the Washington Consensus Dead? Growth,
Openness, and the Great Liberalization, 1970s-2000s”; IDB working paper IDB-WP-I38;
Washington, DC: Inter-American Development Bank.
McMillan, Margaret S. and Dani Rodrik, “Globalization, Structural Change and Productivity
Growth,” Working Paper No. 17143, NBER (http://www.nber.org/papers/w17143), June 2011.
Rodrik, Dani, and F. Rodriguez (2001), “Trade Policy and Economic Growth: A Skeptic's Guide to
the Cross-National Evidence”; in Ben S. Bernanke and Kenneth Rogoff, editors, NBER
Macroeconomics Annual 2000, Volume 15, p. 261 – 338; Boston, MA: National Bureau of
Economic Research.
Sachs, Jeffrey, and Andrew Warner (1995), “Economic Reform and the Process of Global
Integration”; Brookings Papers on Economic Activity 26, 1-118.
Wacziarg, Romain, and K. Welch (2008), “Trade Liberalization and Growth: New Evidence”;
World Bank Economic Review 22, 187-231.
The World Bank (1993), The East Asian miracle : economic growth and public policy; Washington,
DC: The World Bank.
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