Gains from trade and total factor productivity across economies Pedro Cavalcanti Ferreira EPGE - Fundação Getulio Vargas
Alberto Trejosy INCAE
July 17, 2007
Abstract This article studies and measures the gains from openness and the e¤ects of international trade policy on productivity and output levels. It is assumed an economy with two tradable and non-storable intermediate goods, used in the production of a non-tradable …nal good. The solution of the static trade and factor allocation problem generates implicitly a mapping between factor endowments and …nal output, which is then used as an exogenous production function. We …nd that for very poor economies gains from trade are sizable and in many cases more than 50% of their per capita income. Most of these countries have high tari¤s but enjoy most of their potential gains from trade as their factor endowment is very di¤erent from that of the rich countries that they trade with. However, there are a group of lowto-middle income countries (e.g., India and Pakistan), with sizeable potential gains from trade, and for whom barriers to trade imply a signi…cant loss.
1
Introduction
We study and measure the e¤ects of international trade policy on total factor productivity (TFP) and output levels. We use as our main instrument a dynamic Hecksher-Ohlin model that follows, among others, Ferreira and Trejos y
Praia de Botafogo, 190, Rio de Janeiro,RJ, Brazil, 22253-900.
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[email protected]
1
(2006). In this framework, it is assumed an economy with two tradable and non-storable intermediate goods, used in the production of a non-tradable …nal good. We focus on the case of a small, price-taking economy. The solution of the static trade and factor allocation problem generates implicitly a mapping between factor endowments and …nal output, which can then be used as an exogenous production function. This formulation is similar to Corden (1971), Trejos (1992) and Ventura (1997) that use a factor-endowments framework to introduce trade in a macro model. In this model, policy instruments that increase the cost of international trade generate an ine¢ cient equilibrium allocation of factors across industries. This ine¢ ciency has an e¤ect similar to a fall in total factor productivity. We …rst use this framework to measure the static gains from trade assuming a move from autarky to free trade. Under a very conservative calibration we show that for a country with around one per cent of the capital-labor ratio of the rich economies (e.g. Mozambique and Rwanda in our sample) these potential gains from trade area sizable, reaching 75% of their own output. We them apply observed tari¤ data to measure what portion of these potential gains are actually being enjoyed. The answer depends on the magnitude of the trade barriers and also on the relative capital-labor ratio, a fact not always observed in the literature. For instance, in 1985 Brazil and Benin had similar nominal tari¤ rates (unweighted averages). However, while the latter realized almost all its potential gains from trade, Brazil lost almost them all. This is because capital-labor ratio in Benin is only, on average, 4% of the rich economies it trade with, while in Brazil it was 57%. However, there are a group of low-to-middle income countries (e.g., India and Pakistan), with sizeable potential gains from trade, and for whom barriers to trade imply a signi…cant loss. These results compare with those in the "pure trade part" (i.e., the model without di¤usion) of Rodriguez-Clare (2006), who also found sizable gains for very poor economies. However, they contrast with those in Eaton and Kurtun (2002) because, by construction, the gains from trade between two rich economies in our model are small, while they found relatively large gains. As opposed to the previous development accounting literature1 , we are not worried whether TFP or factors are more relevant in explaining output 1
See for instance, Mankiw, Romer and Weil (1992) Klenow and Rodriguez-Clare (1997), Prescott (1998) and Hall and Jones (1999).
2
di¤erences. Instead, we perform output decompositions from a distinctive perspective. The fact that countries with very di¤erent factor endowments to the rich economies are trading with them, and obtaining a productivity gain from that trade (that is not enjoyed by the richer nations, at least not in a similar scale), implies that TFP decompositions that ignore the e¤ects of this type of trade would yield a higher TFP residual for many nations; perhaps quite a bit higher, as suggested by the gains from trade numbers. We measure this di¤erence and show that for a group of poor economies the TFP constructed ignoring trade in general overestimate the true TFP. For instance, while in a closed economy model productivity would explain 32.4% of the income di¤erence of Mozambique with respect to the leading economies, once we correct for the gains from trade - which are huge in this case - the TFP residual explains only 18.2% of the income disparity. This article has four sessions in addition to this introduction. The next session presents the model used in our development decomposition exercises, while session three discusses data and calibration. Session four presents the main results and session …ve concludes.
2
The model
The model follows Ferreira and Trejos (2006). Time is discrete and unbounded. The world contains many countries, one of which is a large economy that has converged to its steady state, and that we will call the Center. Other countries are small relative to the Center, in the sense that they are price-takers at the Center´s autarkic price. Our representative country is populated by a continuum of identical, in…nitely-lived individuals. Three goods are produced: two non-storable, tradable intermediate products, A and B, and a a …nal good, Y , which can be consumed or invested, but that cannot be traded. There are also two factors of production in this economy: labor in e¢ cient units H and physical capital K. Labor and capital are used in producing A and B, and these in turn are used to produce Y . The endowment of labor, measured in e¢ ciency units, is given by: H = Lh = Le s ; where L is the number of workers, h represents e¢ ciency-units of labor per worker and s stands for schooling. The production functions of A and B are: 3
A = KAa HA1 B = KBa HB1
a b
:
Without loss of generality, A is labor-intensive: a < b . We use B as numeraire, with the prices of A and Y denoted p and . All markets are perfectly competitive; in the case of intermediate products, these are not domestic markets but rather a single world market, from which local Y producers can import intermediate products provided they pay an ad-valorem tari¤ . This captures all the (policy or non-policy induced) costs of bringing imported intermediate products into the local market. Because intermediate goods are tradable, the amounts of them that are used in the production of the …nal good (denoted by lowercase a and b) may di¤er from the amounts produced A and B. Total output of Y is given by: Y =
a b1 ;
(1)
where is total factor productivity. We derive the allocation of capital K and labor H among the production of A and B, the quantities a and b of intermediate goods used domestically, and the amount of …nal output Y that is produced. Because intermediate goods are assumed to be non-storable, and the …nal good is not tradable, this is a static problem, which yields an equilibrium mapping Y =
F (K; Hj ; p)
that relates …nal output with factor endowments. This mapping is not a production function, in the sense that it does not describe a technology: it describes an equilibrium relationship that takes into account the technologies for all the products, and the equilibrium e¤ects of trade in the intermediate inputs in the optimal choice for …nal good producers. The equilibrium solutions for fA; B; a; b; q; w; r; Ki ; Hi g must satisfy the following properties: 1. Producers of intermediate goods choose Ki ; Hi in order to maximize the period’s pro…ts: A
=
B
=
max qKAa HA1
a
KA ;HA
max KBb HB1
KB ;HB
4
b
wHA wHB
rKA rKB
2. Producers of …nal goods maximize pro…ts, taking domestic prices as given: a; b = arg max a b1 qa b a;b
3. Firms make zero pro…ts, a b1 = qa + b qA = wHA + rKA B = wHB + rKB markets clear, K = KA + K B H = HA + HB and agents neither borrow from nor lend to the world economy, pA + B = pa + b 4. Local prices of tradable goods satisfy an after-tari¤ law of one price: q=
p=(1 + ) p (1 + )
if if
a
B
Based on these requisites, one can derive the equilibrium relationship F . As is standard in the Hecksher-Ohlin model: 1. If K=H is much lower [much higher] than the world’s ratio (K=H) , only the intermediate good A [B] will be produced, as its production uses more intensively the relatively abundant labor [capital]. There are critical levels s1 < (K=H) and z2 > (K=H) such that if K=H s1 then the country only produces A, and if K=H z2 then the country only produces B: Then, Y is a Cobb-Douglas function of K and H, with capital share a [ b ]. Furthermore, the critical values s1 and z2 are sensitive to . In particular, with higher tari¤s the economy is less prone to specialize, so @s1 =@ < 0 [@z2 =@ > 0], with s1 ! 0 [z2 ! 1] as ! 1: 5
2. If K=H is very close to (K=H) a high enough tari¤ will make the economy not trade at all: There exist x1 and x2 , where s1 < x1 (K=H) and (K=H) x2 < z2 such that if (K=H) 2 (x1 ; x2 ) then there is no trade, so a = A, b = B: We have: @x1 =@ < 0 and @x2 =@ > 0. Also, x1 ! 0 and x2 ! 1 as ! 1, while x1 = x2 if = 0. 3. If K=H is neither too close nor too far from (K=H) , the economy will produce both intermediate goods, yet still trade. In those cases holds a result analogous to the Factor Price Equalization Theorem, which states that equilibrium marginal returns of capital and labor are not sensitive to small variations in the factor endowment. What that means is that …nal output Y is linear in K and H when K=H 2 [s1 ; x1 ] or when K=H 2 [x2 ; z2 ].
Hence, the equilibrium relationship from K and H to Y takes the form 8 1 a a if K=H < s1 > 1K H > > > < 2 K + 3 H if K=H 2 [s1 ; x1 ] 1 if K=H 2 [x1 ; x2 ] F (K; Hj ; p) = 4K H > > > 5 K + 6 H if K=H 2 [x2 ; z2 ] > : 1 b b if K=H > z ; 7K H 2
where the values i are functions of parameters, and are a¤ected by p and : For a closed economy it is the case that [x1 ; x2 ) = We present together as Group 1 countries with relatively high capitallabor ratios, for whom the potential increase in productivity from autarky to free trade is small (say, less than 10%). The tari¤s necessary, at those higher levels of k, to prevent trade altogether are not so large; notice that, for example, Mexico, Barbados and Cyprus have tari¤s under 20%, yet they miss all their gains from trade in 1985 according to our model.3 Nevertheless, some of these countries, with really low tari¤s, do specialize somewhat and reap bene…ts from trade, as in the cases of Ireland, Hong Kong or Poland. On the other extreme, the sixteen countries in Group 2 are very poor (the lowest k in the sample), so their gains from trade are very large (over 40%). In the case of Mozambique, for instance, which in 1985 had 1/72 of the US-EU capital-labor ratio, the productivity hike due to trade can be as much as 75%. Interestingly, most of these countries have high tari¤s; much higher than in Group 1. Yet, these poor nations get to enjoy most of their potential gains from trade. Why? Because their factor endowment is very di¤erent from that of the Center with which they trade, so the barriers to trade that would be necessary to drive them to autarky are just immense. Hence, even with a relatively high those countries still remain fully specialized in the production of A, the labor-intensive good, which is the e¢ cient allocation of capital and labor among the intermediate industries when you are that poor. With k = 0:04, as several of those countries have, a tari¤ in excess of 100% is necessary to induce the production of any amount of B, the capital-intensive good. Even with high barriers to trade,which induce a very ine¢ cient choice of a and b by …nal good producers, the allocation of K and H among the intermediate goods is not a¤ected in these cases. Almost all sub-Saharan countries in our sample are in that situation. Group 3 contains ten countries that are low-to-middle income, with sizeable potential gains from trade, and for whom barriers to trade imply a signi…cant loss. Notice for instance that Bangladesh, the country with the highest tari¤ in our sample, could get a 36% boost in productivity from free 3
For instance, with the capital/labor ratio of Mexico, a tari¤ of 16% is enough to rule out trade.
9
trade, yet wastes three quarters of that potential loss due to protectionism. India, Pakistan and Colombia are not very far behind. Finally, neither here nor there, the 26 nations in Group 4 have lower tari¤s, enjoy signi…cant bene…ts from international trade, yet also waste a non-negligible fraction of that potential.
4.1
Productivity decomposition
The fact that countries with very di¤erent factor endowments to the Center are trading with it, and obtaining a productivity gain from that trade (that is not enjoyed by the richer nations, at least not in a similar scale), implies that TFP decompositions that ignore the e¤ects of this type of trade would yield a higher TFP residual for many nations; perhaps quite a bit higher, as suggested by the numbers that we saw above. Now, we try to see the size of this di¤erence. The usual approach yields Y = b K H1
where b = - and is usually labeled TFP in level decomposition exercises - and is the increase in productivity due to trade, so =
F (K; Hj ) F (K; Hj = 1)
If an economy is in autarky, then = 1 = 1, and thus b = : However, if tari¤s are low enough, then > 1, and thus one may overestimate the true TFP; ; if one ignores the impact of international trade. Dividing by the number of workers, L, we get output per worker, or Y =b L
K H
H L
Now, if the country does trade, and thus reaps the gains from trade, we can rewrite the previous equation as Y = L
K H
H F (K; Hj ) : L F (K; Hj = 1)
We use this expression in a otherwise standard level decomposition exercise, in which income di¤erence with respect to Center is measured as 10
Yi =Li = YC =LC
Ki KC = Hi HC
Hi HC = Li LC
F (Ki ; Hi j = i ) F (Ki ; Hi j = 1)
i C
The two …rst components in the right hand side are standard in level decomposition exercises; …rst comes the e¤ect of di¤erent levels of capital per e¢ ciency unit of labor, and then the amount of e¢ ciency units of labor per worker. i.e., human capital. The product of the last two components is b , what usually appears for productivity, which we separate in Tables 2.1 to 2.4 between the trade-related part and the residual productivity, for our sample4 . Countries are arranged in the same groups as in Table 1. > As expected, the relatively well-o¤ countries in Group 1 (not to mention the even better-o¤ countries that were deleted from the sample) display very low levels of . Therefore, estimates of b obtained ignoring trade are very similar to those of . There are still some exceptions: very open economies where gains from trade are not negligible, like Panama, Hong Kong, Ireland or Trinidad. Similarly, for some of the countries in Group 3 it is also the case that b is very close to , not because there are few gains from trade to be obtained, but rather because the high implies low . In fact, the correlation between and b is high for the overall sample. Nevertheless, in the other two groups, productivity is signi…cantly overestimated by assessing b . In the very poor countries of Group 2 trade matters a lot. In the case of Mozambique and Rwanda, for instance, b is almost twice as large than ; because the measured gains from trade are huge. In no country in this group was found to be smaller than 40%; so the discrepancy between measured and trade-corrected TFP. Similarly, for those countries in Group 4 enough trade takes place, for the usual measure of TFP, b , to be quite an overestimation of . Guatemala and Jordan, for instance, two countries that usually surprise in standard TFP measures, resemble much more closely others with similar income once a correction for trade is made. What about the opposite question: Are the losses of productivity from imposing trade barriers signi…cant relative to overall TFP? We calculate 0 4
For simplicity we called the …rst component of the expression above k and the second h:The latter measure the impact of H=L after account for di¤erences in K=H:
11
and compare it to 1= 1, to verify if the productivity increase that could have been obtained by trade liberalization in 1985 was a large component of the overall productivity di¤erence for these countries. We know that, relative to their own output, gains from trade liberalization are large. Are they large relative to the distance that these countries must make up? The answer, not surprisingly, is that for most countries, TFP losses due to the undone trade liberalization are not large relative to their productivity backwardness. In Group 1, this is the case because the gains to be ripped from trade are not large. In Group 2, because most of those gains are enjoyed anyway. Nevertheless, it is the case that in Groups 3 and 4, additional trade liberalization could make up for a signi…cant fraction of the TFP di¤erentials: 10% of them, on average, for Group 3, around 20% for Bangladesh and Colombia, and at least 4% for 13 countries in total.
4.2
2000 data
Between 1985 and 2000 most countries in the world experienced aggressive trade liberalization. In our sample of developing countries, average tari¤ dropped from 27% to 13% in the period, while the coe¢ cient of variation the ratio between variance and mean - went from 10.1 to 3.0. Not surprisingly, the number of countries that wasted a signi…cant share of their potential gains from trade decreased. For instance, average nominal tari¤ in Bangladesh fell to 21.6% from 94.5% in the period. Hence, while in 1985 it lost more than three quarters of the potential gains from trade, in 2000 it reap them all. Nonetheless, there is still a group of middle-income countries - with relatively high capital-labor ratios - that lose a large part of their potential gains from trade (e.g., Brazil, Malaysia, Thailand, Hungary, etc.). As seen before, the potential increase in productivity from autarky to free trade is small in this case and the tari¤s necessary to prevent trade are not large. Some countries such as Mexico, Iran and Cyprus did not improve at all and still miss all bene…ts from trade. However, there are marked changes. Because tari¤s are now much lower, there is a group of countries - for instance, India and Pakistan, in addition to Bangladesh - that used to miss these gains from trade in the past but now bene…t from it. Although tari¤s are still relatively high - in all three cases well above the average 2000 tari¤ - they are now low enough so that, given their relative low k, these countries are not shut down from trade as in the past. 12
5
Conclusion
In this paper we presented evidence that gains from trade are very relevant. We used a very simple dynamic version of the Hecksher-Ohlin model so that the only reason countries trade are factor di¤erences. This contrasts with Eaton and Kurtum (2002) Ricardian trade model in which there is a continuum of goods and countries have di¤erential access to technology. In that model e¢ ciency varies across commodities and countries. As opposed to Rodriguez-Clare (2006), which builds on Eaton and Kurtun(2002), there is no di¤usion in our model. Nonetheless, the model is able to capture some important features of the international comerce - poor countries do trade because of factor di¤erences - and so our measured gains from trade may be be seen as a (large) lower bound of the gains from openness. As a matter of fact, they are very close to those Rodriguez-Clare (2006) obtained in the pure trade model. Moreover, the methodology we use does not capture the fact that barriers to trade do a¤ect investment decisions and so capital stocks, something we have shown in a previous paper (Ferreira and Trejos (2006)). In this sense, the current exercise is also limited as it takes stocks as given but does not consider that, if it were not for trade restrictions, they would be considerably larger. Of course, the fact that poor countries with high tari¤s are still enjoying most of the gains from trade could be reverted if we have more realistic data, and not only nominal tari¤s data. Anderson and van Wincoop (2004) survey the literature on trade costs and show that for the OECD economies they are quite large and well above nominal tari¤s. We wanted, however, to use homogeneous data and the only source we know for this is the WorldBank database on nominal tari¤. A natural extension of this work is to use (and construct in some cases) data of trade cost based on gravitation models for a large set of economies.
References [1] Anderson and van Wincoop (2004) "Trade Costs", Journal of Economic Literature, [2] Barro, R. and J. W. Lee, 2000. “International Data on Educational Attainment: Updates and Implications,”NBER Working Paper #7911. 13
[3] Corden, W. , 1971. "The e¤ects of trade on the rate of growth", in Bhagwati, Jones, Mundell e Vanek, Trade, Balance of Payments and Growth, (North-Holland), 117-143. [4] Eaton, J. and S. Kortum, 2002, "Technology, Geography, and Trade," Econometrica, 70. [5] Ferreira, P. C. and L. Rossi Jr, 2003. “New Evidence on Trade Liberalization and Productivity Growth,” International Economic Review 44, 1383-1407. [6] Ferreira, P.C. and A. Trejos , 2006. “On the Long-run E¤ects of Barriers to Trade.”International Economic Review, 47, 1319-1340.. [7] Hall,R. and C. Jones, 1999. “Why Do Some Countries Produce So Much More Output per Worker Than Others?,” Quarterly Journal of Economics, 114, 83-116. [8] Klenow, P. J. and A. Rodriguez-Clare, 1997. “The neoclassical revival in growth economics: has it gone too far?,” in Ben S. Bernanke and Julio J. Rotemberg, eds, NBER Macroeconomics Annual 1997 (Cambridge, MA: The MIT Press), 73-103. [9] Mankiw, N. G., Romer, D. and D.Weil., 1992. “A Contribution To The Empirics Of Economic Growth.” Quarterly Journal of Economics 107 (May): 407-437. [10] Prescott, E., 1998. “Needed: a Total Factor Productivity Theory,” International Economic Review, 39: 525-552. [11] Psacharopoulos, G., 1994. “Returns to Investment in Education: A Global Update,”World Development, 22(9): 1325-1343. [12] Rodriguez-Clare (2006) [13] Trejos, A., 1992 “On the Short-Run Dynamic E¤ects of Comparative Advantage Trade,”manuscript, University of Pennsylvania. [14] Ventura, J, 1997. “Growth and Interdependence”, Quarterly Journal of Economics, 112, 57-84 [15] World Bank(2005) 14
A.1 Gains from Trade, 1985 Group 1: Richer countries with small gains from trade Country K/H (%) Pot.Gains (%) Realized (%) Barbados Brazil Cyprus Ecuador Hong Kong Hungary Iran Ireland Mexico Panama Peru Poland South Africa Trindad and Tobago Tunisia Uruguay
0,60 0,57 0,67 0,38 0,49 0,54 0,58 0,65 0,59 0,37 0,51 0,48 0,57 0,38 0,46 0,50
17,30 47,00 12,80 34,30 24,00 20,70 8,70 19,70 12,80 37,60 13,40 21,20 17,20 25,90 36,30
15
2.,81 3,33 1,69 9,25 5,18 3,86 3,06 2,02 2,93 9,64 4,68 5,70 3,37 8,97 6,15 5,07
5,18 1,15 8,46 3,81 6,35 -
Group 2: Very poor countries with large gains from trade Country K/H (%) Pot.Gains (%) Realized (%) Benin Central African Republic China Congo Guinea Bisseau Haiti Lesotho Malawi Mali Mozambique Nepal Niger Rwanda Senegal Sierra Leone Togo
0,04 0,04 0,05 0,03 0,06 0,03 0,04 0,04 0,06 0,01 0,05 0,05 0,02 0,06 0,02 0,04
48,30 32,00 49,50 22,60 27,80 27,70 17,40 31,60 17,00 15,60 21,90 18,50 33,00 13,20 25,80 19,50
51,22 48,49 46,06 59,00 42,60 57,97 50,87 48,63 42,79 75,54 46,74 44,35 71,98 42,74 66,83 51,03
48,34 47,07 43,16 58,18 41,54 56,80 50,38 47,24 42,36 75,08 46,02 43,83 70,24 42,46 65,74 50,44
Group 3: Low-to-middle income countries that waste signi…cant gains due to tari¤s Country K/H (%) Pot.Gains (%) Realized (%) Bangladesh Chile Colombia Egypt Honduras India Korea Mauritius Pakistan Thailand
0,08 0,32 0,25 0,14 0,14 0,06 0,33 0,22 0,09 0,21
94,50 20,80 35,70 47,40 51,30 91,00 21,00 36,20 72,20 38,10
35,82 11,69 15,73 25,71 26,30 40,80 11,55 17,88 33,36 19,23
16
8,60 8,69 7,97 20,07 18,87 24,41 8,41 11,41 20,29 12,80
Group 4: Developing countries with somewhat freer trade policy Country K/H (%) Pot.Gains (%) Realized (%) Bolivia Botswana Cameron Costa Rica Dominican Republic El Salvador Fiji Ghana Guatemala Guyana Indonesia Jamaica Jordan Kenya Malaysia Nicaragua Papua New Guinea Paraguay Philippines Sri Lanka Syria Taiwan Tanzania Turkey Zambia Zimbabwe
0,18 0,21 0,09 0,28 0,21 0,17 0,32 0,07 0,22 0,33 0,09 0,34 0,28 0,07 0,31 0,23 0,19 0,21 0,18 0,08 0,26 0,25 0,07 0,23 0,17 0,35
17,60 30,00 30,20 19,50 27,80 20,00 12,40 26,30 19,40 18,70 30,20 17,90 15,20 39,90 14,00 22,10 14,20 11,00 29,20 36,20 14,80 23,30 28,50 27,90 29,90 9,40
21,71 18,96 34,45 14,07 19,26 22,01 11,67 38,12 18,33 11,49 34,67 10,83 13,77 39,48 12,15 17,29 21,02 18,98 21,53 36,03 15,51 15,79 39,00 17,48 22,47 10,61
17
21,31 16,45 33,29 12,64 17,98 21,50 11,23 37,19 17,86 9,17 33,51 8,52 13,49 37,54 11,50 16,71 20,75 18,82 20,54 34,42 15,23 13,95 37,91 14,84 21,43 10,45
A.2 Productivity Decomposition, 1985 Group 1: Richer countries with small gains from trade b Country y k h 1 Barbados Brazil Cyprus Ecuador Hong Kong Hungary Iran Ireland Mexico Panama Peru Poland South Africa Trindad & Tobago Tunisia Uruguay
49,0% 38,3% 48,7% 30,8% 55,8% 44,6% 36,1% 68,2% 55,2% 39,8% 32,9% 29,6% 55,6% 62,0% 36,3% 37,9%
84,2% 82,9% 87,6% 72,3% 79,0% 81,7% 83,6% 86,5% 83,9% 71,7% 80,0% 78,1% 82,8% 72,7% 77,3% 79,2%
18
68,9% 47,3% 71,0% 51,2% 70,1% 76,0% 47,3% 72,7% 55,8% 54,1% 57,2% 71,9% 55,6% 56,4% 43,3% 61,4%
71,2% 81,0% 68,6% 60,1% 79,6% 58,6% 76,3% 93,8% 98,9% 73,5% 57,6% 41,2% 100,0% 110,0% 83,7% 61,6%
0,0% 0,0% 0,0% 0,0% 5,2% 0,0% 0,0% 1,1% 0,0% 8,5% 0,0% 3,8% 0,0% 6,3% 0,0% 0,0%
71,2% 81,0% 68,6% 60,1% 75,7% 58,6% 76,3% 92,8% 98,9% 67,8% 57,6% 39,7% 100,0% 103,4% 83,7% 61,6%
Group 2: Very poor countries with large gains from trade b Country y k h 1 Benin Central Africa Repub China Congo Guinea Bisseau Haiti Lesotho Malawi Mali Mozambique Nepal Niger Rwanda Senegal Sierra Leone Togo
6,0% 7,4%
33,9% 35,4%
37,2% 43,9%
48,3% 47,1%
25,1% 29,9%
6,0% 36,8% 23,9% 25,1%
43,2%
17,5%
3,9% 2,7% 5,4% 6,5% 3,5% 6,5% 3,5% 5,7% 4,2% 5,1% 8,2% 7,6% 7,3%
58,2% 41,5% 56,8% 50,4% 47,2% 42,4% 75,1% 46,0% 43,8% 70,2% 42,5% 65,7% 50,4%
15,5% 11,2% 20,6% 21,5% 12,5% 26,6% 18,5% 23,1% 17,3% 23,9% 29,1% 34,6% 27,0%
30,2% 38,9% 30,7% 34,1% 35,3% 38,8% 24,0% 36,4% 37,8% 25,2% 38,8% 27,0% 34,0%
16,1% 16,9% 15,9% 16,9% 16,6% 20,0% 18,9% 17,1% 10,7% 16,9% 16,8% 12,4% 19,7% 13,3% 18,1%
24,5% 15,8% 32,3% 32,4% 18,4% 37,8% 32,4% 33,7% 24,9% 40,7% 41,5% 57,4% 40,5%
Group 3: Low-to-middle income countries that waste signi…cant gains due to tari¤s b Country y k h 1 Bangladesh Chile Colombia Egypt Honduras India Korea Mauritius Pakistan Thailand
9,7% 33,3% 32,2% 24,0% 18,0% 8,4% 38,3% 28,8% 11,5% 15,0%
43,6% 68,7% 63,2% 52,2% 51,6% 40,1% 68,9% 60,6% 45,5% 59,0%
21,9% 52,3% 39,9% 30,0% 31,1% 23,1% 62,8% 41,0% 22,9% 39,2%
19
44,2% 63,7% 80,9% 80,2% 58,0% 36,4% 61,0% 70,1% 50,4% 38,1%
8,6% 8,7% 8,0% 20,1% 18,9% 24,4% 8,4% 11,4% 20,3% 12,8%
40,7% 58,7% 74,9% 66,8% 48,8% 29,3% 56,3% 62,9% 41,9% 33,8%
Group 4: Developing countries with somewhat freer trade policy b Country y k h 1 Bolivia 19,3% 56,3% 36,1% 53,6% 21,3% 44,2% Botswana 28,4% 59,3% 34,2% 83,1% 16,4% 71,3% Cameroon Costa Rica Dominican Republic El Salvador Fiji Ghana Guatemala Guyama Indonesia Jamaica Jordan Kenya Malaysia Nicaragua Papua New Guinea Paraguay Philippines Sri Lanka Syria Taiwan Tanzania Turkey Zambia Zimbabwe
17,3% 31,7% 24,6% 26,0% 30,8% 7,6% 29,9% 14,9% 14,2% 16,7% 46,4% 6,9% 32,6% 23,4% 15,2% 31,1% 18,0% 12,9% 29,5% 41,5% 3,1% 26,7% 7,7% 17,4%
44,6% 65,4% 59,0% 55,9% 68,7% 41,9% 60,1% 69,0% 44,5% 69,9% 65,8% 41,0% 68,0% 61,3% 57,0% 59,3% 56,4% 43,4% 63,5% 63,2% 41,3% 61,1% 55,4% 70,3%
23,7% 44,3% 35,5% 32,2% 56,2% 24,1% 32,2% 47,1% 26,5% 43,3% 43,8% 23,0% 46,5% 34,7% 28,4% 39,4% 43,0% 30,7% 39,7% 52,1% 22,3% 35,5% 33,1% 37,3%
20
72,8% 71,5% 69,2% 80,7% 54,8% 31,3% 92,8% 31,7% 53,4% 38,5% 106,1% 30,1% 70,1% 67,4% 53,3% 78,8% 41,8% 42,0% 74,3% 79,7% 13,8% 75,3% 23,2% 46,6%
33,3% 12,6% 18,0% 21,5% 11,2% 37,2% 17,9% 9,2% 35,5% 8,5% 13,5% 37,5% 11,5% 16,7% 20,8% 18,8% 20,5% 34,4% 15,2% 13,9% 37,9% 14,8% 21,4% 10,4%
54,6% 63,4% 58,7% 66,5% 49,3% 22,8% 78,8% 29.1% 40,0% 35,5% 93,5% 21,9% 62,0% 57,8% 44,2% 66,3% 34,7% 31,3% 64,5% 69,9% 10,0% 65,6% 19,1% 42,2%
