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Free Trade Area of the Americas An Impact Assessment for Colombia Miles K. Light miles@mileslight.com Thomas F. Rutherford rutherford@colorado.edu April 14, 2003 Abstract This paper describes how entrance into the Free Trade of Americas Agreement may impact the Colombia s economy and public welfare. Our central tool for this analysis is a global Computable General Equilibrium (CGE) model of trade and production. We focus primarily upon the economic interaction between Colombia and key trading partners. These partners are: USA, European Union, and other Andean Pact countries. We find that Colombia does not stand to gain substantially from an FTAA-style agreement. Since Colombia already enjoys preferential access to key trading partners, the benefits from increased access to foreign markets is positive, but small. The authors would like to thank Gustavo Hernndez, Juan Pablo Herrera andömer Ozak from National Department of Planning for a number of helpful comments. This is a working paper for discussion, the views expressed in this paper are those of the authors and not necessarily those of the National Department of Planning.

Contents 1 Introduction 3 2 The GTAP Datasets 4 2.1 Elasticities......................................... 4 2.2 Distortions........................................ 6 2.3 Existing Trade Agreements............................... 7 3 The Global Trade Model 7 3.1 General Features..................................... 7 3.2 Formal Specification................................... 9 3.2.1 GTAP in Mathiesen s Equilibrium Format................... 9 3.2.2 Production.................................... 10 3.2.3 Public and Private Demand........................... 11 3.2.4 Bilateral Trade.................................. 12 3.2.5 Income and Expenditure............................. 13 3.2.6 Market Clearance................................. 14 3.2.7 Zero Profit.................................... 15 4 Policy Results 16 4.1 Trade Volumes...................................... 17 4.2 Other Scenarios...................................... 18 4.3 Factor Returns...................................... 18 4.4 Relative Prices and Competitiveness.......................... 19 4.5 Agriculture for Colombia in the FTAA......................... 21 4.6 The Role of the ATPA.................................. 21 5 Conclusions 22 A Regions and Sectoral Aggregation 27 B Descriptive Statistics for Colombia 29 B.1 Production and Trade.................................. 29 B.2 Tariff Rates and Revenues................................ 29 2

1 Introduction In the early nineties Colombia modified its tariff structure in a process called Apertura Econmica. Tariffs were reduced from an average rate of 43.0% in 1989 to 11.7% in 1992. Colombia also subscribed to some commercial agreements with the Andean Pact, Mexico and Chile. Non-tariff barriers were also lowered in some situations, like licensing for some importers. The agricultural sector remains the only sector still highly protected through band prices. The aim of this reform was to promote Colombian competitiveness and diversify Colombian exports. Non-traditional exports have consequently increased between 1992 and 2002, especially chemicals and machinery, which has encouraged industrial growth between 2000 and 2002. Colombian participation into the Andean market has also grown from 10.8% in 1991 to 19.5% 2002. Much of the remaining exports go to the USA as a principal comercial partner. This market represents 43.3% of Colombian exports. Various internal and external shocks have made it difficult to evaluate the net effect of the 1991 trade reforms. Changes to the US and Venezuelan economies, exchange-rate changes, and the preciptious decline in coffee prices give a common perception that trade liberalization is not welfare-improving. Further difficulties occured because domestic institutions (public and private), were not prepared for such dramatic commercial liberalization. Despite these difficulties, most Colombians recognize that FTAA accession could be an important source of growth for Colombia and also an important opportunity to diversify its exports to other markets in Latin America. Because there are numerous possible agreement types, both bilater and multilateral is important to evaluate several different alternatives during the FTAA negotiations. To do this, we use a model multi-regional computable general equilibrium model to evaluate the effects of entry into the FTAA. We use the GTAP dataset 1. The GTAP version 5 (GTAP5) database represents global production and trade for 65 country/regions, 56 commodities and 5 primary factors. The data characterize intermediate demand and bilateral trade in 1997, including tax rates on imports and exports. This paper consists of three sections following the introduction. Section 2 describes the GTAP dataset. This section provides information about the data organization of the GTAPinGAMS dataset. Section 3 presents the illustrative static models. It starts with a description of the GTAPinGAMS model using Mathiesen s format for the Arrow-Debreu model. This section provides notation and equations describing technology, preferences and equilibrium conditions. It also describes how the GTAPinGAMS model can be expressed in GAMS, either as an MPSGE model 1 The Global Trade Analysis Project (GTAP) is a research program initiated in 1992 to provide the economic research community with a global economic dataset for use in the quantitative analyses of international economic issues. The Project s objectives include the provision of a documented, publicly available, global, general equilibrium data base, and to conduct seminars on a regular basis to inform the research community about how to use the data in applied economic analysis. A list of applications based on the GTAP framework can be found at the GTAP home page: http://www.agecon.purdue.edu/gtap/.) For more details see Hertel [1997], McDougall [1998]. 3

or as a system of algebraic equations. This material provides a short but complete overview of how the technology and preferences are calibrated along with GAMS code which performs this task. In section 4 we shows the results for different kind of simulations to examine the impact of FTAA on Colombia. Finally, we write some final remarks. 2 The GTAP Datasets Domestic and international production and trade comes from the GTAP5 database. The Global Trade Analysis Project (GTAP), based at Purdue University in Indiana produces the best data for international trade analysis. Their database is a compilation of social accounts from separate countries as well as tabulated international trade flows from the United Nations. All of the data is combined and cleaned to provide a consistent measurement of production and trade worldwide. Except where we indicate otherwise, we use the GTAP5 database that is current as of November 2001. The 16 region version of the model retains all regions of the GTAP5 database that are directly relevant to our policy simulations. The full GTAP database contains 57 sectors, but we have aggregated to 29 sectors while retaining the sectors most important to Colombian trade policy. All GTAP datasets are defined in terms of three primary sets: r -the set of countries and regions, i -the set of sectors and produced commodities, and f -the set of primary factors. The GTAP data describe economic transactions in 1997. All parameters in GTAP are expressed in terms of values (i.e. price times quantity). Units of account in GTAP5, in its original GEMPACK representation, are millions of 1997$. But in our model the units are different by a factor of 10,000, then we measures transactions in tens of billions of 1997$ 2. Figure 1 presents the general GTAP database flows, which are explicitly represented in the dataset. Because the GTAP dataset must combine several disparate reports, some concessions and data manipulation are inevitable. To ensure that we have a good handshake with the 1997 Colombian national accounts (GTAP5 is based upon 1997 accounts), we produce several tables of production and trade for Colombia in Appendix B. In general, we find that after correcting the trade levies between Andean Pact countries, the data seem reasonably close to the 1997 social accounts produced by the Macroeconomics Division of the Colombian Ministry of Finance. Table 1 below compares broad economic indicators 3. 2.1 Elasticities We generally assume that the lower-level elasticity of substitution between imports from different regions is σ MM = 8, and that the higher-level elasticity between aggregate imports and domestic 2 Scaling units in this way assures better numerical precision in equilibrium calculations. 3 The GATP5 dataset for Colombia was built with preliminar national accounts while the social accounts from Ministry of Finance was constructed to the final national accounts 4

Figure 1: GTAP flows explicitly represented in the dataset Domestic Economy ty Production tx tf ti vafm tm vdpm vipm vdgm vigm tp vfm tg Int.Trade vxmd vtwr vst Other Region Private Household Government production is σ DM = 4. We refer to these values as our central elasticities. There are econometric studies, such as those of Reinert and Roland-Holst [1992], Shiells and Reinert [1993], and Hernndez [1998], that suggest values which are lower than these. However, Reidel [1988] and Athukorala and Reidel [1994] argue that when the model is properly specified the demand elasticities are not statistically different from infinity, and their point estimates are close to the central elasticity values we have chosen. To be clear, a value of σ MM = 8 means that if Colombia tried to raise its prices by 1% on world markets relative to an average of aggregate imports, Colombian imports would decline relative to aggregate imports by 8%. Given that there may be some economists who would prefer lower elasticity estimates, we also perform most of the important policy simulations with σ MM = 4 and σ DM = 2. We refer to these as our low elasticities. In our view, a high elasticity scenario, for an economy such as Colombia with little market power on world markets in most products, would be a specification with still less market power for exports, such as would occur with in the popular theoretical models of international trade where goods are homogeneous. The elasticity of transformation between exports and domestic production is assumed to be η = 2 for each sector. Elasticities of substitution between primary factors of production is unity. We assume fixed coefficients between all intermediates and value added. 5

Table 1: Economic Data for Colombia from Two 1997 Datasets Economic Data Comparison: GTAP5 SAM97 Domestic Output: 213,627 198,971 Exports: 21,178 16,804 Imports: 22,695 23,812 Import Tariff Revenues: 1,424 1,392 Output Tax Revenues: 2,333 2,378 Total Tax Revenues: 8,500 9,788 *Notes: 1) GTAP results are reported after re-computing the benchmark tariff rates for MERCOSUR and the Andean Pact. 2) Tax revenues are taxes on output only (i.e., doesn t include the corporate tax, which is some 5, 600 pesos. 2.2 Distortions All distortions are represented as ad-valorem price-wedges. Border protection estimates combine tariff protection and the tariff equivalents of non-tariff barriers. Outside of some trading agreements, as the Andean Pact, or tariffs preferences, such ATPA 4, we find that GTAP tariff levels reasonably reflect the average Colombian tariff rates for most GTAP product categories. In services, however, the GTAP dataset contains both some subsidies to imports in some services sectors and significant tariffs on other services imports. We judge neither to be reasonable, and impose zero tariffs on services in our tariff database for Brazil (and for other countries as well). In addition, contrary to the GTAP database, we impose zero tariffs on imports within the Andean Pact. After these corrections, the implied collected tariff in the corrected GTAP database is 9.2%, which is slightly larger than the actual collected tariff average in Colombia of about 8% for those sectors with import tariffs. 5 We employ the GTAP tariff rates for countries outside of Colombia as well. These tariff rates are trade weighted average tariffs, and consequently typically differ according to trading partner. That is, since there are thousands of tariff lines in the tariff schedules of most countries, literally hundreds of tariff lines must be mapped into a single sector in the GTAP database. Since the product mix of imports differs across countries, the trade weighted average tariff rate will differ according to the country of origin. Other distortions include factor taxes in production, value-added taxes, export subsidies (especially on agricultural exports from the EU, but to a limited extent elsewhere), and export taxes on textiles and apparel. 4 ATPA stands for Andean Trade Preference Act, an agreement by the US to lower trade barriers to Andean countries (Peru, Bolivia, Ecuador, and Colombia), in order to diversify the export base away from narco-trafficing. 5 Colombian tariffs are computed from the 1997 Colombian Social Accounts. 6

2.3 Existing Trade Agreements Several trade agreements were signed since 1997 which are not reflected in the data. In order to begin the modeling with a benchmark consistent with the most recent tax and tariff structure, we impose newer trade structures onto the data and re-compute the benchmark. For example, Brazilian accession to the MERCOSUR trading pact implies zero tariffs for partner countries. We set these particular import tariffs to zero then re-solve the model. This constitutes the new benchmark dataset. Table 2: Regional Trading Agreements in the Western Hemisphere since 1997 Agreement NAFTA MERCOSUR Multi-fiber Agreement Andean Pact ATPA Description North American Free Trade Agreement. Free access to most products between Canada, USA, and Mexico. Free Trade Zone for Brazil, Argentina and Uruguay. Special Tariff structure for textiles. Free Trade Zone for Colombia, Venezuela, Ecuador, Peru and Bolivia. Andean Trade Preference Act. Zero import tariffs for most goods exported from Andean countries to the United States. For Colombia, we impose a free-trading zone for the Andean Pact countries in addition to including other agreements outside of the region (e.g., NAFTA). Table 2 describes various agreements imposed on the GTAP dataset. The resulting import tariff structure for Colombia and its trading-partners is listed in Tables 16 and 17. The basic procedure behind the FTAA-Colombia accounting is described in the Figure 2. 3 The Global Trade Model 3.1 General Features The quantitative model developed to evaluate the trade policy options facing Colombia is multiregional and multi-sectoral. Table 12 lists the 16 regions included explicitly in the model, as well as Table 14 lists the 29 sectors included in each region. The model is quite detailed in the Americas: with 13 distinct countries or regions. Outside of the Americas, we have the European Union 15, Japan and Rest of the World. The general specification of this model follows earlier studies of trade agreements in South America, such as the model of trade policy options for Chile and Brazil 6. 6 See Harrison, Rutherford and Tarr [2001]. 7

Figure 2: Approach to Include Recent Trade Agreements 1997 GTAP Data GTAPinGAMS Model ------- NAFTA, MFA, Mercasur FTAA Model FTAA Scenario Analysis Results We adopt a multi-region model, rather than a small open economy model, since we need to consider the possible effects on Colombia of a reduction in Colombia s import tariffs for Andean Pact countries as well as Colombia. We also need to account for the market access effects on Colombian exports of a reduction of import tariffs by NAFTA regions with which Colombia agrees to a free trade agreement. Although the general theory of the welfare effects of preferential trading arrangements does allow for the impact of changes in partner country tariffs on the home countrys terms-of-trade, 7 some empirical approaches to evaluating preferential trading arrangements ignore them. 8 The GTAPinGAMS framework allows us to explicitly evaluate the importance to Colombia of improved market access to regions such as the EU and the Americas, as well as losses Colombia may suffer as partner countries raise export prices to Colombia. In addition to MERCOSUR and the Andean Pact, we assume that NAFTA operates as an effective free trade area with zero tariffs among the U.S. Canada and Mexico, but each of the three countries has its own external tariff. Although there are many other regional preferential trading arrangements in the Americas that are implemented at different levels of effectiveness, the GTAP dataset does not incorporate these preferential tariff rates. Further notes on the tariff rates in the GTAP5 dataset are presented in Appendix B, along with relevant statistics. 7 See Wooton [1986] and Harrison, Rutherford 8 An example is the approach adopted by Bond [1996]. He develops a simple general equilibrium specification of the effects on Chile of these preferential trading arrangements with an impressive level of detail with respect to tariff data. His results for Chile joining NAFTA, however differ significantly from Harrison et.al.[2002] because his CGE model does not incorporate the impact on Chile of access to NAFTA markets. 8

3.2 Formal Specification The general specification of the model follows earlier work on the Uruguay Round and on Chile. We concentrate here on the base model, which is static and assumes constant returns to scale (CRTS). Briefly, production entails the use of intermediate inputs and primary factors (Labor, Capital and Land). Primary factors are mobile across sectors within a region, but are internationally immobile. We assume Constant Elasticity of Substitution (CES) production functions for value added, and Leontief production functions for intermediates and the value added composite. Output is differentiated between domestic output and exports, but exports are not differentiated by country of destination. Each region has a single representative consumer who maximizes utility, as well as a single government agent. Demand is characterized by a nested CES utility function for the representative agent, which allows for multi-stage budgeting. Demand at the top level, for the composite Armington aggregate of each of the 29 goods in Table 12, is Cobb-Douglas. Consumers first choose how much of each Armington aggregate good to consume, such as wheat, subject to aggregate income and composite prices of the aggregate goods. The Armington aggregate good is in turn a CES composite of domestic production and aggregate imports. Consumers decide how much to spend on aggregate imports and the domestic good subject to the prior decision of how much income will be spent on this sector, and preferences for aggregate imports and domestic goods are represented by a CES utility function. Finally, consumers decide how to allocate expenditures across imports from the 15 other regions based on their CES utility function for imports from different regions and income allocated to consumption on imports from the previous higher level decision. 3.2.1 GTAP in Mathiesen s Equilibrium Format An Arrow-Debreu model concerns the interaction of consumers and producers in markets. Lars Mathiesen [1985] proposed a representation of this class of models in which two types of equations define an equilibrium: zero profit and market clearance. The corresponding variables defining an equilibrium are activity levels (for constant-returns-to-scale firms) and commodity prices. 9 Commodity markets merge primary endowments of households with producer outputs. In equilibrium the aggregate supply of each good must be at least as great as total intermediate and final demand. Initial endowments are exogenous. Producer supplies and demands are defined by producer activity levels and relative prices. Final demands are determined by market prices. Economists who have worked with conventional textbook equilibrium models can find Math- 9 Under a maintained assumption of perfect competition, Mathiesen may characterize technology as CRTS without loss of generality. Decreasing returns are accommodated through introduction of a specific factor, while increasing returns are inconsistent with the assumption of perfect competition. In this environment zero excess profit is consistent with free entry for atomistic firms producing an identical product. 9

iesen s framework to be somewhat opaque because many quantity variables are not explicitly specified in the model. Variables such as final demand by consumers, factor demands by producers and commodity supplies by producers, are defined implicitly in Mathiesen s model. For example, given equilibrium prices for primary factors, consumer incomes can be computed, and given income and goods prices, consumers demands can then be determined. The consumer demand functions are written down in order to define an equilibrium, but quantities demanded need not appear in the model as separate variables. The same is true of inputs or outputs from the production process: relative prices determine conditional demand, and conditional demand times the activity level represents market demand. Omitting decisions variables and suppressing definitional equations corresponding to intermediate and final demand provides significant computational advantages at the cost of a somewhat more complex model statement. The core model described here is a static, multi-regional model which tracks the production and distribution of goods in the global economy. In GTAP the world is divided into regions, and each region s final demand structure is portrayed by a representative agent who allocates expenditure across goods so as to maximize welfare, with fixed levels of investment and public output. Production incorporates intermediate inputs, and primary factors include skilled and unskilled labor, land, resources and physical capital. The dataset includes a full set of bilateral trade flows with associated transport costs, export taxes and tariffs. In the following section, before writing down the equilibrium conditions per se, production technology and producer choices are described. Then the structure of private and public final demand are outlined. Finally, the zero profit and market clearance equations are written down. 3.2.2 Production In the model there are two types of produced commodities, goods produced for domestic markets and goods produced for export. In the base these goods are assumed to be imperfect substitutes produced as joint products with a constant elasticity of transformation. Specifically, if D ir is domestic output and X ir is exports, then Y ir = [ α Y ird 1+1/η ir ] 1/(1+1/η) + βirx Y 1+1/η ir where Y ir is the activity level for good i in region r. Producers are competitive, implying that given a value of Y ir, supplies to the domestic and export markets are given by: 10 D ir = Y ir a D ir(p D ir, p X ir) and 10 For the sake of brevity, I present functional forms explicitly but represent unit demand and supply functions in reduced form, e.g. a D ir (pd ir, px ir ). 10

X ir = Y ir a X ir(p D ir, p X ir). Inputs to production include primary factors and intermediate inputs. Intermediate demands are proportional to the level of activity, so the total intermediate demand for good i in region r is: ID ir = j Y jr a ijr. In the core model we assume that all intermediate input coefficients (a ijr ) are fixed, unresponsive to price. 11 Following Armington [1969] intermediate demand is represented as a composite of imported and domestic goods as imperfect substitutes. Thus, we have: ID ir = [ αirdi I ρ ir + βi irmi ρ ] 1/ρ ir in which ID ir is domestic intermediate and MI ir is imported intermediate demand. A Cobb-Douglas production function relates activity level and factor inputs. Producers minimize unit cost given factor prices and applicable taxes. The factor demands solve: min f p F fr(1 + t F fir)f D fir s.t. ψ ir f F D θ fir fir = Y ir taking Y ir as given. Linear homogeneity of the production function implies that factor demands, F D fir, may be expressed as the product of an activity level and compensated demand function depending on factor prices (p F fr ) and factor taxes (tf fir ): F D fir = Y ir a F fir(p F r, t F ir) 3.2.3 Public and Private Demand Public sector output, G r, is assumed to represent a Cobb-Douglas aggregation of market commodities: G r = Γ r i GD θg ir ir 11 There is no reason that this functional form should be employed in every study. For example, when we use the GTAP dataset to study energy and environmental issues, it is important to account for the nature of substitution possibilities among energy carriers as well as between energy and non-energy inputs to production; so in those applications a nested CES function is employed in which energy trades off against value-added with a non-zero elasticity of substitution. 11

As is the case for intermediate demand, GD ir, an Armington aggregation of domestic (DG ir ) and imported inputs (MG ir ) defines public sector demand: GD ir = [ αirdg G ρ ir + βg irmg ρ ] 1/ρ ir Public sector output is exogenous, however the composition of public sector inputs responds to relative prices, gross of applicable tax, hence: GD ir = G r a G ir(p D ir, p M ir, t G ir) A representative agent determines final demand in each region. These consumers are endowed with primary factors, tax revenue, and an exogenously-specified net transfer from other regions. This income is allocated to investment, public demand and private demand. Investment and public output are exogenous while private demand is determined by utility maximizing behavior. The utility function is Cobb-Douglas: U r = i θ C ir log(cd ir ) As in the case of intermediate and public demand, an Armington aggregation of domestic and imported inputs defines each commodity, so CD ir = [ αirdc C ρ ir + βc irmc ρ ] 1/ρ ir Aggregate final demand (CD ir ) is then defined by regional expenditure and the unit price of aggregate of domestic and imported goods (p C ir ), gross of applicable tax (tc ir ): CD ir = θc ir M r p C ir (1 + tc ir ) Regional expenditure (M r ) includes factor income, net capital flows and tax revenue, net of the cost of investment and public expenditure. 3.2.4 Bilateral Trade There are three types of imports in the model: imports to intermediate demand (MI ir ), imports to public sector demand (MG ir ) and imports to final consumer demand (MC ir ). The maintained assumption is that while the aggregate import share may differ between these three functions, each of these shares have the same regional composition within the import aggregate. A CES aggregation across imports from different regions s forms the total import composite: 12

MI ir + MG ir + MC ir = [ s α M isrm ρ isr Two tax margins and a transportation cost apply on bilateral trade in the model. Real transport costs, T irs, are proportional to trade: ] 1/ρ T irs = τ irs M irs and these inputs are defined by a Cobb-Douglas aggregate of international transport inputs supplied by different countries: T irs = ψ T T D θt ir ir irs It is helpful to think of international transportation margins as transportation services which are provided by perfectly competitive producers from different regions with an Armginton aggregation across services from different countries and an elasticity of substitution equal to unity. The technology providing transportation services exhibits constant returns to scale, so we can specify a price p T representing the unit cost of transportation on all commodity trade flows. 12 Bilateral trade flows are determined by cost-minimizing choice, given the f ob export price from region r, p X ir, the export tax rate, tx ir, and the import tariff rate, tm ir.13 demand for bilateral imports as: i,r M irs = M is a M irs(p X ir, tx ir s, p T, t M ir s) We then may write the 3.2.5 Income and Expenditure Consumer expenditure for a representative agent are the sum of factor earnings and tax revenue, net the cost of investment, public sector output and net capital outflows: 12 There are some simplifications here. For example, the regional composition of transportation services is identical across all bilateral trade flows. Furthermore, while the dataset incorporates explicit trade and transport margins on international trade flows, wholesale and retail margins on domestic sales are ignored in the dataset, so there is some asymmetry in the database s price level. 13 The model formulation assumes that the export tax applies on the fob price (net of transport margins), while the import tariff applies on the cif price, gross of export tax and transport margin. 13

M r = f pf fr F fr! factor income + i ty ir (pd ir D ir + p X ir X ir)! indirect taxes + ij tid ijr pid ir Y jr a ijr! taxes on intermediate goods + fi tf fir pf fr F D fir! factor tax revenue + i tg ir pgd ir GD ir! public tax revenue + i tc ir pcd ir CD ir! consumption tax revenue + is tx irs px ir M irs! export tax revenue + is tm isr (px is M isr (1 + t X isr ) + pt T isr )! tariff revenue i pd ir I ir i pg ir (1 + tg ir ) GD ir p C n B r! investment demand! public sector demand! current account balance Capital flows in the base year are represented by B r in this expression, and in a counterfactual equilibrium these are held fixed and denominated in terms of the numeraire price index, the consumer price level in region n (USA). 3.2.6 Market Clearance Having defined technology, preferences and compensated demand functions, we now may turn to the market clearance conditions. Domestic Output Domestic output equals demand for intermediate inputs to production, public sector use, final consumer demand plus domestic investment: 14 D ir = DI ir +DG ir +DC ir +I ir = ID ir a D,I ir +GD ir a D,G ir +CD ir a D,C ir +I ir in which a D,I ir, ad,g ir, and a D,C ir represent the compensated demands for domestic inputs by submarket, each of which are functions of p D ir and pm ir. Imports Aggregate supply of imports, defined by the Armington aggregation across imports from different regions must equal aggregate import demand for intermediate, public and private consumption: M ir = MI ir +MG ir +MC ir = ID ir a M,I ir +GD ir a M,G ir +CD ir a M,C ir 14 Within the dataset investment inputs flow to the cgd sector, and demand for cgd sectoral output appears as the sole non-zero in the I ir vector for each region r. 14

in which a M,I ir, a M,G ir, and a M,C ir represent compensated demands for imported inputs by submarket, each functions of p D ir and pm ir. Exports Export supplies equals import demand across all trading partners plus demands for international transport: 15 X ir = s M irs +T D ir = s M isa M irs +T a T ir In the second equation a M irs represents the unit demand for region r output per unit of region s aggregate imports. Armington Aggregate Supply The model includes supply-demand conditions for the Armington composite goods entering intermediate demand, public and private demand, as has already been specified above in the equations defining ID ir, GD ir and CD ir. Primary Factors Primary factor (labor, capital, land, resource) endowment equals primary factor demand: F fr = i Y ir a F fir 3.2.7 Zero Profit Production Competitive producers operating constant-returns technology earn zero profit in equilibrium. For the GTAP producer, the value of output to the firm equals the value of sales in the domestic and export markets net of applicable indirect taxes. Costs of production include factor inputs (taxed at rate t F ) and intermediate inputs (taxed at rate t ID ): (p D ir a D ir + p X ir a X ir)(1 t Y ir) = f a F firp F fr(1 + t F fir) + j a jir p ID jr (1 + t ID jir) 15 When the elasticity of transformation between goods produced for the domestic and export markets is infinite, the market clearance conditions for D ir and X ir are merged, i.e. Y ir = DI ir + DG ir + DC ir + I ir + M irs + T D ir. s and prices p D ir and px ir are replaced throughout the model by a single price index, py ir. 15

Imports Zero profit conditions apply to trade activities as well as production. In equilibrium, the value of imports at the domestic cif price therefore equals the fob price gross of export tax, the transportation margin and the applicable tariff: p M ir = s a M [ irs p X is (1 + t X isr) + τ irs p T ] (1 + t M isr) Intermediate, Public and Private Demand Armington aggregation functions transform domestic and imported goods into composite goods for intermediate demand, public sector demand and private demand. Zero profit for these activities provide the following equilibrium identities: p I ir = c(p D ir, p M ir, α I ir, β I ir) p G ir = c(p D ir, p M ir, α G ir, β G ir) in which p C ir = c(p D ir, p M ir, α C ir, β C ir) c(p D, p M, α, β) min D,M p D D + p M M s.t. (αd ρ + βm ρ ) 1/ρ = 1 = ( α σ p 1 σ D + βσ p 1 σ M ) 1/1 σ is the unit cost function defined by the constant-elasticity-of-substitution aggregate of domestic and imported inputs. 4 Policy Results In the base scenario (FTAA), we consider full access to all markets in North and South America. In this scenario, all import tariffs and export taxes are completely eliminated. The central results are discussed, followed by results from some other plausible scenarios. We also conduct a sensitivity analysis to identify a range for potential impacts. Colombia does not realize substantial gains from the FTAA because the existing tariffs facing Colombia are already low. Because of this, the economic impact of the FTAA is similar to unilateral tariff reductions. In the base scenario, welfare increases by 0.26%, imports increase by 24% and exports rise 7.5%. The government stands to lose approximately $800 million USD in tariff revenues, most of which (about $500 million) comes from US imports. 16

4.1 Trade Volumes Imports increase more than exports because Colombia s import tariffs are high relative to the tradebarriers faced by Colombia in the US and Venezuela. Tables 3 and 4 show the largest changes to export volume and import volume for Colombia. Table 3: Largest Changes in Exports by Sector Export Prod US Value-added Shares % % % Tariff Labor Skilled Land Captl Other Crops 31 83 2 22 46 1 28 25 Sugar 11 18 1 53 37 8 0 55 Textiles 14 16 1 12 46 7 0 48 Wearing Apparel 52 18 1 15 54 8 0 39 Cereals and grains -19 0 0 1 47 0 28 25 Motor Vehicles and Parts -24 10 1 1 60 12 0 28 Table 4: Largest Changes in Imports by Sector Import Prod Import Value-added Shares % % % Tariff Labor Skilled Land Capital Resource Crops 23 11 4 7 42 3 7 43 5 Cereals and grains 24 48 0 10 47 0 28 25 0 V F 36 6 2 10 46 1 28 25 0 Oil seeds 35 22 0 9 47 0 28 25 0 Meats 31 2 7 11 47 3 19 31 0 Wearing Apparel 29 7 1 18 54 8 0 39 0 Leather, wood, and paper 19 14 3 9 44 7 0 49 0 Other Crops -19 6 2 8 46 1 28 25 0 Sugar -18 1 1 2 37 8 0 55 0 Exports rise the most for other crops (mostly Colombian coffee), sugar, textiles, and finished wearing apparel. Exports fall for cereal and grains, as well as motor vehicles and parts. Export sectors that gain face relatively high barriers to trade in the United States, while the losers faced low existing trade barriers. The fall in exports for these items occurs because trade is diverted away from Colombia by competing South American exporters. This is known in the literature as trade diversion. Colombian tariffs are high for agriculture. So it is not surprising that imports increase the 17

most for these sectors if all tariffs are eliminated. The import response is also higher because agricultural products are consumed directly by households, where the elasticity of substitution is unity. 16 Higher imports of agricultural products may hurt low-skilled wages. But this effect is balanced by the increase in agricultural exports, which also uses low-skilled labor. 4.2 Other Scenarios Besides our base scenario of free trade in the Americas, we also consider a number of plausible scenarios to help identify key linkages between the Colombian economy and the Western Hemisphere trading partners. We consider five alternative scenarios listed in Table 5. Table 5: Trading Scenarios Considered Parallell to the FTAA Scenario FTAA XUS FTAA XAG ATPA UNI FTASA Description FTAA scenario where the United States does not participate. FTAA scenario with no concessions on agricultural goods. US sets all import tariffs to zero for Colombia, Peru, and Bolivia. Unilateral 50% reduction of import tariffs for Colombia. Free trade in South America. Zero tariffs or export taxes for all South American regions. The role of the United States for Colombia is large, so we consider how the results change if the FTAA agreement does not include the US (FTAA XUS). Given that agricultural concessions are more difficult to negotiate, we consider an agreement without changes to agriculture (FTAA XAG). The role of the ATPA preferences between Colombia, Peru, Bolivia and the US is examined in the ATPA scenario. We consider what a unilateral 50% tariff reduction would do for Colombian trade. The unilateral scenario was included because the FTAA scenario is similar, since most of the impact comes from lowering Colombian tariffs rather than increased market access. Finally, we have a scenario with Free Trade across South America. 4.3 Factor Returns If agriculture is included in the FTAA, returns to unskilled labor and land increase somewhat as demand for those factors increases. Energy exports also increase the return to natural resources and physical capital. Oil and Coal exports increase by 1.4 and 2.0 percent, respectively, which increases the value of in-situ coal and oil resources by 2.6%. The return to factor inputs is listed 16 We assume the elasticity of substitution for intermediate inputs is zero for producers. This implies that lower import prices lowers production costs, but that firms cannot substitute to the low-cost good. The elasticity of substitution between domestic and imported goods, however is σ DM = 4, which implies that firms can substitute toward foreign goods if prices fall. 18

in Table 6. Table 6: Return to Production Factors in Colombia FTAA FTAA XUS FTAA XAG ATPA UNI FTASA Skilled Labor 0.92 0.35 0.65 0.00 0.82-0.01 Unskilled Labor 1.28 0.24 0.61 0.78 0.64 0.64 Capital 0.95 0.24 0.46 0.50 0.59 0.43 Land 0.90 0.21 0.58 0.51 0.65 0.45 Natural Resources 2.66 1.94 3.53-2.19 3.04-1.94 Factor returns can be traced directly to sectoral production and exports. Scenarios which increase exports for a sector, also increase the relative return to the factor used intensively in production. For example, the ATPA scenario invokes a fall in Coal and Oil exports 17, which in turn pushes natural resources returns downward by 2.2%. Table 7: Resource-Intensity and Exports for Oil and Coal Export Prod US Value-added Shares % % Tariff Labor Skilled Land Captl Resources Coal 91 1 0 16 1 0 43 40 Oil 52 2 0 10 2 0 49 38 Change in Exports by Scenario FTAA FTAA XUS FTAA XAG ATPA UNI FTASA Coal 2.00 1.21 4.28-5.03 3.95-4.93 Oil 1.37 1.87 3.36-3.93 2.46-3.59 4.4 Relative Prices and Competitiveness Table 8 shows the change in terms of trade for each sector. Two factors determine relative prices and the competitive position of sectors in a constant-returns model: the change in tariff rates, and the real exchange rate. We find that if agriculture is allowed into the FTAA, this sector increases substantially. Other sectors which had low trade barriers in the benchmark may suffer from worse terms of trade if the appreciation of the Colombian peso outweighs the tariff reductions. For example, several manufactures already enjoy low tariffs in the US. So in the ATPA scenario, exports fall. Table 8 shows the relative terms-of-trade for Colombian sectors. The terms-of-trade 17 These sectors export less because the exchange rate appreciation from other exports outweighs the small change in import tariffs. 19