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Foreign direct investment liberalization between Canada and the USA: a CGE investigation.


On January 1, 1989, Canada and the United States of America (USA) signed a free trade agreement (FTA), the Canadian-United States Free Trade Agreement (CUSFTA). Virtually all tariffs on Canada-USA trade in goods originating in the two countries were eliminated. CUSFTA was incorporated into the North American Free Trade Agreement (NAFTA) in January 1994, which extended the free trade arrangements to Mexico. Almost all tariffs on goods originating in Canada, USA, and Mexico will be eliminated by January 1, 2008. However, barriers to trade in services and foreign direct investment (FDI) remain, particularly in banking and other financial services, and control by a foreigner of a communication services company is precluded.

Fifteen years later and amidst continued controversy about the impacts and benefits for Canada from the two landmark agreements, debates about new initiatives to promote further regional economic integration continue apace. Fuelled by the September 11 terrorist attacks, scenarios are rampant ranging from a selective application of a custom union to particular industries to a full economic union that will include a common Canada-USA currency. In this context and without prejudging the outcome of the debate over deeper integration, which is largely a political decision, it is nevertheless useful to ground the discussion of the economic costs and benefits of further economic integration on as rigorous a basis as possible.

In this paper, we develop a computable general equilibrium (CGE) model to shed quantitative light on the implications of a scenario of deeper economic integration, where the barriers for foreign direct investment are preferentially eliminated. Our model distinguishes between the activities of domestic and foreign-owned firms at the microeconomic level, both in terms of demand and production characteristics, as inspired by similar approaches by Petri (1997) and Verikios and Zhang (2001). The paper proceeds as follows: the next section gives of a brief overview of the impact of Canada-USA CUSFTA and NAFTA to provide a context for the prospect of further economic integration and then we present the model structure of the CGE model; we continue by presenting and analyzing the results, before concluding.

Setting the Context: Assessing the Impact of CUSFTA and NAFTA

Empirical evidence is persuasive that CUSFTA/NAFTA increased trade. Clausing (2001) finds that 54% of the $42 billion increase in USA imports from Canada between 1989 and 1994 was due to the CUSFTA. Treffler (2004) finds that CUSFTA tariff reductions explained most of the increase in imports from the USA in industries whose tariff cuts exceeded 8%, in the 1988-1996 period, though industries with tariff cuts between 4% and 8% were not impacted by the tariff cuts. According to Romalis (2005), the CUSFTA increased bilateral trade by 5.35%. The impact of CUSFTA and NAFTA on foreign direct investment is more ambiguous both theoretically and in terms of empirical evidence. Economic theory of free trade predicts that within the free trade zone, trade creation will promote accompanying investment by firms from partner countries. However, as the need to circumvent tariffs dissipates with free trade, trade could displace inward foreign direct investment from partners. The net effect of these opposite outcomes is uncertain, particularly for Canada, who has relied extensively on USA FDI. Globerman and Shapiro (1999), using 1950-1995 time series data, conclude that CUSFTA and NAFTA increased in Canada's inward and, especially, outward FDI. Feinberg et al. (1998) find that as tariff rates fell, USA multinationals increased their capital and employment in Canada, thus contradicting the view that tariff liberalization would lead to an exit of US firms from Canada. Minas and Scholnick (1998) suggest trade creation and the FDI enhancing effects of the CUSFTA have prevailed over tariff jumping production.

Figure 1 shows that USA direct investment in Canada has modestly increased over the 1989-1999 period, rising from 65% in 1989 to 70% in 1999. A small number of large acquisitions by French companies in 2000 and 2001 resulted to a decline in the share of USA direct investment in Canada during that period. In recent years, US direct investment has stabilized at 64% of total inward Canadian FDI. Canada's direct investment in the USA has increased by a factor of 3 and its share of total US FDI has increased from 7.5% in 1990 to 9.5% in 1999, slightly declining in the 2000-2005 period (Fig. 2). Furthermore, Canada's direct investment in the USA has increased at the same pace as US imports from Canada (Fig. 3), indicating Canadian direct investment in the USA was not displaced by Canadian exports.

At the sector level, Table 1 demonstrates that the US direct investment in Wood & Paper, declined as a fraction of total US FDI in Canada. A similar trend was observed for the Energy & Metallic's sector up to 2000, but the trend reversed after 2000, mostly driven by acquisitions of Canadian companies operating in the oil patch. The share of technology intensive sectors such as Computer & Electronics, as well as Services & Retailing increased over the period 1989-2000. As initial pre-FTA tariffs were higher in the those sectors, these trends are consistent with the trade creation and FDI enhancing effects of a regional free trade agreement prevailing over tariff jumping production.

In the post-FTA period in the USA, we also witness a dramatic increase in the presence of Canadian direct investment in services and the technology intensive sectors of Machinery & Transportation Equipment, Chemicals, and Computer & Electronics (Table 2). The economic boom in the USA during the 1990s, especially in technology-intensive sectors, could partly explain these results.



Against this background, we now turn to a consideration of the remaining gains from deepening Canada's economic relationship with the USA by first describing our FDI-CGE model.

Description of the FDI-CGE Model

Our eight-sector CGE model features perfectly competitive markets and constant returns to scale. The regions of the model currently consist of Canada, the USA, and the Rest of the World (ROW). The model, however, departs from the traditional CGE approach by distinguishing the activities of domestic and foreign owned firms at the microeconomic level, in terms of both demand and production characteristics. Accordingly, firms are identified by their headquarters region. The firms headquartered in each region produce a good that is differentiated from goods produced by local firms. Moreover, as they locate plants around the world, each plant produces a commodity that is differentiated from the commodity produced in a plant in another host region. The resulting demand system shows that foreign commodities are available not just as imports, but also as local purchases from the subsidiaries of foreign firms. Also, domestic commodities can be bought not just from domestic firms operating at home, but also from their subsidiaries operating abroad. Thus, the resulting demand system offers a rich framework for analyzing competition among different production locations and between trade and foreign investment.


In each country, we assume a single representative household chooses consumption and wealth allocation to maximize its utility. Figure 4 illustrates the decision for consumption demand of our model with the presence of FDI. As we can see, the conventional Armington structure is now extended by an additional branch, where choices among production sources for each commodity are introduced. Under this framework, household demands would have a region-region-region-commodity dimension, which indicates respectively the origin of the firm, the location of the firm, from which region the demand is originating, and the type of commodity desired.

Another key feature of our FDI model is the determination of FDI investment or, more broadly, the regional allocation of capital. Investment permits the acquiring physical capital which subsequently generates rental returns accruing to domestic and foreign owners. The various types of capital assets are assumed less than perfect substitutes; hence, their corresponding rates of return may differ. The allocation of capital across regions is modeled in an optimizing framework that allocates capital to the highest return activities, but also takes into account investor preferences for a particular mix of available assets. As illustrated in Fig. 5, the capital allocation mechanism has three stages. First, the representative agent allocates its aggregate regional wealth across sectors as a function of the relative rate of return on capital invested in various sectors. Second, capital in each sector is allocated between domestic and an aggregation of foreign investment. Finally, foreign investment is allocated across specific foreign production locations.


We now turn to the specifications of the model. Sectors of activity are identified by s and t, with S representing the set of all industries so that s, t= 1, ... S. Regions are identified by indices i and j with R representing the set of all regions so that i, j = 1, ... , R. In a multi-country multi-sector framework, it is necessary to keep track of trade flows by their geographical and sector origin and destination. Thus, a subscript ijst indicates a flow originated in sector s of country i with industry t of country j as the recipient. The subscript v will also be used here to refer to the commodity associated with the producers from a specific region. Therefore vijst indicates a firm of origin v located in region i exporting in region j good s to industry t. Consequently, if v is different from i, the firm in question is foreign. To avoid unnecessary proliferation of symbols, occasionally we substitute a dot for the subscript on which aggregation has been performed; for instance, [] is an aggregate of [C.sub.jis] with respect to the first subscript. In each country, we assume a single representative household makes portfolio decisions to maximize his capital income and subsequently makes consumption choices to maximize its utility. We present first portfolio allocations and then consumption decisions. In what follows, we describe the portfolio and subsequently the consumption decision-making processes implied in our model.


Wealth Allocation

The representative agent living in region i is endowed with a stock of wealth [W.sub.i] that needs to be allocated across sectors and regions. To this end, he maximizes the capital return of his portfolio allocation across regions v and sectors s subject to a nested constant elasticity of transformation (CET) function. Following Verikios and Zhang (2000), we model barriers to FDI as tax on capital rentals. Since our model distinguishes between domestic and foreign firms and FDI is explicitly specified, taxes on capital restrict the movement of financial resources. The rends on capital are modeled as accruing to the region of ownership. Let [R.sub.i,v,s] be the return to wealth [Wivs.sub.i,v,s] invested in region v and sector s, and [[tau].sub.i,v,s] be the corresponding capital tax rate imposed by region v for foreign investment in sector s. Algebraically the optimization problem takes the form:

Max [summation over (v,s)] [R.sub.i,v,s] (1 - [[tau].sub.i,v,s]) [Wivs.sub.i,v,s] (1)

subject to the following set of embedded constraints that characterize the nested CET problem of wealth allocation:

[W.sub.i] = CET ([Ws.sub.i,s]; [[delta]s.sub.i,s], [[sigma].sup.W.sub.i,s]), (2)

[Ws.sub.i,s] = CET ([Wiis.sub.i,s], [Wfor.sub.i,s]; [[delta]d.sub.i,s], [[delta]f.sub.i,s], [[sigma].sup.W.sub.dom,for]) (3)

[Wfor.sub.i,s] = CET ([Wivs.sub.i,v,s]; [[delta].sub.i,v,s], [[sigma].sup.W.sub.i,v,s]) (4)

Here, the constant-elasticity-of-transformation functions are denoted by CET (.;[delta], [[sigma].sup.w]) parameterized by preference parameter [delta] and substitution elasticity [[sigma].sup.W]. Total wealth [W.sub.i], which is given, is a CET function of wealth allocated to sectors [Ws.sub.i,s], the latter being a CET function of domestic and foreign wealth (Wiis, Wfor), and finally foreign wealth is a CET function of specific foreign region v wealth (Wivs). Given a portfolio allocation, we can determine the revenue that belongs to the representative agent i, labeled [Rev.sub.i] which equals to:


where [wage.sub.i] is the wage rate in region i, [L.sup.i.sub.v,s] is labor supplied by the representative agent i to firm v of sector s. Notice that labor is assumed perfectly mobile within a region. The second term of the revenue equation represents the total return of capital allocation net of the capital taxes imposed by foreign regions. The last term confirms that tax revenue resulting from the capital tax imposed by region i on foreign investment, which is returned in a lump sum manner to the representative agent.

Consumption Decisions

Consumption decisions also follow a multi-stage procedure. In the first stage, each household allocates its consumption expenditure in a sector between an aggregate set of locally produced and imported goods. In the second stage, local good expenditures are allocated across the domestic and the foreign varieties. In the third stage, consumers allocate imports across goods produced by each trade partner, and then across commodities available in each region.

We postulate that the representative agent of a region i maximizes a Cobb-Douglas utility function:


subject to

Re [v.sub.i] = [summation over (s)] [Pc.sub.i,s][c.sub.i,s] and [summation over (s)] [[rho].sub.i,s] = 1 (7)






Here [] is consumption in country i of good s; [Pc.sub.i,s] is the price in country i of good s; [[rho].sub.i,s] is the Cobb-Douglas share parameter in country i of good s. Country i household preferences, with respect to domestic [c.sub.dom] and imported commodity [c.sub.for], are represented by a constant elasticity of substitution (CES) function with preference parameters [delta] and substitution elasticities [sigma]. Imported commodity [c.sub.for] is a CES function of consumption goods from all possible three regions [c.sub.jifor]. Finally, regional composite consumption good [c.sub.jrfor] is a CES function of all possible varieties [c.sub.vijs].


Each region is characterized by perfectly competitive firms. Demand for capital, labor and intermediate inputs by producers result from minimization of variable unit costs subject to a Cobb Douglas production function. Intermediate demand is also subject to a multi-stage procedure to determine the region and the variety of the commodity demand. A nested Leontief form is assumed for intermediate demands.

Aggregation and Equilibrium Conditions

There are two types of equilibrium conditions in the model. First, in each region, demand for primary factors must equal their supply. Second, total supply of each commodity (v,i,s) equals its demand in each market.


The model is calibrated to social accounting matrices constructed primarily from the Global Trade Analysis Project (GTAP) database version 6, reflecting trade flows in 2001. The GTAP data is further aggregated into three regions and eight sectors. Besides Canada and the USA, all other countries of the world are aggregated into a single region ROW. Value added by labor and capital in each sector, output, bilateral trade flows, intermediate inputs, consumption and investment by countries, and tariffs are derived from the GTAP 6 database.

The data source for capital taxes in the services sectors is Dee and Hanslow (2000). We assume that the capital tax on FDI is the difference between the tax imposed on foreign and domestic capital. Barriers to investment in the merchandise sectors were assumed to be half the size of the barriers to service sectors, as per convention (Petri 1997, Lee and van der Mensbrugghe 2001).

Unfortunately, there exists no unique data source of FDI data for Canada and USA. The Organization for Economic Co-operation and Development (OECD) International Direct Investment Statistics Yearbook and the United Nations World Investment Report provide either too aggregated data or data that is not available in the specification required for out model. This obliged us to recur to national data, which always causes disparity in terms of sector mapping and aggregation. Between the Canadian and US sources, Statistics Canada (1) and the Bureau of Economic Analysis, (2) respectively, we have narrowed the sector definitions and aggregation in order to ensure the right correspondence. For Canada, this information was provided by the Corporation Return Act; (3) because a parallel to the Corporation Return Act does not exist in the USA, we had to infer the figure by distributing total assets following fixed non-residential private assets (4) stocks by industry and then subtracting the inward FDI in the USA for every corresponding sector.

To calculate the ROW direct investment in Canada, we used Canadian data on the stock of FDI from which we subtracted the stock of US direct investment in Canada. A similar approach was used to calculate ROW direct investment in the USA. Following this methodology, we circumvent the reconciliation problems between direct investment abroad and inward FDI occurring when different statistical sources are used.

Once the database is ready, the model is first calibrated to social accounting matrices (SAMs) of the three regions for the year 2001. The next step is the determination of the share parameters in the supply side and demand side of the model such that the various supply and demand equations in the benchmark year are satisfied. Table 3 below reports the values of the CES and CET elasticities used in the model. (5)


The magnitude of the economic effects of investment liberalization will depend primarily on the investment and savings structure of the preferential partners, the significance of bilateral investment in the two countries, and the size of barriers to investment prior to investment liberalization. As commodities in our model are imperfect substitutes, we expect trade and FDI to be complementary. In other words, an increase in FDI from the USA to Canada would stimulate output, revenue and domestic demand in Canada, which in turn would increase the demand for goods produced in the USA. Consequently, US exports to Canada will be stimulated as well. It is interesting to consider how the complementary relationship between trade, FDI, and other mechanisms mentioned above interact at the macro and sector levels. The simulation conducted consists of eliminating the taxes between Canada and the USA (Table 4).

Macro-Economic Impacts

Despite the relative small size of barriers to FDI imposed by both the USA and Canada, there will be gains from preferential liberalization. Most of these gains accrue to Canada, as this country imposes larger restrictions than its southern partner. Bilateral investment liberalization provides US producers improved access to the Canadian market, while it also improves the rates of return of Canadian investment in the US market. Canada's real revenue increases both as result of an increase in domestic capacity, but also as a result of revenue from increased investments in the USA. The attraction of US direct investment in Canada, leads to an expansion in Canada's output by 0.09%, despite an increase in Canadian total imports, by 0.72% (see Table 5). The latter is mostly due to an increase in imports from USA, by 0.96%, which are boosted by positive terms of trade and real revenue effects that follows the FDI liberalization. Total investment in Canada increases, both in real, 0.4%, and nominal, 0.9%, terms. As Canadian domestic demand increases more than Canadian output, Canadian exports slightly decline. Overall, Canada's benefits from welfare gains amounts to 0.13% in terms of GDP, the equivalent of CDN$144 billion.

Sector Impacts

The elimination of taxes on capital generate significant inter-sector reallocation of resources as the tax structures differ not only across countries but also across sectors of economic activities. At the initial equilibrium, capital taxes are present in all sectors of the Canadian and US economies, but characterized by a larger magnitude in the Finance & Insurance and Services & Retailing sectors in both countries. Moreover, in general, the capital tax rate imposed on Canadian firms located in the USA is one third lower than the rate imposed on US firms operating in Canada. Table 6 shows that, in Canada, the largest increase in capital stock occurs in the Finance & insurance sector, leading to a corresponding boost in output. Output declines, however, in the sectors of Wood & Paper, Machinery & Transportation Equipment, and Computer & Electronics, as resources are reallocated to the higher yielding industries. Consequently, exports in these sectors slightly decrease.

In the case of the USA, the impacts are in general positive, but too small to make a significant difference. The only sector slightly negatively impacted is Computers & Electronics, whose total output and exports decrease, by 0.059% and 0.01% respectively.

Not surprisingly, the elimination of capital taxes stimulates foreign direct investment. In fact, even though the initial capital tax rates are relatively low, the sector impacts are sometimes substantial. For instance, Table 7 indicates that US direct investment in Canada in the Finance & Insurance and the Services & Retailing sectors increases by 7.51% and 8.26% respectively, despite the fact that the initial Canadian capital tax rate imposed on US investment in these two sectors was only 5.6%. Similarly, Canadian direct investment in the USA in these two sectors increases by more than 5% even though the US tax rate is 3.8% at the initial equilibrium. Although there is an inflow of capital in the other sectors as well, output produced by foreign affiliates in the sectors of Wood & Paper, Machinery & Transportation, and Computers & Electronics, decreases. Furthermore, exports of these sectors to USA also decrease, reflecting a re-allocation of resources to the sectors with higher yields to capital.


Government policy, global events, geographic location, and history, among others factors, have shaped the industrial structure, patterns of trade, and foreign direct investment of Canada. This paper suggests that government policies intended to further promote economic integration between the two countries, by eliminating remaining barriers to foreign direct investment, could be beneficial to Canada by attracting more US direct investment, boosting Canada's productive capacity, and improving the welfare of its consumers. The service sectors, particularly the sector of Finance & Insurance, benefit the most from an increase in inward FDI and a boost in its output. However, given the structure of Canada's industry following recent global events, it is unlikely that further liberalization will reverse the current trend of reallocation of resources from certain manufacturing, high technology sectors towards natural resource based sectors, in particular the sector of Energy & Metallic Minerals.

The basis of our analysis is a CGE model that explicitly models FDI, subject to limitations in the availability of data. The complexities of integrating an intertemporal optimization mechanism, more appropriate in the case of investment, remain for future work. However, it would be realistic to assume that in a dynamic context, benefits from preferential liberalization would be larger.

We thank Li Xiu Jun for valuable research assistance. Please note that this paper does not necessarily reflect the views of the Government of Canada. All errors belong to the authors.


Clausing, K. (2001). Trade creation and trade diversion in the Canada-United states free trade agreement. Canadian Journal of Economics, 34(3), 667-696.

Dee, P., & Hanslow, K. (2000). Multilateral liberalization of services trade. Staff Research Paper, Productivity Commission, Canberra.

Feinberg, S. E., Keane, M. P., & Bognanno, M. F. (1998). Trade liberalization and delocation: New evidence from firm-level panel data. Canadian Journal of Economics, 31(4), 749-777.

Globerman, S., & Shapiro, D. (1999). The impact of government policies on foreign direct investment: The Canadian experience. Journal of International Business Studies, 30(3), 513-552.

Lee, H., & van der Mensbrugghe, D. (2001). A general equilibrium analysis of the interplay between foreign direct investment and trade adjustments. Kobe U. Research Institute for Economics & Business Admin., Discussion Paper No. 119.

Mirus, R., & Scholnick, B. (1998). US foreign direct investment into Canada after the free trade agreement. Joint Series of Competitiveness, 15.

Petri, P. A. (1997). Foreign direct investment in a general computable equilibrium framework. Paper presented at the conference. Making APEC Work: Economic Challenges and Policy Alternatives, 1314 March, Keio University, Tokyo.

Romalis, J. (2005). NAFTA's and CUSFTA's Impact on International Trade. NBER Working Paper 11059.

Trefler, D. (2004). The long and short of the Canadian US free trade agreement. American Economics Review, 94, 870-895 (September).

Verikios, G., & Zhang, X.-G. (2000). Sectoral impacts of liberalizing trade in services. Paper presented to the Third Annual Conference on Global Economic Analysis, Melbourne, Australia, June 27-30.

Verikios, G., & Zhang, X.-G. (2001). The FTAP2 model: Theory and DATA. Research Memorandum, Cat NO. MC61.

M. Merette ([mail])

Department of Economics, University of Ottawa, Ottawa, Canada


E. Papadaki

Canada Border Services Agency, Ottawa, Canada


J. Hernandez

Statistics Canada, Ottawa, Canada


Y. Lan

Human Resources and Skills Development, Ottawa, Canada


(1) See tables in CANSIM 376-0053 and tables CDIA 2-Digit SIC-C and FDIC 2-Digit SIC-C.

(2) Go to to get the United States DIA or FDI.

(3) CANSIM table 179-0004.

(4) Table 3.1ES. Current-Cost Net Stock of Private Fixed Assets by Industry, 1987-2003. BEA.

(5) These values were taken from GTAP data and Verikios and Zhang (2001).
Table 1 Industry distribution of USA direct investment in Canada, in

Sectors FDI Model                      1989   2000   2005

Wood & Paper                            6.4    4.9    3.1
Energy & Metallic                      22.9   16.9   28.3
Machinery & Transportation Equipment   17.0   17.0   14.5
Chemicals                               7.5    6.6     Na
Computers & Electronics                 4.6    9.0     Na
Finance & Insurance                    13.3   17.7   16.7
Services & Retailing                    5.4    9.1   12.0
All other industries                   20.8   17.7   25.3

Source: Statistics Canada. CANSIM 11. Table 376-0043. Percentages
do not sum to 100 due to suppressed information

Table 2 Industry distribution of USA direct investment in USA, in

Sectors FDI Model                      1989   2000   2005

Wood & Paper                            3.7    2.4    3.4
Energy & Metallic                      19.2   16.3   20.0
Machinery & Transportation Equipment    1.9    3.3    3.6
Chemicals                               1.7    2.9     Na
Computers & Electronics                 6.0   17.4     Na
Finance & Insurance                    22.5   21.9   39.4
Services & Retailing                    1.3    1.8   17.3
All other industries                   23.3   15.0   16.3

Source: Statistics Canada. CANSIM 11. Table 376-0043. Percentages do
not sum to 100 due to suppressed information

Table 3 Value of elasticity of substitution

CES [sigma]                     Wood &      Energy &   Machinery &
                                 Paper      Metallic     Transport

[[sigma].sub.i,s.sup.C]           3.10          3.04          3.64
[[sigma].sub.j,i,s.sup.C]         6.32          6.31          7.40
[[sigma].sub.v,i,s.sup.C]         7.58          7.57          8.88

CES [sigma]                  Chemicals   Computers &     Finance &
                                         Electronics     Insurance

[[sigma].sub.i,s.sup.C]           3.30          4.40          1.90
[[sigma].sub.j,i,s.sup.C]         6.60          8.80          3.80
[[sigma].sub.v,i,s.sup.C]         7.92         10.56          4.56

CES [sigma]                 Services &     All Other
                             Retailing    Industries

[[sigma].sub.i,s.sup.C]           1.96          2.47
[[sigma].sub.j,i,s.sup.C]         3.86          7.57
[[sigma].sub.v,i,s.sup.C]         4.63          9.09

CES [sigma]                                 CET [sigma]

[[sigma].sub.i,s.sup.C]         [[sigma].sub.i,s.sup.W]   1.2
[[sigma].sub.j,i,s.sup.C]   [[sigma].sub.dom,for.sup.W]   1.3
[[sigma].sub.v,i,s.sup.C]     [[sigma].sub.i,v,s.sup.W]   1.4

Source: GTAP 6 database and Verikios and Zhang (2001)

Table 4 Capital tax rates, in percentage

                             Canada   USA on   Canada
                             on USA   Canada   on USA

Wood & Paper                   2.79     1.92     2.79
Energy & Metallic              2.79     1.92     2.79
Machinery & Transportation     2.79     1.92     2.79
  Chemicals                    2.79     1.92     2.79
  Computers & Electronics      2.79     1.92     2.79
  Finance & Insurance          5.58     3.83     5.58
  Services & Retailing         5.58     3.83     5.58
  All other industries         2.79     1.92     2.79

                             USA on   ROW on   ROW on
                             ROW      Canada   USA

Wood & Paper                   1.92    23.95    23.95
Energy & Metallic              1.92    23.95    23.95
Machinery & Transportation     1.92    23.95    23.95
  Chemicals                    1.92    23.95    23.95
  Computers & Electronics      1.92    23.95    23.95
  Finance & Insurance          3.83    47.90    47.90
  Services & Retailing         3.83    47.90    47.90
  All other industries         1.92    23.95    23.95

Source: Dee and Hanslow (2000), authors' calculation

Table 5 Aggregate results, in percentage

Economic Indicator    Canada   USA      ROW

Exports (total)        -0.22    0.048    0.157
  Exports to Canada             0.963    0.358
  Exports to USA      -0.116             0.142
Imports (total)        0.721    0.102   -0.155
Terms of trade         0.079    0.016   -0.043
Output                 0.090    0.008   -0.002
Domestic demand        0.166    0.007   -0.007
Real revenue           0.079    0.016   -0.043
Investment             0.397    0.019   -0.001
Investment in value    0.937    0.102   -0.054
Welfare                0.126   -0.002   -0.003

Source: Authors' calculation

Table 6 Sectoral results, in percentage

                                         Total     Total     Domestic
                                         Exports   Imports   Demand
  Wood & Paper                             -0.27      0.57       0.03
  Energy & Metallic                         0.39      0.61       0.39
  Machinery & Transportation Equipment     -0.57      0.95       0.67
  Chemicals                                 0.20      0.34       0.18
  Computer & Electronics                   -0.57      0.59       0.02
  Finance & Insurance                       0.27      0.44       0.55
  Services & Retailing                      0.38      0.67       0.09
  All other industries                      0.11      0.53       0.18
  Wood & Paper                             0.236    -0.021      0.011
  Energy & Metallic                        0.147     0.122      0.034
  Machinery & Transportation Equipment     0.043     0.094      0.011
  Chemicals                                0.031     0.080     -0.005
  Computer & Electronics                  -0.059     0.152      0.012
  Finance & Insurance                      0.046     0.077      0.027
  Services & Retailing                     0.103     0.108      0.004
  All other industries                     0.056     0.103      0.003

                                         Output    Capital

  Wood & Paper                             -0.12      0.05
  Energy & Metallic                         0.39      0.46
  Machinery & Transportation Equipment     -0.27      0.40
  Chemicals                                 0.19      0.18
  Computer & Electronics                   -0.34      0.53
  Finance & Insurance                       0.52      0.82
  Services & Retailing                      0.11      0.19
  All other industries                      0.18      0.04
  Wood & Paper                             0.022     0.025
  Energy & Metallic                        0.041     0.083
  Machinery & Transportation Equipment     0.016     0.040
  Chemicals                                0.000     0.018
  Computer & Electronics                   -0.01     0.025
  Finance & Insurance                      0.027    -0.002
  Services & Retailing                     0.006     0.006
  All other industries                     0.004     0.019

Source: Authors' calculation

Table 7 Impact on trade and FDI with the United States, in percentage

                            Canada's     Capital      Output
                            Exports      Located in   Produce in
                            to USA       Canada by    Canada by
                                         USA          USA
                                         Affiliates   Affiliates

Wood & Paper                     -0.15         2.83        -0.14
Energy & Metallic                 0.26         3.28         0.99
Machinery &                      -0.42         2.64        -0.48
Chemicals                         0.21         3.12         0.54
Computer & Electronics a         -0.39         2.70        -0.34
Finance & Insurance               1.13         7.51         3.38
Services & Retailing              1.86         8.26         5.15
All other industries              0.38         3.45         1.08

                            USA's        Capital      Output
                            Exports to   Located      produce
                            Canada       in USA by    in USA by
                                         Canadian     Canadian
                                         Affiliates   Affiliates

Wood & Paper                      0.58         2.17         0.77
Energy & Metallic                 0.60         2.48         1.47
Machinery &                       0.98         2.37         1.03
Chemicals                         0.33         2.03         0.53
Computer & Electronics a          0.80         2.32         1.06
Finance & Insurance               0.72         5.31         3.28
Services & Retailing              2.00         5.74         4.39
All other industries              0.80         2.39         1.21

Source: Authors' calculation
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Title Annotation:computable general equilibrium
Author:Merette, Marcel; Papadaki, Evangelia; Hernandez, Jorge; Lan, Yu
Publication:Atlantic Economic Journal
Article Type:Report
Geographic Code:1USA
Date:Jun 1, 2008
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