The Free Trade Agreements and specialisation in the Canadian Manufacturing Sector

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31F0027MIE98001

Dragos Ifrim

This paper reflects the views of the author and does not necessarily reflect the opinions of Statistics Canada.

The past decade has witnessed an unprecedented move towards free trade. As expected, the Free Trade Agreement (FTA) of 1989 and the North American Free Trade Agreement (NAFTA) of 1994, influenced the Canadian economy: the volume of trade and investment has been growing rapidly – faster than that of world output – as producers take advantage of increasing trade and investment liberalisation and dramatic improvements in information and communication technology.

Do the free trade agreements lead to an increased specialisation in manufacturing? In this paper, a number of ways of looking at the specialisation in manufacturing are presented in an attempt to obtain evidence for a mechanism linking openness and specialisation.

Section I of the paper discusses the traditional approach to specialisation theory. Different models, which try to analyse the specialisation, are presented along with the conclusions. Section II presents the methodology used in this analysis along with the conclusions of the research. When considering the specialisation in manufacturing, it is important to have meaningful economic indicators to assess, monitor, and compare the evolution of specialisation in Canada. Ideally, such indicators should be computed not only for the period 1989 – 1996 but for the period preceding this one as well. However, given the constraints encountered in research, this paper examines the evolution of specialisation in the Canadian Manufacturing for the period 1989 – 1996. Section III presents a case study of the Canadian chemical sector.

I. Attempts to Explain the Economic Impact of the NAFTA and Some Classical Models Regarding the Free Trade Agreements

Presently, the analytical instrument of choice among economists is the "applied general equilibrium" (AGE) model. AGE models are large-scale computer models of the economy or, in this case, the three economies (Canada, United States, and Mexico). They are "equilibrium" models because they assume that, in whatever base year chosen, the economy being studied is in equilibrium. This means that if no policy change took place, and the economy was not disturbed by the external events, it would continue to produce the base year Gross Domestic Product (GDP) year after year. If a disturbance did occur, the economy eventually would establish a new equilibrium, and it would continue to replicate that equilibrium if no further disturbances took place. AGE models are "general equilibrium" models because they try to trace the effects of tariff and other policy changes all the way through the economy. The economy does not settle back into a new equilibrium until every last ripple has made its way through the economy and a "general" equilibrium is re-established. AGE models are "applied" because they attempt to mimic the behaviour of real-world economies.

Partly because the technology of these models has advanced rapidly since the mid-1980s and partly because the United States sees free trade with Mexico as being more consequential than free trade with Canada, there have been many more AGE studies of the NAFTA than there were of the FTA. On the other hand, because the United States focus is essentially southward, not all of these models have investigated the likely effects of the NAFTA on Canada. Three that have are reviewed in this paper.

Richard Harris of Simon Fraser University and David Cox of the University of Waterloo have extended their AGE model of Canada - United States trade to effects of granting FTA-style trading privileges to Mexico(1). The Harris-Cox model divides the economy into 19 industries and uses 1989 trade data to establish the three countries’ shares in the North American market, which are assumed to be "equilibrium" shares, in the sense described above. Harris and Cox use their model to examine a number of policy alternatives. To begin with, they look at the implications of completing the FTA tariff changes. Their model predicts that, once the reductions are fully in place, the new equilibrium that the economy will reach would see Canadian GDP 4.56 % higher than it otherwise would be. (The authors stress that no significance attaches to precise numbers, which represent "midpoints in a confidence interval.") The main reason Canadian GDP is higher is that Canadian labour productivity rises by 9.96 %. In the Harris-Cox model, this is mainly because United States goods no longer face tariffs at the Canadian border. This lowers their price in the Canadian market and forces an increase in Canadian productivity. The principal mechanism for achieving greater efficiency is that the number of firms in most Canadian industries falls, even as output and employment rises in many of these industries. According to this model, completing the FTA gives rise to a big increase (18.3 %) in Canada - United States trade flows. As might be expected, the FTA causes United States - Mexico trade to decline slightly – by 0.22 % – as a result of Canada’s acquiring privileged access to the United States market.

Using the completion of the FTA as a base case, Harris and Cox then simulate the effect of a genuine NAFTA in which all three countries reduce their tariffs on each other’s goods to zero. With a NAFTA, Canadian GDP rises by 0.12 %, although Canada - United States trade falls, but by only 0.09 %. As suggested earlier, these numbers are unrealistically precise. What is important is that they are very small, which suggests that, while the NAFTA may not bring a big gain for the Canadian economy, neither will it cause very large losses. In terms of the price competition from Mexico, assuming that Canadian firms have little independent influence over the prices they charge and must simply meet the Mexican prices, this model predicts that the labour productivity rises an extra 2.4 %, since "giving Mexico access to the Canadian market forces some additional rationalisation of Canadian industry that competition from the US alone does not achieve."(2)

Drusilla Brown of Tufts University, Allan Deardorff and Robert Stern of the University of Michigan have also produced a model of the North American free trade (the BDS model) that provides detailed results for Canada. Their model divides each of the three economies into 29 sectors and, as does the Harris-Cox model, uses 1989 as the base year for its data.

In terms of the results, this model predicts (again) that from the Canadian point of view there is not much to choose between a NAFTA and the FTA. The BDS model’s measure of overall Canadian economic well-being rises 0.6 % under the FTA and 0.7 % under a NAFTA. Thus, as in the Harris-Cox model, a NAFTA is marginally beneficial to Canada. Regarding Canadian wages, the model predicts that they will increase by a factor of 0.4 to 0.5 %. It may seem unusual that Canada’s entrance into a free trade agreement with Mexico, a low-wage country, could actually cause an increase in Canadian wages beyond what is produced by the FTA. The explanation is, however, that under the NAFTA, Mexico opens its market to Canadian trade more than Canada opens its market to Mexican trade, which already faces low barriers to entry to Canada. Thus the demand for the kinds of goods Canada produces could reasonably be expected to increase relatively more than the demand for the kinds of goods that Mexico produces.

The third AGE model presented here was built by three economists, David Roland-Holst, Kenneth A. Reinert, and Clinton R. Shiells, whose work was published by the United States International Trade Commission (ITC Group)(4). Their model divides each of the three countries into 26 sectors and is "calibrated" to 1988 data. The authors note that, contrary to many Canadian’s presumptions, Canadian economic activity is more concentrated in manufacturing than is the case in the United States, and that both Canadian primary goods production and manufacturing are more labour intensive than in the United States – though Canada’s service sector is somewhat less labour intensive than its United States counterpart.

Different versions of the ITC group’s model give significantly different results. In one version, it is assumed that a NAFTA eliminates all tariffs among the three countries but no nontariff barriers (NTBs), and that most industries do not exhibit increasing returns to scale – which means that there is no major advantage to specialisation: producing more does not necessarily mean producing more cheaply. Not surprisingly, in this model, a NAFTA does not do very much. Economic welfare increases by 0.07 % in the United States, by 0.11 % in Mexico, and by 0.24 % in Canada. Canada’s ranking as the biggest beneficiary of the NAFTA is surprising but this is at least partly because the basis of comparison is pre-FTA Canada. When both tariffs and all NTBs are removed, the effect is much more dramatic. Economic welfare rises by 1.67 % in the United States, by 2.28 % in Mexico, and by 4.87 % in Canada, almost 20 times the increase from tariffs alone. When increasing returns to scale are added to the model, the potential gain to all three industries increases even more – which only stands to reason since, if producing more of a good means a country can produce it more cheaply, there is greater opportunity for gains from international specialisation in production. However, it is important to show that NAFTA does not remove all nontariff barriers among its three member countries, so neither its benefits nor its costs are likely to be this great. At the same time, it is important to remember that the specialisation in production is a consequence of the increasing returns to scale. But can we assume this when we look at the overall Canadian manufacturing?

In a variety of theoretical models, we encounter an important mechanism linking openness (trade) to specialisation(5). In these models, openness to trade generally increases the size of markets for producers, thus leading to greater specialisation and a higher average scale of production.

In the present study, the statistical methodology is based on considering a number of possible relationships among data series. The data work done is intended to be explanatory in that I am looking for some simple statistical regularities rather than performing sophisticated hypothesis testing. Thus finding, for example, that there is no direct relationship between the evolution in the value of shipments and the percentage of goods in a certain year, is viewed more as indicating a direction for future research than as a confirmation of a particular theory. We should now turn to our data sources and the specific definitions of the variables.

The data used for this study come from two sources: Statistics Canada and the Canadian Chemical Producers’ Association. Data was collected from 1989 to 1996 for the entire manufacturing industry. Appendix A contains detailed accounting of which industries are part of the manufacturing sector. Four measures of specialisation within the manufacturing sector were constructed for the empirical analysis. For all of them, data come from the Statistics Canada’s Annual Survey of Manufactures (ASM). Data was collected on value of shipments and Standard Classification of Goods (SCG) code for each of the different manufacturing industries listed in Appendix A. Finally, for one of these measures, the Statistics Canada’s Specialisation Ratio for The Manufacturing Industries in Canada is used. The first two measures are adaptations of the Herfindahl Index.(6)

where i = 1,…,I represents different industries within the manufacturing sector, y_it represents the value of shipments of a particular industry i at time t, and Y_t refers to the total shipments of the manufacturing sector at time t.

where v_it is value-added in industry i at time t and V_t is the total value-added at time t.

The question is now: can we interpret the positive change in the mean of both our indices as representing an increase in the specialisation? In this case, one can say that the two specialisation indices do not provide significant explanatory power for the potential change in the specialisation for manufacturing as a whole. In fact, in a study where the relationship between specialisation and productivity growth is analysed, the authors find that the specialisation variables were not significantly correlated with the growth of gross-output in manufacturing per employee.(7)

The specialisation ratios are produced and published by Statistics Canada, for all the Canadian Manufacturing industries.(8) The primary products of a given Standard Industrial Classification (SIC) industry are the goods and/or services that result from the activities which define that industry.

In terms of our analysis, the primary product specialisation ratio gives us the extent to which the establishments classified to an industry, specialise in making the products primary to that industry. It is important to remember that the primary product specialisation ratios are not a measure of the degree to which establishments focus on one product. Rather, they show us the degree to which establishments focus on a whole group of products identified as being primary to that industry to which the establishment is classified. For this reason, we can consider that, when used with the above-mentioned indices and with the next technique (Lorenz Curves), the primary product specialisation ratios will supplement the measures of industrial concentration. The use of the primary product specialisation ratios when analysing the specialisation in manufacturing is justified by the fact that these two measures tend to move together in time.(10) Table 3. The Primary Product Specialisation Ratio for the Total Manufacturing Sector (1980 SIC), contains the specialisation ratios for the total manufacturing for the period 1989 to 1997.

As this table indicates, between 1989 and 1997 there has been an increase of 2 % in the primary product specialisation ratio. In other words, in 1989, 91 % of shipments were accounted for by defining activities of the manufacturing sector, while in 1997, 93 % of shipments were accounted for by the same activities.

It is, without any doubt, a very small change and we cannot derive a strong conclusion regarding the specialisation in manufacturing from these data.

The fourth measure used in attempting to measure the specialisation in manufacturing is an adaptation of the Lorenz Curve. It is an adaptation because the Lorenz Curve is an important tool in applied work on income distribution. A Lorenz Curve graphs the cumulative percentage of income against the cumulative percentage of families. The adapted Lorenz Curve graphs the cumulative percentage of goods in manufacturing against the cumulative percentage of the value of shipments. Under the assumption of specialisation, we expect to see an increase in the cumulative percentage of the value of shipments for the same cumulative percentage of goods.

Table 4. The Distribution of the Value of Shipments, Total Manufacturing 1989-1996 shows the distribution of the value of shipments. The table divides the goods in manufacturing into 11 groups, ranging from 1 % to 50 % and shows the percentages of shipments of these groups in different years, ranging from 1989 to 1996. More detailed information is provided in Appendix B.

Figure 1. Lorenz Curves - Manufacturing Sector (adapted) 1989-1996 shows the Lorenz Curves for value of shipments during the above-mentioned period. The curve is based on the distribution described above. As one can see from the table, in 1989, 5 % of the total products gives us just under 65 % of the value of shipments. The same percentage of the total products gives us an increase of approximately 0.7 % in the value of shipments in 1996. As in the previous attempts, we cannot identify a significant change in the data between 1989 and 1996. However, one important fact is revealed by the data: in every year (except the outlier year 1991), a low percentage of total products, gave us a fairly high percentage of the value of shipments. If we take the same example, we can see that for 5 % of the products we obtain more than 60 % of the value of shipments. At the same time, there is only a small increase in the value of shipments between 1989 and 1996 for the same percentage of total products. Thus, for the whole of the manufacturing sector, there is no change in efficiency; the evidence is too weak to draw conclusions about a change in specialisation after 1989. This is because, for an increase in efficiency, we would expect an increase in the value of shipments for the same number of products, or the same value of shipments for a smaller number of products. Because there is no major change in the efficiency, we can draw the conclusion that there is no change in the way in which we used our comparative advantage from 1989 to 1996. Had there been a change in the comparative advantage after 1989, we would have seen a change in the efficiency.

This shows that the Canadian manufacturing sector was already producing according to the comparative advantage before entering the FTA of 1989. Also, a high level of efficiency was already present in 1989. How else can we define an industry in which such a low percentage of products gives us such a high value of shipments? All the evidence shows that the resources such as labour, energy, and capital were directed towards production of goods in which we had a comparative advantage.

But because the economic theory suggests that the specialisation occurs according to the comparative advantage, once we have established that there is no change in the comparative advantage, it follows that we had specialisation in the Canadian manufacturing before 1989 and the situation, at the industry level, did not change much since then. This might sound provocative but in fact is not. The modern literature on international trade shows that, despite economic theory’s prediction that trading nations will further specialise in different industries, most industrialised countries - and thus Canada - are in fact active producers and exporters in most industries, being already specialised, at least at the level of aggregation required by this analysis. This will considerably limit the impact of free trade agreements on manufacturing specialisation. On the other hand, we can also see "substitution effects." The specialisation in different industries within the manufacturing sector will not advance equally, on all fronts, at once. At the same time, we should keep in mind that the methods used here, while useful, might be deficient in several ways. For example, one might say, that they simplify a great deal. The consequence is that the detail gets lost.

Many empirical studies have found a positive relationship between openness and specialisation in less developed countries, and economists have produced many explanations for this correlation. Quah and Rauch(11) show how increased openness to international trade can lead to increased specialisation in models of endogenous growth through learning by doing. These models imply that increased specialisation accelerates productivity growth by more fully realising dynamic economies of scale. The results of these models have particular relevance to the case of less developed countries. This is because openness promotes more rapid absorption of technological knowledge from the developed world.(12) Grossman and Helpman(13) built on Krueger(14) to suggest that openness reduces rent-seeking that diverts resources from activities that generate growth. Finally, it has been suggested that openness allows economies to take full advantage of dynamic economies of scale associated with learning by doing.(15) The final result of these studies is that – as a consequence of the free trade – specialisation is higher among the less developed countries who also have greater variability in the degree of specialisation than do the industrialised countries. At the same time, it is shown that specialisation within manufacturing sector could have a much greater impact on productivity growth in less developed countries than in countries with mature economies in which long run technological change, rather than learning by doing, is likely to be the primary source of productivity growth.

The empirical analysis mentioned above, shows strong evidence that specialisation in less developed countries is significantly and positively correlated with productivity growth, even when controlling for other variables commonly found in growth regressions. This is in direct contrast to the relationship in industrialised countries where specialisation seems to have no direct impact on productivity growth. Quah and Rauch(16) show how increased openness to international trade can lead to increased specialisation through learning by doing. These models imply that increased specialisation accelerates productivity growth by more fully realising dynamic economies of scale. There is also substantial evidence to support the hypothesis that specialisation in the manufacturing sector increases the rate of growth of manufacturing productivity in less developed countries. The relations openness to trade-specialisation and specialisation to productivity growth hold when looking at a less developed country, in which learning by doing is the primary source of growth. Canada is a mature economy in which the long-run technological change rather than learning by doing is likely to be the primary source of specialisation and productivity growth.

The analysis above is one possible way of looking at the relationship openness -specialisation. There are certainly other ways of looking at it and additional research is necessary to explain the openness - specialisation relationship. At the same time, the effects of the FTA/NAFTA should not be underestimated. These trade agreements have been a success for both Canada and its partners.(17) Some of the achievements are mentioned here. But not everything was changed by the FTA/NAFTA. One of the unchanged elements is the specialisation in manufacturing. Once again, we obtain this result when we look at the total manufacturing sector. As we shall see soon, the situation might change if we direct our attention at particular industries.

The chemical sector is one of Canada’s leading manufacturing sectors, employing 82,556 workers and producing shipments valued at $28.7 billion in 1996 (the fourth largest Canadian manufacturing sector, measured by value of shipments). This is why the chemical sector’s well being is a good indicator of the economy as a whole, and vice versa, because the majority of the other industries use chemicals as raw materials. The sector converts raw materials into many products that affect every aspect of our lives. The products of this sector include industrial inorganic and organic chemicals, plastics, chemical fertilisers and adhesives, to name only a few. Consumer-ready items produced by chemical companies include soaps and detergents, pharmaceuticals, paints and varnishes.

Table 5. Component Industries of Chemicals and Chemical Products, 1996 shows the major subgroups of the chemical sector in 1996 (latest year for which economic data are available). The largest industry is the plastic and synthetic resin industry, with a value of shipments of about $5.16 billion although this subgroup ranked the fourth in terms of employment. Producers of industrial organic chemicals account for about $5.12 billion in terms of the value of shipments, followed by pharmaceutical and medicine industry (almost $4.7 billion), and industrial inorganic chemical industries ($3 billion).

As it can be seen from Table 6. Evolution of Employment in the Chemical Sector, 1989-1996, the employment in the chemical sector declined from the 1989 level of 95,403 employees to 82,556, an eight year low. Aside from the growth in the mixed fertilisers, in plastic and synthetic resin, and pharmaceutical and medicine industry (one of the largest), most industries decreased their employment.

Stimulated by the Canada - United States Free Trade Agreement of 1989 and by NAFTA in 1994, the value of shipments rose 21% to $28.6 billion (See Figure 2. The Evolution of the Value of Shipments (Chemical Sector) 1989-1996). At the same time the chemical trade between Canada and the United States grew throughout the 1989-1996 period making Canada the number one supplier of United States chemical imports with 20.2%. However, over all this period, the United States had a favourable trade balance with Canada of US $3.1 billion, compared with 1.6 billions in 1990. In conclusion, between 1990 and 1996, the Canada’s deficit grew 94% and, if we try to look at the data after the NAFTA came into effect (1994), the Canada’s trade deficit climbed 12%.

The outlook for chemical products(18) continues positive for the near future as a result of expanding economic and industrial activity worldwide. Production of chemicals is expected to rise and likely growth areas include pharmaceuticals, organics, and plastic resins. In the foreign market, demand is expanding in virtually all major outlets, especially the United States and Mexico, Western Europe and Japan. The vibrant United States economy, and the strong US dollar relative to other currencies constitutes the determinants of the future growth in the Canadian export of chemical products.

As in many other industries, growth in production and profits has been achieved despite declining employment. Downsizing, outsourcing, and increased investment in technology will tend to suppress employment growth over the short term, although a sharp increase in economic growth is likely to reverse this trend.

The Canadian Chemicals Producer’s Association in its outlook for 1999 found chemical producers to be confident about business prospects, showing that the total sales value (domestic and export) of manufactured chemicals will equal the level of the previous year and the value of exports to the United States will register a 1.5% increase.

This being the case, we want to see now what is the result of applying the same methods (Herfindahl Index, specialisation ratios, and Lorenz Curves) in the case of Canadian chemical sector.

As it was shown above, both Herfindahl indices can take values between 0 and 1, with higher values corresponding to higher specialisation. When computed for the entire chemical sector, the mean of the Herfindahl indices varies between 0.10 (in 1989) and 0.12 (in 1995) for the value of shipments. The same small variation is present in the evolution of the mean for the value added: it varies from 0.11 in 1989 to 0.15 in 1995. While the trend is obvious, one should not forget that by looking at the mean, one cannot see the actual observations. These observations will either exceed or fall below the mid-point. This remark applies also to the first part of the paper, when the Herfindahl mean was used to derive conclusions regarding the manufacturing sector. Thus, we should try to analyse the Herfindahl indices in another context: at the industry level.

As this table shows, there is an increase in the specialisation indices for the following industries: the chemical fertilisers industry (SIC 3721) registers an increase from 0.2 to 0.31 (SHIPHERF) and from 0.22 to 0.35 (VALHERF); the mixed fertilisers industry’s (SIC 3722) indices increase from 0.04 to 0.10 (SHIPHERF) and from 0.08 to 0.15 (VALHERF); finally, the adhesives industry’s (SIC 3792) indices increase from 0.09 to 0.14 (SHIPHERF) and from 0.13 to 0.27 (VALHERF). It is interesting to note that, while the total number of workers has decreased for the whole chemical sector,(19) in two of these industries (mixed fertilisers and adhesives), the number of employed persons has increased. Also, for all of these industries, the value of shipments of goods of own manufacture has increased during the same period by a factor of almost 2. Hence we interpret the above information as a positive sign towards specialisation.

The primary product specialisation ratio gives us the extent to which the establishments classified to an industry specialise in making the products primary to that industry. While the primary product specialisation ratios are not a measure of the degree to which establishments focus on one product, their use when analysing the specialisation in the manufacturing is justified by the fact that these two indicators tend to move together in time. For the whole chemical sector, the primary product specialisation ratio has increased between 1989 and 1997 from 86% to 92%.(20) One of the biggest increases was realised in the industrial organic chemicals (SIC 3712), from 75% in 1989 to 90% in 1997. This is why we can conclude that during this period, there is a big increase in the degree to which establishments focus on a whole group of products identified as being primary to the industrial organic chemicals industry. The same increase can be identified in the chemical fertilisers industry (SIC 3721) where the specialisation ratio moves from 70% in 1989 to 96% in 1997. A very high degree of specialisation is encountered in the pharmaceutical and medicine industry (SIC 3741), where the specialisation ratio was 97% in 1997. Even in this high-specialised industry we can identify an increase: the ratio was 95% in 1989. Finally, another industry where we can find a significant increase in the primary product specialisation ratio is the soap and cleaning compounds industry (SIC 3761) where the increase is of 21%, reaching 90% in 1997.

As it was shown previously, a Lorenz Curve graphs the cumulative percentage of income against the cumulative percentage of families. The adapted Lorenz Curve graphs the cumulative percentage of goods in manufacturing against the cumulative percentage of the value of shipments. Under the assumption of specialisation, we expect to see an increase in the cumulative percentage of the value of shipments for the same cumulative percentage of goods. Table 8. The Distribution of the Value of Shipments in the Chemical Sector, 1989-1996, shows the distribution of the value of shipments. The table divides the goods in manufacturing into eleven groups, ranging from 1% to 50% and shows the percentages of shipments of these groups in different years, ranging from 1989 to 1996. The Lorenz Curve is based on the distribution described above. We are now able to see an increase in the cumulative percentage of the value of shipments for the same cumulative percentage of goods (Figure 3. Lorenz Curves (Chemical Sector) 1989-1996). If in 1989 10% of the total products gave us 58.28% of the value of shipments, in 1996 the same percentage of total products will give us now 62.75% of the value of shipments. This is an increase of more than 4% and is hard for this value to pass unnoticed. The same increase is present whether we look at the 15, 20, or other percent of the total products.

There is no doubt that the Free Trade Agreement of 1989 and the NAFTA of 1994 have contributed to an increase in the specialization of the Canadian chemical sector. The chemical sector can count many positive achievements in the past period including increased specialization. These free trade agreements have helped create a more integrated North American market, by reducing barriers and guaranteeing access to each country’s market. The United States is Canada’s largest trading partner and the trade between these countries has increased since 1994 at an annual rate of 10%. When we consider all these facts, it appears that the future evolution of the chemical products industry looks bright. The more active in export trade with the United States the Canadian chemical sector will be, the better performing it will become in the future.

References

1. See Harris, R and Cox D., "North American Free Trade and Its Implications for Canada: Results from a CGE model of North American Trade."

3. See Brown D.K., "An Overview of a North American Free Trade Agreement," in W.G.Watson, ed. A North American Free Trade Area.

4. See Roland-Holst, D. Reinert K.A., and Shiells C.R., "North American Trade Liberalization and the Role of Nontariff Barriers," in U.S.I.T.C., Economy-wide Modelling, pp. 532-580.

5. Another mechanism encountered in these studies is the one linking growth to trade.

6. The Herfindahl Index was employed in analysing the export concentration in Backus, Kehoe and Kehoe. The authors show that for some production functions, "…the appropriate specialisation index is based on other powers of the output shares y_it / Y_t , but we think that this simple measure captures the dispersion of production across industries." p.389.

7. See Weinhold. D. and Rauch J.E., p.14. Their conclusion is that "…the specialisation indices are not significant for the industrialised countries."

8. For a comprehensive presentation regarding the specialisation ratios see the "Specialization And Coverage Ratios For The Manufacturing Industries Of Canada", Statistics Canada, Manufacturing, Construction and Energy Division (MCED).

10. "As a practical matter, although high product specialization and high primary product specialization do not necessarily go together, they do tend to do so" in Crysdale John S., p. 5.

17. See THE NAFTA AT FIVE YEARS; A PARTENERSHIP AT WORK, Department of Foreign Affairs and International Trade (DFAIT), April 1999, and NAFTA WORKS – FIVE YEARS-THREE COUNTRIES, ONE PARTNERSHIP (DFAIT), and US REGIONAL TRADE WITH CANADA IN THE FIRST FIVE YEARS OF FREE TRADE by Sneddon, Little, J.

18. Information here is based on reports by the Canadian Chemicals Producer’s Association, as 1998 Year End Survey of Business Conditions in the Chemical Manufacturing Industry: (http://www.ccpa.ca/Reports)

19. See Table 6: The Herfindahl Index for Chemical Industry (Based on the Value of Shipments).

20. See the Manufacturing Industries in Canada: Primary Product Specialisation and Coverage Ratios, produced by Statistics Canada / MCED.

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Further information on Canadian manufacturing can be found in the publications Manufacturing Industries of Canada: National and Provincial Areas (Catalogue 31-203-XPB), available annually for $68 per issue in Canada and for $68 U.S. outside Canada, and Products Shipped by Canadian Manufacturers (Catalogue 31-211-XCB), available annually for $430 per issue in Canada and for $430 U.S. outside Canada. Order these products and other Statistics Canada publications by telephone, dial 1-800-267-6677, by fax: 1-800-889-9734, or by Internet.

For more information about manufacturing data or time-series, call the Disclosure and Dissemination Unit, Manufacturing, Construction and Energy Division at (613) 951-9497 or by Internet: manufact@statcan.gc.ca. For information from International Trade Division telephone 1-800-294-5583 or by Internet: trade@statcan.gc.ca.

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