Inter-Industrial Linkage Effects of Non-Traditional
Natural Resource-Based Export Sectors in Chile
February 28, 2013


Yoshimichi MURAKAMI

Abstract
Producing three input-output tables from 1986, 1996, and 2003, this study analyzes whether
non-traditional natural resource-based export sectors in Chile, such as fish, fruit, and forestry
products, produced different domestic inter-industrial linkage effects, compared with the traditional
mining export sector. The findings show that the backward linkage effects of non-traditional natural
resource-based export sectors increased, with the trend being especially evident in the wood andwood products, and the fish products sectors. However, the backward linkage effects of the copper
sector did not increase and continued to be stably low. On the other hand, backward linkage effects
of manufacturing sectors did not increase, contradicting the general assumption of the transformationof industrial structure when accompanied by economic development. Moreover, this study finds thatthe ratio of domestic intermediate inputs, like prepared animal feeds, substantially increased in thefish products sector. These findings corroborate the fact that salmon aquaculture has developed
backward linkages with domestic suppliers.

JEL classification: D57, L16, and O13
Key words: Chile, Backward linkage effects, Non-traditional natural resource-based exports,
Transformation of industrial structure

1. Introduction
Chile presents a very interesting study of economic development in Latin American and Caribbean
countries (henceforth, LACs), in that it has recorded the most stable economic growth among the
LACs since the mid-1980s in spite of having an economic structure that is strongly dependent onThis paper is a revised version of Murakami (2010), originally written in Japanese.
The author is a former professional intern at the International Trade and Integration Division of theUnited Nations Economic Commission for Latin America and the Caribbean (ECLAC/CEPAL), andis now a Ph.D. candidate at the Graduate School of Economics, Kobe University.
exports of primary products.1 Since the 1980s, Chile’s export strategy has been characterized notjust by the expansion of primary products, such as copper in line with its comparative advantage, butalso by the diversification of natural resources2 contained in its export basket, in order to prevent thefluctuations in world prices of commodities from exposing the Chilean economy to external shocks(Meller, 1996). Thus, Chile has succeeded in creating new kinds of export products, such as fish,
fruits, and forestry products, which were hardly exported before the economic liberalization.
This study defines the “non-traditional natural resource-based export sector,” when aproduct sector satisfies the following two criteria. First, it defines a “non-traditional natural
resource-based product” as a product derived from a natural resource, and one that is not ranked
within the top ten exports in Anuario estadístico de América Latina y el Caribe (Statistical Yearbook
for Latin America and the Caribbean) published by the Economic Commission for Latin America
and the Caribbean (ECLAC) in 1975 (i.e., at the beginning of the economic liberalization), but iscontinuously ranked in the Yearbook during 2000–2003.3 Second, it defines the “export sector” as asector for which the ratio of export to total output exceeds 30% in the input-output tables publishedby the Central Bank of Chile.4 However, this definition of “non-traditional natural resource-based
export sector” does not strictly coincide with exportaciones no tradicionales defined by ProChile.5
We can confirm the aforementioned export diversification of natural resources and theincrease in the importance of non-traditional natural resource-based products from descriptive
statistics. The evolution of exports of the ten leading products from 1970 to 2003 is presented inTable 1. The share of copper (i.e., the sum of refined copper, ores and concentrates of copper, blistercopper, and other unrefined copper) in total exports decreased from 78.8% in 1970 to 36.2% in 2003.
On the other hand, the non-traditional natural resource-based products (i.e., fresh, chilled or frozen
fish, fresh grapes, wine from fresh grapes, and sawn lumber) accounted for 17.5% of total exports in
1

Chile’s GDP growth averaged 5.8% per year from 1984 to 2007.
This study defines “natural resources” according to the classification in ECLAC (2008a), namely,
as including both commodities and natural resource-based manufacturing.
3
The entries in the Year-book are classified according to the Standard International Trade
Classification (SITC) Rev.1.
4This definition of the export sector is based on Meller and Tokman (1996). The product sectors of
the input-output table of 1986, published by the Central Bank of Chile, are classified according to
the International Standard Industrial Classification (ISIC) Rev.2. However, some sectors from 1986
were aggregated in the 1996 input-output table, as explained in greater detail in Section 3.
5
ProChile is the Trade Commission of Chile and a part of the General Directorate of International
Economic Affairs of Chile’s Ministry of Foreign Affairs. ProChile (2004; 2005) defines
exportaciones no traditionales as all products except for copper, fish meal, some fruits, cellulose,
iron, nitrate, metallic silver, oxide and ferromolybdenum, minerals of gold, sawn and brushed lumber,and methanol. Thus, exportaciones no traditionales include blueberry, salmon, chicken, dairy
products, and so on. ProChile (2005) also classify no traditionales and fruta (fruits). Therefore, thedefinitions used in this study do not differ considerably from those of ProChile, although sawn
lumber is excluded in the latter.
2

2003. Moreover, the export share of the ten leading products showed a decreasing trend; that is, it
decreased from 89.9% in 1970 to 60.0% in 2003, although the majority of the ten leading products
continued to be natural resource-based. The same is also suggested by the Herfindahl–HirschmanIndex (HHI) used to measure the export concentration; the value decreased from 0.41 in 1980 to 0.27
in 2002, one of the most prominent decreases in the LACs during this period (Agosin, 2009).6
Therefore, while Chile continues to be strongly dependent on exports of natural resources, it has
succeeded in diversifying its natural resource-based exports.
Chile’s development process since the 1980s lays the ground for a very relevant debate
about natural resources and economic development. ECLAC, which strongly influenced
development strategies of LACs, especially from the 1950s to the debt crises in the early 1980s,
argues that natural resource products are intrinsically different from manufacturing products; thedependence on exports on primary products harms their economic development. The main
assumptions of its argument are based on the falling long-term trend of prices of primary products interms of manufacturing products. As indicated by the Prebisch–Singer thesis, this falling trend ismainly attributable to low income-elasticity of demand for primary products and asymmetric
distribution of the fruits of technical progress (Prebisch, 1949; Singer, 1950).7 The assumptions arealso based on high price volatility, very limited back- and forward- linkage effects, and low scope forhigh value added for their export.8 Regarding the linkage effects, which our study focuses on, themining sector (nitrate prior to World War I and copper during 1930–1970) has been regarded as the“enclave”, which has very limited back and forward linkage effects with the rest of the domestic
economy (Meller, 1995).
However, in recent years, especially after 2000, not only Chile but other LACs also havesucceeded in expanding natural resource exports; the emergence of non-traditional natural
resource-based exports is evident in other LACs, such as winter vegetables from Guatemala andcommercial grains from Paraguay (Carter et al. 1996). Those non-traditional natural resource-based
products share common features in that they can be highly differentiated and processed. In thisregard, recently, ECLAC has provided a positive assessment of development strategies based on

6

The HHI for country j is defined in the following manner: HHI j xij 2 ( x ) , where x is the
ij

i

j

value of exports of good i by country j and x j represents the total value of exports from country j.
The simple average of HHI of the 17 prominent LACs decreased from 0.36 in 1980 to 0.25 in 2002.
Moreover, Mexico experienced the largest decrease during this period, from 0.48 to 0.13 (Agosin,2009).
7
They argued that the benefits of technical progress are passed on as rising of wages inmanufacturing export countries and as lowering of prices in primary export countries.
8
For more details, see Palma (1987).

natural resource-based exports. For example, Díaz and Ramos (1998) argue that the aforementioned
negative assumptions on natural resource products can be rejected as myths, and they supported“Nordic” development strategies for Chile. Ramos (1998) also argues in favor of development basedon production complexes or clusters of processed natural resource products. On the other hand,
Rodrik (2005) finds that an indicator, which measures the quality of the country’s export basket, ishighly correlated with the per capita income of that country. Agosin (2009) also finds that export
diversification was positively significant in explaining per capita GDP growth during 1980–2003,
after controlling for other variables that affected per capita GDP growth. These recent findings still
support ECLAC’s traditional view that dependence on a limited number of primary product exports
harms or delays economic development.
In this regard, it is very relevant that Chile, the most successful among the LACs in termsof export-led growth based on non-traditional natural resource-based products, has produced
different outcomes compared to ECLAC’s traditional assumptions on natural resource-based productexports. This study focuses on the linkage effects among the aforementioned assumptions, because
the nature of the countries’ export sectors would show the production patterns of the economies inquestion (ECLAC, 1990).9 It is also because countries that have witnessed economic development
based on natural resource-based exports, such as New Zealand, Australia, Norway, Finland, andSweden, show a common pattern, namely, that exports act as an engine of growth by creating
domestic linkages and generating new associated technologies (Machinea and Vera, 2006). Therefore,
the objective of this paper is to precisely analyze whether non-traditional natural resource-based
export sectors in Chile, such as fish, fruits, and forestry products, have produced different domestic
linkage effects, compared with the traditional mining export sector, by producing three input-output
tables allowing inter-temporal comparisons.
This paper is organized as follows. Section 2 critically reviews previous studies. Section 3
describes the methodology, that is, how to reconstruct input-output tables in order to perform
inter-temporal comparisons and measure the linkage effects. Section 4 analyzes the empirical results.
The conclusions are summarized in Section 5.

9This study terms inter-industrial linkage effects alone as “linkage effects,” although this term mayrefer to both inter-industrial and intra-industrial linkage effects.

Table 1. The evolution of exports of 10 leading products, 1970–2003 (%)

Source: CEPAL (1989:120–121), CEPAL (2005:151)

2. Literature Review
A few studies have analyzed the evolution of linkage effects for each product sector in Chile, byreconstructing input-output tables to perform inter-temporal comparisons. For example,
Albala-Bertrand (1999) performs inter-temporal comparisons by aggregating the input-output tablesfrom 1962, and from 1977 to 1986, into 25 sectors. He also classifies these 25 sectors into primary,light manufacturing, heavy manufacturing, construction, and services sectors. He finds that the
backward linkage effects for both light and heavy manufacturing decreased from 1977 to 1986, justwhen the Washington Consensus Model (a package of neoliberal reforms) was applied to Chile.
However, these linkage effects increased from 1962 to 1977, in the era of import substitution
industrialization. Moreover, the ratio of domestic inputs to total intermediations persistently
decreased from 1962 to 1977, with this trend being particularly severe in the heavy industry from1977 to 1986. Therefore, he concludes that Chile’s development process since the mid-1970s, when
neoliberal reforms were implemented, is in clear contrast with that of Taiwan and South Korea,
where intermediate linkage effects increased systematically over time. Moreover, these intermediate
linkage effects increased at a quicker rate in heavy manufacturing, although both Chile andTaiwan/South Korea stressed on export-led development. Therefore, the findings of Albala-Bertrand(1999) are striking, because linkage effects of the manufacturing sector weakened over time in Chile,in contrast to the general assumption that one of the main features of transformation of the industrial

structure when accompanied by economic development is a rapid rise in the importance of
manufacturing sector. An increase in linkages of manufacturing sectors is associated with theirhigher output growth, as typically seen in the development process of Taiwan and South Korea(Kubo et al., 1986).10
However, Albala-Bertrand (1999) does not analyze the differences of linkage effects
among natural resources, as he aggregated the primary sector into the non-mining sector and threemining sectors. Thus, non-traditional natural resource-based products, which increased importancein the export of Chile, as discussed in the Introduction, are excluded from the analyses. Moreover, an
excessive aggregation of product sectors tends to wash out meaningful inter-sectoral linkage
differentials (Jones, 1976). Therefore, we should use input-output tables with as detailed sector
classifications as possible, when performing inter-temporal comparisons, as discussed in the next
section. Albala-Bertrand (2006) extends the analysis from 1986 to 1996. However, besides
aggregating the primary sector into the non-mining sector and three mining sectors, he also
aggregates the input-output tables into 28 sectors, thus presenting findings that are very similar to
those of his earlier work. Thus, the excessive aggregation of product sectors persists andnon-traditional natural resource-based products are excluded from his analyses.

3. Methodology
In this section, I first describe how to reconstruct input-output tables in order to perform
inter-temporal comparisons of linkage effects. The 1986, 1996, and 2003 input-output tables
published by the Central Bank of Chile are classified into 75, 73, and 73 sectors, respectively, andthus, the classification of 1986 differs from that of 1996 and 2003. Therefore, if the sectors are to beaggregated in another period, I aggregate multiple sectors into one sector only, in order toreconstruct input-output tables with a sector classification that is as detailed as possible. A detailed
analysis of the correspondence table of the Banco Central de Chile (2001) shows that theaggregation of two sectors in 1986 into one sector in 1996 was implemented for six sectors, whilethat of two sectors in 1996 into one sector in 1986 was implemented for four sectors.11 As a result of
the implementation of classification adjustments, the reconstructed input-output tables from 1986,
and 1996 to 2003, have 69 sectors.
Moreover, the Central Bank of Chile does not collate product-by-product or
10

It does not mention any causality between linkages of manufacturing sectors and the sectors’ total
output. We may assume that the larger the linkage effects of manufacturing sectors, the higher their
total output, and vice versa.
11
The 69 sectors are calculated as 75 − 6 = 73 − 4 = 69. For more details, see Table A-1.

industry-by-industry input-output tables, although it did collate the input coefficient matrix in the
product-by-product form, and the Leontief inverse matrices in both product-by-product andindustry-by-industry forms, for 1996 and 2003. Therefore, we need to convert product-by-industry
input-output tables into product-by-product or industry-by-industry input-output tables, when
implementing

theaforementioned

classification

adjustments.

This

study

produces

product-by-product input-output tables in line with the industry-technology assumption that anindustry uses the same technology to produce all its products. This is because there is a possibility
that the elements of the produced input coefficient matrix take a negative value under the
product-technology assumption. Thus, the industry-technology assumption allows for simpler
mathematical operation (Bulmer-Thomas, 1982; Venegas, 1994). This study employs themethodology of Venegas (1994), which explains the conversion of a product-by-industry
input-output table from 1986 into a product-by-product input-output table, and applies thismethodology for the other two years also, i.e., 1996 and 2003. The product-by-industry tables
exogenously give us U, the V matrix, the e vector, and the following balanced equations:(1)q  Ui  e and(2)g  Vi ,where U is a 69 product × 69 industry absorption matrix, whose element i, j show that input i isabsorbed by industry j, that is, it corresponds to the domestic flow matrix (Bulmer-Thomas, 1982); e
is a 69 product × 1 column vector of net final demands (excluding imports); and i is a 69 × 1 unity
column vector. Therefore, q is a 69 product × 1 column vector of domestic product output. V isa 69 industry × 69 product make matrix, which shows the distribution of industrial output; theelement i, j show that i industry produces j product. It is relevant to note here that one industry does
not necessarily produce one product; it also produces a secondary product. For example, the metalindustry produces not only metal goods, but also chemicals and other manufacturing products. In
that sense, the V matrix is dominated by the elements on the diagonal, which represent the
principal products, while the off-diagonal elements represent the secondary products(Bulmer–Thomas, 1982). Thus, g is a 69 industry × 1 column vector of domestic industry output.
The industry-technology assumption is given a formal expression in the matrix items asfollows:(3)

B  Ugˆ 1(4)

D  Vqˆ 1 ,and

where ĝ is a 69 industry × 69 industry diagonal matrix of domestic industry output g . q̂ is a 69
product × 69 product diagonal matrix of domestic product output q . We also term equation (4) as
the market share hypothesis, which assumes that the product is supplied in fixed proportions bydifferent contributing industries (Bulmer-Thomas, 1982). Therefore, the solution for unknownddomestic input coefficient matrix A of the product-by-product input-output table is as follows. If
we substitute equation (3) into equation (1), we obtain the following equation:q  Bg  e .

(5)Then, if we substitute the equations (2) and (4) into equation (5), we obtain the following
equation:q  BDq  e .

(6)

Therefore, we obtain equation (7).

q  (I  BD)1 e .

(7)Now, we obtain the domestic input coefficient matrix A  BD and the domesticdd 1

Leontief inverse matrix (I  A ) (I  BD)1 of the reconstructed 69 product-by-productinput-output table. In these procedures, I choose all matrices and vectors evaluated by basic prices,
according to Venegas (1994), although those evaluated at purchasers’ and producers’ prices are alsopresented in the original product-by-industry input-output tables. This is because the input
coefficients evaluated at basic prices are purer; that is, they do not include any margins of
distribution or indirect taxes (Venegas, 1994). The prices are deflated by the wholesale price index(June 1992 = 1).
Second, I explain how to measure the linkage effects. In line with Jones’ (1976)
observation, this study assumes that the column sums of the Leontief inverse matrix provide theappropriate measure of the backward linkage proposed by Hirschman (1958).12 This study does notanalyze forward linkages, because the main focus is the export sector, which is defined in the
Introduction. Thus, it is meaningless to analyze the effects of the export sector, which induce
attempts to utilize its output as inputs in some new domestic activities. Moreover, this study excludes
12

Yotopoulos and Nugent (1973) assumed the column sums of the Leontief inverse matrix as themeasure of the total linkage, and not backward linkage alone. Hirschman (1958) defined backward
linkage effects as the economic activity that induces attempts to supply, through domestic production,
the inputs needed in that activity.

imports from intermediate inputs, and uses the domestic input coefficient matrix produced
previously in this section. This is very relevant for this study, because the lack of linkage effects, i.e.,the “enclave” nature of underdeveloped countries, as mentioned in the Introduction, is characterized
by the fact that inputs from other domestic sectors in advanced countries serve as imports tounderdeveloped countries (Hirschman, 1958). Thus, this study calculates only the domestic
intermediate inputs stimulated by an increase in one unit of net final demand for a particular sector.
However, this study does not take into consideration heterogeneity within the same industries, i.e.,the coexistence of small/medium and large firms, and the lack of linkages between them.13
Therefore, this study calculates the measure of backward linkage effects (henceforth, BL)of j sector as follows:(8)

BL j   zijd ,iwhere z ijd denotes i,j elements of the domestic Leontief inverse matrix. BL j represents the sum of
direct and indirect domestic intermediate inputs stimulated by an increase in one unit of net final
demand by a particular sector j. To compare the BL of each sector, this study normalizes the BL, bycomparing the average stimulus created by sector j with the overall average. Thus, the normalized
backward linkage effects (henceforth, NBL) are calculated as follows:(9)

NBL j 1 / 69 zijdi

1 / 69  zijd
2

i

,

j

where the numerator represents the stimulus imparted to other sectors by an increase in one unit of
net final demand by a particular sector j, while the denominator represents the average stimulus forthe whole economy when all net final demands increase by one unit (Bulmer-Thomas, 1982).
Therefore, in line with Albala-Bertrand (1999), for this study, if the NBL for a particular sector j isexceeds one, then this sector, on account of its above average BL, is said to have high BL.
Conversely, if the NBL is smaller than one, then this sector, on account of its below average BL, issaid to have low BL.

13

The lack of both inter- and intra-industrial linkages among small/medium and large firms
continues to be a prominent issue in Chile today. For more details, see, for example, Infante andSunkel (2009).

4. Analysis of Empirical Results
4-1. The evolution of backward linkage effects of non-traditional natural resource-based
export sectors
First, I show the evolution of the 10 highest BL and NBL by product, and the simple average of BL
and NBL classified into seven sectors, that is, non-mining primary products, mining products,
natural resource-based manufacturing, light manufacturing, heavy manufacturing, construction, andservices sectors,14 for 1986, 1996, and 2003 (Table 2). This will reveal the characteristics of the
production structure of the entire economy for the stated period. The results show that the meat andmeat products sector has the highest BL and NBL. Light manufacturing products, except for natural
resource-based products, and heavy manufacturing products, are not ranked within the 10 highest BL
and NBL during this period. Moreover, the heavy manufacturing sector had very small BL and NBL,
and notably, it recorded the smallest BL and NBL among the aforementioned seven sectors in 1996.
On the other hand, the non-mining primary products sector shows increasing trends of BL and NBL;
the BL increased from 1.550 in 1986 to 1.848 in 2003. An additional striking finding is that the
average BL of all products did not increase at all; on the contrary, it decreased from 1.713 in 1986 to
1.645 in 1996.
Therefore, Chile’s production structure is characterized by non-increasing BL for theentire economy, while the BL of the manufacturing sector and the non-mining primary products
sector decreased and increased respectively during this period in spite of sustainable growth. Thus,
the transformation tendency of Chile’s industrial structure, as noted by Albala-Bertrand (1999; 2006),
has persisted after 1996, contradicting the general assumption of the transformation of industrial
structure accompanied by economic development.

14

Non-resource based light manufacturing products are included within the light manufacturingsector in this classification.

Table 2. The evolution of 10 highest BL and NBL by product, 1986–2003

Source: Author’s calculations based on data from Banco Central de Chile (1992; 2001; 2006)
Note: I refer to Banco Central de Chile (2001:215–216) for Spanish to English translations.

Second, Tables 3 to 5 provide the BL and NBL of export sectors, with an export ratio (i.e.,
the ratio of exports to the total output) exceeding 30%, in descending order of the export ratios. In
1986, 11 product sectors satisfied the aforementioned definition of the export sector, which included
four non-traditional natural resource-based products,15 that is, the prepared and preserved fruits andvegetables sector, the prepared and preserved fish sector (both of which had high BL), the wood andwood products sector, and the fruit products sector. The simple average of NBL among those 4
non-traditional natural resource-based export sectors (1.036) was higher than that among the 3mining export sectors (0.918), and that of all 11 export sectors (0.936).
In 1996, 12 products sectors satisfied the aforementioned definition of the export sector.
These include five non-traditional natural resource-based products, that is, the prepared and15

For the definition of non-traditional natural resource-based products, this study refers to Anuario
estadístico de América Latina y el Caribe published by ECLAC, and the definition used by the
input-output tables published by the Central Bank of Chile. Thus, non-traditional natural
resource-based products are defined to include the following: fresh, chilled, or frozen fish products(SITC 0311) corresponding to fish products (ISIC 130) and fish product-based manufacturing, i.e.,
prepared and preserved fish (ISIC 3114); fresh grapes (SITC 0515) corresponds to fruit products(ISIC 111), and fruit product-based manufacturing, i.e., prepared and preserved fruits and vegetables(ISIC 3113); wine of fresh grapes (SITC11212) corresponds to distilled alcoholic beverages andwines (ISIC 3131); and sawn lumber products (SITC 24321) corresponds to wood and wood
products (ISIC 331). Thus, this study defines these six product sectors as non-traditional natural
resource-based products in the reconstructed 69 product-by-product input-output table.

preserved fish sector, the prepared and preserved fruits and vegetables sector, the distilled alcoholic
beverages and wine sector, the wood and wood products sector (all of which had high BL), and thefruit products sector. The simple average of NBL among these five non-traditional natural
resource-based export sectors (1.107) was higher than that of the three mining export sectors (0.995),
that of one manufacturing sector (0.931), and that of all 12 export sectors (1.025).
Finally, in 2003, 15 products sectors satisfied the aforementioned definition of the export
sector. This included six non-traditional natural resource-based products, that is, the wood and wood
products sector, the prepared and preserved fish sector, the fish products sector, the prepared andpreserved fruits and vegetables sector, the distilled alcoholic beverages and wine sector (all of which
had high BL), and the fruit products sector. The simple average of NBL among these 6
non-traditional natural resource-based export sectors (1.111) was higher than that of the three mining
export sectors (1.031), that of the three manufacturing sectors (0.951), and that of all 15 export
sectors (1.019). Although the copper sector had the highest or second-highest export ratios from1986 to 2003, the NBL of this sector were 0.962 in 1986, 0.980 in 1996, and 0.988 in 2003. Thus, it
had stably low BL.
Therefore, the findings shows that, from 1986 to 2003, the number of the non-traditional
natural resource-based export sectors with high BL and the average of NBL of the non-traditional
natural resource-based export sectors both increased. Moreover, the non-traditional natural
resource-based export sectors always had high BL. The average of NBL of non-traditional natural
resource-based export sectors was always higher than the average of NBL of the mining export
sectors and that of all export sectors. The NBL of the copper sector did not increase and it had stably
low BL during this period. This increasing trend of NBL was especially evident in the wood andwood products, and fish products sectors. It is relevant to note here that, as per the features of
non-traditional natural resource-based export sectors, the wood and wood products, and fish products
sectors experienced a substantial increase in export ratios. The export ratio of the former increased
from 33.0% in 1986 to 63.5% in 2003, while its NBL increased from 0.990 from 1.251 during thistime. The export ratio of the fish products sector increased from only 3.0% in 1986 to 64.3% in 2003,
while its NBL increased from 0.963 from 1.127.16 This trend is also seen in the meat and meatproducts sector, which had the highest BL from 1986 to 2003 (as seen in Table 2). The export ratioof the meat and meat products sector increased substantially from only 2.3% in 1986 to 16.0% in
2003; thus, it was still not classified as an export sector in 2003.

16

Thus, the fish products sector in 1986 and 1996 is not classified as an export sector. In otherwords, it is not ranked in tables 5-3 and 5-4.

Table 3. Backward linkage effects of export sectors, 1986

Table 4. Backward linkage effects of export sectors, 1996

Table 5. Backward linkage effects of export sectors, 2003

Source: Author’s calculations based on data from Banco Central de Chile (1992; 2001; 2006)
Note: Export and total output values are expressed as 1,000,000 Chilean pesos, at prices deflated by thewholesale price index (June 1992 = 1). Rank of NBL shows the descending order of NBL. I show thesums of the exports and total output values of non-traditional natural resource-based products, mining
products, manufacturing products, and total export sectors vis-à-vis the products sector. Their BL and
NBL are simple averages vis-à-vis the products sector. I refer to Banco Central de Chile (2001:215–216)
for Spanish to English translations.

4-2. The evolution of domestic intermediate inputs of non-traditional natural
resource-based export sectors
This sub-section discusses the products sectors associated with the high NBL of non-traditional
natural resource-based export sectors discovered in section 4-1. This is accomplished by analyzing
their domestic intermediate inputs. In this regard, I focus on the evolution of domestic intermediate
inputs of the four highest BL among the non-traditional natural resource-based export sectors in
2003, that is, the wood and wood products sector, the prepared and preserved fish sector, the fish
products sector, and the prepared and preserved fruits and vegetables sector.
The evolution of the 10 highest domestic intermediate inputs and the sum of domestic
input coefficients of the aforementioned four non-traditional natural resource-based export sectors
from 1986 to 2003 are presented in tables 6 to 10. The results show that the sum of domestic input
coefficients of the wood and wood products, and the fish products sectors, substantially increased
from 44.7% in 1986 to 62.6% in 2003, and from 39.9% in 1986 to 50.8% in 2003, respectively. The
increasing trend of the sum of domestic input coefficient in the wood and wood products sector wasassociated with domestic intermediate inputs from forestry products, and wood and wood products,that is, inputs from its raw material and itself (see Table 6). On the other hand, the increasing trendof the sum of domestic input coefficient in the fish products sector was associated with the
manufacturing sector, such as prepared animal feeds, plastic products, and basic chemicals. The
increasing trend is especially evident in the prepared animal feeds sector; it increased from 0.22% in1986 to 24.3% in 2003. Therefore, this particular increase is the main reason for the increase in thedomestic intermediate inputs of the fish products sector. Moreover, as Agosin (1997) noted, thesemanufacturing sectors are considered as the backward linkage industries for salmon aquaculture,
which recorded a rise in fishing exports during this particular period,17 and included nutrients,
packing materials, and fish medicine. Therefore, present study’s findings quantitatively concur withthose of Iizuka (2005), who showed that some inputs to Chilean salmon aquaculture, such as fish
feed, are locally supplied, while other inputs, such as nets, chemicals, and packing materials, arepartially locally supplied, based on the field surveys conducted in early 2004 in the 10th region ofChile.
Regarding the prepared and preserved fish sector, and the prepared and preserved fruits
and vegetables sector, we find that the sum of domestic input coefficients did not show an increasing
trend. However, we did find increasing trends of domestic intermediate inputs from business services
in these sectors. The findings may be a reflection of how knowledge intensive these sectors havebecome.

Table 6. The evolution of the domestic inputs coefficient of the wood and wood products sector,
1986–2003

17

The revenues from salmon aquaculture to total fishing exports increased from 28% in 1990 to
56% in 2000 (Perez-Aleman, 2005).

Table 7. The evolution of the domestic inputs coefficient of the prepared and preserved fish sector,
1986–2003

Table 8. The evolution of the domestic inputs coefficient of the fish products sector, 1986–2003

Table 9. The evolution of the domestic inputs coefficient of the prepared and preserved fruits andvegetables sector, 1986–2003

Source: Author’s calculations based on data from Banco Central de Chile (1992; 2001; 2006)
Note: I refer to Banco Central de Chile (2001:215–216) for Spanish to English translations.

5. Conclusions
This study analyzed whether non-traditional natural resource-based export sectors in Chile, such as
fish, fruits, and forestry products, have produced different domestic inter-industrial linkage effects,
compared with the traditional mining export sector, by reconstructing input-output tables from 1986,
1996, and 2003. The main findings are as follows. First, the number of non-traditional natural
resource-based export sectors with high BL, and the average of NBL of the non-traditional natural
resource-based export sectors, both increased from 1986 to 2003. Moreover, the non-traditional
natural resource-based export sectors always had high BL, while the average of NBL of the
non-traditional natural resource-based export sectors was always higher than that of the mining
export sectors and that of all export sectors. The NBL of the copper sector did not increase and it had
stably low BL during this period. Second, this increasing trend of NBL was especially evident in thewood and wood products, and the fish products sectors, for which export ratios notably increased
from 1986 to 2003. Moreover, among those non-traditional natural resource-based export sectors
with high BL, the fish products sector substantially increased domestic intermediate inputs from the
backward linkage industries.
Therefore, this study found that some non-traditional natural resource-based export sectors,
which have come about as a result of export diversification since the 1980s, certainly increased BL

and had higher BL than the traditional copper export sector. Among these, the fish products sector,
mainly constituted by the salmon aquaculture industry, succeeded in creating BL with domestic
manufacturing suppliers. In this regard, one contribution of this study is that, in contrast to all otherindustrial sectors, salmon aquaculture has developed BL with domestic backward linkages at theindustry level. This study made this finding based on reconstructed input-output tables with products
sectors classified in as detailed a manner as possible, and my finding concurs with that of Iizuka(2005), who conducted firm-level field surveys. Thus, these findings provide important
counter-evidence to the “enclave” features of exports on primary products in Chile.
However, this study also showed the persistent weakness of BL of the entire economy andthe manufacturing sector, especially the heavy manufacturing sector. The findings indicated thelimitations of Chile’s current export-led development strategy, which promotes export diversificationof natural resources, according to the principles of comparative advantage, and the absence ofenabling industrial policies. Therefore, it is uncertain whether the non-traditional natural
resource-based export sectors with high BL will be able to establish BL of a required range anddepth. In other words, it is uncertain whether the intermediate inputs of these sectors will be able torepeatedly stimulate other intermediate inputs, as Hirschman (1958) assumed in the case of
manufacturing sectors. In this regard, the findings of Chenery and Taylor (1968), that small primaryexport-oriented countries are slower to transform their industrial structure than industry
export-oriented countries, is still suggestive.
This topic clearly needs further research. First, it will be interesting to analyze how
increases in BL of non-traditional natural resource-based export sectors have contributed tosustainable economic growth in Chile since the mid-1980s. Second, it will also help to analyze how
increases in BL of non-traditional natural resource-based export sectors have been related to therecent changes in the production chain, especially the global commodity chain. Moreover, a focus on
the sustainability of Chile’s primary export-led development strategy is also necessary. Since 2007,
salmon aquaculture has been hit by an infectious disease, i.e., infectious salmon anemia (ISA),
although it was said that the coast of Chile was safe from ISA. The ambient contamination caused bysalmon aquaculture is also of concern. While Díaz and Ramos (1998) rejected the traditional
negative assumptions on natural resource products as myths, they nevertheless admitted that the
primary export-led development strategy is still not immune to ambient contamination and the Dutch
disease. I hope to focus on these topics in future studies.

Acknowledgements
I am grateful to Mr. Hernán Frigolett (former ECLAC) for providing very important suggestions
concerning the input-output tables for Chile, and to Mr. Andrea Pellandra (ECLAC) for helping me
to obtain the input-output tables for Chile. I am also deeply obliged to Prof. Shoji Nishijima (Kobe
University), Prof. Nobuaki Hamaguchi (Kobe University), Dr. Mikio Kuwayama (ECLAC), Prof.
Toru Yanagihara (Takushoku University), and Prof. Setsuko Yukawa (Kyoto Sangyo University), forproviding insightful comments and suggestions.

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Appendix
Table A-1. Comparable product sectors in Chile’s input-output tables for 1986 and 1996

Source: Author’s calculations based on data from Banco Central de Chile (1992:87; 2001:207)
Note: I refer to Banco Central de Chile (2001:215–216) for Spanish to English translations.