Export Sophistication,Export-Led Growth and Product Space: Evidence from Selected Asian Economies

Abstract

This research aims to examine the sophistication of export portfolios of selected Association of South East Asian Nation (ASEAN) and developed Asian economies. It aims to provide evidence of where exactly ASEAN economies are in the context of exports sophistication and structural transformation. Results from a product space analysis indicate that although limited in product scope, there are prospects for ASEAN economies to converge to the level of export sophistication of developed Asian countries. The analysis finds a need for governments to take a more active role in promoting more appropriate industrial and economic policies.

Keywords

Product space export diversification economic development Asian economies ASEAN exports

Introduction

Based on the experience of newly industrialized Asian economies, the ability of a country to move from agriculture to high-technology manufacturing exports is one manifestation of successful structural transformation and economic development. In the words of Hausmann and Klinger (2006), structural transformation is a development process that involves the movement of production from simple poor-country goods to more complex rich-country products. This is consistent with a successful export-led growth strategy where trade in high-technology and scale products takes an active role.

ASEAN economies have benefited from trade and they can further reap benefits from it. The Philippines, tagged as the “sick man of Asia,” can explore improvements in export sophistication as a potential avenue towards the path to higher economic development instead of relying mainly on the remittances of overseas workers. While trade in goods or services are both vulnerable to political turmoil and social unrest in the host countries, growth derived from trade in goods is more self-sustaining once the right mix of infrastructure, skills and knowledge-based structures are developed.

Asian economies have significantly improved their export composition, moving from agricultural and primary commodities and low-skilled goods production to more sophisticated products such as electronic and high-technology manufactured goods. Evaluating the performance of the export basket of these countries is one important objective of this paper.

While a number of studies on export-led growth have been done using econometric techniques (Crespo and Worz, 2005; Dodaro, 1991), recent literature introduces new methods of assessing the performance of a country’s exports through their location in the product space. The product space analysis started in Hausmann and Rodrik (2003), which explores the cost discovery process of firms or their ability to venture into new products and technological innovation. The cost discovery generates positive externalities when other firms learn from the successful innovator and produce goods that push the economy to its technological and production frontier. Later, Hausmann et al. (2005) have quantified the process of cost discovery by constructing an index that measures an export product’s sophistication (PRODY) and an index that measures the overall sophistication of a country’s export basket (EXPY).

Building on these, Hausmann and Klinger (2006) have investigated deeper the sophistication of export products by working on the fact that while vertical specialization through improved productivity is necessary, horizontal specialization is indispensable so that firms will upgrade technology and manpower skills.¹ Based on this idea, Hausmann and Klinger (2006) have developed a measure called proximity, or the revealed distance between products, and demonstrated that a country’s speed of structural transformation depends on whether its existing exports have many nearby high value-added goods in the product space. This has significant implications on the portfolios that countries can diversify into over time.

Later, Hidalgo et al. (2007) have visually illustrated that there are regions of the product space where goods are densely connected to many products while other regions have goods that are sparsely connected with each other. The former region is the core while the latter is the periphery. Hausmann and Klinger (2006) have shown that labor intensive goods such as garments, cereals and tropical agriculture have low PRODY and are mostly found in the periphery, while machinery and high-technology manufactured products are found in the core. The export basket of wealthier countries also tends to be in the denser regions of the product space.

Since the existing exports of the lagging developing countries are in the less-connected region of the product space, they have fewer options for horizontal diversification. Within the context of product space, the location of current exports has implications on a country’s economic growth. If the country’s export portfolio is in the sparse parts or in the periphery, then the country has limited options for diversification and an even more limited opportunity to penetrate the denser or richer part of the product space. To converge with industrialized economies, the country needs significant adjustment in its production structure.

Using the product space, this research aims to assess the performance of the export portfolio of selected ASEAN countries by analyzing the trends in the sophistication of their export basket. This will be done alongside Korea and the People’s Republic of China to provide a sense of how far the ASEAN countries have gone in export upscaling and how much further they should go compared to their more successful neighbors. This will reveal the kind of structural transformation that will have to be undertaken by the less-developed ASEAN economies. While relatively simpler than Hausmann and Klinger’s (2008) analysis of Colombia’s opportunities for economic growth, the paper performs simulation exercises that determine whether the ASEAN economies can reach the core of the product space given their existing exports. Based on these, the paper identifies some viable options for diversification in the short run and offers some insights for future policy. Herein lies the contribution of our study.

The study uses the United Nations Commodity Trade Statistics (UN-COMTRADE) Standard Industrial Trade Classification (SITC) Revision 2 at the four-digit disaggregation. The research is organized as follows: the next section discusses the history of the product space and how it is related with the earlier works on product similarity and horizontal specialization. The section titled “Results and discussion” uses the product space to analyze the export portfolios of the seven Asian countries, namely, China, Korea, Indonesia, Malaysia, the Philippines, Singapore and Thailand. It then uses the proximity and productivity indices to discuss the current capacity of these countries to diversify into more sophisticated goods. The role of the government is discussed, followed by the summary and conclusions.

Export sophistication and proximity: a product space analysis

History and related literature

The product space is a relatively new approach to analyzing a country’s existing exports and their implications for economic growth. Its brief history dates back to Hausmann and Rodrik’s (2003) cost discovery process, which is related to the literature on cost heterogeneity and uncertainty. Building on this, Hausmann et al. (2005) explored the role of positive externalities and information costs on economic growth. Central to their argument is that the positive externalities generated by a successful firm in producing a product should drive other firms to replicate this success. The greater the number of firms producing goods with higher productivity, the more likely the economy will reach and expand its technological and production frontier. In this context, Hausmann et al. (2005) have developed indices that differentiate goods based on their implied productivity: the PRODY score to measure the sophistication at the product level and the EXPY score to measure the sophistication of a country’s export basket.

The construction of these indices begins with a simple model² which assumes that each good has a productivity level to represent the units of output generated by an investment of a given size (Hausmann et al., 2005). However, the productivity level of a given investment is revealed only after the investment has been made. Once the project is discovered, other firms will replicate the project. This dissipates the profits, prodding the firms not only to replicate but to innovate, pushing the economy’s production frontier forward.

Hausmann et al. (2005) proxy the productivity level discussed above by the EXPY. They argue that using the export data to compute the EXPY is the most sensible strategy since countries will export goods in which they are the most productive. To construct EXPY, a product-level sophistication index (PRODY) is computed as $P R O D Y_{k} = \sum_{j} \frac{x_{j, k} / X_{j}}{\sum (x_{j, k} / X_{j})} * G D P p e r c a p i t a_{j}$ where the subscripts j and k represent country and product respectively and $X_{j} = \sum_{k} x_{j, k}$ and $x_{j, k}$ is the export value of product k in country j. Each exported good will have a corresponding PRODY, which is just the GDP (gross domestic product) per capita of each country weighted by the revealed comparative advantage of the country in that product. The use of the revealed comparative advantage as a weight is to ensure that the country size does not distort the ranking of goods (Hausmann et al., 2005)

The country’s EXPY is then constructed by summing all the PRODY weighted by the product’s share of the country’s total exports, $E X P Y_{j} = \sum_{j} (x_{j, k} / X_{j}) * P R O D Y_{k}$ . A higher EXPY score indicates that the country’s export portfolio comprises of sophisticated commodities. Since the productivity/sophistication is inferred from the types of countries exporting the good, Hausmann and Klinger (2008) caution that these indices are indirect measures of productivity/sophistication. However, Hausmann et al. (2005) have shown that primary commodities have low PRODY and that countries with high initial EXPY also experience higher subsequent economic growth. They have also shown that EXPY and GDP per capita are strongly correlated even after country j exports are excluded from the $E X P Y_{j}$ calculation.

Hausmann and Klinger (2006) have investigated further the productivity/sophistication of products by emphasizing the importance of horizontal specialization. They then developed a measure called proximity, or the revealed distance between products. The idea behind the proximity measure is that products close to each other will share a similar level of input, technological infrastructure and institutional requirements. Therefore, horizontal specialization between products sharing a similar production structure will not be as costly as between products that are farther apart in production requisites. For example, fewer modifications are needed to the production structure of footwear when moving to textiles than when moving to electronics. Formally, proximity is defined as $φ_{i j} = \min {P (R C A x_{i} | R C A x_{j}), P (R C A x_{j} | R C A x_{i})}$ .³ The proximity between products i and j is the minimum of the pairwise conditional probabilities of a country exporting a good given that it exports another (Hidalgo et al., 2007). It can be seen that the proximity measure uses the idea of the conditional probability, $P (A | B)$ .⁴ Since P(A|B ≠ P(B|A), the measure further uses the minimum of the pairs of these conditional probabilities and the revealed comparative advantage to capture true similarities and not just marginal exports (Hausmann and Klinger, 2006). Having a comparative advantage in a product means having the right endowments and capabilities and if two products need the same capabilities, the proximity measure would show up in a higher probability of a country having comparative advantage in both (Hausmann and Klinger, 2006). ϕ _ij close to 1 means that the products will be close to each other in the product space. In the above example of products, the ϕ for footwear and textile will have values closer to 1 than the ϕ for footwear and electronics. Proximity measures had been computed by Hidalgo et al. (2007) for each pair of products using the four-digit UN-COMTRADE SITC Revision 2.

Later, Hidalgo et al. (2007) have visually illustrated the relatedness of goods in what is now known as the product space. The product space has dense and sparse parts, the latter being less connected to the rest of the products and the former being close to many products that countries can upgrade to in the future. Hidalgo et al. (2007) have shown that wealthier countries are in the denser regions of the product space. Their simulation results indicate that the exports of lagging developing countries will not be as sophisticated as the exports of industrialized economies since these economies have export portfolios that are located in the periphery. This implies that there are few sophisticated products available for these economies to branch out into and suggests that diversification into sophisticated products requires significant transformation in technology, infrastructure, institutions and human capital. Within this framework, policies related to the upgrade of production structure can substantially shape what countries can be in the future.

Analysis using product space is relatively recent, and there is not much literature that can be claimed to have benefited from the product space analysis. The most that can be offered is a general observation regarding the paths taken up by countries that conform to the product space analysis. China has started out using export processing zones as a key strategy to learn from foreign firms in the advanced countries (Zhang and Song, 2000) and eventually expanded to steel production and higher value-added goods. By the 1980s it already had a comparative advantage on a number of machinery commodities in the denser region of the product space. China’s position in the world economy today did not happen overnight. Rather, it has been defined by a target that has been achieved through deliberate efforts such as industrialization and open-economy policies.

Summary

It is clear from the literature discussed above that the product space is just a visual representation of how close the goods are to each other, the closeness of which is defined by the proximity measure. The proximity index, in turn, is a formal representation of the idea that the closeness of goods is defined by their production requisites.⁵ The product space also incorporates the PRODY index, or the implied sophistication level of each good.

The visual representation is done by mapping all the products in a space such that the network connections among goods are dictated by the proximity measure. The higher the proximity values, the closer the goods are to each other. The product space has outer and inner regions. In the outer periphery and sparse sections of the product space are the products with low PRODY or those with a low level of implied contribution to income, such as oil, fishing, tropical agriculture, animal agriculture, garments and forest and petroleum products. At the core and the denser section of the product space are the more sophisticated products with higher PRODY such as metallurgy, machinery, capital-intensive products and motor vehicles. In this region, there are many products that can lead to even more sophisticated products.

The standard measure of similarity of goods in the traditional literature of international trade is based on factor endowments such as the Leamer (1984) clusters of products. While Hausmann and Klinger (2006) have provided evidence for the striking similarity between the product space and the Leamer classification, their key difference is that the former is an outcomes-based approach that introduces a new measure of similarity of products without making a priori assumptions on how goods are going to be related. The product space also provides a large amount of detailed information with ease. It provides information such as what goods can be produced, whether these goods lead to other goods with higher value added and whether the existing export portfolio can take a country to the export baskets of developed economies. The product space is therefore more helpful in providing a more specific guideline on structural transformation. This is the major innovation and contribution of the product space analysis.

Results and discussion

The PRODY and EXPY indices discussed above are computed for the selected Asian countries using the UN-COMTRADE SITC Revision 2 at the four-digit disaggregation. The contributions to EXPY of exports whose PRODY is more than half of the highest PRODY score are summarized in Table 1. It can be seen that the Philippines’ export basket has the lowest contribution with an average of 6.5% between the years 2000 to 2006. This indicates that its export portfolio consists of less sophisticated products. The other countries, such as Indonesia and Thailand, have a more diversified export basket generally consisting of more highly sophisticated products. China, Korea and Singapore have more than 25% of their EXPYs coming from highly sophisticated commodities.

Table 1.

Contribution to the EXPY of products with more than half of the PRODY_world, selected ASEAN countries, Korea and China.

		Total contribution to EXPY of products with more than half of the highest PRODY world	EXPY	% of the contribution
China	2000	2108	8860	23.80
	2001	2450	9126	26.85
	2002	2628	9386	28.00
	2003	2672	9612	27.80
	2004	2786	9881	28.19
	2005	2817	10,059	28.00
	2006	2897	10,157	28.52
Korea	2000	2599	11,184	23.24
	2001	3027	11,637	26.01
	2002	3017	11,741	25.69
	2003	3148	11,878	26.50
	2004	3338	12,028	27.75
	2005	3578	12,294	29.10
	2006	3571	12,300	29.03
Indonesia	2000	1162	7598	15.29
	2001	1017	7431	13.69
	2002	1094	7488	14.61
	2003	1053	7377	14.27
	2004	1182	7362	16.06
	2005	1044	7290	14.33
	2006	999	7082	14.11
Malaysia	2000	1070	10,249	10.44
	2001	1339	10,269	13.04
	2002	1276	10,371	12.30
	2003	1269	10,208	12.44
	2004	1342	10,153	13.21
	2005	1394	10,238	13.61
	2006	1499	10,233	14.65
Philippines	2000	639	10,792	5.92
	2001	685	10,620	6.45
	2002	667	10,779	6.19
	2003	666	10,710	6.22
	2004	649	10,693	6.07
	2005	587	10,245	5.73
	2006	572	9943	5.75
Singapore	2000	2988	12,413	24.07
	2001	3137	12,415	25.27
	2002	3202	12,508	25.60
	2003	3805	12,776	29.78
	2004	3921	12,813	30.60
	2005	3688	12,696	29.05
	2006	3803	12,727	29.88
Thailand	2000	990	9297	10.65
	2001	1036	9274	11.17
	2002	1092	9280	11.77
	2003	1082	9299	11.64
	2004	1207	9421	12.82
	2005	1268	9655	13.14
	2006	1310	9663	13.56

Note: Highest PRODY_world =28571 is computed using all the exports of all countries based on the UN-COMTRADE SITC (United Nations Commodity Trade Statistics Standard Industrial Trade Classification) Revision 2, 4-digit disaggregation. PRODY is the sophistication index of each good while EXPY is the sophistication index of the country’s export portfolio. These indices are computed as follows:

P R O D Y_{k} = \sum_{j} \frac{x_{j, k} / X_{j}}{\sum (x_{j, k} / X_{j})} * G D P p e r c a p i t a_{j} while E X P Y_{j} = \sum_{j} (x_{j, k} / X_{j}) * P R O D Y_{k}

This table summarizes the contributions to EXPY of exports whose PRODY is more than half of the highest PRODY world.

Given the current export performance of the less-developed countries, this research aims to ascertain their trade potentials and future challenges. To do this, the proximity matrix is borrowed from Hidalgo et al. (2007), which is then merged with the export data of selected Asian countries using the four-digit UN-COMTRADE SITC Revision 2. To facilitate the exercises that follow, the following notation will be adopted: exports in 2006 will be products i while the products close to them will be products j. Products j should have $P R O D Y_{j} > P R O D Y_{i}$ . In addition, products j should have no significant portion in the 2006 export share, $s h a r e_{j} < . 09 %$ , implying that the country is yet to produce the products in full scale. Products i should have $R C A_{i} \geq 1$ .

It should be noted that the boundaries on the relevant parameters are set such that the current research can provide directions towards high value-added products given the countries’ existing export portfolios. To attain this objective, the most feasible starting point would be the current exports for which the country has a comparative advantage ( $R C A_{i}$ restriction). To identify plausible products for future diversification, the product that countries should branch out to should be more sophisticated (PRODY restrictions) and not yet significantly produced ( $s h a r e_{j}$ restrictions).

Using the restrictions discussed above, Table 2 attempts to look at the potential of the countries’ existing exports to evolve into highly sophisticated goods. It shows the summary statistics of the products j close to the existing exports with $R C A \geq 1$ at different rounds. The first round contains the products j close to the current exports at $φ_{i j} \geq 0.55$ . Products j must satisfy the criteria set above. The second round contains the products close to the first round products. This search process is repeated for several rounds at $φ_{i j} \geq 0.55$ for each round until the search no longer produces any result. Following this procedure, figures in Table 2 also show the time it takes for countries to reach the products with high PRODY. It can be seen that the Philippines has the lowest average PRODY in the first round. By round two, the number of potential products which the Philippines can choose to branch out into has increased to 36% from 9% in round one. By round three, the average sophistication index of the potential products that the Philippines can expand into is already close to that of the developed Asian economies. The same trends can be observed for Indonesia. These imply that both countries have the potential to move from their current location to the denser part of the product space. Korea, China and Singapore need a lower number of rounds to reach the highly sophisticated products. This is because their existing exports are already in the denser parts of the product space and their production set-up needs little modification to produce goods that are more sophisticated than their existing export basket.

Table 2.

Summary statistics of the products j with $φ_{i j} \geq 0.55$ per round given the country’s 2006 export basket.

	China	Korea	Indonesia	Malaysia	Philippines	Singapore	Thailand
Round 1
AVE. PRODY	12,765	14,020	8016	12,126	7656	17,108	9475
# of products	116	41	48	44	77	16	95
# of products with 17,000>=PRODY<20,000	14	6	3	5	3	4	5
# of products with 20,000>=PRODY<23,000	12	8	0	10	4	5	9
# of products with PRODY>=23,000	0	0	0	0	0	1	0
Round 2
AVE. PRODY	16,989	16,232	12,213	12,368	13,410	17,647	15,909
# of products	36	29	10	41	28	10	32
# of products with 17,000>=PRODY<20,000	9	6	1	7	6	4	7
# of products with 20,000>=PRODY<23,000	7	7	1	5	4	2	8
# of products with PRODY>=23,000	2	1	0	1	0	1	2
Round 3
AVE. PRODY	18,051	16,941	14,505	13,471	16,300	15,875	16,720
# of products	25	26	11	51	32	13	30
# of products with 17,000>=PRODY<20,000	7	3	2	4	10	3	6
# of products with 20,000>=PRODY<23,000	7	6	2	7	6	2	6
# of products with PRODY>=23,000	3	3	0	3	1	1	3
Round 4
AVE. PRODY	18,012	16,965	18,286	13,639	17,338	16,135	16,936
# of products	20	27	15	43	25	14	33
# of products with 17,000>=PRODY<20,000	6	4	9	8	9	3	10
# of products with 20,000>=PRODY<23,000	6	7	3	5	7	2	7
# of products with PRODY>=23,000	1	1	0	2	1	1	2
Round 5
AVE. PRODY	18,690	16,477	19,331	15,116	19,238	15,173	17,441
# of products	21	25	17	36	21	24	32
# of products with 17,000>=PRODY<20,000	6	2	10	7	10	2	7
# of products with 20,000>=PRODY<23,000	6	5	4	6	6	3	7
# of products with PRODY>=23,000	2	2	1	2	2	1	3
Round 6
AVE. PRODY	18,545	17,244	19,489	15,934	19,772	17,358	18,442
# of products	24	23	18	40	19	21	27
# of products with 17,000>=PRODY<20,000	6	6	10	11	9	5	8
# of products with 20,000>=PRODY<23,000	7	6	5	7	7	5	8
# of products with PRODY>=23,000	2	0	1	2	1	1	2
Round 7
AVE. PRODY	20,541	19,423	20,427	17,390	20,471	18,473	19,323
# of products	13	17	16	31	16	11	24
# of products with 17,000>=PRODY<20,000	2	5	9	9	9	2	7
# of products with 20,000>=PRODY<23,000	7	6	5	7	5	4	7
# of products with PRODY>=23,000	2	2	2	3	2	1	3
Round 8
AVE. PRODY	21,324	20,941	20,865	17,094	21,157	18,975	19,521
# of products	7	11	11	32	11	3	18
# of products with 17,000>=PRODY<20,000	1	3	5	11	4	0	8
# of products with 20,000>=PRODY<23,000	4	6	5	7	6	2	6
# of products with PRODY>=23,000	1	1	1	2	1	0	1
Round 9
AVE. PRODY	21,478	22,767	21,870	18,386	21,983	18,022	20,252
# of products	3	5	9	24	8	4	16
# of products with 17,000>=PRODY<20,000	0	0	3	7	3	2	7
# of products with 20,000>=PRODY<23,000	3	4	4	7	3	1	5
# of products with PRODY>=23,000	0	1	2	3	2	0	2
Round 10
AVE. PRODY	24196	24196	21,235	18,028	21,577	21,349	19,718
# of products	3	3	8	20	7	2	16
# of products with 17,000>=PRODY<20,000	0	0	4	8	3	0	8
# of products with 20,000>=PRODY<23,000	2	2	3	6	3	2	5
# of products with PRODY>=23,000	1	1	1	1	1	0	1
Round 11
AVE. PRODY			22,448	19,338	22,818		21,362
# of products			5	17	4		12
# of products with 17,000>=PRODY<20,000			0	7	0		5
# of products with 20,000>=PRODY<23,000			4	5	3		5
# of products with PRODY>=23,000			1	2	1		2
Round 12
AVE. PRODY			21,957	19,718	21,957		21,519
# of products			1	16	1		9
# of products with 17,000>=PRODY<20,000			0	8	0		3
# of products with 20,000>=PRODY<23,000			1	5	1		5
# of products with PRODY>=23,000			0	1	0		1
Round 13
AVE. PRODY				21,362			22,818
# of products				12			4
# of products with 17,000>=PRODY<20,000				5			0
# of products with 20,000>=PRODY<23,000				5			3
# of products with PRODY>=23,000				2			1

Note: This table shows the summary statistics of the potential products that the countries can produce (product j). These are close to the existing exports (products i) with RCA ≥ 1 at different rounds. Products j should have PRODY_j > PRODY_i and share_j < .09%. ϕ _ij is the proximity measure between products i and j. PRODY is the product-level sophistication index and EXPY is the export portfolio sophistication index.

RCA: revealed comparative advantage.

The table contains the number of products j that satisfy the criteria above. The number of products j that have high sophistication index (PRODY) is also shown and is further disaggregated into various PRODY intervals so that the readers will see how many sophisticated products j are available for diversification. The first interval can be interpreted as the least sophisticated among the sophisticated products, the second interval as the mid-sophisticated and the third as the most sophisticated.

To identify directions for export diversification in the short run, Table 3 lists the products that have significant export shares in 2006 and that have goods which require much less alteration in the production structure. Data in this table show the potential of the countries’ existing exports to evolve into highly sophisticated goods given that they opted for less modification in their production structures. The 2006 exports that can lead to higher value-added goods and the paths leading to them are also identified. This is done by choosing products i with at least a 3% share of the 2006 exports that have products j proximate to them at $φ_{i j} \geq 0.60$ for all rounds. Results show that the exports of Korea, China and Singapore are varied and the products close to these exports have very high PRODY. This indicates that these economies have more opportunities to diversify their future export basket into an even more sophisticated export portfolio. The Philippines and Indonesia, on the other hand, have few exports and the average PRODY of the close products is the lowest. Thailand currently exports a commodity that has a proximate product with high PRODY at $φ_{i j} = 0.75$ . This shows that Thailand can penetrate the core region of the product space more easily than Indonesia and the Philippines. It currently has a comparative advantage in the form of an export that has a production structure requiring less modification to be able to expand into a more sophisticated product. While Indonesia has an export that has a proximate product at $φ_{i j} = 0.70$ , the product close to it is not as sophisticated. Like the Philippines, the rest of Thailand’s exports have proximate products at $φ_{i j} = 0.6$ . However, the proximate products to Thailand’s exports are more sophisticated than those of the Philippines and Indonesia.

Table 3.

Products close to the 2006 exports for the selected East Asian economies at $φ_{i j} \geq 0.60$ for all rounds.

2006 Exports (product i) with at least 3%	Round 1			Round 2			Round 3			Round 4
Share	$φ_{i j}$	PRODY	Products j	PRODY	$φ_{i j}$	Products j	$φ_{i j}$	PRODY	Products j	PRODY	$φ_{i j}$	Products j
KOREA
Abrasive powder or grain, on a base of woven fabrics	0.64	21,401	Printing paper and writing paper, in rolls or sheets
Machinery for specialized industries and parts thereof, nes	0.63	20,965	Machine for making cellulosic pulp
Silicones	0.75	20,644	Printing ink
Other machine-tools for working metal or metal carbides, nes	0.63	20,625	Machine for extruding man-made textiles and parts
Construction and mining machinery, nes	0.65	17,332	Natural or artificial abrasive powder, grain
CHINA
Power hand tools, pneumatic or non-electric, and parts thereof, nes	0.60	22,730	Cellulose acetates
Inorganic esters, their salts and derivatives	0.62	22,611	Organo-sulphur compounds
Cocks, valves and similar appliances, for pipes, boiler shells, etc.	0.63	21,957	Industrial and laboratory furnaces and ovens and parts
Aldehyde, ketone and quinone-function compounds	0.66	17,691	Phenols and phenol-alcohol and their halogenated derivatives	22,611	0.62	Organo-sulphur compounds
Cocks, valves and similar appliances, for pipes boiler shells, etc.	0.65	17,332	Natural or artificial abrasive powder or grain
Lifting, handling and loading machinery, telphers and conveyors	0.62	17,332	Natural or artificial abrasive powder or grain
Locksmiths’ wares, safes, etc., and hardware, nes, of base metal	0.65	17,332	Natural or artificial abrasive powder or grain
Electric lighting components; plastic	0.65	15,128	Glass, mirrors
SINGAPORE
Parts, nes of pumps and liquids elevators falling under heading 742	0.67	28,571	Furnace burners for liquid fuel and parts thereof
Power hand tools, pneumatic or non-electric, and parts thereof, nes	0.60	22,730	Cellulose acetates
Welding, brazing, cutting, etc. machines and appliances, parts, nes	0.60	22,036	Parts of the machine of 725-
Parts, nes of and accessories for machine-tools of heading 736	0.67	20,740	Workholders, self-opening dieheads and tool holders
Parts, nes of pumps and liquids elevators falling under heading 742	0.60	20,740	Workholders, self-opening dieheads and tool holders	21,957	0.61	Industrial and laboratory furnaces and ovens, etc., parts, nes
Other condensation, polycondensation or polyaddition products	0.61	20,547	Epoxide resins
Parts, nes of pumps and liquids elevators falling under heading 742	0.71	19,005	Parts of the machinery of 726.31,726.4-,726.7-	28,571	0.62	Furnace burners, mechanical stokers, etc., and parts thereof, nes
Parts, nes of pumps and liquids elevators falling under heading 742	0.66	18,630	Other printing machines for uses ancillary to printing	19,005	0.74	Parts, nes of machines falling within headings 72631, 7264, 7267
Parts, nes of pumps and liquids elevators falling under heading 742	0.66	18,630	Other printing machines for uses ancillary to printing	19,170	0.61	Parts, nes of the machines falling within headings 7435 and 7436	0.60	21,957	Industrial and laboratory furnaces and ovens, etc., parts, nes
Parts, nes of pumps and liquids elevators falling under heading 742	0.66	18,630	Other printing machines for uses ancillary to printing	19,170	0.61	Parts, nes of the machines falling within headings 7435 and 7436	0.61	20,740	Work holders, dividing heads for machine-tools, etc.; tool holders	21,957	0.61	Industrial and laboratory furnaces and ovens, etc., parts, nes
Aldehyde, ketone and quinone-function compounds	0.66	17,691	Phenols and phenol-alcohol and their halogenated derivatives
INDONESIA
Craft paper and paperboard, in rolls or sheets	0.70	17,070	Chemical wood pulp, sulphite
Paper and paperboard, in rolls or sheets, nes	0.65	17,070	Chemical wood pulp, sulphite
MALAYSIA
Sound recording tape, discs	0.63	22,343	Instruments and apparatus for physical or chemical analysis
Off-line data processing equipment, nes	0.64	17,568	Complete digital central processing units
PHILIPPINES
Other parts and accessories, for vehicles of headings 722, 781–783	0.60	17,121	Taps, cocks, valves for pipes, tanks, etc.
Other parts and accessories, for vehicles of headings 722, 781–783	0.61	16,285	Transmission shafts, cranks, bearing housing
Other parts and accessories, for vehicles of headings 722, 781–783	0.63	14,840	Bodies for the motor vehicles of 722/781/782/783
Other parts and accessories, for vehicles of headings 722, 781–783	0.60	14,661	Lifting, handling and loading machines and conveyors	17,121	0.63	Cocks, valves, pipes, boiler shells and similar appliances, etc.	0.65	17,332	Abrasive powder or grain, on a base of woven fabrics
THAILAND
Silicones	0.75	20,644	Printing ink
Other condensation, polycondensation or polyaddition products	0.61	20,547	Epoxide resins
Piston engines parts, nes, falling in headings 7132, 7133 and 7138	0.61	17,332	Natural or artificial abrasive powder or grain
Paper and paperboard, in rolls or sheets, nes	0.65	17,070	Chemical wood pulp, sulphite	17,693	0.65	Newsprint
Automotive electrical equipment and parts thereof, nes	0.61	16,285	Transmission shafts, cranks, bearing housing

Note: This table identifies directions for export diversification and contains the 2006 exports (product i) that have significant export shares (at least 3%) and the sophisticated products j close to it at ϕ_ij ≥ 0.60. The products j under the columns in various rounds are goods with PRODY_j > PRODY_i and require less alteration in the production structure compared to products j at ϕ_ij ≥ 0.55 in Table 2. This essentially shows the potential of the countries’ existing and major exports to evolve into highly sophisticated goods if the countries opted for less modification in their production structure. nes: not elsewhere specified. The 3- or 4-digit numbers as part of the commodity description pertains to the commodity codes in the SITC Comtrade data.

Results indicate that using the existing export baskets as the starting point, the less-developed Asian economies may, with proper policies or incentives, produce high value-added goods. However, the diversification portfolios of these economies are limited when they institute lesser modifications in their production structure. This can happen when the state fails to provide an enabling environment for adaptation and innovation so that firms are limited in their vertical and horizontal integration efforts. This hampers the ability of the country to push itself into the development frontier. Korea and Singapore, owing to their efforts to translate the opportunities for backward and forward linkages presented by the production networks that proliferated in the region in the1960s, currently have a bigger export base that is close to many sophisticated products. China, despite its dual trade approach to industrialization, also has a wide array of existing exports that can lead to sophisticated goods.

While the gains from the production networks in the region have been realized by Korea, Singapore and China, the less-developed economies have yet to reap the benefits in terms of technological adaptation and innovation. Outsourcing firms from the developed economies are aware that the technological resources within Asia are heterogeneous so that high value-added production will be typically fielded out to high-skilled economies such as Malaysia, Korea and Singapore. In the semiconductor chain, jobs outsourced to the Philippines and Indonesia are low-end portions of the value chain that need no new technology such as testing and assembly. This is a reflection of the countries’ weak technological capabilities (Castillo, 2005) and may limit the potential diversification and backward linkaging in electronics to more sophisticated chips and circuits.

Finally, the “rounds” used above warrant a short discussion. While this may appear as a simulation exercise only, historical evidence would show that the economic development of some countries reflects the accumulation of production capabilities that has followed a deliberate search process. China’s economic success, for example, can be traced back to their conscious efforts to become an industrialized nation. China started out using export processing zones as a key strategy to learn from foreign firms in the advanced countries (Zhang and Song, 2000). As early as the 1950s, it had instituted capital and industrial expansions. This has led to China’s steel and electric production and, in the 1960s, to higher value-added goods. By the 1980s it already had a comparative advantage on a number of machinery commodities in the denser region of the product space. Clearly, China’s position in the world economy today did not happen overnight. Rather, it has been defined by a target achieved through deliberate efforts such as industrialization and open-economy policies to acquire and accumulate physical and human skills. In this context, the “rounds” can be viewed as the paths that have taken China to high value-added goods given their conscious efforts of cumulative technological and institutional learning.

The role of the government

How countries technologically upgrade to nearby products is a controversial matter. Some would suggest that comparative advantage theory is enough to allow the markets and the private sector to effect the structural transformation, while Schumpeterians would emphasize the role of innovators and entrepreneurs in the specific country. Hausmann views the process as a combination of the Schumpeterian process and market failures (Hausman and Rodrik, 2003).⁶

Hausmann et al. (2005) tackle two types of market failures that entail government intervention. One type would be the first-mover or “cost discovery” problem, where high technology and economies-of-scale industries are not entered into because the first-mover (the Schumpeterian innovator) takes up the entire risk of the innovation but shares profits with other firms if it succeeds since the other firms will just imitate or replicate the first-mover’s innovation, and dissipate his reward or profits. Another type of market failure would be coordination failure problems where upscale products with high value added are not produced because the required adjustments to the technology, input requirements, infrastructure and legal and social institutions are not in place, and the simultaneous attainment of these adjustments are not attempted by anybody. Both market failures require government interventions. Hausmann and Rodrik (2003) join the endogenous growth models where positive externalities pose market failure problems for developing economies. This is one of the most plausible explanations of why the Philippines remains underdeveloped even though it has similar paths to product upgrade to the other countries. It failed to provide incentives for the Schumpeterian innovators. This is reflected on the Philippines’ low rating in the Global Competitiveness Report 2010–2011 (World Economic Forum, 2010) as a result of bad governance.

The role of the government in the context of regional production networks has been discussed in Borrus et al. (2000). Murphy et al. (1989) have also recognized the government’s role for the small and less-developed economy to make a big push towards industrialization.

Based on the results above, we cite some areas that may call for governmental action. (1) The government should attract the right investments by providing the correct investment climate. Stemming corruption, eliminating excessive bureaucracy and developing physical infrastructures are three such examples. (2) The government should strengthen its human capital by strengthening the link between the academe and industry. Once the correct investments are in place, a large number of local firms should be able to replicate the production of goods and then innovate into a wider range of high value-added products. This will push the economy’s development frontier. This has been done by Korea and Singapore through backward and forward integration early on.

The results clearly show that while relatively limited, there are paths towards structural and industrial transformation for the less-developed Asian economies. However, diversification to sophisticated goods does not naturally happen. It can only occur when the production requisites are satisfied, emphasizing the role of the government to provide enabling environments so that the positive externalities and opportunities brought about by trade, production networks and economic cooperation within the region can be exploited by local firms. Developing economies can look into institutional changes, the development of human and physical infrastructures and investment into research and development. Improvement in these areas comes at a cost and may take some time, but will prove to be beneficial when done. As the results have shown, there are opportunities for Indonesia, the Philippines and Thailand to produce sophisticated exports in the future, provided they have the correct policies to make a bigger push towards product upgrades.

Summary and conclusions

Using the product space and the metrics for export sophistication, results indicate that while the current export basket of the less-developed Asian countries is still in the less-connected parts of the product space, opportunities for diversification exist. There are paths from their existing export portfolios that lead the countries to the richer region of product space. For moderately close products, the countries can branch out – assuming the right ingredients of technology, productivity enhancement, infrastructure and institutions – into quite sophisticated products. The possibilities of diversification into more sophisticated products in the long-run are limited if these economies choose to branch out to goods that do not require as much modification in their production structure. This emphasizes the need for the countries’ governments to take a more active role in promoting more appropriate industrial and economic policies for the country.

The research has identified some existing exports that can lead to the richer area of product space. This should not be misconstrued as recommending that the countries focus only on these commodities. Rather, this research is geared towards the assessment of where the countries are in terms of their achievements in their structural transformation efforts and to evaluate the opportunities available to them for economic growth. It carries the positive message that although limited in product scope, there are prospects for Asian countries to converge to the export sophistication level of the developed Asian economies. Export upgrading and structural transformation are key elements in the pursuit of an ASEAN Economic Community. ASEAN is currently composed of industrialized and developing economies. In order to pursue a single market and production base, the export commodities of each ASEAN member should be competitive within the region and in the global setting.

It is the objective of this research to provide information by narrowing down the search for viable options in the immediate future. Ultimately, collective efforts within each country and among Asian countries will most likely be needed to achieve the goal of export upgrading and structural transformation.

Footnotes

Acknowledgements

The authors would like to acknowledge the ADMU-SOSS research load program.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Notes

Author biographies

Connie Bayudan-Dacuycuy is an assistant professor in the Economics Department at the Ateneo de Manila University. Prior to joining the academe, she worked as a supervising research specialist in the Philippine Institute for Development Studies and as a consultant in the Asian Development Bank.

Joseph Anthony Y Lim is a professor in the Economics Department at the Ateneo de Manila University. Prior to joining Ateneo, he was a professor at the University of the Philippines. He also worked as policy adviser on Debt and External Finance for Developing Countries in United Nations Development Programme (UNDP) in New York.

References

Acemoglu

Robinson

(2000) Political losers as a barrier to economic development. The American Economic Review 90(2): 126–130.

Balassa

(1965) Trade liberalisation and revealed comparative advantage. The Manchester School and Social Studies 33: 99–123.

Borrus

Ernst

Haggard

(2000) Introduction: Cross-border production networks and the industrial integration of the Asia-Pacific region. pp. 1-30. In: Borrus

Ernst

Haggard

(eds) International Production Networks: Riches or Rivalry? London: Routledge.

Castillo

(2005) Regional production networks and implications on trade and investment policies, and regional cooperation: The case of the Philippines. De La Salle University–Angelo King Institute Research Paper, Manila.

Crespo

Worz

(2005) On export composition and growth. Review of World Economy 141: 33–49.

Dodaro

(1991) Comparative advantage, trade and growth: Export-led growth revisited. World Development 19: 1153–1165.

Fontagne

Gaulier

Zignago

(2008) Specialization across varieties and North-South competition. Economic Policy 23(53): 51–91.

Hausmann

Klinger

(2006) Structural transformation and patterns of comparative advantage in the product space. Center for International Development Working Paper No. 128, Harvard University.

Hausmann

Klinger

(2008) Achieving export-led growth in Colombia. Center for International Development Working Paper No. 182, Harvard University.

10.

Hausmann

Rodrik

(2003) Economic development as self discovery. Journal of Development Economics 72: 603–633.

11.

Hausmann

Hwang

Rodrik

(2005) What you export matters. Center for International Development Working Paper No. 123, Harvard University.

12.

Hidalgo

Klinger

Barabasi

. (2007) The product space conditions the development of nations. Science 317: 482–487.

13.

Hirschman

(1958) The Strategy of Economic Development. New Haven, Connecticut: Yale University Press.

14.

Jaffe

Trajtenberg

Henderson

(1993) Geographic localization of knowledge spillovers as evidenced by patent citations. Quarterly Journal of Economics 108: 577–598.

15.

Leamer

(1984) Sources of Comparative Advantage: Theory and Evidence. Cambridge, Mass.: MIT Press.

16.

Murphy

Shleifer

Vishny

(1989) Industrialization and the big push. The Journal of Political Economy 97: 1003–1026.

17.

Przeworski

Limongi

(1993) Political regimes and economic growth. Journal of Economic Perspectives 7(3): 51–69.

18.

World Economic Forum (2010) Global Competitiveness Report 2010–2011. Geneva, Switzerland: World Economic Forum.

19.

Zhang

Song

(2000) Promoting exports: The role of inward FDI in China. China Economic Review 11: 385–396.