Structural transformation is a development process where a country moves from simple low-cost goods to more complex, expensive ones. In standard trade theory, the change in the export basket is a passive consequence of changing factor endowments and does not require policy modifications or additions. However, this may not be the case in reality as market failures, technological spillovers, industry and information externalities are present.
This paper argues that producing new products is different from producing more of the same. Every product requires specific inputs to the firm. Established industries somehow have already addressed the potential failures involved in acquiring these inputs. However, firms that venture into new industries will find it harder to obtain the required inputs.
The assets and capabilities needed to produce one good are imperfect substitutes for those needed to produce another good. This degree of asset specificity will vary. Hence, the speed of structural transformation will depend on the density of the product space near the area where each country has developed its productive capabilities. In theory, the space may be either homogenous or heterogeneous with highly dense areas in some parts and scarce in others.
A new outcomes-based measure of similarity between products is proposed in this paper, gauging the distance between each pair of products based on the probability that countries in the world export both products. The proximity or distance between products is also observed in this study to be heterogeneous.
One metaphor that can help illustrate this observation is that products are like trees that can be planted close together or far apart, depending on the similarity of the required capabilities and firms are like monkeys, who derive their livelihood from the trees. The forest is the product space. Structural transformation is like having monkeys jump from the poorer part of the forest to the richer part. But success will depend on the productivity of the trees and how close the trees are to each other. In this illustration, proximity is related to the usefulness of the specific assets the country has for the production of the new good. As for the productivity of the tree, Hausmann, Hwang and Rodrik (2006) measured the income per capita of the product based on the income per capita of countries with comparative advantage in that product and they called it PRODY.
This paper is related to several studies of growth in developing countries. But unlike prior studies, the assumption here is that the product space is heterogeneous. This study is closest to that of Jovanovic and Nyarko (1996) who stated that improvements in an existing product (vertical shifts) improve productivity but shifts to different products (horizontal shifts) are required since gains are limited in vertical shifts. They focused more on improvements within products while this paper concentrated on the varying distances between goods. The relevant dimension here is how assets, capabilities and opportunities of a particular good affect the productivity of another good in addition the teaching of standard trade theory that a country develops comparative advantage in two goods if their required production endowments are similar.
A Model of Structural Transformation and the Product Space
The set required for production is unique for each good. But even so, substitutability is still possible. Goods that require relatively similar inputs are said to be “closer” together, while those that require different capabilities are said to be “farther” apart. Producing a new good will require a fixed cost that is higher than the cost required for producing the existing standard good. The cost rises relative to the distance between the two good as it is more costly to move the goods where the capabilities required are totally different. Usually, the firm only moves to the new good if its returns are higher from the returns of the standard one. An intra-industry spillover occurs when a firm moving to a new good does not internalize the benefits it creates for subsequent entrants in that industry. Moreover, an inter-industry spillover occurs when this model is extended to three (or more) goods.
Stagnation occurs in the process of structural transformation when firms opt not to innovate because there are no goods at the right distance that are sufficiently attractive to pay for the adjustment costs. With this in mind, it can be deduced that the process of structural transformation depends on the distance, the cost of jumping, and the degree to which the price of the new good exceeds the current goods. The process of structural transformation could also be interrupted if firms would not have the incentive to move out of their location because nearby goods fetch a lower price than the current good and the upscale goods are too far away.
Data & Methodology
The methodological challenge is to develop an empirical measure of distance in order to map the product space. To develop this measure the product-level data of exports is used. For a country to have revealed comparative advantage, the good must have the right endowments and capabilities to produce it and export it successfully. If two goods need the same capabilities, this should show up in a higher probability[1] of a country having comparative advantage in both.
The primary source of the data is the World Trade Flows data from Feenstra et. al. (2005). The data reveals that the densest part of the forest tends to be dominated by manufactured products while the sparsest goods tend to be unprocessed agricultural goods. An analysis of the proximity matrix, the representation of the product space, shows that for each commodity cluster, the average proximity is higher within commodity clusters than between them. This simple analysis of the products space masks heterogeneity.
Proximity and the Speed of Structural Transformation
The probability that a country will acquire comparative advantage in a particular good is associated with the density of the country’s current production relative to that good. The probability of monkeys jumping to an available tree depends on the closeness between the current location of the monkeys and the good in question and to the exclusive character of the good measured by the relationship between the income level of the product[2] (PRODY) and the level of sophistication of a country’s export basket[3] (EXPY) of the country. Controlling for unobserved country and product characteristics as well as other variables such as the level of development of the country, it is found that density, PRODY and EXPY have strong effects on the probability of developing comparative advantage in the good.
The Product Space & Country Level Export Sophistication
The differences in structural transformation relative to the characteristics of the product space and structural transformation at the country level is examined by testing if the increase in the level of sophistication or the income level implicit in a country’s exports is affected by the opportunities that the current productive structure provides relative to its location in the product space.
The data is aggregated to the national level to study whether the structure of the product space and the current pattern of specialization affect the speed of structural transformation. A measure of the value of the unoccupied product space was developed for each country where the distance between the country’s current areas of comparative advantage and each potential product are taken account of. The resulting variable is called “open forest”. Even if wealthier countries tend to be in a denser part of the forest as compared to poorer countries, this variable is observed to be different for each country. Some countries are in a sparsely populated part of the forest, while other countries are in a much more densely populated section of the forest. This variable strongly predicts the speed of structural transformation measured by the growth in the level of sophistication of exports.
Implications of the Analysis
The heterogeneity of the product space has several consequences. The speed at which countries can transform their productive structure and upgrade their exports depends on the existence of a path of nearby goods that have significant higher values. The fact that countries differ in this dimension explains why growth performance across the world is very different. Some countries are specialized in goods that require assets and skills that are very specific to that product and do not prepare the country to move onto other goods. For example, oil exporting countries have an unusually low ‘open forest’. Oil requires very specific endowments and this does not easily prepare a country to produce other goods. By contrast, light manufactures, electronics and capital goods tend to involve skills and assets that are much closer to those required by other goods and support the transition from one product to another.
This creates two types of externalities. It creates an intra-industry spillover if a country develops comparative advantage in a certain good and many firms can enter to it. Inter-industry spillovers are also produced since these capabilities now shorten the distance to other goods.
It is unlikely that markets under perfect competition would internalize these spillovers especially in those countries with comparative advantage located in the sparse part of the forest space. This sheds a different light to the principles of development economics. The belief that industrialization created externalities and that it could lead to accelerated growth can be interpreted not as being related to forward and backward linkages (Hirschman, 1957) or complementarities in investment requiring a ‘big push’ (Rosenstein-Rodan, 1943) but in terms of the greater flexibility with which the accumulated assets and capabilities could be redeployed.
The work in this paper can be further extended to do the following:
· Integrate the analysis of changes across products and quality improvements within products, measured by the changes in the export unit values at the product level.
· Study the evolution of the distance matrix over time.
· Analyze the role of economic policy and industrial organization in achieving structural transformation.
· Enhance the proximity matrix using the tools of network analysis.
Source:
Hausmann, Ricardo and Bailey Klinger, “Structural Transformation and Patterns of Comparative Advantage in the Product Space” CID Working Paper No. 128 (August 2006).
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