Product Space Perspective on Structural Change in Morocco

1 Introduction

On what sectors will Morocco’s future export growth be based? What are the implications of Morocco’s current export structure for future structural transformation? This paper tries to shed some light on these issues by means of a detailed analysis of the evolution of Morocco’s structure of goods exports since 1990 and the implications of these developments for the future sector priorities. In terms of method, we rely on product space (PS) analysis, pioneered by Hausmann and Klinger (2006).

The paper is organized as follows: Section 2 provides a brief introduction to the basic features of the PS framework. Section 3 elaborates on the PS methodology and the PS concepts used in this paper, including a discussion of how its design and data limitations point to the need to complement it with analysis using other approaches. Section 4 presents the results of our PS analysis for Morocco. Appendix presents complementary PS statistics for Morocco. ^[1]

On a cautionary note, the findings presented in this paper are preliminary since they have not yet benefitted from discussions with local experts and policy makers – they are exclusively derived from empirical analysis of international trade data.

2 Basic Features of the Product Space Framework

The process of structural change, experienced by developing countries as they move up in the development spectrum, may be seen as characterized by two phenomena that come hand in hand. The first is economic diversification (Imbs and Wacziarg 2003). Empirical evidence suggests that non-agricultural activities in poor, stagnant, and underdeveloped economies are concentrated in a small number of sectors that tend to be very low-value added and geographically concentrated. Over time, as economic growth accelerates, a wider range of capacities are created, permitting the production of a wider range of goods and services. As a result, non-agricultural production starts to become more diversified, both in terms of sector structure and geographical location. Given this fairly regular pattern, economic diversification is recognized as an intrinsic part of sustained economic growth, leading to the pursuit of policies that promote diversification in growth strategies, especially for low-income countries (Commission on Growth and Development 2008).

A second phenomenon that appears during the process of structural change is an increase in the complexity of the economic system, in other words, an increase in the human capacity to produce goods and services that are technologically more sophisticated and that satisfy a larger variety of needs. As part of this second phenomenon, the economy starts to employ new production inputs coming from different sources: discovered or created locally, or brought in via foreign trade; and firms advance their capacity to integrate these inputs more efficiently or at a larger scale. The production inputs that matter do not only include standard production factors (such as labor, land, physical and human capital) and public goods (including physical infrastructure and institutional frameworks), but also various less tangible inputs as leadership, trust, values, or work ethic. Over time, surviving firms, both large and small, are prompted to become more strongly integrated into larger production networks (without necessarily being aware of this) (Hausmann et al. 2013).

In order to recognize these two phenomena, the PS framework proposes a view of economic production that complements the standard neoclassical approach. Products and services are conceptualized, not only in terms of physical attributes or monetary values, but also in relation to knowledge: they are made of knowledge and they are also vehicles for knowledge. The underlying assumption is that the embedment of knowledge in products and services requires people who possess certain related capabilities. The standard economic view is that the stock of knowledge in a society is the sum of all capabilities that individuals possess meaning that the greater the set of capabilities of an individual, the larger the number of products and services that this individual can generate. ^[2] The complementary view of the PS approach is that the amount of knowledge embedded in a society does not mainly depend on how much knowledge each individual holds, but on the diversity of knowledge across individuals and on their ability to use and combine this knowledge through a complex web of interactions: markets and organizations allow the knowledge that is held by the few to reach the many – in other words, division of labor and difference in tastes and consumption patterns together generate and allow us to access a quantity of knowledge that none of us would be able to hold individually. The PS approach holds that the composition of produced goods and services mirrors the underlying structures that possess and combine this knowledge, and that this composition is not well captured by standard aggregate economic indicators.

The ease with which the knowledge embedded in available production inputs can be transferred and recombined is a major determinant of the ability of producers to offer a larger and more complex set of goods and services (associated with higher productivity levels). The ease with which an input can be moved between two products depends on their degree of commonality; for example, it is easier to move inputs from wheat to barley than from wheat to microchips, simply because of the presence of a larger set of commonalities between two agricultural products than between an agricultural product and an electronic manufacture. In a conceptual straight line that draws the distance between these three products, the distance between the two agricultural products (wheat and barley) is smaller (their proximity is larger) than the distance between agricultural product and the electronic manufacture (microchip). It is possible to add more products to wheat’s straight line of distances. The distance lines of barley and microchips can similarly be generated, linking each product to all other products. The result of this complex web of production interactions can be represented in a network based on proximity data.

In this context, Hausmann and Klinger (2006) propose a measure of proximity that is based on observed patterns of diversification across countries. More specifically, they use the concept of conditional probabilities of co-exporting pairs of products as the building block in the construction of a square matrix of proximities for all products according to a comprehensive classification. Global trade data is used in the definition of proximities due to the lack of comparable global production statistics for goods (or services). ^[3]Hausmann and Klinger (2006) also propose concepts from network theory for the analysis of this matrix of proximities. Among other things, using a minimum-spanning tree algorithm with proximities across all products in the global trade database, they construct a product-space map that clusters products into categories with similar production inputs. They show that products exported by stagnant countries tend to be isolated, located in the sparsest and less connected parts of the PS map, while products exported by countries with higher long-run GDP growth rates tend to be in the densest part. In the PS framework, this provides initial support to the idea that producers in more dynamic economies have a larger set of capabilities, and that they can use their capabilities and knowledge more freely to recombine available production inputs.

The location of a country’s export mix in PS matters for growth. Hidalgo et al. (2007) and Hidalgo and Hausmann (2009) provide evidence that a country’s position in PS is strongly correlated with its level of GDP per capita. Moreover, they show that there is a large heterogeneity in the distribution of capabilities across countries and that changes in this distribution are not linearly related to future growth. Countries with very few capabilities will experience small diversification gains if just a small number of capabilities are added whereas a country that starts out with many capabilities will experience much larger gains if the same number of capabilities is added. The structure of the PS has important implications for technology spillovers across regions. To exemplify, the probability that a product is added to a country’s export basket is, on average, 65 percent higher if a neighboring country is a successful exporter of that same product (Bahar, Hausmann, and Hidalgo 2012). This technology diffusion is stronger at shorter geographical distances, weaker for more knowledge-intensive products, and accelerating over time.

3 Product Space Methodology and Concepts

The PS method is based on a set of empirical measures that are focused on the relatedness between different products and the income levels that are associated with exporters of individual products. Among these measures, the most central, proximity (with distance as its opposite) was discussed above. In country analyses based on PS concepts, alternative exports baskets may be evaluated. In this context, PS analysis suggests that a country that strives to use exports as a means of accelerating growth should take into account several key aspects. Among other things, such a strategy should consider the dynamics of revealed comparative advantage (RCA) to identify traditional, emerging, and sluggish exporting sectors. In addition, the country should strive to diversify, increasing competitiveness in product categories that are within reach and that offer higher scope for further diversification – using PS terminology, such categories have relatively high values for density and PATH, respectively. Lastly, when assessing different products, it is important to consider their income potential (PRODY; defined on the basis of GDP per capita and the shares of a product in the export baskets of countries with RCA>1 in the product); products with a high PRODY relative to the country’s EXPY (defined on the basis of PRODY data and the product export shares for the country) promise to bring about stronger growth in the country’s GDP per capita. (Definitions of key PS concepts are found in Appendix). ^[4]

In the following analysis of Morocco, the PS methodology is applied in a stepwise process. Drawing on previous World Bank applications, products are categorized according to structural shifts in RCA and ranked according to prospects for further diversification (PATH) and income potential (PRODY). Products with high density, high PATH, and high PRODY are usually the best candidates for diversification, as they combine strong production capability, large scope for further diversification, and high income potential. An increase in the share of products with high PRODY raises the income potential of the country’s export basket (EXPY).

In general, there is a trade-off between products with high density, high PATH, and high PRODY, i. e. between products that are within reach (“low-hanging fruit,” which often means doing things that are only slightly different; the case of high density), products that offer greater diversification potential (often new products that require non-marginal start-up investments; the high PATH category), and products that raise potential income (often those for which it is most difficult to become an efficient producer; products with high PRODY). Empirically, the relationships are often negative between density and PRODY and between density and PATH, but positive between PRODY and PATH. In other words, PS analysis often points to the difficulty of generating a successful development strategy as it tends to show that products that are highly profitable and add to diversification are difficult to reach, while easily reachable products offer limited scope for diversification and growth.

A PS analysis does not provide answers to questions about future export winners for the focus country. However, on the basis of international experience (captured by detailed global trade data), PS analysis helps identify sectors that are attractive considering a country’s capabilities and the potential contributions of different sectors to diversification and income potential. The approach manages to accomplish this at a finely disaggregated sector level thanks to the fact that it is designed to make good use of a rich database for merchandise trade, with annual data and global coverage at the country level. However, it is important to be aware that its design and data constraints together exclude a wide range of issues from the purview of PS analysis. Among other things, PS analysis explains changes in export structure on the basis of sectoral proximities without reference to other issues that clearly matter (for example sectoral policies and human capital) but for which matching global databases do not exist. As a result, it is often advisable to combine or integrate PS analysis with other approaches that address some of these other aspects, albeit with limitations of their own. Such approaches may include expanded historical analysis that highlights the roles of policy and factor endowments in sectoral trade and production growth. In general, when envisaging the future roles of different sectors, it is important to draw on insights from sector experts and policy makers in the context of broader development objectives.

Among the data-related shortcomings of most applications of PS analysis is that they do not address service sectors. In this paper, we try to mitigate this shortcoming by including a discussion of services, albeit not very detailed due to data limitations. Another shortcoming, which in practice probably is less serious, is related to the fact that the ability of different sector indicators to reflect country capabilities is hampered by the presence of high sector-level subsidies in some countries.

4 The Case of Morocco

In this section, the tools of PS analysis are applied to the case of Morocco. The analysis uses detailed export data starting in 1980 and examines patterns of changes in RCA and technology content (Section 4.1), and how the country’s export structure has positioned Morocco in PS and prepared the country for future growth (Section 4.2). Finally, we discuss some important sector priorities (Section 4.3) informed by PS metrics.

4.1 Evolution of Morocco’s Exports in Recent Decades

Figure 1 summarizes the evolution of Morocco’s merchandise exports from 1980–2010, with observations in five-year intervals, according to patterns of RCA shifts. ^[5] As can be seen, the most striking development is the growing share for emerging products, from 2 percent to almost 40 percent. This product category has also affected the technological composition of Morocco’s export basket: a dominant and increasing share is manufactures (increasing from 60 to 90 percent of all emerging products); and, among the manufactures, the largest but only slowly growing share is med- or high-tech manufactures (increasing from 50 to 60 percent; Figure 2).

Figure 1:

Morocco’s merchandise exports 1980–2010 by pattern of RCA shifts.

Figure 2:

Emerging exports in Morocco by technological content.

Growth in emerging exports has been rapid and, during the last fifteen years accelerating. However, it has been driven by a relatively small number of products. In fact, two product categories accounted for half of the observed growth between 1995 and 2010: the first is “Fertilizers, n. e. s.” (SITC 5629) and the second “Insulated and electric wire, cable, bars, etc.” (SITC 7731). One tenth of the observed export growth was due to various small exports, including “Diodes, transistors, photocells, etc.” (SITC 7763) and various export discoveries in the textile industry.

Returning to Figure 1, among non-emerging products, the major change is a decline in classicals (from 83 to 48 percent); in terms of technology, Morocco’s classical products are mostly primary and resource-based or low-tech manufactures. Among the remaining two product categories, disappearing products decline (by 7 percentage points) while marginals increase (by 3 percentage points).

Figure 3 shows the composition of Morocco’s merchandise exports in 2010 – its percent figures add up to 100. As shown, using rounded data, the main four items (accounting for 71 percent) were as follows: garments (25 percent); inorganic salts and acids (21 percent); vegetables, fruits, and fish (15 percent); and electric wire (SITC 7731; 10 percent). Among electronics, “Electronic microcircuits” (SITC 7764) and “Diodes and transistors” (SITC 7763) are the two most important items (a total of 5 percent). Figure 4 shows the evolution of export values 1990–2010 for the world (the global total) and for Morocco for a set of products that are among Morocco’s emerging exports (with the scales for world and Moroccan values on the left and right vertical axes, respectively). In general, it suggests that Morocco’s export growth for these products is not dramatically different from the growth in total world exports (or imports). It also suggests that, inside the Moroccan economy, different sectors are subject to common policy changes and constraints, as a result competing in markets for labor and other factors and responding to changes in exchange rates and other changes in incentives.

Figure 3:

Moroccan merchandise exports in 2010.

Figure 4:

Trends for selected emerging Moroccan exports for Morocco and the world, 1990–2010.

4.2 Exports, GDP Growth, and Morocco’s Position in the Product Space

As noted in Section 3, global export data combined with country data on GDP per capita may be used to define PRODY (a global measure of the income potential of a product) and EXPY (a country-specific measure of income potential based on PRODY and country export data). These concepts are of interest since empirical cross-country analysis indicates that GDP per capita and EXPY are highly correlated – countries with a high GDP per capita tend to have a high EXPY and vice versa – and that increases in EXPY tend to lead to increases in subsequent GDP growth. ^[6] As an illustration of this relationship with reference to Morocco, Figure 5 shows an estimate of the cross-country relationship between country EXPY and GDP per capita in 2010, to make some relevant country detail visible highlighting the positions of Morocco and other textile exporting countries.

Figure 5:

EXPY for Morocco and selected textile exporters (1990–2010).

In addition, Figure 5 shows that movements of Morocco’s EXPY across the GDP per capita space closely follow the estimated cross-country relationship throughout the period 1990–2010 – in other words, the evolution of GDP per capita is consistent with changes in the sophistication of the export basket (marked by an increasing merchandise export shares of products with higher PRODY values), supporting the validity of the PS approach to analyses of growth and trade for Morocco. The obvious implication that follows from this perspective is that, ceteris paribus, for Morocco (or any other country), accelerated growth in the income potential of its export basket would propel stronger GDP growth. A key strategic question is: Can the current structure of exports and its underpinning production structure provide the base for a future rapid structural transformation? In general terms, this increased sophistication of the export basket has not been strong enough to propel GDP growth to rates that exceed those of other middle-income countries.

Figure 6, a map of the PS in 2010 that reflects proximities between products, is relevant to a discussion of issues related to the income potential of country’s exports and how it may change over time. ^[7] The map highlights the positions of Morocco’s classical, emerging and marginal products, reflecting the data on long-term shifts in RCA for Morocco between 1980 and 2010, discussed in Section 4.1 It is evident that most classical exports (in red) and emerging exports (in blue) are located in the periphery of the PS, meaning that their underlying capabilities are not easily transferable to other, perhaps, more sophisticated products; given this, these products offer only a limited diversification potential. By contrast, marginal products (in green) are closer to the core of the PS, which is the densest part. This may mean that Morocco is building the capacities to export these products but that these capacities are not yet mature enough to permit exports in much larger quantities. A closer inspection is needed to evaluate the feasibility of marginal merchandise exports, among other things considering the extent to which they are affected by trade policies, favoring or disfavoring these sectors.

Figure 6:

Morocco’s position in the product space in 2010.

Data on density – a country-, time-, and product-specific measure – provides a perspective that complements that of the PS map by indicating the likelihood that a country will be able to develop an RCA>1 in specific products. More specifically, density is defined on the basis of the proximities of the product to other products in which the country has an RCA>1; i. e. on the basis of the country’s current position in the network, it strives to capture the capability of the country to develop RCAs>1 in other products. Crucially, Hausmann and Klinger (2006) show that products with high density are more likely to gain importance in the export basket, over time developing RCAs>1.

Empirically, there is an overall positive relationship between the PS related measures of income potential (PRODY), and diversification potential (PATH) meaning that, as countries export new products with higher income potential (PRODY), they also develop products that offer larger sets of diversification opportunities in the future (PATH). ^[8] Nevertheless, the higher the income and diversification potential of a product, the more difficult it tends to be for a country to become competitive in that product, a phenomenon that is reflected in a lower value of density. The pattern that we observe for Morocco is similar to that observed in other developing countries: traditional exports, or classics, have less income potential (low PRODY) and offer lesser opportunities for further diversification (low PATH) than emerging and marginal products; however, the latter are more difficult to develop and scale-up, as reflected in their lower density values (Table 1).

Table 1:

Product space measures for merchandise exports in Morocco.

Product classification	Number of products	Exports, % of total	Average PRODY	Average Path	Average density
Classics	46	51.7	9,641	114	0.263
Emerging	49	36.7	10,607	129	0.237
Disappearing	22	1.1	8,684	110	0.215
Marginals	93	3.4	16,060	150	0.183

^[9]

The relationship between potential income gain (ln PRODY – ln EXPY) and lack of capability (1/density) for Morocco’s goods exports in 2010 is shown in Figures 7 and 8 below. Products above (below) the zero line on the vertical axis have a higher (lower) potential income than the average for Morocco’s 2010 export basket of goods (measured by EXPY). The higher the value for a product along the horizontal axis, the lower the capability of Morocco to develop an RCA > 1 in the product. As expected, the upward-sloping relationship in both figures indicates that the larger the potential income gain, the more severe the lack in the capabilities needed for competitive production. Interestingly, compared to classical and emerging products, marginal products show a stronger potential income gain and a more severe lack of capabilities (Figure 7). Figure 8, which scales the size of product bubbles by export values, shows that a subset of the emerging products and most marginal products have a PRODY well above Morocco’s EXPY while the opposite holds for the bulk of classical products; as a result of small export values, the bubbles for the marginal products are indeed very small. In sum, Figures 7 and 8 both suggest that the marginal products offer payoffs that may be worth exploring. ^[9]

Figure 7:

PRODY. EXPY, density, and export goods for Morocco in 2010.

Figure 8:

PRODY, EXPY, density and export values for Morocco, 2010.

Figure 9 is similar to Figure 7, except that the products are aggregated to the I-digit level, which may be viewed as representing industrial clusters. For some purposes, information at this higher level of aggregation may be more relevant for policy – discrimination in favor of sectors at a very fine level of disaggregation may be inefficient and require more knowledge than typically possessed by policy makers. Aggregation does not alter the positive relationship between potential income gain and lack of capabilities.

In addition to PRODY, EXPY, and density, it may be important to consider and bring the concept PATH into the analysis when possible options for diversification are considered. For example, for “Animal and vegetable oils, fats and waxes” (in Figure 9 labeled “Anim-oils”), Morocco’s potential income gain is high relative to other products with a similar density. Under this heading, the main disaggregated products are “Fat and oils of fish and marine mammals” (4111) and “Olive oil” (4235), both of which have relatively high density and PRODY values (like their aggregate). However, these two products have very low values for PATH (84 and 81, respectively), indicating that it is not likely that they will pave the way for further growth-promoting diversification. ^[10] By contrast, major exports under “Food” and “Miscellaneous manufactured articles” (including apparel and clothing) with comparable levels of density offer larger diversification potential but only moderate direct income gains (i. e., income gains in the absence of such diversification). ^[11] This suggests that countries may face (and policy makers may have to consider) trade-offs between more immediate and more distant gains in GDP and income growth.

Figure 9:

PRODY, EXPY, and density in Morocco at the 1-digit level, 2010.

Favorable PS measures do not implicate the absence of fierce competition in global markets. For instance, product 8424 “Men’s jackets” has relatively high-density, high PATH, and one of the largest income potentials among Morocco’s clothing and apparel export categories; however, Morocco has only a limited share (1.8 %) of a global market that is dominated by China (37 %) and Italy (11 %).

4.3 Product-Level Diagnostic

4.3.1 Phosphates

Some specific products may be important for Morocco’s future export strategy, including phosphates, electronic components, and the auto-industry. Phosphate, used as fertilizer, is an irreplaceable input that powers modern agriculture, and its reserves are in decline almost everywhere except Morocco. According to estimates (Schröder et al. 2010), Morocco possesses 37 percent of the global economic phosphorus reserves, suggesting that its market may be a quasi-monopoly. A growing gap between phosphorus supply and demand in the coming decades is expected in the absence of large-scale implementation of innovative phosphorus efficiency methods and recovery systems. In 2012, world prices of fertilizers were 250 percent above their 2005 level, reflecting these growing pressures (see Figure 10). Large windfalls of phosphate revenues might serve to alleviate many economic problems; however, Morocco needs to address the dangers of over-dependence and mismanagement of its mineral resources, not only because the well-known risk of Dutch disease, but also because of the risks of corruption and state capture.

Figure 10:

World price of fertilizers, 2005=100.

In terms of the PS measures, “Fertilizers” and “Phosphatic Fertilizers” (SITC 5629 and 5622) have some of the lowest PCI values (rank 564 and 648 respectively), reflecting their extractive nature and the few forward-linkages that they can generate. Density is high but the PRODY values of these two products are low, suggesting that it is difficult for Morocco to aspire to become an upper-middle income country if it is focused on fertilizer extraction. (The PATH values are 137 for SITC 5629 and 97 for SITC 5622).

4.3.2 Electronics

Some exports related to the assembly of electronic components have gained importance in Morocco. In “Diodes and transistors” (SITC 7763), “Switchboards and relays” (SITC 7721) “Electronic microcircuits” (SITC 7764), and “Electric wire” (SITC 7731) – with complexity-index rankings of 86, 120, 125, and 464 respectively – Morocco has attracted important R&D investments in the last decade: SQLI (France) set up an R&D platform in the country in 2003 Eolane Electronics Manufacturing Services (France) opened an R&D center in 2004 next to its manufacturing and distribution unit; STMicroelectronics has had a chip design Centre in Casablanca since 2000; and Gespac Maroc Usine Novatech, which is present in the city of Temara since 2001, manufactures electric wiring for aviation equipment. Nevertheless, Morocco is still considered an extension to Europe’s industrial capacities and it is still an open question whether the country can be upgraded to become a significant manufacturing center, especially given fierce competition, both from large emerging economies (such as India, China, and Brazil) and regional competitors (such as Egypt, Lebanon, and Tunisia). Moreover, Morocco’s density in these export categories is not particularly high.

4.3.3 Auto Industry

In the automotive industry, the Renault group is the largest firm on the Moroccan market, with a market share of 37 percent in 2011; among its brands, Dacia and Renault rank first and second, with market shares of 20 and 17 percent, respectively. In 2011, vehicle sales in Morocco topped the 112,000 mark. The number of cars on the road is estimated at 1.5 million, with an average age of 9–10 years. Although limited, the Moroccan automotive market is growing strongly. Morocco has only one car plant in Casablanca and seeks to develop its car industry further with the Renault Group, which is exempt from both corporate and export taxes up to 2017. The Renault mega project, which consists of a 1 billion euro investment in a 300-hectare plant located 30 kilometers from the new Tanger-Med port, will reach a production capacity of up to 170,000 vehicles per year at first and is expected to generate 6,000 direct jobs and some 30,000 indirect jobs in the northern region of Morocco. Moreover, in the automotive area, the country might serve as an important hub for the North-Africa corridor as well as Southern Europe. Nevertheless, Morocco’s density in the auto-industry is still weak (density = 0.122) in comparison with other countries in the Middle East and North Africa Region, such as Egypt (density=0.202) or Tunisia (density=0.157) (Figure 11).

Figure 11:

Density in the auto-industry in selected countries. Source: Authors’ calculations using UN-Comtrade Data.

4.3.4 Service Sector

Finally, as noted earlier, service exports has gained importance in Morocco’s total exports as their share has increased by an annual average of 0.55 percentage points since 1980. During the period 2006–2010, service exports accounted for 44 percent of total exports. Not only have they gained importance, but their composition has also become more balanced. While “Personal travel services” is still the single most important service category – representing USD$6.7 billion in 2010 – their importance has diminished, passing from two thirds to one half of the total between 1995 and 2010. More recently, Air and Sea transport services have gained momentum, reflecting Morocco’s increasing importance as a regional hub in North Africa for shipping logistics, assembly, production and sales. Similarly, “Miscellaneous business, professional, and technical services,” and Telecom now add up to close to 20 percent of Morocco’s service exports (Table 2). This shift in service exports is positioning Morocco with a more balance service export basket than the average country in Middle East and North Africa or compared to what is typical among lower-middle-income countries. In part, this outcome reflects successful efforts to attract foreign investments in key sectors.

Table 2:

Service exports in Morocco.

	% of total service exports				Billions of Current USD
	1995	2000	2005	2010	1995	2000	2005	2010
Personal travel	66.9	66.5	56.3	52.2	1.3	2.0	4.6	6.7
Air transport	8.9	8.0	9.7	11.1	0.2	0.2	0.8	1.4
Misc. business, prof., and tech.	11.8	5.3	15.2	15.0	0.2	0.2	1.2	1.9
Telecom services	0.0	3.7	4.0	5.5	0.0	0.1	0.3	0.7
Sea transport	11.5	6.8	5.2	3.3	0.2	0.2	0.4	0.4
Other private services	0.8	3.7	3.1	9.8	0.0	0.1	0.3	1.3
Government services	0.0	5.9	6.5	3.2	0.0	0.2	0.5	0.4
Total	100.0	100.0	100.0	100.0	1.9	3.1	8.2	12.8

^[13]

5 Conclusion

This paper analyzes the evolution of Morocco’s structure of goods exports and its implications for future structural change. The conclusions of this paper are exclusively derived from empirical evidence from international trade patterns. In sum, the analysis finds that, in recent decades, Morocco has developed a revealed comparative advantage (RCA>1) for a set of rapidly growing medium- and high-tech products, in 2010 representing around 40 percent of total merchandise exports. While these developments are encouraging, a relatively small number of products accounts for most of the growth, making the country quite vulnerable to external shocks. Moreover, whatever its contribution may have been, this export transformation has not been sufficient to raise per capita growth to the average level for middle-income countries.

To date, Morocco’s capabilities are primarily in products with a relatively low income potential. Morocco’s GDP level and growth in the last decade closely match what would have been predicted in light of the evolution of the income potential of its merchandise export basket. In terms of the underlying network of production, Morocco’s structure is such that diversification into more sophisticated products still remains difficult. Overall, there is a trade-off between sectors that are within reach and sectors that offer higher potential gains in income or diversification.

Considering Morocco’s natural resources and PS indicators based on its current exports, at a disaggregated level, phosphate-based fertilizers are likely to grow rapidly. Considering their low income-potential (measured by their PRODY), their position in the periphery of the PS, and potential Dutch disease effects, strong reliance on fertilizers may have serious drawbacks unless the foreign exchange earnings that they generate are used in ways that promote growth in other sectors. Among other products, it may be important to consider electronics and the automotive industry; Morocco has established a foothold in both. However, the difficulties are greater – Morocco’s capabilities are still fairly low and international competition is fierce.

At a more aggregate level, which may be viewed as representing industrial clusters, edible oil products (like olive oil) may offer relatively immediate income gains but limited diversification potential. However, in the long run, various other manufactured products, including both products that are related and unrelated to Morocco’s primary sectors, may offer paths toward stronger diversification and income growth. Finally, it is important to note that, in recent times, Morocco’s service exports have grown rapidly and become more diversified; they may offer attractive areas for future expansion.