Product-level trade data from the Atlas of Economic Complexity, examining Italy's export structure, comparative advantages, and diversification opportunities across 1,241 products and 9 sectors (1995–2022). Part of a broader growth diagnostic for PP413 at the LSE School of Public Policy.
The analysis draws on the economic complexity framework developed by Hidalgo and Hausmann, which measures a country’s productive capabilities through the sophistication and diversity of its exports. Rather than treating all export revenue equally, this framework distinguishes between products that require advanced knowledge, institutional capacity, and specialised inputs (pharmaceuticals, precision instruments, turbines) and those that do not (raw materials, simple manufactures). Countries that export many complex products tend to have higher incomes and faster growth.
Four metrics structure the analysis. Revealed Comparative Advantage (RCA) compares Italy’s share of a product in its own export basket to that product’s share in world trade; an RCA above 1.0 means Italy exports proportionally more of that product than the global average. Product Complexity Index (PCI) ranks each product by how many countries can competitively produce it and how diversified those countries are; higher PCI indicates rarer, more sophisticated capabilities. Distance measures how far a product sits from Italy’s current export basket in the product space. Complexity Outlook Gain (COG) estimates the improvement in a country’s overall complexity position if it were to develop a comparative advantage in a given product.
The source data is the Harvard Growth Lab’s Atlas of Economic Complexity dataset, covering bilateral trade flows at the HS-92 4-digit product level. The pipeline computes product-level and sector-level metrics for 2022 and time-series trends from 1995 to 2022 using 5-year rolling averages. Products are grouped into nine sectors: Agriculture, Chemicals, Electronics, Machinery, Metals, Minerals, Stone, Textiles, and Vehicles.
Italy’s ten largest exports by value immediately reveal a tension at the core of its trade profile. The list mixes high-complexity manufactured goods (packaged pharmaceuticals at $33B, thermostat valves at $8.3B with a PCI of 1.42, vehicle parts at $14B) with products that require far less sophisticated capabilities (trunks and leather goods at $10.7B, precious jewellery at $9.5B, leather shoes at $8.2B). Italy generates large revenues from both ends of the complexity spectrum, but the lower end contributes a disproportionate share.
The sector-level view makes this clearer. Machinery is Italy’s largest sector ($123B) and its most complex (weighted PCI of 1.12). But the next three sectors by size, Chemicals ($112B), Agriculture ($92B), and Textiles ($69B), average PCIs of 0.71, −0.54, and −0.43 respectively. Agriculture and Textiles together account for over $160 billion in exports while pulling the country’s overall complexity downward.
Italy’s strongest comparative advantages and highest global market shares concentrate in products with low or negative complexity. Patent leather commands 64% of world exports at a PCI of −0.35. Wool stock holds 51% (PCI −0.16), chamois leather 48% (PCI −0.65), and tomatoes 40% (PCI −1.50). Carded wool fabric is the only product in the top ten by market share with a PCI above 1.0.
This is the signature of a specialisation trap: Italy has built deep comparative advantages in mature niches where few competitors invest because the products offer limited growth potential. Meanwhile, Italy’s most complex exports (oxometallic salts at PCI 3.25, precious compounds at PCI 2.77, machining centres at PCI 2.22) remain small in absolute terms, from $36M to $439M. The standout exception is Machines n.e.c. at $5.9B with a PCI of 2.05, but it is an outlier.
Gross export figures overstate competitive strength in sectors where Italy simultaneously imports large quantities of similar goods. Net exports (exports minus imports) show where Italy is a genuine supplier to the world.
The net picture is stark. Machinery generates $52.6B in net exports, more than the next five positive sectors combined. Textiles ($25.7B net), Stone ($11.8B), Agriculture ($9.9B), Vehicles ($9.4B), and Chemicals ($9.4B) are all positive but at considerably smaller scale. On the deficit side, Minerals records −$93.4B, reflecting Italy’s near-total dependence on imported energy. Electronics is also negative at −$8.2B, meaning Italy consumes more electronic goods than it produces.
At the product level, thermostat valves ($5.7B net, PCI 1.42) and Machines n.e.c. ($3.4B net, PCI 2.05) drive the machinery surplus. But the largest individual net exporters also include wine ($7.6B, PCI −0.51), trunks ($7.6B, PCI −0.51), and jewellery ($7.2B, PCI 0.29), again underscoring the dependence on low-complexity goods for trade surpluses.
Three decades of data reveal how Italy’s export composition has shifted. The volume chart shows which sectors have gained or lost structural weight. The complexity chart tracks whether each sector has been upgrading its product mix. All lines use 5-year rolling averages.
Two patterns stand out. First, Machinery and Chemicals have grown steadily in volume, while Textiles and Stone, once pillars of the export basket, have stagnated. The 1995 treemap makes this visible: Textiles occupied a much larger share of total exports than it does today. Second, the complexity trends show limited upgrading across most sectors. Italy’s Economic Complexity Index has actually declined over the past decade, despite remaining the third-highest among its peer group. New products added to the basket over the last 15 years contributed $2.4 billion, but 80% of that came from tobacco processing, a pattern more characteristic of Spain or Greece than of Germany or South Korea.
Market share trends complete the picture. Even in sectors where Italy retains comparative advantages (RCA above 1.0), its absolute market share has been declining, meaning other countries are growing faster in the same products. Italy is not losing its niches outright, but it is failing to grow them or to break into new ones.
The treemap decomposes Italy’s 1995 export basket by sector and product. Comparing it to the 2022 rankings above shows where structural weight has shifted: Textiles and Stone have contracted, while Chemicals and Machinery have expanded.
The growth diagnostic conducted for PP413 connects the export data to Italy’s underlying structural problem. More than 90% of all Italian firms are micro-enterprises employing fewer than 10 workers, far more than any other major European economy. The share of employment in micro and small firms accounts for about 55%, compared to roughly 30% in France or Germany.
Smaller firms produce fewer products, target fewer markets, and are less productive. Most post-recession export growth has been driven by larger firms; small firms’ exports have failed to keep pace since 2008. The overreliance on low-complexity sectors can be attributed in large part to these smaller firms, which lack the scale and capabilities to enter complex product markets.
The diagnostic identifies the cause: Italy’s labour regulations and tax system create sharp size-based thresholds that discourage expansion. Firms cluster below regulatory cutoffs (15 employees for employment protections, revenue thresholds for preferential tax regimes). This produces a self-reinforcing cycle: regulation keeps firms small, small firms invest less in productivity and innovation, lower productivity limits their ability to produce complex goods, and the absence of complex exports holds back overall economic growth.
The opportunity analysis identifies products where Italy does not hold a comparative advantage (RCA below 1.0) but which exceed a minimum complexity threshold (PCI above 1.49). Each candidate is scored using three normalised variables: proximity to Italy’s current export basket, product complexity, and complexity outlook gain. Three strategies apply different weights.
A notable finding is that all three strategies largely converge on the same products. Cermets (PCI 1.80), flat-rolled alloy steel (PCI 1.76), instruments for chemical analysis (PCI 1.61), and cermet utensil articles (PCI 2.14) appear in all three top-10 lists. This happens because the most promising candidates are both close to Italy’s existing capabilities and high in complexity outlook gain. They cluster in Metals, Machinery, and Chemicals, sectors where Italy already has productive infrastructure but has not developed comparative advantages in these specific products.
Weights: 75% proximity, 10% PCI, 15% COG
Nearest products. Modest complexity gains, achievable short-term.
Weights: 50% proximity, 25% PCI, 25% COG
Middle path between feasibility and structural upgrading.
Weights: 40% proximity, 20% PCI, 40% COG
Highest structural payoff. Requires longer time horizons.
The scatter below shows the Balanced Strategy candidates. Horizontal axis is normalised distance (lower = closer), vertical axis is normalised product complexity, and bubble size reflects global export value.
Source: Harvard Growth Lab Atlas of Economic Complexity (atlas_2022.dta). HS-92, 4-digit (1,241 products excluding “Other”). Product names from external CSV lookup. Net exports = export_value minus import_value. Sector mapping restricted to 2022 to prevent merge duplicates.
Product-level: RCA, PCI, distance, COG, market share, PCI percentile. Sector-level: export-value-weighted PCI, summed volumes, computed RCA and market shares. Time-series: 5-year rolling averages. PCI weighting uses gross export values to avoid zero-weight instability.
Candidates: RCA < 1.0 and PCI > 1.49. Distance, PCI, COG min-max normalised. Proximity = 1 minus normalised distance. Three weighted composite scores per strategy.
Interactive Plotly HTML embeds. Unified portfolio style: IBM Plex Sans, #fafafa background, muted 9-colour sector palette. Treemap via Plotly Express.