For most of the history of international economics, the basic unit of trade was a good. Countries exported wine and imported cloth, or exported wheat and imported textiles. The Ricardian and Heckscher-Ohlin models, the workhorses of trade theory, both built their predictions around finished goods crossing borders. By the early 2000s, this framing had become visibly out of date. An iPhone designed in California, with chips from Taiwan, screens from South Korea, components from a dozen other countries, and final assembly in China, is not really a Chinese export. It is a bundle of tasks performed in many countries and added together along a chain. The good is the residue.
The Grossman-Rossi-Hansberg model of trade in tasks, published by Gene Grossman and Esteban Rossi-Hansberg in the American Economic Review in 2008, formalized this shift. The framework treats production as a sequence of tasks rather than as the output of a single industry, and shows that offshoring some of those tasks is best understood as a form of productivity gain rather than as conventional trade in goods. The implications for wages, inequality, and policy are different from those of older models in ways that have become increasingly important as global value chains and digital services have expanded.
From Goods to Tasks
The intuitive starting point is what production actually looks like in a modern industry. A product is the result of many distinct steps: research and development, design, sourcing of inputs, manufacturing of components, assembly, quality control, branding, marketing, distribution, and after-sales service. In a closed economy, all of these steps happen within the same country, often within the same firm. In a globally integrated economy, each step can be located wherever it can be performed most cheaply, provided the cost of coordinating across borders is low enough.
Some tasks are highly tradable. Software development, accounting, call-center work, and routine assembly can be performed thousands of miles from where the final product is consumed, and the cost of moving the output across that distance is low. Other tasks are not tradable. A haircut, a dental appointment, or a construction job must be performed where the customer is. The economy of any country is a mix of tradable and non-tradable tasks, and the boundary between the two has been shifting steadily for decades, driven by improvements in communication technology and falling transport costs.
The Grossman-Rossi-Hansberg framework treats this shift as the central feature of modern globalization. What used to be a single domestic activity is now a chain of tasks, and trade is increasingly the cross-border exchange of those tasks. The model is built to answer a specific question: when a country can offshore some tasks to a lower-cost location, what happens to wages, output, and welfare at home?
The Offshoring Cost Schedule
The model’s central idea is the offshoring cost schedule. Each task has its own cost of being performed abroad rather than at home. Some tasks have a very low offshoring cost: data entry, software coding, telephone customer service. Others have a very high offshoring cost: in-person legal advice, on-site equipment maintenance, hands-on training.
Rank all the tasks in an industry from lowest to highest offshoring cost. The result is an upward-sloping schedule. At one end of the schedule sit the easy-to-offshore tasks. At the other end sit the impossible-to-offshore ones. Improvements in communication technology, falling transport costs, and easing trade barriers shift this schedule downward, making more tasks offshorable than before.
The firm in the home country compares, for each task, the cost of performing it domestically against the cost of performing it abroad plus the offshoring cost. Tasks where the foreign cost plus offshoring cost is less than the domestic cost get offshored. Tasks where it is greater stay home. As the offshoring cost schedule shifts down, the cutoff moves and more tasks cross the boundary into the offshore category. This is the mechanism that drives the rise of global value chains.
Three Effects on Home-Country Wages
The most important contribution of the Grossman-Rossi-Hansberg framework is the decomposition of how offshoring affects wages in the home country. Earlier models, particularly the Stolper-Samuelson theorem, predicted that trade hurts the wages of workers in the country’s scarce factor (often unskilled labor in advanced economies). The trade-in-tasks framework agrees this can happen, but identifies two other effects that pull in the opposite direction. Whether wages rise or fall depends on which of the three dominates.
The productivity effect. When a firm offshores a task to a cheaper location, its overall production cost falls. This is mathematically identical to a productivity improvement: the firm gets the same output for less input. A more productive firm expands output, hires more workers, and pays them more. This effect tends to raise wages, including the wages of the workers performing the very tasks that compete with the offshored ones, because the firm is now larger and more profitable.
The relative-price effect. Offshoring is more available for some types of tasks than others. If offshoring mainly affects routine tasks performed by less-skilled workers, the relative price of tasks performed by more-skilled workers rises. This is the channel through which offshoring tends to widen wage gaps between skilled and unskilled workers, even when both groups remain employed.
The labor-supply effect. If a task is offshored, the workers who previously performed it at home are released into the rest of the labor market. They compete for other jobs, increasing the supply of labor in those remaining sectors and putting downward pressure on wages there. This is the conventional adjustment cost of trade liberalization, the same mechanism that operates in classical models.
| Effect | Mechanism | Direction on home wages | Strongest when |
|---|---|---|---|
| Productivity effect | Lower production cost expands output and demand for workers | Positive | Firms pass cost savings into expansion rather than profit margins |
| Relative-price effect | Tasks not offshored become relatively more valuable | Positive for non-offshored workers, negative or neutral for offshored ones | Offshoring is concentrated in specific task types |
| Labor-supply effect | Displaced workers compete for remaining domestic jobs | Negative | Displaced workers cannot easily move to non-offshored tasks |
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The net effect on home-country wages depends on which of the three forces dominates. Grossman and Rossi-Hansberg showed that under plausible parameter values, the productivity effect can be large enough to dominate the other two, meaning offshoring can raise the wages of the very workers whose tasks are being offshored. This was a controversial result when it appeared, because it contradicted both the popular intuition and the predictions of older trade models. The conditions under which it holds, particularly the requirement that the productivity gains are passed through to workers rather than captured entirely as profits, became the focus of much subsequent research.
Why the productivity effect matters. The trade-in-tasks framework reframes offshoring as a form of imported productivity. From the firm’s perspective, offshoring is equivalent to a technological improvement: it gets more output for less input. This insight shifted how economists think about the welfare consequences of offshoring, moving the analysis closer to the literature on technology adoption than to the literature on classical trade in goods.
From Goods Offshoring to Service Offshoring
When the Grossman-Rossi-Hansberg paper appeared in 2008, most of the public attention focused on manufacturing offshoring, especially the movement of assembly work from the United States and Europe to China and Southeast Asia. But the model was always designed to apply more broadly. The same logic applies to services, and within a few years of the paper’s publication, service offshoring had become at least as important as goods offshoring for advanced economies.
The boundary of what counts as a tradable task has expanded steadily. Call centers were first. Software development followed. Then back-office work, accounting, legal research, medical transcription, radiology reading, and architectural drafting. By the late 2010s, parts of journalism, financial analysis, and design work had become routinely offshored. By 2025, the rise of AI-enabled remote work and global hiring platforms had pushed even more service tasks into the tradable category.
The framework anticipates this expansion almost mechanically. As the offshoring cost schedule shifts downward, the boundary between offshorable and non-offshorable tasks moves toward more skilled and more complex work. Each technological improvement in communication, software, or AI translates into a new wave of tasks crossing the boundary. The political and labor-market reactions in advanced economies have followed roughly the same pattern: surprise, followed by adjustment, followed by acceptance that the offshorable category is larger than previously assumed.
The Smile Curve and Value Distribution
One empirical pattern that the trade-in-tasks framework helps explain is what the value chain literature calls the smile curve. Plot the value added at each stage of a global value chain on a vertical axis, against the stages of production on a horizontal axis from initial design through final distribution. The resulting shape is typically a smile: high value at the design and R&D end, high value at the marketing and distribution end, and low value in the middle, where manufacturing and assembly sit.
The pattern is consistent with the trade-in-tasks logic. The tasks at the ends of the smile, design and marketing, are the least offshorable to lower-cost locations because they require deep market knowledge, regulatory familiarity, brand control, or proximity to specialized talent. The tasks in the middle, manufacturing and assembly, are the most offshorable. Competition has pushed their value added down, while the non-offshorable tasks at the end retain higher margins.
This is why advanced economies have not lost the iPhone supply chain even as China has become the assembly hub. The high-value tasks remain at the ends of the smile, in the country where Apple is headquartered. The middle of the smile is contestable. The ends are not, at least not yet.
Origins and Extensions of the Framework
The 2008 paper was titled “Trading Tasks: A Simple Theory of Offshoring,” and it built on earlier work on production fragmentation by Ronald Jones, Henryk Kierzkowski, and others. What distinguished Grossman and Rossi-Hansberg’s contribution was the formal model that gave the three-effect decomposition and the productivity-effect result.
Since publication, the framework has been extended in several directions. Work by Pol Antràs, Davin Chor, and others has connected the trade-in-tasks logic to global value chain analysis, formalizing how firms decide which stages of production to perform internally versus through arm’s-length suppliers. Research on automation and AI has used the same task-based framework to study how technology, not just trade, changes which tasks remain in advanced economies. The empirical literature on the China shock applied the trade-in-tasks framework to interpret regional wage losses in US manufacturing communities after Chinese imports surged in the 2000s.
More recently, debates around nearshoring, reshoring, and friendshoring have returned attention to the question of which tasks should be performed at home for reasons of resilience or geopolitical risk. The trade-in-tasks framework remains the natural language for these debates, even when the policy goal is to reverse some of the offshoring that the model originally described.
Model Limitations
Three limitations of the framework are worth noting.
First, the model treats the offshoring cost as exogenous. In practice, the cost depends on coordination technology, contract enforcement, intellectual property protection, and trust between firms in different countries. These are endogenous and change over time, sometimes sharply, as the COVID-19 disruptions to global supply chains demonstrated.
Second, the productivity-effect result is sensitive to assumptions about how cost savings are passed through. If firms capture the gains as profits rather than expanding output, the productivity effect on wages weakens. Empirical estimates of pass-through vary considerably across industries and time periods.
Third, the framework abstracts from the geographic concentration of displaced workers. The model assumes displaced workers are absorbed into other sectors, but in practice, the workers whose jobs are offshored are often concentrated in specific regions and find it costly to retrain or relocate. The China shock literature has documented persistent regional adjustment costs that the aggregate trade-in-tasks model does not capture.
Impact on Trade Policy Debates
The trade-in-tasks framework changed how economists discuss several policy questions. Tariffs designed to protect domestic industries look different when the imported goods are bundles of tasks rather than finished products. A tariff on a smartphone imported from China taxes the small fraction of the phone’s value added in China, while leaving the much larger share added in the United States, South Korea, and Taiwan untouched. The effective tariff burden depends on the value-chain structure, not just on the headline rate. This insight has become important in current debates about industrial policy and tariff design.
The framework also reshaped the discussion of labor-market adjustment programs. If offshoring affects specific tasks rather than entire industries, policy support should target workers performing those tasks, regardless of which industry they happen to work in. A radiologist whose work is being read by an AI system in another country has more in common, from a policy standpoint, with an assembly-line worker whose tasks have been offshored than with other radiologists whose tasks remain non-tradable.
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The Grossman-Rossi-Hansberg framework for trade in tasks reframes globalization as the cross-border exchange of production stages rather than finished goods. By decomposing the wage effects of offshoring into three forces, productivity, relative price, and labor supply, the model showed that offshoring’s distributional consequences depend on which mechanism dominates in a given context. The productivity effect, in particular, can be large enough to raise the wages of the very workers whose tasks are being offshored, a result that runs against both popular intuition and the predictions of classical trade models.
Two decades after publication, the framework has become the standard language for analyzing global value chains, service offshoring, the rise of remote work, and the recent shift toward nearshoring and reshoring. The world it describes has only deepened: each new wave of communication and AI technology pushes more tasks across the offshorable boundary, and policy debates about resilience, industrial strategy, and labor adjustment continue to be argued in its terms. Understanding the trade-in-tasks framework is now closer to understanding modern globalization itself than to understanding any specific trade model.
Frequently Asked Questions
What is the trade-in-tasks model?
The trade-in-tasks model is a framework developed by Gene Grossman and Esteban Rossi-Hansberg in 2008 that treats production as a sequence of distinct tasks rather than as the output of a single industry. The model analyzes how offshoring individual tasks affects wages, productivity, and welfare in the home country, and it has become the standard language for discussing global value chains and service offshoring.
How does the trade-in-tasks model differ from classical trade theory?
Classical trade theory, including the Ricardian and Heckscher-Ohlin models, treats finished goods as the unit of trade. The trade-in-tasks framework treats tasks as the unit of trade, recognizing that modern products are produced through chains of activities that can be split across countries. The framework also identifies a new effect, the productivity effect, that can offset the wage losses predicted by older models.
What are the three effects of offshoring on home-country wages?
The productivity effect raises wages because offshoring reduces production costs and lets firms expand. The relative-price effect raises the wages of workers performing tasks that cannot be offshored. The labor-supply effect lowers wages because displaced workers compete for remaining domestic jobs. The net wage effect depends on which of the three dominates in a given context.
Why is offshoring sometimes called a form of productivity gain?
When a firm offshores a task to a cheaper location, it produces the same output at lower total cost. Mathematically, this is identical to a productivity improvement: more output per unit of input. The firm becomes effectively more productive, expands its scale, and hires more workers in the tasks it retains. This is the productivity effect, and it is the central insight that distinguishes the trade-in-tasks framework from earlier trade models.
Does the trade-in-tasks model apply to services as well as goods?
Yes, and service offshoring has become at least as important as goods offshoring for advanced economies. The framework’s offshoring cost schedule applies to any task that can be performed remotely, including call-center work, software development, accounting, legal research, medical imaging analysis, and design. AI-enabled remote work has further extended the range of tradable services, deepening the framework’s relevance.
How does the trade-in-tasks model relate to global value chains?
Global value chains are the empirical manifestation of trade in tasks. A product produced through a global value chain is the result of many tasks performed in different countries, with each country contributing its most cost-effective activities. The trade-in-tasks framework provides the formal language to describe how value-chain structures form, how value is distributed across stages, and how changes in trade costs reshape the geographic location of production.
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