Structural change
Structural change, also known as structural transformation, refers to the reallocation of labor, capital, and output shares across an economy's major sectors—typically from agriculture to manufacturing and then to services—as economies develop.[1] This process is driven primarily by differential productivity growth rates between sectors, where advances in modern sectors outpace traditional ones, pulling resources toward higher-productivity activities.[2] Empirical evidence indicates that successful structural change contributes substantially to aggregate economic growth by enhancing overall productivity through these reallocation effects.[3] Key theoretical frameworks, such as the dual-sector model developed by W. Arthur Lewis, explain structural change as the transfer of surplus labor from low-productivity subsistence agriculture to a high-productivity industrial sector, fostering capital accumulation and sustained growth until labor markets equilibrate.[4] Multi-sector extensions of neoclassical growth models further incorporate push and pull factors, including rising incomes shifting demand via Engel's law (reducing food shares) and technological progress enabling non-agricultural expansion.[5] Historical patterns observed in advanced economies, like the United States, demonstrate a secular decline in agricultural employment from over 40% in 1900 to under 2% today, alongside rises in industry and services, correlating with per capita income increases.[6] While structural change has underpinned rapid development in East Asian economies through manufacturing-led reallocation, contemporary challenges include "premature deindustrialization" in some developing nations, where service-sector shifts occur before industrial peaks, potentially limiting productivity gains and exacerbating inequality if skill mismatches or policy barriers hinder effective resource movement.[7] Causal analysis emphasizes that endogenous factors like human capital accumulation and physical infrastructure investments amplify the growth benefits of structural transformation, underscoring the need for policies that facilitate sectoral mobility rather than distort it.[2][5]Conceptual Foundations
Definition and Core Characteristics
Structural change refers to the long-term, systematic reallocation of resources—primarily labor and capital—across economic sectors, typically from low-productivity activities in agriculture to higher-productivity ones in manufacturing and services, as economies develop.[1] [8] This process alters the sectoral composition of aggregate output and employment, often driven by differential productivity growth rates between sectors.[2] Empirical evidence from developing economies shows that such shifts can account for up to 50% of aggregate productivity improvements in early industrialization phases, as resources move to sectors with higher marginal returns.[6] Core characteristics include persistence over decades rather than short-term cycles, with employment shares declining in traditional sectors (e.g., agriculture's global share fell from 60% in 1950 to under 25% by 2020 in many middle-income countries) and rising in modern ones.[8] These transformations frequently generate structural unemployment during transitions, as workers' skills mismatch sectoral demands, though successful cases mitigate this via education and mobility.[9] Productivity gains stem not only from within-sector advances but crucially from between-sector reallocations, where labor moves to activities yielding 2-3 times higher output per worker.[2] A distinguishing feature is unevenness across space and time: rural-urban migration accelerates the process, but institutional barriers like labor regulations or trade policies can distort it, leading to premature deindustrialization in some nations where services expand before manufacturing peaks.[10] Unlike cyclical fluctuations, structural change reflects fundamental alterations in comparative advantages, often irreversible without policy reversal, as seen in post-1980s shifts where manufacturing's employment share in OECD countries dropped below 20% amid automation.[11]Theoretical Models and Frameworks
The dual-sector model, developed by W. Arthur Lewis in 1954, provides a foundational framework for understanding structural change in developing economies as a transition from a traditional agricultural sector characterized by surplus labor to a modern industrial sector.[12] In this model, the marginal product of labor in agriculture remains near zero due to overemployment, allowing unlimited labor supply to migrate to industry at a subsistence wage without raising rural wages initially; capital accumulation in the modern sector absorbs this labor, driving output growth until the surplus is depleted at a "turning point," after which wages rise economy-wide. Extensions, such as the Harris-Todaro model of 1970, incorporate urban unemployment risks to explain migration dynamics more realistically, highlighting expected wage differentials as a causal driver of sectoral reallocation. Simon Kuznets' 1955 analysis integrated structural transformation with income distribution, positing that shifts from low-productivity agriculture to higher-productivity urban sectors initially widen inequality due to differential factor returns and skill demands, followed by convergence as education and capital diffuse.[5] Empirical cross-country data supported this, showing agriculture's output share declining from over 40% in low-income economies to under 10% in high-income ones, alongside rising non-agricultural employment.[5] Hollis Chenery and Moises Syrquin's 1975 study formalized these patterns using regression analysis on 1950-1970 data from 101 countries, identifying invariant relationships such as agriculture's employment share falling by about 1% per 1% GDP per capita growth, industry's peaking at intermediate income levels, and services expanding thereafter, driven by demand shifts and productivity gaps.[13] Joseph Schumpeter's framework of creative destruction, articulated in 1942, emphasizes endogenous innovation as the mechanism for structural change, where entrepreneurial introduction of new technologies and processes obsolesces old production methods, reallocating resources from declining to emergent sectors via market competition. This gale of destruction generates discontinuous shifts, with empirical evidence from firm-level data showing incumbents' market shares eroding under technological shocks, enabling sustained growth through sectoral reconfiguration. Modern extensions, such as those incorporating directed technical change, model how skill-biased innovations accelerate de-agriculturalization in advanced economies while potentially causing "premature deindustrialization" in others via uneven productivity growth across tradable and non-tradable sectors.[14] These frameworks collectively underscore productivity differentials and demand non-homotheticities as core causal engines, though they vary in emphasis on labor mobility versus technological disruption.[14]Historical Evolution
Early Economic Transformations
In pre-industrial England, agriculture dominated the economy, employing approximately 72% of the male labor force in the mid-16th century (1540–1559), compared to 19% in industry and 9% in services, based on adjusted probate records from 23 English counties.[15] This structure reflected limited technological constraints and reliance on land-based production, with output shares similarly weighted toward agriculture, though exact GDP breakdowns remain estimates due to sparse data; agriculture likely contributed 40–50% of national income by the late 17th century, supported by subsistence farming and rudimentary trade.[16] Proto-industrial activities, such as rural textile production and metalworking, began eroding agricultural dominance as early as the 17th century, with male agricultural employment falling to 68% by 1600–1619 and further to 52% by 1700–1719, as industry rose to 32%.[15] These shifts were concentrated in England, contrasting with Wales, where agricultural shares remained stable at 77–79% over the same period, highlighting regional variations driven by resource endowments and institutional factors like guild weakening.[15] The onset of these transformations was propelled by agricultural productivity gains from innovations like crop rotation, selective breeding, and enclosure movements, which reduced labor requirements per unit of output; wheat yields in England rose by about 25% between 1700 and 1800, enabling surplus labor reallocation without widespread famine.[17] Concurrently, rural manufacturing expanded through household-based "putting-out" systems, particularly in woolens and cottons, absorbing displaced workers and increasing the goods-producing share of the male labor force by 50% between 1600 and 1700, reaching nearly half of working men.[18] This proto-industrialization laid causal groundwork for urbanization, as rising non-agricultural output—fueled by domestic demand and export markets—drew labor to proto-factories and trades, with services growing to 15% of male employment by the early 18th century.[15] Empirical evidence from apprenticeship records (over 231,000 observations) confirms this reallocation, showing apprenticeships in industry surging relative to agriculture, though total employment growth remained modest at 0.2–0.3% annually pre-1750.[15] The classic Industrial Revolution, commencing around 1760 in Britain, accelerated these dynamics through mechanization; inventions like James Hargreaves' spinning jenny (1764) and James Watt's steam engine improvements (1769) shifted production from artisanal to factory-based manufacturing, reducing agricultural employment to approximately 45% by 1710 and further to 22% by 1851 in England and Wales.[15][19] Manufacturing's GDP share exceeded 30% by the early 19th century in Britain, Belgium, and the Netherlands, reflecting capital-intensive innovations that amplified labor productivity in textiles and iron, while agriculture's output share declined despite stable land use.[19] This era's transformations were not uniform across Europe—France and continental regions lagged, with agricultural employment exceeding 60% into the 19th century—due to institutional barriers like stronger guilds and fragmented landholdings, underscoring the role of property rights and market integration in enabling reallocation.[19] Overall, early structural change prioritized efficiency gains over rapid de-agriculturalization, with employment lags behind productivity shifts explaining sustained rural ties amid urban industrial expansion.[15]20th-Century Industrial and Postwar Shifts
The early 20th century marked accelerated industrialization in advanced economies, building on 19th-century foundations, with labor reallocating from agriculture to manufacturing amid technological innovations like electrification and the assembly line. In the United States, agricultural employment constituted about 41% of the nonfarm labor force in 1900 but declined to 27% by 1930 as mechanization and urbanization drew workers to factories.[20] Henry Ford's introduction of the moving assembly line in 1913 for the Model T automobile enabled mass production, reducing vehicle assembly time from 12 hours to 93 minutes and spurring growth in related sectors like steel and rubber.[20] By 1929, manufacturing accounted for roughly 28% of US nonagricultural employment, reflecting a structural pivot toward capital-intensive industry.[21] World War II intensified these shifts through wartime mobilization, which boosted industrial output and integrated women into the labor force. US manufacturing employment rose from 10.8 million in 1939 to a wartime peak of 17.5 million in 1943, with total industrial production increasing by 96% between 1939 and 1944 due to government contracts and resource reallocation.[22] In Europe, destruction from the war disrupted pre-existing structures, but Allied occupation policies laid groundwork for postwar recovery, emphasizing de-agriculturalization and industrial rebuilding. Japan's economy, devastated by defeat, saw initial hyperinflation but stabilized under US occupation reforms that dissolved zaibatsu conglomerates and enacted land reforms, reducing agricultural tenancy from 46% in 1946 to near zero by 1950.[23] Postwar reconstruction from 1945 to the early 1970s, often termed the "Golden Age of Capitalism," featured rapid GDP growth and further sectoral reallocation, driven by pent-up demand, institutional aids like the Marshall Plan, and productivity gains. In Western Europe, the Marshall Plan disbursed $13 billion (equivalent to $150 billion today) from 1948 to 1952, facilitating industrial revival; Germany's Wirtschaftswunder saw annual growth averaging 8% from 1950 to 1960, with manufacturing's GDP share rising to over 40%.[24] Japan's "economic miracle" achieved 10% average annual growth in the 1950s and 1960s through export-led industrialization, shifting employment from agriculture (45% in 1950) to manufacturing and services, supported by the Dodge Line stabilization in 1949 that curbed inflation and promoted efficiency.[23] In the US, agricultural employment share dropped to 7.9% by 1950 and further to 4.8% by 1970, while manufacturing peaked at around 30% of total employment in the mid-1950s before stabilizing, as suburbanization and consumer durables like automobiles and appliances fueled a nascent service economy expansion.[25][26] These changes were underpinned by causal factors including technological diffusion, such as tractors reducing farm labor needs by 75% per output unit from 1948 to 1973, and international trade liberalization via GATT rounds that enhanced industrial competitiveness.[24]Late 20th to Early 21st-Century Developments
In advanced economies, the late 20th century witnessed accelerated deindustrialization, with manufacturing's share of total employment declining sharply from the 1970s onward. Across 23 high-income countries, manufacturing employment fell from approximately 28% of the workforce in 1970 to 18% by 1994, driven by productivity gains in manufacturing, rising international competition, and offshoring to lower-cost regions.[27] In the United States specifically, manufacturing employment dropped from 24% in 1970 to 14% by 2000, reflecting automation, trade liberalization, and shifts toward non-tradable sectors.[28] This period marked a broader transition where resources reallocated from goods-producing industries to services, which by the early 2000s accounted for over 70% of employment and value added in OECD countries.[29] The 1990s information technology revolution further propelled structural shifts, particularly in service-oriented and knowledge-based sectors. IT-producing industries exhibited average annual productivity growth of 24% during the decade, outpacing traditional manufacturing and fostering the expansion of finance, telecommunications, and software services.[30] In the US, this contributed to a productivity resurgence, with nonfarm business sector labor productivity accelerating from 1.5% annual growth in the prior decades to 2.5% in the late 1990s, largely attributable to investments in computers, software, and networks.[31] These changes elevated the role of high-skill, IT-intensive occupations, altering labor demands and accelerating the decline of routine manual jobs in both manufacturing and routine services.[32] Globalization intensified these transformations from the 1990s into the early 2000s, as trade barriers fell and developing economies like China integrated into global supply chains, leading to further manufacturing relocation from advanced to emerging markets.[33] In OECD nations, this amplified deindustrialization while boosting service exports, though structural reallocation often reduced overall productivity growth in Latin America and Africa due to labor moving to lower-productivity informal sectors.[34] Conversely, successful Asian economies experienced growth-enhancing shifts, with output and labor moving toward modern manufacturing and services amid rapid export-led industrialization.[35] By the early 21st century, these dynamics had entrenched a bifurcated global structure, with advanced economies emphasizing high-value services and innovation, while emerging markets pursued catch-up industrialization before facing premature deindustrialization pressures.[36]Primary Drivers
Technological Advancements and Innovation
Technological advancements propel structural economic change by generating uneven productivity gains across sectors, prompting the reallocation of labor and capital toward activities with higher returns. This process aligns with causal mechanisms where innovations reduce production costs and expand output capabilities in adopting sectors, drawing resources from stagnant areas as per relative productivity differentials observed in economic models. Empirical studies confirm that such shifts have historically amplified aggregate growth, though they often entail short-term disruptions in employment patterns.[37][38] In the United States, mechanization in agriculture exemplifies early technological impacts, with employment share dropping from approximately 41 percent in 1900 to 1.3 percent by 2020, driven by innovations like tractors and harvesters that boosted farm output per worker by over 20-fold during the 20th century. Similarly, manufacturing underwent automation-fueled transformation; industrial robots and computer-aided processes contributed to a decline in sector employment from a peak of 19.5 million workers in 1979 to about 13 million in 2023, even as real output rose due to productivity enhancements averaging 2-3 percent annually from technological adoption. These reallocations favored services, where information and communication technologies (ICT) from the 1990s onward accelerated productivity growth, particularly in finance and professional sectors, underpinning a rise in service employment to over 80 percent of the workforce.[39][40][41] Contemporary innovations, including artificial intelligence (AI) and advanced robotics, are poised to intensify these dynamics by automating routine cognitive and manual tasks, potentially displacing up to 60 percent of jobs in advanced economies while enhancing productivity in exposed roles. Research indicates a displacement effect from automation reduces labor demand in affected sectors, countered partially by a productivity effect expanding overall output and new task creation, though net employment reallocation toward tech-complementary activities like software development and data analysis. For instance, AI integration in manufacturing has lowered unit labor costs, facilitating further shifts toward knowledge-intensive services, with empirical evidence from firm-level data showing accelerated within-industry labor shedding post-2010. Such changes underscore technology's role in fostering long-term efficiency, albeit with challenges in reskilling displaced workers across economies.[42][43][44]Labor Market and Demographic Dynamics
![US employment distribution by sectors for both genders][float-right] Demographic shifts, including declining fertility rates and increasing life expectancy, alter the composition of the labor force and thereby influence sectoral reallocations in structural change. In advanced economies, population aging has been associated with a reduced share of employment in goods-producing sectors and an expansion in services, particularly healthcare and personal services, as older workers retire from manufacturing and younger cohorts enter skill-intensive roles. For instance, analysis of U.S. household data from 1850 to 2010 indicates that a one-percentage-point increase in the elderly population share correlates with a decline in the goods sector employment share by approximately 0.5 percentage points.[45] Similarly, in OECD countries, the rise in the working-age population dependency ratio from 2010 to 2022 has tightened labor markets, with vacancy growth outpacing employment increases, prompting reallocation toward sectors accommodating lower physical labor demands.[46] In developing economies, the demographic transition—characterized by a temporary surge in the working-age population relative to dependents—facilitates structural transformation by providing abundant labor for industrialization and service expansion. This "demographic dividend" boosts savings and investment, enabling shifts from agriculture to manufacturing, as observed in East Asia during the late 20th century where fertility declines from above 5 children per woman in the 1960s to below replacement levels by the 1990s coincided with manufacturing employment rising to over 20% of the workforce.[47] Empirical studies across sub-Saharan Africa confirm that a higher youth dependency ratio slows structural change, while a balanced age structure accelerates reallocation to higher-productivity sectors, with panel data from 26 countries showing a 10% increase in the working-age share linked to 1-2% faster GDP growth via sectoral shifts.[48] Labor market dynamics amplify these demographic effects through variations in worker mobility, skill acquisition, and frictional barriers that determine the pace of reallocation. High labor mobility, as measured by job-to-job transition rates, enables rapid shifts during economic expansions, but frictions such as skill mismatches delay transformation in rigid markets; for example, in China from 1982 to 2000, rural-urban migration driven by demographic pressures accounted for 40% of the decline in agricultural employment, though institutional barriers slowed full adjustment.[49] In the U.S., structural forces including automation and offshoring have reduced bargaining power in tradable sectors, contributing to a 5-7% drop in the labor share since 1980, which incentivizes workers to relocate to non-tradable services.[50] Recent global trends, per the World Economic Forum's 2025 report, project that demographic aging combined with skill-biased technological change will displace 85 million jobs by 2025 while creating 97 million in emerging sectors like green energy and digital services, underscoring labor market adaptability as a key driver.[51] These dynamics interact causally: demographic pressures alter relative labor supplies across sectors, while market responses—via wage adjustments and migration—facilitate or hinder efficient reallocation, with evidence from search-theoretic models showing that growth in labor productivity amplifies turnover rates, accelerating structural shifts by 10-15% in flexible economies.[52] In Europe and Japan, where fertility rates fell to 1.3-1.5 children per woman by 2020, persistent labor shortages in manufacturing have driven policy responses like increased female participation, raising service sector employment by 5-10 percentage points since 2000.[53] Overall, empirical quantification reveals that demographics explain 20-30% of observed sectoral employment changes in post-1950 advanced economies, independent of technological drivers.[54]Trade, Globalization, and Institutional Factors
Trade liberalization drives structural change by altering relative prices and incentivizing specialization in sectors with comparative advantage, as posited in classical models like Heckscher-Ohlin, where factor endowments dictate shifts toward capital- or labor-intensive industries. Empirical studies confirm that reductions in trade barriers lead to contraction in import-competing sectors and expansion in export-oriented ones; for instance, prefecture-level analysis in China post-liberalization showed accelerated transformation from agriculture to manufacturing and services due to export growth.[55] In advanced economies, this manifests as manufacturing decline, with one cross-country investigation finding imports negatively correlated with employment shifts to tradable sectors.[56] A prominent case is the "China shock" following China's 2001 accession to the World Trade Organization, which lowered tariffs and boosted its exports, exposing U.S. local labor markets to intensified competition. Autor, Dorn, and Hanson (2013) documented that this import surge explained one-quarter of the U.S. manufacturing employment decline from 1990 to 2007, with affected commuting zones experiencing persistent wage reductions and reduced labor force participation, particularly among less-educated workers.[57] Subsequent updates indicate these effects endured, accounting for 59.3% of manufacturing job losses between 2001 and 2019, highlighting how trade-induced reallocations can generate long-term dislocations without full offsets from other sectors.[58] Globalization amplifies these dynamics through multinational production networks and foreign direct investment, fragmenting value chains and relocating routine tasks to low-wage countries, thereby accelerating sectoral shifts in high-income economies toward services and high-skill manufacturing. Micro-empirical evidence reveals that trade changes reallocate labor across sectors, boosting productivity in exposed firms via efficiency gains, though aggregate benefits depend on adjustment frictions.[59] In developing economies, such integration facilitates catch-up by drawing resources into modern sectors, with hypothetical productivity gains from reallocation estimated as substantial for low-income nations.[60] Institutional factors, including trade agreements and domestic regulatory frameworks, condition the pace and equity of these transformations. Multilateral pacts like the Uruguay Round (concluded 1994) reduced global tariffs by an average of 40%, enabling deeper integration but requiring supportive policies such as labor market flexibility to mitigate adjustment costs.[61] Rigid institutions, conversely, exacerbate mismatches by impeding worker mobility and firm entry, as evidenced in analyses linking institutional quality to effective resource reallocation during globalization episodes.[62] Trade imbalances further influence patterns, with deficits prompting outsized reallocation from goods to non-tradable sectors in deficit countries.[63]Empirical Manifestations
Sectoral Reallocations in Advanced Economies
In advanced economies, sectoral reallocations have predominantly featured a contraction in agriculture and manufacturing alongside expansion in services, driving shifts in employment composition since the mid-20th century. Agricultural employment shares plummeted from around 20-30% in the early 1900s to under 3% by the 2010s across OECD nations, reflecting mechanization and urbanization. Manufacturing employment peaked at approximately 25-35% in the 1950s-1970s but declined to 8-12% by 2020, as automation boosted output per worker and global trade relocated labor-intensive production. Services, encompassing finance, healthcare, and information technology, rose to 70-80% of total employment by the 2020s, absorbing displaced workers while exhibiting heterogeneous productivity trajectories.[64][65] These reallocations contributed significantly to aggregate productivity growth, with labor shifts from low-productivity agriculture to higher-productivity manufacturing and services accounting for 20-40% of labor productivity gains in OECD countries from 1950-2000. Within services, reallocation toward high-productivity subsectors like professional services and ICT amplified gains, though low-productivity areas such as retail and hospitality expanded due to inelastic demand and Baumol's cost disease effects. In the United States, manufacturing's share fell from 32% of nonfarm jobs in 1910 to under 9% in 2015, correlating with overall productivity acceleration from reallocation to more efficient firms and sectors. Post-2000, digital transformation induced further shifts, with tech-enabled services growing at 2-3 times the rate of traditional sectors, though manufacturing's absolute output increased despite employment declines.[66][65][64] Empirical analysis reveals uneven reallocation patterns, with faster deindustrialization in Europe compared to the US; for instance, EU manufacturing employment dropped below 15% by 2010 versus the US's 10%. Reallocation efficiency varies, as rigid labor markets in some advanced economies slowed transitions, prolonging structural unemployment during shocks like the 2008 financial crisis. Recent data indicate ongoing shifts, including within services toward knowledge-intensive activities, supporting productivity but exacerbating skill demands and regional disparities. Official statistics from bodies like the BLS and OECD underscore these trends, though measurement challenges arise from gig work and self-employment blurring sector boundaries.[67][39][64]Structural Transformations in Emerging Markets
In emerging markets, structural transformations primarily manifest as labor reallocation from agriculture toward manufacturing and services, driven by urbanization, trade openness, and policy reforms, though outcomes vary by region and exhibit diminishing productivity gains compared to historical advanced economy patterns. Between 2000 and 2022, the agricultural share of total employment across low- and middle-income countries fell from approximately 52% to 40%, with manufacturing absorbing a portion of the shift in Asia but services dominating elsewhere, often in low-productivity informal activities.[68] This reallocation has contributed to aggregate growth, yet empirical analyses reveal uneven within-sector productivity improvements, with some regions experiencing "productivity-reducing" structural change due to premature shifts away from tradable manufacturing.[69] China exemplifies rapid industrialization-led transformation following Deng Xiaoping's 1978 economic reforms, which dismantled collective farming and integrated the economy into global supply chains. Agricultural employment share dropped from 50% in 2000 to 23.3% in 2022, while manufacturing employment peaked at around 30% in the mid-2010s before stabilizing amid automation and service expansion; correspondingly, manufacturing's GDP share rose to nearly 40% by 2010 but has since hovered around 28-30% as services grew to 54% of GDP by 2023.[70] In contrast, India's growth has been service-oriented, with agricultural employment declining from 58.5% in 2000 to 42.6% in 2022, but manufacturing employment remaining stagnant at 12-14% due to rigid labor laws and infrastructure deficits, leading to a services GDP share exceeding 50% by 2023 despite limited formal job creation.[71] Brazil's trajectory reflects commodity dependence and policy volatility, with agricultural employment falling from 20% to 9.4% over the same period, but deindustrialization evident as manufacturing's GDP share declined from 25% in 2000 to 11% in 2022, offset by services at 67% amid urban informal expansion.[72] A key challenge is premature deindustrialization, where manufacturing employment peaks at lower per capita income levels—around $10,000 in PPP terms for recent emergers versus $20,000 historically—curtailing the sector's role as an engine of convergence.[73] Dani Rodrik's analysis of cross-country data from 1950-2005, extended to later periods, shows this trend accelerating post-1990 due to globalization's uneven benefits, automation, and service sector competition from advanced economies, resulting in slower aggregate productivity growth in Latin America and sub-Saharan Africa compared to East Asia. World Bank studies confirm that while Asian emergers like China and Vietnam achieved positive structural change contributions to GDP per capita growth (up to 1-2 percentage points annually in the 1990s-2000s), many others saw neutral or negative effects from reallocations to low-skill services, exacerbated by institutional barriers like weak property rights and overregulation.[74] IMF assessments highlight that without complementary reforms in education, infrastructure, and trade policy, these transformations risk entrenching dual economies, where formal sectors stagnate while informal ones absorb surplus labor without commensurate output gains.[75]| Country | Year | Agriculture Employment (%) | Industry Employment (%) | Services Employment (%) |
|---|---|---|---|---|
| China | 2000 | 50.0 | 22.5 | 27.5 |
| China | 2022 | 23.3 | 28.8 | 47.9 |
| India | 2000 | 58.5 | 17.4 | 24.1 |
| India | 2022 | 42.6 | 25.6 | 31.8 |
| Brazil | 2000 | 20.0 | 18.0 | 62.0 |
| Brazil | 2022 | 9.4 | 20.8 | 69.8 |