How Do Construction and Agricultural Equipment Companies Navigate Commodity Cycles?

Caterpillar and Deere are among the most recognizable industrial companies in the world — their yellow construction machines and green farm equipment represent the physical backbone of infrastructure building and food production. These businesses are also among the most cyclically sensitive in the equity market — construction equipment demand follows infrastructure spending and mining capital investment; agricultural equipment demand follows farm income, which correlates with commodity prices. Understanding the specific demand drivers, the dealer network economics that buffer manufacturer revenue, and the precision agriculture and services transformation that Deere has executed enables sophisticated analysis of these iconic industrial businesses.

Quick definition: Construction equipment companies (Caterpillar, Komatsu, Volvo CE) manufacture excavators, bulldozers, loaders, and graders used in construction, mining, and quarrying. Agricultural equipment companies (Deere, CNH Industrial, AGCO) manufacture tractors, combines, planters, and sprayers for crop production. Caterpillar also has a large energy and transportation segment (turbines, engines for oil and gas). Both segments are highly cyclical — construction correlates with infrastructure investment; agriculture correlates with farm income driven by commodity prices.

Key takeaways

• Caterpillar generates approximately 30–35% of revenue from resource industries (mining) and 25–30% from construction equipment — making it a direct proxy for global commodity capital investment, which correlates with metal prices and energy investment cycles
• Deere has executed a strategic transformation toward precision agriculture — integrating GPS-guided planting, machine learning yield optimization, and John Deere Operations Center data platform to create technology differentiation above commodity equipment competition
• Dealer networks are critical infrastructure for both businesses — Cat dealers provide equipment financing, parts availability (24-hour delivery commitment), and maintenance services that independent dealers cannot replicate; dealer health is an early warning indicator for manufacturer demand
• Agricultural equipment demand follows the farm income cycle: corn, soybean, and wheat prices determine farmer profitability, which determines equipment investment capacity; strong commodity prices (2020–2022) generated exceptionally strong Deere demand; declining commodity prices compress farm income and defer equipment purchases
• Caterpillar's financial services segment (Cat Financial) provides dealer and customer financing — its loan portfolio quality reflects equipment demand cycle health and serves as a leading indicator for business deterioration

Caterpillar: global construction and mining proxy

Segment structure: Caterpillar reports three primary segments: Construction Industries (backhoes, excavators, skid steer loaders for general construction — approximately 30% of sales); Resource Industries (large mining trucks, electric rope shovels, underground mining equipment — approximately 25% of sales); and Energy and Transportation (turbines, reciprocating engines for oil and gas, marine, industrial, and rail applications — approximately 35% of sales). Financial Products (Cat Financial) adds dealer and customer financing services.

Mining capital investment sensitivity: Resource Industries revenue correlates strongly with mining company capital expenditure — which correlates with metal prices (copper, iron ore, gold) and energy prices. When mining companies are investing in new mine development and fleet expansion, Caterpillar equipment orders surge; when commodity prices decline and mining companies cut capital budgets, orders collapse. The 2011–2016 commodity bear market generated sustained Resource Industries revenue declines; the 2020–2022 commodity surge reversed this trend.

Services and aftermarket growth: Caterpillar has explicitly targeted aftermarket services growth — Cat Financial, equipment monitoring (Cat Inspect), and maintenance agreements (Cat PRO) provide recurring revenue less sensitive to equipment purchase cycles. Equipment connected to Cat's digital platform enables proactive maintenance recommendations, creating service revenue opportunities. Services revenue growth reduces Caterpillar's historical pattern of extreme earnings volatility through equipment cycles.

Dealer network advantages: Caterpillar's global dealer network — approximately 165 Cat dealers operating 2,500+ locations — provides competitive advantage in parts availability and equipment financing. Cat's 24-hour parts availability commitment (a Cat machine should never be idle waiting for a part) requires dealers to maintain substantial inventory. This parts availability creates switching cost — mining operators running Cat fleets depend on Cat dealer support infrastructure; switching to Komatsu equipment requires rebuilding maintenance relationships and parts inventory.

Deere: precision agriculture transformation

Precision agriculture strategy: Deere has invested substantially in agricultural technology — GPS-guided steering (AutoTrac), variable rate application (fertilizer and seed rate adjusted by soil conditions), machine learning yield prediction (See and Spray Ultimate for targeted herbicide application), and the Operations Center data management platform. These technologies create differentiation above commodity equipment competition (AGCO, CNH) and generate recurring software revenue from technology subscriptions.

See and Spray technology: Deere's See and Spray Ultimate system uses computer vision and machine learning to distinguish crop plants from weeds in real-time, applying herbicide only to weeds — reducing herbicide usage by approximately 77% compared to broadcast application. This technology commands significant premium pricing (several hundred thousand dollars per sprayer) and reduces farmers' herbicide operating costs, enabling Deere to justify value-based pricing that preserves margin above commodity competitors.

Farm income cycle exposure: Deere's agricultural equipment demand correlates strongly with farm income — which correlates with commodity prices. The 2020–2022 period of high corn, soybean, and wheat prices (driven by La Niña drought and Russia-Ukraine supply disruption) generated exceptional farm income and corresponding Deere equipment demand. As commodity prices normalized from 2022 peaks, farm income compressed and Deere's agricultural segment demand began declining from historically elevated levels.

Construction equipment segment: Deere's construction segment (approximately 20% of total revenue) — excavators, dozers, and compact construction equipment for residential and commercial construction — provides somewhat differentiated cycle exposure from the agricultural segment. Infrastructure investment (IIJA-funded projects) has partially supported construction equipment demand when agricultural demand normalizes.

How it flows

Agricultural equipment demand cycle mechanics

Commodity price transmission to equipment: The mechanism from commodity prices to equipment demand involves several steps: (1) commodity prices rise → farmer revenue increases; (2) farmer profitability improves → net farm income rises; (3) farmers defer equipment replacement in down cycles; (4) deferred equipment ages and requires replacement; (5) income improvement enables purchase of deferred replacement and new capacity. This multi-step process creates lag between commodity price changes and equipment order changes — typically 6–12 months from commodity price inflection to equipment order response.

Crop mix implications: Corn and soybean prices are the most important drivers for large-row crop equipment (planters, combines, large tractors). Wheat prices matter for European and North American winter wheat regions. Specialty crop equipment (tree nuts, vegetables, soft fruits) follows different demand patterns tied to specific crop economics.

Used equipment market as leading indicator: Used agricultural equipment prices are a leading indicator for new equipment demand — when used equipment prices are high (demand exceeding supply), farmers can trade in used machines at favorable values, reducing the effective cost of new equipment. When used equipment prices decline (supply exceeding demand), the trade-in value subsidy for new equipment diminishes, weakening effective demand. Dealers' used equipment inventory levels are publicly tracked through industry publications.

Mining equipment cycle analysis

Mining capital expenditure cycle phases: Mining companies follow specific capital investment cycles: (1) exploration — identifying new resources; (2) development — building mine infrastructure; (3) ramp-up — installing and commissioning production equipment; (4) steady-state — replacement and expansion; and (5) decline — minimal new investment. The transition from development to ramp-up generates the largest equipment demand spike (initial large mining truck fleet orders); steady-state generates more predictable replacement demand.

Fleet electrification transition: Mining equipment electrification — battery-electric and trolley-assist mining trucks — is emerging as a sustainability requirement for mining companies committed to net-zero operations. Caterpillar and Komatsu are developing electric mining truck platforms (Cat 793 XE, Komatsu AHS autonomous haulage). The electrification transition could accelerate fleet replacement cycles as mining companies upgrade legacy diesel fleets, creating demand stimulus beyond normal replacement cycles.

Valuation considerations

Through-cycle EV/EBITDA: Caterpillar and Deere are most appropriately valued on through-cycle EBITDA — averaging earnings across multiple cycle peaks and troughs. Peak earnings are not sustainable; trough earnings are not representative of business quality. Through-cycle EV/EBITDA ranges: Caterpillar 10–14x (cyclical with services growth improving stability); Deere 12–16x (agricultural cycle sensitivity but technology premium for precision agriculture differentiation).

Order book as leading indicator: Both companies publish order book data with quarterly earnings — new machine orders versus deliveries provide forward visibility into revenue trajectory. Rising order books suggest future revenue growth; declining order books suggest revenue headwinds in subsequent quarters. Dealer inventory levels (also disclosed) provide additional early warning of demand inflection.

Financial services portfolio quality: Cat Financial and John Deere Financial provide dealer and retail financing — their loan portfolio quality (delinquency rates, credit loss rates) reflects the financial health of dealers and end customers. Deteriorating loan quality in financial services segments is an early warning of broader equipment demand problems.

Common mistakes

Buying Caterpillar near commodity price peaks. Caterpillar's earnings peak when mining capital investment is at its highest — which correlates with commodity price peaks. Buying CAT at peak commodity prices and peak earnings multiples frequently leads to buying at cycle highs. The optimal Caterpillar entry is when commodity prices are recovering from lows and mining companies are beginning to resume capital investment, not when investment is already at full run rate.

Ignoring the used equipment market in agricultural analysis. Used equipment market conditions substantially affect new equipment demand through trade-in values. Monitoring used combine and tractor auction prices (tracked by industry services like AuctionTime) provides leading signal for new equipment demand before it appears in manufacturer order data.

FAQ

How does the Infrastructure Investment and Jobs Act (IIJA) affect construction equipment demand?

The Infrastructure Investment and Jobs Act (2021) authorized approximately $550 billion in incremental infrastructure spending over five years — roads, bridges, airports, waterways, broadband, and clean water systems. This federal investment creates construction equipment demand as contractors build and rehabilitate infrastructure across the country. The impact on Caterpillar and Deere construction segments is meaningful but distributed over multi-year project timelines (infrastructure projects require significant planning and procurement before construction begins). IIJA-funded construction has provided a demand floor for construction equipment during periods when residential construction slowed. Federal infrastructure program data is available at transportation.gov and Department of Commerce construction spending data at census.gov.

Related concepts

• Industrials Economic Cycle
• Capital Goods and Machinery
• Industrials Valuation
• Industrials Historical Performance
• Industrials Portfolio Sizing

Summary

Caterpillar and Deere represent the most cyclically exposed capital goods businesses within Industrials — Caterpillar as a proxy for global construction and mining capital investment (correlating with metal prices and infrastructure spending); Deere as the leader in agricultural equipment with strategic transformation toward precision agriculture technology. Caterpillar's competitive moat lies in its global dealer network (24-hour parts availability, equipment financing) and growing services revenue (Cat Inspect, maintenance agreements, Cat Financial). Deere's competitive positioning increasingly rests on technology differentiation — precision agriculture software (Operations Center), machine vision herbicide application (See and Spray), and GPS-guided automation that justify premium pricing above commodity competitors. Both companies are best evaluated on through-cycle earnings rather than peak earnings; order books, dealer inventory levels, and financial services portfolio quality provide leading indicators of cycle inflection. Commodity prices (for Caterpillar's mining exposure) and farm income dynamics (for Deere's agricultural demand) are the primary external demand drivers requiring continuous monitoring.

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