Business Cycle

Aggregate activity moves around potential output because spending decisions are lumpy and expectations shift. Firms build inventories when demand surprises to the upside and liquidate them when it disappoints, and because inventory swings are large relative to GDP changes, they amplify turning points. Capital expenditure behaves similarly: capacity utilisation rises through an expansion until firms commit to new plant and equipment, which then arrives just as demand cools. Credit conditions reinforce both channels, easing when collateral values and profits are strong and tightening abruptly when they are not.

The gap between actual and potential real GDP, the output gap, is the compact way to describe where the economy sits. A positive gap implies resources are stretched and unit costs are rising; a negative gap implies slack, disinflationary pressure and underused labour. Potential output itself grows with labour force and productivity, which is why a slowing trend can look like weakness without any cyclical downturn at all.

Early expansion typically shows recovering industrial production, falling unemployment claims, inventory rebuilding, accommodative monetary policy and subdued inflation. Late expansion brings high capacity utilisation, tight labour markets, accelerating wages and unit labour costs, rising short rates and often a flattening yield curve. Around the peak, sales growth stalls while output is still high, so inventory-to-sales ratios drift up.

Contraction is the mirror image: production is cut, inventories are run down, capital spending plans are shelved, and profits fall faster than revenue because of operating leverage. Employment is a lagging variable, so unemployment usually keeps rising after the trough has passed. At the trough, the inventory-to-sales ratio peaks and then falls sharply as firms sell from stock before restarting production, which is one reason the earliest evidence of recovery appears in orders and hours worked rather than headline GDP.

Indicator sets are conventionally split into leading, coincident and lagging. Leading measures include new orders, building permits, consumer expectations, equity prices, the term spread and initial jobless claims. Coincident measures include industrial production, real personal income and payroll employment. Lagging measures include the average duration of unemployment, unit labour costs and commercial lending, which tends to expand well after activity has turned.

Asset behaviour follows the same logic. Credit spreads widen ahead of and through contractions as default expectations rise, government bonds rally as policy easing is priced, and cyclical sectors such as industrials, materials and consumer discretionary underperform defensive sectors such as utilities, staples and healthcare. In financial statements the cycle appears as inventory build-ups, receivable ageing, impairment charges and margin compression, which is why cyclical firms are valued on normalised rather than trailing earnings.

A typical task is to place an economy in a phase given a short data set, then infer the likely direction of inflation, policy rates and sector performance. Work from the slack in the system: if utilisation and wage growth are high and unemployment is below any plausible natural rate, the economy is late-cycle regardless of whether GDP growth still looks healthy. If claims are rising while payrolls are flat, the peak may already be behind.

Be able to distinguish the schools of thought on why cycles occur, since the policy conclusion differs. Keynesian analysis emphasises deficient aggregate demand and a role for fiscal stimulus; monetarist analysis emphasises erratic money growth and rule-based policy; the Austrian view treats downturns as the necessary correction of credit-driven misallocation; new classical and real business cycle models attribute fluctuations to technology and supply shocks with optimising agents, implying little gain from stabilisation.