Analyzing Inflation Dynamics

Analyzing Inflation Dynamics

Structures inflation analysis with component decomposition, expectations tracking, and Phillips curve assessment.

When To Use

• Decomposing CPI or PCE inflation into component drivers (food, energy, shelter, core goods, core services)
• Assessing whether current inflation is demand-pull, cost-push, or expectations-driven
• Tracking inflation expectations across market-based and survey-based measures
• Evaluating Phillips curve dynamics (output gap vs. inflation tradeoff)
• Preparing macro research notes, policy briefs, or investment committee memos on the inflation outlook
• Analyzing pass-through effects from commodity prices, wages, or supply shocks

Inputs To Gather

• Headline and core inflation series: CPI-U, CPI-W, Core CPI (ex food & energy), PCE, Core PCE, trimmed-mean PCE, median CPI — specify frequency (monthly, quarterly, annual) and time horizon
• Component-level data: BLS CPI component weights and contributions; shelter (OER, rent of primary residence), medical care, transportation, apparel, etc.
• Inflation expectations measures: 5y5y breakeven, TIPS breakeven spreads, University of Michigan survey (1-year, 5-year), NY Fed Survey of Consumer Expectations, SPF median forecasts
• Labor market inputs: unemployment rate, NAIRU estimate, unit labor costs, average hourly earnings, employment cost index (ECI)
• Supply-side indicators: commodity price indices (WTI, Henry Hub, FAO food index), shipping rates, ISM prices-paid, supplier delivery times
• Policy context: current federal funds rate, Fed dot plot, recent FOMC statement language, QT pace, fiscal impulse estimates

Workflow

1. Establish the inflation snapshot

   • Report latest headline and core readings for CPI and PCE (month-over-month, 3-month annualized, year-over-year)
   • Compare to Fed's 2% PCE target and recent trend
   • Flag any divergence between CPI and PCE due to weighting or methodological differences [VERIFY methodology changes in current BLS/BEA releases]

2. Decompose by component

   • Break headline CPI into major categories: food at home, food away from home, energy (gasoline, electricity, natural gas), shelter, core goods, core services ex-shelter
   • Calculate contribution to headline change for each component (weight x price change)
   • Identify sticky vs. flexible components using Atlanta Fed sticky-price CPI
   • Flag any one-off or seasonal distortions (e.g., used car index volatility, airfare seasonal adjustment issues)

3. Assess underlying inflation momentum

   • Compute trimmed-mean PCE (Dallas Fed) and median CPI (Cleveland Fed) to strip outliers
   • Track supercore (core services ex-housing PCE) as the Fed's preferred demand-sensitive gauge
   • Evaluate 3-month annualized vs. 12-month to detect acceleration or deceleration trends
   • Determine if diffusion is broadening (share of CPI components above 2%, 3%, 5% thresholds)

4. Analyze inflation expectations

   • Compare market-based measures: 5y breakeven, 5y5y forward, inflation swap rates
   • Compare survey-based measures: Michigan 1y and 5y, SPF, NY Fed SCE
   • Assess whether expectations remain anchored near 2% or show de-anchoring risk
   • Note any divergence between short-term and long-term expectations (signal of transitory vs. persistent perception)

5. Evaluate Phillips curve and macro drivers

   • Estimate output gap position (CBO potential GDP vs. actual) [VERIFY latest CBO estimates]
   • Compare unemployment rate to NAIRU/natural rate estimates [VERIFY current Fed/CBO NAIRU range]
   • Track unit labor cost growth and wage-price spiral indicators (ECI vs. productivity growth)
   • Assess fiscal impulse: government spending contribution to aggregate demand

6. Identify supply-side and pass-through dynamics

   • Track commodity input costs and their lagged pass-through to consumer prices
   • Evaluate supply chain normalization (supplier delivery times, inventory-to-sales ratios)
   • Assess exchange rate pass-through for import prices
   • Note any sector-specific shocks (e.g., insurance, auto repair, housing supply constraints)

7. Synthesize outlook and risk assessment

   • State base case inflation trajectory (next 6-12 months) with key assumptions
   • Identify upside risks (energy shock, wage acceleration, fiscal expansion, de-anchored expectations)
   • Identify downside risks (demand destruction, credit tightening, commodity deflation, productivity gains)
   • Assess policy implications: likelihood of rate cuts/hikes, QT continuation, forward guidance shift

Output

• Inflation Dashboard Table: latest headline CPI, core CPI, headline PCE, core PCE, trimmed-mean PCE, supercore — each with MoM, 3M annualized, and YoY
• Component Contribution Chart Description: ranked list of components by contribution to headline change
• Expectations Summary: table of market-based and survey-based expectations with trend arrows
• Phillips Curve Assessment: current positioning (unemployment vs. inflation) and directional call
• Outlook Narrative: 2-4 paragraph synthesis with base case, risk skew, and policy implication
• Key Monitoring Points: 3-5 specific data releases or thresholds to watch going forward

Quality Checks

• Confirm CPI and PCE readings match official BLS/BEA releases — do not rely on stale data [VERIFY release dates]
• Verify component weights are current (BLS updates CPI weights annually in January) [VERIFY weight revision timing]
• Ensure breakeven inflation figures are adjusted for inflation risk premium and liquidity premium where relevant
• Cross-check survey expectations against the most recent release dates (Michigan is preliminary then final; SPF is quarterly)
• Distinguish between seasonally adjusted and non-seasonally adjusted figures — never mix them in comparisons
• Flag if analysis period spans a methodological change (e.g., OER calculation updates, geometric mean vs. arithmetic mean)
• Mark any forward-looking projection as an estimate, not a forecast guarantee