Frequently Asked Questions

Everything you need to know about the Deflation Index, our methodology, and how to use the data.

Understanding the Index

What is the Deflation Index? +

The Deflation Index (DI) measures technological deflation across four fundamental sectors: computing, communications, energy, and transportation. It tracks how much cheaper technology makes these essential inputs over time.

The core finding: From 1990-2024, technology delivered 96.26% deflation across these sectors. What cost $100 in 1990 should cost $3.74 today in real terms. Yet consumer prices rose 155% during the same period.

The DI quantifies this divergence—measuring the force of technological progress against monetary expansion and revealing where the productivity gains went.

Why 1990 as the base year? +

Three key reasons:

1. Data availability: 1990 is the earliest year where we have reliable, comprehensive data across all four sectors. Computing performance metrics (FLOPS), communications costs, solar efficiency data, and early battery technology all have solid measurement foundations by 1990.

2. Technology inflection point: The early 1990s marked the beginning of the modern computing era—Windows 3.0, early internet, mobile phones transitioning from luxury to consumer products. It's a natural starting point for measuring digital-age deflation.

3. Long enough to show exponential effects: 35 years (1990-2024) is sufficient to demonstrate exponential cost reduction curves. Shorter periods might show volatility; longer periods lack reliable data.

Setting 1990 = 100 as the baseline makes it easy to track percentage changes over time.

How is this different from CPI? +

The Consumer Price Index (CPI) measures what consumers pay for certain goods. The Deflation Index measures what technology more broadly makes possible.

Key differences:

Scope: CPI tracks a basket of consumer goods. The DI focuses specifically on technological inputs (computing, communications, energy, transportation) that underpin the entire economy.

Methodology: CPI uses hedonic adjustments (quality improvements) but often understates technological progress. The DI directly measures cost-per-unit-performance ($/GFLOPS, $/GB, $/kWh), capturing the full force of technological deflation.

Purpose: CPI aims to measure "price stability" for monetary policy. The DI aims to measure technological progress and reveal where productivity gains flow.

CPI shows +155% inflation (1990-2024). The DI shows -96.26% deflation. The gap reveals a massive divergence between technological potential and monetary reality.

How do you calculate the Master Deflation Index? +

The DI is a weighted composite of four sector indices:

Sector Weights:

  • Computing (29.41%): FLOPS/$, storage $/GB, memory $/GB
  • Communications (23.53%): Data $/GB, voice $/minute, network $/Mbps
  • Energy (29.41%): Solar $/kWh, batteries $/kWh, LEDs $/lumen
  • Transportation (17.65%): EV batteries $/kWh, efficiency gains

Formula: We use a weighted sum of sector indices to capture how technological deflation compounds across the economy. Each year, sector indices are calculated from cost-per-performance metrics, then combined using the weights above.

Result: DI fell from 100 (1990) to 3.74 (2024) = 96.26% total deflation.

For full technical details, see our methodology documentation.

The Gaps & Findings

What is the gap between DI and M2? +

The gap measures the divergence between two powerful economic forces:

Technology (DI): Pushed prices down -9.21% annually (96.26% cumulative deflation)

Monetary Expansion (M2): Pushed prices up +5.7% annually (550% cumulative growth)

The Annual Gap: 14.9 percentage points per year (9.21% + 5.7%)

This gap represents the systematic divergence between technological productivity gains and monetary expansion. Technology makes things cheaper; money creation makes them more expensive. These forces move in opposite directions, and the gap between them reveals where productivity gains flow in the economy.

The question: If technology delivered 96% cost reductions, and money supply expanded 550%, why did consumer prices only rise 155%? Where did the remaining productivity go?

Why compare against M2 money supply instead of CPI? +

The short answer: M2 measures monetary expansion itself. CPI measures prices of a specific government-defined basket. They answer different questions.

What each metric tells us:

Metric Measures Annual Rate (1990-2024)
M2 Dollars in circulation +5.7%
CPI Government-defined consumer basket +2.8%
Deflation Index Core technology costs -9.2%

Why M2 is the right comparison:

M2 represents the monetary environment in which technology operates. When the money supply expands, that expansion must flow somewhere. The question is: where?

The Deflation Index shows that technology costs fell 9.2% annually against a backdrop of 5.7% monetary expansion. That's a 14.9 percentage point divergence. This divergence is real regardless of what CPI reports.

What about CPI?

CPI averaged 2.8% over this period—lower than M2 growth. This doesn't disprove the DI-M2 gap. It raises a different question: where did the rest of the monetary expansion go?

The answer is visible in asset prices—equities, real estate, and education costs have far outpaced both CPI and M2 since 1990.

Key insight: Inflation is not a single number—it's a vector affecting different goods, services, and assets at vastly different rates. The DI-M2 gap reveals the scale of technological deflation relative to monetary expansion, and raises the question of why these efficiencies don't appear in consumer prices.

So where does the productivity go? +

This is the central question. The 14.9pp annual DI-M2 gap compounds into massive divergence—technology makes things cheaper, but consumers don't see the benefit. Where does it go?

1. Corporate Profits: Up 300%+ since 1990, heavily concentrated in the top 10% of earners. Productivity gains often boost margins rather than reducing prices.

2. Asset Inflation: Stocks +1,500%, housing +400% since 1990. These aren't captured in CPI but represent where much of the monetary expansion flows. Asset holders capture the gains.

3. Technology Platforms: Network effects and monopoly pricing power allow tech companies to capture value rather than pass savings to consumers (despite costs falling).

4. Complexity Costs: Healthcare, education, and housing costs rising faster than wages. Some productivity gains absorbed by increasing regulatory, compliance, and distribution complexity.

5. Quality Improvements: Better goods at the same nominal price (partially captured in hedonic CPI adjustments, but often understated).

6. International Arbitrage: Manufacturing moves offshore (capturing labor cost deflation), but profits stay domestic and flow to shareholders/management.

The pattern: Productivity gains flow upward to capital holders and asset owners rather than downward to consumers through lower prices.

Why only four sectors? What about housing/healthcare/education? +

Short answer: We're focused on sectors showing clear, measurable technological deflation. Housing, healthcare, and education are planned for future expansion.

The four current sectors (computing, communications, energy, transportation) were chosen because:

  • Exponential cost reduction: All show 20-40% annual deflation rates
  • Clean measurement: Objective cost-per-performance metrics ($/GFLOPS, $/GB, $/kWh)
  • Fundamental inputs: These technologies underpin the entire economy
  • Data availability: Reliable 35-year datasets from authoritative sources

Why not housing/healthcare/education yet?

These sectors show inflation (costs rising) despite technological improvements. They're critical to understanding the full picture, but require different analytical frameworks. We're developing methodologies to incorporate them in v4.0.

Future roadmap: Version 4.0 (planned for 2027-2028) will add healthcare, education, and housing sectors with rebalanced weights across all seven sectors.

Data & Methodology

Is the data public and verifiable? +

Yes. Complete transparency is foundational to this project.

What's public:

  • All raw data: Available on GitHub in Excel and CSV formats
  • All formulas: 700+ verified formulas with zero errors, all documented in Excel files
  • All sources: Every data point includes source citations (FRED, IRENA, BloombergNEF, DOE, FCC, AI Impacts, etc.)
  • Complete methodology: 100,000+ words of documentation explaining calculations, assumptions, and quality standards

Data quality verification:

  • 400+ data points across 35 years (1990-2024)
  • 700+ formulas verified with zero errors
  • Average source reliability: 92/100 (A-grade)
  • All data has quality flags (A/B/C/D grades)

Reproducibility: Anyone can download the Excel files, verify every formula, check every source, and reproduce the DI. This is open research.

Do you have a glossary of terms? +

Key Terms:

Deflation Index (DI): Composite measure of technological cost reductions across computing, communications, energy, and transportation (1990-2024).

DI: Weighted average of four sector indices. Fell from 100 (1990) to 3.74 (2024) = 96.26% total deflation.

M2 Money Supply: Broad measure of money supply including cash, checking deposits, savings deposits, and money market funds. Grew 550% from 1990-2024.

CPI (Consumer Price Index): Government measure of consumer price inflation. Rose 155% from 1990-2024.

The DI-M2 Gap: The divergence between technological deflation (-9.21% annually) and monetary expansion (+5.7% annually) = 14.9 percentage points annually.

Cost-per-performance: Metric measuring price per unit of capability (e.g., $/GFLOPS for computing, $/kWh for energy). Captures true technological progress better than nominal prices.

Percentage points (pp): Absolute difference between percentages. Example: 10% minus 5% = 5 percentage points, not 5%.

For comprehensive definitions, see the methodology documentation.

How often is the index updated? +

Current status: The Deflation Index v3.0.2 is complete through 2024 with zero formula errors and comprehensive 1990-2024 coverage.

Update schedule:

  • Annual updates: Full recalculation with new year's data (typically released Q1 of following year)
  • Quarterly reviews: Minor corrections and data quality improvements
  • Major versions: New sectors or methodology changes (e.g., v4.0 will add healthcare/education/housing)

Planned for 2026:

  • Monthly DI updates (automated data pipeline)
  • API v1.0 launch for real-time access
  • Email newsletter with monthly updates

Data freshness: Most underlying data sources (M2, CPI) are updated monthly by authoritative sources (Federal Reserve, BLS). We'll incorporate these as they become available.

Follow GitHub for update notifications.

Comparisons & Usage

How does this compare to other deflation indices? +

While price indices and hedonic adjustments exist, no publicly available index specifically isolates technology-driven cost deflation across multiple sectors and measures it against monetary expansion. The Deflation Index fills that gap. Here's how it compares to related work:

vs. CPI (BLS): CPI measures consumer prices, not technological capability. Hedonic adjustments attempt to capture quality improvements but systematically understate technology's deflationary force.

vs. PCE Price Index (BEA): Similar to CPI but uses different methodology and weights. Still focused on consumer experience, not technological potential.

vs. GDP Deflator: Broad measure of price changes across entire economy. Useful for macroeconomics but doesn't isolate technological deflation.

vs. Nordhaus (2007) computing price index: Groundbreaking work measuring computing deflation (which we build upon), but limited to computing sector only. We extend across four sectors.

vs. Quality-Adjusted Price Indices (various): Academic work on hedonic pricing is excellent but scattered across sectors and time periods. The DI provides unified, consistent methodology across decades.

What makes the DI different:

  • Multi-sector scope: Computing + Communications + Energy + Transportation in one index
  • Explicit monetary comparison: DI vs. M2 vs. CPI reveals where productivity gains flow
  • Long time horizon: 35 years (1990-2024) shows exponential effects
  • Complete transparency: All data, formulas, and methodology public on GitHub
  • Forward-looking: Designed to expand (healthcare, education, housing in v4.0)

To our knowledge, no other index measures economy-wide technological deflation against monetary expansion with this level of rigor and transparency.

Can I use this data for my own research/analysis? +

Yes, with attribution.

The data is currently under a proprietary license, but we strongly encourage academic, journalistic, and policy research using the Deflation Index.

Permitted uses:

  • Academic research: Cite the Deflation Index in papers, dissertations, and publications
  • Journalism: Reference findings in articles and reports
  • Policy analysis: Use data to inform economic policy recommendations
  • Educational: Teaching economics, monetary policy, or technology trends
  • Personal analysis: Blog posts, Twitter threads, newsletter content

Required attribution:

"The Deflation Index: Measuring Technological Progress (1990-2024), Deflation Index LLC, v3.0.2, available at github.com/deflation-index/deflation-index"

Not permitted without permission:

  • Commercial redistribution or resale of the data
  • Incorporation into proprietary financial products
  • Derivative indices marketed commercially

API access: Premium institutional API access will be available in 2026 ($10k-50k annual). Contact us for early access.

Collaboration welcome: If you're working on related research, we'd love to hear about it. Reach out at [email protected].

Engagement

How can I contribute or provide feedback? +

We welcome contributions, suggestions, and constructive criticism.

Ways to contribute:

1. Data improvements: If you have better data sources or spot errors, please open an issue on GitHub with details and citations.

2. Methodology feedback: Challenge our assumptions, suggest alternative calculations, or propose new sectors to track. We're committed to rigor and welcome scholarly debate.

3. Sector expansion: Have expertise in healthcare, education, or housing cost dynamics? We need domain experts for v4.0 expansion.

4. Code contributions: Improvements to data pipelines, visualization tools, or API development welcome via GitHub pull requests.

5. Spread the word: Share the research with economists, policymakers, journalists, and investors who might find it valuable.

Contact channels:

What we value: Precision, transparency, intellectual honesty, and constructive engagement. If you see something that looks wrong, speak up. If you have ideas to improve the work, we want to hear them.

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