The Price of Everything Is the Price of the Dollar
in the companion piece i used the Big Mac – same recipe, same burger, fifty-nine years running – to show that prices outpace official inflation by a wide margin. a 154% increase on a fixed product against an 82% CPI reading. the data case was clear
but this isn't about burgers. the same pattern shows up everywhere you look. housing, cars, eggs, healthcare, education – products that benefited from real technological improvement yet cost dramatically more than they did a quarter century ago. this piece asks the harder question: why is anything getting more expensive when we keep getting better at making it?
five products, one pattern
pick five products from unrelated sectors so no single industry quirk can explain the result. then look at what happened between 2000 and 2024:
| product | ~2000 price | ~2024 price | increase | key productivity gain | |---------|-------------|-------------|----------|----------------------| | median home | ~$165,000 | ~$420,000 | ~155% | prefab, materials science, CAD/BIM – yet construction labor productivity fell ~30% since 1970 | | new car | ~$21,000 | ~$48,000 | ~129% | global robot installations up 10% in 2024; automakers report 2-3x productivity from automation | | dozen eggs | ~$0.96 | ~$3.24 | ~238% | 27% more eggs per hen per day, 42% better feed conversion (United Egg Producers) | | college tuition (private 4-yr) | $15,470 | $38,421 | ~148% | online learning, digital textbooks, massive enrollment scale | | healthcare (per capita) | ~$4,800 | ~$14,500 | ~202% | MRI, robotic surgery, telemedicine, genomics – yet technology is "the most important long-run driver of spending growth" (KFF) |
every one of these sectors experienced genuine productivity improvement. every one saw prices rise anyway. over the same period, M2 money supply grew ~330%. official CPI claims inflation was ~82%. not a single one of these five products stayed within the CPI range
the chart tells a story that CPI can't. the official index says your dollar lost about 45% of its purchasing power since 2000. your house says it lost 61%. your healthcare says 67%. your eggs – when avian flu hit an already-inflated base – say 70%. the gap between CPI and lived experience isn't a mystery. it's measurement error compounding over decades
the proof case: things measured in physics
a flat-screen TV cost $5,000 in 2000. today the equivalent costs $300. but electronics aren't the only example. the pattern repeats across every technology-intensive sector:
- solar panels fell from $4-5/watt to under $0.40/watt – a 90%+ decline. swanson's law: cost drops 20% for every doubling of cumulative production
- genome sequencing dropped from $95 million per genome in 2001 to ~$200 today – a 99.9998% reduction that outpaces Moore's Law
- data storage went from $12/GB in 2000 to $0.01/GB – down 99.9%
- LED lighting collapsed from $40 per 60-watt-equivalent bulb in 2010 to under $3 – haitz's law drives a 10x cost drop per decade
- lithium-ion batteries fell from $1,474/kWh in 2010 to $115/kWh in 2024 – a 93% decline despite rising raw material costs
these products all use raw materials, energy, labor, and logistics – the same input categories as homes, cars, eggs, and everything else. the difference is that their performance is measured in physical units: watts, lumens, gigabytes, base pairs. when you measure progress in physics, you see deflation. when you measure it in dollars, you see inflation
housing, food, cars, healthcare, and education all experienced the same category of improvement – just at a smaller scale. 20-40% cumulative efficiency gains across their input stacks. real gains, not enough to outrun M2
so why did solar panels get cheaper while eggs got more expensive?
the threshold
the answer is magnitude
M2 grew ~330% from 2000 to 2024. to show a lower nominal price, a product's real cost reduction must exceed that expansion. solar panels had a 90%+ decline. genome sequencing had a 99.9998% decline. LEDs had a 95%+ decline. these gains were so massive that they overwhelmed the money printer and still showed falling prices in dollar terms
now look at the five products. construction gained maybe 20-30% in materials efficiency but lost ground in labor productivity. automotive assembly got faster but vehicles got heavier and more complex. egg production improved 27-42% across different metrics. healthcare developed extraordinary technology that often raises rather than lowers per-unit costs
the pattern is clear: when productivity gains exceed monetary expansion, nominal prices fall (solar, LEDs, storage). when productivity gains are real but smaller than monetary expansion, prices rise anyway (housing, cars, eggs, healthcare, tuition). the dividing line is M2
every one of the five products should be cheaper. the gains were genuine. they just weren't 330% genuine
the answer is the money
here's the critical reframe: input cost inflation IS monetary inflation
the median home didn't become 155% more expensive because lumber got harder to mill or concrete got harder to pour. lumber mills got more productive. concrete mixing went from manual batching to computer-controlled automation. what happened is that lumber, concrete, land, labor, permits, and financing are all denominated in dollars. when you expand the dollar supply by 330%, everything priced in dollars adjusts upward
milton friedman put it plainly: "inflation is always and everywhere a monetary phenomenon." ludwig von mises was more precise: "what people today call inflation is not inflation, i.e., the increase in the quantity of money and money substitutes, but the general rise in commodity prices and wage rates which is the inevitable consequence of inflation"
eggs didn't triple because hens got less productive – they got 27% more productive. cars didn't double because robots got slower – they got faster. healthcare didn't triple because MRI machines got worse – they got dramatically better. in every case, the supply chain improved while the price rose. the "rising cost" of each product is not an independent variable. it's the same variable – monetary expansion – measured at different points in the production structure
this is the cantillon effect in action: new money enters the economy at specific points and ripples through unevenly. housing sits closest to credit creation (mortgages are literally new money), which is why it often leads the pack. eggs sit at the end of a long supply chain, so the inflation arrives last and looks like "food costs going up" rather than what it actually is
actual prices vs sound-money counterfactual
the green line isn't a precise forecast – individual prices fluctuate year to year, droughts happen, housing crashes happen, supply shocks are real. the point is the trend direction. george selgin made the theoretical case in less than zero: in a growing economy, prices should naturally fall as productivity rises. central banks inject money specifically to prevent this deflation. the 2% inflation target doesn't maintain stability – it actively prevents prices from falling when they should
the gap between the green line and the actual prices is the monetary expansion component – real productivity gains that were produced, absorbed, and never reached you
why do actual prices sit below the M2 line? because M2 velocity fell from 2.13 in 2000 to 1.39 in 2024 – a 35% decline. each dollar circulated fewer times. velocity hit a record low of 1.13 during COVID (Q2 2020) precisely when the Fed was adding ~$4 trillion to M2. much of the expansion was trapped as excess bank reserves or channeled into asset prices rather than the goods market. the effective monetary throughput – M2 multiplied by velocity – grew roughly 215%, not 330%. actual price increases across the five products sit squarely within that adjusted range
we've seen this before
the sound-money counterfactual isn't hypothetical. we have a 26-year test case
from 1870 to 1896, under the classical gold standard, US wholesale prices fell 37% while real GDP grew at roughly 4% per year – one of the highest sustained growth periods in American history. real wages rose. the middle class was born. this was not a depression. it was what happens when productivity compounds and the unit of account doesn't expand
the numbers were dramatic. steel rails went from $140 per ton in 1872 to $11.50 by 1900. wheat fell 40%. cotton fell 49%. railroad freight rates dropped 63%. every productivity gain flowed to consumers as lower prices because the measuring stick was fixed
when steel technology improved under a fixed money supply, steel prices fell. when construction technology improved under an expanding money supply, housing prices rose. when egg production improved under a fixed money supply, food got cheaper. when egg production improved under an expanding money supply, eggs cost three times as much. the difference between these outcomes is the monetary regime
what about the objections
fair question. each product has its own complications:
housing: zoning restrictions, NIMBYism, environmental review, and genuine land scarcity in desirable cities. these are real constraints – but they're denominated in dollars. impact fees, permit costs, labor costs, land prices. when the dollar loses value, every layer of regulation gets more expensive in nominal terms. zoning didn't change M2. M2 changed the price of everything zoning touches
cars: vehicles got bigger, heavier, and more feature-laden. the average new car gained ~700 lbs since 2000. consumers chose SUVs over sedans. this is real quality change – but also margin extraction enabled by monetary expansion. the fed funds rate made 72- and 84-month auto loans normal, obscuring the total cost
healthcare: baumol's cost disease is genuine – services that require skilled human time resist productivity gains. the AMA limits physician supply. regulatory capture adds layers. but even Baumol acknowledged that cost disease operates within a monetary context. when the money supply is fixed, the Baumol effect is bounded – labor costs can't rise faster than productivity elsewhere in the economy
eggs: avian flu in 2022-2023 killed 96 million birds. a genuine supply shock. but egg prices were already 60% above 2000 levels before the first outbreak. the flu was real. the underlying trend was monetary
all valid nuances. none explain the full gap between productivity improvement and price increase. and every one of these complications – land prices, labor costs, regulatory fees, feed costs, construction materials – is denominated in dollars
what this means
most people experience inflation as a cost-of-living problem – can I afford what I used to afford? that's the question CPI was built to answer, and it answers it by quietly adjusting the basket downward, showing you the cheapest path through rising prices
but there's a deeper question that this framing hides: why is anything getting more expensive when we're getting better at making it? and it's not just one product. houses are better-insulated and worse-affordable. cars are safer and less-reachable. eggs come from more productive hens and cost three times as much. healthcare uses space-age technology and bankrupts patients. education scales to millions online and charges more per seat
the pattern isn't hiding. it's on every receipt you've ever gotten – you just need to hold the productivity improvement fixed long enough to see it. technology improves the inputs. monetary expansion consumes the gains. the price goes up. and we're told that's normal
it isn't normal. it's a policy choice. and every product in this article – five unrelated sectors, five sets of genuine productivity gains, five prices that rose anyway – makes that choice visible
sources: median home prices: FRED MSPUS. new car prices: BLS CPI and Kelley Blue Book. egg prices: BLS series APU0000708111. college tuition: NCES Digest of Education Statistics. healthcare spending: CMS National Health Expenditure Data. CPI: BLS series CUUR0000SA0. M2: FRED series M2SL. M2 velocity: FRED series M2V. construction productivity: McKinsey Global Institute; Richmond Fed. automotive robotics: IFR World Robotics 2024. egg production: United Egg Producers. healthcare technology and spending: KFF; Health Affairs. solar costs: Our World in Data. genome sequencing: NIH/NHGRI. battery prices: BloombergNEF. excess reserves: Cleveland Fed. gold standard deflation: NBER. productivity norm: Selgin, Less Than Zero (IEA, 1997). cantillon effects: Sieron, Money, Inflation and Business Cycles (Routledge, 2019). baumol's cost disease: Nordhaus, NBER Working Paper 12218 (2006). quantity theory (150-year panel): Jung, ECB Working Paper 2940 (2024). avian flu: USDA APHIS. vehicle weight trends: EPA Automotive Trends. physician supply: AAMC. enrollment data: NCES.
