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I appreciate you've provided more specific data points, as it helps clarify our core disagreement. You're arguing the CPI is systematically manipulated, while I'm arguing that your examples are a misunderstanding of purpose of a constant quality index in statistics and the very methods used to ensure its statistical accuracy. Your claim that the CPI doesn’t match what the majority of working class households are experiencing' relies on a key assumption: that the CPI is designed to measure the personal inflation rate of a specific demographic. It's not. The CPI is a national, statistical average for all urban consumers. It's impossible for a single number to perfectly represent every household, from a single retiree to a family of five. You're using an anecdotal argument about a specific group and trying to apply it to a national average. If the CPI was only weighted for low-income budgets, it would be inaccurate for everyone else You point out that electricity and car insurance are weighted low, even though they can be a large part of a working class budget. This brings us back to the central issue. The CPI is not designed to show what a single household spends. It reflects that the national average household budget isn't composed solely of these rising costs. Some people don't own cars, and for others, car insurance is a small fraction of their expenses. The weights are determined by the CES, which tracks the actual spending habits not assumed, of thousands of households to create a representative national picture, not a manipulated one. Regarding rent and OER, If they just used the index for residential rent, CPI would be excluding home owners costs/behaviours. You're right to question if a homeowner's survey response is a perfect proxy for the real world. However, the Bureau of Labor Statistics (BLS) uses this method for a specific reason and critically supplements it with other data. CPI It includes a separate index for residential rent which tracks the rent paid by actual tenants. Both are combined to accurately represent shelter for all renters and all homeowners. Real time transaction data from online real estate marketplaces has been debated or is still being debated, it might be more accurate and be better than a home owners estimates, using real time transaction data might happen in the future but there a number very real issues with introducing and lowering the accuracy of the CPI, but there are also advantages so the its no settled, just using a feed of price data is inaccurate as It is designed to measure the change in the price of a constant basket of goods, not just the prices of new listings. A simple index of asking rents could overstate inflation by not accounting for the difference between new and renewed leases. Or new home prices don't account for the cost of people who didn't buy current home. On your point about health insurance premiums, you've stumbled upon quite a technical aspect of the CPI, but your conclusion is incorrect. The CPI doesn't use 'insurer retained earnings' to 'show decreases when premiums spike.' The methodology is a way to avoid double counting inflation. The CPI already measures the cost of hospital stays, doctor visits, and prescriptions. If it also included the portion of your premium that pays for those exact same services, it would be double counting the inflation. The index is designed to measure the change in the administrative service of insurance itself. It's a precise, if counterintuitive, way to isolate price changes and not double count. Your argument that removing these makes the CPI less correct is backwards. These are not manipulations, they are critical to creating an accurate, constant quality index. Substitution isn't a random assumption, it's based on how consumers actually behave. When the price of steak goes up, people buy more ground beef. A fixed basket of goods would ignore this real world consumer behavior and overstate inflation. If people aren't swaping its not changed. Hedonic adjustments ensure that we are comparing apples to apples. If a new phone costs more but has a better camera and processor, the CPI adjusts for the fact that you are getting a higher quality product. Without this, the CPI would be wildly inflated, because you are not buying the same product as you were a year ago. It would be like saying the cost of a car went up 20% when a new model now has airbags and GPS, which the old one didn't. The adjustment separates a true price increase from a quality improvement. A criticism might be that while a phone might get a processor that's twice a powerful is adjusted in CPI to account for the improvment, its also very true that other features and software updates might require this and phone is not twice as fast, while CPI accounts for this and is highly exhaustive, it does not account for the realties that you are virtually required to use a better phone than 25 years ago. So it's very true it doesn't account for the costs to stay up to date with current technology, same with a new car example, certain new features are now required in all cars. You might think this is a failure to account for, but again it's intentional, CPI is truly focused on a absolute direct comparison of goods, the goal is exclude so it's like we always comparing the same items. Like core inflation, it purposely excludes volatile items like food and energy, it's not manipulated down further, it serves a different purpose to headline inflation. Your specific examples of electricity, insurance, and rent are not evidence of manipulation. On the contrary, they are all real world data points that the CPI collects and uses. The issue is that you are looking at specific items in isolation, while the CPI is looking at a weighted average of the entire national economy. Looking at the inflation items individually might make more sense. The CPIs methods, from its weighting to its adjustments, are specifically designed to provide an accurate, non anecdotal measure of headline inflation. To suggest they are structurally downplayed is simply a misunderstanding of the CPIs goal - To measure the average change in prices, not to represent a specific personal or working class budget, it's not meant to show the full burden you experience, it's not including the cost to rent/buy a home today, buying a home today is not average, the current cost to buy/rent isn't is far from the average. Or the true to cost to stay up to date in our world, like the technology or car example. These are intentional specific features not a flaws.
The arguments I have made about the CPI not being a reflection of your personal life are a direct response to your previous comments about "what the average consumer actually experiences" and "what households actually experience." These are not strawman arguments; they are direct rebuttals to the common misconception that an individual's financial reality should perfectly align with a national statistical average. I assumed your previous claims were anecdotal because you provided no data to support them. My point is that the CPIs purpose is to provide that national average, and its backed by rigorous, evidence based data collection. Respectfully, the examples of evidence you're providing only strengthen CPIs accuracy. The CPI doesnt ignore the data you cited it measures it. You are simply confusing the percentage increase of an individual item with its overall impact on the total cost of living. The CPIs job is to reflect the change in the total cost of living, not just the change in the cost of a single item. Claiming that the CPI is wrong because one items price has risen significantly is to ignore the reality that people don't spend 100% of their income on that one item. The CPI does not ignore that a specific item like electricity, went up by 20%. Instead, it accurately accounts for that increase based on how much of the average household budget is spent on that item. For instance, if the average household spends only 3% of its budget on electricity, then a 20% increase in electricity costs would only add a small amount 0.6% to the overall inflation number. The CPI includes data for electricity, car insurance, rent, and health insurance. Your specific numbers are valid real world data points specifically used to improve the CPIs accuracy. The core of that issue is that you are looking at specific, individual price increases while the CPI is looking at a weighted average of the entire national economy. The CPI's weights are determined by the CES, which tracks the spending habits of thousands of households. The CPI reflects that the average household budget is not composed solely of these rising costs. It also includes items that may have seen a smaller price increase or even a decrease, such as electronics or clothing. The CPI's methodology ensures the final number is a reflection of the overall cost of living, not just the most painful rising expenses. Your claim that the CPI is disconnected from the "real-world budgets of ordinary households" is a fallacy of internal contradiction. You are using the exact data that is collected for the CPI—like the price increases for electricity and car insurance—to argue that the CPI is incorrect. It's like arguing that a recipe is wrong, and your only evidence is a list of the ingredients from that very recipe.
I understand you feel my argument is a strawman fallacy, but I'm not arguing that your personal experience or others is invalid. I am arguing that anecdotal evidence, whether from a single person or a group of people, is not a valid basis for refuting a massive, comprehensive, open/transparent, evidence based, globally scrutinsed, national data set. My point about treating every data point that doesn't align with your personal experience as a sign of a conspiracy is simple, the only evidence you have provided is anecdotal. I'm guessing you haven't rigorously assessed the spending of the entire nation, so your argument appeared based on feelings, not data. My point has always been that the CPI measures the average consumer, and the experience of an individual household is not always reflected in a national average. This is not a strawman, it's a direct rebuttal of the claim that the CPI is 'disconnected from the people it's supposed to measure'. Your claim that CPI should 'better reflect housing costs' is also at odds with you own logic. The CPI already reflects housing costs, but it uses OER because it measures consumption not investment. A home is not a typical consumed good or service. The CPI's use of OER is the most accurate way to reflect the cost of a home as a service. You clealy said there values are being adjusted down, thats also the opposite of reality. Are you saying you would want it adjusted up more or you simply want to include the total costs? Your claim that CPI 'underweights or adjusts away the biggest pressures people feel' is incorrect. The data from the CES is used to determine those weights. These are large scale, ongoing surveys that track the spending habits of thousands of households across the country. For example, if the data shows that the average household spends 3% of its budget on electricity and 15% on transportation, that's exactly how much those items are weighted in the CPI calculation. To claim this process is inaccurate is to ignore the statistical reality of how people actually spend their money. Your claim that the CPI doesn't align with the "real world budgets of ordinary households" and that there's no evidence for its accuracy is an unsupported argument. The evidence for the CPI being the best available approximation of the average consumer is its own exhaustive, transparent methodology. The CPI is a direct, evidence based approximation of the average consumers budget. Its disconnect from a specific household is not a flaw in its design, it is simply the nature of any statistical average. A specific household's budget may not perfectly align with the national average, but the CPI is the best, most rigorously collected data we have to show the collective spending patterns of the population. Acting like you know more than the combined knowledge of the global pension funds, hedge funds, global banks, foreign governments, and all individual market participants who collectively hold a vast amount of a government’s debt isnt a strong position. The market's collective judgment, based on real financial risk, is a far more reliable indicator of the true state of the economy than any individual's opinion. It aggregates the collective intelligence and financial decisions of millions of participants and it carries much more weight.
The article "https://www.mdpi.com/1911-8074/18/2/66" by Murray A. Rudd and Dennis Porter (2025) develops a rigorous economic model to forecast Bitcoin prices based on its fixed, inelastic supply (capped at 21 million coins) and evolving demand dynamics, particularly institutional adoption and long-term holding behavior. Summary of Key Points: Bitcoin Supply Characteristics:** Bitcoin’s supply is fixed and perfectly inelastic with a 21 million coin cap. Supply expansion slows via periodic halvings (block reward reductions) roughly every 4 years; the latest occurred in April 2024. Liquid supply is significantly less than total issuance due to lost, long-term held (HODL) coins, and coins held as strategic reserves. Demand Side Factors:** Demand is modeled using a Constant Elasticity of Substitution (CES) demand function with parameters calibrated to market data. Institutional, sovereign, and corporate accumulation (strategic reserves) reduces liquid supply, intensifying scarcity. Credit-driven demand expansion and increasing adoption shift demand curves outward over time. Model Framework:** The model sets April 20, 2024 (fourth halving) as the baseline with: Issued Bitcoins: ~19.7 million. Liquid supply estimated at ~11.2 million. Market price at $ 64,858 USD. Projections extend to the seventh halving (~April 2036), a 12-year horizon. Model parameters can be adjusted for demand growth (demand shift multiplier), daily Bitcoin withdrawals into reserves, elasticity, adoption curve timing, and lost coins. Uses a discrete daily supply-demand equilibrium approach implemented in Analytica software. Price Forecasts and Scenarios:** | Scenario | Demand Multiplier (D) | Daily Withdrawals to Reserve | Forecast Price Range by 2036 (USD) | Notes | |----------|-----------------------|------------------------------|------------------------------------|-------| | Baseline | 1x | 0 to 2000 | Approx. $62,000 to $ 106,000 | Near current price, stable | | Moderate | 10x - 20x | 0 to 2000 | $639,000 to $ 2.2 million | Moderate adoption, growing reserves | | Bull | 30x - 40x | 0 to 2000 | $1.9 million to $ 4.4 million | Aggressive institutional adoption and high withdrawals | | Conservative (Dec 2024 Recalibration) | D=20, elasticity ~ -2.1 | 0 to 4000 | $98,577 to $102,808 (as of Dec 2024) | Prices ~$1M by mid-2028 with withdrawals | | Bull (Fast Adoption) | D=30, elasticity ~ -1.8 | 0 to 4000 | $1M by early 2027, up to$5M by early 2031 | High institutional demand | Price Trajectory Insights:** Price appreciation is sensitive to both increased demand and reductions in liquid supply. Modest withdrawals to long-term reserves (e.g., thousands per day) could drive Bitcoin to $ 1 million+ within 3-6 years. High withdrawal rates accelerate supply shocks, causing hyperbolic price growth and increased volatility. Demand growth has a more substantial short-run impact than modest changes in liquid supply. Power law models predicting decreasing volatility may be incorrect; price volatility may increase as supply dwindles. Comparisons with Other Models:** Model forecasts align well with MicroStrategy’s financial models (multi-million dollar price by 2036-2045). ARK Invest’s forecast ( $3.8M by 2030) suggests even higher demand multipliers or more constrained supply scenarios. Limitations & Future Work:** Assumptions about lost coins, HODL behavior, and market elasticities remain uncertain. The framework excludes complex network effects, Layer-2 impacts, and macro shocks explicitly. Future modelling could include stochastic simulations, multi-commodity interactions, or survey-derived demand curves. Bitcoin Price Prediction Schedule Summary: | Date/Period | Event/Predictor | Forecast Price Range (USD) | |--------------------------|------------------------------------|-------------------------------------| | April 2024 (Baseline) | Price at 4th halving (start) | $ 64,858 | | Mid-December 2024 | Market price update; scenario recalibration | ~ $98,577 - $ 102,808 | | Mid-2027 to Early 2028 | Bull scenario (high demand, withdrawals) | $1 million+ | | Mid-2028 to 2030 | Moderate to high adoption & withdrawals | $1M to$2.5 million | | Early 2031 | Bull scenario peak prices | Up to $ 5 million | | April 2036 (7th halving) | Long-term equilibrium prices | $62k (low adoption, no withdrawals) to multiple millions (high demand & withdrawals) | Summary of What Drives Price Increases: Institutional & sovereign investors withdrawing Bitcoin from the liquid market (strategic reserves). Growth in adoption shifting demand curves outward significantly (multipliers 10x to 40x). Rising scarcity as the supply schedule approaches the hard cap. The interaction of inelastic supply with evolving demand creates potential for steep price appreciation and volatility. For Reference and Further Reading You can read the full article and see detailed figures, charts, and data at the official MDPI link to the article: https://www.mdpi.com/1911-8074/18/2/66 In brief, this framework presents a flexible, realistic economic foundation for Bitcoin price forecasting showing significant long-term upside potential driven by supply constraints and increasing institutional demand, with predicted price targets ranging from ~$100K today to several million USD by 2036 depending on market dynamics.
Some brokers are offering white glove services - although these come in handy when volume is particularly high in consideration of liquidity (say, above 10-15% of the total liquidity). What is usually done, is selling through several DEXes at once, to benefit from several liquidity pockets. Some platforms allow for smart routing, splitting the order across multiple DEXes and working them in-line with volume (think, Coinbase Prime for instance). It is however not always sufficient. In such cases, some counterparties may offer to source liquidity OTC and execute in blocks until the order is filled. Again, it is the activity of certain desks, such as CES (the “white glove” service from Coinbase).
When you say his economy lost a net 178k jobs during his presidency, you omit the fact that by March 2020, Trump's admin had seen a net [gain](https://data.bls.gov/timeseries/CES3000000001) of over 350,000 manufacturing jobs. The losses were very clearly due to covid. Why do you find it necessary to present misleading "facts" like that?
[Those are rookie numbers](https://www.youtube.com/watch?v=CES1OIkFhg4)