Let's run that scenario in a simplified manner of how CPIs are likely actually going to be calculated. First, they have to determine the conceptual basket of g

Let's run that scenario in a simplified manner of how CPIs are likely actually going to be calculated. First, they have to determine the conceptual basket of goods to track. Ok, that's comparable to your 1000 "highest volume" items methodology (albeit yours is a bit simplified too, we'll ignore the problem that good or volume is complicated for everyone). Generally stats bodies do this by looking at what consumers actually spend things on. This seems emminently sensible to me, and no offense intended, superior to a top 1000 volume method. Fuel, presumably, gets included in both. Then they need to assign a weight for every good to determine how much its mixture of quantity + price movements contribute to the CPI figure. I put it to you this is necessary. Every item shouldn't be equally weighted even in your methodology (the distribution of volume of relative goods purcahsed/consumed is guaranteed to not be uniform across all 1000 goods, and it makes no sense for no. 1 to be given an equal weight to no. 999). Stats bodies do this too. This is what is meant by weight adjustment in this context. And both you and stat agencies should be doing it. At some point, your "top 1000" goods is going to change and you're going to have to figure out what is in a new basket at a new time. So too does the CPI basket of goods. You both need to do this. Note that your methodology does not actually fix the fuel-budget-substitution issue. Price movements in your method that invoke a strong enough substitution or consumption effect result in fuel dropping out of your top 1000 as well. By keeping your basket constant for a given period of time and just tracking the good's prices, you track expenditure somewhat consistently for a given period. That's a good thing. There's no reference to changes in a consumer's budget. But...CPI calculating stats agencies do this too for a set basket of goods just like you do. They fix the basket and track it over time, adjusting, like yours, only for re-inclusion the basket of goods under consideration. Lastly, comes the hedonic quality problem. Changes in quality of consumption/goods over time. Some substitutions seem just because of taste or culture (see for example, relative consumption of antimacassars over time, or certain culture's preference for certain foods or items). Others are obviously qualitative in nature (i.e. computer processing power), and most things are a complex mix of tech/economy/culture/price/quality. This is the part that captures and tries to control for your qualitative substitution problem (it's not without its controversies, but I argue that your method needs it as well because it suffers similar problems, and indeed all ones which try to standardise subjective consumption of a national economy into a single figure). Relevant to 'fuel' is its price, but also substitution to other new fuels that turn up (hydrogen, LPG, lithium-ion), but also technology efficiency gains that have changed the consumption to utility ratio. Again, stats agencies try to control for this too. Aside from the definition of the basket of goods (a weakness and methodology shared by your "fix"), there is generally no explicit reference to consumer's budget or assumed spending patterns when tracking within a given basket. There is nothing inherently equivalent to "assumed spare money or choosing to spend or not". (I suppose I'm happy to be proven wrong on this for a given countries methodology). it's not just a simplified survey of median households or expenditure. Now, you can (and many people justifiably do) take issue with ideas and quantification of hedonic quality problems: but it's a universal problem, your method doesn't fix it, and I think you're generally misconstruing how CPIs are calculated around the world. The problems you mention are already attempted to be tackled and controlled for in methodology, and the official methodology is already generally superior to your suggested replacement. Edit: it's also not like stats/economics agencies are doing this WITHOUT an accesible measures of nominal wages (that is wages and resource flows without inflation taken into account) available to them. edit 2: in the real world, further considerations like geography, seasonality, population, etc is additionally controlled and adjusted for. And many stat agencies, in my experience, offer additional breakdowns of other price series, such as geographical and categorical indexes, or various additional weightings and combinations, so if you take issue with headline CPI you can investigate other more appropriate measures for your specific use cases.