figures in parentheses are cpi basket weights in 2024. the food component is defined as food and non - alcoholic beverages. the mpc monitors closely a range of measures of underlying inflation. we take a forward - looking approach given the lags in monetary policy. a simple and observable proxy measure is services inflation, as services prices are mainly affected by domestic and slowermoving factors. even though headline inflation fell steeply from its peak and has been around target for half a year, services inflation is still above its pre - pandemic average ( chart 2 ) – it was 5 % in october and we expect it to stay around that rate for another few months. as a result, as the tailwind from lower energy prices dissipates, we expect headline inflation to rise back to 2. 8 % in the third quarter of 2025. chart 2 : services inflation still above its pre - pandemic average sources : ons and bank calculations. chart shows the mpc ’ s latest near - term inflation forecast, consistent with the november mpr. it does not reflect the october cpi data released on 20 november, which was broadly in line with this forecast. core goods = goods excluding food and non - alcoholic beverages, alcohol, tobacco and energy. dashed lines represent 2010 - 19 averages which are 3. 0 % and 0. 8 % for services and core goods respectively. wages are a material driver of services prices, and the slower - moving nature of services inflation reflects in large part the relatively high ‘ stickiness ’ of wages compared with other prices. this is clear in chart 3, which shows a model - based decomposition of a “ core ” measure of services inflation. [ 1 ] this model specifies core services inflation in terms of pay growth and manufacturing producer output inflation ; the latter captures the cost of goods used to produce services, including energy. the model suggests that most of services inflation is driven by what ’ s happening to pay growth. chart 3 : wage growth is a material driver of services inflation sources : ons and bank calculations. core services inflation excluding rents. final data point is 2024 q3. the model is estimated on seasonally adjusted quarterly data excluding vat. estimated contributions to services inflation are based on autoregressive distributed lag regressions of services inflation on pay growth ( orange bars ) and manufacturing ppi inflation ( aqua bars ). see also greene ( 2024 ) and mann ( 2024 ). in principle, higher -

. the theoretical clues come from a literature that flourished after the stock market crash of 1987 – the so - called market microstructure literature. 5 this departs from the notion of frictionless trading and information - efficient prices. in its place it introduces frictions in the price - setting process, which arise from characteristics of market participants ( such as their trading speed ) and of the trading infrastructure ( such as its degree of fragmentation ). “ latency ” refers to the time it takes from sending an order to it being executed. for example, o ’ hara ( 2004 ). bis central bankers ’ speeches frictions in pricing arise from the process of matching buyers and sellers. here, the role of market - makers is key. the market - maker faces two types of problem. one is an inventorymanagement problem – how much stock to hold and at what price to buy and sell. the market - maker earns a bid - ask spread in return for solving this problem since they bear the risk that their inventory loses value. 6 market - makers face a second, information - management problem. this arises from the possibility of trading with someone better informed about true prices than themselves – an adverse selection risk. again, the market - maker earns a bid - ask spread to protect against this informational risk. 7 the bid - ask spread, then, is the market - makers ’ insurance premium. it provides protection against risks from a depreciating or mis - priced inventory. as such, it also proxies the “ liquidity ” of the market – that is, its ability to absorb buy and sell orders and execute them without an impact on price. a wider bid - ask spread implies greater risk in the sense of the market ’ s ability to absorb volume without affecting prices. this basic framework can be used to assess the impact of the changing trading topology on systemic risk, moving from analysing market microstructure to market macrostructure. take the effects of fragmentation. that heightens competition among trading platforms, offering differing execution options and wider access to participants. this would tend to attract liquidity providers, including cross - market arbitraging hft. as new liquidity - providers enter the market, execution certainty and price efficiency might be expected to improve. inventory and information risk would thereby fall and, with it, bid - ask spreads. some of the early empirical fingerprints suggest just such a pattern. for example, brogaard ( 2010 ) analyses the