Core Inflation Measures Research Articles

Singular spectrum analysis to estimate core inflation in Brazil

This paper presents a set of new core inflation measures for Brazil based on the Singular Spectrum Analysis (SSA) method. The measures are based on the official target used in the Brazilian inflation targeting regime. The period of analysis ranges from the beginning of the inflation targeting regime in 1999 and 2021. The SSA measures were compared to the inflation core ones used by the Central Bank of Brazil, through the evaluation of unbiasedness, short-term adjustment dynamics and predictive ability. The measures estimated by SSA meet the desired properties and have a greater predictive capacity than the other inflation cores.

Weighted Median Inflation Around the World: A Measure of Core Inflation

The standard measure of core or underlying inflation is the inflation rate excluding food and energy prices. This paper constructs an alternative measure, the weighted median inflation rate, for 38 advanced and emerging economies using subclass level disaggregation of the CPI over 1990–2021, and compares the properties of this measure to those of standard core. For quarterly data, we find that the weighted median is less volatile than standard core, more closely related to economic slack, and more closely related to headline inflation over the next year. The weighted median also has a drawback: in most countries, it has a lower average level than headline inflation. We therefore also consider a measure of core inflation that eliminates this bias, which is based on the percentile of sectoral inflation rates that matches the sample average of headline CPI inflation.

An Alternative Measure of Core Inflation: The Trimmed Persistence PCE Price Index

An Alternative Measure of Core Inflation: The Trimmed Persistence PCE Price Index

Euro area inflation and a new measure of core inflation

This paper introduces a new decomposition of euro area headline inflation into core, cyclical, and residual components. Our new core inflation measure, the structural core inflation rate, is the expected headline inflation, conditional to medium to long-term demand and supply-side developments. It shows smoothness and trending properties, economic content, and forecasting ability for headline inflation and other available core inflation measures routinely used at the ECB for internal or external communication. Hence, it carries additional helpful information for policy-making decisions. Concerning recent developments, all the inflation components contributed to its post-pandemic upsurge. Since mid-2021, core inflation has been downward, landing at about 3% in 2022. Cyclical and residual inflation-associated with idiosyncratic supply chains, energy markets, and geopolitical tensions- are currently the major threats to price stability. While some cyclical stabilization is ongoing, a stagflation scenario cum weakening overall financial conditions might emerge. A pressing issue for ECB monetary policy will be to face -mostly supply-side- inflationary pressure without triggering a financial crisis.

An alternative measure of core inflation: the Trimmed Persistence PCE price index

An alternative measure of core inflation: the Trimmed Persistence PCE price index

Evaluating core inflation measures: A statistical inference approach

We propose a framework for consistently evaluating core inflation measures via a straightforward application of sound statistical inference principles. Under this framework, inflation measures (both headline and core) are regarded as estimators tracking the economy’s true, unobserved inflation rate. We depart from the arbitrary convention in the literature of approximating true (or trend) inflation as some moving average of the observed headline inflation. Instead, we regard trend inflation as the unobserved inflation rate that corresponds to the whole population of consumer price changes while the observed inflation measures are estimators of trend inflation based on particular samples of consumer price changes. Hence, the evaluation of inflation measures is rigorously derived from the sampling distribution properties of the corresponding estimators, in contrast to the use of ad hoc criteria for evaluating core inflation measures, prevalent both in the academic literature and in most central banks’ practices. We implement our evaluation approach for the Guatemalan Consumer Price Index (CPI) data by applying a computational bootstrapping technique. Finally, we showcase the evaluation results for the Guatemalan data regarding the performance of some widely used core inflation measures.

A proposal for constructing and evaluating core inflation measures

There is no unifying framework for evaluating core inflation measures, so we propose a methodological framework to close this gap. It allows us to construct, evaluate, and rank core inflation measures by applying it to countries and regions with different characteristics, such as Chile, Colombia, Peru, the euro area, and the United States. Our methodology uses highly disaggregated data of consumer price indexes, and hinges on a standard quadratic loss function. We show that the usual indicator that excludes food and energy, which is the most widespread measure of core inflation among central banks, performs poorly across the five countries analyzed, due to substantial bias, low persistence, high volatility, and low forecasting power. Therefore, our recommendation is to revise its use. By optimally selecting the CPI components to be excluded, the properties of core inflation measures can be significantly improved. Finally, we argue that when there is a preference regarding the use of fixed exclusion measures, nothing is lost and much can be gained by optimally selecting the excluded items, instead of sticking with the usual ad hoc criteria of excluding food and energy. Results remain robust to changes in the sample and methodology.

Euro Area Inflation and a New Measure of Core Inflation

Euro Area Inflation and a New Measure of Core Inflation

PERFORMANCE OF CHINA’S CORE INFLATION MEASURES FOR MONETARY POLICY

In this paper, China’s core inflation is defined as any price changes that are caused by the money supply. This definition is especially relevant to examining monetary policy because the money supply is controllable by China’s central bank. This paper develops a New Keynesian DSGE model with a quantity-based monetary rule that fits real aggregated data from China to analyze core inflation’s key characteristics. Eight different approaches are used to estimate core inflation in China. By constructing VAR models of output growth, money supply growth and core inflation, we estimate the response of core inflation measures to the money supply shock. By matching the response to money supply shocks in both the model and the data, we compare the performance of different core inflation measures for monetary policy in China.

A Multivariate Unobserved Components Model to Estimate Potential Output in the Euro Area: A Production Function Based Approach

This paper builds an unobserved components model that combines a multivariate filter approach with a Cobb-Douglas production function. This combination allows potential output estimates to incorporate more economic structure than the traditional production function approach, while retaining the ability to conduct growth accounting exercises. The model is a backward-looking state space model estimated with Bayesian methods employing the Kalman filter to jointly decompose six key observable variables (real GDP, unemployment rate, labour force participation rate, hours worked per person, a measure of core inflation and wage inflation) into trend and cyclical components. To do so, it relies on several reduced form relationships across the cyclical components, such as a wage and a price Phillips curve and an Okun's law type relationship, while it also assumes common trends for a few variables and allows for hysteresis effects. The model is estimated on aggregate euro area data with Bayesian methods. The paper finds that the resulting output gap estimates have good revision properties and reasonable forecasting performance in particular in terms of GDP and core inflation vis-a-vis a set of benchmarks.

Estimating Trend Inflation with Moving Average and Stochastic Volatility for Nigeria

This study was carried out to estimate underlying inflation in Nigeria using Unobserved Component (UC) model. Also, different channels were used to identify the source of inflation persistence and volatility. This was estimated using Bayesian analysis in order to examine the role of priors in improving the precision of the estimates. Following the analysis, a number of observations were made. Firstly, in terms of methodological contribution, we found that the observed inflation in Nigeria can be modelled by assuming constant volatility as the evidence shows that stochastic volatility (SV) is not a source of observed inflation persistence. However, the variance of the trend inflation can be modelled using regime switching models, where both the mean and variance can be subjected to regime changes. This is because we were only able to establish an evidence of instability not volatility in the variance of the trend inflation. Secondly, we found that the inclusion of autoregressive component in the UC specification leads to volatility in the variance of the observed inflation. Therefore, unobserved component model with MA is more appropriate in modeling inflation persistence in Nigeria which is consistent with empirical regularities. Furthermore, the study found that the observed core inflation (which is the headline less food inflation as released by Bureau of National Statistics, NBS) is being understated. This finding has significant implication for the current measure of core inflation and its application in policy decisions. Therefore, we recommend that the NBS should remove energy components from the observed core inflation in order to have a consistent permanent inflation component in Nigeria.

Alternative Core Inflation Measures in Nigeria: An Examination

Core inflation measures have played an important role in the conduct of monetary policy at various central banks around the world. We examine core inflation in Nigeria using non-traditional measures and assess their persistence, to determine whether the Central Bank of Nigeria (CBN) should pay attention to one or other of these measures when assessing inflation developments. We find that the two new measures outperform the official core rate in tracking the persistence of headline inflation. The findings of this study will aid policy making within the Central bank of Nigeria (CBN) particularly where inflation targeting is adopted as the monetary policy framework. These core inflation measures provide a useful guide to central bankers both for monetary policy decisions and as a communication tool. They are a better predictor of future inflation depicting the more persistent influences on underlying inflation, which are of interest to policymakers (e.g. Clark, 2001; Blinder and Reis, 2005; Smith, 2004 and Dolmas &Wynne, 2008).

Denoised Inflation: A New Measure of Core Inflation

Abstract Existing measures of core inflation ignore a part of ‘should be’ the core inflation. Exclusion based measures ‘exclude’ a part of persistent inflation inherently existing in the excluded part whereas filter based measures ‘filter-out’ the cyclical part also rather than the irregular component only. This study proposes a new idea to define and measure core inflation – noise free inflation or denoised inflation. As against considering only trend to define core inflation, this study proposes using cyclical component also to be part of core inflation. If core inflation is to be useful, for monetary policy making, as an indicator of underlying inflation, it has to include demand related component of inflation associated with current economic cycle. By using wavelet analysis approach to decompose seasonally adjusted price index into noise, cyclical component and trend, we estimate a denoised inflation series for Pakistan for the period July 1992 to June 2017. Since denoised inflation passes ‘statistical’ as well as ‘theoretical’ tests necessary for a series to be core inflation, we think it can be used as a new core inflation measure for Pakistan. This can also be estimated and tested for any country.

Inflation dynamics in Uganda: a quantile regression approach

ABSTRACTThis paper considers the measurement of inflation persistence in Uganda and how this has changed over time within different quantiles. The measures of inflation include headline inflation and two measures of core inflation. The results suggest that while a unit root is found in many of the upper quantiles of headline inflation, there is evidence of mean reversion within the lower quantiles, which implies that large positive deviations influence the permanent behaviour of inflation. In addition, we find higher levels of persistence after 2006 and during the inflation-targeting period, where potential structural changes may have arisen within the regression quantiles.

Comparing Two Measures of Core Inflation: PCE Excluding Food & Energy vs. the Trimmed Mean PCE Index

The goal of this note is to provide an assessment of two of the most commonly used indicators of core inflation: the PCE price index excluding food and energy (an exclusion index), and the Dallas Fed trimmed mean PCE price index (a central-tendency statistical measure).

Constructing and evaluating core inflation measures from component‐level inflation data

AbstractThis paper undertakes a comprehensive examination of 10 measures of core inflation and evaluates which measure produces the best forecast of headline inflation out‐of‐sample. We use the Personal Consumption Expenditure Price Index as our measure of inflation. We use two sets of components (17 and 50) of the Personal Consumption Expenditure Price Index to construct these core inflation measures and evaluate these measures at the three time horizons (6, 12 and 24 months) most relevant for monetary policy decisions. The best measure of core inflation for both sets of components and over all time horizons uses weights based on the first principal component of the disaggregated (component‐level) prices. Interestingly, the results vary by the number of components used; when more components are used the weights based on the persistence of each component is statistically equivalent to the weights generated by the first principal component. However, those forecasts using the persistence of 50 components are statistically worse than those generated using the first principal component of 17 components. The statistical superiority of the principal component method is due to the fact that it extracts (in the first principal component) the common source of variation in the component level prices that accurately describes trend inflation over the next 6–24 months.

Two Measures of Core Inflation: A Comparison

Trimmed-mean personal consumption expenditure (PCE) inflation does not clearly dominate PCE inflation excluding food and energy in real-time forecasting of headline PCE inflation. However, trimmed-mean inflation is the superior communications and policy tool because it has been a less-biased real-time estimator of headline inflation and because it more successfully filters out headline inflation?s transitory variation, leaving only cyclical and trend components.

Residual Seasonality in Core Consumer Price Inflation: An Update

In this Note, we take another look at residual seasonality in several measures of core inflation.

Two Measures of Core Inflation: A Comparison

Trimmed-mean personal consumption expenditure (PCE) inflation does not clearly dominate PCE inflation excluding food and energy in real-time forecasting of headline PCE inflation. However, trimmed-mean inflation is the superior communications and policy tool because it has been a less-­biased real-time estimator of headline inflation and because it more successfully filters out headline inflation’s transitory variation, leaving only cyclical and trend components.

Robust Measures of Core Inflation for Vietnam

The paper develops robust measures of core inflation for Vietnam that can be used in policy making. These core inflation measures (CIMs) are based on an analytical evaluation of the inflation process in Vietnam, and use a filtering approach to narrow down potential measures that satisfy certain empirically desirable criteria. The paper finds that commonly used exclusion-based measures (EBMs) do not perform well against these empirical criteria; trimmed mean measures (TMMs) do better. Among TMMs, “one trim does not fit all periods”; periods of high and variable inflation require larger trims, and conversely. EVIEWS and MATLAB programs which accompany the paper allow quick, timely replication of CIMs as new data become available, making them valuable tools for the State Bank of Vietnam on an ongoing basis.