Core Inflation Measures Research Articles

Nowcasting U.S. Headline and Core Inflation

Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. price index for personal consumption expenditures (PCE) and the consumer price index (CPI). The model relies on relatively few variables and is tested using real-time data. The model’s nowcasting accuracy improves as information accumulates over the course of a month or quarter, and it easily outperforms a variety of statistical benchmarks. In head-to-head comparisons, the model’s nowcasts of CPI inflation outperform those from the Blue Chip consensus, with especially significant outperformance as the quarter goes on. The model’s nowcasts for CPI and PCE inflation also significantly outperform those from the Survey of Professional Forecasters, with similar nowcasting accuracy for core inflation measures. Across all four inflation measures, the model’s nowcasting accuracy is generally comparable to that of the Federal Reserve’s Greenbook.

The FRBNY Staff Underlying Inflation Gauge: UIG

Monetary policymakers and long-term investors would benefit greatly from a measure of underlying inflation that uses all relevant information, is available in real time, and forecasts inflation better than traditional underlying inflation measures such as core inflation measures. This paper presents the “FRBNY Staff Underlying Inflation Gauge (UIG)” for CPI and PCE. Using a dynamic factor model approach, the UIG is derived from a broad data set that extends beyond price series to include a wide range of nominal, real, and financial variables. It also considers the specific and time-varying persistence of individual subcomponents of an inflation series. An attractive feature of the UIG is that it can be updated on a daily basis, which allows for a close monitoring of changes in underlying inflation. This capability can be very useful when large and sudden economic fluctuations occur, as at the end of 2008. In addition, the UIG displays greater forecast accuracy than traditional measures of core inflation.

Asymmetric Quantile Persistence and Predictability: the Case of US Inflation

AbstractThis article investigates the evidence of time‐variation and asymmetry in the persistence of US inflation. We compare the out‐of‐sample performance of different forecasting models and find that quantile forecasts from an Auto‐Regressive (AR) model with level‐dependent volatility are at least as accurate as the forecasts of the Quantile Auto‐Regressive model, in particular for the core inflation measures. Our results indicate that the persistence of core inflation has been relatively constant and high, but it declined for the headline inflation measures. We also find that the asymmetric persistence of inflation shocks can be mostly attributed to the positive relation between inflation level and its volatility.

Measuring Core Inflation in India: An Empirical Evaluation of Alternative Methods

In view of formulating credible monetary policy to attain the price stability objective, the difficult part for the central banks is to distinguish, within ongoing inflation evolutions, between short term volatility and the underlying pressure of inflation. While it has now become a standard practice for most central banks around the world to monitor core inflation, little progress has so far been made in the Indian context. This paper takes a pioneering look in measuring core inflation in India focusing on the popular exclusion and trimmed mean approaches. The performance criteria adopted in this analysis show that the measure of core inflation developed in the paper has strong money-induced characteristics and therefore, can credibly be used as a short or medium term guide of monetary policy in India. This paper aims to introduce the concept of core inflation and to calculate alternative measures of core inflation for India. We have used two approaches: (1) Exclusion based approach (2) Trimmed mean method, to identify the measures of core inflation. We have obtained five alternative measures of core inflation using exclusion approach these are: WPI excluding food articles, WPI excluding food articles and non food articles, WPI excluding food articles and fuel (minerals oils), WPI excluding fuel (minerals oils) and manufactured products (Beverages, Tobacco and Tobacco Products, Non-Metallic Mineral Products, Basic Metals Alloys and Metals Products), WPI excluding Minerals, Basic Metals Alloys and Metals Products, Minerals Oils, Non-Metallic Mineral Products, Beverages, Tobacco and Tobacco Products., two measures TRIM15_15 and TRIM20_20 using trimmed mean For this we have evaluated these measures of core inflation in India based on new series of WPI (1993–94 =100). These measures were tested for volatility and unbiasedness and co- integration with headline inflation. The co-integration test statistics confirm long run relationship between the core inflation measures and headline inflation. The study found that the exclusion based measures are more appropriate for inflation targeting purposes and the measures based on the trimming may be better for identifying the underlying trends and also in providing a robust forecast of future inflation rates in India.

Comparing the measures of core inflation in India: trimmed mean and structural vector auto-regression approach

This paper estimates core inflation through trimmed mean method and structural vector auto-regression (SVAR) method by using monthly data of wholesale price index (WPI) and index of industrial production (IIP) from April 2005 to March 2014 for India. In this paper, we have compared 25% trimmed mean and SVAR method and it was found that SVAR measure provides better results than trimmed mean method. In SVAR method, we found the exact movements of core and non-core shocks in impulse response functions and variance decomposition. It is based on the definitions of core inflation but trimmed mean method excludes the outliers in the price index, whereas SVAR method is difficult to estimate.

On the Asymmetric U‐Shaped Relationship between Inflation, Inflation Uncertainty, and Relative Price Skewness in the UK

We investigate the asymmetric relationships between aggregate inflation and the second and third moments of the cross‐sectional distribution of relative prices using a modified Calvo pricing model with regime‐dependent price rigidities. Calibration experiments reveal that the inflation‐standard deviation and inflation‐skewness relationships exhibit U‐shaped asymmetries around the historical mean inflation rate. UK sectoral data support our results. We conclude that monetary policy should target an inflation rate proximate to the (common) minima of these nonlinear relationships and that core inflation measures should not be used for policy purposes as they exclude much of the information contained in the higher moments.

Which Core Inflation Measure for Vietnam?

This paper attempts to designate the most efficient core inflation measure for Vietnam. Five measures of core inflation are constructed to be considered based on different approaches proposed in the literature. These are: the excluding food price, the trimmed-mean, the weighted median, the exponentially smoothed and the output-neutral inflation. They are subsequently evaluated empirically for tracking the trend, predictive power and cointegration with the headline inflation. The key finding is that the output-neutral, which satisfies almost all of the evaluation criteria, can be a useful core inflation indicator for Vietnam. Besides, the central bank may also rely on either the trimmed-mean or weighted median for communication purposes due to their rather simple construction.

Inflation forecasts and core inflation measures: Where is the information on future inflation?

• We compare the inflation forecast errors from the Greenbook, SPF and core inflation measures to a random walk model. • Forecasts from a random walk model are poor. • Greenbook forecasts no longer consistently maintain their information advantage. • The weighted median and trimmed mean do provide valuable information about the tendency of prices in the medium run. • The weighted median and trimmed mean provide information similar to the information in the Greenbook forecasts. This paper uses the forecast from a random walk model of inflation as a benchmark to test and compare the forecast performance of several alternatives of future inflation, including the Greenbook forecast by the Fed staff, the Survey of Professional Forecasters median forecast, CPI inflation minus food and energy, CPI weighted median inflation, and CPI trimmed mean inflation. The Greenbook forecast was found in previous literature to be a better forecast than other private sector forecasts. Our results indicate that both the Greenbook and the Survey of Professional Forecasters median forecasts of inflation and core inflation measures may contain better information than forecasts from a random walk model. The Greenbook's superiority appears to have declined against other forecasts and core inflation measures.

Towards a Measure of Core Inflation using Singular Spectrum Analysis

AbstractThis paper constructs a number of possible core measures of inflation using singular spectrum analysis (SSA). Annual changes in monthly inflation are decomposed into its trend, oscillatory and noise components in order to develop an understanding of the trend and cyclicality in South African headline inflation. Three cyclical components with differing amplitude and frequency are identified. The trend and cyclical components of inflation are found to be a good approximation of core inflation, the inertial part of inflation. These core measures are compared with other candidate core measures based on the properties of a good core inflation measure. Generally, the SSA measures outperform commonly used measures of core inflation based on both in‐ and out‐of‐sample performance.

Stability price index, core inflation and output volatility

This article examines the relationship between the ‘exclusion’ type Core Inflation (CI) measures and the stability price index. Empirical results for Malaysia and Pakistan suggest that if targeting CI index is to stabilize output, weights of the export-oriented sectors (energy for Malaysia and foodstuffs for Pakistan) should be reduced, in relation to the CPI weights, and weights of the import-oriented sectors should be increased. It also indicates that, in order to maintain real sector stability, central bankers should include the fundamental component of the stock market prices in the price index they target.

Constructing U.K. Core Inflation

The recent volatile behaviour of U.K. inflation has been officially attributed to a sequence of “unusual” price changes, prompting renewed interest in the construction of measures of “core inflation”, from which such unusual price changes may be down-weighted or even excluded. This paper proposes a new approach to constructing core inflation based on detailed analysis of the temporal stochastic structure of the individual prices underlying a particular index. This approach is illustrated using the section structure of the U.K. retail price index (RPI), providing a number of measures of core inflation that can be automatically calculated and updated to provide both a current assessment and forecasts of the underlying inflation rate in the U.K.

Different statistical core inflation measures for India: construction and evaluation

This paper computes several statistical measures for core inflation for India and provides methodology of construction of these core measures. Some of these have been computed for the first time for India, such as: persistence weighted, variations of ‘Neo-Edgeworthian Index’, asymmetric trimmed mean, and month-by‐month exclusion (dynamic trimmed mean) core measures. For computing these core measures, the study uses both aggregate WPI and a detailed breakdown of the WPI. It covers the period April 1994–April 2009, with 1993–1994 as the base year. Subsequently, a comparison of these estimated core measures based on the criteria of usefulness of a measure of core inflation from a monetary policy point of view is carried out. The study finds only some representative measures of core inflation to be useful.

Core Measures of Inflation as Predictors of Total Inflation

Policymakers tend to focus on core inflation measures because they are thought to be better predictors of total inflation over time horizons of import to policymakers. We find little support for this assumption. While some measures of core inflation are less volatile than total inflation, core inflation is not necessarily the best predictor of total inflation. The relative forecasting performance of models using core inflation and those using only total inflation depends on the inflation measure and time horizon of the forecast. Unlike previous studies, we provide a measure of the statistical significance of the difference in forecast errors.

Revisiting the Phillips curve for India and inflation forecasting

This paper focuses on modeling and forecasting inflation in India using an augmented Phillips curve framework. Both demand and supply factors are seen as drivers of inflation. Demand conditions are found to have a stronger impact on non-food manufactured products (NFMP) inflation vis-a-vis headline wholesale price inflation; moreover, NFMP inflation is found to be more persistent than headline inflation. Both these findings support the use of NFMP inflation as a core measure of inflation. But, the impact of global non-fuel commodities on NFMP inflation is found to be substantial. Inflation in non-fuel commodities is seen as a more important driver of domestic inflation rather than fuel inflation. The exchange rate pass-through coefficient is found to be modest, but nonetheless sharp depreciation in a short period of time can add to inflationary pressures. The estimated equations show a satisfactory in sample as well as out-of-sample performance based on dynamic simulations. Nonetheless, forecasting challenges emanate from volatility in international oil and other commodity prices and domestic food supply dynamics.

Monetary Policy with Sectoral Linkages and Durable Goods

We study the normative implications of a New Keynesian model featuring intersectoral trade of intermediate goods between two sectors that produce durables and non-durables. The interplay between durability and sectoral production linkages fundamentally alters the intersectoral stabilization trade-off as it emerges in otherwise standard two-sector models. We compare the welfare properties of a timeless-perspective monetary policy with the performance of simple instrumental rules that adjust the policy rate in response to the output gap and alternative aggregate measures of final goods price inflation. Aggregating durable and non-durable inflation depending on the relative degrees of sectoral price stickiness may induce a severe bias. Input materials attenuate the response of sectoral inflations to movements in the real marginal costs, so that the effective slopes of the sectoral supply schedules are not properly accounted for by conventional measures of core inflation.

Asymmetric Quantile Persistence and Predictability: The Case of U.S. Inflation

The aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a parametric Auto-Regressive (AR) model in which the volatility of the errors depends on the level of inflation. The results of the comparison show that the parametric quantile forecasts are at least as accurate as the semi-parametric QAR model, in particular for the core inflation measures. This leads us to conclude that the persistence of core inflation can be considered constant and high, but declined for the headline inflation measures. In addition, we find that the recent findings of asymmetric persistence of inflation shocks can be mostly attributed to the positive relation between inflation level and its volatility.

A factorial decomposition of inflation in Peru: an alternative measure of core inflation

A dynamic factorial decomposition model of inflation is estimated using Peruvian monthly data for January 1995–July 2008. This model allows the identification of changes in three relevant inflation components: idiosyncratic relative prices, aggregate relative prices and absolute prices. Furthermore, following Reis and Watson (2007), the model allows measuring pure inflation as the common factor in the inflation rate that has a proportionate effect to all prices and that is not correlated with relative-price changes at any period of time. This pure inflation estimate relates closely to standard measures of core inflation. The results are robust to different lag structures and various stochastic assumptions on the estimated factors.

Inflation Forecasting: Issues and Challenges in India

This paper focuses on modelling and forecasting inflation in India using an augmented Phillips curve framework. Both demand and supply factors are seen as drivers of inflation. Demand conditions are found to have a stronger impact on non-food manufactured products inflation (NFMP) vis-a-vis headline WPI inflation; moreover, NFMP is found to be more persistent than headline inflation. Both these findings support the use of NFMP as a core measure of inflation. But, the impact of global non-fuel commodities on NFMP is found to be substantial. Inflation in non-fuel commodities is seen as a more important driver of domestic inflation rather than fuel inflation. The exchange rate pass-through coefficient is found to be modest, but nonetheless sharp depreciation in a short period of time can add to inflationary pressures. The estimated equations show a satisfactory in-sample as well as out-of-sample performance based on dynamic simulations. Nonetheless, forecasting challenges emanate from volatility in international oil and other commodity prices and domestic food supply dynamics.

How does the performance of core inflation indicators differ in less stable times?

In this study, we discuss the overall performance of different core inflation measures for Turkey. We first describe and derive the core measures based on exclusion, statistical and model-based methods. We then compare their performances during the entire sample period of January 2003 – January 2011. Apart from the shocks that they are subject to, performance of core inflation measures depends also on the nature of the inflationary process. Therefore we evaluate the performance of measures period wise, for two subsample periods, one being relatively stable and other being less stable in terms of inflation process. We show that permanent exclusion based measures perform much better in stable times, while their performance deteriorate in less stable periods. Model based measures have a robust performance under both states. Statistical measures dominate in terms of their performance in predictive ability under both states and their trend tracking ability improves in less stable periods.

PCE Inflation and Core Inflation

This paper investigates the forecasting accuracy of the trimmed mean inflation rate of the Personal Consumption Expenditure (PCE) deflator. Earlier works have examined the forecasting ability of limited-influence estimators (trimmed means and the weighted median) of the Consumer Price Index but none have compared the weighted median and trimmed mean of the PCE. Also addressed is the systematic bias that appears due to the differences in the means of inflation measures over the sample. This paper supports earlier results that limited-influence estimators provide better forecasts of future inflation than does the popular measure of core inflation, PCE inflation minus food and energy; therefore, these limited-influence estimators are core inflation.