Decomposing household,professional and market forecasts on inflation: a dynamic factor model analysis

A dynamic factor model with stochastic volatility is used to investigate the relationships between three alternative measures of inflation expectations. The results show evidence of both a common time-varying trend and a common transitory component between inflation and short-term inflation expectations from households, professionals and markets. While the common time-varying trend has declined in both level and volatility since the early 1980s, it was found that consumer expectations are disproportionately influenced by the visibility of prices of select few goods. Roughly speaking, a 1% point increase in food and energy prices leads to about 1/3% point increase in consumer forecasts of inflation. In terms of policymaking, this finding suggests that stability in highly visible prices can moderate inflation in a meaningful way.     

Forecasting UK consumer price inflation using inflation forecasts

The inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modeling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modeling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework.     

Cost-based Phillips Curve forecasts of inflation

It is a well-established idea that prices are a function of marginal cost, yet estimating a reliable measure of marginal cost is difficult to do. Stock and Watson (1999) use the Phillips Curve to forecast inflation for a variety of existing activity variables that researchers commonly use to proxy for marginal cost. This paper uses a similar type of approach to examine the performance of a new candidate for the activity variable, which is marginal cost measured following the theoretical methodology of Bils (1987), which we find to be simple yet powerful when implemented empirically. We then use the Phillips Curve to conduct pseudo out-of-sample inflation forecasts for the US using: output, unemployment, hours, the labor share, the capacity utilization rate, and the new measure of marginal cost. For almost all cases, forecast errors are lowest in the regressions with the new marginal cost variable, indicating that this new measure is an improvement over previous attempts to proxy for marginal cost.     

Multi-horizon inflation forecasts using disaggregated data

In this paper we use multi-horizon evaluation techniques to produce monthly inflation forecasts for up to twelve months ahead. The forecasts are based on individual seasonal time series models that consider both, deterministic and stochastic seasonality, and on disaggregated Consumer Price Index (CPI) data. After selecting the best forecasting model for each index, we compare the individual forecasts to forecasts produced using two methods that aggregate hierarchical time series, the bottom-up method and an optimal combination approach. Applying these techniques to 16 indices of the Mexican CPI, we find that the best forecasts for headline inflation are able to compete with those taken from surveys of experts.     

Optimizing time-series forecasts for inflation and interest rates using simulation and model averaging

Motivated by economic-theory concepts – the Fisher hypothesis and the theory of the term structure – we consider a small set of simple bivariate closed-loop time-series models for the prediction of price inflation and of long- and short-term interest rates. The set includes vector autoregressions (VAR) in levels and in differences, a cointegrated VAR and a non-linear VAR with threshold cointegration based on data from Germany, Japan, UK and the US. Following a traditional comparative evaluation of predictive accuracy, we subject all structures to a mutual validation using parametric bootstrapping. Ultimately, we utilize the recently developed technique of Mallows model averaging to explore the potential of improving upon the predictions through combinations. While the simulations confirm the traded wisdom that VARs in differences optimize one-step prediction and that error correction helps at larger horizons, the model-averaging experiments point at problems in allotting an adequate penalty for the complexity of candidate models.     

Rational expectations and fixed-event forecasts: An application to UK inflation

This paper tests a version of the rational expectations hypothesis using ‘fixed-event’ inflation forecasts for the UK. Fixed-event forecasts consist of a panel of forecasts for a set of outturns of a series at varying horizons prior to each outturn. The forecasts are the prediction of fund managers surveyed by Merrill Lynch. Fixed-event forecasts allow tests for whether expectations are unbiased in a similar fashion to the rest of the literature. But they also permit the conduct of particular tests of forecast efficiency - whether the forecasts make best use of available information - that are not possible with rolling-event data. We find evidence of a positive bias in inflation expectations. Evidence for inefficiency is much less clear cut.First version received: June 2002/ Final version received: November 2003We would like two anonymous referees and an editor for comments that have significantly improved the paper. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank of England.     

Using inflation to erode the US public debt

Projections indicate the US Federal debt held by the public may exceed 70–100% of GDP within 10 years. In many respects, the temptation to inflate away some of this debt burden is similar to that at the end of World War II. In 1946, the debt ratio was 108.6%. Inflation reduced this ratio by more than a third within a decade. Yet there are some important differences – shorter debt maturities today reduce the temptation to inflate, while the larger share of debt held by foreigners increases it. This paper lays out an analytical framework for determining the impact of a large nominal debt overhang on the temptation to inflate. It suggests that when economic growth is stalled, the US debt overhang may induce an increase in inflation of about 5% for several years that could significantly reduce the debt ratio.     

A cross-impact model applicable to forecasts for long-range planning

A methodology is developed, which is based on cross-impact analysis and which is useful in estimating the effects of uncertainty in future sales programs and the effects of program interaction on long-range sales forecasts. The utility of the cross-impact methodology vis-a-vis the conventional decision-tree approach lies in the reduction of complexity made possible when a large number of programs must be considered.     

Time-varying persistence in US inflation

The persistence property of inflation is an important issue not only for economists, but especially for central banks, given that the degree of inflation persistence determines the extent to which central banks can control inflation. Further, not only is it the level of inflation persistence that is important in economic analyses, but also the question of whether the persistence varies over time, for instance, across business cycle phases, is equally pertinent, since assuming constant persistence across states of the economy is sure to lead to misguided policy decisions. Against this backdrop, we extend the literature on long-memory models of inflation persistence for the US economy over the monthly period of 1920:1–2014:5, by developing an autoregressive fractionally integrated moving-average-generalized autoregressive conditional heteroskedastic model with a time-varying memory coefficient which varies across expansions and recessions. In sum, we find that inflation persistence does vary across recessions and expansions, with it being significantly higher in the former than in the latter. As an aside, we also show that persistence of inflation volatility is higher during expansions than in recessions. Understandably, our results have important policy implications.     

Unit roots,interest rate spreads,and inflation forecasts

Recent research suggests that long-term interest rate spreads provide information that can be useful in forecasting inflation, but that the spread between the three-month and six-month Treasury bill rates appears to have little forecasting ability. This paper uses the concepts of unit roots and cointegration to examine the failure of the short-term T-bill spread to forecast inflation. The results suggest that the interest rate spread has little forecasting value because inflation and the interest rate spread exhibit distinctly different time-series properties.     

Comparative accuracy of forecasts of inflation: a Canadian study

An inaccurate forecast of inflation is costlier to economic agents when the inflation rate is high and volatile. In this situation, the use of more sophisticated and information-oriented forecasting models become economically efficient. We test this hypothesis by analysing the forecasting accuracy of vector auto-regressive (VAR), auto-regressive integrated moving average (ARIMA) and static expectation models. We use Canadian data and divide the post-sample forecasting period into four sub-periods, based on high/low and volatile/stable inflation. Prediction errors are compared for both short-term and long-term forecasts. Finally, the paper proposes a portfolio approach for obtaining a more accurate forecast of inflation.     

A critical assessment of existing estimates of US core inflation

Core inflation rates are widely calculated. The perceived benefit of core inflation rates is that they help to inform monetary policy. This is achieved by uncovering the underlying trend in inflation or by helping to forecast inflation. Studies which compare core inflation rates frequently assess candidate core rates on these two criteria. Using US data, the two standard tests of core inflation – the ability to track trend inflation and the ability to forecast inflation – are applied to a more comprehensive set of core inflation rates than has been the case in the literature to date. Furthermore, the tests are applied in a more rigorous fashion. A key difference in this paper is the inclusion of benchmarks to the tests, which is non-standard in the literature. Two problems with core inflation rates emerge. Firstly, it is very difficult to distinguish between different core rates according to these tests, as they tend to perform to a very similar level. Secondly, once the benchmarks are introduced to the tests, the core inflation rates fail to outperform the benchmarks. This failure suggests that core inflation rates are of less practical usefulness than previously thought.     

US inflation dynamics on long-range data

In this article, we evaluate inflation persistence in the United States using long-range monthly and annual data. The importance of inflation persistence is crucial to policy authorities and market participants, since the level of inflation persistence provides an indication on the susceptibility of the economy to exogenous shocks. Departing from classic econometric approaches found in the relevant literature, we evaluate inflation persistence through the nonparametric Hurst exponent within both a global and a rolling window framework. Moreover, we expand our analysis to detect the potential existence of chaos in the data generating process, in order to enhance the robustness of our conclusions. Overall, we find that inflation persistence is high from 1775 to 2013 for the annual data-set and from February 1876 to May 2014 in monthly frequency, respectively. Especially from the monthly data-set, the rolling window approach allows us to derive that inflation persistence has reached to historically high levels in the post–Bretton Woods period and remained there ever since.     

Time variation in inflation persistence: New evidence from modelling US inflation

This article explores how inflation persistence relates to the conduct and goals of monetary policy by presenting a new approach to modelling US inflation persistence and the Fed's dual mandate. Our framework fills a gap in pre-existing models by more flexibly accounting for diverse dynamic properties and shocks. Estimating a Phillips Curve model augmented with inflation volatilities and expectations, we find that the degree of monthly inflation persistence is time variant since World War II. Variations in persistence continue to be observed regardless of the absolute level of inflation and the extent of the trade-off between inflation and unemployment. We demonstrate that inflation persistence varies in line with expectations formed by memories of past inflation. This supports the case for more flexible monetary policy at times, as in the 1980s or especially the present decade, when inflation is more persistent.     

The information content of the Reserve Bank of Australia's inflation forecasts

In this article, the inflation forecasts produced by the Reserve Bank of Australia (RBA) and that generated by private forecasters, are used to assess whether the Reserve Bank possesses information about inflation that the private sector does not have. The results show that the Reserve Bank inflation forecasts embody useful predictive information about inflation, beyond that contained in private forecasts, over the recent inflation targeting period.     

The dynamics of persistence in US inflation

Using a recently developed time-series approach, we show that post-WWII US inflation became highly persistent during the ‘Great Inflation’ period, and then switched back to a low persistence process during 1984, and has remained stationary until the present day.     

The expectations theory of the term structure: Evidence from inflation forecasts

This paper tests the joint hypothesis of rational expectations and the expectations theory of the term structure using the Livingston survey data on price inflation forecasts. For a variety of sample periods, the paper presents evidence that the data are consistent with the theory. Since inflation forecasts, unlike interest rates, are not linked to specific underlying financial assets, the relationship between longterm and short-term inflation forecasts should not embody risk premia. This paper's findings therefore lend support to the view that a time-varying risk premium is needed to explain the observed term structure of interest rates.     

Evaluating the effect of monetary policy on unemployment with alternative inflation forecasts

This paper explores the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. We use the inflation forecasts of 8 competing models in a standard Bayesian VAR to analyse the size and the timing of these effects, as well as to quantify the uncertainty relative to the different inflation models under two rules. The results suggest that model uncertainty can be a serious issue and strengthen the case for a policy strategy that takes into account several sources of information. We find that combining inflation forecasts from many models not only yields more accurate forecasts than those of any specific model, but also reduces the uncertainty associated with the real effects of policy decisions. These results are in line with the model-combination approach that central banks already follow when conceiving their strategy.     

A common trends model of UK core inflation

In this paper the long-run trend in RPI inflation (core inflation) for the UK over the 1961–1997 period is estimated within the framework of a multivariate common trends model which extends the bivariate VAR approach of Quah and Vahey (1995). In this context core inflation is directly linked to money and wage growth and interpreted as the long-run forecast of inflation from a small-scale, cointegrated macroeconomic system. First version received: September 1999/Final version received: October 2001 RID="*" ID="*"  We thank two anonymous referees for many helpful comments and suggestions. Work on this paper was partially conducted when C. Morana was at Heriot-Watt University.     

US inflation and consumption: A long-term perspective with a level shift

This article examines the existence and stability of the consumption function in the United States of America (US) beginning in the 1950s. In order to obtain a stable long run relationship, we have introduced two innovative elements into the analysis of the life-cycle of the consumption function with wealth effects: 1) a shift level break in the cointegrating relationship, and 2) using inflation as an additional explanatory variable. By implementing a well structured estimation strategy, we found that after taking the level shift into account, a cointegrating equation, including inflation, exists and is more stable for the critical sub-samples than traditional consumption function models.