Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?

Inflation forecasts of the Federal Reserve seem to have systematically under-predicted inflation from the fourth quarter of 1968 until Volcker's appointment as Chairman, and to systematically over-predict it afterwards until the second quarter of 1998. Furthermore, under quadratic loss, commercial forecasts seem to have information not contained in those forecasts. To investigate the cause of this apparent irrationality, this paper recovers the loss function implied by Federal Reserve's inflation forecasts. The results suggest that the cost of having inflation above an implicit time-varying target was larger than the cost of having inflation below it for the period since Volcker, and that the opposite was true for the pre-Volcker era. Once these asymmetries are taken into account, the Federal Reserve's inflation forecasts are found to be rational.     

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. consumer price index and price index for personal consumption expenditures that relies on relatively few variables. The model's nowcasting accuracy improves as information accumulates over a month or quarter, outperforming statistical benchmarks. In real‐time comparisons, the model's headline inflation nowcasts substantially outperform those from the Blue Chip consensus and the Survey of Professional Forecasters. Across all four inflation measures, the model's nowcasting accuracy is comparable to that of the Federal Reserve Board's Greenbook.     

The Great Inflation and the Greenbook

Can the story of evolving Federal Reserve beliefs in The Conquest of American Inflation simultaneously explain the Great Inflation and the forecasts published in the Greenbook during that time? If Sargent is correct then evolving beliefs should be reflected not only in policy outcomes but also in Greenbook forecasts. In this paper they are. By conditioning on the Greenbook, it is show that both inflation outcomes and Greenbook forecasts can be rationalised by evolving beliefs. The results improve on recent empirical evidence that has been criticised for relying on unrealistic beliefs that produce forecasts inconsistent with the Greenbook.     

Using private forecasts to estimate the effects of monetary policy

I develop a methodology that uses the forecasts of market participants and of policy makers to estimate the effects of monetary policy on output and inflation. My approach has advantages over the standard practice of fitting a vector autoregression to the data. I apply my methodology to data on output, interest rates and prices. I find that, even using the Federal Reserve Board's Greenbook forecasts to control for the policy maker's information set, prices rise initially in response to a monetary contraction. This finding undermines the standard justification for including an index of commodity prices in VARs.     

Monetary Policy Estimation in Real Time: Forward‐Looking Taylor Rules without Forward‐Looking Data

I propose a methodology for estimating forward‐looking Taylor rules in real time when forward‐looking real‐time central bank data are unavailable. The methodology consists of choosing appropriate models to closely replicate U.S. Greenbook forecasts and then applying these models to Canada, Germany, and the U.K. The results show that German and U.S. Taylor rules are characterized by inflation coefficients increasing with the forecast horizon and a positive output gap response. The U.K. and Canada interest rate reaction functions achieve maximum inflation response at middle‐term horizons of about 1/2 years and the output gap coefficient is insignificant.     

Inflation targeting,credibility, and non-linear Taylor rules

In this paper we systematically evaluate how central banks respond to deviations from the inflation target. We present a stylized New Keynesian model in which agents' inflation expectations are sensitive to deviations from the inflation target. To (re-) establish credibility, monetary policy under discretion sets higher interest rates today if average inflation exceeded the target in the past. Moreover, the central bank responds non-linearly to past inflation gaps. This is reflected in an additional term in the central bank's instrument rule, which we refer to as the ”credibility loss.” Augmenting a standard Taylor (1993) rule with the latter term, we provide empirical evidence for the interest rate response for a sample of five inflation targeting (IT) economies. We find, first, that past deviations from IT feed back into the reaction function and that this influence is economically meaningful. Deterioration in credibility (ceteris paribus) forces central bankers to undertake larger interest rate steps. Second, we detect an asymmetric reaction to positive and negative credibility losses, with the latter dominating the former.     

Survey forecasts in Brazil: A prismatic assessment of epidemiology,performance, and determinants

This paper assesses the behavior of survey forecasts in Brazil during the inflation targeting regime, when managing expectations is one of the cornerstones of the conduct of monetary policy. The distinctive database of the survey conducted by the Central Bank of Brazil (BCB) among professional forecasters allows for a thorough investigation of the epidemiology, determinants, and performance of forecasts. The main results are: i) top performing forecasters are influential to other forecasters; ii) survey forecasts perform better than vector autoregressive model-based forecasts; iii) common forecast errors prevail over idiosyncratic components across respondents; iv) inflation targets play an important role in inflation expectations; and v) agents perceive the BCB as following a Taylor rule consistent with inflation targeting. The last two suggest high credibility of the monetary authority.     

Tracking U.S. inflation expectations with domestic and global indicators

Are foreign variables important for tracking U.S. inflation expectations? This paper estimates a reduced-form model that takes both domestic and global indicators of economic slack and inflationary pressures into account. Our main findings point towards the instability of the estimated parameters over the last four decades. In particular, global indicators appear to have played a statistically significant role in shaping forecasters’ expectations until the mid-1980s. By contrast, the U.S. monetary policy stance turns out to be relevant in the 1980s and 1990s. We relate this finding to the more aggressive monetary policy conduct implemented by the Fed since the end of the Volcker experiment.     

Does Inflation Targeting Affect the Dispersion of Inflation Expectations?

In this paper, we examine the effect of having an inflation targeting framework on the dispersion of inflation forecasts from professional forecasters. We use a panel data set of 25 countries—including 14 inflation targeters—with 16 years of monthly information. We find that the dispersion of long-run inflation expectations is smaller in targeting regimes after controlling for country-specific effects, time-specific effects, the level and the variance of inflation, disinflation periods, and global inflation. On average, the full effect is not observed until the third year after implementation of inflation targeting. When we differentiate between developed and developing countries, the dispersion of inflation expectations after inflation targeting is smaller and statistically significant only in developing countries.     

A Phillips Curve with Anchored Expectations and Short‐Term Unemployment

This paper examines the behavior of U.S. core inflation, as measured by the weighted median of industry price changes. We find that core inflation since 1985 is well‐explained by an expectations‐augmented Phillips curve in which expected inflation is measured with professional forecasts and labor‐market slack is captured by the short‐term unemployment rate. We also find that expected inflation was backward‐looking until the late 1990s, but then became strongly anchored at the Federal Reserve's target. This shift in expectations changed the relationship between inflation and unemployment from an accelerationist Phillips curve to a level‐level Phillips curve. Our specification explains why high unemployment during the Great Recession did not reduce inflation greatly: partly because inflation expectations were anchored, and partly because short‐term unemployment rose less sharply than total unemployment.     

Do macro variables, asset markets, or surveys forecast inflation better?

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time-series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.     

Estimating Trend Inflation Based on Unobserved Components Model: Is It Correlated with the Inflation Gap?

Building on the work of Stock and Watson (2007), this paper empirically shows that a negative correlation between innovations to trend inflation and the inflation gap plays an important role in the dynamics of postwar U.S. inflation. Additional features that we incorporate in our model include regime‐switching inflation gap persistence and association between inflation and inflation uncertainty. The resulting estimate of trend inflation is smooth, and our model provides superior out‐of‐sample forecasts than Stock and Watson's (2007) unobserved components model with stochastic volatility or than Atkeson and Ohanian's (2001) random walk model does.     

An Inflation‐Predicting Measure of the Output Gap in the Euro Area

Using a small Bayesian dynamic factor model of the euro area, we estimate the deviations of output from its trend that are consistent with the behavior of inflation. We label these deviations the output gap. In order to pin down the features of the model, we evaluate the accuracy of real‐time inflation forecasts from different model specifications. The version that forecasts inflation best implies that after the 2011 sovereign debt crisis, the output gap in the euro area has been much larger than the official estimates. Versions featuring a secular stagnation‐like slowdown in trend growth, and hence a small output gap after 2011, do not adequately capture the inflation developments.     

The Real‐Time Properties of the Bank of Canada's Staff Output Gap Estimates

We study the revision properties of the Bank of Canada's staff output gap estimates since the mid‐1980s and show that the average revision has been significantly smaller since the early 2000s. Alternatively, revisions from econometric output gap estimates have not experienced a similar improvement. We show that the overestimation of potential output in real time following the 1991–92 recession explains the large revisions in the first half of the sample. Although Phillips‐curve inflation forecasts slightly worsen when conditioned on real time instead of final gaps, their relative poor performance reflects the general lack of inflation predictability rather than real‐time gap measurement issues.     

FOMC Forecasts as a Focal Point for Private Expectations

We explore empirically the theoretical prediction that public information acts as a focal point in the context of the U.S. monetary policy. We aim at establishing whether the publication of Federal Open Market Committee (FOMC) inflation forecasts affects the cross‐sectional dispersion of private inflation expectations. Our main finding is that publishing FOMC inflation forecasts has a negative effect on the cross‐sectional dispersion of private current‐year inflation forecasts. This effect is found to be robust to another survey data set and to various macroeconomic controls. Moreover, we find that the dispersion of private inflation forecasts is not affected by the dispersion of views among FOMC members.     

A New Model of Inflation,Trend Inflation,and Long‐Run Inflation Expectations

This paper develops a bivariate model of inflation and a survey‐based long‐run forecast of inflation that allows for the estimation of the link between trend inflation and the long‐run forecast. Thus, our model allows for the possibilities that long‐run forecasts taken from surveys can be equated with trend inflation, that the two are completely unrelated, or anything in between. Using a variety of inflation measures and survey‐based forecasts for several countries, we find that long‐run forecasts can provide substantial help in refining estimates and fitting and forecasting inflation. It is less helpful to simply equate trend inflation with the long‐run forecasts.     

Do Central Bank Forecasts Influence Private Agents? Forecasting Performance versus Signals

Focusing on a set of central banks that publish inflation forecasts in real time, this paper aims to establish whether central bank inflation forecasts influence private inflation forecasts. The response is positive in the five countries studied: Sweden, the United Kingdom, Canada, Switzerland, and Japan. Three hypotheses may explain this central bank influence: central bank forecasts are more accurate than private ones, are based on different information sets, and/or convey signals about future policy decisions and policymakers’ preferences and objectives. We provide evidence that the source of these central banks’ influence is not linked to their forecasting performance.     

Does Global Liquidity Help to Forecast U.S. Inflation?

We construct a measure of global liquidity using the growth rates of broad money for the G7 economies. Global liquidity produces forecasts of U.S. inflation that are significantly more accurate than the forecasts based on U.S. money growth, Phillips curve, and autoregressive and moving average models. The marginal predictive power of global liquidity is strong at 3-year horizons. Results are robust to alternative measures of inflation.