The effect of central bank credibility on forward guidance in an estimated New Keynesian model

This paper examines the effectiveness of forward guidance shocks in the US. We estimate a New Keynesian model with imperfect central bank credibility and heterogeneous expectations using Bayesian methods and survey data from the Survey of Professional Forecasters (SPF). The results provide important takeaways: (1) The estimated credibility of the Fed’s forward guidance announcements is relatively high, but anticipation effects are attenuated. Accordingly, output and inflation do not respond as favorably as in the fully credible counterfactual. (2) The so-called “forward guidance puzzle” arises partly from the unrealistically large responses of macroeconomic variables to forward guidance under perfect credibility and homogeneous fully informed rational expectations, assumptions which are found to be jointly inconsistent with the observed US data. (3) Imperfect credibility provides a plausible explanation for the empirical evidence of forecasting error predictability based on forecasting disagreement found in the SPF data. Thus, we show that accounting for imperfect credibility and forecasting disagreements is important to understand the formation of expectations and the transmission mechanism of forward guidance.

Forecasting US Inflation in Real Time

We analyze real-time forecasts of US inflation over 1999Q3–2019Q4 and subsamples, investigating whether and how forecast accuracy and robustness can be improved with additional information such as expert judgment, additional macroeconomic variables, and forecast combination. The forecasts include those from the Federal Reserve Board’s Tealbook, the Survey of Professional Forecasters, dynamic models, and combinations thereof. While simple models remain hard to beat, additional information does improve forecasts, especially after 2009. Notably, forecast combination improves forecast accuracy over simpler models and robustifies against bad forecasts; aggregating forecasts of inflation’s components can improve performance compared to forecasting the aggregate directly; and judgmental forecasts, which may incorporate larger and more timely datasets in conjunction with model-based forecasts, improve forecasts at short horizons.

Long-run inflation expectations in the ECB survey of professional forecasters: what do the survey responses tell us?

Research background: At the background, there are issues related to policy credibility and policy targets. For these issues, long-term forecasts can provide important information. Of course, long-term forecasts are needed also e.g. for evaluation of real returns. Purpose of the article: This paper tries to find out how informative the ECB Survey of Professional Forecasters data on long-term inflation prospects are from the point of view of the overall quality of the survey and on the other hand from the point of view of monetary policy credibility. Methods: The analysis makes use of individual forecaster level quarterly panel data for the period 1999Q1?2018Q4. Conventional panel econometrics tools are used to find out whether forecasts are sensitive to changes in actual inflation and other relevant variables. Findings & Value added: We find some weaknesses considering the size of the survey, the selection of the sample (more precisely the participation to the survey) and the inertial responses of forecasters which suggest that the survey values are not actively updated. Moreover, we find that towards the end of the sample period, the survey values are related to actual inflation and to short-term expectations, which is not consistent with the credibility of the official inflation target.

Estimating Macroeconomic Uncertainty and Discord

We apply generalized beta and triangular distributions to histograms from the Survey of Professional Forecasters (SPF) to estimate forecast uncertainty, shocks. and discord using an information framework, and we compare these with moment-based estimates. We find that these two approaches produce analogous results, except in cases where the underlying densities deviate significantly from normality. Even though the Shannon entropy is more inclusive of different facets of a forecast density, we find that with SPF forecasts it is largely driven by the variance of the densities. We use Jenson–Shannon Information to measure ex ante “news” or “uncertainty shocks” in real time, and we find that this “news” is closely related to revisions in forecast means, is countercyclical, and raises uncertainty. Using standard vector autoregression analysis, we confirm that uncertainty affects the real sector of the economy negatively.

Cost Structure, Operating Leverage and CDS Spreads

We provide evidence that credit investors do not fully impound the implications of firms' cost structure (or operating leverage) when pricing credit default swaps. Information about firms' cost structure is not disclosed and needs to be estimated. Furthermore, the performance implications of firms' cost structure depend on the expected macroeconomic conditions. We focus on the debt market because of the strong emphasis of this market on downside risk. To measure expected aggregate macroeconomic conditions, we employ the change in the anxious index (AI), which is the probability of a decline in real GDP provided by the SPF-the survey of professional forecasters. We find that the interaction between the firm's cost structure and change in AI predicts one-quarter-ahead CDS spreads. Portfolio-level analysis confirms this result.

Growth Expectations, Undue Optimism, and Short-Run Fluctuations

This paper proposes a two-step procedure in order to identify belief shocks—shocks to expectations about the current state of the economy. First, we use the Survey of Professional Forecasters to measure nowcast errors about contemporaneous output growth. Second, we extract belief shocks from nowcast errors, once by regressing them on existing measures of structural shocks, and once by imposing sign restrictions on a VAR model. Using both approaches, we find that belief shocks trigger similar adjustment dynamics and a high degree of co-movement across macroeconomic variables. Belief shocks account for about one third of short-run output fluctuations.

Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to simple variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts.

Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility

This paper studies the joint dynamics of U.S. inflation and a term structure of average inflation predictions taken from the Survey of Professional Forecasters (SPF). We estimate these joint dynamics by combining an unobserved components (UC) model of inflation and a sticky‐information forecast mechanism. The UC model decomposes inflation into trend and gap components, and innovations to trend and gap inflation are affected by stochastic volatility. A novelty of our model is to allow for time‐variation in inflation‐gap persistence as well as in the frequency of forecast updating under sticky information. The model is estimated with sequential Monte Carlo methods that include a particle learning filter and a Rao–Blackwellized particle smoother. Based on data from 1968 Q4 to 2018 Q3, estimates show that (i) longer horizon average SPF inflation predictions inform estimates of trend inflation; (ii) inflation gap persistence is countercyclical before the Volcker disinflation and acyclical afterwards; (iii) by 1990 sticky‐information inflation forecast updating is less frequent than it was earlier in the sample; and (iv) the drop in the frequency of the sticky‐information forecast updating occurs at the same time persistent shocks become less important for explaining movements in inflation. Our findings support the view that stickiness in survey forecasts is not invariant to the inflation process.

Heterogeneity, Inattention, and Bayesian Updates

We formulate a theory of expectations updating that fits the dynamics of accuracy and disagreement in a new survey of professional forecasters. We document new stylized facts, including the puzzling persistence of disagreement as uncertainty resolves. Our theory explains these facts by allowing for different channels of heterogeneity. Agents produce an initial forecast based on heterogeneous priors and are heterogeneously “inattentive.” Updaters use Bayes’ rule and interpret public information using possibly heterogeneous models. Structural estimation of our theory supports the conclusion that in normal times heterogeneous priors and inattention are enough to generate persistent disagreement, but not during the crisis. (JEL C53, D81, D83, D84, E31, E37)