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.     

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.     

Asymmetry,Complementarities, and State Dependence in Federal Reserve Forecasts

Forecasts are a central component of policymaking; the Federal Reserve's forecasts are published in a document called the Greenbook. Previous studies of the Greenbook's inflation forecasts have found them to be rationalizable but asymmetric if considering particular subperiods, for example, before and after the Volcker appointment. In these papers, forecasts are analyzed in isolation, assuming policymakers value them independently. We analyze the Greenbook forecasts in a framework in which the forecast errors for different variables are allowed to interact. We find that allowing the losses to interact makes the unemployment forecasts virtually symmetric, the output forecasts symmetric prior to the Volcker appointment, and the inflation forecasts symmetric after the onset of the Great Moderation.     

Economic Literacy and Inflation Expectations: Evidence from a Laboratory Experiment

We present experimental evidence of a link between economic literacy and inflation forecast accuracy. The experiment investigates two channels through which economic literacy may enable better forecasts: (i) choice of information and (ii) use of information. More literate subjects choose more relevant information and use the given information more effectively. Starting from a 10th percentile score, the boost in literacy from taking an economics course predicts a 0.64 standard deviation decline in mean absolute forecasting error. Our findings suggest that a significant portion of demographic heterogeneity in inflation expectations—observed in survey data—may be driven by heterogeneity in economic literacy.     

Serial Correlation in Management Earnings Forecast Errors

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs should not exhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long‐horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self‐selection does not seem to drive this phenomenon. Further analyses suggest that managers’ unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.     

Using Survey Data to Correct the Bias in Policy Expectations Extracted from Fed Funds Futures

Many studies estimate risk premiums on federal funds futures to extract monetary policy expectations by assuming that average forecast errors of the expectations are zero or that survey forecasts are good proxies for the expectations. These assumptions, however, may fail due to an unanticipated declining trend in the federal funds rate and to survey respondents' strategic behavior. Consequently, the premiums estimated under these assumptions may be biased. We propose a new method to estimate the premiums and find that the premiums have been often negative since 2000, which is generally consistent with the negative betas observed in the 2000s.     

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 Actions Speak Louder Than Words? Household Expectations of Inflation Based on Micro Consumption Data

Survey data on household expectations of inflation are routinely used in economic analysis, yet it is not clear how accurately households are able to articulate their expectations in survey interviews. We propose an alternative approach to recovering households' expectations of inflation from their consumption expenditures. We show that these expectations measures have predictive power for consumer price index (CPI) inflation. They are better predictors of CPI inflation than household survey responses and more highly correlated with professional inflation forecasts, except for highly educated consumers, consistent with the view that more educated consumers are better able to articulate their expectations. We also document that households' inflation expectations respond to inflation news, as measured by the unpredictable component of inflation predictions in the Survey of Professional Forecasters. The response to inflation news tends to increase with households' level of education, consistent with the existence of constraints on household's ability to process this information.     

Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.     

Additional Evidence on Analysts’ Decision to Issue Disaggregated Earnings Forecasts: Strategic Biasing

This study examines why analysts issue disaggregated earnings forecasts to I/B/E/S. Some recent studies suggest that analysts with superior forecasting ability issue disaggregated earnings forecasts to build reputation in the marketplace and stop forecast disaggregation once their reputation has been established. Based on an analysis of I/B/E/S forecast data for U.S. firms from 1998 to 2008, we find that, in a given year, about 20%–34% of analysts disaggregate for some, but not for all the firms that they follow. This evidence of selective disaggregation by analysts suggests that reputation building alone does not fully explain the decision to disaggregate forecasts. We hypothesize that the decision to disaggregate earnings forecasts is at the firm‐level as well and is systematically related to the analysts’ bias in the issued forecasts. Our findings are that (a) analysts’ overall optimistic bias and forecast errors decrease monotonically with the level of forecast disaggregation, and (b) analysts that selectively disaggregate their forecasts for some firms or who do not persistently disaggregate a given firm's forecasts exhibit more positive bias and larger forecast errors. Our findings are consistent with the notion that the analysts who issue biased forecasts, for example, to curry favour with the management, are less likely to provide disaggregated information as part of the forecast.     

Inflation,earnings forecasts,and post-earnings announcement drift

We examine whether financial analysts fully incorporate expected inflation in their earnings forecasts for individual stocks. We find that expected inflation proxies, such as lagged inflation and inflation forecasts from the Michigan Survey of Consumers, predict the future earnings change of a portfolio long in high inflation exposure firms and short in low or negative inflation exposure firms, but analysts do not fully adjust for this relation. Analysts’ earnings forecast errors can be predicted using expected inflation proxies, and these systematic forecast errors are related to future stock returns. Overall, our evidence is consistent with the Chordia and Shivakumar (J Account Res 43(4):521–556, 2005) hypothesis that the post-earnings announcement drift is related to investor underestimation of the impact of expected inflation on future earnings change.     

The changing relationship between earnings expectations and earnings for value and growth stocks during Reg FD

Regulation Fair Disclosure (Reg FD) altered the voluntary disclosure practices of firms with publicly traded securities, thereby affecting relationships between value and growth stock expectations and actual earnings. The results show that earnings forecasts for both stock groups are biased but that bias is less after the introduction of Reg FD. In fact, the difference in pre/post FD forecast bias is larger for growth stocks, suggesting that before Reg FD, analysts did not just misinterpret news but consciously tried to maintain relationships with growth firm managers. However, Reg FD limited these relationships severing the monetary advantage that might be gained from manipulating forecasts.     

A ‘rational’ explanation for ‘irrational’ forecasts of inflation

This paper analyzes professionals' forecasts of nominal income and the inflation rate. The analysis indicates that both monetary and fiscal policy data was used efficiently to forecast income, but the monetary policy data was not used efficiently to forecast the inflation rate. Further analysis suggests that the apparent inefficient use of the monetary data results from the non-stationary money-inflation relationship predicted by rational expectations models. These models then provide an explanation for the inconsistent conclusions regarding the income forecasts and the inflation rate forecasts.     

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.     

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.     

Are inflation expectations rational?

Several recent papers report evidence of an apparent statistical bias in inflation expectations and interpret these findings as overturning the rational expectations hypothesis. In this paper, we investigate the validity of such an interpretation. We present a computational dynamic general equilibrium model capable of generating aggregate behavior similar to the data along several dimensions. By construction, model agents form “rational” expectations. We run a standard regression on equilibrium realizations of inflation and inflation expectations over sample periods corresponding to those tests performed on actual data and find evidence of an apparent bias in inflation expectations. Our experiments suggest that this incorrect inference is largely the product of a small sample problem, exacerbated by short-run learning dynamics in response to infrequent shifts in monetary policy regimes.     

Heterogeneous Inflation Expectations and Learning

Using the panel component of the Michigan Survey of Consumers, we estimate a learning model of inflation expectations, allowing for heterogeneous use of private information and lifetime inflation experience. Life experience inflation has a significant impact on individual expectations, but only for 1‐year‐ahead inflation. Public information is substantially more relevant for longer horizon expectations. Even controlling for life experience inflation and public information, idiosyncratic information explains a nontrivial proportion of the inflation forecasts of agents. Women, ethnic minorities, and less educated agents have a higher degree of heterogeneity in their idiosyncratic information, and give less importance to recent movements in inflation.     

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.     

Management disclosure bias and audit services

This paper considers the level of bias observed in management disclosures of earnings forecasts and historic earnings data in Australian prospectuses. Management forecasts and naïve forecasts derived from managements’ normalised historic data are analysed. A key focus is upon the possible association between such forecast bias and differential audit services performed upon the data. Audit firm size and level of engagement are modelled against bias. The full sample revealed no overestimation bias for any of the forecast models, but underestimation was observed for elements of the management and random walk naïve forecasts. Cross-sectionally, a significant association was observed between forecast bias and audit firm size across all three forecast models. Specifically, the audit firm size variable (Non Big-5/Big-5) was inversely associated with the extent to which forecasted and normalised historic earnings data were upwardly biased. On the other hand, the level of engagement was not a significant discriminator for forecast bias. These outcomes are contrasted against others reported elsewhere in the literature and suggest a risk in generalising across contexts. The findings imply a level of ‘disclosure management’ regarding company IPO forecasts and normalised historic accounting data, with forecast overestimation and error size more extreme when the monitoring expertise and/or reputation of auditors is lower (JEL D80, G14, M41, N27).     

The effect of Regulation FD on the properties of management earnings forecasts

We investigate Regulation FD’s (FD) effect on management earnings forecast properties. We posit FD’s prohibition on private manager-analyst communication reduces (increases) optimism (pessimism) in management earnings forecasts. Prior to FD, managers could avoid publicly retracting prior optimistic forecasts by privately communicating with analysts, who could lower investor expectations with a new analyst forecast. After FD, managers with optimistic forecasts must either publicly admit their optimism by issuing a new management forecast or they must negatively surprise investors at the earnings announcement. Further, FD forces managers to use public forecasts instead of private communications to establish beatable expectations. Our evidence suggests FD reduced optimism in management forecasts. This reduction in optimistic bias is not offset by an increase in pessimistic bias. Consistent with this, we further find post-FD improvements in forecast accuracy and informativeness. We find no such changes around several potentially confounding events or for foreign firms surrounding FD. Overall, our evidence suggests FD improved firms’ forecast properties (less bias, greater accuracy, and greater informativeness).