Professional Forecasters Research Articles

Understanding Multi‐horizon Forecasts: Identification, Estimation and Testing

The properties of multi‐horizon forecasts are investigated by specifying and estimating a model nesting rational forecasts, as well as deviations from rationality resulting from horizon‐specific biases and idiosyncratic errors. Identification of the model's parameters is achieved by combining information on forecasts for a given point in time with different information sets, and forecasts at different points in time based on the same information set. Both sets of forecasts are used to estimate the model's parameters by generalised method of moments. A test of rationality is proposed with the twin advantages of circumventing parameter identification and boundary issues. The finite sample properties of the GMM estimator and the rationality test are also investigated. Applying the approach to US GDP growth forecasts of the Survey of Professional Forecasters, the empirical results show that forecasts deviate from rationality over all forecast horizons, with the strength of the deviations from rationality increasing with the forecast horizon.

Learning integrated inflation forecasts in a simple multi-agent macroeconomic model

This paper implements a model with a population of heterogeneous macro forecasters. Their objectives are to forecast output and inflation, both inputs in standard New Keynesian macro models. The model is implemented by first calibrating the agents to professional forecasters at the micro level. Model runs then try to replicate both the dynamics, bias and cross sectional heterogeneity of forecasts and the economy. These are done both in a model with static forecasters, and one where the forecasters are learning from each other in a social fashion. We find that expectations about the inflation process which conjecture near random walk behavior can be self-fulfilling, yielding inflation volatility and persistence on the order of magnitude of U.S. macro data. However, our forecasting populations often fall short of the heterogeneity of predictions from survey data. In some cases, monetary policy can be used to shift the model from its volatile/persistent equilibrium over to a more stable, strongly mean reverting inflation rate.

Determinants of Household and Professional Forecasters’ Inflation Expectations in India

ABSTRACTThis study analyses and compares the determinants of inflation expectations among households and professional forecasters in India. To this end, we utilize quarterly survey data from the Reserve Bank of India (RBI), specifically the Inflation Expectations Survey of Households (IESH) and the Professional Forecasters’ Survey (SPF). The analysis employs a non‐recursive structural vector autoregressive (SVAR) model to explore the relationships between variables. The impulse response function and variance decomposition analysis shed light on the response of inflation expectations to macroeconomic shocks. Our findings indicate that apart from conventional macroeconomic factors like realized inflation and monetary policy, exogenous factors such as oil prices significantly shape inflation expectations. Comparing IESH and SPF, we found out that household expectations are more sensitive to shocks related to food prices, reflecting the influence of food expenses on household decision‐making. Conversely, professional forecasters’ expectations are more influenced by core inflation. Finally, we observed that inflation expectations adjust more quickly than realized inflation in response to macroeconomic shocks, suggesting a leading role. This study is novel with the contribution to the existing literature as it provides a comparative analysis of determinants of inflation expectations between households and professional forecasters in India, while also considering inflation targeting as a significant factor.

Trust the experts? The performance of inflation expectations, 1960–2023

Using the oldest continuous surveys of U.S. inflation expectations, I find that when inflation is low, the average professional forecaster is generally rational (unbiased, with serially uncorrelated errors) and efficient (exploits available information), and inflation moves one-for-one with their expectations, whereas the average consumer is biased, underreacts to inflation, and inflation moves independently of their expectations. In contrast, when inflation is high the average consumer is generally unbiased, rational, and efficient, and inflation moves one-for-one with their expectations, while the opposite is true of professionals. Neither the median consumer nor median professional is fully rational and efficient, with the consumer underreacting when inflation is low and overreacting when inflation is high. However, inflation moves one-for-one with the median consumer forecast when inflation is high. Results are consistent with an inflation process characterized by two regimes—a low-inflation regime in which consumers are inattentive, and a high-inflation regime in which consumers are highly attentive and inflation moves with their expectations.11The numerical results presented in the manuscript were reproduced by CASCaD on the 19th of September 2024.

Assessing the accuracy of directional forecasts

ABSTRACT Directional predictions are used in a variety of settings, including economics, finance, meteorology and medicine. Since the objectives in each setting can be quite different, appropriate tests for assessing the predictions are necessary. After summarizing existing tests, we propose new tests to assess the accuracy for cases where getting extreme events wrong is particularly costly and where there is serial dependence in small samples. We show in simulations that the latter test has a more favourable power-size trade-off relative to existing tests. The new tests are then applied to the directional EUR/USD forecasts in the ifo-Institute’s World Economic Survey and to the point forecasts in the Philadelphia Fed’s Survey of Professional Forecasters. For the former, the new tests show that while there is profitability and predictive accuracy in some cases, a simple time-series model is not beaten. For the latter, extreme values are not the main driver of the predictive value up to two quarters ahead. This shows that the additional tests allow a more precise determination of predictive accuracy and economic value and where it is coming from.

Understanding uncertainty shocks and the role of black swans

Uncertainty shocks can trigger business cycles, bank runs and asset price fluctuations. But how do those shocks translate into changes in beliefs and actions? What makes people suddenly become uncertain? This paper provides an explanation for subjective uncertainty shocks, estimated on real-time GDP data, that fits puzzling features of professional forecasts. The key ingredients are that agents do not know the true model governing the distribution of macroeconomic outcomes, but they believe that distribution to be potentially skewed. When agents estimate higher probabilities of extreme tail events, their uncertainty rises. Our estimates reveal that learning about probabilities of tail events – black swans – explains much of the fluctuations in subjective uncertainty.

Disagreement About the Term Structure of Inflation Expectations

We develop a model of the individual term structure of inflation expectations across forecasting horizons. Using the Survey of Professional Forecasters, we decompose disagreement about inflation expectations into individuals' long-term beliefs, private information, and public information. We find that in normal times, long-horizon disagreement is predominantly driven by individuals' long-term beliefs, while short-horizon disagreement stems from private information. During economic downturns, heterogeneous reactions to public information become a key driver of disagreement at all horizons. When forecasters disagree about public information, monetary policy exhibits a delayed response and a price puzzle emerges, underscoring the importance of anchoring inflation expectations.

How Credible Is the Central Bank of Russia to Russian Households?

The article examines the degree of public trust in the Central Bank of Russia after the transition to inflation targeting. For this purpose, the author analyzes available data from inFOM consumer surveys of confidence in the Bank of Russia as a whole as well as in its inflation targets from 2014 to 2024. Public confidence in the Bank of Russia remained relatively high from 2014 to 2017 as inflation targeting was adopted, but the Bank became far less credible to households from 2019 to 2022 because they did not believe the inflation target of 4% was achievable by the end of the current year or over the medium term. This is probably due to their lack of awareness that the Bank’s principal goal is price stability even though they are actually experiencing high inflation. The households surveyed think that government authorities are largely responsible for controlling inflation. Furthermore, consumers do not take notice of the information provided by the Central Bank of Russia. Using news articles from Russian media, posts from news communities on the VKontakte social network, and Google Trends search queries, the author shows that consumers who ignore information about the Bank’s policy are at a serious disadvantage when there is economic uncertainty. The discrepancy between the inflation expectations of consumers and professional forecasters diminishes as the volume of information tied to the phrase “Bank of Russia” increases in media, social network posts, and online searches.

One money, one voice? Evaluating ideological positions of euro area central banks

We provide new insights into the effectiveness of central bank communication in the euro area relying on a novel methodology. The time-varying text based ideal point model (TV-TBIP) is used focusing on two crucial topics communicated by central bankers, namely price stability and financial stability. The methodology permits identification of the ideological position of the speaker. We find that the ECB transitions between a high ideal point state reminiscent of interventionist monetary policy and their effects on financial markets and a low ideal point state with emphasis on risks to fragmentation from monetary policy and financial stability policies. The individual euro area central banks tend to mirror the ECB’s position which suggests that some specialization/coordination of responsibilities from the communications activities of euro area national central banks takes place. National central banks’ positions change gradually and usually during crisis periods. In contrast, the ECB’s ideological position is very stable. We also conduct several econometric tests that point to national inflation rates influencing ideological positions. Additionally, we find that professional forecasts are responsive to the position taken of central bankers in their speeches.

Forecaster (Mis-)Behavior

Abstract We document two stylized facts in expectational data. First, professional forecasters overrevise their macroeconomic expectations. Second, such overrevisions mask evidence of both over- and underreactions to public signals. We show that the first fact is inconsistent with standard models of noisy rational expectations, but consistent with behavioral and strategic models. The second fact, in contrast, presents a puzzle for existing theories. We propose an extension of noisy rational expectations that allows forecasters to be overconfident in their information. We show that this feature when combined with the endogeneity of public signals leads to over- and undereactions consistent with the data.

INFLATION VS INFLATION EXPECTATIONS IN 2020–2021 – THE IMPACT OF THE COVID-19 PANDEMIC

Aim: During the COVID-19 pandemic in 2020–2021, there was a significant increase in inflation and inflation expectations due to the government policies of the United States (US) and the European Union (EU), including the Euro Area (EA). With that being said, the evolving situation within these three po­litical-economic areas highlights the importance of understanding the relationship between inflation and inflation expectations, as perceived by both consumers and professional forecasters. The purpose of this article is to analyze the changes in these phenomena, using descriptive survey’ data analysis and a hybrid model of inflation expectations. Methods: The research methods refer to the descriptive survey data anal­ysis that provides evidence on the long-term courses of inflation in the US, the EU, and the EA, as well as the consumers’ and professional forecasters’ inflation expectations within the period 1999–2019. A hybrid model of inflation expectations has been used to estimate this data during the period of 2021. The study correlates and compares the findings of both types of research. Results: The results demonstrate that dur­ing the pandemic, the evidence supports the occurrence of periodic medium-high inflation in the studied economic areas. Inflation expectations in the US and the EU were periodically weakly anchored, although they were stabilized in the EA. Conclusions: The research, conducted by analyzing price trends and their expected trajectories over various timeframes, revealed consistent patterns. These patterns highlighted similarities in anticipated price changes before and during the pandemic.

Perceptions About Monetary Policy

Abstract We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time, in particular over the monetary policy cycle. Forecasters update their perceptions about the Fed’s policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that they have imperfect information about the rule. Monetary policy perceptions matter for monetary transmission, as they affect the sensitivity of interest rates to macroeconomic news, term premia in long-term bonds, and the response of the stock market to monetary policy surprises. A simple learning model with forecaster heterogeneity and incomplete information about the policy rule motivates and explains our empirical findings.

Testing for differences in survey‐based density expectations: A compositional data approach

SummaryWe propose to treat survey‐based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach that involves multiple testing for differences of individual parts of the density. In addition, the test is computationally much faster than the KLIC‐based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the US Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.

Firms’ economic growth expectations and reactions to micro and macro news in Japan

ABSTRACT This study investigates whether firms’ expectations of aggregate output growth overreact or underreact to micro and macro news by examining firm surveys conducted by a Japanese newspaper company, Nikkei. We capture micro news measured by forecast revisions and macro news measured by a new variable, the Japanese government’s growth forecast and that of professional forecasters’ consensus. We found that firms’ economic growth expectations overreact only to macro news. Our results indicate the heterogeneity of firm expectations formation across target variables and news types. Our findings suggest that firms excessively rely on government forecasts in turbulent times. The overreaction of firms’ output growth expectations to the government’s forecast may be associated with their lower performance, and that the government’s macroeconomic forecasts play a role in macroeconomic performance through firms’ expectation channels.

Are professional forecasters inattentive to public discussions about inflation? The case of Argentina

AbstractWe evaluate whether professional forecasters incorporate valuable information from public discussions on social media. The study covers the case of inflation in Argentina for the period 2016–2022. We find solid evidence consistent with inattention. A simple indicator of attention to inflation on social media is shown to anticipate professional forecast errors. A one standard deviation increment in the indicator is followed by a rise of 0.4% in mean forecast errors in the subsequent month and by a cumulative increment of 0.7% over the next 6 months. Furthermore, social media content anticipates significant revisions in forecasts that target multiple months ahead inflation and calendar year inflation. These findings are different from previously documented forms of inattention. Consistent results are verified by implementing out‐of‐sample forecasts and using content from an alternative social network. The study has implications for the use of professional forecasts in the context of policymaking and sheds new evidence on the nature of imperfect information in macroeconomics.

Unusual shocks in our usual models

We propose a method to allow usual business cycle models to account for the unusual COVID episode. The pandemic and the public and private responses to it are represented by a new shock called the Covid shock, which loads onto wedges that underlie the usual shocks and comes with news about its evolution. We apply our method to a standard medium-scale model, estimating the loadings with 2020q2 data and the evolving news using professional forecasts. The Covid shock accounts for most of the early macroeconomic dynamics, was inflationary and a persistent drag on activity, and the majority of its effects were unanticipated. We also show how the Covid shock can be used to estimate DSGE models with data before, during, and after the pandemic.

Do oil price forecast disagreement of survey of professional forecasters predict crude oil return volatility?

This paper explores whether the dispersion in forecasted crude oil prices from the European Central Bank Survey of Professional Forecasters can provide insights for predicting crude oil return volatility. It is well-documented that higher disagreement among forecasters of asset price implies greater uncertainty and higher return volatility. Using several Generalized Autoregressive Conditional Heteroskedasticity with Mixed Data Sampling (GARCH-MIDAS) models, we find, based on the in-sample estimation results, the oil market experiences greater volatility when the forecasters’ disagreements increase. The model that integrates both historical realized variance and forward-looking forecaster disagreement into the conditional variance, along with the model focusing solely on pure forward-looking forecaster disagreement, exhibits a much superior fit to the data compared to the model relying solely on realized variance and the models considering forward-looking forecasted mean return. The out-of-sample forecasting results unequivocally illustrate that incorporating forecaster disagreement offers valuable insights, markedly enhancing the predictive accuracy of crude oil return volatility within the GARCH-MIDAS model. Moreover, we illustrate the economic benefit of considering forecasters’ disagreement when forecasting volatility, demonstrating its significance for VaR risk management.

Tale About Inflation Tails

We study probabilities of extreme inflation events in the Unites States and the euro area. Using a state-space model that incorporates information from a large set of professional forecasters, we generate the term structure of inflation forecasts as well as probabilities of future inflation for any range of inflation outcomes in closed form at any horizon. Since the onset of the COVID-19 pandemic, inflation expectations increased materially amid heightened uncertainty about future inflation. Likelihood of significant departures of inflation targets in the longer term reached about 15 percent in the middle of 2022, increasing from near zero levels in 2020. Such an increase in the right tail of the probability distribution over future inflation outcomes drives an increase in inflation expectations and inflation risk premiums. Several popular external uncertainty measures are associated with variation in tail probabilities.

(Mis)Alignment between observed and expected monetary policy: The case of Brazil

The economic agents’ perception of the monetary policy might not coincide with the central bank conduct. We investigate this issue by using both actual and expected data identified by professional forecasters for Brazil, an emerging economy that has long adopted the inflation-targeting regime. We estimate observed, expected, and forward-looking interest rate rules, apply Full-Information Rational Expectations (FIRE) tests, assess restrictions implied by models of information rigidity, and perform several robustness checks. The estimated policy rules respond to inflation deviations and output gap according to theoretical grounds. Professional forecasters, however, do not believe in aggressiveness to fight inflation in longer forecasting horizons, while FIRE tests unveil information rigidity in the short run. There is a misalignment between the Central Bank practice and the private agents’ perception of the monetary policy in the long but not in the short run, suggesting unanchored long-term inflation expectations.

The effects of economic uncertainty and economic policy uncertainty on banks’ loan loss provision in Brazil

This paper investigates the effects of economic uncertainty and economic policy uncertainty on banks’ loan loss provision in Brazil, and it seeks to identify which uncertainties have the greatest impact on loan loss provisions. Regarding uncertainties, it is possible to proxy economic uncertainty and economic policy uncertainty through disagreements among professional forecasters and through news-based proxies. Thus, as a novelty, disagreements among professional forecasters are used to proxy both economic and economic policy uncertainties, and for checking robustness, news-based proxies are employed. The disagreements in expectations are divided into two groups: the first focuses on uncertainties related to economic policy instruments (i.e., monetary policy interest rate and primary surplus), and the second on uncertainties related to economic outcomes (i.e., inflation, exchange rate, GDP growth, and public debt). Regarding the news-based proxies of economic policy uncertainty and economic uncertainty, two indicators were employed: the first is the Economic Policy Uncertainty index, and the second is the index of economic uncertainty unrelated to economic policy that we calculate. Based on dynamic panel data analysis for 125 Brazilian banks, the findings suggest uncertainties in economic outcomes have greater influence on banking provisions than uncertainties in economic policy. The study validates the results using news-based indexes and a subsample representing the post-global financial crisis period.